|
1
|
Gao PY, Ma LZ, Wang XJ, Wu BS, Huang YM, Wang ZB, Fu Y, Ou YN, Feng JF, Cheng W, Tan L, Yu JT. Physical frailty, genetic predisposition, and incident dementia: a large prospective cohort study. Transl Psychiatry 2024; 14:212. [PMID: 38802408 PMCID: PMC11130190 DOI: 10.1038/s41398-024-02927-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 05/10/2024] [Accepted: 05/13/2024] [Indexed: 05/29/2024] Open
Abstract
Physical frailty and genetic factors are both risk factors for increased dementia; nevertheless, the joint effect remains unclear. This study aimed to investigated the long-term relationship between physical frailty, genetic risk, and dementia incidence. A total of 274,194 participants from the UK Biobank were included. We applied Cox proportional hazards regression models to estimate the association between physical frailty and genetic and dementia risks. Among the participants (146,574 females [53.45%]; mean age, 57.24 years), 3,353 (1.22%) new-onset dementia events were recorded. Compared to non-frailty, the hazard ratio (HR) for dementia incidence in prefrailty and frailty was 1.396 (95% confidence interval [CI], 1.294-1.506, P < 0.001) and 2.304 (95% CI, 2.030-2.616, P < 0.001), respectively. Compared to non-frailty and low polygenic risk score (PRS), the HR for dementia risk was 3.908 (95% CI, 3.051-5.006, P < 0.001) for frailty and high PRS. Furthermore, among the participants, slow walking speed (HR, 1.817; 95% CI, 1.640-2.014, P < 0.001), low physical activity (HR, 1.719; 95% CI, 1.545-1.912, P < 0.001), exhaustion (HR, 1.670; 95% CI, 1.502-1.856, P < 0.001), low grip strength (HR, 1.606; 95% CI, 1.479-1.744, P < 0.001), and weight loss (HR, 1.464; 95% CI, 1.328-1.615, P < 0.001) were independently associated with dementia risk compared to non-frailty. Particularly, precise modulation for different dementia genetic risk populations can also be identified due to differences in dementia risk resulting from the constitutive pattern of frailty in different genetic risk populations. In conclusion, both physical frailty and high genetic risk are significantly associated with higher dementia risk. Early intervention to modify frailty is beneficial for achieving primary and precise prevention of dementia, especially in those at high genetic risk.
Collapse
Affiliation(s)
- Pei-Yang Gao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ling-Zhi Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xue-Jie Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi-Ming Huang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Zhi-Bo Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
| |
Collapse
|