2018
DOI: 10.1101/258533
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Genetic meta-analysis identifies 9 novel loci and functional pathways for Alzheimer’s disease risk

Abstract: Late onset Alzheimer’s disease (AD) is the most common form of dementia with more than 35 million people affected worldwide, and no curative treatment available. AD is highly heritable and recent genome-wide meta-analyses have identified over 20 genomic loci associated with AD, yet only explaining a small proportion of the genetic variance indicating that undiscovered loci exist. Here, we performed the largest genome-wide association study of clinically diagnosed AD and AD-by-proxy (71,880 AD cases, 383,378 co… Show more

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Cited by 51 publications
(58 citation statements)
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“…Of the four new SNPs that strongly influenced Alzheimer’s risk, we found that MBLAC, DDB2 and MINK1 were associated with proxy AD status in the UKB sample. Importantly, five of the six IGAP/ADGC2 SNPs replicated in UKB consistent with prior work highlighting the usefulness of the by-proxy phenotype approach for AD [52]. Although a proxy phenotype is not equivalent to a clinical diagnosis of dementia, our findings illustrate that a subset of cardiovascular genes influences disease risk even in people with a genetic predisposition for developing AD.…”
Section: Discussionsupporting
confidence: 86%
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“…Of the four new SNPs that strongly influenced Alzheimer’s risk, we found that MBLAC, DDB2 and MINK1 were associated with proxy AD status in the UKB sample. Importantly, five of the six IGAP/ADGC2 SNPs replicated in UKB consistent with prior work highlighting the usefulness of the by-proxy phenotype approach for AD [52]. Although a proxy phenotype is not equivalent to a clinical diagnosis of dementia, our findings illustrate that a subset of cardiovascular genes influences disease risk even in people with a genetic predisposition for developing AD.…”
Section: Discussionsupporting
confidence: 86%
“…[52]). Individuals with one or two parents with AD were defined as proxy cases, while putting more weight on the proxy cases with two parents.…”
Section: Methodsmentioning
confidence: 99%
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“…For real phenotypes, we calculated SNP minor allele frequency (MAF) and LD between SNPs using the 1000 Genomes phase 3 data set for 503 subjects/samples of European ancestry [28,29,30]. In order to carry out realistic simulations (i.e., with realistic heterozygosity and LD structures for SNPs), we used HAPGEN2 [31,32,33] [38]; (7) late onset Alzheimer's disease (LOAD; N cases = 17,008, N controls = 37,154) [39] (in the Supplementary Material we present results for a more recent GWAS with N cases = 71,880 and N controls = 383,378 [40]); (8) amyotrophic lateral sclerosis (ALS) (N cases = 12,577, N controls = 23,475) [41]; (9) number of years of formal education (N = 293,723) [42]; (10) intelligence (N = 262,529) [43,44]; (11) body mass index (N = 233,554) [45]; (12) height (N = 251,747) [46]; (13) putamen volume (normalized by intracranial volume, N = 11,598) [47]; (14) low-(N = 89,873) and (15) high-density lipoprotein (N = 94,295) [48]; and (16) total cholesterol (N = 94,579) [48]. Most participants were of European ancestry.…”
Section: Data Preparationmentioning
confidence: 99%
“…For example, damage to and loss of glial cells, secondary to infection, trauma, or radiation, results in glial cell replacement via cell division, accelerating the basal rate of cell senescence. Many independent variables can affect (almost always increase) the rate of cell senescence including genes, chemotherapy, toxins, trauma, hypertension, stroke, hyperglycemia, microbiome, stress, hormones, infection, senolytic therapy, and so on (Figure ). These variables may be subdivided into subcategories, with supportive data, such as the host of possible infectious etiologies due to bacterial, chlamydial, fungal, viral, or prion‐related causes.…”
Section: Part 2: Summary Of the Modelmentioning
confidence: 99%