Evidence map›Paper›PMID 40231505›Full record

ReviewCNS & neurological disorders drug targets2025

Exploring LRRK2-dependent Mechanisms in Parkinson's Disease Therapy.

Veerta Sharma, Shiwali Sharma, Shareen Singh, Thakur Gurjeet Singh

Abstract readReview
PubMed Publisher
In one paragraph

Review in CNS & neurological disorders drug targets, 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.

Veerta SharmaChitkara College of Pharmacy, Chitkara University, Rajpura, 140401, Punjab, India.
Shiwali SharmaChitkara University School of Pharmacy, Chitkara University, Himachal Pradesh, 174103, India.
Shareen SinghChitkara College of Pharmacy, Chitkara University, Rajpura, 140401, Punjab, India.
Thakur Gurjeet SinghChitkara College of Pharmacy, Chitkara University, Rajpura, 140401, Punjab, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson's disease (PD) is the second most common progressive neurodegenerative disease worldwide and presents as a progressive motor disorder. Gene mutations play a pivotal role in the degeneration of dopaminergic neurons in the substantia nigra region. Mutations in the Leucine rich repeat kinase 2 (LRRK2) gene have been identified as one of the most common genetic causes of PD. LRRK2 is a multi-functional protein involved in several critical cellular processes, including mitochondrial function, autophagy, vesicular trafficking, and immune system regulation. Dysregulation of these processes due to aberrant LRRK2 activity contributes to neuronal degeneration, particularly in dopaminergic neurons, which are most affected in PD. The current review discusses the structure of LRRK2, its function, and pathogenic mutations in the context of PD. However, significant challenges remain, particularly in terms of ensuring drug specificity, minimizing off-target effects, and understanding the long-term safety and efficacy of these treatments. As we advance our understanding of LRRK2 biology, it remains a highly promising target for therapeutic strategies aimed at modifying the course of Parkinson's disease.

Indexed as

Antiparkinson AgentsLeucine-Rich Repeat Serine-Threonine Protein Kinase-2Parkinson DiseaseProtein Serine-Threonine KinasesAnimalsHumansMutationAntiparkinson AgentsLeucine-Rich Repeat Serine-Threonine Protein Kinase-2LRRK2 protein, humanProtein Serine-Threonine Kinasesleucine rich repeat kinase 2LRRK2 mutationsmitochondrial dysfunctionneurodegenerationParkinson’s diseasevesicle trafficking.α-synuclein

Identifiers

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.