Repeat polymorphisms in non-coding DNA underlie top genetic risk loci for glaucoma and colorectal cancer

Abstract

Many regions in the human genome vary in length among individuals due to variable numbers of tandem repeats (VNTRs). We recently showed that protein-coding VNTRs underlie some of the strongest known genetic associations with diverse phenotypes. Here, we assessed the phenotypic impact of VNTRs genome-wide, 99% of which lie in non-coding regions. We applied a statistical imputation approach to estimate the lengths of 9,561 autosomal VNTR loci in 418,136 unrelated UK Biobank participants. Association and statistical fine-mapping analyses identified 107 VNTR-phenotype associations (involving 58 VNTRs) that were assigned a high probability of VNTR causality (PIP≥0.5). Non-coding VNTRs at TMCO1 and EIF3H appeared to generate the largest known contributions of common human genetic variation to risk of glaucoma and colorectal cancer, respectively. Each of these two VNTRs associated with >2-fold risk range across individuals. These results reveal a substantial and previously unappreciated role of non-coding VNTRs in human health.

Protein-altering variants at copy number-variable regions influence diverse human phenotypes

“…This strategy proved fruitful: association analyses with 57 quantitative traits identified 375 associations at 99 loci not explainable by linkage disequilibrium (LD) to nearby SNPs (Supplementary Data 4), recovering strong VNTR-phenotype associations we recently reported (including a 39-bp coding repeat in GP1BA associated with platelet traits 35 ; P = 1.1 × 10 −133 ), and revealing several new loci involving multicopy variation poorly tagged by SNPs. Follow-up analyses of the most intriguing associations, detailed below, enabled further exploration of genetic variation at these loci and its influences on human health.…”

Exome-wide tandem repeats confer large effects on subcortical volumes in UK Biobank participants

“…58 Our findings pave the way for a novel approach to investigating the influence of genetic factors on brain biology. We, and others, [15][16][17]59 have demonstrated the power of TR-wide association studies to identify significant genetic effects independent of those discovered by SNP-focused GWAS. In particular, this work expands our understanding of the genetic architecture of subcortical volumes, underscoring the importance of considering repetitive elements in the broader landscape of brain genetics.…”

MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data

“…Exclusion of causal variants could in principle induce false-positive results at tagging variants that survive this filter; however, the functional enrichment of fine-mapped (PIP > 0.5) variants that are rare or low-frequency (MAF < 0.05) in at least one population is similar to that of variants that are common (MAF > 0.05) in both populations (2.85 vs 2.88, p = 0.91 for difference), suggesting that our exclusion criteria did not produce substantial false positives in practice. Second, as with all fine-mapping methods, exclusion of variants that are difficult to genotype, even in WGS data, (including tandem repeats [77][78][79] and other structural variants 80,81 ) could induce false-positive results at tagging variants. Indeed, at the HBA locus for mean corpuscular volume, SuSiE using Afr47k fine-mapped (at PIP > 0.5) 17 single nucleotide variants, 1 insertion, and 1 deletion (Supplementary Table 15); all fine-mapped variants were jointly significant in a multiple linear regression model.…”