Nuova ricerca

ALFONSO METELLO FRANCESCO ANDRETTA

Docente a contratto
Dipartimento di Ingegneria "Enzo Ferrari"

Home | Curriculum(pdf) | Didattica |


Pubblicazioni

2021 - A methodology for designing short-term stationary air quality campaigns with mobile laboratories using different possible allocation criteria [Articolo su rivista]
Marinello, S.; Andretta, M.; Lucialli, P.; Pollini, E.; Righi, Serena
abstract

Air quality monitoring and control are key issues for environmental assessment and management in order to protect public health and the environment. Local and central authorities have developed strategies and tools to manage environmental protection, which, for air quality, consist of monitoring networks with fixed and portable instrumentation and mathematical models. This study develops a methodology for designing short-term air quality campaigns with mobile laboratories (laboratories fully housed within or transported by a vehicle and maintained in a fixed location for a period of time) as a decision support system for environmental management and protection authorities. In particular, the study provides a methodology to identify: (i) the most representative locations to place mobile laboratories and (ii) the best time period to carry out the measurements in the case of short-term air quality campaigns. The approach integrates atmospheric dispersion models and allocation algorithms specifically developed for optimizing the measuring campaigns. The methodology is organized in two phases, each of them divided into several steps. Fourteen allocation algorithms dedicated to three type of receptors (population, vegetation and physical cultural heritage) have been proposed. The methodology has been applied to four short-term air quality campaigns in the Emilia-Romagna region.

2021 - Association of toll-like receptor 7 variants with life-threatening COVID-19 disease in males: Findings from a nested case-control study [Articolo su rivista]
Fallerini, C.; Daga, S.; Mantovani, S.; Benetti, E.; Picchiotti, N.; Francisci, D.; Paciosi, F.; Schiaroli, E.; Baldassarri, M.; Fava, F.; Palmieri, M.; Ludovisi, S.; Castelli, F.; Quiros-Roldan, E.; Vaghi, M.; Rusconi, S.; Siano, M.; Bandini, M.; Spiga, O.; Capitani, K.; Furini, S.; Mari, F.; Renieri, A.; Mondelli, M. U.; Frullanti, E.; Valentino, F.; Doddato, G.; Giliberti, A.; Tita, R.; Amitrano, S.; Bruttini, M.; Croci, S.; Meloni, I.; Mencarelli, M. A.; Rizzo, C. L.; Pinto, A. M.; Sarno, L. D.; Beligni, G.; Tommasi, A.; Iuso, N.; Montagnani, F.; Fabbiani, M.; Rossetti, B.; Zanelli, G.; Bargagli, E.; Bergantini, L.; D'Alessandro, M.; Cameli, P.; Bennett, D.; Anedda, F.; Marcantonio, S.; Scolletta, S.; Franchi, F.; Mazzei, M. A.; Guerrini, S.; Conticini, E.; Cantarini, L.; Frediani, B.; Tacconi, D.; Spertilli, C.; Feri, M.; Donati, A.; Scala, R.; Guidelli, L.; Spargi, G.; Corridi, M.; Nencioni, C.; Croci, L.; Caldarelli, G. P.; Spagnesi, M.; Romani, D.; Piacentini, P.; Desanctis, E.; Cappelli, S.; Canaccini, A.; Verzuri, A.; Anemoli, V.; Ognibene, A.; D'Arminio Monforte, A.; Miraglia, F. G.; Girardis, M.; Venturelli, S.; Busani, S.; Cossarizza, A.; Antinori, A.; Vergori, A.; Emiliozzi, A.; Gabrieli, A.; Riva, A.; Scotton, P. G.; Andretta, F.; Panese, S.; Scaggiante, R.; Gatti, F.; Parisi, S. G.; Baratti, S.; Antoni, M. D.; Monica, M. D.; Piscopo, C.; Capasso, M.; Russo, R.; Andolfo, I.; Iolascon, A.; Fiorentino, G.; Carella, M.; Castori, M.; Merla, G.; Squeo, G. M.; Aucella, F.; Raggi, P.; Marciano, C.; Perna, R.; Bassetti, M.; Biagio, A. D.; Sanguinetti, M.; Masucci, L.; Valente, S.; Mandala, M.; Giorli, A.; Salerni, L.; Zucchi, P.; Parravicini, P.; Menatti, E.; Trotta, T.; Giannattasio, F.; Coiro, G.; Lena, F.; Coviello, D. A.; Mussini, C.; Bosio, G.; Martinelli, E.; Mancarella, S.; Tavecchia, L.; Gori, M.; Crotti, L.; Parati, G.; Gabbi, C.; Zanella, I.; Rizzi, M.; Maggiolo, F.; Ripamonti, D.; Bachetti, T.; Rovere, M. T. L.; Sarzi-Braga, S.; Bussotti, M.; Chiariello, M.; Belli, M. A.; Dei, S.
abstract

