Allelic Heterogeneity at the CRP Locus Identified by Whole-Genome Sequencing in Multi-ancestry Cohorts. - Raffield, Laura M; Iyengar, Apoorva K; Wang, Biqi; Gaynor, Sheila M; Spracklen, Cassandra N; Zhong, Xue; Kowalski, Madeline H; Salimi, Shabnam; Polfus, Linda M; Benjamin, Emelia J; Bis, Joshua C; Bowler, Russell; et al. (Am J Hum Genet, 2020)
Whole-genome sequencing (WGS) can improve assessment of low-frequency and rare variants, particularly in non-European populations that have been underrepresented in existing genomic studies. The genetic determinants of C-reactive protein (CRP), a biomarker of chronic inflammation, have been extensively studied, with existing genome-wide association studies (GWASs) conducted in >200,000 individuals of European ancestry. In order to discover novel loci associated with CRP levels, we examined a multi-ancestry population (n = 23,279) with WGS (∼38× coverage) from the Trans-Omics for Precision Medicine (TOPMed) program. We found evidence for eight distinct associations at the CRP locus, including two variants that have not been identified previously (rs11265259 and rs181704186), both of which are non-coding and more common in individuals of African ancestry (∼10% and ∼1% minor allele frequency, respectively, and rare or monomorphic in 1000 Genomes populations of East Asian, South Asian, and European ancestry). We show that the minor (G) allele of rs181704186 is associated with lower CRP levels and decreased transcriptional activity and protein binding in vitro, providing a plausible molecular mechanism for this African ancestry-specific signal. The individuals homozygous for rs181704186-G have a mean CRP level of 0.23 mg/L, in contrast to individuals heterozygous for rs181704186 with mean CRP of 2.97 mg/L and major allele homozygotes with mean CRP of 4.11 mg/L. This study demonstrates the utility of WGS in multi-ethnic populations to drive discovery of complex trait associations of large effect and to identify functional alleles in noncoding regulatory regions.
Keywords: African Continental Ancestry Group; Asian Continental Ancestry Group; C-Reactive Protein; Cohort Studies; European Continental Ancestry Group; Gene Frequency; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Linkage Disequilibrium; Polymorphism, Single Nucleotide; Whole Genome Sequencing

Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies. - Chen, Han; Huffman, Jennifer E; Brody, Jennifer A; Wang, Chaolong; Lee, Seunggeun; Li, Zilin; Gogarten, Stephanie M; Sofer, Tamar; Bielak, Lawrence F; Bis, Joshua C; Blangero, John; Bowler, Russell P; et al. (Am J Hum Genet, 2019)
With advances in whole-genome sequencing (WGS) technology, more advanced statistical methods for testing genetic association with rare variants are being developed. Methods in which variants are grouped for analysis are also known as variant-set, gene-based, and aggregate unit tests. The burden test and sequence kernel association test (SKAT) are two widely used variant-set tests, which were originally developed for samples of unrelated individuals and later have been extended to family data with known pedigree structures. However, computationally efficient and powerful variant-set tests are needed to make analyses tractable in large-scale WGS studies with complex study samples. In this paper, we propose the variant-set mixed model association tests (SMMAT) for continuous and binary traits using the generalized linear mixed model framework. These tests can be applied to large-scale WGS studies involving samples with population structure and relatedness, such as in the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program. SMMATs share the same null model for different variant sets, and a virtue of this null model, which includes covariates only, is that it needs to be fit only once for all tests in each genome-wide analysis. Simulation studies show that all the proposed SMMATs correctly control type I error rates for both continuous and binary traits in the presence of population structure and relatedness. We also illustrate our tests in a real data example of analysis of plasma fibrinogen levels in the TOPMed program (n = 23,763), using the Analysis Commons, a cloud-based computing platform.
Keywords: Chromosomes, Human, Pair 4; Cloud Computing; Female; Fibrinogen; Genetic Association Studies; Genetics, Population; Humans; Male; Models, Genetic; National Heart, Lung, and Blood Institute (U.S.); Precision Medicine; Research Design; Time Factors; United States; Whole Genome Sequencing