Colocalization analysis of polycystic ovary syndrome to identify potential disease-mediating genes and proteins

Jenny C Censin,Cecilia M Lindgren,Michael V Holmes,Jonas Bovijn

doi:10.1038/s41431-021-00835-8

Abstract

Polycystic ovary syndrome (PCOS) is a common complex disease in women with a strong genetic component and downstream consequences for reproductive, metabolic and psychological health. There are currently 19 known PCOS risk loci, primarily identified in women of Han Chinese or European ancestry, and 14 of these risk loci were identified or replicated in a genome-wide association study of PCOS performed in up to 10,074 cases and 103,164 controls of European descent. However, for most of these loci the gene responsible for the association is unknown. We therefore use a Bayesian colocalization approach (Coloc) to highlight genes in PCOS-associated regions that may have a role in mediating the disease risk. We evaluated the posterior probabilities of evidence consistent with shared causal variants between 14 PCOS genetic risk loci and intermediate cellular phenotypes in one protein (N = 3301) and two expression quantitative trait locus datasets (N = 31,684 and N = 80–491). Through these analyses, we identified seven proteins or genes with evidence of a possibly shared causal variant for almost 30% of known PCOS signals, including follicle stimulating hormone and ERBB3, IKZF4, RPS26, SUOX, ZFP36L2, and C8orf49. Several of these potential effector proteins and genes have been implicated in the hypothalamic–pituitary–gonadal signalling pathway and provide an avenue for functional follow-up in order to demonstrate a causal role in PCOS pathophysiology.

Highlights

Polycystic ovary syndrome (PCOS) is a common endocrinopathy, affecting between 6 and 10% of women of reproductive age [1], with consequences for reproductive, metabolic, and psychological health [2, 3]
colocalization approach (Coloc) requires the assignment of prior probabilities for a single nucleotide polymorphism (SNP) being associated with each trait (p1 and p2) and for a SNP being associated with both traits (p12)
Hypothesis H0, H1 and H2 correspond to situations without associated/causal SNPs in both the PCOS and the protein/ gene dataset, H3 to a situation where PCOS and the protein/ gene have different associated/causal SNPs, and H4 where PCOS and the protein/gene have evidence consistent with a shared associated/causal SNP, i.e., colocalization [10]

Summary

Introduction

Polycystic ovary syndrome (PCOS) is a common endocrinopathy, affecting between 6 and 10% of women of reproductive age [1], with consequences for reproductive, metabolic, and psychological health [2, 3]. There is evidence of a clear genetic component [4], and genome-wide association studies (GWASs) have identified 19 risk loci [5,6,7,8,9]. Some of these risk loci are close to genes with a plausible connection to PCOS pathophysiology, including genes involved in for example insulin and hypothalamic–pituitary–gonadal (HPG) signalling (e.g., INSR, the insulin receptor gene and FSHR, the FSHreceptor gene) [3, 6,7,8].

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Conclusion