3/23/2012
Nutritional Genomics
• Nutrigenomics
– How bioactive food components affect gene expression
Nutritional Genomics:
What It Means for Your Practice
• Epigenetics
– Heritable changes in gene function that occur without a change in the sequence of nuclear DNA
• Nutrigenetics
Adela Hruby, MS, MPH
– How variation in genetic code dictate our response to bioactive food components
2012 Massachusetts Dietetic Association Annual Nutrition Conference and Exposition
March 23, 2012, Framingham, MA
1
Disclosures
Variability: Response to Environment
• Doctoral student at Tufts University Friedman School of Nutrition Science and Policy
National Cholesterol Education Program (NCEP) Step 2 diet:
• ≤30% of calories from total fat
• <7% saturated fat
• <200 mg/d cholesterol
– Previous funding: NIH NIDDK Training Grant #5 T32 DK 62032‐19
– Current funding: American Heart Association Predoctoral Fellowship
• Research assistant at the Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University
• Not a Registered Dietitian
• Views expressed in this presentation are my own and do not necessarily represent the views of Tufts University, the USDA, NIH, AHA, their employees, or their affiliates.
• The mention of commercial companies, brands, products, or services does not constitute endorsement. I am not receiving remuneration from any of these entities. I declare no conflicts of interest.
2
Outline
•
•
•
•
•
4
Debusk RM, et al. J Am Diet Assoc 2005.
EJ Schaefer, et al. Arterioscler Thromb Vasc Biol 1995.
5
Variability: Response to Environment
Definitions, in brief
Complexity and variability
Definitions, revisited, with examples
State of the science
Genetics in your practice
3
EJ Schaefer. Am J Clin Nutr 2002.
6
1
3/23/2012
7
http://www.genome.gov/Glossary/index.cfm
Methyl groups
Common Sources of Genetic Variation:
Point Mutations
• Non‐sense, mis‐sense, may lead to loss of protein function, shortened proteins, longer proteins, etc. • Single nucleotide changes are the most common type of genetic variant
• A given variant may be common or rare
• Example: Cystic fibrosis
www.studentconsult.com
10
http://www.genome.gov/Glossary/index.cfm
Methyl groups
Acetyl groups
8
http://www.genome.gov/Glossary/index.cfm; Molecular Biology of the Cell, ed. Alberts, 2002.
Common Sources of Genetic Variation: Copy Number Variants (CNVs)
11
Epigenetic Phenomena
• Repeating patterns of DNA (2 to 100s of nucleotides, 2 to 100s of repeats)
• Example: Huntington’s Disease
C Xie and MT Tammi. BMC Bioinformatics, 2009.
9
MF Fraga, et al. PNAS 2005.
12
2
3/23/2012
Revisiting Our Definitions
• Nutrigenomics
Covalent adduct of a metabolically activated form benzopyrene, the major mutagen in tobacco smoke.
http://en.wikipedia.org/wiki/DNA
– How bioactive food components affect gene expression
• Epigenetics
• Nutrigenetics
13
16
Debusk RM, et al. JAm Diet Assoc 2005.
Royal jelly
Genetically identical
http://knol.google.com/k/‐/‐/BUxWT11X/wnmpHw/Carusi%20normal%20female.tif
14
Explaining “Missing” Variability
Images: en.wikipedia.org/wiki/Royal_jelly; www.queenbeeremoval.com; wikis.lib.ncsu.edu/index.php/Mary_and_Hannah
17
Nutrigenomics: A Human Example
• Interactions between environmental variables
• 4‐week crossover trial of placebo vs. magnesium supplementation
• 14 healthy, overweight participants
• Microarray of 58 differentially regulated genes after 4 weeks
– Drug ↔ drug
– Drug ↔ diet
– Diet ↔ lifestyle (smoking, physical activity, etc.)
• Epigenetic
– Environmental impact on gene expression
• Gene‐gene interactions
• Interactions between genes and environment
– Gene ↔ drug
– Gene ↔ lifestyle
– Gene ↔ diet
– 36 genes down‐regulated
– 22 genes up‐regulated
– About half of the gene names/functions unknown
15
Chacko SA et al. Am J Clin Nutr 2010.
18
3
3/23/2012
Revisiting Our Definitions
Epigenetics: The Dutch Famine
• Nutrigenomics
• Epigenetics
November 1944
May 1945
• Rations <1000 kcal/d
– Heritable changes in gene function that occur without a change in the sequence of nuclear DNA
• Liberation
• Nutrigenetics
Dec 1944‐
April 1945
• Rations 400‐
800 kcal/d
19
Debusk RM, et al. JAm Diet Assoc 2005.
