# A Retrospective Study for the Evaluation of Serum Anti-Müllerian Hormone and Its Correlation With Insulin Resistance and Lipid Profile in Polycystic Ovary Syndrome in Adolescents

## TL;DR

This study finds that AMH, along with insulin and blood sugar levels, can help diagnose and manage PCOS in adolescents.

## Contribution

The study identifies AMH as a novel predictive marker for PCOS in adolescents, alongside FBS and LH.

## Key findings

- PCOS adolescents had significantly higher AMH, insulin, and LH levels compared to controls.
- AMH, FBS, and LH were identified as key predictors of PCOS with strong statistical significance.

## Abstract

Background and rationale

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder in adolescents, marked by hormonal imbalances, insulin resistance, and metabolic dysfunction. Early identification of reliable biochemical markers is crucial for timely diagnosis and management to prevent long-term complications like type 2 diabetes and cardiovascular disease. This study investigates serum anti-Müllerian hormone (AMH) and its correlation with insulin resistance and lipid profiles to identify predictive markers for PCOS risk in adolescents.

Methods

A retrospective study analyzed 91 women (49 PCOS cases per Rotterdam criteria, 42 age-matched controls; mean age 25.5 ± 5.3 years). Biochemical parameters, including AMH, insulin, fasting blood sugar (FBS), luteinizing hormone (LH), interleukin-6 (IL-6), lipid profiles (total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG)), and electrolytes (sodium, chloride), were measured using standardized protocols on the Beckman Coulter AU series autoanalyzer. Insulin resistance was assessed via Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and Quantitative Insulin Sensitivity Check Index (QUICKI). Statistical analyses included t-tests, logistic regression, exploratory factor analysis (EFA), and heatmap visualization of PCOS phenotypes (Groups A-D, based on clinical/biochemical severity).

Results

The PCOS group showed significantly higher insulin (mean difference: 5.2 µIU/mL, p = 0.003), HOMA-IR (p = 0.004), LH (p = 0.002), AMH (p < 0.001), and chloride (p < 0.001), with lower Na:Cl ratio (p < 0.001) and QUICKI (p = 0.005) compared to controls. Logistic regression identified AMH (odds ratio (OR): 1.45, p < 0.001), FBS (OR: 1.12, p = 0.02), and LH (OR: 1.33, p = 0.01) as key predictors. Model 5 (AMH, FBS, IL-6, LH) achieved a McFadden R² of 0.85 and area under the curve (AUC) of 1.00. EFA revealed five factors (36.4% variance): insulin resistance, liver/lipid function, lipid metabolism, liver/kidney function, and electrolyte/protein balance, all correlated with PCOS (p < 0.05). Heatmap analysis showed severe insulin resistance in Group D and elevated FBS/chloride in Group C.

Conclusion

AMH, LH, and FBS are robust markers for diagnosing and managing PCOS in adolescents. These, alongside insulin resistance and lipid alterations, support early risk stratification and personalized interventions across PCOS phenotypes, improving long-term health outcomes.