Attenzione: i dati modificati non sono ancora stati salvati. Per confermare inserimenti o cancellazioni di voci è necessario confermare con il tasto SALVA/INSERISCI in fondo alla pagina
IRIS
Background: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. Methods: We analyzed ∼250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. Results: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. Conclusions: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.
Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use / Brazel, David M.; Jiang, Yu; Hughey, Jordan M.; Turcot, Valerie; Zhan, Xiaowei; Gong, Jian; Batini, Chiara; Weissenkampen, J. Dylan; Liu, Mengzhen; Barnes, Daniel R.; Bertelsen, Sarah; Chou, Yi-Ling; Erzurumluoglu, A. Mesut; Faul, Jessica D.; Haessler, Jeff; Hammerschlag, Anke R.; Hsu, Chris; Kapoor, Manav; Lai, Dongbing; Le, Nhung; de Leeuw, Christiaan A.; Loukola, Anu; Mangino, Massimo; Melbourne, Carl A.; Pistis, Giorgio; Qaiser, Beenish; Rohde, Rebecca; Shao, Yaming; Stringham, Heather; Wetherill, Leah; Zhao, Wei; Agrawal, Arpana; Bierut, Laura; Chen, Chu; Eaton, Charles B.; Goate, Alison; Haiman, Christopher; Heath, Andrew; Iacono, William G.; Martin, Nicholas G.; Polderman, Tinca J.; Reiner, Alex; Rice, John; Schlessinger, David; Scholte, H. Steven; Smith, Jennifer A.; Tardif, Jean-Claude; Tindle, Hilary A.; van der Leij, Andries R.; Boehnke, Michael; Chang-Claude, Jenny; Cucca, Francesco; David, Sean P.; Foroud, Tatiana; Howson, Joanna M. M.; Kardia, Sharon L. R.; Kooperberg, Charles; Laakso, Markku; Lettre, Guillaume; Madden, Pamela; Mcgue, Matt; North, Kari; Posthuma, Danielle; Spector, Timothy; Stram, Daniel; Tobin, Martin D.; Weir, David R.; Kaprio, Jaakko; Abecasis, Goncalo R.; Liu, Dajiang J.; Vrieze, Scott; Surendran, Praveen; Young, Robin; Barnes, Daniel R.; Nielsen, Sune Fallgaard; Rasheed, Asif; Samuel, Maria; Zhao, Wei; Kontto, Jukka; Perola, Markus; Caslake, Muriel; de Craen, Anton J. M.; Trompet, Stella; Uria-Nickelsen, Maria; Malarstig, Anders; Reily, Dermot F.; Hoek, Maarten; Vogt, Thomas; Jukema, J. Wouter; Sattar, Naveed; Ford, Ian; Packard, Chris J.; Alam, Dewan S.; Majumder, Abdulla al Shafi; Di Ange-Lantonio, Emanuele; Chowdhury, Rajiv; Amouyel, Philippe; Arveiler, Dominique; Blankenberg, Stefan; Ferrieres, Jean; Kee, Frank; Kuulasmaa, Kari; Mueller-Nurasyid, Martina; Veronesi, Giovanni; Virtamo, Jarmo; Frossard, Philippe; Nordestgaard, Borge Gronne; Saleheen, Danish; Danesh, John; Butterworth, Adam S.; Howson, Joanna M. M.; Erzurumluoglu, A. Mesut; Jackson, Victoria E.; Melbourne, Carl A.; Varga, Tibor V.; Warren, Helen R.; Tragante, Vinicius; Tachmazidou, Ioanna; Harris, Sarah E.; Evangelou, Evangelos; Marten, Jonathan; Zhang, Weihua; Altmaier, Elisabeth; Luan, Jian'An; Langenberg, Claudia; Scott, Robert A.; Yaghootkar, Hanieh; Stirrups, Kathleen; Kanoni, Stavroula; Marouli, Eirini; Karpe, Fredrik; Dominiczak, Anna F.; Sever, Peter; Poulter, Neil; Rolandsson, Olov; Baumbach, Clemens; Afaq, Saima; Chambers, John C.; Kooner, Jaspal S.; Wareham, Nicholas J.; Renstrom, Frida; Hallmans, Goran; Marioni, Riccardo E.; Corley, Janie; Starr, John M.; Verweij, Niek; de Boer, Rudolf A.; van der Meer, Peter; Yavas, Ersin; Vaartjes, Ilonca; Bots, Michiel L.; Asselbergs, Folkert W.; Grabe, Hans J.; Volzke, Henry; Nauck, Matthias; Weiss, Stefan; Pharoah, Paul D. P.; Dunning, Alison M.; Dennis, Joe G.; Thompson, Deborah J.; Michailidou, Kyriaki; Easton, Douglas F.; Antoniou, Antonis C.; Tyrrell, Jessica; Mihailov, Evelin; Samani, Nilesh J.; Zhou, Kaixin; Neville, Matthew J.; Metspalu, Andres; Palmer, Colin N. A.; Hall, Ian P.; Strachan, David P.; Deary, Ian J.; Frayling, Tim M.; Hayward, Caroline; van der Harst, Pim; Zeggini, Eleftheria; Munroe, Patricia B.; Jansson, Jan-Hakan; Franks, Paul W.; Deloukas, Panos; Caulfield, Mark J.; Wain, Louise V.; Tobin, Martin D.. - In: BIOLOGICAL PSYCHIATRY. - ISSN 0006-3223. - 85:11(2019), pp. 946-955. [10.1016/j.biopsych.2018.11.024]
Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use
Brazel, David M.;Jiang, Yu;Hughey, Jordan M.;Turcot, Valerie;Zhan, Xiaowei;Gong, Jian;Batini, Chiara;Weissenkampen, J. Dylan;Liu, MengZhen;Barnes, Daniel R.;Bertelsen, Sarah;Chou, Yi-Ling;Erzurumluoglu, A. Mesut;Faul, Jessica D.;Haessler, Jeff;Hammerschlag, Anke R.;Hsu, Chris;Kapoor, Manav;Lai, Dongbing;Le, Nhung;de Leeuw, Christiaan A.;Loukola, Anu;Mangino, Massimo;Melbourne, Carl A.;Pistis, Giorgio;Qaiser, Beenish;Rohde, Rebecca;Shao, Yaming;Stringham, Heather;Wetherill, Leah;Zhao, Wei;Agrawal, Arpana;Bierut, Laura;Chen, Chu;Eaton, Charles B.;Goate, Alison;Haiman, Christopher;Heath, Andrew;Iacono, William G.;Martin, Nicholas G.;Polderman, Tinca J.;Reiner, Alex;Rice, John;Schlessinger, David;Scholte, H. Steven;Smith, Jennifer A.;Tardif, Jean-Claude;Tindle, Hilary A.;van der Leij, Andries R.;Boehnke, Michael;Chang-Claude, Jenny;Cucca, Francesco;David, Sean P.;Foroud, Tatiana;Howson, Joanna M. M.;Kardia, Sharon L. R.;Kooperberg, Charles;Laakso, Markku;Lettre, Guillaume;Madden, Pamela;Mcgue, Matt;North, Kari;Posthuma, Danielle;Spector, Timothy;Stram, Daniel;Tobin, Martin D.;Weir, David R.;Kaprio, Jaakko;Abecasis, Goncalo R.;Liu, Dajiang J.;Vrieze, Scott;Surendran, Praveen;Young, Robin;Barnes, Daniel R.;Nielsen, Sune Fallgaard;Rasheed, Asif;Samuel, Maria;Zhao, Wei;Kontto, Jukka;Perola, Markus;Caslake, Muriel;de Craen, Anton J. M.;Trompet, Stella;Uria-Nickelsen, Maria;Malarstig, Anders;Reily, Dermot F.;Hoek, Maarten;Vogt, Thomas;Jukema, J. Wouter;Sattar, Naveed;Ford, Ian;Packard, Chris J.;Alam, Dewan S.;Majumder, Abdulla al Shafi;Di Ange-Lantonio, Emanuele;Chowdhury, Rajiv;Amouyel, Philippe;Arveiler, Dominique;Blankenberg, Stefan;Ferrieres, Jean;Kee, Frank;Kuulasmaa, Kari;Mueller-Nurasyid, Martina;Veronesi, Giovanni;Virtamo, Jarmo;Frossard, Philippe;Nordestgaard, Borge Gronne;Saleheen, Danish;Danesh, John;Butterworth, Adam S.;Howson, Joanna M. M.;Erzurumluoglu, A. Mesut;Jackson, Victoria E.;Melbourne, Carl A.;Varga, Tibor V.;Warren, Helen R.;Tragante, Vinicius;Tachmazidou, Ioanna;Harris, Sarah E.;Evangelou, Evangelos;Marten, Jonathan;Zhang, Weihua;Altmaier, Elisabeth;Luan, Jian'an;Langenberg, Claudia;Scott, Robert A.;Yaghootkar, Hanieh;Stirrups, Kathleen;Kanoni, Stavroula;Marouli, Eirini;Karpe, Fredrik;Dominiczak, Anna F.;Sever, Peter;Poulter, Neil;Rolandsson, Olov;Baumbach, Clemens;Afaq, Saima;Chambers, John C.;Kooner, Jaspal S.;Wareham, Nicholas J.;Renstrom, Frida;Hallmans, Goran;Marioni, Riccardo E.;Corley, Janie;Starr, John M.;Verweij, Niek;de Boer, Rudolf A.;van der Meer, Peter;Yavas, Ersin;Vaartjes, Ilonca;Bots, Michiel L.;Asselbergs, Folkert W.;Grabe, Hans J.;Volzke, Henry;Nauck, Matthias;Weiss, Stefan;Pharoah, Paul D. P.;Dunning, Alison M.;Dennis, Joe G.;Thompson, Deborah J.;Michailidou, Kyriaki;Easton, Douglas F.;Antoniou, Antonis C.;Tyrrell, Jessica;Mihailov, Evelin;Samani, Nilesh J.;Zhou, Kaixin;Neville, Matthew J.;Metspalu, Andres;Palmer, Colin N. A.;Hall, Ian P.;Strachan, David P.;Deary, Ian J.;Frayling, Tim M.;Hayward, Caroline;van der Harst, Pim;Zeggini, Eleftheria;Munroe, Patricia B.;Jansson, Jan-Hakan;Franks, Paul W.;Deloukas, Panos;Caulfield, Mark J.;Wain, Louise V.;Tobin, Martin D.
2019-01-01
Abstract
Background: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. Methods: We analyzed ∼250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. Results: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. Conclusions: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11388/226495
Citazioni
ND
55
52
social impact
Conferma cancellazione
Sei sicuro che questo prodotto debba essere cancellato?
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.