Transcriptomic Signatures in Four Brain Regions for Substance Use Disorders

Avinash Veerappa's dataset, published on figshare in March 2026, contains transcriptomic analysis results from four brain regions related to substance use disorders. The data, stored in a 104.1 KB XLSX file, identifies unique and shared gene expression signatures, including 186 genes exclusive to the midbrain and 442 in the amygdala. It results from clustering, biclustering, WGCNA, and pathway enrichment analyses on case versus control samples.

Use Cases

• Identify shared and unique gene expression biomarkers for addiction risk based on the identified transcriptomic signatures.
• Analyze pathway enrichment in brain regions based on the reported upregulation of genes like CSF3, GADD45B, SOCS3, and NPAS4.
• Investigate the neuropeptide-neurotransmitter axis disruption in substance use based on the network analysis of DEGs.
• Compare differential gene expression patterns across the midbrain, DLPFC, NAc, and amygdala for substance use studies.

Strengths

• Focuses on four key brain regions (midbrain, DLPFC, NAc, amygdala) with distinct functional roles in substance use.
• Identifies specific counts of unique genes per region (e.g., 186 in midbrain, 442 in amygdala).
• Results from multiple analytical methods (clustering, biclustering, WGCNA, pathway enrichment).
• Openly licensed under CC-BY-4.0 for reuse and redistribution.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (104.1 KB), indicating limited scope, likely containing summary results rather than raw sequencing data.

Provenance

Source

figshare, author Avinash Veerappa

Collection Method

Transcriptome profiling from four brain regions, integrated with clustering, biclustering, WGCNA, and pathway enrichment analyses.

Time Range

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Freshness

Last updated 2026-03-18 05:22:43; freshness should be verified.

Geography

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