ArticleScientific data2020
Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions.
Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 9 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
77 citing papers in PubMed, 9 syntheses or guidelines pooled it, 328 citations in OpenAlex.
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- Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies known and novel cross-population and ancestry-specific associations as novel risk loci for Alzheimer's disease.Genome biology · 2025Pooled it
- Genome-wide association meta-analysis of age at onset of walking in over 70,000 infants of European ancestry.Nature human behaviour · 2025Pooled it
- Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Pooled it
- GALC variants affect galactosylceramidase enzymatic activity and risk of Parkinson's disease.Brain : a journal of neurology · 2023Pooled it
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- Genome-wide analysis of common and rare variants via multiple knockoffs at biobank scale, with an application to Alzheimer disease genetics.American journal of human genetics · 2021Pooled it
- Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders.Genome biology · 2021Pooled it
- Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes.Nature genetics · 2021Pooled it
- Alzheimer's disease target and drug discovery by leveraging multiomics and electronic health data.Nature neuroscience · 2026Article
- Inhibition of Moesin and CD44 in stem cell-derived neurons affects the pathological genetic signature associated with Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- A TAD-informed aging-brain xQTL atlas of multi-modal and cell-type-resolved regulatory variation.medRxiv : the preprint server for health sciences · 2026Article
- Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease.American journal of human genetics · 2026Article
- Identification of Alzheimer's disease subtypes and biomarkers from human multi-omics data using subspace merging algorithm.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Proteomic profiling of brain organoids and extracellular vesicles identifies early Alzheimer's disease biomarkers and drug response heterogeneity.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Multiple-testing corrections in case-control studies using identity-by-descent segments.American journal of human genetics · 2026Article
- Distinct Regulatory Genomic Architectures Distinguish Early-Onset from Late-Onset Alzheimer's Disease.Genes · 2026Article
- Functional implications of polygenic risk for schizophrenia in human neurons.Nature communications · 2026Article
- Integrating axis quantitative trait loci looks beyond cell types and offers insights into brain-related traits.Nature communications · 2025Article
- Multi-ancestry Transcriptome-Wide Association Study Reveals Shared and Population-Specific Genetic Effects in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2025Article
17 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
21 authors at 20 institutions in 7 countries.
Funding
Abstract
The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer's Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes). We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. Additionally, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a resource for use by the research community. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalization with lncRNA RP11-677M14.2 (posterior probability of colocalization 0.975).
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Registered trials
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.