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1. Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

Author

Gabriele Martelloni, Alessio Turchi, Chiara Fallerini, Andrea Degl’Innocenti, Margherita Baldassarri, Simona Olmi, Simone Furini, Alessandra Renieri, GEN-COVID Multicenter study, Francesca Mari, Sergio Daga, Ilaria Meloni, Mirella Bruttini, Susanna Croci, Mirjam Lista, Debora Maffeo, Elena Pasquinelli, Giulia Brunelli, Kristina Zguro, Viola Bianca Serio, Enrica Antolini, Simona Letizia Basso, Samantha Minetto, Giulia Rollo, Martina Rozza, Angela Rina, Rossella Tita, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Francesca Ariani, Francesca Montagnani, Mario Tumbarello, Ilaria Rancan, Massimiliano Fabbiani, Elena Bargagli, 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, Arianna Emiliozzi, 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, Maria Lorubbio, Alessandro Pancrazzi, Massimo Vaghi, Antonella D’Arminio Monforte, Federica Gaia Miraglia, Mario U. Mondelli, Stefania Mantovani, Raffaele Bruno, Marco Vecchia, Marcello Maffezzoni, Enrico Martinelli, Massimo Girardis, Stefano Busani, Sophie Venturelli, Andrea Cossarizza, Andrea Antinori, Alessandra Vergori, Stefano Rusconi, Matteo Siano, Arianna Gabrieli, Agostino Riva, Daniela Francisci, Elisabetta Schiaroli, Carlo Pallotto, Saverio Giuseppe Parisi, Monica Basso, Sandro Panese, Stefano Baratti, Pier Giorgio Scotton, Francesca Andretta, Mario Giobbia, Renzo Scaggiante, Francesca Gatti, 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, Giuseppe Merla, Gabriella Maria Squeo, Filippo Aucella, Pamela Raggi, Rita Perna, Matteo Bassetti, Antonio Di Biagio, Maurizio Sanguinetti, Luca Masucci, Alessandra Guarnaccia, Serafina Valente, Alex Di Florio, Marco Mandalà, Alessia Giorli, Lorenzo Salerni, Patrizia Zucchi, Pierpaolo Parravicini, Elisabetta Menatti, Tullio Trotta, Ferdinando Giannattasio, Gabriella Coiro, Fabio Lena, Gianluca Lacerenza, Cristina Mussini, Luisa Tavecchia, Lia Crotti, Gianfranco Parati, Roberto Menè, Maurizio Sanarico, Marco Gori, Francesco Raimondi, Alessandra Stella, Filippo Biscarini, Tiziana Bachetti, Maria Teresa La Rovere, Maurizio Bussotti, Serena Ludovisi, Katia Capitani, Simona Dei, Sabrina Ravaglia, Annarita Giliberti, Giulia Gori, Rosangela Artuso, Elena Andreucci, 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, Giulia Micheli, Marco Falcone, Donato Urso, Giusy Tiseo, 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, Alessio Bellucci, Marta Colaneri, Patrizia Casprini, Cristoforo Pomara, Massimiliano Esposito, Roberto Leoncini, Michele Cirianni, Lucrezia Galasso, Marco Antonio Bellini, Chiara Gabbi, and Nicola Picchiotti

Subjects
COVID-19, host genetics, integrated polygenic score, genetic algorithm, logistic regression, genetic science modeling, Genetics, QH426-470
Abstract

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147–173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity.. IPGS leads to an accuracy of 55%–60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into “Boolean quantum features,” inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores (IPGSph1 and IPGSph2). By applying a logistic regression with both IPGS, (IPGSph2 (or indifferently IPGSph1) and age as inputs, we reached an accuracy of 84%–86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147–173) by a factor of 10%.

Published
2024
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2. Performance evaluation of four surrogate Virus Neutralization Tests (sVNTs) in comparison to the in vivo gold standard test

Author

Massimo Pieri, Maria Infantino, Mariangela Manfredi, Marzia Nuccetelli, Valentina Grossi, Barbara Lari, Flaminia Tomassetti, Serena Sarubbi, Edda Russo, Amedeo Amedei, Maurizio Benucci, Patrizia Casprini, Lorenzo Stacchini, Concetta Castilletti, and Sergio Bernardini

Subjects
surrogate virus neutralization tests, live virus neutralization test, anti-sars-cov-2 antibodies, immunoassays, Biochemistry, QD415-436, Biology (General), QH301-705.5
Abstract

Background: Several commercial surrogate Virus Neutralization Tests (sVNTs) have been developed in the last year. Neutralizing anti-SARS-CoV-2 antibodies through interaction with Spike protein Receptor Binding Domain (S-RBD) can block the virus from entering and infecting host cells. However, there is a lack of information about the functional activity of SARS-CoV-2 antibodies that may be associated with protective responses. For these reasons, to counteract viral infection, the conventional virus neutralization test (VNT) is still considered the gold standard. The aim of this study was to contribute more and detailed information about sVNTs’ performance, by determining in vitro the anti-SARS-CoV-2 neutralizing antibody concentration using four different commercial assays and then comparing the obtained data to VNT. Methods: Eighty-eight samples were tested using two chemiluminescence assays (Snibe and Mindray) and two ELISA assays (Euroimmun and Diesse). The antibody titers were subsequently detected and quantified by VNT. Results: The overall agreement between each sVNT and VNT was 95.45% for Euroimmun and 98.86% for Diesse, Mindray and Snibe. Additionally, we investigated whether the sVNTs were closer to the gold standard than traditional anti-SARS-CoV-2 antibody assays S-RBD or S1 based, finding a higher agreement mean value for sVNTs (98.01 ± 1.705% vs 95.45 ± 1.921%; p < 0.05). Furthermore, Spearman’s statistical analysis for the correlation of sVNT versus VNT showed r = 0.666 for Mindray; r = 0.696 for Diesse; r = 0.779 for Mindray and r = 0.810 for Euroimmun. Conclusions: Our data revealed a good agreement between VNT and sVNTs. Despite the VNT still remains the gold standard, the sVNT might be a valuable tool for screening wider populations.

Published
2022
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3. Prevalence of Ureaplasma parvum in the area of Prato, Italy

Author

Tamara Brunelli, Antonella Conti, Patrizia Miglietta, Elisa Rovinati, Daniele Ferri, Patrizia Casprini, and Roberto Degl'Innocenti

Subjects
Urogenital, ureaplasma, infection, prevalence, Microbiology, QR1-502
Abstract

In this study, the prevalence of Ureaplasma parvum in the area of Prato (Italy) was investigated. Samples from 1197 consecutive patients were analyzed. Our results showed that the prevalence of U. parvum was 33.6%, with a higher percentage in females than in males (40.6% vs 9%). In addition, the prevalence of U. parvum was significantly lower in older patients.

Published
2015
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4. Use of XpertMTB/RIF for Mycobacterium tuberculosis identification

Author

Roberto Deg'Innocenti, Tamara Brunelli, Lorenzo Pellegrini, Daniele ferri, Elisa Rovinati, Alfredo Ruggeri, Antonella Conti, and Patrizia Casprini

Subjects
PCR, Mycobacterium tuberculosis, Xpert, Microbiology, QR1-502
Abstract

In this study we describe the use of Xpert MTB/RIF to give a rapid answer in case of strong clinical suspicion of tuberculosis and/or positive microscopy slide, from sample or culture, for auramine-rhodamine stain.

Published
2014
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5. Screening for Klebsiella pneumoniae producing carbapenemase in Prato, Italy

Author

Tamara Brunelli, Antonella Conti, Loredana Ortega De Luna, Patrizia Miglietta, Mayra Sosa, Alfredo Ruggeri, Patrizia Casprini, and Roberto Degl'Innocenti

Subjects
Klebsiella pneumoniae, Carbapenemase, KPC, Microbiology, QR1-502
Abstract

In this study, the prevalence of carbapenemase in the area of Prato (Italy), from January 2011 to August 2013, is reported. Samples showing carbapenem resistance were tested for lactamase production with disc diffusion and molecular methods. Totally, 48 out of 1542 patients with K. pneumoniae showed carbapenem resistance (42 KPC 5 MBL and 1 OXA-48).

Published
2014
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6. Usefulness of MALDI-TOF mass spectrometry in epidemiological control of etiologic agents of infection

Author

Roberto Degl’Innocenti, Tamara Brunelli, Lorenzo Pellegrini, Daniele Ferri, Elisa Rovinati, Michele Rispoli, Antonella Conti, and Patrizia Casprini

Subjects
mass-spectrometry, epidemiology, Staphylococcus epidermidis, Staphylococcus aureus, Microbiology, QR1-502
Abstract

Introduction: The use of the MALDI-TOF mass spectrometry in the routine of microbiological diagnostics has revolutionized procedures and response times of bacteriology.The use of this technique aims to epidemiological investigations in a hospital environment and represents a further significant opportunity, quickly feasible and extremely economical. Methods: By means of the MALDI-TOF-MS Vitek2 (MS Vitek2) mass spectrometer, accompanied by the AgnosTec-SARAMIS (bioMérieux, France) software, were analyzed the spectra of 149 bacterial isolates (139 Staphylococcus aureus and 10 Staphylococcus epidermidis) obtained from cultures of 148 patients (141 inpatients and 7 outpatients). Clinical isolates were stored at a temperature of -20°C.The isolates were then thawed and immediately cultured on agar blood medium. The colonies were subjected to analysis by MS Vitek on the day after sowing. The spectra obtained were analyzed and compared using the software AgnosTec-SARAMIS, which allowed the construction of a dendrogram. Results and conclusions: The evaluation of the data collected suggests that mass spectrometry could be an useful tool in epidemiological surveys. Speed of analysis and low costs make the MS Vitek2 an usable tool by many microbiology laboratories.

