Details

Autor(en) / Beteiligte

• Patel, Devanshi
• Zhang, Xiaoling
• Farrell, John J
• Lunetta, Kathryn L
• Farrer, Lindsay A

Titel

Set-Based Rare Variant Expression Quantitative Trait Loci in Blood and Brain from Alzheimer Disease Study Participants

Ist Teil von

• Genes, 2021-03, Vol.12 (3), p.419

Ort / Verlag

Switzerland: MDPI AG

Erscheinungsjahr

2021

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Because studies of rare variant effects on gene expression have limited power, we investigated set-based methods to identify rare expression quantitative trait loci (eQTL) related to Alzheimer disease (AD). Gene-level and pathway-level cis rare-eQTL mapping was performed genome-wide using gene expression data derived from blood donated by 713 Alzheimer's Disease Neuroimaging Initiative participants and from brain tissues donated by 475 Religious Orders Study/Memory and Aging Project participants. The association of gene or pathway expression with a set of all cis potentially regulatory low-frequency and rare variants within 1 Mb of genes was evaluated using SKAT-O. A total of 65 genes expressed in the brain were significant targets for rare expression single nucleotide polymorphisms (eSNPs) among which 17% (11/65) included established AD genes and . In the blood, 307 genes were significant targets for rare eSNPs. In the blood and the brain, , , , , and were targets for significant eSNPs. Pathway enrichment analysis revealed significant pathways in the brain ( = 9) and blood ( = 16). Pathways for apoptosis signaling, cholecystokinin receptor (CCKR) signaling, and inflammation mediated by chemokine and cytokine signaling were common to both tissues. Significant rare eQTLs in inflammation pathways included five genes in the blood ( , , , , ) that were previously linked to AD. This study identified several significant gene- and pathway-level rare eQTLs, which further confirmed the importance of the immune system and inflammation in AD and highlighted the advantages of using a set-based eQTL approach for evaluating the effect of low-frequency and rare variants on gene expression.