Evidence map›Paper›PMID 42608581›Full record

ArticleEuropean archives of psychiatry and clinical neuroscience2026

Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.

Peng Shen, Haohao Xu, Yan Zhou, Xinming Sun, Ruijun Cai, Di Jia, Weiming Zhao

Abstract read
In one paragraph

Article in European archives of psychiatry and clinical neuroscience, 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
–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

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

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

7 authors.

Peng Shen *The First Psychiatric Hospital of Harbin, Harbin, 150056, Heilongjiang, China.
Haohao Xu *Department of Medical Technology, Qiqihar Medical University, Qiqihar, 161006, Heilongjiang, China.
Yan ZhouThe First Clinical Medicine College, Mudanjiang Medical University, Mudanjiang, 157011, Heilongjiang, China.
Xinming SunQiqihar Medical University, Qiqihar, 161006, Heilongjiang, China.
Ruijun CaiDepartment of Pharmacy, Shanghai General Hospital Jiuquan Hospital (The People's Hospital of Jiuquan), Jiuquan, 735000, Gansu, China. ruijun0311@126.com.
Di JiaDepartment of Medical Technology, Qiqihar Medical University, Qiqihar, 161006, Heilongjiang, China. jiadi86@163.com.
Weiming ZhaoHeilongjiang University of Chinese Medicine, Harbin, 150040, Heilongjiang, China. zhaowm1969@163.com.

Funding

Construction Project of Dominant Characteristic Disciplines of Qiqihar Medical University QYZDXK-003Innovation and Entrepreneurship Project for College Students of Qiqihar Medical University 202111230053Self-selected Research Fund Project of the Qiqihar Academy of Medical Sciences QMSI2026Z
6 · The paper itself

Abstract

backgroundBipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood.

methodsWe integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening.

resultsThe integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure.

conclusionThis integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.

Indexed as

Bipolar DisorderGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMultiomicsQuantitative Trait LociTranscriptomeBipolar disorderMendelian randomizationSingle-cell expression quantitative trait lociTranscriptome-wide association study

Identifiers

PMID42608581
PMCPMC13562346

What OpenQuestion holds

Textmetadata
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.