Published
2013
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7. MALDI-TOF mass spectrometry for the rapid identification of aetiological agents of sepsis

Author

Roberto Degl’Innocenti, Tamara Brunelli, Loredana Ortega De Luna, Patrizia Miglietta, Mayra Sosa, Antonella Conti, and Patrizia Casprini

Subjects
Sepsis, Mass-spectrometry, Blood cultures identification, Microbiology, QR1-502
Abstract

Introduction: The MALDI-TOF has recently become part of the methods of microbiological investigation in many laboratories of bacteriology with advantages both practical and economical.The use of this technique for the rapid identification of the causative agents of sepsis is of strategic importance to the ability to provide the clinician with useful information for a prompt and rapid establishment of an empirical antimicrobial “targeted” therapy. Methods: It was tested a total of 343 positive blood culture bottles from 211 patients. The samples after collection were incubated in the BACTEC FX (Becton Dickinson, USA). From these bottles were taken a few milliliters of broth culture and transferred into a vacutainer tube containing gel. This was centrifuged, the supernatant was decanted, and finally recovered the bacterial suspension on the gel. With micro-organisms recovered in this way, after several washes with distilled water, was prepared a slide for microscopic examination with Gram stain, and a plate for mass spectrometry (MS-Vitek, bioMérieux, France).Then, the same samples were inoculated on solid agar media according to the protocol in use in our laboratory.The next day was checked the possible bacterial growth on solid media; we then proceeded to the identification of the colonies by Vitek MS and / or with the system Vitek2 (bioMérieux, France). Results: 258 (75.2%) positive vials show concordant results between direct identification and identification after growth on agar. For 83 (24.2%) positive bottles there has been full compliance with the microscopic examination but not with culture. In particular, two bottles (0.6%) have given complete discordance between the direct identification and that after growth. Conclusions: The protocol we use for the direct identification of organisms responsible for sepsis, directly on positive bottles, seems to be a quick and inexpensive procedure, which in less than 60 minutes can give valuable feedback to the clinician.

Published
2013
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8. Prevalence of Clostridium difficile infections in Prato hospital in the years 2010-2011

Author

Tamara Brunelli, Antonella Conti, Loredana Ortega De Luna, Patrizia Miglietta, Mayra Sosa, Alfredo Ruggeri, Patrizia Casprini, and Roberto Degl’Innocenti

Subjects
Clostridium difficile, Infection, Prevalence, Microbiology, QR1-502
Abstract

Clostridium difficile, a Gram positive, spore-forming, anaerobic bacillus, is an important nosocomial enteric pathogen causing diarrhoea and pseudomembranous colitis. Aim of this study was to evaluate the prevalence of Clostridium difficile in Prato Hospital. Stool samples were collected from 1197 patients hospitalized from January 2010 to December 2011. In all the samples the common antigen GDH was investigated and only in samples positive for the antigen the presence of the A and B toxins was investigated. Our results showed that 170/1197 samples (14%) were positive for the antigen, and of these 170 patients, 84 (49%) were found positive also for the toxins. In addition the percentage of samples positive for toxins was higher in 2010 (8.6%) than in 2011 (5.9%).

Published
2013
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9. Detection of T. vaginalis,M. hominis,M. genitalium, C. trachomatis, N. gonorrhoeae and U. urealyticum using Multiplex PCR

Author

Tamara Brunelli, Roberto Degl’Innocenti, Patrizia Miglietta, Loredana Ortega De Luna, Elisa Rovinati, Stefania Apolito, Antonella Conti, and Patrizia Casprini

Subjects
multiplex PCR, pathogens, sexually transmitted diseases, Microbiology, QR1-502
Abstract

Intoduction. The sexually transmitted diseases include a large group of infections affecting both the sexes. In this study we evaluated the prevalence of Trichomonas vaginalis, Mycoplasma hominis, Mycoplasma genitalium, Chlamydia trachomatis, Neisseria gonorrhoeae and Ureaplasma urealyticum in the Prato area during the period September 2010 – July 2011. Methods.We analysed different kind of samples (urine, endocervical swabs, urethral swabs, seminal fluids) from hospitalized patients or referred to the Prato clinic subjects.The DNA was obtained using EZ1-DNA extraction kit and EZ1 instrument.The DNA was then amplified using the Seeplex STD6 kit (Seegene, Korea), identifying multiple pathogens simultaneously (T. vaginalis, M. hominis, M. genitalium, C. trachomatis, N. gonorrhoeae e U. urealyticum). The revelation was performed by electrophoresis on microchip (instrument Multina, Shimadzu, Japan). Results. 1136 samples from Italian and foreign patients were examined: 876 were endocervical swabs (77%), 103 urethral swabs (9%), 103 seminal fluids (9%), and 54 urines (5%). The number of females was higher than males [894 (78.7%) vs 242 (21.3%)]; the mean age of females was 37.0±11.6 years, whereas that of males was 41.5 ±12.63 years.The prevalence of urogenital pathogens was: 15 positive samples for T. vaginalis (1.3%), 56 for M. hominis (4.9%), 13 for M. genitalium (1.1%), 28 for C. trachomatis (2.5%), 8 for N. gonorrhoeae (0.7%) and 87 for U. urealyticum (7.7%).Among all positive, 25 subjects were positive for more than one pathogen and in particular: one was positive for the presence of 4 pathogens, five presented 3 pathogens simultaneously and the remaining nineteen for 2 pathogens. Conclusions. This study provides data on the prevalence of sexually transmitted diseases in the hospital of Prato.

Published
2013
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10. Use of Maldi-Tof Mass spectrometry in direct microorganism identification in clinical laboratories

Author

Tamara Brunelli, Roberto Degl’Innocenti, Antonella Conti, and Patrizia Casprini

Subjects
MALDI-TOF, spectrometry, identification, microorganism, bacteria, Microbiology, QR1-502
Abstract

Mass Spectrometry is an old technique that has recently been introduced in the clinical microbiology laboratory as Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS). MALDI is a soft ionization technique used in mass spectrometry that allows the analysis of biomolecules and large organic molecules which tend to be fragile and fragment when ionized.To obtain ions biological specimens are mixed with a matrix which specifically absorbs the ionization source (a laser beam). The high energy impact is followed by the formation of ions which are extract through an elastic field, focussed and detected as mass/charge (m/z) spectrum.The differences between ions are seen with TOF, a revelation system that relates the time of flight of a ion to the charge/mass value: ion with a higher m/z have are slower (a bigger time of flight) than ions with lower m/z. MALDI-TOF MS, in clinical microbiology laboratory, is used to identify bacteria and fungi directly from samples. The identification of microorganisms can be performed directly from body fluids (e.g. urine, blood culture, after centrifugation and recovery of microorganisms) or from colonies (after cultivation). The rapidity of identification is of great importance in blood cultures. Positive cultures with one microorganism are processed in a different way than those with more than one microorganism. In positive monomicrobial cultures, after separation of microbs from blood cells,we can perform an immediate identification with MALDI-TOF MS that we can communicate to the clinician, and that gives indication to perform the correct antibiogram. Major problems are present when more than one microorganism are in the culture: in this case we have to use the method of subcultivation and then the identification with mass-spectrometry can be performed. MALDI-TOF MS is a rapid, reliable and low cost technique, that can identify a growing number of microorganisms. This technique can significantly reduce the time to give an identification, that is of great importance, particularly in blood culture, where the success of therapy is strictly linked to its early beginning.

Published
2010
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11. The role of neutralizing antibodies by sVNT after two doses of BNT162b2 mRNA vaccine in a cohort of Italian healthcare workers

Author

Maria Infantino, Mariangela Manfredi, Lorenzo Stacchini, Claudia Cosma, Valentina Grossi, Barbara Lari, Edda Russo, Amedeo Amedei, Maurizio Benucci, Francesca Veneziani, Patrizia Casprini, Cateno Mario Catalano, Giuseppe Cirrincione, Guglielmo Bonaccorsi, and Adolfo Pompetti

Subjects
Vaccines, Synthetic, COVID-19 Vaccines, SARS-CoV-2, Health Personnel, Biochemistry (medical), Clinical Biochemistry, COVID-19, General Medicine, Antibodies, Viral, Antibodies, Neutralizing, anti-SARS-CoV-2 antibodies, antibody kinetics, health care workers, immune response, neutralizing antibodies, surrogate virus neutralization test, vaccine, Immunoglobulin G, Humans, Serologic Tests, mRNA Vaccines, BNT162 Vaccine
Abstract

Objectives Evaluating anti-SARS-CoV-2 antibody levels is a current priority to drive immunization, as well as to predict when a vaccine booster dose may be required and for which priority groups. The aim of our study was to investigate the kinetics of anti-SARS-CoV-2 Spike S1 protein IgG (anti-S1 IgG) antibodies and neutralizing antibodies (NAbs) in an Italian cohort of healthcare workers (HCWs), following the Pfizer/BNT162b2 mRNA vaccine, over a period of up to six months after the second dose. Methods We enrolled 57 HCWs, without clinical history of COVID-19 infection. Fluoroenzyme-immunoassay was used for the quantitative anti-S1 IgG antibodies at different time points T1 (one month), T3 (three months) and T6 (six months) following the second vaccine shot. Simultaneously, a commercial surrogate virus neutralization test (sVNT) was used for the determination of NAbs, expressed as inhibition percentage (% IH). Results Median values of anti-S1 IgG antibodies decreased from T1 (1,452 BAU/mL) to T6 (104 BAU/mL) with a percent variation of 92.8% while the sVNT showed a percent variation of 34.3% for the same time frame. The decline in anti-S1 IgG antibodies from T1 to T6 was not accompanied by a loss of the neutralizing capacity of antibodies. In fact at T6 a neutralization percentage Conclusions Our findings reveal that the decrease of anti-S1 IgG levels do not correspond in parallel to a decrease of NAbs over time, which highlights the necessity of using both assays to assess vaccination effectiveness.

