132 results on '"Glessner JT"'
Search Results
2. High rate of disease-related copy number variations in childhood onset schizophrenia
- Author
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Ahn, K, Gotay, N, Andersen, TM, Anvari, AA, Gochman, P, Lee, Y, Sanders, S, Guha, S, Darvasi, A, Glessner, JT, Hakonarson, H, Lencz, T, State, MW, Shugart, YY, and Rapoport, JL
- Subjects
Biological Psychology ,Pharmacology and Pharmaceutical Sciences ,Biomedical and Clinical Sciences ,Psychology ,Brain Disorders ,Intellectual and Developmental Disabilities (IDD) ,Pediatric ,Serious Mental Illness ,Genetics ,Autism ,Schizophrenia ,Prevention ,Mental Health ,Neurosciences ,Clinical Research ,Human Genome ,Aetiology ,2.1 Biological and endogenous factors ,Mental health ,Adult ,Child ,Child Development Disorders ,Pervasive ,DNA Copy Number Variations ,Female ,Genetic Pleiotropy ,Genotyping Techniques ,Humans ,Male ,Polymorphism ,Single Nucleotide ,Schizophrenia ,Childhood ,Sequence Deletion ,Siblings ,CNV ,genetics ,neurodevelopment ,schizophrenia ,Biological Sciences ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Psychiatry ,Clinical sciences ,Biological psychology ,Clinical and health psychology - Abstract
Copy number variants (CNVs) are risk factors in neurodevelopmental disorders, including autism, epilepsy, intellectual disability (ID) and schizophrenia. Childhood onset schizophrenia (COS), defined as onset before the age of 13 years, is a rare and severe form of the disorder, with more striking array of prepsychotic developmental disorders and abnormalities in brain development. Because of the well-known phenotypic variability associated with pathogenic CNVs, we conducted whole genome genotyping to detect CNVs and then focused on a group of 46 rare CNVs that had well-documented risk for adult onset schizophrenia (AOS), autism, epilepsy and/or ID. We evaluated 126 COS probands, 69 of which also had a healthy full sibling. When COS probands were compared with their matched related controls, significantly more affected individuals carried disease-related CNVs (P=0.017). Moreover, COS probands showed a higher rate than that found in AOS probands (P
- Published
- 2014
3. A first update on mapping the human genetic architecture of COVID-19
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COVID-19 Host Genetics Initiative, Pathak, GA, Karjalainen, J, Stevens, C, Neale, BM, Daly, M, Ganna, A, Andrews, SJ, Kanai, M, Cordioli, M, Polimanti, R, Harerimana, N, Pirinen, M, Liao, RG, Chwialkowska, K, Trankiem, A, Balaconis, MK, Nguyen, H, Solomonson, M, Veerapen, K, Wolford, B, Roberts, G, Park, D, Ball, CA, Coignet, M, McCurdy, S, Knight, S, Partha, R, Rhead, B, Zhang, M, Berkowitz, N, Gaddis, M, Noto, K, Ruiz, L, Pavlovic, M, Hong, EL, Rand, K, Girshick, A, Guturu, H, Baltzell, AH, Niemi, MEK, Rahmouni, S, Guntz, J, Beguin, Y, Pigazzini, S, Nkambule, L, Georges, M, Moutschen, M, Misset, B, Darcis, G, Guiot, J, Azarzar, S, Gofflot, S, Claassen, S, Malaise, O, Huynen, P, Meuris, C, Thys, M, Jacques, J, Leonard, P, Frippiat, F, Giot, J-B, Sauvage, A-S, Frenckell, CV, Belhaj, Y, Lambermont, B, Nakanishi, T, Morrison, DR, Mooser, V, Richards, JB, Butler-Laporte, G, Forgetta, V, Li, R, Ghosh, B, Laurent, L, Belisle, A, Henry, D, Abdullah, T, Adeleye, O, Mamlouk, N, Kimchi, N, Afrasiabi, Z, Rezk, N, Vulesevic, B, Bouab, M, Guzman, C, Petitjean, L, Tselios, C, Xue, X, Afilalo, J, Afilalo, M, Oliveira, M, Brenner, B, Brassard, N, Durand, M, Schurr, E, Lepage, P, Ragoussis, J, Auld, D, Chassé, M, Kaufmann, DE, Lathrop, GM, Adra, D, Hayward, C, Glessner, JT, Shaw, DM, Campbell, A, Morris, M, Hakonarson, H, Porteous, DJ, Below, J, Richmond, A, Chang, X, Polikowski, H, Lauren, PE, Chen, H-H, Wanying, Z, Fawns-Ritchie, C, North, K, McCormick, JB, Glessner, JR, Gignoux, CR, Wicks, SJ, Crooks, K, Barnes, KC, Daya, M, Shortt, J, Rafaels, N, Chavan, S, Timmers, PRHJ, Wilson, JF, Tenesa, A, Kerr, SM, D’Mellow, K, Shahin, D, El-Sherbiny, YM, von Hohenstaufen, KA, Sobh, A, Eltoukhy, MM, Nkambul, L, Elhadidy, TA, Abd Elghafar, MS, El-Jawhari, JJ, Mohamed, AAS, Elnagdy, MH, Samir, A, Abdel-Aziz, M, Khafaga, WT, El-Lawaty, WM, Torky, MS, El-shanshory, MR, Yassen, AM, Hegazy, MAF, Okasha, K, Eid, MA, Moahmed, HS, Medina-Gomez, C, Ikram, MA, Uitterlinden, AG, Mägi, R, Milani, L, Metspalu, A, Laisk, T, Läll, K, Lepamets, M, Esko, T, Reimann, E, Naaber, P, Laane, E, Pesukova, J, Peterson, P, Kisand, K, Tabri, J, Allos, R, Hensen, K, Starkopf, J, Ringmets, I, Tamm, A, Kallaste, A, Alavere, H, Metsalu, K, Puusepp, M, Batini, C, Tobin, MD, Venn, LD, Lee, PH, Shrine, N, Williams, AT, Guyatt, AL, John, C, Packer, RJ, Ali, A, Free, RC, Wang, X, Wain, LV, Hollox, EJ, Bee, CE, Adams, EL, Palotie, A, Ripatti, S, Ruotsalainen, S, Kristiansson, K, Koskelainen, S, Perola, M, Donner, K, Kivinen, K, Kaunisto, M, Rivolta, C, Bochud, P-Y, Bibert, S, Boillat, N, Nussle, SG, Albrich, W, Quinodoz, M, Kamdar, D, Suh, N, Neofytos, D, Erard, V, Voide, C, Friolet, R, Vollenweider, P, Pagani, JL, Oddo, M, zu Bentrup, FM, Conen, A, Clerc, O, Marchetti, O, Guillet, A, Guyat-Jacques, C, Foucras, S, Rime, M, Chassot, J, Jaquet, M, Viollet, RM, Lannepoudenx, Y, Portopena, L, Bochud, PY, Desgranges, F, Filippidis, P, Guéry, B, Haefliger, D, Kampouri, EE, Manuel, O, Munting, A, Papadimitriou-Olivgeris, M, Regina, J, Rochat-Stettler, L, Suttels, V, Tadini, E, Tschopp, J, Van Singer, M, Viala, B, Boillat-Blanco, N, Brahier, T, Hügli, O, Meuwly, JY, Pantet, O, Gonseth Nussle, S, Bochud, M, D’Acremont, V, Estoppey Younes, S, Albrich, WC, Cerny, A, O’Mahony, L, von Mering, C, Frischknecht, M, Kleger, G-R., Filipovic, M, Kahlert, CR, Wozniak, H, Negro, TR, Pugin, J, Bouras, K, Knapp, C, Egger, T, Perret, A, Montillier, P, di Bartolomeo, C, Barda, B, de Cid, R, Carreras, A, Moreno, V, Kogevinas, M, Galván-Femenía, I, Blay, N, Farré, X, Sumoy, L, Cortés, B, Mercader, JM, Guindo-Martinez, M, Torrents, D, Garcia-Aymerich, J, Castaño-Vinyals, G, Dobaño, C, Gori, M, Renieri, A, Mari, F, Mondelli, MU, Castelli, F, Vaghi, M, Rusconi, S, Montagnani, F, Bargagli, E, Franchi, F, Mazzei, MA, Cantarini, L, Tacconi, D, Feri, M, Scala, R, Spargi, G, Nencioni, C, Bandini, M, Caldarelli, GP, Canaccini, A, Ognibene, A, D’Arminio Monforte, A, Girardis, M, Antinori, A, Francisci, D, Schiaroli, E, Scotton, PG, Panese, S, Scaggiante, R, Monica, MD, Capasso, M, Fiorentino, G, Castori, M, Aucella, F, Biagio, AD, Masucci, L, Valente, S, Mandalà, M, Zucchi, P, Giannattasio, F, Coviello, DA, Mussini, C, Tavecchia, L, Crotti, L, Rizzi, M, Rovere, MTL, Sarzi-Braga, S, Bussotti, M, Ravaglia, S, Artuso, R, Perrella, A, Romani, D, Bergomi, P, Catena, E, Vincenti, A, Ferri, C, Grassi, D, Pessina, G, Tumbarello, M, Pietro, MD, Sabrina, R, Luchi, S, Furini, S, Dei, S, Benetti, E, Picchiotti, N, Sanarico, M, Ceri, S, Pinoli, P, Raimondi, F, Biscarini, F, Stella, A, Zguro, K, Capitani, K, Tanfoni, M, Fallerini, C, Daga, S, Baldassarri, M, Fava, F, Frullanti, E, Valentino, F, Doddato, G, Giliberti, A, Tita, R, Amitrano, S, Bruttini, M, Croci, S, Meloni, I, Mencarelli, MA, Rizzo, CL, Pinto, AM, Beligni, G, Tommasi, A, Sarno, LD, Palmieri, M, Carriero, ML, Alaverdian, D, Busani, S, Bruno, R, Vecchia, M, Belli, MA, Mantovani, S, Ludovisi, S, Quiros-Roldan, E, Antoni, MD, Zanella, I, Siano, M, Emiliozzi, A, Fabbiani, M, Rossetti, B, Bergantini, L, D’Alessandro, M, Cameli, P, Bennett, D, Anedda, F, Marcantonio, S, Scolletta, S, Guerrini, S, Conticini, E, Frediani, B, Spertilli, C, Donati, A, Guidelli, L, Corridi, M, Croci, L, Piacentini, P, Desanctis, E, Cappelli, S, Verzuri, A, Anemoli, V, Pancrazzi, A, Lorubbio, M, Miraglia, FG, Venturelli, S, Cossarizza, A, Vergori, A, Gabrieli, A, Riva, A, Paciosi, F, Andretta, F, Gatti, F, Parisi, SG, Baratti, S, Piscopo, C, Russo, R, Andolfo, I, Iolascon, A, Carella, M, Merla, G, Squeo, GM, Raggi, P, Marciano, C, Perna, R, Bassetti, M, Sanguinetti, M, Giorli, A, Salerni, L, Parravicini, P, Menatti, E, Trotta, T, Coiro, G, Lena, F, Martinelli, E, Mancarella, S, Gabbi, C, Maggiolo, F, Ripamonti, D, Bachetti, T, Suardi, C, Parati, G, Bottà, G, Domenico, PD, Rancan, I, Bianchi, F, Colombo, R, Barbieri, C, Acquilini, D, Andreucci, E, Segala, FV, Tiseo, G, Falcone, M, Lista, M, Poscente, M, Vivo, OD, Petrocelli, P, Guarnaccia, A, 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Boezen, M, Deelen, P, Claringbould, A, Lopera, E, Warmerdam, R, Vonk, JM, van Blokland, I, Lanting, P, Ori, APS, Feng, Y-CA, Mercader, J, Weiss, ST, Karlson, EW, Smoller, JW, Murphy, SN, Meigs, JB, Woolley, AE, Green, RC, Perez, EF, Zöllner, S, Wang, J, Beck, A, Sloofman, LG, Ascolillo, S, Sebra, RP, Collins, BL, Levy, T, Buxbaum, JD, Sealfon, SC, Jordan, DM, Thompson, RC, Gettler, K, Chaudhary, K, Belbin, GM, Preuss, M, Hoggart, C, Choi, S, Underwood, SJ, Salib, I, Britvan, B, Keller, K, Tang, L, Peruggia, M, Hiester, LL, Niblo, K, Aksentijevich, A, Labkowsky, A, Karp, A, Zlatopolsky, M, Zyndorf, M, Charney, AW, Beckmann, ND, Schadt, EE, Abul-Husn, NS, Cho, JH, Itan, Y, Kenny, EE, Loos, RJF, Nadkarni, GN, Do, R, O’Reilly, P, Huckins, LM, Ferreira, MAR, Abecasis, GR, Leader, JB, Cantor, MN, Justice, AE, Carey, DJ, Chittoor, G, Josyula, NS, Kosmicki, JA, Horowitz, JE, Baras, A, Gass, MC, Yadav, A, Mirshahi, T, Hottenga, JJ, Bartels, M, de geus, EEJC, Nivard, MMG, Verma, A, Ritchie, MD, Rader, D, Li, B, Verma, SS, Lucas, A, Bradford, Y, Abedalthagafi, M, Alaamery, M, Alshareef, A, Sawaji, M, Massadeh, S, AlMalik, A, Alqahtani, S, Baraka, D, Harthi, FA, Alsolm, E, Safieh, LA, Alowayn, AM, Alqubaishi, F, Mutairi, AA, Mangul, S, Almutairi, M, Aljawini, N, Albesher, N, Arabi, YM, Mahmoud, ES, Khattab, AK, Halawani, RT, Alahmadey, ZZ, Albakri, JK, Felemban, WA, Suliman, BA, Hasanato, R, Al-Awdah, L, Alghamdi, J, AlZahrani, D, AlJohani, S, Al-Afghani, H, AlDhawi, N, AlBardis, H, Alkwai, S, Alswailm, M, Almalki, F, Albeladi, M, Almohammed, I, Barhoush, E, Albader, A, Alotaibi, S, Alghamdi, B, Jung, J, fawzy, MS, Alrashed, M, Zeberg, H, Frithiof, R, Hultström, M, Lipcsey, M, Tardif, N, Rooyackers, O, Grip, J, Maricic, T, Helgeland, Ø, Magnus, P, Trogstad, L-IS, Lee, Y, Harris, JR, Mangino, M, Spector, TD, Emma, D, Moutsianas, L, Caulfield, MJ, Scott, RH, Kousathanas, A, Pasko, D, Walker, S, Stuckey, A, Odhams, CA, Rhodes, D, Fowler, T, Rendon, A, Chan, G, Arumugam, P, Karczewski, KJ, Martin, AR, Wilson, DJ, Spencer, CCA, Crook, DW, Wyllie, DH, O’Connell, AM, Atkinson, EG, Tsuo, K, Baya, N, Turley, P, Gupta, R, Walters, RK, Palmer, DS, Sarma, G, Cheng, N, Lu, W, Churchhouse, C, Goldstein, JI, King, D, Seed, C, Daly, MJ, Finucane, H, Bryant, S, Satterstrom, FK, Band, G, Earle, SG, Lin, S-K, Arning, N, Koelling, N, Armstrong, J, Rudkin, JK, Callier, S, Cusick, C, Soranzo, N, Zhao, JH, Danesh, J, Angelantonio, ED, Butterworth, AS, Sun, YV, Huffman, JE, Cho, K, O’Donnell, CJ, Tsao, P, Gaziano, JM, Peloso, G, Ho, Y-L, Smieszek, SP, Polymeropoulos, C, Polymeropoulos, V, Polymeropoulos, MH, Przychodzen, BP, Fernandez-Cadenas, I, Planas, AM, Perez-Tur, J, Llucià-Carol, L, Cullell, N, Muiño, E, Cárcel-Márquez, J, DeDiego, ML, Iglesias, LL, Soriano, A, Rico, V, Agüero, D, Bedini, JL, Lozano, F, Domingo, C, Robles, V, Ruiz-Jaén, F, Márquez, L, Gomez, J, Coto, E, Albaiceta, GM, García-Clemente, M, Dalmau, D, Arranz, MJ, Dietl, B, Serra-Llovich, A, Soler, P, Colobrán, R, Martín-Nalda, A, Martínez, AP, Bernardo, D, Rojo, S, Fiz-López, A, Arribas, E, de la Cal-Sabater, P, Segura, T, González-Villa, E, Serrano-Heras, G, Martí-Fàbregas, J, Jiménez-Xarrié, E, de Felipe Mimbrera, A, Masjuan, J, García-Madrona, S, Domínguez-Mayoral, A, Villalonga, JM, Menéndez-Valladares, P, Chasman, DI, Sesso, HD, Manson, JE, Buring, JE, Ridker, PM, Franco, G, Davis, L, Lee, S, Priest, J, Sankaran, VG, van Heel, D, Biesecker, L, Kerchberger, VE, Baillie, JK, Pathak, Gita A., Karjalainen, Juha, Stevens, Christine, Neale, Benjamin M., Daly, Mark, Ganna, Andrea, Andrews, Shea J., Kanai, Masahiro, Cordioli, Mattia, Polimanti, Renato, Harerimana, Nadia, Pirinen, Matti, Liao, Rachel G., Chwialkowska, Karolina, Trankiem, Amy, Balaconis, Mary K., Nguyen, Huy, Solomonson, Matthew, Veerapen, Kumar, Wolford, Brooke, Roberts, Genevieve, Park, Danny, Ball, Catherine A., Coignet, Marie, McCurdy, Shannon, Knight, Spencer, Partha, Raghavendran, Rhead, Brooke, Zhang, Miao, Berkowitz, Nathan, Gaddis, Michael, Noto, Keith, Ruiz, Luong, Pavlovic, Milo, Hong, Eurie L., Rand, Kristin, Girshick, Ahna, Guturu, Harendra, Baltzell, Asher Haug, Niemi, Mari E. K., Rahmouni, Souad, Guntz, Julien, Beguin, Yve, Pigazzini, Sara, Nkambule, Lindokuhle, Georges, Michel, Moutschen, Michel, Misset, Benoit, Darcis, Gille, Guiot, Julien, Azarzar, Samira, Gofflot, Stéphanie, Claassen, Sabine, Malaise, Olivier, Huynen, Pascale, Meuris, Christelle, Thys, Marie, Jacques, Jessica, Léonard, Philippe, Frippiat, Frederic, Giot, Jean-Baptiste, Sauvage, Anne-Sophie, Frenckell, Christian Von, Belhaj, Yasmine, Lambermont, Bernard, Nakanishi, Tomoko, Morrison, David R., Mooser, Vincent, Richards, J. Brent, Butler-Laporte, Guillaume, Forgetta, Vincenzo, Li, Rui, Ghosh, Biswarup, Laurent, Laetitia, Belisle, Alexandre, Henry, Danielle, Abdullah, Tala, Adeleye, Olumide, Mamlouk, Noor, Kimchi, Nofar, Afrasiabi, Zaman, Rezk, Nardin, Vulesevic, Branka, Bouab, Meriem, Guzman, Charlotte, Petitjean, Loui, Tselios, Chri, Xue, Xiaoqing, Afilalo, Jonathan, Afilalo, Marc, Oliveira, Maureen, Brenner, Bluma, Brassard, Nathalie, Durand, Madeleine, Schurr, Erwin, Lepage, Pierre, Ragoussis, Jianni, Auld, Daniel, Chassé, Michaël, Kaufmann, Daniel E., Lathrop, G. Mark, Adra, Darin, Hayward, Caroline, Glessner, Joseph T., Shaw, Douglas M., Campbell, Archie, Morris, Marcela, Hakonarson, Hakon, Porteous, David J., Below, Jennifer, Richmond, Anne, Chang, Xiao, Polikowski, Hannah, Lauren, Petty E., Chen, Hung-Hsin, Wanying, Zhu, Fawns-Ritchie, Chloe, North, Kari, McCormick, Joseph B., Glessner, Joseph R., Gignoux, Christopher R., Wicks, Stephen J., Crooks, Kristy, Barnes, Kathleen C., Daya, Michelle, Shortt, Jonathan, Rafaels, Nichola, Chavan, Sameer, Timmers, Paul R. H. J., Wilson, James F., Tenesa, Albert, Kerr, Shona M., D’Mellow, Kenton, Shahin, Doaa, El-Sherbiny, Yasser M., von Hohenstaufen, Kathrin Aprile, Sobh, Ali, Eltoukhy, Madonna M., Nkambul, Lindokuhle, Elhadidy, Tamer A., Abd Elghafar, Mohamed S., El-Jawhari, Jehan J., Mohamed, Attia A. S., Elnagdy, Marwa H., Samir, Amr, Abdel-Aziz, Mahmoud, Khafaga, Walid T., El-Lawaty, Walaa M., Torky, Mohamed S., El-shanshory, Mohamed R., Yassen, Amr M., Hegazy, Mohamed A. F., Okasha, Kamal, Eid, Mohammed A., Moahmed, Hanteera S., Medina-Gomez, Carolina, Ikram, M. Arfan, Uitterlinden, Andre G., Mägi, Reedik, Milani, Lili, Metspalu, Andre, Laisk, Triin, Läll, Kristi, Lepamets, Maarja, Esko, Tõnu, Reimann, Ene, Naaber, Paul, Laane, Edward, Pesukova, Jaana, Peterson, Pärt, Kisand, Kai, Tabri, Jekaterina, Allos, Raili, Hensen, Kati, Starkopf, Joel, Ringmets, Inge, Tamm, Anu, Kallaste, Anne, Alavere, Helene, Metsalu, Kristjan, Puusepp, Mairo, Batini, Chiara, Tobin, Martin D., Venn, Laura D., Lee, Paul H., Shrine, Nick, Williams, Alexander T., Guyatt, Anna L., John, Catherine, Packer, Richard J., Ali, Altaf, Free, Robert C., Wang, Xueyang, Wain, Louise V., Hollox, Edward J., Bee, Catherine E., Adams, Emma L., Palotie, Aarno, Ripatti, Samuli, Ruotsalainen, Sanni, Kristiansson, Kati, Koskelainen, Sami, Perola, Marku, Donner, Kati, Kivinen, Katja, Kaunisto, Mari, Rivolta, Carlo, Bochud, Pierre-Yve, Bibert, Stéphanie, Boillat, Noémie, Nussle, Semira