MSc Genes, Environment & Development
7PADGGB1 Research Projects
The research project should provide students with the opportunity to work,
uninterrupted, on a closely-supervised research project for approximately 6 months fulltime study. The project would need to involve some data analysis. (A meta analysis
based project would be suitable but a literature review would not be appropriate). The
topic of the research could be anything that falls with the theme of genes or
environment or development related to behavioural and/or psychiatric traits but would
not need to include all three themes or wet laboratory work. The research project should
enable students to use the specialist knowledge that they have acquired from the
previous taught modules to generate testable hypotheses and then, using appropriate
techniques, to obtain data or analyse existing data which they can present and critically
evaluate in a discussion resulting in conclusions that either support or refute their
hypotheses. (* In this case, laboratory refers to research work that is either
office/computer-based or run in a wet laboratory).
Duration: The full-time project period will start on 27 February 2017 and run, without a
break, until the submission of the project thesis on the 25 August 2017. Students are
expected to work on their projects full-time (at least 5 days a week). The poster
presentations will be held on Friday 1 September 2017. Although all projects must start
before the end of February 2017, in some cases projects may start earlier if the student
and supervisor agree an earlier start date. Early project start dates must be approved
by the Module Leader.
Assessment: In addition to the submission of a dissertation (7,500 - 10,000 words) on
their research project, students will be required to keep a laboratory notebook of
everything that they do and observe in the laboratory*, according to good laboratory
practice (GLP) standards and to behave as a member of a research team, with regard to
their own safety and that of the other team members. The laboratory notebook should
be assessed and signed off regularly by the supervisor. Students also will be required to
prepare a scientific poster that concisely communicates their research findings. The
dissertation, laboratory notebook and poster will be assessed and contribute 70%, 10%
and 20% respectively to the final mark of the project.
Guidance Notes: Guidelines and further advice on what can be expected from a project
can be found in the student handbook.
Allocating projects: The list of projects will be made available to the students at the
earliest opportunity. Students will then be able to view the list of projects available and
choose their top three. The projects will be officially launched on 11 January 2017 at an
event that will give students and supervisors an opportunity to meet and learn more
about the projects and project selection process. Students and supervisors are welcome
to make their own arrangements to meet but we would like to emphasise that the
students are not applying for a project and therefore should not be formally interviewed
by supervisors. Students are welcome to submit their CV’s to potential supervisors but
we ask that supervisors do not request CV’s directly from students. After students have
indicated their preferred projects to the Programme Administrator, supervisors will be
contacted with names of the students interested in their project and then supervisors
may indicate their preferred students to the Programme Administrator. The Module
Leader will subsequently confirm allocation of projects.
2016-2017:
1.
Neurobehavioural correlates of sensory symptoms in young people with tuberous
sclerosis complex with and without autism spectrum disorder
(Supervisors: Lizzie Shephard [1st] & Patrick Bolton [2nd])
2.
Mobile EEG in Neurodevelopmental Disorders: Attention Deficit Hyperactivity
Disorder (ADHD) and Autism Spectrum Disorder (ASD) in young adulthood
(Supervisors: Gráinne McLoughlin [1st] & Alex Lau-Zhu [2nd])
3.
Genetic and environmental influences on the continuity of social isolation in
childhood
(Supervisor: Louise Arseneault [1st])
4.
Family environment and the persistence of ADHD into young adulthood? A
prospective longitudinal study
(Supervisors: Jessica Agnew-Blais [1st] & Louise Arseneault [2nd])
5.
A longitudinal, multivariate genetic analysis of adolescent psychiatric resilience
and its correlates in two UK-based twin samples
(Supervisors: Thalia Eley [1st], Tom McAdams [2nd])
6.
Fear Learning and Anxiety Response (FLARe)
st
(Supervisor: Thalia Eley [1 ])
7.
Molecular profiling of glioma tissue samples
(Supervisors: Ross Laxton [1st] & Safa Al-Sarraj [2nd])
8.
Building a Big Data Genomics Pipeline for Pathogen Identification from Human
Next Generation Sequencing Data.
st
nd
(Supervisors: Alfredo Iacoangeli [1 ] & Stephen J. Newhouse [2 ])
9.
Exploiting SNP information in Next-Generation-Sequencing reads mapping
Generation Sequencing Data
(Supervisors: Alfredo Iacoangeli [1st] & Stephen J. Newhouse [2nd])
10.
Machine Learning analysis of ALS phenotypic and genetic data
(Supervisor: Alfredo Iacoangeli [1st])
11.
Stress and Depression: Distinguishing between the effect of social isolation
stress and that of unpredictable mild chronic stress (UCMS) in adult male mice
(Supervisor: Cathy Fernandes [1st])
12.
Investigating the cognitive mechanisms underpinning social anxiety in young
people with autism spectrum disorders
(Supervisor: Francesca Happé [1st])
13.
Understanding women with Autism
(Supervisor: Francesca Happé [1st])
14.
How do social skills and autistic traits affect us in old age? Exploring data from a
huge on-line study of ageing.
(Supervisor: Francesca Happé [1st])
15.
The Role of Primary and Secondary Visual Cortices in Reward Processing
st
nd
(Supervisors: Tianye Jia [1 ] & Alex Ing [2 ])
16.
Urbanicity and Associations with Mental Health
st
nd
(Supervisors: Gunter Schumann [1 ] & Udita Iyengar [2 ])
17.
Improving psychiatric nosology
st
(Supervisor: Gunter Schumann [1 ])
18.
The Colombo Twin and Singleton (CoTaSS) study: mental health, life style and
metabolic indicators in a non-western population
(Supervisors: Frühling Rijsdijk [1st] & Helena Zavos [2nd])
19.
Mental health meets literature: definition of causative and contributing
environmental factors
(Supervisor: Honghan Wu [1st])
20.
The role of DNA methylation in the development of youth conduct problems and
comorbid psychiatric symptoms
(Supervisors: Ted Barker [1st] & Charlotte Cecil [2nd])
21.
First episode Psychosis patients with high PRS for Bipolar have a better
functional outcome at 5+years Follow up than those with Higher PRS for SCZ
(Supervisor: Marta di Forti [1st])
22.
PRS for Schizophrenia explains differences in white noises and facial recognition
in normal controls and predicts changes over time
(Supervisors: Marta di Forti [1st])
23.
In patients with a psychotic disorder, do Polygenic risks scores for Obesity
explain independently of Antipsychotic treatment changes in body mass index
between baseline and 5 years follow up?
st
(Supervisor: Evangelos Vassos [1 ])
24.
The association of response time variability with ADHD and autism traits:
specific or common neurocognitive impairment?
(Supervisors: Jonna Kuntsi [1st])
25.
Characterising developmental trajectories of infant temperament
(Supervisor: Charlotte Tye [1st])
26.
Happily depressed
st
(Supervisor: Sam Choi [1 ])
27.
The chicken & the egg of medical research
(Supervisors: Paul O’Reilly [1st] & Sam Choi [2nd])
28.
A polygenic risk score for psychiatry
(Supervisor: Paul O’Reilly [1st] & Sam Choi [2nd])
29.
Genetic prediction using UK Biobank
(Supervisors: Cathryn Lewis [1st] & Paul O’Reilly [2nd])
30.
Genetic risk for psychiatric disorders and reproductive fitness in the general
population
(Supervisor: Cathryn Lewis [1st])
31.
DNA methylation and psychotic experiences at age 18
(Supervisor: Susanna Roberts [1st])
32.
Functional characterisation of top hits from epigenome-wide meta-analyses of
hippocampal volume
(Supervisor: Sylvane Desrivières [1st])
33.
Developing bio-behavioural risk/prediction models of eating disorders, weight
gain and obesity in a large well-characterised cohort
st
(Supervisor: Sylvane Desrivières [1 ])
34.
Can the integration of cortical GWAS and brain expression Quantitative Trait Loci
(eQTLs) boost our ability to identify genes that contribute to human cognitive
abilities?
(Supervisor: Sylvane Desrivières [1st])
35.
Individual Differences in Perception of Agency
(Supervisor: Geoff Bird [1st])
36.
How self-experience influences social perception
(Supervisor: Geoff Bird [1st])
37.
The Recognition of Facial Emotion in Older adults
st
(Supervisor: Geoff Bird [1 ])
Projects 2015-2016:
38.
Electrophysiological markers of ASD and ADHD in tuberous sclerosis complex
(Supervisor: Lizzie Shephard)
39.
The Colombo Twin and Singleton (CoTaSS) study: The genetic aetiology of PostTraumatic Stress Disorder in a non-western population
(Supervisors: Frühling Rijsdijk, Helena Zavos & Matthew Hotopf)
40.
The genetic and environmental overlap between depression and fatigue in a
population of Sri-Lankan twins and singletons
(Supervisors: Helena Zavos & Frühling Rijsdijk)
41.
Cellular Aging in Schizophrenia
(Supervisor: Tim Powell
42.
Gene-Environment Interactions in Major Depressive Disorder
(Supervisor: Tim Powell
43.
DNA methylation in telomerase-encoding genes and its relationship to major
depression and childhood stress
(Supervisors: Tim Powell & Agnes Kepa)
44.
Does perception of trustworthiness gleaned from facial first impressions differ in
ASD populations?
(Supervisors: Geoff Bird)
45.
Is interoceptive ability (IA) a unified phenomenon or and how does this impact
perception within a target clinical population?
(Supervisor: Geoff Bird)
46.
Can alexithymia severity also predict individuals' ability to perceive time, in
those with and without ASD?
(Supervisor: Geoff Bird)
47.
Fear conditioning in young adults: A feasibility study
(Supervisors: Thalia Eley, Kathryn Lester, Tom Barry)
48.
Exploring potential gene-environment interaction between Callous-Unemotional
traits and measures of social disadvantage
(Supervisor: Tom McAdams)
49.
Pharmacogenetics of anti-depressant response
(Supervisors: Cathryn Lewis, Chiara Fabbri)
50.
Adverse life events and psychosocial risk factors in women with ADHD and
women with BD
(Supervisors: Jonna Kuntsi & Giorgia Michelini)
51.
The role of DNA methylation in the development of youth conduct problems and
comorbid psychiatric symptoms
(Supervisors: Dr Charlotte Cecil (First), Dr Edward Barker (Second))
52.
Neuropsychological correlates of childhood maltreatment: systematic review and
meta-analysis
(Supervisor: Andrea Danese)
53.
Anorexia nervosa: Identifying risk factors affecting survival rates in genetic
subtypes of anorexia – doing epidemiology in clinical records
(Supervisors: Gursharan Kalsi & Gerome Breen)
54.
Anorexia Nervosa: Exploring the genetic relationship between anorexia nervosa,
body mass index and metabolic traits in the UK BioBank cohort
(Supervisors: Gerome Breen & Paul O’Reilly)
55.
Investigate the effect of Fam19A2 in Eating disorder patients
(Supervisor: Aoife Keohane)
56.
The advantages of being on the spectrum
(Supervisor: Paul O’Reilly)
57.
A new approach to gene*environment and gene*gene interaction studies
(Supervisor: Paul O’Reilly)
58.
Uncovering the causal relationships underlying genetic correlations between
phenotypes
(Supervisor: Paul O’Reilly)
59.
Using genetics to investigate the interaction between physical and psychiatric
health
(Supervisor: Paul O’Reilly)
60.
Family environment and the persistence of ADHD into young adulthood (A
prospective longitudinal study)
(Supervisors: Jessica Blais-Agnew & Louise Arseneault)
61.
Is parent-youth disagreement in reports of parenting predictive of young adults’
antisocial behaviour? A prospective longitudinal study
(Supervisors: Louise Arseneault & Jasmin Wertz)
62.
Is parental monitoring an effective strategy for parents to reduce their children’s
antisocial behaviour? A prospective longitudinal study
(Supervisors: Louise Arseneault & Jasmin Wertz)
63.
To identify genes that relate to brain structure and/or behaviour in adolescents
(Supervisor: Erin Quinlan)
64.
Finding biomarkers in brain behaviour relationships in ADHD
(Supervisors: Bing Xu and Gunter Schumann)
65.
Robust personalised daily activity classifier for remote monitoring of patients
with mental health issues
(Supervisor: Dr Yevgeniya Kovalchuk)
66.
Developmental disorders and transient gestational hypothyroidism
(Supervisor: Cathy Fernandes)
67.
DNA methylation biomarkers and susceptibility to neuropsychiatric diseases
(Supervisors: Sylvane Desrivières & Barbara Ruggeri)
68.
Brain maturation and risk factors for schizophrenia
(Sylvane Desrivières & Tianye Jia)
69.
Genetic influences of reward sensitivity and hyperactive behaviours and
dopamine and noradrenaline receptors: developing a co-expression network for
VPS4A
(Supervisor: Tianye Jie)
70.
Mental health meets literature: definition of causative and contributing
environmental factors
(Supervisor: Anika Oellrich)
71.
Applied Predictive Models in Alzheimer's Disease: A Comparison of Standard
Machine Learning Methods and Evaluation of Tensorflow
(Supervisor: Stephen Newhouse)
72.
Pharmacogenetics of Antidepressant Treatment for Major Depressive Disorder: A
Systematic Review of Candidate Gene and Genome-wide studies
(Supervisor: Robert Keers & Rudolf Uher)
73.
To assess the changes gene expression in blood and saliva samples in eating
disorders
(Supervisor: Aoife Keohane)
Projects 2014-2015:
74.
The Colombo Twin and Singleton (CoTaSS-2) study: The aetiological relationship
between Metabolic Syndrome and Psychiatric Disorders
(Supervisors: Helena Zavos and Fruhling Rijsdijk)
75.
A Twin Study of Hopelessness
(Supervisors: Thalia Eley & Monika Waszczuk)
76.
The role of chromatin remodelling factors in cerebellar development and autism
(Supervisors: Cathy Fernandes and Albert Basson)
77.
Epigenetic alteration of RELN in mouse
(Supervisors: Albert Basson & Chloe Wong)
78.
White matter pathology in the Neurexin 1 alpha knock out mouse
(Supervisors: Anthony Vernon & Cathy Fernandes)
79.
Stress, genes, brain and alcohol: association studies in adolescents
(Supervisors: Sylvane Desrivières)
80.
Autism Spectrum Disorders and social cognition (Supervisors: Francesca Happé)
81.
Does environment influence outcomes in Tuberous Sclerosis?
(Supervisors: Holan Liang, Patrick Bolton, Fiona McEwen & Charlotte Tye)
82.
Cognitive profiles in autism spectrum disorders (ASD) and attention deficit
hyperactivity disorder (ADHD): similarities and differences across conditions.
(Supervisors: Patrick Bolton, Karen Ashwood & Charlotte Tye)
83.
Do children with Tuberous Sclerosis and autism spectrum disorder (ASD) have
the same cognitive strengths and weaknesses as children with idiopathic ASD?
(Supervisors: Fiona McEwen, Patrick Bolton, Holan Liang/Charlotte Tye)
84.
Imitation in adults with autism spectrum disorder: exploring the role of imitation
inhibition in empathy. (Supervisors: Fiona McEwen & Geoff Bird)
85.
The impact of Alexithymia on emotion understanding
(Supervisor: Geoff Bird)
86.
Investigating the use of Theory of Mind in Autistic Individuals
(Supervisor: Geoff Bird)
87.
Proprioception and weight lifting judgments in autism and alexithymia:
(Supervisor: Geoff Bird)
88.
Can we tickle ourselves?
(Supervisor: Geoff Bird)
89.
Creating a 'pleiotropy map' of the human genome
(Supervisor: Paul O’Reilly)
90.
Can we get more power from GWAS by considering related traits together?
(Supervisor: Paul O’Reilly)
models of CHARGE syndrome.
91.
Using Polygenic Risk Scores to inform psychiatric diagnoses with underlying
biology
(Supervisor: Paul O’Reilly)
92.
Multi-trait Polygenic Risk Scores
(Supervisor: Paul O’Reilly)
Projects 2013-2014:
93.
Trans-generational study of the effects of advanced paternal age on behaviour
(Dr Cathy Fernandes)
94.
The impact of Alexithymia on emotion understanding
(Dr Geoff Bird)
95.
Investigating the use of Theory of Mind in Autistic Individuals
(Dr Geoff Bird)
96.
“When I was born I was so surprised I didn’t talk for a year and a half”
Gracie Allen
(Dr Rosalind Arden)
97.
Gene Expression in twins discordant for depression and anxiety
(Dr Matthew Davies)
98.
Children’s Attentional Training Study (CATS): Piloting of a school-based
“cognitive vaccine” for the reduction and prevention of child anxiety
(Dr Kathryn Lester & Professor Thalia Eley)
99.
Candidate genes associated with Behavioural Inhibition from infancy to middle
childhood
(Prof Thalia Eley, Dr Chloe Wong, Ms Susanna Roberts)
100.
Therapygenetics: The Serotonin Transporter Promoter polymorphism and
response to Exposure-based Cognitive Behaviour Therapy in Adult Anxiety
(Prof Thalia Eley, Dr Rob Keers)
101.
Genetic associations with the functional decline in Alzheimer’s Disease patients
(Dr Martina Sattlecker, Dr Stephen Newhouse)
102.
ADHD in Tuberous Sclerosis
(Dr Charlotte Tye, Professor Patrick Bolton)
103.
Epigenetic differences associated with Autism Spectrum Disorder
(Dr Chloe Wong, Professor Jonathan Mill)
104.
Genes related to aggression
(Dr Leonard Schalkwyk, Dr Karim Malki)
1. Neurobehavioural correlates of sensory symptoms in young people with
tuberous sclerosis complex with and without autism spectrum disorder
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterised by
deficits in social-communication and the presence of restricted and repetitive
behaviours. Many individuals with ASD also have atypicalities in sensory processing,
such as hypersensitivity to particular sounds, which can cause significant distress and
functional impairment. Research suggests that slowed habituation to sensory
stimulation may underlie the sensory symptoms in ASD (Guiraud et al., 2011; Webb et
al., 2010). However, few studies have investigated the neurobehavioural basis of
sensory processing in ASD and the link between slowed habituation and sensory
atypicalities requires further investigation.
The current project will investigate neural and behavioural correlates of sensory
symptoms in a sample of young people with tuberous sclerosis complex (TSC) with and
without ASD. TSC is a rare genetic condition with a known cause (mutation on the
TSC1 or TSC2 gene) that is characterised by harmatomatous growths in the major
organs of the body, including the brain (cortical tubers). TSC carries a high risk for ASD
as well as other impairing conditions, including epilepsy (Harrison & Bolton, 1997). This
project aims to identify neurobehavioural atypicalities, such as slowed habituation, that
are present in individuals with TSC and co-occurring ASD (TSC+ASD) compared to
individuals with TSC without ASD, and to examine which factors (epilepsy severity,
location and number of cortical tubers) are associated with sensory symptoms and their
correlates in young people with TSC+ASD.
References
Guiraud, J. A., Kushnerenko, E., Tomalski, P., Davies, K., Ribeiro, H., Johnson, M. H., &
BASIS Team. (2011). Differential habituation to repeated sounds in infants at high risk
for autism. Neuroreport, 22(16), 845-849.
Harrison, J. E., & Bolton, P. F. (1997). Annotation: tuberous sclerosis.Journal of Child
Psychology and Psychiatry, 38(6), 603-614.
Webb, S. J., Jones, E. J., Merkle, K., Namkung, J., Toth, K., Greenson, J., ... & Dawson,
G. (2010). Toddlers with elevated autism symptoms show slowed habituation to faces.
Child Neuropsychology, 16(3), 255-278.
Supervisors:
Dr Lizzie Shephard & Professor Patrick Bolton
2. Mobile EEG in Neurodevelopmental Disorders: Attention Deficit
Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) in
young adulthood
This project will investigate the cognition and wellbeing of young adults with Attention
Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD) using
cognitive-electrophysiological measures of executive and social function. Resultant data
will improve our understanding of the overlap and distinction between these two
common neurodevelopmental disorders, paving the way for optimal treatment targets.
The student will be part of a team working on the IDEAS project (Individual Differences
in EEG in young Adults Study), the first of its kind to bring next-generation cutting-edge
mobile electroencephalography (mobile EEG) technology into a large scale twin study.
The study capitalises on a subsample of one of the largest longitudinal twin study in the
world (the Twins Early Development Study [TEDS]). The student will develop their own
project from a sub-dataset and gain knowledge in mobile EEG data acquisition/ analysis
and neurodevelopmental disorders
References
McLoughlin, G., Asherson, P., Albrecht, B., Banaschewski, T., Rothenberger, A.,
Brandeis, D. & Kuntsi, J. (2011). Cognitive-electrophysiological indices of attentional
and inhibitory processing in adults with ADHD: familial effects. Behavioural and Brain
Functions, 7(26).
McLoughlin, G., Makeig, S. & Tsuang, M. T. (2014). In Search of Biomarkers in
Psychiatry: EEG-Based Measures of Brain Function. American Journal of Medical
Genetics. Part B: Neuropsychiatric Genetics, 165(2), 111-121.
Tye, C., Asherson, P., Ashwood, K. L., Azadi, B., Bolton, P. & McLoughlin (2014).
Attention and inhibition in children with ASD, ADHD and co-morbid ASD + ADHD: an
event-related potential study. Psychological Medicine, 44(5), 1101-1116.
Tye, C., Mercure, E., Ashwood, K. L., Azadi, B., Asherson, P., Johnson, M. H., Bolton, P.
& McLoughlin, G. (2013). Neurophysiological responses to faces and gaze direction
differentiate children with ASD, ADHD and ASD + ADHD. Developmental Cognitive
Neuroscience, 5, 71-85.
Supervisors:
Dr Gráinne McLoughlin and Dr Alex Lau-Zhu
3. Genetic and environmental influences on the continuity of social isolation in
childhood
Social isolation in childhood is a risk factor for poor educational attainment and, when
experienced chronically, predicts ill health and mortality later in life. Social isolation is
also substantially heritable (Matthews et al, 2016), indicating that it is not merely an
adversity that arises from the environment, but can also be influenced by children’s own
heritable characteristics. It also shows moderate stability: most children who experience
social isolation in early childhood will have escaped it by the start of adolescence, but a
not-insubstantial minority of children are isolated persistently through the early school
years (Matthews et al, 2015).
The aim of this study will be to calculate the extent to which genetic and environmental
factors explain the continuity of social isolation in childhood. The data will be drawn
from the Environmental Risk Longitudinal Twin Study, a birth cohort of 1,116
monozygotic and same-sex dizygotic twin pairs born in 1994 and 1995. Social isolation
was measured via mother and teacher reports, provided when participants were aged 5,
7, 10 and 12. Behavioural genetic methods will be used to fit a multivariate ACE model
to the twin data, decomposing the variance in social isolation at each age into genetic
and environmental effects, in order to estimate the extent to which the same influences
on isolation at one age contribute to isolation at subsequent ages.
References
Matthews, T., Danese, A., Wertz, J., Ambler, A., Kelly, M., Diver, A., Caspi, A., Moffitt,
T. E., & Arseneault, L. (2015). Social isolation and mental health at primary and
secondary school entry: A longitudinal cohort study. Journal of the American Academy
of Child and Adolescent Psychiatry, 54(3), 225–232.
Matthews, T., Danese, A., Wertz, J., Odgers, C., Ambler, A., Moffitt, T. E., & Arseneault
L. (2016). Social isolation, loneliness and depression in young adulthood: A behavioural
genetic analysis. Social Psychiatry and Psychiatric Epidemiology, 51(3), 339-348.