June 1945
• Rations >2000 kcal/d
22
TJ Roseboom, et al. Maturitas, 2011; BT Heijmans, et al. Epigenetics, 2009.
Epigenetics: The Dutch Famine
Conception/
Early Gestation
Late Gestation
• Most vulnerable period
• ↑ schizophrenia and depression
• ↑ atherogenic lipid profile
• ↑ stress response
• 2X rate of CHD
• ↓ cogni ve tasks
• ↑ obese
RL Jirtle and MK Skinner. Nature Reviews Genetics 2007; and http://sciencewatch.com/ana/st/epigen/09augEpiJirt/#Figure_1
20
Mid‐Gestation
• ↑ microalbuminuria
• ↓ creatinine clearance
• ↓ lung func on
• 200g lighter at birth
• ↓ obese
• ↑ CHD
23
TJ Roseboom, et al. Maturitas, 2011.
Select Nutrients with Epigenetic Roles
Nutrient
Genistein
Food Origin
Leafy vegetables, seeds, baker's yeast, liver
Meats, shellfish, milk, whole grains, vegetables, nuts
Yolks, liver, soy, beef, chicken, veal, turkey
Soy, soy products
Sulforaphane
Broccoli
Diallyl sulphide
Garlic
Folic Acid
Vitamins B6,
B12
Choline
Time Magazine
Jan 18, 2010, 175(2)
Epigenetic Role
Methionine synthesis
Methionine synthesis
Methyl donor
↑ methyla on
↑ histone acetylation turning on anti‐cancer genes
↑ histone acetylation turning on anti‐cancer genes
Time Magazine
Oct 4, 2010, 176(14)
21
http://learn.genetics.utah.edu/content/epigenetics/nutrition/table.html
24
4
3/23/2012
>100 Inborn “Errors” of Metabolism
Revisiting Our Definitions
(single gene disorders, 1 in 1000 births)
• Nutrigenomics
• Epigenetics
• Nutrigenetics
– How variation in genetic code dictates our response to bioactive food components
RM Debusk, et al. J Am Diet Assoc. 2005.
25
What About Chronic Disease?
Nutrigenetics: Two Familiar Examples
Many genes with individually small risks
1. Phenylketonuria (PKU)
– Inability to properly break down phenylalanine (missing phenylalanine hydroxylase)
– PAH is on chromosome 12
– 400+ disease‐causing mutations found in PAH
– Autosomal recessive trait
– Dietary regimen with limited phenylalanine
Genes
26
Celiac Disease
Environment acts with genetic predisposition
29
• Obesity
– Autoimmune enteropathy caused by a permanent intolerance to gluten in genetically predisposed
– General population: 1 in 133
1st degree relatives of people with CD: 1 in 22
– HLA‐DQ protein is part of the MHC class II antigen‐presenting receptor system
– APOA2
• Lipids and lipoproteins
• 7 versions of protein: DQ2, DQ4–DQ9
• 97% of individuals with CD have DQ2 and DQ8 protein version
40% of general population also carry these protein version
– APOE
– 2 subunits of the HLA‐DQ protein coded by HLA‐DQA1 and HLA‐DQB1, on chromosome 6
– Presence of mutations for DQ2 or DQ8 in these genes necessary for development of CD, but absence virtually excludes diagnosis
– Gluten amount and gene dose at HLA‐DQA1 and HLA‐DQB1 important determinants of CD manifestation and severity
– Strict gluten‐free diet is the only treatment to date
MM Niewinski. J Amer Diet Assoc. 2008.
Food
Nutrigenetics and Chronic Disease
Nutrigenetics: Two Familiar Examples
2.
28
JS Isaacs JS and DJ Zand. J Am Diet Assoc. 2007.
• Type 2 diabetes
– TCF7L2
• Vitamin C
– GSTM1, GSTT1, and GSTP1
27
30
5
3/23/2012
Genetics of Obesity
Obesity: APOA2 and SFA
• 265T>C CC homozygotes
• Heritability of BMI and WC as high as 77%
• Some “top” genes include:
– More likely to exhibit behaviors that impede weight loss (“Do you skip meals”)
– Less likely to exhibit protective behavior (“Do you plan meals in advance”)
– Fat mass and obesity associated gene (FTO)
– Melanocortin 4 receptor gene (MC4R)
– Perilipin (PLIN)
• 265T>C CC and high SFA intake associated with
↑ BMI
↑ Prevalence of obesity
↑ Insulin resistance (certain ethnicities only)
↑ Plasma ghrelin (stimulates hunger)
• 32 BMI risk loci “explain” <3% of variation in BMI between people
31
J Wardle, et al. Am J Clin Nutr. 2008; EK Speliotes, et al. Nature Genetics. 2010.
