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Huang LY, Ge YJ, Fu Y, Zhao YL, Ou YN, Zhang Y, Ma LZ, Chen SD, Guo ZX, Feng JF, Cheng W, Tan L, Yu JT. Identifying modifiable factors and their joint effect on brain health: an exposome-wide association study. GeroScience 2024; 46:6257-6268. [PMID: 38822946 PMCID: PMC11493923 DOI: 10.1007/s11357-024-01224-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 05/24/2024] [Indexed: 06/03/2024] Open
Abstract
Considerable uncertainty remains regarding the associations of multiple factors with brain health. We aimed to conduct an exposome-wide association study on neurodegenerative disease and neuropsychiatry disorders using data of participants from the UK Biobank. Multivariable Cox regression models with the least absolute shrinkage and selection operator technique as well as principal component analyses were used to evaluate the exposures in relation to common disorders of central nervous system (CNS). Restricted cubic splines were conducted to explore potential nonlinear correlations. Then, weighted standardized scores were generated based on the coefficients to calculate the joint effects of risk factors. We also estimated the potential impact of eliminating the unfavorable profiles of risk domains on CNS disorders using population attributable fraction (PAF). Finally, sensitivity analyses were performed to reduce the risk of reverse causality. The current study discovered the significantly associated exposures fell into six primary exposome categories. The joint effects of identified risk factors demonstrated higher risks for common disorders of CNS (HR = 1.278 ~ 3.743, p < 2e-16). The PAF varied by exposome categories, with lifestyle and medical history contributing to majority of disease cases. In total, we estimated that up to 3.7 ~ 64.1% of disease cases could be prevented.This study yielded modifiable variables of different categories and assessed their joint effects on common disorders of CNS. Targeting the identified exposures might help formulate effective strategies for maintaining brain health.
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Affiliation(s)
- Liang-Yu Huang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yi-Jun Ge
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yong-Li Zhao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yi Zhang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ling-Zhi Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Shi-Dong Chen
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ze-Xin Guo
- 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
| | - Wei Cheng
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier 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 Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
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Shang X, Wang W, Tian L, Shi D, Huang Y, Zhang X, Zhu Z, Zhang X, Liu J, Tang S, Hu Y, Ge Z, Yu H, He M. Association of greenspace and natural environment with brain volumes mediated by lifestyle and biomarkers among urban residents. Arch Gerontol Geriatr 2024; 126:105546. [PMID: 38941948 DOI: 10.1016/j.archger.2024.105546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 05/28/2024] [Accepted: 06/22/2024] [Indexed: 06/30/2024]
Abstract
OBJECTIVES To examine the associaiton between environmental measures and brain volumes and its potential mediators. STUDY DESIGN This was a prospective study. METHODS Our analysis included 34,454 participants (53.4% females) aged 40-73 years at baseline (between 2006 and 2010) from the UK Biobank. Brain volumes were measured using magnetic resonance imaging between 2014 and 2019. RESULTS Greater proximity to greenspace buffered at 1000 m at baseline was associated with larger volumes of total brain measured 8.8 years after baseline assessment (standardized β (95% CI) for each 10% increment in coverage: 0.013(0.005,0.020)), grey matter (0.013(0.006,0.020)), and white matter (0.011(0.004,0.017)) after adjustment for covariates and air pollution. The corresponding numbers for natural environment buffered at 1000 m were 0.010 (0.004,0.017), 0.009 (0.004,0.015), and 0.010 (0.004,0.016), respectively. Similar results were observed for greenspace and natural environment buffered at 300 m. The strongest mediator for the association between greenspace buffered at 1000 m and total brain volume was smoking (percentage (95% CI) of total variance explained: 7.9% (5.5-11.4%)) followed by mean sphered cell volume (3.3% (1.8-5.8%)), vitamin D (2.9% (1.6-5.1%)), and creatinine in blood (2.7% (1.6-4.7%)). Significant mediators combined explained 18.5% (13.2-25.3%) of the association with total brain volume and 32.9% (95% CI: 22.3-45.7%) of the association with grey matter volume. The percentage (95% CI) of the association between natural environment and total brain volume explained by significant mediators combined was 20.6% (14.7-28.1%)). CONCLUSIONS Higher coverage percentage of greenspace and environment may benefit brain health by promoting healthy lifestyle and improving biomarkers including vitamin D and red blood cell indices.
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Affiliation(s)
- Xianwen Shang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China; Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China; Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC 3002, Australia; Department of Medicine (Royal Melbourne Hospital), University of Melbourne, Melbourne, VIC 3050, Australia; School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong, PR China.
| | - Wei Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510060, PR China
| | - Le Tian
- Comprehensive department, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, PR China
| | - Danli Shi
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510060, PR China; School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong, PR China; Research Centre for SHARP Vision, The Hong Kong Polytechnic University, Kowloon, Hong Kong, PR China
| | - Yu Huang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China; Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China
| | - Xueli Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China
| | - Zhuoting Zhu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China; Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China; Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC 3002, Australia
| | - Xiayin Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China; Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China
| | - Jiahao Liu
- Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC 3002, Australia
| | - Shulin Tang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China
| | - Yijun Hu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China
| | - Zongyuan Ge
- Monash e-Research Center, Faculty of Engineering, Airdoc Research, Nvidia AI Technology Research Center, Monash University, Melbourne, VIC 3800, Australia
| | - Honghua Yu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China.
| | - Mingguang He
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, PR China; Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC 3002, Australia; State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510060, PR China; School of Optometry, The Hong Kong Polytechnic University, Kowloon, Hong Kong, PR China; Research Centre for SHARP Vision, The Hong Kong Polytechnic University, Kowloon, Hong Kong, PR China.
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Zhang X, Li D, Ye S, Liu S, Ma S, Li M, Peng Q, Hu L, Shang X, He M, Zhang L. Decoding the genetic comorbidity network of Alzheimer's disease. BioData Min 2024; 17:40. [PMID: 39385276 PMCID: PMC11465508 DOI: 10.1186/s13040-024-00394-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Accepted: 10/02/2024] [Indexed: 10/12/2024] Open
Abstract
Alzheimer's disease (AD) has emerged as the most prevalent and complex neurodegenerative disorder among the elderly population. However, the genetic comorbidity etiology for AD remains poorly understood. In this study, we conducted pleiotropic analysis for 41 AD phenotypic comorbidities, identifying ten genetic comorbidities with 16 pleiotropy genes associated with AD. Through biological functional and network analysis, we elucidated the molecular and functional landscape of AD genetic comorbidities. Furthermore, leveraging the pleiotropic genes and reported biomarkers for AD genetic comorbidities, we identified 50 potential biomarkers for AD diagnosis. Our findings deepen the understanding of the occurrence of AD genetic comorbidities and provide new insights for the search for AD diagnostic markers.
