The genetic basis for a high level in clinical variability among COVID-19 patients – an interview with Alessandra Renieri


In this interview, we speak to Alessandra Renieri from the University of Siena (Italy), who is leading the GEN-COVID network encompassing over 35 hospitals in Italy. Renieri discusses the work they have been conducting into discovering the genetic basis for clinical variability seen in COVID-19 patients and why this is so important in tackling the pandemic. 

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Could you please introduce yourself and provide a brief summary of your career to date?

I am an expert clinical geneticist, leading one of the biggest medical genetics centers in Italy offering genetic counselling, genetic testing and gene editing for rare diseases and genetic cancers. Since 2007 I am Full Professor of Medical Genetics at the University of Siena. From 1 July 2019 I have been a member of the Committee for Advanced Therapies (CAT) at the European Medicines Agency (Amsterdam, The Netherlands).

My main research interest has always been the study of the genetic basis of rare diseases, with a special focus on Rett syndrome and other conditions with intellectual disabilities, Alport syndrome, retinoblastoma and other rare cancers. My lab was among the first in Italy to introduce array-CGH (comparative genomic hybridization) and Next Generation Sequencing (NGS) for clinical diagnosis as well as the use of NGS for liquid biopsy in cancer. Since 2017, my research has been  focused on gene editing using CRISPR systems and its translation into clinical practice. More recently, in Siena, I have been working on a “factory” for producing plasmids and vectors for gene editing in vitro and in animal models for preliminary research before moving on to clinical trials for several diseases, including Rett syndrome, Parkinson’s disease, Alport syndrome and Pompe disease.

I have directed the Genetic Biobank of Siena (GBS; Siena, Italy) since 1998. It is one of the few biobanks in Italy that is certified SIGU-CERT and ISO9001 and it has been funded by Fondazione Telethon since 2002. GBS is the Italian Partner of BBMRI (Biobanking and Biomolecular Resources Research Infrastructure, Austria), member of EuroBioBank and RD-Connect. I also coordinate the international Rett Database Network and the Italian Registry of Alport disease.

I am a Health Care Provider representative or sub-representative for Azienda Ospedaliero-Universitaria Senese (AOUS; Siena, Italy) in five European Reference Networks (ERNs): ERN ITHACA (on ID and congenital anomalies); ERKNET (on rare kidney diseases); EuroBloodNet (on rare hematological diseases); PaedCan-ERN (on pediatric cancers) and EURACAN (for rare adult solid cancers). I am an active member of the Telethon Network of Genetic Biobanks (TNGB, Milan, Italy) and I act as a medical advisor with several patient organizations and as a supervisor in specialist clinics for rare disorders within AOUS.

To rapidly respond to the ongoing COVID-19 pandemic, I am focusing on developing an informative diagnostic test and a potential therapy on the basis of the host genome. I am leading the GEN-COVID Multicenter Study and am member and co-founder of the international Host Genetic Initiative.

Could you give an overview of the GEN-COVID project and the rationale behind whole exome sequencing for COVID-19?

GEN-COVID is a network of more than 35 Hospitals and 16 Continuity Assistance Special Units across Italy. Physicians of several specialties from infectious diseases to respiratory diseases, anesthesiology, cardiology, rheumatology, neurology, ear, nose and throat and medical genetics will provide the basis for a detailed patient registry and biobank of samples. GEN-COVID started its activity on March 16, 2020 after IRB approval. The network plans to enroll 2,000 patients for host genetic analysis in order to develop a genetic-based approach to further understand the clinical variability of COVID-19 in this public health emergency. Phenotypic information is collected via questionnaires comprising of 160 clinical items.

This project aims to rapidly respond to the current COVID-19 outbreak that has spread around the world. Since the beginning of the outbreak, one of the first observations has been a highly heterogeneous phenotypic response to SARS-CoV-2 infection among patients. Although age and comorbidity have been described as the main determinants of disease progression, these factors alone do not fully explain the differences in disease severity. The most reasonable hypothesis is that at the basis of these different outcomes there are host predisposing genetic factors leading to different levels of effectiveness of antiviral defenses as well as specific receptor permissiveness to the virus and immunogenicity. To investigate this hypothesis and to establish an association between host genetic variants and COVID-19 severity and prognosis, we are performing clinical and molecular characterization by Whole Exome Sequencing (WES) analysis in the cohort of 2,000 COVID-19 patients.


What are the main challenges associated with the varied genetic susceptibility to COVID-19 observed between individuals?

