327 research outputs found

    Multipoint identity-by-descent computations for single-point polymorphism and microsatellite maps

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    We used the LOKI software to generate multipoint identity-by-descent matrices for a microsatellite map (with 31 markers) and two single-nucleotide polymorphism (SNP) maps to examine information content across chromosome 7 in the Collaborative Study on the Genetics of Alcoholism dataset. Despite the lower information provided by a single SNP, SNP maps overall had higher and more uniform information content across the chromosome. The Affymetrix map (578 SNPs) and the Illumina map (271 SNPs) provided almost identical information. However, increased information has a computational cost: SNP maps require 100 times as many iterations as microsatellites to produce stable estimates

    Advances in land surface modelling

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    Land surface models have an increasing scope. Initially designed to capture the feedbacks between the land and the atmosphere as part of weather and climate prediction, they are now used as a critical tool in the urgent need to inform policy about land-use and water-use management in a world that is changing physically and economically. This paper outlines the way that models have evolved through this change of purpose and what might the future hold. It highlights the importance of distinguishing between advances in the science within the modelling components, with the advances of how to represent their interaction. This latter aspect of modelling is often overlooked but will increasingly manifest as an issue as the complexity of the system, the time and space scales of the system being modelled increase. These increases are due to technology, data availability and the urgency and range of the problems being studied. © 2021, The Author(s)

    Assembly of 809 whole mitochondrial genomes with clinical, imaging, and fluid biomarker phenotyping

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    INTRODUCTION: Mitochondrial genetics are an important but largely neglected area of research in Alzheimer's disease. A major impediment is the lack of data sets. METHODS: We used an innovative, rigorous approach, combining several existing tools with our own, to accurately assemble and call variants in 809 whole mitochondrial genomes. RESULTS: To help address this impediment, we prepared a data set that consists of 809 complete and annotated mitochondrial genomes with samples from the Alzheimer's Disease Neuroimaging Initiative. These whole mitochondrial genomes include rich phenotyping, such as clinical, fluid biomarker, and imaging data, all of which is available through the Alzheimer's Disease Neuroimaging Initiative website. Genomes are cleaned, annotated, and prepared for analysis. DISCUSSION: These data provide an important resource for investigating the impact of mitochondrial genetic variation on risk for Alzheimer's disease and other phenotypes that have been measured in the Alzheimer's Disease Neuroimaging Initiative samples

    Genome-Wide Association Study for Variants That Modulate Relationships Between Cerebrospinal Fluid Amyloid-Beta 42, Tau, and P-Tau Levels

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    Background: A relationship quantitative trait locus exists when the correlation between multiple traits varies by genotype for that locus. Relationship quantitative trait loci (rQTL) are often involved in gene-by-gene (G×G) interactions or gene-by-environmental interactions, making them a powerful tool for detecting G×G. Methods: We performed genome-wide association studies to identify rQTL between tau and Aβ42 and ptau and Aβ42 with over 3000 individuals using age, gender, series, APOE ε2, APOE ε4, and two principal components for population structure as covariates. Each significant rQTL was separately screened for interactions with other loci for each trait in the rQTL model. Parametric bootstrapping was used to assess significance. Results: We found four significant tau/Aβ42 rQTL from three unique locations and six ptau/Aβ42 rQTL from five unique locations. G×G screens with these rQTL produced four significant G×G interactions (one Aβ42, two ptau, and one tau) with four rQTL where each second locus was from a unique location. On follow-up, rs1036819 and rs74025622 were associated with Alzheimer’s disease (AD) case/control status; rs15205 and rs79099429 were associated with rate of decline. Conclusions: The two most significant rQTL (rs8027714 and rs1036819) for ptau/Aβ42 are on different chromosomes and both are strong hits for pelvic organ prolapse. While diseases of the nervous system can cause pelvic organ prolapse, it is unlikely related to the ptau/Aβ42 relationship but may suggest that these two loci share a pathway. In addition to a ptau/Aβ42 rQTL and association with AD case/control status, rs1036819 is a strong rQTL for case/control status/Aβ42 and for tau/Aβ42. It resides in the ZFAT gene, which is related to autoimmune thyroid disease. For tau, rs9817620 interacts with the tau/Aβ42 rQTL rs74025622. It is in the CHL1 gene, which is a neural cell adhesion molecule and may be involved in signal transduction pathways. CHL1 is related to BACE1, which is a β-secretase enzyme that initiates production of the β-amyloid peptide involved in AD and is a primary drug target. Overall, there are numerous loci that affect the relationship between these important AD endophenotypes and some are due to interactions with other loci. Some affect the risk of AD and/or rate of progression

