37 research outputs found

    Severe CTE and TDP-43 pathology in a former professional soccer player with dementia: a clinicopathological case report and review of the literature

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    In the last decades, numerous post-mortem case series have documented chronic traumatic encephalopathy (CTE) in former contact-sport athletes, though reports of CTE pathology in former soccer players are scarce. This study presents a clinicopathological case of a former professional soccer player with young-onset dementia. The patient experienced early onset progressive cognitive decline and developed dementia in his mid-50 s, after playing soccer for 12 years at a professional level. While the clinical picture mimicked Alzheimer's disease, amyloid PET imaging did not provide evidence of elevated beta-amyloid plaque density. After he died in his mid-60 s, brain autopsy showed severe phosphorylated tau (p-tau) abnormalities fulfilling the neuropathological criteria for high-stage CTE, as well as astrocytic and oligodendroglial tau pathology in terms of tufted astrocytes, thorn-shaped astrocytes, and coiled bodies. Additionally, there were TAR DNA-binding protein 43 (TDP-43) positive cytoplasmic inclusions in the frontal lobe and hippocampus, and Amyloid Precursor Protein (APP) positivity in the axons of the white matter. A systematic review of the literature revealed only 13 other soccer players with postmortem diagnosis of CTE. Our report illustrates the complex clinicopathological correlation of CTE and the need for disease-specific biomarkers

    What does heritability of Alzheimer's disease represent?

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    INTRODUCTION: Both late-onset Alzheimer's disease (AD) and ageing have a strong genetic component. In each case, many associated variants have been discovered, but how much missing heritability remains to be discovered is debated. Variability in the estimation of SNP-based heritability could explain the differences in reported heritability. METHODS: We compute heritability in five large independent cohorts (N = 7,396, 1,566, 803, 12,528 and 3,963) to determine whether a consensus for the AD heritability estimate can be reached. These cohorts vary by sample size, age of cases and controls and phenotype definition. We compute heritability a) for all SNPs, b) excluding APOE region, c) excluding both APOE and genome-wide association study hit regions, and d) SNPs overlapping a microglia gene-set. RESULTS: SNP-based heritability of late onset Alzheimer's disease is between 38 and 66% when age and genetic disease architecture are correctly accounted for. The heritability estimates decrease by 12% [SD = 8%] on average when the APOE region is excluded and an additional 1% [SD = 3%] when genome-wide significant regions were removed. A microglia gene-set explains 69-84% of our estimates of SNP-based heritability using only 3% of total SNPs in all cohorts. CONCLUSION: The heritability of neurodegenerative disorders cannot be represented as a single number, because it is dependent on the ages of cases and controls. Genome-wide association studies pick up a large proportion of total AD heritability when age and genetic architecture are correctly accounted for. Around 13% of SNP-based heritability can be explained by known genetic loci and the remaining heritability likely resides around microglial related genes

    Cognitive composites for genetic frontotemporal dementia: GENFI-Cog.

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    BACKGROUND: Clinical endpoints for upcoming therapeutic trials in frontotemporal dementia (FTD) are increasingly urgent. Cognitive composite scores are often used as endpoints but are lacking in genetic FTD. We aimed to create cognitive composite scores for genetic frontotemporal dementia (FTD) as well as recommendations for recruitment and duration in clinical trial design. METHODS: A standardized neuropsychological test battery covering six cognitive domains was completed by 69 C9orf72, 41 GRN, and 28 MAPT mutation carriers with CDRÂź plus NACC-FTLD ≄ 0.5 and 275 controls. Logistic regression was used to identify the combination of tests that distinguished best between each mutation carrier group and controls. The composite scores were calculated from the weighted averages of test scores in the models based on the regression coefficients. Sample size estimates were calculated for individual cognitive tests and composites in a theoretical trial aimed at preventing progression from a prodromal stage (CDRÂź plus NACC-FTLD 0.5) to a fully symptomatic stage (CDRÂź plus NACC-FTLD ≄ 1). Time-to-event analysis was performed to determine how quickly mutation carriers progressed from CDRÂź plus NACC-FTLD = 0.5 to ≄ 1 (and therefore how long a trial would need to be). RESULTS: The results from the logistic regression analyses resulted in different composite scores for each mutation carrier group (i.e. C9orf72, GRN, and MAPT). The estimated sample size to detect a treatment effect was lower for composite scores than for most individual tests. A Kaplan-Meier curve showed that after 3 years, ~ 50% of individuals had converted from CDRÂź plus NACC-FTLD 0.5 to ≄ 1, which means that the estimated effect size needs to be halved in sample size calculations as only half of the mutation carriers would be expected to progress from CDRÂź plus NACC FTLD 0.5 to ≄ 1 without treatment over that time period. DISCUSSION: We created gene-specific cognitive composite scores for C9orf72, GRN, and MAPT mutation carriers, which resulted in substantially lower estimated sample sizes to detect a treatment effect than the individual cognitive tests. The GENFI-Cog composites have potential as cognitive endpoints for upcoming clinical trials. The results from this study provide recommendations for estimating sample size and trial duration

