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"In conclusion, we present an unbiased data driven, network-based approach that identified molecular signatures of CFS and implicates a number of highly coherent co-expression modules to CFS.
For the top 5 modules, the complementary analysis shown here point to a common underlying biology that shares immune and metabolic dysregulation also present in other clinically similar diseases such as Lyme, MIS-C, Kawasaki, and recovering COVID-19.
Moreover, the top KDs we identified as regulators of these CFS-associated modules are biased towards higher pLI scores, indicating that loss of function mutations in these genes cannot be well tolerated, confirming their critical importance to normal system function.
These top KDs we identified for CFS offer interesting points of therapeutic intervention to explore, with the most promising being MXD1, STX3, DYSF, LYN, MLL2, NCOA2, PTPRE, REPS2, RP11-701P16.2, TECPR2, and TUBB1.
To help facilitate continued CFS community research we are also providing an interactive website containing the signatures, modules, KDs, and Bayesian network which can be found here: https://irenefp.github.io/bcellm7.html"
Full Text:
https://www.medrxiv.org/content/10.1101/2021.01.29.21250755v1.full-text
For the top 5 modules, the complementary analysis shown here point to a common underlying biology that shares immune and metabolic dysregulation also present in other clinically similar diseases such as Lyme, MIS-C, Kawasaki, and recovering COVID-19.
Moreover, the top KDs we identified as regulators of these CFS-associated modules are biased towards higher pLI scores, indicating that loss of function mutations in these genes cannot be well tolerated, confirming their critical importance to normal system function.
These top KDs we identified for CFS offer interesting points of therapeutic intervention to explore, with the most promising being MXD1, STX3, DYSF, LYN, MLL2, NCOA2, PTPRE, REPS2, RP11-701P16.2, TECPR2, and TUBB1.
To help facilitate continued CFS community research we are also providing an interactive website containing the signatures, modules, KDs, and Bayesian network which can be found here: https://irenefp.github.io/bcellm7.html"
Full Text:
https://www.medrxiv.org/content/10.1101/2021.01.29.21250755v1.full-text