Evidence map›Paper›PMID 34356078›Full record

ArticleGenes2021

Limited Association between Schizophrenia Genetic Risk Factors and Transcriptomic Features.

Alice W Yu, J David Peery, Hyejung Won

Open access · goldAbstract read
In one paragraph

Article in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Antidepressant Augmentation of Antipsychotic Treatment in Schizophrenia: A Narrative Review.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Review
  2. Article
  3. Article
  4. Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023
    Article
  5. 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

3 authors at 1 institution in 1 country.

Alice W YuDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.ORCID 0000-0003-2640-1737
J David PeeryDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Hyejung WonDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.ORCID 0000-0003-3651-0566
University of North Carolina at Chapel Hill · US

Funding

Deciphering Cell-type Specific Regulatory Landscape in Human BrainDP2MH122403 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WON, HYEJUNG · 2019 to 2019
$2.3M
Connecting gene regulatory mechanisms in human brain to psychiatric illnessR00MH113823 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WON, HYEJUNG · 2018 to 2020
$719k
Using H-MAGMA to decipher neurobiological bases of smoking and alcohol use traitsR21DA051921 · NIDA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WON, HYEJUNG · 2020 to 2021
$453k
NIDA NIH HHS R21DA051921NIMH NIH HHS DP2MH122403NIMH NIH HHS R00MH113823
6 · The paper itself

Abstract

Schizophrenia is a polygenic disorder with many genomic regions contributing to schizophrenia risk. The majority of genetic variants associated with schizophrenia lie in the non-coding genome and are thought to contribute to transcriptional regulation. Extensive transcriptomic dysregulation has been detected from postmortem brain samples of schizophrenia-affected individuals. However, the relationship between schizophrenia genetic risk factors and transcriptomic features has yet to be explored. Herein, we examined whether varying gene expression features, including differentially expressed genes (DEGs), co-expression networks, and central hubness of genes, contribute to the heritability of schizophrenia. We leveraged quantitative trait loci and chromatin interaction profiles to identify schizophrenia risk variants assigned to the genes that represent different transcriptomic features. We then performed stratified linkage disequilibrium score regression analysis on these variants to estimate schizophrenia heritability enrichment for different gene expression features. Notably, DEGs and co-expression networks showed nominal heritability enrichment. This nominal association can be partly explained by cellular heterogeneity, as DEGs were associated with the genetic risk of schizophrenia in a cell type-specific manner. Moreover, DEGs were enriched for target genes of schizophrenia-associated transcription factors, suggesting that the transcriptomic signatures of schizophrenia are the result of transcriptional regulatory cascades elicited by genetic risk factors.

Indexed as

Gene Regulatory NetworksGenetic Predisposition to DiseasePolymorphism, Single NucleotideQuantitative Trait LociTranscriptomeGene Expression RegulationGenome-Wide Association StudyHumansMultifactorial InheritanceSchizophreniaco-expression networksdifferentially expressed genesGWASLD score regressionschizophreniatranscriptional regulation

Identifiers

PMID34356078
PMCPMC8304922
OpenAlexW3180822706

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.