Abstract

Ovulation induction is a first-line medical treatment for infertility in polycystic ovary syndrome (PCOS). Poor ovulation responses are assumed to be due to insulin resistance and hyperandrogenism. In a prospective cohort (PCOSAct) of 1000 infertile patients with PCOS, whole-exome plus targeted single-nucleotide polymorphism (SNP) sequencing and comprehensive metabolomic profiling were conducted. Significant genome-wide common variants and rare mutations associated with anovulation were identified, and a prediction model was built using machine learning. Common variants in zinc-finger protein 438 gene ( ZNF438 ) indexed by rs2994652 ( p = 2.47 × 10 –8 ) and a rare functional mutation in REC114 (rs182542888, p = 5.79 × 10 –6 ) were significantly associated with failure of ovulation induction. Women carrying the A allele of rs2994652 and REC114 p.Val101Leu (rs182542888) had lower ovulation (odds ratio (OR) = 1.96, 95% confidence interval (95%CI) = 1.55–2.49; OR = 11.52, 95%CI = 3.08–43.05, respectively) and prolonged time to ovulation (mean = 56.7 versus (vs) 49.0 days, p < 0.001; 78.1 vs 68.6 days, p = 0.014, respectively). L -phenylalanine was found to be increased and correlated with the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index ( r = 0.22, p = 0.050) and fasting glucose ( r = 0.33, p = 0.003) for rs2994652, while arachidonic acid metabolism was found to be decreased and associated with increased anti-Müllerian hormone (AMH; r = –0.51, p = 0.01) and total testosterone (TT; r = –0.71, p = 0.02) for rs182542888. A combined model of genetic variants, metabolites, and clinical features increased the prediction of ovulation (area under the curve (AUC) = 76.7%). Common variants in ZNF438 and rare functional mutations in REC114 , associated with phenylalanine and arachidonic acid metabolites, contributed to the failure of infertility treatment in women with PCOS.

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