The Genetic Epidemiology of
Complex Diseases: Myopia
Eric Yap
Research Director
Biomedical Sciences Laboratory
Defence Medical Research Institute
[email protected]
Johannes Kepler
(1571-1630)
• inverted image on retina
• role of cornea and lens
• concave & convex lenses
• myope’s image in front of retina
• alterations in eye shape allow
distant and near vision
• “near work” hypothesis: study
and fine work in childhood
accustoms eye to near objects,
resulting in permanent finite far
point.
"...a sickly child, with thin limbs and a large, pasty face surrounded by dark curly hair. He
was born with defective eyesight-myopia plus anocular polyopy (multiple vision). His
stomach and gall bladder gave constant trouble; he suffered from boils, rashes, and
possibly from piles, for he tells us that he could never sit still for any length of time..."
FACE-REST DESIGNED BY
KALLMANN, A GERMAN
OPTICIAN
Optics of Myopia
EMMETROPIA
MYOPIA
Axial length
Corneal
curvature
Refractive
Lens power
1 D = 0.32 - 0.45 mm axial length
Biometric variation
Normally distributed:
–
–
–
–
lens power
corneal power
total refraction
anterior chamber depth
Peaked, Skewed:
– axial length
Tron (1934): 275 eyes
Stenstrom (1946): 1000 eyes
Emmetropization
Schooling and Myopia
Prevalence of myopia in 10,060 children
Thirty three Schools
in Breslau
5 Village schools
20 Municipal elementary
2 Middle schools
2 Girls’ high schools
Holy Ghost Real
Zwinger
Elizabeth Gymnasium
Magdelen Gymnasium
Grade and % of Myopia
VIII
1
VII
2
VI
0
7
7
11
11
14
V
10
8
12
21
17
19
IV
III
II
I
6
6
25
13
19
28
1
3
13
16
27
23
31
30
2
4
9
12
25
28
48
35
3
10
15
19
59
29
65
47
Cohn H: Hygiene of the eye. London, Simpkin, Marshall & Co, 1886
Education and Myopia
Education strongly
associated with risk
of myopia
Myopia in Different Educational Groups
Myopia
Severe Myopia
100%
90%
90%
80%
Prevalence
70%
88%
86%
81%
73%
71%
68%
60%
50%
40%
30%
24%
20%
10%
3%
4%
12%
6%
18%
21%
0%
NFE
Pri
PSLE
O
A
Educational Status
Dip
Uni
Severity of myopia
increased with
increasing level of
education
Genetic Epidemiology
Stages in identifying disease genes
RESEARCH QUESTION
METHOD/APPROACH
Disease characteristics? – Descriptive epidemiology
Familial clustering?
– Family aggregation
Genetic or Environmental? studies
Mode of inheritance?
– Twin/Adoption studies
– Segregation analysis
Disease susceptibility loci?
Gene? Mutation?
– Linkage analysis
– Association studies
OBJECT
Species
Population
Family
Genetic locus
Gene
Mutation
Genetic Epidemiology of Complex Diseases
Logic flow in identifying disease genes
RESEARCH QUESTIONS
Disease prevalence and features?
Familial clustering?
Genetic or Environmental?
Mode of inheritance?
Disease susceptibility loci?
Gene? Mutation?
Population Studies
Disease prevalence? Phenotypes? Risk
factors?
