Disease Systems Biology

Infection is, in most patients, a commonplace, self-limiting condition that improves either by natural host defense processes or with iatrogenic assistance through antibiotics and source control. For reasons still poorly understood, a proportion of these infected patients develop organ dysfunction (sepsis) through a dysregulated host response. These complicated patients are at high risk of mortality (20-70%, depending on illness severity). Indeed, sepsis represents one of the major causes of death worldwide. Even in survivors, many develop long-term or even permanent physical and/or cognitive disability. Early identification and treatment is the most effective way of preventing these high morbidity and mortality rates.

Our group aims to overcome the challenges that currently limit the development and exploitation of novel personalized combinatorial therapies for sepsis by improving the understanding of infections and sepsis pathophysiology, developing novel approaches for the early diagnosis and optimal treatment of sepsis and sepsis-related organ failure. The specific objectives of our group are: SO1: to identify host biomarker signatures through multi-omics high-throughput analysis that would enable early diagnosis of infection and sepsis, and that can trigger early pre-symptomatic treatment; SO2: to recognize appropriate subsets of sepsis patients through integration of biological and clinical data to target with novel therapies; and SO3: to design combinatorial therapies based on in-silico pathway drug networks and validate them in preclinical and clinical studies.


It is well known that nutrition is the cornerstone of an individual’s environment, as such understanding how diet influences metabolic regulation and how dietary interventions can improve health is a key scientific goal. Furthermore, diet has a major influence on the overall quality of life beyond the prevention of diseases and its role is fundamental for individual performance and enjoyment. Even though the personalized approach to diet is the logical next step – much like the transition from pharmacology to personalized medicine – this task is extraordinarily complicated. Most foods are composed of hundreds of bioactive compounds, often interacting with each other. Furthermore, the targets are of varied concentrations and different targets have different affinities and specificities. Unfortunately, nutritional trials are not designed for mechanism-based preclinical studies, and little is known about their molecular targets. Our group integrates text mining, chemoinformatics and network biology for performing global analyses of diet that elucidates the synergistic interactions of small molecules that yield specific phenotypes and hopefully contribute towards personalized nutrition.