Evidence map›Paper›PMID 39385284›Full record

ArticleChinese medicine2024

Identification of molecular targets of Hypericum perforatum in blood for major depressive disorder: a machine-learning pharmacological study.

Zewen Xu, Ayana Meegol Rasteh, Angela Dong, Panpan Wang, Hengrui Liu

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Article in Chinese medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

39 citing papers in PubMed.

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  6. [Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026
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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.

Zewen XuSchool of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, China.
Ayana Meegol RastehArchbishop Mitty High School, San Jose, CA, USA.
Angela DongHavergal College, Toronto, Canada.
Panpan WangThe First Affiliated Hospital of Jinan University, Guangzhou, China. wangpp@jnu.edu.cn.
Hengrui LiuCancer Research Institute, Jinan University, Guangzhou, China. lh@yinuobiomedical.cn.ORCID http://orcid.org/0000-0002-5369-3926

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMajor depressive disorder (MDD) is one of the most common psychiatric disorders worldwide. Hypericum perforatum (HP) is a traditional herb that has been shown to have antidepressant effects, but its mechanism is unclear. This study aims to identify the molecular targets of HP for the treatment of MDD.

methodsWe performed differential analysis and weighted gene co-expression network analysis (WGCNA) with blood mRNA expression cohort of MDD and healthy control to identify DEGs and significant module genes (gene list 1). Three databases, CTD, DisGeNET, and GeneCards, were used to retrieve MDD-related gene intersections to obtain MDD-predicted targets (gene list 2). The validated targets were retrieved from the TCMSP database (gene list 3). Based on these three gene lists, 13 key pathways were identified. The PPI network was constructed by extracting the intersection of genes and HP-validated targets on all key pathways. Key therapeutic targets were obtained using MCODE and machine learning (LASSO, SVM-RFE). Clinical diagnostic assessments (Nomogram, Correlation, Intergroup expression), and gene set enrichment analysis (GSEA) were performed for the key targets. In addition, immune cell analysis was performed on the blood mRNA expression cohort of MDD to explore the association between the key targets and immune cells. Finally, molecular docking prediction was performed for the targets of HP active ingredients on MDD.

resultsDifferential expression analysis and WGCNA module analysis yielded 933 potential targets for MDD. Three disease databases were intersected with 982 MDD-predicted targets. The TCMSP retrieved 275 valid targets for HP. Separate enrichment analysis intersected 13 key pathways. Five key targets (AKT1, MAPK1, MYC, EGF, HSP90AA1) were finally screened based on all enriched genes and HP valid targets. Combined with the signaling pathway and immune cell analysis suggested the effect of peripheral immunity on MDD and the important role of neutrophils in immune inflammation. Finally, the binding of HP active ingredients (quercetin, kaempferol, and luteolin) and all 5 key targets were predicted based on molecular docking.

conclusionsThe active constituents of Hypericum perforatum can act on MDD and key targets and pathways of this action were identified.

Indexed as

Hypericum perforatumMachine learningMajor depressive disorderPharmacological targets

Identifiers

PMID39385284
PMCPMC11465934

What Socratic holds

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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 Socratic graph.