Evidence map›Paper›PMID 40211091›Full record

ArticlePsychological medicine2025

Associations of polygenic risk score, environmental factors, and their interactions with the risk of schizophrenia spectrum disorders.

Fatima Zahra Rami, Hyungwoo Seo, Chaeyeong Kang, Seunghwan Park, Ling Li, Thi-Hung Le, Sung-Wan Kim, Seung-Hee Won, Wonil Chung, Young-Chul Chung

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Article in Psychological medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Review
  2. DNA methylation as proxy of genetic, prenatal and perinatal psychiatric risk factors.medRxiv : the preprint server for health sciences · 2026
    Article
  3. Gestational kynurenine metabolites mediate effects of pregnancy adiposity on child negative affect.Journal of child psychology and psychiatry, and allied disciplines · 2026
    Article
  4. Article
4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Fatima Zahra RamiResearch Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea.
Hyungwoo SeoDepartment of Statistics and Actuarial Science, Soongsil University, Seoul, South Korea.
Chaeyeong KangResearch Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea.
Seunghwan ParkDepartment of Statistics and Actuarial Science, Soongsil University, Seoul, South Korea.
Ling LiResearch Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea.
Thi-Hung LeResearch Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea.
Sung-Wan KimDepartment of Psychiatry, Chonnam National University Medical School, Gwangju, South Korea.
Seung-Hee WonDepartment of Psychiatry, School of Medicine, Kyungpook National University, Daegu, South Korea.
Wonil ChungDepartment of Statistics and Actuarial Science, Soongsil University, Seoul, South Korea.ORCID 0000-0002-5766-6247
Young-Chul ChungResearch Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, South Korea.ORCID 0000-0001-9491-1822

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEmerging evidence indicates that gene-environment interactions (GEIs) are important underlying mechanisms for the development of schizophrenia (SZ). We investigated the associations of polygenic risk score for SZ (PRS-SZ), environmental measures, and their interactions with case-control status and clinical phenotypes among patients with schizophrenia spectrum disorders (SSDs).

methodsThe PRS-SZ for 717 SSD patients and 356 healthy controls (HCs) were calculated using the LDpred model. The Korea-Polyenvironmental Risk Score-I (K-PERS-I) and Early Trauma Inventory-Self Report (ETI-SR) were utilized as environmental measures. Logistic and linear regression analyses were performed to identify the associations of PRS-SZ and two environmental measures with case-control status and clinical phenotypes.

resultsThe PRS-SZ explained 8.7% of SZ risk. We found greater associations of PRS-SZ and total scores of the K-PERS-I with case-control status compared to the ETI-SR total score. A significant additive interaction was found between PRS-SZ and K-PERS-I. With the subdomains of the K-PERS-I and ETI-SR, we identified significant multiplicative or additive interactions of PRS-SZ and parental socioeconomic status (pSES), childhood adversity, and recent life events in association with case-control status. For clinical phenotypes, significant interactions were observed between PRS-SZ and the ETI-SR total score for negative-self and between PRS-SZ and obstetric complications within the K-PERS-I for negative-others.

conclusionsOur findings suggest that the use of aggregate scores for genetic and environmental measures, PRS-SZ and K-PERS-I, can more accurately predict case-control status, and specific environmental measures may be more suitable for the exploration of GEIs.

Indexed as

Gene-Environment InteractionMultifactorial InheritanceSchizophreniaAdultCase-Control StudiesFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreHumansMaleMiddle AgedPhenotypeRepublic of KoreaRisk Factorsgene–environment interactionsKorea-Polyenvironmental Risk Scorepolygenic risk scoreSchizophrenia spectrum disorders

Identifiers

PMID40211091
PMCPMC12094650

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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.