Family Based Analyses to Identify
Rare Genetic Variants
Platelet function assays are moderately to highly heritable supporting the hypothesis that genetic variations underlie individual variability in the tendency for arterial thrombosis. During the past seven years, in GeneSTAR GWAS revealed multiple common genetic loci that pass stringent GWAS thresholds in African American and European Americans families at high risk for CHD. Common variants were found to determine variability in native platelet aggregation as well as residual platelet aggregation after low dose aspirin (ASA) intervention. However, collectively the loci identified through this common variant approach account for less than 35% the total heritability of these phenotypes in the GeneSTAR families. Extending a family-based design in an integrative approach, our approach is currently : 1) identifying rare variants in genes that are associated with native and residual post- ASA platelet aggregation, testing the hypothesis that a significant fraction of the 'missing heritability' in platelet aggregation phenotypes is due to these rare variants; and 2) follow up -identified loci to determine the underlying 'causal' variants tagged by the GWAS association signal. In a family-based exome sequencing approach havel sequenced 200 hyper-aggregable individuals selected from African American and European American GeneSTAR families with clustering of platelet aggregation.
Validated exome sequencing-identified genes along with the GWAS-identified loci will be followed up relying on a targeted deep resequencing approach of 1,300 African American and European American subjects from additional GeneSTAR families. The results from this integrative GWAS and exome approach will lead to a better understanding of the role of genetic variants (common and rare) in the determination of platelet aggregation native and residual post-ASA, including possible racial differences, and should enable genotypic tailoring of preventive therapy for CHD in high-risk individuals.Native and residual post aspirin platelet hyper aggregation, a strong risk factor for ischemic syndromes, is moderately to highly heritable.
Our in families suggest a high degree 'missing heritability' (i.e. that not explained by the common GWAS signal detected). The primary hypothesis is that genes harboring rare genetic variants determining platelet aggregation account for a substantial fraction of missing trait heritability, and an integrative family-based approach of GWAS and exome-sequencing will be applied to test this hypothesis.
Working closely with the Bisostatistics Department , we are honing in on methods that utilize the full capacity of family-based methods,and that we will extend to whole genome sequencing, providing integration of our different approaches to understanding platelet function. Transitioning these novel anlaytic models to whole genome data and the mult-iomic data we are collecting in other studies will provide a valuable adjunct to larger studies using discovery approached in Big Data efforts.
Whole Genome Sequencing; TOPMed
Trans-Omics for Precision Medicine (TOPMed) Program: NHLBI
The NHLBI goal is to collect WGS data for individuals who have well-defined clinical phenotypes and outcomes from earlier NHLBI-funded studies. Initially, the WGS project planned to sequence 20,000 genomes. The TOPMed program is conducting studies to collect -omics data in a subset of WGS project participants. Currently, the TOPMed program consortium includes centers that support program activities such as data coordination, informatics research, whole-genome sequencing, RNA sequencing, and metabolite and methylation profiling. Two of these centers, the Data Coordination Center and the Informatics Research Center, serve the entire TOPMed program. The National Center for Biotechnology Information (NCBI) will provide data repository and access service for the TOPMed program. GeneSTAR’s award allows us to participant in many phenotypic aspects of WGA as well as to refine family based methods to amplify findings from the discovery samples.
to this work was approved for NHLBI Whole Genome Sequencing Project (NHLBI-WGS)
in 1800 subjects to significantly boost the study design of the parent work in
families with platelet function. The new
TOPMed work involves two additional RNASeq projects on specific target tissue of
platelets and iPS derived megakaryocytes.
Our primary emphasis is on the genetics of platelet aggregation and our original
WGS study design was a two-step approach to identifying genes harboring rare
variants that determine platelet hyper-aggregation in families at high risk for
CAD. We are also generating data in
families that will be far reaching beyond the primary phenotypes using the extensive
phenotyping available of the participating subjects from families identified at
high risk over a 32 year period of the GeneSTAR Program. In TOPMed under Dr.
Mathias’s leadership we are participating in work groups on atherosclersis,
hematologic traits, neurology and related traits, anthropometrics, diabetes,
and many other traits.
Innovation of the Family Based Design
application of the family based study design is multi-fold wherein we (1) identify
families that have clustering
of baseline hyper-aggregation and residual post-ASA hyper-aggregation; (2) whole
a set of families prioritized on the basis of both phenotypes; (3) replicate the
identified genes/loci in additional
independent families with measured phenotype; and (4) leverage WGS and transcript
data to prioritize
non-coding sequence identified variants based on exhaustive eQTL analysis. Our
original study design
is vastly improved in its innovation with points 3 and 4 above yielding a
comprehensive multi-step approach
which not only yields high statistical power for rare variant association
signal, but also limits the false positive
signal seen as a limitation of rare variant investigation in the case-control
design. Finally this approach offers
new insight into how much of the 'missing heritability' can
be explained by rare
variants in the context of true familial heritability in place of total
phenotypic trait variability.
Rasika A Mathias, ScD
Associate Professor, Medicine
Associate Professor, Epidemiology
Kai Kammers, PhD
Department of Biostatistics
Jeff Leek, PhD
Associate Professor of Biostatistics and Oncology
Ingo Ruczinski, PhD
Department of Biostatistics
Margaret A Taub, PhD
Department of Biostatistics