Search

Your search keyword '"Minnai F"' showing total 14 results
Start Over Author "Minnai F"
14 results on '"Minnai F"'

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

Author

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, Crotti, L, 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, Crotti, Lia, 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, Crotti, L, 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, and Crotti, Lia

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.

Published
2022

2. 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, May, P, Alldis, Z, Mitchelmore, O, Bowles, R, Easthorpe, A, Bibi, F, Lancoma-Malcolm, I, Gurasashvili, J, Pheby, J, Shiel, J, Bolton, M, Patel, M, Taylor, M, Zongo, O, Ebano, P, Harding, P, Astin-Chamberlain, R, Choudhury, Y, Cox, A, Kallon, D, Burton, M, Hall, R, Blowes, S, Prime, Z, Biddle, J, Prysyazhna, O, Newman, T, Tierney, C, Kassam, J, Shankar-Hari, M, Ostermann, M, Campos, S, Bociek, A, Lim, R, Grau, N, O Jones, T, Whitton, C, Marotti, M, Arbane, G, Bonner, S, Hugill, K, Reid, J, Welters, I, Waugh, V, Williams, K, Shaw, D, J Fernandez Roman, M Lopez Martinez, Johnson, E, Waite, A, Johnson, B, Hamilton, O, Mulla, S, Mcphail, M, Smith, J, K Baillie, J, Barclay, L, Hope, D, Mcculloch, C, Mcquillan, L, Clark, S, Singleton, J, Priestley, K, Rea, N, Callaghan, M, Campbell, R, Andrew, G, Marshall, L, Mckechnie, S, Hutton, P, Bashyal, A, Davidson, N, Summers, C, Polgarova, P, Stroud, K, Pathan, N, Elston, K, Agrawal, S, Battle, C, Newey, L, Rees, T, Harford, R, Brinkworth, E, Williams, M, Murphy, C, White, I, Croft, M, Bandla, N, Gellamucho, M, Tomlinson, J, Turner, H, Davies, M, Quinn, A, Hussain, I, Thompson, C, Parker, H, Bradley, R, Griffiths, R, Scriven, J, Gill, J, Puxty, A, Cathcart, S, Salutous, D, Turner, L, Duffy, K, Puxty, K, Joseph, A, Herdman-Grant, R, Simms, R, Swain, A, Naranjo, A, Crowe, R, Sollesta, K, Loveridge, A, Baptista, D, Morino, E, Davey, M, Golden, D, Jones, J, J Moreno Cuesta, Haldeos, A, Bakthavatsalam, D, Vincent, R, Elhassan, M, Xavier, K, Ganesan, A, Purohit, D, Abdelrazik, M, Morgan, J, Akeroyd, L, Bano, S, Warren, D, Bromley, M, Sellick, K, Gurr, L, Wilkinson, B, Nagarajan, V, Szedlak, P, Cupitt, J, Stoddard, E, Benham, L, Preston, S, Slawson, N, Bradshaw, Z, Brown, J, Caswell, M, Smelling, Bamford, P, Faulkner, M, Cawley, K, Jeffrey, H, London, E, Sainsbury, H, Nagra, I, Nasir, F, Dunmore, Ce, Jones, R, Abraheem, A, Al-Moasseb, M, Girach, R, Brantwood, C, Alexander, P, Bradley-Potts, J, Allen, S, Felton, T, Manna, S, Farnell-Ward, S, Leaver, S, Queiroz, J, Maccacari, E, Dawson, D, C Castro Delgado, R Pepermans Saluzzio, Ezeobu, O, Ding, L, Sicat, C, Kanu, R, Durrant, G, Texeira, J, Harrison, A, Samakomva, T, Willis, H, Hopkins, B, Thrasyvoulou, L, Jackson, M, Zaki, A, Tibke, C, Bennett, S, Woodyatt, W, Kent, A, Goodwin, E, Brandwood, C, Clark, R, Smith, L, Rooney, K, Thomson, N, Rodden, N, Hughes, E, Mcglynn, D, Clark, C, Clark, P, Abel, L, Sundaram, R, Gemmell, L, Brett, M, Hornsby, J, Macgoey, P, Price, R, Digby, B, O'Neil, P, Mcconnell, P, Henderson, P, Henderson, S, Sim, M, Kennedy-Hay, S, Mcparland, C, Rooney, L, Baxter, N, Pogson, D, Rose, S, Daly, Z, Brimfield, L, K Phull, M, Hussain, M, Pogreban, T, Rosaroso, L, E Salciute, L Grauslyte, Brealey, D, Wraith, E, Maccallum, N, Bercades, G, Hass, I, Smyth, D, Reyes, A, Martir, G, D Clement, I, Webster, K, Hays, C, Gulati, A, Hodgson, L, Margarson, M, Gomez, R, Baird, Y, Thirlwall, Y, Folkes, L, Butler, A, Meadows, E, Moore, S, Raynard, D, Fox, H, Riddles, L, King, K, Kimber, S, Hobden, G, Mccarthy, A, Cannons, V, Balagosa, I, Chadbourn, I, Gardner, A, Horner, D, Mclaughlanv, D, Charles, B, Proudfoot, N, Marsden, T, L Mc Morrow, Blackledge, B, Pendlebury, J, Harvey, A, Apetri, E, Basikolo, C, Catlow, L, Doonan, R, Knowles, K, Lee, S, Lomas, D, Lyons, C, Perez, J, Poulaka, M, Slaughter, M, Slevin, K, Thomas, V, Walker, D, Harris, J, Drummond, A, Tully, R, Dearden, J, Philbin, J, Munt, S, Rishton, C, O'Connor, G, Mulcahy, M, Dobson, E, Cuttler, J, Edward, M, Rose, A, Sloan, B, Buckley, S, Brooke, H, Smithson, E, Charlesworth, R, Sandu, R, Thirumaran, M, Wagstaff, V, J Cebrian Suarez, Kaliappan, A, Vertue, M, Nicholson, A, Riches, J, Solesbury, A, Kittridge, L, Forsey, M, Maloney, G, Cole, J, Davies, R, Hill, H, Thomas, E, Williams, A, Duffin, D, Player, B, Radhakrishnan, J, Gibson, S, Lyle, A, Mcneela, F, Patel, B, Gummadi, M, Sloane, G, Dormand, N, Salmi, S, Farzad, Z, Cristiano, D, Liyanage, K, Thwaites, V, Varghese, M, Meredith, M, Mills, G, Willson, J, Harrington, K, Lenagh, B, Cawthron, K, Masuko, S, Raithatha, A, Bauchmuller, K, Ahmad, N, Barker, J, Jackson, Y, Kibutu, F, Bird, S, Watson, G, Martin, J, Bevan, E, C Wrey Brown, Trodd, D, English, K, Bell, G, Wilcox, L, Katary, A, Gopal, S, Lake, V, Harris, N, Metherell, S, Radford, E, Moore, F, Bancroft, H, Daglish, J, Sangombe, M, Carmody, M, Rhodes, J, Bellamy, M, Garg, A, Kuravi, A, Virgilio, E, Ranga, P, Butler, J, Botfield, L, Dexter, C, Fletcher, J, Shanmugasundaram, P, Hambrook, G, Burn, I, Manso, K, Thornton, D, Tebbutt, J, Penn, R, Hulme, J, Hussain, S, Maqsood, Z, Joseph, S, Colley, J, Hayes, A, Ahmed, C, Haque, R, Clamp, S, Kumar, R, Purewal, M, Baines, B, Frise, M, Jacques, N, Coles, H, Caterson, J, S Gurung Rai, Brunton, M, Tilney, E, Keating, L, Walden, A, Antcliffe, D, Gordon, A, Templeton, M, Rojo, R, Banach, D, S Sousa Arias, Fernandez, Z, Coghlan, P, Williams, D, Jardine, C, Bewley, J, Sweet, K, Grimmer, L, Johnson, R, Garland, Z, Gumbrill, B, Phillips, C, L Ortiz-Ruiz de Gordoa, Peasgood, E, Tridente, A, K Shuker, S Greer, Lynch, C, Pothecary, C, Roche, L, Deacon, B, Turner, K, Singh, J, G Sera