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51. Association analysis of common variants of STAT6, GATA3, and STAT4 to asthma and high serum IgE phenotypes.

Author

Pykäläinen, Maritta, Kinos, Riikka, Valkonen, Sanna, Rydman, Pia, Kilpeläinen, Maritta, Laitinen, Lauri A., Karjalainen, Jussi, Nieminen, Markku, Hurme, Mikko, Kere, Juha, Laitinen, Tarja, and Lahesmaa, Riitta

Subjects
ASTHMA, IMMUNOGLOBULIN E, PHENOTYPES, IMMUNE response, TRANSCRIPTION factors, GENETIC polymorphisms, INTERLEUKINS, CELLULAR signal transduction
Abstract

Background: Immune responses characterized by TH2 type cells and IgE are important for the development of asthma and atopy. The transcription factors STAT6, GATA3, and STAT4 mediate the cytokine-induced development of naïve CD4+ T cells into either TH1 or TH2 type. Objective: We studied genetic variation of the STAT6, GATA3, and STAT4 genes and examined whether single nucleotide polymorphisms (SNPs) in these loci were associated with asthma or serum high IgE levels in the Finnish asthmatic families. Methods: With denaturing high-performance liquid chromatography we screened all exons and exon-intron boundaries of the genes in 14 to 22 patients. All identified SNPs were genotyped in 120 nuclear families, and the haplotypes were analyzed by Haplotype Pattern Mining based statistical analysis. When potential association was observed, the analysis was replicated among 245 asthmatic patients and 405 population-based control subjects. Results: A total of 23 SNPs were identified, of which 8 were not previously listed in the SNP database. Interestingly, a haplotype analysis of GATA3 showed 3 related haplotypes that associated with different asthma and atopy related phenotypes among both the family and case-control data sets. For STAT6 and STAT4, no significant association to asthma or serum total IgE levels was observed. Conclusions: We identified a panel of novel SNPs in genes coding for proteins important in the TH1/TH2 cell differentiation. SNPs of the GATA3 gene showed an initial association to asthma-related phenotypes. Elucidation of the importance of the identified panel of SNPs in other TH1/TH2 mediated diseases will be of great interest. [ABSTRACT FROM AUTHOR]

Published
2005
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52. A catalog of genetic loci associated with kidney function from analyses of a million individuals

Author

Wuttke, Matthias, Li, Yong, Li, Man, Sieber, Karsten B., Feitosa, Mary F., Gorski, Mathias, Tin, Adrienne, Wang, Lihua, Chu, Audrey Y., Hoppmann, Anselm, Kirsten, Holger, Giri, Ayush, Chai, Jin-Fang, Sveinbjornsson, Gardar, Tayo, Bamidele O., Nutile, Teresa, Fuchsberger, Christian, Marten, Jonathan, Cocca, Massimiliano, Ghasemi, Sahar, Xu, Yizhe, Horn, Katrin, Noce, Damia, van der Most, Peter J., Sedaghat, Sanaz, Yu, Zhi, Akiyama, Masato, Afaq, Saima, Ahluwalia, Tarunveer S., Almgren, Peter, Amin, Najaf, Ärnlöv, Johan, Bakker, Stephan J. L., Bansal, Nisha, Baptista, Daniela, Bergmann, Sven, Biggs, Mary L., Biino, Ginevra, Boehnke, Michael, Boerwinkle, Eric, Boissel, Mathilde, Bottinger, Erwin P., Boutin, Thibaud S., Brenner, Hermann, Brumat, Marco, Burkhardt, Ralph, Butterworth, Adam S., Campana, Eric, Campbell, Archie, Campbell, Harry, Canouil, Mickaël, Carroll, Robert J., Catamo, Eulalia, Chambers, John C., Chee, Miao-Ling, Chee, Miao-Li, Chen, Xu, Cheng, Ching-Yu, Cheng, Yurong, Christensen, Kaare, Cifkova, Renata, Ciullo, Marina, Pina Concas, Maria, Cook, James P., Coresh, Josef, Corre, Tanguy, Sala, Cinzia Felicita, Cusi, Daniele, Danesh, John, Daw, E. Warwick, de Borst, Martin H., De Grandi, Alessandro, de Mutsert, Renée, de Vries, Aiko P. J., Degenhardt, Frauke, Delgado, Graciela, Demirkan, Ayse, Di Angelantonio, Emanuele, Dittrich, Katalin, Divers, Jasmin, Dorajoo, Rajkumar, Eckardt, Kai-Uwe, Ehret, Georg, Elliott, Paul, Endlich, Karlhans, Evans, Michele K., Felix, Janine F., Foo, Valencia Hui Xian, Franco, Oscar H., Franke, Andre, Freedman, Barry I., Freitag-Wolf, Sandra, Friedlander, Yechiel, Froguel, Philippe, Gansevoort, Ron T., Gao, He, Gasparini, Paolo, Gaziano, J. Michael, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Giulianini, Franco, Gögele, Martin, Gordon, Scott D., Gudbjartsson, Daniel F., Gudnason, Vilmundur, Haller, Toomas, Hamet, Pavel, Harris, Tamara B., Hartman, Catharina A., Hayward, Caroline, Hellwege, Jacklyn N., Heng, Chew-Kiat, Hickst, Andrew A., Hofer, Edith, Huang, Wei, Hutri-Kähönen, Nina, Hwang, Shih-Jen, ikram, M. Arfan, indridason, Olafur S., Ingelsson, Erik, ising, Marcus, Jaddoe, Vincent W. V., Jakobsdottir, Johanna, Jonas, Jost B, Joshi, Peter K., Shilpa Josyula, Navya, Jung, Bettina, Kähönen, Mika, Kamatani, Yoichiro, Kammerer, Candace M., Kanai, Masahiro, Kastarinen, Mika, Kerr, Shona M., Khor, Chiea-Chuen, Kiess, Wieland, Kleber, Marcus E., Koenig, Wolfgang, Kooner, Jaspal S., Körner, Antje, Kovacs, Peter, Kraja, Aldi T., Krajcoviechova, Alena, Kramer, Holly, Krämer, Bernhard K., Kronenberg, Florian, Kubo, Michiaki, Kühnel, Brigitte, Kuokkanen, Mikko, Kuusisto, Johanna, La Bianca, Martina, Laakso, Markku, Lange, Leslie A., Langefeld, Carl D., Jen-Mai Lee, Jeannette, Lehne, Benjamin, Lehtimäki, Terho, Lieb, Wolfgang, Cohort Study, Lifelines, Lim, Su-Chi, Lind, Lars, Lindgren, Cecilia M., Liu, Jun, Liu, Jianjun, Loeffler, Markus, Loos, Ruth J. F., Lucae, Susanne, Ann Lukas, Mary, Lyytikäinen, Leo-Pekka, Mägi, Reedik, Magnusson, Patrik K. E., Mahajan, Anubha, Martin, Nicholas G., Martins, Jade, März, Winfried, Mascalzoni, Deborah, Matsuda, Koichi, Christa Meisinger, Meitinger, Thomas, Melander, Olle, Metspalu, Andres, Mikaelsdottir, Evgenia K., Milaneschi, Yuri, Miliku, Kozeta, Mishra, Pashupati P., Veteran Program, V. A. Million, Mohlke, Karen L., Mononen, Nina, Montgomery, Grant W., Mook-Kanamori, Dennis O., Mychaleckyj, Josyf C., Nadkarni, Girish N, Nalls, Mike A., Nauck, Matthias, Nikus, Kjell, Ning, Boting, Nolte, ilja M., Noordam, Raymond, O’Connell, Jeffrey, O’Donoghue, Michelle L., Olafsson, Isleifur, Oldehinkel, Albertine J., Orho-Melander, Marju, Ouwehand, Willem H., Padmanabhan, Sandosh, Palmer, Nicholette D., Palsson, Runolfur, Penninx, Brenda W. J. H., Perls, Thomas, Perola, Markus, Pirastu, Mario, Pirastu, Nicola, Pistis, Giorgio, Podgornaia, Anna I., Polasek, Ozren, Ponte, Belen, Porteous, David J., Poulain, Tanja, Pramstaller, Peter P., Preuss, Michael H., Prins, Bram P., Province, Michael A., Rabelink, Ton J., Raffield, Laura M., Raitakari, Olli T., Reilly, Dermot F., Rettig, Rainer, Rheinberger, Myriam, Rice, Kenneth M., Ridker, Paul M., Rivadeneira, Fernando, Rizzi, Federica, Roberts, David J., Robino, Antonietta, Rossing, Peter, Rudan, Igor, Rueedi, Rico, Ruggiero, Daniela, Ryan, Kathleen A., Saba, Yasaman, Sabanayagam, Charumathi, Salomaa, Veikko, Salvi, Erika, Saum, Kai-Uwe, Schmidt, Helena, Schmidt, Reinhold, Schöttker, Ben, Schulz, Christina-Alexandra, Schupf, Nicole, Shaffer, Christian M., Shi, Yuan, Smith, Albert V., Smith, Blair H., Soranzo, Nicole, Spracklen, Cassandra N., Strauch, Konstantin, Stringham, Heather M., Stumvoll, Michael, Svensson, Per O., Szymczak, Silke, Tai, E-Shyong, Tajuddin, Salman M., Tan, Nicholas Y. Q., Taylor, Kent D., Teren, Andrej, Tham, Yih-Chung, Thiery, Joachim, Thio, Chris H. L., Thomsen, Hauke, Thorleifsson, Gudmar, Toniolo, Daniela, Tönjes, Anke, Tremblay, Johanne, Tzoulaki, Ioanna, Uitterlinden, André G., Vaccargiu, Simona, van Dam, Rob M., van der Harst, Pim, van Duijn, Cornelia M., Velez Edward, Digna R., Verweij, Niek, Vogelezang, suzanne, Völker, üwe, Vollenweider, Peter, Waeber, Gerard, Waldenberger, Melanie, Wallentin, Lars, Wang, Ya Xing, Wang, Chaolong, Waterworth, Dawn M., Bin Wei, Wen, White, Harvey, Whitfield, John B., Wild, Sarah H., Wilson, James F., Wojczynski, Mary K., Wong, Charlene, Wong, Tien-Yin, Xu, Liang, Yang, Qiong, Yasuda, Masayuki, Yerges-Armstrong, Laura M., Zhang, Weihua, Zonderman, Alan B., Rotter, Jerome I., Bochud, Murielle, Psaty, Bruce M., Vitart, Veronique, Wilson, James G., Dehghan, Abbas, Parsa, Afshin, Chasman, Daniel I., Ho, Kevin, Morris, Andrew P., Devuyst, Olivier, Akilesh, Shreeram, Pendergrass, Sarah A., Sim, Xueling, Böger, Carsten A., Okada, Yukinori, Edwards, Todd L., Snieder, Harold, Stefansson, Kari, Hung, Adriana M., Heid, Iris M., Markus Scholz, Teumer, Alexander, Köttgen, Anna, Pattaro, Cristian, Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Cardiovascular Centre (CVC), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Life Course Epidemiology (LCE), Internal Medicine, Epidemiology, Erasmus MC other, Pediatrics, Psychiatry, APH - Mental Health, APH - Digital Health, Wuttke, M, Li, Y, Li, M, Sieber, Kb, Feitosa, Mf, Gorski, M, Tin, A, Wang, L, Chu, Ay, Hoppmann, A, Kirsten, H, Giri, A, Chai, Jf, Sveinbjornsson, G, Tayo, Bo, Nutile, T, Fuchsberger, C, Marten, J, Cocca, M, Ghasemi, S, Xu, Y, Horn, K, Noce, D, van der Most, Pj, Sedaghat, S, Yu, Z, Akiyama, M, Afaq, S, Ahluwalia, T, Almgren, P, Amin, N, Ärnlöv, J, Bakker, Sjl, Bansal, N, Baptista, D, Bergmann, S, Biggs, Ml, Biino, G, Boehnke, M, Boerwinkle, E, Boissel, M, Bottinger, Ep, Boutin, T, Brenner, H, Brumat, M, Burkhardt, R, Butterworth, A, Campana, Eric, Campbell, A, Campbell, H, Canouil, M, Carroll, Rj, Catamo, E, Chambers, Jc, Chee, Ml, Chen, X, Cheng, Cy, Cheng, Y, Christensen, K, Cifkova, R, Ciullo, M, Concas, Mp, Cook, Jp, Coresh, J, Corre, T, Sala, Cf, Cusi, D, Danesh, J, Daw, Ew, de Borst, Mh, De Grandi, A, de Mutsert, R, de Vries, Apj, Degenhardt, F, Delgado, G, Demirkan, A, Di Angelantonio, E, Dittrich, K, Divers, J, Dorajoo, R, Eckardt, Ku, Ehret, G, Elliott, P, Endlich, K, Evans, Mk, Felix, Jf, Foo, Vhx, Franco, Oh, Franke, A, Freedman, Bi, Freitag-Wolf, S, Friedlander, Y, Froguel, P, Gansevoort, Rt, Gao, H, Gasparini, P, Gaziano, Jm, Giedraitis, V, Gieger, C, Girotto, G, Giulianini, F, Gögele, M, Gordon, Sd, Gudbjartsson, Df, Gudnason, V, Haller, T, Hamet, P, Harris, Tb, Hartman, Ca, Hayward, C, Hellwege, Jn, Heng, Ck, Hicks, Aa, Hofer, E, Huang, W, Hutri-Kähönen, N, Hwang, Sj, Ikram, Ma, Indridason, O, Ingelsson, E, Ising, M, Jaddoe, Vwv, Jakobsdottir, J, Jonas, Jb, Joshi, Pk, Josyula, N, Jung, B, Kähönen, M, Kamatani, Y, Kammerer, Cm, Kanai, M, Kastarinen, M, Kerr, Sm, Khor, Cc, Kiess, W, Kleber, Me, Koenig, W, Kooner, J, Körner, A, Kovacs, P, Kraja, At, Krajcoviechova, A, Kramer, H, Krämer, Bk, Kronenberg, F, Kubo, M, Kühnel, B, Kuokkanen, M, Kuusisto, J, La Bianca, M, Laakso, M, Lange, La, Langefeld, Cd, Lee, Jj, Lehne, B, Lehtimäki, T, Lieb, W, Lifelines Cohort, Study, Lim, Sc, Lind, L, Lindgren, Cm, Liu, J, Loeffler, M, Loos, Rjf, Lucae, S, Lukas, Ma, Lyytikäinen, Lp, Mägi, R, Magnusson, Pke, Mahajan, A, Martin, Ng, Martins, J, März, W, Mascalzoni, D, Matsuda, K, Meisinger, C, Meitinger, T, Melander, O, Metspalu, A, Mikaelsdottir, Ek, Milaneschi, Y, Miliku, K, Mishra, Pp, V. A., Million Veteran Program, Mohlke, Kl, Mononen, N, Montgomery, Gw, Mook-Kanamori, Do, Mychaleckyj, Jc, Nadkarni, Gn, Nalls, Ma, Nauck, M, Nikus, K, Ning, B, Nolte, Im, Noordam, R, O'Connell, J, O'Donoghue, Ml, Olafsson, I, Oldehinkel, Aj, Orho-Melander, M, Ouwehand, Wh, Padmanabhan, S, Palmer, Nd, Palsson, R, Penninx, Bwjh, Perls, T, Perola, M, Pirastu, M, Pirastu, N, Pistis, G, Podgornaia, Ai, Polasek, O, Ponte, B, Porteous, Dj, Poulain, T, Pramstaller, Pp, Preuss, Mh, Prins, Bp, Province, Ma, Rabelink, Tj, Raffield, Lm, Raitakari, Ot, Reilly, Df, Rettig, R, Rheinberger, M, Rice, Km, Ridker, Pm, Rivadeneira, F, Rizzi, F, Roberts, Dj, Robino, A, Rossing, P, Rudan, I, Rueedi, R, Ruggiero, D, Ryan, Ka, Saba, Y, Sabanayagam, C, Salomaa, V, Salvi, E, Saum, Ku, Schmidt, H, Schmidt, R, Schöttker, B, Schulz, Ca, Schupf, N, Shaffer, Cm, Shi, Y, Smith, Av, Smith, Bh, Soranzo, N, Spracklen, Cn, Strauch, K, Stringham, Hm, Stumvoll, M, Svensson, Po, Szymczak, S, Tai, E, Tajuddin, Sm, Tan, Nyq, Taylor, Kd, Teren, A, Tham, Yc, Thiery, J, Thio, Chl, Thomsen, H, Thorleifsson, G, Toniolo, D, Tönjes, A, Tremblay, J, Tzoulaki, I, Uitterlinden, Ag, Vaccargiu, S, van Dam, Rm, van der Harst, P, van Duijn, Cm, Velez Edward, Dr, Verweij, N, Vogelezang, S, Völker, U, Vollenweider, P, Waeber, G, Waldenberger, M, Wallentin, L, Wang, Yx, Wang, C, Waterworth, Dm, Bin Wei, W, White, H, Whitfield, Jb, Wild, Sh, Wilson, Jf, Wojczynski, Mk, Wong, C, Wong, Ty, Xu, L, Yang, Q, Yasuda, M, Yerges-Armstrong, Lm, Zhang, W, Zonderman, Ab, Rotter, Ji, Bochud, M, Psaty, Bm, Vitart, V, Wilson, Jg, Dehghan, A, Parsa, A, Chasman, Di, Ho, K, Morris, Ap, Devuyst, O, Akilesh, S, Pendergrass, Sa, Sim, X, Böger, Ca, Okada, Y, Edwards, Tl, Snieder, H, Stefansson, K, Hung, Am, Heid, Im, Scholz, M, Teumer, A, Köttgen, A, and Pattaro, C.

