Clinical-exome sequencing unveils the genetic landscape of polycystic ovarian syndrome (PCOS) focusing on lean and obese phenotypes: implications for cost-effective diagnosis and personalized treatment.

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Polycystic ovarian syndrome (PCOS) is one of the most common endocrinopathies among reproductive women worldwide, contributing greatly on the incidence of female infertility and gynecological cancers. It is a complex health condition combining of multiple symptoms like androgen excess, uncontrolled weight gain, alopecia, hirsutism, etc. Conventionally PCOS was associated with obesity while it is often found among lean women nowadays, making the disease more critical to diagnose as well treatment. The disorder has an impact on several signal transduction pathways, including steroidogenesis, steroid hormone activity, gonadotrophin regulation, insulin secretion, energy balance, and chronic inflammation. Understanding the aetiology and pathophysiology of PCOS is difficult due to its multiple causes, which include environmental factors, intricate genetic predisposition, and epigenetic modifications. Despite research supporting the role of familial aggregations in PCOS outcomes, the inheritance pattern remains unknown. Henceforth, to reduce the burden of PCOS, it is inevitably important to diagnose at early ages as well as intervene through personalized medicine. With this brief background, it was imperative to elucidate the genetic architecture of PCOS considering BMI as an controlling factor. This study aims to investigate the genetic basis behind obesity-mediated PCOS, focusing on both obese and lean individuals. It uses a comprehensive bioinformatics methodology to depict pathways and functionality enrichment, allowing for cost-effective risk prediction and management. In the present research, the representative study participants (N = 2) were chosen from a cross-sectional epidemiological survey, based on their anthropometric parameters and confirmation of PCOS. Upon voluntary participation and written consent, biological fluids (whole blood and buccal swab) were taken from where DNA was extracted. The clinical-exome sequencing was performed by the Next-generation Illumina platform using the Twist Human Comprehensive Exome Kit. A comprehensive bioinformatics methodology was employed to identify the most important, unique, and common genes. A total of 26,550 variants were identified in clinically important exomes from two samples, with 5170 common and 2232 and 2322 unique among PCOS lean and obese phenotypes, respectively. Only 262 and 94 variants were PCOS-specific in lean and obese PCOS. Three filters were applied to shortlist the most potent variants, with 4 unique variants in lean PCOS, 2 unique variants in obese PCOS, and 5 common variants in both. The study found that leptin signalling impairment and insulin resistance, as well as mutations in CYP1A1, CYP19A1, ESR1, AR, AMH, AdipoR1, NAMPT, NPY, PTEN, EGFR, and Akt, all play significant roles in PCOS in the studied group. Young women in West Bengal, India, are more likely to have co-occurring PCOS, which includes estrogen resistance, leptin receptor insufficiency, folate deficiency, T2DM, and acanthosis nigricans, with obesity being a common phenotypic expression.