Low vs. High Genetic Susceptibility
D Corella, et al. Int J Obes (Lond). 2011 (graphic); CE Smith, et al. Int J Obes (Lond). 2012.
34
Genetics of Lipids
0 to <22 risk alleles
>38 risk alleles
(2.2%)
(1.5%)
• 100s of studies of lipid and lipoprotein response in different genotype groups
• Frequently studied
– Apolipoprotein (Apo) A‐I to A‐V (APOA1… APOA5)
– APOB, APOE
– LIPC
Average BMI difference of 2.73 kg/m2
Per risk allele, ~1 lb higher weight in a 5’3” adult
(15.4 lb weight difference in a 5’3” adult)
Apolipoprotein E
100s of gene‐diet interactions…
ADRB2
• Apolipoprotein E is a main apoprotein of the chylomicron, which binds to a specific receptor on liver and peripheral cells
• It is essential for the normal catabolism of TG‐rich lipoprotein constituents
• Defects result in familial dysbetalipoproteinemia, or type III hyperlipoproteinemia (HLP III)
CHO
Physical activity
ADRB3
Total Energy
FTO Fat
SFA
IL6R
PUFA
PPARG
35
32
EK Speliotes, et al. Nature Genetics. 2010.
– Increased plasma cholesterol and TGs result from impaired clearance of chylomicron and VLDL remnants
P:S Ratio
33
G Rimbach and AM Minihane. Proc Nutr Society. 2009.
6
3/23/2012
APOE
Genetics of T2D
• APOE on chromosome 19
• 3 variants
• Dozens of genes involved
– Monogenic
– T1D, MODY, T2D…
– ε2 – “protective”
– ε3 – “neutral” (65% Caucasians are ε3/ε3)
– ε4 – “risk”
• Transcription factor 7‐like 2 (TCF7L2)
– Impaired insulin secretion and beta cell function, not sensitivity
– OR per risk allele
• Role as an anti‐inflammatory and antioxidant agent, linked to CVD, Alzheimer’s, Parkinson’s, and other neurodegenerative disease
• rs12255372 (C/T) : 1.3–1.5
• rs7903146 (G/T): 1.3–1.5
G Rimbach and AM Minihane. Proc Nutr Society. 2009.
MN Weedon. Diab Med, 2007.
Diabetes Prevention Program Results
ε4s Are Sensitive to Dietary Cholesterol
11 cases/100 per‐yrs
7.8 cases/100 per‐yrs
4.8 cases/100 per‐yrs
E Sarkkinen, et al. Am J Clin Nutr. 1998.
Diabetes Prevention Program Research Group, N Engl J Med, 2002.
ε4s and Other Dietary Fats
DHA and EPA
Plant Sterols
• DHA+EPA tends to increase LDL (5–10%) in doses >2g/d
• LDL‐raising effects of 3g/d EPA+DHA in E4
• Appears to be DHA rather than EPA in E4
• No genotype effect at <2g/d EPA+DHA
•
DPP and TCF7L2
• Overall
5‐wk plant sterol spread vs. control spread RCT in hypercholesterolemic
adults
– TT more likely to progress to T2D than CC (HR 1.55)
E2
• ↓ TGs, total cholesterol, LDL, ApoB, Chol:LDL, LDL:HDL
• ↓ beta‐carotene, lycopene, lutein
E3
• ↓ total cholesterol, LDL, ApoB, Chol:LDL, LDL:HDL
• ↓ alpha‐carotene, cryptoxanthin
E4
• ↓ beta‐carotene, lycopene, cryptoxanthin, zeaxanthin
G Rimbach and AM Minihane. Proc Nutr Society. 2009; FJ Sanchez‐Muniz, et al. J Nutr. 2009.
• Placebo, incidence in…
– TT: 18.5 cases per 100 person‐years
– CT: 10.7 cases per 100 person‐years
– CC: 10.8 cases per 100 person‐years
39
JC Florez, et al. N Engl J Med, 2006.
