Evidence map›Paper›PMID 29100087›Full record

ArticleAmerican journal of human genetics2017

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

Huwenbo Shi, Nicholas Mancuso, Sarah Spendlove, Bogdan Pasaniuc

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of human genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 206 papers, 17 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
206citing papers in PubMed, 17 pooled it
–field-weighted citation impact
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

206 citing papers in PubMed, 17 syntheses or guidelines pooled it.

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  5. A genome-wide association meta-analysis of all-cause and vascular dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
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146 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.

Huwenbo ShiBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90024, USA. Electronic address: shihuwenbo@ucla.edu.
Nicholas MancusoDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90024, USA.
Sarah SpendloveDepartment of Biology, Brigham Young University, Provo, UT 84602, USA.
Bogdan PasaniucBioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90024, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90024, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90024, USA.

Funding

STATISTICAL METHODS FOR GENE MAPPINGR01GM053275 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LANGE, KENNETH L · 1995 to 2019
$9.3M
Quantifying and Characterizing the shared genetic contribution to common cancersU01CA194393 · NCI · UNIVERSITY OF WASHINGTON · PI KRAFT, PETER, LINDSTROEM, SARA · 2015 to 2023
$3.0M
Integrative approaches for mapping the genetic risk of complex traitsR01HG009120 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PASANIUC, BOGDAN · 2017 to 2021
$2.3M
Undergraduate Research Experience in Neuropsychiatric GenomicsR25MH109172 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ESKIN, ELEAZAR, FREIMER, NELSON B. · 2016 to 2020
$429k
NCI NIH HHS U01 CA194393NHGRI NIH HHS R01 HG009120NIGMS NIH HHS R01 GM053275NIMH NIH HHS R25 MH109172
6 · The paper itself

Abstract

Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships.

Indexed as

Genetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyGenomicsHumansLinkage DisequilibriumModels, GeneticPhenotypeQuantitative Trait Locicomplex traitsepidemiologyetiologygenetic correlationgenetic covariancegenome-wide association studyheritabilitysummary statistics

Identifiers

PMID29100087
PMCPMC5673668

What OpenQuestion holds

Textmetadata
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Registered trials

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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.