Evidence map›Paper›PMID 38637810›Full record

SynthesisJournal of translational medicine2024

Dissecting the shared genetic landscape of anxiety, depression, and schizophrenia.

Yiming Tao, Rui Zhao, Bin Yang, Jie Han, Yongsheng Li

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
17.6field-weighted citation impact, top 1% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Pooled it
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  7. Review
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  9. ZDHHC5 and ZDHHC14 promote depression via the mediation of double-negative T cells.Mammalian genome : official journal of the International Mammalian Genome Society · 2025
    Article
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  11. Review
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  14. Observational
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  18. Genetic factors associated with erectile dysfunction- mendelian randomisation analysis.American journal of clinical and experimental urology · 2025
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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

5 authors at 4 institutions in 1 country.

Yiming Tao *Department of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan, 430030, China.
Rui Zhao *Department of Laboratory Medicine, The First Afliated Hospital of Chongqing Medical University, Chongqing, 400042, China.
Bin YangDepartment of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan, 430030, China.
Jie HanDepartment of Emergency, School of Medicine, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China. 958987973@qq.com.
Yongsheng LiDepartment of Intensive Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hankou, Wuhan, 430030, China. tjh_ysli@163.com.ORCID 0000-0003-4164-9589
Tongji Hospital · CNQingdao University · CNShandong Provincial Hospital · CNThe Affiliated Yongchuan Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNumerous studies highlight the genetic underpinnings of mental disorders comorbidity, particularly in anxiety, depression, and schizophrenia. However, their shared genetic loci are not well understood. Our study employs Mendelian randomization (MR) and colocalization analyses, alongside multi-omics data, to uncover potential genetic targets for these conditions, thereby informing therapeutic and drug development strategies.

methodsWe utilized the Consortium for Linkage Disequilibrium Score Regression (LDSC) and Mendelian Randomization (MR) analysis to investigate genetic correlations among anxiety, depression, and schizophrenia. Utilizing GTEx V8 eQTL and deCODE Genetics pQTL data, we performed a three-step summary-data-based Mendelian randomization (SMR) and protein-protein interaction analysis. This helped assess causal and comorbid loci for these disorders and determine if identified loci share coincidental variations with psychiatric diseases. Additionally, phenome-wide association studies, drug prediction, and molecular docking validated potential drug targets.

resultsWe found genetic correlations between anxiety, depression, and schizophrenia, and under a meta-analysis of MR from multiple databases, the causal relationships among these disorders are supported. Based on this, three-step SMR and colocalization analyses identified ITIH3 and CCS as being related to the risk of developing depression, while CTSS and DNPH1 are related to the onset of schizophrenia. BTN3A1, PSMB4, and TIMP4 were identified as comorbidity loci for both disorders. Molecules that could not be determined through colocalization analysis were also presented. Drug prediction and molecular docking showed that some drugs and proteins have good binding affinity and available structural data.

conclusionsOur study indicates genetic correlations and shared risk loci between anxiety, depression, and schizophrenia. These findings offer insights into the underlying mechanisms of their comorbidities and aid in drug development.

Indexed as

SchizophreniaAntigens, CDAnxietyAnxiety DisordersButyrophilinsDepressionGenome-Wide Association StudyHumansMolecular Docking SimulationPolymorphism, Single NucleotideProteasome Endopeptidase ComplexAntigens, CDBTN3A1 protein, humanButyrophilinsProteasome Endopeptidase ComplexPSMB4 protein, humanAnxietyDepressionDrug targetsSchizophreniaShared genetic architecture

Identifiers

PMID38637810
PMCPMC11025255
OpenAlexW4394931329

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.