    Influence of coding variability in APP-Aβ metabolism genes in sporadic Alzheimer’s disease

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    This is the final version of the article. Available from the publisher via the DOI in this record.The cerebral deposition of Aβ42, a neurotoxic proteolytic derivate of amyloid precursor protein (APP), is a central event in Alzheimer's disease (AD)(Amyloid hypothesis). Given the key role of APP-Aβ metabolism in AD pathogenesis, we selected 29 genes involved in APP processing, Aβ degradation and clearance. We then used exome and genome sequencing to investigate the single independent (single-variant association test) and cumulative (gene-based association test) effect of coding variants in these genes as potential susceptibility factors for AD, in a cohort composed of 332 sporadic and mainly late-onset AD cases and 676 elderly controls from North America and the UK. Our study shows that common coding variability in these genes does not play a major role for the disease development. In the single-variant association analysis, the main hits, none of which statistically significant after multiple testing correction (1.9e-4<p-value<0.05), were found to be rare coding variants (0.009%<MAF<1.4%) with moderate to strong effect size (1.84<OR<Inf) that map to genes mainly involved in Aβ extracellular degradation (TTR, ACE), clearance (LRP1) and APP trafficking and recycling (SORL1). These results were partially replicated in the gene-based analysis (c-alpha and SKAT tests), that reports ECE1, LYZ and TTR as nominally associated to AD (1.7e-3 <p-value <0.05). In concert with previous studies, we suggest that 1) common coding variability in APP-Aβ genes is not a critical factor for AD development and 2) Aβ degradation and clearance, rather than Aβ production, may play a key role in the etiology of sporadic AD.This study was supported by the Alzheimer's Research UK, the Medical Research Council (MRC), the Wellcome Trust/MRC Joint Call in Neurodegeneration Award (WT089698) to the UK Parkinson's Disease Consortium (whose members are from the University College London Institute of Neurology, the University of Sheffield, and the MRC Protein Phosphorylation Unit at the University of Dundee), grants (P50 AG016574, U01 AG006786, and R01 AG18023), the National Institute for Health Research Biomedical Research Unit in Dementia at University College London Hospitals, University College London; the Big Lottery (to Dr. Morgan); a fellowship from Alzheimer's Research UK (to Dr. Guerreiro); and the Intramural Research Programs of the National Institute on Aging and the National Institute of Neurological Disease and Stroke, National Institutes of Health (Department of Health and Human Services Project number, ZO1 AG000950-10). The MRC London Neurodegenerative Diseases Brain Bank and the Manchester Brain Bank from Brains for Dementia Research are jointly funded from ARUK and AS. Tissue samples were supplied by The London Neurodegenerative Diseases Brain Bank, which receives funding from the MRC and as part of the Brains for Dementia Research programme, jointly funded by Alzheimer’s Research UK and Alzheimer’s Society

    Influence of coding variability in APP-Aß metabolism genes in sporadic Alzheimer's disease

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    The cerebral deposition of Aß42, a neurotoxic proteolitic derivate of amyloid precursor protein (APP), is a central event in Alzheimer’s disease (AD)(Amyloid hypothesis). Given the key role of APP-Aß metabolism in AD pathogenesis, we selected 29 genes involved in APP processing, Aß degradation and clearance. We then used exome and genome sequencing to investigate the single independent (single-variant association test) and cumulative (gene-based association test) effect of coding variants in these genes as potential susceptibility factors for AD, in a cohort composed of 435 sporadic and mainly late-onset AD cases and 801 elderly controls from North America and the UK. Our study shows that common coding variability in these genes does not play a major role for the disease development. In the single-variant association analysis, the main hits, which were nominally significant, were found to be very rare coding variants (MAF 0.3%-0.8%) that map to genes involved in APP processing (MEP1B), trafficking and recycling (SORL1), Aß extracellular degradation (ACE) and clearance (LRP1). Moreover, four genes (ECE1, LYZ, TTR and MME) have been found as nominally associated to AD using c-alpha and SKAT tests. We suggest that Aβ degradation and clearance, rather than Aβ production, may play a crucial role in the etiology of sporadic AD

    Systems Biology Approach to Late-Onset Alzheimer\u27s Disease Genome-Wide Association Study Identifies Novel Candidate Genes Validated Using Brain Expression Data and \u3cem\u3eCaenorhabditis elegans\u3c/em\u3e Experiments

