Whole genome sequence analysis of platelet traits in the NHLBI trans-omics for precision medicine initiative

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing from NHLBI\u27s Trans-Omics for Precision Medicine Initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several GWAS identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of whole genome sequencing in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits

Generalization of kernel machine methods for association testing of multi-omics data

Thesis (Ph.D.)--University of Washington, 2023Over the past couple of decades, genome-wide association studies (GWASs) have successfully identified thousands of loci associated with complex traits and diseases in humans. Despite the immense success of these statistical tools, post-GWAS, we are often left underwhelmed by findings that are difficult to interpret or fail to to lead to causal mechanisms and deeper understanding of trait etiology. Studies utilizing omics, including transcriptomics, proteomics, metabolomics, etc, are gaining popularity, and, used in conjunction with genomics, may aid in providing insight into complex trait etiology and disease pathogenesis. To fully harness the availability of multi-omics data types, we propose to jointly evaluate, at the gene or pathway level, the cumulative effect of all data types simultaneously. We perform these analyses using the kernel machine regression (KMR) testing framework. Within this context, we propose three projects. For project one, we extend an existing KMR testing method to accommodate joint association testing of two data types with a trait of interest in correlated samples. For project two, we generalize existing KMR testing methods to allow for joint association testing of as many data types as desired against a trait of interest in correlated samples. Finally in project three, we propose a pseudo-permutation approach to association testing of an omics data type with a trait in correlated samples for studies with small sample sizes. These statistical tools facilitate analysis of complex multi-omics studies that are applicable to a broad range of studies with correlated samples, including family-based studies with extensive relatedness and studies in ancestrally diverse populations

Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative.

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits