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Objective: To identify shared polygenic risk and causal associations in amyotrophic lateral sclerosis (ALS). Methods: Linkage disequilibrium score regression and Mendelian randomization were applied in a large-scale, data-driven manner to explore genetic correlations and causal relationships between >700 phenotypic traits and ALS. Exposures consisted of publicly available genome-wide association studies (GWASes) summary statistics from MR Base and LD-hub. The outcome data came from the recently published ALS GWAS involving 20,806 cases and 59,804 controls. Multivariate analyses, genetic risk profiling, and Bayesian colocalization analyses were also performed. Results: We have shown, by linkage disequilibrium score regression, that ALS shares polygenic risk genetic factors with a number of traits and conditions, including positive correlations with smoking status and moderate levels of physical activity, and negative correlations with higher cognitive performance, higher educational attainment, and light levels of physical activity. Using Mendelian randomization, we found evidence that hyperlipidemia is a causal risk factor for ALS and localized putative functional signals within loci of interest. Interpretation: Here, we have developed a public resource (https://lng-nia.shinyapps.io/mrshiny) which we hope will become a valuable tool for the ALS community, and that will be expanded and updated as new data become available. Shared polygenic risk exists between ALS and educational attainment, physical activity, smoking, and tenseness/restlessness. We also found evidence that elevated low-desnity lipoprotein cholesterol is a causal risk factor for ALS. Future randomized controlled trials should be considered as a proof of causality. Ann Neurol 2019;85:470–481.
Shared polygenic risk and causal inferences in amyotrophic lateral sclerosis
Bandres-Ciga, Sara;Noyce, Alastair J.;Hemani, Gibran;Nicolas, Aude;Calvo, Andrea;Mora, Gabriele;Arosio, Alessandro;Barberis, Marco;Bartolomei, Ilaria;Battistini, Stefania;Benigni, Michele;Borghero, Giuseppe;Brunetti, Maura;Calvo, Andrea;Cammarosano, Stefania;Cannas, Antonino;Canosa, Antonio;Capasso, Margherita;Caponnetto, Claudia;Caredda, Carla;Carrera, Paola;Casale, Federico;Cavallaro, Sebastiano;Chiò, Adriano;Colletti, Tiziana;Conforti, Francesca L.;Conte, Amelia;Corrado, Lucia;Costantino, Emanuela;D'Alfonso, Sandra;Fasano, Antonio;Femiano, Cinzia;Ferrarese, Carlo;Fini, Nicola;Floris, Gianluca;Fuda, Giuseppe;Giannini, Fabio;Grassano, Maurizio;Ilardi, Antonio;La Bella, Vincenzo;Lattante, Serena;Logroscino, Giancarlo;Logullo, Francesco O.;Loi, Daniela;Lunetta, Christian;Mancardi, Gianluigi;Mandich, Paola;Mandrioli, Jessica;Manera, Umberto;Marangi, Giuseppe;Marinou, Kalliopi;Marrali, Giuseppe;Marrosu, Maria Giovanna;Mazzini, Letizia;Melis, Maurizio;Messina, Sonia;Moglia, Cristina;Monsurro, Maria Rosaria;Mora, Gabriele;Mosca, Lorena;Occhineri, Patrizia;Origone, Paola;Pani, Carla;Penco, Silvana;Petrucci, Antonio;Piccirillo, Giovanni;Pirisi, Angelo;Pisano, Fabrizio;Pugliatti, Maura;Restagno, Gabriella;Ricci, Claudia;Rita Murru, Maria;Riva, Nilo;Sabatelli, Mario;Salvi, Fabrizio;Santarelli, Marialuisa;Sideri, Riccardo;Simone, Isabella;Spataro, Rossella;Tanel, Raffaella;Tedeschi, Gioacchino;Tranquilli, Stefania;Tremolizzo, Lucio;Trojsi, Francesca;Volanti, Paolo;Zollino, Marcella;Abramzon, Yevgeniya;Arepalli, Sampath;Baloh, Robert H.;Bowser, Robert;Brady, Christopher B.;Brice, Alexis;Broach, James;Campbell, Roy H.;Camu, William;Chia, Ruth;Chiò, Adriano;Cooper-Knock, John;Cusi, Daniele;Ding, Jinhui;Drepper, Carsten;Drory, Vivian E.;Dunckley, Travis L.;Eicher, John D.;Faghri, Faraz;Feldman, Eva;Kay Floeter, Mary;Fratta, Pietro;Geiger, Joshua T.;Gerhard, Glenn;Gibbs, J. Raphael;Gibson, Summer B.;Glass, Jonathan D.;Hardy, John;Harms, Matthew B.;Heiman-Patterson, Terry D.;Hernandez, Dena G.;Jansson, Lilja;Kamel, Freya;Kirby, Janine;Kowall, Neil W.;Laaksovirta, Hannu;Landi, Francesco;Le Ber, Isabelle;Lumbroso, Serge;MacGowan, Daniel J. L.;Maragakis, Nicholas J.;Mouzat, Kevin;Murphy, Natalie A.;Myllykangas, Liisa;Nalls, Mike A.;Nicolas, Aude;Orrell, Richard W.;Ostrow, Lyle W.;Pamphlett, Roger;Pickering-Brown, Stuart;Pioro, Erik;Pliner, Hannah A.;Pulst, Stefan M.;Ravits, John M.;Renton, Alan E.;Rivera, Alberto;Robbrecht, Wim;Rogaeva, Ekaterina;Rollinson, Sara;Rothstein, Jeffrey D.;Salvi, Erika;Scholz, Sonja W.;Sendtner, Michael;Shaw, Pamela J.;Sidle, Katie C.;Simmons, Zachary;Singleton, Andrew B.;Stone, David C.;Sulkava, Raimo;Tienari, Pentti J.;Traynor, Bryan J.;Trojanowski, John Q.;Troncoso, Juan C.;Van Damme, Philip;Van Deerlin, Vivianna M.;Van Den Bosch, Ludo;Zinman, Lorne;Tienari, Pentti J.;Stone, David J.;Nalls, Mike A.;Singleton, Andrew B.;Chiò, Adriano;Traynor, Bryan J.
2019
Abstract
Objective: To identify shared polygenic risk and causal associations in amyotrophic lateral sclerosis (ALS). Methods: Linkage disequilibrium score regression and Mendelian randomization were applied in a large-scale, data-driven manner to explore genetic correlations and causal relationships between >700 phenotypic traits and ALS. Exposures consisted of publicly available genome-wide association studies (GWASes) summary statistics from MR Base and LD-hub. The outcome data came from the recently published ALS GWAS involving 20,806 cases and 59,804 controls. Multivariate analyses, genetic risk profiling, and Bayesian colocalization analyses were also performed. Results: We have shown, by linkage disequilibrium score regression, that ALS shares polygenic risk genetic factors with a number of traits and conditions, including positive correlations with smoking status and moderate levels of physical activity, and negative correlations with higher cognitive performance, higher educational attainment, and light levels of physical activity. Using Mendelian randomization, we found evidence that hyperlipidemia is a causal risk factor for ALS and localized putative functional signals within loci of interest. Interpretation: Here, we have developed a public resource (https://lng-nia.shinyapps.io/mrshiny) which we hope will become a valuable tool for the ALS community, and that will be expanded and updated as new data become available. Shared polygenic risk exists between ALS and educational attainment, physical activity, smoking, and tenseness/restlessness. We also found evidence that elevated low-desnity lipoprotein cholesterol is a causal risk factor for ALS. Future randomized controlled trials should be considered as a proof of causality. Ann Neurol 2019;85:470–481.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/406432
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.