Abundant Pleiotropy in Human Complex Diseases and Traits

Abstract

We present a systematic review of pleiotropy among SNPs and genes reported to show genome-wide association with common complex diseases and traits. We find abundant evidence of pleiotropy; 233 (16.9%) genes and 77 (4.6%) SNPs show pleiotropic effects. SNP pleiotropic status was associated with gene location (p = 0.024; pleiotropic SNPs more often exonic [14.5% versus 4.9% for nonpleiotropic, trait-associated SNPs] and less often intergenic [15.8% versus 23.6%]), "predicted transcript consequence" (p = 0.001; pleiotropic SNPs more often predicted to be structurally deleterious [5% versus 0.4%] but not more often in regulatory sequences), and certain disease classes. We develop a method to calculate the likelihood that pleiotropic links between traits occurred more often than expected and demonstrate that this approach can identify etiological links that are already known (such as between fetal hemoglobin and malaria risk) and those that are not yet established (e.g., between plasma campesterol levels and gallstones risk; and between immunoglobulin A and juvenile idiopathic arthritis). Examples of pleiotropy will accumulate over time, but it is already clear that pleiotropy is a common property of genes and SNPs associated with disease traits, and this will have implications for identification of molecular targets for drug development, future genetic risk-profiling, and classification of diseases.

Pleiotropic effects of obesity-susceptibility loci on metabolic traits: a meta-analysis of up to 37,874 individuals

“…A recent analysis of the loci identified in GWASs for common diseases and quantitative traits showed pleiotropic effects for almost 17% of analysed genes and for 4.6% of SNPs [55]. These and our findings indicate that pleiotropy is more common in complex diseases than previously anticipated, and suggest that many proteins play different roles in independent biological pathways.…”

10 Years of GWAS Discovery: Biology, Function, and Translation

“…[20][21][22] In the case of auto-immune diseases, evidence implies that at some loci, the same causal variants are driving the observations of associations across diseases. [23][24][25] Fourth, analytical methods that estimate genetic correlations from GWAS data have provided evidence for widespread pleiotropy.…”

The ubiquity of pleiotropy in human disease

“…Pleiotropy, defined here as one gene affecting more than one phenotype, has become increasingly important in interpreting both genotype-phenotype maps and underlying factors that affect comorbidity, and has been integrated into several methods for genome wide association studies (GWAS) (Chung et al 2014;Hill and Zhang 2012;Lee et al 2012;Li et al 2014a, b;Pendergrass et al 2013;Rzhetsky et al 2007;Sivakumaran et al 2011;Solovieff et al 2013;Stearns 2010;Wagner et al 2008;Wagner and Zhang 2011;Yang et al 2015). Studies of pleiotropy can impact our understanding of underlying disease processes, and implicitly, the prevention and treatment of disease as well as predicting adverse reactions to drugs.…”

“…et al 2007;Sivakumaran et al 2011;Solovieff et al 2013;Stearns 2010;Wagner et al 2008;Wagner and Zhang 2011;Yang et al 2015), little has been done to investigate the relationship between pleiotropy and risk variation as measured by effect sizes. Studies investigating this question have focused on exploring the correlation of effect sizes of different traits associated with a single locus; however, no study has investigated the relationship between effect size and the degree of pleiotropy in humans.…”