SynthesisAlzheimer's research & therapy2020
An analysis of genetically regulated gene expression across multiple tissues implicates novel gene candidates in Alzheimer's disease.
Synthesis in Alzheimer's research & therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 30 citations in OpenAlex.
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- Genetically regulated expression in late-onset Alzheimer's disease implicates risk genes within known and novel loci.Translational psychiatry · 2021Pooled it
- Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease.American journal of human genetics · 2026Article
- Integrating genetically predicted transcriptomic signatures with longitudinal real-world data enables scalable drug repurposing for Alzheimer's disease.Research square · 2026Article
- Network pharmacology-based discovery and experimental validation of novel drug repurposing candidates in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2026Article
- Distinct Regulatory Genomic Architectures Distinguish Early-Onset from Late-Onset Alzheimer's Disease.Genes · 2026Article
- GENEasso: a curated resource of credible disease-gene associations across complex diseases from GWAS summary statistics.Nucleic acids research · 2026Article
- Multi-ancestry Transcriptome-Wide Association Study Reveals Shared and Population-Specific Genetic Effects in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2025Article
- Transcription factors and candidate functional SNPs associated with variation in fatty acid composition from skeletal muscle of pigs.Animal genetics · 2025Article
- 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
- Review
- Article
- Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data.Translational psychiatry · 2023Article
- A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer's disease risk and rates of disease progression.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023Article
- A Functional Pipeline of Genome-Wide Association Data Leads to Midostaurin as a Repurposed Drug for Alzheimer's Disease.International journal of molecular sciences · 2023Article
- 'Fly-ing' from rare to common neurodegenerative disease mechanisms.Trends in genetics : TIG · 2022Review
- A transcriptome-wide association study identifies novel blood-based gene biomarker candidates for Alzheimer's disease risk.Human molecular genetics · 2021Article
- Integrative Network-Based Analysis Reveals Gene Networks and Novel Drug Repositioning Candidates for Alzheimer Disease.Neurology. Genetics · 2021Article
- A transcriptome-wide association study of Alzheimer's disease using prediction models of relevant tissues identifies novel candidate susceptibility genes.Genome medicine · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
introductionGenome-wide association studies (GWAS) have successfully identified multiple independent genetic loci that harbour variants associated with Alzheimer's disease, but the exact causal genes and biological pathways are largely unknown.
methodsTo prioritise likely causal genes associated with Alzheimer's disease, we used S-PrediXcan to integrate expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression (GTEx) study and CommonMind Consortium (CMC) with Alzheimer's disease GWAS summary statistics. We meta-analysed the GTEx results using S-MultiXcan, prioritised disease-implicated loci using a computational fine-mapping approach, and performed a biological pathway analysis on the gene-based results.
resultsWe identified 126 tissue-specific gene-based associations across 48 GTEx tissues, targeting 50 unique genes. Meta-analysis of the tissue-specific associations identified 73 genes whose expression was associated with Alzheimer's disease. Additional analyses in the dorsolateral prefrontal cortex from the CMC identified 12 significant associations, 8 of which also had a significant association in GTEx tissues. Fine-mapping of causal gene sets prioritised gene candidates in 10 Alzheimer's disease loci with strong evidence for causality. Biological pathway analyses of the meta-analysed GTEx data and CMC data identified a significant enrichment of Alzheimer's disease association signals in plasma lipoprotein clearance, in addition to multiple immune-related pathways.
conclusionsGene expression data from brain and peripheral tissues can improve power to detect regulatory variation underlying Alzheimer's disease. However, the associations in peripheral tissues may reflect tissue-shared regulatory variation for a gene. Therefore, future functional studies should be performed to validate the biological meaning of these associations and whether they represent new pathogenic tissues.
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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 OpenQuestion graph.