Association of a wide range of individual chronic diseases and their multimorbidity with brain volumes in the UK Biobank: A cross-sectional study. (May 2022)

• Record Type: Journal Article
• Authors: Shang, Xianwen; Zhang, Xueli; Huang, Yu; Zhu, Zhuoting; Zhang, Xiayin; Liu, Jiahao; Wang, Wei; Tang, Shulin; Yu, Honghua; Ge, Zongyuan; Yang, Xiaohong; He, Mingguang
• Is Part Of: EClinicalMedicine. Volume 47(2022)
• Publication Date: 2022-05
• Subjects: Major diseases -- Multimorbidity -- Brain volume -- Grey matter -- Hippocampus -- White matter hyperintensity -- Moderation analysis; AD Alzheimer's disease -- APOE4 Apolipoprotein E ε4 -- BMI body mass index -- 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 -- OLS ordinary least squares -- WMH white matter hyperintensity; Medicine -- Research -- Periodicals; Medical policy -- Periodicals; Clinical Medicine; Health Policy; Public Health; Medical policy; Medicine -- Research; Periodical; Electronic journals; Periodicals; 613
• DOI: 10.1016/j.eclinm.2022.101413
• Languages: English
• ISSNs: 2589-5370

Abstract

Summary: 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 (R 2 =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).