Evidence map›Paper›PMID 39953559›Full record

ArticleAlzheimer's research & therapy2025

Pathway-based network medicine identifies novel natural products for Alzheimer's disease.

Yumei Liang, Siqi Xie, Jianping Jia

Abstract read
In one paragraph

Article in Alzheimer's research & therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 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

3 authors.

Yumei LiangInnovation Center for Neurological Disorders, Department of Neurology, National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Xicheng District, Beijing, 100053, China.
Siqi XieInnovation Center for Neurological Disorders, Department of Neurology, National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Xicheng District, Beijing, 100053, China.
Jianping JiaInnovation Center for Neurological Disorders, Department of Neurology, National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Changchun Street 45, Xicheng District, Beijing, 100053, China. jjp@ccmu.edu.cn.

Funding

Beijing Brain Initiative from Beijing Municipal Science & Technology Commission Z201100005520016, Z201100005520017the grant from the Chinese Institutes for Medical Research CX23YZ15the Key Project of the National Natural Science Foundation of China U20A20354the National Key Scientific Instrument and Equipment Development Project 31627803the STI2030-Major Projects No.2021ZD0201802
6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) is the leading cause of dementia, characterized by a complex pathogenesis that complicates the development of effective treatments. Natural products are promising multitarget agents because of their ability to interact with multiple molecular targets. Network-based medicine presents a robust strategy for discovering such agents, which can address the intricate mechanisms underlying AD.

methodsIn this study, we constructed an AD-related pathway-gene network via text mining and pathway database construction. This network facilitated the identification of natural products that target multiple pathways and genes associated with AD. We evaluated the safety profiles of two selected natural products in C57BL/6J mice through assessments of general behavior, body weight changes, vital organ weight and morphology, and hematological and biochemical parameters. APP/PS1 transgenic mice were subsequently treated with these natural products-either individually or in combination-to assess their therapeutic effects. Cognitive function was evaluated via behavioral tests, such as novel object recognition, Y-maze, and Morris water maze tests. Additionally, immunohistochemical staining and enzyme-linked immunosorbent assays were performed to examine Aβ-associated pathological changes. Transcriptomic analysis and quantitative real-time polymerase chain reaction (qRT-PCR) were employed to elucidate the mechanisms underlying the effects of the natural products.

resultsThe constructed AD-related pathway-gene network encompassed three perspectives: (i) Most Studied Pathways (21 pathways with 5325 genes), (ii) Gene-Associated Pathways (26 pathways with 2557 genes), and (iii) Popular Pathways (24 pathways with 3435 genes). Two natural products, (-)-Vestitol and Salviolone, were selected for further validation. Their safety was confirmed in C57BL/6J mice. Notably, the combination of (-)-Vestitol and Salviolone synergistically affected cognitive function in APP/PS1 transgenic mice by reducing Aβ deposition and lowering toxic soluble Aβ levels in the brain. Transcriptomic analysis and qRT-PCR experiments revealed that their combination regulated AD-related pathways and genes more comprehensively, particularly affecting the Neuroactive ligand-receptor interaction and Calcium signaling pathway.

conclusionsOur findings demonstrate that screening potential natural products through an AD-related pathway-gene network is a promising strategy for discovering novel therapeutics for AD. The therapeutic potential of (-)-Vestitol and Salviolone as novel candidates for AD treatment is underscored by their synergistic effects, attributed to their comprehensive regulation of AD-associated pathways and genes.

Indexed as

Alzheimer DiseaseBiological ProductsGene Regulatory NetworksAmyloid beta-PeptidesAmyloid beta-Protein PrecursorAnimalsBrainDisease Models, AnimalMaleMiceMice, Inbred C57BLMice, TransgenicAmyloid beta-PeptidesAmyloid beta-Protein PrecursorBiological ProductsAlzheimer’s diseaseNatural productNetwork medicinePathwayTreatment

Identifiers

PMID39953559
PMCPMC11829514

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LicenceCC BY-NC-ND
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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.