Gonseth, Albrich, Werner, Quinodoz, Mathieu, Kamdar, Dhryata, Suh, Noémie, Neofytos, Dionysio, Erard, Véronique, Voide, Cathy, Friolet, R., Vollenweider, P., Pagani, J. L., Oddo, M., zu Bentrup, F. Meyer, Conen, A., Clerc, O., Marchetti, O., Guillet, A., Guyat-Jacques, C., Foucras, S., Rime, M., Chassot, J., Jaquet, M., Viollet, R. Merlet, Lannepoudenx, Y., Portopena, L., Bochud, P. Y., Desgranges, F., Filippidis, P., Guéry, B., Haefliger, D., Kampouri, E. E., Manuel, O., Munting, A., Papadimitriou-Olivgeris, M., Regina, J., Rochat-Stettler, L., Suttels, V., Tadini, E., Tschopp, J., Van Singer, M., Viala, B., Boillat-Blanco, N., Brahier, T., Hügli, O., Meuwly, J. Y., Pantet, O., Gonseth Nussle, S., Bochud, M., D’Acremont, V., Estoppey Younes, S., Albrich, W. C., Suh, N., Cerny, A., O’Mahony, L., von Mering, C., Frischknecht, M., Kleger, G-R., Filipovic, M., Kahlert, C. R., Wozniak, H., Negro, T. Rochat, Pugin, J., Bouras, K., Knapp, C., Egger, T., Perret, A., Montillier, P., di Bartolomeo, C., Barda, B., de Cid, Rafael, Carreras, Anna, Moreno, Victor, Kogevinas, Manoli, Galván-Femenía, Iván, Blay, Natalia, Farré, Xavier, Sumoy, Lauro, Cortés, Beatriz, Mercader, Josep Maria, Guindo-Martinez, Marta, Torrents, David, Garcia-Aymerich, Judith, Castaño-Vinyals, Gemma, Dobaño, Carlota, Gori, Marco, Renieri, Alessandra, Mari, Francesca, Mondelli, Mario Umberto, Castelli, Francesco, Vaghi, Massimo, Rusconi, Stefano, Montagnani, Francesca, Bargagli, Elena, Franchi, Federico, Mazzei, Maria Antonietta, Cantarini, Luca, Tacconi, Danilo, Feri, Marco, Scala, Raffaele, Spargi, Genni, Nencioni, Cesira, Bandini, Maria, Caldarelli, Gian Piero, Canaccini, Anna, Ognibene, Agostino, D’Arminio Monforte, Antonella, Girardis, Massimo, Antinori, Andrea, Francisci, Daniela, Schiaroli, Elisabetta, Scotton, Pier Giorgio, Panese, Sandro, Scaggiante, Renzo, Monica, Matteo Della, Capasso, Mario, Fiorentino, Giuseppe, Castori, Marco, Aucella, Filippo, Biagio, Antonio Di, Masucci, Luca, Valente, Serafina, Mandalà, Marco, Zucchi, Patrizia, Giannattasio, Ferdinando, Coviello, Domenico A., Mussini, Cristina, Tavecchia, Luisa, Crotti, Lia, Rizzi, Marco, Rovere, Maria Teresa La, Sarzi-Braga, Simona, Bussotti, Maurizio, Ravaglia, Sabrina, Artuso, Rosangela, Perrella, Antonio, Romani, Davide, Bergomi, Paola, Catena, Emanuele, Vincenti, Antonella, Ferri, Claudio, Grassi, Davide, Pessina, Gloria, Tumbarello, Mario, Pietro, Massimo Di, Sabrina, Ravaglia, Luchi, Sauro, Furini, Simone, Dei, Simona, Benetti, Elisa, Picchiotti, Nicola, Sanarico, Maurizio, Ceri, Stefano, Pinoli, Pietro, Raimondi, Francesco, Biscarini, Filippo, Stella, Alessandra, Zguro, Kristina, Capitani, Katia, Tanfoni, Marco, Fallerini, Chiara, Daga, Sergio, Baldassarri, Margherita, Fava, Francesca, Frullanti, Elisa, Valentino, Floriana, Doddato, Gabriella, Giliberti, Annarita, Tita, Rossella, Amitrano, Sara, Bruttini, Mirella, Croci, Susanna, Meloni, Ilaria, Mencarelli, Maria Antonietta, Rizzo, Caterina Lo, Pinto, Anna Maria, Beligni, Giada, Tommasi, Andrea, Sarno, Laura Di, Palmieri, Maria, Carriero, Miriam Lucia, Alaverdian, Diana, Busani, Stefano, Bruno, Raffaele, Vecchia, Marco, Belli, Mary Ann, Mantovani, Stefania, Ludovisi, Serena, Quiros-Roldan, Eugenia, Antoni, Melania Degli, Zanella, Isabella, Siano, Matteo, Emiliozzi, Arianna, Fabbiani, Massimiliano, Rossetti, Barbara, Bergantini, Laura, D’Alessandro, Miriana, Cameli, Paolo, Bennett, David, Anedda, Federico, Marcantonio, Simona, Scolletta, Sabino, Guerrini, Susanna, Conticini, Edoardo, Frediani, Bruno, Spertilli, Chiara, Donati, Alice, Guidelli, Luca, Corridi, Marta, Croci, Leonardo, Piacentini, Paolo, Desanctis, Elena, Cappelli, Silvia, Verzuri, Agnese, Anemoli, Valentina, Pancrazzi, Alessandro, Lorubbio, Maria, Miraglia, Federica Gaia, Venturelli, Sophie, Cossarizza, Andrea, Vergori, Alessandra, Gabrieli, Arianna, Riva, Agostino, Paciosi, Francesco, Andretta, Francesca, Gatti, Francesca, Parisi, Saverio Giuseppe, Baratti, Stefano, Piscopo, Carmelo, Russo, Roberta, Andolfo, Immacolata, Iolascon, Achille, Carella, Massimo, Merla, Giuseppe, Squeo, Gabriella Maria, Raggi, Pamela, Marciano, Carmen, Perna, Rita, Bassetti, Matteo, Sanguinetti, Maurizio, Giorli, Alessia, Salerni, Lorenzo, Parravicini, Pierpaolo, Menatti, Elisabetta, Trotta, Tullio, Coiro, Gabriella, Lena, Fabio, Martinelli, Enrico, Mancarella, Sandro, Gabbi, Chiara, Maggiolo, Franco, Ripamonti, Diego, Bachetti, Tiziana, Suardi, Claudia, Parati, Gianfranco, Bottà, Giordano, Domenico, Paolo Di, Rancan, Ilaria, Bianchi, Francesco, Colombo, Riccardo, Barbieri, Chiara, Acquilini, Donatella, Andreucci, Elena, Segala, Francesco Vladimiro, Tiseo, Giusy, Falcone, Marco, Lista, Mirjam, Poscente, Monica, Vivo, Oreste De, Petrocelli, Paola, Guarnaccia, Alessandra, Baroni, Silvia, van Heel, David A., Hunt, Karen A., Trembath, Richard C., Huang, Qin Qin, Martin, Hilary C., Mason, Dan, Trivedi, Bhavi, Wright, John, Finer, Sarah, Akhtar, Shaheen, Anwar, Mohammad, Arciero, Elena, Ashraf, Samina, Breen, Gerome, Chung, Raymond, Curtis, Charles J., Chowdhury, Maharun, Colligan, Grainne, Deloukas, Pano, Durham, Ceri, Griffiths, Chri, Hurles, Matt, Hussain, Shapna, Islam, Kamrul, Khan, Ahsan, Khan, Amara, Lavery, Cath, Lee, Sang Hyuck, Lerner, Robin, MacArthur, Daniel, MacLaughlin, Bev, Martin, Hilary, Miah, Shefa, Newman, Bill, Safa, Nishat, Tahmasebi, Farah, Griffiths, Christopher J., Smith, Albert V., Boughton, Andrew P., Li, Kevin W., LeFaive, Jonathon, Annis, Aubrey, Niavarani, Ahmadreza, Aliannejad, Rasoul, Sharififard, Bahareh, Amirsavadkouhi, Ali, Naderpour, Zeinab, Tadi, Hengameh Ansari, Aleagha, Afshar Etemadi, Ahmadi, Saeideh, Moghaddam, Seyed Behrooz Mohseni, Adamsara, Alireza, Saeedi, Morteza, Abdollahi, Hamed, Hosseini, Abdolmajid, Chariyavilaskul, Pajaree, Jantarabenjakul, Watsamon, Hirankarn, Nattiya, Chamnanphon, Monpat, Suttichet, Thitima B., Shotelersuk, Vorasuk, Pongpanich, Monnat, Phokaew, Chureerat, Chetruengchai, Wanna, Putchareon, Opa, Torvorapanit, Pattama, Puthanakit, Thanyawee, Suchartlikitwong, Pintip, Nilaratanakul, Voraphoj, Sodsai, Pimpayao, Brumpton, Ben M., Hveem, Kristian, Willer, Cristen, Zhou, Wei, Rogne, Tormod, Solligard, Erik, Åsvold, Bjørn Olav, Franke, Lude, Boezen, Marike, Deelen, Patrick, Claringbould, Annique, Lopera, Esteban, Warmerdam, Robert, Vonk, Judith. M., van Blokland, Irene, Lanting, Pauline, Ori, Anil P. S., Feng, Yen-Chen Anne, Mercader, Josep, Weiss, Scott T., Karlson, Elizabeth W., Smoller, Jordan W., Murphy, Shawn N., Meigs, James B., Woolley, Ann E., Green, Robert C., Perez, Emma F., Zöllner, Sebastian, Wang, Jiongming, Beck, Andrew, Sloofman, Laura G., Ascolillo, Steven, Sebra, Robert P., Collins, Brett L., Levy, Te, Buxbaum, Joseph D., Sealfon, Stuart C., Jordan, Daniel M., Thompson, Ryan C., Gettler, Kyle, Chaudhary, Kumardeep, Belbin, Gillian M., Preuss, Michael, Hoggart, Clive, Choi, Sam, Underwood, Slayton J., Salib, Irene, Britvan, Bari, Keller, Katherine, Tang, Lara, Peruggia, Michael, Hiester, Liam L., Niblo, Kristi, Aksentijevich, Alexandra, Labkowsky, Alexander, Karp, Avromie, Zlatopolsky, Menachem, Zyndorf, Marissa, Charney, Alexander W., Beckmann, Noam D., Schadt, Eric E., Abul-Husn, Noura S., Cho, Judy H., Itan, Yuval, Kenny, Eimear E., Loos, Ruth J. F., Nadkarni, Girish N., Do, Ron, O’Reilly, Paul, Huckins, Laura M., Ferreira, Manuel A. R., Abecasis, Goncalo R., Leader, Joseph B., Cantor, Michael N., Justice, Anne E., Carey, Dave J., Chittoor, Geetha, Josyula, Navya Shilpa, Kosmicki, Jack A., Horowitz, Julie E., Baras, Ari, Gass, Matthew C., Yadav, Ashish, Mirshahi, Tooraj, Hottenga, Jouke Jan, Bartels, Meike, de geus, Eco E. J. C., Nivard, Michel M. G., Verma, Anurag, Ritchie, Marylyn D., Rader, Daniel, Li, Binglan, Verma, Shefali S., Lucas, Anastasia, Bradford, Yuki, Abedalthagafi, Malak, Alaamery, Manal, Alshareef, Abdulraheem, Sawaji, Mona, Massadeh, Salam, AlMalik, Abdulaziz, Alqahtani, Saleh, Baraka, Dona, Harthi, Fawz Al, Alsolm, Ebtehal, Safieh, Leen Abu, Alowayn, Albandary M., Alqubaishi, Fatimah, Mutairi, Amal Al, Mangul, Serghei, Almutairi, Mansour, Aljawini, Nora, Albesher, Nour, Arabi, Yaseen M., Mahmoud, Ebrahim S., Khattab, Amin K., Halawani, Roaa T., Alahmadey, Ziab Z., Albakri, Jehad K., Felemban, Walaa A., Suliman, Bandar A., Hasanato, Rana, Al-Awdah, Laila, Alghamdi, Jahad, AlZahrani, Deema, AlJohani, Sameera, Al-Afghani, Hani, AlDhawi, Nouf, AlBardis, Hadeel, Alkwai, Sarah, Alswailm, Moneera, Almalki, Faisal, Albeladi, Maha, Almohammed, Iman, Barhoush, Eman, Albader, Anoud, Alotaibi, Sara, Alghamdi, Bader, Jung, Junghyun, fawzy, Mohammad S., Alrashed, May, Zeberg, Hugo, Nkambul, Lindo, Frithiof, Robert, Hultström, Michael, Lipcsey, Miklo, Tardif, Nicola, Rooyackers, Olav, Grip, Jonathan, Maricic, Tomislav, Helgeland, Øyvind, Magnus, Per, Trogstad, Lill-Iren S., Lee, Yunsung, Harris, Jennifer R., Mangino, Massimo, Spector, Tim D., Emma, Duncan, Moutsianas, Louka, Caulfield, Mark J., Scott, Richard H., Kousathanas, Athanasio, Pasko, Dorota, Walker, Susan, Stuckey, Alex, Odhams, Christopher A., Rhodes, Daniel, Fowler, Tom, Rendon, Augusto, Chan, Georgia, Arumugam, Prabhu, Karczewski, Konrad J., Martin, Alicia R., Wilson, Daniel J., Spencer, Chris C. A., Crook, Derrick W., Wyllie, David H., O’Connell, Anne Marie, Atkinson, Elizabeth G., Tsuo, Kristin, Baya, Nikola, Turley, Patrick, Gupta, Rahul, Walters, Raymond K., Palmer, Duncan S., Sarma, Gopal, Cheng, Nathan, Lu, Wenhan, Churchhouse, Claire, Goldstein, Jacqueline I., King, Daniel, Seed, Cotton, Daly, Mark J., Finucane, Hilary, Bryant, Sam, Satterstrom, F. Kyle, Band, Gavin, Earle, Sarah G., Lin, Shang-Kuan, Arning, Nicola, Koelling, Nil, Armstrong, Jacob, Rudkin, Justine K., Callier, Shawneequa, Cusick, Caroline, Soranzo, Nicole, Zhao, Jing Hua, Danesh, John, Angelantonio, Emanuele Di, Butterworth, Adam S., Sun, Yan V., Huffman, Jennifer E., Cho, Kelly, O’Donnell, Christopher J., Tsao, Phil, Gaziano, J. Michael, Peloso, Gina, Ho, Yuk-Lam, Smieszek, Sandra P., Polymeropoulos, Christo, Polymeropoulos, Vasilio, Polymeropoulos, Mihael H., Przychodzen, Bartlomiej P., Fernandez-Cadenas, Israel, Planas, Anna M., Perez-Tur, Jordi, Llucià-Carol, Laia, Cullell, Natalia, Muiño, Elena, Cárcel-Márquez, Jara, DeDiego, Marta L., Iglesias, Lara Lloret, Soriano, Alex, Rico, Veronica, Agüero, Daiana, Bedini, Josep L., Lozano, Francisco, Domingo, Carlo, Robles, Veronica, Ruiz-Jaén, Francisca, Márquez, Leonardo, Gomez, Juan, Coto, Eliecer, Albaiceta, Guillermo M., García-Clemente, Marta, Dalmau, David, Arranz, Maria J., Dietl, Beatriz, Serra-Llovich, Alex, Soler, Pere, Colobrán, Roger, Martín-Nalda, Andrea, Martínez, Alba Parra, Bernardo, David, Rojo, Silvia, Fiz-López, Aida, Arribas, Elisa, de la Cal-Sabater, Paloma, Segura, Tomá, González-Villa, Esther, Serrano-Heras, Gemma, Martí-Fàbregas, Joan, Jiménez-Xarrié, Elena, de Felipe Mimbrera, Alicia, Masjuan, Jaime, García-Madrona, Sebastian, Domínguez-Mayoral, Anna, Villalonga, Joan Montaner, Menéndez-Valladares, Paloma, Chasman, Daniel I., Sesso, Howard D., Manson, JoAnn E., Buring, Julie E., Ridker, Paul M., Franco, Giulianini, Davis, Lea, Lee, Sulggi, Priest, Jame, Sankaran, Vijay G., van Heel, David, Biesecker, Le, Kerchberger, V. Eric, Baillie, J. Kenneth, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Biological Psychology, APH - Mental Health, AMS - Sports, AMS - Ageing & Vitality, APH - Methodology, Mccurdy, Shannon, Mccormick, Joseph B., Macarthur, Daniel, Maclaughlin, Bev, Lefaive, Jonathon, Almalik, Abdulaziz, Alzahrani, Deema, Aljohani, Sameera, Aldhawi, Nouf, Albardis, Hadeel, Fawzy, Mohammad S., Dediego, Marta L., Stem Cell Aging Leukemia and Lymphoma (SALL), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Life Course Epidemiology (LCE), Groningen Research Institute for Asthma and COPD (GRIAC), University of Zurich, COVID-19 Host Genetics Initiative, Barcelona Supercomputing Center, COVID-19 Genetics Initiative, including authors, Institute for Molecular Medicine Finland, and Data Science Genetic Epidemiology Lab
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Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC] ,Quantitative Trait Loci ,MUC5B PROMOTER POLYMORPHISM ,Genome-wide association studies ,COVID-19 (Malaltia) ,UFSP13-7 Evolution in Action: From Genomes to Ecosystems ,COVID-19 (Disease) ,Settore BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA ,SDG 3 - Good Health and Well-being ,Humans ,genetics ,Genetic variation ,Genomes ,Medicinsk genetik ,1000 Multidisciplinary ,Multidisciplinary ,Chromosome Mapping ,COVID-19 ,Human Genetics ,10124 Institute of Molecular Life Sciences ,covid-19 ,3121 General medicine, internal medicine and other clinical medicine ,570 Life sciences ,biology ,Medical Genetics - Abstract
Matters arising from: Mapping the human genetic architecture of COVID-19 Original Article published on 08 July 2021 https://www.nature.com/articles/s41586-021-03767-x The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity. Here we present meta-analyses bringing together 60 studies from 25 countries (Fig. 1 and Supplementary Table 1) for three COVID-19-related phenotypes: (1) individuals critically ill with COVID-19 on the basis of requiring respiratory support in hospital or who died as a consequence of the disease (9,376 cases, of which 3,197 are new in this data release, and 1,776,645 control individuals); (2) individuals with moderate or severe COVID-19 defined as those hospitalized due to symptoms associated with the infection (25,027 cases, 11,386 new and 2,836,272 control individuals); and (3) all cases with reported SARS-CoV-2 infection regardless of symptoms (125,584 cases, 76,022 new and 2,575,347 control individuals). Most studies have reported results before the roll out of the COVID-19 vaccination campaign. An overview of the study design is provided in Supplementary Fig. 1. We found a total of 23 genome-wide significant loci (P
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- 2022
4. ADHD & Pharmacotherapy: Past, Present and Future: A Review of the Changing Landscape of Drug Therapy for Attention Deficit Hyperactivity Disorder
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Connolly, JJ, Glessner, JT, Elia, J, and Hakonarson, H
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mental disorders ,Article - Abstract
Attention deficit hyperactivity disorder (ADHD) is the most common neurobiological disorder in children, with a prevalence of ~6–7%1,2 that has remained stable for decades2. The social and economic burden associated with patients3, families, and broader systems (healthcare/educational) is substantial, with the annual economic impact of ADHD exceed $30 billion in the US alone4. Efficacy of pharmacotherapy in treating ADHD symptoms has generally been considerable with at least ¾ of individuals benefitting from pharmacotherapy, typically in the form of stimulants5. In this review, we begin by briefly reviewing the history of pharmacotherapy in relation to ADHD, before focusing (primarily) on the state-of-the-field on themes such as biophysiology, pharmacokinetics, and pharmacogenomics. We conclude with a summary of emerging clinical and research studies, particularly the potential role for precision therapy in matching ADHD patients and drug types.
