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3. An explainable model of host genetic interactions linked to COVID-19 severity

Author

Onoja, A., Picchiotti, N., Fallerini, C., Baldassarri, M., Fava, F., Mari, F., Daga, S., Benetti, E., Bruttini, M., Palmieri, Marco, Croci, S., Amitrano, S., Meloni, I., Frullanti, E., Doddato, G., Lista, Maddalena, Beligni, G., Valentino, Francesca, Zguro, K., Tita, R., Giliberti, A., Mencarelli, Marta, Rizzo, C. L., Pinto, A. M., Ariani, F., Di Sarno, Lorenzo, Montagnani, F., Tumbarello, Mario, Rancan, I., Fabbiani, M., Rossetti, Barbara, Bergantini, L., D'Alessandro, Michele, Cameli, P., Bennett, D., Anedda, F., Marcantonio, S., Scolletta, S., Franchi, Francesca, Mazzei, M. A., Guerrini, S., Conticini, E., Cantarini, L., Frediani, B., Tacconi, D., Raffaelli, C. S., Feri, M., Donati, Andrea, Scala, R., Guidelli, L., Spargi, G., Corridi, M., Nencioni, C., Croci, L., Caldarelli, G. P., Romani, D., Piacentini, P., Bandini, M., Desanctis, E., Cappelli, S., Canaccini, A., Verzuri, A., Anemoli, V., Pisani, M., Ognibene, A., Pancrazzi, A., Lorubbio, M., Vaghi, M., D'Arminio Monforte, A., Miraglia, F. G., Bruno, R., Vecchia, M., Girardis, M., Venturelli, S., Busani, S., Cossarizza, A., Antinori, Armando, Vergori, A., Emiliozzi, A., Rusconi, S., Siano, M., Gabrieli, A., Riva, A., Francisci, D., Schiaroli, E., Paciosi, F., Tommasi, A., Zuccon, U., Vietri, L., Scotton, P. G., Andretta, F., Panese, S., Baratti, S., Scaggiante, R., Gatti, F., Parisi, S. G., Castelli, F., Quiros-Roldan, E., Antoni, M. D., Zanella, I., Della Monica, M., Piscopo, C., Capasso, Monica, Russo, R., Andolfo, I., Iolascon, A., Fiorentino, Giuseppe, Carella, M., Castori, M., Aucella, F., Raggi, P., Perna, Raffaella, Bassetti, M., Di Biagio, Anna, Sanguinetti, Maurizio, Masucci, Luca, Guarnaccia, A., Valente, S., De Vivo, O., Bargagli, E., Mandala, M., Giorli, A., Salerni, L., Zucchi, P., Parravicini, P., Menatti, E., Trotta, T., Giannattasio, F., Coiro, G., Lena, Francesco, Lacerenza, G., Coviello, D. A., Mussini, C., Martinelli, E., Tavecchia, L., Belli, M. A., Crotti, L., Parati, G., Sanarico, M., Biscarini, F., Stella, A., Rizzi, M., Maggiolo, F., Ripamonti, D., Suardi, C., Bachetti, T., La Rovere, M. T., Sarzi-Braga, S., Bussotti, M., Capitani, K., Dei, S., Ravaglia, S., Artuso, R., Andreucci, E., Gori, Giovanni Cristiano, Pagliazzi, A., Fiorentini, E., Perrella, A., Bianchi, F., Bergomi, P., Catena, E., Colombo, R., Luchi, S., Morelli, G., Petrocelli, Paolo, Iacopini, S., Modica, S., Baroni, Silvia, Segala, F. V., Menichetti, F., Falcone, M., Tiseo, G., Barbieri, Cristiano, Matucci, T., Grassi, D., Ferri, C., Marinangeli, F., Brancati, F., Vincenti, A., Borgo, V., Lombardi, S., Lenzi, M., Di Pietro, Maria Luisa, Vichi, F., Romanin, B., Attala, L., Costa, C., Gabbuti, A., Mene, R., Colaneri, M., Casprini, P., Merla, G., Squeo, G. M., Maffezzoni, M., Mantovani, Susanna, Mondelli, M. U., Ludovisi, S., Colombo, F., Chiaromonte, F., Renieri, A., Furini, S., Raimondi, F., Palmieri M. (ORCID:0000-0001-8263-336X), Lista M., Valentino F., Mencarelli M. A., Di Sarno L., Tumbarello M. (ORCID:0000-0002-9519-8552), Rossetti B., D'Alessandro M., Franchi F., Donati A., Antinori A. (ORCID:0000-0002-6019-2417), Capasso M., Fiorentino G., Perna R., Di Biagio A., Sanguinetti M. (ORCID:0000-0002-9780-7059), Masucci L. (ORCID:0000-0002-8358-6726), Lena F. (ORCID:0000-0001-5528-319X), Gori G. (ORCID:0000-0002-3308-5309), Petrocelli P., Barbieri C., Di Pietro M. A. (ORCID:0000-0002-3893-8788), Mantovani S., Onoja, A., Picchiotti, N., Fallerini, C., Baldassarri, M., Fava, F., Mari, F., Daga, S., Benetti, E., Bruttini, M., Palmieri, Marco, Croci, S., Amitrano, S., Meloni, I., Frullanti, E., Doddato, G., Lista, Maddalena, Beligni, G., Valentino, Francesca, Zguro, K., Tita, R., Giliberti, A., Mencarelli, Marta, Rizzo, C. L., Pinto, A. M., Ariani, F., Di Sarno, Lorenzo, Montagnani, F., Tumbarello, Mario, Rancan, I., Fabbiani, M., Rossetti, Barbara, Bergantini, L., D'Alessandro, Michele, Cameli, P., Bennett, D., Anedda, F., Marcantonio, S., Scolletta, S., Franchi, Francesca, Mazzei, M. A., Guerrini, S., Conticini, E., Cantarini, L., Frediani, B., Tacconi, D., Raffaelli, C. S., Feri, M., Donati, Andrea, Scala, R., Guidelli, L., Spargi, G., Corridi, M., Nencioni, C., Croci, L., Caldarelli, G. P., Romani, D., Piacentini, P., Bandini, M., Desanctis, E., Cappelli, S., Canaccini, A., Verzuri, A., Anemoli, V., Pisani, M., Ognibene, A., Pancrazzi, A., Lorubbio, M., Vaghi, M., D'Arminio Monforte, A., Miraglia, F. G., Bruno, R., Vecchia, M., Girardis, M., Venturelli, S., Busani, S., Cossarizza, A., Antinori, Armando, Vergori, A., Emiliozzi, A., Rusconi, S., Siano, M., Gabrieli, A., Riva, A., Francisci, D., Schiaroli, E., Paciosi, F., Tommasi, A., Zuccon, U., Vietri, L., Scotton, P. G., Andretta, F., Panese, S., Baratti, S., Scaggiante, R., Gatti, F., Parisi, S. G., Castelli, F., Quiros-Roldan, E., Antoni, M. D., Zanella, I., Della Monica, M., Piscopo, C., Capasso, Monica, Russo, R., Andolfo, I., Iolascon, A., Fiorentino, Giuseppe, Carella, M., Castori, M., Aucella, F., Raggi, P., Perna, Raffaella, Bassetti, M., Di Biagio, Anna, Sanguinetti, Maurizio, Masucci, Luca, Guarnaccia, A., Valente, S., De Vivo, O., Bargagli, E., Mandala, M., Giorli, A., Salerni, L., Zucchi, P., Parravicini, P., Menatti, E., Trotta, T., Giannattasio, F., Coiro, G., Lena, Francesco, Lacerenza, G., Coviello, D. A., Mussini, C., Martinelli, E., Tavecchia, L., Belli, M. A., Crotti, L., Parati, G., Sanarico, M., Biscarini, F., Stella, A., Rizzi, M., Maggiolo, F., Ripamonti, D., Suardi, C., Bachetti, T., La Rovere, M. T., Sarzi-Braga, S., Bussotti, M., Capitani, K., Dei, S., Ravaglia, S., Artuso, R., Andreucci, E., Gori, Giovanni Cristiano, Pagliazzi, A., Fiorentini, E., Perrella, A., Bianchi, F., Bergomi, P., Catena, E., Colombo, R., Luchi, S., Morelli, G., Petrocelli, Paolo, Iacopini, S., Modica, S., Baroni, Silvia, Segala, F. V., Menichetti, F., Falcone, M., Tiseo, G., Barbieri, Cristiano, Matucci, T., Grassi, D., Ferri, C., Marinangeli, F., Brancati, F., Vincenti, A., Borgo, V., Lombardi, S., Lenzi, M., Di Pietro, Maria Luisa, Vichi, F., Romanin, B., Attala, L., Costa, C., Gabbuti, A., Mene, R., Colaneri, M., Casprini, P., Merla, G., Squeo, G. M., Maffezzoni, M., Mantovani, Susanna, Mondelli, M. U., Ludovisi, S., Colombo, F., Chiaromonte, F., Renieri, A., Furini, S., Raimondi, F., Palmieri M. (ORCID:0000-0001-8263-336X), Lista M., Valentino F., Mencarelli M. A., Di Sarno L., Tumbarello M. (ORCID:0000-0002-9519-8552), Rossetti B., D'Alessandro M., Franchi F., Donati A., Antinori A. (ORCID:0000-0002-6019-2417), Capasso M., Fiorentino G., Perna R., Di Biagio A., Sanguinetti M. (ORCID:0000-0002-9780-7059), Masucci L. (ORCID:0000-0002-8358-6726), Lena F. (ORCID:0000-0001-5528-319X), Gori G. (ORCID:0000-0002-3308-5309), Petrocelli P., Barbieri C., Di Pietro M. A. (ORCID:0000-0002-3893-8788), and Mantovani S.