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Affiliation(s)
- Xueli Zhang
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, 510080, China.
| | - Dantong Li
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Siting Ye
- Department of Ultrasound, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
- Department of Orthopaedics, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Shunming Liu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Shuo Ma
- Clinical Data Center, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Department of Ethicon Minimally Invasive Procedures and Advanced Energy, Johnson & Johnson Medical (Shanghai) Device Company, Shanghai, China
| | - Min Li
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Qiliang Peng
- Department of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Radiotherapy & Oncology, Soochow University, Suzhou, China
| | - Lianting Hu
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Xianwen Shang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Experimental Ophthalmology, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.
| | - Mingguang He
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Experimental Ophthalmology, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.
| | - Lei Zhang
- Clinical Medical Research Center, Children's Hospital of Nanjing Medical University, Nanjing, China.
- School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia.
- Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia.
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Jakobsson J, Burtin C, Hedlund M, Boraxbekk CJ, Westman J, Karalija N, Stål P, Sandström T, Ruttens D, Gosker HR, De Brandt J, Nyberg A. Effects and mechanisms of supramaximal high-intensity interval training on extrapulmonary manifestations in people with and without chronic obstructive pulmonary disease (COPD-HIIT): study protocol for a multi-centre, randomized controlled trial. Trials 2024; 25:664. [PMID: 39375781 PMCID: PMC11460198 DOI: 10.1186/s13063-024-08481-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 09/17/2024] [Indexed: 10/09/2024] Open
Abstract
BACKGROUND Beyond being a pulmonary disease, chronic obstructive pulmonary disease (COPD) presents with extrapulmonary manifestations including reduced cognitive, cardiovascular, and muscle function. While exercise training is the cornerstone in the non-pharmacological treatment of COPD, there is a need for new exercise training methods due to suboptimal adaptations when following traditional exercise guidelines, often applying moderate-intensity continuous training (MICT). In people with COPD, short-duration high-intensity interval training (HIIT) holds the potential to induce a more optimal stimulus for training adaptations while circumventing the ventilatory burden often associated with MICT in people with COPD. We aim to determine the effects of supramaximal HIIT and MICT on extrapulmonary manifestations in people with COPD compared to matched healthy controls. METHODS COPD-HIIT is a prospective, multi-centre, randomized, controlled trial with blinded assessors and data analysts, employing a parallel-group designed trial. In phase 1, we will investigate the effects and mechanisms of a 12-week intervention of supramaximal HIIT compared to MICT in people with COPD (n = 92) and matched healthy controls (n = 70). Participants will perform watt-based cycling two to three times weekly. In phase 2, we will determine how exercise training and inflammation impact the trajectories of neurodegeneration, in people with COPD, over 24 months. In addition to the 92 participants with COPD performing HIIT or MICT, a usual care group (n = 46) is included in phase 2. In both phases, the primary outcomes are a change from baseline in cognitive function, cardiorespiratory fitness, and muscle power. Key secondary outcomes include change from baseline exercise tolerance, brain structure, and function measured by MRI, neuroinflammation measured by PET/CT, systemic inflammation, and intramuscular adaptations. Feasibility of the interventions will be comprehensively investigated. DISCUSSION The COPD-HIIT trial will determine the effects of supramaximal HIIT compared to MICT in people with COPD and healthy controls. We will provide evidence for a novel exercise modality that might overcome the barriers associated with MICT in people with COPD. We will also shed light on the impact of exercise at different intensities to reduce neurodegeneration. The goal of the COPD-HIIT trial is to improve the treatment of extrapulmonary manifestations of the disease. TRIAL REGISTRATION Clinicaltrials.gov: NCT06068322. Prospectively registered on 2023-09-28.
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Affiliation(s)
- Johan Jakobsson
- Section of Physiotherapy, Department of Community Medicine and Rehabilitation, Umeå University, Umeå, 901 87, Sweden.
| | - Chris Burtin
- REVAL - Rehabilitation Research Center, BIOMED - Biomedical Research Institute, Hasselt University, Diepenbeek, 3590, Belgium
| | - Mattias Hedlund
- Section of Physiotherapy, Department of Community Medicine and Rehabilitation, Umeå University, Umeå, 901 87, Sweden
| | - Carl-Johan Boraxbekk
- Umeå Centre for Functional Brain Imaging (UFBI), Umeå University, Umeå, 901 87, Sweden
- Diagnostic Radiology, Department of Radiation Sciences, Umeå University, Umeå, 901 87, Sweden
- Institute of Sports Medicine Copenhagen (ISMC) and Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, 2400, Denmark
- Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, 2200, Denmark
| | - Jonas Westman
- Section of Physiotherapy, Department of Community Medicine and Rehabilitation, Umeå University, Umeå, 901 87, Sweden
| | - Nina Karalija
- Umeå Centre for Functional Brain Imaging (UFBI), Umeå University, Umeå, 901 87, Sweden
- Department of Medical and Translational Biology, Umeå University, Umeå, 901 87, Sweden
| | - Per Stål
- Department of Medical and Translational Biology, Umeå University, Umeå, 901 87, Sweden
| | - Thomas Sandström
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, 901 87, Sweden
| | - David Ruttens
- Department of Respiratory Medicine, Ziekenhuis Oost-Limburg, Genk, 3600, Belgium
- Faculty of Medicine and Life Sciences, Hasselt University, Diepenbeek, 3590, Belgium
| | - Harry R Gosker
- Department of Respiratory Medicine, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center+, Maastricht, the Netherlands
| | - Jana De Brandt
- Section of Physiotherapy, Department of Community Medicine and Rehabilitation, Umeå University, Umeå, 901 87, Sweden
| | - André Nyberg
- Section of Physiotherapy, Department of Community Medicine and Rehabilitation, Umeå University, Umeå, 901 87, Sweden
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Huang L, Fu Y, Zhang Y, Hu H, Ma L, Ge Y, Zhao Y, Zhang Y, Chen S, Feng J, Cheng W, Tan L, Yu J. Identifying modifiable factors associated with neuroimaging markers of brain health. CNS Neurosci Ther 2024; 30:e70057. [PMID: 39404063 PMCID: PMC11474882 DOI: 10.1111/cns.70057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Revised: 08/20/2024] [Accepted: 09/07/2024] [Indexed: 10/19/2024] Open
Abstract
AIMS Brain structural alterations begin long before the presentation of brain disorders; therefore, we aimed to systematically investigate a wide range of influencing factors on neuroimaging markers of brain health. METHODS Utilizing data from 30,651 participants from the UK Biobank, we explored associations between 218 modifiable factors and neuroimaging markers of brain health. We conducted an exposome-wide association study using the least absolute shrinkage and selection operator (LASSO) technique. Restricted cubic splines (RCS) were further employed to estimate potential nonlinear correlations. Weighted standardized scores for neuroimaging markers were computed based on the estimates for individual factors. Finally, stratum-specific analyses were performed to examine differences in factors affecting brain health at different ages. RESULTS The identified factors related to neuroimaging markers of brain health fell into six domains, including systematic diseases, lifestyle factors, personality traits, social support, anthropometric indicators, and biochemical markers. The explained variance percentage of neuroimaging markers by weighted standardized scores ranged from 0.5% to 7%. Notably, associations between systematic diseases and neuroimaging markers were stronger in older individuals than in younger ones. CONCLUSION This study identified a series of factors related to neuroimaging markers of brain health. Targeting the identified factors might help in formulating effective strategies for maintaining brain health.