7
3/23/2012
Emphasis on Achieving RDA
TT
TT
CC and CT
CC and CT
TT
• A gene‐diet interaction at GSTM1 and GSTT1 but not for GSTP1
• Overall OR for deficiency 3.2 (95%CI: 1.9, 5.4) with <RDA vitamin C
CC and CT
– Non‐functional GSTT1 OR 12.3 vs. OR 2.17 functional GSTT1
– Non‐functional GSTM1 OR 4.0 vs. OR 2.3 functional GSTM1
JC Florez, et al. N Engl J Med, 2006.
46
LE Cahill, et al. Am J Clin Nutr, 2009.
State of the Science:
A field in its infancy
TCF7L2: Adding Complexity
• Thousands of genes, millions of SNPs
• Each locus may have differential response to
• T2D and carbohydrate quality (GI) and quantity (GL)
– TT women with highest GI or GL had >2X odds compared to GG
– Risk with TT genotype magnified under increased insulin demand
– High fat diet vs. low fat diet
– Low carb vs. low fat
– High MUFA vs. low MUFA… etc.
• An interaction that may be beneficial on one outcome, may be harmful on another outcome
• Relative sizes of genetic effects in relation to other sources of variation in disease risk – like environmental effects – not established
• Any recommendations will rely on replicated findings
and a lot more evidence
• Other conditions and dietary fat
– T allele associated with more atherogenic profile with higher n‐6 PUFA intake (≥6.6% of energy)
– T allele in women associated with >2X odds of metabolic syndrome with higher SFA intake (≥15.5% of energy)
– No genotype effect in those with lower PUFA or SFA intake
MC Cornelis, et al. Am J Clin Nutr, 2009; D Warodomwichit, et al. J Nutr, 2009; CM Phillips, et al. J Nutr Biochem, 2012.
44
47
Pharmocogenetics:
Always one step ahead?
One Last Example…
• Glutathione S‐transferases (GSTs) are detoxifying enzymes in the glutathione‐ascorbic acid (vitamin C) antioxidant cycle
• Dosing Recommendations without Consideration of Genotype
– If CYP2C9 and VKORC1 genotypes are not known, initial dose of warfarin sodium tablets is usually 2–5 mg per day
– Regenerate glutathione – thus regenerates antioxidant capacity
– Mu, theta, and pi classes are coded for by GSTM1, GSTT1, and GSTP1
• Dosing Recommendations with Consideration of Genotype
• Question: Do polymorphisms in these genes affect dietary vitamin C requirements?
• Population: Nonsmoking men and women (n = 905), 20‐29 yo
• Intake: A 196‐item FFQ to estimate vitamin C intake
Three Ranges of Expected Maintenance Warfarin Sodium Tablets Daily Doses Based on CYP2C9 and VKORC1 Genotypes* – RDA: 75 mg/d for nonsmoking women, 90 mg/d for nonsmoking men
CYP2C9
• Outcome: Serum ascorbic acid concentrations
– Deficiency: <11 μmol/L
• Genotypes: Polymorphisms in GSTM1, GSTT1 and GSTP1
LE Cahill, et al. Am J Clin Nutr, 2009.
45
VKORC1
*1/*1
*1/*2
*1/*3
*2/*2
*2/*3
*3/*3
GG
5–7 mg
5–7 mg
3–4 mg
3–4 mg
3–4 mg
0.5–2 mg
AG
5–7 mg
3–4 mg
3–4 mg
3–4 mg
0.5–2 mg
0.5–2 mg
AA
3–4 mg
3–4 mg
0.5–2 mg
0.5–2 mg
0.5–2 mg
0.5–2 mg
http://whatsthedose.com/spl/0378‐8801.html#i4i_section_id_ffc606ce‐ad3b‐44da‐b616‐1ad8ff41a7c3
48
8
3/23/2012
There is LONG Way to Go
• Nutrigenetic testing does not produce the same kind of information as genetic testing to determine a predisposition to a particular disease
• Variants that may not themselves cause disease
• Risk depends on diet and lifestyle choices in/appropriate for particular genotype
49
http://www.dnadiet.co.za/weight‐loss‐health‐products/DNA‐Diet.aspx
http://www.dnadiet.co.za/weight‐loss‐health‐products/DNA‐Health‐for‐optimal‐health.aspx
52
50
https://www.23andme.com/health/response‐to‐diet/
53
Nutritional Genomic Testing • Specific regulations do not exist
• Genetic tests, like any sort of lab test, need to have
– Analytic validity
– Clinical validity
– Clinical utility
• As of 2008, testing does not yet meet acceptable standards for clinical utility
• Genetic tests should be evaluated in the individual’s context and test details
Nutritional Genomic Testing
Random Sample of
Companies/Services
23andMe
Lumigenix
DeCODEme
Knome (researchers, clinics)
Genetic Testing Laboratories
Things to Look For
• How good is the company/service?
