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Multiomics Analysis–Based Biomarkers in Diagnosis of Polycystic Ovary Syndrome

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Abstract

Polycystic ovarian syndrome is an utmost communal endocrine, psychological, reproductive, and metabolic disorder that occurs in women of reproductive age with extensive range of clinical manifestations. This may even lead to long-term multiple morbidities including obesity, diabetes mellitus, insulin resistance, cardiovascular disease, infertility, cerebrovascular diseases, and ovarian and endometrial cancer. Women affliction from PCOS in midst assemblage of manifestations allied with menstrual dysfunction and androgen exorbitance, which considerably affects eminence of life. PCOS is recognized as a multifactorial disorder and systemic syndrome in first-degree family members; therefore, the etiology of PCOS syndrome has not been copiously interpreted. The disorder of PCOS comprehends numerous allied health conditions and has influenced various metabolic processes. Due to multifaceted pathophysiology engaging several pathways and proteins, single genetic diagnostic tests cannot be supportive to determine in straight way. Clarification of cellular and biochemical pathways and various genetic players underlying PCOS could upsurge our consideration of pathophysiology of this syndrome. It is requisite to know pathophysiological relationship between biomarker and their reflection towards PCOS disease. Biomarkers deliver vibrantly and potent ways to apprehend the spectrum of PCOS with applications in screening, diagnosis, characterization, and monitoring. This paper relies on the endeavor to point out many candidates as potential biomarkers based on omics technologies, thus highlighting correlation between PCOS disease with innovative technologies. Therefore, the objective of existing review is to encapsulate more findings towards cutting-edge advances in prospective use of biomarkers for PCOS disease. Discussed biomarkers may be fruitful in guiding therapies, addressing disease risk, and predicting clinical outcomes in future.

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Acknowledgments

S.R is grateful for the financial support of the Indian Council of Medical Research (ICMR) project (BMI/11(75)/2020) for carrying out research on PCOS. The authors are extremely thankful to Dr. Manisha Goel, Professor, Department of Biophysics, University of Delhi, South Campus, New Delhi, for giving us this opportunity.

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  1. Shikha Rani and Piyush Chandna contributed equally to this work.

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  1. Department of Biophysics, University of Delhi, South Campus, Benito Juarez Road, New Delhi , 110021, India

    Shikha Rani

  2. Natdynamics Biosciences Confederation, Gurgaon, Haryana, 122001, India

    Piyush Chandna

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Conceptualization, S.R.; writing, S.R., and P.C.; review and editing, S.R. and P.C.; both the authors have read and agreed to the published version of the manuscript.

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Rani, S., Chandna, P. Multiomics Analysis–Based Biomarkers in Diagnosis of Polycystic Ovary Syndrome. Reprod. Sci. 30, 1–27 (2023). https://doi.org/10.1007/s43032-022-00863-9

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