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Affiliation(s)
- Liang‐Yu Huang
- Department of NeurologyQingdao Municipal Hospital, Qingdao UniversityQingdaoChina
| | - Yan Fu
- Department of NeurologyQingdao Municipal Hospital, Qingdao UniversityQingdaoChina
| | - Yi Zhang
- Department of Neurology and Institute of NeurologyHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - He‐Ying Hu
- Department of NeurologyQingdao Municipal Hospital, Qingdao UniversityQingdaoChina
| | - Ling‐Zhi Ma
- Department of NeurologyQingdao Municipal Hospital, Qingdao UniversityQingdaoChina
| | - Yi‐Jun Ge
- Department of Neurology and Institute of NeurologyHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Yong‐Li Zhao
- Department of NeurologyQingdao Municipal Hospital, Qingdao UniversityQingdaoChina
| | - Ya‐Ru Zhang
- Department of Neurology and Institute of NeurologyHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Shi‐Dong Chen
- Department of Neurology and Institute of NeurologyHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Jian‐Feng Feng
- Institute of Science and Technology for Brain‐Inspired Intelligence, Fudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University), Ministry of EducationShanghaiChina
- Fudan ISTBI—ZJNU Algorithm Centre for Brain‐Inspired IntelligenceZhejiang Normal UniversityJinhuaChina
- MOE Frontiers Center for Brain ScienceFudan UniversityShanghaiChina
| | - Wei Cheng
- Department of Neurology and Institute of NeurologyHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
- Institute of Science and Technology for Brain‐Inspired Intelligence, Fudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University), Ministry of EducationShanghaiChina
- Fudan ISTBI—ZJNU Algorithm Centre for Brain‐Inspired IntelligenceZhejiang Normal UniversityJinhuaChina
| | - Lan Tan
- Department of NeurologyQingdao Municipal Hospital, Qingdao UniversityQingdaoChina
| | - Jin‐Tai Yu
- Department of Neurology and Institute of NeurologyHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
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Stephan BCM, Cochrane L, Kafadar AH, Brain J, Burton E, Myers B, Brayne C, Naheed A, Anstey KJ, Ashor AW, Siervo M. Population attributable fractions of modifiable risk factors for dementia: a systematic review and meta-analysis. THE LANCET. HEALTHY LONGEVITY 2024; 5:e406-e421. [PMID: 38824956 PMCID: PMC11139659 DOI: 10.1016/s2666-7568(24)00061-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 03/20/2024] [Accepted: 03/25/2024] [Indexed: 06/04/2024] Open
Abstract
BACKGROUND More than 57 million people have dementia worldwide. Evidence indicates a change in dementia prevalence and incidence in high-income countries, which is likely to be due to improved life-course population health. Identifying key modifiable risk factors for dementia is essential for informing risk reduction and prevention strategies. We therefore aimed to estimate the population attributable fraction (PAF) for dementia associated with modifiable risk factors. METHODS In this systematic review and meta-analysis, we searched Embase, MEDLINE, and PsycINFO, via Ovid, from database inception up to June 29, 2023, for population-derived or community-based studies and reviews reporting a PAF value for one or more modifiable risk factor for later-life dementia (prevalent or incident dementia in people aged ≥60 years), with no restrictions on dementia subtype, the sex or baseline age of participants, or the period of study. Articles were independently screened for inclusion by four authors, with disagreements resolved through consensus. Data including unweighted and weighted PAF values (weighted to account for communality or overlap in risk) were independently extracted into a predefined template by two authors and checked by two other authors. When five or more unique studies investigated a given risk factor or combination of the same factors, random-effects meta-analyses were used to calculate a pooled PAF percentage estimate for the factor or combination of factors. The review protocol was registered on PROSPERO, CRD42022323429. FINDINGS 4024 articles were identified, and 74 were included in our narrative synthesis. Overall, PAFs were reported for 61 modifiable risk factors, with sufficient data available for meta-analysis of 12 factors (n=48 studies). In meta-analyses, the highest pooled unweighted PAF values were estimated for low education (17·2% [95% CI 14·4-20·0], p<0·0001), hypertension (15·8% [14·7-17·1], p<0·0001), hearing loss (15·6% [10·3-20·9], p<0·0001), physical inactivity (15·2% [12·8-17·7], p<0·0001), and obesity (9·4% [7·3-11·7], p<0·0001). According to weighted PAF values, low education (9·3% [6·9-11·7], p<0·0001), physical inactivity (7·3% [3·9-11·2], p=0·0021), hearing loss (7·2% [5·2-9·7], p<0·0001), hypertension (7·1% [5·4-8·8], p<0·0001), and obesity (5·3% [3·2-7·4], p=0·0001) had the highest pooled estimates. When low education, midlife hypertension, midlife obesity, smoking, physical inactivity, depression, and diabetes were combined (Barnes and Yaffe seven-factor model; n=9 studies), the pooled unweighted and weighted PAF values were 55·0% (46·5-63·5; p<0·0001) and 32·0% (26·6-37·5; p<0·0001), respectively. The pooled PAF values for most individual risk factors were higher in low-income and middle-income countries (LMICs) versus high-income countries. INTERPRETATION Governments need to invest in a life-course approach to dementia prevention, including policies that enable quality education, health-promoting environments, and improved health. This investment is particularly important in LMICs, where the potential for prevention is high, but resources, infrastructure, budgets, and research focused on ageing and dementia are limited. FUNDING UK Research and Innovation (Medical Research Council).
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Affiliation(s)
- Blossom C M Stephan
- Dementia Centre of Excellence, Curtin enAble Institute, Faculty of Health Sciences, Curtin University, Perth, WA, Australia; Institute of Mental Health, The University of Nottingham Medical School, Nottingham, UK.