Published
2022
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12. Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder

Author

Bergantini, Laura, Baldassarri, Margherita, D'Alessandro, Miriana, Brunelli, Giulia, Fabbri, Gaia, Zguro, Kristina, Degl'Innocenti, Andrea, Fallerini, Chiara, Bargagli, Elena, Renieri, Alessandra GEN-COVID Multicenter study: Francesca Mari, Sergio, Daga, Ilaria, Meloni, Mirella, Bruttini, Susanna, Croci, Mirjam, Lista, Debora, Maffeo, Elena, Pasquinelli, Viola Bianca Serio, Enrica, Antolini, Simona Letizia Basso, Samantha, Minetto, Rossella, Tita, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Francesca, Ariani, Francesca, Montagnani, Mario, Tumbarello, Ilaria, Rancan, Massimiliano, Fabbiani, 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, Arianna, Emiliozzi, 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, Maria, Lorubbio, Alessandro, Pancrazzi, Massimo, Vaghi, Antonella, D 'Arminio Monforte, Federica Gaia Miraglia, Mario, U Mondelli, Stefania, Mantovani, Raffaele, Bruno, Marco, Vecchia, Marcello, Maffezzoni, Enrico, Martinelli, Massimo, Girardis, Stefano, Busani, Sophie, Venturelli, Andrea, Cossarizza, Andrea, Antinori, Alessandra, Vergori, Stefano, Rusconi, Matteo, Siano, Arianna, Gabrieli, Agostino, Riva, Daniela, Francisci, Elisabetta, Schiaroli, Carlo, Pallotto, Saverio Giuseppe Parisi, Monica, Basso, Sandro, Panese, Stefano, Baratti, Pier Giorgio Scotton, Francesca, Andretta, Mario, Giobbia, Renzo, Scaggiante, Francesca, Gatti, 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, Giuseppe, Merla, Gabriella Maria Squeo, Filippo, Aucella, Pamela, Raggi, Rita, Perna, Matteo, Bassetti, Antonio Di Biagio, Maurizio, Sanguinetti, Luca, Masucci, Alessandra, Guarnaccia, Serafina, Valente, Alex Di Florio, Marco, Mandalà, Alessia, Giorli, Lorenzo, Salerni, Patrizia, Zucchi, Pierpaolo, Parravicini, Elisabetta, Menatti, Tullio, Trotta, Ferdinando, Giannattasio, Gabriella, Coiro, Fabio, Lena, Gianluca, Lacerenza, Cristina, Mussini, Luisa, Tavecchia, Lia, Crotti, Gianfranco, Parati, Roberto, Menè, Maurizio, Sanarico, Marco, Gori, Francesco, Raimondi, Alessandra, Stella, Filippo, Biscarini, Tiziana, Bachetti, Maria Teresa La Rovere, Maurizio, Bussotti, Serena, Ludovisi, Katia, Capitani, Simona, Dei, Sabrina, Ravaglia, Annarita, Giliberti, Giulia, Gori, Rosangela, Artuso, Elena, Andreucci, 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, Micheli, Giulia, Marco, Falcone, Donato, Urso, Giusy, Tiseo, 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, Alessio, Bellucci, Marta, Colaneri, Patrizia, Casprini, Cristoforo, Pomara, Massimiliano, Esposito, Roberto, Leoncini, Michele, Cirianni, Lucrezia, Galasso, Marco Antonio Bellini, Chiara, Gabbi, Nicola, Picchiotti, and Simone, Furini

Subjects
COVID-19, Long COVID, Pulmonary fibrosis, RTEL1
Published
2023

13. Carriers of ADAMTS13 Rare Variants Are at High Risk of Life-Threatening COVID-19

Author

Zguro, Kristina, Baldassarri, Margherita, Fava, Francesca, Beligni, Giada, Daga, Sergio, Leoncini, Roberto, Galasso, Lucrezia, Cirianni, Michele, Rusconi, Stefano, Siano, Matteo, Francisci, Daniela, Schiaroli, Elisabetta, Luchi, Sauro, Morelli, Giovanna, Martinelli, Enrico, Girardis, Massimo, Busani, Stefano, Parisi, Saverio Giuseppe, Panese, Sandro, Piscopo, Carmelo, Capasso, Mario, Tacconi, Danilo, Spertilli Raffaelli, Chiara, Giliberti, Annarita, Gori, Giulia, Katsikis, Peter D, Lorubbio, Maria, Calzoni, Paola, Ognibene, Agostino, Bocchia, Monica, Tozzi, Monica, Bucalossi, Alessandro, Marotta, Giuseppe, Furini, Simone, Gen-Covid Multicenter Study, Null, Renieri, Alessandra, Fallerini, Chiara, GEN-COVID Multicenter Study, Mari, Francesca, Bruttini, Mirella, Meloni, Ilaria, Croci, Susanna, Gabriella, Doddato, Serio, VIOLA BIANCA, Mirjam, Lista, Maffeo, Debora, Pasquinelli, Elena, Ludovica, Mercuri, Brunelli, Giulia, Rossella, Tita, Maria Antonietta Mencarelli, LO RIZZO, Caterina, Pinto, ANNA MARIA, Ariani, Francesca, Montagnani, Francesca, Tumbarello, Mario, Ilaria, Rancan, Massimiliano, Fabbiani, Bargagli, Elena, Bergantini, Laura, D'Alessandro, Miriana, Cameli, Paolo, Bennett, David, Federico, Anedda, Simona, Marcantonio, Scolletta, Sabino, Franchi, Federico, Mazzei, MARIA ANTONIETTA, Susanna, Guerrini, Edoardo, Conticini, Cantarini, Luca, Frediani, Bruno, 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, Alessandro, Pancrazzi, Massimo, Vaghi, Antonella D’Arminio Monforte, Federica Gaia Miraglia, Mondelli, Mario U., Stefania, Mantovani, Raffaele, Bruno, Marco, Vecchia, Marcello, Maffezzoni, Sophie, Venturelli, Andrea, Cossarizza, Andrea, Antinori, Alessandra, Vergori, Arianna, Emiliozzi, Arianna, Gabrieli, Agostino, Riva, Andrea, Tommasi, Pier Giorgio Scotton, Francesca, Andretta, Stefano, Baratti, Renzo, Scaggiante, Francesca, Gatti, Francesco, Castelli, Eugenia, Quiros-Roldan, Melania Degli Antoni, Isabella, Zanella, Matteo della Monica, Roberta, Russo, Immacolata, Andolfo, Achille, Iolascon, Giuseppe, Fiorentino, Massimo, Carella, Marco, Castori, Giuseppe, Merla, Gabriella Maria Squeo, Filippo, Aucella, Pamela, Raggi, Rita, Perna, Matteo, Bassetti, Antonio Di Biagio, Maurizio, Sanguinetti, Luca, Masucci, Alessandra, Guarnaccia, Valente, Serafina, Alex Di Florio, Mandala', Marco, Giorli, Alessia, Salerni, Lorenzo, Patrizia, Zucchi, Pierpaolo, Parravicini, Elisabetta, Menatti, Tullio, Trotta, Ferdinando, Giannattasio, Gabriella, Coiro, Fabio, Lena, Gianluca, Lacerenza, Cristina, Mussini, Luisa, Tavecchia, Lia, Crotti, Gianfranco, Parati, Roberto, Menè, Maurizio, Sanarico, Gori, Marco, Nicola, Picchiotti, Francesco, Raimondi, Alessandra, Stella, Filippo, Biscarini, Tiziana, Bachetti, Maria Teresa La Rovere, Maurizio, Bussotti, Serena, Ludovisi, Katia, Capitani, Chiara, Gabbi, Simona, Dei, Sabrina, Ravaglia, Rosangela, Artuso, Elena, Andreucci, Angelica, Pagliazzi, Erika, Fiorentini, Antonio, Perrella, Francesco, Bianchi, Paola, Bergomi, Emanuele, Catena, Riccardo, Colombo, Paola, Petrocelli, Sarah, Iacopini, Sara, Modica, Silvia, Baroni, Giulia, Micheli, 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, Alessio, Bellucci, Marta, Colaneri, Patrizia, Casprini, Cristoforo, Pomara, Massimiliano, Esposito, Marco Antonio Bellini, Zguro, Kristina, Baldassarri, Margherita, Fava, Francesca, Beligni, Giada, Daga, Sergio, Leoncini, Roberto, Galasso, Lucrezia, Cirianni, Michele, Rusconi, Stefano, Siano, Matteo, Francisci, Daniela, Schiaroli, Elisabetta, Luchi, Sauro, Morelli, Giovanna, Martinelli, Enrico, Girardis, Massimo, Busani, Stefano, Parisi, Saverio Giuseppe, Panese, Sandro, Piscopo, Carmelo, Capasso, Mario, Tacconi, Danilo, Spertilli Raffaelli, Chiara, Giliberti, Annarita, Gori, Giulia, Katsikis, Peter D, Lorubbio, Maria, Calzoni, Paola, Ognibene, Agostino, Bocchia, Monica, Tozzi, Monica, Bucalossi, Alessandro, Marotta, Giuseppe, Furini, Simone, Gen-Covid Multicenter Study, Null, Renieri, Alessandra, Fallerini, Chiara, Gen-Covid Multicenter Study, null, and Immunology

Subjects
Thrombotic Thrombocytopenic, Purpura, Thrombotic Thrombocytopenic, SARS-CoV-2, COVID-19, ADAMTS13, thromboembolism, add-on therapy, ADAMTS13 Protein, ADAM Proteins, Infectious Diseases, SDG 3 - Good Health and Well-being, Virology, von Willebrand Factor, Humans, Purpura
Abstract

Thrombosis of small and large vessels is reported as a key player in COVID-19 severity. However, host genetic determinants of this susceptibility are still unclear. Congenital Thrombotic Thrombocytopenic Purpura is a severe autosomal recessive disorder characterized by uncleaved ultra-large vWF and thrombotic microangiopathy, frequently triggered by infections. Carriers are reported to be asymptomatic. Exome analysis of about 3000 SARS-CoV-2 infected subjects of different severities, belonging to the GEN-COVID cohort, revealed the specific role of vWF cleaving enzyme ADAMTS13 (A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 13). We report here that ultra-rare variants in a heterozygous state lead to a rare form of COVID-19 characterized by hyper-inflammation signs, which segregates in families as an autosomal dominant disorder conditioned by SARS-CoV-2 infection, sex, and age. This has clinical relevance due to the availability of drugs such as Caplacizumab, which inhibits vWF–platelet interaction, and Crizanlizumab, which, by inhibiting P-selectin binding to its ligands, prevents leukocyte recruitment and platelet aggregation at the site of vascular damage.