Supervisor:
Professor Louise Arseneault
4. Family environment and the persistence of ADHD into young adulthood? A
prospective longitudinal study
ADHD is now recognized to occur in adulthood and is associated with a range of
negative outcomes. However, less is known about the prospective course of ADHD into
adulthood, the risk factors for its persistence past childhood, and the possibility of its
emergence in young adulthood in non-clinical populations.
We found in a population cohort of young adults that characteristics of the family
environment did not distinguish individuals who persisted from those who remitted,
except that families of persistent individuals had comparatively higher maternal warmth
and less maternal depression (Agnew-Blais et al., under review). This finding is
surprising and deserves further investigation. It is possible that some children exhibit
symptoms in response to poor family environments, but once these individuals move
away from home, symptoms abate. However, other aspects of the environment were
not less compromised in the persistent group, suggesting that if this association is
causative, it may be specific to pathways related to maternal-child bonding.
For this project, we propose to examine the association between children’s family
environment and the persistence of ADHD into young adulthood to understand how and
why it may be linked to the persistence of the disorder.
This project is based on data from the Environmental Risk (E-Risk) Longitudinal Twin
Study, which tracks the development of a birth cohort of 2,232 British children (Moffitt
et al., 2002). We ascertained ADHD diagnosis in childhood on the basis of mother and
teacher reports of symptoms of inattention and hyperactivity-impulsivity and adult
ADHD diagnosis based on private structured interviews with participants at age 18. We
collected measures of the family environment when the participants were age 5.
References
Agnew-Blais, J.C, Polanczyk, G., Danese, A., Wertz, J., Moffitt, T.E., & Arseneault L.
(under review). Persistence, remission and emergence of ADHD in young adulthood:
Results from a longitudinal, prospective population-based cohort. JAMA Psychiatry.
Moffitt, T.E., & the E-Risk Study Team (2002). Teen-aged mothers in contemporary
Britain. Journal of Child Psychology and Psychiatry, 43, 727-742.
Supervisors:
Dr Jessica Agnew-Blais & Professor Louise Arseneault
5. A longitudinal, multivariate genetic analysis of adolescent psychiatric
resilience and its correlates in two UK-based twin samples
Background. Psychiatric resilience has been conceptualised as better-than-expected
outcomes in the presence of risk (Amstadter, Myers, & Kendler, 2014; Kim-Cohen,
Moffitt, Caspi, & Taylor, 2004) and has been shown to be genetically associated with
specific psychiatric disorders (Amstadter, Maes, Sheerin, Myers, & Kendler, 2016).
However, the developmental significance of psychiatric resilience has not been fully
explored.
Aims. In this study, we will conduct multivariate genetic analysis of psychiatric
resilience and its developmental correlates (cognitive performance, emotional and
behavioural problems, educational engagement &attainment, & parent-child and peer
relationships) in two longitudinal twin datasets (TEDS & G1219). Decomposition of the
associations between these variables across adolescence will reveal the extent to which
they are driven by shared genetic and environmental factors.
Methods. Psychiatric resilience will be operationalised as the residual of an individual’s
score on the short Moods and Feelings Questionnaire (sMFQ), a commonly used
measure of depressive symptoms, regressed on general (SES) and specific (stressful life
events, parenting) risk factors. With this approach, an individual whose sMFQ score is
lower than predicted by the regression on the risk factor is characterised as having high
resilience and one whose score is higher than the prediction as having lower resilience.
Structural equation modelling of twin data will be used to ascertain the nature of the
relationships between psychiatric resilience and the other study variables.
Implications. Understanding the nature and extent of associations between psychiatric
resilience and other developmental outcomes can help to highlight specific factors that
may be involved in mitigating risk for psychopathology.
References
Amstadter, A. B., Maes, H. H., Sheerin, C. M., Myers, J. M., & Kendler, K. S. (2016). The
relationship between genetic and environmental influences on resilience and on common
internalizing and externalizing psychiatric disorders. Social Psychiatry and Psychiatric
Epidemiology, 51(5), 669–678. http://doi.org/10.1007/s00127-015-1163-6
Amstadter, A. B., Myers, J., & Kendler, K. S. (2014). Psychiatric resilience: longitudinal
twin study. The British Journal of Psychiatry. http://doi.org/10.1192/bjp.bp.113.130906
Kim-Cohen, J., Moffitt, T. E., Caspi, A., & Taylor, A. (2004). Genetic and Environmental
Processes in Young Children’s Resilience and Vulnerability to Socioeconomic Deprivation.
Child Development, 75(3), 651–668. http://doi.org/10.1111/j.1467-8624.2004.00699.x
Supervisors:
Professor Thalia Eley & Dr Tom McAdams
6. Fear Learning and Anxiety Response (FLARe)
The FLARe study team have places available for up to two students to work with us on
this exciting project.
FLARe is an experimental study of learning and anxiety relevant processes in young
adults (aged 21-25). This period of emerging adulthood is considered to be a critical
developmental stage, with many psychiatric disorders having their onset in this agerange. We aim to investigate individual differences in the outcomes of a Fear
Conditioning paradigm, and associations with measures of psychopathology and
personality.
Fear conditioning uniquely provides an opportunity to consider individual mechanisms
thought to contribute to anxiety, in non-clinical individuals. These paradigms have been
used to model aetiology, maintenance, treatment and relapse processes in anxiety
disorders for over four decades (e.g. Eysenck, 1968; Lissek et al., 2008; Mineka &
Oehlberg, 2008).
Students will have the opportunity to collect experimental data using both traditional
lab-based techniques and mobile phone technology. Students will also get the
opportunity to devise a project and analyse data looking at the associations between
measures of anxiety, psychopathology and personality with fear conditioning outcomes.
There is scope for the inclusion of additional measures for the right student. Please be
sure to contact Kirstin or Thalia as early as possible if you would be interested in doing
so.
References
Duits, P., Cath, D. C., Lissek, S., Hox, J. J., Hamm, A. O., Engelhard, I. M., … Baas, J.
M. (2015). Updated meta-analysis of classical fear conditioning in the anxiety disorders.
Depression and Anxiety, 32(4), 239–253. doi:10.1002/da.22353
Lissek, S., Powers, A. S., McClure, E. B., Phelps, E. A., Woldehawariat, G., Grillon, C., &
Pine, D. S. (2005). Classical fear conditioning in the anxiety disorders: a meta-analysis.
Behaviour Research and Therapy, 43(11), 1391–1424. doi:10.1016/j.brat.2004.10.007
Mineka, S., & Oehlberg, K. (2008). The relevance of recent developments in classical
conditioning to understanding the etiology and maintenance of anxiety disorders. Acta
Psychologica, 127(3), 567–580. doi:10.1016/j.actpsy.2007.11.007
Supervisors:
Professor Thalia Eley
7. Molecular profiling of glioma tissue samples
Recent studies on lower grade gliomas i.e. WHO grades II and III, have highlighted that
the majority of gliomas without mutation to either IDH1 or IDH2 have a similar clinical
course and molecular profile to WHO grade IV gliomas, namely glioblastomas.
This project will review the clinical and pathological characteristics of a series of IDH
wild type gliomas diagnosed at King’s College Hospital in combination with in depth
molecular profiling using NGS technology. Investigations will ascertain whether the
series is uniform in molecular profile or represents a more heterogeneous group of
tumours.
The results will add to the body of academic literature and help inform clinical decisions
and diagnosis at King’s College Hospital.
Supervisors:
Dr Ross Laxton & Professor Safa Al-Sarraj
8. Building a Big Data Genomics Pipeline for Pathogen Identification from
Human Next Generation Sequencing Data.
Pathogenic viruses pose significant threats to public health throughout the world. Their
detection in human tissues and investigating virus integration sites in host cell
chromosomes have significant clinical implications and are the object of wide interest in
the international research community.
Next generation Sequencing has recently emerged as a powerful approach to identify
both known and novel viruses as well as to study their integration sites.
Stimulated by the strong demand for NGS investigations of virus-host interactions, a
large number of tools were developed in the past years.
Considering the available tools, this project consists of the design and testing of a “state
of the art” pipeline for virology investigation on NGS data. The student will have to
achieve a deep and critical understanding of the strategies used by the existing tools.
The student will test and combine them on public and simulated datasets, assessing
their performance. Based on the results of this study the student will develop their own
pipeline and use it for a virology study on whole-genome and transcriptome sequencing
datasets.
The student taking up this project will have the opportunity to learn and work in the
fascinating field of genomics, using state-of-art tools and techniques to work on NGS
data.
References
(Sharma et al., 2015) Unraveling the web of viroinformatics: computational tools and
databases in virus research. Journal of virology.
Skills required
Being familiar with at least one language eg. Python, Perl. Interest in genomics, Good
time management and motivated.
Deliverables
The expected outcome of this project is a contribution to a novel pipeline for virology
studies on NGS data which will be used in many other projects carried out by our team.
Preliminary results might be produced by the pipeline testing on public databases.
Supervisors:
Dr Alfredo Iacoangeli and Dr Stephen J. Newhouse
9. Exploiting SNP information in Next-Generation-Sequencing reads mapping
Generation Sequencing Data
Accurate mapping of next-generation sequencing (NGS) reads to reference genomes is
crucial for almost all NGS applications and downstream analyses. Incorrect mapping of
NGS reads may cause many problems in downstream data analyses, including biased
genome/transcriptome profiling, false prediction of novel genes/transcripts, false singlenucleotide polymorphism (SNP) prediction, or even identification of false disease
variations.
Widely used aligners use scores based on the similarity between the reads and the
reference genome, applying penalties when mismatches occur. Such approach does not
take into account common polymorphisms such as SNP, insertions and deletions in the
sequenced genome, introducing a bias in the mapping.
AlignerBoost is a generalised software toolkit for boosting NGS mapping accuracy using
a bayesian-based mapping quality framework.
In this project we want to show how an SNP-aware approach can improve the mapping
of NGS reads. The student will use AlignerBoost to include the SNP information
contained in public databases (ExAC, 1000genomes, etc) in the mapping of NGS reads.
Such an approach will be tested on both simulated DNA-sequencing datasets and real
DNA-sequencing datasets. The student will work together with geneticists,
bioinformaticians and data scientists on unique datasets and in a highly multidisciplinary
context.
Skills required
Being familiar with the command line. Interest in genomics and bioinformatics, good
time organisation and motivation.
Deliverables
The expected outcome of this project is a contribution to a novel approach and method
to the mapping of NGS reads . Preliminary results might be produced by the method
testing on our datasets.
Supervisors:
Dr Alfredo Iacoangeli and Dr Stephen J. Newhouse
10.
Machine Learning analysis of ALS phenotypic and genetic data
Random Forest (RF) is an ensemble machine learning algorithm, which is best defined
as a “combination of tree predictors such that each tree depends on the values of a
random vector sampled independently and with the same distribution for all trees in the
forest” (Breiman et al 2001).
RF method is able to handle highly non-linear biological data, robustness to noise,
tuning simplicity (compared to other ensemble learning algorithms) (De Bruyn et al.
2013; Caruana and Niculescu-Mizil et al. 2006; Menze et al. 2009) and it is an ideal
candidate method for handling high-dimensional problems, where the number of
features is often redundant (Tuv et al. 2009).
We aim to apply a Random Forest analysis using a recursive feature elimination (Kuhn
et al. 2012) to identify groupings of clinical variables in Amyotrophic lateral sclerosis
patients that describe hidden disease subgroups using the following clinical and
demographic variables: Age of onset of weakness, sex, Family history of ALS in a first
degree relative, diagnostic delay, diagnosis (physician-classified phenotypic group: ALS,
PMA, PLS), Site of onset of first symptoms (Bulbar or non-bulbar), El Escorial criteria,
EEC (ALS probable or definite versus no ALS) and diagnostic delay.
The student will have to apply machine learning techniques for the analysis of our
phenotypic and genetic data of ALS patients in order to build grouping and survivor
predictive models.
The student will work together with geneticists, bioinformaticians and data scientists on
unique datasets and in a highly multidisciplinary context.
Skills required
Basic programming skills. Being familiar with at least one language eg. Python, Perl and
R. Interest in genetics, Good time organisation and motivation.
Deliverables
The expected outcome of this project is a contribution to a novel approach and method
to the study of phenotypic and genetic data of ALS patients . Preliminary results might
be produced by the method testing on our databases.
Location: Maurice Wohl Clinical Neuroscience Institute and MRC Social, Genetic and
Developmental Psychiaty Centre, Denmark Hill Campus
Supervisors:
Dr Alfredo Iacoangeli
11. Stress and Depression: Distinguishing between the effect of social
isolation stress and that of unpredictable mild chronic stress (UCMS) in
adult male mice
Background: To date, various animal models of stress are used to study and enhance
our understanding of depression, with UCMS and social isolation being two commonly
used paradigms. Both chronic stress paradigms have been known to alter hypothalamicpituitary-adrenal (HPA) axis activity, immune system functioning, and induce anxietylike and depressive-like behaviour in rodents. Interestingly however, no published paper
to date has differentiated between UCMS and social isolation, and an effort to do so is
particularly pertinent given that social isolation is used as part of the UCMS model.
Aim: To investigate whether there are any behavioural and biological differences
between social isolation and UCMS. Previous work in our laboratory has already
collected data on UCMS (with isolation) and social isolation. Here, we specifically aim to
collect the relevant data pertaining to UCMS without social isolation.
Methods: Pair housed male adult mice will be exposed to UCMS for 6 weeks. There will
also be a stress-free pair housed group of animals. All animals will then undergo a
battery of behavioural testing to assess any anxiety-and/or depressive-like behaviours,
including the Sucrose Preference Test, Forced Swim Test and the Open Field Test. Blood
and brain tissue will also be collected to measure any systemic and brain associated
changes between the types of treatment.
Training: The student will be involved in all aspects of the study, working closely with
my PhD student, Andrea Du Preez. This will predominantly involve aiding in the
implementation of UCMS, and assessing behavioural changes associated with treatment.
Moreover, there may also be an opportunity to do some ELISA and Luminex work,
specifically assessing changes in plasma levels of corticosterone, testosterone and
cytokine markers of inflammation.
References
Czéh B, Fuchs E, Wiborg O, & Simon M (2016). Animal models of major depression and
their clinical implications. . Elsevier Inc. Progress in Neuro-Psychopharmacology and
Biological Psychiatry 64, 293–310.
Ménard C, Hodes GE, & Russo SJ (2015). Pathogenesis of depression: Insights from
human and rodent studies. IBRO Neuroscience
Supervisor:
Dr Cathy Fernandes
12. Investigating the cognitive mechanisms underpinning social anxiety in
young people with autism spectrum disorders
Anxiety is one of the most common mental health problems for individuals with autism
spectrum disorders (ASD), with research showing that 40% of individuals suffer from
clinical anxiety levels throughout their lifetime. In particular, high rates of social anxiety
are frequently reported in children, adolescents and adults with ASD, compared to
prevalence estimates observed in the general population. While emerging evidence
highlights the increased prevalence of social anxiety in young people with ASD, we still
have very limited knowledge of the developmental/maintenance factors that contribute
towards social anxiety in this population.
This research project aims to explore the cognitive mechanisms underpinning the
development of social anxiety in young people with and without a diagnosis of ASD, with
the view to answering two key research questions. Are the same cognitive mechanisms
associated with social anxiety in typically developing individuals (e.g. negative
interpretation biases) also observed in young people with ASD and high social anxiety?
Are there some cognitive mechanisms associated with social anxiety in ASD that are
specific to this clinical group?
To answer these questions, we aim to recruit a total of 80 young people (40 with ASD
and 40 typically developing) between 12 and 18 years old. Each participant will take
part in several established experimental tasks and questionnaires, as well as novel
experimental tasks, to address the research questions outlined above.
The student will have the opportunity to collect, analyse and write up a subset of data
within the studies available measures, for example examining the association between
social insight, theory of mind and social anxiety. The student will be given freedom to
choose what they would be interested in exploring, which will be carefully guided by the
supervisors.
This research project is a fantastic opportunity for a student to gain hands on
experience working on a clinical study, with the chance to develop skills in experimental
design, data collection and data analyses using a wide range of experimental and
questionnaire measures.
References
Kerns, C., & Kendall, P. (2014). Autism and Anxiety: Overlap, Similarities, and
Differences. In T. Davis III, S. White, & T. Ollendick (Eds.), Handbook of Autism and
Anxiety (pp. 75–89). Cham: Springer International Publishing. doi:10.1007/978-3-31906796-4_6
Kuusikko, S., Pollock-Wurman, R., Jussila, K., Carter, A. S., Mattila, M. L., Ebeling, H., …
Moilanen, I. (2008). Social anxiety in high-functioning children and adolescents with
Autism and Asperger syndrome. Journal of Autism and Developmental Disorders, 38(9),
1697–1709. doi:10.1007/s10803-008-0555-9
Maddox, B. B., & White, S. W. (2015). Comorbid Social Anxiety Disorder in Adults with
Autism Spectrum Disorder. Journal of Autism and Developmental Disorders, 45(12),
3949–3960. doi:10.1007/s10803-015-2531-5
Simonoff, E., Pickles, A., Charman, T., Chandler, S., Loucas, T., & Baird, G. (2008).
Psychiatric disorders in children with autism spectrum disorders: prevalence,
comorbidity, and associated factors in a population-derived sample. Journal of the
American Academy of Child and Adolescent Psychiatry, 47(8), 921–929.
doi:10.1097/CHI.0b013e318179964f
White, S., Schry, A., & Kreiser, N. (2014). Social Worries and Difficulties: Autism and/or
Social Anxiety Disorder? In T. Davis III, S. White, & T. Ollendick (Eds.), Handbook of
Autism and Anxiety (pp. 121–136). Cham: Springer International Publishing.
doi:10.1007/978-3-319-06796-4_9
Supervisor:
Professor Francesca Happé
13.
Understanding women with Autism
The student will join a research team investigating gender differences in Autism
Spectrum Disorder (ASD); a neurodevelopmental condition characterised by difficulties
in social behaviour and communication, with restricted/repetitive behaviours and
interests. One of the most striking features of ASD is the high male to female ratio,
which varies across the spectrum, but is usually estimated at 4-5:1.
The higher rate of ASD in males has been seen as a clue to the etiology of ASD; e.g.
Baron-Cohen's 'extreme male brain' theory (Baron-Cohen, 2002) or the Female
Protective Effect (FPE; e.g. Robinson et al., 2013). However, it is also possible that ASD
is less well recognised in females, either due to male-stereotypes or genuine
compensation. Our ESRC-funded study aims to address directly the question of whether
females with high ASD traits are being missed by diagnostic practices or are instead
coping/compensating and do not need a diagnosis.
To do this we will compare 4 participant groups drawn from the Twins Early
Development Study; females and males who meet diagnostic criteria for ASD, and
females and males who score highly for ASD traits, but who do not meet diagnostic
criteria. A battery of gold standard diagnostic tools, cognitive tasks, measures of coping,
quality of life, co-morbidities and mental and physical health will be completed by the 4
groups.
The student will have the opportunity to join the team, perhaps taking part in
assessment visits, coding data, or collecting pilot data. In addition, we have existing
data from earlier time points in our Social Relationships Study, which can be analysed
for the research dissertation.
References
Dworzynski, K., Ronald, A., Bolton, P. & Happé, F. (2012) How different are girls and
boys above and below the diagnostic threshold for autism spectrum disorders? Journal
of the American Academy of Child and Adolescent Psychiatry, 51, 788-797.
Robinson EB, Lichtenstein P, Anckarsäter H, Happé F, Ronald A. (2013) Examining and
interpreting the female protective effect against autistic behavior. Proceedings of the
National Academy of Sciences USA, 110, 5258-62
Supervisor:
Professor Francesca Happé
14. How do social skills and autistic traits affect us in old age? Exploring data
from a huge on-line study of ageing.
Cognitive decline is common in older age. While usually a healthy part of ageing, decline
may also be a precursor to dementia, a devastating condition that affects 850,000
people in the UK. Finding early markers and understanding risk factors is vital to enable
tailoring of large-scale public health interventions.
Social cognition - the ability to understand and interact with others - is often affected in
people with dementia, and in the neurodevelopmental disorder, autism. However, little
is known about how social decline may be linked to dementia, or whether social
interventions could slow cognitive decline. Similarly, little is known about cognitive
function in old age in autism.
This project will seek to establish the cognitive profile of older adults with current
(and/or developmental) impaired social cognition, using an online cohort of 10,000
people. Data from the PROTECT study are available for analysis in this project, providing
a unique opportunity to answer questions about ageing in those with impaired social
cognition/ASD traits.
References
Ferreira N, Owen A, Mohan A, Corbett A, Ballard C. Associations between cognitively
stimulating leisure activities, cognitive function and age-related cognitive decline. Int J
Geriatr Psychiatry. 2015 Apr;30(4)
Happé, F. & Charlton, R.A. (2012) Aging in Autism Spectrum Disorders: A Mini-Review.
Gerontology, 58, 70-78.
Supervisor:
Professor Francesca Happé
15.
The Role of Primary and Secondary Visual Cortices in Reward Processing
Despite the fact that the activations of primary and secondary visual cortices have been
consistently observed in reward related task, e.g. n-back task 1 and monetary incentive
delay (MID) task 2, 3, of which the direct registry of visual input has been eliminated by
establishing contrast of competitive conditions, little attention has been paid into their
exact functions in reward processing, which is largely due to their implied passive role in
visual processing.
However, it has been shown that the primary and secondary visual cortices show higher
activations in learners than non-learners during a gambling task 4, suggesting their
involvement in the reinforcement learning. On the other hand, it has been shown that
the activation of primary and secondary visual cortices during the anticipation phase of
MID task show association with alcohol consumption 3, even stronger than that of the
striatum, which then suggests that the visual cortex might actively pre-evaluate the
input signal, and server as a mediator between outer input and the reward processing,
i.e. through striatum, in the brain.
In order to understand the role of primary and secondary visual cortices during a reward
process further, we could conduct the following analyses in the IMAGEN sample:
1. Further investigating the link between the visual cortices and the striatum, e.g. using
fMRI and DTI data;
2. Conducting mediation analysis to prove the role of visual cortices as a mediator
between striatum and substance use;
3. As visual cortices were also suggested in reinforcement learning, we could test for the
association between their activation and the performance of MID task.
Skills Required:
The candidate student is expected to be familiar with computational programming with
R.
References
Pochon JB, Levy R, Fossati P, Lehericy S, Poline JB, Pillon B et al. The neural system
that bridges reward and cognition in humans: An fMRI study. Proceedings of the
National Academy of Sciences of the United States of America 2002; 99(8): 5669-5674.
Scheres A, Milham MP, Knutson B, Castellanos FX. Ventral striatal hyporesponsiveness
during reward anticipation in attention-deficit/hyperactivity disorder. Biol Psychiat 2007;
61(5): 720-724.
Jia TY, Macare C, Desrivieres S, Gonzalez DA, Tao CY, Ji XX et al. Neural basis of reward
anticipation and its genetic determinants. Proceedings of the National Academy of
Sciences of the United States of America 2016; 113(14): 3879-3884.
Schonberg T, Daw ND, Joel D, O'Doherty JP. Reinforcement learning signals in the
human striatum distinguish learners from nonlearners during reward-based decision
making. J Neurosci 2007; 27(47): 12860-12867.
Supervisors:
Dr Tianye Jia & Dr Alex Ing
16.