Howe, Paul, P, Gill, M, Wynter, I, Ratnam, V, Shelton, S, Naisbitt, J, Melville, J, Baruah, R, Morrison, S, Mcgregor, A, Parris, V, Mpelembue, M, Srikaran, S, Dennis, C, Sukha, A, Verlande, M, Holding, K, Riches, K, Downes, C, Swan, C, Rostron, A, Roy, A, Woods, L, Cornell, S, Wakinshaw, F, Creagh-Brown, B, Blackman, H, Salberg, A, Smith, E, Donlon, S, Mtuwa, S, Michalak-Glinska, N, Stone, S, Beazley, C, Pristopan, V, Nikitas, N, Lankester, L, Wells, C, S Raj, A, Fletcher, K, Khade, R, Tsinaslanidis, G, Mcmahon, M, Fowler, S, Coventry, T, Stewart, R, Wren, L, Mwaura, E, Mew, L, Scaletta, D, Williams, F, Inweregbu, K, Lancaster, N, Cunningham, M, Daniels, A, Harrison, L, Hope, S, Jones, S, Crew, A, Wray, G, Matthews, J, Crawley, R, Carter, J, Birkinshaw, I, Ingham, J, Scott, Z, Howard, K, Joy, R, Roche, S, Clark, M, Purvis, S, Morrison, A, Strachan, D, Clements, S, Black, K, Parmar, C, Altabaibeh, A, Simpson, K, Mostoles, L, Gilbert, K, L, Ma, Alvaro, A, Thomas, M, Faulkner, B, Worner, R, Hayes, K, Gendall, E, Blakemore, H, Borislavova, B, Goff, E, Vuylsteke, A, Mwaura, L, Zamikula, J, Garner, L, Mitchell, A, Mepham, S, Cagova, L, Fofano, A, Holcombe, H, Praman, K, Szakmany, T, E Heron, A, Cherian, S, Cutler, S, Roynon-Reed, A, Randell, G, Convery, K, K Stammers, D Fottrell-Gould, Hudig, L, Keshet-Price, J, Peters, M, O'Neill, L, Ray, S, Belfield, H, Mchugh, T, Jones, G, Akinkugbe, O, Tomas, A, Abaleke, E, Beech, E, Meghari, H, Yussuf, S, Bamford, A, Hairsine, B, Dooks, E, Farquhar, F, Packham, S, Bates, H, Armstrong, L, Kaye, C, Allan, A, Medhora, J, Liew, J, Botello, A, Anderson, F, Cusack, R, Golding, H, Prager, K, Williams, T, Leggett, S, Golder, K, Male, M, Jones, O, Criste, K, Marani, M, Anumakonda, V, Amin, V, Karthik, K, Kausar, R, Anastasescu, E, Reid, K, Jacqui, M, Hormis, A, Walker, R, Duncan, T, Uriel, A, Ustianowski, A, T-Michael, H, Bruce, M, Connolly, K, Smith, K, Partridge, R, Griffin, D, Mcdonald, M, Muchenje, N, Martin, D, Filipe, H, Eastgate, C, Jackson, C, Gratrix, A, Foster, L, Martinson, V, Stones, E, Caroline, Abernathy, Parkinson, P, Reed, A, Prendergast, C, Rogers, P, Woodruff, M, Shokkar, R, Kaul, S, Barron, A, Collins, C, Beavis, S, Whileman, A, Dale, K, Hawes, J, Pritchard, K, Gascoyne, R, Stevenson, L, Jha, R, Lim, L, Krishnamurthy, V, Parker, R, Turner-Bone, I, Wilding, L, Reddy, A, Whiteley, S, Wilby, E, Howcroft, C, Aspinwall, A, Charlton, S, Ogg, B, Menzies, D, Pugh, R, Allan, E, Lean, R, Davies, F, Easton, J, Qiu, X, Kumar, S, Darlington, K, Houston, G, O'Brien, P, Geary, T, Allan, J, Meikle, A, Hughes, G, Balasubramaniam, M, Latham, S, Mckenna, E, Flanagan, R, Sathe, S, Davies, E, Chablani, M, Kirkby, A, Netherton, K, Archer, S, Yates, B, Ashbrook-Raby, C, Cole, S, Casey, M, Cabrelli, L, Chapman, S, Austin, P, Hutcheon, A, Whyte, C, Almaden-Boyle, C, Pattison, N, Cruz, C, Vochin, A, Kent, H, Thomas, A, Murdoch, S, David, B, Penacerrada, M, Lubimbi, G, Bastion, V, Wulandari, R, Valentine, J, Clarke