Background: Recently, loss-of-function variants in TLR7 were identified in two families in which COVID-19 segregates like an X-linked recessive disorder environmentally conditioned by SARS-CoV-2. We investigated whether the two families represent the tip of the iceberg of a subset of COVID-19 male patients. Methods: This is a nested case-control study in which we compared male participants with extreme phenotype selected from the Italian GEN-COVID cohort of SARS-CoV-2-infected participants (<60 y, 79 severe cases versus 77 control cases). We applied the LASSO Logistic Regression analysis, considering only rare variants on young male subsets with extreme phenotype, picking up TLR7 as the most important susceptibility gene.

2021 - Employing a systematic approach to biobanking and analyzing clinical and genetic data for advancing COVID-19 research [Articolo su rivista]
Daga, S.; Fallerini, C.; Baldassarri, M.; Fava, F.; Valentino, F.; Doddato, G.; Benetti, E.; Furini, S.; Giliberti, A.; Tita, R.; Amitrano, S.; Bruttini, M.; Meloni, I.; Pinto, A. M.; Raimondi, F.; Stella, A.; Biscarini, F.; Picchiotti, N.; Gori, M.; Pinoli, P.; Ceri, S.; Sanarico, M.; Crawley, F. P.; Birolo, G.; Montagnani, F.; Di Sarno, L.; Tommasi, A.; Palmieri, M.; Croci, S.; Emiliozzi, A.; Fabbiani, M.; Rossetti, B.; Zanelli, G.; Bergantini, L.; D'Alessandro, M.; Cameli, P.; Bennet, D.; Anedda, F.; Marcantonio, S.; Scolletta, S.; Franchi, F.; Mazzei, M. A.; Guerrini, S.; Conticini, E.; Cantarini, L.; Frediani, B.; Tacconi, D.; Spertilli, C.; Feri, M.; Donati, A.; Scala, R.; Guidelli, L.; Spargi, G.; Corridi, M.; Nencioni, C.; Croci, L.; Caldarelli, G. P.; Spagnesi, M.; Piacentini, P.; Bandini, M.; Desanctis, E.; Cappelli, S.; Canaccini, A.; Verzuri, A.; Anemoli, V.; Ognibene, A.; Vaghi, M.; D'Arminio Monforte, A.; Merlini, E.; Mondelli, M. U.; Mantovani, S.; Ludovisi, S.; Girardis, M.; Venturelli, S.; Sita, M.; Cossarizza, A.; Antinori, A.; Vergori, A.; Rusconi, S.; Siano, M.; Gabrieli, A.; Riva, A.; Francisci, D.; Schiaroli, E.; Scotton, P. G.; Andretta, F.; Panese, S.; Scaggiante, R.; Gatti, F.; Parisi, S. G.; Castelli, F.; Quiros-Roldan, M. E.; Magro, P.; Zanella, I.; Della Monica, M.; Piscopo, C.; Capasso, M.; Russo, R.; Andolfo, I.; Iolascon, A.; Fiorentino, G.; Carella, M.; Castori, M.; Merla, G.; Aucella, F.; Raggi, P.; Marciano, C.; Perna, R.; Bassetti, M.; Di Biagio, A.; Sanguinetti, M.; Masucci, L.; Gabbi, C.; Valente, S.; Meloni, I.; Mencarelli, M. A.; Rizzo, C. L.; Bargagli, E.; Mandala, M.; Giorli, A.; Salerni, L.; Zucchi, P.; Parravicini, P.; Menatti, E.; Baratti, S.; Trotta, T.; Giannattasio, F.; Coiro, G.; Lena, F.; Coviello, D. A.; Mussini, C.; Bosio, G.; Mancarella, S.; Tavecchia, L.; Renieri, A.; Mari, F.; Frullanti, E.
abstract

