Evidence map›Paper›PMID 36028495›Full record

ArticleTranslational psychiatry2022

Sex-specific genetic association between psychiatric disorders and cognition, behavior and brain imaging in children and adults.

Yuanyuan Gui, Xiaocheng Zhou, Zixin Wang, Yiliang Zhang, Zhaobin Wang, Geyu Zhou, Yize Zhao, Manhua Liu, Hui Lu, Hongyu Zhao

Open access · goldAbstract read
In one paragraph

Article in Translational psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.5field-weighted citation impact, top 5% 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

12 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
  2. Article
  3. Sex-Specific Genetic Architecture and Comorbidities of Alcohol Use Behaviors.medRxiv : the preprint server for health sciences · 2025
    Article
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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

10 authors at 2 institutions in 2 countries.

Yuanyuan GuiState Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Xiaocheng ZhouState Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0001-5635-9395
Zixin WangState Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Yiliang ZhangDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Zhaobin WangState Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Geyu ZhouProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
Yize ZhaoDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Manhua LiuMoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China.
Hui LuState Key Laboratory of Microbial metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China. huilu@sjtu.edu.cn.ORCID 0000-0001-8347-0830
Hongyu ZhaoDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA. hongyu.zhao@yale.edu.ORCID 0000-0003-1195-9607
Shanghai Jiao Tong University · CNYale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
ABCD-USA Consortium: Coordinating CenterU24DA041147 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SANDRA A BROWN, TERRY L. JERNIGAN · 2015 to 2026
$54.7M
ABCD-USA Consortium: Data Analysis, Informatics and Resource CenterU24DA041123 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE · 2015 to 2026
$51.5M
Adolescent Substance Use Initiation: Disentangling neurocognitive risks from consequences using longitudinal and genetically-informed methodsU01DA041120 · NIDA · UNIVERSITY OF MINNESOTA · PI Monica Luciana, Sylia Wilson · 2015 to 2026
$34.5M
ABCD-USA Consortium: Research ProjectU01DA041089 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Joanna Jacobus, Susan F. Tapert · 2015 to 2026
$31.7M
Prospective Research Studies of Maturation (PRISM)- Research ProjectU01DA041134 · NIDA · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI ERIN MCGLADE, PERRY FRANKLIN RENSHAW · 2015 to 2026
$29.2M
ABCD-USA CONSORTIUM: RESEARCH PROJECTU01DA041048 · NIDA · CHILDREN'S HOSPITAL OF LOS ANGELES · PI Megan Marie Herting, ELIZABETH R SOWELL · 2015 to 2026
$28.7M
ABCD-USA Consortium: Research ProjectU01DA041106 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mary M Heitzeg, Chandra Sekhar Sripada · 2015 to 2026
$24.9M
FIU-ABCD: Pathways and Mechanisms to Addiction in the Latino Youth of South FloridaU01DA041156 · NIDA · FLORIDA INTERNATIONAL UNIVERSITY · PI Raul Gonzalez, Angela R Laird · 2015 to 2026
$22.8M
ABCD-USA Consortium: Research ProjectU01DA041148 · NIDA · OREGON HEALTH & SCIENCE UNIVERSITY · PI Damien A Fair, Rebekah S Huber · 2015 to 2026
$22.3M
ABCD-USA: NYC Research ProjectU01DA041174 · NIDA · YALE UNIVERSITY · PI Arielle Ryan Baskin-Sommers, Betty J Casey · 2015 to 2026
$19.7M
Adolescent Brain Cognitive Development (ABCD) Prospective Research in Studies of Maturation (PRISM) ConsortiumU01DA041117 · NIDA · UNIVERSITY OF MARYLAND BALTIMORE · PI LINDA CHANG, THOMAS M ERNST · 2015 to 2026
$19.5M
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NCATS NIH HHS UL1 TR001863NIDA NIH HHS U01 DA041022NIDA NIH HHS U01 DA041025NIDA NIH HHS U01 DA041028NIDA NIH HHS U01 DA041048NIDA NIH HHS U01 DA041089NIDA NIH HHS U01 DA041093NIDA NIH HHS U01 DA041106NIDA NIH HHS U01 DA041117NIDA NIH HHS U01 DA041120NIDA NIH HHS U01 DA041134NIDA NIH HHS U01 DA041148NIDA NIH HHS U01 DA041156NIDA NIH HHS U01 DA041174NIDA NIH HHS U24 DA041123NIDA NIH HHS U24 DA041147
6 · The paper itself

Abstract

Although there are pronounced sex differences for psychiatric disorders, relatively little has been published on the heterogeneity of sex-specific genetic effects for these traits until very recently for adults. Much less is known about children because most psychiatric disorders will not manifest until later in life and existing studies for children on psychiatric traits such as cognitive functions are underpowered. We used results from publicly available genome-wide association studies for six psychiatric disorders and individual-level data from the Adolescent Brain Cognitive Development (ABCD) study and the UK Biobank (UKB) study to evaluate the associations between the predicted polygenic risk scores (PRS) of these six disorders and observed cognitive functions, behavioral and brain imaging traits. We further investigated the mediation effects of the brain structure and function, which showed heterogeneity between males and females on the correlation between genetic risk of schizophrenia and fluid intelligence. There was significant heterogeneity in genetic associations between the cognitive traits and psychiatric disorders between sexes. Specifically, the PRSs of schizophrenia of boys showed stronger correlation with eight of the ten cognitive functions in the ABCD data set; whereas the PRSs of autism of females showed a stronger correlation with fluid intelligence in the UKB data set. Besides cognitive traits, we also found significant sexual heterogeneity in genetic associations between psychiatric disorders and behavior and brain imaging. These results demonstrate the underlying early etiology of psychiatric disease and reveal a shared and unique genetic basis between the disorders and cognition traits involved in brain functions between the sexes.

Indexed as

Mental DisordersMultifactorial InheritanceAdolescentAdultChildCognitionFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleNeuroimagingRisk Factors

Identifiers

PMID36028495
PMCPMC9418275
OpenAlexW4293199501

What OpenQuestion holds

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Registered trials

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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.