MYD88, NFKB1, and IL6 transcripts overexpression are associated with poor outcomes and short survival in neonatal sepsis

Abstract

Toll-like receptor (TLR) family signature has been implicated in sepsis etiopathology. We aimed to evaluate the genetic profile of TLR pathway-related key genes; the myeloid differentiation protein 88 (MYD88), IL1 receptor-associated kinase 1 (IRAK1), the nuclear factor kappa-B1 (NFKB1), and interleukin 6 (IL6) in the blood of neonates with sepsis at the time of admission and post-treatment for the available paired-samples. This case-control study included 124 infants with sepsis admitted to the neonatal intensive care unit and 17 controls. The relative gene expressions were quantified by TaqMan Real-Time qPCR and correlated to the clinic-laboratory data. MYD88, NFKB1, and IL6 relative expressions were significantly higher in sepsis cases than controls. Higher levels of MYD88 and IL6 were found in male neonates and contributed to the sex-based separation of the cases by the principal component analysis. ROC analysis revealed MYD88 and NFKB1 transcripts to be good biomarkers for sepsis. Furthermore, patients with high circulatory MYD88 levels were associated with poor survival, as revealed by Kaplan-Meier curves analysis. MYD88, NFKB1, and IL6 transcripts showed association with different poor-outcome manifestations. Clustering analysis split the patient cohort into three distinct groups according to their transcriptomic signature and CRP levels. In conclusion, the study TLR pathway-related transcripts have a gender-specific signature, diagnostic, and prognostic clinical utility in neonatal sepsis.

Figure 1

Toll-like receptor (TLR) signaling pathway. On exposure to pathogens secreting pathogen-associated molecular patterns (PAMPs), their recognition is initiated via pattern recognition receptors, including several Toll-like receptors (TLRs). For example, lipopolysaccharides on gram-negative bacteria activate TLR4, lipoteichoic acid of gram-positive bacteria activates TLR2, while TLR3 recognizes viral PAMPs, generating innate immune responses via the MyD88-dependent pathway that leads to the production of pro-inflammatory cytokines with activation of nuclear factor kappa B (NFKB) and the downstream gene targets^,. The MyD88-independent pathway associated with the induction of type I interferon (IFN) and IFN-inducible genes [Data source: KEGG pathway, hsa04620 and created by Biorender.com].

Figure 2

The relative expression level of circulatory Toll-like receptor signaling pathway genes. Four genes were analyzed: MYD88, IRAK1, NFKB1, and IL6. Whiskers and bars represented the median (Q1 and Q3). All values were log-transformed with the control level sets at the zero lines. Unpaired Mann–Whitney U test was used for all the analysis except the paired comparison between pretreatment and post-treatment, where Wilcoxon matched-pairs signed-rank test was employed instead. Bold p-values were significant at < 0.05. Transformed values of gene expression are presented as median (Q1 and Q3) in the attached table.

Figure 3

Clustering analysis. (A) Gene co-expression analysis for MYD88, IRAK1, NFKB1, and IL6. Spearman's correlation analysis was applied. Correlation coefficients are shown in corresponding cells. Asterisk sign is for significant correlations. Gene co-expression analysis across the 124 sepsis cohorts showed that IL6 gene expression was directly correlated to MYD88 (r = 0.26, p = 0.004) and NFKB1 (r = 0.19, p = 0.039) gene levels. (B) Principal component analysis with axes 1 and 2 explaining variability in samples by 35.7% and 23.3%, respectively. The transcriptomic pattern showed clear demarcation between males and females with a small overlapping part. Over-expressed MYD88 and IL6 had a major contribution to the separation between male and female sepsis patients. (C) Hierarchical clustering analysis using the following parameters: Ward's minimum variance clustering method, Euclidian distance, scaling, and centering. The dendrogram shows the patients were clustered into three groups according to the pattern of 4 gene expression and C-reactive protein. (D) K-means clustering with scaling and centering. The five parameters used clustered patients into three groups: cluster 1 included 67 infants with low IRAK1 gene expression, cluster 2 including 49 neonates characterized by high IRAK1 gene expression, while cluster 3 of 8 patients exhibited remarkably lower MYD88 and IL6 expressions. (E–H) Box plots for the gene expression in each cluster.

Figure 4

Survival analysis in sepsis patients. (A–D) Box plots for the expression level of alive and expired neonates. Mann–Whitney U test was used. (E–H) Kaplan–Meier survival curves. Log-Rank test was used to test the significant difference.

Figure 5

Multivariate analysis for risk factors of mortality. Cox hazard proportionate regression analysis was employed. Hazard ratio (HR) and confidence intervals (CI) are shown with p values set significant at < 0.05.

Figure 6

Pathway enrichment of MYD88, IRAK1, NFKB1, and IL6 genes. The query genes are displayed as nodes colored by their abundance, with yellow corresponding to high abundance. Enriched pathways and diseases are colored according to the enrichment test P-value from "Enricher", with darker red corresponding to more significant enrichment. Edges connect enriched pathways/diseases and their members in the query gene set [Data source: pinet-server.org].