Research Paper Volume 16, Issue 4 pp 3989—4013
Unlocking the potential of senescence-related gene signature as a diagnostic and prognostic biomarker in sepsis: insights from meta-analyses, single-cell RNA sequencing, and in vitro experiments
Figure 3. Identification of TGFBI and MAD1L1 as significant predictors of sepsis mortality. (A) LASSO regression identified 15 out of 80 genes as significant predictors of sepsis mortality. (B) Random forest analysis identified four genes, including ABI3, TGFBI, MAD1L1, and WIPI1, as significant predictors of sepsis mortality. (C) LASSO, random forest, and univariate Cox analyses identified ABI3, TGFBI, and MAD1L1 as co-determined predictors of sepsis mortality. (D) Multivariate Cox regression with stepwise selection ultimately included TGFBI and MAD1L1 in the predictive model for sepsis mortality. (E) High expression levels of TGFBI (up) and low expression levels of MAD1L1 (down) were associated with favorable prognoses in the training cohort. (F, G) Meta-analyses indicated the prognostic value of TGFBI (F) and MAD1L1 (G) in predicting sepsis mortality. Abbreviations: LASSO, Least Absolute Shrinkage and Selection Operator; TGFBI, transforming growth factor-beta induced protein; MAD1L1, mitotic spindle assembly checkpoint protein.