Subjects
catalog, Inheritance Patterns, Hasso-Plattner-Institut für Digital Engineering GmbH, Genome-wide association study, Disease, Kidney Function Tests, Bioinformatics, DISEASE, 0302 clinical medicine, Uromodulin/urine, kidney function, 11 Medical and Health Sciences, Genetics & Heredity, ddc:616, 0303 health sciences, Kidney, Genome-wide association, HERITABILITY, GENOME-WIDE ASSOCIATION, COMMON VARIANTS, RENAL-FUNCTION, TRANS-EQTLS, METAANALYSIS, TRANSPORTER, CLASSIFICATION, INTEGRATION, Chromosome Mapping, 3. Good health, Phenotype, medicine.anatomical_structure, Medical genetics, Common variants, Renal function, Trans-EQTLS, Metaanalysis, Heritability, Transporter, Life Sciences & Biomedicine, Glomerular Filtration Rate, Metaanalysi, medicine.medical_specialty, Genotype, European Continental Ancestry Group, Quantitative Trait Loci, Common variant, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Article, White People, V. A. Million Veteran Program, 03 medical and health sciences, Quantitative Trait, Heritable, Lifelines Cohort Study, Uromodulin, Genetics, medicine, Humans, Genetic Predisposition to Disease, Renal Insufficiency, Chronic, Genetic Association Studies, 030304 developmental biology, Genetic association, Science & Technology, urogenital system, association, genetic loci, 06 Biological Sciences, medicine.disease, Renal Insufficiency, Chronic/genetics/physiopathology/urine, Genetic Association Studies/methods, ddc:000, 030217 neurology & neurosurgery, Developmental Biology, Genome-Wide Association Study, Kidney disease
Abstract

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.

Published
2019

54. Analysis of the Influence of microRNAs in Lithium Response in Bipolar Disorder

Author

Céline S. Reinbold, Andreas J. Forstner, Julian Hecker, Janice M. Fullerton, Per Hoffmann, Liping Hou, Urs Heilbronner, Franziska Degenhardt, Mazda Adli, Kazufumi Akiyama, Nirmala Akula, Raffaella Ardau, Bárbara Arias, Lena Backlund, Antonio Benabarre, Susanne Bengesser, Abesh K. Bhattacharjee, Joanna M. Biernacka, Armin Birner, Cynthia Marie-Claire, Pablo Cervantes, Guo-Bo Chen, Hsi-Chung Chen, Caterina Chillotti, Scott R. Clark, Francesc Colom, David A. Cousins, Cristiana Cruceanu, Piotr M. Czerski, Alexandre Dayer, Bruno Étain, Peter Falkai, Louise Frisén, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Paul Grof, Oliver Gruber, Ryota Hashimoto, Joanna Hauser, Stefan Herms, Stéphane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Nina Lackner, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Carlos A. López Jaramillo, Glenda MacQueen, Mirko Manchia, Lina Martinsson, Manuel Mattheisen, Michael J. McCarthy, Susan L. McElroy, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Urban Ösby, Norio Ozaki, Roy H. Perlis, Andrea Pfennig, Daniela Reich-Erkelenz, Guy A. Rouleau, Peter R. Schofield, K. Oliver Schubert, Barbara W. Schweizer, Florian Seemüller, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Kazutaka Shimoda, Christian Simhandl, Claire M. Slaney, Jordan W. Smoller, Alessio Squassina, Thomas J. Stamm, Pavla Stopkova, Sarah K. Tighe, Alfonso Tortorella, Gustavo Turecki, Julia Volkert, Stephanie H. Witt, Adam J. Wright, L. Trevor Young, Peter P. Zandi, James B. Potash, J. Raymond DePaulo, Michael Bauer, Eva Reininghaus, Tomáš Novák, Jean-Michel Aubry, Mario Maj, Bernhard T. Baune, Philip B. Mitchell, Eduard Vieta, Mark A. Frye, Janusz K. Rybakowski, Po-Hsiu Kuo, Tadafumi Kato, Maria Grigoroiu-Serbanescu, Andreas Reif, Maria Del Zompo, Frank Bellivier, Martin Schalling, Naomi R. Wray, John R. Kelsoe, Martin Alda, Francis J. McMahon, Thomas G. Schulze, Marcella Rietschel, Markus M. Nöthen, Sven Cichon, University Hospital Basel [Basel], Universitätsklinikum Bonn (UKB), Neuroscience Research Australia (NeuRA), Translational Centre for Regenerative Medicine (TRM), Department of Cell Therapy, Universität Leipzig [Leipzig]-Universität Leipzig [Leipzig], Human Genetics Branch, National Institutes of Health [Bethesda] (NIH)-National Institute of Mental Health (NIMH), Department of Psychiatry and Psychotherapy, Georg-August-University [Göttingen], Department of Genomics, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Unit of Clinical Pharmacology, University-Hospital of Cagliari, Department of Psychiatry, Trinity College Dublin-St. James's Hospital, Mayo Clinic, University of Adelaide, McGill University = Université McGill [Montréal, Canada], Psychiatric Genetic Unit, Poznan University of Medical Sciences, Variabilité de réponse aux Psychotropes (VariaPsy - U1144), Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Sorbonne Paris Cité (USPC), Université Paris Diderot - Paris 7 (UPD7), Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), University of Homburg, Department of Molecular Medicine, Karolinska Institutet [Stockholm], Service de psychiatrie adulte, Université Bordeaux Segalen - Bordeaux 2-Hôpital Charles Perrens, Dalhousie University [Halifax], Johns Hopkins University (JHU), Mood Disorders Center of Ottawa (MDCO), University of Ottawa [Ottawa], Department of Psychiatry [Heidelberg], University of Heidelberg, Medical Faculty, Molecular Research Center for Children’s Mental Development, United Graduate School of Child Development, Osaka University [Osaka], 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), IrsiCaixa (Institut de Recerca de la Sida), Service de Psychiatrie et Psychologie Clinique, Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Hôpital Jeanne-d'Arc, Mental Health Sciences Unit, University College of London [London] (UCL), Department of Adult Psychiatry, Abteilung Informatik und angewandte Kognitionswissenschaft [Duisburg] (INKO), Universität Duisburg-Essen [Essen], Hokkaido University Graduate School of Medicine, Department of medicine [Stockholm], Karolinska Institutet [Stockholm]-Karolinska University Hospital [Stockholm], Molecular Medicine and Surgery department, University of California [San Diego] (UC San Diego), University of California-University of California, University of Antioquia, Università degli Studi di Salerno (UNISA), Department of Clinical Neuroscience, R&D Unit, Department of Psychiatry, Danderyd University Hospital–Karolinska Institutet, Fujita Health University School of Medicine, Center for Human Genetic Research, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Technische Universität Dresden = Dresden University of Technology (TU Dresden), Prince of Wales Medical Research Institute, University of New South Wales [Sydney] (UNSW), Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Massachusetts General Hospital [Boston], Prague Psychiatric Center, University of Prague, Università degli Studi di Perugia (UNIPG), Department of Psychiatry [Montréal], School of Psychiatry, Black Dog Institute-University of New South Wales [Sydney] (UNSW), Department of Mental Health, Johns Hopkins University and Hospital, Center for Sepsis Control & Care, Jena University Hospital, Medical University Graz, Department of Mental Health and Psychiatry, University Hospital of Geneva, Università degli studi della Campania 'Luigi Vanvitelli', Institute of Neuroscience, Hospital Clinic-IDIBAPS - CIBERSAM - ENBREC-University of Barcelona, Institute of Epidemiology and Preventive Medicine, National Taiwan University [Taiwan] (NTU), Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science [Wako] (RIKEN CBS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN)-RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Biometric Psychiatric Genetics Research Unit, Alexandru Obregia Psychiatric Hospital, Service de psychiatrie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Hôpital Albert Chenevier, King‘s College London, Univerity of Mannheim, Institute of Human Genetics [Erlangen, Allemagne], Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, McGill University, Optimisation Thérapeutique en Neuropsychopharmacologie (VariaPsy - U1144), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Diderot - Paris 7 (UPD7), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP), University of Ottawa [Ottawa] (uOttawa), Technische Universität Dresden (TUD), University of New South Wales [Sydney] (UNSW)-Black Dog Institute, RIKEN Brain Science Institute, Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpital Henri Mondor-Hôpital Albert Chenevier, Friedrich Alexander University [Erlangen-Nürnberg], Universitat de Barcelona, Georg-August-University = Georg-August-Universität Göttingen, University of California (UC)-University of California (UC), Università degli Studi di Salerno = University of Salerno (UNISA), Danderyds sjukhus = Danderyd University Hospital, Università degli Studi di Perugia = University of Perugia (UNIPG), Università degli studi della Campania 'Luigi Vanvitelli' = University of the Study of Campania Luigi Vanvitelli, Reinbold, Céline S., Forstner, Andreas J., Hecker, Julian, Fullerton, Janice M., Hoffmann, Per, Hou, Liping, Heilbronner, Ur, Degenhardt, Franziska, Adli, Mazda, Akiyama, Kazufumi, Akula, Nirmala, Ardau, Raffaella, Arias, Bárbara, Backlund, Lena, Benabarre, Antonio, Bengesser, Susanne, Bhattacharjee, Abesh K., Biernacka, Joanna M., Birner, Armin, Marie-Claire, Cynthia, Cervantes, Pablo, Chen, Guo-Bo, Chen, Hsi-Chung, Chillotti, Caterina, Clark, Scott R., Colom, Francesc, Cousins, David A., Cruceanu, Cristiana, Czerski, Piotr M., Dayer, Alexandre, Étain, Bruno, Falkai, Peter, Frisén, Louise, Gard, Sébastien, Garnham, Julie S., Goes, Fernando S., Grof, Paul, Gruber, Oliver, Hashimoto, Ryota, Hauser, Joanna, Herms, Stefan, Jamain, Stéphane, Jiménez, Esther, Kahn, Jean-Pierre, Kassem, Layla, Kittel-Schneider, Sarah, Kliwicki, Sebastian, König, Barbara, Kusumi, Ichiro, Lackner, Nina, Laje, Gonzalo, Landén, Mikael, Lavebratt, Catharina, Leboyer, Marion, Leckband, Susan G., Jaramillo, Carlos A. López, Macqueen, Glenda, Manchia, Mirko, Martinsson, Lina, Mattheisen, Manuel, Mccarthy, Michael J., Mcelroy, Susan L., Mitjans, Marina, Mondimore, Francis M., Monteleone, Palmiero, Nievergelt, Caroline M., Ösby, Urban, Ozaki, Norio, Perlis, Roy H., Pfennig, Andrea, Reich-Erkelenz, Daniela, Rouleau, Guy A., Schofield, Peter R., Schubert, K. Oliver, Schweizer, Barbara W., Seemüller, Florian, Severino, Giovanni, Shekhtman, Tatyana, Shilling, Paul D., Shimoda, Kazutaka, Simhandl, Christian, Slaney, Claire M., Smoller, Jordan W., Squassina, Alessio, Stamm, Thomas J., Stopkova, Pavla, Tighe, Sarah K., Tortorella, Alfonso, Turecki, Gustavo, Volkert, Julia, Witt, Stephanie H., Wright, Adam J., Trevor Young, L., Zandi, Peter P., Potash, James B., Depaulo, J. Raymond, Bauer, Michael, Reininghaus, Eva, Novák, Tomáš, Aubry, Jean-Michel, Maj, Mario, Baune, Bernhard T., Mitchell, Philip B., Vieta, Eduard, Frye, Mark A., Rybakowski, Janusz K., Kuo, Po-Hsiu, Kato, Tadafumi, Grigoroiu-Serbanescu, Maria, Reif, Andrea, Zompo, Maria Del, Bellivier, Frank, Schalling, Martin, Wray, Naomi R., Kelsoe, John R., Alda, Martin, Mcmahon, Francis J., Schulze, Thomas G., Rietschel, Marcella, Nöthen, Markus M., and Cichon, Sven