Abstract

We 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.

Published
2022

4. An explainable model of host genetic interactions linked to COVID-19 severity

Author

Anthony, O, Nicola, P, Chiara, F, Margherita, B, Francesca, F, Francesca, C, Alessandra, R, Simone, F, Francesco, R, Mari, F, Daga, S, Benetti, E, Bruttini, M, Palmieri, M, Croci, S, Amitrano, S, Meloni, I, Frullanti, E, Doddato, G, Lista, M, Beligni, G, Valentino, F, Zguro, K, Tita, R, Giliberti, A, Antonietta Mencarelli, M, Lo Rizzo, C, Maria Pinto, A, Ariani, F, Di Sarno, L, Montagnani, F, Tumbarello, M, Rancan, I, Fabbiani, M, Rossetti, B, Bergantini, L, D’Alessandro, M, Cameli, P, Bennett, D, Anedda, F, Marcantonio, S, Scolletta, S, Franchi, F, Antonietta Mazzei, M, Guerrini, S, Conticini, E, Cantarini, L, Frediani, B, Tacconi, D, Spertilli Raffaelli, C, Feri, M, Donati, A, Scala, R, Guidelli, L, Spargi, G, Corridi, M, Nencioni, C, Croci, L, Piero Caldarelli, G, Romani, D, Piacentini, P, Bandini, M, Desanctis, E, Cappelli, S, Canaccini, A, Verzuri, A, Anemoli, V, Pisani, M, Ognibene, A, Pancrazzi, A, Lorubbio, M, Vaghi, M, D’Arminio Monforte, A, Gaia Miraglia, F, Bruno, R, Vecchia, M, Girardis, M, Venturelli, S, Busani, S, Cossarizza, A, Antinori, A, Vergori, A, Emiliozzi, A, Rusconi, S, Siano, M, Gabrieli, A, Riva, A, Francisci, D, Schiaroli, E, Paciosi, F, Tommasi, A, Zuccon, U, Vietri, L, Giorgio Scotton, P, Andretta, F, Panese, S, Baratti, S, Scaggiante, R, Gatti, F, Giuseppe Parisi, S, Castelli, F, Quiros-Roldan, E, Degli Antoni, M, Zanella, I, Della Monica, M, Piscopo, C, Capasso, M, Russo, R, Andolfo, I, Iolascon, A, Fiorentino, G, Carella, M, Castori, M, Aucella, F, Raggi, P, Perna, R, Bassetti, M, Di Biagio, A, Sanguinetti, M, Masucci, L, Guarnaccia, A, Valente, S, De Vivo, O, Bargagli, E, Mandalà, M, Giorli, A, Salerni, L, Zucchi, P, Parravicini, P, Menatti, E, Trotta, T, Giannattasio, F, Coiro, G, Lena, F, Lacerenza, G, Coviello, D, Mussini, C, Martinelli, E, Tavecchia, L, Ann Belli, M, Crotti, L, Parati, G, Sanarico, M, Biscarini, F, Stella, A, Rizzi, M, Maggiolo, F, Ripamonti, D, Suardi, C, Bachetti, T, Teresa La Rovere, M, Sarzi-Braga, S, Bussotti, M, Capitani, K, Dei, S, Ravaglia, S, Artuso, R, Andreucci, E, Gori, G, Pagliazzi, A, Fiorentini, E, Perrella, A, Bianchi, F, Bergomi, P, Catena, E, Colombo, R, Luchi, S, Morelli, G, Petrocelli, P, Iacopini, S, Modica, S, Baroni, S, Vladimiro Segala, F, Menichetti, F, Falcone, M, Tiseo, G, Barbieri, C, Matucci, T, Grassi, D, Ferri, C, Marinangeli, F, Brancati, F, Vincenti, A, Borgo, V, Lombardi, S, Lenzi, M, Antonio Di Pietro, M, Vichi, F, Romanin, B, Attala, L, Costa, C, Gabbuti, A, Menè, R, Colaneri, M, Casprini, P, Merla, G, Maria Squeo, G, Maffezzoni, M, Mantovani, S, Mondelli &amp, M, Ludovisi, S, Onoja, Anthony, Picchiotti, Nicola, Fallerini, Chiara, Baldassarri, Margherita, Fava, Francesca, Colombo, Francesca, Chiaromonte, Francesca, Renieri, Alessandra, Furini, Simone, Raimondi Francesco, Francesca Mari, Sergio Daga, Elisa Benetti, Mirella Bruttini, Maria Palmieri, Susanna Croci, Sara Amitrano, Ilaria Meloni, Elisa Frullanti, Gabriella Doddato, Mirjam Lista, Giada Beligni, Floriana Valentino, Kristina Zguro, Rossella Tita, Annarita Giliberti, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Francesca Ariani, Laura Di Sarno, Francesca Montagnani, Mario Tumbarello, Ilaria Rancan, Massimiliano Fabbiani, Barbara Rossetti, Laura Bergantini, Miriana D’Alessandro, Paolo Cameli, David Bennett, Federico Anedda, Simona Marcantonio, Sabino Scolletta, Federico Franchi, Maria Antonietta Mazzei, Susanna Guerrini, Edoardo Conticini, Luca Cantarini, Bruno Frediani, Danilo Tacconi, Chiara Spertilli Raffaelli, Marco Feri, Alice Donati, Raffaele Scala, Luca Guidelli, Genni Spargi, Marta Corridi, Cesira Nencioni, Leonardo Croci, Gian Piero Caldarelli, Davide Romani, Paolo Piacentini, Maria Bandini, Elena Desanctis, Silvia Cappelli, Anna Canaccini, Agnese Verzuri, Valentina Anemoli, Manola Pisani, Agostino Ognibene, Alessandro Pancrazzi, Maria Lorubbio, Massimo Vaghi, Antonella D’Arminio Monforte, Federica Gaia Miraglia, Raffaele Bruno, Marco Vecchia, Massimo Girardis, Sophie Venturelli, Stefano Busani, Andrea Cossarizza, Andrea Antinori, Alessandra Vergori, Arianna Emiliozzi, Stefano Rusconi, Matteo Siano, Arianna Gabrieli, Agostino Riva, Daniela Francisci, Elisabetta Schiaroli, Francesco Paciosi, Andrea Tommasi, Umberto Zuccon, Lucia Vietri, Pier Giorgio Scotton, Francesca Andretta, Sandro Panese, Stefano Baratti, Renzo Scaggiante, Francesca Gatti, Saverio Giuseppe Parisi, Francesco Castelli, Eugenia Quiros-Roldan, Melania Degli Antoni, Isabella Zanella, Matteo Della Monica, Carmelo Piscopo, Mario Capasso, Roberta Russo, Immacolata Andolfo, Achille Iolascon, Giuseppe Fiorentino, Massimo Carella, Marco Castori, Filippo Aucella, Pamela Raggi, Rita Perna, Matteo Bassetti, Antonio Di Biagio, Maurizio Sanguinetti, Luca Masucci, Alessandra Guarnaccia, Serafina Valente, Oreste De Vivo, Elena Bargagli, Marco Mandalà, Alessia Giorli, Lorenzo Salerni, Patrizia Zucchi, Pierpaolo Parravicini, Elisabetta Menatti, Tullio Trotta, Ferdinando Giannattasio, Gabriella Coiro, Fabio Lena, Gianluca Lacerenza, Domenico A. Coviello, Cristina Mussini, Enrico Martinelli, Luisa Tavecchia, Mary Ann Belli, Lia Crotti, Gianfranco Parati, Maurizio Sanarico, Filippo Biscarini, Alessandra Stella, Marco Rizzi, Franco Maggiolo, Diego Ripamonti, Claudia Suardi, Tiziana Bachetti, Maria Teresa La Rovere, Simona Sarzi-Braga, Maurizio Bussotti, Katia Capitani, Simona Dei, Sabrina Ravaglia, Rosangela Artuso, Elena Andreucci, Giulia Gori, Angelica Pagliazzi, Erika Fiorentini, Antonio Perrella, Francesco Bianchi, Paola Bergomi, Emanuele Catena, Riccardo Colombo, Sauro Luchi, Giovanna Morelli, Paola Petrocelli, Sarah Iacopini, Sara Modica, Silvia Baroni, Francesco Vladimiro Segala, Francesco Menichetti, Marco Falcone, Giusy Tiseo, Chiara Barbieri, Tommaso Matucci, Davide Grassi, Claudio Ferri, Franco Marinangeli, Francesco Brancati, Antonella Vincenti, Valentina Borgo, Stefania Lombardi, Mirco Lenzi, Massimo Antonio Di Pietro, Francesca Vichi, Benedetta Romanin, Letizia Attala, Cecilia Costa, Andrea Gabbuti, Roberto Menè, Marta Colaneri, Patrizia Casprini, Giuseppe Merla, Gabriella Maria