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- 2015
5. Erratum: Meta-analysis of dense genecentric association studies reveals common and uncommon variants associated with height ((The American Journal of Human Genetics (2010) 88 (6-18))
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Lanktree, MB, Guo, Y, Murtaza, M, Glessner, JT, Bailey, SD, Onland-Moret, NC, Lettre, G, Ongen, H, Rajagopalan, R, Johnson, T, Shen, H, Nelson, CP, Klopp, N, Baumert, J, Padmanabhan, S, Pankratz, N, Pankow, JS, Shah, S, Taylor, K, Barnard, J, Peters, BJ, Maloney, CM, Lobmeyer, MT, Stanton, A, Zafarmand, MH, Romaine, SPR, Mehta, A, Van Iperen, EPA, Gong, Y, Price, TS, Smith, EN, Kim, CE, Li, YR, Asselbergs, FW, Atwood, LD, Bailey, KM, Bhatt, D, Bauer, F, Behr, ER, Bhangale, T, Boer, JMA, Boehm, BO, Bradfield, JP, Brown, M, Braund, PS, Burton, PR, Carty, C, Chandrupatla, HR, Chen, W, Connell, J, Dalgeorgou, C, De Boer, A, Drenos, F, Elbers, CC, Fang, JC, Fox, CS, Frackelton, EC, Fuchs, B, Furlong, CE, Gibson, Q, Gieger, C, Goel, A, Grobbee, DE, Hastie, C, Howard, PJ, Huang, G-H, Johnson, WC, Li, Q, Kleber, ME, Klein, BEK, Klein, R, Kooperberg, C, Ky, B, Lacroix, A, Lanken, P, Lathrop, M, Li, M, Marshall, V, Melander, O, Mentch, FD, Meyer, NJ, Monda, KL, Montpetit, A, Murugesan, G, Nakayama, K, Nondahl, D, Onipinla, A, Rafelt, S, Newhouse, SJ, Otieno, FG, Patel, SR, Putt, ME, Rodriguez, S, Safa, RN, Sawyer, DB, Schreiner, PJ, Simpson, C, Sivapalaratnam, S, Srinivasan, SR, Suver, C, Swergold, G, Sweitzer, NK, Thomas, KA, Thorand, B, Timpson, NJ, Tischfield, S, Tobin, M, Tomaszewski, M, Verschuren, WMM, Wallace, C, Winkelmann, B, Zhang, H, Zheng, D, Zhang, L, Zmuda, JM, Clarke, R, Balmforth, AJ, Danesh, J, Day, IN, Schork, NJ, De Bakker, PIW, Delles, C, Duggan, D, Hingorani, AD, Hirschhorn, JN, Hofker, MH, Humphries, SE, Kivimaki, M, Lawlor, DA, Kottke-Marchant, K, Mega, JL, Mitchell, BD, Morrow, DA, Palmen, J, Redline, S, Shields, DC, Shuldiner, AR, Sleiman, PM, Smith, GD, Farrall, M, Jamshidi, Y, Christiani, DC, Casas, JP, Hall, AS, Doevendans, PA, Christie, JD, Berenson, GS, Murray, SS, Illig, T, Dorn, GW, Cappola, TP, Boerwinkle, E, Sever, P, Rader, DJ, Reilly, MP, Caulfield, M, Talmud, PJ, Topol, E, Engert, JC, Wang, K, Dominiczak, A, Hamsten, A, Curtis, SP, Silverstein, RL, Lange, LA, Sabatine, MS, Trip, M, Saleheen, D, Peden, JF, Cruickshanks, KJ, März, W, O'Connell, JR, Klungel, OH, Wijmenga, C, Maitland-Van Der Zee, AH, Schadt, EE, Johnson, JA, Jarvik, GP, Papanicolaou, GJ, Grant, SFA, Munroe, PB, North, KE, Samani, NJ, Koenig, W, Gaunt, TR, Anand, SS, Van Der Schouw, YT, Soranzo, N, Fitzgerald, GA, Reiner, A, Hegele, RA, Hakonarson, H, and Keating, BJ
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- 2012
6. Erratum: Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci (American Journal of Human Genetics (2012) 90 (410-425))
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Saxena, R, Elbers, CC, Guo, Y, Peter, I, Gaunt, TR, Mega, JL, Lanktree, MB, Tare, A, Castillo, BA, Li, YR, Johnson, T, Bruinenberg, M, Gilbert-Diamond, D, Rajagopalan, R, Voight, BF, Balasubramanyam, A, Barnard, J, Bauer, F, Baumert, J, Bhangale, T, Böhm, BO, Braund, PS, Burton, PR, Chandrupatla, HR, Clarke, R, Cooper-Dehoff, RM, Crook, ED, Davey-Smith, G, Day, IN, De Boer, A, De Groot, MCH, Drenos, F, Ferguson, J, Fox, CS, Furlong, CE, Gibson, Q, Gieger, C, Gilhuijs-Pederson, LA, Glessner, JT, Goel, A, Gong, Y, Grant, SFA, Grobbee, DE, Hastie, C, Humphries, SE, Kim, CE, Kivimaki, M, Kleber, M, Meisinger, C, Kumari, M, Langaee, TY, Lawlor, DA, Li, M, Lobmeyer, MT, Maitland-Van Der Zee, A-H, Meijs, MFL, Molony, CM, Morrow, DA, Murugesan, G, Musani, SK, Nelson, CP, Newhouse, SJ, O'Connell, JR, Padmanabhan, S, Palmen, J, Patel, SR, Pepine, CJ, Pettinger, M, Price, TS, Rafelt, S, Ranchalis, J, Rasheed, A, Rosenthal, E, Ruczinski, I, Shah, S, Shen, H, Silbernagel, G, Smith, EN, Spijkerman, AWM, Stanton, A, Steffes, MW, Thorand, B, Trip, M, Van Der Harst, P, Van Der A, DL, Van Iperen, EPA, Van Setten, J, Van Vliet-Ostaptchouk, JV, Verweij, N, Wolffenbuttel, BHR, Young, T, Hadi Zafarmand, M, Zmuda, JM, Boehnke, M, Altshuler, D, McCarthy, M, Linda Kao, WH, Pankow, JS, Cappola, TP, Sever, P, Poulter, N, Caulfield, M, Dominiczak, A, Shields, DC, Bhatt, DL, Zhang, L, Curtis, SP, Danesh, J, Casas, JP, Van Der Schouw, YT, Onland-Moret, NC, Doevendans, PA, Dorn II, GW, Farrall, M, Fitzgerald, GA, Robert Hegele, AH, Hingorani, AD, Hofker, MH, Huggins, GS, Illig, T, Jarvik, GP, Johnson, JA, Klungel, OH, Knowler, WC, Koenig, W, März, W, Meigs, JB, Melander, O, Munroe, PB, Mitchell, BD, Bielinski, SJ, Rader, DJ, Reilly, MP, Rich, SS, Rotter, JI, Saleheen, D, Samani, NJ, Schadt, EE, Shuldiner, AR, Silverstein, R, Kottke-Marchant, K, Talmud, PJ, Watkins, H, Asselbergs, FW, De Bakker, PIW, McCaffery, J, Wijmenga, C, Sabatine, MS, Wilson, JG, Reiner, A, Bowden, DW, Hakonarson, H, Siscovick, DS, and Keating, BJ
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- 2012
7. Association of the TRAF1-C5 locus on chromosome 9 with juvenile idiopathic arthritis.
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Behrens EM, Finkel TH, Bradfield JP, Kim CE, Linton L, Casalunovo T, Frackelton EC, Santa E, Otieno FG, Glessner JT, Chiavacci RM, Grant SF, and Hakonarson H
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- 2008
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8. Common variations in BARD1 influence susceptibility to high-risk neuroblastoma
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Wendy B. London, Shahab Asgharzadeh, Nazneen Rahman, Sharon J. Diskin, Robert C. Seeger, Edward F. Attiyeh, Struan F.A. Grant, Marcella Devoto, Hongzhe Li, Carmel McConville, Cynthia Winter, Richard H Scott, Jonathan P. Bradfield, Maria Garris, Marci Laudenslager, Yael P. Mosse, Jayanti Jagannathan, Kristina A. Cole, Cecilia Kim, Kristopher R. Bosse, Eric F. Rappaport, John M. Maris, Mario Capasso, Joseph T. Glessner, Cuiping Hou, Hakon Hakonarson, Maura Diamond, Capasso, Mario, Devoto, M, Hou, C, Asgharzadeh, S, Glessner, Jt, Attiyeh, Ef, Mosse, Yp, Kim, C, Diskin, Sj, Cole, Ka, Bosse, K, Diamond, M, Laudenslager, M, Winter, C, Bradfield, Jp, Scott, Rh, Jagannathan, J, Garris, M, Mcconville, C, London, Wb, Seeger, Rc, Grant, Sf, Li, H, Rahman, N, Rappaport, E, Hakonarson, H, and Maris, J. M.
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Heterozygote ,Genotype ,Ubiquitin-Protein Ligases ,Genome-wide association study ,Single-nucleotide polymorphism ,Locus (genetics) ,Biology ,Polymorphism, Single Nucleotide ,Article ,03 medical and health sciences ,Neuroblastoma ,0302 clinical medicine ,Risk Factors ,Genetics ,Genetic predisposition ,medicine ,Odds Ratio ,SNP ,Humans ,Genetic Predisposition to Disease ,Allele ,030304 developmental biology ,0303 health sciences ,Tumor Suppressor Proteins ,Genetic Variation ,Odds ratio ,medicine.disease ,030220 oncology & carcinogenesis ,Chromosomes, Human, Pair 6 - Abstract
We conducted a SNP-based genome-wide association study (GWAS) focused on the high-risk subset of neuroblastoma. As our previous unbiased GWAS showed strong association of common 6p22 SNP alleles with aggressive neuroblastoma, we restricted our analysis here to 397 high-risk cases compared to 2,043 controls. We detected new significant association of six SNPs at 2q35 within the BARD1 locus (P(allelic) = 2.35 x 10(-9)-2.25 x 10(-8)). We confirmed each SNP association in a second series of 189 high-risk cases and 1,178 controls (P(allelic) = 7.90 x 10(-7)-2.77 x 10(-4)). We also tested the two most significant SNPs (rs6435862, rs3768716) in two additional independent high-risk neuroblastoma case series, yielding combined allelic odds ratios of 1.68 each (P = 8.65 x 10(-18) and 2.74 x 10(-16), respectively). We also found significant association with known BARD1 nonsynonymous SNPs. These data show that common variation in BARD1 contributes to the etiology of the aggressive and most clinically relevant subset of human neuroblastoma.
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- 2009
9. Individual common variants exert weak effects on the risk for autism spectrum disorderspi
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Naisha Shah, William M. McMahon, Barbara Parrini, Jeremy R. Parr, Thomas Bourgeron, Vanessa Hus, Gudrun Nygren, Sabine M. Klauck, John B. Vincent, Nadine M. Melhem, Jillian P. Casey, Christina Corsello, Jonathan L. Haines, Andrew D. Paterson, Raffaella Tancredi, Alistair T. Pagnamenta, Jonathan Green, Richard Delorme, Geraldine Dawson, Andrew Pickles, Carine Mantoulan, Alexander Kolevzon, Bridget A. Fernandez, Frederico Duque, Inês Sousa, Tara Paton, Kathryn Roeder, Joana Almeida, Richard Anney, Margaret A. Pericak-Vance, Joachim Hallmayer, Gerard D. Schellenberg, Sabata C. Lund, Rita M. Cantor, Daniel H. Geschwind, Janine A. Lamb, Annette Estes, Sven Bölte, Hakon Hakonarson, Gillian Hughes, Gillian Baird, John I. Nurnberger, Jessica Brian, Bernie Devlin, Roberta Igliozzi, Vera Stoppioni, Jiannis Ragoussis, Peter Szatmari, Ghazala Mirza, Eric Fombonne, Thomas H. Wassink, Emily L. Crawford, Nuala Sykes, Danielle Zurawiecki, Graham Kenny, David J. Posey, Elena Maestrini, Vlad Kustanovich, Elena Bacchelli, Veronica J. Vieland, Stephen W. Scherer, Guiomar Oliveira, Simon Wallace, John R. Gilbert, Latha Soorya, Sean Brennan, Tiago R. Magalhaes, Hilary Coon, Elizabeth A. Heron, Sabine Schlitt, Fritz Poustka, Astrid M. Vicente, Patrick Bolton, Linda Lotspeich, Nancy J. Minshew, Val C. Sheffield, Bennett L. Leventhal, Xiao-Qing Liu, Andrew Green, Joseph D. Buxbaum, Shawn Wood, Susan E. Folstein, Sean Ennis, Catarina Correia, James S. Sutcliffe, Carolyn Noakes, Ann Le Couteur, Marion Leboyer, Ann P. Thompson, Christine M. Freitag, Fred R. Volkmar, Katerina Papanikolaou, Dalila Pinto, Agatino Battaglia, Frances Lombard, Joseph Piven, Maretha de Jonge, Michael Rutter, Clara Lajonchere, Kerstin Wittemeyer, Herman van Engeland, Michael L. Cuccaro, Richard Holt, Lonnie Zwaigenbaum, Louise Gallagher, Jeff Munson, Ana Tryfon, John Tsiantis, Lambertus Klei, Christopher Gillberg, Penny Farrar, Joseph T. Glessner, Ellen M. Wijsman, Anthony P. Monaco, Wendy Roberts, Nadia Bolshakova, Cecilia Kim, Judith Miller, Stephen J. Guter, Susanne Thomson, Catherine Lord, Anthony J. Bailey, Miriam Law-Smith, Michael Gill, Christopher J. McDougle, Bernadette Rogé, Alison K. Merikangas, Jacob A. S. Vorstman, Suma Jacob, Judith Conroy, Kirsty Wing, Regina Regan, Jennifer L. Howe, Stanley F. Nelson, Edwin H. Cook, Catalina Betancur, Eftichia Duketis, Division of Mental Health and Addiction, Oslo University Hospital [Oslo], Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), The Centre for Applied Genomics, Toronto, University of Toronto-The Hospital for sick children [Toronto] (SickKids)-Department of Molecular Genetics-McLaughlin Centre, Unidade de Neurodesenvolvimento e Autismo (UNDA), Hospital Pediatrico de Coimbra, Department of Pharmacy and Biotechnology, Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Newcomen Centre, Guy's Hospital [London], Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Goethe-Universität Frankfurt am Main, Department of Child and Adolescent Psychiatry, Institute of psychiatry, Molecular and Cellular Neurobiology, Autism Research Unit, The Hospital for sick children [Toronto] (SickKids)-University of Toronto, Academic Centre on Rare Diseases (ACoRD), University College Dublin [Dublin] (UCD), Instituto Nacional de Saùde Dr Ricardo Jorge [Portugal] (INSA), BioFIG, Center for Biodiversity, Functional and Integrative Genomics, Autism and Communicative Disorders Centre, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Department of Molecular Physiology & Biophysics and Psychiatry, Vanderbilt University [Nashville]-Centers for Human Genetics Research and Molecular Neuroscience, Vanderbilt Brain Institute, Vanderbilt University School of Medicine [Nashville], Department of Psychiatry, University Medical Center [Utrecht]-Brain Center Rudolf Magnus, Service de psychopathologie de l'enfant et de l'adolescent, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Robert Debré-Université Paris Diderot - Paris 7 (UPD7), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Department of Speech and Hearing Sciences [Washington], University of Washington [Seattle], The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], Disciplines of Genetics and Medicine, Memorial University of Newfoundland [St. John's], University of Miami School of Medicine, John P. Hussman Institute for Human Genomics, University of Miami [Coral Gables], Research Unit on Children's Psychosocial Maladjustment, Université Laval [Québec] (ULaval)-Department of Psychology, University of Gothenburg (GU), The Center for Applied Genomics, Children’s Hospital of Philadelphia (CHOP ), Manchester Academic Health Sciences Centre, Department of Disability and Human Development, University of Illinois [Chicago] (UIC), University of Illinois System-University of Illinois System, Program in Genetics and Genomic Biology, Hospital for Sick Children-University of Toronto McLaughlin Centre, Department of Psychiatry and Behavioral Sciences [Stanford], Stanford Medicine, Stanford University-Stanford University, Human Genetics Center, The University of Texas Health Science Center at Houston (UTHealth), Autism Genetic Resource Exchange, Autism Speaks, Centre for Integrated Genomic Medical Research, Manchester, University of Manchester [Manchester], Service de psychiatrie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Hôpital Albert Chenevier, European Network of Bipolar Research Expert Centres (ENBREC), ENBREC, Newcastle University [Newcastle]-Institute of Health & Society (Child & Adolescent Psychiatry), New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU), Centre de Référence du Syndrome de Prader-Willi, CHU Toulouse [Toulouse], Indiana University School of Medicine, Indiana University System-Indiana University System, Department of Psychiatry and Behavioral Sciences, University Department of Child Psychiatry, National and Kapodistrian University of Athens (NKUA), Department of Medicine, Manchester, University of Manchester [Manchester]-School of Epidemiology and Health Science, Department of Statistics, Carnegie Mellon University [Pittsburgh] (CMU), Octogone Unité de Recherche Interdisciplinaire (Octogone), Université Toulouse - Jean Jaurès (UT2J), Social, Genetic and Developmental Psychiatry Centre, Department of Pediatrics, University of Iowa [Iowa City]-Howard Hughes Medical-Institute Carver College of Medicine, Neuropsichiatria Infantile, Ospedale Santa Croce, Department of Psychiatry and Behavioural Neurosciences, McMaster University [Hamilton, Ontario]-Offord Centre for Child Studies, University of Toronto, Child Study Centre, Yale University School of Medicine, University of Oxford [Oxford]-Warneford Hospital, University of Alberta, MRC Social, Genetic and Developmental Psychiatry Centre (SGDP), The Institute of Psychiatry-King‘s College London, Department of Human Genetics, Los Angeles, David Geffen School of Medicine [Los Angeles], University of California [Los Angeles] (UCLA), University of California-University of California-University of California [Los Angeles] (UCLA), University of California-University of California, Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris [Pisa], Autism Speaks and the Department of Psychiatry, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Department of Neurology, University of California-University of California-David Geffen School of Medicine [Los Angeles], Division of Molecular Genome Analysis, German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Institutes of Neuroscience and Health and Society, Newcastle University [Newcastle], Carolina Institute for Developmental Disabilities, Pathology and Laboratory Medicine, University of Pennsylvania [Philadelphia], Carver College of Medicine [Iowa City], University of Iowa [Iowa City]-University of Iowa [Iowa City], Departments of Biostatistics and Medicine, Physiopathologie des Maladies du Système Nerveux Central, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Stanford School of Medicine [Stanford], Battelle Center for Mathematical Medicine, Ohio State University [Columbus] (OSU)-Nationwide Children's Hospital, Children’s Hospital of Philadelphia (CHOP )-Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia], The Hospital for sick children [Toronto] (SickKids)-University of Toronto-Department of Molecular Genetics-McLaughlin Centre, Memorial University of Newfoundland = Université Memorial de Terre-Neuve [St. John's, Canada] (MUN), Yale School of Medicine [New Haven, Connecticut] (YSM), King‘s College London-The Institute of Psychiatry, University of California (UC)-University of California (UC)-University of California [Los Angeles] (UCLA), University of California (UC)-University of California (UC), University of California (UC)-University of California (UC)-David Geffen School of Medicine [Los Angeles], Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia]-Children’s Hospital of Philadelphia (CHOP ), Anney R, Klei L, Pinto D, Almeida J, Bacchelli E, Baird G, Bolshakova N, Bölte S, Bolton PF, Bourgeron T, Brennan S, Brian J, Casey J, Conroy J, Correia C, Corsello C, Crawford EL, de Jonge M, Delorme R, Duketis E, Duque F, Estes A, Farrar P, Fernandez BA, Folstein SE, Fombonne E, Gilbert J, Gillberg C, Glessner JT, Green A, Green J, Guter SJ, Heron EA, Holt R, Howe JL, Hughes G, Hus V, Igliozzi R, Jacob S, Kenny GP, Kim C, Kolevzon A, Kustanovich V, Lajonchere CM, Lamb JA, Law-Smith M, Leboyer M, Le Couteur A, Leventhal BL, Liu XQ, Lombard F, Lord C, Lotspeich L, Lund SC, Magalhaes TR, Mantoulan C, McDougle CJ, Melhem NM, Merikangas A, Minshew NJ, Mirza GK, Munson J, Noakes C, Nygren G, Papanikolaou K, Pagnamenta AT, Parrini B, Paton T, Pickles A, Posey DJ, Poustka F, Ragoussis J, Regan R, Roberts W, Roeder K, Roge B, Rutter ML, Schlitt S, Shah N, Sheffield VC, Soorya L, Sousa I, Stoppioni V, Sykes N, Tancredi R, Thompson AP, Thomson S, Tryfon A, Tsiantis J, Van Engeland H, Vincent JB, Volkmar F, Vorstman J, Wallace S, Wing K, Wittemeyer K, Wood S, Zurawiecki D, Zwaigenbaum L, Bailey AJ, Battaglia A, Cantor RM, Coon H, Cuccaro ML, Dawson G, Ennis S, Freitag CM, Geschwind DH, Haines JL, Klauck SM, McMahon WM, Maestrini E, Miller J, Monaco AP, Nelson SF, Nurnberger JI Jr, Oliveira G, Parr JR, Pericak-Vance MA, Piven J, Schellenberg GD, Scherer SW, Vicente AM, Wassink TH, Wijsman EM, Betancur C, Buxbaum JD, Cook EH, Gallagher L, Gill M, Hallmayer J, Paterson AD, Sutcliffe JS, Szatmari P, Vieland VJ, Hakonarson H, Devlin B, University of Oxford, Pôle Enfants [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), University of Oxford-Warneford Hospital, University of Pennsylvania, University of Pennsylvania-University of Pennsylvania-Children’s Hospital of Philadelphia (CHOP ), Betancur, Catalina, and Université de Toulouse (UT)-Université de Toulouse (UT)
- Subjects
Male ,CNTNAP2 ,Genotype ,Genome-wide association study ,Single-nucleotide polymorphism ,Nerve Tissue Proteins ,[SDV.GEN] Life Sciences [q-bio]/Genetics ,Biology ,Language Development ,Polymorphism, Single Nucleotide ,03 medical and health sciences ,0302 clinical medicine ,autism spectrum disorders (ASDs) ,Gene Frequency ,Risk Factors ,mental disorders ,Genetics ,medicine ,Humans ,Genetic Predisposition to Disease ,Copy-number variation ,Allele ,GENOME-WIDE ASSOCIATION ,Child ,Molecular Biology ,Allele frequency ,Genetics (clinical) ,Alleles ,030304 developmental biology ,0303 health sciences ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,Association Studies Articles ,Membrane Proteins ,General Medicine ,medicine.disease ,Genetic architecture ,Child Development Disorders, Pervasive ,common variant ,Perturbações do Desenvolvimento Infantil e Saúde Mental ,Autism ,Female ,030217 neurology & neurosurgery ,Genome-Wide Association Study - Abstract
International audience; While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.
