Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry

Abstract

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained %20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

Association Analysis of Candidate Variants in Admixed Brazilian Patients With Genetic Generalized Epilepsies

“…Lack of transferability of GWAS results and polygenic risk scores obtained from Europeans and American admixed populations have previously been reported (Martin et al, 2017(Martin et al, , 2019, making it important to investigate whether these SNPs are associated with GGEs in our admixed Brazilian sample. An alternative explanation for the lack of reproducibility among populations relies on the observation that only tagging SNPs are ascertained in GWAS, and the lack of replication in different populations could be due to broken linkage between the tagging SNPs and the causal variants (Akiyama et al, 2019;Chen et al, 2020;Graff et al, 2021). Thus, we searched for SNPs flanking 1 Mb upstream and downstream of the candidate regions to investigate this issue.…”

“…An alternative explanation for the lack of reproducibility among populations relies on the observation that only tagging SNPs are ascertained in GWAS, and the lack of replication in different populations could be due to broken linkage between the tagging SNPs and the causal variants ( Akiyama et al, 2019 ; Chen et al, 2020 ; Graff et al, 2021 ). Thus, we searched for SNPs flanking 1 Mb upstream and downstream of the candidate regions to investigate this issue.…”

“…It has been reported that SNPs found to be associated with the phenotype by GWAS in one population may be only nominally associated or non-associated in another population due to difference in LD across populations ( Akiyama et al, 2019 ; Chen et al, 2020 ; Graff et al, 2021 ); however, it does not mean that an associated signal in the genomic region cannot be replicated. This is because the SNPs ascertained from GWAS are only tagging variants linked to causal ones.…”

Mixed ancestry analysis of whole-genome sequencing identifies TBX5 and PTK7 as susceptibility genes for posterior urethral valves

“…47 GWAS findings have been shown to replicate across populations in a variety of common diseases, [74][75][76][77][78][79][80][81] suggesting sharing of common causal variants between ancestries despite differences in allele frequencies and effect sizes. 82 Furthermore, the benefit of combining population groups has been clearly demonstrated in trans-ancestry metaanalyses, [83][84][85] where differences in LD structure are specifically utilized to improve the resolution of fine-mapping. Mixed ancestry rare variant analyses are also a useful way to boost power for gene discovery through increased sample size, 86 with the 'collapsing' approach used to aggregate rare variants removing concerns regarding differing allele frequencies across population groups.…”

Evaluation of height as a disease risk factor through a phenome-wide association study of genetically-predicted height

“…Lead SNPs were defined within each locus if they were independent (r 2 < 0.1) and genome-wide significant (p < 510 -8 ). Novel loci were defined as those with genome-wide significance (p < 510 -8 ) and a distance > 500kb from previously published variants in European and African ancestries 10,37 . All GWAS summary statistics will be deposited in the database of genotypes and phenotypes (dbGaP) at the time of publication.…”