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

IF 5.7 2区医学 Q1 ENDOCRINOLOGY & METABOLISM Diabetes, Obesity & Metabolism Pub Date : 2025-02-19 DOI:10.1111/dom.16262

Hang Dong MD, Yingzhou Shi PhD, Yicheng Ma MD, Yiping Cheng PhD, Luna Liu PhD, Shengyang Xiao PhD, Zinuo Yuan MD, Zhen Wang PhD, Tuo Li PhD, Jiajun Zhao PhD, Xiude Fan PhD

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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.

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新的超重/肥胖代谢和炎症分层来表征不良后果的风险：一项基于人群的队列研究

目的：超重和肥胖的日益流行增加了疾病风险，代谢紊乱和炎症在致病机制中起关键作用。本研究使用代谢和炎症标记物来细化超重和肥胖的亚型，以加强风险评估和个性化预防。材料和方法：基于UK Biobank，本回顾性研究纳入了超重或肥胖（BMI≥25 kg/m2）的参与者。使用代谢和炎症生物标志物进行k均值聚类。多变量Cox回归分析评估了13.5年随访期间并发症和死亡率的风险。全基因组关联研究（GWAS）和全表型关联研究（PheWAS）探索集群特异性遗传性状。结果：126 145名参与者(平均[IQR]年龄：55.0[14.0]岁；61 983例男性[49.1%])，鉴定出5类：(1)低代谢风险相关，(2)高血压相关，(3)混合性高脂血症相关，(4)脂蛋白升高(a)相关，(5)高BMI和炎症相关。第1组出现并发症的风险低于其他组。第二组中风发病率最高，与影响血液循环的变异有关。集群3显示缺血性心脏病的风险最高，其特征是胆固醇代谢途径的变异丰富。第4组与高心血管风险相关。第5类人群患糖尿病、哮喘、慢性阻塞性肺病、骨关节炎和死亡率的风险最高，这些疾病与肥胖相关的基因变异有关。我们还提出了一种在临床环境中应用这种分类的方法。结论：该分类提供了对超重和肥胖个体异质性的见解，有助于识别可能受益于针对性干预的高危患者。

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来源期刊

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.