, D, Serrano-Ruiz, A, Hierons, S, Ramos, L, Demetriou, C, Mitchard, S, White, K, White, N, Pitts, S, Branney, D, Frankham, J, Watters, M, Langton, H, Prout, R, Page, V, Varghes, T, Cowton, A, Kay, A, Potts, K, Birt, M, Kent, M, Wilkinson, A, Jude, E, Turner, V, Savill, H, Mccormick, J, Coulding, M, Siddiqui, S, Mercer, O, Rehman, H, Potla, D, Capps, N, Donaldson, D, Button, H, Martin, T, Hard, K, Agasou, A, Tonks, L, Arden, T, Boyle, P, Carnahan, M, Strickley, J, Adams, C, Childs, D, Rikunenko, R, Leigh, M, Breekes, M, Wilcox, R, Bowes, A, Tiveran, H, Hurford, F, Summers, J, Carter, A, Hussain, Y, Ting, L, Javaid, A, Motherwell, N, Moore, H, Millward, H, Jose, S, Schunki, N, Noakes, A, Clulow, C, Sadera, G, Jacob, R, Jones, C, Blunt, M, Coton, Z, Curgenven, H, S Mohamed Ally, Beaumont, K, Elsaadany, M, Fernandes, K, I Ali Mohamed Ali, Rangarajan, H, Sarathy, V, Selvanayagam, S, Vedage, D, White, M, Smith, M, Truman, N, Chukkambotla, S, Keith, S, Cockerill-Taylor, J, Ryan-Smith, J, Bolton, R, Springle, P, Dykes, J, Thomas, J, Khan, M, T Hijazi, M, Massey, E, Croston, G, Reschreiter, H, Camsooksai, J, Patch, S, Jenkins, S, Humphrey, C, Wadams, B, Bhatia, N, Msiska, M, Adanini, O, Attwood, B, Parsons, P, Tatham, K, Jhanji, S, Black, E, A Dela Rosa, Howle, R, Thomas, B, Bemand, T, Raobaikady, R, Saha, R, Staines, N, Daniel, A, Finn, J, Hutter, J, Doble, P, Shovelton, C, Pawley, C, Kannan, T, Hill, M, Combes, E, Monnery, S, Joefield, T, Popescu, M, Thankachen, M, Oblak, M, Little, J, Mcivor, S, Brady, A, Whittle, H, Prady, H, Chan, R, Ahmed, A, Morris, A, Gibson, C, Gordon, E, Keenan, S, Quinn, H, Benyon, S, Marriott, S, Zitter, L, Park, L, Baines, K, Lyons, M, Holland, M, Keenan, N, Young, M, Garrioch, S, Dawson, J, Tolson, M, Scholefield, B, R, Bi, Richardson, N, Schumacher, N, Cosier, T, Millen, G, Higham, A, Turki, S, Allen, L, Crisp, N, Hazleton, T, Knight, A, Deery, J, Price, C, Turney, S, Tilbey, S, Beranova, E, Wright, D, Georg, L, Twiss, S, Wadd, S, Postlethwaite, K, Gondo, P, Masunda, B, Kayani, A, Hadebe, B, Whiteside, J, Clarke, N, Donnison, P, Trim, F, Leadbitter, I, Butcher, D, O'Sullivan, S, Purewal, B, Bell, S, Rivers', V, O'Leary, R, Birch, J, Collins, E, Anderson, S, Hammerton, K, Andrews, E, Burns, K, Edmond, I, Todd, A, Donnachie, J, Turner, P, Prentice, L, Symon, L, Runciman, N, Auld, F, Halkes, M, Mercer, P, Thornton, L, Debreceni, G, Wilkins, J, Brown, A, Crickmore, V, Subramanian, G, Marshall, R, Jennings, C, Latif, M, Bunni, L, Spivey, M, Bean, S, Burt, K, Linnett, V, Ritzema, J, Sanderson, A, Mccormick, W, Bokhari, M, Kapoor, R, Loader, D, Ayers, A, Harrison, W, North, J, Belagodu, Z, Parasomthy, R, Olufuwa, O, Gherman, A, Fuller, B, Stuart, C, Kelsall, O, Davis, C, Wild, L, Wood, H, Thrush, J, Durie, A, Austin', K, Archer, K, Anderson, P, Vigurs, C, 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
Full Text
View/download PDF