Published
2022

14. 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

15. 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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16. Performance evaluation of four surrogate Virus Neutralization Tests (sVNTs) in comparison to the in vivo gold standard test

Author

Sergio Bernardini, Concetta Castilletti, Lorenzo Stacchini, Patrizia Casprini, Maurizio Benucci, Amedeo Amedei, Edda Russo, Serena Sarubbi, Flaminia Tomassetti, Barbara Lari, Valentina Grossi, Marzia Nuccetelli, Mariangela Manfredi, Maria Infantino, and Massimo Pieri

Subjects
immunoassays, General Immunology and Microbiology, Settore BIO/12, live virus neutralization test, General Biochemistry, Genetics and Molecular Biology, surrogate Virus Neutralization Tests, anti-SARS-CoV-2 antibodies
Published
2022

17. Performance evaluation of four surrogate Virus Neutralization Tests (sVNTs) in comparison to the

Author

Massimo, Pieri, Maria, Infantino, Mariangela, Manfredi, Marzia, Nuccetelli, Valentina, Grossi, Barbara, Lari, Flaminia, Tomassetti, Serena, Sarubbi, Edda, Russo, Amedeo, Amedei, Maurizio, Benucci, Patrizia, Casprini, Lorenzo, Stacchini, Concetta, Castilletti, and Sergio, Bernardini

Subjects
Neutralization Tests, SARS-CoV-2, COVID-19, Humans, Antibodies, Viral, Antibodies, Neutralizing
Abstract

Several commercial surrogate Virus Neutralization Tests (sVNTs) have been developed in the last year. Neutralizing anti-SARS-CoV-2 antibodies through interaction with Spike protein Receptor Binding Domain (S-RBD) can block the virus from entering and infecting host cells. However, there is a lack of information about the functional activity of SARS-CoV-2 antibodies that may be associated with protective responses. For these reasons, to counteract viral infection, the conventional virus neutralization test (VNT) is still considered the gold standard. The aim of this study was to contribute more and detailed information about sVNTs' performance, by determiningEighty-eight samples were tested using two chemiluminescence assays (Snibe and Mindray) and two ELISA assays (Euroimmun and Diesse). The antibody titers were subsequently detected and quantified by VNT.The overall agreement between each sVNT and VNT was 95.45% for Euroimmun and 98.86% for Diesse, Mindray and Snibe. Additionally, we investigated whether the sVNTs were closer to the gold standard than traditional anti-SARS-CoV-2 antibody assays S-RBD or S1 based, finding a higher agreement mean value for sVNTs (98.01 ± 1.705% vs 95.45 ± 1.921%;Our data revealed a good agreement between VNT and sVNTs. Despite the VNT still remains the gold standard, the sVNT might be a valuable tool for screening wider populations.

Published
2021

18. Prevention and control of COVID-19 in the penitentiary of Florence

Author

Mirco Capacci, Sergio Fabbri, Lorenza Cristiano, Maurizio Benucci, Patrizia Casprini, Alessio Bellucci, Sandra Rogialli, Francesca Veneziani, Mariangela Manfredi, Valentina Grossi, Silvia Pancani, Patrizia Sani, Barbara Lari, Maria Infantino, Alessandro Perri, and Luciana Amendola

Subjects
2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), SARS-CoV-2, media_common.quotation_subject, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Biochemistry (medical), Clinical Biochemistry, COVID-19, Prison, General Medicine, Antibodies, Viral, Virology, COVID-19 Serological Testing, Geography, Italy, Prisons, Humans, media_common
Published
2021
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19. Assessing T-Cell Immunity in Kidney Transplant Recipients with Absent Antibody Production after a 3rd Dose of the mRNA-1273 Vaccine

Author

Maria Infantino, Aris Tsalouchos, Edda Russo, Selene Laudicina, Valentina Grossi, Barbara Lari, Maurizio Benucci, Lorenzo Stacchini, Amedeo Amedei, Patrizia Casprini, Danilo Villalta, Pietro Claudio Dattolo, and Mariangela Manfredi

Subjects
interferon-gamma release assay, COVID-19, kidney transplantation, T cells, COVID-19 Vaccines, SARS-CoV-2, T-Lymphocytes, Organic Chemistry, General Medicine, Antibodies, Viral, Kidney Transplantation, Transplant Recipients, Catalysis, Computer Science Applications, Inorganic Chemistry, Interferon-gamma, Antibody Formation, Humans, Physical and Theoretical Chemistry, Molecular Biology, Spectroscopy, 2019-nCoV Vaccine mRNA-1273
Abstract

The vulnerable population of kidney transplant recipients (KTRs) are low responders to COVID-19 vaccines, so specific immune surveillance is needed. The interferon-gamma (IFN-γ) release assay (IGRA) is effective in assessing T cell-mediated immunity. We assessed SARS-CoV-2-directed T cell responses in KTRs with absent antibody production after a third dose of the mRNA-1273 vaccine, using two different IGRAs. A cohort of 57 KTRs, who were actively followed up, received a third dose of the mRNA-1273 vaccine. After the evaluation of humoral immunity to SARS-CoV-2, 14 seronegative patients were tested with two commercial IGRAs (SD Biosensor and Euroimmun). Out of 14 patients, one and three samples were positive by IGRAs with Euroimmun and SD Biosensor, respectively. The overall agreement between the two assays was 85.7% (κ = 0.444). In addition, multivariate linear regression analysis showed no statistically significant association between the IFN-γ concentration, and the independent variables analyzed (age, gender, years since transplant, total lymphocytes cells/mcl, CD3+ cells/mcl, CD3+ CD4+ cells/mcl, CD3+ CD8+ cells/mcl, CD19+ cells/mcl, CD3-CD16+CD56+ cells/mcl) (p > 0.01). In a vulnerable setting, assessing cellular immune response to complement the humoral response may be advantageous. Since the two commercial IGRAs showed a good agreement on negative samples, the three discordant samples highlight the need for further investigations.

Published
2022
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20. Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

