Evidence map›Paper›PMID 42181293›Full record

ArticleBiological psychiatry global open science2026

Do Genetic Variants Directly Shape Population-Level Schizophrenia Burden? A Global Genomic Analysis.

Junxian Tao, Haiyan Chen, Siyu Wei, Yuping Zou, Chen Sun, Jing Xu, Lian Duan, Yuanbo Zhan, Ruilin Li, Jiacheng Wang and 17 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biological psychiatry global open science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

27 authors.

Junxian TaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Haiyan ChenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Siyu WeiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yuping ZouCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Chen SunCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Jing XuFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China.
Lian DuanCentral Laboratory, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Yuanbo ZhanDepartment of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Ruilin LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Jiacheng WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Linna YuanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Wei SheCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Songlin LuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Ning WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Qinduo RenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yan GuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yuan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Chang WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Hongsheng TianCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Chen ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yu DongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Guoping TangDepartment of Medical Engineering, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China.
Zhenwei ShangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Wenhua LvCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Mingming ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Hongchao LvCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yongshuai JiangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Schizophrenia imposes a substantial global health burden, with marked geographic variation in incidence, prevalence, and disability-adjusted life years (DALYs). Although genome-wide association studies (GWASs) have identified numerous individual-level risk variants, it remains unclear whether cross-population differences in allele frequencies are associated with variation in population-level disease burden. Methods: We integrated allele frequencies from the 1000 Genomes Project with age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), and age-standardized DALY rate (ASDR) across 20 countries (1990-2021) using the Global Burden of Disease 2021 data. Associations between allele frequencies and burden metrics were evaluated using linear mixed-effects models. Independent signals were defined through linkage disequilibrium-based clumping and annotated via multi-omic gene prioritization. Polygenic risk score (PRS) analyses were conducted in the UK Biobank for validation. Results: We identified 20, 20, and 14 independent single nucleotide polymorphisms (SNPs) significantly associated with ASIR, ASPR, and ASDR, respectively. Two loci overlapped with Psychiatric Genomics Consortium GWAS findings, including variants within Conclusions: These findings suggest that population-level allele frequency variation is associated with global differences in schizophrenia burden and accounts for a meaningful proportion of cross-population variation. This transferable population-genomic epidemiological framework may inform future research on complex diseases and mental health disparities.

Indexed as

EpidemiologyGenetic variationGlobal Burden of Disease (GBD)Population genomicsSchizophrenia

Identifiers

PMID42181293
PMCPMC13195605

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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.