ArticleNature communications2024
Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Immune Cell-Stratified Regulatory Contexts Associated With BMI-Related Multi-System Disease Risk: A Cell-Stratified Mendelian Randomization Study Using Single-Cell eQTL Data.Diabetes, obesity & metabolism · 2026Article
- Multi-Omics Mendelian Randomization Maps Lipid-Related Brain Cell-Type Associations with Kidney Disease.Genes · 2026Article
- Multi-Omics Integration Reveals the Genetic Mechanisms of Periodontitis and Predicts Therapeutic Drugs.International dental journal · 2026Article
- Translating genome-wide association studies at multiple scales: Drug target prioritization, cellular architectures, and organ imaging.Cell genomics · 2026Review
- Article
- Identifying therapeutic target genes for stroke through systematic druggable Mendelian randomization analysis.Medicine · 2026Article
- Single-Cell Transcriptome-Wide Mendelian Randomization and Colocalization Uncover Potential Immunocytes-Related Therapeutic Targets for Obesity.Journal of cellular and molecular medicine · 2026Article
- Association study uncovers obesity-linked variants in mobile elements as potential regulators of gene expression.iScience · 2026Article
- Article
- Decoding Alzheimer's Disease One Cell Class at a Time.Cellular and molecular neurobiology · 2026Review
- Identifying Potential Drug Targets in Coronary Atherosclerosis: Insights from the Druggable Genome and Mendelian Randomization.Cardiovascular drugs and therapy · 2026Article
- Single-Cell eQTL Revealing Brain Cell-Type-Specific Genetic Control of Insomnia.Journal of molecular neuroscience : MN · 2026Article
- Unraveling novel therapeutic targets for diffuse large B-cell lymphoma: a plasma multi-omics study.Frontiers in pharmacology · 2026Article
- The crotonylation reader DPF2 promotes the development and progression of colon adenocarcinoma through cell-type-specific immune regulation and metabolic reprogramming.Frontiers in pharmacology · 2026Article
- Integrating single-cell RNA sequencing and Mendelian randomization analysis to identify potential drug targets for dilated cardiomyopathy.Hereditas · 2025Article
- Integrative genetic analysis reveals new relationships between intraocular pressure, glaucoma, and ischemic stroke risk: a study based on combined SNP-to-gene, Mendelian randomization and pathway investigations.Briefings in bioinformatics · 2025Article
- Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases.Cardiovascular diabetology · 2025Article
- Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression.Nature communications · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
The human brain has been implicated in the pathogenesis of several complex diseases. Taking advantage of single-cell techniques, genome-wide association studies (GWAS) have taken it a step further and revealed brain cell-type-specific functions for disease loci. However, genetic causal associations inferred by Mendelian randomization (MR) studies usually include all instrumental variables from GWAS, which hampers the understanding of cell-specific causality. Here, we developed an analytical framework, Cell-Stratified MR (csMR), to investigate cell-stratified causality through colocalizing GWAS signals with single-cell eQTL from different brain cells. By applying to obesity-related traits, our results demonstrate the cell-type-specific effects of GWAS variants on gene expression, and indicate the benefits of csMR to identify cell-type-specific causal effect that is often hidden from bulk analyses. We also found csMR valuable to reveal distinct causal pathways between different obesity indicators. These findings suggest the value of our approach to prioritize target cells for extending genetic causation studies.
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