An explainable model of host genetic interactions linked to COVID-19 severity
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Published:2022-10-26
Issue:1
Volume:5
Page:
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ISSN:2399-3642
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Container-title:Communications Biology
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language:en
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Short-container-title:Commun Biol
Author:
Onoja Anthony, Picchiotti Nicola, Fallerini Chiara, Baldassarri Margherita, Fava Francesca, Mari Francesca, Daga Sergio, Benetti Elisa, Bruttini Mirella, Palmieri Maria, Croci Susanna, Amitrano Sara, Meloni Ilaria, Frullanti Elisa, Doddato Gabriella, Lista Mirjam, Beligni Giada, Valentino Floriana, Zguro Kristina, Tita Rossella, Giliberti Annarita, Mencarelli Maria Antonietta, Rizzo Caterina Lo, Pinto Anna Maria, Ariani Francesca, Di Sarno Laura, Montagnani Francesca, Tumbarello Mario, Rancan Ilaria, Fabbiani Massimiliano, Rossetti Barbara, Bergantini Laura, D’Alessandro Miriana, Cameli Paolo, Bennett David, Anedda Federico, Marcantonio Simona, Scolletta Sabino, Franchi Federico, Mazzei Maria Antonietta, Guerrini Susanna, Conticini Edoardo, Cantarini Luca, Frediani Bruno, Tacconi Danilo, Raffaelli Chiara Spertilli, Feri Marco, Donati Alice, Scala Raffaele, Guidelli Luca, Spargi Genni, Corridi Marta, Nencioni Cesira, Croci Leonardo, Caldarelli Gian Piero, Romani Davide, Piacentini Paolo, Bandini Maria, Desanctis Elena, Cappelli Silvia, Canaccini Anna, Verzuri Agnese, Anemoli Valentina, Pisani Manola, Ognibene Agostino, Pancrazzi Alessandro, Lorubbio Maria, Vaghi Massimo, D’Arminio Monforte Antonella, Miraglia Federica Gaia, Bruno Raffaele, Vecchia Marco, Girardis Massimo, Venturelli Sophie, Busani Stefano, Cossarizza Andrea, Antinori Andrea, Vergori Alessandra, Emiliozzi Arianna, Rusconi Stefano, Siano Matteo, Gabrieli Arianna, Riva Agostino, Francisci Daniela, Schiaroli Elisabetta, Paciosi Francesco, Tommasi Andrea, Zuccon Umberto, Vietri Lucia, Scotton Pier Giorgio, Andretta Francesca, Panese Sandro, Baratti Stefano, Scaggiante Renzo, Gatti Francesca, Parisi Saverio Giuseppe, Castelli Francesco, Quiros-Roldan Eugenia, Antoni Melania Degli, Zanella Isabella, Della Monica Matteo, Piscopo Carmelo, Capasso Mario, Russo Roberta, Andolfo Immacolata, Iolascon Achille, Fiorentino Giuseppe, Carella Massimo, Castori Marco, Aucella Filippo, Raggi Pamela, Perna Rita, Bassetti Matteo, Di Biagio Antonio, Sanguinetti Maurizio, Masucci Luca, Guarnaccia Alessandra, Valente Serafina, De Vivo Oreste, Bargagli Elena, Mandalà Marco, Giorli Alessia, Salerni Lorenzo, Zucchi Patrizia, Parravicini Pierpaolo, Menatti Elisabetta, Trotta Tullio, Giannattasio Ferdinando, Coiro Gabriella, Lena Fabio, Lacerenza Gianluca, Coviello Domenico A., Mussini Cristina, Martinelli Enrico, Tavecchia Luisa, Belli Mary Ann, Crotti Lia, Parati Gianfranco, Sanarico Maurizio, Biscarini Filippo, Stella Alessandra, Rizzi Marco, Maggiolo Franco, Ripamonti Diego, Suardi Claudia, Bachetti Tiziana, La Rovere Maria Teresa, Sarzi-Braga Simona, Bussotti Maurizio, Capitani Katia, Dei Simona, Ravaglia Sabrina, Artuso Rosangela, Andreucci Elena, Gori Giulia, Pagliazzi Angelica, Fiorentini Erika, Perrella Antonio, Bianchi Francesco, Bergomi Paola, Catena Emanuele, Colombo Riccardo, Luchi Sauro, Morelli Giovanna, Petrocelli Paola, Iacopini Sarah, Modica Sara, Baroni Silvia, Segala Francesco Vladimiro, Menichetti Francesco, Falcone Marco, Tiseo Giusy, Barbieri Chiara, Matucci Tommaso, Grassi Davide, Ferri Claudio, Marinangeli Franco, Brancati Francesco, Vincenti Antonella, Borgo Valentina, Lombardi Stefania, Lenzi Mirco, Di Pietro Massimo Antonio, Vichi Francesca, Romanin Benedetta, Attala Letizia, Costa Cecilia, Gabbuti Andrea, Menè Roberto, Colaneri Marta, Casprini Patrizia, Merla Giuseppe, Squeo Gabriella Maria, Maffezzoni Marcello, Mantovani Stefania, Mondelli Mario U., Ludovisi Serena, Colombo FrancescaORCID, Chiaromonte Francesca, Renieri AlessandraORCID, Furini Simone, Raimondi FrancescoORCID,
Abstract
AbstractWe employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as “Respiratory or thoracic disease”, supporting their link with COVID-19 severity outcome.
Publisher
Springer Science and Business Media LLC
Subject
General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)
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