URL
http://www.23andme.com http://www.lumigenix.com http://www.decodeme.com http://www.knome.com http://www.gtldna.com
–
–
–
–
Approx. Cost
$207
$479
$1100
$4‐5000
$285
• Do they offer genetic counseling?
• How do they interpret results – giving recommendations vs. providing evidence?
– Scientific evidence and quality of evidence
• Many companies, many tests
• Tests mislead consumers by "making predictions that are medically unproven and so ambiguous that they do not provide meaningful information to consumers” • Replications
• Size of studies
• Timeliness of evidence
– Race/ethnicity of populations studied
• Is the company “selling” something beyond genotyping (e.g., supplements)?
(General Accounting Office report on nutrigenetic testing, 2006)
Adapted from http://www.dnapolicy.org/news.release.php?action=detail&pressrelease_id=145
Types of tests, quality, and reliability
Number of loci
Privacy policy
Complaints?
51
54
9
3/23/2012
Genetics in Your Practice (Part 1) Genetics in Your Practice (Part 2)
C. Address patient hopes, fears, and questions
• Monogenic or inborn “errors” (PKU, etc.)
– Therapeutic approaches remain the same
– Deciphering complexity of test results – tests don’t give yes or no answers
– Determinism – all characteristics of a person are “hard‐wired” by the genome
– Reductionism – with complete knowledge of the human genome, our understanding of gene functions and interactions will completely explain human variability
– Distinguishing “susceptibility” vs. “risk”
• Complex, chronic disease (T2D, CVD, etc.)
– “One size” may not fit all, but still fits most
• Already personalized – age, sex, clinical presentation, personal preferences and behaviors
• Family history and family history assessment
– Some evidence that lifestyle modifications (DPP, NCEP2) trump genetic susceptibility
– Nutrigenetic evidence base not yet sufficient
– “One gene, one diet” not the right approach
55
Genetics in Your Practice (Part 2)
National Coalition for Health Professional Education in Genetics http://www.nchpeg.org/nutrition/ and Venter JC, et al. Science 2001.
58
Genetics in Your Practice (Part 2)
2.Be aware of ethical considerations…
• Unlikely to do formal genetic counseling…
• Informed decision‐making
– Based on sufficient knowledge of decision alternatives and outcomes
– Consistent with the decision maker's values
… But there will be patients who come in with direct‐to‐consumer test results
• Informed consent
– A patient has the capacity to understand the benefits and risks of a medical intervention
– Without sufficient comprehension of all the risks, patients are not fully autonomous to make a truly informed decision
– Standard medical consent does not cover potential genetic issues
… and ask whether they should get genetic or nutrigenetic testing done
56
Genetics in Your Practice (Part 2)
59
Genetics in Your Practice (Part 2)
1. Assess your own genetic literacy
3. Assess your own ability to communicate susceptibility and risk
A. Take and interpret a family history
B. Explain genetic testing and implications
– Low numeracy (and low literacy)
– Use absolute risks, not relative risks
– Complex diseases are caused by the interaction between multiple genes and environmental influences
• A drug reduces risk of heart attack by 37%
• This means that in a large study, 3 in 100 patients taking a placebo had a heart attack compared to 2 in 100 patients taking the drug
• Clinical manifestations will vary based on different combinations of genes and exposures
– Susceptibility genes – Numerical risk estimates increase trust in and satisfaction with information
– Verbal information more readily usable to patient
– Visual aids help present risk information
• Increase susceptibility instead of directly causing the disorder
• Do not guarantee that the person will be affected
• Absence does not guarantee absence of disease
57
CMR Smerecnik, et al. J Genet Counsel, 2009.
60
10
3/23/2012
A Simple Pictograph
Genetics in Your Practice (Part 3)
• Keep providing personalized, preventive medicine and nutrition interventions
• Stay informed and learn genetic literacy
• Help educate providers and public
• Contribute to the development of an evidence base
A disease occurs in 5 out of 100,000 people in 1 year.
