Strong Heart Family Study Phase VI Genetics Center Aims

October 8, 2009

Overview of genetics presentation

• Progress– Both from the SHFS Phase V and from relevant

ancillary studies

• Discussion of Genetics Aim – Capitalize on progress and new screening procedures– Data from ongoing studies will solidify which loci are

fine mapped and proposed for further investigation in Phase VI.

– Will consider adjusting approaches as technologies change.

Progress

Despite the lack of genome-wide SNP data, we still have significant progress to follow-up using state-of-the-art approaches

• In Phase V, the genetics center has had 14 published or in press manuscripts, has 5 manuscripts in the journal submission process, and has published/presented 18 abstracts.

Progress continued• Ancillary studies/collaborations

– CALiCo/PAGE – NHGRI consortium to characterize population- and environmental- specific effects on GWAS-identified functional SNPs

• not all GWAS results replicate in all population subgroups, including American Indians, demonstrating the need to consider population differences and therefore the continued need for studies such as the SHFS

• Gene localization– Have unique QTLs, some related to preclinical markers,

identified through linkage and confirmed by follow-up association analysis in SHFS

Linkage/association progress:candidates for sequencing follow-up

Trait w QTL in SHFS Chr Candidate Gene (s) Association

Replication

Heart rate 9 KIAA1797 Expression correlated with HR in Mexican Americans of SAFHS>1 Mb away from GWAS SNPs

presence or absence of plaque

22 TXN2 ? Novel locus

bilirubin 2 UGT1A1 Replicates Framingham and others, but evidence for additional novel variation

diastolic blood pressure 10 FANK1 Possibly other QTLs

Uric acid 11 SLC22A12 Novel locus

LVM 12 > 2,000 SNPs being analyzed

Dominican families

BMI 4 IRF2, ENPP6,

LOC442120; Additional association analyses ongoing

Novel locus, gene poor region

BMI/obesity 7 > 2,000 SNPs being analyzed

Replicates reports from multiple populations

Phase VI: Specific Aim 1

• To identify the genetic polymorphisms that are responsible for variation in phenotypic risk factors for obesity, diabetes and preclinical and clinical CVD – Genotyping– DNA sequencing– Gene expression– Gene x environment

This will be presented in 3 sub-aims

Genetics: Specific Sub Aim 1

Identify the functional variant(s) responsible for one or more of our linked and associated loci (Additional fine mapping of QTLs & linkage analysis of new phenotypes)

Applies state-of-the-art sequencing technologies to follow-up promising results and ongoing efforts

Genetics: Specific Sub Aim 1Identify the functional variant/polymorphism(s) responsible for one or more of our linked and associated loci

• Using flexible, high-density NimbleGen microarrays to capture any desired fraction of the human genome for ultra high-throughput sequencing (Illumina Genetic Analyzer, or “Solexa”) for polymorphism and rare variant identification

- Up to 5Mb analyzed at one time in 40 to 50 participants- Individuals chosen from families showing linkage and

representing those with and without the associated allele or haplotype.

- Technique being established in house

• Genotyping and association analyses using all identified variation, including rare variants

- Infinium iSelect, thousands of polymorphisms typed simultaneously

• Alternative strategy for some loci: Deep sequencing of candidate genes

- Hundreds of samples sequenced for a targeted gene region

Have two loci worthy of intensive follow-up, but the opportunity exists for additional loci to become available as our ongoing studies progress over the coming months.

Genetics: Specific Sub Aim 2

Whole genome gene expression profiling of lymphocytes collected at the time of liver/abdominal MRI for functional pathway analysis and confirmation of linked/associated loci to liver, subQ and abdominal fat phenotypes

Capitalizes on proposed MRI scans

Genetics: Specific Sub Aim 2Whole genome gene expression analysis (microarrays) of lymphocytes collected at the time of liver/abdominal MRI for functional pathway analysis and confirmation of linked/associated loci to liver, subcutaneous and abdominal fat phenotypes

• Lymphocytes chosen as an easily-available tissue for a genetic-epidemiological study

• Discovery and candidate gene association studies– Select ~250 cases, 250 controls based on extent of fat infiltration of

liver and size of abdominal and subcutaneous fat depots– Use correlation analysis to identify genes that are up and down

regulated– Use pathway analysis to discover gene pathways that are

coordinately up and/or down regulated, and to identify genes that may not be expressed in lymphocytes but are part of pathway

– Use data available from collaborations to identify likely cis-regulated genes (SAFHS, baboons, NAFLD study)

– Perform association analysis between genetic variation in promoter regions of cis-regulated genes in pathway with CVD-related phenotypes

Genetics: Specific Sub Aim 2 (cont.)

• Gene identification– Discovery through linkage/association

analysis on new liver/fat phenotypes (non-expression)

– For our linked and associated loci to liver/fat phenotypes, use expression levels to assist in gene discovery or pathway completion (such as was done with the heart rate QTL).

• Confirmation of individual expression results can be done using remaining samples (TaqMan)

Genetics Specific Sub Aim 3

Refined analyses of existing loci (linked and associated variants and putative functional variants), incorporating GxE and/or longitudinal analyses.

Capitalizes on environmental measures (including stress response from the proposed cold pressor test) and the rich longitudinal dataset of the SHFS as well as the Cohort Study.

Genetics: Specific Sub Aim 3

Refined analyses of established loci (linked and associated variant and putative functional variants), incorporating GxE and/or longitudinal analyses

• Will address variant/polymorphism specific questions• Types of environmental factors: dietary components, stress,

physical activity parameters, sex, smoking, etc.– Example: The effect of a heart rate variant may be altered in

individuals who are more susceptible to stress as indicated by the cold pressor test.

• Longitudinal data: progression to diabetes, weight gain, change in BP, etc.

– Example: The effect of a variant on plaque development may be altered in those who progress, or don’t progress, to diabetes

• Cohort samples will be genotyped to allow studies in both the Family Study and Cohort samples.

– Increases longitudinal dataset and available environmental phenotypes