Evidence map›Paper›PMID 40148390›Full record

ArticleScientific reports2025

Network based approach for drug target identification in early onset Parkinson's disease.

Ashmita Dey, Mrittika Chakraborty, Ujjwal Maulik, Sanghamitra Bandyopadhyay

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Ashmita DeyMachine Intelligence Unit, Indian Statistical Institute, Kolkata, India.
Mrittika ChakrabortyMachine Intelligence Unit, Indian Statistical Institute, Kolkata, India.
Ujjwal MaulikComputer Science and Engineering, Jadavpur University, Kolkata, India. ujjwal.maulik@jadavpuruniversity.in.
Sanghamitra BandyopadhyayMachine Intelligence Unit, Indian Statistical Institute, Kolkata, India. sanghami@gmail.com.

Funding

Indo-French Centre for the Promotion of Advanced Research, Ministry of Science and Technology, Govt of India 6702-1
6 · The paper itself

Abstract

Despite the abundance of large-scale molecular and drug-response data, current research on early-onset Parkinson's disease (EOPD) markers often lacks mechanistic interpretations of drug-gene relationships, limiting our understanding of how drugs exert their therapeutic effects. While existing studies provide valuable EOPD markers, the mechanisms by which targeted drugs act remain poorly understood. We propose DTI-Prox, a novel workflow that identifies potentially overlooked EOPD markers and suggests relevant drug targets. DTI-Prox employs network proximity to measure how closely connected a drug and gene are within a biological network. Additionally, node similarity, which assesses the functional resemblance between network nodes, reveals meaningful drug-gene connections. DTI-Prox identifies 417 novel drug-target pairs and four previously unreported EOPD markers (PTK2B, APOA1, A2M, and BDNF), demonstrating significant pathway enrichment in neurodegenerative processes. Notably, shared pathway analysis shows that prioritized drugs such as Amantadine, Apomorphine, Atropine, Benztropine, Biperiden, Bromocriptine, Cabergoline, Carbidopa, and Citalopram, currently used for other conditions, interact with key EOPD-associated diagnostic markers, suggesting their potential for drug repurposing. The constructed functional network's validity is reinforced by statistically significant drug-target pairs. The findings provide new insights into EOPD drug mechanisms and identify promising therapeutic candidates, potentially leading to more effective, personalized treatment approaches for EOPD patients.

Indexed as

Antiparkinson AgentsGene Regulatory NetworksParkinson DiseaseAge of OnsetBiomarkersHumansAntiparkinson AgentsBiomarkersDrug repurposingDrug target identificationEarly-onset Parkinson’s diseaseNetwork-based approachPharmacogenomics

Identifiers

PMID40148390
PMCPMC11950373

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.