Bio-psycho-social factors’ associations with brain age: a large-scale UK Biobank diffusion study of 35,749 participants

Abstract

Brain age refers to age predicted by brain features. Brain age has previously been associated with various health and disease outcomes and suggested as a potential biomarker of general health. Few previous studies have systematically assessed brain age variability derived from single and multi-shell diffusion magnetic resonance imaging data. Here, we present multivariate models of brain age derived from various diffusion approaches and how they relate to bio-psycho-social variables within the domains of sociodemographic, cognitive, life-satisfaction, as well as health and lifestyle factors in midlife to old age (N = 35,749, 44.6 to 82.8 years of age). Bio-psycho-social factors could uniquely explain only a small proportion of the brain age variance. We observed a similar pattern across diffusion approaches. We consistently identified bio-psycho-social associations of interest across models. Waist-to-hip ratio, diabetes, hypertension, smoking, matrix puzzles solving, and job and health satisfaction and perception were associated with brain age. At the same time, sex and ethnicity showed large variability in their predictor strengths. As expected, chronological age contributed the strongest to explaining variability in brain age. Our results show that brain age cannot be sufficiently explained by bio-psycho-social variables alone. However, the observed associations suggest to adjust for sex, ethnicity, cognitive factors, as well as health and lifestyle factors.

Brain asymmetries from mid- to late life and hemispheric brain age

“…Second, body and brain ageing trajectories differ between sexes, for example, outlined by sex-dependent importance of cardiometabolic risk factors 43 . Hence, the tendency of males' predicted brain age being lower using T 1 -weighted and multimodal in contrast to diffusion-derived brain ages, with these trends reversed in females, might also reflect stronger brain age associations with cardiometabolic risk factors in males (Supplementary Figure 7), which have been demonstrated earlier for WM features and WM brain age 38,39 . HBA allows to assess the structural integrity of each hemisphere individually, and to set brain ages from the two hemispheres in relationship to each other providing a general marker of asymmetry.…”

“…We furthermore tested whether there was an effect of hemisphere (Hypothesis 2) and handedness (Hypothesis 3) on brain age predictions. Exploratory analyses included (a) revealing hemispheric differences between GM and WM features, (b) examining LI associations with age, including the LI of the brain features as well as left and right brain ages, and (c) testing the consistency of brain age-covariate associations (specifically, health-and-lifestyle factors, as these were previously associated with brain age 20,26,[38][39][40][41] ).…”

Brain age as a biomarker for pathological versus healthy ageing – a REMEMBER study

“…Accordingly, the potential impact of a number of non-measured confounders, including demographic factors (e.g. ethnicity) [12], psychological factors (e.g. mental health conditions, stress levels, and emotional well-being), other lifestyle factors (e.g.…”

“…These models estimate an individual's 'brain age' based on the structural variations and alterations in different regions of the brain, which can be interpreted as a neuroimaging-driven marker of brain health. As brain age is sensitive to lifestyle-and health-related factors [12], it could serve as a (secondary) reliable objective metric, either parallel to other measures of ageing, such as physiological (incl. ECGs, EEGs, imaging for tumor detection and lesion identification, blood tests (e.g.…”

Considerations on brain age predictions from repeatedly sampled data across time

“…Brain age becomes particularly interesting when assuming that lifespan changes in the brain follow normative patterns and that deviations from such patterns might be indicative of disease or disease development (Marquand et al., 2019; Kaufmann et al., 2019). An elevated predicted compared with chronological age in adults may be indicative of psychiatric, neurodegenerative, and neurological disorders (Kaufmann et al., 2019) and poorer health, for example measured by various cardiometabolic risk factors (Beck et al., 2022; Korbmacher et al., 2022). Hence, brain age is a promising developing biomarker of general brain health (Franke & Gaser, 2019).…”