Urbanicity and Associations with Mental Health
Currently more than 50% of the world’s population lives in urban cities, with 70%
estimated to live in urban areas by 2050 (WHO, 2010), and with this rapid change of
environment comes significant alterations to lifestyles, social behaviour, and a greater
risk of developing a mental health disorder. However, which aspects of urbanicity are
responsible for these higher rates of psychological disorders and if they have an impact
on neural and biological processes underlying these disorders is not well investigated.
Utilising the data from a longitudinal adolescent imaging genetic cohort (IMAGEN,
n=1400) and potentially the UK Biobank (n=500K), students will apply a range of
statistical methods to a battery of environmental, psychosocial, and clinical
assessments, to better understand the role of the environment and mental health
features (including but not limited to brain structure and function using imaging data).
References
World Health Organization, U. a. h. ( 2010). Urbanization and health. Bull. World Health
Organ, 88, 245-246
Supervisors:
Dr Gunter Schumann & Dr Udita Iyengar
17.
Improving psychiatric nosology
Problem: There is a major socio-economic problem arising from mental health disorder
which account for 23% of years lived with disability (1). Part of this problem stems from
a heterogeneity of outcome when patients are classified by traditional diagnostic
classifications (DSM and ICD) which are predominantly categorical and based merely on
clinical observation and subjective-verbal measures. A more promising approach is to
look at dimensions that are not constrained by such diagnostic categories (e.g. Research
Domain Criteria, RDoC [2-4]).
Aim: This project proposes to improve psychiatric nosology by linking patient symptoms
to functional outcomes as part of a larger research endeavour.
Method: Interrogate electronic health records using CRIS (Clinical Record Interactive
Search) to identify clinical symptoms related to adverse functional outcome and, map
symptom profiles to outcomes. For example, self-harm and suicide may be highly
predicted by a specific cluster of symptoms which is independent of diagnosis. What are
these symptoms? Outcome and symptom measures will be refined according to the
results of the data inventory.
Expected results: First, the resulting symptom-outcome mapping will be useful for
identifying risk factors to adverse outcomes transdiagnostically. Second, it will be critical
in informing future research on how such new behavioural constructs map on
biologically plausible substrates. Hence, overall, this research will facilitate a more
targeted approach by mental health service providers.
Skills required: ideally,
psychopathology.
intermediate
level of
statistics
and
basic
concepts
in
Skills developed: advanced knowledge in psychiatric classification, advanced statistics.
References
Whiteford, H., M. Harris, and S. Diminic, Mental health service system improvement:
translating evidence into policy. Aust N Z J Psychiatry, 2013. 47(8): p. 703-6.
Cuthbert, B.N., Translating intermediate phenotypes to psychopathology: the NIMH
Research Domain Criteria. Psychophysiology, 2014. 51(12): p. 1205-6.
Robbins, T.W., et al., Neurocognitive endophenotypes of impulsivity and
compulsivity:towards dimensional psychiatry. Trends Cogn Sci, 2012. 16(1): p. 81-91.
Schumann, G., et al., Stratified medicine for mental disorders. Eur
Neuropsychopharmacol,2014. 24(1): p. 5-50.
Supervisor:
Dr Gunter Schumann
18. The Colombo Twin and Singleton (CoTaSS) study: mental health, life
style and metabolic indicators in a non-western population
The CoTaSS-1 and follow-up CoTaSS-2 studies are Wellcome Trust funded projects
based in Sri Lanka. The overall aim of these studies was to investigate the genetic
aetiology of mental health variables as well as cardiovascular and metabolic risk
markers in a south-Asian population.
Twin studies are a common method for understanding the extent to which genetic and
environmental influences are important for traits or disorders. However, the majority of
twin studies have been conducted in high-income western countries. This is problematic
as the estimates from twin studies are specific to the population studied and different
levels of environmental effects could potentially change heritability estimates. Cultural
differences might also explain sex differences in aetiology of traits. Investigating
heritability in this sample therefore enables interesting comparisons to established
estimates as reported in western populations.
This is a project meant for students interested in twin research. We have a range of
phenotypes available for investigation. Based on the student’s main interest and
availability of data, we will together decide on the best topic of study. The student will
perform quantitative analyses including some simple twin model-fitting analyses.
Possible topics of study:
Depression and/or metabolic indicators in relation with: General Health, Social Support,
Physical Activity, Alcohol Use/ Smoking, Fatigue, Somatic Symptoms
References
Siribaddana SH, Ball HA, Hewage SN, Glozier N, Kovas Y, Dayaratne D, Sumathipala A,
McGuffin P, Hotopf M: Colombo Twin and Singleton Study (CoTASS): a description of a
population based twin study of mental disorders in Sri Lanka. BMC psychiatry 2008,
8:49.
Kaushalya Jayaweera1 & Lisa Aschan, Gayani Pannala, Anushka Adikari, Nicholas
Glozier, Khalida Ismail, Carmine M. Pariante, Fruhling Rijsdijk, Sisira Siribaddana,
Helena M.S. Zavos, Patricia A. Zunszain, Athula Sumathipala & Matthew Hotopf.
Prevalence and distributions of metabolic syndrome and psychiatric disorders: a crosssectional analysis of a longitudinal community health study in Sri Lanka (under Review).
Supervisors:
Dr Frühling Rijsdijk & Dr Helena Zavos
19. Mental health meets literature: definition of causative and contributing
environmental factors
After its initial success in playing Jeopardy, Watson the IBM developed supercomputer is
now utilised in decision support for lung cancer at the Memorial Sloan Kettering Cancer
Center [1, 2]. With estimations that mental illnesses account for 11 to 27 % of the
disability burden in Europe [3] and the number of people suffering from mental illnesses
increasing [4], applications such as Watson are urgently needed to develop patientcentred and cost-effective treatments for mental illnesses. In order to improve existing
treatments and increase the recovery rate, a better understanding of the underlying
mechanisms is required. As with other diseases, it has been established that mental
illnesses are influenced in their origins and pathology by environmental factors. For
example, it has been found that higher rates of schizophrenia occur in people of
Caribbean origin than ethnically similar white people living in the UK [5]. To date, no
complete list of environmental factors for all existing mental illnesses has been compiled
that can be used for patient screening and planning treatment strategies [6].
While the published scientific literature is used in a biomedical context such as building
gene networks for disease gene discovery [7] or symptom networks of inheritable
human disorders [8], it seems to be an under-valued resource with respect to mental
illnesses. It has been rarely explored for the purpose of gaining psychopathology
insights. The potential of this resource lies within the amount and variety of data
available: all journals that publish scientific results are covered mostly since 1966,
though some even date back to 1809. In order to make use of this tremendous resource
for finding potential environmental factors that (i) cause, (ii) contribute to and (iii)
influence the origin and pathology of mental illnesses, automated methods are needed
to digest the large quantities of existing data.
In order to start on this endeavour, a preliminary study would be required to assess the
quality and the representation of environmental factors in the published literature.
Furthermore, the project covers the application of existing software tools to
automatically assess this information from the literature. While no knowledge of
automation techniques and programming are required, a keen interest in learning how
to program and do automated literature analyses is a prerequisite. An automation
framework will be set up prior to the project, ready to be worked with to extract
environmental factors. It is also expandable with respect to the findings of the project.
The work will be in line with other ongoing research projects, so that it can be
complemented in later stages depending on progress.
References
[1] https://en.wikipedia.org/wiki/Watson (computer)
[2] https://www.youtube.com/watch?v=WIKM732oEek
[3] T. Wykes et al. “Mental health research priorities for Europe.” The Lancet Psychiatry
(2015).
[4] http://www.bbc.co.uk/news/health-34313127
[5] W. A. Fung, et al. “Ethnicity and mental health: the example of schizophrenia in
migrant populations across Europe.” Psychiatry (2006).
[6] M. Rutter. “How the environment affects mental health.” The British Journal of
Psychiatry (2005).
[7] K. Lage et al. “A human phenome-interactome network of protein complexes
implicated in genetic disorders.” Nature Biotechnology (2007).
[8] X. Zhou et al. “Human symptoms–disease network.” Nature Communications
(2014).
Supervisor: Dr Honghan Wu
20. The role of DNA methylation in the development of youth conduct
problems and comorbid psychiatric symptoms
Conduct problems (CP; e.g. fighting, stealing) are a major public health concern and the
leading cause of youth treatment referral in the UK. Compared to typically developing
youth, CP youth are more likely to have experienced childhood adversity (e.g. maternal
depression, harsh parenting, family conflict) and to develop a range of comorbid
psychiatric symptoms, such as depression, anxiety, and hyperactivity. However, little is
currently known about the biological mechanisms by which environmental adversity
increases risk of CP and comorbid symptoms.
The aim of this project is to investigate the role of DNA methylation - an epigenetic
mechanism sensitive to environmental influences - in the development of CP and
comorbid symptoms. Analyses will be based on longitudinal data on environmental risk
(pre/postnatal), DNA methylation (birth-age 7) and psychiatric outcomes (age 4-18),
drawn from the Avon Longitudinal Study of Parents and Children, and will involve a
combination of epigenome-wide analyses and structural equation modelling.
The project will offer students an exciting opportunity to learn about epigenetic
processes in the context of psychiatric health, as well as to develop skills in a range of
methodologies and statistical packages (R, Mplus).
Supervisors:
Dr Edward Barker & Dr Charlotte Cecil
21. First episode Psychosis patients with high PRS for Bipolar have a better
functional outcome at 5+years Follow up than those with Higher PRS for
SCZ.
Polygenic risk score have been successfully applied to explain the genetic variance
between cases of schizophrenia and healthy controls (Purcell et al 2009). In the PGC
paper on the last and largest GWAS in Schizophrenia (PGC2, 2014), the PRS analyses
showed that PRS for Schizophrenia explain less of the genetic variance in samples,
though still significant, in samples with first episode of psychosis rather than chronic
cases. The latter, might be explained by a proportion of the cases in first episode
samples suffering from an affective psychosis rather than schizophrenia. Despite the
genetic overlap shown between Schizophrenia and bipolar (Lancet 2013), clinically they
remain two separate entities with for instance very different outcomes. It is now
possible to calculate a PRS for Bipolar, therefore we aim to apply PRS for SCZ and
Bipolar to our large European sample to improve both casesness and outcome
prediction.
Methods: DNA samples and clinical data are available from a large 5 European
Epidemiological study, EU-GEI, on first onset psychosis patients N= 935 and N=1500
population controls. Polygenic risks scores will be calculated using the PRCise program.
Measures of clinical and functional outcome are being collected at 3+ years follow up in
a subsample - estimated N=240 (only London site) patients.
The students will participate in the follow up data collection and will carry out the
appropriate analyses, to:
1) Build a PRS for Schizophrenia (SCZ) and a PRS for Bipolar (BD)
2) Estimate the variance explained between cases and controls by the PRS for SCZ and
the one for Bipolar in the sample different ethnic groups
3) Investigate if high scores in PRS for BD predict a better outcome than PRS for SCZ.
References
Purcell SM, Wray NR, Stone JL, Visscher PM, O’Donovan MC, Sullivan PF, et al. Common
polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature.
2009; 460(7256):748–52. Epub 2009/07/03.
Identification of risk loci with shared effects on five major psychiatric disorders: a
genome-wide analysis. Lancet. 2013 Epub 2013/03/05.
Douglas M. Ruderfer et al. Polygenic dissection of diagnosis and clinical dimensions of
bipolar disorder and schizophrenia .Mol Psychiatry. 2014 September ; 19(9): 1017–
1024. doi:10.1038/mp.2013.138.
Supervisor:
Dr Marta Di Forti
22. PRS for Schizophrenia explains differences in white noises and facial
recognition in normal controls and predicts changes over time
Social cognition is defined as the ability to construct representations of others, oneself,
and relations between others and oneself (Adolphs, 2006). This is the result of welladjusted emotions processing, salient perception, attribution style and data gathering
(van Hooren et al., 2008). It has been reported that stable differences in the tendency
to attribute meaning and emotional value to experiences is associated with the tendency
to express psychotic symptoms and thus may represent an indicator of liability to
psychosis (Galdos et al., 2011; Catalan et al., 2014). These abnormal patterns of social
cognition have been measured using Facial recognition tasks (DFAR) and White Noise
test.
Methods: Baseline data on social cognition and DNA samples are available from a large
5 European Epidemiological study, EU-GEI, on first onset psychosis patients N= 905 and
N=1377 population controls. Polygenic risks scores will be calculated using the PRCise
program.
Measures of social cognition will be repeated at 3 years follow up in a subsample estimated N=100 controls and 200 patients. This proposal will focus on the controls,
which represents epidemiological samples of the population of each EU country part of
the study.
Degraded Facial Affect Recognition (DFAR) task
DFAR task (van ‘t Wout et al., 2004) measures emotional face recognition in degraded
photographs of four different actors (two females, and two males) representing four
emotions: angry, fearful, happy, and neutral. Subjects are asked to indicate the
expression of each face by a bottom press. In order to increase the difficulty and to
enhance the contribution of perceptual expectancies and interpretation, the emotions
are shown with 75% intensity.
White noise task
Subjects are presented 25 fragments of 3 different types of stimuli: white noise only,
white noise + clearly audible neutral speech, and white noise + barely audible neutral
speech. They are asked to respond to each by pressing 1 of 5 buttons hereafter referred
to as 1: positive speech illusion (endorsed hearing positive voice), 2: negative speech
illusions (endorsed hearing negative voice), 3: neutral speech illusion (endorsed hearing
neutral voice), 4: no speech heard, and 5: uncertain (Galdos et al., 2011).
The students will participate in the follow up data collection and will carry out the
appropriate analyses, to:
1) identify patterns of social cognition in the controls samples
2) estimate the variance in social explained by PRS for SCZ in the control samples
3) Investigate changes in DFAR and white noise test profile between baseline and
follow up and their association with PRS for Schizophrenia.
References
Adolphs R. How do we know the minds of others? Domain-specific, simulation, and
enactive social cognition. Brain Research. 2006; 1079(1), 25-35.
Galdos M, Simons C, Fernandez-Rivas A, Wichers M, Peralta C, Lataster T, Amer G,
Myin-Germeys I, Allardyce J, Gonzalez-Torres MA, van Os J. Affectively salient meaning
in random noise: a task sensitive to psychosis liability. Schizophrenia Bulletin. 2011;
37(6), 1179-1186.
van Hooren S, Versmissen D, Janssen I, Myin-Germeys I, à Campo J, Mengelers R, van
Os J, Krabbendam L. Social cognition and neurocognition as independent domains in
psychosis. Schizophrenia Research. 2008; 103, 257-265.
van’t Wout M, Aleman A, Kessels RPC, Laroi F, Kahn RS. Emotional processing in a nonclinical psychosis-prone sample. Schizophrenia Research. 2004; 68, 271-281.
Supervisor:
Dr Marta Di Forti
23. In patients with a psychotic disorder, do Polygenic risks scores for
Obesity explain independently of Antipsychotic treatment changes in body
mass index between baseline and 5 years follow up?
Population-based retrospective studies have shown that the standardized mortality ratio
(SMR), which compares the observed mortality in a cohort suffering from severe mental
illnesses with the expected mortality rates in a demographically matched standard
population, has been rising in recent years. One set of explanations of upward SMR
trend points to the adverse health outcome of long term antipsychotic (AP) medication,
mainly in terms of premature cardiovascular diseases. Strong evidence exists for two
modalities through which SGAs raise cardio mortality risk: either directly by cardio toxic
effects; or indirectly by hypothalamic dysregulation of appetite due to the blockade of
both histamine 1 (H1) serotonin 2C (5HT2C). The latter way results in a severe impact
on weight gain, leading to dyslipidaemia; lack of exercise; hypertension; and eventually
increasing body mass index (BMI), with the activation of the cascade towards the insulin
resistance.
Primary hypothesis:
1.
Patients in long-term AP treatment 5 year after psychosis onset would have greater
increased in BMI compared to patients who discontinued APs and healthy controls.
2.
The above will be independent of individual PRS for Obesity scores and substance
misuse (i.e. tobacco smoking)
Methods: From a large first episode psychosis case/control European study, the EUGEI
project, we have available baseline data on medication, clinical assessments, Ethnicity,
socio-demographics substance misuse, anthropometric measurement and GWAS data on
cases N=905; and controls =1300.
The on-going 5 years follow up of the London site of the EUGEI sample (N=200) aims to
repeat anthropometric measurement and collect data on medication and on substance
misuse over the follow up period on both cases and controls. PRS for Obesity will be
calculated using the PRSice program.
References
Hoang, U., R. Stewart, and M.J. Goldacre, Mortality after hospital discharge for people
with schizophrenia or bipolar disorder: retrospective study of linked English hospital
episode statistics, 1999-2006. BMJ, 2011. 343: p. d5422.
Zhang JP, Lencz T, Zhang RX, Nitta M, Maayan L, John M, et al. Pharmacogenetic
Associations of Antipsychotic Drug-Related Weight Gain: A Systematic Review and Metaanalysis. Schizophr Bull 2016; 42: 1418-37
Benjamin W. Domingue .Polygenic Risk Predicts Obesity in Both White and Black Young
Adults.PlosONE July 2014 | Volume 9 | Issue 7 | e101596
Supervisor:
Dr Evangelos Vasssos
24. The association of response time variability with ADHD and autism traits:
specific or common neurocognitive impairment?
Although attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders
(ASD) show significant behavioural and genetic overlap (Rommelse, Franke, Geurts,
Hartman, & Buitelaar, 2010; Simonoff et al., 2008; Sinzig, Walter, & Doepfner, 2009),
the mechanisms underlying such co-occurrence are under-explored. A potential
candidate for investigation is response time intra-subject variability (RT-ISV), a
suggested marker of attentional lapses. However, direct comparisons of RT-ISV
measures in ASD versus ADHD in clinical and general population samples are limited.
Studies examining the RT distribution have shown that high RTV is largely determined
by an excess of a few ultra-slow RTs, which may reflect periodic lapses in attention
(Castellanos & Tannock, 2002; Weissman, Roberts, Visscher, & Woldorff, 2006). The
proposed project aims to examine, using RT-distribution analyses, which portions of the
RT distribution are linked to ADHD symptoms and which to ASD traits.
The student will analyse RT data from a general population sample of 1312 children,
who participated to the Study of Activity and Impulsivity Levels in children (SAIL)
(Kuntsi et al., 2006). Data are available from a task probing attentional processes (Fast
Task), which includes a slow, unrewarded baseline condition and a comparison condition
with faster stimulus presentation and rewards. The analysis will aim to examine whether
high RT distribution subcomponents relate to elevated scores of parent ratings on ADHD
or ASD symptoms or both, with the possibility to extend the analysis to additional
psychopathology traits.
References
Castellanos, F. X., & Tannock, R. (2002). Neuroscience of attention-deficit/hyperactivity
disorder: the search for endophenotypes. Nat Rev Neurosci, 3(8), 617-628.
Kuntsi, J., Rogers, H., Swinard, G., Borger, N., van der Meere, J., Rijsdijk, F., et al.
(2006). Reaction time, inhibition, working memory and 'delay aversion' performance:
genetic influences and their interpretation. Psychol Med, 36(11), 1613-1624.
Rommelse, N. N., Franke, B., Geurts, H. M., Hartman, C. A., & Buitelaar, J. K. (2010).
Shared heritability of attention-deficit/hyperactivity disorder and autism spectrum
disorder. Eur Child Adolesc Psychiatry, 19(3), 281-295.
Simonoff, E., Pickles, A., Charman, T., Chandler, S., Loucas, T., & Baird, G. (2008).
Psychiatric disorders in children with autism spectrum disorders: prevalence,
comorbidity, and associated factors in a population-derived sample. J Am Acad Child
Adolesc Psychiatry, 47(8), 921-929.
Sinzig, J., Walter, D., & Doepfner, M. (2009). Attention deficit/hyperactivity disorder in
children and adolescents with autism spectrum disorder: symptom or syndrome? J Atten
Disord, 13(2), 117-126.
Weissman, D. H., Roberts, K. C., Visscher, K. M., & Woldorff, M. G. (2006). The neural
bases of momentary lapses in attention. Nat Neurosci, 9(7), 971-978.
Supervisor:
Professor Jonna Kuntsi
25.
Characterising developmental trajectories of infant temperament
Early infant temperament, which reflects domains such as emotional regulation, affect,
adaptability, activity and inhibition, may predispose children to and be predictive of later
psychiatric disorders and functional impairment. Previous work has focused on
temperament at one time-point in infancy, so we know little about the developmental
trajectories of temperament in typical and atypical populations.
This project will be part of the ongoing Early Development in Tuberous Sclerosis (EDiTS)
study, a longitudinal study of infants with TS, which is a rare genetic disorder associated
with a high incidence of autism, ADHD and intellectual disability. In order to understand
how early development is altered in TS, we are also collecting information with typically
developing infants. We are using a range of assessments, including innovative portable
eye-tracking, which can be administered in the home environment. Infants are being
seen at multiple time points in the first two years of life, with temperament being
assessed using selected activities from the Laboratory Temperament Assessment
Battery (Lab-TAB) and the Infant Behaviour Questionnaire (IBQ-R).
The student will be trained in the assessments of temperament and have the
opportunity to collect and analyse data from both typically developing infants and
infants with TS in the home environment, depending on availability and timing. We will
conduct longitudinal statistical analyses. The student will be encouraged to develop his
or her own ideas and hypotheses in relation to temperament coding and the extensive
EDiTS protocol.
References
Sayal, K., Heron, J., Maughan, B., Rowe, R., & Ramchandani, P. (2014). Infant
temperament and childhood psychiatric disorder: longitudinal study. Child: care, health
and development, 40(2), 292-297.
Tye, C., Varcin, K., Bolton, P., & Jeste, S.S. (2016). Early developmental pathways to
autism spectrum disorder in tuberous sclerosis complex. Advances in Autism, 2(2), 8493.
www.edits-study.org
Supervisor:
Dr Charlotte Tye
26.
Happily Depressed
Genetic studies typically focus on discovering risk alleles associated with traits, diseases
and disorders, such as smoking, diabetes and depression. However, far less emphasis
has been placed on discovering genetic alleles that protect individuals from such
outcomes. There is now evidence that this focus on identifying risk alleles has led
genome-wide association studies to miss potentially many protective alleles residing in
the genome1. It is extremely important that these protective alleles are detected
because they are more likely to be better targets for the development of drugs to treat
harmful diseases and disorders.
To illustrate the action of protective factors, consider smoking. Despite being one of the
leading causes of death there is a sizable minority of individuals who smoke heavily
throughout life but live to an old age, indicating possible genetic markers protecting
them from the damaging effects of long-term smoking2. Likewise, there are individuals
highly exposed to HIV infection who remain uninfected.
The aim of this project is to identify protective genetic factors in psychiatry. This will be
done by performing genetic association testing on samples of individuals who are at
high risk of suffering from a disorder but who do not – for example, individuals who
have been exposed to a large number of traumatic events, or who are highly neurotic,
but who do not suffer from depression or individuals with a particularly high genetic risk
for psychiatric disorders but who remain healthy. The project will require performing
genome-wide association testing, some programming (eg. in R and bash) and will
involve application to various real data sets. In addition, multivariate analyses will be
performed using the software MultiPhen2.
References
Chan et al. 2014. An excess of risk-increasing low-frequency variants can be a signal of
polygenic inheritance in complex diseases. Am.J.Hum.Genet. 94: 437-52.
Levine, M. E. & Crimmins, E. M. 2016. A Genetic Network Associated With Stress
Resistance, Longevity, and Cancer in Humans. J. Gerontol. A. Biol. Sci. Med. Sci. 71,
703–712.