Subjects
0301 basic medicine, Genome-wide association study, Lithium (medication), lcsh:RC435-571, Bipolar disorder, Common variants, Lithium response, MicroRNA, Psychiatry and Mental Health, Common variant, Lithium, Biology, ddc:616.89, 03 medical and health sciences, lcsh:Psychiatry, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], common variants, medicine, Manic-depressive illness, ddc:610, Gene, ComputingMilieux_MISCELLANEOUS, Trastorno Bipolar, Original Research, Psychiatry, bipolar disorder, Genetics, MicroARNs, Trastorn bipolar, genome-wide association study, microRNA, medicine.disease, genome-wide association stud, Liti, Phenotype, 3. Good health, MicroRNAs, Psychiatry and Mental health, 030104 developmental biology, Schizophrenia, Multiple comparisons problem, Litio, medicine.symptom, Mania, lithium response, medicine.drug
Abstract

Bipolar disorder (BD) is a common, highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. Lithium is the best-established long-term treatment for BD, even though individual response is highly variable. Evidence suggests that some of this variability has a genetic basis. This is supported by the largest genome-wide association study (GWAS) of lithium response to date conducted by the International Consortium on Lithium Genetics (ConLiGen). Recently, we performed the first genome-wide analysis of the involvement of miRNAs in BD and identified nine BD-associated miRNAs. However, it is unknown whether these miRNAs are also associated with lithium response in BD. In the present study, we therefore tested whether common variants at these nine candidate miRNAs contribute to the variance in lithium response in BD. Furthermore, we systematically analyzed whether any other miRNA in the genome is implicated in the response to lithium. For this purpose, we performed gene-based tests for all known miRNA coding genes in the ConLiGenGWAS dataset (n = 2,563 patients) using a set-based testing approach adapted from the versatile gene-based test for GWAS (VEGAS2). In the candidate approach, miR-499a showed a nominally significant association with lithium response, providing some evidence for involvement in both development and treatment of BD. In the genomewide miRNA analysis, 71 miRNAs showed nominally significant associations with the dichotomous phenotype and 106 with the continuous trait for treatment response. A total of 15 miRNAs revealed nominal significance in both phenotypes with miR-633 showing the strongest association with the continuous trait (p = 9.80E-04) and miR-607 with the dichotomous phenotype (p = 5.79E-04). No association between miRNAs and treatment response to lithium in BD in either of the tested conditions withstood multiple testing correction. Given the limited power of our study, the investigation of miRNAs in larger GWAS samples of BD and lithium response is warranted. COL0029147

Published
2018

55. Effect of FTO rs9939609 variant on insulin resistance in obese female adolescents

Author

Madarina Julia, Kristy Iskandar, Rina Susilowati, Emy Huriyati, Suryono Yudha Patria, and Harry Freitag Luglio

Subjects
0301 basic medicine, Pediatric Obesity, medicine.medical_specialty, Waist, Adolescent, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, lcsh:Medicine, Common variant, General Biochemistry, Genetics and Molecular Biology, Fasting insulin, 03 medical and health sciences, Insulin resistance, Internal medicine, Genotype, medicine, Humans, Allele, Child, lcsh:Science (General), lcsh:QH301-705.5, Polymorphism, Genetic, Obese female adolescents, business.industry, lcsh:R, nutritional and metabolic diseases, General Medicine, rs9939609, medicine.disease, Research Note, 030104 developmental biology, Endocrinology, lcsh:Biology (General), Multicenter study, Indonesia, Homeostatic model assessment, Female, FTO, business, Body mass index, lcsh:Q1-390
Abstract

Objectives FTO rs9939609 variant has been shown to be associated with insulin resistance in Caucasian children. However, studies in Asia show inconsistent findings. We investigated the association between FTO rs9939609 polymorphisms and insulin resistance in obese female adolescents in Indonesia, a genetically distinct group within Asia. Results A total of 78 obese female adolescents participated in this study. The risk allele (A) frequency of FTO rs9939609 variant in Indonesian obese female adolescence was 44.2%. The frequency of insulin resistance was higher in the subjects with AA (54.6%) or AT (59.6%) than the subject with TT genotype (50%), but did not statistically different (p = 0.81 and p = 0.47, respectively). The insulin resistance rate was also higher in the risk allele (A) than the non-risk allele (T) subjects (0.58 vs. 0.55), but did not statistically different (p = 0.75). There was no association between FTO rs9939609 variant and body mass index, fasting glucose level, fasting insulin level, homeostatic model assessment of insulin resistance, and waist circumference (p > 0.05). In conclusion, FTO rs9939609 variant may not be associated with insulin resistance in Indonesian obese female adolescents. A multicenter study with a larger sample size is needed to clarify these findings.

Published
2018

56. Common variants of chemokine receptor gene CXCR3 and its ligands CXCL10 and CXCL11 associated with vascular permeability of dengue infection in peninsular Malaysia

Author

Zaid Masliza, M.Z. Zaiharina, AbuBakar Sazaly, Boon Peng Hoh, K. C. Lee Christopher, S. Rafidah-Hanim, Z. Zuraihan, L.H. Sim Benedict, H. Umi-Shakina, N.Y. Nik Khairudin, and Mustafa Mahiran

Subjects
Adult, Male, Candidate gene, Receptors, CXCR3, Immunology, Gene Expression, Common variant, Biology, CXCR3, Ligands, Severity of Illness Index, Article, Dengue fever, Pathogenesis, Dengue, Capillary Permeability, Gene Frequency, parasitic diseases, medicine, Immunology and Allergy, CXCL10, Humans, CXCL11, Genetic Predisposition to Disease, Vascular permeability, Alleles, Genetic association, Haplotype, Malaysia, General Medicine, Dengue Virus, medicine.disease, Virology, Chemokine CXCL11, Chemokine CXCL10, Haplotypes, Case-Control Studies, Female
Abstract

Dengue causes significantly more human disease than any other arboviruses. It causes a spectrum of illness, ranging from mild self-limited fever, to severe and fatal dengue hemorrhagic fever, as evidenced by vascular leakage and multifactorial hemostatic abnormalities. There is no specific treatment available till date. Evidence shows that chemokines CXCL10, CXCL11 and their receptor CXCR3 are involved in severity of dengue, but their genetic association with the susceptibility of vascular leakage during dengue infection has not been reported. We genotyped 14 common variants of these candidate genes in 176 patients infected with dengue. rs4859584 and rs8878 (CXCL10) were significantly associated with vascular permeability of dengue infection (P

Published
2015

57. Targeted resequencing showing novel common and rare genetic variants increases the risk of asthma in the Chinese Han population.

Author

Liu J, Deng Y, Yu B, Mo B, Luo L, Yang J, Zhang X, Wang Z, Wang Y, Zhu J, Yang H, Fang S, Cheng Z, Li J, Shu Y, Luo G, Xiong W, Wei J, and Li Z

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Asthma epidemiology, Biomarkers analysis, Case-Control Studies, Child, Child, Preschool, China epidemiology, Cohort Studies, Female, Follow-Up Studies, Genome-Wide Association Study, Humans, Infant, Infant, Newborn, Male, Middle Aged, Prognosis, Young Adult, Asthma genetics, Asthma pathology, Biomarkers metabolism, Genetic Predisposition to Disease, High-Throughput Nucleotide Sequencing methods, Polymorphism, Single Nucleotide
Abstract

Background: Although studies have identified hundreds of genetic variants associated with asthma risk, a large fraction of heritability remains unexplained, especially in Chinese individuals., Methods: To identify genetic risk factors for asthma in a Han Chinese population, 211 asthma-related genes were first selected based on database searches. The genes were then sequenced for subjects in a Discovery Cohort (284 asthma patients and 205 older healthy controls) using targeted next-generation sequencing. Bioinformatics analysis and statistical association analyses were performed to reveal the associations between rare/common variants and asthma, respectively. The identified common risk variants underwent a validation analysis using a Replication Cohort (664 patients and 650 controls)., Results: First, we identified 18 potentially functional rare loss-of-function (LOF) variants in 21/284 (7.4%) of the asthma cases. Second, using burden tests, we found that the asthma group had nominally significant (p < 0.05) burdens of rare nonsynonymous variants in 10 genes. Third, 23 common single-nucleotide polymorphisms were associated with the risk of asthma, 7/23 (30.4%) and 9/23 (39.1%) of which were modestly significant (p < 9.1 × 10 -4 ) in the Replication Cohort and Combined Cohort, respectively. According to our cumulative risk model involving the modestly associated alleles, middle- and high-risk subjects had a 2.0-fold (95% CI: 1.621-2.423, p = 2.624 × 10 -11 ) and 6.0-fold (95% CI: 3.623-10.156, p = 7.086 × 10 -12 ) increased risk of asthma, respectively, compared with low-risk subjects., Conclusion: This study revealed novel rare and common genetic risk factors for asthma, and provided a cumulative risk model for asthma risk prediction and stratification in Han Chinese individuals., (© 2021 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC.)