Squeo, Marcello Maffezzoni, Stefania Mantovani, Mario U. Mondelli &, Serena Ludovisi, Anthony, O, Nicola, P, Chiara, F, Margherita, B, Francesca, F, Francesca, C, Alessandra, R, Simone, F, Francesco, R, Mari, F, Daga, S, Benetti, E, Bruttini, M, Palmieri, M, Croci, S, Amitrano, S, Meloni, I, Frullanti, E, Doddato, G, Lista, M, Beligni, G, Valentino, F, Zguro, K, Tita, R, Giliberti, A, Antonietta Mencarelli, M, Lo Rizzo, C, Maria Pinto, A, Ariani, F, Di Sarno, L, Montagnani, F, Tumbarello, M, Rancan, I, Fabbiani, M, Rossetti, B, Bergantini, L, D’Alessandro, M, Cameli, P, Bennett, D, Anedda, F, Marcantonio, S, Scolletta, S, Franchi, F, Antonietta Mazzei, M, Guerrini, S, Conticini, E, Cantarini, L, Frediani, B, Tacconi, D, Spertilli Raffaelli, C, Feri, M, Donati, A, Scala, R, Guidelli, L, Spargi, G, Corridi, M, Nencioni, C, Croci, L, Piero Caldarelli, G, Romani, D, Piacentini, P, Bandini, M, Desanctis, E, Cappelli, S, Canaccini, A, Verzuri, A, Anemoli, V, Pisani, M, Ognibene, A, Pancrazzi, A, Lorubbio, M, Vaghi, M, D’Arminio Monforte, A, Gaia Miraglia, F, Bruno, R, Vecchia, M, Girardis, M, Venturelli, S, Busani, S, Cossarizza, A, Antinori, A, Vergori, A, Emiliozzi, A, Rusconi, S, Siano, M, Gabrieli, A, Riva, A, Francisci, D, Schiaroli, E, Paciosi, F, Tommasi, A, Zuccon, U, Vietri, L, Giorgio Scotton, P, Andretta, F, Panese, S, Baratti, S, Scaggiante, R, Gatti, F, Giuseppe Parisi, S, Castelli, F, Quiros-Roldan, E, Degli Antoni, M, Zanella, I, Della Monica, M, Piscopo, C, Capasso, M, Russo, R, Andolfo, I, Iolascon, A, Fiorentino, G, Carella, M, Castori, M, Aucella, F, Raggi, P, Perna, R, Bassetti, M, Di Biagio, A, Sanguinetti, M, Masucci, L, Guarnaccia, A, Valente, S, De Vivo, O, Bargagli, E, Mandalà, M, Giorli, A, Salerni, L, Zucchi, P, Parravicini, P, Menatti, E, Trotta, T, Giannattasio, F, Coiro, G, Lena, F, Lacerenza, G, Coviello, D, Mussini, C, Martinelli, E, Tavecchia, L, Ann Belli, M, Crotti, L, Parati, G, Sanarico, M, Biscarini, F, Stella, A, Rizzi, M, Maggiolo, F, Ripamonti, D, Suardi, C, Bachetti, T, Teresa La Rovere, M, Sarzi-Braga, S, Bussotti, M, Capitani, K, Dei, S, Ravaglia, S, Artuso, R, Andreucci, E, Gori, G, Pagliazzi, A, Fiorentini, E, Perrella, A, Bianchi, F, Bergomi, P, Catena, E, Colombo, R, Luchi, S, Morelli, G, Petrocelli, P, Iacopini, S, Modica, S, Baroni, S, Vladimiro Segala, F, Menichetti, F, Falcone, M, Tiseo, G, Barbieri, C, Matucci, T, Grassi, D, Ferri, C, Marinangeli, F, Brancati, F, Vincenti, A, Borgo, V, Lombardi, S, Lenzi, M, Antonio Di Pietro, M, Vichi, F, Romanin, B, Attala, L, Costa, C, Gabbuti, A, Menè, R, Colaneri, M, Casprini, P, Merla, G, Maria Squeo, G, Maffezzoni, M, Mantovani, S, Mondelli &amp, M, Ludovisi, S, Onoja, Anthony, Picchiotti, Nicola, Fallerini, Chiara, Baldassarri, Margherita, Fava, Francesca, Colombo, Francesca, Chiaromonte, Francesca, Renieri, Alessandra, Furini, Simone, Raimondi Francesco, Francesca Mari, Sergio Daga, Elisa Benetti, Mirella Bruttini, Maria Palmieri, Susanna Croci, Sara Amitrano, Ilaria Meloni, Elisa Frullanti, Gabriella Doddato, Mirjam Lista, Giada Beligni, Floriana Valentino, Kristina Zguro, Rossella Tita, Annarita Giliberti, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Francesca Ariani, Laura Di Sarno, Francesca Montagnani, Mario Tumbarello, Ilaria Rancan, Massimiliano Fabbiani, Barbara Rossetti, Laura Bergantini, Miriana D’Alessandro, Paolo Cameli, David Bennett, Federico Anedda, Simona Marcantonio, Sabino Scolletta, Federico Franchi, Maria Antonietta Mazzei, Susanna Guerrini, Edoardo Conticini, Luca Cantarini, Bruno Frediani, Danilo Tacconi, Chiara Spertilli Raffaelli, Marco Feri, Alice Donati, Raffaele Scala, Luca Guidelli, Genni Spargi, Marta Corridi, Cesira Nencioni, Leonardo Croci, Gian Piero Caldarelli, Davide Romani, Paolo Piacentini, Maria Bandini, Elena Desanctis, Silvia Cappelli, Anna Canaccini, Agnese Verzuri, Valentina Anemoli, Manola Pisani, Agostino Ognibene, Alessandro Pancrazzi, Maria Lorubbio, Massimo Vaghi, Antonella D’Arminio Monforte, Federica Gaia Miraglia, Raffaele Bruno, Marco Vecchia, Massimo Girardis, Sophie Venturelli, Stefano Busani, Andrea Cossarizza, Andrea Antinori, Alessandra Vergori, Arianna Emiliozzi, Stefano Rusconi, Matteo Siano, Arianna Gabrieli, Agostino Riva, Daniela Francisci, Elisabetta Schiaroli, Francesco Paciosi, Andrea Tommasi, Umberto Zuccon, Lucia Vietri, Pier Giorgio Scotton, Francesca Andretta, Sandro Panese, Stefano Baratti, Renzo Scaggiante, Francesca Gatti, Saverio Giuseppe Parisi, Francesco Castelli, Eugenia Quiros-Roldan, Melania Degli Antoni, Isabella Zanella, Matteo Della Monica, Carmelo Piscopo, Mario Capasso, Roberta Russo, Immacolata Andolfo, Achille Iolascon, Giuseppe Fiorentino, Massimo Carella, Marco Castori, Filippo Aucella, Pamela Raggi, Rita Perna, Matteo Bassetti, Antonio Di Biagio, Maurizio Sanguinetti, Luca Masucci, Alessandra Guarnaccia, Serafina Valente, Oreste De Vivo, Elena Bargagli, Marco Mandalà, Alessia Giorli, Lorenzo Salerni, Patrizia Zucchi, Pierpaolo Parravicini, Elisabetta Menatti, Tullio Trotta, Ferdinando Giannattasio, Gabriella Coiro, Fabio Lena, Gianluca Lacerenza, Domenico A. Coviello, Cristina Mussini, Enrico Martinelli, Luisa Tavecchia, Mary Ann Belli, Lia Crotti, Gianfranco Parati, Maurizio Sanarico, Filippo Biscarini, Alessandra Stella, Marco Rizzi, Franco Maggiolo, Diego Ripamonti, Claudia Suardi, Tiziana Bachetti, Maria Teresa La Rovere, Simona Sarzi-Braga, Maurizio Bussotti, Katia Capitani, Simona Dei, Sabrina Ravaglia, Rosangela Artuso, Elena Andreucci, Giulia Gori, Angelica Pagliazzi, Erika Fiorentini, Antonio Perrella, Francesco Bianchi, Paola Bergomi, Emanuele Catena, Riccardo Colombo, Sauro Luchi, Giovanna Morelli, Paola Petrocelli, Sarah Iacopini, Sara Modica, Silvia Baroni, Francesco Vladimiro Segala, Francesco Menichetti, Marco Falcone, Giusy Tiseo, Chiara Barbieri, Tommaso Matucci, Davide Grassi, Claudio Ferri, Franco Marinangeli, Francesco Brancati, Antonella Vincenti, Valentina Borgo, Stefania Lombardi, Mirco Lenzi, Massimo Antonio Di Pietro, Francesca Vichi, Benedetta Romanin, Letizia Attala, Cecilia Costa, Andrea Gabbuti, Roberto Menè, Marta Colaneri, Patrizia Casprini, Giuseppe Merla, Gabriella Maria Squeo, Marcello Maffezzoni, Stefania Mantovani, Mario U. Mondelli &, and Serena Ludovisi

