The impact of self-reported ethnicity versus genetic ancestry on phenotypic characteristics of polycystic ovary syndrome (PCOS).

Context: It is well established that ethnicity is associated with the phenotype of polycystic ovary syndrome (PCOS). Self-reported ethnicity was shown to be an inaccurate proxy for ethnic origin in other disease traits, and it remains unclear how in PCOS patients self-reported ethnicity compares with a biological proxy such as genetic ancestry.
Objective: We compared the impact of self-reported ethnicity versus genetic ancestry on PCOS and tested which of these 2 classifications better predicts the variability in phenotypic characteristics of PCOS.
Patients: A total of 1499 PCOS patients from The Netherlands, comprising 11 self-reported ethnic groups of European, African, American, and Asian descent were genotyped with the Illumina 610K Quad BeadChip and merged with the data genotyped with the Illumina HumanHap650K available for the reference panel collected by the Human Genome Diversity Project (HGDP), in a collaboration with the Centre Etude Polymorphism Humain (CEPH), including 53 populations for ancestry reference.
Main Outcome Measures: Algorithms for inferring genetic relationships among individuals, including multidimensional scaling and ADMIXTURE, were applied to recover genetic ancestry for each individual. Regression analysis was used to determine the best predictor for the variability in PCOS characteristics.
Results: The association between self-reported ethnicity and genetic ancestry was moderate. For amenorrhea, total follicle count, body mass index, SHBG, dehydroepiandrosterone sulfate, and insulin, mainly genetic ancestry clusters ended up in the final models (P values < .004), indicating that they explain a larger proportion of variability of these PCOS characteristics compared with self-reported ethnicity. Especially variability of insulin levels seems predominantly explained by genetic ancestry.
Conclusions: Self-reported ancestry is not a perfect proxy for genetic ancestry in patients with PCOS, emphasizing that by using genetic ancestry data instead of self-reported ethnicity, PCOS-relevant misclassification can be avoided. Moreover, because genetic ancestry explained a larger proportion of phenotypic variability associated with PCOS than self-reported ethnicity, future studies should focus on genetic ancestry verification of PCOS patients for research questions and treatment as well as preventive strategies in these women.