Published
2021
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58. A Common Variant in the MC1R Gene (p.V92M) is associated with Alzheimer's Disease Risk

Author

Estel Plana, Daniel Alcolea, Rubén Fernández-Santiago, Miriam Potrony, Anna Antonell, Gemma Tell-Marti, Raquel Sánchez-Valle, Celia Badenas, Joan Anton Puig-Butille, Albert Lladó, Jordi Clarimón, José Luis Molinuevo, Alberto Lleó, Susana Puig, Juan Fortea, and Universitat de Barcelona

Subjects
Male, 0301 basic medicine, Apolipoprotein E, Apolipoprotein E4, Disease, 03 medical and health sciences, 0302 clinical medicine, Human genetics, Alzheimer Disease, Cerebrospinal fluid biomarkers, Genotype, Genetic variation, medicine, Humans, Genetic Predisposition to Disease, late-onset Alzheimer's disease, Age of Onset, Gene, Genetic Association Studies, Aged, risk, Genètica humana, p.V92M, business.industry, General Neuroscience, Biochemical markers, Case-control study, General Medicine, Alzheimer's disease, melanocortin 1 receptor (MC1R) gene, medicine.disease, Psychiatry and Mental health, Clinical Psychology, 030104 developmental biology, Malaltia d'Alzheimer, Case-Control Studies, common variant, Immunology, Marcadors bioquímics, Female, Geriatrics and Gerontology, Age of onset, business, Receptor, Melanocortin, Type 1, Biomarkers, 030217 neurology & neurosurgery
Abstract

Despite the recent identification of some novel risk genes for Alzheimer's disease (AD), the genetic etiology of late-onset Alzheimer's disease (LOAD) remains largely unknown. The inclusion of these novel risk genes to the risk attributable to the APOE gene accounts for roughly half of the total genetic variance in LOAD. The evidence indicates that undiscovered genetic factors may contribute to AD susceptibility. In the present study, we sequenced the MC1R gene in 525 Spanish LOAD patients and in 160 controls. We observed that a common MC1R variant p.V92M (rs2228479), not related to pigmentation traits, was present in 72 (14%) patients and 15 (9%) controls and confers increased risk of developing LOAD (OR: 1.99, 95% CI: 1.08-3.64, p = 0.026), especially in those patients whose genetic risk could not be explained by APOE genotype. This association remains and even increased in the subset of 69 patients with typical AD cerebrospinal fluid profile (OR: 3.40 95% CI: 1.40-8.27, p = 0.007). We did not find an association between p. V92M and age of onset of AD. Further studies are necessary to elucidate the role of MC1R in brain cells through the different MC1R pathways.

Published
2017

59. FTO genotype and weight loss: a systematic review and meta-analysis of 9,563 individual participant data from eight randomized controlled trials

Author

Paul W. Franks, Jeanne M. McCaffery, Amelia Marti, Jose Lara, Kathleen A. Jablonski, Tiina Jääskeläinen, Arne Astrup, Lu Qi, Frank M. Sacks, Katherine M. Livingstone, Jaana Lindström, Mathilde Svendstrup, Torben Hansen, George A. Bray, Thorkild I. A. Sørensen, Yoriko Heianza, Bahar Erar, Wim H. M. Saris, Matti Uusitupa, Jose C. Florez, Tuomo Rankinen, John C. Mathers, J. Alfredo Martínez, Jaakko Tuomilehto, George D. Papandonatos, Tao Huang, Oluf Pedersen, Xuemei Sui, Miguel Ángel Martínez-González, Cristina Razquin, Timothy S. Church, Carlos Celis-Morales, RS: NUTRIM - HB/BW section A, RS: NUTRIM - R1 - Metabolic Syndrome, Humane Biologie, Medicum, Pregnancy and Genes, and Department of Medical and Clinical Genetics

Subjects
0301 basic medicine, DIABETES PREVENTION PROGRAM, Weight loss, Overweight, B400, Corrections, law.invention, 0302 clinical medicine, Randomized controlled trial, law, Genotype, 030212 general & internal medicine, Adiposity, Randomized Controlled Trials as Topic, 2. Zero hunger, ASSOCIATION, General Medicine, 3. Good health, Meta-analysis, medicine.symptom, medicine.medical_specialty, Waist, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, GENETIC PREDISPOSITION, Randomised controlled trials, 030209 endocrinology & metabolism, Ciencias de la Salud::Nutrición y dietética [Materias Investigacion], 03 medical and health sciences, Ciencias de la Salud::Medicina preventiva [Materias Investigacion], Internal medicine, Weight Loss, medicine, EUROPEAN ADULTS, Humans, Genetic Predisposition to Disease, Obesity, POLYMORPHISMS, Alleles, 030109 nutrition & dietetics, business.industry, Research, Individual participant data, nutritional and metabolic diseases, medicine.disease, COMMON VARIANT, BODY-MASS INDEX, Minor allele frequency, B900, MAINTENANCE, 3111 Biomedicine, FAT-MASS, business, Body mass index, FTO genotype
Abstract

Objective To assess the effect of the FTO genotype on weight loss after dietary, physical activity, or drug based interventions in randomised controlled trials. Design Systematic review and random effects meta-analysis of individual participant data from randomised controlled trials. Data sources Ovid Medline, Scopus, Embase, and Cochrane from inception to November 2015. Eligibility criteria for study selection Randomised controlled trials in overweight or obese adults reporting reduction in body mass index, body weight, or waist circumference by FTO genotype (rs9939609 or a proxy) after dietary, physical activity, or drug based interventions. Gene by treatment interaction models were fitted to individual participant data from all studies included in this review, using allele dose coding for genetic effects and a common set of covariates. Study level interactions were combined using random effect models. Metaregression and subgroup analysis were used to assess sources of study heterogeneity. Results We identified eight eligible randomised controlled trials for the systematic review and meta-analysis (n=9563). Overall, differential changes in body mass index, body weight, and waist circumference in response to weight loss intervention were not significantly different between FTO genotypes. Sensitivity analyses indicated that differential changes in body mass index, body weight, and waist circumference by FTO genotype did not differ by intervention type, intervention length, ethnicity, sample size, sex, and baseline body mass index and age category. Conclusions We have observed that carriage of the FTO minor allele was not associated with differential change in adiposity after weight loss interventions. These findings show that individuals carrying the minor allele respond equally well to dietary, physical activity, or drug based weight loss interventions and thus genetic predisposition to obesity associated with the FTO minor allele can be at least partly counteracted through such interventions. Systematic review registration PROSPERO CRD42015015969.

Published
2016

60. Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21

Author

Anne Tjønneland, Jason W. Hoskins, Kala Visvanathan, Yogesh K. Vashist, Dimitrios Trichopoulos, Matthew H. Kulke, Ruth C. Travis, Charles S. Fuchs, Herbert Yu, Kai Yu, Phyllis J. Goodman, Michael Goggins, Jean Wactawski-Wende, Laurie Burdette, Joanne W. Elena, Andrea Mambrini, Petra H.M. Peeters, H. Bas Bueno-de-Mesquita, Maria Teresa Landi, Ulrike Peters, Mingfeng Zhang, Laurence N. Kolonel, Hermann Brenner, Elżbieta Iskierka-Jażdżewska, Robert C. Kurtz, Stephen J. Chanock, Marie-Christine Boutron-Ruault, Ann L. Oberg, Elio Riboli, Maarten F. Bijlsma, Eric J. Jacobs, Manolis Kogevinas, Evelina Mocci, Steven Gallinger, Jinping Jia, Mark P. Purdue, Raffaele Pezzilli, Harvey A. Risch, Demetrius Albanes, Irene Collins, Maria Gazouli, Michelle Cotterchio, Oliver Strobel, Erica J. Childs, Charles C. Chung, Geoffrey S. Tobias, J. Ramón Quirós, Núria Malats, Robert N. Hoover, Pavel Vodicka, Brian M. Wolpin, Ugo Boggi, Patricia Hartge, Gloria M. Petersen, Peter Kraft, Christopher Hautman, Gary E. Goodman, Manal Hassan, Donghui Li, Howard D. Sesso, Malin Sund, Julie E. Buring, Loic Le Marchand, Wei Zheng, Xiao-Ou Shu, Ewa Małecka-Panas, Pavel Soucek, Salvatore Panico, Nicolas Wentzensen, Graham G. Giles, Alpa V. Patel, Daniele Campa, Myron D. Gross, Ghislaine Scelo, J. Michael Gaziano, Juozas Kupcinskas, Debra T. Silverman, Laufey T. Amundadottir, Rachael S. Stolzenberg-Solomon, Neil E. Caporaso, Mazda Jenab, Sara H. Olson, Stefano Landi, Giulia Martina Cavestro, Aruna Kamineni, Laura Beane-Freeman, Roger L. Milne, Rachel E. Neale, Aldo Scarpa, Kathy J. Helzlsouer, Miquel Porta, Emily White, Eric J. Duell, Paige M. Bracci, Nan Hu, Federico Canzian, Eric A. Klein, Gabriele Capurso, Anne Zeleniuch-Jacquotte, Eithne Costello, David J. Hunter, Rudolf Kaaks, Sonja I. Berndt, Kay-Tee Khaw, Nathaniel Rothman, Christian C. Abnet, Francesca Tavano, Christopher A. Haiman, Zhaoming Wang, Ofure Obazee, Alan A. Arslan, Edward Giovannucci, Alison P. Klein, Daniela Basso, Charles Kooperberg, Philip R. Taylor, Satu Männistö, Timothy J. Key, Mark D. Thornquist, Gabriella Andreotti, Lauren K. Brais, Gisella Figlioli, Vittorio Krogh, University Medical Center Utrecht, Imperial College Trust, Cancer Research UK, Medical Research Council UK (MRC), National Institute for Health Research (NIHR), Cancer Research UK (Reino Unido), Medical Research Council (Reino Unido), National Institute for Health Research (Reino Unido), Zhang, Mingfeng, Wang, Zhaoming, Obazee, Ofure, Jia, Jinping, Childs, Erica J, Hoskins, Jason, Figlioli, Gisella, Mocci, Evelina, Collins, Irene, Chung, Charles C, Hautman, Christopher, Arslan, Alan A, Beane Freeman, Laura, Bracci, Paige M, Buring, Julie, Duell, Eric J, Gallinger, Steven, Giles, Graham G, Goodman, Gary E, Goodman, Phyllis J, Kamineni, Aruna, Kolonel, Laurence N, Kulke, Matthew H, Malats, Núria, Olson, Sara H, Sesso, Howard D, Visvanathan, Kala, White, Emily, Zheng, Wei, Abnet, Christian C, Albanes, Demetriu, Andreotti, Gabriella, Brais, Lauren, Bueno de Mesquita, H. Ba, Basso, Daniela, Berndt, Sonja I, Boutron Ruault, Marie Christine, Bijlsma, Maarten F, Brenner, Hermann, Burdette, Laurie, Campa, Daniele, Caporaso, Neil E, Capurso, Gabriele, Cavestro, Giulia Martina, Cotterchio, Michelle, Costello, Eithne, Elena, Joanne, Boggi, Ugo, Gaziano, J. Michael, Gazouli, Maria, Giovannucci, Edward L, Goggins, Michael, Gross, Myron, Haiman, Christopher A, Hassan, Manal, Helzlsouer, Kathy J, Hu, Nan, Hunter, David J, Iskierka Jazdzewska, Elzbieta, Jenab, Mazda, Kaaks, Rudolf, Key, Timothy J, Khaw, Kay Tee, Klein, Eric A, Kogevinas, Manoli, Krogh, Vittorio, Kupcinskas, Juoza, Kurtz, Robert C, Landi, Maria T, Landi, Stefano, Le Marchand, Loic, Mambrini, Andrea, Mannisto, Satu, Milne, Roger L, Neale, Rachel E, Oberg, Ann L, Panico, Salvatore, Patel, Alpa V, Peeters, Petra H. M, Peters, Ulrike, Pezzilli, Raffaele, Porta, Miquel, Purdue, Mark, Quiros, J. Ramón, Riboli, Elio, Rothman, Nathaniel, Scarpa, Aldo, Scelo, Ghislaine, Shu, Xiao Ou, Silverman, Debra T, Soucek, Pavel, Strobel, Oliver, Sund, Malin, Małecka Panas, Ewa, Taylor, Philip R, Tavano, Francesca, Travis, Ruth C, Thornquist, Mark, Tjønneland, Anne, Tobias, Geoffrey S, Trichopoulos, Dimitrio, Vashist, Yogesh, Vodicka, Pavel, Wactawski Wende, Jean, Wentzensen, Nicola, Yu, Herbert, Yu, Kai, Zeleniuch Jacquotte, Anne, Kooperberg, Charle, Risch, Harvey A, Jacobs, Eric J, Li, Donghui, Fuchs, Charle, Hoover, Robert, Hartge, Patricia, Chanock, Stephen J, Petersen, Gloria M, Stolzenberg Solomon, Rachael S, Wolpin, Brian M, Kraft, Peter, Klein, Alison P, Canzian, Federico, Amundadottir, Laufey T., Khaw, Kay-Tee [0000-0002-8802-2903], Apollo - University of Cambridge Repository, CCA -Cancer Center Amsterdam, Center of Experimental and Molecular Medicine, Radiotherapy, Zhang, M, Wang, Z, Obazee, O, Jia, J, Childs, Ej, Hoskins, J, Figlioli, G, Mocci, E, Collins, I, Chung, Cc, Hautman, C, Arslan, Aa, Beane Freeman, L, Bracci, Pm, Buring, J, Duell, Ej, Gallinger, S, Giles, Gg, Goodman, Ge, Goodman, Pj, Kamineni, A, Kolonel, Ln, Kulke, Mh, Malats, N, Olson, Sh, Sesso, Hd, Visvanathan, K, White, E, Zheng, W, Abnet, Cc, Albanes, D, Andreotti, G, Brais, L, Bueno de Mesquita, Hb, Basso, D, Berndt, Si, Boutron Ruault, Mc, Bijlsma, Mf, Brenner, H, Burdette, L, Campa, D, Caporaso, Ne, Capurso, G, Cavestro, GIULIA MARTINA, Cotterchio, M, Costello, E, Elena, J, Boggi, U, Gaziano, Jm, Gazouli, M, Giovannucci, El, Goggins, M, Gross, M, Haiman, Ca, Hassan, M, Helzlsouer, Kj, Hu, N, Hunter, Dj, Iskierka Jazdzewska, E, Jenab, M, Kaaks, R, Key, Tj, Khaw, Kt, Klein, Ea, Kogevinas, M, Krogh, V, Kupcinskas, J, Kurtz, Rc, Landi, Mt, Landi, S, Le Marchand, L, Mambrini, A, Mannisto, S, Milne, Rl, Neale, Re, Oberg, Al, Panico, S, Patel, Av, Peeters, Ph, Peters, U, Pezzilli, R, Porta, M, Purdue, M, Quiros, Jr, Riboli, E, Rothman, N, Scarpa, A, Scelo, G, Shu, Xo, Silverman, Dt, Soucek, P, Strobel, O, Sund, M, Małecka Panas, E, Taylor, Pr, Tavano, F, Travis, Rc, Thornquist, M, Tjønneland, A, Tobias, G, Trichopoulos, D, Vashist, Y, Vodicka, P, Wactawski Wende, J, Wentzensen, N, Yu, H, Yu, K, Zeleniuch Jacquotte, A, Kooperberg, C, Risch, Ha, Jacobs, Ej, Li, D, Fuchs, C, Hoover, R, Hartge, P, Chanock, Sj, Petersen, Gm, Stolzenberg Solomon, R, Wolpin, Bm, Kraft, P, Klein, Ap, Canzian, F, and Amundadottir, L. T.

