Biomimetic Digital Twins and Multiomics: Applications to Rheumatoid Arthritis and the Potential Reclassification of Variants of Unknown Clinical Significance.

The National Academies of Sciences, Engineering, and Medicine issued a report on December 15, 2023, "Foundational Research Gaps and Future Directions for Digital Twins." This described the importance of using biomimetic digital twins and multiomics in research. These were incorporated in the current analysis of patients with rheumatoid arthritis (RA). Exome sequencing, genotype-phenotype ranking, and biomimetic digital twin analysis were used to identify five pathogenic and one likely pathogenic DNA variants in patient samples analyzed, which were absent from controls. The variants identified in these genes, P2RX7, HTRA2, PTPN22, FLG, CD46, and EIF4G1, play a role in the development of RA. Additionally, 3172 variants of unknown clinical significance (VUSs) were identified in patient samples, which were absent from controls. All VUSs appeared to be associated with RA. Hidden or dark data were identified from six genes. These genes, often found in patient samples, included HIF1A, HLA-DOA, PTGER3, HIPK3, TGFBR3, and HIF1A-AS3. VUSs identified in genes HIF1A, HLA-DOA, PTGER3, and HIPK3 were directly related to the pathogenesis of RA, whereas VUSs identified in genes TGFBR3 and HIF1A-AS3 were indirectly related. The current results suggest that biomimetic digital twins and multiomics can provide further insight into the development of RA. This may also potentially help with the process of reclassifying VUSs. The reclassification of VUSs will play a critical role in complex molecular diagnostics and drug development.