Evidence map›Paper›PMID 39677459›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Genomic network analysis characterizes genetic architecture and identifies trait-specific biology.

Jackson G Thorp, Zachary F Gerring, William R Reay, Eske M Derks, Andrew D Grotzinger

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Jackson G ThorpDepartment of Brain and Mental Health, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.ORCID 0000-0002-9461-6417
Zachary F GerringDepartment of Brain and Mental Health, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.ORCID 0000-0002-2445-1266
William R ReayMenzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.ORCID 0000-0001-7689-2453
Eske M DerksDepartment of Brain and Mental Health, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.ORCID 0000-0002-6292-6883
Andrew D GrotzingerInstitute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO.ORCID 0000-0001-7852-9244

Funding

Dissecting the Multivariate Genetic Architecture of Psychiatric DiseasesR01MH120219 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI NIVARD, MICHEL GUILLAUME, TUCKER-DROB, ELLIOT MAX · 2020 to 2024
$3.3M
Large-Scale Genomic Analysis of Aging-Related Cognitive Change Prior to Dementia OnsetRF1AG073593 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI TUCKER-DROB, ELLIOT MAX · 2021 to 2021
$2.1M
Large-Scale Genomic Analysis of Aging-Related Cognitive Change Prior to Dementia OnsetR01AG073593 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI TUCKER-DROB, ELLIOT MAX · 2024 to 2025
$1.3M
NIA NIH HHS R01 AG073593NIA NIH HHS RF1 AG073593NIMH NIH HHS R01 MH120219
6 · The paper itself

Abstract

Pervasive genetic overlap across human complex traits necessitates developing multivariate methods that can parse pleiotropic and trait-specific genetic signals. Here, we introduce Genomic Network Analysis (GNA), an analytic framework that applies the principles of network modelling to estimates of genetic overlap derived from genome-wide association study (GWAS) summary statistics. The result is a genomic network that describes the conditionally independent genetic associations between traits that remain when controlling for shared signal with the broader network of traits. Graph theory metrics provide added insight by formally quantifying the most important traits in the genomic network. GNA can discover additional trait-specific pathways by incorporating gene expression or genetic variants into the network to estimate their conditional associations with each trait. Extensive simulations establish GNA is well-powered for most GWAS. Application to a diverse set of traits demonstrate that GNA yields critical insight into the genetic architecture that demarcate genetically overlapping traits at varying levels of biological granularity.

Identifiers

PMID39677459
PMCPMC11643167

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.