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The medial temporal lobe (MTL) is a hotspot for neuropathology, and measurements of MTL atrophy are often used as a biomarker for cognitive decline associated with neurodegenerative disease. Due to the aggregation of multiple proteinopathies in this region, the specific relationship of MTL atrophy to distinct neuropathologies is not well understood. Here, we develop two quantitative algorithms using deep learning to measure phosphorylated tau (p-tau) and TDP-43 (pTDP-43) pathology, which are both known to accumulate in the MTL and are associated with MTL neurodegeneration. We focus on these pathologies in the context of Alzheimer's disease (AD) and limbic predominant age-related TDP-43 encephalopathy (LATE) and apply our deep learning algorithms to distinct histology sections, on which MTL subregions were digitally annotated. We demonstrate that both quantitative pathology measures show high agreement with expert visual ratings of pathology and discriminate well between pathology stages. In 140 cases with antemortem MR imaging, we compare the association of semi-quantitative and quantitative postmortem measures of these pathologies in the hippocampus with in vivo structural measures of the MTL and its subregions. We find widespread associations of p-tau pathology with MTL subregional structural measures, whereas pTDP-43 pathology had more limited associations with the hippocampus and entorhinal cortex. Quantitative measurements of p-tau pathology resulted in a significantly better model of antemortem structural measures than semi-quantitative ratings and showed strong associations with cortical thickness and volume. By providing a more granular measure of pathology, the quantitative p-tau measures also showed a significant negative association with structure in a severe AD subgroup where semi-quantitative ratings displayed a ceiling effect. Our findings demonstrate the advantages of using quantitative neuropathology to understand the relationship of pathology to structure, particularly for p-tau, and motivate the use of quantitative pathology measurements in future studies.

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In behavioral-variant frontotemporal degeneration (bvFTD) and amyotrophic lateral sclerosis (ALS), the presence of secondary motor or cognitive-behavioral symptoms, respectively, is associated with shorter survival. However, factors influencing the risk and hazard of secondary symptom development remain largely unexplored. We performed a retrospective evaluation of the entire disease course of individuals with amyotrophic lateral sclerosis (n=172) and behavioral-variant frontotemporal degeneration (n=69). Only individuals who had neuropathological confirmation of a TDP-43 proteinopathy at autopsy or had a C9orf72 repeat expansion were included for analysis. We examined the odds and hazard of secondary symptom development and assessed whether they were modified by the presence of a C9orf72 repeat expansion or initial clinical syndrome. Binary logistic regression and Cox proportional hazard analyses revealed increased odds (OR=4.25 [1.97-9.14]; p<0.001) and an increased hazard (HR= 4.77 [2.33-9.79], p<0.001) for developing secondary symptoms in C9orf72 expansion carriers compared to noncarriers. Initial clinical syndrome (bvFTD or ALS), age at symptom onset, and sex were not associated with development of secondary motor or cognitive-behavioral symptoms. These findings highlight the need for clinician vigilance to detect the onset of secondary motor symptoms and cognitive-behavioral in patients carrying a C9orf72 repeat expansion, regardless of initial clinical syndrome, and may warrant dual referrals between cognitive and neuromuscular clinics in these cases.

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Introduction: SuperAgers are individuals over age 80 with superior episodic memory, at a level consistent with individuals 20 to 30 years their junior and who seem to show resistance to age-related neurofibrillary degeneration. Here we examine whether low genetic risk for Alzheimer's disease (AD) contributes to SuperAgers' unusually high episodic memory performance in advanced age. Methods: The AD polygenic hazard score (PHS) was calculated for each SuperAger and cognitively normal participant and compared between groups. Results: A total of 37 SuperAgers (73% female, mean [standard deviation] 82.7 [2.8] years old) and 35 controls (54% female, 83.7 [4.3] years old) were included. There was no significant difference in the AD PHS between SuperAgers and cognitively normal controls. Discussion: Unusually successful cognitive aging cannot be simply explained by low polygenic risk for AD as assessed by common genetic variants. However, rare variants and common protective genetic factors may contribute to resistance or resilience. Highlights: SuperAging cannot be simply explained by low polygenic risk for Alzheimer's disease.Rare variants and common protective genetic factors may contribute to SuperAging.A protective factors polygenic score may uncover mechanisms for SuperAging.

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INTRODUCTION: Elevated ß-amyloid is used to enroll individuals into preclinical Alzheimer's disease trials, but the screening process is inefficient and expensive. Novel enrichment methods are needed to improve efficiency of enrollment. METHODS: Alzheimer's disease incidence rates and a polygenic hazard score were used to create a gene- and age-defined ADAge. An ADAge cutpoint was chosen to optimally predict ß-amyloid positivity among clinically normal Alzheimer's Disease Neuroimaging Initiative participants and applied to an independent Alzheimer's Disease Research Center validation cohort. The impact of ADAge enrichment on screening costs was evaluated in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease trial data. RESULTS: In the validation cohort, the ADAge-enriched sample had a higher proportion of individuals with elevated ß-amyloid (difference [95% CI] 0.19[0.07 to 0.33]) than the unenriched sample. ADAge enrichment lowered screening costs by $4.41 million (31.00%) in the real-world clinical trial scenario. DISCUSSION: ADAge enrichment provides for a more efficient and cost-effective means to enroll clinically normal individuals with elevated ß-amyloid in clinical trials.

