Psoriasis Lactate Metabolism Biomarker Data from Bulk and Single-Cell RNA-Seq

A collection of 23 differentially expressed lactate-related genes (DE-LRGs) identified from integrated bulk RNA-seq datasets for psoriasis research. The data was generated by Yakun Wang and last updated in May 2026, supporting the identification of diagnostic biomarkers like SLC25A4. It includes results from machine learning, Mendelian randomization, and single-cell RNA-seq analyses.

Use Cases

• Validate diagnostic biomarkers for psoriasis based on lactate metabolism-related gene expression.
• Analyze immune cell infiltration patterns correlated with specific gene markers like GOT2, PYGL, and SLC25A4.
• Study keratinocyte subtype remodeling and differentiation trajectories using single-cell RNA-seq data.
• Train artificial neural network models for psoriasis diagnosis based on the identified biomarker panel.

Strengths

• Identifies 23 differentially expressed lactate-related genes with potential causal relevance to psoriasis.
• Machine learning approaches validated three robust biomarkers, with an ANN model achieving AUC > 0.90 across independent cohorts.
• Analysis integrates multiple methodologies: bulk RNA-seq, Mendelian randomization, WGCNA, and single-cell RNA-seq.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• The study is primarily based on public databases and in vitro experiments, lacking animal model validation as noted in the description.

Provenance

Source

figshare

Collection Method

Integrated analysis of bulk RNA-seq datasets, Mendelian randomization, and single-cell RNA-seq data.

Freshness

Last updated 2026-05-29 06:11:37; freshness should be verified.