Reid, Robert I.

AbstractBackgroundThe critical‐period theory of menopausal hormone therapy (mHT) suggests that if menopausal hormone therapy begins shortly after menopause, it may have beneficial effects on brain structure and cognitive health. We investigated white matter integrity with diffusion tensor MRI (DTI) 3 years after the end of mHT trial in recently menopausal women who were randomized shortly after menopause.MethodParticipants of this study were enrolled in the Kronos Early Estrogen Prevention Study (aged 42–56 years; 5–36 months past menopause). Participants received the following treatments: 0.45 mg/d oral conjugated equine estrogen (oCEE, n=19); 50 μg/d transdermal 17β‐estradiol (tE2, n=22); or placebo (n=33) for 4 years. Oral progesterone (200 mg/d) was given to hormone therapy groups for 12 days each month. DTI was performed 3 years after the end of 4 years of hormone therapy (n=75), which corresponded to 7 years after randomization. Voxel‐based analysis was performed on DTI to evaluate fractional anisotropy (FA) and mean diffusivity (MD) differences between treatment groups (uncorrected p<0.001).ResultVoxel based analysis showed higher FA, a measure of white matter integrity, in the superior corona radiata, anterior limb of the internal capsule and splenium of the corpus callosum of participants treated with oCEE compared to placebo (p <0.001, Figure 1A). Furthermore, higher FA was observed in the superior corona radiata, anterior limb of internal capsule and thalamus in participants treated with tE2 compared to placebo (p <0.001, Figure 1B). There were no differences in FA findings between oCEE and tE2 groups, and no MD differences between treatments groups.ConclusionA relatively higher FA in a variety of white matter regions in the oCEE and tE2 groups compared to placebo suggest that mHT may have long‐term protective effects on white matter integrity. Previously, we had shown that women in the tE2 group preserved their dorsolateral prefrontal cortex volumes better than the placebo group over 7 years. Our findings suggest that the tracts that connect the dorsolateral prefrontal cortex and the thalamus such as the superior corona radiata and the anterior limb of internal capsule may particularly benefit from mHT.

AbstractBackgroundRecently, hearing loss has been identified as a promising modifiable risk factor for dementia. Several hypotheses explaining a potential underlying pathway have been proposed, including the sensory deprivation hypothesis, describing a direct causal relationship in which hearing loss leads to neuroplastic changes in the brain. Indeed, hearing loss has been associated with smaller macrostructural brain volumes, which is believed to at least partly explain the association between hearing loss and neurodegenerative disease. However, microstructural changes precede macrostructural changes. Therefore, we aimed to assess the association between hearing loss and microstructural integrity of the brain.Methods1,086 dementia‐free older adults from the Atherosclerosis Risk in Communities (ARIC) study (mean age = 75.2 [SD: 4.9], 61.4% female) underwent hearing assessment (2016‐2017) and magnetic resonance imaging (MRI) of the brain (2011‐2013). Hearing was assessed with pure‐tone audiometry. Microstructural integrity (fractional anisotropy (FA) and mean diffusivity (MD)) of multiple brain regions was determined with diffusion tensor imaging (DTI). Multivariable linear regression models were used to investigate the association between hearing loss and microstructural integrity of the lobes, temporal lobe gyri, medial temporal lobe structures and white matter (WM) tracts, adjusting for relevant confounders.ResultHearing loss was associated with lower WM microstructural integrity in the temporal lobe (difference in SD FA for moderate/severe hearing loss as compared to normal hearing: ‐0.19 [95% CI: ‐0.35, ‐0.03]; and difference in SD MD for moderate/severe hearing loss as compared to normal hearing: 0.15 [95% CI: 0.01, 0.28]). Hearing loss was associated with lower gray matter (GM) microstructure of the hippocampus, but not the amygdala. Moreover, hearing loss was associated with lower WM microstructural integrity of the limbic tracts and the uncinate fasciculus (Figure 1).ConclusionOur results demonstrate that age‐related hearing loss is associated with lower WM microstructural integrity in the temporal lobe, the limbic tracts and the uncinate fasciculus and lower GM microstructure in the hippocampus. These associations suggest that poorer hearing may affect brain regions that are important for different cognitive processes. However, the results should be interpreted with caution as this study is of a cross‐sectional design.

AbstractIntroductionAs hearing loss has been identified as an important risk factor for dementia, we aimed to assess the association between hearing loss and microstructural integrity of the brain.MethodsA total of 1086 dementia‐free participants (mean age = 75.2 [standard deviation: 4.9], 61.4% female) of the population‐based Atherosclerosis Risk in Communities (ARIC) study underwent hearing assessment (2016–2017) and magnetic resonance imaging of the brain (2011–2013). Microstructural integrity was determined with diffusion tensor imaging. Multivariable linear regression was used to investigate associations between hearing loss and microstructural integrity of different brain regions and white matter (WM) tracts.ResultsHearing loss was associated with lower WM microstructural integrity in the temporal lobe, lower gray matter integrity of the hippocampus, and with lower WM microstructural integrity of the limbic tracts and the uncinate fasciculus.ConclusionOur results demonstrate that hearing loss is indepedently associated with lower microstructural integrity in brain regions that are important for different cognitive processes.

