Regulatory risk loci link disrupted androgen response to pathophysiology of Polycystic Ovary Syndrome.

Jaya Srivastava, Ivan Ovcharenko
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Abstract

A major challenge in deciphering the complex genetic landscape of Polycystic Ovary Syndrome (PCOS) lies in the limited understanding of how susceptibility loci drive molecular mechanisms across diverse phenotypes. To address this, we integrated molecular and epigenomic annotations from proposed causal cell-types and employed a deep learning (DL) framework to predict cell-type-specific regulatory effects of PCOS risk variants. Our analysis revealed that these variants affect key transcription factor (TF) binding sites, including NR4A1/2, NHLH2, FOXA1, and WT1, which regulate gonadotropin signaling, folliculogenesis, and steroidogenesis across brain and endocrine cell-types. The DL model, which showed strong concordance with reporter assay data, identified enhancer-disrupting activity in approximately 20% of risk variants. Notably, many of these variants disrupt TFs involved in androgen-mediated signaling, providing molecular insights into hyperandrogenemia in PCOS. Variants prioritized by the model were more pleiotropic and exerted stronger downregulatory effects on gene expression compared to other risk variants. Using the IRX3-FTO locus as a case study, we demonstrate how regulatory disruptions in tissues such as the fetal brain, pancreas, adipocytes, and endothelial cells may link obesity-associated mechanisms to PCOS pathogenesis via neuronal development, metabolic dysfunction, and impaired folliculogenesis. Collectively, our findings highlight the utility of integrating DL models with epigenomic data to uncover disease-relevant variants, reveal cross-tissue regulatory effects, and refine mechanistic understanding of PCOS.

多囊卵巢综合征的病理生理与雄激素反应紊乱的调控风险位点相关。
在解读多囊卵巢综合征(PCOS)复杂的遗传景观方面,一个主要的挑战是对易感位点驱动的分子机制的了解有限,因此需要对多囊卵巢综合征(PCOS)多种表型表现的调控途径进行研究。在这项研究中,我们整合了提出的致病细胞类型的分子和表观基因组注释,并采用深度学习(DL)模型来推断风险变异的细胞类型特异性影响。我们的分析揭示了这些变异在脑和内分泌细胞类型中的作用,影响关键转录因子(TFs)的结合位点:FOXA1, FOXL1, WT1, SALL4和CPEB1,这些转录因子调节卵巢发育,卵泡发生和类固醇激素信号,促进疾病相关的转录组谱。我们的DL模型与MPRA数据密切相关,在20%的风险变异中发现了增强子破坏活性,特别是影响涉及雄激素介导信号的tf,从而揭示了高雄激素血症的分子后果。以FTO/IRX3位点为例,我们探索了胎儿大脑、胰腺、脂肪细胞和内皮细胞系中风险变异的潜在细胞类型特异性调节作用,这表明IRX3调节的中断(以前与肥胖有关)可能通过多种机制促进多囊卵巢综合征的发病,包括神经元发育、代谢调节和卵泡形成。我们的研究结果强调了将DL模型与表观基因组注释相结合的价值,以识别疾病相关变异,探索疾病风险位点的多效性影响,并获得跨细胞类型调节相互作用的新见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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