That’s 5 out of 1,000 people over 10 years.
What does 20% increase in risk look like?
http://medicaladvocate.com/?p=1451
64
61
Genetics in Your Practice (Part 2)
• Should you recommend genetic testing?
– Genetic variations cluster in, and diet‐related conditions disproportionately affect, certain ethnic/racial groups
– A tool to help us understand disproportionate burden of disease?
– A tool that will only be accessed by higher SES?
•
•
•
•
•
Cost of testing may be higher than its value Little support for interpreting and using test results
Patient concerns about use of genetic information
Unclear how industry regulations will unfold
Genetic testing affects families, not just individuals
THANK YOU!
62
65
Genetics in Your Practice (Part 3)
• Paradigm shifts
– From disease management to health promotion and disease prevention
– Individualization of dietary advice based on a person’s genotype (nutrigenetics)
– More dimensions to food (more functional foods, specialized supplements), where genes are dietary targets since food can change gene expression (nutrigenomics)
• Consumer empowerment – Food choices appropriate for genotype
63
11
Slides Sources/Additional Information
Adela Hruby “Nutritional Genomics: What It Means for Your Practice”
2012 Massachusetts Dietetic Association Annual Nutrition Conference and Exposition
March 23, 2012, Framingham, MA
Slide
No.
4
5
6
7
8
9
10
11
12
13
14
16
17
18
19
20
21
22
23
24
25
27
Source(s)
Ruth M. Debusk, Colleen P. Fogarty, José M. Ordovas, Kenneth S. Kornman. Nutritional genomics in practice: Where do we
begin? Journal of the American Dietetic Association, April 2005; 105(4):589-598, ISSN 0002-8223.
doi:10.1016/j.jada.2005.01.002.
Ernst J. Schaefer, Alice H. Lichtenstein, Stefania Lamon-Fava, John H. Contois, Zhengling Li, Helen Rasmussen, Judith R.
McNamara, José M. Ordovas. Efficacy of a National Cholesterol Education Program Step 2 Diet in Normolipidemic and
Hypercholesterolemic Middle-Aged and Elderly Men and Women. Arterioscler Thromb Vasc Biol. 1995;15:1079-1085,
doi:10.1161/01.ATV.15.8.1079
Ernst J. Schaefer. Lipoproteins, nutrition, and heart disease Am J Clin Nutr 2002;75(2):191-212.
Image: National Institutes of Health. National Human Genome Research Institute. “Talking Glossary of Genetic Terms.”
Retrieved January 31, 2012 from http://www.genome.gov/glossary/
Image: StudentConsult, Elsevier Press, Retrieved January 31, 2012 from http://www.studentconsult.com
C Xie and MT Tammi. CNV-seq, a new method to detect copy number variation using high-throughput sequencing. BMC
Bioinformatics 2009;10:80. doi:10.1186/1471-2105-10-80
Image: National Institutes of Health. National Human Genome Research Institute. “Talking Glossary of Genetic Terms.”
Retrieved January 31, 2012 from http://www.genome.gov/glossary/
Images: National Institutes of Health. National Human Genome Research Institute. “Talking Glossary of Genetic Terms.”
Retrieved January 31, 2012 from http://www.genome.gov/glossary/
Molecular Biology of the Cell, ed. Alberts, B., et al. Garland Science, 2002.
Mario F. Fraga, Esteban Ballestar, Maria F. Paz, Santiago Ropero, Fernando Setien, Maria L. Ballestar, Damia Heine-Suñer,
Juan C. Cigudosa, Miguel Urioste, Javier Benitez, Manuel Boix-Chornet, Abel Sanchez-Aguilera, Charlotte Ling, Emma
Carlsson, Pernille Poulsen, Allan Vaag, Zarko Stephan, Tim D. Spector, Yue-Zhong Wu, Christoph Plass, and Manel Esteller.
Epigenetic differences arise during the lifetime of monozygotic twins. PNAS 2005;102(30):10604-10609;
doi:10.1073/pnas.0500398102
Image: http://en.wikipedia.org/wiki/DNA
Image: http://knol.google.com/k/-/-/BUxWT11X/wnmpHw/Carusi%20normal%20female.tif
Ruth M. Debusk, Colleen P. Fogarty, José M. Ordovas, Kenneth S. Kornman. Nutritional genomics in practice: Where do we
begin? Journal of the American Dietetic Association, April 2005; 105(4):589-598, ISSN 0002-8223.
doi:10.1016/j.jada.2005.01.002.