Abstract

We 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.

Published
2022

7. The WISSH quasars project

Author

M. Bischetti, E. Piconcelli, C. Feruglio, F. Duras, A. Bongiorno, S. Carniani, A. Marconi, C. Pappalardo, R. Schneider, A. Travascio, R. Valiante, G. Vietri, L. Zappacosta, F. Fiore

Published
2017
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8. An explainable model of host genetic interactions linked to COVID-19 severity

Author

Onoja, Anthony, Picchiotti, Nicola, Fallerini, Chiara, Baldassarri, Margherita, Fava, Francesca, Colombo, Francesca, Chiaromonte, Francesca, Renieri, Alessandra, Furini, Simone, Raimondi, Francesco GEN-COVID Multicenter Study: Francesca Mari, Sergio, Daga, Elisa, Benetti, Mirella, Bruttini, Maria, Palmieri, Susanna, Croci, Sara, Amitrano, Ilaria, Meloni, Elisa, Frullanti, Gabriella, Doddato, Mirjam, Lista, Giada, Beligni, Floriana, Valentino, Kristina, Zguro, Rossella, Tita, Annarita, Giliberti, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Francesca, Ariani, Laura Di Sarno, Francesca, Montagnani, Mario, Tumbarello, Ilaria, Rancan, Massimiliano, Fabbiani, Barbara, Rossetti, Laura, Bergantini, Miriana, D'Alessandro, Paolo, Cameli, David, Bennett, Federico, Anedda, Simona, Marcantonio, Sabino, Scolletta, Federico, Franchi, Maria Antonietta Mazzei, Susanna, Guerrini, Edoardo, Conticini, Luca, Cantarini, Bruno, Frediani, Danilo, Tacconi, Chiara Spertilli Raffaelli, Marco, Feri, Alice, Donati, Raffaele, Scala, Luca, Guidelli, Genni, Spargi, Marta, Corridi, Cesira, Nencioni, Leonardo, Croci, Gian Piero Caldarelli, Davide, Romani, Paolo, Piacentini, Maria, Bandini, Elena, Desanctis, Silvia, Cappelli, Anna, Canaccini, Agnese, Verzuri, Valentina, Anemoli, Manola, Pisani, Agostino, Ognibene, Alessandro, Pancrazzi, Maria, Lorubbio, Massimo, Vaghi, Antonella D'Arminio Monforte, Federica Gaia Miraglia, Raffaele, Bruno, Marco, Vecchia, Massimo, Girardis, Sophie, Venturelli, Stefano, Busani, Andrea, Cossarizza, Andrea, Antinori, Alessandra, Vergori, Arianna, Emiliozzi, Stefano, Rusconi, Matteo, Siano, Arianna, Gabrieli, Agostino, Riva, Daniela, Francisci, Elisabetta, Schiaroli, Francesco, Paciosi, Andrea, Tommasi, Umberto, Zuccon, Lucia, Vietri, Pier Giorgio Scotton, Francesca, Andretta, Sandro, Panese, Stefano, Baratti, Renzo, Scaggiante, Francesca, Gatti, Saverio Giuseppe Parisi, Francesco, Castelli, Eugenia, Quiros-Roldan, Melania Degli Antoni, Isabella, Zanella, Matteo Della Monica, Carmelo, Piscopo, Mario, Capasso, Roberta, Russo, Immacolata, Andolfo, Achille, Iolascon, Giuseppe, Fiorentino, Massimo, Carella, Marco, Castori, Filippo, Aucella, Pamela, Raggi, Rita, Perna, Matteo, Bassetti, Antonio Di Biagio, Maurizio, Sanguinetti, Luca, Masucci, Alessandra, Guarnaccia, Serafina, Valente, Oreste De Vivo, Elena, Bargagli, Marco, Mandalà, Alessia, Giorli, Lorenzo, Salerni, Patrizia, Zucchi, Pierpaolo, Parravicini, Elisabetta, Menatti, Tullio, Trotta, Ferdinando, Giannattasio, Gabriella, Coiro, Fabio, Lena, Gianluca, Lacerenza, Domenico, A Coviello, Cristina, Mussini, Enrico, Martinelli, Luisa, Tavecchia, Mary Ann Belli, Lia, Crotti, Gianfranco, Parati, Maurizio, Sanarico, Filippo, Biscarini, Alessandra, Stella, Marco, Rizzi, Franco, Maggiolo, Diego, Ripamonti, Claudia, Suardi, Tiziana, Bachetti, Maria Teresa La Rovere, Simona, Sarzi-Braga, Maurizio, Bussotti, Katia, Capitani, Simona, Dei, Sabrina, Ravaglia, Rosangela, Artuso, Elena, Andreucci, Giulia, Gori, Angelica, Pagliazzi, Erika, Fiorentini, Antonio, Perrella, Francesco, Bianchi, Paola, Bergomi, Emanuele, Catena, Riccardo, Colombo, Sauro, Luchi, Giovanna, Morelli, Paola, Petrocelli, Sarah, Iacopini, Sara, Modica, Silvia, Baroni, Francesco Vladimiro Segala, Francesco, Menichetti, Marco, Falcone, Giusy, Tiseo, Chiara, Barbieri, Tommaso, Matucci, Grassi, Davide, Ferri, Claudio, Marinangeli, Franco, Brancati, Francesco, Antonella, Vincenti, Valentina, Borgo, Lombardi, Stefania, Mirco, Lenzi, Massimo Antonio Di Pietro, Francesca, Vichi, Benedetta, Romanin, Letizia, Attala, Cecilia, Costa, Andrea, Gabbuti, Roberto, Menè, Marta, Colaneri, Patrizia, Casprini, Giuseppe, Merla, Gabriella Maria Squeo, Marcello, Maffezzoni, Stefania, Mantovani, Mario, U Mondelli, Serena, Ludovisi, Onoja, Anthony, Picchiotti, Nicola, Fallerini, Chiara, Baldassarri, Margherita, Fava, Francesca, nbsp, Multicenter Study, GEN-COVID, Colombo, Francesca, Chiaromonte, Francesca, Renieri, Alessandra, Furini, Simone, Raimondi, Francesco, Anthony, O, Nicola, P, Chiara, F, Margherita, B, Francesca, F, Francesca, C, Alessandra, R, Simone, F, Francesco, R, Mari, F, Daga, S, Benetti, E, Bruttini, M, Palmieri, M, Croci, S, Amitrano, S, Meloni, I, Frullanti, E, Doddato, G, Lista, M, Beligni, G, Valentino, F, Zguro, K, Tita, R, Giliberti, A, Antonietta Mencarelli, M, Lo Rizzo, C, Maria Pinto, A, Ariani, F, Di Sarno, L, Montagnani, F, Tumbarello, M, Rancan, I, Fabbiani, M, Rossetti, B, Bergantini, L, D’Alessandro, M, Cameli, P, Bennett, D, Anedda, F, Marcantonio, S, Scolletta, S, Franchi, F, Antonietta Mazzei, M, Guerrini, S, Conticini, E, Cantarini, L, Frediani, B, Tacconi, D, Spertilli Raffaelli, C, Feri, M, Donati, A, Scala, R, Guidelli, L, Spargi, G, Corridi, M, Nencioni, C, Croci, L, Piero Caldarelli, G, Romani, D, Piacentini, P, Bandini, M, Desanctis, E, Cappelli, S, Canaccini, A, Verzuri, A, Anemoli, V, Pisani, M, Ognibene, A, Pancrazzi, A, Lorubbio, M, Vaghi, M, D’Arminio Monforte, A, Gaia Miraglia, F, Bruno, R, Vecchia, M, Girardis, M, Venturelli, S, Busani, S, Cossarizza, A, Antinori, A, Vergori, A, Emiliozzi, A, Rusconi, S, Siano, M, Gabrieli, A, Riva, A, Francisci, D, Schiaroli, E, Paciosi, F, Tommasi, A, Zuccon, U, Vietri, L, Giorgio Scotton, P, Andretta, F, Panese, S, Baratti, S, Scaggiante, R, Gatti, F, Giuseppe Parisi, S, Castelli, F, Quiros-Roldan, E, Degli Antoni, M, Zanella, I, Della Monica, M, Piscopo, C, Capasso, M, Russo, R, Andolfo, I, Iolascon, A, Fiorentino, G, Carella, M, Castori, M, Aucella, F, Raggi, P, Perna, R, Bassetti, M, Di Biagio, A, Sanguinetti, M, Masucci, L, Guarnaccia, A, Valente, S, De Vivo, O, Bargagli, E, Mandalà, M, Giorli, A, Salerni, L, Zucchi, P, Parravicini, P, Menatti, E, Trotta, T, Giannattasio, F, Coiro, G, Lena, F, Lacerenza, G, Coviello, D, Mussini, C, Martinelli, E, Tavecchia, L, Ann Belli, M, Crotti, L, Parati, G, Sanarico, M, Biscarini, F, Stella, A, Rizzi, M, Maggiolo, F, Ripamonti, D, Suardi, C, Bachetti, T, Teresa La Rovere, M, Sarzi-Braga, S, Bussotti, M, Capitani, K, Dei, S, Ravaglia, S, Artuso, R, Andreucci, E, Gori, G, Pagliazzi, A, Fiorentini, E, Perrella, A, Bianchi, F, Bergomi, P, Catena, E, Colombo, R, Luchi, S, Morelli, G, Petrocelli, P, Iacopini, S, Modica, S, Baroni, S, Vladimiro Segala, F, Menichetti, F, Falcone, M, Tiseo, G, Barbieri, C, Matucci, T, Grassi, D, Ferri, C, Marinangeli, F, Brancati, F, Vincenti, A, Borgo, V, Lombardi, S, Lenzi, M, Antonio Di Pietro, M, Vichi, F, Romanin, B, Attala, L, Costa, C, Gabbuti, A, Menè, R, Colaneri, M, Casprini, P, Merla, G, Maria Squeo, G, Maffezzoni, M, Mantovani, S, Mondelli &amp, M, and Ludovisi, S

