Project 457220
Epigenetic signatures in sepsis-survivors associated with one-year outcome: A model-based clustering analysis of prospective cohorts
Epigenetic signatures in sepsis-survivors associated with one-year outcome: A model-based clustering analysis of prospective cohorts
Project Information
| Study Type: | Unclear |
| Research Theme: | Biomedical |
Institution & Funding
| Principal Investigator(s): | Soussi, Sabri M |
| Supervisor(s): | Gayat, Etienne; Dos Santos, Claudia C |
| Institution: | St. Michael's Hospital (Toronto, Ontario) |
| CIHR Institute: | Circulatory and Respiratory Health |
| Program: | |
| Peer Review Committee: | Doctoral Research Awards - B |
| Competition Year: | 2021 |
| Term: | 3 yrs 0 mth |
Abstract Summary
In Canada, sepsis strikes young and old alike with an incidence of ~100 000 cases per year. Mortality remains between 20 and 40%, and the incidence is rising (8.7%/year). Survivors have long term morbidity and elevated risk of death. The risk of having post-sepsis syndrome is higher among people admitted to an intensive care unit (ICU) and for those who have been in the hospital for extended periods of time. Severe sepsis survivors are at higher risk for long-term cognitive impairment and physical problems. Even children may live with sequelae related to sepsis. Problems range from inability to walk to not being able to participate in everyday activities, such as bathing, toileting, or preparing meals. A single severe sepsis episode can also accelerate underlying chronic conditions such as atherosclerosis and diabetes. Currently, there are no markers that allow us identify survivors at risk for post-sepsis syndrome. Using clustering analysis our team determined that sepsis ICU-survivors fall into 2 subclasses - one with good outcomes (A) and the other (B) with increased morbidity and mortality. We compared microRNAs (miRs) - a small molecule important in the regulation of genes - circulating in the plasma from these two groups at the time of ICU discharge. We found that a set of 42 circulating miRs were predictive of subclass B. Here we propose to validate these miRs in a larger patient sample and in an independent sepsis-survivors population. We also propose to see if non-septic patients also fall into two separate subclasses and if our miRs of interest are predictive of subclass B in this group. Our research will provide new insight into post-sepsis syndrome pathways and immediate applications to identifying sepsis-survivors more likely to benefit from early and late intervention and follow up.
No special research characteristics identified
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