Author

Fallerini, Chiara, Picchiotti, Nicola, Baldassarri, Margherita, Zguro, Kristina, Daga, Sergio, Fava, Francesca, Benetti, Elisa, Amitrano, Sara, Bruttini, Mirella, Palmieri, Maria, Croci, Susanna, Lista, Mirjam, Beligni, Giada, Valentino, Floriana, Meloni, Ilaria, Tanfoni, Marco, Minnai, Francesca, Colombo, Francesca, Cabri, Enrico, Fratelli, Maddalena, Gabbi, Chiara, Mantovani, Stefania, Frullanti, Elisa, Gori, Marco, Crawley, Francis P, Butler-Laporte, Guillaume, Richards, Brent, Zeberg, Hugo, Lipcsey, Miklos, Hultström, Michael, Ludwig, Kerstin U, Schulte, Eva C, Pairo-Castineira, Erola, Baillie, John Kenneth, Schmidt, Axel, Frithiof, Robert, Mari, Francesca, Renieri, Alessandra, Furini, Simone Simone Furini, 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, Maurizio, Spagnesi, 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, Mario, U Mondelli, 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, 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, Gabriella, Doddato, Rossella, Tita, Annarita, Giliberti, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Valentina, Perticaroli, Francesca, Ariani, Miriam Lucia Carriero, Laura Di Sarno, Diana, Alaverdian, Elena, Bargagli, Marco, Mandalà, Alessia, Giorli, Lorenzo, Salerni, Patrizia, Zucchi, Pierpaolo, Parravicini, Elisabetta, Menatti, Tullio, Trotta, Ferdinando, Giannattasio, Gabriella, Coiro, Fabio, Lena, Leonardo Gianluca Lacerenza, Domenico, A Coviello, Cristina, Mussini, Enrico, Martinelli, Sandro, Mancarella, Luisa, Tavecchia, Mary Ann Belli, Lia, Crotti, Gianfranco, Parati, Maurizio, Sanarico, Francesco, Raimondi, 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, Menè, Roberto, Umberto, Zuccon, Lucia, Vietri, Stefano, Ceri, Pietro, Pinoli, Patrizia, Casprini, Giuseppe, Merla, Gabriella Maria Squeo, Marcello, Maffezzoni, Raffaele, Bruno, Marco, Vecchia, Marta, Colaneri, Serena, Ludovisi, Yanara, Marincevic-Zuniga, Jessica, Nordlund, Tomas, Luther, Anders, Larsson, Katja Hanslin Anna Gradin, Sarah, Galien, Sara Bulow Anderberg, Jacob, Rosén, Sten, Rubertsson, Hugo, Zeberg, Robert, Frithiof, Miklós, Lipcsey, Michael, Hultström, Sara Clohisey Peter Horby, Johnny, Millar, Julian, Knight, Hugh, Montgomery, David, Maslove, Lowell, Ling, Alistair, Nichol, Charlotte, Summers, Tim, Walsh, Charles, Hinds, Malcolm, G Semple, Peter J, M Openshaw, Manu, Shankar-Hari, Antonia, Ho, Danny, Mcauley, Chris, Ponting, Kathy, Rowan, J Kenneth Baillie, Fiona, Griffiths, Wilna, Oosthuyzen, Jen, Meikle, Paul, Finernan, James, Furniss, Ellie, Mcmaster, Andy, Law, Sara, Clohisey, Trevor, Paterson, Tony, Wackett, Ruth, Armstrong, Lee, Murphy, Angie, Fawkes, Richard, Clark, Audrey, Coutts, Lorna, Donnelly, Tammy, Gilchrist, Katarzyna, Hafezi, Louise, Macgillivray, Alan, Maclean, Sarah, Mccafferty, Kirstie, Morrice, Jane, Weaver, Ceilia, Boz, Ailsa, Golightly, Mari, Ward, Hanning, Mal, Helen, Szoor-McElhinney, Adam, Brown, Ross, Hendry, Andrew, Stenhouse, Louise, Cullum, Dawn, Law, Sarah, Law, Rachel, Law, Max Head Fourman, Maaike, Swets, Nicky, Day, Filip, Taneski, Esther, Duncan, Marie, Zechner, Nicholas, Parkinson, Erola, Pairo-Castineira, Lucija, Klaric, Andrew, D Bretherick, Konrad, Rawlik, Dorota, Pasko, Susan, Walker, Nick, Parkinson, Clark, D Russell, Anne, Richmond, Elvina, Gountouna, David, Harrison, Wang, Bo, Yang, Wu, Alison, Meynert, Athanasios, Kousathanas, Loukas, Moutsianas, Zhijian, Yang, Ranran, Zhai, Chenqing, Zheng, Graeme, Grimes, Jonathan, Millar, Barbara, Shih, Jian, Yang, Xia, Shen, Chris, P Ponting, Albert, Tenesa, Andrew, Law, Veronique, Vitart, James, F Wilson, Collier, D, Wood, S, Zak, A, Borra, C, Matharu, M, 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Thorpe, C, Knights, E, Boyle, N, Price, A, Kubisz-Pudelko, A, Wood, D, Lewis, A, Board, S, Pippard, L, Perry, J, Beesley, K, Rattray, A, Lee, E, Lennon, L, Douglas, K, Bell, D, Boyle, R, Glass, L, M Nauman Akhtar, Dent, K, Potoczna, D, Pearson, S, Horsley, E, Spencer, S, Mullan, D, Skinner, D, Gaylard, J, Ortiz-Ruizdegordoa, L, Barber, R, Hewitt, C, Hilldrith, A, Shepardson, S, Wills, M, Jackson-Lawrence, K, Gupta, A, Easthope, A, Timlick, E, Gorman, C, Otaha, I, Gales, A, Coetzee, S, Raj, M, Peiu, M, Quaid, S, Watson, E, Elliott, K, Mallinson, J, Chandler, B, Turnbull, A, Finch, C, Holl, C, Cooper, J, Evans, A, Khaliq, W, Collins, A, E Treus Gude, Love, N, L van Koutrik, Hunt, J, Kaye, D, Fisher, E, Brayne, A, Tuckey, V, Jackson, P, Parkin, J, Raith, E, Tariq, A, Houlden, H, Tucci, A, Hardy, J, Moncur, E, Highgate, J, Cowley, A, Mitra, A, Stead, R, Behan, T, Burnett, C, Newton, M, Heeney, E, Pollard, R, Hatton, J, Patel, A, Kasipandian, V, Allibone, S, M Genetu, R, Otahal, I, O'Brien, L, Omar, Z, Perkins, E, Davies, K, Tetla, D, Shelley, B, Irvine, V, Williams, S, Williams, P, Goodsell, J, Tutton, R, Bough, L, Winter-Goodwin, B, Kitson, R, Pinnell, J, Wilson, A, Nortcliffe, T, Wood, T, Home, M, Holdroyd, K, Robinson, M, Shaw, R, Greig, J, Brady, M, Haigh, A, Matupe, L, Usher, M, Mellor, S, Dale, S, Gledhill, L, Shaw, L, Turner, G, Kelly, D, Anwar, B, Riley, H, Sturgeon, H, Ali, A, Thomis, L, Melia, D, Dance, A, Hanson, K, Humphreys, S, Frost, I, Gopal, V, Godden, J, Holden, A, Swann, S, Smith, T, Clapham, M, Poultney, U, Harper, R, Rice, P, Reece-Anthony, R, Gurung, B, Moultrie, S, Odam, M, Mayer, A, Bellini, A, Pickard, A, Bryant, J, Roe, N, Sowter, J, Lang, K, Taylor, J, Barry, P, Hobrok, M, Tench, H, Wolf-Roberts, R, Mcguinness, H, Loosley, R, Hawcutt, D, Rad, L, O'Malley, L, Saunderson, P, Seddon, G, Anderson, T, Rogers, N, Ruddy, J, Harkins, M, Beith, C, Mcalpine, A, Ferguson, L, Grant, P, Macfadyen, S, Mclaughlin, M, Baird, T, Rundell, S, Welsh, B, Hamill, R, Fisher, F, Gregory, J, Axel, Schmidt, Kerstin, U Ludwig, Selina, Rolker, Markus, M Nöthen, Julia, Fazaal, Verena, Keitel, Björn, Jensen, Torsten, Feldt, Lisa, Knopp, Julia, Schröder, Carlo, Maj, Fabian, Brand, Marc, M Berger, Thorsten, Brenner, Anke, Hinney, Oliver, Witzke, Robert, Bals, Christian, Herr, Nicole, Ludwig, Jörn, Walter, Jochen, Schneider, Johanna, Erber, Christoph, D Spinner, Clemens, M Wendtner, Christof, Winter, Ulrike, Protzer, Nicolas, Casadei, Stephan, Ossowski, Olaf, H Riess, Eva, C Schulte, J Brent Richards, Guillaume, Butler-Laporte, Mirosław, Kwasniewski, Urszula, Korotko, Karolina, Chwialkowska, Magdalena, Niemira, Jerzy, Jaroszewicz, Barbara, Sobala-Szczygiel, Beata, Puzanowska, Anna, Parfieniuk-Kowerda, Diana, Martonik, Anna, Moniuszko-Malinowska, Sławomir, Pancewicz, Dorota, Zarębska-Michaluk, Krzysztof, Simon, Monika, Pazgan-Simon, Iwona, Mozer-Lisewska, Maciej, Bura, Agnieszka, Adamek, Krzysztof Tomasiewicz Małgorzata Pawłowska, Anna, Piekarska, Aleksandra, Berkan-Kawinska, Andrzej, Horban, Justyna, Kowalska, Regina, Podlasin, Piotr, Wasilewski, Arsalin, Azzadin, Miroslaw, Czuczwar, Slawomir, Czaban, Paweł, Olszewski, Jacek, Bogocz, Magdalena, Ochab, Anna, Kruk, Sandra, Uszok, Agnieszka, Bielska, Anna, Szałkowska, Justyna, Raczkowska, Gabriela, Sokołowska, Joanna, Chorostowska-Wynimko, Aleksandra, Jezela-Stanek, Adriana, Roży, Urszula, Lechowicz, Urszula, Polowianiuk, Kamil, Grubczak, Aleksandra, Starosz, Andrzej, Eljaszewicz, Wiktoria, Izdebska, Adam, Krętowski, Robert, Flisiak, Marcin Moniuszko Malak Abedalthagafi Manal Alaamery, Salam, Massadeh, Mohamed, Fawzy, Hadeel, Albardis, Nora, Aljawini, Moneera, Alsuwailm, Faisal, Almalki, Serghei, Mangul, Junghyun, Jung, Hamdi, Mbarek, Chadi, Saad, Yaser, Al-Sarraj, Wadha, Al-Muftah, Radja, Badji, Asma Al Thani, Said, I Ismail, HGI, WES/WGS Working Group Within the, Consortium, GenOMICC, Study, GEN-COVID Multicenter, Renieri, Alessandra [0000-0002-0846-9220], Apollo - University of Cambridge Repository, NIHR, Fallerini, C, Picchiotti, N, Baldassarri, M, Zguro, K, Daga, S, Fava, F, Benetti, E, Amitrano, S, Bruttini, M, Palmieri, M, Croci, S, Lista, M, Beligni, G, Valentino, F, Meloni, I, Tanfoni, M, Minnai, F, Colombo, F, Cabri, E, Fratelli, M, Gabbi, C, Mantovani, S, Frullanti, E, Gori, M, Crawley, F, Butler-Laporte, G, Richards, B, Zeberg, H, Lipcsey, M, Hultström, M, Ludwig, K, Schulte, E, Pairo-Castineira, E, Baillie, J, Schmidt, A, Frithiof, R, Mari, F, Renieri, A, Furini, S, and Crotti, L

Subjects
Male, Medicin och hälsovetenskap, Linkage disequilibrium, Medizin, severity, Genome-wide association study, Disease, WES/WGS Working Group Within the HGI, Logistic regression, Severity of Illness Index, Medical and Health Sciences, Whole Exome Sequencing, Cohort Studies, 0302 clinical medicine, Lasso (statistics), GEN-COVID Multicenter Study, Germany, 80 and over, Genetics (clinical), Exome sequencing, Original Investigation, Genetics & Heredity, Aged, 80 and over, 0303 health sciences, Adult, Aged, COVID-19, Female, Humans, Italy, Middle Aged, Polymorphism, Single Nucleotide, Quebec, SARS-CoV-2, Sweden, United Kingdom, Genetic Predisposition to Disease, Phenotype, Single Nucleotide, covid-19, 1104 Complementary and Alternative Medicine, GenOMICC Consortium, Human, coding variants, Computational biology, Biology, 03 medical and health sciences, Exome Sequencing, Genetics, Polymorphism, Gene, 030304 developmental biology, 0604 Genetics, 1114 Paediatrics and Reproductive Medicine, Cohort Studie, 030217 neurology & neurosurgery, Coding (social sciences)
Abstract

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. Supplementary Information The online version contains supplementary material available at 10.1007/s00439-021-02397-7.

Published
2021
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21. The who international standard for covid-19 serological tests: towards harmonization of anti-spike assays

Author

Massimo Pieri, Valentina Grossi, Maurizio Benucci, Mariangela Manfredi, Silvia Pancani, Maria Infantino, Patrizia Casprini, Sergio Bernardini, Barbara Lari, Graziella Calugi, Flaminia Tomassetti, and Marzia Nuccetelli

Subjects
Adult, Male, serological tests, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Immunology, Population, Biology, Antibodies, Viral, World Health Organization, Article, Serology, COVID-19 Serological Testing, Antigen, Humans, Immunology and Allergy, education, Aged, Pharmacology, education.field_of_study, SARS-CoV-2, COVID-19, WHO international standard, Middle Aged, Vaccination, Immunoglobulin G, harmonization, Spike Glycoprotein, Coronavirus, biology.protein, Female, Antibody, Kappa, anti-SARS-CoV-2 antibodies
Abstract

Background and aims SARS-CoV-2 antibody assays are relevant in managing the COVID-19 pandemic, providing valuable data on the immunization status of the population. However, current serology tests are highly variable, due to their different characteristics and to the lack of reference materials. The aim of the World Health Organization (WHO) first International Standard (IS) for anti-SARS-CoV-2 immunoglobulin is to harmonize humoral immune response assessment after natural infection or vaccination, and recommend reporting the results for binding activity in Binding Antibody Units (BAU). Materials and methods This study analyzed six commercial quantitative anti-SARS-CoV-2 S-protein assays in a head-to-head comparison, using the manufacturers' conversion factors for the WHO IS to obtain BAU/mL values. Results Our data showed good alignment up to 1000 BAU/mL, then began to disperse, exhibiting some discrepancies. Moreover, correlations among methods varied with Cohen’s Kappa ranging from 0.580 to 1.00, with the lowest agreement values for kits using different target antigens or different antibody isotypes, making it clear that the laboratory report should include this information. Values expressed as BAU/ml showed a reduced between-assays variability compared to AU/ml (median coefficients of variation 0.38 and 0.68, respectively; p Conclusion On the basis of these data at present anti-SARS CoV-2 serological assays’ results are not interchangeable, and, more importantly, individual immune monitoring should be performed with the same method.

