Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression.

Nature communications - 7 Jun 2024

Hao Ruo-Han, Zhang Tian-Pei, Jiang Feng, Liu Jun-Hui, Dong Shan-Shan, Li Meng, Guo Yan, Yang Tie-Lin

Abstract excerpt

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...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Brain
Share to Causality

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Gene Expression

Share to Gene Expression Regulation

Share to Mendelian Randomization Analysis

Share to Obesity

Share to Quantitative Trait Loci

Share to Single-Cell Analysis

Source

Open in PubMed Open full text

Identifiers

PMID: 38849352
DOI: 10.1038/s41467-024-49263-4
PMCID: PMC11161590

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression.PMID 38849352Read ↗

Counterfactual inference for single-cell gene expression analysisSemantic proximity Read ↗

Conditional polygenic enrichment distinguishes causal from tagging disease-critical cell populations in single-cell RNA-seqSemantic proximity Read ↗

EPIC: inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencingSemantic proximity Read ↗

Single-cell Mendelian randomisation identifies cell-type specific genetic effects on human brain disease and behaviourSemantic proximity Read ↗

EPIC: Inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing.Semantic proximity Read ↗

Deciphering cell type-specific causal genetic effects on brain imaging-derived phenotypes and disorders with single-cell Mendelian randomization.Semantic proximity Read ↗

Identifying independent causal cell types for human diseases and risk variantsSemantic proximity Read ↗

Machine Learning-Based Prediction of Cell-type Resolved Brain eQTLs Enhances Discovery of Variants Explaining Alzheimer’s Disease HeritabilitySemantic proximity Read ↗

Inferring relevant cell types for complex traits using single-cell gene expressionSemantic proximity Read ↗

Single-Cell Mendelian Randomization Identifies Cell-Type Specific Genetic Drivers of Lung Cancer SubtypesSemantic proximity Read ↗

sc2GWAS: a comprehensive platform linking single cell and GWAS traits of human.Semantic proximity Read ↗

A unified framework for cell-type-specific eQTL prioritization by integrating bulk and scRNA-seq data.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.