Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jul 11;17(7):e87755.
doi: 10.7759/cureus.87755. eCollection 2025 Jul.

Adipokine Dysregulation in Obese and Non-Obese Polycystic Ovary Syndrome (PCOS) Patients: Association With Visceral Adiposity Index and Metabolic Risk

Affiliations

Adipokine Dysregulation in Obese and Non-Obese Polycystic Ovary Syndrome (PCOS) Patients: Association With Visceral Adiposity Index and Metabolic Risk

Minakshi Kumari et al. Cureus. .

Abstract

Background Polycystic ovary syndrome (PCOS) is a multifactorial endocrine disorder characterized by metabolic and reproductive abnormalities. Obesity exacerbates PCOS-associated insulin resistance, inflammation, and hormonal imbalances, potentially influencing adipokine secretion. This study evaluated variations in adipokines between obese and non-obese PCOS patients and their association with the Visceral Adiposity Index (VAI), metabolic parameters, and disease severity. Methods A cross-sectional study was conducted at a tertiary care center in North India on 90 women diagnosed with PCOS using the Rotterdam 2003 criteria. Participants were categorized into obese (n=45) and non-obese (n=45) groups based on body mass index (BMI). Clinical, biochemical, and inflammatory markers were assessed, including leptin, adiponectin, resistin, tumor necrosis factor alpha (TNF-α), and interleukin-6 (IL-6). Metabolic parameters such as fasting glucose, insulin, homeostatic model assessment for insulin resistance (HOMA-IR), and lipid profile were evaluated. Pearson correlation and receiver operating characteristic (ROC) analyses were used to assess associations and diagnostic accuracy. Results Obese PCOS patients had significantly higher leptin (24.5 ± 6.2 vs. 14.2 ± 5.8 ng/mL, p<0.001) and lower adiponectin (5.2 ± 1.4 vs. 7.8 ± 1.9 µg/mL, p=0.002) than non-obese counterparts. Resistin, TNF-α, and IL-6 were also elevated in the obese group (p<0.05). Obesity was associated with increased fasting glucose (mean difference = 5.6 mg/dL, 95% CI: 0.2-11.0, p=0.043), insulin (mean difference = 4.1 µIU/mL, 95% CI: 2.1-6.1, p<0.001), HOMA-IR (mean difference = 1.2, 95% CI: 0.7-1.7, p<0.001), triglycerides (mean difference = 24.3 mg/dL, 95% CI: 3.1-45.5, p=0.025), and lower high-density lipoprotein cholesterol (HDL-C) (mean difference = -6.2 mg/dL, 95% CI: -11.4 to -1.0, p=0.018). Leptin correlated positively with BMI (r=0.742, p<0.001) and VAI (r=0.763, p<0.001), while adiponectin showed a negative correlation (r=-0.515, p=0.010). ROC analysis indicated that leptin had the highest diagnostic accuracy for predicting obesity in PCOS (area under the curve [AUC] =0.85, 95% CI: 0.79-0.91, p<0.001). Conclusion Obesity in PCOS is associated with significant alterations in adipokine profiles, metabolic dysfunction, and elevated inflammatory markers. Leptin demonstrated the strongest association with obesity and metabolic disturbances, supporting its potential as a biomarker for identifying metabolic risk in PCOS. Targeted interventions addressing adipokine imbalances may help mitigate metabolic complications in obese PCOS patients.

Keywords: adipokines; insulin resistance; metabolic syndrome; polycystic ovary syndrome; visceral adiposity index.

PubMed Disclaimer

Conflict of interest statement

Human subjects: Informed consent for treatment and open access publication was obtained or waived by all participants in this study. Netaji Subhas Medical College and Hospital issued approval NSMCH/IEC/2022/259, dated: 12 May 2022. Approved. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.

Figures

Figure 1
Figure 1. ROC curves illustrating the performance of each adipokine (leptin, adiponectin, and resistin) along with their AUC values in distinguishing between obese PCOS and non-obese PCOS.
AUC: Area under the curve; ROC curve: Receiver operating characteristic curve

Similar articles

References

    1. Prevalence of polycystic ovarian syndrome in India: a systematic review and meta-analysis. Bharali MD, Rajendran R, Goswami J, et al. Cureus. 2022;14:0. - PMC - PubMed
    1. Understanding variation in prevalence estimates of polycystic ovary syndrome: a systematic review and meta-analysis. Skiba MA, Islam RM, Bell RJ, Davis SR. Hum Reprod Update. 2018;24:694–709. - PubMed
    1. Polycystic ovary syndrome: an updated overview foregrounding impacts of ethnicities and geographic variations. Yasmin A, Roychoudhury S, Paul Choudhury A, et al. Life (Basel) 2022;12 - PMC - PubMed
    1. Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome (PCOS) The Rotterdam ESHRE/ASRM‐Sponsored PCOS Consensus Workshop Group. Hum Reprod. 2004;19:41–47. - PubMed
    1. The complex roles of adipokines in polycystic ovary syndrome and endometriosis. Schüler-Toprak S, Ortmann O, Buechler C, Treeck O. Biomedicines. 2022;10 - PMC - PubMed

LinkOut - more resources