11 research outputs found

    Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease

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    Background 1Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches

    Correction: genetic evidence implicates the immune system and cholesterol metabolism in the aetiology of Alzheimer's disease.

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    [This corrects the article on p. e13950 in vol. 5.]. Background: Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology: We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings: We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance: Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches

    Additional file 1: Figure S1. of A 26-hour system of highly sensitive whole genome sequencing for emergency management of genetic diseases

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    Screen-shots demonstrating the functionality of SSAGA. A. The clinical feature entry page. Synonyms for each feature are entered in the top left box. Upon entry, a list of matching HPO terms is displayed. The appropriate HPO term is selected and added to the patient’s feature list in the box on the right. This is performed for each clinical feature. In this case, patient CMH672ref, the patient had 11 clinical features that included neonatal seizures and a characteristic facies. B. Upon clicking the ‘Get Diagnosis’ button, the list of all matching diseases is generated. In this case, the differential diagnosis had 1,136 rows, representing 597 genes, of which 222 matched two or more clinical features. (PDF 240 kb
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