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Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online. [ABSTRACT FROM AUTHOR]

Despite the dramatic underrepresentation of non-European populations in human genetics studies, researchers continue to exclude participants of non-European ancestry, as well as variants rare in European populations, even when these data are available. This practice perpetuates existing research disparities and can lead to important and large effect size associations being missed. Here, we conducted genome-wide association studies (GWAS) of 31 serum and urine biomarker quantitative traits in African (n = 9354), East Asian (n = 2559), and South Asian (n = 9823) ancestry UK Biobank (UKBB) participants. We adjusted for all known GWAS catalog variants for each trait, as well as novel signals identified in a recent European ancestry-focused analysis of UKBB participants. We identify 7 novel signals in African ancestry and 2 novel signals in South Asian ancestry participants (p < 1.61E-10). Many of these signals are highly plausible, including a cis pQTL for the gene encoding gamma-glutamyl transferase and PIEZO1 and G6PD variants with impacts on HbA1c through likely erythrocytic mechanisms. This work illustrates the importance of using the genetic data we already have in diverse populations, with novel discoveries possible in even modest sample sizes., (© 2021. The Author(s), under exclusive licence to The Japan Society of Human Genetics.)