Images: en.wikipedia.org/wiki/Royal_jelly; www.queenbeeremoval.com; wikis.lib.ncsu.edu/index.php/Mary_and_Hannah
Chacko SA, Sul J, Song Y, Li X, LeBlanc J, You Y, Butch A, Liu S. Magnesium supplementation, metabolic and inflammatory
markers, and global genomic and proteomic profiling: a randomized, double-blind, controlled, crossover trial in overweight
individuals. Am J Clin Nutr. 2011 Feb;93(2):463-73. Epub 2010 Dec 15.
Ruth M. Debusk, Colleen P. Fogarty, José M. Ordovas, Kenneth S. Kornman. Nutritional genomics in practice: Where do we
begin? Journal of the American Dietetic Association, April 2005; 105(4):589-598, ISSN 0002-8223.
doi:10.1016/j.jada.2005.01.002.
Randy L. Jirtle and Michael K. Skinner. Environmental epigenomics and disease susceptibility. Nature Reviews Genetics 8,
253-262 (April 2007); doi:10.1038/nrg2045
Photo: http://sciencewatch.com/ana/st/epigen/09augEpiJirt/#Figure_1:
Time Magazine Jan 18, 2010, 175(2) and Oct 4, 2010, 176(14)
EW Tobi, et al. DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific.
Hum Mol Genet. 2009;18(21):4046–4053. doi:10.1093/hmg/ddp353;
BT Heijmans, EW Tobi, LH Lumey, PE Slagboom. The epigenome: Archive of the prenatal environment. Epigenetics
2009;4(8):526-531. doi:10.4161/epi.4.8.10265
TJ Roseboom, Rebecca C. Painter, Annet F.M. van Abeelen, Marjolein V.E. Veenendaal, Susanne R. de Rooij, Hungry in the
womb: What are the consequences? Lessons from the Dutch famine, Maturitas, 2011;70(2):141-145.
doi:10.1016/j.maturitas.2011.06.017.
http://learn.genetics.utah.edu/content/epigenetics/nutrition/table.html
Ruth M. Debusk, Colleen P. Fogarty, José M. Ordovas, Kenneth S. Kornman. Nutritional genomics in practice: Where do we
begin? Journal of the American Dietetic Association, April 2005; 105(4):589-598, doi:10.1016/j.jada.2005.01.002.
Mary M. Niewinski, Advances in Celiac Disease and Gluten-Free Diet, J Am Diet Assoc, 2008;108(4): 661-672.
28
31
32
34
36,37
38
39
40
41
42,43
44
45
48
51
52
53
58
60
61
Janet Sugarman Isaacs, Dina J. Zand. Single-Gene Autosomal Recessive Disorders and Prader-Willi Syndrome: An Update for
Food and Nutrition Professionals, Journal of the American Dietetic Association 2007;107(3):466-478;
doi:10.1016/j.jada.2006.12.006.
Jane Wardle, Susan Carnell, Claire MA Haworth, and Robert Plomin. Evidence for a strong genetic influence on childhood
adiposity despite the force of the obesogenic environment Am J Clin Nutr 2008 87: 2 398-404;
Clifton Bogardus. Missing Heritability and GWAS Utility. Obesity (2009) 17 2, 209–210. doi:10.1038/oby.2008.613
EK Speliotes, et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nature
Genetics 42, 937–948 (2010) doi:10.1038/ng.686
Image: http://healthisourwealth.wordpress.com/2011/11/12/hello-world/
Corella D, Tai ES, Sorlí JV, Chew SK, Coltell O, Sotos-Prieto M, García-Rios A, Estruch R, Ordovas JM. Association between
the APOA2 promoter polymorphism and body weight in Mediterranean and Asian populations: replication of a genesaturated fat interaction. Int J Obes (Lond). 2011;35(5):666-675;
Smith CE, Ordovás JM, Sánchez-Moreno C, Lee YC, Garaulet M. Apolipoprotein A-II polymorphism: relationships to
behavioural and hormonal mediators of obesity. Int J Obes (Lond). 2012 Jan;36(1):130-6. doi: 10.1038/ijo.2011.24. Epub
2011 Mar 8.
G Rimbach and AM Minihane. Nutrigenetics and personalised nutrition: how far have we progressed and are we likely to
get there? Proceedings of the Nutrition Society 2009;68:162. doi:10.1017/S0029665109001116
Sarkkinen E, Korhonen M, Erkkilä A, Ebeling T, Uusitupa M. Effect of apolipoprotein E polymorphism on serum lipid
response to the separate modification of dietary fat and dietary cholesterol. Am J Clin Nutr 1998 Dec;68(6):1215-22.
