<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Gao X</submitter><funding>NCATS NIH HHS</funding><funding>NICHD NIH HHS</funding><funding>NCCIH NIH HHS</funding><funding>NHLBI NIH HHS</funding><funding>U.S. Department of Health &amp; Human Services | National Institutes of Health (NIH)</funding><funding>National Natural Science Foundation of China (National Science Foundation of China)</funding><pagination>4214-4224</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12705455</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>31(12)</volume><pubmed_abstract>Polycystic ovary syndrome (PCOS) is a common and heterogeneous endocrine disorder that affects 11%-13% of women worldwide, with profound implications for fertility and long-term metabolic health. Here we identify four reproducible subtypes-PCOS with hyperandrogen, with obesity, with high-sex hormone-binding globulin and with high-luteinizing hormone-anti-Müllerian hormone-through unsupervised clustering of 9 clinical variables in 11,908 affected women, validated across 5 international cohorts. Prospective 6.5-year follow-up and in vitro fertilization treatment data revealed distinct reproductive and metabolic trajectories: hyperandrogenic PCOS showed the highest risk of second trimester pregnancy loss and dyslipidemia incidence; PCOS with obesity exhibited the most severe metabolic complic</pubmed_abstract><journal>Nature medicine</journal><pubmed_title>Data-driven subtypes of polycystic ovary syndrome and their association with clinical outcomes.</pubmed_title><pmcid>PMC12705455</pmcid><funding_grant_id>R01AT009484-A1</funding_grant_id><funding_grant_id>UL1 TR002014</funding_grant_id><funding_grant_id>32370916</funding_grant_id><funding_grant_id>R01 HD091350</funding_grant_id><funding_grant_id>32588201</funding_grant_id><funding_grant_id>R01 HD091350-04</funding_grant_id><funding_grant_id>R01 HD100630</funding_grant_id><funding_grant_id>R01 AT009484</funding_grant_id><funding_grant_id>82101707</funding_grant_id><funding_grant_id>1R01HD100630</funding_grant_id><funding_grant_id>1R43HD11427-01</funding_grant_id><funding_grant_id>UG3/UH3 HL162971</funding_grant_id><funding_grant_id>UG3 HL162971</funding_grant_id><pubmed_authors>Liang X</pubmed_authors><pubmed_authors>Zhang H</pubmed_authors><pubmed_authors>Du Y</pubmed_authors><pubmed_authors>Shi Y</pubmed_authors><pubmed_authors>Wang Q</pubmed_authors><pubmed_authors>Xia M</pubmed_authors><pubmed_authors>Wang S</pubmed_authors><pubmed_authors>Bian Y</pubmed_authors><pubmed_authors>Yuan X</pubmed_authors><pubmed_authors>Zhang C</pubmed_authors><pubmed_authors>Yildiz BO</pubmed_authors><pubmed_authors>He F</pubmed_authors><pubmed_authors>Li J</pubmed_authors><pubmed_authors>Ha L</pubmed_authors><pubmed_authors>Sun Y</pubmed_authors><pubmed_authors>China Women’s Reproductive Metabolic Network</pubmed_authors><pubmed_authors>Li X</pubmed_authors><pubmed_authors>Yang Z</pubmed_authors><pubmed_authors>Li Y</pubmed_authors><pubmed_authors>Li S</pubmed_authors><pubmed_authors>Hu J</pubmed_authors><pubmed_authors>Gao X</pubmed_authors><pubmed_authors>Legro RS</pubmed_authors><pubmed_authors>Gao S</pubmed_authors><pubmed_authors>Liu J</pubmed_authors><pubmed_authors>Ou XH</pubmed_authors><pubmed_authors>Ma X</pubmed_authors><pubmed_authors>Qin Y</pubmed_authors><pubmed_authors>Yong EL</pubmed_authors><pubmed_authors>Ding L</pubmed_authors><pubmed_authors>Zhao Y</pubmed_authors><pubmed_authors>Liu X</pubmed_authors><pubmed_authors>Jiang Y</pubmed_authors><pubmed_authors>Liu Y</pubmed_authors><pubmed_authors>Zhao S</pubmed_authors><pubmed_authors>Tang R</pubmed_authors><pubmed_authors>Chen ZJ</pubmed_authors><pubmed_authors>Song X</pubmed_authors><pubmed_authors>Zhao J</pubmed_authors><pubmed_authors>Zhao H</pubmed_authors><pubmed_authors>Zhou L</pubmed_authors><pubmed_authors>Yan J</pubmed_authors><pubmed_authors>Cui L</pubmed_authors><pubmed_authors>Wei D</pubmed_authors><pubmed_authors>Santos BR</pubmed_authors><pubmed_authors>Gu Z</pubmed_authors><pubmed_authors>Qian Y</pubmed_authors><pubmed_authors>Zhang Y</pubmed_authors><pubmed_authors>Tian Y</pubmed_authors><pubmed_authors>Spritzer PM</pubmed_authors><pubmed_authors>Stener-Victorin E</pubmed_authors><pubmed_authors>Zhang X</pubmed_authors><pubmed_authors>Ma J</pubmed_authors></additional><is_claimable>false</is_claimable><name>Data-driven subtypes of polycystic ovary syndrome and their association with clinical outcomes.</name><description>Polycystic ovary syndrome (PCOS) is a common and heterogeneous endocrine disorder that affects 11%-13% of women worldwide, with profound implications for fertility and long-term metabolic health. Here we identify four reproducible subtypes-PCOS with hyperandrogen, with obesity, with high-sex hormone-binding globulin and with high-luteinizing hormone-anti-Müllerian hormone-through unsupervised clustering of 9 clinical variables in 11,908 affected women, validated across 5 international cohorts. Prospective 6.5-year follow-up and in vitro fertilization treatment data revealed distinct reproductive and metabolic trajectories: hyperandrogenic PCOS showed the highest risk of second trimester pregnancy loss and dyslipidemia incidence; PCOS with obesity exhibited the most severe metabolic complic</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Dec</publication><modification>2026-06-06T04:02:00.918Z</modification><creation>2026-05-25T03:12:06.77Z</creation></dates><accession>S-EPMC12705455</accession><cross_references><pubmed>41162652</pubmed><doi>10.1038/s41591-025-03984-1</doi></cross_references></HashMap>