Subjects
Genetics, Coronavirus disease 2019 (COVID-19), Host (biology), COVID-19, Medicine (miscellaneous), Settore BIO/11 - Biologia Molecolare, Biology, Settore MED/07 - MICROBIOLOGIA E MICROBIOLOGIA CLINICA, Whole Exome Sequencing, General Biochemistry, Genetics and Molecular Biology, machine learning, Phenotype, Exome Sequencing, Humans, Genetic Predisposition to Disease, Genome-Wide Association Study, General Agricultural and Biological Sciences, COVID, Human
Abstract

We 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 training of multiple supervised classifiers, to predict severity on the basis of screened features. Feature importance analysis from tree-based models allowed to identify a handful of 16 variants with 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 good accuracy (ACC=81.88%; ROC_AUC=96%; MCC=61.55%). Principal Component Analysis (PCA) and clustering of patients on important variants orthogonally identified two groups of individuals with a higher fraction of severe cases. 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, such as JAK-STAT, Cytokine, Interleukin, and C-type lectin receptor signaling. It also identified additional processes cross-talking with immune pathways, such as GPCR signalling, 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”, confirming their link with COVID-19 severity outcome. Taken together, our analysis suggests that curated genetic information can be effectively integrated along with other patient clinical covariates to forecast COVID-19 disease severity and dissect the underlying host genetic mechanisms for personalized medicine treatments.

Published
2022
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11. Serum CD59: a novel biomarker of idiopathic pulmonary fibrosis?

Author

Cameli P, Bergantini L, D'Alessandro M, Vietri L, Cameli M, Sestini P, and Bargagli E

Subjects
Adult, Aged, Aged, 80 and over, Biomarkers blood, Case-Control Studies, Female, Humans, Idiopathic Pulmonary Fibrosis blood, Kaplan-Meier Estimate, Male, Middle Aged, Prognosis, Retrospective Studies, Survival, CD59 Antigens blood, Idiopathic Pulmonary Fibrosis diagnosis
Abstract

Background: Idiopathic pulmonary fibrosis (IPF) is the most common among idiopathic interstitial pneumonia. Life expectancy is estimated around 3-5 years at diagnosis. No reliable prognostic biomarker has been approved for routinary clinical practice of IPF. The aim of this study is to investigate the potential prognostic value of serum CD59 in a cohort of IPF patients., Methods: Fifty-seven patients (45 males, 66.1±10 years old) were recruited in Siena Regional Referral Center for Interstitial Lung Disease and underwent serum sampling for CD59 detection during diagnostic pathway. Clinical, functional, radiological and survival data were retrospectively collected. As control group for CD59 values, we recruited eight healthy volunteers (five males, 59.2±18 years old)., Results: CD59 levels were significantly higher in IPF patients in respect with healthy controls (P=0.0238). Patients with CD59 concentrations lower than 15 ng/mL reported a significant reduction of survival time (P=0.009); current or former smokers with CD59 <15 ng/mL showed the worst prognosis (P=0.014)., Conclusions: CD59 levels were significantly increased in IPF patients, supporting the existence of epithelial damage in the pathogenesis of disease. Lower values of CD59 were associated with a significantly worse prognosis, suggesting a potential role of CD59 in the prognostic estimation of IPF patients.

Published
2021
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12. Antithrombin III as predictive indicator of survival in idiopathic pulmonary fibrosis (IPF) patients treated with nintedanib: a preliminary study.

Author

Bergantini L, d'Alessandro M, Cameli P, Carleo A, Landi C, Vietri L, Lanzarone N, Pieroni M, Sestini P, and Bargagli E

Subjects
Humans, Indoles therapeutic use, Proteomics, Antithrombin III, Idiopathic Pulmonary Fibrosis diagnosis, Idiopathic Pulmonary Fibrosis drug therapy
Abstract

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease often managed with nintedanib, a tyrosine kinase inhibitor targeting several profibrotic pathways. Although clotting processes are involved in wound healing and repair in the lung, there are no data on the role of antithrombin III (ATIII) in IPF patients treated with nintedanib. A previous proteomic analysis of serum of IPF patients before and after 1 year of nintedanib treatment showed differential protein expression of ATIII., Aims: Here we used quantitative methods to evaluate differential ATIII concentrations in IPF patients before and after 1 year of nintedanib treatment and to assess the potential of ATIII as a prognostic biomarker in IPF patients., Methods: Serum levels of ATIII were measured by enzyme-linked immunosorbent assay in 14 IPF patients before and after 1 year of nintedanib treatment., Results: A statistically significant inverse correlation was found between serum ATIII concentrations and pulmonary function test parameters in all patients at baseline and follow up. Baseline serum ATIII and bronchoalveolar lavage (BAL) neutrophils proved to be reliable predictors of poor prognosis. A baseline ATIII threshold of 126.5 μg/mL discriminated survivors from non-survivors., Conclusions: After 12 months of antifibrotic treatment, IPF patients with high serum ATIII concentrations and high BAL neutrophil percentages had a poor prognosis and increased survival risk. The results of this preliminary study suggest that ATIII has potential as a biomarker of IPF severity and in predicting response to nintedanib therapy. As a marker, ATIII showed several advantages over BAL neutrophil percentage., (© 2020 Royal Australasian College of Physicians.)

