Novel metabolic and inflammatory stratification of overweight/obesity to characterize risks of adverse outcomes: A large population-based cohort study.

IF 5.4 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Hang Dong, Yingzhou Shi, Yicheng Ma, Yiping Cheng, Luna Liu, Shengyang Xiao, Zinuo Yuan, Zhen Wang, Tuo Li, Jiajun Zhao, Xiude Fan
{"title":"Novel metabolic and inflammatory stratification of overweight/obesity to characterize risks of adverse outcomes: A large population-based cohort study.","authors":"Hang Dong, Yingzhou Shi, Yicheng Ma, Yiping Cheng, Luna Liu, Shengyang Xiao, Zinuo Yuan, Zhen Wang, Tuo Li, Jiajun Zhao, Xiude Fan","doi":"10.1111/dom.16262","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>The growing epidemic of overweight and obesity elevates disease risks, with metabolic disorders and inflammation critically involved in the pathogenic mechanisms. This study refines the subtyping of overweight and obesity using metabolic and inflammatory markers to enhance risk assessment and personalized prevention.</p><p><strong>Materials and methods: </strong>Based on the UK Biobank, this retrospective study included participants classified as overweight or obese (BMI ≥25 kg/m<sup>2</sup>). K-means clustering was performed using metabolic and inflammatory biomarkers. Multivariate Cox regression analysis assessed the risk of complications and mortality over a follow-up period of 13.5 years. Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS) explored cluster-specific genetic traits.</p><p><strong>Results: </strong>Among 126 145 participants (mean [IQR] age: 55.0 [14.0] years; 61 983 males [49.1%]), five clusters were identified: (1) Low Metabolic Risk-related, (2) Hypertension-Related, (3) Mixed Hyperlipidemia-Related, (4) Elevated Lipoprotein(a)-Related and (5) High BMI and Inflammation-Related. Cluster 1 exhibited a lower risk of complications than other clusters. Cluster 2 had the highest incidence of stroke, linked to variants affecting blood circulation. Cluster 3 showed the highest risks for ischaemic heart disease, characterized by variants enriched in cholesterol metabolism pathways. Cluster 4 was associated with high cardiovascular risks. Cluster 5 had the highest risks for diabetes, asthma, chronic obstructive pulmonary disease, osteoarthritis and mortality, linked to obesity-related genetic variants. We also proposed a method for applying this classification in clinical settings.</p><p><strong>Conclusions: </strong>This classification provides insights into the heterogeneity of individuals with overweight and obesity, aiding in the identification of high-risk patients who may benefit from targeted interventions.</p>","PeriodicalId":158,"journal":{"name":"Diabetes, Obesity & Metabolism","volume":" ","pages":""},"PeriodicalIF":5.4000,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes, Obesity & Metabolism","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/dom.16262","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0

Abstract

Aims: The growing epidemic of overweight and obesity elevates disease risks, with metabolic disorders and inflammation critically involved in the pathogenic mechanisms. This study refines the subtyping of overweight and obesity using metabolic and inflammatory markers to enhance risk assessment and personalized prevention.

Materials and methods: Based on the UK Biobank, this retrospective study included participants classified as overweight or obese (BMI ≥25 kg/m2). K-means clustering was performed using metabolic and inflammatory biomarkers. Multivariate Cox regression analysis assessed the risk of complications and mortality over a follow-up period of 13.5 years. Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS) explored cluster-specific genetic traits.

Results: Among 126 145 participants (mean [IQR] age: 55.0 [14.0] years; 61 983 males [49.1%]), five clusters were identified: (1) Low Metabolic Risk-related, (2) Hypertension-Related, (3) Mixed Hyperlipidemia-Related, (4) Elevated Lipoprotein(a)-Related and (5) High BMI and Inflammation-Related. Cluster 1 exhibited a lower risk of complications than other clusters. Cluster 2 had the highest incidence of stroke, linked to variants affecting blood circulation. Cluster 3 showed the highest risks for ischaemic heart disease, characterized by variants enriched in cholesterol metabolism pathways. Cluster 4 was associated with high cardiovascular risks. Cluster 5 had the highest risks for diabetes, asthma, chronic obstructive pulmonary disease, osteoarthritis and mortality, linked to obesity-related genetic variants. We also proposed a method for applying this classification in clinical settings.

Conclusions: This classification provides insights into the heterogeneity of individuals with overweight and obesity, aiding in the identification of high-risk patients who may benefit from targeted interventions.

求助全文
约1分钟内获得全文 求助全文
来源期刊
Diabetes, Obesity & Metabolism
Diabetes, Obesity & Metabolism 医学-内分泌学与代谢
CiteScore
10.90
自引率
6.90%
发文量
319
审稿时长
3-8 weeks
期刊介绍: Diabetes, Obesity and Metabolism is primarily a journal of clinical and experimental pharmacology and therapeutics covering the interrelated areas of diabetes, obesity and metabolism. The journal prioritises high-quality original research that reports on the effects of new or existing therapies, including dietary, exercise and lifestyle (non-pharmacological) interventions, in any aspect of metabolic and endocrine disease, either in humans or animal and cellular systems. ‘Metabolism’ may relate to lipids, bone and drug metabolism, or broader aspects of endocrine dysfunction. Preclinical pharmacology, pharmacokinetic studies, meta-analyses and those addressing drug safety and tolerability are also highly suitable for publication in this journal. Original research may be published as a main paper or as a research letter.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信