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IRIS
Despite numerous attempts to discover genetic variants associated with elite athletic performance, injury predisposition, and elite/world-class athletic status, there has been limited progress to date. Past reliance on candidate gene studies predominantly focusing on genotyping a limited number of single nucleotide polymorphisms or the insertion/deletion variants in small, often heterogeneous cohorts (i.e., made up of athletes of quite different sport specialties) have not generated the kind of results that could offer solid opportunities to bridge the gap between basic research in exercise sciences and deliverables in biomedicine. A retrospective view of genetic association studies with complex disease traits indicates that transition to hypothesis-free genome-wide approaches will be more fruitful. In studies of complex disease, it is well recognized that the magnitude of genetic association is often smaller than initially anticipated, and, as such, large sample sizes are required to identify the gene effects robustly. A symposium was held in Athens and on the Greek island of Santorini from 14 -17 May 2015 to review the main findings in exercise genetics and genomics and to explore promising trends and possibilities. The symposium also offered a forum for the development of a position stand (the Santorini Declaration). Among the participants, many were involved in ongoing collaborative studies (e.g., ELITE, GAMES, Gene SMART, GENESIS, and POWERGENE). A consensus emerged among participants that it would be advantageous to bring together all current studies and those recently launched into one new large collaborative initiative, which was subsequently named the Athlome Project Consortium.
Athlome project consortium: A concerted effort to discover genomic and other "omic" markers of athletic performance
Pitsiladis, Yannis P.;Tanaka, Masashi;Eynon, Nir;Bouchard, Claude;North, Kathryn N.;Williams, Alun G.;Collins, Malcolm;Moran, Colin N.;Britton, Steven L.;Fuku, Noriyuki;Ashley, Euan A.;Klissouras, Vassilis;Lucia, Alejandro;Ahmetov, Ildus I.;De Geus, Eco;Alsayrafi, Mohammed;Webborn, Nick;Wang, Guan;Bishop, David J.;Papadimitriou, Ioannis;Yan, Xu;Tirosh, Oren;Kuang, Jujiao;Rankinen, Tuomo;Sarzinsky, Mark;Mikael Mattsson, C.;Wheeler, Matthew;Waggott, Daryl;Byrne, Nuala M.;Artioli, Guilherme G.;September, Alison;Posthumus, Michael;Van der Merwe, Willem;Cieszczyk, Pawel;Leonska-Duniec, Agata;Ficek, Krzysztof;Maciejewska-Karlowska, Agnieszka;Sawczuk, Marek;Stepien-Slodkowska, Marta;Feller, Julian;Dijkstra, Paul;Chmutov, Aleksandr M.;Dyatlov, Dmitry A.;Orekhov, Evgeniy F.;Pushkareva, Yuliya E.;Shvedkaya, Irina A.;Massidda, Myosotis;Calò, Carla M.;Day, Stephen H.;Stebbings, Georgina K.;Erskine, Robert M.;Montgomery, Hugh E.;Garton, Fleur C.;Houweling, Peter;Derave, Wim;Baguet, Audrey;Muniesa, Carlos A.;Sessa, Francesco;Petito, Annamarie;Sale, Craig;Hughes, David C.;Varley, Ian;Boomsma, Dorret;Bartels, Meike;Davies, Gareth E.;Ginevičienė, Valentina;Jakaitienė, Audronė;Kučinskas, Vaidutis;Tubelis, Linas;Utkus, Algirdas;Milašius, Kazys;Venckunas, Tomas;Skurvydas, Albertas;Stasiulis, Arvydas;Malkova, Dalia;Wilson, Richard;Koch, Lauren G.;Zempo, Hirofumi;Naito, Hisashi;Kikuchi, Naoki;Miyamoto-Mikami, Eri;Murakami, Haruka;Miyachi, Motohiko;Takahashi, Hideyuki;Ohiwa, Nao;Kawahara, Takashi;Tsuchie, Hiroyasu;Tobina, Takuro;Ichinoseki-Sekine, Noriko;Tanaka, Hiroaki;Kaneoka, Koji;Nakazato, Koichi;Egorova, Emiliya S.;Gabdrakhmanova, Leysan J.;Arkhipova, Alina A.;Borisova, Alyona V.;Gabbasov, Rashid T.;Stepanova, Albina A.;Kashapov, Ravil I.;Rogozkin, Victor A.;Astratenkova, Irina V.;Druzhevskaya, Anastasiya M.;Fedotovskaya, Olga N.;Golberg, Natalya D.;Hakimullina, Albina M.;Kostryukova, Elena S.;Alexeev, Dmitry G.;Generozov, Edward V.;Ischenko, Dmitry S.;Kulemin, Nickolay A.;Larin, Andrey K.;Ospanova, Elena A.;Pavlenko, Alexander V.;Govorun, Vadim M.;Gilep, Andrei A.;Gilep, Irina L.;Haidukevich, Irina V.;Rybina, Irina L.;Drozdovska, Svitlana B.;Docenko, Victor E.;Ilyin, Vladimir N.;Lekontsev, Eugeniy;Akimov, Egor B.;El-Rayess, Mohamed;Georgakopoulos, Costas;Botre, Francesco;Suhre, Karsten;Hubank, Mike;Wolfarth, Bernd;Greeves, Julie P.;Stellingwerff, Trent;Ranson, Craig;Fraser, William D.;Grealy, Rebecca;Griffiths, Lyn;Scott, Robert;Pushkarev, Vladimir P.
2016-01-01
Abstract
Despite numerous attempts to discover genetic variants associated with elite athletic performance, injury predisposition, and elite/world-class athletic status, there has been limited progress to date. Past reliance on candidate gene studies predominantly focusing on genotyping a limited number of single nucleotide polymorphisms or the insertion/deletion variants in small, often heterogeneous cohorts (i.e., made up of athletes of quite different sport specialties) have not generated the kind of results that could offer solid opportunities to bridge the gap between basic research in exercise sciences and deliverables in biomedicine. A retrospective view of genetic association studies with complex disease traits indicates that transition to hypothesis-free genome-wide approaches will be more fruitful. In studies of complex disease, it is well recognized that the magnitude of genetic association is often smaller than initially anticipated, and, as such, large sample sizes are required to identify the gene effects robustly. A symposium was held in Athens and on the Greek island of Santorini from 14 -17 May 2015 to review the main findings in exercise genetics and genomics and to explore promising trends and possibilities. The symposium also offered a forum for the development of a position stand (the Santorini Declaration). Among the participants, many were involved in ongoing collaborative studies (e.g., ELITE, GAMES, Gene SMART, GENESIS, and POWERGENE). A consensus emerged among participants that it would be advantageous to bring together all current studies and those recently launched into one new large collaborative initiative, which was subsequently named the Athlome Project Consortium.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11369/377699
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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.