| | - Louie Cochrane
- Institute of Mental Health, The University of Nottingham Medical School, Nottingham, UK
| | | | - Jacob Brain
- Institute of Mental Health, The University of Nottingham Medical School, Nottingham, UK; Freemasons Foundation Centre for Men's Health, Discipline of Medicine, School of Psychology, The University of Adelaide, Adelaide, SA, Australia
| | - Elissa Burton
- Dementia Centre of Excellence, Curtin enAble Institute, Faculty of Health Sciences, Curtin University, Perth, WA, Australia; Curtin School of Allied Health, Faculty of Health Sciences, Curtin University, Perth, WA, Australia
| | - Bronwyn Myers
- Dementia Centre of Excellence, Curtin enAble Institute, Faculty of Health Sciences, Curtin University, Perth, WA, Australia; Mental Health, Alcohol, Substance Use, and Tobacco Research Unit, South African Medical Research Council, Tygerberg, South Africa; Division of Addiction Psychiatry, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Carol Brayne
- Cambridge Public Health, University of Cambridge, Cambridge, UK
| | - Aliya Naheed
- Non-Communicable Diseases, Nutrition Research Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | - Kaarin J Anstey
- UNSW Ageing Futures Institute, University of New South Wales, Sydney, NSW, Australia; Brain Health and Dementia Centre, Neuroscience Research Australia, Sydney, NSW, Australia
| | - Ammar W Ashor
- Department of Internal Medicine, College of Medicine, Mustansiriyah University, Baghdad, Iraq
| | - Mario Siervo
- Dementia Centre of Excellence, Curtin enAble Institute, Faculty of Health Sciences, Curtin University, Perth, WA, Australia; School of Population Health, Curtin University, Perth, WA, Australia
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Zhang T, An Y, Shen Z, Yang H, Jiang J, Chen L, Lu Y, Xia Y. Serum urate levels and neurodegenerative outcomes: a prospective cohort study and mendelian randomization analysis of the UK Biobank. Alzheimers Res Ther 2024; 16:106. [PMID: 38730474 PMCID: PMC11088014 DOI: 10.1186/s13195-024-01476-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 05/06/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND Previous studies on the associations between serum urate levels and neurodegenerative outcomes have yielded inconclusive results, and the causality remains unclear. This study aimed to investigate whether urate levels are associated with the risks of Alzheimer's disease and related dementias (ADRD), Parkinson's disease (PD), and neurodegenerative deaths. METHODS This prospective study included 382,182 participants (45.7% men) from the UK Biobank cohort. Cox proportional hazards models were used to assess the associations between urate levels and risk of neurodegenerative outcomes. In the Mendelian randomization (MR) analysis, urate-related single-nucleotide polymorphisms were identified through a genome-wide association study. Both linear and non-linear MR approaches were utilized to investigate the potential causal associations. RESULTS During a median follow-up period of 12 years, we documented 5,400 ADRD cases, 2,553 PD cases, and 1,531 neurodegenerative deaths. Observational data revealed that a higher urate level was associated with a decreased risk of ADRD (hazard ratio [HR]: 0.93, 95% confidence interval [CI]: 0.90, 0.96), PD (HR: 0.87, 95% CI: 0.82, 0.91), and neurodegenerative death (HR: 0.88, 95% CI: 0.83, 0.94). Negative linear associations between urate levels and neurodegenerative events were observed (all P-values for overall < 0.001 and all P-values for non-linearity > 0.05). However, MR analyses yielded no evidence of either linear or non-linear associations between genetically predicted urate levels and the risk of the aforementioned neurodegenerative events. CONCLUSION Although the prospective cohort study demonstrated that elevated urate levels were associated with a reduced risk of neurodegenerative outcomes, MR analyses found no evidence of causality.
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Affiliation(s)
- Tingjing Zhang
- School of Public Health, Wannan Medical College, Wuhu, China
- Institutes of Brain Science, Wannan Medical College, Wuhu, China
| | - Yu An
- Department of Endocrinology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Zhenfei Shen
- Department of Clinical Nutrition, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Honghao Yang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
| | - Jinguo Jiang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
| | - Liangkai Chen
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yanhui Lu
- School of Nursing, Peking University, No. 38 Xueyuan Rd, Haidian District, Beijing, 100191, China.
| | - Yang Xia
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China.
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Zhao L, Wang Y, Bawa EM, Meng Z, Wei J, Newman-Norlund S, Trivedi T, Hasturk H, Newman-Norlund RD, Fridriksson J, Merchant AT. Identifying a group of factors predicting cognitive impairment among older adults. PLoS One 2024; 19:e0301979. [PMID: 38603668 PMCID: PMC11008866 DOI: 10.1371/journal.pone.0301979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 03/26/2024] [Indexed: 04/13/2024] Open
Abstract
BACKGROUND Cognitive impairment has multiple risk factors spanning several domains, but few studies have evaluated risk factor clusters. We aimed to identify naturally occurring clusters of risk factors of poor cognition among middle-aged and older adults and evaluate associations between measures of cognition and these risk factor clusters. METHODS We used data from the National Health and Nutrition Examination Survey (NHANES) III (training dataset, n = 4074) and the NHANES 2011-2014 (validation dataset, n = 2510). Risk factors were selected based on the literature. We used both traditional logistic models and support vector machine methods to construct a composite score of risk factor clusters. We evaluated associations between the risk score and cognitive performance using the logistic model by estimating odds ratios (OR) and 95% confidence intervals (CI). RESULTS Using the training dataset, we developed a composite risk score that predicted undiagnosed cognitive decline based on ten selected predictive risk factors including age, waist circumference, healthy eating index, race, education, income, physical activity, diabetes, hypercholesterolemia, and annual visit to dentist. The risk score was significantly associated with poor cognitive performance both in the training dataset (OR Tertile 3 verse tertile 1 = 8.15, 95% CI: 5.36-12.4) and validation dataset (OR Tertile 3 verse tertile 1 = 4.31, 95% CI: 2.62-7.08). The area under the receiver operating characteristics curve for the predictive model was 0.74 and 0.77 for crude model and model adjusted for age, sex, and race. CONCLUSION The model based on selected risk factors may be used to identify high risk individuals with cognitive impairment.
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Affiliation(s)
- Longgang Zhao
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Yuan Wang
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Eric Mishio Bawa
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Zichun Meng
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Jingkai Wei
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Sarah Newman-Norlund
- Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Tushar Trivedi
- Regional Medical Center Primary Care Stroke, Orangeburg, SC, United States of America
| | - Hatice Hasturk
- Center for Clinical and Translational Research, Forsyth Institute, Boston, MA, United States of America
| | - Roger D. Newman-Norlund
- Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Julius Fridriksson
- Communication Sciences and Disorders, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
| | - Anwar T. Merchant
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America
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Ren Y, Li Y, Tian N, Liu R, Dong Y, Hou T, Liu C, Han X, Han X, Wang L, Vetrano DL, Ngandu T, Marengoni A, Kivipelto M, Wang Y, Cong L, Du Y, Qiu C. Multimorbidity, cognitive phenotypes, and Alzheimer's disease plasma biomarkers in older adults: A population-based study. Alzheimers Dement 2024; 20:1550-1561. [PMID: 38041805 PMCID: PMC10984420 DOI: 10.1002/alz.13519] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 09/21/2023] [Accepted: 09/28/2023] [Indexed: 12/04/2023]
Abstract
INTRODUCTION To examine the burden and clusters of multimorbidity in association with mild cognitive impairment (MCI), dementia, and Alzheimer's disease (AD)-related plasma biomarkers among older adults. METHODS This population-based study included 5432 participants (age ≥60 years); of these, plasma amyloid beta (Aβ), total tau, and neurofilament light chain (NfL) were measured in a subsample (n = 1412). We used hierarchical clustering to generate five multimorbidity clusters from 23 chronic diseases. We diagnosed dementia and MCI following international criteria. Data were analyzed using logistic and linear regression models. RESULTS The number of chronic diseases was associated with dementia (multivariable-adjusted odds ratio = 1.22; 95% confidence interval [CI] = 1.11 to 1.33), AD (1.13; 1.01 to 1.26), vascular dementia (VaD) (1.44; 1.25 to 1.64), and non-amnestic MCI (1.25; 1.13 to 1.37). Metabolic cluster was associated with VaD and non-amnestic MCI, whereas degenerative ocular cluster was associated with AD (p < 0.05). The number of chronic diseases was associated with increased plasma Aβ and NfL (p < 0.05). DISCUSSION Multimorbidity burden and clusters are differentially associated with subtypes of dementia and MCI and AD-related plasma biomarkers in older adults. HIGHLIGHTS We used hierarchical clustering to generate five clusters of multimorbidity. The presence and load of multimorbidity were associated with dementia and mild cognitive impairment. Multimorbidity clusters were differentially associated with subtypes of dementia and Alzheimer's disease plasma biomarkers.
