Regular articleSuperficial white matter as a novel substrate of age-related cognitive decline
Introduction
Normal aging is accompanied by continuous decline in cognitive abilities (Bishop et al., 2010), which may in part be caused by disruption in brain connectivity (Madden et al., 2009). In recent years, diffusion tensor imaging (DTI) studies have shed light on white matter microstructural abnormalities associated with aging (Bennett et al., 2010, Salat et al., 2005, Voineskos et al., 2012, Westlye et al., 2010). DTI exploits random translational motion of water molecules to probe microarchitectural properties of tissues in vivo (Assaf and Pasternak, 2008). Fractional anisotropy (FA), derived from the diffusion tensor model, indexes directionality of water diffusion. FA has been used as a sensitive marker of white matter integrity in aging and other conditions (Ciccarelli et al., 2008).
Almost all DTI studies to date examining cognitive aging have focused on the deep white matter (DWM) tracts that connect distant brain regions (Davis et al., 2009, Voineskos et al., 2012, Ziegler et al., 2010). In contrast, to our knowledge, only one published study has explored the relationship of superficial white matter (SWM) in vivo with age (Phillips et al., 2013). SWM fibers rest just beneath the cortex and mediate local connectivity between adjacent cortical gyri in the form of U-fibers or as longer intralobar fibers (Catani et al., 2012, Yeterian et al., 2012). These superficially located structures were first described in the 19th century (Meynert, 1872). However, their functional and neuropsychological correlates in humans remain largely unknown. In particular, the extent to which SWM microstructural integrity, relative to that of DWM, contributes to age-related cognitive decline is also unknown.
Although recent advances in DTI-based tractography methods have improved the capability to map DWM long-range brain connections in the human brain (Jbabdi and Behrens, 2013, Voineskos et al., 2009), group-wise comparisons of SWM structures is difficult with tractography because of high interindividual variability (Oishi et al., 2008). To overcome this limitation we designed a 2-step method that augments probabilistic tractography of SWM via tract-based spatial statistics (TBSS) (Smith et al., 2006). This method permits specific voxel-wise examination of SWM tracts across the brain and enhances between-subject registration of these tracts. Using this approach in a sample of healthy individuals across the adult lifespan, we aimed to: (1) assess the relationship between age and SWM-FA (and other DTI metrics); and (2) determine the contribution of SWM-FA (relative to DWM-FA) to cognitive performance. We hypothesized that we would find (1) widespread age-related SWM-FA decline and (2) regionally specific relationships between SWM microarchitecture and cognitive performance.
Section snippets
Study participants
One hundred forty-one healthy participants across the adult lifespan (18–86 years of age; 66 female; 75 male) were recruited at the Centre for Addiction and Mental Health n Toronto, Canada, via referrals, study registries, and advertisements. All participants completed the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Edition IV Disorders, the Mini Mental Status examination, and a urine toxicology screen. All participants were fluent English speakers.
SWM microstructure and aging
Significant linear age-related decline of FA values was observed in 83.5% of SWM voxels (PFWE < 0.01, Fig. 2). Probabilistic tractography seeded from the largest clusters that demonstrated the most prominent effects of age on FA (>100 voxels, thresholded at t > 6.0) revealed 7 independent SWM tracts (Fig. 3). Two of these SWM tracts were located adjacent to the left and right dorsolateral prefrontal cortices; another tract was in right orbitofrontal cortex, whereas the remaining 4 tracts were
Discussion
To our knowledge, this is the first study that has comprehensively evaluated age-related changes in SWM-FA and the contribution of SWM-FA to age-related cognitive decline. First, we observed broad age-related decline in SWM-FA across the adult lifespan at the voxel-wise level. Then, we demonstrated that SWM-FA predicts performance in cognitive/behavioral tasks involving visuomotor coordination, processing speed, and motor speed across the adult lifespan, after accounting for the effects of age.
Disclosure statement
Conflict of Interest: Within the past 5 years, B.H.M. has received travel support from Roche. All other authors declare no conflicts of interest. A.N.V. had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Acknowledgements
This work was supported by grants from the Canadian Institutes of Health Research (Clinician Scientist Award: A.N.V.; operating grant: B.H.M.), the National Institute of Mental Health (A.N.V., R01MH099167 and R01MH102324), NARSAD (A.N.V., T.K.R.), Ontario Mental Health Foundation (A.N.V.), the Centre for Addiction and Mental Health (CAMH) Fellowship Award 2014 (A.N.), and the CAMH Foundation through the Kimel Family, Koerner New Scientist Award, and Paul E. Garfinkel New Investigator Catalyst
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2023, Brain ResearchCitation Excerpt :Declines in FA were concurrent with increases in RD and AD in the lateral prefrontal regions, while callosal and cingulate WM experienced an FA decline and RD increase without significant effects on AD. Nazeri et al. showed similar results, with strong linear and non-linear declines in FA occurring in prefrontal superficial WM with age, particularly in the MOFC and MPFC (Nazeri et al., 2015). The study also found that there is a significant relationship between WM FA and frontal surface area, demonstrating that brain size, or ICV, may influence FA values.