TY - JOUR
T1 - Metabolomic age and risk of 50 chronic diseases in community-dwelling adults
T2 - A prospective cohort study
AU - Shang, Xianwen
AU - Liu, Jiahao
AU - Zhu, Zhuoting
AU - Zhang, Xueli
AU - Huang, Yu
AU - Liu, Shunming
AU - Wang, Wei
AU - Zhang, Xiayin
AU - Ma, Shuo
AU - Tang, Shulin
AU - Hu, Yijun
AU - Ge, Zongyuan
AU - Yu, Honghua
AU - He, Mingguang
N1 - Funding Information:
The study was in part supported by XLZ receives GDPH Supporting Fund for Talent Program (KJ2020633). ZZ receives support from the National Natural Science Foundation of China (82101173), the Research Foundation of Medical Science and Technology of Guangdong Province (B2021237). HY receives support from the National Natural Science Foundation of China (81870663, 82171075), the Outstanding Young Talent Trainee Program of Guangdong Provincial People's Hospital (KJ012019087), Guangdong Provincial People's Hospital Scientific Research Funds for Leading Medical Talents and Distinguished Young Scholars in Guangdong Province (KJ012019457), Talent Introduction Fund of Guangdong Provincial People's Hospital (Y012018145). MH receives support from the High‐level Talent Flexible Introduction Fund of Guangdong Provincial People's Hospital (No. KJ012019530). MH also receives support from the University of Melbourne at Research Accelerator Program and the CERA Foundation. The Centre for Eye Research Australia receives Operational Infrastructure Support from the Victorian State Government. The sponsor or funding organization had no role in the design or conduct of this research. The sponsor or funding organization had no role in the design, conduct, analysis, or reporting of this study. The funding sources did not participate in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Publisher Copyright:
© 2024 The Authors. Aging Cell published by Anatomical Society and John Wiley & Sons Ltd.
PY - 2024/5
Y1 - 2024/5
N2 - It 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.
AB - It 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.
KW - cardiometabolic disorder
KW - chronic kidney disease
KW - chronic obstructive pulmonary disease
KW - liver disease
KW - metabolomic age
KW - moderation analysis
KW - oesophageal cancer
UR - http://www.scopus.com/inward/record.url?scp=85186489146&partnerID=8YFLogxK
U2 - 10.1111/acel.14125
DO - 10.1111/acel.14125
M3 - Article
C2 - 38380547
AN - SCOPUS:85186489146
SN - 1474-9718
VL - 23
JO - Aging Cell
JF - Aging Cell
IS - 5
M1 - e14125
ER -