LargeScale Population Studies using Genetic Polymorphisms

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Large-Scale Population Studies using Genetic
Polymorphisms
Jonathan C. CohenUT Southwestern Medical Center
Financial Disclosure NoneUnlabeled/Unapproved
Uses None
For slide narration see notes for text.
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Genetic Architecture of Heart Disease
Common Variant
Rare Variants
Age
Ancient
Recent
Ancestry
Common
Different
Frequency
High
Low
Effect
Small
Large
alleles
Few
Many
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Association Studies

Dallas Heart Study (DHS) Extensive Phenotyping
Southwestern PGA High Throughput Genotyping
Association Studies
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Dallas Heart Study
Dallas Heart Study
AA (50)
Caucasian (35)
Hispanic (15)
Other (lt1)
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Dallas Heart Study
Dallas Heart Study
DXA
MRI
n 3000 ages 30-60 50 Black 15 Hispanic
EBCT
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Southwestern PGA Conceptual Framework
Candidate Gene List Expression studies, Computer
prediction, Expert opinion
Identify SNPs in Candidate Genes DNA sequencing
in affected individuals
Genotype SNPs in DHS Mass Spectrometry (Sequenom)
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Heart Disease SNPs
Heart Disease SNPs

• Identify SNPs in 356 candidate genes (n3266)

• Atherosclerosis

• Hyperlipidemia
• ? LDL-cholesterol
• Triglycerides
• HDL-cholesterol
• Insulin resistance
• Hepatic fat (MR-spectroscopy)
• coronary calcium (EBCT)

• HTN / LVH / CHF

451 nonsynonymous SNPs
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Heart Disease SNPs
Heart Disease SNPs
2. Determine association with phenotypes

• Genotype DHS (Mass Spectrometry)
• Test SNPs against all phenotypes (ANOVA)
• Test 4 groups independently
• Black men, Black women, White men, White women

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Genetic Association Studies InitialScreen
Phenotypes
SNPs
WM 0.04
BM 0.03
BW 0.02
WW 0.04
WM 0.4
BM 0.03
BW 0.6
WW 0.5
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Sources of Error in Genetic Associations

• Genotyping Errors
• False Positive Associations

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Genotyping Errors in DHS

• - Validated Sequenom assay 7 SNPs, 50 samples

- Determine if SNPs in Hardy Weinberg
equilibrium (HWE) 16/151 SNPs analyzed in DHS
not in HWE
Error rate using mass-spectrometry real-time
PCR
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• False Positive Associations

Association study 129 SNPs and
LDL-cholesterol 16 SNPs Plt0.05 in 1 of 4
groups 2 SNPs Plt0.05 in 2 of 4 groups 1 SNP
Plt0.05 in 4 of 4 groups APOE
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Strategies to Avoid False Associations
Adjusting for Multiple Testing

• Correct for multiple testing using Bonferroni
  correction Pka/n

Example 129 SNPs analyzed in 4 groups To
obtain P 0.05 would require a Pk 0.0001 For
APOE on LDL-C, P 0.02 in Black Men (n772) For
APOE on LDL-C, P 0.002 in White Men
(n499) Neither would be considered at the
adjusted P-value
Problem loss of power to detect true
associations
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Strategies to Avoid False Associations

• 2. Use nominal P-value (0.05) and replicate,
  replicate

Example APOE and LDL-cholesterol Nominal P
values in consecutive groups Black men 0.02
White men 0.002 Black women 0.0001 White
women 0.0001 Cumulative Probability 0.02 X
0.002 X 0.0001 X 0.0001 0
Replication eliminates false positives without
increased risk of false negatives
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APOAV S19W Allele and Plasma Triglyceride
Concentrations in DHS

300
wt
250
S19W

200


Plasma Triglyceride (mg/dl)
150
100
Plt 0.05
50
0
Black Women
White Women
White Men
Black Men
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APOAV Alleles and Plasma Triglyceride
Concentrations
TG lt 10th percentile
TG gt 90th percentile


25
20
15
with S19W
10
Plt 0.005
5
0
Men (n164)
Women (n100)
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Conclusions

• Large-scale studies generate many false-positive
  associations
• Very low P-values will eliminate true
  associations
• Replication is critical to validation of genetic
  associations
• Optimal strategy Use nominal P-value for initial
  screen and validate by replication
• Reliability of high-throughput genotyping assays
  should be carefully examined

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Genetic Architecture of Heart Disease
Rare Variants
Common Variant
Age
Ancient
Recent
Ancestry
Common
Different
Frequency
High
Low
Effect
Small
Large
alleles
Few
Many
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Genetics of Congenital Heart Disease (CHD)

• Most CHD sporadic, familial cases uncommon
• Multifactorial etiology
• Genes plus environment
• 5-fold increase in recurrence risk
• Few known genetic causes of CHD
• Multiple AD syndromes with CHD in which gene is
  known
• Only one non-syndromic cause of CHD NKX2-5

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Identification of Mutations Causing CHD

• Sequence all genes known to be required for
  cardiac development in patients with CHD
• Identify nonconservative mutations
• Test for i) Segregation in family
• ii) Effect on function in vitro
• iii) Effect on function in vivo (animal
  models)

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Prevalence of Sequence Variations

• Selection of candidate genes (n100)
• Disruption of gene alters cardiogenesis in model
  organism (flies, fish, mice)
• Sequenced exons, flanking intronic sequences
• Subjects CHD (42 sporadic, 17 familial)
• - Septal defects, Tetralogy of Fallot, pulmonic
  stenosis, patent ductus arteriosus, etc
• Mutations detected 149 nonsynonymous variants
  
• 44 found in only a single subject

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Nature of Rare Sequence Variations
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Candidate Gene GATA4

• Transcription factor
• - 2 zinc finger domains
• Expressed in heart during embryogenesis
• Essential for cardiogenesis in flies, fish, and
  mice

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Mutation of a Highly Conserved Residue (G296S) in
GATA4
Transcription activating domains
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Atrial and Ventricular Septal Defect
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GATA4 G296S Segregates With Cardiac Septal Defects
No mutation found in 3500 controls
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Genome-wide Linkage Analysis Limits Linkage to
8p22-23

• Genome wide linkage analysis 358 microsatellite
  markers
• Single linked region (12.7 Mb) on chromosome 8p

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GATA4 G295S has reduced DNA binding
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Frameshift Mutation in GATA4 in Unrelated
Patient with ASD
c.1075delG E359X
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Frameshift Mutation in GATA4 Segregates with CHD
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Screening other Patients with ASD and VSD for
GATA4 mutations

• Generating mutant constructs and testing function
• Other non-synonymous changes S377G, V380M, and
  P394T

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Conclusions

• Mutations in GATA4 mutations cause CHD
• Large-scale sequencing in targeted populations
  may reveal mutations with large phenotypic
  effects that are common in aggregate

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Acknowledgements
Bioinformatics Alex Pertsemlidis Jeff
Schageman Bob Barnes
Dallas Heart Study Helen H. Hobbs Rudy Guerra
Congenital Heart Disease Deepak Srivastava Vidu
Garg