Evidence map›Paper›PMID 23369358›Full record

ArticleBMC medical genomics2013

Exploring the pathogenetic association between schizophrenia and type 2 diabetes mellitus diseases based on pathway analysis.

Yanli Liu, Zezhi Li, Meixia Zhang, Youping Deng, Zhenghui Yi, Tieliu Shi

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 3 pooled it
4.0field-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

44 citing papers in PubMed, 3 syntheses or guidelines pooled it, 87 citations in OpenAlex.

  1. Cholesterol and triglyceride levels in first-episode psychosis: systematic review and meta-analysis.The British journal of psychiatry : the journal of mental science · 2017
    Pooled it
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  8. miRNA-Based Diagnosis of Schizophrenia Using Machine Learning.International journal of molecular sciences · 2025
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  17. Mechanisms Underlying the Comorbidity of Schizophrenia and Type 2 Diabetes Mellitus.The international journal of neuropsychopharmacology · 2021
    Review
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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

6 authors at 5 institutions in 2 countries.

Yanli LiuCenter for Bioinformatics and Computational Biology, and The Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China.
Zezhi Li
Meixia Zhang
Youping Deng
Zhenghui Yi
Tieliu Shi
East China Normal University · CNRush University Medical Center · USSecond Military Medical University · CNShanghai Jiao Tong University · CNWest China Hospital of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSchizophrenia (SCZ) and type 2 diabetes mellitus (T2D) are both complex diseases. Accumulated studies indicate that schizophrenia patients are prone to present the type 2 diabetes symptoms, but the potential mechanisms behind their association remain unknown. Here we explored the pathogenetic association between SCZ and T2D based on pathway analysis and protein-protein interaction.

resultsWith sets of prioritized susceptibility genes for SCZ and T2D, we identified significant pathways (with adjusted p-value < 0.05) specific for SCZ or T2D and for both diseases based on pathway enrichment analysis. We also constructed a network to explore the crosstalk among those significant pathways. Our results revealed that some pathways are shared by both SCZ and T2D diseases through a number of susceptibility genes. With 382 unique susceptibility proteins for SCZ and T2D, we further built a protein-protein interaction network by extracting their nearest interacting neighbours. Among 2,104 retrieved proteins, 364 of them were found simultaneously interacted with susceptibility proteins of both SCZ and T2D, and proposed as new candidate risk factors for both diseases. Literature mining supported the potential association of partial new candidate proteins with both SCZ and T2D. Moreover, some proteins were hub proteins with high connectivity and interacted with multiple proteins involved in both diseases, implying their pleiotropic effects for the pathogenic association. Some of these hub proteins are the components of our identified enriched pathways, including calcium signaling, g-secretase mediated ErbB4 signaling, adipocytokine signaling, insulin signaling, AKT signaling and type II diabetes mellitus pathways. Through the integration of multiple lines of information, we proposed that those signaling pathways, which contain susceptibility genes for both diseases, could be the key pathways to bridge SCZ and T2D. AKT could be one of the important shared components and may play a pivotal role to link both of the pathogenetic processes.

conclusionsOur study is the first network and pathway-based systematic analysis for SCZ and T2D, and provides the general pathway-based view of pathogenetic association between two diseases. Moreover, we identified a set of candidate genes potentially contributing to the linkage between these two diseases. This research offers new insights into the potential mechanisms underlying the co-occurrence of SCZ and T2D, and thus, could facilitate the inference of novel hypotheses for the co-morbidity of the two diseases. Some etiological factors that exert pleiotropic effects shared by the significant pathways of two diseases may have important implications for the diseases and could be therapeutic intervention targets.

Indexed as

Databases, FactualDiabetes Mellitus, Type 2Genetic Predisposition to DiseaseGenome-Wide Association StudyHumansMetabolic Networks and PathwaysPolymorphism, Single NucleotideProtein Interaction MapsSchizophreniaSignal Transduction

Identifiers

PMID23369358
PMCPMC3552677
OpenAlexW2168162959

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.