Epidemiology of Genetic Traits and
Disease
Descriptive studies of distribution
– geographic differences
– ethnic differences
– phenotype, intermediate phenotypes
Refractive Errors in Singapore
2500
Overall Mean Sph Eq = -2.6D
Mild & Moderate Myopes: 67.9%
1500
1000
500
Severe Myopes: 15.4%
0.5%
-12
-11
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
1
0
2
No. of Subjects
2000
Emmetropes: 16.2%
Spherical Equivalence (D)
15095 male subjects, mean age: 19 yrs, cohort: 1996/7
Distribution of Refractive Errors in Young Singaporean
Long:
0.5%
0.25
Nor:
16.2
%
Severe Myopia:
15.4%
Mild & Moderate Myopia:
67.9%
Overall Median Sph Eq = -2.25D
0.2
- 0.88D
Indian
-1.13D
Chinese - 2.75D
0.15
0.1
0.05
17.3%
7.7%
0
Refraction of worse eye (D)
15,095 subjects, mean age: 19 yrs, cohort: 1996/7
2
-1
-1
1
-1
0
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
1
2
5.9%
3
Frequency
Malay
Age of Onset of Myopia
Age when spectacles first worn
20
18
Onset
16
Ave Onset
14
12
10
8
6
4
2
0
0
-2
-4
-6
-8
-10
-12
Refractive Error at Age 19
-14
-16
-18
-20
Myopia Complications
Macular Changes
Prevalence
Peripheral Retinal Degeneration
100%
100%
90%
90%
Grade VI
80%
80%
Grade III
70%
70%
Grade II
60%
60%
Grade I
50%
50%
40%
40%
30%
30%
20%
20%
10%
10%
0%
0%
-1
-2
-3
-4
-5
-6
-7
-8
-9
Refractive Error (D)
Peripheral retinal changes in
myopia (943 eyes)
-10
-11
2
1
0
-1 -2 -3 -4 -5 -6 -7 -8 -9 -10 -11 -12 -13
Refractive Error (D)
Stages of macular change in
myopia (1110 eyes)
Contrast Sensitivity Function
0.1
1
10
100
0
1.5
3
6
12
20
Spatial Frequency (CPD)
Emmetropes
+1.00 D to -1.00 D
Low Myopes
-1.00 D to -6.00 D
High Myopes
above -6.00 D
Visual Acuity Trends in Young Males
Population Frequency
SAF Pre-enlistees
100%
80%
11.6
14.7
23.3
33.5
20
60%
Very poor < 6
32.1
40%
73.7
Good 6/6 - 6/
56.7
20%
34.4
0%
1974-1984
1987-1991
Poor 6/15 - 6
1996-1997
Population Frequency
Refractive Error Trends in Males
100%
80%
60%
40%
20%
0%
1993
1996-7
<-12.25
0.2%
0.3%
-8.25 to –12.00
1.5%
3.2%
-3.25 to –8.00
30.8%
37.4%
-0.75 to –3.00
28.5%
34.2%
+0.50 to –0.50
39.0%
24.9%
Familial clustering
Is there clustering of cases in families?
Family aggregation studies
“Is disease more prevalent in relatives of affected than
relatives of non-affecteds?”
– Relative risk, λs
– Biases: ascertainment, self-reporting (over/under),
diagnostic categories, double-blind/co-morbidity
studies, sampling bias
Resemblences between first degree relatives in
refractive error
Reference
Parent-child
mother
English
0.23
(Sorsby 66)
Alaskan Inuit
0.23
(Young 69)
Greenland Inuit
0.07
(Alsbirk 79)
Newfoundland
0.23
(Bear 81)
European, Japanese
0.25
(Ashton 85)
Sib-sib
Father-
0.36
-0.12
0.45
-
0.25
0.03
0.29
0.04
0.37
0.01
Family History
Parental History & Myopia (952 subjects)
No. of Myopic
Parents
0
1 or 2
Odds Ratio
P
No. of Subjects who are
Emmetropic
Myopic
Severely Myopic
47
20
1
215
330
3.61
< 0.001
106
234
5.19
< 0.001
Sibling History & Myopia (947 subjects)
Myopic
Siblings
YES
NO
Odds Ratio
P
No. of Subjects who are
Emmetropic
Myopic
Severely Myopic
34
42
1
473
68
8.59
< 0.001
304
26
14.4
< 0.001
Evidence of Familial Clustering of Myopia
DMRI Survey of 617 refracted subjects, 1997
100%
Severe Myopia
80%
60%
Mild-Moderate
Myopia
40%
Non-myopia
20%
0%
No myopic
parent
With myopic
parent(s)
Non-myopic sibMyopic sib(s)
Increased relative risks of myopia and severe myopia:
OR = 3.6 and 5.2 (parental history)
OR = 8.6 and 14.4 (sibling history)
Genetics or Environment
Is familial clustering due to common environment,
inherited (genetic) susceptibility or shared cultural
risk factors?
Twin studies
“Is risk in identical twin of affected greater than in fraternal twin of
affected?” Concordance, discordance
Adoption studies
“Is risk in biological relatives of affected adoptees greater than adopted
relatives of affected adoptees?” [Adoption bias]
“Is risk in biological relatives of affected adoptees greater than biological
relatives of unaffected adoptees?”