O'Reilly et al. 2012. MultiPhen: Joint Model of Multiple Phenotypes can increase
discovery in GWAS. 7(5): e34861.
Supervisors:
Dr Sam Choi
27.
The chicken and egg of medical research
Much of medical research focuses on discovering associations between potential risk
factors and outcomes such as diseases or psychiatric disorders. While the direction of
causal effect may sometimes be clear (such as smoking leading to lung cancer), for the
vast majority of associations identified in medical or epidemiological studies, the
direction of causal effect is unknown and there may often be effects in both directions
(eg. BMI - Depression, Cannabis smoking - Schizophrenia, Urbanisation –
Schizophrenia1,2).
The aim of this project is to develop a statistical genetic approach to infer which
direction of effect dominates in the relationship between two phenotypes. The polygenic
nature of complex diseases will be exploited here, with a key intuition being that if, say,
cannabis smoking leads to schizophrenia more than the reverse, then all genetic
variants for cannabis smoking should also affect schizophrenia but there could still be
many genetic variants affecting schizophrenia with no effect on cannabis smoking. The
project will require the application of the PRSice software3 (www.PRSice.info), some
programming (eg. in R and bash) and will involve both computational simulations and
application to real data to test how well the method works in real life examples.
References
Power, RA et al. 2014. Genetic predisposition to schizophrenia associated with increased
risk of cannabis. Mol.Psychiatry. 19: 1201-4.
Krabbendam, L and van Os, J. 2005. Schizophrenia and Urbanicity: A Major
Environmental Influence—Conditional on Genetic Risk. Schizophr Bull. 31: 795-99.
Euesden, J., Lewis, CM., O'Reilly, PF. 2015. PRSice: Polygenic Risk Score software. 31:
1466-68.
Supervisors:
Dr Sam Choi & Dr Paul O’Reilly
28.
A polygenic risk score for psychiatry
The application of polygenic risk scores (PRS) to gain insights into disease aetiology, in
particular in psychiatric genetics, is burgeoning. PRS are being used to infer the
heritability of different diseases and disorders, to estimate the level of shared genetic
aetiology among related disorders1, to establish causality between putative risk factors
and diseases, and are being viewed as a key tool in the future of precision medicine2,3.
However, PRS are usually calculated so that they only capture the genetic risk for a
single disease or disorder, so that, for instance, there is no polygenic risk score for
immunology or psychiatry.
The aim of this project is to construct a polygenic risk score that represents an
individuals’ risk of developing any psychiatric disorder - which is important because we
know that there are strong connections and correlations between many psychiatric
disorders. Once a ‘polygenic risk score for psychiatry’ has been developed, then the
student will apply this to a variety of real data to test whether individuals with a high
score really are at high risk of suffering from one of the major psychiatric disorders. The
project will require the application of the PRSice software4 (www.PRSice.info), some
programming (eg. in R and bash) and will involve both computational simulations and
application to real data to test how well this approach works in real life examples.
References
Power, RA et al. 2014. Genetic predisposition to schizophrenia associated with increased
risk of cannabis. Mol.Psychiatry. 19: 1201-4.
Chatterjee, N et al. 2016. Developing and evaluating polygenic risk prediction models
for stratified disease prevention. Nature Reviews Genetics. 17: 392-406.
Breen, G et al. 2016. Translating genome-wide association findings into new
therapeutics for psychiatry. Nature Neuroscience. 19: 1392-1396.
Euesden, J., Lewis, CM., O'Reilly, PF. 2015. PRSice: Polygenic Risk Score software. 31:
1466-68.
Supervisor:
Dr Paul O’Reilly
29.
Genetic prediction using UK Biobank
This project will use UK Biobank data to investigate how cardiovascular disease, cancer
and age-at-mortality are mediated by psychiatric disorders.
The UK Biobank recruited 500,000 people aged between 40-69 years in 2006-2010 from
across the UK to take part in this longitudinal, epidemiological project. There are
detailed baseline measures of health, with follow-up information from a detailed mental
health questionnaire (led by the IoPPN), cancer registry data, hospital episode statistics
and death registry.
This project will develop1 and apply multivariate models of prediction of major
morbidities such as heart disease, stroke and cancer, and assess how the these are
influenced by presence of a mental health disorder or genetic susceptibility to
psychiatric disorders. Genetic susceptibility to major morbidities and to psychiatric
disorders2 will be estimated using polygenic risk scores3.
Specific Aims:
(1)
How accurately can the risk of morbidity and major morbidity be estimated using
multivariable prognostic models based on detailed epidemiological risk factor
data?
(2)
How does diagnosis with a mental health disorder affect these risks?
(3)
Do polygenic risk scores of psychiatric disorders provide additional predictive
value for non-psychiatric co-morbidities?
Training will be given in use of the UK Biobank data, high performance computing, and
statistical modelling.
References
Chatterjee, N et al. 2016. Developing and evaluating polygenic risk prediction models
for stratified disease prevention. Nature Reviews Genetics. 17: 392-406.
Breen, G et al. 2016. Translating genome-wide association findings into new
therapeutics for psychiatry. Nature Neuroscience. 19: 1392-1396.
Euesden, J., Lewis, CM., O'Reilly, PF. 2015. PRSice: Polygenic Risk Score software. 31:
1466-68.
Supervisors:
Professor Cathryn Lewis & Dr Paul O’Reilly
30. Genetic risk for psychiatric disorders and reproductive fitness in the
general population
Psychiatric disorders usually onset in early reproductive age and affected individuals
have significantly fewer offspring compared with the general population1. This, along
with the substantial heritability and prevalence of psychiatric disorders, raises the
question of why variants that increase the risk of such diseases have not been purged
from the gene pool by natural selection.
The mechanism by which susceptibility alleles for mental disorders persist in the
population remains elusive, but two key mechanisms have been proposed to explain this
evolutionary paradox2,3,4. Mutation-selection balance postulates that selection
against deleterious sequence variants is balanced by the continuous occurrence of new
mutations. Balancing selection suggests that genes for psychiatric disorders are
beneficial under some circumstances, compensating for negative selection in affected
individuals. Indeed, genetic risk for schizophrenia and bipolar disorder has been
associated with creativity, in the general population of Iceland5.
We will test the two proposed mechanisms using genomic data in a sample of 500,000
subjects in the UK Biobank. Psychiatric disorders have a polygenic component arising
from the combined effect of many common risk variants with small effect sizes.
Polygenic risk scores (PRS) for five psychiatric disorders will be generated using
PRSice software from the results of the largest available genome-wide association
studies on schizophrenia, bipolar disorder, autism, attention deficit hyperactivity
disorder and major depression. Zero-inflated Poisson models will be used to test for
association between PRS and fecundity, defined as number of children born to
individuals in the UK Biobank. Sex-specific analyses will also be conducted.
This study will provide insight into the current selection pressures on common genetic
variants for psychiatric disorders in the general population. The project will involve
working with large phenotypic and genotypic datasets, statistical analysis in R software
and polygenic risk scoring using PRSice.
References
Power, R. A. et al. Fecundity of patients with schizophrenia, autism, bipolar disorder,
depression, anorexia nervosa, or substance abuse vs their unaffected siblings. JAMA
psychiatry 70, 22-30 (2013).
Keller, M. C. & Miller, G. Resolving the paradox of common, harmful, heritable mental
disorders: which evolutionary genetic models work best? Behav. Brain Sci. 29, 385-404
(2006).
Uher, R. The role of genetic variation in the causation of mental illness: an evolutioninformed framework. Mol. Psychiatry 14, 1072-1082 (2009).
van Dongen, J. & Boomsma, D. I. The evolutionary paradox and the missing heritability
of schizophrenia. Am J Med Genet B Neuropsychiatr Genet 162B, 122-136, (2013).
Power, R. A. et al. Polygenic risk scores for schizophrenia and bipolar disorder predict
creativity. Nat. Neurosci. 18, 953-955 (2015).
Supervisor:
Professor Cathryn Lewis
31.
DNA methylation and psychotic experiences at age 18
Psychotic experiences in adolescence (e.g., hearing or seeing things that others don’t,
having unusual beliefs, etc.) are less common than in childhood, but are predictive of
both psychotic disorders and other psychopathologies [1]. Uncovering biomarkers
associated with pre-clinical psychotic experiences during this period has the potential to
facilitate identification of at-risk individuals, and improve targeting of preventive
interventions.
Despite high estimates of genetic influence on psychotic experiences in young
individuals, there is still considerable discordance within monozygotic (MZ) twin-pairs,
indicating that person-specific non-genetic factors are also important in mediating their
onset [2]. Epigenetic processes are dynamic mechanisms that have the potential to
regulate gene expression without changing the underlying genetic sequence, and as
such may be one potential biomarker in the aetiology of psychotic experiences.
Research in MZ twin pairs discordant for psychosis and in patient-control samples has
identified DNA methylation differences associated with clinically-relevant psychosis [3,
4]. Previously published work from the E-Risk study found epigenetic variation
associated with childhood psychotic symptoms [5]. However, to date, no studies have
investigated epigenetic variation with respect to concurrent psychotic experiences in late
adolescence/early adulthood.
In this project, the student will conduct analyses to investigate whether DNA
methylation patterns at age 18 are associated with concurrent psychotic experiences in
discordant monozygotic twins. This represents a powerful strategy in epigenetic
epidemiology as identical twins are matched for a number of potential confounding
effects [6]. The sample will be taken from the E-Risk cohort, a longitudinal twin study
which tracks the development of a birth cohort of 1,116 British twin pairs.
References
Kelleher, I., et al., Prevalence of psychotic symptoms in childhood and adolescence: a
systematic review and meta-analysis of population-based studies. Psychological
Medicine, 2012. 42(9): p. 1857-1863.
Zavos, H.M.S., et al., Consistent etiology of severe, frequent psychotic experiences and
milder, less frequent manifestations: a twin study of specific psychotic experiences in
adolescence. JAMA psychiatry, 2014. 71(9): p. 1049-1057.
Dempster, E.L., et al., Disease-associated epigenetic changes in monozygotic twins
discordant for schizophrenia and bipolar disorder. Human molecular genetics, 2011.
20(24): p. 4786-4796.
Pidsley, R., et al., Methylomic profiling of human brain tissue supports a
neurodevelopmental origin for schizophrenia. Genome biology, 2014. 15(10): p. 483.
Fisher, H.L., et al., Methylomic analysis of monozygotic twins discordant for childhood
psychotic symptoms. Epigenetics, 2015. 10(11): p. 1014-1023.
Mill, J. and B.T. Heijmans, From promises to practical strategies in epigenetic
epidemiology. Nature reviews. Genetics, 2013. 14(8): p. 585-594.
Supervisors:
Dr Susanna Roberts & Dr Helen Fisher
32. Functional characterisation of top hits from epigenome-wide metaanalyses of hippocampal volume
The highly complex structure of the human brain is strongly shaped by genetic factors
that can have lasting effects on brain functions associated with cognition, behaviour and
predisposition to disease. Yet, although inter-individual variations in human brain
structure and function exist and are heritable, scientists are just beginning to identify
genes that influence the human brain. Within the context of international consortia, we
have conducted large-scale genetic analyses of magnetic resonance imaging (MRI)
scans and identified genetic variants influencing the volumes of specific subcortical
regions, such as the putamen, the hippocampus and the caudate nucleus (1).
We have now extended this work by peforming the first epigenome-wide association
studies of blood DNA methylation with brain measures in 3,337 individuals from 11
cohorts and identified two CpG loci influencing the volume of the hippocampus.
For this project, we propose to characterise differentially methylated loci that associate
with hippocampal volume. The student will analyse collected data to test if these CpG
loci associate with gene expression and cognition, as measured by the CANTAB
neuropsychological assessments. The student will also perform experiments aimed at
quantifying expression the levels of the associated genes in the mouse and human brain
samples. This will involve mRNA extraction from various brain regions, real-time PCR
and comparative gene expression analysis.
References
Hibar et al. Nature. 2015 Apr 9;520(7546):224-9
Ruggeri B et al. Am J Psychiatry. 2015 Jun;172(6):543-52
Supervisor:
Dr Sylvane Desrivières
33. Developing bio-behavioural risk/prediction models of eating disorders,
weight gain and obesity in a large well-characterised cohort
Eating disorders (EDs) are disabling psychiatric disorders, with a peak age of onset of
15–25 years. One in every six or seven young women has an eating disorder that, if
untreated, has lasting effects on brain, body, behaviour and life expectancy.
Furthermore, 30-40% of people with bulimia nervosa or binge eating disorder (i.e. the
most common EDs) are or will become obese, making them susceptible to obesityrelated complications. Early intervention is key in achieving full recovery. Yet very little
is known about neurobiological predictors of EDs that might allow targeted prevention or
early intervention.
The aims of this project are to elucidate the neurobiological basis of EDs and identify
predictor of EDs, weight gain and obesity in young adulthood.
1. The student will familiarise themselves with the neurobiological basis of EDs and
obesity (1) and the conceptual and practical aspects of the IMAGEN project (2) and
database.
2. They will utilise IMAGEN behavioural and body mass index (BMI) data (ages 14 to 19)
to identify and characterise different clusters of participants with distinct trajectories of
eating disorder symptoms (e.g., restrained eating, binge eating and/or purging) and
BMI change.
3. Using age 14 IMAGEN data, the student will identify environmental, neural, genomic
and psychological factors to characterize the different clusters derived.
References
Kaye WH, Fudge JL, Paulus M. New insights into symptoms and neurocircuit function of
anorexia nervosa. Nat Rev Neurosci. 2009 Aug;10(8):573-84.
Schumann G, Loth E, Banaschewski T, Barbot A, Barker G, Büchel C, Conrod PJ, Dalley
JW, Flor H, Gallinat J, Garavan H, Heinz A, Itterman B, Lathrop M, Mallik C, Mann K,
Martinot JL, Paus T, Poline JB, Robbins TW, Rietschel M, Reed L, Smolka M, Spanagel R,
Speiser C, Stephens DN, Ströhle A, Struve M; IMAGEN consortium. The IMAGEN study:
reinforcement-related behaviour in normal brain function and psychopathology. Mol
Psychiatry. 2010 Dec;15(12):1128-39.
Supervisors:
Dr Sylvane Desrivières
34. Can the integration of cortical GWAS and brain expression Quantitative
Trait Loci (eQTLs) boost our ability to identify genes that contribute to
human cognitive abilities?
Changes in brain volumes are hallmarks of several common neurological and psychiatric
disorders, including intellectual disability. Given that a network of cortical brain areas
involved in general cognitive functions (1), we have begun the investigation of genetic
influences that shape the brain (2). Learning and memory deficits of subjects with
intellectual disability are associated with decreased size of the hippocampus and
impairments of the prefrontal cortex and hippocampal system. In agreement, we found
that genetic variation affecting spatiotemporal expression of genes related to cognitive
abilities in the hippocampus and/or the cortex affect human cognitive abilities (3, and in
press).
We would like to extend these analyses to genome-wide and brain-wide dimensions to
identify genes that contribute to human cognitive abilities.
The project (that can be shared by two students) will:
1. Make use of data collected in the IMAGEN cohort of healthy adolescents to correlate
cortical and subcortical brain structures with measures of cognitive function (memory,
attention and executive function, as assessed by the Cambridge Neuropsychological Test
Automated Battery (CANTAB)).
2. Integrate our genome-wide association studies (GWAS) of cortical measures
(thickness and surface area) of individual brain regions (selected from step 1, above),
brain gene expression data (eQTLs) and a selection of genes known to affect cognitive
abilities to generate polygenic risk scores (PRS) for each selected brain region.
3. Test how well such PRS can predict brain structure and their associated cognitive
measure(s).
4.A wet-lab aspect of the project will compare the expressions of the top PRS signals in
regions of the mouse and the human brains.
References
Deary IJ, et al. The neuroscience of human intelligence differences. Nat Rev Neurosci.
2010 Mar;11(3):201-11.
Hibar et al. Common genetic variants influence human subcortical brain structures.
Nature. 2015 Apr 9;520(7546):224-9.
Desrivières S, et al. Single nucleotide polymorphism in the neuroplastin locus associates
with cortical thickness and intellectual ability in adolescents. Mol Psychiatry. 2015
Feb;20(2):263-74.
Supervisors:
Dr Sylvane Desrivières
35.
Individual Differences in Perception of Agency
Our sense of control over our actions and their consequences is a crucial component of
self-awareness. Yet, until recently, there has been little investigation into individual
differences in our awareness of our control. Moreover, the extent to which individual
differences in other related processes predict metacognitive awareness of our own
control has yet to be tested. This will be the primary goal of your MSc project.
You will examine the value of personality factors, higher order beliefs of control and
motivation from control in predicting metacognition of our control. This will be the first
study to systematically investigate individual differences in styles of perception of
control and will have important implications for intervention research in clinical
conditions where perception of control is shown to break down (e.g. Schizophrenia).
References
Moore, J. W., & Bravin, J. (2015). Schizotypy and awareness of intention: Variability of
W judgments predicts schizotypy scores. Psychology of Consciousness: Theory,
Research, and Practice, 2(3), 283.
Eitam, B., Kennedy, P. M., & Higgins, E. T. (2013). Motivation from control.
Experimental brain research, 229(3), 475-484.
Metcalfe, J., & Greene, M. J. (2007). Metacognition of agency. Journal of Experimental
Psychology: General, 136(2), 184.
Supervisor:
Dr Geoff Bird
36.
How self-experience influences social perception
In many areas of social perception, self-experience shapes our ability to perceive others
(e.g. emotion perception, movement perception). Recently, it has been shown that
individuals with autism spectrum disorder show atypical movement patterns (compared
to controls) and higher levels of atypicality correlate with a bias towards judging
biological movement as unnatural.
The current project will investigate how self movement experience influences perception
of movement in others. There will be a focus on how movement similarity influences
perception of others. Additionally, the extent to which we can modulate self-experience
(and the resulting impact on perception of others) will be explored. This work has
important implications for individuals with ASD.
References
Cook, J.L., Swapp, D., Pan, X., Bianchi-Berthouze, N. & Blakemore, S-J. (2014). Atypical
interference effect of action observation in autism spectrum conditions. Psychological
Medicine. 44(4):731-40.
Cook, J. L., Blakemore, S-J. & Press, C. (2013). Atypical basic movement kinematics in
autism spectrum conditions. Brain. 136(9):2816-24.
Lane, R. D., Sechrest, L., Riedel, R., Shapiro, D. E., & Kaszniak, A. W. (2000). Pervasive
emotion recognition deficit common to alexithymia and the repressive coping style.
Psychosomatic medicine, 62(4), 492-501.
Supervisor:
Dr Geoff Bird
37.
The Recognition of Facial Emotion in Older adults
Facial expression recognition follows an inverted U-shaped curve across the lifespan
peaking at middle age. Whilst not always observed, generally specific deficits are
observed for negative emotions in older adults, a pattern of performance referred to as
the 'positivity bias' (e.g., Horning et al., 2012).
The exact reason for this age related decline is unclear although it has been suggested
that processing speed (Horning et al., 2012), general cognitive ability (West et al.,
2012) and personality (Grady et al., 2007) may play a role.
One possibility is that alexithymia and impaired interoception also contribute towards
the observed age related decline. Alexithymia increases with age (Mattila et al., 2006),
interoceptive awareness, as measured by heartbeat tasks, decreases with age (Khalsa
et al., 2009) and alexithymic individuals appear to have the greatest difficulties with
negative emotions (e.g., Jessimer & Markham, 1997) as do older adults (e.g., Horning
et al., 2012).
By testing participants from early adulthood into older adulthood this experiment aims
to examine the contribution of previously highlighted factors (e.g., IQ) and possible
factors (e.g., alexithymia/interoceptive awareness) to the well-documented age related
decline in emotion recognition.
References
Horning, S. M., Cornwell, R. E., & Davis, H. P. (2012). The recognition of facial
expressions: An investigation of the influence of age and cognition. Aging,
Neuropsychology, and Cognition, 19(6), 657-676.
West, J. T., Horning, S. M., Klebe, K. J., Foster, S. M., Cornwell, R. E., Perrett, D., ... &
Davis, H. P. (2012). Age effects on emotion recognition in facial displays: From 20 to 89
years of age. Experimental aging research, 38(2), 146-168.
Grady, C. L., Hongwanishkul, D., Keightley, M., Lee, W., & Hasher, L. (2007). The effect
of age on memory for emotional faces. Neuropsychology, 21(3), 371-380.
Jessimer, M., & Markham, R. (1997). Alexithymia: a right hemisphere dysfunction
specific to recognition of certain facial expressions?. Brain and cognition, 34(2), 246258.
Khalsa, S. S., Rudrauf, D., & Tranel, D. (2009b). Interoceptive awareness declines with
age. Psychophysiology, 46(6), 1130-1136.
Mattila, A. K., Salminen, J. K., Nummi, T., & Joukamaa, M. (2006). Age is strongly
associated with alexithymia in the general population. Journal of psychosomatic
research, 61(5), 629-635.
Supervisor:
Dr Geoff Bird
38. Electrophysiological markers of ASD and ADHD in tuberous sclerosis
complex
Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are
common neurodevelopmental disorders that frequently co-occur. Our understanding of
the genetic and neurobiological basis of these conditions is limited, but recent research
highlights the importance of abnormalities in the development of connections between
key parts of brain circuitry. In our current research, headed by Professor Patrick Bolton
at the SGDP, we are investigating this further by analysing electrophysiological patterns
of neural connectivity in already acquired data from children with ASD, ADHD, and ASD
with co-occurring ADHD (ADHD+ASD). We are also collecting new electrophysiological
data from children and young people with tuberous sclerosis complex (TSC), a rare
genetic condition that carries a high risk for both ASD and ADHD but has a known cause
(mutation on the TSC1 or TSC2 genes). We will assess whether individuals with TSC and
co-occurring ASD/ADHD show the same connectivity abnormalities as individuals with
ASD/ADHD without TSC. The MSc student(s) joining this project will be involved in
collecting new electrophysiological data from individuals with TSC and their siblings, as
well as analysing the existing electrophysiological data.
Supervisors:
Dr Lizzie Shephard
39. The Colombo Twin and Singleton (CoTaSS) study: The genetic aetiology
of Post-Traumatic Stress Disorder in a non-western population
The CoTaSS-1 and follow-up CoTaSS-2 studies are Wellcome Trust funded projects
based in Sri Lanka. The overall aim of these studies was to investigate the genetic
aetiology of mental health variables as well as cardiovascular and metabolic risk
markers in a south Asian population. In this project the student will perform univariate
and multivariate Structural Equation Model-fitting twin analyses on PTSD questionnaire
data.
Background
Post-traumatic stress disorder (PTSD) is a mental health condition that may develop
after a terrifying ordeal, involving physical harm or the threat of physical harm. In the
CoTaSS-1 study participants were asked about different traumatic exposures (excluding
sexual trauma)1. Despite high rates of trauma exposure (36.3%), the prevalence of
PTSD was lower (2%) compared to high-income populations.
PTSD, like most complex behavioural traits, is due to the interplay of genetic and
environmental factors. In high risk as well as population samples, the risk to trauma
exposure and PTSD were shown to be influenced by genetic factors (30-40%)2,3. PTSD
and trauma exposure were also shown to be (genetically) linked to depression and
anxiety symptoms4. To date no PTSD heritability estimates are reported for non-western
populations.