- Published
- 2012
10. A genome-wide scan for common alleles affecting risk for autism
- Author
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Veronica J. Vieland, Stephen W. Scherer, Elizabeth A. Heron, Barbara Parrini, Jeremy R. Parr, Louise Gallagher, Jeff Munson, Annemarie Poustka, Susan E. Folstein, Irene Drmic, Gudrun Nygren, John P. Rice, Jeff Salt, Simon Wallace, Geraldine Dawson, Daniel H. Geschwind, Annette Estes, Sean Brennan, Alistair T. Pagnamenta, Nancy J. Minshew, Christina Corsello, Jonathan Green, William M. McMahon, Christopher Gillberg, Kathryn Roeder, Lambertus Klei, Anath C. Lionel, Bridget A. Fernandez, Thomas Bourgeron, Ellen M. Wijsman, Gerard D. Schellenberg, Wendy Roberts, Jeremy Goldberg, Frederico Duque, Ghazala Mirza, Sean Ennis, Joana Almeida, Nadine M. Melhem, Jillian P. Casey, Roberta Igliozzi, Ricardo Segurado, Carine Mantoulan, Katy Renshaw, Kai Wang, Andrew D. Paterson, Raffaella Tancredi, Matthew Nicholas Hill, Richard Anney, Christian R. Marshall, Anthony P. Monaco, Linda Lotspeich, Marion Leboyer, Richard Holt, Andrew Pickles, Vlad Kustanovich, William M. Mahoney, Jessica Brian, Inês Sousa, Peter Szatmari, Vanessa Hus, Janine A. Lamb, Hakon Hakonarson, Lonnie Zwaigenbaum, John Tsiantis, David J. Posey, Olena Korvatska, Guillermo Casallo, Rita M. Cantor, Bhooma Thiruvahindrapduram, Nadia Bolshakova, Sven Bölte, Alison K. Merikangas, Brian L. Yaspan, Cecilia Kim, Andrew Crossett, Fritz Poustka, Danielle Zurawiecki, Agatino Battaglia, Sabata C. Lund, Ann P. Thompson, Bennett L. Leventhal, Jessica Rickaby, Zhouzhi Wang, John I. Nurnberger, Astrid M. Vicente, Maretha de Jonge, Tiago R. Magalhaes, Michael L. Cuccaro, Val C. Sheffield, Nuala Sykes, Elena Maestrini, Guiomar Oliveira, Joseph D. Buxbaum, Fred R. Volkmar, Shawn Wood, Magdalena Laskawiec, Katherine Sansom, Herman van Engeland, Jane McGrath, Thomas H. Wassink, Su H. Chu, Elena Bacchelli, Carolyn Noakes, Ann Le Couteur, Catarina Correia, Ohsuke Migita, Bernie Devlin, Hilary Coon, Gillian Baird, Joseph Piven, Tom Berney, Ana Tryfon, Abdul Noor, Patrick Bolton, Latha Soorya, Vera Stoppioni, Stephen J. Guter, Joseph T. Glessner, Michael Gill, Christopher J. McDougle, Anthony J. Bailey, Margaret A. Pericak-Vance, Joachim Hallmayer, Christine M. Freitag, Penny Farrar, Kirsty Wing, Katherine E. Tansey, Bernadette Rogé, Michael Rutter, Christina Strawbridge, Brett S. Abrahams, Kerstin Wittemeyer, Laura J. Bierut, Tara Paton, Emily L. Crawford, Jonathan L. Haines, Alexander Kolevzon, Gillian Hughes, Lili Senman, James S. Sutcliffe, John B. Gilbert, Katerina Papanikolaou, Andrew R. Carson, Lynne E Cochrane, Regina Regan, Judith Miller, Susanne Thomson, Helen McConachie, Daisuke Sato, Richard Delorme, Jiannis Ragoussis, Eric Fombonne, Clara Lajonchere, Judith Conroy, Dalila Pinto, Aparna Prasad, Naisha Shah, Stanley F. Nelson, Sabine M. Klauck, Catalina Betancur, John B. Vincent, Eftichia Duketis, Jennifer L. Howe, Edwin H. Cook, Xiao-Qing Liu, Catherine Lord, Division of Mental Health and Addiction, Oslo University Hospital [Oslo], Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), Program in Genetics and Genomic Biology, Hospital for Sick Children-University of Toronto McLaughlin Centre, Academic Centre on Rare Diseases (ACoRD), University College Dublin [Dublin] (UCD), Instituto Nacional de Saùde Dr Ricardo Jorge [Portugal] (INSA), BioFIG, Center for Biodiversity, Functional and Integrative Genomics, Department of Neurology, University of California [Los Angeles] (UCLA), University of California-University of California-David Geffen School of Medicine [Los Angeles], University of California-University of California, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], Unidade de Neurodesenvolvimento e Autismo (UNDA), Hospital Pediatrico de Coimbra, Department of Pharmacy and Biotechnology, Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Department of Psychiatry, University of Oxford [Oxford]-Warneford Hospital, Newcomen Centre, Guy's Hospital [London], Department of Psychiatry and Behavioral Sciences [Stanford], Stanford Medicine, Stanford University-Stanford University, Child and Adolescent Mental Health, Newcastle University [Newcastle], Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Goethe-Universität Frankfurt am Main, Department of Child and Adolescent Psychiatry, Institute of psychiatry, Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Autism Research Unit, University of Toronto-The Hospital for sick children [Toronto] (SickKids), Autism and Communicative Disorders Centre, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Department of Molecular Physiology & Biophysics and Psychiatry, Vanderbilt University [Nashville]-Centers for Human Genetics Research and Molecular Neuroscience, Department of Statistics, Carnegie Mellon University [Pittsburgh] (CMU), Scientific Affairs, Autism Speaks, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), University Medical Center [Utrecht]-Brain Center Rudolf Magnus, Service de psychopathologie de l'enfant et de l'adolescent, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Robert Debré-Université Paris Diderot - Paris 7 (UPD7), Department of Speech and Hearing Sciences [Washington], University of Washington [Seattle], Disciplines of Genetics and Medicine, Memorial University of Newfoundland [St. John's], John P. Hussman Institute for Human Genomics, University of Miami [Coral Gables], Department of Child Psychiatry, McGill University = Université McGill [Montréal, Canada]-Montreal Children's Hospital, McGill University Health Center [Montreal] (MUHC)-McGill University Health Center [Montreal] (MUHC), University of Gothenburg (GU), The Center for Applied Genomics, Children’s Hospital of Philadelphia (CHOP ), Department of Psychiatry and Behavioural Neurosciences, McMaster University [Hamilton, Ontario], Manchester Academic Health Sciences Centre, Institute for Juvenile Research-University of Illinois [Chicago] (UIC), University of Illinois System-University of Illinois System, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia]-Children’s Hospital of Philadelphia (CHOP ), Division of Molecular Genome Analysis, German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Human Genetics Center, The University of Texas Health Science Center at Houston (UTHealth), Department of Medicine, Autism Genetic Resource Exchange, Centre for Integrated Genomic Medical Research, Manchester, University of Manchester [Manchester], Institut Universitaire d'Hématologie (IUH), Université Paris Diderot - Paris 7 (UPD7), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Nathan Kline Institute for Psychiatric Research (NKI), Nathan Kline Institute for Psychiatric Research, New York University [New York] (NYU), NYU System (NYU)-NYU System (NYU)-NYU Child Study Center, Centre d'Etudes et de Recherches en PsychoPathologie, Université Toulouse - Jean Jaurès (UT2J), Indiana University School of Medicine, Indiana University System-Indiana University System, Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris [Pisa], Departments of Psychiatry and Neurology, Department of Psychiatry and Behavioral Sciences, Department of Human Genetics, Los Angeles, David Geffen School of Medicine [Los Angeles], University of California-University of California-University of California [Los Angeles] (UCLA), Centre for Addiction and Mental Health, Clarke Institute, University Department of Child Psychiatry, National and Kapodistrian University of Athens (NKUA), Institutes of Neuroscience and Health and Society, Department of Medicine, Manchester, University of Manchester [Manchester]-School of Epidemiology and Health Science, Carolina Institute for Developmental Disabilities, Social, Genetic and Developmental Psychiatry Centre, Washington University in Saint Louis (WUSTL), Howard Hughes Medical-Institute Carver College of Medicine-University of Iowa [Iowa City], Neuropsichiatria Infantile, Ospedale Santa Croce, Child Study Centre, Yale University School of Medicine, Carver College of Medicine [Iowa City], University of Iowa [Iowa City]-University of Iowa [Iowa City], University of Alberta, Physiopathologie des Maladies du Système Nerveux Central, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Vanderbilt Brain Institute, Vanderbilt University School of Medicine [Nashville], Pathology and Laboratory Medicine, University of Pennsylvania [Philadelphia], Battelle Center for Mathematical Medicine, Ohio State University [Columbus] (OSU)-Nationwide Children's Hospital, Departments of Biostatistics and Medicine, This research was primarily supported by Autism Speaks (USA), the Health Research Board (HRB, Ireland), The Medical Research Council (MRC, UK), Genome Canada/Ontario Genomics Institute, and the Hilibrand Foundation (USA). Additional support for individual groups was provided by the US National Institutes of Health [HD055751, HD055782, HD055784, HD35465, MH52708, MH55284, MH057881, MH061009, MH06359, MH066673, MH077930, MH080647, MH081754, MH66766, NS026630, NS042165, NS049261], the Canadian Institutes for Health Research (CIHR), Assistance Publique-Hôpitaux de Paris (France), Autistica, Canada Foundation for Innovation/Ontario Innovation Trust, Deutsche Forschungsgemeinschaft (grant: Po 255/17-4) (Germany), EC Sixth FP AUTISM MOLGEN, Fundação Calouste Gulbenkian (Portugal), Fondation de France, Fondation FondaMental (France), Fondation Orange (France), Fondation pour la Recherche Médicale (France), Fundação para a Ciência e Tecnologia (Portugal), GlaxoSmithKline-CIHR Pathfinder Chair (Canada), the Hospital for Sick Children Foundation and University of Toronto (Canada), INSERM (France), Institut Pasteur (France), the Italian Ministry of Health [convention 181 of 19.10.2001], the John P Hussman Foundation (USA), McLaughlin Centre (Canada), Netherlands Organization for Scientific Research [Rubicon 825.06.031], Ontario Ministry of Research and Innovation (Canada), Royal Netherlands Academy of Arts and Sciences [TMF/DA/5801], the Seaver Foundation (USA), the Swedish Science Council, The Centre for Applied Genomics (Canada), the Utah Autism Foundation (USA) and the Wellcome Trust core award [075491/Z/04 UK]. Funding support for the Study of Addiction: Genetics and Environment (SAGE) was provided through the NIH Genes, Environment and Health Initiative [GEI] (U01 HG004422)., University of California (UC)-University of California (UC)-David Geffen School of Medicine [Los Angeles], University of California (UC)-University of California (UC), The Hospital for sick children [Toronto] (SickKids)-University of Toronto, Memorial University of Newfoundland = Université Memorial de Terre-Neuve [St. John's, Canada] (MUN), University of California (UC)-University of California (UC)-University of California [Los Angeles] (UCLA), University of Iowa [Iowa City]-Howard Hughes Medical-Institute Carver College of Medicine, Yale School of Medicine [New Haven, Connecticut] (YSM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), University of Oxford, University of Oxford-Warneford Hospital, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania-University of Pennsylvania-Children’s Hospital of Philadelphia (CHOP ), Université de Toulouse (UT)-Université de Toulouse (UT), University of Pennsylvania, Betancur, Catalina, Anney R, Klei L, Pinto D, Regan R, Conroy J, Magalhaes TR, Correia C, Abrahams BS, Sykes N, Pagnamenta AT, Almeida J, Bacchelli E, Bailey AJ, Baird G, Battaglia A, Berney T, Bolshakova N, Bölte S, Bolton PF, Bourgeron T, Brennan S, Brian J, Carson AR, Casallo G, Casey J, Chu SH, Cochrane L, Corsello C, Crawford EL, Crossett A, Dawson G, de Jonge M, Delorme R, Drmic I, Duketis E, Duque F, Estes A, Farrar P, Fernandez BA, Folstein SE, Fombonne E, Freitag CM, Gilbert J, Gillberg C, Glessner JT, Goldberg J, Green J, Guter SJ, Hakonarson H, Heron EA, Hill M, Holt R, Howe JL, Hughes G, Hus V, Igliozzi R, Kim C, Klauck SM, Kolevzon A, Korvatska O, Kustanovich V, Lajonchere CM, Lamb JA, Laskawiec M, Leboyer M, Le Couteur A, Leventhal BL, Lionel AC, Liu XQ, Lord C, Lotspeich L, Lund SC, Maestrini E, Mahoney W, Mantoulan C, Marshall CR, McConachie H, McDougle CJ, McGrath J, McMahon WM, Melhem NM, Merikangas A, Migita O, Minshew NJ, Mirza GK, Munson J, Nelson SF, Noakes C, Noor A, Nygren G, Oliveira G, Papanikolaou K, Parr JR, Parrini B, Paton T, Pickles A, Piven J, Posey DJ, Poustka A, Poustka F, Prasad A, Ragoussis J, Renshaw K, Rickaby J, Roberts W, Roeder K, Roge B, Rutter ML, Bierut LJ, Rice JP, Salt J, Sansom K, Sato D, Segurado R, Senman L, Shah N, Sheffield VC, Soorya L, Sousa I, Stoppioni V, Strawbridge C, Tancredi R, Tansey K, Thiruvahindrapduram B, Thompson AP, Thomson S, Tryfon A, Tsiantis J, Van Engeland H, Vincent JB, Volkmar F, Wallace S, Wang K, Wang Z, Wassink TH, Wing K, Wittemeyer K, Wood S, Yaspan BL, Zurawiecki D, Zwaigenbaum L, Betancur C, Buxbaum JD, Cantor RM, Cook EH, Coon H, Cuccaro ML, Gallagher L, Geschwind DH, Gill M, Haines JL, Miller J, Monaco AP, Nurnberger JI Jr, Paterson AD, Pericak-Vance MA, Schellenberg GD, Scherer SW, Sutcliffe JS, Szatmari P, Vicente AM, Vieland VJ, Wijsman EM, Devlin B, Ennis S, and Hallmayer J.