Twin Concordance Studies
Unique Environment
MZ
Genetics
Phenotype
sharing
DZ
Shared Environment
0
0.5
Genetic sharing
1
Twin Studies in Myopia
MZ
DZ
Country
Age
Diag
MZ
DZ
ConMZ ConDZ
h
Ref
Finland
Adult
0.5D
54
55
0.80
0.51
0.58
Teikari 91
Taipei
7-23yrs
QTL
49
37
0.65
0.46
0.24
Lin 87
Shanghai 7-19yrs
Lo, 5D
49
37
0.82
0.58
0.61
Hu 81
Taipei
10-15yrs
0.5D
238
123
0.89
0.51
-
Italy
3-7yrs
QTL
19
20
-
-
Chen 87
0.08-0.14 Angi 93
Next Session
Wayne Stayskal, Tampa, FL
Genetic Epidemiology
Stages in identifying disease genes
RESEARCH QUESTION
METHOD/APPROACH
Disease characteristics? – Descriptive epidemiology
Familial clustering?
– Family aggregation
Genetic or Environmental? studies
Mode of inheritance?
– Twin/Adoption studies
– Segregation analysis
Disease susceptibility loci?
Gene? Mutation?
– Linkage analysis
– Association studies
OBJECT
Species
Population
Family
Genetic locus
Gene
Mutation
Mode of Inheritance
How is genetic susceptibility inherited?
Segregation analysis
“Is distribution of affected individuals within families
consistent with a specific genetic model?”
Modes of inheritance
Single gene (Mendelian)
– Autosomal
• recessive
• dominant
– X-linked
Single gene (non-Mendelian)
– Mitochondrial, Imprinted
Multiple gene (complex, quantitative trait)
– digenic
– oligogenic
– polygenic
X-linked Myopia
BED
Partial BED
Deuteranopia
M Schwartz et al (1990) Clinical Genetics 38:281-6
Bornholm Eye Disease:
• bilateral myopia >=6D
• amblyopia
• optic nerve hypoplasia
• RPE thinning
• subnormal ERG flicke
• deuteranopia
An L-type calcium-channel gene mutated in
incomplete X-linked congenital stationary night
blindness
Tim M. Strom et al. Nature Genetics 19, 260 – 263 (1998)
Loss-of-function mutations in a calcium-channel 1subunit gene in Xp11.23 cause incomplete X-linked
congenital stationary night blindness
N. Torben Bech-Hansen et al. Nature Genetics 19, 264 – 267 (1998)
Pseudo-Mendelian Traits
Category of Adult Relatives (n)
Fathers (249)
Mothers (249)
Siblings (137)
Grandparents (598)
Uncles / Aunts (1313)
•
•
•
•
•
Overall first degree relatives
General population
Relative risk (first degree relative)
Overall second degree relatives
Relative risk (second degree relative)
Trait (%)
16.1
6.0
21.9
2.8
2.1
13.4
0.22
60.9
2.4
10.7
“Simulation of Mendelism revisted: the recessive trait for attending medical school”
P McGuffin & P Huckle 1990: Am J Hum Genet 46:994-9
Genetic Loci
Where are the genetic loci / susceptibility genes?
Linkage analysis
“Is hypothetical susceptibility gene near a known genetic
marker?”
– Parametric (requires known model, estimation of θ,
penetrance): extended pedigree
– Nonparametric: Affected relative pair analysis (eg. sib-pair)
Approaches to Linkage and Association
Linkage Analysis
Parametric Analysis
Non-parametric Analysis
Affected relative pairs
Linkage Disequilibrium / Association Analysis
Case-control
Family-based association
Genetic Linkage Analysis
a/b
Classical Linkage
c/d
Sib-pair Linkage
•120 concordant Sib Pairs
•SAF and SERI
•top 10 percentile
•Chinese
Human Genetics Approaches
Genome Wide
“Discovery”
Candidate Gene
“Hypothesis”
a/b
c/d
a/c
Sib-pair Linkage
n = 120 concordant sib
pairs
Case Control
Association
n = 95 severe myopes
Family
Based
Association
Tools for Linkage and Association Analysis
Markers
Short Tandem Repeats / Microsatellites
Minisatellites / Variable Number of Tandem
Repeats
Single Nucleotide Polymorphisms
Maps
Genotyping Technologies
CHROMOSOME LINKAGE MAP OF THE
OXFORD MICROSATELLITE SET (Reed)
Non-Parametric Linkage Analysis
a/b
c/d
Alleles IBD
a/c
0
b/d
a/c
1
b/c
a/c
1
a/d
a/c
2
a/c
Affected Relative Pairs
Sib Pair - concordant
discordant
Alleles Identical by Descent
Sib-pairs sharing 0
1
2
No linkage
25% 50% 25%
Linkage eg
10% 55% 35%
Non-Parametric Linkage Analysis
without parental info
Alleles IBS
a/c
0
b/d
a/c
1
b/c
a/c
1
a/d
a/c
2
a/c
Alleles Identical by State
Mapping Complex Traits by Genome Wide Linkage
Analysis
Type I diabetes
Type II diabetes
Multiple sclerosis
Rheumatoid arthritis
Crohn’s disease
Essential hypertension
Coronary artery disease
Asthma
Alcoholism
Schizophrenia
Many others
cM
D18S1140
11.32
1.5
11.31
D18S476
0.1 D18S1146
11.2
11.1
D18S59
7.6cM
4.5
D18S481
1.4
D18S63
0.1 D18S1138
0.7 D18S52
9.4
D18S62
18.6
4.1
D18S1150
D18S1116
Idiogram of
Chromosome 18
Genethon Genetic Map
“Evidence that a locus for
familial high myopia maps
to chromosome 18p.”