Published
2021
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13. Specificity of serum amyloid A as a biomarker of idiopathic pulmonary fibrosis.

Author

Vietri L, d'Alessandro M, Bergantini L, Carleo A, Cameli P, Mazzei MA, Sestini P, and Bargagli E

Subjects
Biomarkers, Humans, Serum Amyloid A Protein, Idiopathic Pulmonary Fibrosis diagnosis, Lung Diseases, Interstitial
Abstract

Serum amyloid A (SAA) is an apo-lipoprotein produced by the liver in response to proinflammatory cytokines. Few data are available on SAA levels in patients with idiopathic pulmonary fibrosis (IPF), the most common idiopathic form of interstitial pneumonitis (ILD). This study compared SAA concentration in IPF patients to other ILD groups to explore its potential use as a clinical biomarker., (© 2020 Royal Australasian College of Physicians.)

Published
2020
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14. Utility of serological biomarker' panels for diagnostic accuracy of interstitial lung diseases.

Author

Bergantini L, d'Alessandro M, Vietri L, Rana GD, Cameli P, Acerra S, Sestini P, and Bargagli E

Subjects
Adult, Aged, Diagnosis, Differential, Disease Susceptibility, Female, Humans, Male, Middle Aged, ROC Curve, Radiography, Thoracic, Respiratory Function Tests, Serologic Tests, Tomography, X-Ray Computed, Biomarkers blood, Lung Diseases, Interstitial blood, Lung Diseases, Interstitial diagnosis
Abstract

Interstitial lung diseases (ILD) are a heterogeneous group of illnesses of known and unknown aetiology. Differential diagnosis among the three disorders is often challenging. Specific biomarkers with good sensitivity and specificity are therefore needed to predict clinical outcome and guide clinical decisions. The aim of this study was to investigate inflammatory/fibrotic biomarkers, to determine whether single mediators or panels of mediators could be useful to stratify patients into three distinct domains: sarcoidosis, idiopathic pulmonary fibrosis (IPF) and chronic hypersensitivity pneumonitis (cHP). A total of 163 ILD patients monitored at Siena Referral Centre for Sarcoidosis and other Interstitial Lung Diseases were enrolled in the study. Clinical data, pulmonary function tests and biochemical analytes were retrospectively collected. SAA levels were detected by ELISA kit and Krebs von den Lungen 6 (KL-6) were measured by CLEIA method, for sarcoidosis, cHP and IPF patients. Multiple comparison analysis showed significant differences in C reactive protein (CRP), white blood cell count (WBC) and creatinine levels between the three groups. In the logistic regression model, KL-6, CRP and WBC showed areas under curves (AUC) 0.86, for sarcoidosis diagnosis. The logistic regression model KL-6 and SAA showed the best performance with an AUC 0.81 for discriminating IPF than cHP and sarcoidosis. For differential diagnosis of IPF and cHP, KL-6 and SAA were considered in the logistic regression model, showed an AUC 0.79. The combination of serum biomarkers proposed here offers insights into the pathobiology of ILDs. These panels of bioindicators will improve diagnostic accuracy and will be useful in the clinical management of ILDs.

Published
2020
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15. Bronchoalveolar lavage and serum KL-6 concentrations in chronic hypersensitivity pneumonitis: correlations with radiological and immunological features.

Author

Lanzarone N, Gentili F, Alonzi V, Bergantini L, d'Alessandro M, Rottoli P, Refini RM, Pieroni M, Vietri L, Bianchi F, Mazzei MA, Volterrani L, Perrone A, Cameli P, Bargagli E, and Sestini P

Subjects
Aged, Alveolitis, Extrinsic Allergic physiopathology, Biomarkers metabolism, Chronic Disease, Delphi Technique, Female, Humans, Male, Middle Aged, Prognosis, Respiratory Function Tests, Retrospective Studies, Alveolitis, Extrinsic Allergic diagnostic imaging, Alveolitis, Extrinsic Allergic immunology, Bronchoalveolar Lavage Fluid chemistry, Mucin-1 blood, Tomography, X-Ray Computed
Abstract

Chronic hypersensitivity pneumonitis (cHP) is a fibrotic interstitial lung disease (ILD) resulting from inhalation of different organic substances and chemical compounds determining an inflammatory and immunological response in sensitized individuals. KL-6, a human mucin protein expressed by type 2 pneumocytes, has been proposed as a prognostic biomarker of cHP. Assessment of usefulness KL-6 in ILD has been investigated primarily in Asiatic population. The aim of this study was to evaluate clinical utility of KL-6 in serum and bronchoalveolar lavage (BAL). In this study, we retrospectively analysed clinical, radiological and immunological data of a cohort of 42 patients affected by cHP: KL-6 concentrations were collected from serum and BAL. KL-6 clinical value was assessed through the analysis of association between KL-6 concentrations and clinical, functional, immunological and radiological features. KL-6 serum concentration results increased in 28/34 patients (82%). A positive direct correlation was observed between KL-6 concentrations in BAL and serum (r = 0.62, p < 0.05). In our study population we found that patients with extensive presence of ground glass opacities and centrilobular nodules at high-resolution computed tomography (HRCT) showed the highest concentrations of KL-6 in BAL and a predominantly CD3+ CD8+ BAL lymphocytosis. BAL lymphocytosis and KL-6 concentrations showed a direct correlation. BAL KL-6, a result of alveolar damage, caused in cHP by CD3+ CD8+ mediated flogosis and suggested by radiological evidence of ground-glass opacities and centrilobular nodules, can be considered a useful biomarker to assess, along with BAL cellular analysis and HRCT findings, disease activity.

Published
2020
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16. Alveolar nitric oxide is related to periostin levels in idiopathic pulmonary fibrosis.

Author

Cameli P, Bergantini L, D'alessandro M, Vietri L, Refini RM, Pieroni M, Sestini P, and Bargagli E

Subjects
Aged, Biomarkers analysis, Correlation of Data, Female, Humans, Male, Middle Aged, Prognosis, Retrospective Studies, Cell Adhesion Molecules blood, Idiopathic Pulmonary Fibrosis metabolism, Idiopathic Pulmonary Fibrosis mortality, Nitric Oxide analysis, Pulmonary Alveoli chemistry
Abstract

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive diffuse lung disease leading to chronic respiratory failure and death in 3-5 years. Among potential prognostic biomarkers, alveolar nitric oxide (CaNO) and serum periostin showed to predict mortality and disease progression in these patients. The aim of this study is to investigate potential correlations between CaNO and serum periostin and evaluate their prognostic value., Methods: Fifty-nine patients with IPF (47 males, 65.5±9.5 years old) were recruited in Siena Regional Referral Center for Interstitial Lung Disease. In this population, we retrospectively collected multiple-flows exhaled nitric oxide parameters and serum periostin at diagnosis and compared these values with a control group of 60 and 8 healthy volunteers, respectively. Clinical, functional and survival data were collected according to our Center follow-up program., Results: IPF patients reported higher levels of CaNO but not of periostin in respect with healthy controls (P<0.0001 and P=0.1096, respectively). CaNO significantly correlated with periostin levels and TLCO% (P<0.0001 and P=0.0205, respectively). Patients with CaNO>6 ppb showed a worse prognosis, close to statistical significance (P=0.0628). No difference in survival time was found according to periostin levels., Conclusions: CaNO was significantly higher in IPF patients and was related to functional severity of disease. CaNO levels correlated with periostin, suggesting a potential common pathway between the biomarkers.

Published
2020
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17. A case report on expanding horizon of endobronchial ultrasound through esophagus.