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Genome-wide association study ,[SDV.GEN] Life Sciences [q-bio]/Genetics ,MESH: Genotype ,0302 clinical medicine ,Risk Factors ,MESH: Risk Factors ,Databases, Genetic ,Copy-number variation ,MESH: Genetic Variation ,Genetics (clinical) ,MESH: Databases, Genetic ,Genetics ,0303 health sciences ,education.field_of_study ,MESH: Polymorphism, Single Nucleotide ,Association Studies Articles ,MESH: Genetic Predisposition to Disease ,General Medicine ,MESH: European Continental Ancestry Group ,Autism spectrum disorders ,MESH: DNA Copy Number Variations ,Genotyping ,DNA Copy Number Variations ,Genotype ,Population ,MESH: Autistic Disorder ,Single-nucleotide polymorphism ,Biology ,Polymorphism, Single Nucleotide ,White People ,03 medical and health sciences ,Genetic variation ,Humans ,Genetic Predisposition to Disease ,ddc:610 ,Allele ,Autistic Disorder ,SNP association ,education ,Molecular Biology ,Alleles ,MESH: Genome, Human ,030304 developmental biology ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,MESH: Humans ,Genome, Human ,MESH: Alleles ,Haplotype ,Genetic Variation ,Genetic architecture ,Perturbações do Desenvolvimento Infantil e Saúde Mental ,MESH: Genome-Wide Association Study ,030217 neurology & neurosurgery ,Genome-Wide Association Study - Abstract
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C. Author has checked copyright TS 14.06.13 The subscript characters from the abstract have not copied across properly. TS
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- 2010
11. A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder
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Veronica J. Vieland, Stephen W. Scherer, Alison K. Merikangas, Naisha Shah, Edwin H. Cook, William M. McMahon, Kirsty Wing, Sabata C. Lund, Jacob A. S. Vorstman, Judith Conroy, Sabine M. Klauck, John B. Vincent, Astrid M. Vicente, Carine Mantoulan, Barbara Parrini, Jeremy R. Parr, Herman van Engeland, Jane McGrath, Guiomar Oliveira, Jonathan Green, James S. Sutcliffe, Peter Szatmari, Ann Le Couteur, Katerina Papanikolaou, Joseph Piven, Andrew Pickles, Gillian Baird, Inês Sousa, Gerard D. Schellenberg, Catarina Correia, Bennett L. Leventhal, Helen McConachie, Joseph T. Glessner, Fritz Poustka, Alistair T. Pagnamenta, Marion Leboyer, Nuala Sykes, Elena Maestrini, Penny Farrar, Maïté Tauber, Suzanne Foley, Richard Holt, Lonnie Zwaigenbaum, David J. Posey, John Tsiantis, Alexander Kolevzon, Agatino Battaglia, Maretha de Jonge, Hilary Coon, Gillian Hughes, John R. Gilbert, Patrick Bolton, Louise Gallagher, Jeff Munson, Kathy White, Michael L. Cuccaro, Annemarie Poustka, Daniel H. Geschwind, Richard Delorme, Annette Estes, Christine M. Freitag, Jillian P. Casey, Joana Almeida, Dalila Pinto, Simon Wallace, Sean Brennan, Stephen J. Guter, Stanley F. Nelson, Michael Rutter, Ghazala Mirza, Anthony J. Bailey, Christina Corsello, Kerstin Wittemeyer, Christian R. Marshall, Janine A. Lamb, Catherine Lord, Hakon Hakonarson, Jiannis Ragoussis, Catalina Betancur, Geraldine Dawson, Eftichia Duketis, Sean Ennis, Fiorella Minopoli, Christopher Gillberg, Vera Stoppioni, Bridget A. Fernandez, Frederico Duque, Eric Fombonne, Ellen M. Wijsman, Bernadette Rogé, Vanessa Hus, Susan E. Folstein, Jonathan L. Haines, Denis C. Shields, Tiago R. Magalhaes, Andrew Green, Thomas Bourgeron, Brian L. Yaspan, Ann P. Thompson, Gudrun Nygren, Judith Miller, Susanne Thomson, Roberta Igliozzi, Ana Filipa Sequeira, Kai Wang, Brett S. Abrahams, John I. Nurnberger, Michael Gill, Thomas H. Wassink, Christopher J. McDougle, Marc N. Coutanche, Anthony P. Monaco, Nadia Bolshakova, Cecilia Kim, Raffaella Tancredi, Rita M. Cantor, Phil Cali, Fred R. Volkmar, Tom Berney, Margaret A. Pericak-Vance, Joachim Hallmayer, Joseph D. Buxbaum, Elena Bacchelli, Latha Soorya, Richard Anney, Regina Regan, University of Bologna, Open University of Israël, IRCCS Fondazione Stella Maris [Pisa], Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris]-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris], AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Goethe-University Frankfurt am Main, Memorial University of Newfoundland [St. John's], McGill University = Université McGill [Montréal, Canada], Johns Hopkins University (JHU), Autism Research Centre and Section of Developmental Psychiatry, University of Cambridge [UK] (CAM), German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Psychiatrie génétique, Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Mondor de Recherche Biomédicale, The Hospital for sick children [Toronto] (SickKids), University of Toronto, Australian Resources Research Centre, Kensington, Sécurité et Qualité des Produits d'Origine Végétale (SQPOV), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Hôpital des Enfants, CHU Toulouse [Toulouse], School of Chemistry, Dalhousie University [Halifax], DLR Institut für Planetenforschung, Deutsches Zentrum für Luft- und Raumfahrt [Berlin] (DLR), Department of Human Genetics, University of Chicago, University of Alberta, Génétique de l'autisme = Genetics of Autism (NPS-01), Neurosciences Paris Seine (NPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai [New York] (MSSM), Institut Charles Gerhardt Montpellier - Institut de Chimie Moléculaire et des Matériaux de Montpellier (ICGM ICMMM), Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Institut de Chimie du CNRS (INC), University of Koblenz-Landau, McMaster University [Hamilton, Ontario], The authors acknowledge the families participating in the study and the main funders of the Autism Genome Project Consortium (AGP): Autism Speaks (USA), the Health Research Board (HRB, Ireland), The Medical Research Council (MRC, UK), Genome Canada/Ontario Genomics Institute, and the Hilibrand Foundation (USA). Additional support for individual groups was provided by the US National Institutes of Health (NIH grants HD055751, HD055782, HD055784, HD35465, MH52708, MH55284, MH57881, MH061009, MH06359, MH066673, MH080647, MH081754, MH66766, NS026630, NS042165, NS049261), the Canadian Institute for Advanced Research (CIFAR), the Canadian Institutes for Health Research (CIHR), Assistance Publique–Hôpitaux de Paris (France), Autistica, Canada Foundation for Innovation/Ontario Innovation Trust, Deutsche Forschungsgemeinschaft (grant Po 255/17-4) (Germany), EC Sixth FP AUTISM MOLGEN, Fundação Calouste Gulbenkian (Portugal), Fondation de France, Fondation FondaMental (France), Fondation Orange (France), Fondation pour la Recherche Médicale (France), Fundação para a Ciência e Tecnologia (Portugal), the Hospital for Sick Children Foundation and University of Toronto (Canada), INSERM (France), Institut Pasteur (France), the Italian Ministry of Health (convention 181 of 19.10.2001), the John P. Hussman Foundation (USA), McLaughlin Centre (Canada), Ontario Ministry of Research and Innovation (Canada), the Seaver Foundation (USA), the Swedish Science Council, The Centre for Applied Genomics (Canada), the Utah Autism Foundation (USA) and the Wellcome Trust core award 075491/Z/04 (UK). We acknowledge support from the Autism Genetic Resource Exchange (AGRE) and Autism Speaks. We gratefully acknowledge the resources provided by the AGRE consortium and the participating AGRE families. AGRE is a program of Autism Speaks and is supported, in part, by grant 1U24MH081810 from the National Institute of Mental Health to Clara M. Lajonchere (PI). We wish to acknowledge the National Children’s Research Centre Our Lady’s Children’s Hospital Crumlin Ireland for providing additional support and the Wellcome Trust Case–Control Consortium for providing data sets that were used as part of this study. J.P.C is supported by an EMBARK postgraduate award from the Irish Research Council for Science, Engineering and Technology (IRCSET)., The AGRE Consortium, Casey JP, Magalhaes T, Conroy JM, Regan R, Shah N, Anney R, Shields DC, Abrahams BS, Almeida J, Bacchelli E, Bailey AJ, Baird G, Battaglia A, Berney T, Bolshakova N, Bolton PF, Bourgeron T, Brennan S, Cali P, Correia C, Corsello C, Coutanche M, Dawson G, de Jonge M, Delorme R, Duketis E, Duque F, Estes A, Farrar P, Fernandez BA, Folstein SE, Foley S, Fombonne E, Freitag CM, Gilbert J, Gillberg C, Glessner JT, Green J, Guter SJ, Hakonarson H, Holt R, Hughes G, Hus V, Igliozzi R, Kim C, Klauck SM, Kolevzon A, Lamb JA, Leboyer M, Le Couteur A, Leventhal BL, Lord C, Lund SC, Maestrini E, Mantoulan C, Marshall CR, McConachie H, McDougle CJ, McGrath J, McMahon WM, Merikangas A, Miller J, Minopoli F, Mirza GK, Munson J, Nelson SF, Nygren G, Oliveira G, Pagnamenta AT, Papanikolaou K, Parr JR, Parrini B, Pickles A, Pinto D, Piven J, Posey DJ, Poustka A, Poustka F, Ragoussis J, Roge B, Rutter ML, Sequeira AF, Soorya L, Sousa I, Sykes N, Stoppioni V, Tancredi R, Tauber M, Thompson AP, Thomson S, Tsiantis J, Van Engeland H, Vincent JB, Volkmar F, Vorstman JA, Wallace S, Wang K, Wassink TH, White K, Wing K, Wittemeyer K, Yaspan BL, Zwaigenbaum L, Betancur C, Buxbaum JD, Cantor RM, Cook EH, Coon H, Cuccaro ML, Geschwind DH, Haines JL, Hallmayer J, Monaco AP, Nurnberger JI Jr, Pericak-Vance MA, Schellenberg GD, Scherer SW, Sutcliffe JS, Szatmari P, Vieland VJ, Wijsman EM, Green A, Gill M, Gallagher L, Vicente A, Ennis S., McGill University, Institut National de la Recherche Agronomique (INRA)-Avignon Université (AU), Neuroscience Paris Seine (NPS), Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), University of Bologna/Università di Bologna, Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris] (IP), Memorial University of Newfoundland = Université Memorial de Terre-Neuve [St. John's, Canada] (MUN), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur [Paris], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
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Male ,Candidate gene ,Genome-wide association study ,Linkage Disequilibrium ,MESH: Child Development Disorders, Pervasive ,Cohort Studies ,MESH: Genotype ,0302 clinical medicine ,MESH: Child ,Cluster Analysis ,Genetics(clinical) ,Copy-number variation ,Child ,MESH: Cohort Studies ,Genetics (clinical) ,Original Investigation ,SNPS ,Genetics ,0303 health sciences ,education.field_of_study ,MESH: Middle Aged ,MESH: Nuclear Family ,MESH: Polymorphism, Single Nucleotide ,Homozygote ,MESH: Genetic Predisposition to Disease ,Middle Aged ,Autism spectrum disorder (ASD) ,3. Good health ,MESH: Linkage Disequilibrium ,Female ,MESH: DNA Copy Number Variations ,[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,MESH: Homozygote ,Adult ,DNA Copy Number Variations ,Genotype ,Population ,Single-nucleotide polymorphism ,Biology ,Polymorphism, Single Nucleotide ,Nuclear Family ,03 medical and health sciences ,HOMOZYGOSITY MAPPING ,mental disorders ,medicine ,Humans ,Genetic Predisposition to Disease ,ddc:610 ,AUTISM ,GENOME-WIDE ASSOCIATION ,education ,030304 developmental biology ,MESH: Humans ,Genetic heterogeneity ,Haplotype ,MESH: Adult ,MESH: Haplotypes ,medicine.disease ,MESH: Cluster Analysis ,MESH: Male ,Haplotypes ,Child Development Disorders, Pervasive ,Perturbações do Desenvolvimento Infantil e Saúde Mental ,MESH: Genome-Wide Association Study ,Autism ,MESH: Female ,030217 neurology & neurosurgery ,Genome-Wide Association Study - Abstract
Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data. Electronic supplementary material The online version of this article (doi:10.1007/s00439-011-1094-6) contains supplementary material, which is available to authorized users.
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12. Revealing novel genomic insights and therapeutic targets for juvenile idiopathic arthritis through omics.
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Fan J, Li X, Yang J, Zhang S, Qu HQ, Ji D, Glessner JT, Hao J, Ding Z, Wang N, Meng X, Xia Q, Hakonarson H, Wei W, and Li J
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- Humans, Genetic Predisposition to Disease, Genomics, Interferon Regulatory Factors genetics, Arthritis, Juvenile genetics, Arthritis, Juvenile drug therapy, Genome-Wide Association Study
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Background: The genetic architecture of JIA remains only partially comprehended. There is a clear imperative for continued endeavours to uncover insights into the underlying causes of JIA., Methods: This study encompassed a comprehensive spectrum of endeavours, including conducting a JIA genome-wide association study (GWAS) meta-analysis that incorporated data from 4550 JIA cases and 18 446 controls. We employed in silico and genome-editing approaches to prioritizing target genes. To investigate pleiotropic effects, we conducted phenome-wide association studies. Cell-type enrichment analyses were performed by integrating bulk and single-cell sequencing data. Finally, we delved into potential druggable targets for JIA., Results: Fourteen genome-wide significant non-HLA loci were identified, including four novel loci, each exhibiting pleiotropic associations with other autoimmune diseases or musculoskeletal traits. We uncovered strong genetic correlation between JIA and BMD traits at 52 genomic regions, including three GWAS loci for JIA. Candidate genes with immune functions were captured by in silico analyses at each novel locus, with additional findings identified through our experimental approach. Cell-type enrichment analysis revealed 21 specific immune cell types crucial for the affected organs in JIA, indicating their potential contribution to the disease. Finally, 24 known or candidate druggable target genes were prioritized., Conclusions: Our identification of four novel JIA-associated genes, CD247, RHOH, COLEC10 and IRF8, broadens the novel potential drug repositioning opportunities. We established a new genetic link between COLEC10, TNFRSF11B and JIA/BMD. Additionally, the identification of RHOH underscores its role in positive thymocyte selection, thereby illuminating a critical facet of JIA's underlying biological mechanisms., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
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- 2024
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13. Identification of genetic variants associated with clinical features of sickle cell disease.
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Tsukahara K, Chang X, Mentch F, Smith-Whitley K, Bhandari A, Norris C, Glessner JT, and Hakonarson H
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- Humans, Male, Female, Adult, Phenotype, Genetic Predisposition to Disease, Adolescent, Fetal Hemoglobin genetics, Genotype, Acute Chest Syndrome genetics, Child, Young Adult, Genetic Variation, Anemia, Sickle Cell genetics, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Quantitative Trait Loci
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Sickle cell disease (SCD) is an inherited blood disorder marked by homozygosity of hemoglobin S, which is a defective hemoglobin caused by a missense mutation in the β-globin gene. However, clinical phenotypes of SCD vary among patients. To investigate genetic variants associated with various clinical phenotypes of SCD, we genotyped DNA samples from 520 SCD subjects and used a genome-wide association study (GWAS) approach to identify genetic variants associated with phenotypic features of SCD. For HbF levels, the previously reported 2p16.1 locus (BCL11A) reached genome significance (rs1427407, P = 8.58 × 10
-10 ) in our GWAS as expected. In addition, we found a new genome-wide significance locus at 15q14 (rs8182015, P = 2.07 × 10-8 ) near gene EMC7. GWAS of acute chest syndrome (ACS) detected a locus (rs79915189, P = 3.70 × 10-8 ) near gene IDH2 at 15q26.1. The SNP, rs79915189, is also an expression quantitative trait locus (eQTL) of IDH2 in multiple tissues. For vasoocclusive episode (VOE), GWAS detected multiple significant signals at 2p25.1 (rs62118798, P = 4.27 × 10-8 ), 15q26.1 (rs62020555, P = 2.04 × 10-9 ) and 15q26.3 (rs117797325, P = 4.63 × 10-8 ). Our findings provide novel insights into the genetic mechanisms of SCD suggesting that common genetic variants play an important role in the presentation of the clinical phenotypes of patients with SCD., (© 2024. The Author(s).)- Published
- 2024
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14. Mitochondrial DNA Haplogroup K Is Protective Against Autism Spectrum Disorder Risk in Populations of European Ancestry.
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Chang X, Qu HQ, Liu Y, Glessner JT, and Hakonarson H
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- Humans, Male, Female, Case-Control Studies, Child, Polymorphism, Single Nucleotide, Genotype, Cohort Studies, Autism Spectrum Disorder genetics, Autism Spectrum Disorder ethnology, DNA, Mitochondrial genetics, Haplotypes, White People genetics, Jews genetics, Genetic Predisposition to Disease
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Objective: Accumulative evidence indicates a critical role of mitochondrial function in autism spectrum disorders (ASD), implying that ASD risk may be linked to mitochondrial dysfunction due to DNA (mtDNA) variations. Although a few studies have explored the association between mtDNA variations and ASD, the role of mtDNA in ASD is still unclear. Here, we aimed to investigate whether mitochondrial DNA haplogroups are associated with the risk of ASD., Method: Two European cohorts and an Ashkenazi Jewish (AJ) cohort were analyzed, including 2,062 ASD patients in comparison with 4,632 healthy controls. DNA samples were genotyped using Illumina HumanHap550/610 and Illumina 1M arrays, inclusive of mitochondrial markers. Mitochondrial DNA (mtDNA) haplogroups were identified from genotyping data using HaploGrep2. A mitochondrial genome imputation pipeline was established to detect mtDNA variants. We conducted a case-control study to investigate potential associations of mtDNA haplogroups and variants with the susceptibility to ASD., Results: We observed that the ancient adaptive mtDNA haplogroup K was significantly associated with decreased risk of ASD by the investigation of 2 European cohorts including a total of 2,006 cases and 4,435 controls (odds ratio = 0.64, P=1.79 × 10
-5 ), and we replicated this association in an Ashkenazi Jewish (AJ) cohort including 56 cases and 197 controls (odds ratio = 0.35, P = 9.46 × 10-3 ). Moreover, we demonstrate that the mtDNA variants rs28358571, rs28358584, and rs28358280 are significantly associated with ASD risk. Further expression quantitative trait loci (eQTLs) analysis indicated that the rs28358584 and rs28358280 genotypes are associated with expression levels of nearby genes in brain tissues, suggesting those mtDNA variants may confer risk for ASD via regulation of expression levels of genes encoded by the mitochondrial genome., Conclusion: This study helps to shed light on the contribution of mitochondria in ASD and provides new insights into the genetic mechanism underlying ASD, suggesting the potential involvement of mtDNA-encoded proteins in the development of ASD., Plain Language Summary: Increasing evidence indicates that mitochondrial dysfunction may be linked to autism spectrum disorder (ASD). This study investigated potential associations of mitochondrial DNA (mtDNA) variants in 2 European and Ashkenazi Jewish cohorts including 2,062 individuals with ASD and 4,632 healthy controls. Researchers found that the ancient mtDNA haplogroup K was linked to a reduced risk of ASD in both European and Ashkenazi Jewish populations. Additionally, specific mtDNA variants were associated with ASD risk and were shown to influence the expression of nearby genes in the brain. These findings highlight the potential involvement of mtDNA in ASD development, offering new insights into the genetic mechanisms underlying the disorder., (Copyright © 2023 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)- Published
- 2024
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15. Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders.
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Xiu Z, Sun L, Liu K, Cao H, Qu HQ, Glessner JT, Ding Z, Zheng G, Wang N, Xia Q, Li J, Li MJ, Hakonarson H, Liu W, and Li J
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- Humans, Neurodevelopmental Disorders genetics, Genome-Wide Association Study, Immune System Diseases genetics, Genetic Predisposition to Disease genetics, Polymorphism, Single Nucleotide genetics, Multifactorial Inheritance genetics
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The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: ZD and NW are employees of Mills Institute for Personalized Cancer Care, Fynn Biotechnologies Ltd., Jinan, China. All other authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)
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- 2024
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16. Multi-ancestry Genome-Wide Association Meta-Analysis Identifies Novel Loci in Atopic Dermatitis.
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Oliva M, Sarkar MK, March ME, Saeidian AH, Mentch FD, Hsieh CL, Tang F, Uppala R, Patrick MT, Li Q, Bogle R, Kahlenberg JM, Watson D, Glessner JT, Tsoi LC, Hakonarson H, Gudjonsson JE, Smith KM, and Riley-Gillis B
- Abstract
Atopic dermatitis (AD) is a highly heritable and common inflammatory skin condition affecting children and adults worldwide. Multi-ancestry approaches to AD genetic association studies are poised to boost power to detect genetic signal and identify ancestry-specific loci contributing to AD risk. Here, we present a multi-ancestry GWAS meta-analysis of twelve AD cohorts from five ancestral populations totaling 56,146 cases and 602,280 controls. We report 101 genomic loci associated with AD, including 15 loci that have not been previously associated with AD or eczema. Fine-mapping, QTL colocalization, and cell-type enrichment analyses identified genes and cell types implicated in AD pathophysiology. Functional analyses in keratinocytes provide evidence for genes that could play a role in AD through epidermal barrier function. Our study provides new insights into the etiology of AD by harnessing multiple genetic and functional approaches to unveil the mechanisms by which AD-associated variants impact genes and cell types.
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- 2024
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17. Target genes regulated by CLEC16A intronic region associated with common variable immunodeficiency.
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Huang X, Huang J, Li X, Fan J, Zhou D, Qu HQ, Glessner JT, Ji D, Jia Q, Ding Z, Wang N, Wei W, Lyu X, Li MJ, Liu Z, Liu W, Wei Y, Hakonarson H, Xia Q, and Li J
- Subjects
- Humans, Polymorphism, Single Nucleotide, Gene Expression Regulation, Female, Male, Signal Transduction genetics, CD4-Positive T-Lymphocytes immunology, Adult, Lectins, C-Type genetics, Introns genetics, Monosaccharide Transport Proteins genetics, Common Variable Immunodeficiency genetics, Common Variable Immunodeficiency immunology
- Abstract
Background: CLEC16A intron 19 has been identified as a candidate locus for common variable immunodeficiency (CVID)., Objectives: This study sought to elucidate the molecular mechanism by which variants at the CLEC16A intronic locus may contribute to the pathogenesis of CVID., Methods: The investigators performed fine-mapping of the CLEC16A locus in a CVID cohort, then deleted the candidate functional SNP in T-cell lines by the CRISPR-Cas9 technique and conducted RNA-sequencing to identify target gene(s). The interactions between the CLEC16A locus and its target genes were identified using circular chromosome conformation capture. The transcription factor complexes mediating the chromatin interactions were determined by proteomic approach. The molecular pathways regulated by the CLEC16A locus were examined by RNA-sequencing and reverse phase protein array., Results: This study showed that the CLEC16A locus is an enhancer regulating expression of multiple target genes including a distant gene ATF7IP2 through chromatin interactions. Distinct transcription factor complexes mediate the chromatin interactions in an allele-specific manner. Disruption of the CLEC16A locus affects the AKT signaling pathway, as well as the molecular response of CD4
+ T cells to immune stimulation., Conclusions: Through multiomics and targeted experimental approaches, this study elucidated the underlying target genes and signaling pathways involved in the genetic association of CLEC16A with CVID, and highlighted plausible molecular targets for developing novel therapeutics., (Copyright © 2024 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)- Published
- 2024
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18. Author Correction: Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes.
- Author
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Bradfeld JP, Kember RL, Ulrich A, Balkhiyarova Z, Alyass A, Aris IM, Bell JA, Broadaway KA, Chen Z, Chai JF, Davies NM, Fernandez-Orth D, Bustamante M, Fore R, Ganguli A, Heiskala A, Hottenga JJ, Íñiguez C, Kobes S, Leinonen J, Lowry E, Lyytikainen LP, Mahajan A, Pitkänen N, Schnurr TM, Have CT, Strachan DP, Thiering E, Vogelezang S, Wade KH, Wang CA, Wong A, Holm LA, Chesi A, Choong C, Cruz M, Elliott P, Franks S, Frithiof-Bøjsøe C, Gauderman WJ, Glessner JT, Gilsanz V, Griesman K, Hanson RL, Kaakinen M, Kalkwarf H, Kelly A, Kindler J, Kähönen M, Lanca C, Lappe J, Lee NR, McCormack S, Mentch FD, Mitchell JA, Mononen N, Niinikoski H, Oken E, Pahkala K, Sim X, Teo YY, Baier LJ, van Beijsterveldt T, Adair LS, Boomsma DI, de Geus E, Guxens M, Eriksson JG, Felix JF, Gilliland FD, Hansen T, Hardy R, Hivert MF, Holm JC, Jaddoe VWV, Järvelin MR, Lehtimäki T, Mackey DA, Meyre D, Mohlke KL, Mykkänen J, Oberfeld S, Pennell CE, Perry JRB, Raitakari O, Rivadeneira F, Saw SM, Sebert S, Shepherd JA, Standl M, Sørensen TIA, Timpson NJ, Torrent M, Willemsen G, Hypponen E, Power C, McCarthy MI, Freathy RM, Widén E, Hakonarson H, Prokopenko I, Voight BF, Zemel BS, Grant SFA, and Cousminer DL
- Published
- 2024
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19. The copy number variant architecture of psychopathology and cognitive development in the ABCD ® study.