3. A genome-wide association study of European advanced cancer patients treated with opioids identifies regulatory variants on chromosome 20 associated with pain intensity.

Author

Minnai F, Shkodra M, Noci S, Esposito M, Brunelli C, Pigni A, Zecca E, Skorpen F, Klepstad P, Kaasa S, Corli O, Pallotti MC, Maltoni MC, Caraceni AT, and Colombo F

Subjects
Humans, Male, Female, Middle Aged, Aged, Receptors, Opioid genetics, Pain Measurement, Nociceptin Receptor, Europe, Quantitative Trait Loci, Adult, Neoplasms genetics, Neoplasms drug therapy, Genotype, Polymorphism, Single Nucleotide, Cancer Pain drug therapy, Cancer Pain genetics, Genome-Wide Association Study, Analgesics, Opioid therapeutic use
Abstract

Background: Opioids in step III of the WHO analgesic ladder are the standard of care for treating cancer pain. However, a significant minority of patients do not benefit from therapy. Genetics might play a role in predisposing patients to a good or poor response to opioids. Here, we investigated this issue by conducting a genome-wide association study (GWAS)., Methods: We genotyped 2057 European advanced cancer patients treated with morphine, buprenorphine, fentanyl and oxycodone. We carried out a whole-genome regression model (using REGENIE software) between genotypes and the opioid response phenotype, defined as a numerical score measuring patient pain intensity., Results: The GWAS identified five non-coding variants on chromosome 20 with a p-value <5.0 × 10 -8 . For all of them, the minor allele was associated with lower pain intensity. These variants were intronic to the PCMTD2 gene and were 200 kbp downstream of OPRL1, the opioid related nociceptin receptor 1. Notably according to the eQTLGen database, these variants act as expression quantitative trait loci, modulating the expression mainly of PCMTD2 but also of OPRL1. Variants in the same chromosomal region were recently reported to be significantly associated with pain intensity in a GWAS conducted in subjects with different chronic pain conditions., Conclusions: Our results support the role of genetics in the opioid response in advanced cancer patients. Further functional analyses are needed to understand the biological mechanism underlying the observed association and lead to the development of individualized pain treatment plans, ultimately improving the quality of life for cancer patients., Significance Statement: This genome-wide association study on European advanced cancer patients treated with opioids identifies novel regulatory variants on chromosome 20 (near PCMTD2 and OPRL1 genes) associated with pain intensity. These findings enhance our understanding of the genetic basis of opioid response, suggesting new potential markers for opioid efficacy. The study is a significant advancement in pharmacogenomics, providing a robust dataset and new insights into the genetic factors influencing pain intensity, which could lead to personalized cancer pain management., (© 2024 The Author(s). European Journal of Pain published by John Wiley & Sons Ltd on behalf of European Pain Federation ‐ EFIC ®.)

Published
2025
Full Text
View/download PDF

4. Genomic Study in Opioid-Treated Cancer Patients Identifies Variants Associated With Nausea-Vomiting.

Author

Minnai F, Shkodra M, Noci S, Brunelli C, Pigni A, Zecca E, Skorpen F, Klepstad P, Kaasa S, Corli O, Pallotti MC, Maltoni MC, Caraceni AT, and Colombo F

Abstract

Context: Opioids are the mainstay therapy for patients affected by cancer pain. However, about 10%-20% of patients do not benefit from the received analgesic treatment or experience side effects. Genetic variability might account for the variation in individual responses to opioids, both in terms of efficacy and toxicity., Objectives: The aim of this genome-wide association study (GWAS) was to identify genetic markers of opioid toxicity, in terms of nausea-vomiting., Methods: Cancer patients receiving morphine, oxycodone, buprenorphine, and fentanyl were recruited from different European countries. Data about toxicity (nausea-vomiting score, NVS) and other relevant clinical information were collected, as well as genotyping data. Regression analysis between genotypes of 2052 patients and NVS was performed, using appropriate covariates, with REGENIE software., Results: We found 65 variants associated with NVS (P-value < 1.0×10 -5 ). Of note, 14 intronic variants on chromosome 2 were in NPAS2 gene, encoding a circadian transcription factor reported to play a role in another opioid side effect, the alteration of sleep. Some of these variants were previously identified as splicing quantitative trait loci of the NPAS2 gene., Conclusions: This is the first GWAS, performed in more than two thousand individually genotyped patients treated with opioids for cancer pain, that investigated the genetic bases of opioid-induced nausea-vomiting. Although further studies are needed to confirm our findings and to characterize the functional role of the identified variants, our results emphasize the importance of performing large pharmacogenomic studies to identify germline variants associated with opioid response, with the ultimate goal of tailoring cancer pain therapies., (Copyright © 2024 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.)

Published
2025
Full Text
View/download PDF

5. Germline Polymorphisms Associated with Overall Survival in Lung Adenocarcinoma: Genome-Wide Analysis.

Author

Minnai F, Noci S, Esposito M, Schneider MA, Kobinger S, Eichhorn M, Winter H, Hoffmann H, Kriegsmann M, Incarbone MA, Mattioni G, Tosi D, Muley T, Dragani TA, and Colombo F

Abstract

Background/objectives: Lung cancer remains a global health concern, with substantial variation in patient survival. Despite advances in detection and treatment, the genetic basis for the divergent outcomes is not understood. We investigated germline polymorphisms that modulate overall survival in 1464 surgically resected lung adenocarcinoma patients., Methods: A multivariable Cox proportional hazard model was used to assess the association of more than seven million polymorphisms with overall survival at the 60-month follow-up, considering age, sex, pathological stage, decade of surgery and principal components as covariates. Genes in which variants were identified were studied in silico to investigate functional roles., Results: Six germline variants passed the genome-wide significance threshold. These single nucleotide polymorphisms were mapped to non-coding (intronic) regions on chromosomes 2, 3, and 5. The minor alleles of rs13000315, rs151212827, and rs190923216 (chr. 2, 3 and 5, respectively) were found to be independent negative prognostic factors. All six variants have been reported to regulate the expression of nine genes, seven of which are protein-coding, in different tissues. Survival-associated variants on chromosomes 2 and 3 were already reported to regulate the expression of NT5DC2 and NAGK , with high expression associated with the minor alleles. High NT5DC2 and NAGK expression in lung adenocarcinoma tissue was already shown to correlate with poor overall survival., Conclusions: This study highlights a potential regulatory role of the identified polymorphisms in influencing outcome and suggests a mechanistic link between these variants, gene expression regulation, and lung adenocarcinoma prognosis. Validation and functional studies are warranted to elucidate the mechanisms underlying these associations.

