Age-related networks of regional covariance in MRI gray matter: reproducible multivariate patterns in healthy aging

Healthy aging is associated with brain volume reductions that involve the frontal cortex, but also affect other brain regions. We sought to identify an age-related network pattern of MRI gray matter using a multivariate statistical model of regional covariance, the Scaled Subprofile Model (SSM) with voxel based morphometry (VBM) in 29 healthy adults, 23-84 years of age (Group 1). In addition, we evaluated the reproducibility of the age-related gray matter pattern derived from a prior SSM VBM study of 26 healthy adults, 22-77 years of age (Group 2; Alexander et al., 2006) in relation to the current sample and tested the ability of the network analysis to extract an age-related pattern from both cohorts combined. The SSM VBM analysis of Group 1 identified a regional pattern of gray matter atrophy associated with healthy aging (R(2)=0.64, p\u3c0.000001) that included extensive reductions in bilateral dorsolateral and medial frontal, anterior cingulate, insula/perisylvian, precuneus, parietotemporal, and caudate regions with areas of relative preservation in bilateral cerebellum, thalamus, putamen, mid cingulate, and temporal pole regions. The age-related SSM VBM gray matter pattern, previously reported for Group 2, was highly expressed in Group 1 (R(2)=0.52, p\u3c0.00002). SSM analysis of the combined cohorts extracted a common age-related pattern of gray matter showing reductions involving bilateral medial frontal, insula/perisylvian, anterior cingulate and, to a lesser extent, bilateral dorsolateral prefrontal, lateral temporal, parietal, and caudate brain regions with relative preservation in bilateral cerebellum, temporal pole, and right thalamic regions. The results suggest that healthy aging is associated with a regionally distributed pattern of gray matter atrophy that has reproducible regional features. Whereas the network patterns of atrophy included parietal, temporal, and subcortical regions, involvement of the frontal brain regions showed the most consistently extensive and reliable reductions across samples. Network analysis with SSM VBM can help detect reproducible age-related MRI patterns, assisting efforts in the study of healthy and pathological aging

Gray matter network associated with risk for Alzheimer\u27s disease in young to middle-aged adults

The apolipoprotein E (APOE) ε4 allele increases the risk for late-onset Alzheimer\u27s disease (AD) and age-related cognitive decline. We investigated whether ε4 carriers show reductions in gray matter volume compared with ε4 non-carriers decades before the potential onset of AD dementia or healthy cognitive aging. Fourteen cognitively normal ε4 carriers, aged 26 to 45 years, were compared with 10 age-matched, ε4 non-carriers using T1-weighted volumetric magnetic resonance imaging (MRI) scans. All had reported first- or second-degree family histories of dementia. Group differences in gray matter were tested using voxel-based morphometry (VBM) and a multivariate model of regional covariance, the Scaled Subprofile Model (SSM). A combination of the first two SSM MRI gray matter patterns distinguished the APOE ε4 carriers from non-carriers. This combined pattern showed gray matter reductions in bilateral dorsolateral and medial frontal, anterior cingulate, parietal, and lateral temporal cortices with covarying relative increases in cerebellum, occipital, fusiform, and hippocampal regions. With these gray matter differences occurring decades before the potential onset of dementia or cognitive aging, the results suggest longstanding, gene-associated differences in brain morphology that may lead to preferential vulnerability for the later effects of late-onset AD or healthy brain aging

Blood Pressure Control in Aging Predicts Cerebral Atrophy Related to Small-Vessel White Matter Lesions

Cerebral small-vessel damage manifests as white matter hyperintensities and cerebral atrophy on brain MRI and is associated with aging, cognitive decline and dementia. We sought to examine the interrelationship of these imaging biomarkers and the influence of hypertension in older individuals. We used a multivariate spatial covariance neuroimaging technique to localize the effects of white matter lesion load on regional gray matter volume and assessed the role of blood pressure control, age and education on this relationship. Using a case-control design matching for age, gender, and educational attainment we selected 64 participants with normal blood pressure, controlled hypertension or uncontrolled hypertension from the Northern Manhattan Study cohort. We applied gray matter voxel-based morphometry with the scaled subprofile model to (1) identify regional covariance patterns of gray matter volume differences associated with white matter lesion load, (2) compare this relationship across blood pressure groups, and (3) relate it to cognitive performance. In this group of participants aged 60–86 years, we identified a pattern of reduced gray matter volume associated with white matter lesion load in bilateral temporal-parietal regions with relative preservation of volume in the basal forebrain, thalami and cingulate cortex. This pattern was expressed most in the uncontrolled hypertension group and least in the normotensives, but was also more evident in older and more educated individuals. Expression of this pattern was associated with worse performance in executive function and memory. In summary, white matter lesions from small-vessel disease are associated with a regional pattern of gray matter atrophy that is mitigated by blood pressure control, exacerbated by aging, and associated with cognitive performance

Age-Related Regional Network Covariance of Magnetic Resonance Imaging Gray Matter in the Rat

Healthy human aging has been associated with brain atrophy in prefrontal and selective temporal regions, but reductions in other brain areas have been observed. We previously found regional covariance patterns of gray matter with magnetic resonance imaging (MRI) in healthy humans and rhesus macaques, using multivariate network Scaled Subprofile Model (SSM) analysis and voxel-based morphometry (VBM), supporting aging effects including in prefrontal and temporal cortices. This approach has yet to be applied to neuroimaging in rodent models of aging. We investigated 7.0T MRI gray matter covariance in 10 young and 10 aged adult male Fischer 344 rats to identify, using SSM VBM, the age-related regional network gray matter covariance pattern in the rodent. SSM VBM identified a regional pattern that distinguished young from aged rats, characterized by reductions in prefrontal, temporal association/perirhinal, and cerebellar areas with relative increases in somatosensory, thalamic, midbrain, and hippocampal regions. Greater expression of the age-related MRI gray matter pattern was associated with poorer spatial learning in the age groups combined. Aging in the rat is characterized by a regional network pattern of gray matter reductions corresponding to aging effects previously observed in humans and non-human primates. SSM MRI network analyses can advance translational aging neuroscience research, extending from human to small animal models, with potential for evaluating mechanisms and interventions for cognitive aging.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]