{"title":"患有多囊卵巢综合症的非肥胖年轻女性长期罹患心血管疾病的风险很高。","authors":"Xingpig Zhao, Jie Wang, Dan Sun, Dabao Xu, Yao Lu","doi":"10.1093/eurjpc/zwae375","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>Whether polycystic ovary syndrome (PCOS) is an independent risk factor for long-term cardiovascular disease (CVD) is unclear, and the risk of CVD in easily overlooked young nonobese PCOS patients is unknown. This study aimed to investigate the associations of PCOS with CVD and identify the management priorities.</p><p><strong>Methods and results: </strong>3864 participants (645 with PCOS) from UK Biobank were recruited from 2006-2010. The cumulative incidences of the CVD were calculated and compared between patients with and without PCOS via the log rank test. Cox proportional risk regression models were used to assess the relationships of PCOS with CVD and the impact of PCOS treatments on CVD risk. Polygenic risk scores and linkage disequilibrium score regression were used to assess the genetic-level associations. Then proteomics subgroup cohort was conducted to explore the significant biomarker involved in the PCOS-CVD associations. Compared with participants without PCOS, participants with PCOS had greater risks of CVD (hazard ratio (HR)=1.77, 95% confidence interval (CI)=1.19-2.65), coronary artery disease (HR=2.27, 95% CI=1.35-3.81) and myocardial infarction (HR=2.08, 95% CI=1.11-3.90) independent of genetic risk, especially for young nonobese PCOS patients (Pfor interaction <0.05). Current commonly used treatments did not affect CVD incidence. Proteomics cohort revealed that discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) may be specific CVD biomarker for patients with PCOS.</p><p><strong>Conclusion: </strong>Patients with PCOS had an increased risk of CVD, and young nonobese PCOS patients should be prioritized for CVD risk management. These findings support the necessity of clinical surveillance and suggest DCBLD2 as a possible CVD biomarker in females with PCOS.</p>","PeriodicalId":12051,"journal":{"name":"European journal of preventive cardiology","volume":" ","pages":""},"PeriodicalIF":8.4000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nonobese young females with PCOS are at high risk for long-term cardiovascular disease.\",\"authors\":\"Xingpig Zhao, Jie Wang, Dan Sun, Dabao Xu, Yao Lu\",\"doi\":\"10.1093/eurjpc/zwae375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims: </strong>Whether polycystic ovary syndrome (PCOS) is an independent risk factor for long-term cardiovascular disease (CVD) is unclear, and the risk of CVD in easily overlooked young nonobese PCOS patients is unknown. This study aimed to investigate the associations of PCOS with CVD and identify the management priorities.</p><p><strong>Methods and results: </strong>3864 participants (645 with PCOS) from UK Biobank were recruited from 2006-2010. The cumulative incidences of the CVD were calculated and compared between patients with and without PCOS via the log rank test. Cox proportional risk regression models were used to assess the relationships of PCOS with CVD and the impact of PCOS treatments on CVD risk. Polygenic risk scores and linkage disequilibrium score regression were used to assess the genetic-level associations. Then proteomics subgroup cohort was conducted to explore the significant biomarker involved in the PCOS-CVD associations. Compared with participants without PCOS, participants with PCOS had greater risks of CVD (hazard ratio (HR)=1.77, 95% confidence interval (CI)=1.19-2.65), coronary artery disease (HR=2.27, 95% CI=1.35-3.81) and myocardial infarction (HR=2.08, 95% CI=1.11-3.90) independent of genetic risk, especially for young nonobese PCOS patients (Pfor interaction <0.05). Current commonly used treatments did not affect CVD incidence. Proteomics cohort revealed that discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) may be specific CVD biomarker for patients with PCOS.</p><p><strong>Conclusion: </strong>Patients with PCOS had an increased risk of CVD, and young nonobese PCOS patients should be prioritized for CVD risk management. These findings support the necessity of clinical surveillance and suggest DCBLD2 as a possible CVD biomarker in females with PCOS.</p>\",\"PeriodicalId\":12051,\"journal\":{\"name\":\"European journal of preventive cardiology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":8.4000,\"publicationDate\":\"2024-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European journal of preventive cardiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/eurjpc/zwae375\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European journal of preventive cardiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/eurjpc/zwae375","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Nonobese young females with PCOS are at high risk for long-term cardiovascular disease.
Aims: Whether polycystic ovary syndrome (PCOS) is an independent risk factor for long-term cardiovascular disease (CVD) is unclear, and the risk of CVD in easily overlooked young nonobese PCOS patients is unknown. This study aimed to investigate the associations of PCOS with CVD and identify the management priorities.
Methods and results: 3864 participants (645 with PCOS) from UK Biobank were recruited from 2006-2010. The cumulative incidences of the CVD were calculated and compared between patients with and without PCOS via the log rank test. Cox proportional risk regression models were used to assess the relationships of PCOS with CVD and the impact of PCOS treatments on CVD risk. Polygenic risk scores and linkage disequilibrium score regression were used to assess the genetic-level associations. Then proteomics subgroup cohort was conducted to explore the significant biomarker involved in the PCOS-CVD associations. Compared with participants without PCOS, participants with PCOS had greater risks of CVD (hazard ratio (HR)=1.77, 95% confidence interval (CI)=1.19-2.65), coronary artery disease (HR=2.27, 95% CI=1.35-3.81) and myocardial infarction (HR=2.08, 95% CI=1.11-3.90) independent of genetic risk, especially for young nonobese PCOS patients (Pfor interaction <0.05). Current commonly used treatments did not affect CVD incidence. Proteomics cohort revealed that discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) may be specific CVD biomarker for patients with PCOS.
Conclusion: Patients with PCOS had an increased risk of CVD, and young nonobese PCOS patients should be prioritized for CVD risk management. These findings support the necessity of clinical surveillance and suggest DCBLD2 as a possible CVD biomarker in females with PCOS.
期刊介绍:
European Journal of Preventive Cardiology (EJPC) is an official journal of the European Society of Cardiology (ESC) and the European Association of Preventive Cardiology (EAPC). The journal covers a wide range of scientific, clinical, and public health disciplines related to cardiovascular disease prevention, risk factor management, cardiovascular rehabilitation, population science and public health, and exercise physiology. The categories covered by the journal include classical risk factors and treatment, lifestyle risk factors, non-modifiable cardiovascular risk factors, cardiovascular conditions, concomitant pathological conditions, sport cardiology, diagnostic tests, care settings, epidemiology, pharmacology and pharmacotherapy, machine learning, and artificial intelligence.