Primary Immunodeficiency Genes as Risk Factors in Systemic Lupus Erythematosus

453 primary immunodeficiency (PID) genes were analyzed for genetic association and expression in systemic lupus erythematosus (SLE). The dataset, authored by Haley Davis and last updated in March 2026, includes results from protein-protein interaction clustering, differential expression analysis across multiple sample types, and machine learning classifier performance. Classifiers using PID genes achieved accuracies of 0.80 for distinguishing lupus from healthy controls and 0.74 for classifying active versus inactive disease.

Use Cases

• Identifying novel SLE risk genes based on overlap with known PID genes.
• Analyzing differential expression patterns of PID genes in specific immune cell subsets like T cells and monocytes.
• Training machine learning classifiers to predict SLE disease status and severity using PID gene groupings.
• Mapping protein-protein interaction networks to reveal functional clusters relevant to lupus pathogenesis.

Strengths

• Analysis is based on a defined set of 453 PID genes.
• Results include machine learning classifier accuracies of 0.80 and 0.74 for specific prediction tasks.
• Data is openly licensed under CC-BY-4.0.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 13.6 KB file size suggests a limited scope, likely containing summary results rather than raw genomic data.

Provenance

Source

figshare, author Haley Davis.

Collection Method

Compilation of a PID gene database, followed by genetic overlap analysis, differential expression studies, and machine learning modeling.

Time Range

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Freshness

Last updated 2026-03-18 10:09:47; freshness should be verified.

Geography

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