Published
2021

22. Soluble urokinase Plasminogen Activator Receptor (suPAR) levels are predictive of COVID-19 severity: an Italian experience

Author

Maria Infantino, Lorenza Morena, Massimo Antonio Di Pietro, Benedetta Romanin, Barbara Cimolato, Beatrice Anna Luisa Rocca, Silvia Tunnera, Giulia Modi, Marta Tilli, Valentina Grossi, Barbara Lari, Helena Cerutti, Giulia Tesi, Valentina Anrò, Alessandra Cartocci, Maurizio Benucci, Francesca Veneziani, Patrizia Casprini, and Mariangela Manfredi

Subjects
Interleukin-6, Tumor Necrosis Factor-alpha, Immunology, COVID-19, Humans, Immunology and Allergy, Prognosis, Leukocyte L1 Antigen Complex, Biomarkers, Receptors, Urokinase Plasminogen Activator
Abstract

The soluble urokinase Plasminogen Activator Receptor (suPAR) has been identified as a reliable marker of COVID-19 severity, helping in personalizing COVID-19 therapy. This study aims to evaluate the correlation between suPAR levels and COVID-19 severity, in relation to the traditional inflammatory markers.Sera from 71 COVID-19 patients were tested for suPAR levels using Chorus suPAR assay (Diesse Diagnostica Senese SpA, Italy). suPAR levels were compared with other inflammatory markers: IL-1β, IL-6, TNF-α, circulating calprotectin, neutrophil and lymphocyte counts, and Neutrophil/Lymphocytes Ratio (NLR). Respiratory failure, expressed as P/F ratio, and mortality rate were used as indicators of disease severity.A positive correlation of suPAR levels with IL-6 (r = 0.479, p = 0.000), TNF-α (r = 0.348, p = 0.003), circulating calprotectin (r = 0.369, p = 0.002), neutrophil counts (r = 0.447, p = 0.001), NLR (r = 0.492, p = 0.001) has been shown. Stratifying COVID-19 population by suPAR concentration above and below 6 ng/mL, we observed higher levels of circulating calprotectin (10.1 μg/mL, SD 7.9 versus 6.4 μg/mL, SD 7.5, p lt; 0.001), higher levels of P/F ratio (207.5 IQR 188.3 vs 312.0 IQR 127.8, p = 0.013) and higher mortality rate. Median levels of suPAR were increased in all COVID-19 patients requiring additional respiratory support (Nasal Cannula, Venturi Mask, BPAP and CPAP) (6.5 IQR = 4.9) compared to the group at room air (4.6 IQR = 4.2).suPAR levels correlate with disease severity and survival rate of COVID-19 patients, representing a promising prognostic biomarker for the risk assessment of the disease.

Published
2022
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23. Universal screening for SARS-CoV-2 in pregnant women admitted for delivery: how to manage antibody testing?

Author

Daniela Matarrese, Tamara Brunelli, Pier Luigi Vasarri, Patrizia Casprini, Anna Franca Cavaliere, Alis Iuliana Carabaneanu, and Federica Perelli

Subjects
0301 basic medicine, 2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), law.invention, 03 medical and health sciences, 0302 clinical medicine, COVID-19 Testing, law, Pregnancy, Medicine, Humans, 030212 general & internal medicine, Pregnancy Complications, Infectious, Polymerase chain reaction, biology, business.industry, Clinical Laboratory Techniques, SARS-CoV-2, Obstetrics and Gynecology, COVID-19, Virology, 030104 developmental biology, Pediatrics, Perinatology and Child Health, biology.protein, Female, Pregnant Women, Antibody, business
Abstract

SARS-Cov-2 has rapidly spread in Italy, with a significant unexplainable difference between different regions, the most affected being in the North [1]. The real-time polymerase chain reaction (RT-...

Published
2020

24. Vantaggi, limiti e prospettive dei test sierologici nell'infezione da SARS-CoV-2 (COVID-19)

Author

Patrizia Casprini, Maurizio Benucci, Piero Cappelletti, Mariangela Manfredi, Luca Quartuccio, Arianna Damiani, Martina Fabris, Francesca Li Gobbi, Francesca Veneziani, Maria Infantino, Barbara Lari, Valentina Grossi, Nicola Bizzaro, Donatella Macchia, and Danilo Villalta

Subjects
Medical Laboratory Technology, Infectious disease (medical specialty), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Biochemistry (medical), Medicine, business, Virology, Serology
Published
2020
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25. Diagnostic accuracy of an automated chemiluminescent immunoassay for anti‐SARS‐CoV‐2 IgM and IgG antibodies: an Italian experience

Author

Sergio Fabbri, Valentina Grossi, Irene Liotti, Adolfo Pompetti, Francesca Veneziani, Alessandro Perri, Mariangela Manfredi, Maria Infantino, Barbara Lari, Patrizia Casprini, Giovanni Terenzi, Riccardo Bambi, Cristina Taddei, Matteo Manneschi, Maurizio Benucci, and Giovanni Ciotta

Subjects
Male, SARS coronavirus, Short Communication, Short Communications, coronavirus, medicine.disease_cause, Antibodies, Viral, Sensitivity and Specificity, Serology, law.invention, 03 medical and health sciences, 0302 clinical medicine, law, Virology, humoral immunity, medicine, Humans, 030212 general & internal medicine, virus classification, Polymerase chain reaction, Coronavirus, Aged, Aged, 80 and over, Automation, Laboratory, Immunoassay, Receiver operating characteristic, biology, business.industry, SARS-CoV-2, Area under the curve, COVID-19, Reproducibility of Results, Gold standard (test), Middle Aged, immune responses, Infectious Diseases, Immunoglobulin M, ROC Curve, Immunoglobulin G, Humoral immunity, Luminescent Measurements, biology.protein, 030211 gastroenterology & hepatology, Female, Antibody, business
Abstract

A pandemic of coronavirus disease 2019 (COVID‐19) caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has been spreading throughout the world. Though molecular diagnostic tests are the gold standard for COVID‐19, serological testing is emerging as a potential surveillance tool, in addition to its complementary role in COVID‐19 diagnostics. Indubitably quantitative serological testing provides greater advantages than qualitative tests but today there is still little known about serological diagnostics and what the most appropriate role quantitative tests might play. Sixty‐one COVID‐19 patients and 64 patients from a control group were tested by iFlash1800 CLIA analyzer for anti‐SARS CoV‐2 antibodies IgM and IgG. All COVID‐19 patients were hospitalized in San Giovanni di Dio Hospital (Florence, Italy) and had a positive oro/nasopharyngeal swab reverse‐transcription polymerase chain reaction result. The highest sensitivity with a very good specificity performance was reached at a cutoff value of 10.0 AU/mL for IgM and of 7.1 for IgG antibodies, hence near to the manufacturer's cutoff values of 10 AU/mL for both isotypes. The receiver operating characteristic curves showed area under the curve values of 0.918 and 0.980 for anti‐SARS CoV‐2 antibodies IgM and IgG, respectively. iFlash1800 CLIA analyzer has shown highly accurate results for the anti‐SARS‐CoV‐2 antibodies profile and can be considered an excellent tool for COVID‐19 diagnostics.

Published
2020

26. Serological Assays for SARS-CoV-2 Infectious Disease: Benefits, Limitations and Perspectives

Author

Maria, Infantino, Arianna, Damiani, Francesca Li, Gobbi, Valentina, Grossi, Barbara, Lari, Donatella, Macchia, Patrizia, Casprini, Francesca, Veneziani, Danilo, Villalta, Nicola, Bizzaro, Piero, Cappelletti, Martina, Fabris, Luca, Quartuccio, Maurizio, Benucci, and Mariangela, Manfredi

Subjects
CD4-Positive T-Lymphocytes, Clinical Laboratory Techniques, Reverse Transcriptase Polymerase Chain Reaction, SARS-CoV-2, Pneumonia, Viral, COVID-19, Enzyme-Linked Immunosorbent Assay, CD8-Positive T-Lymphocytes, Antibodies, Viral, Severe Acute Respiratory Syndrome, Coronavirus, Betacoronavirus, COVID-19 Testing, Immunoglobulin M, Immunoglobulin G, Humans, RNA, Viral, Serologic Tests, Coronavirus Infections, Pandemics
Published
2020

27. Reflex testing of speckled cytoplasmic patterns observed in routine ANA HEp-2 indirect immunofluorescence with a multiplex anti-synthetase dot-blot assay: a multicentric pilot study

Author

Maria Infantino, Arianna Damiani, Maurizio Benucci, Fabio Almerigogna, Patrizia Casprini, Boaz Palterer, Roberta Biagiotti, Giovanni Bacci, Valentina Grossi, Maria Grazia Giudizi, Mariangela Manfredi, and Annalisa Azzurri

Subjects
0301 basic medicine, Pathology, medicine.medical_specialty, Cytoplasm, Immunology, Immunoblotting, Dot blot, Immunofluorescence, Autoantigens, Serology, Autoimmune Diseases, Cohort Studies, Ligases, 03 medical and health sciences, 0302 clinical medicine, Antigen, medicine, Humans, Multiplex, Fluorescent Antibody Technique, Indirect, Retrospective Studies, 030203 arthritis & rheumatology, medicine.diagnostic_test, biology, Myositis, business.industry, Diagnostic Tests, Routine, Arthritis, Syndrome, medicine.disease, Connective tissue disease, Blot, 030104 developmental biology, Antibodies, Antinuclear, biology.protein, Antibody, business, Lung Diseases, Interstitial
Abstract

