Association of biological age with health outcomes and its modifiable factors

Author:

Liu Wei‐Shi1,You Jia23,Ge Yi‐Jun1,Wu Bang‐Sheng1,Zhang Yi1,Chen Shi‐Dong1,Zhang Ya‐Ru1,Huang Shu‐Yi1,Ma Ling‐Zhi4,Feng Jian‐Feng235,Cheng Wei12367,Yu Jin‐Tai1ORCID

Affiliation:

1. Department of Neurology and National Center for Neurological Diseases, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Shanghai Medical College, Fudan University Shanghai China

2. Institute of Science and Technology for Brain‐Inspired Intelligence, Fudan University Shanghai China

3. Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University), Ministry of Education Shanghai China

4. Department of Neurology, Qingdao Municipal Hospital Qingdao University Qingdao China

5. Department of Computer Science University of Warwick Coventry UK

6. Fudan ISTBI—ZJNU Algorithm Centre for Brain‐Inspired Intelligence Zhejiang Normal University Jinhua China

7. Shanghai Medical College and Zhongshan Hosptital Immunotherapy Technology Transfer Center Shanghai China

Abstract

AbstractIdentifying the clinical implications and modifiable and unmodifiable factors of aging requires the measurement of biological age (BA) and age gap. Leveraging the biomedical traits involved with physical measures, biochemical assays, genomic data, and cognitive functions from the healthy participants in the UK Biobank, we establish an integrative BA model consisting of multi‐dimensional indicators. Accelerated aging (age gap >3.2 years) at baseline is associated incident circulatory diseases, related chronic disorders, all‐cause, and cause‐specific mortality. We identify 35 modifiable factors for age gap (p < 4.81 × 10−4), where pulmonary functions, body mass, hand grip strength, basal metabolic rate, estimated glomerular filtration rate, and C‐reactive protein show the most significant associations. Genetic analyses replicate the possible associations between age gap and health‐related outcomes and further identify CST3 as an essential gene for biological aging, which is highly expressed in the brain and is associated with immune and metabolic traits. Our study profiles the landscape of biological aging and provides insights into the preventive strategies and therapeutic targets for aging.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Cell Biology,Aging

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