Within the GEN-COVID Multicenter Study, biospecimens from more than 1000 SARS-CoV-2 positive individuals have thus far been collected in the GEN-COVID Biobank (GCB). Sample types include whole blood, plasma, serum, leukocytes, and DNA. The GCB links samples to detailed clinical data available in the GEN-COVID Patient Registry (GCPR). It includes hospitalized patients (74.25%), broken down into intubated, treated by CPAP-biPAP, treated with O2 supplementation, and without respiratory support (9.5%, 18.4%, 31.55% and 14.8, respectively); and non-hospitalized subjects (25.75%), either pauci- or asymptomatic. More than 150 clinical patient-level data fields have been collected and binarized for further statistics according to the organs/systems primarily affected by COVID-19: heart, liver, pancreas, kidney, chemosensors, innate or adaptive immunity, and clotting system. Hierarchical clustering analysis identified five main clinical categories: (1) severe multisystemic failure with either thromboembolic or pancreatic variant; (2) cytokine storm type, either severe with liver involvement or moderate; (3) moderate heart type, either with or without liver damage; (4) moderate multisystemic involvement, either with or without liver damage; (5) mild, either with or without hyposmia. GCB and GCPR are further linked to the GCGDR, which includes data from whole-exome sequencing and high-density SNP genotyping. The data are available for sharing through the Network for Italian Genomes, found within the COVID-19 dedicated section. The study objective is to systematize this comprehensive data collection and begin identifying multi-organ involvement in COVID-19, defining genetic parameters for infection susceptibility within the population, and mapping genetically COVID-19 severity and clinical complexity among patients.

2020 - ACE2 gene variants may underlie interindividual variability and susceptibility to COVID-19 in the Italian population [Articolo su rivista]
Benetti, E.; Tita, R.; Spiga, O.; Ciolfi, A.; Birolo, G.; Bruselles, A.; Doddato, G.; Giliberti, A.; Marconi, C.; Musacchia, F.; Pippucci, T.; Torella, A.; Trezza, A.; Valentino, F.; Baldassarri, M.; Brusco, A.; Asselta, R.; Bruttini, M.; Furini, S.; Seri, M.; Nigro, V.; Matullo, G.; Tartaglia, M.; Mari, F.; Elisa, F.; Chiara, F.; Sergio, D.; Susanna, C.; Sara, A.; Francesca, F.; Montagnani, F.; Di Sarno, L.; Tommasi, A.; Palmieri, M.; Emiliozzi, A.; Fabbiani, M.; Rossetti, B.; Zanelli, G.; Bergantini, L.; D'Alessandro, M.; Cameli, P.; Bennet, D.; Anedda, F.; Marcantonio, S.; Scolletta, S.; Franchi, F.; Mazzei, M. A.; Conticini, E.; Cantarini, L.; Frediani, B.; Tacconi, D.; Feri, M.; Scala, R.; Spargi, G.; Corridi, M.; Nencioni, C.; Caldarelli, G. P.; Spagnesi, M.; Piacentini, P.; Bandini, M.; Desanctis, E.; Canaccini, A.; Spertilli, C.; Donati, A.; Guidelli, L.; Croci, L.; Verzuri, A.; Anemoli, V.; Ognibene, A.; Vaghi, M.; D'Arminio Monforte, A.; Merlini, E.; Mondelli, M. U.; Mantovani, S.; Ludovisi, S.; Girardis, M.; Venturelli, S.; Sita, M.; Cossarizza, A.; Antinori, A.; Vergori, A.; Rusconi, S.; Siano, M.; Gabrieli, A.; Riva, A.; Francisci, D.; Schiaroli, E.; Scotton, P. G.; Andretta, F.; Panese, S.; Scaggiante, R.; Parisi, S. G.; Castelli, F.; Quiros-Roldan, M. E.; Magro, P.; Minardi, C.; Castelli, D.; Polesini, I.; Della Monica, M.; Piscopo, C.; Capasso, M.; Russo, R.; Andolfo, I.; Iolascon, A.; Carella, M.; Castori, M.; Merla, G.; Aucella, F.; Raggi, P.; Marciano, C.; Perna, R.; Bassetti, M.; Di Biagio, A.; Sanguinetti, M.; Masucci, L.; Gabbi, C.; Valente, S.; Guerrini, S.; Meloni, I.; Mencarelli, M. A.; Rizzo, C. L.; Bargagli, E.; Mandala, M.; Giorli, A.; Salerni, L.; Fiorentino, G.; Zucchi, P.; Parravicini, P.; Menatti, E.; Baratti, S.; Trotta, T.; Giannattasio, F.; Coiro, G.; Lena, F.; Coviello, D. A.; Mussini, C.; Renieri, A.; Pinto, A. M.
abstract

