PANDAS Autoantibody Screening Data from Nucleic Acid Protein Programmable Array

Jelena Eremija's dataset on figshare contains autoantibody screening results for Pediatric Autoimmune Neuropsychiatric Disorder Associated with Streptococcal Infections (PANDAS). The data was generated using a Nucleic Acid Protein Programmable Array (NAPPA) system, comparing children with PANDAS to patients with autism spectrum disorder and healthy controls. The dataset was last updated on April 29, 2026.

Use Cases

• Identify potential autoimmune targets based on the 1,235 non-overlapping protein targets initially identified.
• Analyze the heterogeneity of autoantibody profiles based on the finding that 67.5% of PANDAS-positive targets were reactive in only a single patient.
• Evaluate the diagnostic performance of autoantibody-based classifiers based on the reported poor cross-validation results.
• Perform functional enrichment analysis based on the described overrepresentation of transcription factors, apoptosis regulators, and neural development proteins.

Strengths

• Dataset employs an unbiased screening method (NAPPA) for protein-autoantibody interactions.
• Includes comparisons across three distinct cohorts: PANDAS, autism spectrum disorder, and healthy controls.
• Functional enrichment analysis reveals specific biological pathways associated with PANDAS-specific targets.

Limitations

• Dataset size is 36.8 KB, indicating a very limited scope.
• Row count and column-level documentation are unknown, requiring manual inspection after download.
• Autoantibody profiles were highly heterogeneous, with no individual protein or panel achieving reliable diagnostic discrimination.

Provenance

Source

figshare

Collection Method

Unbiased screening using Nucleic Acid Protein Programmable Array (NAPPA).

Freshness

Last updated 2026-04-29 05:41:43; freshness should be verified.