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Ye S, Roccati E, Wang W, Zhu Z, Kiburg K, Huang Y, Zhang X, Zhang X, Liu J, Tang S, Hu Y, Ge Z, Yu H, He M, Shang X. Leading determinants of incident dementia among individuals with and without the apolipoprotein E ε4 genotype: a retrospective cohort study. BMC Neurol 2024; 24:71. [PMID: 38378514 PMCID: PMC10877929 DOI: 10.1186/s12883-024-03557-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/30/2024] [Indexed: 02/22/2024] Open
Abstract
BACKGROUND Little is known regarding the leading risk factors for dementia/Alzheimer's disease (AD) in individuals with and without APOE4. The identification of key risk factors for dementia/Alzheimer's disease (AD) in individuals with and without the APOE4 gene is of significant importance in global health. METHODS Our analysis included 110,354 APOE4 carriers and 220,708 age- and sex-matched controls aged 40-73 years at baseline (between 2006-2010) from UK Biobank. Incident dementia was ascertained using hospital inpatient, or death records until January 2021. Individuals of non-European ancestry were excluded. Furthermore, individuals without medical record linkage were excluded from the analysis. Moderation analysis was tested for 134 individual factors. RESULTS During a median follow-up of 11.9 years, 4,764 cases of incident all-cause dementia and 2065 incident AD cases were documented. Hazard ratios (95% CIs) for all-cause dementia and AD associated with APOE4 were 2.70(2.55-2.85) and 3.72(3.40-4.07), respectively. In APOE4 carriers, the leading risk factors for all-cause dementia included low self-rated overall health, low household income, high multimorbidity risk score, long-term illness, high neutrophil percentage, and high nitrogen dioxide air pollution. In non-APOE4 carriers, the leading risk factors included high multimorbidity risk score, low overall self-rated health, low household income, long-term illness, high microalbumin in urine, high neutrophil count, and low greenspace percentage. Population attributable risk for these individual risk factors combined was 65.1%, and 85.8% in APOE4 and non-APOE4 carriers, respectively. For 20 risk factors including multimorbidity risk score, unhealthy lifestyle habits, and particulate matter air pollutants, their associations with incident dementia were stronger in non-APOE4 carriers. For only 2 risk factors (mother's history of dementia, low C-reactive protein), their associations with incident all-cause dementia were stronger in APOE4 carriers. CONCLUSIONS Our findings provide evidence for personalized preventative approaches to dementia/AD in APOE4 and non-APOE4 carriers. A mother's history of dementia and low levels of C-reactive protein were more important risk factors of dementia in APOE4 carriers whereas leading risk factors including unhealthy lifestyle habits, multimorbidity risk score, inflammation and immune-related markers were more predictive of dementia in non-APOE4 carriers.
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Affiliation(s)
- Siting Ye
- The Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, 510405, China
- Department of Ultrasound, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China
| | - Eddy Roccati
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, TAS, 7001, Australia
| | - Wei Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Zhuoting Zhu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia
| | - Katerina Kiburg
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia
| | - Yu Huang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Xueli Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Xiayin Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Jiahao Liu
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia
| | - Shulin Tang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Yijun Hu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Zongyuan Ge
- Monash e-Research Center, Faculty of Engineering, Airdoc Research, Nvidia AI Technology Research Center, Monash University, Melbourne, VIC, 3800, Australia
| | - Honghua Yu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
| | - Mingguang He
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia.
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China.
| | - Xianwen Shang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia.
- Department of Medicine (Royal Melbourne Hospital), University of Melbourne, Melbourne, VIC, 3050, Australia.
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Li R, Li R, Xie J, Chen J, Liu S, Pan A, Liu G. Associations of socioeconomic status and healthy lifestyle with incident early-onset and late-onset dementia: a prospective cohort study. THE LANCET. HEALTHY LONGEVITY 2023; 4:e693-e702. [PMID: 38042162 DOI: 10.1016/s2666-7568(23)00211-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 10/03/2023] [Accepted: 10/05/2023] [Indexed: 12/04/2023] Open
Abstract
BACKGROUND Modifiable risk factor estimates are sparse for early-onset dementia incidence. This study aimed to estimate and compare the risk factor profiles of early-onset dementia and late-onset dementia, and to explore the complex relationships between socioeconomic status, lifestyles, and early-onset dementia risk. METHODS In this prospective cohort study, we used data from the UK Biobank for analysis of early-onset dementia and late-onset dementia. For early-onset dementia analyses, data were collected on those aged younger than 60 years without prevalent dementia at baseline. For late-onset dementia analyses, data were collected on those aged 65 years or older at the end of follow-up. Participants with missing information on socioeconomic factors were excluded. Two models were used to test associations between early-onset dementia incidence and socioeconomic status. The first model tested associations between socioeconomic status and early-onset and late-onset dementia incidence, adjusting for covariates. Participant socioeconomic status was defined using education level, income, and employment status via latent class analysis. The second model additionally included a healthy lifestyle score, which was constructed using data on smoking, alcohol consumption, physical activity, and the Healthy Diet Index. Incident early-onset dementia was defined as a dementia case diagnosed before 65 years of age. Multivariable-adjusted Cox proportional hazard regression models were used to estimate the hazard ratio (HR) for risk of dementia. We used multivariable-adjusted Cox proportional-hazard regression models to estimate the HR for risk of both early-onset dementia and late-onset dementia. FINDINGS Between 2007 and 2010, 257 345 individuals were included in the analysis of early-onset dementia, and 294 133 older individuals were included in the analysis of late-onset dementia. During a mean follow-up of 11·9-12·5 years, 502 early-onset dementia cases and 5768 late-onset dementia cases were documented. Risk factor profiles were typically dissimilar between early-onset dementia and late-onset dementia. For instance, the age and sex adjusted HR for low socioeconomic status (vs high) was 4·40 (95% CI 3·43-5·65) for early-onset dementia and 1·90 (1·74-2·07) for late-onset dementia, yielding a ratio of HRs of 2·32 (1·78-3·02). After adjusting for various risk factors, participants with low socioeconomic status (vs high) had increased risk for early-onset dementia (3·38, 2·61-4·37), and overall lifestyle mediated 3·2% (1·8-5·7) of the association. Individuals with both low socioeconomic status and unhealthy lifestyles had a higher risk of early-onset dementia (5·40, 3·66-7·97). No significant interaction was observed between lifestyle and socioeconomic status. The association between socioeconomic status and early-onset dementia seemed to be more pronounced in individuals with type 2 diabetes (HR 11·21, 95% CI 2·70-46·57). INTERPRETATION Early-onset dementia and late-onset dementia might have different risk factor profiles; although risk factors were similar, the magnitude of associations between risk factors and dementia incidence was greater for early-onset dementia. Only a small proportion of the socioeconomic inequity in dementia risk was mediated by healthy lifestyles, which indicates that measures other than healthy lifestyle promotion to improve social determinants of health are warranted. FUNDING The National Key Research and Development Program of China, the National Natural Science Foundation of China, the Hubei Province Science Fund for Distinguished Young Scholars, and the Fundamental Research Funds for the Central Universities.
