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


While the majority of coronavirus disease 2019 patients develop a mild disease, up to 20% become severely ill, with a severe interstitial pneumonia with high levels of acute phase mediators (cytokine storm) and other complications. There is a lack of knowledge on the role of individual genetic variability in conferring differential viral susceptibility, response to treatments, and severity of disease. This study aims at addressing this question, to identify factors predictive for the different evolution of the disease.

Facts and Figures

Project Lead
I Ceccherini
IRCCS Istituto Giannina Gaslini
FOREUM research grant: €100.000
2021 - 2022

Meet the Team

I Ceccherini
IRCCS Istituto Giannina Gaslini
M Gattorno
IRCCS Istituto Giannina Gaslini
P Uva
IRCCS Istituto Giannina Gaslini
S Croci
Azienda Unità Sanitaria Locale
P L Meroni
University of Milano
A Cavalli
Fondazione Istituto Italiano di Tecnologia (IIT)


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


Patient Voice

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