Sepsis, a deranged immune response of a host, to an infection called systemic inflammatory response syndrome (SIRS). The inflammatory state of a whole body is caused by bacteria, virus, fungi, and parasites. It is a life-threatening disease which induces organ dysfunction (severe sepsis) or impaired tissue perfusion (septic shock). Globally, every year more than 30 million people are affected, potentially leading to 6 million deaths by sepsis. The incidence of sepsis increases in extreme age groups, newborn and young children.
This devastating disease has been listed by WHO for the coming decade, as a key healthcare priority. Treatment of sepsis for host organ system includes antimicrobial therapy, hemodynamic resuscitation, and supportive therapy. Because of the evolving nature of the disease over time, it is an intriguing issue for clinicians and researchers, despite the above best possible therapies.
Factors involved in this heterogenous disease phenotype are host, pathogen, microbiome and the environment. The major cause of sepsis clinical entity is lack of knowledge about the pathophysiological and biochemical mechanism behind the perturbation of host immune response which reflects the delay in diagnosis and stratification of patients at risk. The pathogenesis of sepsis on genetic basis is under appreciated but death from this acute condition is more heritable than cancer.
A Phenotype of disease can be observed both at whole organism level (susceptibility, disease severity, degree of organ dysfunction, treatment response and outcomes) and molecular phenotype biomarkers level (serum biomarkers, transcriptomics gene expression ratio, noncoding RNAs, proteomic, metabolomics and epigenetics). To understand the severity of sepsis disease, the altered expression of genes biomarkers using expression analysis platfrom is a potentially usefull tool. Disease-associated genes hunt has obtained impetus over the past decade.
Uncovering the genes responsible for the disease is requisite for identification and diagnosis of disease promptly. High throughput techniques such as microarray and next generation sequencing have been used to study the molecular profiling of dysregulated host response. Datasets obtained through these techniques are used in elucidating the functional role of diverse gene and their participation in underlying pathways.
Several studies have delineated a number of plausible gene biomarkers of sepsis using a microarray data. Consequently, the idea of these considerable microarray data appears to be of extent challenge currently. Microarray is a quantitative technology which assess the various mRNAs level of diverse genes simultaneously in a highly cost effective manner. Through this high throughput technology which holds much of assurance for the scrutiny of diverse disease, the notable gene signatures obtained and are assessed in clinical trials.
Gene expression analysis through this technology help us to understand and analyse the worldwide genomic patterns of diverse diseases. Regardless of advancements, various studies reported findings that are inconsistent and rugged of the technique due to inappropriate investigation and validation, false positive control inadequacy and lack in reporting of methods.
Furthermore, the transcription profiling experiments are conventionally examine in solitude and the state is aggravated by tiny sample size comparative to large potent predictors. Hence, across studies generalisability needs to be assessed which is required by widespread practical application. For instance, the finding of a historical control study from one geographical region may not be applicable to another geographical region. Here comes a meta-analysis into limelight whose approach is combinatorial.
Meta-analysis is a statistical technique which merge information from publicly available datasets which shared molecular mechanism of disease, increases the reliability and generalizability of studies. Howbeit, the term is not only statistical but also widely used to expound the whole body process. A conclusive statement on metaanalysis can be made that an accurate estimation of gene expression differentials can be obtained and the heterogeneity of comprehensive estimate can be assessed through it.
Metaanalysis thoroughly studies the already available data in a relatively inexpensive approach. A diligent metaanalysis compounding manyfold data of a large number of affected population from several platforms and diverse methods of data attainement determine genes that may have been omitted by the individual study of gene expression.
Our current criteria for studying sepsis whirl around the establishment of crucial genes of sepsis among manually curated genes. Albeit novel therapeutic strategies development has impact on mortality of severe sepsis but still it’s a great challenge, due to its heterogeneity and complexity.