Technically speaking, PTSD is a difficult variable to model as it cannot be assessed in
individuals who have not experienced a traumatic event. Rather than treating this
information as missing, the use of a causal contingency common pathway (CCC) model
is suggested. It involves modelling two causally linked liabilities (trauma exposure and
PTSD), which means that in addition to the heritability of each trait we can also assess
the aetiological relationship between them. In first instance the student will investigate
the CCC model described above. If this part of the modelling is successful, we will
consider adding depression and/or anxiety measures to the model. Questionnaire data
were collected in personal interviews conducted during home visits and available for a
sample of 1950 twin pairs and 2000 singletons.
References
1. Dorrington, Zavos, Ball, McGuffin, Rijsdijk, Siribaddana, Sumathipala & Hotopf
(2014). Trauma, post-traumatic stress disorder and psychiatric disorders in a
middle-income setting: prevalence and comorbidity. Br J Psychiatry, 205(5):
383–389.
2. Lyons, Goldberg, Eisen, True, Tsuang, Meyer et al. (1993). Do genes influence
exposure to trauma? A twin study of combat. Am J Med Genet, 48: 22-27
3. Stein, Jang, Taylor, Vernon & Livesley (2002). Genetic and Environmental Influences
on Trauma Exposure and Posttraumatic Stress Disorder Symptoms: A Twin Study.
Am J of Psychiatry, 159(10): 1675-1681.
4. Sartor, Grant, Lynskey et al., (2012). Common Heritable Contributions to Low-Risk
Trauma, High-Risk Trauma, Posttraumatic Stress Disorder, and Major Depression.
Arch Gen Psychiatry, 69(3): 293–299.
5. Kendler, Neale, Sullivan, Corey, Gardner & Prescott (1999). A population-based twin
study in women of smoking initiation and nicotine dependence. Psychol Med, 29,
299-308.
Supervisors:
Fruhling Rijsdijk, Helena Zavos & Matthew Hotopf
40. The genetic and environmental overlap between depression and fatigue
in a population of Sri-Lankan twins and singletons
The CoTaSS-1 and follow-up CoTaSS-2 studies are Wellcome Trust funded projects
based in Sri Lanka. The overall aim of these studies was to investigate the genetic
aetiology of mental health variables as well as cardiovascular and metabolic risk
markers in a south Asian population. In this project the student will perform univariate
and bivariate Structural Equation Model-fitting twin analyses on fatigue and depression
questionnaire data.
Background
Chronic fatigue syndrome (CFS) is a primarily characterised by severe persistent or
relapsing fatigue lasting for 6 months or longer accompanied by somatic and cognitive
symptoms (1). Whilst the precise etiology of CFS is unclear, there have been a number
of studies showing that psychiatric disorders, including depression, represent a
significant risk factor for the development of CFS (e.g. 2). Behavioural genetic research
has shown that both CFS and depression are moderately heritable. Shared genes may
therefore drive the association between CFS and depression. The evidence from twin
studies investigating the etiological overlap between CFS and depression is mixed.
Several studies have found little support for a genetic overlap (e.g.4), however others,
including a study using the current sample, have found modest evidence of shared
genes (5).
The current project would seek to replicate previous research in the current sample
using continuous measures of fatigue and depression. This will expand previous work
which used dichotomous definitions of depression and fatigue. We will consider adding
a longitudinal element to the analysis if time allows and of interest to the student.
Questionnaire data were collected in personal interviews conducted during home visits
and available for a sample of 1950 twin pairs and 2000 singletons.
References
1.
Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A, et al. The
Chronic Fatigue Syndrome - a Comprehensive Approach to Its Definition and
Study. Ann Intern Med. 1994;121(12):953-9.
2.
Watanabe N, Stewart R, Jenkins R, Bhugra DK, Furukawa TA. The
epidemiology of chronic fatigue, physical illness, and symptoms of common
mental disorders: a cross-sectional survey from the second British National
Survey of Psychiatric Morbidity. Journal of psychosomatic research.
2008;64(4):357-62. Epub 2008/04/01.
3.
Hempel S, Chambers D, Bagnall AM, Forbes C. Risk factors for chronic fatigue
syndrome/myalgic encephalomyelitis: a systematic scoping review of multiple
predictor studies. Psychological medicine. 2008;38(7):915-26. Epub
2007/09/26.
4.
Fowler TA, Rice F, Thapar A, Farmer A. Relationship between disabling fatigue and
depression in children: genetic study. The British journal of psychiatry : the journal of
mental science. 2006;189:247-53. Epub 2006/09/02.
5.
Ball HA, Sumathipala A, Siribaddana SH, Kovas Y, Glozier N, McGuffin P, et al.
Aetiology of fatigue in Sri Lanka and its overlap with depression. The British journal of
psychiatry : the journal of mental science. 2010;197(2):106-13. Epub 2010/08/04.
Supervisors:
Helena Zavos & Fruhling Rijsdijk
41.
Cellular Aging in Schizophrenia
Telomeres are regions of repetitive nucleotide sequences at the end of each
chromosome, and act to protect the chromosome from deterioration or from fusion with
neighbouring chromosomes. Older individuals (who have experienced a greater number
of cell divisions) characteristically have shorter telomeres.
Telomere length has been characterised as a “molecular clock” measuring cellular aging
effects. Schizophrenia diagnosis is associated with shorter lifespan (10-25 years). This
suggests that accelerated ‘cellular aging’ may be a mechanism involved in the
pathophysiology of schizophrenia.
Studies have revealed shorter telomere lengths amongst schizophrenia patients but
most studies performed so far have utilised relatively small samples sizes (<100) and in
only medicated patients. Thus, larger studies are now required to confirm whether
shorter telomeres are a consistent feature of schizophrenia.
We will use a quantitative PCR protocol to assess differences in relative telomere length
between ~450 schizophrenia cases (including treatment naïve samples) and ~250
control subjects using DNA extracted from blood. The results will provide conclusive
evidence as to whether advanced cellular aging is a molecular mechanisms underlying
schizophrenia. This is a largely wet-lab based project.
Supervisors:
Dr Tim Powell
42.
Gene-Environment Interactions in Major Depressive Disorder
Childhood stress (emotional abuse, physical abuse, sexual abuse, emotional neglect,
physical neglect) can have devastating effects on later life psychiatric health, increasing
the risk for illnesses such as major depressive disorder in adulthood. In addition, genetic
backgrounds can moderate the risk of major depressive disorder in response to
childhood stress.
Studies have consistently shown increased cellular aging (reduced telomere length) in
the DNA (blood) of adults who have experienced childhood stress, and amongst major
depressive disorder patients, suggesting advanced cellular aging may be involved in
major depressive disorder pathophysiology. If shortening telomere length are involved
in the pathophysiology of major depressive disorder, then we would expect genetic
factors controlling telomere length to interact with childhood stress to moderate
telomere length and the likelihood of major depressive disorder case/control status in
adulthood.
This study involves three parts. First, based on results from a recent genome-wide
association study, we will construct a ‘genetic risk score’ for telomere length by
combining data derived from single nucleotide polymorphisms predictive of telomere
length. Secondly, we will validate the genetic risk score by testing if it predicts telomere
length in an independent sample, generated in-house. Finally, we will test if the genetic
risk score interacts with childhood stress to predict major depressive disorder
case/control status, using genotype and childhood trauma questionnaire data collected
as part of Depression Case Control Study (DeCC).
This project is primarily dry-lab but additional wet lab work (telomere quantification)
can be made available if the student so requests.
Supervisors:
Dr Tim Powell
43. DNA methylation in telomerase-encoding genes and its relationship to
major depression and childhood stress
Telomeres are regions of repetitive nucleotide sequences at the end of each
chromosome, and act to protect the chromosome from deterioration or from fusion with
neighbouring chromosomes. Older individuals (who have experienced a greater number
of cell divisions) characteristically have shorter telomeres. Telomere length has been
characterised as a “molecular clock” measuring cellular aging effects. Epigenetic factors
have been found to contribute to differences in telomere length and might be one factor
contributing to the shorter telomere lengths present amongst major depressive disorder
patients, and adults who have experienced childhood stress (emotional abuse, physical
abuse, sexual abuse, emotional neglect, physical neglect).
In this study we will quantify DNA methylation (blood) at two loci known to significantly
affect telomere length at the genetic level, telomerase RNA component (TERC) and
telomerase reverse transcriptase (TERT). We will relate methylation data generated in
this project to telomere data (generated elsewhere) and clinical data collected as part of
the Depression Case Control Study (DeCC). Specifically, we will test whether
methylation status at each loci: (i) significantly predicts telomere length; (ii)
differentiates major depressive disorder cases from controls, (iii) is significantly affected
by childhood maltreatment.
This is primarily a wet-lab based project.
Supervisors:
Dr Tim Powell & Dr Agnes Kepa
44. Does perception of trustworthiness gleaned from facial first impressions
differ in ASD populations?
Character trait inferences based on first impressions from faces are thought to result
from overgeneralisation between emotion cues (e.g. smiling) and a trait (e.g. a friendly
person). In line with this proposal the structural resemblance between facial features
(e.g., narrow eyes) and emotions (e.g., anger) predicts observers' trait evaluations of
faces (Said et al., 2009). Despite evidence suggesting that inferences made on the
dimension of trustworthiness are particularly poor (Efferson, & Vogt, 2013) faces
deemed to be untrustworthy are generally better recalled than faces deemed
trustworthy (Rule et al., 2012) and have a lasting impact on future appraisals (Cassidy,
& Gutchess, 2014).
Reliable social processing differences have been reported across clinical populations;
people with Autism Spectrum Disorders (ASD) generally exhibit more trusting behaviour
than typically developing (TD) populations (Yi, Pan, Fan, Zou et al., 2013) and may
show a tendency to process faces in a piecemeal fashion rather than holistically
(Weigelt, Koldewyn & Kanwisher, 2012), whilst people with alexithymia (a condition
characterised by difficulties recognising emotions) display atypical trait judgements from
faces (Brewer et al., 2015). Crucially, whilst the incidence of alexithymia in the general
population is approximately 10%, the incidence of alexithymia in people with ASD may
be 50% (e.g., Hill et al., 2004).
The aim of the proposed research is to investigate whether the perception of
trustworthiness gleaned from facial first impressions differs in ASD populations, and the
extent to which these changes can be quantified by concurrent alexithymia and/or a
tendency to process faces in a piecemeal fashion rather than holistically.
Supervisor:
Dr Geoff Bird
45. Is interoceptive ability a unified phenomenon or and how does this
impact perception within a target clinical population?
Recent predictive coding models of social cognition and selfhood make a novel
prediction: that our ability to understand ourselves and others is a product of
interoception (the ability to perceive the state of our own body). Interoception underlies
a range of social abilities and impairment in interoceptive ability (IA) is responsible for
specific social symptoms across a number of psychiatric conditions such as Autism
Spectrum Conditions, Eating Disorders, and Major Depressive Disorder.
However, as IA is a broad construct that refers to an awareness of various internal
processes (heart rate, muscular effort, internal temperature etc.) the degree to which IA
is a unitary phenomenon remains unclear. Moreover, as IA is typically measured by
awareness of only one bodily signal (heart rate), it is unknown whether people in
different clinical populations have difficulties with all aspects of IA, and how this relates
to social features of their condition.
By testing participants on a battery of interoceptive tests this project will aim to
establish whether IA is a unified phenomenon or varies as a function of the particular
bodily signal to be perceived.
Work will also focus on a target clinical population (likely Autism Spectrum Disorder,
Eating Disorder or depression); to establish the specific bodily signals patients have
difficulties perceiving and how they relate to social features of the condition.
Supervisor:
Dr Geoff Bird
46. Can alexithymia severity also predict individuals' ability to perceive time,
in those with and without ASD?
Alexithymia is a condition associated with difficulties understanding one's own emotions
and is common in individuals with autism spectrum disorder (ASD). Recent work
suggests that alexithymia may also be associated with problems understanding nonemotional signals from one’s body (e.g. tiredness, hunger etc), and other abilities that
rely on the anterior insula, as this is the main brain region implicated in alexithymia.
Alexithymia has been found to impair the ability to detect one’s own heart beats, for
example, but this task also involves the ability to track time, which also relies on the
anterior insula.
This project will therefore investigate whether alexithymia severity can also predict
individuals' ability to perceive time, in those with and without ASD.
Supervisor:
Dr Geoff Bird
47.
Fear conditioning in young adults: A feasibility study
Fear conditioning is a useful model for the acquisition of fears and phobias, and offers a
paradigm with which to explore aetiological processes underlying their development.
Furthermore, behavioural treatments of anxiety disorders such as exposure therapy, are
based on the related process of extinction (see below). The fear conditioning paradigm
involves systematically pairing an innocuous stimulus (e.g. a light) with an aversive
stimulus (e.g. loud sound or mild shock). The innocuous stimulus is referred to as the
conditional stimulus (CS), the aversive stimulus as the unconditional stimulus (US) and
the fear reaction as the conditional response (CR) {vervliet, 2013}. It is also possible to
remove such fears by presenting the innocuous stimulus (CS) without the aversive
stimulus (CS) which typically leads to a reduction in the fear reaction (CR). This is
known as extinction.
Our group is interested in understanding the role of genetic and environmental
influences on anxiety and it’s treatment. With this in mind we are planning a large twin
study of fear conditioning and extinction. In preparation for this we will be running a
pilot study to explore which paradigms are most useful for our purposes. Specifically, we
will be looking for tasks that show good test re-test reliability and correlations with selfreported anxiety symptoms. Second, we are interested both in tasks that require in
person testing within a lab, and tasks that can be undertaken online, thus allowing for
data collection from a far larger sample.
The student chosen to work on this study will run the pilot study jointly with an SGDP
1+3 student, and will get involved in all associated data management and analyses with
support from the supervisors.
Supervisors:
Prof Thalia Eley, Dr Kathryn Lester, Dr Tom Barry
48. Exploring potential gene-environment interaction between CallousUnemotional traits and measures of social disadvantage
Introduction
Previous studies have found that genetic influence on antisocial behaviour (ASB) is
higher in more advantaged backgrounds (Raine, 2002; Tuvblad, Grann & Lichtenstein,
2006), suggesting that only in disadvantaged environments is the environment of great
importance to the aetiology of ASB. To date such hypotheses have not (to our
knowledge) been investigated in relation to callous-unemotional (CU) traits. We
hypothesise that, using the G1219 twin and sibling study, we will find that genetic
influence on ASB and CU will be greatest in the least disadvantaged environments.
Often CU traits are used to identify heterogeneous groups of antisocial individuals –
those with and without CU traits. Those with CU traits are typically identified as being
more pathological, persistent, violent, and less susceptible to environmental
risk/protective factors than those without. We will also therefore explore hypotheses
within each group separately, assessing whether SES moderates the aetiology of ASB in
both groups, or only those low in CU traits.
Method
You will use the Genesis 12-19 Twin and Sibling Study to decompose the aetiology of
young adult callous-unemotional behaviour. Using Purcell’s (2002) gene-environment
interaction model (GxE), you will evaluate the extent to which genetic and
environmental influences on callous-unemotional behaviour varies according to
measures of social disadvantage (social problems and socioeconomic status).
Supervisor:
Dr Tom McAdams
49.
Pharmacogenetics of anti-depressant response
Personalised medicine is heralded as the next major advance in clinical care. However,
our ability to use genetics to predict disease prognosis, drug response, or drug sideeffects is very limited and few genetic tests are routinely applied in clinic to determine
efficacy of drugs.
In psychiatry, antidepressants may be the most widely prescribed drugs but response
rates for major depressive disorder are low: complete remission is achieved in only 1/3
of patients and many patients must try several different drugs before finding one that is
effective. About 30 different drugs are available, but no effective predictive algorithms
exist to guide prescribing. Using genetics to help predict response to antidepressants
would be a substantial achievement. Several genome-wide association studies using
large patient cohorts have been performed to identify variants that are associated with
response to antidepressants, but these have failed to identify individual genetic variants,
and it seems likely that a polygenic architecture underlies the genetic component of
antidepressant response.
In this project, we will move the focus from identifying single genetic variants, to test
the predictive ability of polygenic risk scores, which combine many genetic variants into
a single measure of genetic liability. Available data sets include the GENDEP study
(from the IoPPN, with EU clinical sites), and STAR*D, a US clinical trial. We will use
results from the Psychiatric Genomics Consortium (PGC) in depression, bipolar disorder
and schizophrenia to construct risk scores for disease liability, and test whether these
predict response to antidepressants in GENDEP and STAR*D. We will test prediction
between these data sets using GENDEP as a discovery study to create scores in STAR*D
patients, and vice versa. This can also be extended to anti-depressant treatments in
bipolar disorder patients, using polygenic scores in the STEP-BD study.
Obtaining positive predictive power in these studies is important in both confirming a
genetic component to antidepressant response, and in forming the first steps to build
pharmacogenetic models that could be used in clinical settings.
This project will enable the student to gain valuable experience in the polygenic risk
score methodology and in pharmacogenetics studies. The methodology applied here is
widely applicable across genetic studies in psychiatry, psychology and behaviour.
References
Uher R, et al. Genome-wide pharmacogenetics of antidepressant response in the
GENDEP project. Am J Psychiatry. 2010 May;167(5):555-64. doi:
10.1176/appi.ajp.2009.09070932.
Fabbri C, Serretti A. Pharmacogenetics of major depressive disorder: top genes and
pathways toward clinical applications. Curr Psychiatry Rep. 2015 17(7):50. doi:
10.1007/s11920-015-0594-9.
New England Centre for Investigative Reporting. http://features.necir.org/more-harmthan-good. More harm than good? Use of genetic mental health tests has grown
rapidly. But evidence they work is scant.
Supervisors:
Professor Cathryn Lewis & Dr Chiara Fabbri
50. Adverse life events and psychosocial risk factors in women with ADHD
and women with BD
Attention deficit hyperactivity disorder (ADHD) and bipolar disorder (BD) affect
approximately 2-3% and 1-2%, respectively, of the adult population worldwide.
They represent a major clinical and economic burden on society. ADHD and BD
often co-occur in adults, and an elevated risk for ADHD is found in first-degree
relatives of probands with BD, and vice-versa.
While both disorders are moderately-to-highly heritable and may share genetic
factors, environmental factors may also play a role in influencing each disorder
and their comorbidity. Increased rates of environmental risk factors (including
adverse life events and psychosocial factors) and social functioning impairments
have been reported in individuals with ADHD and individuals with BD. However,
our understanding of whether these disorders are associated with similar or
different environmental risk factors, and of how these factors are related to the
clinical symptoms and impairment within each disorder, is as yet limited.
The proposed project aims to compare data on life events, psychosocial
functioning and copying strategies in a sample of 20 women with ADHD, 20
women with BD and 20 control women collected as part of the Female
Experiences and Brain activity (FEBA) project. The association between these
variables and the level of clinical symptoms and impairment associated with
either disorder will also be examined.
The results of this project will shed light on the psychosocial and environmental
risk factors associated with ADHD and BD. Ultimately, these new data may lead
to an improved delineation of the pathophysiology of the two disorders and their
comorbidity.
Supervisors:
Dr Jonna Kuntsi & Giorgia Michelini
51. The role of DNA methylation in the development of youth conduct
problems and comorbid psychiatric symptoms
Abstract:
Conduct problems (CP; e.g. fighting, stealing) are a major public health concern and the
leading cause of youth treatment referral in the UK. Compared to typically developing
youth, CP youth are more likely to have experienced childhood adversity (e.g. maternal
depression, harsh parenting, family conflict) and to develop a range of comorbid
psychiatric symptoms, such as depression, anxiety, and hyperactivity. However, little is
currently known about the biological mechanisms by which environmental adversity
increases risk of CP and comorbid symptoms.
The aim of this project is to investigate the role of DNA methylation - an epigenetic
mechanism sensitive to environmental influences - in the development of CP and
comorbid symptoms. Analyses will be based on longitudinal data on environmental risk
(pre/postnatal), DNA methylation (birth-age 7) and psychiatric outcomes (age 4-18),
drawn from the Avon Longitudinal Study of Parents and Children, and will involve a
combination of epigenome-wide analyses and structural equation modelling.
The project will offer students an exciting opportunity to learn about epigenetic
processes in the context of psychiatric health, as well as to develop skills in a range of
methodologies and statistical packages (R, Mplus).
Supervisors:
Dr Charlotte Cecil (First), Dr Edward Barker (Second)
52. Neuropsychological correlates of childhood maltreatment: systematic
review and meta-analysis
Childhood maltreatment has been associated with heightened risk of later
psychopathology, unfavourable longitudinal course of psychiatric illnesses, and poor
treatment response. These mental health sequelae are likely to be, at least partly,
explained by abnormal brain function in individual who have experienced or reported
childhood maltreatment. Several studies have tested neuropsychological differences in
individuals with and without a history of childhood maltreatment.
The proposed project aims to undertake a quantitative summary of this literature and to
identify sources of biases and artefacts.
Supervisor:
Dr Andrea Danese
53. Anorexia nervosa: Identifying risk factors affecting survival rates in
genetic subtypes of anorexia – doing epidemiology in clinical records
Anorexia nervosa (AN) is one of the deadliest psychiatric illnesses and while some
individuals may eventually recover, others struggle throughout their lifetime with
recurring bouts of low weight and disordered eating. Studies indicate that AN is among
the leading causes of death in young women. The Clinical Record Interactive Search
(CRIS) database is a repository of patient records and contains valuable information on
aspects of a patient’s life that may represent risk.
The aim of the project will be to examine patient record data from anorexia nervosa,
extracted from the CRIS database, to evaluate which factors impact survival rates more
than others. As comorbidity is a common feature of anorexia, the CRIS database will be
particularly useful for assessing how specific subtypes may be more vulnerable to
certain comorbid disorders.
The value of this approach has been demonstrated by the recent paper investigating
comorbidity and opioid addiction (Bogdanowicz et al, 2015) in which the CRIS database
was used.
Supervisors:
Dr Gursharan Kalsi and Dr Gerome Breen
54. Anorexia Nervosa: Exploring the genetic relationship between anorexia
nervosa, body mass index and metabolic traits in the UK BioBank cohort
Anorexia nervosa (AN) is one of the deadliest psychiatric illnesses and while some
individuals may eventually recover, others struggle throughout their lifetime with
recurring bouts of low weight and disordered eating. Mounting evidence is suggesting a
biological basis for the illness and twin studies indicate that genetic factors make a
substantial contribution to disease etiology.
Large GWAS data has now become available from AN and the use of a method called LD
Score regression has shown novel genetic correlations between AN and BMI (-0.35) and
Insulin Resistance (-0.36). This type of correlation is unconfounded by the downstream
effects of starvation in AN and indicates an aetiological link. These observations have led
to a developing reconceptualization of AN as both a psychiatric and metabolic based
disorder.
The MSc project will examine genetic correlations between AN, BMI, lipids and related
factors in the UK BioBank GWAS cohort (currently 150K subjects) using both LD Score
and polygenic scoring methods. This project would suit a student keen to learn data
analysis approaches as well as someone keen to develop new metabolic theoretical
thinking for anorexia nervosa.
Supervisors:
Dr Gerome Breen & Paul O’Reilly
55.
Investigate the effect of Fam19A2 in Eating disorder patients
Cytokines and chemokines are small signalling proteins secreted primarily by immune
cells. Their main function is to coordinate cell growth, proliferation, and differentiation.
Cytokines and their receptors participate in a diverse array of functions including innate
and adaptive immunity, inflammation, immune cell differentiation, angiogenesis,
tumorigenesis, development, neurobiology, and viral pathogenesis. Cytokines like TNF-α
has been shown to inhibit adipogenesis and increase lipolysis(Batista et al., 2012).