Published
2024
Full Text
View/download PDF

6. The Genetic Analysis and Clinical Therapy in Lung Cancer: Current Advances and Future Directions.

Author

Rina A, Maffeo D, Minnai F, Esposito M, Palmieri M, Serio VB, Rosati D, Mari F, Frullanti E, and Colombo F

Abstract

Lung cancer, including both non-small cell lung cancer and small cell lung cancer, remains the leading cause of cancer-related mortality worldwide, representing 18% of the total cancer deaths in 2020. Many patients are identified already at an advanced stage with metastatic disease and have a worsening prognosis. Recent advances in the genetic understanding of lung cancer have opened new avenues for personalized treatments and targeted therapies. This review examines the latest discoveries in the genetics of lung cancer, discusses key biomarkers, and analyzes current clinical therapies based on this genetic information. It will conclude with a discussion of future prospects and potential research directions.

Published
2024
Full Text
View/download PDF

7. Human leukocyte antigen variants associate with BNT162b2 mRNA vaccine response.

Author

Esposito M, Minnai F, Copetti M, Miscio G, Perna R, Piepoli A, De Vincentis G, Benvenuto M, D'Addetta P, Croci S, Baldassarri M, Bruttini M, Fallerini C, Brugnoni R, Cavalcante P, Baggi F, Corsini EMG, Ciusani E, Andreetta F, Dragani TA, Fratelli M, Carella M, Mantegazza RE, Renieri A, and Colombo F

Abstract

Background: Since the beginning of the anti-COVID-19 vaccination campaign, it has become evident that vaccinated subjects exhibit considerable inter-individual variability in the response to the vaccine that could be partly explained by host genetic factors. A recent study reported that the immune response elicited by the Oxford-AstraZeneca vaccine in individuals from the United Kingdom was influenced by a specific allele of the human leukocyte antigen gene HLA-DQB1., Methods: We carried out a genome-wide association study to investigate the genetic determinants of the antibody response to the Pfizer-BioNTech vaccine in an Italian cohort of 1351 subjects recruited in three centers. Linear regressions between normalized antibody levels and genotypes of more than 7 million variants was performed, using sex, age, centers, days between vaccination boost and serological test, and five principal components as covariates. We also analyzed the association between normalized antibody levels and 204 HLA alleles, with the same covariates as above., Results: Our study confirms the involvement of the HLA locus and shows significant associations with variants in HLA-A, HLA-DQA1, and HLA-DQB1 genes. In particular, the HLA-A*03:01 allele is the most significantly associated with serum levels of anti-SARS-CoV-2 antibodies. Other alleles, from both major histocompatibility complex class I and II are significantly associated with antibody levels., Conclusions: These results support the hypothesis that HLA genes modulate the response to Pfizer-BioNTech vaccine and highlight the need for genetic studies in diverse populations and for functional studies aimed to elucidate the relationship between HLA-A*03:01 and CD8+ cell response upon Pfizer-BioNTech vaccination., (© 2024. The Author(s).)

Published
2024
Full Text
View/download PDF

8. A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death.

Author

Minnai F, Biscarini F, Esposito M, Dragani TA, Bujanda L, Rahmouni S, Alarcón-Riquelme ME, Bernardo D, Carnero-Montoro E, Buti M, Zeberg H, Asselta R, Romero-Gómez M, Fernandez-Cadenas I, Fallerini C, Zguro K, Croci S, Baldassarri M, Bruttini M, Furini S, Renieri A, and Colombo F

Subjects
Humans, Genome-Wide Association Study methods, Genetic Predisposition to Disease, SARS-CoV-2, Genotype, COVID-19
Abstract

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10 -8 ) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10 -8 ). A total of 113 variants were associated with survival at P-value < 1.0 × 10 -5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways., (© 2024. The Author(s).)

Published
2024
Full Text
View/download PDF

9. A pilot exome sequencing study suggests that germline variants influence methotrexate-induced toxicities in pediatric patients with localized osteosarcoma.