Background Changes in white matter microstructural integrity are detectable before appearance of white matter lesions on magnetic resonance imaging as a manifestation of cerebral small‐vessel disease. The information relating poor white matter microstructural integrity to aortic stiffness, a hallmark of aging, is limited. We aimed to examine the association between aortic stiffness and white matter microstructural integrity among older adults. Methods and Results We conducted a cross‐sectional study to examine the association between aortic stiffness and white matter microstructural integrity among 1484 men and women (mean age, 76 years) at the 2011 to 2013 examination of the ARIC‐NCS (Atherosclerosis Risk in Communities Neurocognitive Study). Aortic stiffness was measured as carotid‐femoral pulse wave velocity. Cerebral white matter microstructural integrity was measured as fractional anisotropy and mean diffusivity using diffusion tensor imaging. Multivariable linear regression was used to examine the associations of carotid‐femoral pulse wave velocity with fractional anisotropy and mean diffusivity of the overall cerebrum and at regions of interest. Each 1‐m/s higher carotid‐femoral pulse wave velocity was associated with lower overall fractional anisotropy (β=−0.03; 95% CI , −0.05 to −0.02) and higher overall mean diffusivity (β=0.03; 95% CI , 0.02–0.04). High carotid‐femoral pulse wave velocity (upper 25th percentile) was associated with lower fractional anisotropy (β=−0.40; 95% CI , −0.61 to −0.20) and higher overall mean diffusivity (β=0.27; 95% CI , 0.10–0.43). Similar associations were observed at individual regions of interest. Conclusions High aortic stiffness is associated with low cerebral white matter microstructural integrity among older adults. Aortic stiffness may serve as a target for the prevention of poor cerebral white matter microstructural integrity.

ObjectiveTo investigate the multifactorial processes underlying cognitive aging based on the hypothesis that multiple causal pathways and mechanisms (amyloid, vascular, and resilience) influence longitudinal cognitive decline in each individual through worsening brain health.MethodsWe identified 1,230 elderly subjects (aged ≥50 years) with an average of 4.9 years of clinical follow‐up and with amyloid positron emission tomography, diffusion tensor imaging, and structural magnetic resonance imaging scans from the population‐based Mayo Clinic Study of Aging. We examined imaging markers of amyloid and brain health (white matter microstructural integrity and cortical thinning), systemic vascular health preceding the imaging markers, and early to midlife intellectual enrichment to predict longitudinal cognitive trajectories. We used latent growth curve models for modeling longitudinal cognitive decline.ResultsAll the pathways (amyloid, vascular, resilience) converged through their effects on cortical thinning and worsening cognition and together explained patterns in cognitive decline. Resilience and vascular pathways (aging process, sex differences, education/occupation, and systemic vascular health) had significant impact on white matter microstructural integrity. Education/occupation levels contributed to white matter integrity through systemic vascular health. Worsening white matter integrity contributed to significant cortical thinning and subsequently longitudinal cognitive decline. Baseline amyloidosis contributed to a significant proportion of cognitive decline that accelerated with longer follow‐up times, and its primary impact was through cortical thinning.InterpretationWe developed an integrated framework to help explain the dynamic and complex process of cognitive aging by considering key causal pathways. Such an approach is important for both better comprehension of cognitive aging processes and will aid in the development of successful intervention strategies. ANN NEUROL 2019;86:866–877

Abstract Agrammatic aphasia affects grammatical language production and can result from a neurodegenerative disease. Although it typically presents with concomitant apraxia of speech, this is not always the case. Little is known about the clinical course and imaging features of patients that present with agrammatism in the absence of apraxia of speech, which we will refer to as progressive agrammatic aphasia. We aimed to make a detailed description of the longitudinal clinical, linguistic, and neuroimaging features of a cohort of 11 patients with progressive agrammatic aphasia to provide a complete picture of this syndrome. All patients underwent detailed speech and language, neurological and neuropsychological assessments, 3 T structural and diffusion tensor imaging MRI, 18F-fluorodeoxyglucose and Pittsburgh compound B PET. The 11 patients were matched by age and gender to 22 patients who had mixed apraxia of speech and agrammatism. The progressive agrammatic aphasia patients performed abnormally on tests of language, general cognition, executive function, and functional ability at baseline and declined in these measures over time. Only two patients eventually developed apraxia of speech, while parkinsonism was absent-to-mild throughout all visits for all patients. When compared to the patients with mixed apraxia of speech and agrammatism, the patients with progressive agrammatic aphasia performed better on tests of motor speech and parkinsonism but more poorly, and declined faster over time, on tests of general aphasia severity, agrammatism, and naming. The patients with progressive agrammatic aphasia also showed different neuroimaging abnormalities, with greater atrophy, hypometabolism and white matter tract degeneration in the prefrontal and anterior temporal lobes compared to patients with mixed apraxia of speech and agrammatism. These differences were more pronounced as the disease progressed. These results demonstrate that progressive agrammatic aphasia has a different clinical disease course and different underlying neuroanatomical abnormalities than patients with the more common syndrome of mixed agrammatism and apraxia of speech. This supports the distinction of progressive agrammatic aphasia and has implications for the classification of patients with agrammatic aphasia.