Associations between biological aging and the risk of endometriosis: Evidence from a large population-based prospective cohort study
文献类型: 外文期刊
作者: Yuxia Chen;Xinxing Peng;Yang Chen;Li Chen;Xingzhu Yin;Wenrou Jiang;Biao Chen;Yuhan Tang
作者机构:
关键词: Biological aging;Cox models;Endometriosis;PhenoAge;UK Biobank
期刊名称: European Journal of Obstetrics and Gynecology and Reproductive Biology
ISSN: 0301-2115
年卷期: 2025 年 313 卷
页码:
收录情况: SCIE(2025版)
摘要: Background: Endometriosis is a common disease for women of reproductive ages. Individuals with accelerated biological aging are at a higher risk of developing various diseases, however, the effect of biological aging on the risk of endometriosis remains unclear. We aimed to explore the associations between biological aging and the risk of endometriosis. Methods: 46,371 women from the UK Biobank who had no endometriosis diagnosis at baseline was involved in our study. We used Phenotypic age (PhenoAge) as a measure of biological aging. PhenoAge biological aging acceleration (PhenoAge_baa) was defined as the residual from the regression of PhenoAge on the basis of chronological age. Cox regression models and restricted cubic spline models with three knots were applied to assess the associations between biological aging and the risk of endometriosis. We also conducted subgroup analyses and assessed the combined effects of BMI and biological aging on endometriosis. Results: During a median follow-up of 12.5 years, 635 incident endometriosis were identified. After adjusting for potential factors, women with a status of accelerated aging were found to have a 35 % higher risk of developing endometriosis compared to those without accelerated aging. We also observed a joint effect of high BMI and accelerated biological aging on the incidence of endometriosis and no significant interactions were observed in our subgroup analyses. Conclusions: Our findings suggest that associations between accelerated biological aging and endometriosis that warrant further investigation.
分类号:
- 相关文献
作者其他论文 更多>>
-
Integrated bioinformatics and quantitative lipidomics reveal temporal lipid dynamics and oxidative metabolic networks in refrigerated pork
作者:Minghui Gu;Cheng Li;Yuqing Ren;Li Chen;Shaobo Li;Dequan Zhang;Xiaochun Zheng
关键词:Lipid transformation;Meat quality;Metabolomic pathway;Quantitative lipidomics;Refrigerated pork
-
Insight into the meat quality differences of Tibetan sheep from different altitudes based on metabolomics
作者:Ruisi Liu;Jianing Fu;Shaobo Li;Minghui Gu;Liang Li;Le Xu;Jiangying Yu;Dequan Zhang;Li Chen
关键词:Cooking loss;HIF-1α signaling;High-altitude adaptation;Lysine degradation;Meat color
-
Effects of mutton with different cooking methods on intestinal flora and metabolites in the elderly based on in vitro fermentation
作者:Jianing Fu;Meizhen Xu;Shaobo Li;Li Chen;Dequan Zhang
关键词:Cooking methods;Elderly;In vitro fermentation;Intestinal microbiota;Mutton;Untargeted metabolomics
-
Two telomere-to-telomere pig genome assemblies and pan-genome analyses provide insights into genomic structural landscape and genetic adaptations
作者:Wencheng Zong;Li Chen;Dongjie Zhang;Yuebo Zhang;Jinbu Wang;Xinhua Hou;Jie Chai;Yalong An;Ming Tian;Xinmiao He;Chengyi Song;Jun He;Xin Liu;Ligang Wang;Enrico D'Alessandro;Lixian Wang;Yulong Yin;Mingzhou Li;Di Liu;Jinyong Wang;Longchao Zhang
关键词:
-
Insights into the effect and mechanism of low-bitterness porcine hemoglobin hydrolysates produced by γ-glutamyl transpeptidase
作者:Chengpeng Cheng;Shaobo Li;Li Chen;Jiangying Yu;Ming Zhu;Christophe Blecker;Dequan Zhang
关键词:Bitter peptide;Bitterness inhibition effect;Hemoglobin hydrolysates;Umami peptide;Γ-Glutamyl peptide
-
Unraveling the microecological mechanisms of phosphate-solubilizing Pseudomonas asiatica JP233 through metagenomics: insights into the roles of rhizosphere microbiota and predatory bacteria
作者:Yuhan Tang;Linlin Wang;Jing Fu;Fangyuan Zhou;Hailei Wei;Xiaoqing Wu;Susu Fan;Xinjian Zhang
关键词:metagenomics;phosphate-solubilizing bacteria;predatory bacteria;Pseudomonas asiatica;soil P cycling
-
A Vegetable-Price Forecasting Method Based on Mixture of Experts
作者:Chenyun Zhao;Xiaodong Wang;Anping Zhao;Yunpeng Cui;Ting Wang;Juan Liu;Ying Hou;Mo Wang;Li Chen;Huan Li;Jinming Wu;Tan Sun
关键词:deep learning;large language models;mixture-of-experts;time-series forecasting;vegetable-price forecasting