Dataset Information

Genome-wide transcriptome analysis identifies novel dysregulated genes implicated in Alzheimer's pathology.

ABSTRACT: INTRODUCTION:Abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer's disease (LOAD). METHODS:We performed transcriptome-wide meta-analysis (N = 1440) of blood-based microarray gene expression profiles as well as neuroimaging and cerebrospinal fluid (CSF) endophenotype analysis. RESULTS:We identified and replicated five genes (CREB5, CD46, TMBIM6, IRAK3, and RPAIN) as significantly dysregulated in LOAD. The most significantly altered gene, CREB5, was also associated with brain atrophy and increased amyloid beta (A?) accumulation, especially in the entorhinal cortex region. cis-expression quantitative trait loci mapping analysis of CREB5 detected five significant associations (P < 5 × 10-8 ), where rs56388170 (most significant) was also significantly associated with global cortical A? deposition measured by [18 F]Florbetapir positron emission tomography and CSF A?1-42 . DISCUSSION:RNA from peripheral blood indicated a differential gene expression pattern in LOAD. Genes identified have been implicated in biological processes relevant to Alzheimer's disease. CREB, in particular, plays a key role in nervous system development, cell survival, plasticity, and learning and memory.

SUBMITTER: Nho K

PROVIDER: S-EPMC7541709 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome-wide transcriptome analysis identifies novel dysregulated genes implicated in Alzheimer's pathology.

Nho Kwangsik K Nudelman Kelly K Allen Mariet M Hodges Angela A Kim Sungeun S Risacher Shannon L SL Apostolova Liana G LG Lin Kuang K Lunnon Katie K Wang Xue X Burgess Jeremy D JD Ertekin-Taner Nilüfer N Petersen Ronald C RC Wang Lisu L Qi Zhenhao Z He Aiqing A Neuhaus Isaac I Patel Vishal V Foroud Tatiana T Faber Kelley M KM Lovestone Simon S Simmons Andrew A Weiner Michael W MW Saykin Andrew J AJ

Alzheimer's & dementia : the journal of the Alzheimer's Association 20200805 9

<h4>Introduction</h4>Abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer's disease (LOAD).<h4>Methods</h4>We performed transcriptome-wide meta-analysis (N = 1440) of blood-based microarray gene expression profiles as well as neuroimaging and cerebrospinal fluid (CSF) endophenotype analysis.<h4>Results</h4>We identified and replicated five genes (CREB5, CD46, TMBIM6, IRAK3, and RPAIN) as significantly dysregulated in LOAD. The most significantly a ...[more]

PMID: 32755048

Similar Datasets

Project description:In this study, we integrated large-scale GWAS summary data and used the predicted transcriptome-wide association study method to discover novel genes associated with osteoporosis. We identified 204 candidate genes, which provide novel clues for understanding the genetic mechanism of osteoporosis and indicate potential therapeutic targets.IntroductionOsteoporosis is a highly polygenetic disease characterized by low bone mass and deterioration of the bone microarchitecture. Our objective was to discover novel candidate genes associated with osteoporosis.MethodsTo identify potential causal genes of the associated loci, we investigated trait-gene expression associations using the transcriptome-wide association study (TWAS) method. This method directly imputes gene expression effects from genome-wide association study (GWAS) data using a statistical prediction model trained on GTEx reference transcriptome data. We then performed a colocalization analysis to evaluate the posterior probability of biological patterns: associations characterized by a single causal variant or multiple distinct causal variants. Finally, a functional enrichment analysis of gene sets was performed using the VarElect and CluePedia tools, which assess the causal relationships between genes and a disease and search for potential gene's functional pathways. The osteoporosis-associated genes were further confirmed based on the differentially expressed genes profiled from mRNA expression data of bone tissue.ResultsOur analysis identified 204 candidate genes, including 154 genes that have been previously associated with osteoporosis, 50 genes that have not been previously discovered. A biological function analysis found that 20 of the candidate genes were directly associated with osteoporosis. Further analysis of multiple gene expression profiles showed that 15 genes were differentially expressed in patients with osteoporosis. Among these, SLC11A2, MAP2K5, NFATC4, and HSP90B1 were enriched in four pathways, namely, mineral absorption pathway, MAPK signaling pathway, Wnt signaling pathway, and PI3K-Akt signaling pathway, which indicates a causal relationship with the occurrence of osteoporosis.ConclusionsWe demonstrated that transcriptome fine-mapping identifies more osteoporosis-related genes and provides key insight into the development of novel targeted therapeutics for the treatment of osteoporosis.

Dataset Information

Genome-wide transcriptome analysis identifies novel dysregulated genes implicated in Alzheimer's pathology.

Publications

Genome-wide transcriptome analysis identifies novel dysregulated genes implicated in Alzheimer's pathology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets