ArticleFrontiers in genetics2018
Prediction of Alzheimer's Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data.
Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 50 citations in OpenAlex.
- Molecular mechanism of Alzheimer's disease using integrated multi-omics.Frontiers in aging neuroscience · 2026Review
- Integrated Multi-Omics Analysis and Cross-Model Validation Reveal Mitochondrial Signatures in Alzheimer's Disease.CNS neuroscience & therapeutics · 2025Article
- Comprehensive characterization of the RNA editing landscape in the human aging brains with Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Computational and functional prioritization identifies genes that rescue behavior and reduce tau protein in fly and human cell models of Alzheimer disease.American journal of human genetics · 2025Article
- Navigating the blurred boundary: Neuropathologic changes versus clinical symptoms in Alzheimer's disease, and its consequences for research in genetics.Journal of Alzheimer's disease : JAD · 2025Review
- Multiome-wide Association Studies: Novel Approaches for Understanding Diseases.Genomics, proteomics & bioinformatics · 2024Review
- Omnibus proteome-wide association study identifies 43 risk genes for Alzheimer disease dementia.American journal of human genetics · 2024Article
- Gaining new insights into the etiology of ulcerative colitis through a cross-tissue transcriptome-wide association study.Frontiers in genetics · 2024Article
- A review and analysis of key biomarkers in Alzheimer's disease.Frontiers in neuroscience · 2024Review
- Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data.Translational psychiatry · 2023Article
- De novo CLPTM1 variants with reduced GABAEpilepsia · 2023Article
- Integrative Transcriptomic Analyses of Hippocampal-Entorhinal System Subfields Identify Key Regulators in Alzheimer's Disease.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- OTTERS: a powerful TWAS framework leveraging summary-level reference data.Nature communications · 2023Article
- Alzheimer's Disease: An Updated Overview of Its Genetics.International journal of molecular sciences · 2023Review
- TWAS Atlas: a curated knowledgebase of transcriptome-wide association studies.Nucleic acids research · 2023Article
- Article
- Prediction of Alzheimer's Disease by a Novel Image-Based Representation of Gene Expression.Genes · 2022Article
- Identification of Potential Driver Genes and Pathways Based on Transcriptomics Data in Alzheimer's Disease.Frontiers in aging neuroscience · 2022Article
- Neuronal ROS-induced glial lipid droplet formation is altered by loss of Alzheimer's disease-associated genes.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- A transcriptome-wide association study identifies novel blood-based gene biomarker candidates for Alzheimer's disease risk.Human molecular genetics · 2021Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alzheimer's disease (AD) is the most common cause of dementia. It is the fifth leading cause of death among elderly people. With high genetic heritability (79%), finding the disease's causal genes is a crucial step in finding a treatment for AD. Following the International Genomics of Alzheimer's Project (IGAP), many disease-associated genes have been identified; however, we do not have enough knowledge about how those disease-associated genes affect gene expression and disease-related pathways. We integrated GWAS summary data from IGAP and five different expression-level data by using the transcriptome-wide association study method and identified 15 disease-causal genes under strict multiple testing (α < 0.05), and four genes are newly identified. We identified an additional 29 potential disease-causal genes under a false discovery rate (α < 0.05), and 21 of them are newly identified. Many genes we identified are also associated with an autoimmune disorder.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.