Chronic administration of TNF (Soscher et al., 1997), or IL-1 to rats or mice (Bendzten
et al., 1988, Butler et al., 1989) results in significant anorexia and weight loss.
Alternatively, the blockade of IL-1 and inhibition of TNF in rats results in the inhibition of
anorexia and increased food intake (Laviano et al., 2000; Opara et al., 1995; Torelli et
al., 1999). A more recent study in humans found that RANTES was elevated in 4
patients while IL-6 was elevated in two; only one patient had an elevated in TNF-α of 33
patients (Pisetsky et al., 2015).
In this study we plan to investigate the effects of a chemokine FAM19A2 in the plasma
of eating disorder patients. FAM19A2 has recently been identified in a recent GWAS
study in eating disorder patients.
Supervisor:
Aoife Keohane
56.
The advantages of being on the spectrum
Psychiatric disorders are often associated with negative life outcomes and a reduction in
number of offspring. However, we now know that many psychiatric disorders are highly
genetic in their aetiology. This raises what many describe as an ‘evolutionary paradox’,
because evolution generally acts to remove genetic alleles from the genome that have a
negative impact on phenotype.
This project hypothesises that this apparent paradox is explained by individuals with a
high genetic burden for a psychiatric disorder (autism, schizophrenia, bipolar etc)
having positive life outcomes - including more offspring - compared to the general
population, despite the negative life outcomes of those with extremely high genetic
burden. Or in other words, that there may often be a non-linear relationship between
genetic burden and phenotype.
Genetic burden will be measured here using polygenic risk scores. A motivating
example could be to test whether an increased genetic burden of autism is first
associated with increased cognitive ability before the association becomes negative for
extremely high genetic risks, which we may expect to observe if science departments
are indeed enriched for individuals ‘on the spectrum’ [1].
The project could also follow-up on intriguing findings earlier this year from Power et al
[2] that individuals with a high genetic burden of schizophrenia and bipolar have higher
levels of creativity when compared to the general population.
References
[1] Clarke TK et al. 2015. Common polygenic risk for autism spectrum disorder (ASD) is
associated with cognitive ability in the general population. Molecular Psychiatry. DOI:
10.1038/mp.2015.12
http://www.nature.com/mp/journal/vaop/ncurrent/full/mp201512a.html
[2] Power RA. 2015. Polygenic risk scores for schizophrenia and bipolar disorder predict
creativity. Nature Neuroscience 18: 953-55.
http://www.nature.com/neuro/journal/v18/n7/abs/nn.4040.html
Supervisor:
Paul O’Reilly
57.
A new approach to gene*environment and gene*gene interaction studies
One of the key questions in biology is: how does our genetic make-up interact with our
environment (‘nature and nurture’) to produce the diseases, disorders and traits that we
experience during life? Despite the scientific and public intrigue into this question, it is
rarely explicitly tested.
So called ‘gene*environment interaction studies’ have been an important part of genetic
epidemiology over the last two decades, but this project investigates the hypothesis that
it is not the interaction between specific genetic variants and the environment (or other
genetic variants) that tackles the central question (given the small effect of individual
genetic variants) but that instead it is the interaction between overall genetic
predispositions and the environmental context that produce human phenotypes.
In this project you will calculate polygenic risk scores in order to measure the overall
genetic susceptibility to disorders of interest. Examples of the specific hypotheses that
you could test in this project are: Does a high genetic burden of environmental
sensitivity interact with stressful life events to increase the risk of schizophrenia? Does a
high genetic burden for addictive behaviour interact with risk taking behaviour to
increase the risk of substance abuse? Or does a genetic predisposition for high IQ
interact with a genetic predisposition for high conscientiousness to produce positive life
outcomes (such as social mobility).
There are many such questions, as well as any that you find interesting, that can be
tested within this project.
Supervisor:
Paul O’Reilly
58. Uncovering the causal relationships underlying genetic correlations
between phenotypes
Right now in psychiatric genetics there are a huge number of studies being performed
and published showing genetic correlations across different psychiatric disorders, as well
as between psychiatric disorders and a range of behavioural, psychological and physical
traits. However, at this stage only the genetic correlations are typically being reported
rather than more in-depth investigations of the causal mechanisms underlying these
correlations.
This project seeks to explore the reasons for the observed correlations and follows-up
on recent work (from Paul O’Reilly and Adam Socrates at the SGDP) that many of the
genetic correlations may not in fact point to shared genetic aetiology but may instead be
mediated by behavioural or lifestyle factors. A motivating example from this recent work
was the observation that a genetic predisposition for a higher educational qualification
was negatively associated with beer drinking but positively associated with wine
drinking, which more likely represents mediation by a change in lifestyle (attending
university) than an inherent biological connection between thirst for knowledge and
thirst for wine. In the same way, this project will attempt to discover the real reasons
underlying numerous intriguing genetic correlations among psychiatric, psychological
and physical outcomes.
Supervisor:
Paul O’Reilly
59. Using genetics to investigate the interaction between physical and
psychiatric health
A critical question in medical research is: how much interaction is there between
physical and psychiatric health? There is now mounting evidence indicating that there
are important biological links between the two, but much research is required to fully
understand how they interact.
This project will build polygenic risk scores (PRS) on broad aetiological categories – such
as metabolic PRS, immune-based PRS and psychiatric PRS – and explore whether cases
for psychiatric or physical diseases can be stratified according to several psychiatric and
physical forms of aetiology.
A second aim of the project will be to test directly for interactions between the genetic
susceptibility of physical and psychiatric disease, to test whether psychiatric disorders
are exacerbated by physical ill-health and vice versa. Given the scope of this research
topic there are a huge number of specific questions that could be asked and tested
within this project.
Supervisor:
Paul O’Reilly
60. Family environment and the persistence of ADHD into young adulthood?
A prospective longitudinal study
ADHD is now recognized to occur in adulthood and is associated with a range of
negative outcomes. However, less is known about the prospective course of ADHD into
adulthood, the risk factors for its persistence past childhood, and the possibility of its
emergence in young adulthood in non-clinical populations.
We found in a population cohort of young adults that characteristics of the family
environment did not distinguish individuals who persisted from those who remitted,
except that families of persistent individuals had comparatively higher maternal warmth
and less maternal depression (Agnew-Blais et al., under review). This finding is
surprising and deserves further investigation. It is possible that some children exhibit
symptoms in response to poor family environments, but once these individuals move
away from home, symptoms abate. However, other aspects of the environment were
not less compromised in the persistent group, suggesting that if this association is
causative, it may be specific to pathways related to maternal-child bonding.
For this project, we propose to examine the association between children’s family
environment and the persistence of ADHD into young adulthood to understand how and
why it may be linked to the persistence of the disorder.
This project is based on data from the Environmental Risk (E-Risk) Longitudinal Twin
Study, which tracks the development of a birth cohort of 2,232 British children (Moffitt
et al., 2002). We ascertained ADHD diagnosis in childhood on the basis of mother and
teacher reports of symptoms of inattention and hyperactivity-impulsivity and adult
ADHD diagnosis based on private structured interviews with participants at age 18. We
collected measures of the family environment when the participants were age 5.
References:
Agnew-Blais, J.C, Polanczyk, G., Danese, A., Wertz, J., Moffitt, T.E., & Arseneault L.
(under review). Persistence, remission and emergence of ADHD in young adulthood:
Results from a longitudinal, prospective population-based cohort. JAMA Psychiatry.
Moffitt, T.E., & the E-Risk Study Team (2002). Teen-aged mothers in contemporary
Britain. Journal of Child Psychology and Psychiatry, 43, 727-742.
Supervisors:
Jessica Agnew-Blais & Louise Arseneault
61. Is parent-youth disagreement in reports of parenting predictive of young
adults’ antisocial behaviour? A prospective longitudinal study
When parents and their children are asked to provide information about the family
environment, such as aspects of parenting, they often disagree with each other. For
example, we have previously shown that parents think of themselves as knowing more
about their children’s lives than children think they do (Wertz et al., under review). Such
disagreements between parents and children are a well-established finding in child
development research and reflect the different perspectives that parents and children
have on their environments.
There is some evidence to suggest that the extent of disagreement can be as useful
indicator of the quality of the parent-child relationship, and that it can predict children’s
future antisocial behaviour. In this student project, we want to test this hypothesis, by
examining whether parent-child disagreement is predictive of children’s future antisocial
behaviour and whether disagreement is associated with aspects of the family
environment in early childhood. We will look at disagreement in parental monitoring,
which includes parents’ setting of rules about where children go, and with whom.
This project will use data from the Environmental Risk (E-Risk) Longitudinal Twin Study,
which tracks the development of a birth cohort of 2,232 British children (Moffitt et al.,
2002).
At age 12, we asked mothers, youth and a subsample of fathers about the extent to
which youths’ activities are regulated by parents’ rules. We have identified different
types of disagreements and agreement in parental rule-setting between parents and
youth, such as parents reporting that they are setting rules whereas youth report that
parents do not; or both parents and youth agreeing that parents are setting rules. We
assessed children’s antisocial behaviour at age 5, 7, 10, 12 and 18. We also assessed
information on the family environment at ages 5 and 7.
Supervisors:
Louise Arseneault & Jasmin Wertz
62. Is parental monitoring an effective strategy for parents to reduce their
children’s antisocial behaviour? A prospective longitudinal study
Antisocial behaviours are the most common type of behavioural problem in children and
young people and significantly compromise their development and well-being. One
suggested strategy to reduce and prevent antisocial behaviour during adolescence is to
encourage parents to track their children’s activities and whereabouts, including setting
rules about where children go, and with whom. These behaviours of parents are defined
as “parental monitoring”. However, previous research has raised doubts about the
effectiveness of parental monitoring, with several studies, including our own (Wertz et
al., under review) suggesting that parents’ monitoring does not prevent or reduce
youths’ future antisocial behaviour.
One possible explanation for this finding is that parental monitoring may not be effective
under certain circumstances, for example if the parent-child relationship is bad, or if
children have already been behaving defiant and aggressive from an early age. In these
situations, parents’ attempts to monitor their children and to set rules may actually
make problems worse, and lead to more parent-child conflict and more problem
behaviour.
This student project tests this hypothesis, by examining how increases (or decreases) in
parents’ monitoring between ages 10 and 12 affect youths’ antisocial behaviour at age
18, depending on the quality of the parent-child relationship and youths’ antisocial
behaviour in early childhood.
This project will use data from the Environmental Risk (E-Risk) Longitudinal Twin Study,
which tracks the development of a birth cohort of 2,232 British children (Moffitt et al.,
2002).
We assessed parents’ monitoring at age 10 and age 12 and children’s antisocial
behaviour at age 5, 7, 10, 12 and 18. We assessed information on the parent-child
relationship at age 5 and 7.
Supervisors:
Louise Arseneault & Jasmin Wertz
63. To identify genes that relate to brain structure and/or behaviour in
adolescents
Project Background: The overall goal of the project is to understand how the
environment influences adolescent brain development and the development of
psychopathology. However, genetic influences, including genes involved in
immunological processes, are likely to be important mediators.
MSc Project Goal: To identify genes that relate to brain structure and/or behaviour in
the adolescent IMAGEN sample. This would require knowledge of statistical software
(e.g., SPSS) and learning genome data analysis (via PLINK software).
Supervisor:
Erin Quinlan
64.
Finding biomarkers in brain behaviour relationships in ADHD
Attention-deficit/hyperactivity disorder (ADHD) symptoms include impulsivity,
hyperactivity, and inattention. The disorder is thought to be dimensional, with the most
extreme manifestations clinically diagnosed as ADHD according to DSM-IV 1 and 2.
Recently, a great deal of attention has been focused on the brain-behaviour
relationships in ADHD disorder.
By using about 300 samples from the IMAGEN study, we aim to investigate whether
there is an association between ADHD symptoms and resting-state functional
connectivity. Especially, we will use an exhaustive brain-wide association study at both
regional and voxel-based levels to find out biomarkers for ADHD.
Supervisors:
Bing Xu and Gunter Schumann
65. Robust personalised daily activity classifier for remote monitoring of
patients with mental health issues
Mental disorders, as well as received treatment, may impact daily activities of patients.
How they feel may also result in changes of their physical behaviour patterns. For
example, patients may become less active, feeling sleepy and fatigued; or vice versa,
hyperactive, irritated or aggressive. Remote monitoring is one of the means to identify
such changes.
The setup is based on a single accelerometer attached to the patient’s body is an
established way to track their daily activities. In fact, there are many wearable devices
available on the market which report periods of various activities such as walking,
running, sitting or lying down. However, the employed algorithms for recognising and
classifying activities are either too general (i.e. are set up to perform well on average),
or other way round – too specific requiring calibration of the algorithms for each
subject.
The problem in both cases is that such algorithms don’t account for different qualities of
the same activity performed by the same person. This makes the algorithms useless in
the scenarios where identifying subtle changes in movement patters over time is crucial
(e.g. as a result of recovery of deterioration of a health condition).
This project will explore features extracted from raw accelerometer data identifying
those which are more suitable for describing inter-person variability (different styles of
performing the same activity by the same person) and intra-person variability (different
styles of performing the same activity by different people). These features will then be
used to build a classifier of various types of daily activities performed with different
quality by the same and different subjects. The classifier will become a basis for a
remote monitoring platform which is robust to inter- and intra-person variability
allowing for more accurate monitoring of disease progression.
Supervisor:
Dr Yevgeniya Kovalchuk
66.
Developmental disorders and transient gestational hypothyroidism
Transient hypothyroidism during the first trimester of pregnancy is a poorly explored
risk factor in childhood cognitive development. To date, there has been no research into
the underlying biological mechanisms that might explain how damage to very early
embryonic endocrine function predisposes the child to behavioural disorders. Our
preliminary data suggests thyroid hormone disruption specifically disrupts the formation
of cerebellar nuclei, which mediate connections between the cerebellum and the rest of
the brain.
We will test a hypothesis in mouse models that transient gestational hypothyroidism
generates a “cerebellar disconnection syndrome” with adverse consequences for
subsequent behavioural development. We will use a mouse model of transient
gestational hypothyroidism to test to what extent the thyroid is involved in the
development of the cerebellum and whether thyroid dysfunction leads to behavioural
deficits of relevance to neurodevelopmental disorders such as autism.
The MSc project will involve handling and testing mice, scoring and analysis of the data
collected from the behavioural tests. The student will gain experience in a range of
rodent behavioural methods, data collection and statistical analysis.
Key references:
Silverman, J.L., Yang, M., Lord, C., Crawley, J.N. (2010) Behavioural phenotyping
assays for mouse models of autism. Nat Rev Neurosci 11:490-502.
Utiger, R.D. (1999). Maternal hypothyroidism and fetal development. The New England
journal of medicine 341, 601-602.
Wang, S.S., Kloth, A.D., and Badura, A. (2014). The Cerebellum, Sensitive Periods, and
Autism. Neuron 83, 518-532.
Supervisor:
Dr Cathy Fernandes
67. DNA methylation biomarkers and susceptibility to neuropsychiatric
diseases
Roles for epigenetic modifications, including DNA methylation, in mammalian early brain
development, postnatal development and aging, and in the etiology of neuropsychiatric
disorders is increasingly being recognized. Recent large-scale studies from our
laboratories and others have indicated that measuring DNA methylation in easily
accessible tissues, such as in peripheral blood, shows promise as a biomarker for
neuropsychiatric disorders. Few studies, focusing on specific genes, have combined
neuroimaging data and DNA methylation to report associations between blood DNA
methylation levels and brain phenotypes. However, there is a lack of large-scale
imaging epigenetic studies.
We have now performed such epigenome-wide associations studies (EWAS) with brain
structural measures from thousands of adolescents from the IMAGEN cohort
(http://www.imagen-europe.com/en/the-imagen-study.php). Our initial analyses,
focused on subcortical brain volumes, identified top hits that indicate that variation in
DNA methylation has distinct effects on subcortical brain areas, revealing potential links
between DNA methylation, the immune system and diseases such as multiple sclerosis
and schizophrenia.
The aim of this project is to enrich these analyses by prioritizing the analysis of DNA
methylation sites based on their effect on gene expression, an effect known as
methylation-expression quantitative trait loci (methyl-eQTL). In a second step, we will
investigate the association of such methyl-eQTL with relevant disease-related
phenotypes, such as stress- and anxiety-, schizophrenia- or reward-related phenotypes,
in our IMAGEN cohort.
There is some evidence of early life changes in stress response genes through
methylation, just as early life events influence later life disease expression - notably
stroke, white matter hyperintensities, and cognitive impairment. We therefore hope that
this approach will help us unravel epigenetic mechanisms that may contribute to
neuropsychiatric endophenotypes and susceptibility to neurological or neuropsychiatric
diseases.
Supervisors:
Sylvane Desrivières & Barbara Ruggeri
68.
Brain maturation and risk factors for schizophrenia
Scientists continue to debate the relative contribution of genetic or environmental
factors to risk for various diseases, but a recent large-scale screen of schizophrenia
patient cohorts worldwide implicated over 100 genetic loci in risk for the disease. This
study pointed to several genes in the dopamine neurotransmission pathway that had
long been implicated in schizophrenia and its treatment - for example, a functional
polymorphism in the DRD2 promoter region, which modulates levels of gene expression,
and affects antipsychotic drug efficacy. This same genomic screen pointed to other
unexpected genetic variants that could offer tantalizing new leads about aetiology of the
disease. However, as the study included cases with a history of hospitalization for
treatment of schizophrenia, the identified variants may instead point to mechanisms
related to response to treatment. In addition, these associations may reflect
comorbidities, such as substance abuse in patients and even sex differences in the
dynamics of brain maturation. In this context, it is important to keep in mind the earlier
onset of schizophrenia in men compared with women; the first signs of schizophrenia,
the first positive symptoms, and the first admissions occur 3 to 5 years earlier in men.
The age range of the first sign of mental disorder is from 15 to 24 years for men
(compared with 20-29 years for women).
OBJECTIVE: The aim of this project is to disentangle such effects by analyzing the
associations between brain maturation in typically developing adolescents and a
polygenic risk score for schizophrenia and identifying drivers and moderators of such
associations.
METHODS: The analyses will be performed with data from the IMAGEN Study, a
longitudinal population-based sample of 2000 adolescents of both sexes recruited from
8 European cities (data collected at ages 14, 16 and 19). We will include information
related to (1) longitudinal changes in brain structure; (2) a polygenic risk score for
schizophrenia across 108 genetic loci identified by the PGC, and (3) information about
early and late environmental risk factors, such as pregnancy and birth complications,
social, behavioural and cognitive deficits during childhood, adverse life events and
substance abuse.
Both additive models of multiple genetic and environmental risk factors of small effect
and interactive models where genetic predisposition is compounded by environmental
effects will be tested, considering the possibility of sex-specific effects.
Supervisors:
Sylvane Desrivières & Tianye Jia
69. Genetic influences of reward sensitivity and hyperactive behaviours and
dopamine and noradrenaline receptors: developing a co-expression network
for VPS4A
In a recent paper submitted to PNAS, we found that VPS4A gene was related to both
reward sensitivity and hyperactive behaviours, which was known to be related to
dopamine or noradrenaline receptors. On the other hand, VPS4A does show strong coexpression patterns with DRD1, DRD2 (dopamine receptors) and ADRA2C
(noradrenaline receptors) in both human frontal cortex and mouse striatum data.
However, knock-out analysis in drosophila fail to provide evidence that VPS4A regulate
the expression of dopamine receptors, and therefore it is possible that there are
upstream genes that regulate both VPS4A and dopamine or noradrenaline receptors.
Nevertheless, a comprehensive co-regulation model with these genes integrated is
required to fully understand the molecular mechanisms behind the above finding.
In this proposed project, the participated MSc student is expected to complete the
following tasks:
1. Understanding causal inference model through mediation analysis
(http://www.biomedcentral.com/1471-2156/10/23).
2. Applying genome-wide mediation analysis to either identify possible upstream
regulator genes for VPS4A, DRD or ADRA genes, or establish an alternative coexpression network which could explain the co-expression patterns among these genes.
3. A more comprehensive mediation analysis can also be applied to exon expression
probes, which will help to target complicated expression patterns due to alternative
splicing, e.g. for DRD2.
Required Resources and Personal Skills:
1. Multiple expression datasets are now available online straightaway.
2. The participant is expected to be familiar with computational programming and basic
statistical models.
3. Some basic understanding of genetics is helpful but not crucial.
Outcome:
By the end of this project, a co-expression network with VPS4A, DRD and ADRA genes
integrated will be established, which will then be validated through animal models. The
hence established co-expression network would help to explain the genetic fundamental
of hyperactivity and thus suggesting possible genetic medical targets.
Supervisor:
Tianye Jia
70. Mental health meets literature: definition of causative and contributing
environmental factors
After its initial success in playing Jeopardy, Watson the IBM developed supercomputer is
now utilised in decision support for lung cancer at the Memorial Sloan Kettering Cancer
Center [1, 2]. With estimations that mental illnesses account for 11 to 27 % of the
disability burden in Europe [3] and the number of people suffering from mental illnesses
increasing [4], applications such as Watson are urgently needed to develop patientcentred and cost-effective treatments for mental illnesses. In order to improve existing
treatments and increase the recovery rate, a better understanding of the underlying
mechanisms is required. As with other diseases, it has been established that mental
illnesses are influenced in their origins and pathology by environmental factors. For
example, it has been found that higher rates of schizophrenia occur in people of
Caribbean origin than ethnically similar white people living in the UK [5]. To date, no
complete list of environmental factors for all existing mental illnesses has been compiled
that can be used for patient screening and planning treatment strategies [6].
While the published scientific literature is used in a biomedical context such as building
gene networks for disease gene discovery [7] or symptom networks of inheritable
human disorders [8], it seems to be an under-valued resource with respect to mental
illnesses. It has been rarely explored for the purpose of gaining psychopathology
insights. The potential of this resource lies within the amount and variety of data
available: all journals that publish scientific results are covered mostly since 1966,
though some even date back to 1809. In order to make use of this tremendous resource
for finding potential environmental factors that (i) cause, (ii) contribute to and (iii)
influence the origin and pathology of mental illnesses, automated methods are needed
to digest the large quantities of existing data.
In order to start on this endeavour, a preliminary study would be required to assess the
quality and the representation of environmental factors in the published literature.
Furthermore, the project covers the application of existing software tools to
automatically assess this information from the literature. While no knowledge of
automation techniques and programming are required, a keen interest in learning how
to program and do automated literature analyses is a prerequisite. An automation
framework will be set up prior to the project, ready to be worked with to extract
environmental factors. It is also expandable with respect to the findings of the project.
The work will be in line with other ongoing research projects, so that it can be
complemented in later stages depending on progress.
[1] https://en.wikipedia.org/wiki/Watson (computer)
[2] https://www.youtube.com/watch?v=WIKM732oEek
[3] T. Wykes et al. “Mental health research priorities for Europe.” The Lancet Psychiatry
(2015).
[4] http://www.bbc.co.uk/news/health-34313127
[5] W. A. Fung, et al. “Ethnicity and mental health: the example of schizophrenia in
migrant populations across Europe.” Psychiatry (2006).
[6] M. Rutter. “How the environment affects mental health.” The British Journal of
Psychiatry (2005).
[7] K. Lage et al. “A human phenome-interactome network of protein complexes
implicated in genetic disorders.” Nature Biotechnology (2007).
[8] X. Zhou et al. “Human symptoms–disease network.” Nature Communications
(2014).