In December 2019, an initial cluster of interstitial bilateral pneumonia emerged in Wuhan, China. A human-to-human transmission was assumed and a previously unrecognized entity, termed coronavirus disease-19 (COVID-19) due to a novel coronavirus (SARS-CoV-2) was described. The infection has rapidly spread out all over the world and Italy has been the first European country experiencing the endemic wave with unexpected clinical severity in comparison with Asian countries. It has been shown that SARS-CoV-2 utilizes angiotensin converting enzyme 2 (ACE2) as host receptor and host proteases for cell surface binding and internalization. Thus, a predisposing genetic background can give reason for interindividual disease susceptibility and/or severity. Taking advantage of the Network of Italian Genomes (NIG), here we mined whole-exome sequencing data of 6930 Italian control individuals from five different centers looking for ACE2 variants. A number of variants with a potential impact on protein stability were identified. Among these, three more common missense changes, p.(Asn720Asp), p.(Lys26Arg), and p.(Gly211Arg) were predicted to interfere with protein structure and stabilization. Rare variants likely interfering with the internalization process, namely p.(Leu351Val) and p.(Pro389His), predicted to interfere with SARS-CoV-2 spike protein binding, were also observed. Comparison of ACE2 WES data between a cohort of 131 patients and 258 controls allowed identifying a statistically significant (P value < 0.029) higher allelic variability in controls compared with patients. These findings suggest that a predisposing genetic background may contribute to the observed interindividual clinical variability associated with COVID-19, allowing an evidence-based risk assessment leading to personalized preventive measures and therapeutic options.

2020 - Clinical and molecular characterization of COVID-19 hospitalized patients [Articolo su rivista]
Benetti, E.; Giliberti, A.; Emiliozzi, A.; Valentino, F.; Bergantini, L.; Fallerini, C.; Anedda, F.; Amitrano, S.; Conticini, E.; Tita, R.; D'Alessandro, M.; Fava, F.; Marcantonio, S.; Baldassarri, M.; Bruttini, M.; Mazzei, M. A.; Montagnani, F.; Mandala, M.; Bargagli, E.; Furini, S.; Renieri, A.; Mari, F.; Doddato, G.; Croci, S.; Di Sarno, L.; Tommasi, A.; Daga, S.; Palmieri, M.; Fabbiani, M.; Rossetti, B.; Zanelli, G.; Cameli, P.; Bennett, D.; Scolletta, S.; Franchi, F.; Cantarini, L.; Frediani, B.; Tacconi, D.; Spertilli, C.; Feri, M.; Donati, A.; Scala, R.; Guidelli, L.; Ognibene, A.; Spargi, G.; Corridi, M.; Nencioni, C.; Croci, L.; Caldarelli, G. P.; Spagnesi, M.; Piacentini, P.; Canaccini, A.; Verzuri, A.; Anemoli, V.; Vaghi, M.; Monforte, A. D.; Merlini, E.; Mondelli, M. U.; Mantovani, S.; Ludovisi, S.; Girardis, M.; Venturelli, S.; Cossarizza, A.; Antinori, A.; Vergori, A.; Rusconi, S.; Siano, M.; Gabrieli, A.; Francisci, D.; Schiaroli, E.; Scotton, P. G.; Andretta, F.; Panese, S.; Scaggiante, R.; Parisi, S. G.; Castelli, F.; Roldan, M. E. Q.; Magro, P.; Minardi, C.; della Monica, M.; Piscopo, C.; Capasso, M.; Carella, M.; Castori, M.; Merla, G.; Aucella, F.; Raggi, P.; Bassetti, M.; Di Biagio, A.; Sanguinetti, M.; Masucci, L.; Gabbi, C.; Valente, S.; Guerrini, S.; Frullanti, E.; Meloni, I.; Mencarelli, M. A.; Rizzo, C. L.; Pinto, A. M.
abstract

Clinical and molecular characterization by Whole Exome Sequencing (WES) is reported in 35 COVID-19 patients attending the University Hospital in Siena, Italy, from April 7 to May 7, 2020. Eighty percent of patients required respiratory assistance, half of them being on mechanical ventilation. Fiftyone percent had hepatic involvement and hyposmia was ascertained in 3 patients. Searching for common genes by collapsing methods against 150 WES of controls of the Italian population failed to give straightforward statistically significant results with the exception of two genes. This result is not unexpected since we are facing the most challenging common disorder triggered by environmental factors with a strong underlying heritability (50%). The lesson learned from Autism-Spectrum-Disorders prompted us to re-analyse the cohort treating each patient as an independent case, following a Mendelian-like model. We identified for each patient an average of 2.5 pathogenic mutations involved in virus infection susceptibility and pinpointing to one or more rare disorder(s). To our knowledge, this is the first report on WES and COVID-19. Our results suggest a combined model for COVID-19 susceptibility with a number of common susceptibility genes which represent the favorite background in which additional host private mutations may determine disease progression.