The main challenge is represented by the complexity of genetic susceptibility to COVID-19, bringing out rare and low-frequency variants. This complexity requires new mathematical models and powerful and sophisticated analysis tools combining WES and machine learning approach based on the use of artificial intelligence (AI). These AI instruments are able to extract interpretable rules within the huge amount of data and untangle the multisystem presentation of COVID-19.

At the same time, the generation of a myriad of genetic data needs the availability of computing resources able to store and to continuously analyze data. This issue was addressed thanks to the long lasting collaboration between the Network for Italian Genomes and CINECA, the largest computing center in Italy and one of the largest in Europe.

What were the most important results/conclusions from the study?

The working hypothesis is that different clinical expressivity of COVID-19 ranging from absence of symptoms to flu or severe pneumonia, is dependent on host genetics. The results of the first pilot phase, posted on May in MedRxiv, and of the first validation phase, presented at the late breaking session of European Society of Human Genetics virtual annual conference (ESHG 2020), pinpointed a combined model in which few common genes represent the favorite background in which additional rare mutations confer to the host a personalized susceptibility to the disease. Using semantic-based regularization for learning and interference, we were also able to identify a number of genes that were specifically relevant for different organs and how individual organs responded to SARS-CoV-2 infection.

To follow up on these discoveries, we are now running a second validation phase using a cohort of 500 hospitalized and not hospitalized patients having in mind that COVID-19 is not a simple pneumonia but a multisystemic disorder. We identified multiple genetic variants that may play a role in determining the severity of COVID-19. In addition to looking at common and rare variants and how they might impact disease susceptibility and severity, we will also look at gender in the second validation phase, as men are typically considered to experience more severe reactions to the virus. The results of this second validation phase will be presented at the American Society of Human Genetics annual conference (ASHG 2020).

What do you think are the implications of these results for health and healthcare policy?

At present, little is known about the impact that host genome variability has on COVID-19. Identifying genetic variants associated with disease severity is of primary importance for public health and healthcare policy. Such discoveries could lead to a more in-depth understanding of the biology of SARS-CoV-2 infection and disease, enabling more informed  generation of hypotheses for drug repurposing,  and identification of individuals at unusually high or low risk. Identifying the most susceptible segments of the population will enable more effective drug development strategies and more effective allocation of resources, leading to rapid public health treatment interventions. The integration of these results into clinical care will facilitate a more personalized approach to treatments and guide the development of  novel diagnostics by taking into account the host genetic variability.

A number of studies have suggested that some ethnic groups may be more susceptible to COVID-19 than others. Do you think your approach could be used to further our knowledge in this area?

The large variation of COVID-19 mortality across countries and ethnic groups certainly supports how  important a role host genetics plays. Our approach aimed at understanding the genetic and molecular basis of susceptibility to SARS-CoV-2 infections and the variety in the severity of the clinical outcomes of COVID-19 may hold clues for the development of personalized effective treatments. But no single group, not even a single consortium alone can undertake this task. That is why, we will address this present challenge by collecting high quality, phenotyped samples and contributing to global initiatives. And the COVID-19 biobank developed via the GEN-COVID project will be made accessible to academic and industry partners in order to further knowledge in this area.

How do you hope to see this project and area of research progress over the coming months?

Our data, although preliminary, are promising and will be validated in a wider population. Our project can provide fast results and make them readily available to the whole scientific community in the coming months for a rapid translation into the clinic and for better management of the national health system and the whole society after the current lockdown. Infected individuals at predisposed risk of severe complication like pneumonia will be identified prior to onset of symptoms. This will allow practicing physicians to act prospectively with personalized treatment algorithms. This information will contribute to the global understanding of SARS-CoV-2 and COVID-19 and thereby to all ongoing research initiatives aimed at rapid action towards the current COVID-19 outbreak and the prevention of future coronavirus outbreaks.

Is there anything else you would like to add?

Going beyond these results, the outcome of this study underlines the need for new mathematical methods to detect the basis of one of the more complex genetic traits, with an environmental causation (such as with the SARS-CoV-2 virus) but a high rate of heritability. We definitely need to develop new mathematical models using AI in order to be able to understand the complexity of this trait.

I would like to thank all my group at Medical Genetics in Siena, the biomedical engineer Professor Simone Furini and his team, and the Siena Artificial Intelligence Lab directed by Professor Marco Gori. A special thank you is also dedicated to all physicians in the 35 Italian Hospitals and 16 Continuity Assistance Special Units of the GEN-COVID network who agreed to cooperate with us for this challenge during the COVID-19 emergency.

The opinions expressed in this interview are those of the interviewee and do not necessarily reflect the views of Infectious Diseases Hub or Future Science Group.

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