Supervisor:
Anika Oellrich
71. Applied Predictive Models in Alzheimer's Disease: A Comparison of
Standard Machine Learning Methods and Evaluation of Tensorflow
A marker of Alzheimer's disease (AD) that can accurately diagnose disease at the
earliest stage would significantly support efforts to develop treatments for early
intervention. We have previously published an AD diagnostic classifier based on
peripheral blood gene expression, using Random Forests [1]. The model achieved an
overall accuracy of 75%.
Further work is needed to assess the clinical utility of the results and the robustness of
the reported model. Using the AddNeuroMed Gene Expression data [1], the student will
explore and compare different feature engineering techniques (data pre-processing,
feature selection), different predictive modelling algorithms (Random Forests, deep
neural networks, Lasso/Elastic-Net, Linear Discriminant Analysis, k-nearest neighbours,
Naive Bayes and Support Vector Machines and Adaptive Boosting).
[1] A blood gene expression marker of early Alzheimer's disease:
http://www.ncbi.nlm.nih.gov/pubmed/23042217
Machine Learning Reading
o
o
o
o
o
http://machinelearningmastery.com/
https://drive.google.com/file/d/0B0om8Cm0OfuwbFR1NDIzQXZpMEU/view?usp=s
haring
The caret package (short for Classification And REgression Training) is a set of
functions that attempt to streamline the process for creating predictive models.
http://topepo.github.io/caret/
h20: http://h2o.ai/product/
http://www.tensorflow.org/
Candidate Requirements





good computer skills
ability to think & learn for themselves & follow simple instructions
experience with R and/or Python or programming
the student must complete one or more of the tutorials from the The caret
package
As a bonus the student must complete one or more of the tutorials here:
http://www.tensorflow.org/tutorials/index.html
Supervisor:
Stephen Newhouse
72. Pharmacogenetics of Antidepressant Treatment for Major Depressive
Disorder: A Systematic Review of Candidate Gene and Genome-wide studies
Individuals with major depressive disorder differ substantially in their response to
antidepressants and indirect evidence suggests that common genetic variants contribute
substantially to these differences. Genetic predictors of antidepressant response may
allow clinicians to personalise treatments and therefore improve outcomes of major
depressive disorder. There is a wealth of literature on pharmacogenetic prediction of
antidepressant response, but the evidence is inconclusive: Reviews of candidate gene
studies suggest some replicable results, but a meta-analysis of genome-wide studies
found no replicable predictor. At present it is unclear if the difference is due to lack of
statistical power in genome-wide studies or to publication bias in candidate-gene
studies. To answer this question, there is need to synthesize results across the entire
literature and compare results from candidate gene and genome-wide studies.
We have identified 10 candidate genes with an adequate number of high quality studies
for meta-analyses. In this MSc project the student will select one of these candidates
and conduct random-effect meta-analyses including published results from candidategene studies and data extracted from two large genome-wide studies (STAR*D and
GENDEP). A significant effect of a genetic variant across both candidate-gene and
genome-wide data suggests a true association which was not detected in genome-wide
studies due to lack of statistical power. Conversely, a significant effect of a variant that
is limited to data taken from candidate gene studies would provide evidence of
publication bias. Differences in effect sizes from candidate-gene and genome-wide data
will be formally tested using meta-regression.
This project will provide students with the opportunity to learn the principles of
pharmacogenetics and the methods of systematic review and meta-analysis. The
student will also have opportunity to work with leading researchers and contribute to
writing a large, high-impact paper combining findings across each of the tested
candidate genes.
Supervisors
Robert Keers and Rudolf Uher
73. To assess the changes gene expression in blood and saliva samples in
eating disorders
Please contact Aoife Keohane for further information.
Supervisor:
Aoife Keohane
74. The Colombo Twin and Singleton (CoTaSS-2) study: The aetiological
relationship between Metabolic Syndrome and Psychiatric Disorders
CoTaSS-2 is a follow-up Wellcome Trust funded project based in Sri Lanka. The aims of
the study are: to describe the prevalence and inter-relationship of a number of key
cardiovascular and metabolic risk markers which make up “metabolic syndrome”.
Secondly, to explore the genetic architecture of metabolic syndrome phenotypes, and
estimate the extent to which phenotypic correlations are explained by shared genetic or
environmental effects. Finally, to explore the association between cardiovascular
disease, diabetes and depression in a south Asian population as well as the extent to
which genetic and environmental factors impact on these overlaps. The student will
have a choice to either perform univariate and multivariate Structural Equation Modelfitting analyse on questionnaire data or perform more epidemiological based analyses on
the population data. The available study topics for this MSc project will be discussed in
an orientation meeting and may partly depend on student’s personal interest.
Background: Metabolic syndrome is of key public health importance in South Asia,
where, with growing urbanisation, the prevalence of central obesity, type-2 diabetes
and coronary heart disease are all on the increase1. People from South Asia seem
particularly susceptible possibly because of a higher prevalence of the so called “thrifty
genotype”2, which gives an evolutionary advantage to individuals carrying the genotype
in times of food shortage, but is associated with increased risk of metabolic syndrome at
times of plenty. One of the key controversies relating to the existence or otherwise of
the metabolic syndrome is the extent to which the constituent phenotypes cluster as a
true syndrome and the degree to which this overlap may have a common aetiological
pathway. In addition to this, there could be a relationship with psychiatric disorder.
Depression is associated with incident cardiovascular disease3, as well as being a risk
factor for poor outcome in established coronary heart disease and type-2 diabetes.
These associations do not seem to be due to confounding factors such as the presence
of physical disease and variables such as smoking, obesity or alcohol consumption.
There are several theories on this association. One is that depression – via serotonergic
or hypothalamic pituitary adrenal axis pathways – may have direct pathophysiological
impacts such as altered autonomic function, or immune dysregulation. An alternative is
that shared “upstream” risk factors - which might include low birth weight, social
adversity or shared genes are responsible. Twin studies have the potential to determine
whether common genetic or environmental risk factors can explain observed phenotypic
relationships. These questions will be addressed in a sample of 1950 twin pairs and
2000 singletons. Questionnaire data were collected in personal interviews; physical
measures, anthropometrics and blood samples were collected during home visits.
References
 Bhardwaj, S., Misra, A., Khurana, L., Gulati S, et al. (2008) Childhood obesity in
Asian Indians: a burgeoning cause of insulin resistance, diabetes and sub-clinical
inflammation. Asia Pacific Journal of Clinical Nutrition 17: 172-175.
 Hoyer, E.H., Mortensen, P.B., Olesen, A.V. (2000) Mortality and causes of death in a
total national sample of patients with affective disorders admitted for the first time
between 1973 and 1993. British Journal of Psychiatry 176: 76-82.
 Yajnik, C.S., Yajnik, C.S. (2004) Early life origins of insulin resistance and type 2
diabetes in India and other Asian countries. Journal of Nutrition 134: 205-210.
Supervisors:
Helena Zavos & Fruhling Rijsdijk
75.
Twin Study of Hopelessness
Hopelessness, defined as generalized negative expectations of the future (Beck et al.
1974), has been described as one of the most important long-term risk factors for
suicide in clinical populations (Joiner et al. 2005). American Psychiatric Association
advises that hopelessness should be examined when assessing suicide risk and, if
present, should be targeted as part of a comprehensive treatment plan. In addition to
its clinical relevance, hopelessness is an interesting construct because it is strongly
associated with depression; however it is not related to anxiety (Beck et al 2006). Thus,
studying hopelessness might provide insight into depression-specific cognitive content
and vulnerabilities.
The aim of the proposed MSc project is to address several related research questions,
using data from an adolescent twin study G1219. The analyses will include using SPSS
and Stata to investigate a factor structure of Beck’s hopelessness measure and its
phenotypic association with depression and anxiety. At the quantitative genetics level,
the aetiology of hopelessness, and the genetic and environmental relationship between
hopelessness and depression remain unclear. The quantitative genetic aspect of the
project will address these questions, using twin modelling programs in R.
We will provide plenty of programming support, but an aptitude for twin modelling is
required! The project would be ideal for a student interested in clinical psychology. The
study can be extended to include a measure of attributional style, and where possible
the initial proposal is open to incorporate student’s interests and ideas. If successful, the
project might be submitted for publication in a peer-reviewed journal.
Supervisors:
Thalia Eley & Monika Waszczuk
76. The role of chromatin remodelling factors in cerebellar development and
autism
Autism is a complex genetic disorder that affects social development. Recent advances
have led to the identification of several autism-associated genes but our knowledge on
how these genetic risk factors can cause changes during brain development to result in
autistic behaviour is extremely limited. Currently, the best way to address this question
directly is to study brain development and the behavioural consequences of altered
brain development on behaviour in mice that have mutations in autism-associated
genes.
We recently produced new mouse models for investigating the roles of two genes
encoding chromodomain helicase DNA binding (CHD) chromatin remodelling factors.
CHD7 haploinsufficiency is associated with a syndromic form of autism (CHARGE
syndrome), whereas nonsense mutations in CHD8 have been identified in several
independent non-syndromic autism cases. The mechanisms underlyingChd7 plays a key
role in the development of the cerebellum, a part of the brain that is consistently
reported to show neuro-anatomical defects in autistic patients. CHD7 and CHD8 proteins
directly interact and might regulate similar pathways during cerebellar development. We
will use mouse models in which either Chd7 or Chd8 has been specifically deleted from
the developing cerebellum, to test to what extent cerebellar defects are responsible for
some of the behavioural features characteristic of autism.
The MSc project will involve handling and testing mice, scoring and analysis of the data
collected from the behavioural tests. As we will already have collected data in this
project, we also can offer a dry lab project which would involve scoring and analysis of
the behavioural data only if you do not want to work with animals directly. The student
would also be trained in genotyping methods to confirm the identity of the mice. The
student will gain experience in a range of rodent behavioural methods, DNA extraction
and genotyping, data collection and statistical analysis.
Key references:
 Hartshorne, T.S., Grialou, T.L., Parker, K.R. (2005) Autistic-like behavior in CHARGE
syndrome. Am J Med Genet A. 133A:257-261.
 Neale, B.M., et al. Patterns and rates of exonic de novo mutations in autism
spectrum disorders. (2012) Nature 485: 242-245.
 Silverman, J.L., Yang, M., Lord, C., Crawley, J.N. (2010) Behavioural phenotyping
assays for mouse models of autism. Nat Rev Neurosci 11:490-502.
Supervisors:
Cathy Fernandes & Albert Basson
77.
Epigenetic alteration of RELN in mouse models of CHARGE syndrome
The Reelin (RELN) gene encodes a secreted glycoprotein that performs key functions in
neural development. Homozygous mutations in RELN in humans cause lissencephaly
and cerebellar hypoplasia. Mice homozygous for a loss-of-function allele of Reln (reeler),
likewise exhibit cerebellar hypoplasia. Reduced RELN expression is associated with a
number of neuropsychiatric disorders including depression, schizophrenia and autism. In
the case of autism, reduced Reelin protein levels have been reported in post-mortem
autism brains (in particular the cerebellum). Intriguingly, RELN is located on
chromosome 7q22, a region that shows consistently strong association with autism in
linkage studies. Taken together, these studies imply a significant contribution of altered
RELN gene expression levels to the autism phenotype. Despite these intriguing findings,
the mechanisms that control cell type-specific expression of RELN, and in particular the
mechanisms that ensure the maintenance of robust RELN expression levels during
development are not known. Our current research focus is on understanding the
mechanisms whereby the chromatin remodelling factor CHD7 controls cerebellar
development. CHD7 is mutated in CHARGE syndrome, a developmental syndrome
associated with intellectual disability and autism. We have identified a cerebellar defects
in 50% of CHARGE syndrome patients and identified CHD7 as a critical regulator of
cerebellar granule neuron progenitor proliferation. Consequently, Chd7 deletion from
these cells result in severe cerebellar hypoplasia, foliation defects and cellular
heterotopia. We have identified Reln as a key CHD7 target gene.
The aim of this project is to determine whether downregulated Reln expression during
early postnatal cerebellar development persists into adulthood and whether reduced
developmental Reln expression may be responsible for altered DNA methylation of the
Reln promotor. DNA and RNA will be isolated from adult cerebellar (experimental) and
neocortical (control) tissue in Chd7-deficient and control mice and subjected to DNA
methylation and qPCR analyses.
Supervisors:
Albert Basson & Chloe Wong
78.
White matter pathology in the Neurexin 1 alpha knock out mouse
Structural variation in the neurexin-1 (NRXN1) gene increases risk for both autism
spectrum disorders (ASD) and schizophrenia. However, the manner in which NRXN1
gene variation may be related to brain morphology to confer risk for ASD or
schizophrenia is unknown.
Through collaboration with Dr Cathy Fernandes, my lab is engaged in phenotyping the
NRXN1 knock out mouse to identify how variation in this gene may confer increased risk
for psychiatric disorders. Recent neuroimaging studies in healthy individuals between 18
and 59 years of age demonstrate that variation in the NRXN1 gene affects brain
structure directly, particularly that of white matter, which was associated with cognitive
deficits and sensorimotor performance in these indivuduals1. Based on these data the
purpose of this project is to conduct a pilot investigation to determine the extent of
white matter pathology in post-mortem brain tissue from NRXN1 mutant mice. This will
involve sectioning of post-mortem brain tissue, immunohistochemistry for myelin basic
protein and markers of mature (GalC) and immature (NG2) oligodendroctyes, followed
by quantification of these markers using high-throughput microscopy. This will be
complemented by molecular analysis of the same markers using quantitative PCR in
different brain regions. The brain tissue has already been collected and thus no handling
of animals is required. The student will receive training in all aspects of post-mortem
histopathology and molecular work in mouse brain tissue as well as data collection and
statistical analysis.
This project has the potential to provide evidence for a neural and cognitive
susceptibility mechanism involving white matter, by which the NRXN1 gene confers risk
for both schizophrenia and ASD.
Key reference:
 Voineskos AN, Lett TA, Lerch JP, Tiwari AK, Ameis SH, Rajji TK, Müller DJ, Mulsant
BH, Kennedy JL. Neurexin-1 and frontal lobe white matter: an overlapping
intermediate phenotype for schizophrenia and autism spectrum disorders. PLoS One.
2011;6(6):e20982. doi: 10.1371/journal.pone.0020982.
Supervisors:
Anthony Vernon & Cathy Fernandes
79.
Stress, genes, brain and alcohol: association studies in adolescents
As stressful life events are key factors in the development of alcoholism, the overall aim
of this project is to identify genes that by mediating responses to stress may influence
initiation and maintenance of alcohol drinking in humans. We have identified such a
gene, using a large-scale gene x neuroimaging approach in a cohort of ~2000 typically
developing adolescents.
Further investigations into the role of this gene in predisposition to alcohol addiction will
be performed.
Supervisor:
Sylvane Desrivières
80.
Autism Spectrum Disorders and social cognition
A variety of projects on Autism Spectrum Disorders, using existing twin or
experimental-group data, or joining current cognitive projects to help collect and code
new data relevant to social cognition and adaptation in children/adults with ASD.
I like to let the student refine the exact project with me according to their interests.
Supervisors:
Professor Francesca Happé
81.
Does environment influence outcomes in Tuberous Sclerosis?
Tuberous sclerosis (TS) is a genetic disorder caused by mutations in the TSC1 or TSC2
genes, characterized by tumour-like lesions called hamartomas. Hamartomas within the
brain often act as epileptogenic foci, increasing the risk for epilepsy, intellectual
impairment and behavioural disturbances such as attention deficit hyperactivity disorder
(ADHD) and autistic spectrum disorder (ASD). Second-hit events result in random
variation between individuals in the number and location of hamartomas. TS is therefore
a true natural experiment that is uniquely informative for developmental cognitive
neuroscience. Given the known genetic aetiology of TS, much work has focussed on the
genetic pathway but the marked variability in behavioural expression despite similar
genetic origins leaves open a consideration for environmental influence.
This project will be part of the TS2000 study, the first ever UK large scale, prospective,
longitudinal study of a representative sample of children with TS. During phase 2 the
children are being assessed on cognitive and behavioural measures, with a specific focus
on intellectual impairment, ASD and ADHD. Environmental measures of obstetric risk
(Obstetric Enquiry Schedule), child early experiences (the HOME questionnaire) and
parental factors (Development and Wellbeing Assessment) are also being collected with
the aim of relating these environmental factors to outcomes and delineating potential
environmental risk pathways.
The MSc GED project will aim to determine if environmental factors impact clinical
outcome in TS. The student will work as part of the TS 2000 Study team to assist with
data collection, data entry and management and under supervision on data analysis of
some of the environmental and outcome data.
Supervisors:
Holan Liang & Patrick Bolton (1st supervisors)
Fiona McEwen & Charlotte Tye (2nd supervisors)
82. Cognitive profiles in autism spectrum disorders (ASD) and attention
deficit hyperactivity disorder (ADHD): similarities and differences across
conditions
Autism Spectrum Disorders (ASD) and Attention Deficit Hyperactivity Disorder (ADHD)
are two distinct neurodevelopmental disorders, however an increasing number of shared
behavioural, neuropsychological and neurobiological characteristics have been identified.
Despite an increase in literature documenting overlaps between the two conditions there
remains a lack of information about the comorbidity of ADHD in research into childhood
ASD. This may be due to the fact that until DSM-5 convention prevented a diagnosis of
ADHD if ASD has already been diagnosed. Further investigation of the phenotypic
overlap between ADHD and ASD is required at behavioural and neurocognitive levels as
there is a need to differentiate the disorders based on objective cognitive profiles.
Clarifying both differences and similarities between ASD and ADHD is of clinical and
research significance as this information can be used to develop strategies to improve
social functioning as well as helping to identify heritable endophenotypes in these
populations.
This MSc GED project aims to compare cognitive profiles in age-matched ASD, ADHD,
ASD+ADHD and TD groups. The project will use data from the Biomarkers in
Neurodevelopmental Disorders (BioNeD) project. Information from a large array of
executive function, central coherence and social cognition tasks has been collected,
providing the unique and exciting opportunity to explore profile differences across
groups on a variety of measures and across a variety of ages (spanning 7 to 16 years
old). The individual working on this project will help with cleaning the collected data and
re-coding new variables to allow for in depth evaluation of variables of interest. There
will be scope for the student to choose which particular area of cognition they would like
to explore in more detail.
Supervisors:
Patrick Bolton (1st supervisor)
Karen Ashwood & Charlotte Tye (2nd supervisors)
83.
Do children with Tuberous Sclerosis and autism spectrum disorder (ASD)
have the same cognitive strengths and weaknesses as children with
idiopathic ASD?
Tuberous sclerosis (TS) is a genetic disorder caused by mutations in the TSC1 or TSC2
genes, characterized by tumour-like lesions called hamartomas. Hamartomas within the
brain often act as epileptogenic foci, increasing the risk for epilepsy, intellectual
impairment and developmental disorders such as autism spectrum disorder (ASD) and
attention deficit hyperactivity disorder (ADHD). TS provides a simplified model of ASD
where the aetiology and risk pathways are constrained and already partially mapped
out, making it uniquely informative for developmental cognitive neuroscience. However,
while the aetiology of TS is constrained, it is not clear if this results in a phenotype that
is also more constrained when compared to idiopathic ASD.
The cognitive profile of children with ASD is characterised by difficulties in social
cognition and executive function, and a tendency to focus on details rather than the
bigger picture (weak central coherence). It is not yet known if children with TS and ASD
show the same cognitive profile or have a different pattern of strengths and
weaknesses. Elucidating the cognitive profile is important in building up a fully worked
out model of the risk pathways in TS, from genes, through brain pathology, to cognition
and behaviour. Furthermore, it could have important implications for behavioural
interventions for ASD in TS.
This project will be part of the TS2000 study, the first ever UK large scale, prospective,
longitudinal study of a representative sample of children with TS. During phase 2 the
children are being assessed on cognitive and behavioural measures, with a specific focus
on intellectual impairment, ASD and ADHD. Data from TS 2000 will be compared to data
from a sample of children with ASD of unknown origin.
The MSc GED project will aim to determine if children with ASD and TS show the same
pattern of cognitive strengths and difficulties as children with idiopathic ASD, or whether
children with TS are characterised by a distinct cognitive profile. The student will work
as part of the TS 2000 Study team to assist with data collection, data entry and
management and under supervision on data analysis of some of the cognitive and
behavioural data.
Supervisors:
Fiona McEwen & Patrick Bolton (1st supervisors)
Holan Liang or Charlotte Tye (2nd supervisors)
84.
Imitation in adults with autism spectrum disorder: exploring the role of
imitation inhibition in empathy
Autism spectrum disorders (ASD) are characterised by impairment in reciprocal social
interaction and communication, as well as repetitive behaviours and a restricted range
of interests. Imitation of other people’s actions is recognised as one aspect of social
interaction that may be atypical, and poor imitation skills have been documented in
children and adults with ASD. However, automatic imitation (that occurs without
conscious awareness) of hand and face actions seems to be intact1,2 or indeed
enhanced.3 Indeed, poor suppression of automatic imitation is associated with higher
level of autistic symptoms.3
One possibility is that poor suppression of automatic imitation indicates difficulties with
recognising and separating self from other effects. This may relate to impaired empathy
and higher levels of personal distress, whereby an individual is susceptible to emotional
contagion but has difficulty taking the perspective of the other and hence does not
appreciate that the source of their own emotion is that the other.
The project will utilise data collected from a sample of adults with ASD and a matched
group of typical adults. A paradigm measuring automatic imitation of hand, mouth and
eye movements was developed for this study and administered to 45 adult participants
(21 ASD, 24 control), as well as standardised measures of IQ, autistic traits and
diagnosis of ASD, theory of mind, empathy (Interpersonal Reactivity Index; IRI),
alexithymia, and adaptive functioning. The student will be trained to analyse data
collected using electromyography (EMG) and micromotion sensors in order to measure
automatic imitation / imitation suppression.
The aims of the project will be to determine if: (a) adults with ASD show poor imitation
suppression; (b) poor imitation suppression occurs equally for hand, mouth and eye
region movements; (c) poor imitation suppression predicts high levels of personal
distress and low levels of perspective taking, as measured by the IRI.
It is hoped that this project will help to clarify the nature and correlates of atypical
imitative behaviour in adults with ASD. A better understanding of these difficulties is
essential if effective intervention strategies are to be designed for this group.
References:
1. Bird G, Leighton J, Press C, Heyes C. (2007). Intact automatic imitation of human
and robot actions in autism spectrum disorders. Proc Biol Sci, 274(1628):3027-31.
2. Press C, Richardson D, Bird G. (2010). Intact imitation of emotional facial actions in
autism spectrum conditions. Neuropsychologia, 48(11):3291-7.
3. Spengler S, Bird G, Brass M. (2010). Hyperimitation of actions is related to reduced
understanding of others' minds in autism spectrum conditions. Biol Psychiatry,
68(12):1148-55.
Supervisors:
Fiona McEwen (1st supervisor)
Geoff Bird (2nd supervisor)
TBC (3rd supervisor)
85.
The impact of Alexithymia on emotion understanding.
Alexithymia is a subclinical trait which refers to an individual's ability to identify and
describe their emotions. Highly alexithymic individuals are usually aware that they are
having an emotion but often have no idea whether they are sad, angry or afraid.
Extremely alexithymic are not sure whether they are having an emotion or whether they
are just hot!
Alexithymia impacts on the ability to recognise emotion in another: Alexithymic
individuals have problems recognising emotional facial expressions and tone of voice
which results in a lack of empathy.
This project attempts to find out the ability of alexithymic individuals to understand and
manipulate the emotions of others through an experimental paradigm. The project
offers lots of contact with alexithymic individuals and provides experience running and
analysing a clinical experimental study.