Subjects
0301 basic medicine, Candidate gene, Pancreatic disease, GENETIC SUSCEPTIBILITY, pancreatic cancer, Datasets as Topic, Genome-wide association study, imputation, TRET, 0302 clinical medicine, Fine-mapping, GWAS, Imputation, NR5A2, Pancreatic cancer, Oncology, Genotype, Genetics, 3. Good health, fine-mapping, Chromosomes, Human, Pair 1, 030220 oncology & carcinogenesis, Chromosomes, Human, Pair 5, Chromosomes, Human, Pair 8, 616.37-006.6 [udc], BLADDER-CANCER, Single-nucleotide polymorphism, GENOTYPE IMPUTATION, BREAST, Polymorphism, Single Nucleotide, 03 medical and health sciences, Journal Article, medicine, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Pàncrees -- Càncer, Cancer och onkologi, LONG-RANGE INTERACTION, business.industry, medicine.disease, Pancreatic neoplasms, genetics, Polymorphism, single nucleotide, RISK LOCI, Fold change, COMMON VARIANT, Cromosomes, Pancreatic Neoplasms, 030104 developmental biology, Cancer and Oncology, business, Imputation (genetics), LRH-1, Priority Research Paper, Genome-Wide Association Study
Abstract

Altres ajuts: The authors acknowledge the contribution of the staff of the Cancer Genomics Research Laboratory (CGR) at the National Cancer Institute, NIH, for their help throughout the project. This work was supported by the Intramural Research Program of the US National Institutes of Health (NIH), National Cancer Institute. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Additional acknowledgements for individual participating studies are listed in the Supplemental Materials. Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88×10 −15), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22×10 −9) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70×10 −8). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 (NR5A2), chr8q24.21 (MYC) and chr5p15.33 (CLPTM1L - TERT) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal (n = 10) and tumor (n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7×10 −8). This finding was validated in a second set of paired (n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5×10 −4 -2.0×10 −3). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology.

Published
2016

61. Predictive Value of Morphological Features in Patients with Autism versus Normal Controls

Author

Gerhard Hellemann, M. V. de Jonge, Frits A. Beemer, Heval Ozgen, and H. van Engeland

Subjects
Morphology, Male, medicine.medical_specialty, Adolescent, Autism, Predictive value, Recursive partitioning, Common variant, Audiology, Minor anomaly, Developmental psychology, Developmental and Educational Psychology, medicine, Humans, ROC, Forehead, Minor physical anomalies, Asperger Syndrome, Autistic Disorder, Child, Original Paper, medicine.disease, Endophenotype, medicine.anatomical_structure, ROC Curve, Schizophrenia, Asperger syndrome, Case-Control Studies, Child, Preschool, Face, Female, Psychology, Facial symmetry
Abstract

We investigated the predictive power of morphological features in 224 autistic patients and 224 matched-pairs controls. To assess the relationship between the morphological features and autism, we used the receiver operator curves (ROC). In addition, we used recursive partitioning (RP) to determine a specific pattern of abnormalities that is characteristic for the difference between autistic children and typically developing controls. The present findings showed that morphological features are significantly increased in patients with autism. Using ROC and RP, some of the morphological measures also led to strong predictive accuracy. Facial asymmetry, multiple hair whorls and prominent forehead significantly differentiated patients with autism from controls. Future research on multivariable risk prediction models may benefit from the use of morphological features. Electronic supplementary material The online version of this article (doi:10.1007/s10803-012-1554-4) contains supplementary material, which is available to authorized users.

Published
2012

62. Genome-wide association and functional studies identify the DOT1L gene to be involved in cartilage thickness and hip osteoarthritis

Author

Sarah Metrustry, Martha C. Castaño Betancourt, Rose A. Maciewicz, Michael Doherty, Sally Doherty, Ana M. Valdes, Deborah J. Hart, Joyce B. J. van Meurs, Frédéric Cailotto, Fernando Rivadeneira, Massimo Mangino, Hanneke J. M. Kerkhof, Albert Hofman, Nigel K Arden, Weiya Zhang, M. Wheeler, F.M. Cornelis, Frank P. Luyten, André G. Uitterlinden, Rik Lories, Marjolein J. Peters, Tim D. Spector, Kenneth Muir, Epidemiology, Internal Medicine, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), and University of Nottingham, UK (UON)

Subjects
joint development, Cartilage, Articular, pleiotropism, Genome-wide association study, Osteoarthritis, Biology, Osteoarthritis, Hip, Cell Line, 03 medical and health sciences, Mice, 0302 clinical medicine, Chondrocytes, Risk Factors, Pleiotropism, medicine, Animals, Humans, Hepatocyte Nuclear Factor 1-alpha, synovial joint, Wnt Signaling Pathway, 030304 developmental biology, 030203 arthritis & rheumatology, Genetics, 0303 health sciences, Multidisciplinary, Cartilage homeostasis, Cartilage, complex disease, Wnt signaling pathway, Age Factors, Genetic Variation, DOT1L, Histone-Lysine N-Methyltransferase, Methyltransferases, Biological Sciences, medicine.disease, Chondrogenesis, medicine.anatomical_structure, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, [SDV.MHEP.RSOA]Life Sciences [q-bio]/Human health and pathology/Rhumatology and musculoskeletal system, common variant, Cancer research, Genome-Wide Association Study
Abstract

Hip osteoarthritis (HOA) is one of the most disabling and common joint disorders with a large genetic component that is, however, still ill-defined. To date, genome-wide association studies (GWAS) in osteoarthritis (OA) and specifically in HOA have yielded only few loci, which is partly explained by heterogeneity in the OA definition. Therefore, we here focused on radiographically measured joint-space width (JSW), a proxy for cartilage thickness and an important underlying intermediate trait for HOA. In a GWAS of 6,523 individuals on hip-JSW, we identified the G allele of rs12982744 on chromosome 19p13.3 to be associated with a 5% larger JSW ( P = 4.8 × 10 −10 ). The association was replicated in 4,442 individuals from three United Kingdom cohorts with an overall meta-analysis P value of 1.1 × 10 −11 . The SNP was also strongly associated with a 12% reduced risk for HOA ( P = 1 × 10 −4 ). The SNP is located in the DOT1L gene, which is an evolutionarily conserved histone methyltransferase, recently identified as a potentially dedicated enzyme for Wnt target-gene activation in leukemia. Immunohistochemical staining of the DOT1L protein in mouse limbs supports a role for DOT1L in chondrogenic differentiation and adult articular cartilage. DOT1L is also expressed in OA articular chondrocytes. Silencing of Dot1l inhibited chondrogenesis in vitro. Dot1l knockdown reduces proteoglycan and collagen content, and mineralization during chondrogenesis. In the ATDC5 chondrogenesis model system, DOT1L interacts with TCF and Wnt signaling. These data are a further step to better understand the role of Wnt-signaling during chondrogenesis and cartilage homeostasis. DOT1L may represent a therapeutic target for OA.

Published
2012

63. dcVar: a method for identifying common variants that modulate differential correlation structures in gene expression data

Author

Brett A. McKinney, Caleb A. Lareau, Bill C. White, and Courtney G. Montgomery

Subjects
lcsh:QH426-470, Genome-wide association study, RNA-Seq, Biology, eQTL, Correlation, 03 medical and health sciences, Genotype, Methods, Genetics, Genetics (clinical), 030304 developmental biology, 0303 health sciences, genome-wide association study, 030305 genetics & heredity, Phenotype, 3. Good health, lcsh:Genetics, molecular phenotype, common variant, Expression quantitative trait loci, microarray gene expression, Molecular Medicine, Function (biology), Differential (mathematics)
Abstract

Recent studies have implicated the role of differential co-expression or correlation structure in gene expression data to help explain phenotypic differences. However, few attempts have been made to characterize the function of variants based on their role in regulating differential co-expression. Here, we describe a statistical methodology that identifies pairs of transcripts that display differential correlation structure conditioned on genotypes of variants that regulate co-expression. Additionally, we present a user-friendly, computationally efficient tool, dcVar, that can be applied to expression quantitative trait loci (eQTL) or RNA-Seq datasets to infer differential co-expression variants (dcVars). We apply dcVar to the HapMap3 eQTL dataset and demonstrate the utility of this methodology at uncovering novel function of variants of interest with examples from a height genome-wide association and cancer drug resistance. We provide evidence that differential correlation structure is a valuable intermediate molecular phenotype for further characterizing the function of variants identified in GWAS and related studies.

