A Saturated Map of Common Genetic Variants Associated with Human Height from 5.4 Million Individuals of Diverse Ancestries

Abstract

Common SNPs are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here we show, using GWAS data from 5.4 million individuals of diverse ancestries, that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a median size of ~90 kb, covering ~21% of the genome. The density of independent associations varies across the genome and the regions of elevated density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs account for 40% of phenotypic variance in European ancestry populations but only ~10%-20% in other ancestries. Effect sizes, associated regions, and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely explained by linkage disequilibrium and allele frequency differences within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than needed to implicate causal genes and variants. Overall, this study, the largest GWAS to date, provides an unprecedented saturated map of specific genomic regions containing the vast majority of common height-associated variants.

Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits

“…Given the relatively short time since admixture in African Americans (approximately 8 generations), we expect that regions of European ancestry in modern-day African Americans feature the same LD structure as the European source population contributing to the admixture event 24 . Moreover, others have previously demonstrated that there is low Fst and high correlation of allele frequencies between various European populations 34–36 . Empirically, we also find that nearly all (95%) SNPs that are tightly linked ( r 2 > 0.8) in European Americans in MESA are also tightly linked in regions of European ancestry in African Americans in MESA.…”

The Economics and Econometrics of Gene-Environment Interplay

“…A concerted effort is underway to address this historical imbalance and develop new methods, such as multi-ancestry meta-analysis (MAMA) (Turley et al, 2021a), that improve genetic prediction for other ancestry groups by utilizing European-ancestry GWAS results in combination with LD structures across populations. Furthermore, GWASs of non-European samples are increasingly being conducted (Yengo et al, 2022), which will also improve the predictive power of PGIs for and the generalizibility of findings for those ancestry groups.…”

“…At the time of writing, the biggest sample size of a GWAS is 5.4 million(Yengo et al, 2022).5 Population stratification is a form of confounding where the genetic makeup of ancestors influences one's genetic makeup as well as an outcome through nongenetic pathways. More specifically, if a population is stratified into subpopulations that do not mate randomly and an outcome happens to be more common in one subpopulation for nongenetic reasons, then the outcome will appear to be correlated with any SNPs that also happen to be more common in that subpopulation.…”

Linkage mapping reveals loci that underlie differences in C. elegans growth

“…However, complex traits, such as body size, are likely affected by many genes. For example, recent studies of human genetic variation using data from 5.4 million individuals report finding over 12,000 independent loci associated with height (Yengo et al 2022). In the laboratory strain of C. elegans, we know many loci that quantitatively affect body size and shape.…”