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This page is alzhub.org's plain-English summary of a published study, not the paper itself. It is generated from the record we hold for this study, sourced and linked below — check the original for the full text and methods.

✓ Peer-reviewed alzhub usefulness score 43 out of 100. Getting a diagnosis

Topic: Brain proteins, microglia and lab models

We identified 51 transcriptome-wide significant (edgeR q < 0.05) DEGs, compared to controls, and 26 transcriptome-wide significant DEGs, compared to PD, in PDD plasma SEV. The identified DEGs, which included WNT5A, MAPT, FOSB, MIR324, MIR574, MIR3161, and MIR6821 were significantly enriched among Tetrahydrofolate salvage, Reelin signalling, tRNA splicing, Wnt signalling, and ERBB signalling pathways. We identified eight potential multiplex plasma SEV RNA biomarker assays that can distinguish PDD from PD with at least 80 % sensitivity and specificity using an artificial intelligence-based algorithm. Future research on the identified dysfunctional molecular pathways may facilitate discovery of novel therapeutic targets for PDD. Diagnostic biomarker potential of the derived multiplex RNA biomarker assays should be investigated by larger clinical studies.

Key findings

Why it matters

This study identified RNA biomarkers in plasma small extracellular vesicles that could distinguish Parkinson's disease dementia from Parkinson's disease with at least 80% sensitivity and specificity. The authors note that future research on the identified pathways may help find new therapeutic targets, but no treatment is tested here.

Study details

How this study scored 43/100
How this study's score is builtJournal tier 7 of 10; Journal's citation record 2 of 4; Study design 0 of 12; Strength of evidence 1 of 5; Peer-review validation 10 of 10; How recent 4 of 5; Sample size 1 of 4; Effect reported 0 of 3; Studied in people 3 of 3; Randomised / blinded 0 of 2; Times cited 1 of 7; Citations per year 1 of 5; Impact for its field and year 1 of 6; Cited by studies here 0 of 6; Still being cited 1 of 4; Senior author's track record 4 of 4; Institution's track record 1 of 3; Multi-centre collaboration 2 of 3; Indexed in PubMed 2 of 2; Free to read 2 of 2. Total 43 of 100.43 of 100 points earned57 not earned

Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.

ComponentPointsWhy
Journal tier 7 / 10 Tier 3 — peer-reviewed journal (Parkinsonism & Related Disorders)
Journal's citation record 2 / 4 Parkinsonism & Related Disorders: journal h-index 155 (OpenAlex, 2026-10-29)
Study design 0 / 12 No study design recorded — scores zero, not guessed (not stated in the record — scored 0)
Strength of evidence 1 / 5 Rated “low” in our summary
Peer-review validation 10 / 10 Peer-reviewed. Published as an article in a named peer-reviewed journal.
How recent 4 / 5 2025 — within 3 year(s) of the newest study here
Sample size 1 / 4 15 participants
Effect reported 0 / 3 No effect size reported — scores zero (not stated in the record — scored 0)
Studied in people 3 / 3 Studied in people (participant count stated)
Randomised / blinded 0 / 2 No randomisation or blinding stated — scores zero (not stated in the record — scored 0)
Times cited 1 / 7 Cited 3 times (OpenAlex, 2026-10-10)
Citations per year 1 / 5 1.0 citations a year over 3 year(s) since 2025
Impact for its field and year 1 / 6 Cited 0.8× the average for papers of its field and year (OpenAlex FWCI)
Cited by studies here 0 / 6 No other study in this library cites it
Still being cited 1 / 4 Cited 3 times in 2024–2026 (2026 still in progress; OpenAlex)
Senior author's track record 4 / 4 Last-listed author Dag Aarsland: h-index 141 (OpenAlex, whole career)
Institution's track record 1 / 3 Karolinska Institutet: institution h-index 1,477 (OpenAlex)
Multi-centre collaboration 2 / 3 OpenAlex lists 5 institution(s) in 2 countries
Indexed in PubMed 2 / 2 Indexed in PubMed (PMID 41385896)
Free to read 2 / 2 Free to read
Total 43 / 100 —

What each of these 20 components measures, and what this score is not →

Read the original

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

Cite this study APA, Vancouver, BibTeX · download .bib or .ris

Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.

APA 7th

Rajkumar, A. P., Hye, A., Tan, S., Green, H., Killick, R., Nizamudeen, Z. A., et al. (2025). Transcriptomic analysis of plasma small extracellular vesicles identifies potential diagnostic biomarkers for Parkinson's disease dementia. Parkinsonism & Related Disorders. https://doi.org/10.1016/j.parkreldis.2025.108150

Vancouver

Rajkumar AP, Hye A, Tan S, Green H, Killick R, Nizamudeen ZA, et al. Transcriptomic analysis of plasma small extracellular vesicles identifies potential diagnostic biomarkers for Parkinson's disease dementia. Parkinsonism & Related Disorders. 2025. doi:10.1016/j.parkreldis.2025.108150. PMID: 41385896.

BibTeX

@article{rajkumar2025-41385896,
  author  = {Rajkumar, Anto Praveen and Hye, Abdul and Tan, Shirlee and Green, Holly and Killick, Richard and Nizamudeen, Zubair Ahmed and Işık, Fatma Büşra and Figueredo, Grazziela Patrocinio and others},
  title   = {{Transcriptomic analysis of plasma small extracellular vesicles identifies potential diagnostic biomarkers for Parkinson's disease dementia}},
  journal = {Parkinsonism \& Related Disorders},
  year    = {2025},
  doi     = {10.1016/j.parkreldis.2025.108150},
  pmid    = {41385896},
  url     = {https://doi.org/10.1016/j.parkreldis.2025.108150}
}

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