Novel early-onset Alzheimer-associated genes influence risk through dysregulation of glutamate, immune activation, and intracellular signaling pathways.
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Bradley Joseph, Pottier Cyril, da Fonseca Eder Lucio, Kurup Jiji Thulaseedhara, Western Daniel, Wang Ciyang, Neupane Achal, Ray Nicholas R, Jean-Francois Melissa, Ali Muhammad, Timsina Jigyasha, Bergmann Kristy, Budde John, Martin Eden R, Pericak-Vance Margaret A, Cuccaro Michael, Naj Adam C, Kunkle Brian W, Alzheimer's Disease Genetics Consortium (ADGC), Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight‐ADRC), Schellenberg Gerard D, Fernandez Victoria, Haines Jonathan, Morris John C, Holtzman David M, Perrin Richard J, Reitz Christiane, Beecham Gary W, Cruchaga Carlos
Аннотация
METHODS: We performed a multi-ancestry (non-Hispanic European, African, and East Asian) genome-wide association study (GWAS) including a total of 7,349 cases and 17,887 control. Cases with age at onset younger than 70 years were included. Sensitivity analysis including cases with onset <65 was performed. Only controls older than 70 were included to decrease the risk of developing LOAD.
RESULTS: We identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. By integrating gene-based analysis, expression quantitative trait loci (eQTL), protein quantitative trait loci (pQTL), and functional annotations, we nominate eight novel genes that are involved in microglia activation, glutamate production, and signaling pathways.
DISCUSSION: EOAD, although sharing genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification.
HIGHLIGHTS: We performed the largest and first multi-ethnic genetic screening for early-onset Alzheimer's disease (AD). We identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. The novel genes are implicated microglia activation, glutamate production, and signaling pathways. EOAD, although sharing many genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification for this type of AD.