Author

Tamburrini M, Thakare P, Zampieri F, Scarda A, Di Paolo A, De Leo G, Gianfagna E, Vietri L, and Zuccon U

Subjects
Aged, Bronchoscopy methods, Carcinoma, Adenosquamous diagnosis, Humans, Lymph Nodes cytology, Lymph Nodes pathology, Lymphadenopathy complications, Lymphadenopathy pathology, Lymphatic Metastasis pathology, Male, Mediastinum pathology, Pleural Effusion diagnosis, Pleural Effusion etiology, Thoracentesis methods, Carcinoma, Adenosquamous secondary, Endoscopic Ultrasound-Guided Fine Needle Aspiration instrumentation, Endosonography methods, Esophagus surgery, Lung Neoplasms pathology
Abstract

Endobronchial ultrasound has revolutionized the field of bronchoscopy and has become one of the most important tools for the diagnosis of intrathoracic lymphadenopathy and para-bronchial structures. The reach of this technique has not been limited to these structures and pleural lesions have been at times accessible. To our knowledge, pleural fluid collections have not been accessed with endobronchial ultrasound (EBUS) through oesophageal approach and rationale behind using this approach. We report a case of 70 years old man who has been referred from physician for the EBUS in view of hilar mass with mediastinal lymphadenopathy with pleural effusion. The endobronchial ultrasound through oesophagus (EUS-B) was done for thoracocentesis and lymph node cytology evaluation and ultimately endobronchial biopsy of hilar mass was done as rapid on-site (ROSE) analysis of lymph node was suggestive of necrotic tissue. The cytology report of lymph node and pleural effusion was positive for malignant cells. The final diagnosis was metastatic poorly differentiating adeno-squamous carcinoma.

Published
2020
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18. Krebs von den Lungen-6 as a biomarker for disease severity assessment in interstitial lung disease: a comprehensive review.

Author

d'Alessandro M, Bergantini L, Cameli P, Vietri L, Lanzarone N, Alonzi V, Pieroni M, M Refini R, Sestini P, Bonella F, and Bargagli E

Subjects
Diagnosis, Differential, Humans, Lung pathology, Lung Diseases, Interstitial diagnosis, Lung Diseases, Interstitial therapy, Predictive Value of Tests, Prognosis, Risk Factors, Biomarkers analysis, Lung metabolism, Lung Diseases, Interstitial metabolism, Mucin-1 analysis, Severity of Illness Index
Abstract

Aim: Interstitial lung diseases (ILD) are a group of lung disorders characterized by interstitial lung thickening. Krebs von den Lungen-6 (KL-6) is a molecule that is predominantly expressed by damaged alveolar type II cells and it has been proposed as a potential biomarker of different ILD. Materials & methods: A growing literature about KL-6 has been reviewed and selected to evaluate its role in the clinical management of ILD to predict disease diagnosis, activity, prognosis and treatment response. Results: KL-6 concentrations have been evaluated in fibrotic and granulomatous lung diseases and it was demonstrated to be a biomarker of disease severity useful for clinical follow-up of ILD patients. KL-6 levels differentiated between fibrotic ILD, such as idiopathic pulmonary fibrosis and chronic hypersensitivity pneumonitis, and nonfibrotic lung disorders, including sarcoidosis and pulmonary alveolar proteinosis. Conclusion: KL-6 is predictive biomarker useful in the clinical management of ILD patients, in particular in patients with severe fibrotic lung disorders.

Published
2020
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19. The effect of cigarette smoking on bronchoalveolar lavage protein profiles from patients with different interstitial lung diseases.

Author

Bargagli E, Cameli P, Carleo A, Refini RM, Bergantini L, D'alessandro M, Vietri L, Perillo F, Volterrani L, Rottoli P, Bini L, and Landi C

Subjects
Biomarkers metabolism, Humans, Lung Diseases, Interstitial diagnosis, Lung Diseases, Interstitial etiology, Non-Smokers, Proteomics, Risk Factors, Smokers, Bronchoalveolar Lavage Fluid chemistry, Cigarette Smoking adverse effects, Lung Diseases, Interstitial metabolism, Proteins metabolism
Abstract

The proteomic approach applied to the analysis of BAL gives a panorama of the complex network of proteins of different origin and function and their modifications at alveolar level. Cigarette smoking may influence BAL protein composition and it represents the most relevant risk factor for several lung diseases. This review, for the first time, discusses the available literature regarding the effects of cigarette smoking on BAL protein composition of healthy subjects and patients affected by interstitial lung diseases (ILD). The comparison of BAL protein profiles of smokers and non-smoker healthy controls revealed alterations of proteins related to oxidative stress and protease/antiprotease imbalance (such as alpha 1 antitrypsin, alpha-1-antichymotrypsin, apolipoprotein A1, peroxiredoxin 1 and glutathione S transferase P). Smoking exposure leads to a significant dysregulation of a large number of molecular pathways involved in interstitial lung diseases and the proteomic studies applied to the study of BAL of idiopathic pulmonary fibrosis, sarcoidosis and other ILD contributed to clarify the underlying pathogenetic mechanisms facilitating ILD development and biomarker discovery.

Published
2020
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20. BAL biomarkers' panel for differential diagnosis of interstitial lung diseases.

Author

d'Alessandro M, Carleo A, Cameli P, Bergantini L, Perrone A, Vietri L, Lanzarone N, Vagaggini C, Sestini P, and Bargagli E

Subjects
Aged, Antigens, CD analysis, CD4-Positive T-Lymphocytes, CD8-Positive T-Lymphocytes, Diagnosis, Differential, Female, Humans, Immunophenotyping, Integrin alpha Chains analysis, Lung Diseases, Interstitial pathology, Male, Middle Aged, Mucin-1 analysis, Neutrophils pathology, Sarcoidosis diagnosis, Biomarkers analysis, Bronchoalveolar Lavage Fluid chemistry, Bronchoalveolar Lavage Fluid cytology, Bronchoalveolar Lavage Fluid immunology, Lung Diseases, Interstitial diagnosis
Abstract

Bronchoalveolar lavage (BAL) is a useful procedure for differential diagnosis of interstitial lung diseases (ILDs) and for identification of granulomatous lung diseases. We investigated a panel of biomarkers from BAL fluid of ILD patients to evaluate their utility in differentiating ILDs. Bronchoscopy with BAL was performed in 100 consecutive patients with suspected ILD (41 sarcoidosis, 11 cHP and 24 other ILDs); the 24 patients negative for ILD diagnosis were included as control group. BAL phenotypes and cell profiles (CD4 + /CD8 + ratio, NK and CD103 + cell counts, chitotriosidase and KL-6 levels in BAL) were determined by flow cytometry. A decision-tree statistical algorithm was applied. Sarcoidosis was discriminated by a higher BAL CD4 + /CD8 + ratio (p = 5.8E-05), a lower BAL CD103 + CD4 + count (p = 5.0E-02) and lower BAL NK percentages (p = 8.8E-03) than the other groups. BAL KL-6 concentrations were higher in sarcoidosis than in other ILDs (p = 1.5E-02) and were directly correlated with CD4 + /CD8 + ratio. We used decision-tree statistical analysis to combine our biomarkers into two diagnostic algorithms for differential diagnosis of ILDs. A panel of BAL biomarkers for diagnosis of ILDs is proposed; CD4 + /CD8 + ratio, KL-6 concentrations, and NK and CD103 + CD4 + cell percentages in BAL could improve the identification and differential diagnosis of sarcoidosis.

Published
2020
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22. Serum Amyloid A in lung transplantation.

Author

Vietri L, Bargagli E, Bennett D, Fossi A, Cameli P, Bergantini L, d'Alessandro M, Paladini P, Luzzi L, Gentili F, Mazzei MA, Spina D, Sestini P, and Rottoli P

Subjects
Acute Disease, Adult, Aged, Biomarkers blood, Bronchiolitis Obliterans diagnosis, Bronchiolitis Obliterans immunology, Case-Control Studies, Female, Graft Rejection diagnosis, Graft Rejection immunology, Humans, Immunocompromised Host, Male, Middle Aged, Opportunistic Infections diagnosis, Opportunistic Infections immunology, Treatment Outcome, Bronchiolitis Obliterans blood, Graft Rejection blood, Lung Transplantation adverse effects, Opportunistic Infections blood, Serum Amyloid A Protein metabolism
Abstract

Background: Serum Amyloid A (SAA) is an acute phase protein and we analyzed its concentrations in lung transplantated patients (LTX)., Methods: 26 LTX patients (58.6 ± 11 years) and 11 healthy controls (55 ± 11.3 years). Three groups of LTX patients: acute rejection (AR, 7) bronchiolitis obliterans syndrome (BOS, 3), acute infection (INF, 9) and stable patients (NEG, 7)., Results: In LTX patients SAA concentrations were significantly increased, particularly in AR and INF. In LTX-AR patients were observed a correlation between SAA levels and peripheral CD4+ lymphocyte percentage (r=0.9, p<0.01) and a reverse correlation with FVC percentages (r -0.94, p=0.01)., Conclusions: SAA may represent a potential biomarker of LTX acute complications, with a prognostic value in AR. (Sarcoidosis Vasc Diffuse Lung Dis 2020; 37 (1): 2-7) ., (Copyright: © 2020 SARCOIDOSIS VASCULITIS AND DIFFUSE LUNG DISEASES.)

