Whole Genome Sequencing in thrombo-inflammatory disorders triggered by SARS-CoV-2: machine learning applied to extensive immunological, genetic, and clinical datasets and implications for systemic rheumatic diseases

The project aims at:

• retrieving all the possible genetic information, by whole genome sequencing, from a heterogeneous set of individuals, affected by autoinflammatory/rheumatic and COVID-19 diseases, showing different disease severity (e.g. requiring versus non requiring hospitalization)
• preliminary data achieved on complement activation and its role in COVID-19 will be confirmed in a larger series of patients with mild, moderate, severe, and critical disease and in serial samples from patients during the follow-up

• 6 months: selection of patients and shipment of samples for WGS at IIT or another identified provider
• 18 months: WGS data elaboration, genetic analysis and deep learning approaches applied
• 21 months: data on complement activation
• 24 months: drawing conclusions, dissemination of results, publications

Matching the two proposed approaches (WGS and ML in parallel to an experimental study) is novel and going to be relevant to gain insights into pathogenic mechanisms playing a role in the onset and progression of COVID-19. This will provide novel biomarkers and original tools to recognize and treat more effectively both COVID-19 and rheumatic disorders, paving the way to personalized medicine interventions. The identification of genetic markers associated with COVID-19 severity will allow, a priori, to inform those subjects at higher risk of developing complications when infected with SARS-CoV-2. This knowledge will allow to plan interventions in those individuals (e.g. vaccination, preventive drugs / behaviours) to decrease the burden of COVID-19.