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AbstractAmong individuals with dementia with Lewy bodies, pathologic correlates of clinical course include the presence and extent of coexisting Alzheimer’s pathology and the presence of transitional or diffuse Lewy body disease. The objectives of this study are to determine (i) whether 18F-fluorodeoxyglucose PET signature patterns of dementia with Lewy bodies are associated with the extent of coexisting Alzheimer’s pathology and the presence of transitional or diffuse Lewy body disease and (ii) whether these 18F-fluorodeoxyglucose pattern(s) are associated with clinical course in dementia with Lewy bodies. Two groups of participants were included: a pathology-confirmed subset with Lewy body disease (n = 34) and a clinically diagnosed group of dementia with Lewy bodies (n = 87). A subset of the clinically diagnosed group was followed longitudinally (n = 51). We evaluated whether 18F-fluorodeoxyglucose PET features of dementia with Lewy bodies (higher cingulate island sign ratio and greater occipital hypometabolism) varied by Lewy body disease subtype (transitional versus diffuse) and Braak neurofibrillary tangle stage. We investigated whether the PET features were associated with the clinical trajectories by performing regression models predicting Clinical Dementia Rating Scale Sum of Boxes. Among autopsied participants, there was no difference in cingulate island sign or occipital hypometabolism by Lewy body disease type, but those with a lower Braak tangle stage had a higher cingulate island sign ratio compared to those with a higher Braak tangle stage. Among the clinically diagnosed dementia with Lewy bodies participants, a higher cingulate island ratio was associated with better cognitive scores at baseline and longitudinally. A higher 18F-fluorodeoxyglucose PET cingulate island sign ratio was associated with lower Braak tangle stage at autopsy, predicted a better clinical trajectory in dementia with Lewy body patients and may allow for improved prognostication of the clinical course in this disease.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

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.

Background: Cerebrovascular disease is often the consequence of cardiac disease. Our aim was to examine associations of biomarkers of cardiovascular disease, high sensitivity troponin T (hs-cTnT), NT-proBNP, and galectin-3, with cerebrovascular signs: lacunar infarcts, lobar and subcortical microhemorrhages, cortical infarcts, and white matter hyperintensity (WMH) volume. We also examined total cortical and Alzheimer’s Disease (AD) signature region volumes. Methods: We conducted a cross-sectional analysis of 1748 ARIC participants from the 2011-2013 exam who had biomarker measurements, completed a brain MRI, and did not have a clinical history of stroke. We used linear regression to model brain volumes, modeled as Z scores, and logistic regression for all other outcomes; biomarkers were log transformed. We repeated analyses excluding persons with coronary heart disease, atrial fibrillation, and heart failure. Results: The mean age of participants was 76, 62% were female, and 21% were Black. All biomarkers were associated with total cortical volume. Each standard deviation increase in log hs-cTnT was associated with lower total cortical volume (adjusted beta = -0.08, 95% CI: -0.12, -0.05); results for the other biomarkers were similar (Figure). All biomarkers were associated with lobar microhemorrhages. Hs-cTnT and NT-proBNP were associated with WMH volume, but galectin-3 was not. No biomarker was associated with subcortical microhemorrhages or cortical infarcts. Results were similar in persons without coronary heart disease, atrial fibrillation, or heart failure (conditions associated with cerebral thromboembolism). Conclusions: In persons free of clinical cardiovascular disease, biomarkers of cardiac stretch, strain, and fibrosis were associated cerebral small vessel disease and reduced cortical volume, but not in a specific pattern suggestive of AD pathogenesis. This suggests subclinical vascular insults affect brain structure through mixed pathogenic processes.

ObjectiveTo investigate β‐amyloid and tau depositions using Pittsburgh compound B (PiB) positron emission tomography (PET) and AV1451 tau PET imaging in aging multiple sclerosis (MS) patients.MethodsPatients with MS (n = 16) and controls (n = 80) matched for age, sex, andAPOEε4 status from the population‐based Mayo Clinic Study of Aging who underwent PiB PET imaging were studied. Of these individuals, 12 patients with MS and 60 matching controls also underwent AV1451 tau PET. Cortical PiB and AV1451 standard uptake value ratios (SUVrs) from the entire cortex and previously determined Alzheimer disease (AD) signature regions in the same population were calculated for group comparisons and testing for associations with age.ResultsAD signature PiB SUVr (odds ratio [OR] [95% confidence interval (CI)] = 0.52 [0.27–0.98],p= 0.044), total cortical PiB SUVr (OR [95% CI] = 0.52 [0.28–0.99],p= 0.048), and the frequency of abnormal PiB SUVrs (OR [95% CI] = 0.10 [0.01–0.90],p= 0.040) were lower in MS than controls. Although AD‐signature and total cortical AV1451 SUVrs were not different between the groups, the frequency of abnormal AV1451 SUVrs was higher (OR [95% CI] = 10.65 [1.10–103.35],p= 0.041) in MS than controls. The association of AD signature PiB SUVr with age was steeper in the controls compared to patients with MS (estimate [95% CI] = −0.14 [−0.023 to −0.006],p= 0.002). Similarly, the association of total cortical PiB SUVr with age was steeper in the controls compared to patients with MS (estimate [95% CI] = −0.13 [−0.021 to −0.005],p= 0.002). There was no difference in the association of AV1451 SUVr findings with age between the MS patients and controls.InterpretationAlthough both β‐amyloid and tau are biomarkers of cognitive aging and AD, cortical β‐amyloid deposition was lower in MS than age‐matched controls, suggesting that some aspect of MS pathobiology retards the accumulation of β‐amyloid but not the accumulation of tau.ANN NEUROL 2020;87:556–567

Background: Transactive response DNA-binding protein of 43 kDa (TDP-43) is associated with hippocampal atrophy in Alzheimer’s disease (AD), but whether the association is modified by other factors is unknown. Objective: To evaluate whether the associations between TDP-43 and hippocampal volume and atrophy rate are affected by age, gender, apolipoprotein E ( APOE) ɛ4, Lewy bodies (LBs), amyloid-β (Aβ), or Braak neurofibrillary tangle (NFT) stage. Methods: In this longitudinal neuroimaging-clinicopathological study of 468 cases with AD neuropathological changes (Aβ-positive) that had completed antemortem head MRI, we investigated how age, gender, APOE ɛ4, presence of LBs, Aβ, TDP-43, and Braak NFT stages are associated with hippocampal volumes and rates of atrophy over time. We included field strength in the models since our cohort included 1.5T and 3T scans. We then determined whether the associations between hippocampal atrophy and TDP-43 are modified by these factors using mixed effects models. Results: Older age, female gender, APOE ɛ4, higher field strength, higher TDP-43, and Braak NFT stages were associated with smaller hippocampi. Rate of atrophy was greater with higher TDP-43 and Braak NFT stage, but lower in older patients. The association of TDP-43 with greater rate of atrophy was enhanced in APOE ɛ4 carriers ( p = 0.04). Conclusion: Neurodegenerative effects of TDP-43 seem to be independent of most factors except perhaps APOE in cases with AD neuropathological changes. TDP-43 and tau appear to behave independently of one another.