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Affiliation(s)
- Rui Li
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ruyi Li
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jinchi Xie
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junxiang Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sen Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - An Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, and State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Zhou Q, Yang D, Xiong C, Li X. Atopic dermatitis and cognitive dysfunction in middle-aged and older adults: A systematic review and meta-analysis. PLoS One 2023; 18:e0292987. [PMID: 37878635 PMCID: PMC10599501 DOI: 10.1371/journal.pone.0292987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/03/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND Atopic dermatitis (AD) is a common chronic inflammatory skin disease that affects adults worldwide. Recent evidence suggests that AD may be associated with cognitive dysfunction, but the results of individual studies have been inconsistent. This systematic review and meta-analysis aimed to evaluate the association between AD and cognitive dysfunction in middle-aged and older adults. METHODS To find relevant research, a comprehensive search of electronic databases from the beginning to March 2023 was carried out. Data were taken from studies that were eligible, and a meta-analysis was done to determine the pooled hazard ratio (HR) and 95% confidence interval (CI). RESULTS We searched three databases and found a total of 15 studied arms included in 5 cohort studies with over 8.5 million participants were included in the analysis. The results showed that individuals with AD had a higher risk of developing dementia of all-cause dementia (pooled hazard ratio (HR) = 1.16; 95% CI, 1.10-1.23,P<0.001) and the Alzheimer type (pooled HR = 1.28; 95% CI, 1.01-1.63,P<0.001) but not vascular dementia (pooled HR = 1.42; 95% CI, 0.99-2.04,P<0.001). Subgroup analyses showed that the association between atopic dermatitis and all-cause dementia was significant in Europe (P = 0.004) but not in Asia (P = 0.173) and was significant in prospective cohort studies (P<0.001) but not in non-prospective cohort studies (P = 0.068). Sensitivity analysis and publication bias detection confirmed the reliability of the overall findings. CONCLUSIONS In conclusion, this study demonstrated that AD was associated with increased risk of cognitive dysfunction, particularly dementia of the Alzheimer type and all-cause dementia, in middle-aged and older participants. Further research is needed to understand the mechanisms behind this association and its potential implications for clinical practice. SYSTEMATIC REVIEW REGISTRATION PROSPERO, identifier (CRD42023411627).
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Affiliation(s)
- Qi Zhou
- Department of Neurology, The First People’s Hospital of Fuzhou, Fuzhou, Jiangxi, China
| | - Dejiang Yang
- Department of Neurology, Nanchang First Hospital, Nanchang, Jiangxi, China
| | - Chongyu Xiong
- Department of Neurology, The First People’s Hospital of Fuzhou, Fuzhou, Jiangxi, China
| | - Xinming Li
- Department of Neurology, Nanchang First Hospital, Nanchang, Jiangxi, China
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Fehsel K. Why Is Iron Deficiency/Anemia Linked to Alzheimer's Disease and Its Comorbidities, and How Is It Prevented? Biomedicines 2023; 11:2421. [PMID: 37760862 PMCID: PMC10526115 DOI: 10.3390/biomedicines11092421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/29/2023] Open
Abstract
Impaired iron metabolism has been increasingly observed in many diseases, but a deeper, mechanistic understanding of the cellular impact of altered iron metabolism is still lacking. In addition, deficits in neuronal energy metabolism due to reduced glucose import were described for Alzheimer's disease (AD) and its comorbidities like obesity, depression, cardiovascular disease, and type 2 diabetes mellitus. The aim of this review is to present the molecular link between both observations. Insufficient cellular glucose uptake triggers increased ferritin expression, leading to depletion of the cellular free iron pool and stabilization of the hypoxia-induced factor (HIF) 1α. This transcription factor induces the expression of the glucose transporters (Glut) 1 and 3 and shifts the cellular metabolism towards glycolysis. If this first line of defense is not adequate for sufficient glucose supply, further reduction of the intracellular iron pool affects the enzymes of the mitochondrial electron transport chain and activates the AMP-activated kinase (AMPK). This enzyme triggers the translocation of Glut4 to the plasma membrane as well as the autophagic recycling of cell components in order to mobilize energy resources. Moreover, AMPK activates the autophagic process of ferritinophagy, which provides free iron urgently needed as a cofactor for the synthesis of heme- and iron-sulfur proteins. Excessive activation of this pathway ends in ferroptosis, a special iron-dependent form of cell death, while hampered AMPK activation steadily reduces the iron pools, leading to hypoferremia with iron sequestration in the spleen and liver. Long-lasting iron depletion affects erythropoiesis and results in anemia of chronic disease, a common condition in patients with AD and its comorbidities. Instead of iron supplementation, drugs, diet, or phytochemicals that improve energy supply and cellular glucose uptake should be administered to counteract hypoferremia and anemia of chronic disease.
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Affiliation(s)
- Karin Fehsel
- Neurobiochemical Research Unit, Department of Psychiatry, Medical Faculty, Heinrich-Heine-University, 240629 Düsseldorf, Germany
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Su L, Liao Y, Liu X, Xie X, Li Y. Increased risk of dementia among people with a history of fractures: a systematic review and meta-analysis of population-based studies. Front Neurol 2023; 14:1185721. [PMID: 37545728 PMCID: PMC10400716 DOI: 10.3389/fneur.2023.1185721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 06/23/2023] [Indexed: 08/08/2023] Open
Abstract
Background Emerging evidence suggests that there may be an association between a history of fractures and dementia risk, but the epidemiological findings are inconsistent. We, therefore, conducted a meta-analysis to systematically assess the risk of dementia among people with a history of fractures. Methods We comprehensively searched four electronic databases (PubMed, Web of Science, Embase, and Cochrane Library) for relevant literature published from inception to 10 January 2023. Longitudinal observational studies that investigated the association between any type of fracture occurrence and the subsequent risk of dementia were included for qualitative and quantitative analysis. Risk estimates were pooled using fixed-effects or random-effects models according to the level of heterogeneity. The Newcastle-Ottawa scale was used to evaluate the risk of bias in the included studies. Results A total of seven population-based studies involving 3,658,108 participants (136,179 with a history of fractures) were eventually included. Pooled results showed a significant association between fracture and subsequent risk of dementia [hazard ratio (HR) = 1.28, 95% confidence interval (CI): 1.11-1.48] in cohort studies. Patients with fractures at different sites showed a similar trend toward increased risk of subsequent dementia. No gender, age, region, duration of follow-up, study quality, or study design specificity were observed. Sensitivity analysis indicates that the current results are robust. No publication bias existed. The results were similar in the cohort study with the standardized incidence ratio (SIR) as the statistical measure (SIR = 1.58, 95% CI: 1.25-2.00) and in the case-control study (OR = 1.38, 95% CI: 1.18-1.61). Of note, the causal relationship between fracture and dementia was not demonstrated in this meta-analysis. Conclusion People with a history of fractures are at increased risk of developing dementia. Enhanced screening and preventive management of dementia in people with a history of fractures may be beneficial.
