Rowe, C. C. | Search bioRxiv

bioRxiv2022

A snapshot of brain and cognition in healthy mid-life and older adults

Deficits in memory are seen as a canonical sign of ageing and a prodrome to dementia in older adults. However, the nature of cognitive and brain changes across a wider aperture of adulthood is not well known. We quantify the relationship between cognitive function and brain morphology from mid-life to older adulthood, and the influence of age, sex, amyloid and genetic risk for dementia. We analyzed three observational cohorts (PISA, AIBL, ADNI) with cognitive, genetic and neuroimaging measures comprising a total of 1570 healthy mid-life and older adults (mean age 72, range 49-90 years, 1330 males) and 1365 age- and sex-matched adults with mild cognitive impairment or Alzheimers disease. Among healthy adults, we find robust modes of co-variation between regional sulcal width and multidomain cognitive function that change from mid-life to the older age range. The most prominent cortical changes in mid-life are predominantly associated with changes in executive functions, whereas they are most strongly associated with poorer memory function in older age. These cognitive changes are accompanied by an age-dependent pattern of sulcal widening. Amyloid exerts a weak, but significant, influence on cognition, but not on sulcal width. The APOE {varepsilon}4 allele also exerts a weak influence on cognition, but only significantly in the (larger and older) AIBL cohort. These findings provide new insights into brain and cognition in mid-life and older adults, suggesting that cognitive screening in mid-life cohorts should encompass executive functions as well as memory.

neuroscience↗

bioRxiv2019

In vivo microstructural heterogeneity of white matter lesions in Alzheimer’s disease using tissue compositional analysis of diffusion MRI data

White matter hyperintensities (WMH) are commonly observed in elderly individuals, and are typically more prevalent in Alzheimers disease subjects than in healthy subjects. These lesions can be identified on fluid attenuated inversion recovery (FLAIR) MRI, on which they are hyperintense compared to their surroundings. These MRI-visible lesions appear homogeneously hyperintense despite known heterogeneity in their pathological underpinnings, and are commonly regarded as surrogate markers of small vessel disease in in vivo studies. Consequently, the extent to which these lesions contribute to Alzheimers disease remains unclear, likely due to the somewhat limited way in which these lesions are assessed in vivo. Diffusion MRI is sensitive to white matter microstructure, and might thus be used to investigate microstructural changes within WMH. In this study, we applied a method called single-shell 3-tissue constrained spherical deconvolution, which models white matter microstructure while also accounting for other tissue compartments, to investigate WMH in vivo. Diffusion MRI data and FLAIR images were obtained from Alzheimers disease (n = 48) and healthy elderly control (n = 94) subjects from the Australian Imaging, Biomarkers and Lifestyle study of ageing. WMH were automatically segmented and classified as periventricular or deep lesions from FLAIR images based on their continuity with the lateral ventricles, and the 3-tissue profile of different classes of WMH was characterised by three metrics, which together characterised the relative tissue profile in terms of the white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our findings revealed that periventricular and deep lesion classes could be distinguished from one another, and from normal-appearing white matter based on their 3-tissue profile, with substantially higher free water content in periventricular lesions than deep. Given the higher lesion load of periventricular lesions in Alzheimers disease patients, the 3-tissue profile of these WMH could be interpreted as reflecting the more deleterious pathological underpinnings that are associated with disease. However, when alternatively classifying lesion sub-regions in terms of distance contours from the ventricles to account for potential heterogeneity within confluent lesions, we found that the highest fluid content was present in lesion areas most proximal to the ventricles, which were common to both Alzheimers disease subjects and healthy controls. We argue that whatever classification scheme is used when investigating WMH, failure to account for heterogeneity within lesions may result in classification-scheme dependent conclusions. Future studies of WMH in Alzheimers Disease would benefit from inclusion of microstructural information when characterising lesions.

neuroscience↗