Published
2015
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64. The contribution of genetic variations in the region of the parathyroid hormone-like hormone, PTHLH, gene to breast cancer susceptibility

Abstract

Aims: • Analyse the evidence for PTHLH and PTHrP, its protein product, playing a role in breast cancer and update the empirical definition of the gene. • Describe the 3-Dimensional structure of the PTHLH region and determine its system of regulatory interactions, including remote regulatory elements affecting PTHLH. • Integrate existing tools in addition to the novel perspectives generated above to enable a comprehensive annotation and analysis of genetic variants identified through molecular epidemiological techniques including Genome-Wide Association Studies (GWAS) and somatic DNA sequencing of tumour tissue to derive putative molecular mechanisms for the region’s involvement in breast cancer susceptibility. Methodology: • Review published studies and databases, integrating findings from diverse sources. • Acquire and analyse DNA and RNA sequencing, regulatory, expression, algorithm-inferred, and proximity-ligation data from multiple public data sources including ENCODE, ROADMAP, dbGAP, COSMIC and other to update the definition of PTHLH, and advance concepts of structure and regulatory function in the region. • Acquire and analyse primary GWAS data, performing imputation with multiple algorithms and references, and annotating associated variants with a suite of tools. • Use genome browsers including UCSC, WUSTL, and Golden Helix SVS, and their associated databases and tools, to analyse and visually integrate findings. Results: • PTHrP has multiple discretely functional segments active throughout the cell. It likely plays a bivalent and context-dependent role in cancer biology. Analysis of somatic variation in cancer suggests PTHrP may have a tumourigenic role within the nucleus. • PTHLH sits within a 1.3Mb TAD featuring multiple sub-structures that are integrated with the region’s regulatory function. There are activated chromatin hubs (ACHs) at protein-coding genes with evidence of extensive interaction between them. This is facilitated by the TAD’s structure, co

Published
2016

65. FTO genotype and weight loss: systematic review and meta-analysis of 9563 individual participant data from eight randomised controlled trials

Abstract

OBJECTIVE:  To assess the effect of the FTO genotype on weight loss after dietary, physical activity, or drug based interventions in randomised controlled trials. DESIGN:  Systematic review and random effects meta-analysis of individual participant data from randomised controlled trials. DATA SOURCES:  Ovid Medline, Scopus, Embase, and Cochrane from inception to November 2015. ELIGIBILITY CRITERIA FOR STUDY SELECTION:  Randomised controlled trials in overweight or obese adults reporting reduction in body mass index, body weight, or waist circumference by FTO genotype (rs9939609 or a proxy) after dietary, physical activity, or drug based interventions. Gene by treatment interaction models were fitted to individual participant data from all studies included in this review, using allele dose coding for genetic effects and a common set of covariates. Study level interactions were combined using random effect models. Metaregression and subgroup analysis were used to assess sources of study heterogeneity. RESULTS:  We identified eight eligible randomised controlled trials for the systematic review and meta-analysis (n=9563). Overall, differential changes in body mass index, body weight, and waist circumference in response to weight loss intervention were not significantly different between FTO genotypes. Sensitivity analyses indicated that differential changes in body mass index, body weight, and waist circumference by FTO genotype did not differ by intervention type, intervention length, ethnicity, sample size, sex, and baseline body mass index and age category. CONCLUSIONS:  We have observed that carriage of the FTO minor allele was not associated with differential change in adiposity after weight loss interventions. These findings show that individuals carrying the minor allele respond equally well to dietary, physical activity, or drug based weight loss interventions and thus gen

Published
2016

66. Genome-Wide Linkage Analysis of Hemodynamic Parameters Under Mental and Physical Stress in Extended Omani Arab Pedigrees

Author

Anthony G. Comuzzie, Sulayma Albarwani, Afshin Aslani, Riad Bayoumi, Mohammed O. Hassan, Deepali Jaju, Zahir M. Al-Anqoudi, Harold Snieder, Saeed Al-Yahyaee, Juan Carlos López-Alvarenga, Behrooz Z. Alizadeh, V. Saroja Voruganti, Life Course Epidemiology (LCE), and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)

Subjects
Adult, Male, Oman, Genetic Linkage, COLD PRESSOR TEST, Quantitative Trait Loci, CARDIOVASCULAR REACTIVITY, Pedigree chart, Blood Pressure, BLOOD-PRESSURE, Quantitative trait locus, Biology, Essential hypertension, LAMIN A/C MUTATIONS, genome-wide, Young Adult, stress, Heart rate, medicine, CARDIAC REPOLARIZATION, Humans, Family, ESSENTIAL-HYPERTENSION, Genetics (clinical), Genetics, Linkage (software), Arab pedigrees, haemodynamics, medicine.diagnostic_test, FUNCTIONAL CONSEQUENCES, Genome, Human, Cold pressor test, Hemodynamics, Obstetrics and Gynecology, medicine.disease, DILATED CARDIOMYOPATHY, COMMON VARIANT, Arabs, Pedigree, Impedance cardiography, Blood pressure, Phenotype, Pediatrics, Perinatology and Child Health, Female, Lod Score, linkage, Stress, Psychological, RESPONSES
Abstract

Background:We performed a genome-wide scan in a homogeneous Arab population to identify genomic regions linked to blood pressure (BP) and its intermediate phenotypes during mental and physical stress tests.Methods:The Oman Family Study subjects (N= 1277) were recruited from five extended families of ~10 generations. Hemodynamic phenotypes were computed from beat-to-beat BP, electrocardiography and impedance cardiography. Multi-point linkage was performed for resting, mental (word conflict test, WCT) and cold pressor (CPT) stress and their reactivity scores (s), using variance components decomposition-based methods implemented in SOLAR.Results:Genome-wide scans for BP phenotypes identified quantitative trait loci (QTLs) with significant evidence of linkage on chromosomes 1 and 12 for WCT-linked cardiac output (LOD = 3.1) and systolic BP (LOD = 3.5). Evidence for suggestive linkage for WCT was found on chromosomes 3, 17 and 1 for heart rate (LOD = 2.3), DBP (LOD = 2.4) and left ventricular ejection time (LVET), respectively. For △WCT, suggestive QTLs were detected for CO on chr11 (LOD = 2.5), LVET on chr3 (LOD = 2.0) and EDI on chr9 (LOD = 2.1). For CPT, suggestive QTLs for HR and LVET shared the same region on chr22 (LOD 2.3 and 2.8, respectively) and on chr9 (LOD = 2.3) for SBP, chr7 (LOD = 2.4) for SV and chr19 (LOD = 2.6) for CO. For △CPT, CO and TPR top signals were detected on chr15 and 10 (LOD; 2.40, 2.08) respectively. Conclusion: Mental stress revealed the largest number of significant and suggestive loci for normal BP reported to date. The study of BP and its intermediate phenotypes under mental and physical stress may help reveal the genes involved in the pathogenesis of essential hypertension.

Published
2011

67. Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions

Author

Suh Yuh Wu, Meir J. Stampfer, Fredrick R. Schumacher, Rick A. Kittles, Ying Han, Jing Ma, Edward Giovannucci, Constance Chen, Robert N. Hoover, Anand P. Chokkalingam, Demetrius Albanes, Gerhard A. Coetzee, Dennis J. Hazelett, Janet L. Stanford, Rosalind A. Eeles, Fredrik Wiklund, Henry W. Long, John S. Witte, John D. Carpten, Jarmo Virtamo, Zhaoming Wang, Laurie Burdette, Sue A. Ingles, Peter Kraft, Ruth C. Travis, Christine Neslund-Dudas, Charles C. Chung, William J. Blot, Ann W. Hsing, Evelyn Tay, Susan M. Gapstur, Richard B. Biritwum, Kristin A. Rand, Jianfeng Xu, Graham Casey, Atsushi Takahashi, Lisa B. Signorello, Suzanne Kolb, S. Lilly Zheng, Sonja I. Berndt, Phyllis J. Goodman, Daniel O. Stram, W. Ryan Diver, Anselm Hennis, S. Lindstrom, Stephen J. Chanock, Michiaki Kubo, Sara S. Strom, Federico Canzian, Brian E. Henderson, Lisa Chu, Amy Hutchinson, M. Yeager, Elio Riboli, Kai Yu, Afshan Siddiq, Stephanie J. Weinstein, David V. Conti, David J. Hunter, Zsofia Kote-Jarai, Fugen Li, Ali Amin Al Olama, Andrew A. Adjei, Michael B. Cook, Curtis A. Pettaway, Wei Zheng, Edward D. Yeboah, Christopher A. Haiman, Victoria L. Stevens, William B. Isaacs, Hidewaki Nakagawa, Barbara Nemesure, Loic Le Marchand, Matthew L. Freedman, Adam B. Murphy, M. Cristina Leske, Timothy J. Key, Ann Truelove, Mark Pomerantz, Shelley Niwa, Mitchell J. Machiela, Yao Tettey, Benjamin A. Rybicki, Henrik Grönberg, Eric A. Klein, Qiyuan Li, Esther M. John, Douglas F. Easton, and National Institutes of Health

Subjects
Male, Linkage disequilibrium, Genome-wide association study, Medical and Health Sciences, ANALYSES REVEAL, Linkage Disequilibrium, Genotype, MULTIPLE, SEQUENCE VARIANTS, 2.1 Biological and endogenous factors, WIDE ASSOCIATION, Aetiology, Genetics (clinical), Cancer, GENE-EXPRESSION, African Continental Ancestry Group, Genetics, Genetics & Heredity, Prostate Cancer, Association Studies Articles, Chromosome Mapping, Single Nucleotide, Hispanic or Latino, General Medicine, 11 Medical And Health Sciences, Biological Sciences, Hispanic Americans, Life Sciences & Biomedicine, Biotechnology, Urologic Diseases, Asian Continental Ancestry Group, Biochemistry & Molecular Biology, European Continental Ancestry Group, Quantitative Trait Loci, TRANSETHNIC METAANALYSIS, Black People, Single-nucleotide polymorphism, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, White People, Asian People, Humans, Genetic Predisposition to Disease, Polymorphism, Molecular Biology, Genotyping, CAUSAL VARIANTS, Science & Technology, IDENTIFICATION, Human Genome, Prostatic Neoplasms, Molecular Sequence Annotation, 06 Biological Sciences, COMMON VARIANT, Expression quantitative trait loci, RISK-ASSOCIATED LOCI, Imputation (genetics), Genome-Wide Association Study
Abstract

Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genomeencoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10−4 –5.6 × 10−3 ) and in 30 regions 5604 | Human Molecular Genetics, 2015, Vol. 24, No. 19 we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10−6 ) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation.