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Affiliation(s)
| | | | | | | | - Yujie Li
- Department of Neurology, The General Hospital of Western Theater Command PLA, Chengdu, China
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Khondoker M, Macgregor A, Bachmann MO, Hornberger M, Fox C, Shepstone L. Multimorbidity pattern and risk of dementia in later life: an 11-year follow-up study using a large community cohort and linked electronic health records. J Epidemiol Community Health 2023; 77:285-292. [PMID: 36889910 DOI: 10.1136/jech-2022-220034] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 02/25/2023] [Indexed: 03/10/2023]
Abstract
BACKGROUND Several long-term chronic illnesses are known to be associated with an increased risk of dementia independently, but little is known how combinations or clusters of potentially interacting chronic conditions may influence the risk of developing dementia. METHODS 447 888 dementia-free participants of the UK Biobank cohort at baseline (2006-2010) were followed-up until 31 May 2020 with a median follow-up duration of 11.3 years to identify incident cases of dementia. Latent class analysis (LCA) was used to identify multimorbidity patterns at baseline and covariate adjusted Cox regression was used to investigate their predictive effects on the risk of developing dementia. Potential effect moderations by C reactive protein (CRP) and Apolipoprotein E (APOE) genotype were assessed via statistical interaction. RESULTS LCA identified four multimorbidity clusters representing Mental health, Cardiometabolic, Inflammatory/autoimmune and Cancer-related pathophysiology, respectively. Estimated HRs suggest that multimorbidity clusters dominated by Mental health (HR=2.12, p<0.001, 95% CI 1.88 to 2.39) and Cardiometabolic conditions (2.02, p<0.001, 1.87 to 2.19) have the highest risk of developing dementia. Risk level for the Inflammatory/autoimmune cluster was intermediate (1.56, p<0.001, 1.37 to 1.78) and that for the Cancer cluster was least pronounced (1.36, p<0.001, 1.17 to 1.57). Contrary to expectation, neither CRP nor APOE genotype was found to moderate the effects of multimorbidity clusters on the risk of dementia. CONCLUSIONS Early identification of older adults at higher risk of accumulating multimorbidity of specific pathophysiology and tailored interventions to prevent or delay the onset of such multimorbidity may help prevention of dementia.
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Affiliation(s)
| | | | - Max O Bachmann
- Norwich Medical School, University of East Anglia, Norwich, UK
| | | | - Chris Fox
- Norwich Medical School, University of East Anglia, Norwich, UK
- College of Medicine and Health, University of Exeter, Exeter, UK
| | - Lee Shepstone
- Norwich Medical School, University of East Anglia, Norwich, UK
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Sutin DAR, Luchetti M, Aschwanden D, Stephan Y, Sesker AA, Terracciano A. Sense of meaning and purpose in life and risk of incident dementia: New data and meta-analysis. Arch Gerontol Geriatr 2023; 105:104847. [PMID: 36347158 PMCID: PMC10015423 DOI: 10.1016/j.archger.2022.104847] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 10/19/2022] [Accepted: 10/22/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE A greater sense of meaning and purpose in life is associated with lower dementia risk. The present research examines meaning and incident dementia in the largest sample to date, the UK Biobank, and combines the findings with the published literature on meaning/purpose and dementia risk in a meta-analysis. METHOD Participants from the UK Biobank reported on their meaning in life in the 2016/2017 mental health assessment (N=153,445). All-cause and cause-specific dementia were derived from hospital and death records through November 2021. Cox regression was used to test the association between meaning in life and risk of incident dementia. Results from the UK Biobank were combined with published studies identified through a systematic literature review in a random-effect meta-analysis (k=8; total N=214,270). RESULTS UK Biobank participants were followed up to five years after their assessment of meaning in life; 551 participants developed dementia. For every one-point higher feeling of meaning, there was a 35% decreased risk of all-cause dementia (HR=.74, 95% CI=.67-.82, p<.001). The association was similar controlling for clinical and behavioral risk factors and was not moderated by age, sex, education, or APOE risk status. Similar associations were found for Alzheimer's disease and vascular dementia. The meta-analysis supported the protective association between meaning/purpose and lower dementia risk (HR=.76, 95% CI=.72-.79, p<.001). CONCLUSIONS The present research supports the growing literature that meaning and purpose in life have a robust association with lower risk of developing dementia. Meaning/purpose is a promising intervention target for healthier cognitive outcomes in older adulthood.
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Affiliation(s)
- Dr Angelina R Sutin
- Behavioral Sciences and Social Medicine, Florida State University College of Medicine, 1115 W. Call Street, Tallahassee, FL 32306, United States.
| | - Martina Luchetti
- Behavioral Sciences and Social Medicine, Florida State University College of Medicine, 1115 W. Call Street, Tallahassee, FL 32306, United States
| | - Damaris Aschwanden
- Behavioral Sciences and Social Medicine, Florida State University College of Medicine, 1115 W. Call Street, Tallahassee, FL 32306, United States
| | | | - Amanda A Sesker
- Behavioral Sciences and Social Medicine, Florida State University College of Medicine, 1115 W. Call Street, Tallahassee, FL 32306, United States
| | - Antonio Terracciano
- Behavioral Sciences and Social Medicine, Florida State University College of Medicine, 1115 W. Call Street, Tallahassee, FL 32306, United States
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Shang X, Roccati E, Zhu Z, Kiburg K, Wang W, Huang Y, Zhang X, Zhang X, Liu J, Tang S, Hu Y, Ge Z, Yu H, He M. Leading mediators of sex differences in the incidence of dementia in community-dwelling adults in the UK Biobank: a retrospective cohort study. Alzheimers Res Ther 2023; 15:7. [PMID: 36617573 PMCID: PMC9827665 DOI: 10.1186/s13195-022-01140-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 12/08/2022] [Indexed: 01/10/2023]
Abstract
BACKGROUND Little is known regarding whether sex assigned at birth modifies the association between several predictive factors for dementia and the risk of dementia itself. METHODS Our retrospective cohort study included 214,670 men and 214,670 women matched by age at baseline from the UK Biobank. Baseline data were collected between 2006 and 2010, and incident dementia was ascertained using hospital inpatient or death records until January 2021. Mediation analysis was tested for 133 individual factors. RESULTS Over 5,117,381 person-years of follow-up, 5928 cases of incident all-cause dementia (452 cases of young-onset dementia, 5476 cases of late-onset dementia) were documented. Hazard ratios (95% CI) for all-cause, young-onset, and late-onset dementias associated with the male sex (female as reference) were 1.23 (1.17-1.29), 1.42 (1.18-1.71), and 1.21 (1.15-1.28), respectively. Out of 133 individual factors, the strongest mediators for the association between sex and incident dementia were multimorbidity risk score (percentage explained (95% CI): 62.1% (45.2-76.6%)), apolipoprotein A in the blood (25.5% (15.2-39.4%)), creatinine in urine (24.9% (16.1-36.5%)), low-density lipoprotein cholesterol in the blood (23.2% (16.2-32.1%)), and blood lymphocyte percentage (21.1% (14.5-29.5%)). Health-related conditions (percentage (95% CI) explained: 74.4% (51.3-88.9%)) and biomarkers (83.0% (37.5-97.5%)), but not lifestyle factors combined (30.1% (20.7-41.6%)), fully mediated sex differences in incident dementia. Health-related conditions combined were a stronger mediator for late-onset (75.4% (48.6-90.8%)) than for young-onset dementia (52.3% (25.8-77.6%)), whilst lifestyle factors combined were a stronger mediator for young-onset (42.3% (19.4-69.0%)) than for late-onset dementia (26.7% (17.1-39.2%)). CONCLUSIONS Our analysis matched by age has demonstrated that men had a higher risk of all-cause, young-onset, and late-onset dementias than women. This association was fully mediated by health-related conditions or blood/urinary biomarkers and largely mediated by lifestyle factors. Our findings are important for understanding potential mechanisms of sex in dementia risk.