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Sha Z, Sun KY, Jung B, Barzilay R, Moore TM, Almasy L, Forsyth JK, Prem S, Gandal MJ, Seidlitz J, Glessner JT, and Alexander-Bloch AF
- Abstract
Importance: Childhood is a crucial developmental phase for mental health and cognitive function, both of which are commonly affected in patients with psychiatric disorders. This neurodevelopmental trajectory is shaped by a complex interplay of genetic and environmental factors. While common genetic variants account for a large proportion of inherited genetic risk, rare genetic variations, particularly copy number variants (CNVs), play a significant role in the genetic architecture of neurodevelopmental disorders. Despite their importance, the relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored., Objective: Investigating CNV associations with dimensions of child psychopathology and cognitive functions., Design Setting and Participants: ABCD
® study focuses on a cohort of over 11,875 youth aged 9 to 10, recruited from 21 sites in the US, aiming to investigate the role of various factors, including brain, environment, and genetic factors, in the etiology of mental and physical health from middle childhood through early adulthood. Data analysis occurred from April 2023 to April 2024., Main Outcomes and Measures: In this study, we utilized PennCNV and QuantiSNP algorithms to identify duplications and deletions larger than 50Kb across a cohort of 11,088 individuals from the Adolescent Brain Cognitive Development® study. CNVs meeting quality control standards were subjected to a genome-wide association scan to identify regions associated with quantitative measures of broad psychiatric symptom domains and cognitive outcomes. Additionally, a CNV risk score, reflecting the aggregated burden of genetic intolerance to inactivation and dosage sensitivity, was calculated to assess its impact on variability in overall and dimensional child psychiatric and cognitive phenotypes., Results: In a final sample of 8,564 individuals (mean age=9.9 years, 4,532 males) passing quality control, we identified 4,111 individuals carrying 5,760 autosomal CNVs. Our results revealed significant associations between specific CNVs and our phenotypes of interest, psychopathology and cognitive function. For instance, a duplication at 10q26.3 was associated with overall psychopathology, and somatic complaints in particular. Additionally, deletions at 1q12.1, along with duplications at 14q11.2 and 10q26.3, were linked to overall cognitive function, with particular contributions from fluid intelligence (14q11.2), working memory (10q26.3), and reading ability (14q11.2). Moreover, individuals carrying CNVs previously associated with neurodevelopmental disorders exhibited greater impairment in social functioning and cognitive performance across multiple domains, in particular working memory. Notably, a higher deletion CNV risk score was significantly correlated with increased overall psychopathology (especially in dimensions of social functioning, thought disorder, and attention) as well as cognitive impairment across various domains., Conclusions and Relevance: In summary, our findings shed light on the contributions of CNVs to interindividual variability in complex traits related to neurocognitive development and child psychopathology., Competing Interests: Conflict of interests AFA-B receives consulting income from Octave Bioscience. AFA-B and JS hold equity in and serve on the board of Centile Bioscience.- Published
- 2024
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20. High Comorbidity of Pediatric Cancers in Patients with Birth Defects: Insights from Whole Genome Sequencing Analysis of Copy Number Variations.
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Qu HQ, Glessner JT, Qu J, Liu Y, Watson D, Chang X, Saeidian AH, Qiu H, Mentch FD, Connolly JJ, and Hakonarson H
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- Male, Child, Female, Humans, Whole Genome Sequencing, Comorbidity, DNA Copy Number Variations genetics, Neoplasms epidemiology, Neoplasms genetics
- Abstract
Background: Patients with birth defects (BD) exhibit an elevated risk of cancer. We aimed to investigate the potential link between pediatric cancers and BDs, exploring the hypothesis of shared genetic defects contributing to the coexistence of these conditions., Methods: This study included 1454 probands with BDs (704 females and 750 males), including 619 (42.3%) with and 845 (57.7%) without co-occurrence of pediatric onset cancers. Whole genome sequencing (WGS) was done at 30X coverage through the Kids First/Gabriella Miller X01 Program., Results: 8211 CNV loci were called from the 1454 unrelated individuals. 191 CNV loci classified as pathogenic/likely pathogenic (P/LP) were identified in 309 (21.3%) patients, with 124 (40.1%) of these patients having pediatric onset cancers. The most common group of CNVs are pathogenic deletions covering the region ChrX:52,863,011-55,652,521, seen in 162 patients including 17 males. Large recurrent P/LP duplications >5MB were detected in 33 patients., Conclusions: This study revealed that P/LP CNVs were common in a large cohort of BD patients with high rate of pediatric cancers. We present a comprehensive spectrum of P/LP CNVs in patients with BDs and various cancers. Notably, deletions involving E2F target genes and genes implicated in mitotic spindle assembly and G2/M checkpoint were identified, potentially disrupting cell-cycle progression and providing mechanistic insights into the concurrent occurrence of BDs and cancers., (Copyright © 2023. Published by Elsevier Inc.)
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- 2024
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21. KOLF2.1J iPSCs carry CNVs associated with neurodevelopmental disorders.
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Gracia-Diaz C, Perdomo JE, Khan ME, Roule T, Disanza BL, Cajka GG, Lei S, Gagne AL, Maguire JA, Shalem O, Bhoj EJ, Ahrens-Nicklas RC, French DL, Goldberg EM, Wang K, Glessner JT, and Akizu N
- Subjects
- Humans, DNA Copy Number Variations, Neurodevelopmental Disorders genetics, Induced Pluripotent Stem Cells
- Abstract
Competing Interests: Declaration of interests The authors declare no competing interests.
- Published
- 2024
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22. Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations.
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Lennon NJ, Kottyan LC, Kachulis C, Abul-Husn NS, Arias J, Belbin G, Below JE, Berndt SI, Chung WK, Cimino JJ, Clayton EW, Connolly JJ, Crosslin DR, Dikilitas O, Velez Edwards DR, Feng Q, Fisher M, Freimuth RR, Ge T, Glessner JT, Gordon AS, Patterson C, Hakonarson H, Harden M, Harr M, Hirschhorn JN, Hoggart C, Hsu L, Irvin MR, Jarvik GP, Karlson EW, Khan A, Khera A, Kiryluk K, Kullo I, Larkin K, Limdi N, Linder JE, Loos RJF, Luo Y, Malolepsza E, Manolio TA, Martin LJ, McCarthy L, McNally EM, Meigs JB, Mersha TB, Mosley JD, Musick A, Namjou B, Pai N, Pesce LL, Peters U, Peterson JF, Prows CA, Puckelwartz MJ, Rehm HL, Roden DM, Rosenthal EA, Rowley R, Sawicki KT, Schaid DJ, Smit RAJ, Smith JL, Smoller JW, Thomas M, Tiwari H, Toledo DM, Vaitinadin NS, Veenstra D, Walunas TL, Wang Z, Wei WQ, Weng C, Wiesner GL, Yin X, and Kenny EE
- Subjects
- Adult, Child, Humans, Communication, Genetic Predisposition to Disease, Genome-Wide Association Study, Risk Factors, United States, Chronic Disease, Genetic Risk Score, Population Health
- Abstract
Polygenic risk scores (PRSs) have improved in predictive performance, but several challenges remain to be addressed before PRSs can be implemented in the clinic, including reduced predictive performance of PRSs in diverse populations, and the interpretation and communication of genetic results to both providers and patients. To address these challenges, the National Human Genome Research Institute-funded Electronic Medical Records and Genomics (eMERGE) Network has developed a framework and pipeline for return of a PRS-based genome-informed risk assessment to 25,000 diverse adults and children as part of a clinical study. From an initial list of 23 conditions, ten were selected for implementation based on PRS performance, medical actionability and potential clinical utility, including cardiometabolic diseases and cancer. Standardized metrics were considered in the selection process, with additional consideration given to strength of evidence in African and Hispanic populations. We then developed a pipeline for clinical PRS implementation (score transfer to a clinical laboratory, validation and verification of score performance), and used genetic ancestry to calibrate PRS mean and variance, utilizing genetically diverse data from 13,475 participants of the All of Us Research Program cohort to train and test model parameters. Finally, we created a framework for regulatory compliance and developed a PRS clinical report for return to providers and for inclusion in an additional genome-informed risk assessment. The initial experience from eMERGE can inform the approach needed to implement PRS-based testing in diverse clinical settings., (© 2024. The Author(s).)
- Published
- 2024
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23. Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes.
- Author
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Bradfield JP, Kember RL, Ulrich A, Balkhiyarova Z, Alyass A, Aris IM, Bell JA, Broadaway KA, Chen Z, Chai JF, Davies NM, Fernandez-Orth D, Bustamante M, Fore R, Ganguli A, Heiskala A, Hottenga JJ, Íñiguez C, Kobes S, Leinonen J, Lowry E, Lyytikainen LP, Mahajan A, Pitkänen N, Schnurr TM, Have CT, Strachan DP, Thiering E, Vogelezang S, Wade KH, Wang CA, Wong A, Holm LA, Chesi A, Choong C, Cruz M, Elliott P, Franks S, Frithioff-Bøjsøe C, Gauderman WJ, Glessner JT, Gilsanz V, Griesman K, Hanson RL, Kaakinen M, Kalkwarf H, Kelly A, Kindler J, Kähönen M, Lanca C, Lappe J, Lee NR, McCormack S, Mentch FD, Mitchell JA, Mononen N, Niinikoski H, Oken E, Pahkala K, Sim X, Teo YY, Baier LJ, van Beijsterveldt T, Adair LS, Boomsma DI, de Geus E, Guxens M, Eriksson JG, Felix JF, Gilliland FD, Biobank PM, Hansen T, Hardy R, Hivert MF, Holm JC, Jaddoe VWV, Järvelin MR, Lehtimäki T, Mackey DA, Meyre D, Mohlke KL, Mykkänen J, Oberfield S, Pennell CE, Perry JRB, Raitakari O, Rivadeneira F, Saw SM, Sebert S, Shepherd JA, Standl M, Sørensen TIA, Timpson NJ, Torrent M, Willemsen G, Hypponen E, Power C, McCarthy MI, Freathy RM, Widén E, Hakonarson H, Prokopenko I, Voight BF, Zemel BS, Grant SFA, and Cousminer DL
- Subjects
- Adult, Adolescent, Humans, Child, Child, Preschool, Puberty genetics, Phenotype, Body Height genetics, Outcome Assessment, Health Care, Longitudinal Studies, Genome-Wide Association Study, Diabetes Mellitus, Type 2
- Abstract
Background: Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank., Results: Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation., Conclusion: We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single "optimal" pubertal growth pattern., (© 2023. The Author(s).)
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- 2024
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24. Biliary atresia is associated with polygenic susceptibility in ciliogenesis and planar polarity effector genes.
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Glessner JT, Ningappa MB, Ngo KA, Zahid M, So J, Higgs BW, Sleiman PMA, Narayanan T, Ranganathan S, March M, Prasadan K, Vaccaro C, Reyes-Mugica M, Velazquez J, Salgado CM, Ebrahimkhani MR, Schmitt L, Rajasundaram D, Paul M, Pellegrino R, Gittes GK, Li D, Wang X, Billings J, Squires R, Ashokkumar C, Sharif K, Kelly D, Dhawan A, Horslen S, Lo CW, Shin D, Subramaniam S, Hakonarson H, and Sindhi R
- Subjects
- Child, Animals, Mice, Humans, Genome-Wide Association Study, Genetic Predisposition to Disease, Zebrafish genetics, Canada, Biliary Atresia genetics
- Abstract
Background & Aims: Biliary atresia (BA) is poorly understood and leads to liver transplantation (LT), with the requirement for and associated risks of lifelong immunosuppression, in most children. We performed a genome-wide association study (GWAS) to determine the genetic basis of BA., Methods: We performed a GWAS in 811 European BA cases treated with LT in US, Canadian and UK centers, and 4,654 genetically matched controls. Whole-genome sequencing of 100 cases evaluated synthetic association with rare variants. Functional studies included whole liver transcriptome analysis of 64 BA cases and perturbations in experimental models., Results: A GWAS of common single nucleotide polymorphisms (SNPs), i.e. allele frequencies >1%, identified intronic SNPs rs6446628 in AFAP1 with genome-wide significance (p = 3.93E-8) and rs34599046 in TUSC3 at sub-threshold genome-wide significance (p = 1.34E-7), both supported by credible peaks of neighboring SNPs. Like other previously reported BA-associated genes, AFAP1 and TUSC3 are ciliogenesis and planar polarity effectors (CPLANE). In gene-set-based GWAS, BA was associated with 6,005 SNPs in 102 CPLANE genes (p = 5.84E-15). Compared with non-CPLANE genes, more CPLANE genes harbored rare variants (allele frequency <1%) that were assigned Human Phenotype Ontology terms related to hepatobiliary anomalies by predictive algorithms, 87% vs. 40%, p <0.0001. Rare variants were present in multiple genes distinct from those with BA-associated common variants in most BA cases. AFAP1 and TUSC3 knockdown blocked ciliogenesis in mouse tracheal cells. Inhibition of ciliogenesis caused biliary dysgenesis in zebrafish. AFAP1 and TUSC3 were expressed in fetal liver organoids, as well as fetal and BA livers, but not in normal or disease-control livers. Integrative analysis of BA-associated variants and liver transcripts revealed abnormal vasculogenesis and epithelial tube formation, explaining portal vein anomalies that co-exist with BA., Conclusions: BA is associated with polygenic susceptibility in CPLANE genes. Rare variants contribute to polygenic risk in vulnerable pathways via unique genes., Impact and Implications: Liver transplantation is needed to cure most children born with biliary atresia, a poorly understood rare disease. Transplant immunosuppression increases the likelihood of life-threatening infections and cancers. To improve care by preventing this disease and its progression to transplantation, we examined its genetic basis. We find that this disease is associated with both common and rare mutations in highly specialized genes which maintain normal communication and movement of cells, and their organization into bile ducts and blood vessels during early development of the human embryo. Because defects in these genes also cause other birth defects, our findings could lead to preventive strategies to lower the incidence of biliary atresia and potentially other birth defects., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)
- Published
- 2023
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25. The Circassians and the Chechens in Jordan: results of a decade of epidemiological and genetic studies.
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Abudahab S, Hakooz N, Al-Etian L, Shishani K, Bashqawi A, Connolly J, Glessner JT, Qu HQ, Qu J, Hakonarson H, and Dajani R
- Abstract
Circassians and Chechens in Jordan, both with Caucasian ancestry, are genetically isolated due to high rate of endogamous marriages. Recent interest in these populations has led to studies on their genetic similarities, differences, and epidemiological differences in various diseases. Research has explored their predisposition to conditions like diabetes, hypertension, and cancer. Moreover, pharmacogenetic (PGx) studies have also investigated medication response variations within these populations, and forensic studies have further contributed to understanding these populations. In this review article, we first discuss the background of these minority groups. We then show the results of a principle component analysis (PCA) to investigate the genetic relationships between Circassian and Chechen populations living in Jordan. We here present a summary of the findings from the 10 years of research conducted on them. The review article provides a comprehensive summary of research findings that are truly valuable for understanding the unique genetic characteristics, diseases' prevalence, and medication responses among Circassians and Chechens living in Jordan. We believe that gaining deeper comprehension of the root causes of various diseases and developing effective treatment methods that benefit the society as a whole are imperative to engaging a wide range of ethnic groups in genetic research., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
- Published
- 2023
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26. Trans-ethnic genomic informed risk assessment for Alzheimer's disease: An International Hundred K+ Cohorts Consortium study.
- Author
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Sleiman PM, Qu HQ, Connolly JJ, Mentch F, Pereira A, Lotufo PA, Tollman S, Choudhury A, Ramsay M, Kato N, Ozaki K, Mitsumori R, Jeon JP, Hong CH, Son SJ, Roh HW, Lee DG, Mukadam N, Foote IF, Marshall CR, Butterworth A, Prins BP, Glessner JT, and Hakonarson H
- Subjects
- Humans, Female, Genome-Wide Association Study, Proteomics, Genomics, Risk Assessment, Alzheimer Disease genetics, Alzheimer Disease epidemiology
- Abstract
Background: As a collaboration model between the International HundredK+ Cohorts Consortium (IHCC) and the Davos Alzheimer's Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for Alzheimer's disease (AD)., Methods: The GIRA model was created to include polygenic risk score calculated from the AD genome-wide association study loci, the apolipoprotein E haplotypes, and non-genetic covariates including age, sex, and the first three principal components of population substructure., Results: We validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD., Conclusions: As the initial effort by the IHCC to leverage existing large-scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
- Published
- 2023
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27. The molecular genetic landscape of human brain size variation.
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Seidlitz J, Mallard TT, Vogel JW, Lee YH, Warrier V, Ball G, Hansson O, Hernandez LM, Mandal AS, Wagstyl K, Lombardo MV, Courchesne E, Glessner JT, Satterthwaite TD, Bethlehem RAI, Bernstock JD, Tasaki S, Ng B, Gaiteri C, Smoller JW, Ge T, Gur RE, Gandal MJ, and Alexander-Bloch AF
- Subjects
- Adult, Humans, Organ Size, Phenotype, Genome-Wide Association Study methods, Molecular Biology, Genetic Predisposition to Disease, Transcriptome, Brain metabolism
- Abstract
Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease., Competing Interests: Declaration of interests J.S., R.A.I.B., J.D.B., and A.F.A.-B. are directors and hold equity in Centile Bioscience. J.D.B. holds positions/equity in UpFront Diagnostics, Treovir, and NeuroX1. A.F.A.-B. receives consulting income from Octave Bioscience., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)
- Published
- 2023
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28. Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse populations.
- Author
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Lennon NJ, Kottyan LC, Kachulis C, Abul-Husn N, Arias J, Belbin G, Below JE, Berndt S, Chung W, Cimino JJ, Clayton EW, Connolly JJ, Crosslin D, Dikilitas O, Velez Edwards DR, Feng Q, Fisher M, Freimuth R, Ge T, Glessner JT, Gordon A, Guiducci C, Hakonarson H, Harden M, Harr M, Hirschhorn J, Hoggart C, Hsu L, Irvin R, Jarvik GP, Karlson EW, Khan A, Khera A, Kiryluk K, Kullo I, Larkin K, Limdi N, Linder JE, Loos R, Luo Y, Malolepsza E, Manolio T, Martin LJ, McCarthy L, Meigs JB, Mersha TB, Mosley J, Namjou B, Pai N, Pesce LL, Peters U, Peterson J, Prows CA, Puckelwartz MJ, Rehm H, Roden D, Rosenthal EA, Rowley R, Sawicki KT, Schaid D, Schmidlen T, Smit R, Smith J, Smoller JW, Thomas M, Tiwari H, Toledo D, Vaitinadin NS, Veenstra D, Walunas T, Wang Z, Wei WQ, Weng C, Wiesner G, Xianyong Y, and Kenny E
- Abstract
Polygenic risk scores (PRS) have improved in predictive performance supporting their use in clinical practice. Reduced predictive performance of PRS in diverse populations can exacerbate existing health disparities. The NHGRI-funded eMERGE Network is returning a PRS-based genome-informed risk assessment to 25,000 diverse adults and children. We assessed PRS performance, medical actionability, and potential clinical utility for 23 conditions. Standardized metrics were considered in the selection process with additional consideration given to strength of evidence in African and Hispanic populations. Ten conditions were selected with a range of high-risk thresholds: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, obesity, and type 2 diabetes. We developed a pipeline for clinical PRS implementation, used genetic ancestry to calibrate PRS mean and variance, created a framework for regulatory compliance, and developed a PRS clinical report. eMERGE's experience informs the infrastructure needed to implement PRS-based implementation in diverse clinical settings., Competing Interests: Conflict of Interest The authors have no conflicts of interest to declare.
- Published
- 2023
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29. Rare recurrent copy number variations in metabotropic glutamate receptor interacting genes in children with neurodevelopmental disorders.
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Glessner JT, Khan ME, Chang X, Liu Y, Otieno FG, Lemma M, Slaby I, Hain H, Mentch F, Li J, Kao C, Sleiman PMA, March ME, Connolly J, and Hakonarson H
- Subjects
- Humans, DNA Copy Number Variations genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Autism Spectrum Disorder genetics, Receptors, Metabotropic Glutamate genetics
- Abstract
Background: Neurodevelopmental disorders (NDDs), such as attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), are examples of complex and partially overlapping phenotypes that often lack definitive corroborating genetic information. ADHD and ASD have complex genetic associations implicated by rare recurrent copy number variations (CNVs). Both of these NDDs have been shown to share similar biological etiologies as well as genetic pleiotropy., Methods: Platforms aimed at investigating genetic-based associations, such as high-density microarray technologies, have been groundbreaking techniques in the field of complex diseases, aimed at elucidating the underlying disease biology. Previous studies have uncovered CNVs associated with genes within shared candidate genomic networks, including glutamate receptor genes, across multiple different NDDs. To examine shared biological pathways across two of the most common NDDs, we investigated CNVs across 15,689 individuals with ADHD (n = 7920), ASD (n = 4318), or both (n = 3,416), as well as 19,993 controls. Cases and controls were matched by genotype array (i.e., Illumina array versions). Three case-control association studies each calculated and compared the observed vs. expected frequency of CNVs across individual genes, loci, pathways, and gene networks. Quality control measures of confidence in CNV-calling, prior to association analyses, included visual inspection of genotype and hybridization intensity., Results: Here, we report results from CNV analysis in search for individual genes, loci, pathways, and gene networks. To extend our previous observations implicating a key role of the metabotropic glutamate receptor (mGluR) network in both ADHD and autism, we exhaustively queried patients with ASD and/or ADHD for CNVs associated with the 273 genomic regions of interest within the mGluR gene network (genes with one or two degrees protein-protein interaction with mGluR 1-8 genes). Among CNVs in mGluR network genes, we uncovered CNTN4 deletions enriched in NDD cases (P = 3.22E - 26, OR = 2.49). Additionally, we uncovered PRLHR deletions in 40 ADHD cases and 12 controls (P = 5.26E - 13, OR = 8.45) as well as clinically diagnostic relevant 22q11.2 duplications and 16p11.2 duplications in 23 ADHD + ASD cases and 9 controls (P = 4.08E - 13, OR = 15.05) and 22q11.2 duplications in 34 ADHD + ASD cases and 51 controls (P = 9.21E - 9, OR = 3.93); those control samples were not with previous 22qDS diagnosis in their EHR records., Conclusion: Together, these results suggest that disruption in neuronal cell-adhesion pathways confers significant risk to NDDs and showcase that rare recurrent CNVs in CNTN4, 22q11.2, and 16p11.2 are overrepresented in NDDs that constitute patients predominantly suffering from ADHD and ASD., Trial Registration: ClinicalTrials.gov Identifier: NCT02286817 First Posted: 10 November 14, ClinicalTrials.gov Identifier: NCT02777931 first posted: 19 May 2016, ClinicalTrials.gov Identifier: NCT03006367 first posted: 30 December 2016, ClinicalTrials.gov Identifier: NCT02895906 first posted: 12 September 2016., (© 2023. The Author(s).)
