Evidence map›Paper›PMID 35853906›Full record

ArticleSchizophrenia (Heidelberg, Germany)2022

Dissecting schizophrenia phenotypic variation: the contribution of genetic variation, environmental exposures, and gene-environment interactions.

Hanxin Zhang, Atif Khan, Steven A Kushner, Andrey Rzhetsky

Open access · diamondAbstract read
In one paragraph

Article in Schizophrenia (Heidelberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

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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

4 authors at 2 institutions in 2 countries.

Hanxin ZhangCommittee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.ORCID http://orcid.org/0000-0001-5069-634X
Atif KhanDepartment of Medicine, and Institute of Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA.
Steven A KushnerDepartment of Psychiatry, Columbia University, New York, NY, USA.
Andrey RzhetskyCommittee on Genetics, Genomics and Systems Biology, The University of Chicago, Chicago, IL, 60637, USA. andrey.rzhetsky@uchicago.edu.ORCID http://orcid.org/0000-0001-6959-7405
University of Chicago · USErasmus MC · NL

Funding

Modeling the temporal succession of phenotypes & environnnental cuesP50MH094267 · NIMH · UNIVERSITY OF CHICAGO · PI RZHETSKY, ANDREY · 2011 to 2015
$10.2M
MAPGen Knowledge Base (MAPGenKB) and Coordination CenterU01HL108634 · NHLBI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CRANDALL, EDWARD DAVID, ZHOU, XIANGHONG JASMINE · 2011 to 2015
$5.3M
Mendelian Disease - Asthma Comorbidity to Find Subgroup-Specific Asthma GenesR01HL122712 · NHLBI · UNIVERSITY OF CHICAGO · PI OBER, CAROLE, RZHETSKY, ANDREY · 2015 to 2018
$3.1M
NHLBI NIH HHS R01 HL122712NHLBI NIH HHS U01 HL108634NIMH NIH HHS P50 MH094267
6 · The paper itself

Abstract

Schizophrenia is among the leading causes of disability worldwide. Prior studies have conclusively demonstrated that the etiology of schizophrenia contains a strong genetic component. However, the understanding of environmental contributions and gene-environment interactions have remained less well understood. Here, we estimated the genetic and environmental contributions to schizophrenia risk using a unique combination of data sources and mathematical models. We used the administrative health records of 481,657 U.S. individuals organized into 128,989 families. In addition, we employed rich geographically specific measures of air, water, and land quality across the United States. Using models of progressively increasing complexity, we examined both linear and non-linear contributions of genetic variation and environmental exposures to schizophrenia risk. Our results demonstrate that heritability estimates differ significantly when gene-environment interactions are included in the models, dropping from 79% for the simplest model, to 46% in the best-fit model which included the full set of linear and non-linear parameters. Taken together, these findings suggest that environmental factors are an important source of explanatory variance underlying schizophrenia risk. Future studies are warranted to further explore linear and non-linear environmental contributions to schizophrenia risk and investigate the causality of these associations.

Identifiers

PMID35853906
PMCPMC9261082
OpenAlexW4280509176

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.