SynthesisNature genetics2026
A meta-analysis of single-nucleus expression quantitative trait loci linking genetic risk to brain disorders.
Synthesis in Nature genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.
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.
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Who cites it
9 citing papers in PubMed.
- Article
- A single-nuclei multiomics resource across four brain regions prioritises human neural cell types influencing brain-related traits.bioRxiv : the preprint server for biology · 2026Article
- Article
- Atypical energy-related symptoms define biologically distinct subtypes of major depressive disorder.medRxiv : the preprint server for health sciences · 2026Article
- Article
- A TAD-informed aging-brain xQTL atlas of multi-modal and cell-type-resolved regulatory variation.medRxiv : the preprint server for health sciences · 2026Article
- APOE*4 risk-modifying genes and drug targets in Alzheimer's disease through cell-type-specific genomic analyses.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Single-cell eQTL mapping reveals convergent glial-neuronal risk architecture in Parkinson's disease.bioRxiv : the preprint server for biology · 2026Article
- An interpretable machine learning model for predicting stroke in patients with hypertension: insights from the SPRINT.Scientific reports · 2026Article
Corrections and comments
- Erratum issued
- Update of
Authors and funding
17 authors.
Funding
Abstract
Most genetic risk variants for neurological diseases are located in noncoding regulatory regions, where they often act as expression quantitative trait loci (eQTLs), modulating gene expression and influencing disease susceptibility. However, eQTL studies in bulk brain tissue or cell lines fail to capture the brain's cellular diversity. Single-nucleus RNA sequencing (snRNA-seq) allows high-resolution mapping of eQTLs across diverse brain cell types. Here we performed a meta-analysis by integrating snRNA-seq and genotype data from four cohorts, totaling 5.8 million nuclei from 983 individuals of European ancestry. We mapped cis-eQTLs and trans-eQTLs across major brain cell types and subtypes, including disease-specific and sex-specific eQTLs, and applied colocalization and Mendelian randomization to identify genes that mediate neurological disease risk. We observed up to tenfold more cis-eQTLs and uncovered cell-type-specific genes linked to neurological disease. SingleBrain is a comprehensive single-cell eQTL resource that provides insights into the genetic mechanism of brain disorders.
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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.