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- 2023
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30. Genomic Disorders in CKD across the Lifespan.
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Verbitsky M, Krishnamurthy S, Krithivasan P, Hughes D, Khan A, Marasà M, Vena N, Khosla P, Zhang J, Lim TY, Glessner JT, Weng C, Shang N, Shen Y, Hripcsak G, Hakonarson H, Ionita-Laza I, Levy B, Kenny EE, Loos RJF, Kiryluk K, Sanna-Cherchi S, Crosslin DR, Furth S, Warady BA, Igo RP Jr, Iyengar SK, Wong CS, Parsa A, Feldman HI, and Gharavi AG
- Subjects
- Humans, Cohort Studies, Prospective Studies, Genomics, Disease Progression, Risk Factors, Longevity, Renal Insufficiency, Chronic epidemiology, Renal Insufficiency, Chronic genetics, Renal Insufficiency, Chronic complications
- Abstract
Significance Statement: Pathogenic structural genetic variants, also known as genomic disorders, have been associated with pediatric CKD. This study extends those results across the lifespan, with genomic disorders enriched in both pediatric and adult patients compared with controls. In the Chronic Renal Insufficiency Cohort study, genomic disorders were also associated with lower serum Mg, lower educational performance, and a higher risk of death. A phenome-wide association study confirmed the link between kidney disease and genomic disorders in an unbiased way. Systematic detection of genomic disorders can provide a molecular diagnosis and refine prediction of risk and prognosis., Background: Genomic disorders (GDs) are associated with many comorbid outcomes, including CKD. Identification of GDs has diagnostic utility., Methods: We examined the prevalence of GDs among participants in the Chronic Kidney Disease in Children (CKiD) cohort II ( n =248), Chronic Renal Insufficiency Cohort (CRIC) study ( n =3375), Columbia University CKD Biobank (CU-CKD; n =1986), and the Family Investigation of Nephropathy and Diabetes (FIND; n =1318) compared with 30,746 controls. We also performed a phenome-wide association analysis (PheWAS) of GDs in the electronic MEdical Records and GEnomics (eMERGE; n =11,146) cohort., Results: We found nine out of 248 (3.6%) CKiD II participants carried a GD, replicating prior findings in pediatric CKD. We also identified GDs in 72 out of 6679 (1.1%) adult patients with CKD in the CRIC, CU-CKD, and FIND cohorts, compared with 199 out of 30,746 (0.65%) GDs in controls (OR, 1.7; 95% CI, 1.3 to 2.2). Among adults with CKD, we found recurrent GDs at the 1q21.1, 16p11.2, 17q12, and 22q11.2 loci. The 17q12 GD (diagnostic of renal cyst and diabetes syndrome) was most frequent, present in 1:252 patients with CKD and diabetes. In the PheWAS, dialysis and neuropsychiatric phenotypes were the top associations with GDs. In CRIC participants, GDs were associated with lower serum magnesium, lower educational achievement, and higher mortality risk., Conclusion: Undiagnosed GDs are detected both in children and adults with CKD. Identification of GDs in these patients can enable a precise genetic diagnosis, inform prognosis, and help stratify risk in clinical studies. GDs could also provide a molecular explanation for nephropathy and comorbidities, such as poorer neurocognition for a subset of patients., (Copyright © 2022 by the American Society of Nephrology.)
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- 2023
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31. ParseCNV2: efficient sequencing tool for copy number variation genome-wide association studies.
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Glessner JT, Li J, Liu Y, Khan M, Chang X, Sleiman PMA, and Hakonarson H
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- Humans, Polymorphism, Single Nucleotide, Software, Algorithms, Genome-Wide Association Study, DNA Copy Number Variations
- Abstract
Improved copy number variation (CNV) detection remains an area of heavy emphasis for algorithm development; however, both CNV curation and disease association approaches remain in its infancy. The current practice of focusing on candidate CNVs, where researchers study specific CNVs they believe to be pathological while discarding others, refrains from considering the full spectrum of CNVs in a hypothesis-free GWAS. To address this, we present a next-generation approach to CNV association by natively supporting the popular VCF specification for sequencing-derived variants as well as SNP array calls using a PennCNV format. The code is fast and efficient, allowing for the analysis of large (>100,000 sample) cohorts without dividing up the data on a compute cluster. The scripts are condensed into a single tool to promote simplicity and best practices. CNV curation pre and post-association is rigorously supported and emphasized to yield reliable results of highest quality. We benchmarked two large datasets, including the UK Biobank (n > 450,000) and CAG Biobank (n > 350,000) both of which are genotyped at >0.5 M probes, for our input files. ParseCNV has been actively supported and developed since 2008. ParseCNV2 presents a critical addition to formalizing CNV association for inclusion with SNP associations in GWAS Catalog. Clinical CNV prioritization, interactive quality control (QC), and adjustment for covariates are revolutionary new features of ParseCNV2 vs. ParseCNV. The software is freely available at: https://github.com/CAG-CNV/ParseCNV2 ., (© 2022. The Author(s), under exclusive licence to European Society of Human Genetics.)
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- 2023
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32. Single Cell Transcriptome Analysis of Peripheral Blood Mononuclear Cells in Freshly Isolated versus Stored Blood Samples.
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Qu HQ, Kao C, Garifallou J, Wang F, Snyder J, Slater DJ, Hou C, March M, Connolly JJ, Glessner JT, and Hakonarson H
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- Humans, Gene Expression Profiling, Transcriptome, Killer Cells, Natural, Leukocytes, Mononuclear metabolism, Single-Cell Gene Expression Analysis
- Abstract
Background: Peripheral blood mononuclear cells (PBMCs) are widely used as a model in the study of different human diseases. There is often a time delay from blood collection to PBMC isolation during the sampling process, which can result in an experimental bias, particularly when performing single cell RNA-seq (scRNAseq) studies., Methods: This study examined the impact of different time periods from blood draw to PBMC isolation on the subsequent transcriptome profiling of different cell types in PBMCs by scRNAseq using the 10X Chromium Single Cell Gene Expression assay., Results: Examining the five major cell types constituting the PBMC cell population, i.e., CD4+ T cells, CD8+ T cells, NK cells, monocytes, and B cells, both common changes and cell-type-specific changes were observed in the single cell transcriptome profiling over time. In particular, the upregulation of genes regulated by NF-kB in response to TNF was observed in all five cell types. Significant changes in key genes involved in AP-1 signaling were also observed. RBC contamination was a major issue in stored blood, whereas RBC adherence had no direct impact on the cell transcriptome., Conclusions: Significant transcriptome changes were observed across different PBMC cell types as a factor of time from blood draw to PBMC isolation and as a consequence of blood storage. This should be kept in mind when interpreting experimental results., Competing Interests: The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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- 2023
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33. COVID-19 in pediatrics: Genetic susceptibility.
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Glessner JT, Chang X, Mentch F, Qu H, Abrams DJ, Thomas A, Sleiman PMA, and Hakonarson H
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The uptick in SARS-CoV-2 infection has resulted in a worldwide COVID-19 pandemic, which has created troublesome health and economic problems. We performed case-control meta-analyses in both African and European ethnicity COVID-19 disease cases based on laboratory test and phenotypic criteria. The cases had laboratory-confirmed SARS-CoV-2 infection. We uniquely investigated COVID infection genetics in a pediatric population. Our cohort has a large African ancestry component, also unique to our study. We tested for genetic variant association in 498 cases vs. 1,533 controls of African ancestry and 271 cases vs. 855 controls of European ancestry. We acknowledge that the sample size is relatively small, owing to the low prevalence of COVID infection among pediatric individuals. COVID-19 cases averaged 13 years of age. Pediatric genetic studies enhance the ability to detect genetic associations with a limited possible environment impact. Our findings support the notion that some genetic variants, most notably at the SEMA6D, FMN1, ACTN1, PDS5B, NFIA, ADGRL3, MMP27, TENM3, SPRY4, MNS1, and RSU1 loci, play a role in COVID-19 infection susceptibility. The pediatric cohort also shows nominal replication of previously reported adult study results: CCR9, CXCR6, FYCO1, LZTFL1, TDGF1, CCR1, CCR2, CCR3, CCR5, MAPT-AS1, and IFNAR2 gene variants. Reviewing the biological roles of genes implicated here, NFIA looks to be the most interesting as it binds to a palindromic sequence observed in both viral and cellular promoters and in the adenovirus type 2 origin of replication., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Glessner, Chang, Mentch, Qu, Abrams, Thomas, Sleiman and Hakonarson.)
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- 2022
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34. A cross-disorder dosage sensitivity map of the human genome.
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Collins RL, Glessner JT, Porcu E, Lepamets M, Brandon R, Lauricella C, Han L, Morley T, Niestroj LM, Ulirsch J, Everett S, Howrigan DP, Boone PM, Fu J, Karczewski KJ, Kellaris G, Lowther C, Lucente D, Mohajeri K, Nõukas M, Nuttle X, Samocha KE, Trinh M, Ullah F, Võsa U, Hurles ME, Aradhya S, Davis EE, Finucane H, Gusella JF, Janze A, Katsanis N, Matyakhina L, Neale BM, Sanders D, Warren S, Hodge JC, Lal D, Ruderfer DM, Meck J, Mägi R, Esko T, Reymond A, Kutalik Z, Hakonarson H, Sunyaev S, Brand H, and Talkowski ME
- Subjects
- Gene Dosage, Haploinsufficiency genetics, Humans, DNA Copy Number Variations genetics, Genome, Human
- Abstract
Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics., Competing Interests: Declaration of interests M.E.T. receives research funding and/or reagents from Levo Therapeutics, Microsoft Inc., and Illumina Inc. R.B., C. Lauricella, A.J., L.M., S.W., and J.M. are employees of GeneDx, Inc. S.A. is an employee of Invitae Corp., (Copyright © 2022 Elsevier Inc. All rights reserved.)
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- 2022
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35. Identification of Novel Loci Shared by Juvenile Idiopathic Arthritis Subtypes Through Integrative Genetic Analysis.
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Li J, Li YR, Glessner JT, Yang J, March ME, Kao C, Vaccaro CN, Bradfield JP, Li J, Mentch FD, Qu HQ, Qi X, Chang X, Hou C, Abrams DJ, Qiu H, Wei Z, Connolly JJ, Wang F, Snyder J, Flatø B, Thompson SD, Langefeld CD, Lie BA, Munro JE, Wise C, Sleiman PMA, and Hakonarson H
- Subjects
- Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Arthritis, Juvenile drug therapy, Arthritis, Juvenile genetics
- Abstract
Objective: Juvenile idiopathic arthritis (JIA) is the most common chronic immune-mediated joint disease among children and encompasses a heterogeneous group of immune-mediated joint disorders classified into 7 subtypes according to clinical presentation. However, phenotype overlap and biologic evidence suggest a shared mechanistic basis between subtypes. This study was undertaken to systematically investigate shared genetic underpinnings of JIA subtypes., Methods: We performed a heterogeneity-sensitive genome-wide association study encompassing a total of 1,245 JIA cases (classified into 7 subtypes) and 9,250 controls, followed by fine-mapping of candidate causal variants at each genome-wide significant locus, functional annotation, and pathway and network analysis. We further identified candidate drug targets and drug repurposing opportunities by in silico analyses., Results: In addition to the major histocompatibility complex locus, we identified 15 genome-wide significant loci shared between at least 2 JIA subtypes, including 10 novel loci. Functional annotation indicated that candidate genes at these loci were expressed in diverse immune cell types., Conclusion: This study identified novel genetic loci shared by JIA subtypes. Our findings identified candidate mechanisms underlying JIA subtypes and candidate targets with drug repurposing opportunities for JIA treatment., (© 2022 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)
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- 2022
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36. An electronic health record (EHR) phenotype algorithm to identify patients with attention deficit hyperactivity disorders (ADHD) and psychiatric comorbidities.
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Slaby I, Hain HS, Abrams D, Mentch FD, Glessner JT, Sleiman PMA, and Hakonarson H
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- Algorithms, Case-Control Studies, Child, Comorbidity, Electronic Health Records, Humans, Phenotype, Prospective Studies, Retrospective Studies, Attention Deficit Disorder with Hyperactivity complications, Attention Deficit Disorder with Hyperactivity diagnosis, Attention Deficit Disorder with Hyperactivity epidemiology
- Abstract
Background: In over half of pediatric cases, ADHD presents with comorbidities, and often, it is unclear whether the symptoms causing impairment are due to the comorbidity or the underlying ADHD. Comorbid conditions increase the likelihood for a more severe and persistent course and complicate treatment decisions. Therefore, it is highly important to establish an algorithm that identifies ADHD and comorbidities in order to improve research on ADHD using biorepository and other electronic record data., Methods: It is feasible to accurately distinguish between ADHD in isolation from ADHD with comorbidities using an electronic algorithm designed to include other psychiatric disorders. We sought to develop an EHR phenotype algorithm to discriminate cases with ADHD in isolation from cases with ADHD with comorbidities more effectively for efficient future searches in large biorepositories. We developed a multi-source algorithm allowing for a more complete view of the patient's EHR, leveraging the biobank of the Center for Applied Genomics (CAG) at Children's Hospital of Philadelphia (CHOP). We mined EHRs from 2009 to 2016 using International Statistical Classification of Diseases and Related Health Problems (ICD) codes, medication history and keywords specific to ADHD, and comorbid psychiatric disorders to facilitate genotype-phenotype correlation efforts. Chart abstractions and behavioral surveys added evidence in support of the psychiatric diagnoses. Most notably, the algorithm did not exclude other psychiatric disorders, as is the case in many previous algorithms. Controls lacked psychiatric and other neurological disorders. Participants enrolled in various CAG studies at CHOP and completed a broad informed consent, including consent for prospective analyses of EHRs. We created and validated an EHR-based algorithm to classify ADHD and comorbid psychiatric status in a pediatric healthcare network to be used in future genetic analyses and discovery-based studies., Results: In this retrospective case-control study that included data from 51,293 subjects, 5840 ADHD cases were discovered of which 46.1% had ADHD alone and 53.9% had ADHD with psychiatric comorbidities. Our primary study outcome was to examine whether the algorithm could identify and distinguish ADHD exclusive cases from ADHD comorbid cases. The results indicate ICD codes coupled with medication searches revealed the most cases. We discovered ADHD-related keywords did not increase yield. However, we found including ADHD-specific medications increased our number of cases by 21%. Positive predictive values (PPVs) were 95% for ADHD cases and 93% for controls., Conclusion: We established a new algorithm and demonstrated the feasibility of the electronic algorithm approach to accurately diagnose ADHD and comorbid conditions, verifying the efficiency of our large biorepository for further genetic discovery-based analyses., Trial Registration: ClinicalTrials.gov, NCT02286817 . First posted on 10 November 2014., Clinicaltrials: gov, NCT02777931 . First posted on 19 May 2016., Clinicaltrials: gov, NCT03006367 . First posted on 30 December 2016., Clinicaltrials: gov, NCT02895906 . First posted on 12 September 2016., (© 2022. The Author(s).)
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- 2022
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37. DeepCNV: a deep learning approach for authenticating copy number variations.
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Glessner JT, Hou X, Zhong C, Zhang J, Khan M, Brand F, Krawitz P, Sleiman PMA, Hakonarson H, and Wei Z
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- Area Under Curve, Benchmarking, Datasets as Topic, Disease classification, False Positive Reactions, Humans, ROC Curve, DNA Copy Number Variations, Deep Learning, Disease genetics, Genome, Human
- Abstract
Copy number variations (CNVs) are an important class of variations contributing to the pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains difficult, and the most currently applied methods suffer from an unacceptably high false positive rate. A common practice is to have human experts manually review original CNV calls for filtering false positives before further downstream analysis or experimental validation. Here, we propose DeepCNV, a deep learning-based tool, intended to replace human experts when validating CNV calls, focusing on the calls made by one of the most accurate CNV callers, PennCNV. The sophistication of the deep neural network algorithm is enriched with over 10 000 expert-scored samples that are split into training and testing sets. Variant confidence, especially for CNVs, is a main roadblock impeding the progress of linking CNVs with the disease. We show that DeepCNV adds to the confidence of the CNV calls with an optimal area under the receiver operating characteristic curve of 0.909, exceeding other machine learning methods. The superiority of DeepCNV was also benchmarked and confirmed using an experimental wet-lab validation dataset. We conclude that the improvement obtained by DeepCNV results in significantly fewer false positive results and failures to replicate the CNV association results., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
- Published
- 2021
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38. Discovery of Novel Host Molecular Factors Underlying HBV/HCV Infection.
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Huang X, Glessner JT, Huang J, Zhou D, March ME, Wang H, Xia Q, Hakonarson H, and Li J
- Abstract
Hepatitis is an inflammatory condition of the liver, which is frequently caused by the infection of hepatitis B virus (HBV) or hepatitis C virus (HCV). Hepatitis can lead to the development of chronic complications including cancer, making it a major public health burden. Co-infection of HBV and HCV can result in faster disease progression. Therefore, it is important to identify shared genetic susceptibility loci for HBV and HCV infection to further understand the underlying mechanism. Through a meta-analysis based on genome-wide association summary statistics of HBV and HCV infection, we found one novel locus in the Asian population and two novel loci in the European population. By functional annotation based on multi-omics data, we identified the likely target genes at each novel locus, such as HMGB1 and ATF3 , which play a critical role in autophagy and immune response to virus. By re-analyzing a microarray dataset from Hmgb1
-/- mice and RNA-seq data from mouse liver tissue overexpressing ATF3 , we found that differential expression of autophagy and immune and metabolic gene pathways underlie these conditions. Our study reveals novel common susceptibility loci to HBV and HCV infection, supporting their role in linking autophagy signaling and immune response., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Huang, Glessner, Huang, Zhou, March, Wang, Xia, Hakonarson and Li.)- Published
- 2021
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39. Insights into non-autoimmune type 1 diabetes with 13 novel loci in low polygenic risk score patients.
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Qu J, Qu HQ, Bradfield JP, Glessner JT, Chang X, Tian L, March M, Connolly JJ, Roizen JD, Sleiman PMA, and Hakonarson H
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- Adolescent, Case-Control Studies, Child, Child, Preschool, Cohort Studies, Diabetes Mellitus, Type 1 epidemiology, Diabetes Mellitus, Type 1 pathology, Female, Genome-Wide Association Study, Humans, Infant, Infant, Newborn, Male, Phenotype, Risk Factors, United States epidemiology, Autoimmune Diseases physiopathology, Diabetes Mellitus, Type 1 genetics, Genetic Loci, Genetic Predisposition to Disease, Glucose Intolerance physiopathology, Obesity physiopathology, Polymorphism, Single Nucleotide
- Abstract
With polygenic risk score (PRS) for autoimmune type 1 diabetes (T1D), this study identified T1D cases with low T1D PRS and searched for susceptibility loci in these cases. Our hypothesis is that genetic effects (likely mediated by relatively rare genetic variants) of non-mainstream (or non-autoimmune) T1D might have been diluted in the previous studies on T1D cases in general. Two cohorts for the PRS modeling and testing respectively were included. The first cohort consisted of 3302 T1D cases and 6181 controls, and the independent second cohort consisted of 3297 T1D cases and 6169 controls. Cases with low T1D PRS were identified using PRSice-2 and compared to controls with low T1D PRS by genome-wide association (GWA) test. Thirteen novel genetic loci with high imputation quality (Quality Score r
2 > 0.91) were identified of SNPs/SNVs associated with low PRS T1D at genome-wide significance (P ≤ 5.0 × E-08), in addition to 4 established T1D loci, 3 reported loci by our previous study, as well as 9 potential novel loci represented by rare SNVs, but with relatively low imputation quality (Quality Score r2 < 0.90). For the 13 novel loci, 9 regions have been reported of association with obesity related traits by previous GWA studies. Three loci encoding long intergenic non-protein coding RNAs (lncRNA), and 2 loci involved in N-linked glycosylation are also highlighted in this study., (© 2021. The Author(s).)- Published
- 2021
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40. Association Between a Common, Benign Genotype and Unnecessary Bone Marrow Biopsies Among African American Patients.
