Psoriasis Vulgaris Comorbidity Network Analysis via Ising Model and Multiomics

Large-scale retrospective cohort data was used to construct a psoriasis vulgaris comorbidity network using the Ising model from statistical physics. The study, authored by Dongwen Shi and last updated in April 2026, integrates clinical data with nontargeted proteomics and lipid peroxidation metabolomics. A prospective intervention study further evaluated the impact of IL-17A inhibition on psoriasis and atherosclerosis.

Use Cases

• Model disease comorbidity networks based on the Ising model methodology described.
• Identify core comorbidities and hub nodes based on network centrality metrics like degree and betweenness.
• Investigate shared molecular mechanisms based on multiomics evidence including proteomics and metabolomics.
• Validate therapeutic pathway impacts based on prospective intervention study outcomes for IL-17A inhibition.

Strengths

• Integrates clinical cohort data with multiomics evidence (proteomics and metabolomics).
• Employs a network analysis method (Ising model) from statistical physics.
• Includes a prospective intervention study for clinical validation.
• Dataset is openly licensed under CC-BY-4.0.

Limitations

• The primary data file is a 56.3 KB DOCX document, suggesting limited raw data scope.
• Column-level documentation and sample data are unavailable, requiring manual inspection.
• Row count and specific data structure are unknown, limiting suitability assessment.

Provenance

Source

figshare, author Dongwen Shi.

Collection Method

Constructed from large-scale retrospective cohort data and a prospective intervention study.

Time Range

The temporal coverage of the clinical data is not specified.

Freshness

Last updated 2026-04-14 05:28:48.

Geography

The geographic coverage of the clinical data is not specified.