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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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In Silico Functional and Structural Analysis of STAT4 Variants of Uncertain Significance.
Karla Mayela Bravo-Villagra1,2, Eric Jonathan Maciel-Cruz3, Rosa Michel Martínez-Contreras2,3
1Centro Universitario de Ciencias de la Salud, Instituto de Nutrigenética y Nutrigenómica Traslacional, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico.
Genes
|January 28, 2026
Summary
Bioinformatics tools predict the functional impact of STAT4 gene variants of uncertain significance. This approach aids in prioritizing variants for further experimental validation in autoimmune disease research.
Area of Science:
- Genetics
- Bioinformatics
- Immunology
Background:
- The STAT4 gene is crucial for immune regulation.
- STAT4 variants are linked to autoimmune diseases like rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE).
Purpose of the Study:
- To analyze STAT4 variants of uncertain significance (VUSs) using bioinformatics.
- Predict the functional and structural impact of these VUSs.
Main Methods:
- Retrieved 48,295 STAT4 variants from Ensembl.
- Employed a tiered filtering approach with in silico tools (SIFT, PolyPhen, MutPred2, Align-GVGD) and structural modeling (Chimera, ModRefiner, Missense3D, HOPE, DynaMut2).
Main Results:
- Identified 80 missense VUSs, prioritizing 13 based on multiple predictors.
- Observed significant alterations in protein physicochemical properties, including hydrophobicity and hydrogen bonding.
- The rs140675301 (Glu128Val) variant may alter kinase specificity.
Conclusions:
- Integrative bioinformatics analysis is a valuable preliminary step for VUS assessment.
- This strategy aids in guiding experimental validation for STAT4 variants.
- Strengthens the interpretative framework for VUS relevance in immune-related genes.
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