Supervisor:
Geoff Bird
86.
Investigating the use of Theory of Mind in Autistic Individuals
Most adults with autism can explicitly understand the mental states of others when it is
clear that they have to do so. Anecdotal evidence suggests that the real problem with
mental state attribution in adults with autism is the ‘use’ of theory of mind to explain
and predict the behaviour of others.
This project uses a novel experimental paradigm in order to investigate the application
of Theory of Mind in autistic research volunteers.
Supervisor:
Geoff Bird
87.
Proprioception and weight lifting judgments in autism and alexithymia:
This study involves determining whether autism or alexithymia (a condition associated
with poor recognition/identification of one’s own emotions) impairs individuals’ ability to
judge the weights of objects, or their awareness of their own body in space. Alexithymia
co-occurs with autism (about 50% of individuals with autism also have alexithymia) and
our recent work has shown that it is not autism itself, but co-occurring alexithymia
instead, which causes difficulties judging one’s own and other’s emotions. This study
aims to determine whether, instead of simply having difficulties identifying their own
emotion, individuals with alexithymia actually have difficulties with all forms of
interoception (the ability to identify all internal states e.g. necessary to judge hunger,
tiredness, balance, temperature, weight etc.).
We therefore aim to test four groups of individuals: people with autism and low
alexithymia, those with autism and high alexithymia, neurotypical controls with low
alexithymia, and those without autism and high alexithymia, and determine
independently whether alexithymia or autism is associated with poor proprioceptive
awareness or weight lifting judgments.
Supervisor:
Geoff Bird
88.
Can we tickle ourselves?
Why is it that if other people tickle us we get a really strong sensation whereas if we
tickle ourselves we don't? The answer to this question is surprisingly important for
understanding how the brain works at a fundamental level.
Previous research suggests that those with schizophrenia can tickle themselves, we
want to find out what happens in autism and alexithymia (and maybe schizophrenia).
Supervisor:
Geoff Bird
89.
Creating a 'pleiotropy map' of the human genome
While numerous methods have been developed to perform GWAS on multiple traits
simultaneously, motivated by their potential increased yield of susceptibility loci, none of
the leading methods specifically search for pleiotropic loci (genomic regions or variants
that affect many different traits).
In this project you will test for the first time a method that we have recently developed
(Paul O'Reilly and PhD student Heather Porter) to identify pleiotropic loci on real data.
You will assess whether the method has really discovered pleiotropic regions by
comparing to published GWAS results and simulated data (in which pleiotropic effects
have been simulated).
There will also be scope for considering new improved ways of detecting pleiotropic loci.
The method(s) will then be applied to recently published large-scale GWAS data in order
to produce a 'pleiotropy map' of the human genome. Such a map could point
researchers to genes of particular importance in human biological function and could be
tailored to highlight those genes that have an effect on multiple psychiatric disorders in
particular.
Supervisor:
Paul O’Reilly
90.
Can we get more power from GWAS by considering related traits
together?
Numerous methods have been developed to perform GWAS on multiple traits
simultaneously, but so far there has been little evidence as to whether they lead to
greater discovery of genetic variants affecting diseases and disorders compared to the
standard approach of performing GWAS on traits separately.
This project uses multiple sources of real data sets and several multi-phenotype
methods to test this. Polygenic Risk scores will be exploited in a novel way in order to
assist in testing whether the multi-phenotype methods are more powerful or not. The
outcome of this work could have importance implications for the future direction of
GWAS, since if it can be shown convincingly that multi-phenotype methods perform
better then this could lead to it becoming the standard approach in the field in the
coming years.
Supervisor:
Paul O’Reilly
91.
Using Polygenic Risk Scores to inform psychiatric diagnoses with
underlying biology
The definition and diagnosis of psychiatric disorders attracts huge controversy; in 2013
the British Psychological Society criticised the diagnostic frameworks applied in the
Diagnostic and Statistical Manual. The main criticism is that psychiatric disorders are
defined in an often arbitrary and subjective way, which may not reflect the underlying
biology well. For instance, Major Depressive Disorder is diagnosed according to having 5
of 9 possible symptoms, which means that one person diagnosed may have an almost
non-overlapping set of symptoms to another.
This project considers ways in which Polygenic Risk Scores could be exploited to produce
better definitions (and thus subsequent diagnoses) for psychiatric disorders, which
should better reflect underlying biology. By building polygenic risk scores on symptoms
of disorders and testing for shared genetic aetiology between those symptoms we could
gain a clearer picture of which combinations of symptoms are biologically connected and
thus warrant the same psychiatric diagnosis. This project will use real data from the
Psychiatric Genomics Consortium as well as data available from IoPPN studies. You may
wish to focus on a psychiatric disorder(s) of particular interest to you for this project,
while the output of the project could be a novel approach to using genetics to inform
diagnoses across the entire range of psychiatric disorders.
NB. The software PRSice will be used for calculating and applying the polygenic risk
scores, making the software analysis straightforward.
Supervisor:
Paul O’Reilly
92.
Multi-trait Polygenic Risk Scores
So far polygenic risk scores have only been produced using a single trait as the 'base'
trait. However, it would be extremely interesting to know not only, say, an individual's
genetic risk of Schizophrenia, but their genetic risk of being diagnosed with any of the
major psychiatric disorders. Similarly, polygenic risk scores could be formed for
cardiovascular diseases, metabolic syndromes, or even for 'ill health' in general (which
may predict individual longevity).
This project will explore how such 'multi-trait polygenic risk scores' should be formed,
and will then apply these to real data to test whether they are in fact able to predict
broader categories of ill health and also test for connections between different broad
categories of disease to answer questions such as: Is there a biological connection
between metabolic health and psychiatric disorders?
NB. The software PRSice will be used for calculating and applying the polygenic risk
scores, making the software analysis straightforward.
Supervisor:
Paul O’Reilly
93. Trans-generational study of the effects of advanced paternal age on
behaviour.
Previous research has linked advanced paternal age (APA) to increased risk of
psychiatric problems (Smith et al, 2009), especially neurodevelopmental disorders
including autism (Reichenberg et al, 2006), schizophrenia (Tsuchiya et al, 2005) and
early-onset bipolar disorder (Frans et al, 2008). This suggests that detrimental effects of
increased paternal age are likely to be mediated by disturbance in early brain
development. The aim of this project is to investigate the effects of increased paternal
age on the risk of developing psychiatric disorders in offspring. Three generations of
offspring will be analysed. The study is designed to permit inferences about sexual
dimorphism, developmental time course, differences between maternal and paternal
lines of inheritance (having an aged maternal versus paternal grandfather) and transgenerational effects of a potential risk factor for neurodevelopmental disorders. It is
hypothesized that (1) aged fathers will be more likely to produce offspring with
behavioural and/or brain abnormalities, that (2) both sex and development will have an
effect on the broad spectrum of measures taken in our study, and that (3) deleterious
paternal ageing effects will persist through generations.
The project will involve scoring and analysis of behavioural data. This is a novel study
looking at whether the effects of advanced paternal age are transmitted across
generations and it will give the student experience in a range of behavioural methods,
data collection and statistical analysis.
Supervisor:
Dr Cathy Fernandes ([email protected])
94.
The impact of Alexithymia on emotion understanding.
Alexithymia is a subclinical trait which refers to an individual's ability to identify and
describe their emotions. Highly alexithymic individuals are usually aware that they are
having an emotion but often have no idea whether they are sad, angry or afraid.
Extremely alexithymic are not sure whether they are having an emotion or whether they
are just hot!
Alexithymia impacts on the ability to recognise emotion in another: Alexithymic
individuals have problems recognising emotional facial expressions and tone of voice
which results in a lack of empathy. This project attempts to find out the ability of
alexithymic individuals to understand and manipulate the emotions of others through an
experimental paradigm. The project offers lots of contact with alexithymic individuals
and provides experience running and analysing a clinical experimental study.
Supervisor:
Dr Geoff Bird ([email protected])
95.
Investigating the use of Theory of Mind in Autistic Individuals
Most adults with autism can explicitly understand the mental states of others when it is
clear that they have to do so. Anecdotal evidence suggests that the real problem with
mental state attribution in adults with autism is the ‘use’ of theory of mind to explain
and predict the behaviour of others. This project uses a novel experimental paradigm in
order to investigate the application of Theory of Mind in autistic research volunteers.
Supervisor:
Dr Geoff Bird ([email protected])
96. “When I was born I was so surprised I didn’t talk for a year and a half”
Gracie Allen
Young children learn their words mostly from parents. As children emerge from the
home into the world of nursery, then school, their exposure to new influences increases
exponentially. Words are everywhere, on posters, television, radio, and phones. It
seems natural to suppose that any observed parental influence on children’s vocabulary
would vanish as children become teenagers and begin to construct their own
environments. This project will investigate childrens’ vocabulary scores in conjuction
with a measure on parent-vocabulary. The secondary analyses will be conducted on
data from a large community sample of twins whose vocabulary has been measured
longitudinally from age 2 to 16. Parent vocabulary was measured in a subset of the
sample.
Children from the Twins early Development Study (TEDS). Around 10,000 twins have
been observed at several ages from age 2 to 16. Parent (N=1666) vocabulary was
measured when the TEDS children were aged 4.5 years.
1.
2.
3.
4.
5.
6.
7.
8.
Conduct a literature review of vocabulary acquisition; where do we get our words
from?
Conduct descriptive analyses of all vocabulary measures in TEDS ages: 2, 3, 4, 7,
9, 10, 12, 14, 16 and parent vocabulary at child’s age 4
Explore the distribution, and ascertain floor or ceiling effects on all measures.
Investigate whether there are sex differences in mean or variability on children’s
vocabulary scores.
Examine correlations between parent-measured vocabulary and twins’ vocabulary
at later ages.
Choose one age at which child vocabulary was measured on which to conduct
analyses to determine whether, and to what extent, there is genetic influence on
it.
Consider and describe the impact of floor or ceiling effects on the effect sizes of
phenotypic correlations.
Describe what the active ingredient might be in any observed relationships
between parent-vocabulary and children’s own vocabulary.
Supervisor:
Dr Rosalind Arden ([email protected])
97.
Gene Expression in twins discordant for depression and anxiety
Previous studies into the genetic basis of Major Depressive Disorder (MDD) have failed
to identify strong associations for the condition. Although genetic variation and
environmental stressors are believed to increase an individual’s susceptibility to MDD,
genome-wide association studies (GWAS) have not yet identified any replicated
associations with depression that could explain the full etiology of the disease (Ripke
2013). Twin studies of MDD have estimated its heritability to be approximately 37%
(Sullivan 2000), but may be higher for recurrent and early onset MDD (McGuffin 1996).
One of the potential problems with analysing MDD is that there may be many numerous
weakly associated variants with are difficult to detect within an unrelated population. We
previously ran a study in collaboration with the University of Queensland looking at
epigenetic differences between monozygotic twins who were discordant for MDD.
Analysis of MeDIP-seq data identified several regions which were differentially
methylated to a statistically significant degree (this work is currently under review). In
addition to the MeDIP-seq data, we have RNA-seq data from both MZ and DZ twins who
are discordant for either MDD or discordant for anxiety taken from the TwinsUK
resource. The aim of the project would to examine the data to identify differences in
expression between discordant twins, in particular looking for differentially splicing or
isoforms that may relate to the phenotype. There is also genotypic data available for the
samples which may be informative in the case of discordance between DZ pairs.
Confounding factors such as age, BMI, smoking and drinking habits will be considered in
the study as will potential effects on expression linked to the use of antidepressants. All
relevant data has already been collected and can be made available to the student.
Sufficient computational resources to do the analysis are also available.
The project will give an opportunity for the student to work with more than one form of
‘omics data and will give them an experience of data handling and statistical analysis.
The work is essentially computational and does not require any laboratory work or direct
access to the subjects used in the study.
Supervisor
Dr Matthew Davies ([email protected])
98. Children’s Attentional Training Study (CATS): Piloting of a school-based
“cognitive vaccine” for the reduction and prevention of child anxiety
Background: One factor that is known to be important for developing and maintaining
childhood anxiety is the way individuals process emotional information, such as pictures
of facial expressions. There is evidence that children who have elevated anxiety pay
greater attention to threatening information, for example an angry face. Targeting how
children pay attention to emotional information may be a promising way of preventing
and reducing childhood anxiety. A simple method for changing how children pay
attention to emotional information already exists; the attentional bias modification task
(ABM). ABM is a computerised task that trains children to get into the habit of not
paying attention to threatening information. In the CATS project, we are investigating
the effects of an ABM intervention on aspects of children’s cognition, behaviour and
mood, particularly in response to stressful experiences. Methodology: In the current
project, you will assist the CATS team in carrying out experimental testing with children
aged 8 to 11 years in primary schools in London. The current sample for experiment 1
consists of approximately 80 children selected to have average or above average
anxiety levels. In this experiment we are comparing the efficacy of multiple versions of
ABM which vary with regard to the type of stimuli to which children’s attention is trained
(e.g. toward, neutral, positive or non-emotional stimuli). By Summer 2014, this sample
will have increased to approximately 140 with a second experiment also recruiting
approximately 60 high anxious children. There is a wealth of data available including
questionnaire measures of anxiety, depression, happiness, life satisfaction and
personality, experimental measures of attentional bias and attentional control and
behavioural measures of response to a stressful task. Hypotheses and Analyses: The
student will (with supervision) develop hypotheses and undertake analyses using
existing measures. However, the opportunity to add a short measure of interest to
Experiment 2 will also be considered. Possible hypotheses that could be explored
include: (a) do ABM interventions reduce attentional bias to emotional stimuli, (b) are
there differences in the effectiveness of different versions of ABM and (c) what is the
impact of ABM on children’s mood and behaviour in response to a stressful task.
This project would suit a student who is keen to get hands-on experience of
experimental testing with children and it would be advantageous if the student could
begin the project on a part-time basis earlier in the year. The student will be included as
an author in any resultant paper.
Supervisors
Methodology and Analyses:
Dr Kathryn Lester ([email protected]), Professor Thalia Eley
([email protected])
Experimental Testing: Fiona Patrick (RA)
The student will be supported more broadly by all members of the editlab
(www.editlab.org.uk) based in SGDP, IoP.
99. Candidate genes associated with Behavioural Inhibition from infancy to
middle childhood
Background. Behavioural inhibition (BI) is a temperamental trait encompassing social
withdrawal, and extreme shyness and wariness in novel, unfamiliar situations. This trait
has been shown to be reliably associated with later anxiety disorders, although not all
children who show high BI go on to develop anxiety disorders. It appears likely that
different risk factors will interact with one another in the development of Anxiety
disorders from BI. Both BI and anxiety disorders are moderately heritable indicating
that genetic markers should be considered as a potential risk factor for BI per se and
also for its association with later anxiety disorders. Hypotheses. In the current project
you will explore (a) associations between selected candidate genotypes and BI and (b)
the interaction between candidate genotypes and BI in the development of subsequent
anxiety disorders. Sample. Participants consist of 202 children of whom 102 are high BI
and 100 and low BI (Hudson et al., 2011). There is a wealth of longitudinal data
available from the outset of the study when the children were aged 3-4 years, then
again at ages 6, 9 and 12 years. Genotyping. The student will (with supervision) select
2-3 genes of interest to genotype on this sample, and will then genotype and analyse
this data. By the start of the project the role of the serotonin transporter promoter
polymorphism will already have been explored in this sample, but many other logical
candidates remain remain (e.g., Glutamic Acid Decarboxylase (GAD), CorticotropinReleasing-Hormone (CRH); Estrogen Receptor (ESR) genes). It would be advantageous
if the student could begin the project on a part-time basis earlier in the year. The
student will be included as an author in any resultant paper.
Reference: Hudson, J. et al (2011) Temperament and family environment and anxiety in
preschool children, Journal of Abnormal Child Psychology, 39, 939-951.
Supervisors:
Analyses: Prof Thalia Eley
Lab work: Dr Chloe Wong/Susanna Roberts (student supervisor).
Collaborators
Prof Jennie Hudson (Macquarie University and PI on the temperament study)
Dr Kate Lester (SGDP)
The student will be supported more broadly by all members of the editlab
(www.editlab.org.uk) based in SGDP, IoP.
100. Therapygenetics: The Serotonin Transporter Promoter polymorphism and
response to Exposure-based Cognitive Behaviour Therapy in Adult Anxiety
Background. Gene-environment interactions are known to be important in
psychopathology. In our therapygenetics work we are examining the role of genetic
markers in predicting psychological treatment response, as a positive aspect of the
environment. To date the majority of work in this field has taken a candidate gene
approach and our study of ~400 anxiety-disordered children undergoing CognitiveBehaviour Therapy is the largest to date. We showed that for children with two copies of
the S allele (that which has been associated with differential susceptibility) were more
likely to respond well to CBT. We now plan to extend this finding to an adult study of
exposure-based CBT for adult panic and specific phobias. Hypotheses. Those with two
copies of the short allele of the serotonin transporter promoter polymorphism will show
a greater reduction in fear symptoms following exposure-based CBT. Sample.
Participants consist of 211 adults at present although more individuals are being
recruited every month. Genotyping. The student will (with supervision) genotype the
5HTTLPR on this sample, and possibly other genetic markers of differential susceptibility
(depending on progress) and will then analyse this data. The student will be included as
an author in any resultant paper. It would be advantageous if the student could begin
the project on a part-time basis earlier in the year.
Supervisors
Analyses: Prof Thalia Eley/Dr Rob Keers
Lab work: Dr Chloe Wong/Susanna Roberts (student supervisor).
The student will be supported more broadly by all members of the editlab
(www.editlab.org.uk) based in SGDP, IoP.
101. Genetic associations with the functional decline in Alzheimer’s Disease
patients
Negative outcomes in drug trials for Alzheimer’s Disease (AD) can potentially be blamed
on a lack of suitable methods to reliably diagnose the disease before clinical symptoms
become apparent. Trials are also hampered by the inherent disease heterogeneity seen
when using current clinical diagnostic criteria. Presenting symptoms, rate of cognitive
and functional decline, and age of onset can vary drastically between individuals as a
result of the underlying variations in pathophysiology. There is therefore a major clinical
need to better define the pathophysiological subtypes comprising AD which would then
enable the development of better treatment strategies. In order to gain a greater
understanding of disease heterogeneity, this project will investigate if there are genetic
risk factors associated with rates of functional decline in AD patients. The student will
have access to clinical and genetic data from the EU funded AddNeuroMed biomarker
study. The first part of the project is to calculate the functional decline of AD patients,
followed by a genome-wide association analysis with the previously calculated functional
decline.
Supervisors:
Dr Martina Sattlecker & Dr Stephen Newhouse
102.
ADHD in Tuberous Sclerosis
Tuberous sclerosis (TS) is a genetic disorder caused by mutations in the TSC1 or TSC2
genes, characterized by tumour-like lesions called hamartomas. Hamartomas within the
brain often act as epileptogenic foci, increasing the risk for epilepsy, intellectual
impairment and behavioural disturbances such as attention deficit hyperactivity disorder
(ADHD). Second-hit events result in random variation between individuals in the
number and location of hamartomas. TS is, therefore, a true natural experiment that is
uniquely informative for developmental cognitive neuroscience. Approximately 50% of
individuals with TS meet research diagnostic criteria for ADHD. The high risk of ADHD in
TS, yet the marked variability in behavioural expression provide an unrivalled
opportunity to map the risk pathways that give rise to ADHD in TS.
This project will be part of the TS2000 study, the first ever UK large scale, prospective,
longitudinal study of a representative sample of children with TS. During phase 2 the
children are being assessed on cognitive and behavioural measures, with a specific focus
on intellectual impairment, ASD and ADHD, with the aim of relating these outcomes to
genetic, brain imaging, and epilepsy data.
The MSc GED project will aim to determine the behavioural and cognitive correlates of
ADHD and ADHD traits in TS, using measures of IQ, adaptive functioning and
performance on tasks that elicit consistent deficits in ADHD (planning, working memory,
reaction-time and response inhibition). The student will work as part of the TS 2000
Study team to assist with data collection, entry and management and under supervision
on analysis of the ADHD neurocognitive data.
Supervisors:
Dr Charlotte Tye & Professor Patrick Bolton
103. Epigenetic differences associated with Autism Spectrum Disorder
Autism spectrum disorder (ASD) including autism is a group of lifelong
neurodevelopmental disorders characterised by social impairments, communication
difficulties and restricted, repetitive behaviours. The exact causes of ASD are largely
unknown; however it is thought that several complex genetic and environmental factors
are involved. Epigenetics, including DNA methylation, is a mechanism that acts at the
interface of genetic and environmental factors to regulate gene expression in response
to environment without changing their underlying DNA code. Recent studies have
suggested that altered profiles of DNA methylation play a crucial role in ASD (Schanen,
2006, Lasalle, 2013) and distinct epigenetic fingerprints were shown in monzygotic
twins discordant for ASD (Wong et al., 2013, Nguyen et al., 2010). A number of
significant ASD-associated differentially-methylated regions (DMRs) have been identified
in a recent ASD epigenome-wide association study (EWAS) using a large collection of
post-mortem brain tissue using and the Illumina Infinium 450K Human Methylation
platform (Wong, in preparation). The aim of this project is to perform verification
experiments on the top 10 ASD-associated differentially methylated regions (DMRs) by
treating genomic DNA with sodium bisulfite, and using the high-throughput Sequenom
EpiTYPER platform or bisulfite-Pyrosequencing to accurately quantify DNA methylation
at specific CpG sites nominated by the genome-wide analyses. This project will give an
exciting opportunity for the student to gain experience in cutting-edge epigenetics
technology. It would be advantageous if the student could begin the project on a parttime basis earlier in the year.
Reference:
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SCHANEN, N. C. (2006) Epigenetics of autism spectrum disorders. Hum Mol Genet,
15 Spec No 2, R138-50.
LASALLE, J. M. (2013) Epigenomic strategies at the interface of genetic and
environmental risk factors for autism. J Hum Genet, 58, 396-401.
NGUYEN, A. T., RAUCH, T. A., PFEIFER, G. P. & HU, V. W. (2010) Global methylation
profiling of lymphoblastoid cell lines reveals epigenetic contributions to autism
spectrum disorders and a novel autism candidate gene, RORA, whose protein product
is reduced in autistic brain. The FASEB Journal, 24, 3036.
WONG, C.C.Y., MEABURN, E. L., RONALD, A., PRICE, T. S., JEFFRIES, A. R.,
SCHALKWYK, L. C., PLOMIN, R. & MILL, J. (2013) Methylomic analysis of
monozygotic twins discordant for autism spectrum disorder and related behavioural
traits. Mol Psychiatry, 1-9, doi:10.1038/mp.2013.41.
Supervisors:
Dr Chloe Wong & Professor Jonathan Mill
104. Genes related to aggression
A central problem in neuroscience is to uncover and understand the molecular and
biological mechanisms underpinning instinctive behaviours, such as aggression. The
project will involve analysing novel data, identifying genes associated with an
aggression related phenotype and conduct enrichment analysis to gain further insight
into pathways that may be relevant to this trait. As a secondary analysis we will use
this data to inform the selection of genes in a comparable Genome-Wide Association
Study in human. The results are expected to highlight several genes in the study that
can serve as potential candidate genes. Moreover we aim to provide insight into the
genetics of excitement-seeking, risk-taking, hyperactivity, or antisocial disorders in
human.
Supervisors:
Dr Leonard Schalkwyk & Dr Karim Malki