An augmented aging process in brain white matter in HIV

Abstract

HIV infection is associated with augmented white matter aging, and greater brain aging is associated with worse cognitive performance in multiple domains.

The joint effect of aging and HIV infection on microstructure of white matter bundles

“…As HIVassociated neurologic damage can occur well before overt cognitive manifestations emerge (as has been demonstrated in healthily-aging individuals prior to converting to mild cognitive impairment [MCI] (Whitwell et al, 2007), as well as MCI prior to conversion to Alzheimer's disease (Ciarmiello et al, 2006), Parkinson's disease (Whitwell et al, 2007), and Huntington's disease (Horvath & Levine, 2015)), and as the pattern of HIV-related neuronal loss is not uniform, computing diffusivity metrics for a particular WM tract may be suboptimal for capturing early changes. Therefore, coupled with the current findings, prior failures to detect interactive effects may indeed be related to cohort effects (O'Connor et al, 2017) Further, these findings are in line with recent machine learning studies (Cole, Caan, et al, 2018;Cole, Ritchie, et al, 2018;Kuhn et al, 2018), as well as a histology study that employed a DNA-methylation technique to demonstrate a 0.1-9.3-year effective age increase in brain tissue in HIV+ participants (Nir et al, 2014). This accelerated aging process was hypothesized to occur via similar cellular mechanisms to those of neural aging (Jin et al, 2017).…”

“…As the HIV-infected population continues to age, understanding the synergistic effects of normal aging and HIV on brain microstructure is of ever-increasing importance. Prior neuroimaging studies showed HIV-associated degradation of the structural integrity of white matter (WM; Chang et al, 2008Chang et al, , 2011Nir et al, 2014;Seider et al, 2016;Towgood et al, 2012;Wu et al, 2006), along with associated cognitive dysfunction (Chang et al, 2011), even in patients on effective antiretroviral therapies (Kuhn et al, 2018;Wu et al, 2006). Additionally, degradation of WM fibers is an established feature of the normal aging process (Gongvatana et al, 2011;Gunning-Dixon, Brickman, Cheng, & Alexopoulos, 2009;McWhinney, Tremblay, Chevalier, Lim, & Newman, 2016;Sexton et al, 2014;Westlye et al, 2010).…”

Brain age prediction reveals aberrant brain white matter in schizophrenia and bipolar disorder: A multi-sample diffusion tensor imaging study

“…Unfortunately, due to the current study design with adults only we cannot address the maturational trajectories in the formative years. Although the application of diffusion MRI as the basis for age prediction is novel, higher gray matter brain age has been shown in several brain and mental disorders (29,53). We expand these previous findings by documenting higher DTI based white matter brain age in both SZ and BD, and, although with moderate effect sizes, we show that the effects generalize relatively well across cohorts and scanners, with only minor heterogeneity in effect sizes between cohorts.…”

Towards an optimised processing pipeline for diffusion magnetic resonance imaging data: Effects of artefact corrections on diffusion metrics and their age associations in UK Biobank

“…On the contrary, the UKB pipeline demonstrated a higher number of significant voxels for DKI metrics. Although subtle, pipeline related global and spatially varying differences in diffusion metrics will have consequences for subsequent analyses, for example, for machine‐learning‐based age prediction or diagnostic classification or prediction of clinical traits (Alnaes et al, ; Doan et al, ; Kuhn et al, ; Richard et al, ).…”