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:
a) 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 hospedalization)
b) 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

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.

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