Author

Minnai F, Noci S, Mangano N, De Cecco L, Meazza C, Terenziani M, Massimino M, and Colombo F

Abstract

Introduction: Osteosarcoma (OS) is a rare pediatric cancer for which therapeutic approaches, including chemotherapy and surgery, show a wide interindividual variability in patient response, both in terms of adverse events and therapy efficacy. There is growing evidence that this individual variable response to therapies is also influenced by inherited genetic variations. However, the results obtained to date in these pediatric cancers have been contradictory and often lack validation in independent series. Additionally, these studies frequently focused only on a limited number of polymorphisms in candidate genes., Methods: In order to identify germline coding variations associated with individual differences in adverse events occurrence in pediatric patients affected by localized OS, we carried out an exome-wide association study in 24 OS patients treated with methotrexate, cisplatin, and doxorubicin, using the SNP-Set (Sequence) Kernel Association Test (SKAT), optimized for small sample size., Results: Gene sets significantly associated (FDR < .05) with neutropenia and hepatotoxicity induced by methotrexate were identified. Some of the identified genes map in loci previously associated with similar phenotypes (e.g., leukocyte count, alkaline phosphatase levels)., Conclusion: Further studies in larger series and with functional characterization of the identified associations are needed; nonetheless, this pilot study prompts the relevance of broadly investigating variants along the whole genome, to identify new potential pharmacogenes, beyond drug metabolism, transport, and receptor candidate genes., (© 2023 The Authors. Pediatric Blood & Cancer published by Wiley Periodicals LLC.)

Published
2023
Full Text
View/download PDF

10. Genetic predisposition to lung adenocarcinoma outcome is a feature already present in patients' noninvolved lung tissue.

Author

Minnai F, Noci S, Chierici M, Cotroneo CE, Bartolini B, Incarbone M, Tosi D, Mattioni G, Jurman G, Dragani TA, and Colombo F

Subjects
Humans, Genetic Predisposition to Disease, Lung pathology, Genotype, Prognosis, Polymorphism, Single Nucleotide, Adenocarcinoma of Lung genetics, Lung Neoplasms genetics, Lung Neoplasms pathology
Abstract

Emerging evidence suggests that the prognosis of patients with lung adenocarcinoma can be determined from germline variants and transcript levels in nontumoral lung tissue. Gene expression data from noninvolved lung tissue of 483 lung adenocarcinoma patients were tested for correlation with overall survival using multivariable Cox proportional hazard and multivariate machine learning models. For genes whose transcript levels are associated with survival, we used genotype data from 414 patients to identify germline variants acting as cis-expression quantitative trait loci (eQTLs). Associations of eQTL variant genotypes with gene expression and survival were tested. Levels of four transcripts were inversely associated with survival by Cox analysis (CLCF1, hazard ratio [HR] = 1.53; CNTNAP1, HR = 2.17; DUSP14, HR = 1.78; and MT1F: HR = 1.40). Machine learning analysis identified a signature of transcripts associated with lung adenocarcinoma outcome that was largely overlapping with the transcripts identified by Cox analysis, including the three most significant genes (CLCF1, CNTNAP1, and DUSP14). Pathway analysis indicated that the signature is enriched for ECM components. We identified 32 cis-eQTLs for CNTNAP1, including 6 with an inverse correlation and 26 with a direct correlation between the number of minor alleles and transcript levels. Of these, all but one were prognostic: the six with an inverse correlation were associated with better prognosis (HR < 1) while the others were associated with worse prognosis. Our findings provide supportive evidence that genetic predisposition to lung adenocarcinoma outcome is a feature already present in patients' noninvolved lung tissue., (© 2022 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.)

Published
2023
Full Text
View/download PDF

11. Gut microbiota composition in colorectal cancer patients is genetically regulated.

Author

Colombo F, Illescas O, Noci S, Minnai F, Pintarelli G, Pettinicchio A, Vannelli A, Sorrentino L, Battaglia L, Cosimelli M, Dragani TA, and Gariboldi M

Subjects
Bacteria genetics, Bacteroides genetics, Faecalibacterium genetics, Humans, RNA, Ribosomal, 16S genetics, Tumor Microenvironment, Colorectal Neoplasms genetics, Colorectal Neoplasms microbiology, Gastrointestinal Microbiome genetics, Microbiota
Abstract

The risk of colorectal cancer (CRC) depends on environmental and genetic factors. Among environmental factors, an imbalance in the gut microbiota can increase CRC risk. Also, microbiota is influenced by host genetics. However, it is not known if germline variants influence CRC development by modulating microbiota composition. We investigated germline variants associated with the abundance of bacterial populations in the normal (non-involved) colorectal mucosa of 93 CRC patients and evaluated their possible role in disease. Using a multivariable linear regression, we assessed the association between germline variants identified by genome wide genotyping and bacteria abundances determined by 16S rRNA gene sequencing. We identified 37 germline variants associated with the abundance of the genera Bacteroides, Ruminococcus, Akkermansia, Faecalibacterium and Gemmiger and with alpha diversity. These variants are correlated with the expression of 58 genes involved in inflammatory responses, cell adhesion, apoptosis and barrier integrity. Genes and bacteria appear to be involved in the same processes. In fact, expression of the pro-inflammatory genes GAL, GSDMD and LY6H was correlated with the abundance of Bacteroides, which has pro-inflammatory properties; abundance of the anti-inflammatory genus Faecalibacterium correlated with expression of KAZN, with barrier-enhancing functions. Both the microbiota composition and local inflammation are regulated, at least partially, by the same germline variants. These variants may regulate the microenvironment in which bacteria grow and predispose to the development of cancer. Identification of these variants is the first step to identifying higher-risk individuals and proposing tailored preventive treatments that increase beneficial bacterial populations., (© 2022. The Author(s).)

