Evidence map›Paper›PMID 36689559›Full record

ArticlePLoS genetics2023

Decomposing heritability and genetic covariance by direct and indirect effect paths.

Jie Song, Yiqing Zou, Yuchang Wu, Jiacheng Miao, Ze Yu, Jason M Fletcher, Qiongshi Lu

Abstract read
In one paragraph

Article in PLoS genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

7 authors.

Jie SongDepartment of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.ORCID 0000-0003-4799-3575
Yiqing ZouDepartment of Statistics, Stanford University, Stanford, CA, United States of America.
Yuchang WuDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Wisconsin, United States of America.
Jiacheng MiaoDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Wisconsin, United States of America.
Ze YuDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Wisconsin, United States of America.ORCID 0000-0002-0583-1351
Jason M FletcherCenter for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Qiongshi LuDepartment of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.ORCID 0000-0002-4514-0969

Funding

Statistical Data Enclave CoreP30AG017266 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Michal Engelman · 1999 to 2026
$17.0M
Medical Research Council MC_PC_17228NIA NIH HHS P30 AG017266
6 · The paper itself

Abstract

Estimation of heritability and genetic covariance is crucial for quantifying and understanding complex trait genetic architecture and is employed in almost all recent genome-wide association studies (GWAS). However, many existing approaches for heritability estimation and almost all methods for estimating genetic correlation ignore the presence of indirect genetic effects, i.e., genotype-phenotype associations confounded by the parental genome and family environment, and may thus lead to incorrect interpretation especially for human sociobehavioral phenotypes. In this work, we introduce a statistical framework to decompose heritability and genetic covariance into multiple components representing direct and indirect effect paths. Applied to five traits in UK Biobank, we found substantial involvement of indirect genetic components in shared genetic architecture across traits. These results demonstrate the effectiveness of our approach and highlight the importance of accounting for indirect effects in variance component analysis of complex traits.

Indexed as

Genome-Wide Association StudyMultifactorial InheritanceGenetic Association StudiesHumansModels, GeneticPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID36689559
PMCPMC9894552

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.