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Affiliation(s)
- Xianwen Shang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia.
- Department of Medicine (Royal Melbourne Hospital), University of Melbourne, Melbourne, VIC, 3050, Australia.
| | - Eddy Roccati
- Department of Medicine (Royal Melbourne Hospital), University of Melbourne, Melbourne, VIC, 3050, Australia
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, TAS, 7001, Australia
| | - Zhuoting Zhu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia
| | - Katerina Kiburg
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia
| | - Wei Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China
| | - Yu Huang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Xueli Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Xiayin Zhang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Jiahao Liu
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia
| | - Shulin Tang
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Yijun Hu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Zongyuan Ge
- Monash e-Research Center, Faculty of Engineering, Airdoc Research, Nvidia AI Technology Research Center, Monash University, Melbourne, VIC, 3800, Australia
| | - Honghua Yu
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
| | - Mingguang He
- Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
- Centre for Eye Research Australia, Melbourne, VIC, 3002, Australia.
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China.
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18
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Shang X, Zhang X, Huang Y, Zhu Z, Zhang X, Liu J, Wang W, Tang S, Yu H, Ge Z, Yang X, He M. Association of a wide range of individual chronic diseases and their multimorbidity with brain volumes in the UK Biobank: A cross-sectional study. EClinicalMedicine 2022; 47:101413. [PMID: 35518119 PMCID: PMC9065617 DOI: 10.1016/j.eclinm.2022.101413] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/27/2022] [Accepted: 04/05/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Little is known regarding associations of conventional and emerging diseases and their multimorbidity with brain volumes. METHODS This cross-sectional study included 36,647 European ancestry individuals aged 44-81 years with brain magnetic resonance imaging data from UK Biobank. Brain volumes were measured between 02 May 2014 and 31 October 2019. General linear regression models were used to associate 57 individual major diseases with brain volumes. Latent class analysis was used to identify multimorbidity patterns. A multimorbidity score for brain volumes was computed based on the estimates for individual groups of diseases. FINDINGS Out of 57 major diseases, 16 were associated with smaller volumes of total brain, 14 with smaller volumes of grey matter, and six with smaller hippocampus volumes, and four major diseases were associated with higher white matter hyperintensity (WMH) load after adjustment for all other diseases. The leading contributors to the variance of total brain volume were hypertension (R2=0·0229), dyslipidemia (0·0190), cataract (0·0176), coronary heart disease (0·0107), and diabetes (0·0077). We identified six major multimorbidity patterns and multimorbidity patterns of cardiometabolic disorders (CMD), and CMD-multiple disorders, and metabolic disorders were independently associated with smaller volumes of total brain (β (95% CI): -6·6 (-8·9, -4·3) ml, -7·3 (-10·4, -4·1) ml, and -10·4 (-13·5, -7·3) ml, respectively), grey matter (-7·1 (-8·5, -5·7) ml, -9·0 (-10·9, -7·1) ml, and -11·8 (-13·6, -9·9) ml, respectively), and higher WMH load (0·23 (0·19, 0·27), 0·25 (0·19, 0·30), and 0·33 (0·27, 0·39), respectively) after adjustment for geographic, socioeconomic, and lifestyle factors (all P-values<0·0001). The percentage of the variance of total brain volume explained by multimorbidity patterns, multimorbidity defined by the number of diseases, and multimorbidity score was 1·2%, 3·1%, and 7·2%, respectively. Associations between CMD-multiple disorders pattern, and metabolic disorders pattern and volumes of total brain, grey matter, and WMH were stronger in men than in women. Associations between multimorbidity and brain volumes were stronger in younger than in older individuals. INTERPRETATION Besides conventional diseases, we found an association between numerous emerging diseases and smaller brain volumes. CMD-related multimorbidity patterns are associated with smaller brain volumes. Men or younger adults with multimorbidity are more in need of care for promoting brain health. These findings are from an association study and will need confirmation. FUNDING The Fundamental Research Funds of the State Key Laboratory of Ophthalmology, Project of Investigation on Health Status of Employees in Financial Industry in Guangzhou, China (Z012014075), Science and Technology Program of Guangzhou, China (202,002,020,049).
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Key Words
- AD, Alzheimer’s disease
- APOE4, Apolipoprotein E ε4
- BMI, body mass index
- Brain volume
- CHD, coronary heart disease
- CI, confidence interval
- CKD, chronic kidney disease
- CMD, cardiometabolic disorders
- COPD, chronic obstructive pulmonary disease
- CVD, cardiovascular disease
- FDR, false discovery rate
- Grey matter
- Hippocampus
- Major diseases
- Moderation analysis
- Multimorbidity
- OLS, ordinary least squares
- WMH, white matter hyperintensity
- White matter hyperintensity
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Affiliation(s)
- Xianwen Shang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Centre for Eye Research Australia, The University of Melbourne, Level 7, 32 Gisborne Street, Melbourne, VIC 3002, Australia
- Corresponding authors at: Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China.
| | - Xueli Zhang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China
| | - Yu Huang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhuoting Zhu
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Centre for Eye Research Australia, The University of Melbourne, Level 7, 32 Gisborne Street, Melbourne, VIC 3002, Australia
| | - Xiayin Zhang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jiahao Liu
- Centre for Eye Research Australia, The University of Melbourne, Level 7, 32 Gisborne Street, Melbourne, VIC 3002, Australia
- Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Wei Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou 510060, China
| | - Shulin Tang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China
| | - Honghua Yu
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China
| | - Zongyuan Ge
- Monash e-Research Center, Faculty of Engineering, Airdoc Research, Nvidia AI Technology Research Center, Monash University, Melbourne, VIC 3800, Australia
| | - Xiaohong Yang
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China
| | - Mingguang He
- Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China
- Centre for Eye Research Australia, The University of Melbourne, Level 7, 32 Gisborne Street, Melbourne, VIC 3002, Australia
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou 510060, China
- Corresponding authors at: Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Rd, Yuexiu District, Guangzhou, Guangdong 510080, China.
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