Published
2015

68. Association study of genes controlling IL-12-dependent IFN-γ immunity: STAT4 alleles increase risk of pulmonary tuberculosis in Morocco

Author

Ahmed Abid, Jamila El Baghdadi, Laurent Abel, Ismail Abderrahmani Rhorfi, Anne Boland, Kristel Cosker, Ayoub Sabri, Safa El Azbaoui, Audrey V. Grant, Hicham Janah, Erwin Schurr, Jacinta Bustamante, Mélanie Migaud, Caroline Deswarte, Marianna Orlova, Stéphanie Boisson-Dupuis, Jean-Laurent Casanova, Majid Benkirane, Yasser Gharbaoui, H. Souhi, and Kebir Alaoui-Tahiri

Subjects
Male, Pathogenesis and Host Response, genetic association, STAT4, Genotype, Immunology and Allergy, Child, IFN-γ, education.field_of_study, biology, Middle Aged, STAT4 Transcription Factor, Interleukin-12, 3. Good health, Morocco, Infectious Diseases, IL-12, Child, Preschool, Female, pulmonary tuberculosis, candidate pathway, Adult, Risk, Tuberculosis, Adolescent, Population, Single-nucleotide polymorphism, eQTL, Polymorphism, Single Nucleotide, Mycobacterium tuberculosis, Interferon-gamma, Young Adult, Major Articles and Brief Reports, medicine, Humans, Genetic Predisposition to Disease, Allele, education, Tuberculosis, Pulmonary, Alleles, Genetic association, Aged, Case-control study, Infant, family-based study, medicine.disease, biology.organism_classification, Case-Control Studies, common variant, Immunology, Behcet disease
Abstract

Background. Only a minority of individuals infected with Mycobacterium tuberculosis develop clinical tuberculosis. Genetic epidemiological evidence suggests that pulmonary tuberculosis has a strong human genetic component. Previous genetic findings in Mendelian predisposition to more severe mycobacterial infections, including by M. tuberculosis, underlined the importance of the interleukin 12 (IL-12)/interferon γ (IFN-γ) circuit in antimycobacterial immunity. Methods. We conducted an association study in Morocco between pulmonary tuberculosis and a panel of single-nucleotide polymorphisms (SNPs) covering 14 core IL-12/IFN-γ circuit genes. The analyses were performed in a discovery family-based sample followed by replication in a case-control population. Results. Out of 228 SNPs tested in the family-based sample, 6 STAT4 SNPs were associated with pulmonary tuberculosis (P = .0013–.01). We replicated the same direction of association for 1 cluster of 3 SNPs encompassing the promoter region of STAT4. In the combined sample, the association was stronger among younger subjects (pulmonary tuberculosis onset

Published
2014

69. AMP deaminase 1 gene polymorphism and heart disease-a genetic association that highlights new treatment

Author

Jacek Turyn, Paul J.R. Barton, Pawel Romaszko, Magdalena A. Zabielska, Ryszard T. Smolenski, Anne B. Taegtmeyer, Ewa M. Slominska, Krystian Kaletha, and Iwona Rybakowska

Subjects
Cardiac function curve, medicine.medical_specialty, Cardiac & Cardiovascular Systems, Heart disease, Heart Diseases, Ischemic heart disease, CARDIAC MYOCYTES, Heart failure, Disease, Review Article, Bioinformatics, CELL-PROLIFERATION, Internal medicine, ACTIVATED-PROTEIN-KINASE, NUCLEOTIDE CATABOLISM, medicine, Humans, Pharmacology (medical), Genetic Predisposition to Disease, Pharmacology & Pharmacy, AMP-DEAMINASE-1 GENE, Protein kinase A, AMP deaminase, Pharmacology, Science & Technology, Polymorphism, Genetic, Genetic polymorphism, business.industry, Nucleotides, General Medicine, ADENOSINE PRODUCTION, medicine.disease, Adenosine, COMMON VARIANT, Endocrinology, Cardiovascular System & Hematology, AMP regulated protein kinase, C34T MUTATION, Cardiovascular System & Cardiology, SKELETAL-MUSCLE, Gene polymorphism, SENSITIVE POTASSIUM CHANNELS, 1115 Pharmacology and Pharmaceutical Sciences, business, Cardiology and Cardiovascular Medicine, Life Sciences & Biomedicine, medicine.drug
Abstract

Nucleotide metabolism and signalling is directly linked to myocardial function. Therefore analysis how diversity of genes coding nucleotide metabolism related proteins affects clinical progress of heart disease could provide valuable information for development of new treatments. Several studies identified that polymorphism of AMP deaminase 1 gene (AMPD1), in particular the common C34T variant of this gene was found to benefit patients with heart failure and ischemic heart disease. However, these findings were inconsistent in subsequent studies. This prompted our detailed analysis of heart transplant recipients that revealed diverse effect: improved early postoperative cardiac function associated with C34T mutation in donors, but worse 1-year survival. Our other studies on the metabolic impact of AMPD1 C34T mutation revealed decrease in AMPD activity, increased production of adenosine and de-inhibition of AMP regulated protein kinase. Thus, genetic, clinical and biochemical studies revealed that while long term attenuation of AMPD activity could be deleterious, transient inhibition of AMPD activity before acute cardiac injury is protective. We suggest therefore that pharmacological inhibition of AMP deaminase before transient ischemic event such as during ischemic heart disease or cardiac surgery could provide therapeutic benefit.

Published
2014

70. MicroRNA related polymorphisms and breast cancer risk

Author

Khan, S., Greco, D., Michailidou, K., Milne, R.L., Muranen, T.A., Heikkinen, T., Aaltonen, K., Dennis, J., Bolla, M.K., Liu, J., Hall, P., Irwanto, A., Humphreys, K., Li, J., Czene, K., Chang-Claude, J., Hein, R., Rudolph, A., Seibold, P., Flesch-Janys, D., Fletcher, O., Peto, J., Silva, I.D., Johnson, N., Gibson, L., Aitken, Z., Hopper, J.L., Tsimiklis, H., Bui, M., Makalic, E., Schmidt, D.F., Southey, M.C., Apicella, C., Stone, J., Waisfisz, Q., Meijers-Heijboer, H., Adank, M.A., Luijt, R.B. van der, Meindl, A., Schmutzler, R.K., Muller-Myhsok, B., Lichtner, P., Turnbull, C., Rahman, N., Chanock, S.J., Hunter, D.J., Cox, A., Cross, S.S., Reed, M.W.R., Schmidt, M.K., Broeks, A., Van't Veer, L.J., Hogervorst, F.B., Fasching, P.A., Schrauder, M.G., Ekici, A.B., Beckmann, M.W., Bojesen, S.E., Nordestgaard, B.G., Nielsen, S.F., Flyger, H., Benitez, J., Zamora, P.M., Perez, J.I.A., Haiman, C.A., Henderson, B.E., Schumacher, F., Marchand, L. le, Pharoah, P.D.P., Dunning, A.M., Shah, M., Luben, R., Brown, J., Couch, F.J., Wang, X., Vachon, C., Olson, J.E., Lambrechts, D., Moisse, M., Paridaens, R., Christiaens, M.R., Guenel, P., Truong, T., Laurent-Puig, P., Mulot, C., Marme, F., Burwinkel, B., Schneeweiss, A., Sohn, C., Sawyer, E.J., Tomlinson, I., Kerin, M.J., Miller, N., Andrulis, I.L., Knight, J.A., Tchatchou, S., Mulligan, A.M., Dork, T., Bogdanova, N.V., Antonenkova, N.N., Anton-Culver, H., Darabi, H., Eriksson, M., Garcia-Closas, M., Figueroa, J., Lissowska, J., Brinton, L., Devilee, P., Tollenaar, R.A.E.M., Seynaeve, C., Asperen, C.J. van, Kristensen, V.N., Slager, S., Toland, A.E., Ambrosone, C.B., Yannoukakos, D., Lindblom, A., Margolin, S., Radice, P., Peterlongo, P., Barile, M., Mariani, P., Hooning, M.J., Martens, J.W.M., Collee, J.M., Jager, A., Jakubowska, A., Lubinski, J., Jaworska-Bieniek, K., Durda, K., Giles, G.G., McLean, C., Brauch, H., Bruning, T., Ko, Y.D., Brenner, H., Dieffenbach, A.K., Arndt, V., Stegmaier, C., Swerdlow, A., Ashworth, A., Orr, N., Jones, M., Simard, J., Goldberg, M.S., Labreche, F., Dumont, M., Winqvist, R., Pylkas, K., Jukkola-Vuorinen, A., Grip, M., Kataja, V., Kosma, V.M., Hartikainen, J.M., Mannermaa, A., Hamann, U., Chenevix-Trench, G., Blomqvist, C., Aittomaki, K., Easton, D.F., Nevanlinna, H., KConFab Investigators, Australian Ovarian Canc Study Grp, GENICA Network, Department of Obstetrics and Gynecology, Clinicum, Department of Oncology, Haartman Institute (-2014), Department of Medical and Clinical Genetics, HUS Gynecology and Obstetrics, Human genetics, CCA - Oncogenesis, Obstetrics & Gynecology, Medical Oncology, Erasmus MC other, and Clinical Genetics

Subjects
Heredity, IDENTIFIES 3, lcsh:Medicine, Estrogen receptor, Genome-wide association study, Bioinformatics, 3123 Gynaecology and paediatrics, HUMAN GENES, lcsh:Science, 3' Untranslated Regions, Multidisciplinary, Research Support, Non-U.S. Gov't, Chromosome Mapping, SINGLE-NUCLEOTIDE POLYMORPHISMS, 3. Good health, Receptors, Estrogen, Female, CASP8 GENE, Research Article, EXPRESSION, Genotype, SUSCEPTIBILITY LOCI, education, 3122 Cancers, MiRNA binding, Single-nucleotide polymorphism, Breast Neoplasms, Biology, Genetic Predisposition, Polymorphism, Single Nucleotide, BINDING-SITES, Breast cancer, REDUCED RISK, Research Support, N.I.H., Extramural, SDG 3 - Good Health and Well-being, microRNA, Genetic predisposition, medicine, Journal Article, Genetics, Cancer Genetics, Humans, GENOME-WIDE ASSOCIATION, Drosha, Genetic Association Studies, Binding Sites, Complex Traits, lcsh:R, Biology and Life Sciences, Computational Biology, Human Genetics, medicine.disease, Research Support, N.I.H., Intramural, COMMON VARIANT, MicroRNAs, Case-Control Studies, Genetics of Disease, lcsh:Q, Research Support, U.S. Gov't, Non-P.H.S, Genome-Wide Association Study
Abstract

Genetic variations, such as single nucleotide polymorphisms (SNPs) in microRNAs (miRNA) or in the miRNA binding sites may affect the miRNA dependent gene expression regulation, which has been implicated in various cancers, including breast cancer, and may alter individual susceptibility to cancer. We investigated associations between miRNA related SNPs and breast cancer risk. First we evaluated 2,196 SNPs in a case-control study combining nine genome wide association studies (GWAS). Second, we further investigated 42 SNPs with suggestive evidence for association using 41,785 cases and 41,880 controls from 41 studies included in the Breast Cancer Association Consortium (BCAC). Combining the GWAS and BCAC data within a meta-analysis, we estimated main effects on breast cancer risk as well as risks for estrogen receptor (ER) and age defined subgroups. Five miRNA binding site SNPs associated significantly with breast cancer risk: rs1045494 (odds ratio (OR) 0.92; 95 confidence interval (CI): 0.88-0.96), rs1052532 (OR 0.97; 95 CI: 0.95-0.99), rs10719 (OR 0.97; 95 Cl: 0.94-0.99), rs4687554 (OR 0.97; 95 CI: 0.95-0.99, and rs3134615 (OR 1.03; 95 CI: 1.01 -1.05) located in the 3' UTR of CASP8, HDDC3, DROSHA, MUSTN1, and MYCL1, respectively. DROSHA belongs to miRNA machinery genes and has a central role in initial miRNA processing. The remaining genes are involved in different molecular functions, including apoptosis and gene expression regulation. Further studies are warranted to elucidate whether the miRNA binding site SNPs are the causative variants for the observed risk effects. This is an open-access article free of all copyright.