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    Introduction—We sought to determine whether a systems biology approach may identify novel late-onset Alzheimer\u27s disease (LOAD) loci. Methods—We performed gene-wide association analyses and integrated results with human protein-protein interaction data using network analyses. We performed functional validation on novel genes using a transgenic Caenorhabditis elegans Aβ proteotoxicity model and evaluated novel genes using brain expression data from people with LOAD and other neurodegenerative conditions. Results—We identified 13 novel candidate LOAD genes outside chromosome 19. Of those, RNA interference knockdowns of the C. elegans orthologs of UBC, NDUFS3, EGR1, and ATP5H were associated with Aβ toxicity, and NDUFS3, SLC25A11, ATP5H, and APP were differentially expressed in the temporal cortex. Discussion—Network analyses identified novel LOAD candidate genes. We demonstrated a functional role for four of these in a C. elegans model and found enrichment of differentially expressed genes in the temporal cortex

    Analysis of Genes (\u3ci\u3eTMEM106B\u3c/i\u3e, \u3ci\u3eGRN\u3c/i\u3e, \u3ci\u3eABCC9\u3c/i\u3e, \u3ci\u3eKCNMB2\u3c/i\u3e, and \u3ci\u3eAPOE\u3c/i\u3e) Implicated in Risk for LATE-NC and Hippocampal Sclerosis Provides Pathogenetic Insights: A Retrospective Genetic Association Study

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    Limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) is the most prevalent subtype of TDP-43 proteinopathy, affecting up to 1/3rd of aged persons. LATE-NC often co-occurs with hippocampal sclerosis (HS) pathology. It is currently unknown why some individuals with LATE-NC develop HS while others do not, but genetics may play a role. Previous studies found associations between LATE-NC phenotypes and specific genes: TMEM106B, GRN, ABCC9, KCNMB2, and APOE. Data from research participants with genomic and autopsy measures from the National Alzheimer’s Coordinating Center (NACC; n = 631 subjects included) and the Religious Orders Study and Memory and the Rush Aging Project (ROSMAP; n = 780 included) were analyzed in the current study. Our goals were to reevaluate disease-associated genetic variants using newly collected data and to query whether the specific genotype/phenotype associations could provide new insights into disease-driving pathways. Research subjects included in prior LATE/HS genome-wide association studies (GWAS) were excluded. Single nucleotide variants (SNVs) within 10 kb of TMEM106B, GRN, ABCC9, KCNMB2, and APOE were tested for association with HS and LATE-NC, and separately for Alzheimer’s pathologies, i.e. amyloid plaques and neurofibrillary tangles. Significantly associated SNVs were identified. When results were meta-analyzed, TMEM106B, GRN, and APOE had significant gene-based associations with both LATE and HS, whereas ABCC9 had significant associations with HS only. In a sensitivity analysis limited to LATE-NC + cases, ABCC9 variants were again associated with HS. By contrast, the associations of TMEM106B, GRN, and APOE with HS were attenuated when adjusting for TDP-43 proteinopathy, indicating that these genes may be associated primarily with TDP-43 proteinopathy. None of these genes except APOE appeared to be associated with Alzheimer’s-type pathology. In summary, using data not included in prior studies of LATE or HS genomics, we replicated several previously reported gene-based associations and found novel evidence that specific risk alleles can differentially affect LATE-NC and HS

    Influence of coding variability in APP-Aß metabolism genes in sporadic Alzheimer's disease

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    The cerebral deposition of Aß42, a neurotoxic proteolitic derivate of amyloid precursor protein (APP), is a central event in Alzheimer’s disease (AD)(Amyloid hypothesis). Given the key role of APP-Aß metabolism in AD pathogenesis, we selected 29 genes involved in APP processing, Aß degradation and clearance. We then used exome and genome sequencing to investigate the single independent (single-variant association test) and cumulative (gene-based association test) effect of coding variants in these genes as potential susceptibility factors for AD, in a cohort composed of 435 sporadic and mainly late-onset AD cases and 801 elderly controls from North America and the UK. Our study shows that common coding variability in these genes does not play a major role for the disease development. In the single-variant association analysis, the main hits, which were nominally significant, were found to be very rare coding variants (MAF 0.3%-0.8%) that map to genes involved in APP processing (MEP1B), trafficking and recycling (SORL1), Aß extracellular degradation (ACE) and clearance (LRP1). Moreover, four genes (ECE1, LYZ, TTR and MME) have been found as nominally associated to AD using c-alpha and SKAT tests. We suggest that Aβ degradation and clearance, rather than Aβ production, may play a crucial role in the etiology of sporadic AD
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