Evidence map›Paper›PMID 36271044›Full record

ArticleNature communications2022

Transcriptome-wide and stratified genomic structural equation modeling identify neurobiological pathways shared across diverse cognitive traits.

Andrew D Grotzinger, Javier de la Fuente, Gail Davies, Michel G Nivard, Elliot M Tucker-Drob

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
5.4field-weighted citation impact, top 4% 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

22 citing papers in PubMed, 32 citations in OpenAlex.

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  19. Artificial intelligence for dementia genetics and omics.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023
    Review
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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 at 4 institutions in 3 countries.

Andrew D GrotzingerInstitute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA. Andrew.Grotzinger@colorado.edu.ORCID 0000-0001-7852-9244
Javier de la FuenteDepartment of Psychology, University of Texas at Austin, Austin, TX, USA.
Gail DaviesLothian Birth Cohorts, University of Edinburgh, Edinburgh, UK.ORCID 0000-0003-1120-7026
Michel G NivardDepartment of Biological Psychology, VU University Amsterdam, Amsterdam, the Netherlands.ORCID 0000-0003-2015-1888
Elliot M Tucker-DrobDepartment of Psychology, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0001-5599-6237
The University of Texas at Austin · USNHS Lothian · GBUniversity of Colorado Boulder · USVrije Universiteit Amsterdam · NL

Funding

Program Development and Pilot CoreP30AG066614 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI DEBRA J. UMBERSON · 2020 to 2026
$5.2M
Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI Elizabeth T. Gershoff · 2017 to 2026
$5.2M
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
Cortisol, Socioeconomic Status, and Genetic Influences on Cognitive DevelopmentR01HD083613 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI TUCKER-DROB, ELLIOT MAX · 2016 to 2020
$3.0M
Evaluating Longitudinal Changes in the Human Structural Connectome in Relation to Cognitive AgingR01AG054628 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI TUCKER-DROB, ELLIOT MAX · 2017 to 2021
$2.7M
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
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NIA NIH HHS P30 AG066614NIA NIH HHS R01 AG054628NIA NIH HHS RF1 AG073593NICHD NIH HHS P2C HD042849NICHD NIH HHS R01 HD083613NIMH NIH HHS R01 MH120219
6 · The paper itself

Abstract

Functional genomic methods are needed that consider multiple genetically correlated traits. Here we develop and validate Transcriptome-wide Structural Equation Modeling (T-SEM), a multivariate method for studying the effects of tissue-specific gene expression across genetically overlapping traits. T-SEM allows for modeling effects on broad dimensions spanning constellations of traits, while safeguarding against false positives that can arise when effects of gene expression are specific to a subset of traits. We apply T-SEM to investigate the biological mechanisms shared across seven distinct cognitive traits (N = 11,263-331,679), as indexed by a general dimension of genetic sharing (g). We identify 184 genes whose tissue-specific expression is associated with g, including 10 genes not identified in univariate analysis for the individual cognitive traits for any tissue type, and three genes whose expression explained a significant portion of the genetic sharing across g and different subclusters of psychiatric disorders. We go on to apply Stratified Genomic SEM to identify enrichment for g within 28 functional categories. This includes categories indexing the intersection of protein-truncating variant intolerant (PI) genes and specific neuronal cell types, which we also find to be enriched for the genetic covariance between g and a psychotic disorders factor.

Indexed as

Genome-Wide Association StudyTranscriptomeCognitionGenomicsHumansLatent Class AnalysisPolymorphism, Single Nucleotide

Identifiers

PMID36271044
PMCPMC9586980
OpenAlexW4307137863

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.