Published
2020
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23. Serum amyloid A: A potential biomarker of lung disorders.

Author

Vietri L, Fui A, Bergantini L, d'Alessandro M, Cameli P, Sestini P, Rottoli P, and Bargagli E

Subjects
Biomarkers blood, Humans, Amyloid blood, Lung Diseases diagnosis
Abstract

Serum amyloid A is an acute-phase protein with multiple immunological functions. Serum amyloid A is involved in lipid metabolism, inflammatory reactions, granuloma formation, and cancerogenesis. Additionally, serum amyloid A is involved in the pathogenesis of different autoimmune lung diseases. The levels of serum amyloid A has been evaluated in biological fluids of patients with different lung diseases, including autoimmune disorders, chronic obstructive pulmonary diseases, obstructive sleep apnea syndrome, sarcoidosis, asthma, lung cancer, and other lung disorders, such as idiopathic pulmonary fibrosis, tuberculosis, radiation pneumonitis, and cystic fibrosis. This review focuses on the cellular and molecular interactions of serum amyloid A in different lung diseases and suggests this acute-phase protein as a prognostic marker., (Copyright © 2019 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.)

Published
2020
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24. Pirfenidone in idiopathic pulmonary fibrosis: real-life experience in the referral centre of Siena.

Author

Vietri L, Cameli P, Perruzza M, Cekorja B, Bergantini L, d'Alessandro M, Refini RM, Pieroni M, Fossi A, Bennett D, Spalletti M, Mazzei MA, Sestini P, Rottoli P, and Bargagli E

Subjects
Aged, Disease Progression, Female, Humans, Idiopathic Pulmonary Fibrosis diagnosis, Idiopathic Pulmonary Fibrosis mortality, Idiopathic Pulmonary Fibrosis physiopathology, Italy, Lung pathology, Lung physiopathology, Male, Middle Aged, Pyridones adverse effects, Recovery of Function, Retrospective Studies, Time Factors, Treatment Outcome, Vital Capacity, Idiopathic Pulmonary Fibrosis drug therapy, Lung drug effects, Pyridones therapeutic use
Abstract

Background: Idiopathic pulmonary fibrosis (IPF) is the most common idiopathic interstitial pneumonia and has a median survival after diagnosis of 2-5 years. Pirfenidone is the first approved antifibrotic drug for the treatment of IPF. Here we report the functional progress, side effects and survival data of a population of patients with IPF, diagnosed at our centre and treated with pirfenidone., Methods: We enrolled 91 patients with IPF (71 males) treated with pirfenidone. Clinical, survival and functional details were collected retrospectively at start of therapy and after 12, 24, 36 and 48 months of treatment. Lung function tests at least 12 months before starting therapy were available for 40 patients and were entered in the database, as well as side effects., Results: During the observation period (922 ± 529 days), 27 patients died, 5 patients underwent lung transplant and 10 patients interrupted therapy due to adverse events or IPF progression. The median survival was 1606 days. There was a significant reduction in disease progression rate, as measured by trend of forced vital capacity, after 1 year of therapy with respect to before treatment ( p  = 0.0085). Forced vital capacity reduction rate was progressively higher in the subsequent years of treatment. Treatment-related side effects were reported in 25 patients and were predominantly mild. Overall, four patients discontinued therapy due to severe photosensitivity., Conclusions: Our findings confirm the efficacy of pirfenidone in reducing functional progression of IPF and its excellent safety profile in a real-life setting. This study, designed on a long-term follow up, contributes to the growing evidence on safety, tolerability and efficacy of pirfenidone in IPF. The reviews of this paper are available via the supplemental material section.

Published
2020
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25. Serum amyloid A in patients with idiopathic pulmonary fibrosis.

Author

Vietri L, Bennett D, Cameli P, Bergantini L, Cillis G, Sestini P, Bargagli E, and Rottoli P

Subjects
Adult, Aged, Biomarkers blood, Enzyme-Linked Immunosorbent Assay, Female, Humans, Idiopathic Pulmonary Fibrosis metabolism, Idiopathic Pulmonary Fibrosis physiopathology, Lipid Metabolism, Male, Middle Aged, Predictive Value of Tests, Severity of Illness Index, Vital Capacity, Idiopathic Pulmonary Fibrosis diagnosis, Serum Amyloid A Protein analysis, Serum Amyloid A Protein metabolism
Abstract

Background: Serum amyloid A (SAA) is an apo-lipoprotein (12-14 kDa) produced by the liver in response to proinflammatory cytokines from activated monocytes. The precursor of SAA is an acute-phase protein involved in the pathogenesis of sarcoidosis and has been found to be increased during exacerbation of chronic obstructive pulmonary disease and lung cancer. However, no data are available on SAA levels in patients with idiopathic pulmonary fibrosis (IPF), the most common and severe idiopathic form of interstitial pneumonitis associated with a usual interstitial histological and radiological pattern. The aim of this preliminary study was to evaluate SAA concentration in patients with IPF and to explore its potential use as a clinical biomarker., Methods: SAA levels were determined by enzyme-linked immunosorbent assay in a population of 21 patients with IPF (14 male, aged 64.8 ± 8.1 years) and compared with those in 11 healthy controls (3 male, aged 55 ± 11.3 years). Clinical, functional, and immunological data were collected in a database., Results: SAA levels were significantly higher in patients with IPF than in controls (p = 0.03). In patients with IPF, statistically significant correlations were found between SAA and HDL cholesterol levels (r = -0.62, p = 0.05) and FVC % predicted value (r = -0.52, p = 0.01)., Conclusions: SAA is a promising marker of disease severity in patients with IPF. Our preliminary data suggest a potential pathogenetic role of alteration in lipid metabolism in this rare disease., (Copyright © 2019 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.)

Published
2019
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26. Serial KL-6 analysis in patients with idiopathic pulmonary fibrosis treated with nintedanib.

Author

Bergantini L, Bargagli E, Cameli P, Cekorja B, Lanzarone N, Pianigiani L, Vietri L, Bennett D, Sestini P, and Rottoli P

Subjects
Aged, Aged, 80 and over, Biomarkers blood, Female, Humans, Idiopathic Pulmonary Fibrosis physiopathology, Male, Prognosis, Vital Capacity, Idiopathic Pulmonary Fibrosis diagnosis, Idiopathic Pulmonary Fibrosis drug therapy, Indoles therapeutic use, Mucin-1 blood
Published
2019
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27. The pathogenetic mechanisms of cough in idiopathic pulmonary fibrosis.

Author

Bargagli E, Di Masi M, Perruzza M, Vietri L, Bergantini L, Torricelli E, Biadene G, Fontana G, and Lavorini F

Subjects
Comorbidity, Cough genetics, Humans, Idiopathic Pulmonary Fibrosis genetics, Prognosis, Risk Factors, Cough physiopathology, Idiopathic Pulmonary Fibrosis physiopathology
Abstract

Idiopathic pulmonary fibrosis is a peripheral subpleural interstitial lung disorder limited to the lung not involving the airways. It has a poor prognosis (survival less than 5 years) and commonly an interstitial pneumonia radiological pattern. Patients complain of a chronic dry cough in 80% of cases. A cough is often the first symptom of this rare disease, preceding dyspnea by years, and is associated with a poor prognosis, high dyspnea scores and low FVC percentages. The pathogenetic mechanisms leading to coughing in IPF are unclear. This review focuses on recent evidence of cough pathophysiology in this disease. Gastroesophageal reflux may promote coughing in IPF patients; bile salts and pepsin may be abundant in BAL of these patients, inducing overproduction of TGF-β by airway epithelial cells and mesenchymal transition with fibroblast recruitment/activation and extracellular matrix deposition. Patients have an enhanced cough reflex to capsaicin and substance P with respect to control subjects. Moreover, patients with the MUC5B polymorphism show more severe coughing as MUC5B encodes for the dominant mucin in the honeycomb cysts of IPF patients. Comorbidities, including asthma, gastroesophageal reflux, hypersensitivity pneumonitis, bronchiectasis, chronic obstructive pulmonary disease and emphysema, can induce coughing in IPF patients. There is no clear explanation of the causes of coughing in IPF. Further research into the pathophysiology of IPF and the pathogenetic mechanisms of coughing is necessary to improve survival and quality of life.

Published
2019
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