Young TL et al. (1998) Am J Hum Genet
63:109-19.
13
12
11.2
12
13
14
15
21
22
23
24.1
24.2
24.3
30.1cM
D12S1052
D12S1684
D12S1708
D12S81
D12S1710
D12S351
D12S327
D12S1716
D12S393
D12S1706
D12S346
D12S1671
D12S1588
D12S306
D12S1607
PAH
D12S318
D12S1074
D12S360
D12S78
D12S338
D12S1075
D12S317
D12S1605
D12S2070
Idiogram of
Genethon Genetic Map
Chromosome 12
“A second locus for familial
high myopia maps to
chromosome 12q.”
Young TL et al. (1998) Am J Hum Genet
63:1419-24
Sib –pair IBD analysis (MLS)
Data not available
Sib –pair IBD analysis
Data not available
Multipoint non-parametric linkage analysis (NPL)
NPL score: 2.23
TDT analysis
Data not available
Population-optimal marker panels
Comparison of established panels among
Caucasian, Japanese and Chinese
Wu Hui Min / Tan Ene Choo
Rita Yong, Selena Tan, Joyce Chang,
Linda Gan, Eric Yap
Heterozygosity
Whole genome STR marker in 200 unrelated Chinese individuals
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
0
5
10
15
Number of Alleles
20
25
Heterozygosity of STR markers in 3 populations
h > 0.7
60
Caucasian 90.8%
Japanese 63.7%
Chinese 63.6%
40
30
20
10
> 0.90
0.81 - 0.90
0.71 - 0.80
0.61 - 0.70
0.51 - 0.60
0.41 - 0.50
0.31 -0.40
0
<0.30
Frequency (%)
50
Heterozygosity
Caucasian
Japanese
Chinese
Heterozygosity of STR markers in 3 populations
30
More informative in Chinese
Less informative in Chinese
Frequency (%)
25
20
15
10
5
0
-45
-40
-35
-30
-25
-20
-15
-10
-5
0
5
10
15
20
25
30
35
40
45
Difference in Heterozygosity
Chinese vs Caucasians
Chinese vs Japanese
• 285 STR marker panel (Reed et al.)
– Oxford panel selected from Genethon
• Median heterozygosity 0.72 (Tan/Wu, Luo)
• h independent of sample size
– Simulation: 10<n<200 for 2-27 alleles
• Propose using 192 STR with h >0.7, covering
84% of genome at 20cM
Mining for polymorphic STR useful for
high resolution genetic mapping
Liu Hai Feng, Teow Loo Nin
Wu Hui Min, Linda Gan, Ng Sock Hoon,
Eric Yap
Genome/Contig sequence
Identify tandem repeats
parser Tandem Repeat Finder
Wet lab validation and use
$$$
Map of Chromosome 12q21(83 Mb to 95 Mb)
1 cM
Repeats
1
2
3
4
5
6
more
Number
12
50
3
24
8
7
112
total
216
Predicted dinucleotide repeats in chromosome 12q (85 Mb - 95 Mb) by TRF
No. of contigs: 18 (build 29)
Total length:
10,468 kb
No. of DTR:
789 (Density : 0.075 per kb or 1 per 13.3kb)
Genome/Contig sequence
Identify tandem repeats
parser Tandem Repeat Finder
Predict highly polymorphic STR
Machine learning MLAP
Wet lab validation and use
Machine Learning for Predicting Polymorphisms
• Learning and test set
– Genethon dinucleotide markers
• Highly polymorphic h>0.8
• Lowly polymorphic h<0.5
• Parameters
– Mechanism: strand slippage during replication
Machine learning algorithm for prediction of high-polymorphic DTRs
Data not available
Characteristics of MLAP Predictions
The no. of predicted polymorphism
of candidate DTRs by MLAP, where
“NP” represents non-polymorphic
(Het < 0.5), “HP” represents highly
polymorphic (Het > 0.8), and “P”
represents those with Het between
0.5 and 0.8.