G Rimbach and AM Minihane. Nutrigenetics and personalised nutrition: how far have we progressed and are we likely to
get there? Proceedings of the Nutrition Society 2009;68:162. doi:10.1017/S0029665109001116;
Sanchez-Muniz FJ, Maki KC, Schaefer EJ, Ordovas JM. Serum lipid and antioxidant responses in hypercholesterolemic men
and women receiving plant sterol esters vary by apolipoprotein E genotype. J Nutr. 2009 Jan;139(1):13-9. Epub 2008 Dec 3.
Weedon, MN. The importance of TCF7L2. Diabetic Medicine 2007;24:1062–1066. doi: 10.1111/j.1464-5491.2007.02258.x
Diabetes Prevention Program Research Group. Reduction in the Incidence of Type 2 Diabetes with Lifestyle Intervention or
Metformin. N Engl J Med 2002; 346:393-403.
Jose C. Florez, M.D., Ph.D., Kathleen A. Jablonski, Ph.D., Nick Bayley, B.A., Toni I. Pollin, Ph.D., Paul I.W. de Bakker, Ph.D.,
Alan R. Shuldiner, M.D., William C. Knowler, M.D., Dr.P.H., David M. Nathan, M.D., and David Altshuler, M.D., Ph.D. for the
Diabetes Prevention Program Research Group. TCF7L2 Polymorphisms and Progression to Diabetes in the Diabetes
Prevention Program. N Engl J Med 2006; 355:241-250.
MC Cornelis, L Qi, P Kraft, FB Hu. TCF7L2, dietary carbohydrate, and risk of type 2 diabetes in US women. Am J Clin Nutr.
2009; 89(4):1256-1262;
D Warodomwichit, DK Arnett, EK Kabagambe, MY Tsai, JE Hixson, RJ Straka, M Province, P An, CQ Lai, I Borecki, JM
Ordovas. Polyunsaturated fatty acids modulate the effect of TCF7L2 gene variants on postprandial lipemia. J Nutr.
2009;139(3):439-436;
CM Phillips, L Goumidi, S Bertrais, MR Field, R McManus, S Hercberg, D Lairon, R Planells, Roche HM. Dietary saturated fat,
gender and genetic variation at the TCF7L2 locus predict the development of metabolic syndrome. J Nutr Biochem.
2012;23(3):239-44.
LE Cahill, B Fontaine-Bisson, A El-Sohemy. Functional genetic variants of glutathione S-transferase protect against serum
ascorbic acid deficiency. Am J Clin Nutr. 2009;90(5)1411-1417. doi:10.3945/ajcn.2009.28327
http://whatsthedose.com/spl/0378-8801.html#i4i_section_id_ffc606ce-ad3b-44da-b616-1ad8ff41a7c3
Adapted from The Genetics and Public Policy Center, Johns Hopkins University Berman Institute of Bioethics;
http://www.dnapolicy.org/news.release.php?action=detail&pressrelease_id=145 on 3/15/2012.
Adapted from http://www.dnadiet.co.za/weight-loss-health-products/DNA-Diet.aspx
http://www.dnadiet.co.za/weight-loss-health-products/DNA-Health-for-optimal-health.aspx on 3/15/2012
Adapted from https://www.23andme.com/health/response-to-diet/ on 3/15/2012.
National Coalition for Health Professional Education in Genetics at http://www.nchpeg.org/nutrition/;
Venter JC, et al. The Sequence of the Human Genome. Science. 2001;291(5507):1304-1351. DOI:10.1126/science.1058040
Smerecnik CMR, Mesters I, Verweij E, de Vries NK, de Vries H. A Systematic Review of the Impact of Genetic Counseling on
Risk Perception Accuracy. J Genet Counsel (2009) 18:217–228. doi:10.1007/s10897-008-9210-z
Helpful resource on risk communication: Angela Fagerlin, Brian J. Zikmund-Fisher, Peter A. Ubel. Helping Patients Decide:
Ten Steps to Better Risk Communication JNCI J Natl Cancer Inst (2011) 103(19): 1436-1443 first published online September
19, 2011 doi:10.1093/jnci/djr318
Image: http://medicaladvocate.com/?p=1451