Metabolic health and genetic predisposition in inflammatory bowel disease: Insights from a prospective cohort study.

Cohort study Genetic risk Inflammatory bowel disease Metabolic health

Journal

European journal of internal medicine
ISSN: 1879-0828
Titre abrégé: Eur J Intern Med
Pays: Netherlands
ID NLM: 9003220

Informations de publication

Date de publication:
02 Jul 2024
Historique:
received: 12 04 2024
revised: 21 05 2024
accepted: 19 06 2024
medline: 3 7 2024
pubmed: 3 7 2024
entrez: 2 7 2024
Statut: aheadofprint

Résumé

Metabolic disorders exhibit strong inflammatory underpinnings and vice versa. This study aimed to investigate the association between metabolic health status, genetic predisposition, and the risk of inflammatory bowel disease (IBD), and to explore the potential benefits of maintaining ideal metabolic status for individuals with a predetermined genetic risk of IBD. This population-based prospective study included 385,820 unrelated European descent participants from the UK Biobank. Using multivariable Cox regression, we assessed the relationship of metabolic phenotypes with risk of IBD and its subtypes. We also developed a polygenic risk score to examine how metabolic health status interacted with genetic risk in relation to IBD risk. During the follow-up period of 4,328,895 person-years, 2,044 newly-diagnosed IBD cases were identified. Higher genetic risk and an increasing number of abnormal metabolic phenotypes were associated with elevated IBD risk (p-trend <0.001). Individuals with high genetic risk and poor metabolic health had a significantly higher risk of IBD (HR=4.56, 95 % CI=3.27-6.36) compared to those with low genetic risk and ideal metabolic health. These results remained consistent for IBD subtypes. Maintaining ideal metabolic status reduced IBD risk within each genetic risk category and jointly decreased subsequent risk by 40 % in high genetic risk individuals. Our study reveals a combined impact of poor metabolic health and genetic risk on IBD incidence. Those with low genetic risk and optimal metabolic health exhibit the lowest IBD risk, offering insights into potential management strategies for individuals at predefined genetic risk.

Sections du résumé

BACKGROUND BACKGROUND
Metabolic disorders exhibit strong inflammatory underpinnings and vice versa. This study aimed to investigate the association between metabolic health status, genetic predisposition, and the risk of inflammatory bowel disease (IBD), and to explore the potential benefits of maintaining ideal metabolic status for individuals with a predetermined genetic risk of IBD.
METHOD METHODS
This population-based prospective study included 385,820 unrelated European descent participants from the UK Biobank. Using multivariable Cox regression, we assessed the relationship of metabolic phenotypes with risk of IBD and its subtypes. We also developed a polygenic risk score to examine how metabolic health status interacted with genetic risk in relation to IBD risk.
RESULTS RESULTS
During the follow-up period of 4,328,895 person-years, 2,044 newly-diagnosed IBD cases were identified. Higher genetic risk and an increasing number of abnormal metabolic phenotypes were associated with elevated IBD risk (p-trend <0.001). Individuals with high genetic risk and poor metabolic health had a significantly higher risk of IBD (HR=4.56, 95 % CI=3.27-6.36) compared to those with low genetic risk and ideal metabolic health. These results remained consistent for IBD subtypes. Maintaining ideal metabolic status reduced IBD risk within each genetic risk category and jointly decreased subsequent risk by 40 % in high genetic risk individuals.
CONCLUSION CONCLUSIONS
Our study reveals a combined impact of poor metabolic health and genetic risk on IBD incidence. Those with low genetic risk and optimal metabolic health exhibit the lowest IBD risk, offering insights into potential management strategies for individuals at predefined genetic risk.

Identifiants

DOI: 10.1016/j.ejim.2024.06.020 PMID: 38955589
pubmed: 38955589
pii: S0953-6205(24)00275-9
doi: 10.1016/j.ejim.2024.06.020
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declared that no competing interests exist.

Auteurs

Ningning Mi (N)

Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China; Chinese Health Risk Management Collaboration (CHRIMAC), Shenzhen, Guangdong, China; The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.

Qiangsheng He (Q)

Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China; Chinese Health Risk Management Collaboration (CHRIMAC), Shenzhen, Guangdong, China.

Yuyao Liu (Y)

Department of Oncology, Cancer Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.

Yingmei Li (Y)

Department of Pharmacy, Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.

Ying Li (Y)

Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.

Yingjie Wu (Y)

Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.

Man Yang (M)

Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.

Yingya Zhao (Y)

Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA.

Peng Xie (P)

Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.

Wenjing Li (W)

Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.

Siqin Wu (S)

Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.

Zijun Li (Z)

Evidence Based Social Science Research Center/Health Technology Assessment Center, School of Public Health, Lanzhou University, Lanzhou, China.

Danni Wang (D)

Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.

Xiwen Qin (X)

Department of Pharmacology and Pharmacy, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China; Laboratory of Data Discovery for Health (D24H), The University of Hong Kong, Hong Kong SAR, China; School of Population and Global Health, Faculty of Medicine, Density and Health Sciences, University of Western Australia, Perth, Australia.

Jinqiu Yuan (J)

Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China; Chinese Health Risk Management Collaboration (CHRIMAC), Shenzhen, Guangdong, China.

Pingguang Lei (P)

Department of Gastroenterology, Shenzhen Bao'an District Songgang People's Hospital, Shenzhen, Guangdong, China.

Jian Qi (J)

Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.

Bin Xia (B)

Department of Epidemiology and Biostatistics, Clinical Big Data Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China; Chinese Health Risk Management Collaboration (CHRIMAC), Shenzhen, Guangdong, China. Electronic address: xiab7@mail.sysu.edu.cn.

Classifications MeSH