Metabolomic age and risk of 50 chronic diseases in community‐dwelling adults: A prospective cohort study

Author:

Shang Xianwen1234ORCID,Liu Jiahao3,Zhu Zhuoting123ORCID,Zhang Xueli15,Huang Yu12,Liu Shunming1,Wang Wei6,Zhang Xiayin12,Ma Shuo7,Tang Shulin1,Hu Yijun1,Ge Zongyuan8,Yu Honghua1ORCID,He Mingguang1369

Affiliation:

1. Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences Southern Medical University Guangzhou China

2. Guangdong Cardiovascular Institute Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences Guangzhou China

3. The Ophthalmic Epidemiology Department Centre for Eye Research Australia Melbourne Victoria Australia

4. Department of Medicine, Royal Melbourne Hospital University of Melbourne Melbourne Victoria Australia

5. Medical Research Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences Southern Medical University Guangzhou China

6. State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center Sun Yat‐sen University Guangzhou China

7. Medical Big Data Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences Southern Medical University Guangzhou China

8. Monash e‐Research Center, Faculty of Engineering, Airdoc Research, Nvidia AI Technology Research Center Monash University Melbourne Victoria Australia

9. Experimental Ophthalmology The Hong Kong Polytechnic University Hong Kong China

Abstract

AbstractIt is unclear how metabolomic age is associated with the risk of a wide range of chronic diseases. Our analysis included 110,692 participants (training: n = 27,673; testing: n = 27,673; validating: n = 55,346) aged 39–71 years at baseline (2006–2010) from the UK Biobank. Incident chronic diseases were identified using inpatient records, or death registers until January 2021. Predicted metabolomic age was trained and tested based on 168 metabolomics. Metabolomic age was linked to the risk of 50 diseases in the validation dataset. The median follow‐up duration for individual diseases ranged from 11.2 years to 11.9 years. After controlling for false discovery rate, chronological age‐adjusted age gap (CAAG) was significantly associated with the incidence of 25 out of 50 chronic diseases. After adjustment for full covariates, associations with 15 chronic diseases remained significant. Greater CAAG was associated with increased risk of eight cardiometabolic disorders (including cardiovascular diseases and diabetes), some cancers, alcohol use disorder, chronic obstructive pulmonary disease, chronic kidney disease, chronic liver disease and age‐related macular degeneration. The association between CAAG and risk of peripheral vascular disease, other cardiac diseases, fracture, cataract and thyroid disorder was stronger among individuals with unhealthy diet than in those with healthy diet. The association between CAAG and risk of some conditions was stronger in younger individuals, those with metabolic disorders or low education. Metabolomic age plays an important role in the development of multiple chronic diseases. Healthy diet and high education may mitigate the risk for some chronic diseases due to metabolomic age acceleration.

Publisher

Wiley

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