31
304
454
NP
P
HP
Heterozygosity
0.90 £ H < 1.00
0.80 £ H < 0.90
0.70 £ H < 0.80
0.60 £ H < 0.70
0.50 £ H < 0.60
0.40 £ H < 0.50
0.30 £ H < 0.40
0.20 £ H < 0.30
0.10 £ H < 0.20
H < 0.10
Type of repeat and polymorphism
12
10
8
AT
6
GA
4
CA
2
0
CA
AT
Heterozygosity
0.90 £ H < 1.00
0.80 £ H < 0.90
0.70 £ H < 0.80
0.60 £ H < 0.70
0.50 £ H < 0.60
0.40 £ H < 0.50
0.30 £ H < 0.40
0.20 £ H < 0.30
0.10 £ H < 0.20
H < 0.10
Position and polymorphism
8
7
6
5
4
3
2
1
0
INTRA
INTER
INTRA
Validation of DTR polymorphisms
Heterozygosity of HP and LP DTRs
14
10
LP DTRs
8
HP DTRs
6
4
2
Heterozygosity
0.90 ≤ Η < 1.00
0.80 ≤ Η < 0.90
0.70 ≤ Η < 0.80
0.60 ≤ Η < 0.70
0.50 ≤ Η < 0.60
0.40 ≤ Η < 0.50
0.30 ≤ Η < 0.40
0.20 ≤ Η < 0.30
0.10 ≤ Η < 0.20
0
0 ≤ Η < 0.10
Frequency
12
20 HP and 9 NP markers were
selected for genotyping in 24
unrelated Chinese individuals.
Frequency of observed
heterozygosity for each marker in
the 2 groups is shown. The
prediction accuracies were 95%
and 33% for HP and NP group
respectively.
Gene and Mutation
What gene and mutations are associated with diseas
Disease-genotype association, linkage dysequilibrium
“Do affected individuals have certain allele/genotype more often
than by chance?”
– Population-based allelic association
– Family-based allelic association
Mutation analysis
“Are there functional mutations that account for phenotype?”
Gene Association Studies
a/b
c/d
a/c
Case Control
Association
Family
Based
Association
Population Admixture
Differing allelic frequencies and
disease prevalences in two
subpopulations, with no biological
association –> Apparent association
If both subpopulations mate
randomly and completely (panmixia),
then population is homogeneous
and admixture is no longer
significant.
To overcome artifacts:
– use homogeneous populations
– replicate study in several
populations
– use meiotic (family-based)
association studies
Population I Population II
Allele m
Allele M
HEALTHY
HEALTHY
DISEASE
Family-Based Association
a/b
c/d
Types of analyses:
Haplotype relative risk (HRR)
Rubinstein
& Falk
Affected family-based controls (AFBAC) Thomson
Transmission distortion test (TDT)
Spielman
a/c
“Are alleles a and c
transmitted more
frequently in affected
than alleles b and
d?”
HRR eg.
Alleles
transmitted
not transmitted
a b c d
1 0 1 0
0 1 0 1
Trabecular Meshwork Inducible Glucocrticoid Receptor
(TIGR) or Myocilin Gene
-103 to –99
NGA17
TATA box
Exon 1
-224
C/T
Exon 2
Exon 3
NGA19
Novel SNP in TIGR 5’UTR
A A A T A A CC T T CCA G A A G T CT GT T T G GA
Population
Chinese
No of
chromosomes
64
Malays
64
Indians
64
Caucasian
20
AfricanAmerican
Middle Eastern
20
AmericanIndians
Mexican
20
Puerto Rican
20
A AA A T AA CC T T CCGG A AGT C T GT T T G GA
100 bp
Marker
T/C
C/C
T/C
T/C
T/T
A A A T A A C C T T CC A/G G A A G T C T G T T T G G
20
20
294 bp
223 bp
Allele
frequency
T1: 0.59
T2: 0.41
T1: 0.59
T2: 0.41
T1: 0.87
T2: 0.13
T1: 0.75
T2: 0.25
T1: 0.45
T2: 0.55
T1: 0.75
T2: 0.25
T1: 0.80
T2: 0.20
T1: 0.95
T2: 0.05
T1: 0.85
T2: 0.15
Heterozygosity
observed
0.50
0.50
0.19
0.30
0.70
0.50
0.44
0.10
0.11
Data for TDT Analysis
Age
Gender Refraction (Mean, SD)
• First sample set
91 cases
16-43 M:46
(21.5,1) F:45
-6.5 to –16.75D
(-11.25, 2.15)
• Second sample
129 cases
5-15 M:75
(10.3, F:54
5.4)
-1.5 to –14.85D
(-5.89, 3.33)
Markers in TIGR Gene
-103 to –99
NGA17
TATA box
Exon 1
Exon 2
-224
Exon 3
NGA19
C/T
18.6kb D’=0.38
0.1kb
D’=0.35
18.7kb D’=0.17
N >= 200 individuals
Family Association analysis of TIGR Gene
Single locus TDT analysis
Chi-square
40
p < 0.001
30
ns
20
10
p = 0.002
0
D1S210
D1S2815
NGA17
Markers
TIGR
NGA19
X2 (Sum)
X2 (Max)
TDT analysis of the 3 markers of the MYOC gene in myopia families.
