06 Jun Why we should look for “gene ensembles” instead of solo genes only?
COVID-19 can cause pneumonia, which is one of the most common causes of sepsis. Effective and safe treatments are urgently being sought by scientists across the world. Recently, the researchers from Gene Learning association developed a new approach to treat and predict disease severity and mortality in COVID-19 patients. Instead of searching for biomarker genes, they looked into how genes act together.
The COVID-19 is an ongoing global pandemic. The virus has spread to every corner of the globe affecting our lives and our economy. More than 160 million infections have been reported worldwide, and more than 3.4 million people have died so far.
Scientific data show that coronavirus can lead to pneumonia, which in turn may lead to sepsis. Sepsis is a life-threatening condition. It’s a complex reaction of the immune system to infection, resulting in septic shock or even death. About 15% of severely ill COVID-19 patients develop acute respiratory failure requiring intubation and artificial ventilation in intensive care units (ICUs), which increases the risk of sepsis.
Finding novel biomarkers for sepsis is challenging due to the highly varied response of individuals. This highly heterogeneous nature of sepsis represents an obstacle in terms of finding treatment and predicting the clinical outcome. Currently, treatment of sepsis remains non-curative despite recent progress in the identification of molecular biomarkers, and clinical outcome is often estimated based on clinical signs.
The search for effective and affordable treatment of pneumonia and sepsis is ongoing. Recently, our researchers developed a new holistic approach. Instead of searching for biomarker genes, they looked into how genes act together. In other words, they identified gene ensembles that become mistuned when the person becomes affected by COVID-19 and other acute respiratory infections.
The gene ensemble noise allows for the holistic identification and interpretation of gene expression disbalance. Therefore, instead of looking at solo gene players only, we should look at “gene ensembles” to find new pharmaceutical targets for treatment.
Our researchers identified common disturbances across all patients with severe pneumonia, sepsis, and COVID-19 symptoms. The mistuned “gene ensembles” include increased fluctuations and gene noise involved in mitochondrial respiration and peroxisomes, which are responsible for the supply of energy and the utilisation of cellular waste.
The gene ensemble noise has excellent potential in terms of investigating molecular mechanisms of pathologies and identifying pharmaceutically targetable pathways. Indeed, our researchers have already identified some FDA and EMA-approved drugs that could be potentially used for the treatment of pneumonia and sepsis caused by acute respiratory infections. This new “gene ensemble” approach can be also used to predict clinical outcomes among COVID-19, pneumonia, and sepsis patients, namely severity and mortality.
While in this study our researchers showed the application of “gene ensemble” noise for COVID-19, pneumonia, and sepsis, this approach can be applied to other pathologies as well.
The full article has been published in Nature and PubMed Estimates of gene ensemble noise highlight critical pathways and predict disease severity in H1N1, COVID-19 and mortality in sepsis patients.