Immunofluorescence on HEp2-cells is the standard diagnostic assay for the detection of anti-nuclear antibodies (ANA). Cytoplasmic speckled patterns are a common finding, and are associated with various antibodies, including anti-synthetase antibodies. However, classic ENA testing generally identifies only anti-Jo-1. Moreover, anti-synthetase syndrome is increasingly recognized as a pleomorphic entity, possibly presenting as isolated arthritis or interstitial lung disease. Sera referred for routine ANA testing were selected on the basis of the presence of a fine dense speckled cytoplasmic pattern (254 samples) and compared to control sera with negative cytoplasm (239 samples). All 493 samples were tested with a commercial synthetase profile dot-blot (D TEK - Alphadia-Alifax) including anti-Jo1, anti-PL7, anti-PL12, anti-EJ, anti-OJ, anti-KS, anti-ZO, anti-HA, anti-SRP, and anti-Ribosome P0. Retrospective clinical data was searched for positive patients. Dot-blot identified 18/254 (7.1%) positive sera in the samples with a cytoplasmic fluorescence pattern and 4/239 (1.7%) in the control group (χ2 = 8.4627; p = 0.003625). Blot intensity was more intense in samples with concordant cytoplasmic staining (cytoplasmic negative 27 ± 12.4; cytoplasmic positive 53.9 27 ± 27.7; p = 0.0027). In the positive samples, 8/18 had a highly compatible diagnosis (myositis, interstitial lung disease, arthritis), 7/18 an uncharacterized connective tissue disease, and 3 a diagnosis not associated with the presence of anti-synthetase antibodies. We evaluated the performance of a dot-blot assay for anti-cytoplasmic antibodies in a serologic cohort presenting a cytoplasmic speckled pattern found during routine ANA testing. This algorithm enabled the identification of a significant quota of patients with rare anti-synthetase antibodies and an incomplete or atypical clinical picture. Reflex testing strategies of speckled cytoplasmic patterns with multiplex assays containing cytoplasm-specific antigens, as opposed to standard ENA testing, may yield important data and for this reason should be implemented in routine ANA testing.

Published
2017

28. Comprehensive global genome dynamics of Chlamydia trachomatis show ancient diversification followed by contemporary mixing and recent lineage expansion

Author

Rebecca Wiggins, Patiyan Andersson, Matthew J. Burton, Cathy Ison, Suyapa Mendoza, María Lucía Gallo Vaulet, Simon R. Harris, David A. Lewis, David Mabey, Alevtina Savicheva, Patrizia Casprini, James Hadfield, Rachel Pitt, Magnus Unemo, Konrad Sachse, Laszlo Kari, Julian Parkhill, Louise Ellison, Philip M. Giffard, Ian N. Clarke, Anthony W. Solomon, Marcelo Rodríguez Fermepin, Helena M. B. Seth-Smith, Hamid Jalal, Surendra Parmar, Julius Schachter, Chris Sonnex, Servaas A. Morré, Elena Shipitsyna, Ronza Hadad, Peter Marsh, Jeanne Moncada, Tamara Brunelli, F Radebe, Nicholas R. Thomson, Sander Ouburg, Suvi Korhonen, Mirja Puolakkainen, RS: GROW - R4 - Reproductive and Perinatal Medicine, and Institute for Public Health Genomics

Subjects
0301 basic medicine, Lineage (evolution), 030106 microbiology, RECOMBINATION, Human pathogen, Biology, HIGH-THROUGHPUT, medicine.disease_cause, SEQUENCE, Genome, DNA sequencing, Bacterial genetics, Evolutionsbiologi, 03 medical and health sciences, INTRACELLULAR PATHOGEN, Antibiotic resistance, Genetics, medicine, Pathogen, Genetics (clinical), Evolutionary Biology, ANTIBIOTIC-RESISTANCE, CLINICAL-SAMPLES, IN-VITRO, GENE, EVOLUTION, 3. Good health, 030104 developmental biology, Chlamydia trachomatis, PHENOTYPIC CHARACTERIZATION
Abstract

Chlamydia trachomatis is the world's most prevalent bacterial sexually transmitted infection and leading infectious cause of blindness, yet it is one of the least understood human pathogens, in part due to the difficulties of in vitro culturing and the lack of available tools for genetic manipulation. Genome sequencing has reinvigorated this field, shedding light on the contemporary history of this pathogen. Here, we analyze 563 full genomes, 455 of which are novel, to show that the history of the species comprises two phases, and conclude that the currently circulating lineages are the result of evolution in different genomic ecotypes. Temporal analysis indicates these lineages have recently expanded in the space of thousands of years, rather than the millions of years as previously thought, a finding that dramatically changes our understanding of this pathogen's history. Finally, at a time when almost every pathogen is becoming increasingly resistant to antimicrobials, we show that there is no evidence of circulating genomic resistance in C. trachomatis., Funding agencies:Sanger Institute through the Wellcome Trust 098051 Australian National Health and Medical Research Council 1060768

Published
2017

29. Hepatitis B and C epidemiology in an urban cohort in Tuscany (Italy)

Author

Cristina Epifani, Cristina Stasi, Patrizia Casprini, Francesco Cipriani, D. Aquilini, Stefano Bravi, Fabio Voller, and Caterina Silvestri

Subjects
Adult, Male, Pediatrics, medicine.medical_specialty, Adolescent, MEDLINE, Young Adult, Epidemiology, medicine, Humans, Young adult, Child, Hepatology, business.industry, Urban Health, Gastroenterology, Infant, Middle Aged, Hepatitis B, medicine.disease, Hepatitis C, Italy, Child, Preschool, Family medicine, Cohort, Female, business, Urban health
Published
2015
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30. Comprehensive global genome dynamics of

Author

James, Hadfield, Simon R, Harris, Helena M B, Seth-Smith, Surendra, Parmar, Patiyan, Andersson, Philip M, Giffard, Julius, Schachter, Jeanne, Moncada, Louise, Ellison, María Lucía Gallo, Vaulet, Marcelo Rodríguez, Fermepin, Frans, Radebe, Suyapa, Mendoza, Sander, Ouburg, Servaas A, Morré, Konrad, Sachse, Mirja, Puolakkainen, Suvi J, Korhonen, Chris, Sonnex, Rebecca, Wiggins, Hamid, Jalal, Tamara, Brunelli, Patrizia, Casprini, Rachel, Pitt, Cathy, Ison, Alevtina, Savicheva, Elena, Shipitsyna, Ronza, Hadad, Laszlo, Kari, Matthew J, Burton, David, Mabey, Anthony W, Solomon, David, Lewis, Peter, Marsh, Magnus, Unemo, Ian N, Clarke, Julian, Parkhill, and Nicholas R, Thomson

Subjects
Ecotype, Evolution, Molecular, Male, Research, Drug Resistance, Bacterial, Humans, Chlamydia trachomatis, Female, Genome, Bacterial
Abstract

Chlamydia trachomatis is the world's most prevalent bacterial sexually transmitted infection and leading infectious cause of blindness, yet it is one of the least understood human pathogens, in part due to the difficulties of in vitro culturing and the lack of available tools for genetic manipulation. Genome sequencing has reinvigorated this field, shedding light on the contemporary history of this pathogen. Here, we analyze 563 full genomes, 455 of which are novel, to show that the history of the species comprises two phases, and conclude that the currently circulating lineages are the result of evolution in different genomic ecotypes. Temporal analysis indicates these lineages have recently expanded in the space of thousands of years, rather than the millions of years as previously thought, a finding that dramatically changes our understanding of this pathogen's history. Finally, at a time when almost every pathogen is becoming increasingly resistant to antimicrobials, we show that there is no evidence of circulating genomic resistance in C. trachomatis.

Published
2016

31. Prevalence of Ureaplasma parvum in the area of Prato, Italy

Author

Patrizia Casprini, Tamara Brunelli, Roberto Degl’Innocenti, Daniele Ferri, Antonella Conti, Elisa Rovinati, and Patrizia Miglietta

Subjects
Gynecology, medicine.medical_specialty, biology, business.industry, Genitourinary system, animal diseases, lcsh:QR1-502, General Medicine, biology.organism_classification, lcsh:Microbiology, Ureaplasma, Ureaplasma parvum, Older patients, parasitic diseases, Medicine, business, Urogenital, ureaplasma, infection, prevalence
Abstract

In this study, the prevalence of Ureaplasma parvum in the area of Prato (Italy) was investigated. Samples from 1197 consecutive patients were analyzed. Our results showed that the prevalence of U. parvum was 33.6%, with a higher percentage in females than in males (40.6% vs 9%). In addition, the prevalence of U. parvum was significantly lower in older patients.

Published
2015

32. Screening for Klebsiella pneumoniae producing carbapenemase (KPC) in Prato (Italy)

Author

Roberto Degl’Innocenti, Mayra Sosa, Patrizia Miglietta, Tamara Brunelli, Antonella Conti, Loredana Ortega De Luna, Alfredo Ruggeri, and Patrizia Casprini

Subjects
Klebsiella pneumoniae, lcsh:QR1-502, polycyclic compounds, Klebsiella pneumoniae, Carbapenemase, KPC, biochemical phenomena, metabolism, and nutrition, Biology, bacterial infections and mycoses, biology.organism_classification, lcsh:Microbiology, Microbiology, Carbapenem resistance
Abstract

In this study, the prevalence of carbapenemase in the area of Prato (Italy), from January 2011 to August 2013, is reported. Samples showing carbapenem resistance were tested for lactamase production with disc diffusion and molecular methods. Totally, 48 out of 1542 patients with K. pneumoniae showed carbapenem resistance (42 KPC 5 MBL and 1 OXA-48).

