Evidence map›Paper›PMID 35085493›Full record

ArticleAmerican journal of human genetics2022

Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity.

Marios Arvanitis, Karl Tayeb, Benjamin J Strober, Alexis Battle

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of human genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 5 pooled it
16.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 5 syntheses or guidelines pooled it, 88 citations in OpenAlex.

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7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Marios ArvanitisDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21211, USA; Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD 21205, USA.
Karl TayebDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21211, USA.
Benjamin J StroberDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21211, USA.
Alexis BattleDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21211, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD 21211, USA; Department of Genetic Medicine, Johns Hopkins University, Baltimore, MD 21205, USA. Electronic address: ajbattle@jhu.edu.
Johns Hopkins University · US

Funding

Utilizing Technology and AI Approaches to Facilitate Independence andResilience in Older AdultsP30AG073104 · NIA · JOHNS HOPKINS UNIVERSITY · PI Alexis Battle · 2021 to 2026
$31.2M
PATHOPHYSIOLOGY OF MYOCARDIAL DISEASEST32HL007227 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Chulan Kwon, WENDY S POST · 1985 to 2026
$21.2M
Modeling the dynamicimpact of rare and common genetic variation on gene expression anddiseaseR35GM139580 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI BATTLE, ALEXIS · 2021 to 2025
$3.1M
Methods for analysis of regulatory variation in cellular differentiationR01GM120167 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI BATTLE, ALEXIS · 2016 to 2019
$1.9M
NHLBI NIH HHS T32 HL007227NIA NIH HHS P30 AG073104NIGMS NIH HHS R01 GM120167NIGMS NIH HHS R35 GM139580
6 · The paper itself

Abstract

Uncovering the functional impact of genetic variation on gene expression is important in understanding tissue biology and the pathogenesis of complex traits. Despite large efforts to map expression quantitative trait loci (eQTLs) across many human tissues, our ability to translate those findings to understanding human disease has been incomplete, and the majority of disease loci are not explained by association with expression of a target gene. Cell-type specificity and the presence of multiple independent causal variants for many eQTLs are potential confounders contributing to the apparent discrepancy with disease loci. In this study, we investigate the tissue specificity of genetic effects on gene expression and the overlap with disease loci while considering the presence of multiple causal variants within and across tissues. We find evidence of pervasive tissue specificity of eQTLs, often masked by linkage disequilibrium that misleads traditional meta-analytic approaches. We propose CAFEH (colocalization and fine-mapping in the presence of allelic heterogeneity), a Bayesian method that integrates genetic association data across multiple traits, incorporating linkage disequilibrium to identify causal variants. CAFEH outperforms previous approaches in colocalization and fine-mapping. Using CAFEH, we show that genes with highly tissue-specific genetic effects are under greater selection, enriched in differentiation and developmental processes, and more likely to be involved in human disease. Last, we demonstrate that CAFEH can efficiently leverage the widespread allelic heterogeneity in genetic regulation of gene expression to prioritize the target tissue in genome-wide association complex trait loci, thereby improving our ability to interpret complex trait genetics.

Indexed as

AllelesGene Expression RegulationGenetic HeterogeneityGenome, HumanMultifactorial InheritanceAdipose TissueBayes TheoremChromosome MappingFibroblastsGenome-Wide Association StudyHeart VentriclesHumansLinkage DisequilibriumOrgan SpecificityQuantitative Trait LociThyroid GlandcolocalizationeQTLfine-mappingGWAStissue specificity

Identifiers

PMID35085493
PMCPMC8874223
OpenAlexW4221022235

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.