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Genetic variation in imprinted genes is associated with risk of late-onset Alzheimer's disease.

ABSTRACT: Epigenetic changes including genomic imprinting may affect risk of late-onset Alzheimer's disease (LOAD). There are >100 known imprinted genes and most of them are expressed in human brain. In this study, we examined the association of single nucleotide polymorphisms (SNPs) in 93 imprinted genes with LOAD risk in 1291 LOAD cases and 958 cognitively normal controls. We performed single-site, gene-based, and haplotype analyses. Single-site analysis showed 14 significant associations at p < 0.01. The most significant SNP (rs11770199; p = 0.0003) in single-site analysis was located on chromosome 7 in the GRB10 gene. Gene-based analyses revealed four significant associations in the WT1, ZC3H12C, DLGAP2, and GPR1 genes at p < 0.05. The haplotype analysis also revealed significant associations with three genes (ZC3H12C, DLGAP2, and GPR1). These findings suggest a possible role of imprinted genes in AD pathogenesis that show specific expression in the brain.

SUBMITTER: Chaudhry M

PROVIDER: S-EPMC4324355 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Genetic variation in imprinted genes is associated with risk of late-onset Alzheimer's disease.

Chaudhry Mamoonah M Wang Xingbin X Bamne Mikhil N MN Hasnain Shahida S Demirci F Yesim FY Lopez Oscar L OL Kamboh M Ilyas MI

Journal of Alzheimer's disease : JAD 20150101 3

Epigenetic changes including genomic imprinting may affect risk of late-onset Alzheimer's disease (LOAD). There are >100 known imprinted genes and most of them are expressed in human brain. In this study, we examined the association of single nucleotide polymorphisms (SNPs) in 93 imprinted genes with LOAD risk in 1291 LOAD cases and 958 cognitively normal controls. We performed single-site, gene-based, and haplotype analyses. Single-site analysis showed 14 significant associations at p < 0.01. T ...[more]

PMID: 25391383

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Project description:BACKGROUND:New genetic and genomic resources have identified multiple genetic risk factors for late-onset Alzheimer's disease (LOAD) and characterized this common dementia at the molecular level. Experimental studies in model organisms can validate these associations and elucidate the links between specific genetic factors and transcriptomic signatures. Animal models based on LOAD-associated genes can potentially connect common genetic variation with LOAD transcriptomes, thereby providing novel insights into basic biological mechanisms underlying the disease. METHODS:We performed RNA-Seq on whole brain samples from a panel of six-month-old female mice, each carrying one of the following mutations: homozygous deletions of Apoe and Clu; hemizygous deletions of Bin1 and Cd2ap; and a transgenic APOE?4. Similar data from a transgenic APP/PS1 model was included for comparison to early-onset variant effects. Weighted gene co-expression network analysis (WGCNA) was used to identify modules of correlated genes and each module was tested for differential expression by strain. We then compared mouse modules with human postmortem brain modules from the Accelerating Medicine's Partnership for AD (AMP-AD) to determine the LOAD-related processes affected by each genetic risk factor. RESULTS:Mouse modules were significantly enriched in multiple AD-related processes, including immune response, inflammation, lipid processing, endocytosis, and synaptic cell function. WGCNA modules were significantly associated with Apoe-/-, APOE?4, Clu-/-, and APP/PS1 mouse models. Apoe-/-, GFAP-driven APOE?4, and APP/PS1 driven modules overlapped with AMP-AD inflammation and microglial modules; Clu-/- driven modules overlapped with synaptic modules; and APP/PS1 modules separately overlapped with lipid-processing and metabolism modules. CONCLUSIONS:This study of genetic mouse models provides a basis to dissect the role of AD risk genes in relevant AD pathologies. We determined that different genetic perturbations affect different molecular mechanisms comprising AD, and mapped specific effects to each risk gene. Our approach provides a platform for further exploration into the causes and progression of AD by assessing animal models at different ages and/or with different combinations of LOAD risk variants.

Dataset Information

Genetic variation in imprinted genes is associated with risk of late-onset Alzheimer's disease.

Publications

Genetic variation in imprinted genes is associated with risk of late-onset Alzheimer's disease.

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