Published
2014
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33. Use of XpertMTB/RIF for Mycobacterium tuberculosis identification

Author

Patrizia Casprini, Roberto Deg'Innocenti, Alfredo Ruggeri, Daniele Ferri, Antonella Conti, Lorenzo Pellegrini, Elisa Rovinati, and Tamara Brunelli

Subjects
GeneXpert MTB/RIF, Tuberculosis, biology, business.industry, lcsh:QR1-502, biology.organism_classification, medicine.disease, bacterial infections and mycoses, Virology, Stain, PCR, Mycobacterium tuberculosis, Xpert, lcsh:Microbiology, Mycobacterium tuberculosis, Medicine, Identification (biology), business
Abstract

In this study we describe the use of Xpert MTB/RIF to give a rapid answer in case of strong clinical suspicion of tuberculosis and/or positive microscopy slide, from sample or culture, for auramine-rhodamine stain.

Published
2014

34. Prevalence of Clostridium difficile infections in Prato hospital in the years 2010-2011

Author

Roberto Degl’Innocenti, Mayra Sosa, Patrizia Casprini, Patrizia Miglietta, Tamara Brunelli, Loredana Ortega De Luna, Alfredo Ruggeri, and Antonella Conti

Subjects
Bacillus (shape), biology, business.industry, lcsh:QR1-502, General Medicine, Enteric pathogen, Pseudomembranous colitis, Clostridium difficile, biology.organism_classification, Clostridium difficile infections, Virology, lcsh:Microbiology, Microbiology, Clostridium difficile, Infection, Prevalence, Antigen, mental disorders, Medicine, business
Abstract

Clostridium difficile, a Gram positive, spore-forming, anaerobic bacillus, is an important nosocomial enteric pathogen causing diarrhoea and pseudomembranous colitis. Aim of this study was to evaluate the prevalence of Clostridium difficile in Prato Hospital. Stool samples were collected from 1197 patients hospitalized from January 2010 to December 2011. In all the samples the common antigen GDH was investigated and only in samples positive for the antigen the presence of the A and B toxins was investigated. Our results showed that 170/1197 samples (14%) were positive for the antigen, and of these 170 patients, 84 (49%) were found positive also for the toxins. In addition the percentage of samples positive for toxins was higher in 2010 (8.6%) than in 2011 (5.9%).

Published
2013
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35. MALDI-TOF mass spectrometry for the rapid identification of aetiological agents of sepsis

Author

Tamara Brunelli, Roberto Degl’Innocenti, Mayra Sosa, Loredana Ortega De Luna, Antonella Conti, Patrizia Miglietta, and Patrizia Casprini

Subjects
food.ingredient, business.industry, lcsh:QR1-502, Becton dickinson, Sepsis, Mass-spectrometry, Blood cultures identification, General Medicine, Bacterial growth, Antimicrobial, medicine.disease, Vial, lcsh:Microbiology, Microbiology, law.invention, Sepsis, Gram staining, food, law, medicine, Agar, business, Vacutainer
Abstract

Introduction: The MALDI-TOF has recently become part of the methods of microbiological investigation in many laboratories of bacteriology with advantages both practical and economical.The use of this technique for the rapid identification of the causative agents of sepsis is of strategic importance to the ability to provide the clinician with useful information for a prompt and rapid establishment of an empirical antimicrobial “targeted” therapy. Methods: It was tested a total of 343 positive blood culture bottles from 211 patients. The samples after collection were incubated in the BACTEC FX (Becton Dickinson, USA). From these bottles were taken a few milliliters of broth culture and transferred into a vacutainer tube containing gel. This was centrifuged, the supernatant was decanted, and finally recovered the bacterial suspension on the gel. With micro-organisms recovered in this way, after several washes with distilled water, was prepared a slide for microscopic examination with Gram stain, and a plate for mass spectrometry (MS-Vitek, bioMérieux, France).Then, the same samples were inoculated on solid agar media according to the protocol in use in our laboratory.The next day was checked the possible bacterial growth on solid media; we then proceeded to the identification of the colonies by Vitek MS and / or with the system Vitek2 (bioMérieux, France). Results: 258 (75.2%) positive vials show concordant results between direct identification and identification after growth on agar. For 83 (24.2%) positive bottles there has been full compliance with the microscopic examination but not with culture. In particular, two bottles (0.6%) have given complete discordance between the direct identification and that after growth. Conclusions: The protocol we use for the direct identification of organisms responsible for sepsis, directly on positive bottles, seems to be a quick and inexpensive procedure, which in less than 60 minutes can give valuable feedback to the clinician.

Published
2013
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36. Detection of T. vaginalis,M. hominis,M. genitalium, C. trachomatis, N. gonorrhoeae and U. urealyticum using Multiplex PCR

Author

Roberto Degl’Innocenti, Patrizia Miglietta, Stefania Apolito, Loredana Ortega De Luna, Elisa Rovinati, Patrizia Casprini, Tamara Brunelli, and Antonella Conti

Subjects
biology, lcsh:QR1-502, General Medicine, Mycoplasma hominis, medicine.disease_cause, biology.organism_classification, urologic and male genital diseases, Virology, lcsh:Microbiology, Microbiology, Multiplex polymerase chain reaction, medicine, Neisseria gonorrhoeae, Trichomonas vaginalis, multiplex PCR, pathogens, sexually transmitted diseases, Mycoplasma genitalium, Chlamydia trachomatis, Pathogen, Ureaplasma urealyticum
Abstract

Intoduction. The sexually transmitted diseases include a large group of infections affecting both the sexes. In this study we evaluated the prevalence of Trichomonas vaginalis, Mycoplasma hominis, Mycoplasma genitalium, Chlamydia trachomatis, Neisseria gonorrhoeae and Ureaplasma urealyticum in the Prato area during the period September 2010 – July 2011. Methods.We analysed different kind of samples (urine, endocervical swabs, urethral swabs, seminal fluids) from hospitalized patients or referred to the Prato clinic subjects.The DNA was obtained using EZ1-DNA extraction kit and EZ1 instrument.The DNA was then amplified using the Seeplex STD6 kit (Seegene, Korea), identifying multiple pathogens simultaneously (T. vaginalis, M. hominis, M. genitalium, C. trachomatis, N. gonorrhoeae e U. urealyticum). The revelation was performed by electrophoresis on microchip (instrument Multina, Shimadzu, Japan). Results. 1136 samples from Italian and foreign patients were examined: 876 were endocervical swabs (77%), 103 urethral swabs (9%), 103 seminal fluids (9%), and 54 urines (5%). The number of females was higher than males [894 (78.7%) vs 242 (21.3%)]; the mean age of females was 37.0±11.6 years, whereas that of males was 41.5 ±12.63 years.The prevalence of urogenital pathogens was: 15 positive samples for T. vaginalis (1.3%), 56 for M. hominis (4.9%), 13 for M. genitalium (1.1%), 28 for C. trachomatis (2.5%), 8 for N. gonorrhoeae (0.7%) and 87 for U. urealyticum (7.7%).Among all positive, 25 subjects were positive for more than one pathogen and in particular: one was positive for the presence of 4 pathogens, five presented 3 pathogens simultaneously and the remaining nineteen for 2 pathogens. Conclusions. This study provides data on the prevalence of sexually transmitted diseases in the hospital of Prato.

Published
2013

37. Use of Maldi-Tof Mass spectrometry in direct microorganism identification in clinical laboratories

Author

Antonella Conti, Roberto Degl’Innocenti, Tamara Brunelli, and Patrizia Casprini

Subjects
MALDI-TOF, spectrometry, identification, microorganism, bacteria, Chromatography, Chemistry, Microorganism, lcsh:QR1-502, General Medicine, Mass spectrometry, lcsh:Microbiology, Ion, Matrix (chemical analysis), Time of flight, Biological specimen, Ionization, Centrifugation
Abstract

Mass Spectrometry is an old technique that has recently been introduced in the clinical microbiology laboratory as Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS). MALDI is a soft ionization technique used in mass spectrometry that allows the analysis of biomolecules and large organic molecules which tend to be fragile and fragment when ionized.To obtain ions biological specimens are mixed with a matrix which specifically absorbs the ionization source (a laser beam). The high energy impact is followed by the formation of ions which are extract through an elastic field, focussed and detected as mass/charge (m/z) spectrum.The differences between ions are seen with TOF, a revelation system that relates the time of flight of a ion to the charge/mass value: ion with a higher m/z have are slower (a bigger time of flight) than ions with lower m/z. MALDI-TOF MS, in clinical microbiology laboratory, is used to identify bacteria and fungi directly from samples. The identification of microorganisms can be performed directly from body fluids (e.g. urine, blood culture, after centrifugation and recovery of microorganisms) or from colonies (after cultivation). The rapidity of identification is of great importance in blood cultures. Positive cultures with one microorganism are processed in a different way than those with more than one microorganism. In positive monomicrobial cultures, after separation of microbs from blood cells,we can perform an immediate identification with MALDI-TOF MS that we can communicate to the clinician, and that gives indication to perform the correct antibiogram. Major problems are present when more than one microorganism are in the culture: in this case we have to use the method of subcultivation and then the identification with mass-spectrometry can be performed. MALDI-TOF MS is a rapid, reliable and low cost technique, that can identify a growing number of microorganisms. This technique can significantly reduce the time to give an identification, that is of great importance, particularly in blood culture, where the success of therapy is strictly linked to its early beginning.

Published
2010

38. Possible sources of error in the calculation of ferrokinetic parameters using Ricketts' triexponential model

Author

G. Zatelli, Cesare Gori, Patrizia Casprini, Paolo Ferri, and Alberto Grossi

Subjects
Iron Radioisotopes, Mathematical model, Calculation error, Iron, Anemia, General Medicine, Models, Biological, Biological materials, Exponential function, Kinetics, Primary Myelofibrosis, Statistics, Applied mathematics, Humans, Radiology, Nuclear Medicine and imaging, Iron Isotopes, Sources of error, Constant (mathematics), Mathematics
Abstract

The triexponential model developed by Ricketts et al. in 1975 for the calculation of ferrokinetic parameters has been widely used to obtain quantitative information about effective and ineffective erythropoiesis. However, a calculation error in one of the formulae of this method may have a considerable effect on those results which depend on the value of the third exponential constant, gamma 3. Moreover, the analysis of plasma 59Fe activity needs to be based on good counting statistics, which lambda-counting seldom provides after the first 24 h; therefore, 59Fe beta-counting is considered to be the best method.

Published
1984

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