AbstractBackgroundThe incidence of dementia in India is 14%, and its prevalence doubles with every five‐year increase in age. Given the lack of ethnic diversity in most brain research to date, it is valuable to study cohorts with diverse genetic and environmental backgrounds, to identify predictors of health and disease that can be generalized to other ethnic groups than the commonly studied populations of European ancestry. To address this gap in the literature, we modeled factors that affect aging patterns in the brain’s white matter in individuals with Indian ancestry using advanced diffusion‐weighted MRI (dMRI).MethodCross‐sectional dMRI data from 123 individuals (males, n=78; females, n=45) of self‐reported Indian ancestry (born in India: 44%; mean age: 60.1±8.3 SD, range: 45‐80) from the UK Biobank were analyzed using diffusion tensor imaging (DTI), the tensor distribution function (TDF), neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator MRI (MAPMRI). Main effects of age, sex, and age‐by‐sex interaction were investigated to characterize trajectories in whole‐brain white matter averages and the corpus callosum (CC), parcellated using the JHU‐ICBM atlas, covarying for years of education, waist/hip ratio, population structure (Figure 1) and the Townsend index. Normative lifespan charts were created to visualize white matter aging trajectories for the major diffusivity metrics.ResultNormative centile curves (Figures 2‐3) show, with increasing age, declining white matter integrity, increased diffusivity, lower white matter density and diffusion restriction at the whole‐brain level and CC (Table 1; Figure 4). There was no detectable effect of sex, nor age‐by‐sex interaction, across whole‐brain metrics. In the CC, a steeper aging trajectory, evidenced by more pronounced white matter changes, was observed in males relative to females (Table 1; Figure 5).ConclusionUsing advanced dMRI modeling, we report diffuse white matter changes with respect to age in a subsample of UK Biobank individuals of self‐reported Indian ancestry. Future studies should include larger sample sizes, comparisons with Indian ancestry individuals residing in India, consider vascular factors, and examine genotype interactions (e.g., with apolipoprotein E genotype), to further characterize risk factors and better understand brain aging in diverse populations with varied genetic and environmental backgrounds.