    Frontotemporal dementia and its subtypes: a genome-wide association study

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    SummaryBackground Frontotemporal dementia (FTD) is a complex disorder characterised by a broad range of clinical manifestations, differential pathological signatures, and genetic variability. Mutations in three genes—MAPT, GRN, and C9orf72—have been associated with FTD. We sought to identify novel genetic risk loci associated with the disorder. Methods We did a two-stage genome-wide association study on clinical FTD, analysing samples from 3526 patients with {FTD} and 9402 healthy controls. To reduce genetic heterogeneity, all participants were of European ancestry. In the discovery phase (samples from 2154 patients with {FTD} and 4308 controls), we did separate association analyses for each {FTD} subtype (behavioural variant FTD, semantic dementia, progressive non-fluent aphasia, and {FTD} overlapping with motor neuron disease FTD-MND), followed by a meta-analysis of the entire dataset. We carried forward replication of the novel suggestive loci in an independent sample series (samples from 1372 patients and 5094 controls) and then did joint phase and brain expression and methylation quantitative trait loci analyses for the associated (p<5 × 10−8) single-nucleotide polymorphisms. Findings We identified novel associations exceeding the genome-wide significance threshold (p<5 × 10−8). Combined (joint) analyses of discovery and replication phases showed genome-wide significant association at 6p21.3, \{HLA\} locus (immune system), for rs9268877 (p=1·05 × 10−8; odds ratio=1·204 95% \{CI\} 1·11–1·30), rs9268856 (p=5·51 × 10−9; 0·809 0·76–0·86) and rs1980493 (p value=1·57 × 10−8, 0·775 0·69–0·86) in the entire cohort. We also identified a potential novel locus at 11q14, encompassing RAB38/CTSC (the transcripts of which are related to lysosomal biology), for the behavioural \{FTD\} subtype for which joint analyses showed suggestive association for rs302668 (p=2·44 × 10−7; 0·814 0·71–0·92). Analysis of expression and methylation quantitative trait loci data suggested that these loci might affect expression and methylation in cis. Interpretation Our findings suggest that immune system processes (link to 6p21.3) and possibly lysosomal and autophagy pathways (link to 11q14) are potentially involved in FTD. Our findings need to be replicated to better define the association of the newly identified loci with disease and to shed light on the pathomechanisms contributing to FTD. Funding The National Institute of Neurological Disorders and Stroke and National Institute on Aging, the Wellcome/MRC Centre on Parkinson's disease, Alzheimer's Research UK, and Texas Tech University Health Sciences Center

    A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia.

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    Several CSF and blood biomarkers for genetic frontotemporal dementia have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain and phosphorylated neurofilament heavy chain), synapse dysfunction [neuronal pentraxin 2 (NPTX2)], astrogliosis (glial fibrillary acidic protein) and complement activation (C1q, C3b). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging and help identify mutation carriers with prodromal or early-stage frontotemporal dementia, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic frontotemporal dementia using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. Two-hundred and seventy-five presymptomatic and 127 symptomatic carriers of mutations in GRN, C9orf72 or MAPT, as well as 247 non-carriers, were selected from the GENFI cohort based on availability of one or more of the aforementioned biomarkers. Nine presymptomatic carriers developed symptoms within 18 months of sample collection ('converters'). Sequences of biomarker abnormalities were modelled for the entire group using discriminative event-based modelling (DEBM) and for each genetic subgroup using co-initialized DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on previous diagnostic information or biomarker cut-off points. Using cross-validation, subjects were subsequently assigned a disease stage based on their position along the disease progression timeline. CSF NPTX2 was the first biomarker to become abnormal, followed by blood and CSF neurofilament light chain, blood phosphorylated neurofilament heavy chain, blood glial fibrillary acidic protein and finally CSF C3b and C1q. Biomarker orderings did not differ significantly between genetic subgroups, but more uncertainty was noted in the C9orf72 and MAPT groups than for GRN. Estimated disease stages could distinguish symptomatic from presymptomatic carriers and non-carriers with areas under the curve of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The areas under the curve to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic frontotemporal dementia revealed that NPTX2 and neurofilament light chain are the earliest to change among the selected biomarkers. Further research should investigate their utility as candidate selection tools for pharmaceutical trials. The model's ability to accurately estimate individual disease stages could improve patient stratification and track the efficacy of therapeutic interventions
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