Biological Data

Exploratory Reanalysis of Substantia Nigra Transcriptomes in Parkinson’s Disease

Document Type : Brief Reports

Authors

Department of Genetics, Faculty of Science, Danesh Alborz University, Qazvin, Iran.

Abstract

Small postmortem cohorts can yield plausible expression signals with unstable statistical significance. This short report reanalyzed deposited substantia nigra pars compacta counts from four Parkinson’s disease (PD) donors and three controls (GSE206308). A condition-only PyDESeq2 model with Benjamini–Hochberg false discovery rate (FDR) control and fold-change shrinkage was complemented by leave-one-sample-out refits, limma-voom, direction-specific functional enrichment, and literature-defined marker scores. PyDESeq2 identified 406 genes at FDR < 0.05, including 125 higher and 281 lower in PD. Leave-one-out refits yielded 157–624 significant genes; only 109 of the primary 406 (26.8%) remained significant in every refit. limma-voom identified 11 significant genes, all contained in the primary and consistently retained sets, giving only 2.7% overlap with the primary list. Effect estimates nevertheless agreed closely across 17,888 genes (Spearman correlation 0.970). The lower-expression list was enriched for synaptic signaling, dopamine biosynthesis, and synaptic vesicle cycle; the higher-expression list included motor-protein annotations. A dopamine-marker transcript score was 3.23 log2 units lower in PD, but depletion relative to a pan-neuronal score was imprecise. This reanalysis illustrates substantial sample and method sensitivity despite coherent expression directions. Small sample size, demographic imbalance, and unresolved tissue composition limit biological attribution and motivate explicit stability reporting in future studies.

Keywords

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Biological Data
Volume 1, Issue 1 - Serial Number 1
June 2026
Pages 44-54
  • Receive Date: 10 March 2026
  • Revise Date: 24 October 2026
  • Accept Date: 20 April 2026
  • First Publish Date: 15 May 2026