Published
2022
Full Text
View/download PDF

12. COVID-19 mortality in Italy varies by patient age, sex and pandemic wave.

Author

Minnai F, De Bellis G, Dragani TA, and Colombo F

Subjects
Aged, Female, Humans, Italy epidemiology, Male, Pandemics, SARS-CoV-2, COVID-19 epidemiology
Abstract

SARS-CoV-2 has caused a worldwide epidemic of enormous proportions, which resulted in different mortality rates in different countries for unknown reasons. We analyzed factors associated with mortality using data from the Italian national database of more than 4 million SARS-CoV-2-positive cases diagnosed between January 2020 and July 2021, including > 415 thousand hospitalized for coronavirus disease-19 (COVID-19) and > 127 thousand deceased. For patients for whom age, sex and date of infection detection were available, we determined the impact of these variables on mortality 30 days after the date of diagnosis or hospitalization. Multivariable weighted Cox analysis showed that each of the analyzed variables independently affected COVID-19 mortality. Specifically, in the overall series, age was the main risk factor for mortality, with HR > 100 in the age groups older than 65 years compared with a reference group of 15-44 years. Male sex presented a two-fold higher risk of death than female sex. Patients infected after the first pandemic wave (i.e. after 30 June 2020) had an approximately threefold lower risk of death than those infected during the first wave. Thus, in a series of all confirmed SARS-CoV-2-infected cases in an entire European nation, elderly age was by far the most significant risk factor for COVID-19 mortality, confirming that protecting the elderly should be a priority in pandemic management. Male sex and being infected during the first wave were additional risk factors associated with COVID-19 mortality., (© 2022. The Author(s).)

Published
2022
Full Text
View/download PDF

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

Author

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 FP, Butler-Laporte G, Richards B, Zeberg H, Lipcsey M, Hultström M, Ludwig KU, Schulte EC, Pairo-Castineira E, Baillie JK, Schmidt A, Frithiof R, Mari F, Renieri A, and Furini S

Subjects
Adult, Aged, Aged, 80 and over, Cohort Studies, Female, Germany, Humans, Italy, Male, Middle Aged, Polymorphism, Single Nucleotide, Quebec, SARS-CoV-2, Sweden, United Kingdom, COVID-19 genetics, COVID-19 physiopathology, Genetic Predisposition to Disease, Phenotype, Severity of Illness Index, Exome Sequencing
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., (© 2021. The Author(s).)

Published
2022
Full Text
View/download PDF

14. The radial expansion of the Diego blood group system polymorphisms in Asia: mark of co-migration with the Mongol conquests.

Author

Petit F, Minnai F, Chiaroni J, Underhill PA, Bailly P, Mazières S, and Costedoat C

Subjects
Asia, Chromosomes, Human, Y genetics, Female, Haplotypes, Humans, Male, Anion Exchange Protein 1, Erythrocyte genetics, Asian People genetics, Human Migration, Polymorphism, Genetic
Abstract

Red cell polymorphisms can provide evidence of human migration and adaptation patterns. In Eurasia, the distribution of Diego blood group system polymorphisms remains unaddressed. To shed light on the dispersal of the Di a antigen, we performed analyses of correlations between the frequencies of DI*01 allele, C2-M217 and C2-M401 Y-chromosome haplotypes ascribed as being of Mongolian-origin and language affiliations, in 75 Eurasian populations including DI*01 frequency data from the HGDP-CEPH panel. We revealed that DI*01 reaches its highest frequency in Mongolia, Turkmenistan and Kyrgyzstan, expanding southward and westward across Asia with Altaic-speaking nomadic carriers of C2-M217, and even more precisely C2-M401, from their homeland presumably in Mongolia, between the third century BCE and the thirteenth century CE. The present study has highlighted the gene-culture co-migration with the demographic movements that occurred during the past two millennia in Central and East Asia. Additionally, this work contributes to a better understanding of the distribution of immunogenic erythrocyte polymorphisms with a view to improve transfusion safety.

Published
2019
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results