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

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).

Keywords: 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.

Figure 1

Age and volumes of total brain, grey matter, hippocampus, and white matter hyperintensity; Pannels A, B, C, and D show the results for total brain, grey matter, hippocampus, and white matter hyperintensity, respectively. The splines curve method was used to smooth the relationship between age and brain volumes. Blue lines refer to the fitted spline curves and grey ribbons refer to confidence intervals for the fitted lines.

Figure 2

Associations of individual major diseases with total brain volume; CI, confidence interval; COPD, chronic obstructive pulmonary disease; Coefficients for total brain volume associated with individual diseases were estimated using general linear regression models. The raw P-values and R² for those diseases with significant associations with total brain volume are present in this figure. Model 1 was the unadjusted model; Model 2 was adjusted for age, gender, apolipoprotein E ε4, education, income, smoking, physical acidity, alcohol consumption, sleep duration, and diet; Model 3 was adjusted for Model 2 plus all other diseases for each disease. Horizontal lines indicate the ranges of the 95% CIs and the vertical dash lines indicate the mean of 0·0.

Figure 3

Interaction between multimorbidity patterns and gender for brain volume; CI, confidence interval; CMD, cardiometabolic disorder.; General linear regression models were used to examine associations between multimorbidity patterns and brain volumes stratified by gender. Analysis was adjusted for age, apolipoprotein E ε4, education, income, diet, smoking, physical acidity, alcohol consumption, and sleep duration. Horizontal lines indicate the ranges of the 95% CIs and the vertical dash lines indicate the mean of 0·0. *Indicates significant interaction.