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In the clinical diagnosis of dementia with Lewy bodies, distinction from Alzheimer's disease is suboptimal and complicated by shared genetic risk factors and frequent co-pathology. In the present study we tested the ability of polygenic scores for Alzheimer's disease, dementia with Lewy bodies, and Parkinson's disease to differentiate individuals in a 2713-participant, pathologically defined sample. A dementia with Lewy bodies polygenic score that excluded apolipoprotein E due to its overlap with Alzheimer's disease risk was specifically associated with at least limbic (transitional) Lewy-related pathology and a pathological diagnosis of dementia with Lewy bodies. An Alzheimer's disease polygenic score was associated with neuritic plaques and neurofibrillary tangles but not Lewy-related pathology, and was most strongly associated with an Alzheimer's pathological diagnosis. Our results indicate that an assessment of genetic risk may be useful to clinically distinguish between Alzheimer's disease and dementia with Lewy bodies. Notably, we found no association with a Parkinson's disease polygenic score, which aligns with evidence that dementia with Lewy bodies has a distinct genetic signature that can be exploited to improve clinical diagnoses.

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BACKGROUND: Biomarkers may soon be used to predict decline in older individuals. Extended follow-up studies are needed to determine the stability of such biomarker-based predictions. OBJECTIVE: To examine the long-term performance of baseline cognitive, neuroimaging, and cerebrospinal fluid (CSF) biomarker-assisted prognosis in patients with mild cognitive impairment. METHODS: Established, biomarker-defined, cohorts of subjects with mild cognitive impairment were examined for progression to dementia. Subjects with a baseline volumetric MRI, lumbar puncture, and Rey Auditory Verbal Learning Test were included. Dementia-free survival time in each biomarker-defined risk group was determined with Kaplan-Meier survival curves. The influence of each risk factor or combination of factors on dementia-free survival was examined with Cox proportional hazard analyses. RESULTS: 185 subjects were followed longitudinally for a mean (SD) 4.3 (2.8) years. 59% of participants converted within the follow-up period and the median dementia-free survival time was 2.8 years. Each individual risk factor predicted conversion to dementia (HR 1.9-3.7). The joint presence of any two risk factors increased risk for conversion (HR 7.1-11.0), with the presence of medial temporal atrophy and memory impairment showing the greatest risk for decline. Concordant atrophy, memory impairment, and abnormal CSF amyloid and tau was associated with the highest risk for conversion (HR 15.1). The presence of medial temporal atrophy was associated with the shortest dementia-free survival time, both alone and in combination with memory impairment, abnormal CSF amyloid and tau, or both. CONCLUSION: These results suggest that baseline biomarker-assisted predictions of decline to dementia are stable over the long term, and that combinations of complementary biomarkers can improve the accuracy of these predictions.

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Despite great interest in using magnetic resonance imaging (MRI) for studying the effects of genes on brain structure in humans, current approaches have focused almost entirely on predefined regions of interest and had limited success. Here, we used multivariate methods to define a single neuroanatomical score of how William's Syndrome (WS) brains deviate structurally from controls. The score is trained and validated on measures of T1 structural brain imaging in two WS cohorts (training, n = 38; validating, n = 60). We then associated this score with single nucleotide polymorphisms (SNPs) in the WS hemi-deleted region in five cohorts of neurologically and psychiatrically typical individuals (healthy European descendants, n = 1863). Among 110 SNPs within the 7q11.23 WS chromosomal region, we found one associated locus (p = 5e-5) located at GTF2IRD1, which has been implicated in animal models of WS. Furthermore, the genetic signals of neuroanatomical scores are highly enriched locally in the 7q11.23 compared with summary statistics based on regions of interest, such as hippocampal volumes (n = 12,596), and also globally (SNP-heritability = 0.82, se = 0.25, p = 5e-4). The role of genetic variability in GTF2IRD1 during neurodevelopment extends to healthy subjects. Our approach of learning MRI-derived phenotypes from clinical populations with well-established brain abnormalities characterized by known genetic lesions may be a powerful alternative to traditional region of interest-based studies for identifying genetic variants regulating typical brain development.

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Brain phenotypes showing environmental influence may help clarify unexplained associations between urban exposure and psychiatric risk. Heritable prefrontal fMRI activation during working memory (WM) is such a phenotype. We hypothesized that urban upbringing (childhood urbanicity) would alter this phenotype and interact with dopamine genes that regulate prefrontal function during WM. Further, dopamine has been hypothesized to mediate urban-associated factors like social stress. WM-related prefrontal function was tested for main effects of urbanicity, main effects of three dopamine genes-catechol-O-methyltransferase (COMT), dopamine receptor D1 (DRD1), and dopamine receptor D2 (DRD2)-and, importantly, dopamine gene-by-urbanicity interactions. For COMT, three independent human samples were recruited (total n = 487). We also studied 253 subjects genotyped for DRD1 and DRD2. 3T fMRI activation during the N-back WM task was the dependent variable, while childhood urbanicity, dopamine genotype, and urbanicity-dopamine interactions were independent variables. Main effects of dopamine genes and of urbanicity were found. Individuals raised in an urban environment showed altered prefrontal activation relative to those raised in rural or town settings. For each gene, dopamine genotype-by-urbanicity interactions were shown in prefrontal cortex-COMT replicated twice in two independent samples. An urban childhood upbringing altered prefrontal function and interacted with each gene to alter genotype-phenotype relationships. Gene-environment interactions between multiple dopamine genes and urban upbringing suggest that neural effects of developmental environmental exposure could mediate, at least partially, increased risk for psychiatric illness in urban environments via dopamine genes expressed into adulthood.

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