2015 - Risk of hospitalization for heart failure in patients with type 2 diabetes newly treated with DPP-4 inhibitors or other oral glucose-lowering medications: A retrospective registry study on 127,555 patients from the Nationwide OsMed Health-DB Database [Articolo su rivista]
Fadini, G. P.; Avogaro, A.; Degli Esposti, L.; Russo, P.; Saragoni, S.; Buda, S.; Rosano, G.; Pecorelli, S.; Pani, L.; Martinetti, S.; Mero, P.; Raeli, L.; Migliazza, S.; Dellagiovanna, M.; Cerra, C.; Gambera, M.; Piccinelli, R.; Zambetti, M.; Atzeni, F.; Valsecchi, V.; Deluca, P.; Scopinaro, E.; Moltoni, D.; Pini, E.; Leoni, O.; Oria, C.; Papagni, M.; Nosetti, G.; Caldiroli, E.; Moser, V.; Roni, R.; Polverino, A.; Bovo, C.; Mezzalira, L.; Andretta, M.; Trentin, L.; Palcic, S.; Pettinelli, A.; Arbo, A.; Bertola, A.; Capparoni, G.; Cattaruzzi, C.; Marcuzzo, L.; Rosa, F. V.; Basso, B.; Saglietto, M.; Delucis, S.; Prioli, M.; Filippi, R.; Coccini, A.; Ghia, M.; Sanfelici, F.; Radici, S.; Scanavacca, P.; Campi, A.; Bianchi, S.; Verzola, A.; Morini, M.; Borsari, M.; Danielli, A.; Dal Maso, M.; Marsiglia, B.; Vujovic, B.; Pisani, M.; Bonini, P.; Lena, F.; Aletti, P.; Marcobelli, A.; Sagratella, S.; Fratini, S.; Bartolini, F.; Riccioni, G.; Meneghini, A.; Di Turi, R.; Fano, V.; Blasi, A.; Pagnozzi, E.; Quintavalle, G.; D'Avenia, P.; De Matthaeis, M. C.; Ferrante, F.; Crescenzi, S.; Marziale, L.; Venditti, P.; Bianchi, C.; Senesi, I.; Baci, R.; De Carlo, I.; Lavalle, A.; Trofa, G.; Marcello, G.; Pagliaro, C.; Troncone, C.; Farina, G.; Tari, M. G.; Motola, G.; De Luca, F.; Saltarelli, M. L.; Granieri, C.; Vulnera, M.; Palumbo, L.; La Viola, F.; Florio, L.; De Francesco, A. E.; Costantino, D.; De Francesco, A. E.; Rapisarda, F.; Lazzaro, P. L.; Pastorello, M.; Parlli, M.; Visconti, M.; Uomo, I.; Sanna, P.; Lombardo, F.
abstract

Aims Oral glucose-lowering medications are associated with excess risk of heart failure (HF). Given the absence of comparative data among drug classes, we performed a retrospective study in 32 Health Services of 16 Italian regions accounting for a population of 18 million individuals, to assess the association between HF risk and use of sulphonylureas, DPP-4i, and glitazones. Methods and results We extracted data on patients with type 2 diabetes who initiated treatment with DPP-4i, thiazolidinediones, or sulphonylureas alone or in combination with metformin during an accrual time of 2 years. The endpoint was hospitalization for HF (HHF) occurring after the first 6 months of therapy, and the observation was extended for up to 4 years. A total of 127 555 patients were included, of whom 14.3% were on DPP-4i, 72.5% on sulphonylurea, 13.2% on thiazolidinediones, with average 70.7% being on metformin as combination therapy. Patients in the three groups differed significantly for baseline characteristics: age, sex, Charlson index, concurrent medications, and previous cardiovascular events. During an average 2.6-year follow-up, after adjusting for measured confounders, use of DPP-4i was associated with a reduced risk of HHF compared with sulphonylureas [hazard ratio (HR) 0.78; 95% confidence interval (CI) 0.62-0.97; P = 0.026]. After propensity matching, the analysis was restricted to 39 465 patients, and the use of DPP-4i was still associated with a lower risk of HHF (HR 0.70; 95% CI 0.52-0.94; P = 0.018). Conclusion In a very large observational study, the use of DPP-4i was associated with a reduced risk of HHF when compared with sulphonylureas.