Investigation of TLR2 and TLR4 Polymorphisms and Sepsis Susceptibility: Computational and Experimental Approaches.

Toll-like receptors (TLR) play an eminent role in the regulation of immune responses to invading pathogens during sepsis. TLR genetic variants might influence individual susceptibility to developing sepsis. The current study aimed to investigate the association of genetic polymorphisms of the TLR2 and TLR4 with the risk of developing sepsis with both a pilot study and in silico tools. Different in silico tools were used to predict the impact of our SNPs on protein structure, stability, and function. Furthermore, in our prospective study, all patients matching the inclusion criteria in the intensive care units (ICU) were included and followed up, and DNA samples were genotyped using real-time polymerase chain reaction (RT-PCR) technology. There was a significant association between TLR2 Arg753Gln polymorphisms and sepsis under the over-dominant model (p = 0.043). In contrast, we did not find a significant difference with the TLR4 Asp299Gly polymorphism with sepsis. However, there was a significant association between TLR4 Asp299Gly polymorphisms and Acinetobacter baumannii infection which is quite a virulent organism in ICU (p = 0.001) and post-surgical cohorts (p = 0.033). Our results conclude that the TLR2 genotype may be a risk factor for sepsis in adult patients.

Role of MBL2 Polymorphisms in Sepsis and Survival: A Pilot Study and In Silico Analysis.

Sepsis is a serious infection-induced syndrome with serious ramifications, especially in intensive care units. Global concern motivated the investigation of the role of related genes' polymorphism in predicting the liability to infection, sepsis, septic shock and survival. Among these genes is the gene encoding mannose-binding lectin (MBL), with its remarkable importance in the immune system. However, the previous studies showed conflicting results and ambiguity that urged us to engage with this issue in the Egyptian population. Prediction of functional and structural impacts of single nucleotide polymorphisms (SNPs) was done using in silico methods. A prospective observational study was conducted in intensive care units; one hundred and thirty patients were followed up. Genotyping was performed using real-time polymerase chain reaction (RT-PCR) technology. MBL SNPs showed a remarkable high frequency in our population, as well. No significant association was found between MBL2 genotypes and any of our analyses (sepsis, septic shock and survival). Only septic shock and age were independently associated with time of survival by Cox regression analysis. Our study may confirm the redundancy of MBL and the absence of significant impact on sepsis liability and mortality in adult patients.

In silico analysis of missense variants of the C1qA gene related to infection and autoimmune diseases.

Objectives: C1q is a key activator of the classical pathway of the complement system and exerts consequences relating to opsonization and phagocytosis. The C1qA gene is one of three genes encoding the C1q molecule. Defects in C1q, and especially in C1qA, have been linked to an increased susceptibility to infection, sepsis, and systemic lupus erythematosus. These defects could arise from missense single nucleotide polymorphisms (SNPs) and their deleterious impacts on protein structure and function. Thus, identifying high-risk missense SNPs in C1qA has become a necessity if we are to identify appropriate measures for prevention and management of affected patients. Methods: A comprehensive in silico study was conducted to screen the 184 missense SNPs in the C1qA gene using different tools with different algorithms and approaches. We investigated the impact of SNPs on protein function, stability, and structure. In addition, we identified the location of the SNPs on protein domains, secondary structure alignment, and the phylogenetic conservation of their positions. Results: Of the 184 missense SNPs, 10 SNPs were predicted to be the most damaging to protein function and structure. Conclusion: Ten missense SNPs were predicted to have the highest risk of damaging protein function and structure, thus leading to infection, sepsis, and systemic lupus erythematosus. These 10 SNPs constitute the best candidates for further experimental investigations.