Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

Abstract

Large-scale whole genome sequencing (WGS) studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests (RVATs) have limited scope to leverage variant functions. We propose STAAR (variant-Set Test for Association using Annotation infoRmation), a scalable and powerful RVAT method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce “annotation Principal Components”, multi-dimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness, and is scalable for analyzing very large cohort and biobank WGS studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery samples and 17,822 replication samples from the Trans-Omics for Precision Medicine program. We discovered and replicated novel RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.

An efficient and accurate frailty model approach for genome-wide survival association analysis controlling for population structure and relatedness in large-scale biobanks

“…The top hit in UKBB (rs157592, MAF = 18.7%, p-value = 1.87 x 10 -8 ) had LD r 2 = 0.7 with rs429358 as presented in the Supplementary Table 3. This variant is in the intergenic region and have no in-silico functions according to the FAVOR functional annotation online portal 56 (See URL).…”

“…Third, the current implementation of GATE is targeted to perform single-variant association analysis, which can suffer from low power to detect associations in extremely rare variants. With whole genome and whole exome sequencing data available, a possible future extension of this method can allow for mask-based or region-based association tests to improve power for the rare variants 56,59 . Finally, the current version of GATE does not incorporate left-truncated data, which may not be valid for early-onset phenotypes in biobanks with relatively older participants.…”

“…Manhattan plots, Q-Q plots, and regional association plots for each TTE phenotype as well as the PheWAS plots can be browsed at http://phewas.genohub.org/. The FAVOR 56 portal is accessed through favor.genohub.org.…”

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

“…We show that TOPMed WGS data provide a rich resource for developing and testing methods for surveying human variation, for inference of human demography and for exploring functional constraints on the genome 73 , 74 . In addition to these uses, we expect that TOPMed data will improve nearly all ongoing studies of common and rare disorders by providing both a deep catalogue of variation in healthy individuals and an imputation resource that enables array-based studies to achieve a completeness that was previously attainable only through direct sequencing.…”

A multi-dimensional integrative scoring framework for predicting functional variants in the human genome

“…MACIE scores have already been used, for example, to identify and characterize inflammation and immune-related risk variants in squamous cell lung cancer41 . Finally, the proposed MACIE scores can be used as a weighting scheme to further empower variant-set analyses of rare variants42 .…”