# Divergent pathophysiological drivers of polycystic ovary syndrome: insulin resistance independently fuels the hyperandrogenic phenotype whilst neuroendocrine factors dominate non-hyperandrogenic presentations

**Authors:** Xiaoxia Wang, Hua Nie, Rong Cui, Guifang Ye, Ying Tan, Jing Zhang, Biyun Zhang, Xingming Zhong

PMC · DOI: 10.3389/fendo.2026.1758861 · Frontiers in Endocrinology · 2026-02-04

## TL;DR

This study shows that polycystic ovary syndrome has two distinct types: one driven by insulin resistance and the other by neuroendocrine issues, independent of obesity.

## Contribution

The study identifies insulin resistance as an independent driver of the hyperandrogenic PCOS phenotype, separate from obesity.

## Key findings

- Hyperandrogenic PCOS is strongly linked to insulin resistance, not just obesity.
- Non-hyperandrogenic PCOS is more associated with neuroendocrine factors like LH levels.
- Metabolic markers like HOMA-IR correlate with testosterone only in the hyperandrogenic group.

## Abstract

Polycystic Ovary Syndrome (PCOS) manifests as a heterogeneous disorder, yet the extent to which metabolic dysfunction drives specific phenotypes independent of obesity remains debated. This study aimed to delineate the distinct clinical and pathophysiological characteristics of Hyperandrogenic (HA) versus 38 Non-Hyperandrogenic (Non-HA) phenotypes, with a specific focus on disentangling the roles of insulin resistance and adiposity in driving androgen excess.

A retrospective cross-sectional study was conducted involving 301 women with PCOS and 144 controls. Patients were stratified into Non-HA (
n=49) and HA (
n=252) subgroups based strictly on comprehensive androgen profiling (biochemical and clinical assessment). We utilised multivariate logistic regression to identify independent predictors of the HA phenotype and stratified linear regression models to map the relationships between metabolic indices (HOMA-IR, BMI) and reproductive parameters.

The HA phenotype was characterised by significantly more severe oligo-anovulation and metabolic disturbance compared to the Non-HA group, despite comparable age (
P=0.069). Multivariate analysis adjusted for potential confounders revealed that HOMA-IR was a robust, independent predictor of the HA phenotype (aOR=1.35, 
P=0.003), comparable to LH (aOR=1.09, 
P=0.012). Crucially, Body Mass Index (BMI) failed to retain statistical significance (aOR=0.98, 
P=0.682) in the adjusted model, indicating that the association between metabolic dysfunction and hyperandrogenism is not mediated solely by adiposity. Stratified linear regression further demonstrated a distinct positive trajectory between HOMA-IR and testosterone specifically within the HA cohort (
R2=0.20,P=0.013), a relationship absent in the Non-HA group. Conversely, in Non-HA patients, menstrual cycle prolongation correlated with LH levels rather than metabolic markers, suggesting a predominant neuroendocrine aetiology.

Our findings demonstrate that PCOS encompasses two pathophysiologically distinct entities. The Non-HA phenotype appears driven primarily by neuroendocrine dysregulation, whereas the HA phenotype is intrinsically linked to metabolic dysfunction, specifically insulin resistance. Most importantly, we confirm that insulin resistance drives the hyperandrogenic phenotype independently of obesity. These data support a paradigm shift towards phenotype-specific management, necessitating aggressive insulin-sensitising strategies for hyperandrogenic patients regardless of their BMI.

## Linked entities

- **Diseases:** Polycystic Ovary Syndrome (MONDO:0008487), PCOS (MONDO:0008487)

## Full-text entities

- **Genes:** GNRH1 (gonadotropin releasing hormone 1) [NCBI Gene 2796] {aka GNRH, GRH, LHRH, LNRH}, POMC (proopiomelanocortin) [NCBI Gene 5443] {aka ACTH, CLIP, LPH, MSH, NPP, OBAIRH}, LEP (leptin) [NCBI Gene 3952] {aka LEPD, OB, OBS}, PRL (prolactin) [NCBI Gene 5617] {aka GHA1, pPRL}, INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}, HK1 (hexokinase 1) [NCBI Gene 3098] {aka CNSHA5, HK, HK1-ta, HK1-tb, HK1-tc, HKD}, SHBG (sex hormone binding globulin) [NCBI Gene 6462] {aka ABP, SBP, TEBG}
- **Diseases:** cardiovascular disease (MESH:D002318), endocrine disorders (MESH:D004700), weight loss (MESH:D015431), IR (MESH:D007333), Oligo-anovulation (MESH:D000858), HA (MESH:D017588), hypertension (MESH:D006973), PCOS (MESH:D011085), menstrual dysfunction (MESH:D004412), Polycystic (MESH:D007690), cysts (MESH:D003560), type 2 diabetes (MESH:D003924), thyroid dysfunction (MESH:D013959), androgen (MESH:D014770), adiposity (MESH:D018205), ovulatory dysfunction (MESH:D006331), disordered eating (MESH:D001068), diabetes mellitus (MESH:D003920), congenital adrenal hyperplasia (MESH:D000312), follicular arrest (MESH:D006323), disruption (MESH:D019958), Hirsutism (MESH:D006628), metabolic disturbance (MESH:D024821), tubal factors (MESH:D005184), FHA (MESH:D007027), hypogonadotropic hypogonadism (MESH:D007006), energy deficit (MESH:D009461), metabolic dysregulation (MESH:D021081), reproductive dysfunction (MESH:D060737), metabolic dysfunction (MESH:D008659), Neuroendocrine disturbances (MESH:D018358), male-factor infertility (MESH:D007248), Cushing's syndrome (MESH:D003480), amenorrhoea (MESH:C537962), obesity (MESH:D009765), hyperprolactinaemia (MESH:D006966)
- **Chemicals:** Cyan (-), LH (MESH:D007986), Glucose (MESH:D005947), E2 (MESH:D004958), PEG (MESH:D011092), T (MESH:D014316), 17-OHP (MESH:D019326), progesterone (MESH:D011374), Testosterone (MESH:D013739)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12913134/full.md

## References

51 references — full list in the complete paper: https://tomesphere.com/paper/PMC12913134/full.md

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Source: https://tomesphere.com/paper/PMC12913134