Evidence map›Paper›PMID 39276178›Full record

ArticleJournal of molecular medicine (Berlin, Germany)2024

Prefrontal cortex astrocytes in major depressive disorder: exploring pathogenic mechanisms and potential therapeutic targets.

Yarui Pan, Lan Xiang, Tingting Zhu, Haiyan Wang, Qi Xu, Faxue Liao, Juan He, Yongquan Wang

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of molecular medicine (Berlin, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. AiScience · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
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

8 authors.

Yarui PanDepartment of Pharmacology, School of Integrated Chinese and Western Medicine, Anhui University of Chinese Medicine, Hefei, 230012, China.
Lan XiangDepartment of Gynecology, Anhui Maternal and Child Health Hospital, Hefei, 230012, China.
Tingting ZhuDepartment of Gynecology, Anhui Maternal and Child Health Hospital, Hefei, 230012, China.
Haiyan WangDepartment of Gynecology, Anhui Maternal and Child Health Hospital, Hefei, 230012, China.
Qi XuSchool of Basic Medical Sciences, Anhui Medical University, Hefei, 230032, China.
Faxue LiaoDepartment of Orthopaedics, The First Affiliated Hospital of Anhui Medical University, Hefei, 230000, China. liaofaxue@126.com.ORCID 0009-0006-9667-895X
Juan HeDepartment of Gynecology, Anhui Maternal and Child Health Hospital, Hefei, 230012, China. hejuanhf@163.com.
Yongquan WangAnhui Public Health Clinical Center, The First Affiliated Hospital of Anhui Medical University, Xinzhan District, No. 100 Huaihai Avenue, Hefei, 230000, China. YongquanWang83@163.com.

Funding

Anhui Institute of translational medicine NO. 2022zhyx-C91Anhui Medical University No.2022xkj201
6 · The paper itself

Abstract

Major depressive disorder (MDD) is a prevalent mental health condition characterized by persistent feelings of sadness and hopelessness, affecting millions globally. The precise molecular mechanisms underlying MDD remain elusive, necessitating comprehensive investigations. Our study integrates transcriptomic analysis, functional assays, and computational modeling to explore the molecular landscape of MDD, focusing on the DLPFC. We identify key genomic alterations and co-expression modules associated with MDD, highlighting potential therapeutic targets. Functional enrichment and protein-protein interaction analyses emphasize the role of astrocytes in MDD progression. Machine learning is employed to develop a predictive model for MDD risk assessment. Single-cell and spatial transcriptomic analyses provide insights into cell type-specific expression patterns, particularly regarding astrocytes. We have identified significant genomic alterations and co-expression modules associated with MDD in the DLPFC. Key genes involved in neuroactive ligand-receptor interaction pathways, notably in astrocytes, have been highlighted. Additionally, we developed a predictive model for MDD risk assessment based on selected key genes. Single-cell and spatial transcriptomic analyses underscored the role of astrocytes in MDD. Virtual screening of compounds targeting GPR37L1, KCNJ10, and PPP1R3C proteins has identified potential therapeutic candidates. In summary, our comprehensive approach enhances the understanding of MDD's molecular underpinnings and offers promising opportunities for advancing therapeutic interventions, ultimately aiming to alleviate the burden of this debilitating mental health condition. KEY MESSAGES: Our investigation furnishes insightful revelations concerning the dysregulation of astrocyte-associated processes in MDD. We have pinpointed specific genes, namely KCNJ10, PPP1R3C, and GPR37L1, as potential candidates warranting further exploration and therapeutic intervention. We incorporate a virtual screening of small molecule compounds targeting KCNJ10, PPP1R3C, and GPR37L1, presenting a promising trajectory for drug discovery in MDD.

Indexed as

AstrocytesMajor Depressive DisorderPotassium Channels, Inwardly RectifyingPrefrontal CortexGene Expression ProfilingHumansKcnj10 ChannelProtein Interaction MapsReceptors, G-Protein-CoupledSingle-Cell AnalysisTranscriptomeKcnj10 ChannelPotassium Channels, Inwardly RectifyingReceptors, G-Protein-CoupledAstrocytesBioinformaticsMajor depressive disorderPrefrontal cortexVirtual screening

Identifiers

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.