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Van Driest SL, Abul-Husn NS, Glessner JT, Bastarache L, Nirenberg S, Schildcrout JS, Eswarappa MS, Belbin GM, Shaffer CM, Mentch F, Connolly J, Shi M, Stein CM, Roden DM, Hakonarson H, Cox NJ, Borinstein SC, and Mosley JD
- Subjects
- Adult, Female, Gene Expression Profiling statistics & numerical data, Genetic Profile, Genome-Wide Association Study, Humans, Leukocyte Count, Male, Polymorphism, Single Nucleotide, United States epidemiology, Unnecessary Procedures methods, Unnecessary Procedures statistics & numerical data, Black or African American genetics, Biopsy methods, Biopsy statistics & numerical data, Bone Marrow Examination methods, Bone Marrow Examination statistics & numerical data, Duffy Blood-Group System genetics, Neutropenia diagnosis, Neutropenia ethnology, Neutropenia genetics, Receptors, Cell Surface genetics
- Abstract
Importance: Up to two-thirds of African American individuals carry the benign rs2814778-CC genotype that lowers total white blood cell (WBC) count., Objective: To examine whether the rs2814778-CC genotype is associated with an increased likelihood of receiving a bone marrow biopsy (BMB) for an isolated low WBC count., Design, Setting, and Participants: This retrospective genetic association study assessed African American patients younger than 90 years who underwent a BMB at Vanderbilt University Medical Center, Mount Sinai Health System, or Children's Hospital of Philadelphia from January 1, 1998, to December 31, 2020., Exposure: The rs2814778-CC genotype., Main Outcomes and Measures: The proportion of individuals with the CC genotype who underwent BMB for an isolated low WBC count and had a normal biopsy result compared with the proportion of individuals with the CC genotype who underwent BMB for other indications and had a normal biopsy result., Results: Among 399 individuals who underwent a BMB (mean [SD] age, 41.8 [22.5] years, 234 [59%] female), 277 (69%) had the CC genotype. A total of 35 patients (9%) had clinical histories of isolated low WBC counts, and 364 (91%) had other histories. Of those with a clinical history of isolated low WBC count, 34 of 35 (97%) had the CC genotype vs 243 of 364 (67%) of those without a low WBC count history. Among those with the CC genotype, 33 of 34 (97%) had normal results for biopsies performed for isolated low WBC counts compared with 134 of 243 individuals (55%) with biopsies performed for other histories (P < .001)., Conclusions and Relevance: In this genetic association study, among patients of African American race who had a BMB with a clinical history of isolated low WBC counts, the rs2814778-CC genotype was highly prevalent, and 97% of these BMBs identified no hematologic abnormality. Accounting for the rs2814778-CC genotype in clinical decision-making could avoid unnecessary BMB procedures.
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- 2021
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41. Genome-Wide Detection of Copy Number Variations and Their Association With Distinct Phenotypes in the World's Sheep.
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Salehian-Dehkordi H, Xu YX, Xu SS, Li X, Luo LY, Liu YJ, Wang DF, Cao YH, Shen M, Gao L, Chen ZH, Glessner JT, Lenstra JA, Esmailizadeh A, Li MH, and Lv FH
- Abstract
Copy number variations (CNVs) are a major source of structural variation in mammalian genomes. Here, we characterized the genome-wide CNV in 2059 sheep from 67 populations all over the world using the Ovine Infinium HD (600K) SNP BeadChip. We tested their associations with distinct phenotypic traits by conducting multiple independent genome-wide tests. In total, we detected 7547 unique CNVs and 18,152 CNV events in 1217 non-redundant CNV regions (CNVRs), covering 245 Mb (∼10%) of the whole sheep genome. We identified seven CNVRs with frequencies correlating to geographical origins and 107 CNVRs overlapping 53 known quantitative trait loci (QTLs). Gene ontology and pathway enrichment analyses of CNV-overlapping genes revealed their common involvement in energy metabolism, endocrine regulation, nervous system development, cell proliferation, immune, and reproduction. For the phenotypic traits, we detected significantly associated (adjusted P < 0.05) CNVRs harboring functional candidate genes, such as SBNO2 for polycerate; PPP1R11 and GABBR1 for tail weight; AKT1 for supernumerary nipple; CSRP1 , WNT7B , HMX1 , and FGFR3 for ear size; and NOS3 and FILIP1 in Wadi sheep; SNRPD3 , KHDRBS2 , and SDCCAG3 in Hu sheep; NOS3 , BMP1 , and SLC19A1 in Icelandic; CDK2 in Finnsheep; MICA in Romanov; and REEP4 in Texel sheep for litter size. These CNVs and associated genes are important markers for molecular breeding of sheep and other livestock species., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Salehian-Dehkordi, Xu, Xu, Li, Luo, Liu, Wang, Cao, Shen, Gao, Chen, Glessner, Lenstra, Esmailizadeh, Li and Lv.)
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- 2021
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42. Association of novel rare coding variants with juvenile idiopathic arthritis.
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Meng X, Hou X, Wang P, Glessner JT, Qu HQ, March ME, Zhang S, Qi X, Zhu C, Nguyen K, Gao X, Li X, Liu Y, Zhou W, Zhang S, Li J, Sun Y, Yang J, Sleiman PMA, Xia Q, Hakonarson H, and Li J
- Subjects
- Child, Databases, Genetic, Female, Gene Expression, Genome-Wide Association Study, Humans, Male, RNA-Seq, Signal Transduction genetics, Exome Sequencing, Arthritis, Juvenile genetics, Genetic Variation genetics, Immune System Phenomena genetics
- Abstract
Objective: Juvenile idiopathic arthritis (JIA) is the most common type of arthritis among children, but a few studies have investigated the contribution of rare variants to JIA. In this study, we aimed to identify rare coding variants associated with JIA for the genome-wide landscape., Methods: We established a rare variant calling and filtering pipeline and performed rare coding variant and gene-based association analyses on three RNA-seq datasets composed of 228 JIA patients in the Gene Expression Omnibus against different sets of controls, and further conducted replication in our whole-exome sequencing (WES) data of 56 JIA patients. Then we conducted differential gene expression analysis and assessed the impact of recurrent functional coding variants on gene expression and signalling pathway., Results: By the RNA-seq data, we identified variants in two genes reported in literature as JIA causal variants, as well as additional 63 recurrent rare coding variants seen only in JIA patients. Among the 44 recurrent rare variants found in polyarticular patients, 10 were replicated by our WES of patients with the same JIA subtype. Several genes with recurrent functional rare coding variants have also common variants associated with autoimmune diseases. We observed immune pathways enriched for the genes with rare coding variants and differentially expressed genes., Conclusion: This study elucidated a novel landscape of recurrent rare coding variants in JIA patients and uncovered significant associations with JIA at the gene pathway level. The convergence of common variants and rare variants for autoimmune diseases is also highlighted in this study., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.)
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- 2021
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43. MONTAGE: a new tool for high-throughput detection of mosaic copy number variation.
- Author
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Glessner JT, Chang X, Liu Y, Li J, Khan M, Wei Z, Sleiman PMA, and Hakonarson H
- Subjects
- Genomics, Humans, Polymorphism, Single Nucleotide, Software, DNA Copy Number Variations, Genome-Wide Association Study
- Abstract
Background: Not all cells in a given individual are identical in their genomic makeup. Mosaicism describes such a phenomenon where a mixture of genotypic states in certain genomic segments exists within the same individual. Mosaicism is a prevalent and impactful class of non-integer state copy number variation (CNV). Mosaicism implies that certain cell types or subset of cells contain a CNV in a segment of the genome while other cells in the same individual do not. Several studies have investigated the impact of mosaicism in single patients or small cohorts but no comprehensive scan of mosaic CNVs has been undertaken to accurately detect such variants and interpret their impact on human health and disease., Results: We developed a tool called Montage to improve the accuracy of detection of mosaic copy number variants in a high throughput fashion. Montage directly interfaces with ParseCNV2 algorithm to establish disease phenotype genome-wide association and determine which genomic ranges had more or less than expected frequency of mosaic events. We screened for mosaic events in over 350,000 samples using 1% allele frequency as the detection limit. Additionally, we uncovered disease associations of multiple phenotypes with mosaic CNVs at several genomic loci. We additionally investigated the allele imbalance observations genome-wide to define non-diploid and non-integer copy number states., Conclusions: Our novel algorithm presents an efficient tool with fast computational runtime and high levels of accuracy of mosaic CNV detection. A curated mosaic CNV callset of 3716 events in 2269 samples is presented with comparability to previous reports and disease phenotype associations. The new algorithm can be freely accessed via: https://github.com/CAG-CNV/MONTAGE .
- Published
- 2021
- Full Text
- View/download PDF
44. Integrative analysis of genome-wide association studies identifies novel loci associated with neuropsychiatric disorders.
- Author
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Yao X, Glessner JT, Li J, Qi X, Hou X, Zhu C, Li X, March ME, Yang L, Mentch FD, Hain HS, Meng X, Xia Q, Hakonarson H, and Li J
- Subjects
- Child, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Attention Deficit Disorder with Hyperactivity genetics, Autism Spectrum Disorder genetics, Bipolar Disorder genetics, Depressive Disorder, Major genetics, Schizophrenia genetics
- Abstract
Neuropsychiatric disorders, such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), bipolar disorder (BIP), and major depressive disorder (MDD) share common clinical presentations, suggesting etiologic overlap. A substantial proportion of SNP-based heritability for neuropsychiatric disorders is attributable to genetic components, and genome-wide association studies (GWASs) focusing on individual diseases have identified multiple genetic loci shared between these diseases. Here, we aimed at identifying novel genetic loci associated with individual neuropsychiatric diseases and genetic loci shared by neuropsychiatric diseases. We performed multi-trait joint analyses and meta-analysis across five neuropsychiatric disorders based on their summary statistics from the Psychiatric Genomics Consortium (PGC), and further carried out a replication study of ADHD among 2726 cases and 16299 controls in an independent pediatric cohort. In the multi-trait joint analyses, we found five novel genome-wide significant loci for ADHD, one novel locus for BIP, and ten novel loci for MDD. We further achieved modest replication in our independent pediatric dataset. We conducted fine-mapping and functional annotation through an integrative multi-omics approach and identified causal variants and potential target genes at each novel locus. Gene expression profile and gene-set enrichment analysis further suggested early developmental stage expression pattern and postsynaptic membrane compartment enrichment of candidate genes at the genome-wide significant loci of these neuropsychiatric disorders. Therefore, through a multi-omics approach, we identified novel genetic loci associated with the five neuropsychiatric disorders which may help to better understand the underlying molecular mechanism of neuropsychiatric diseases.
- Published
- 2021
- Full Text
- View/download PDF
45. Association of DLL1 with type 1 diabetes in patients characterized by low polygenic risk score.
- Author
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Qu J, Qu HQ, Bradfield JP, Glessner JT, Chang X, Tian L, March ME, Roizen JD, Sleiman PM, and Hakonarson H
- Subjects
- Female, Genetic Association Studies, Genome-Wide Association Study, Humans, Male, Calcium-Binding Proteins genetics, Diabetes Mellitus, Type 1 genetics, Genetic Predisposition to Disease, Membrane Proteins genetics, Polymorphism, Single Nucleotide
- Abstract
Type 1 diabetes (T1D) is a heterogeneous disease. This study identified T1D cases with low polygenic risk score (PRS) to better represent T1D cases with less prominent autoimmune response (T1bD), and performed a gene-based association study to identify novel susceptibility loci in two independent cohorts, characterized by low PRS. The Notch ligand Delta-like 1 gene (DLL1) was identified with genome-wide significance in both cohorts, highlighting the roles of DLL1 genetic variants in T1D patients with low PRS, supported by functional evidence from a recent study by Rubey et al., Competing Interests: Declaration of competing interest None to declare., (Copyright © 2020 Elsevier Inc. All rights reserved.)
- Published
- 2021
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- View/download PDF
46. Rare copy number variants in over 100,000 European ancestry subjects reveal multiple disease associations.
- Author
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Li YR, Glessner JT, Coe BP, Li J, Mohebnasab M, Chang X, Connolly J, Kao C, Wei Z, Bradfield J, Kim C, Hou C, Khan M, Mentch F, Qiu H, Bakay M, Cardinale C, Lemma M, Abrams D, Bridglall-Jhingoor A, Behr M, Harrison S, Otieno G, Thomas A, Wang F, Chiavacci R, Wu L, Hadley D, Goldmuntz E, Elia J, Maris J, Grundmeier R, Devoto M, Keating B, March M, Pellagrino R, Grant SFA, Sleiman PMA, Li M, Eichler EE, and Hakonarson H
- Subjects
- Comparative Genomic Hybridization, Databases, Genetic, Genetic Loci, Genetic Predisposition to Disease ethnology, Genome-Wide Association Study, Humans, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, DNA Copy Number Variations, Genetic Predisposition to Disease genetics, Genome, Human genetics, White People genetics
- Abstract
Copy number variants (CNVs) are suggested to have a widespread impact on the human genome and phenotypes. To understand the role of CNVs across human diseases, we examine the CNV genomic landscape of 100,028 unrelated individuals of European ancestry, using SNP and CGH array datasets. We observe an average CNV burden of ~650 kb, identifying a total of 11,314 deletion, 5625 duplication, and 2746 homozygous deletion CNV regions (CNVRs). In all, 13.7% are unreported, 58.6% overlap with at least one gene, and 32.8% interrupt coding exons. These CNVRs are significantly more likely to overlap OMIM genes (2.94-fold), GWAS loci (1.52-fold), and non-coding RNAs (1.44-fold), compared with random distribution (P < 1 × 10
-3 ). We uncover CNV associations with four major disease categories, including autoimmune, cardio-metabolic, oncologic, and neurological/psychiatric diseases, and identify several drug-repurposing opportunities. Our results demonstrate robust frequency definition for large-scale rare variant association studies, identify CNVs associated with major disease categories, and illustrate the pleiotropic impact of CNVs in human disease.- Published
- 2020
- Full Text
- View/download PDF
47. CNV Association of Diverse Clinical Phenotypes from eMERGE reveals novel disease biology underlying cardiovascular disease.
- Author
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Glessner JT, Li J, Desai A, Palmer M, Kim D, Lucas AM, Chang X, Connolly JJ, Almoguera B, Harley JB, Jarvik GP, Ritchie MD, Sleiman PMA, Roden DM, Crosslin D, and Hakonarson H
- Subjects
- Aged, Aged, 80 and over, Cardiovascular Diseases diagnosis, Cardiovascular Diseases physiopathology, Electrocardiography methods, Electronic Health Records, Female, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide genetics, Body Mass Index, Cardiovascular Diseases genetics, DNA Copy Number Variations genetics, Genome-Wide Association Study methods, Genomics methods, Phenotype
- Abstract
Background: Cardiovascular disease is the leading cause of death in the United States. Consequently, individuals who are genetically predisposed for high risk of cardiovascular disease would benefit most from prevention and early intervention approaches. Among common health risk factors affecting adult populations, we evaluated 23 cardiovascular disease-related traits, including BMI, glucose levels and lipid profiling to determine their associations with low-frequency recurrent copy number variations (CNV) (population frequency < 5%)., Results: We examined 10,619 unrelated subjects of European ancestry from the Electronic Medical Records and Genomics (eMERGE) Network who were genotyped with 657,366 markers genome-wide on the Illumina Infinium Quad 660 array. We performed CNV calling based on array marker intensity and evaluated data quality, ancestry stratification, and relatedness to ensure unbiased association discovery. Using a segment-based scoring approach, we assessed the association of all CNVs with each trait. In this large genome-wide analysis of low-frequency CNVs, we observed 11 novel genome-wide significant associations of low-frequency CNVs with major cardiovascular disease traits., Conclusion: In one of the largest genome-wide studies for low-frequency recurrent CNVs, we identified 11 loci associated with cardiovascular disease and related traits at the genome-wide significance level that may serve as biomarkers for prevention and early intervention studies in subjects who are at elevated risk. Our study further supports the role of low-frequency recurrent CNVs in the pathogenesis of common complex disease traits., (Copyright © 2019. Published by Elsevier B.V.)
- Published
- 2020
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48. An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder.
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Werling DM, Brand H, An JY, Stone MR, Zhu L, Glessner JT, Collins RL, Dong S, Layer RM, Markenscoff-Papadimitriou E, Farrell A, Schwartz GB, Wang HZ, Currall BB, Zhao X, Dea J, Duhn C, Erdman CA, Gilson MC, Yadav R, Handsaker RE, Kashin S, Klei L, Mandell JD, Nowakowski TJ, Liu Y, Pochareddy S, Smith L, Walker MF, Waterman MJ, He X, Kriegstein AR, Rubenstein JL, Sestan N, McCarroll SA, Neale BM, Coon H, Willsey AJ, Buxbaum JD, Daly MJ, State MW, Quinlan AR, Marth GT, Roeder K, Devlin B, Talkowski ME, and Sanders SJ
- Subjects
- Female, Genome genetics, Genome-Wide Association Study methods, Humans, Male, Autism Spectrum Disorder genetics, Genetic Predisposition to Disease genetics, INDEL Mutation genetics, Polymorphism, Single Nucleotide genetics, Protein Isoforms genetics
- Abstract
Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.
- Published
- 2018
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49. Copy number variation meta-analysis reveals a novel duplication at 9p24 associated with multiple neurodevelopmental disorders.
- Author
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Glessner JT, Li J, Wang D, March M, Lima L, Desai A, Hadley D, Kao C, Gur RE, Cohen N, Sleiman PMA, Li Q, and Hakonarson H
- Subjects
- Adaptor Proteins, Signal Transducing, Cytoskeletal Proteins, Guanine Nucleotide Exchange Factors genetics, Humans, Tumor Suppressor Proteins genetics, Chromosomes, Human, Pair 9 genetics, DNA Copy Number Variations, Gene Duplication, Neurodevelopmental Disorders genetics
- Abstract
Background: Neurodevelopmental and neuropsychiatric disorders represent a wide spectrum of heterogeneous yet inter-related disease conditions. The overlapping clinical presentations of these diseases suggest a shared genetic etiology. We aim to identify shared structural variants spanning the spectrum of five neuropsychiatric disorders., Methods: We investigated copy number variations (CNVs) in five cohorts, including schizophrenia (SCZ), bipolar disease (BD), autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), and depression, from 7849 cases and 10,799 controls. CNVs were called based on intensity data from genome-wide SNP arrays and CNV frequency was compared between cases and controls in each disease cohort separately. Meta-analysis was performed via a gene-based approach. Quantitative PCR (qPCR) was employed to validate novel significant loci., Results: In our meta-analysis, two genes containing CNVs with exonic overlap reached genome-wide significance threshold of meta P value < 9.4 × 10
-6 for deletions and 7.5 × 10-6 for duplications. We observed significant overlap between risk CNV loci across cohorts. In addition, we identified novel significant associations of DOCK8/KANK1 duplications (meta P value = 7.5 × 10-7 ) across all cohorts, and further validated the CNV region with qPCR., Conclusions: In the first large scale meta-analysis of CNVs across multiple neurodevelopmental/psychiatric diseases, we uncovered novel significant associations of structural variants in the locus of DOCK8/KANK1 shared by five diseases, suggesting common etiology of these clinically distinct neurodevelopmental conditions.- Published
- 2017
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50. Defining the diverse spectrum of inversions, complex structural variation, and chromothripsis in the morbid human genome.
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Collins RL, Brand H, Redin CE, Hanscom C, Antolik C, Stone MR, Glessner JT, Mason T, Pregno G, Dorrani N, Mandrile G, Giachino D, Perrin D, Walsh C, Cipicchio M, Costello M, Stortchevoi A, An JY, Currall BB, Seabra CM, Ragavendran A, Margolin L, Martinez-Agosto JA, Lucente D, Levy B, Sanders SJ, Wapner RJ, Quintero-Rivera F, Kloosterman W, and Talkowski ME
- Subjects
- Autism Spectrum Disorder genetics, Gene Order, Gene Rearrangement, Genetic Predisposition to Disease, High-Throughput Nucleotide Sequencing, Humans, Mutation, Chromosome Aberrations, Chromosome Inversion, Chromothripsis, Genome, Human, Genomics methods
- Abstract
Background: Structural variation (SV) influences genome organization and contributes to human disease. However, the complete mutational spectrum of SV has not been routinely captured in disease association studies., Results: We sequenced 689 participants with autism spectrum disorder (ASD) and other developmental abnormalities to construct a genome-wide map of large SV. Using long-insert jumping libraries at 105X mean physical coverage and linked-read whole-genome sequencing from 10X Genomics, we document seven major SV classes at ~5 kb SV resolution. Our results encompass 11,735 distinct large SV sites, 38.1% of which are novel and 16.8% of which are balanced or complex. We characterize 16 recurrent subclasses of complex SV (cxSV), revealing that: (1) cxSV are larger and rarer than canonical SV; (2) each genome harbors 14 large cxSV on average; (3) 84.4% of large cxSVs involve inversion; and (4) most large cxSV (93.8%) have not been delineated in previous studies. Rare SVs are more likely to disrupt coding and regulatory non-coding loci, particularly when truncating constrained and disease-associated genes. We also identify multiple cases of catastrophic chromosomal rearrangements known as chromoanagenesis, including somatic chromoanasynthesis, and extreme balanced germline chromothripsis events involving up to 65 breakpoints and 60.6 Mb across four chromosomes, further defining rare categories of extreme cxSV., Conclusions: These data provide a foundational map of large SV in the morbid human genome and demonstrate a previously underappreciated abundance and diversity of cxSV that should be considered in genomic studies of human disease.
- Published
- 2017
- Full Text
- View/download PDF
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