a. First family set (44 families):
No of
2
Markers Allele Het (%) X sum
NGA19
7
60.5
27.89*
*p = 0.001, †p = 0.013
Allele
(%)
122
(1.2)
124
(23.3)
126
(0.6)
128
(65.7)
130
(5.2)
132
(2.3)
134
(1.7)
2
TR
NT
X
0
2
2
21
43
7.56
3
0
3
OR
(95% CI)
3.4
57
30
8.38†
6
8
0.29
0
6
6
4
2
0.67
(1.84,
6.13)
TDT analysis of the 3 markers of the MYOC gene in myopia families.
b. Second family set (60 families):
No of
2
Markers Allele Het (%) X sum
NGA19
4
71.9
11.32*
*p = 0.04,
Allele
(%)
124
(27.1)
128
(69.5)
130
(3.0)
132
(0.4)
2
TR
NT
X
38
47
0.95
OR
(95% CI)
2.2
55
36
3.97
3
12
5.4
0
1
1
(1.25,
3.39)
TDT analysis of the 3 markers of the MYOC gene in myopia families.
c. Combined family set (104 families):
No of
Allele
2
Markers Allele Het (%) X sum
(%)
122
NGA19
7
53.4
35.18*
(0.5)
124
(25.5)
126
(0.2)
128
(67.9)
130
(3.9)
132
(1.2)
134
(0.7)
* p < 0.001, ** p = 0.002
2
TR
NT
X
0
2
2
59
90
6.45
3
0
3
OR
(95% CI)
2.7
112
66
11.89**
9
20
4.17
0
7
7
4
2
0.67
(1.80,
4.13)
Family Association analysis of TIGR Gene
Multi-locus TDT analysis
Haplotypes
%
TR
(Obs)
TR
(Exp)
**TIGR-NGA19
T1
128
30.5 113.74 95.38
*NGA17-NGA19
215
128
19.5
70.63 57.78
*NGA17-TIGR NGA19
215
T1
128
19.5
66.5 53.23
* Global p < 0.05, ** Global p = 0.005
X2
P
(1df ) (2sided)
9.88
0.002
7.31
0.007
8.37
0.004
Significant association of
allele 128 of NGA19 and
severe myopia
Summary & Conclusions
Myopia is a complex
(heterogeneous) genetic
disease
Evidence for a novel gene
on chromosome 12
predisposing to myopia
discovered
Locally developed
capability:
– facilities for high
throughput genotyping
capability
– unique expertise in
genetic epidemiology for
disease gene hunting
Application to other dis:
Replicated allelic and
haplotypic association to
TIGR gene
– SLE, Hypertension
– Pb poisoning, Diabetic
nephropathy
Genetics Approaches
Positional Cloning / Linkage
•Discovery-based, systematic*
•Genome-wide*
•Mendelian*
•Study relatives – extended or
nuclear families*
•Large pedigrees with multiple
affecteds ideal*
•Highly informative markers
(Microsatellites)*
Candidate Gene / Association
(Linkage Dysequilibrium)
•Hypothesis-driven, intuitive,
pathways or models*
•Not genome-wide*
•Complex diseases*
•Requires individuals, small
families*
•Isolated homogeneous
population ideal*
•Highly abundant markers
(SNPs)*
* With Exceptions
Research Team
Myopia & Human Genetics Group
DMRI/SERI