{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,11]],"date-time":"2026-11-11T01:20:24Z","timestamp":1794360024352,"version":"4.9.0"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T00:00:00Z","timestamp":1770163200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A retrospective cross-sectional study was conducted involving 301 women with PCOS and 144 controls. Patients were stratified into Non-HA (\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"im1\">\n                          <mml:mrow>\n                            <mml:mi>n<\/mml:mi>\n                            <mml:mo>=<\/mml:mo>\n                            <mml:mn>49<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      ) and HA (\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"im2\">\n                          <mml:mrow>\n                            <mml:mi>n<\/mml:mi>\n                            <mml:mo>=<\/mml:mo>\n                            <mml:mn>252<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      ) 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.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The HA phenotype was characterised by significantly more severe oligo-anovulation and metabolic disturbance compared to the Non-HA group, despite comparable age (\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"im3\">\n                          <mml:mrow>\n                            <mml:mi>P<\/mml:mi>\n                            <mml:mo>=<\/mml:mo>\n                            <mml:mn>0.069<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      ). Multivariate analysis adjusted for potential confounders revealed that HOMA-IR was a robust, independent predictor of the HA phenotype (aOR=1.35,\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"im4\">\n                          <mml:mrow>\n                            <mml:mi>P<\/mml:mi>\n                            <mml:mo>=<\/mml:mo>\n                            <mml:mn>0.003<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      ), comparable to LH (aOR=1.09,\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"im5\">\n                          <mml:mrow>\n                            <mml:mi>P<\/mml:mi>\n                            <mml:mo>=<\/mml:mo>\n                            <mml:mn>0.012<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      ). Crucially, Body Mass Index (BMI) failed to retain statistical significance (aOR=0.98,\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"im6\">\n                          <mml:mrow>\n                            <mml:mi>P<\/mml:mi>\n                            <mml:mo>=<\/mml:mo>\n                            <mml:mn>0.682<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      ) 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 (\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" id=\"im7\">\n                          <mml:mrow>\n                            <mml:msup>\n                              <mml:mi>R<\/mml:mi>\n                              <mml:mn>2<\/mml:mn>\n                            <\/mml:msup>\n                            <mml:mo>=<\/mml:mo>\n                            <mml:mn>0.20<\/mml:mn>\n                            <mml:mo>,<\/mml:mo>\n                            <mml:mi>P<\/mml:mi>\n                            <mml:mo>=<\/mml:mo>\n                            <mml:mn>0.013<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      ), 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.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1758861","type":"journal-article","created":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T05:34:59Z","timestamp":1770183299000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Divergent pathophysiological drivers of polycystic ovary syndrome: insulin resistance independently fuels the hyperandrogenic phenotype whilst neuroendocrine factors dominate non-hyperandrogenic presentations"],"prefix":"10.3389","volume":"17","author":[{"given":"Xiaoxia","family":"Wang","sequence":"first","affiliation":[{"name":"National Key Laboratory of Male Reproductive Genetics","place":["Guangzhou,, China"]},{"name":"Reproductive Immunology, Guangdong Provincial Institute of 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Laboratory of Male Reproductive Genetics","place":["Guangzhou,, China"]},{"name":"Reproductive Immunology, Guangdong Provincial Institute of Reproductive Sciences (Guangdong Provincial Fertility Hospital)","place":["Guangzhou,, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Tan","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Male Reproductive Genetics","place":["Guangzhou,, China"]},{"name":"Centre for Reproductive Medicine, Guangdong Provincial Institute of Reproductive Sciences (Guangdong Provincial Fertility Hospital)","place":["Guangzhou,, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Male Reproductive Genetics","place":["Guangzhou,, China"]},{"name":"Department of Gynaecology, Guangdong Provincial Institute of Reproductive Sciences (Guangdong Provincial Fertility 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