Published
2014

71. Effect of <italic>FTO</italic> rs9939609 variant on insulin resistance in obese female adolescents.

Author

Iskandar, Kristy, Patria, Suryono Yudha, Huriyati, Emy, Luglio, Harry Freitag, Julia, Madarina, and Susilowati, Rina

Subjects
GENETIC polymorphisms, HUMAN genetic variation, INSULIN resistance, ADOLESCENT obesity, WAIST circumference, BODY mass index, GLUCOSE in the body
Abstract

Objectives: FTO rs9939609 variant has been shown to be associated with insulin resistance in Caucasian children. However, studies in Asia show inconsistent findings. We investigated the association between FTO rs9939609 polymorphisms and insulin resistance in obese female adolescents in Indonesia, a genetically distinct group within Asia. Results: A total of 78 obese female adolescents participated in this study. The risk allele (A) frequency of FTO rs9939609 variant in Indonesian obese female adolescence was 44.2%. The frequency of insulin resistance was higher in the subjects with AA (54.6%) or AT (59.6%) than the subject with TT genotype (50%), but did not statistically different (p = 0.81 and p = 0.47, respectively). The insulin resistance rate was also higher in the risk allele (A) than the non-risk allele (T) subjects (0.58 vs. 0.55), but did not statistically different (p = 0.75). There was no association between FTO rs9939609 variant and body mass index, fasting glucose level, fasting insulin level, homeostatic model assessment of insulin resistance, and waist circumference (p > 0.05). In conclusion, FTO rs9939609 variant may not be associated with insulin resistance in Indonesian obese female adolescents. A multicenter study with a larger sample size is needed to clarify these findings. [ABSTRACT FROM AUTHOR]

Published
2018
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72. Individual common variants exert weak effects on the risk for autism spectrum disorderspi

Author

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

73. PNPLA 3I148M genetic variant associates with insulin resistance and baseline viral load in HCV genotype 2 but not in genotype 3 infection

Author

Rembeck, Karolina, Maglio, Cristina, Lagging, Martin, Christensen, Peer Brehm, Färkkilä, Martti, Langeland, Nina, Mørch, Kristine, Buhl, Mads R., Pedersen, Court, Norkrans, Gunnar, Hellstrand, Kristoffer, Lindh, Magnus, Pirazzi, Carlo, Burza, Maria A., Romeo, Stefano, Westin, Johan, for the NORDynamIC group, Department of Medicine, Clinicum, and Gastroenterologian yksikkö

Subjects
Male, Cirrhosis, Hepacivirus, HEPATITIS-C VIRUS, DISEASE, 0302 clinical medicine, Genotype, NONALCOHOLIC FATTY LIVER, Genetics(clinical), Viral load, Genetics (clinical), METABOLIC SYNDROME, 0303 health sciences, education.field_of_study, Fatty liver, HOMEOSTASIS MODEL ASSESSMENT, Hepatitis C, Middle Aged, Viral Load, 3. Good health, LOW-DENSITY, Female, 030211 gastroenterology & hepatology, Research Article, Adult, lcsh:Internal medicine, lcsh:QH426-470, GLUCOSE CLAMP TECHNIQUE, education, Biology, Antiviral Agents, Polymorphism, Single Nucleotide, 03 medical and health sciences, PNPLA 3, Genetics, medicine, STEATOSIS, Humans, Adiponutrin, lcsh:RC31-1245, Alleles, 030304 developmental biology, ADIPONUTRIN, PNPLA, Membrane Proteins, Insulin resistance, Lipase, Hepatitis C, Chronic, medicine.disease, Virology, COMMON VARIANT, Fatty Liver, lcsh:Genetics, 3121 General medicine, internal medicine and other clinical medicine, Immunology, 3111 Biomedicine, Metabolic syndrome, Steatosis
Abstract

Background Hepatic steatosis in HCV patients has been postulated as a risk factor associated with a higher frequency of fibrosis and cirrhosis. A single genetic variant, PNPLA3 I148M, has been widely associated with increased hepatic steatosis. Previous studies of the PNPLA3 I148M sequence variant in HCV infected individuals have reported an association between this variant and prevalence of steatosis, fibrosis, and cirrhosis. To evaluate the impact of PNPLA3 I148M variant on metabolic traits and treatment response in HCV genotype 2 and 3 infected patients. Methods Three hundred and eighty-two treatment naïve HCV genotype 2 or 3 infected patients were included in a phase III, open label, randomized, multicenter, investigator-initiated trial (the NORDynamIC study), in which pretreatment liver biopsies were mandatory. PNPLA3I148M genotyping was performed in a total of 359 Caucasian patients. Results In HCV genotype 2 infected patients carrying the PNPLA3 148M allele, there was significantly increased insulin resistance (P = 0.023) and lower viral load (P = 0.005) at baseline as well as the first seven days of antiviral treatment. These results were not observed in HCV genotype 3 infected patients. Conclusions Our results suggest a possible association between the PNPLA3 148M allele and insulin resistance as well as baseline viral load in HCV genotype 2, but not in genotype 3.

Published
2012

74. A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits

Author

Yanxun Zhou, Amy R. Bentley, Charles N. Rotimi, Guanjie Chen, and Ao Yuan

Subjects
haplotype, Genomics, Genome-wide association study, Disease, Computational biology, Biology, Bioinformatics, Biochemistry, 03 medical and health sciences, 0302 clinical medicine, Missing heritability problem, rare variant, Molecular Biology, lcsh:QH301-705.5, 030304 developmental biology, Genetic association, 0303 health sciences, Applied Mathematics, Haplotype, Methodology, association, Explained variation, 3. Good health, Computer Science Applications, Computational Mathematics, lcsh:Biology (General), common variant, 030217 neurology & neurosurgery, Common disease-common variant
Abstract

Genome-wide association studies (GWAS) have been successful in detecting common genetic variants underlying common traits and diseases. Despite the GWAS success stories, the percent trait variance explained by GWAS signals, the so called “missing heritability” has been, at best, modest. Also, the predictive power of common variants identified by GWAS has not been encouraging. Given these observations along with the fact that the effects of rare variants are often, by design, unaccounted for by GWAS and the availability of sequence data, there is a growing need for robust analytic approaches to evaluate the contribution of rare variants to common complex diseases. Here we propose a new method that enables the simultaneous analysis of the association between rare and common variants in disease etiology. We refer to this method as SCARVA (simultaneous common and rare variants analysis). SCARVA is simple to use and is efficient. We used SCARVA to analyze two independent real datasets to identify rare and common variants underlying variation in obesity among participants in the Africa America Diabetes Mellitus (AADM) study and plasma triglyceride levels in the Dallas Heart Study (DHS). We found common and rare variants associated with both traits, consistent with published results.

Published
2012

75. On the Futility of Screening for Genes That Make You Fat

Author

Terho Lehtimäki, Emily Sonestedt, Göran Hallmans, Andy R Ness, Simin Liu, Tuija Tammelin, John J. Nolan, Massimo Mangino, Nicholas J. Timpson, George Dedoussis, Aline Meirhaeghe, Lu Qi, Pål R. Njølstad, Ruth J. F. Loos, Mustafa Atalay, Mao Fu, Natalia V. Rivera, Marju Orho-Melander, Thorkild I. A. Sørensen, Philippe Froguel, André G. Uitterlinden, Torben Hansen, Debbie A Lawlor, M. Carola Zillikens, Tapani Rönnemaa, Vilmundur Gudnason, Esther Zimmermann, Claes Ohlsson, Cornelia M. van Duijn, Paul M. Ridker, Marjo-Riitta Järvelin, Samia Mora, María Teresa Martínez Larrad, Alena Stančáková, Thomas Illig, Zoltán Kutalik, Sven Bergmann, Jonatan R. Ruiz, Luigi Palla, Kathleen A. Jablonski, Günther Silbernagel, Ulla Sovio, Soren Snitker, Karina Meidtner, Bo Isomaa, Stephen J. Sharp, Jana V. van Vliet-Ostaptchouk, Louis Pérusse, Mika Kähönen, Daniel I. Chasman, Najaf Amin, Johanna Kuusisto, Toshiko Tanaka, Ingrid B. Borecki, John-Olov Jansson, Christine Cavalcanti-Proença, N. Charlotte Onland-Moret, Kay-Tee Khaw, Camilla H. Sandholt, Ulf Ekelund, Luigi Ferrucci, Mark Walker, Yiqing Song, Jose C. Florez, Oluf Pedersen, Leif Groop, Ying Wu, Soren Brage, Tuomas O. Kilpeläinen, Anders Grøntved, Frida Renström, Meena Kumari, Stéphane Cauchi, Michael Boehnke, Tamara B. Harris, Christine S. Autenrieth, Jeffery Metter, Beverley Balkau, Dmitry Shungin, Karen L. Mohlke, Markku Laakso, Matti Uusitupa, Nicholas J. Wareham, Andreas Fritsche, Jaakko Tuomilehto, Albert Hofman, Shah Ebrahim, Mary F. Feitosa, Melissa E. Garcia, Stefan Johansson, Tim D. Spector, Paul W. Franks, E. Shyong Tai, Frank B. Hu, Jonathan T. Tan, Maarit Hakanen, Heiner Boeing, Manuel Serrano Ríos, Olli T. Raitakari, Michael Marmot, Meian He, Jennifer L. Bragg-Gresham, Claude Bouchard, Tariq Ahmad, Ellen W. Demerath, Keri L. Monda, Robert A. Scott, Marika Kaakinen, Chris Power, Stefania Bandinelli, Christina Holzapfel, Timo A. Lakka, Heather M. Stringham, Stavroula Kanoni, Elina Hyppönen, Pamela L. Lutsey, Internal Medicine, Medical Microbiology & Infectious Diseases, Epidemiology, Urology, Institute of Metabolic Science, MRC, Departments of Epidemiology and Nutrition, Harvard School of Public Health, Department of Clinical Sciences, Lund University Diabetes Centre-Lund University [Lund], Division of Epidemiology and Community Health, University of Minnesota [Twin Cities] (UMN), University of Minnesota System-University of Minnesota System, Division of Cardiology, Duke University Medical Center, Brigham and Women's Hospital [Boston], Institute of Health Sciences and Biocenter Oulu, University of Oulu, Hagedorn Research Institute, Else Kroener Fresenius Centre - Zentralinstitut für Ernährungs und Lebensmittelfors (ZIEL), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Department of Population Health Sciences, University of Wisconsin-Madison, Institute of Epidemiology [Neuherberg] (EPI), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Centre for Paediatric Epidemiology and Biostatistics, University College of London [London] (UCL), MRC Centre for Epidemiology of Child Health, UCL Institute of Child Health, Institut de biologie de Lille - UMS 3702 (IBL), Université de Lille-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Centre National de la Recherche Scientifique (CNRS), Department of Medical Genetics, Université de Lausanne (UNIL), Department of Epidemiology and Public Health, Department of Medicine, University of Eastern Finland-Kuopio University Hospital, Department of Epidemiology, Deutsches Institut für Ernährungsforschung Potsdam-Rehbrücke (DifE), Leibniz Association-Leibniz Association, Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), National University of Singapore (NUS)-Yong Loo Lin School of Medicine, King‘s College London, Centre for Causal Analyses in Translational Epidemiology, University of Bristol [Bristol]-Medical Research Council, Division of Preventive Medicine, Netherlands Genomics Initiative, Netherlands Consortium for Healthy Aging [Leiden, Netherlands] (NCHA), Department of Internal Medicine, Erasmus University Medical Center [Rotterdam] (Erasmus MC), The Biostatistics Center, The George Washington University (GW), National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Mental Health Sciences Unit, Department of Clinical Medicine, University of Bergen (UiB), Department of Biostatistics and Center for Statistical Genetics, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Department of Genetics, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Molecular Genetics Section, University of Groningen [Groningen]-University Medical Centre Groningen, Complex Genetics Section, University Medical Center [Utrecht], Julius Center for Health Sciences and Primary Care, Institute of Preventive Medicine, Copenhagen University Hospital, Department of Biomedical Sciences [Copenhagen], Faculty of Health and Medical Sciences, University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Genetic Epidemiology Unit, Medstar Research Institute, Division of Endocrinology, Diabetology, Nephrology, Vascular Disease, and Clinical Chemistry, Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen, Department of Nutrition-Dietetics, Harokopio University of Athens, Division of Statistical Genomics, Washington University School of Medicine, University of Maryland School of Medicine, University of Maryland System, Unit for Preventive Nutrition, Karolinska Institutet [Stockholm], Department of Physical Education and Sport, University of Granada [Granada], Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Hospital Clínico San Carlos, Department of Physiology, University of Eastern Finland-Institute of Biomedicine, The Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Institute of Sport Science and Clinical Biomechanics, University of Southern Denmark (SDU), Department of Public Health and Clinical Medicine/Nutritional Research, Umeå University, Department of Physiology/Endocrinology, Institute of Neuroscience and Physiology [Göteborg]-University of Gothenburg (GU)-Sahlgrenska Academy at University of Gothenburg [Göteborg], Department of Clinical Physiology, University of Tampere [Finland]-Tampere University Hospital, Steno Diabetes Centre, Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), Faculty of Health Sciences, Genetic Epidemiology and Clinical Research Group, Umea University Hospital, Department of Odontology, Department of Medical Statistics, London School of Hygiene and Tropical Medicine (LSHTM), LIKES Research Center for Sport and Health Sciences, Finnish Institute of Occupational Health, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Human Genomics Laboratory, Pennington Biomedical Research Center, Louisiana State University (LSU)-Louisiana State University (LSU), Epidémiologie des maladies chroniques : impact des interactions gène environnement sur la santé des populations, Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé, Division of Endocrinology, Diabetes and Nutrition, University of Maryland System-University of Maryland System, Institute of Cell and Molecular Biosciences, Newcastle University [Newcastle], Centre for Bone and Arthritis Research, Institute of Medicine-University of Gothenburg (GU), Geriatric Rehabilitation Unit, Azienda Sanitaria Firenze, Centre for Medical Systems Biology, Faculty of Epidemiology and Population Health [London], Icelandic Heart Association, Heart Preventive Clinic and Research Institute, University of Iceland [Reykjavik], Department of Public Health, South Ostrobothnia Central Hospital, Department of Clinical and Preventive Medicine, Danube-University Krems, Department of Clinical Chemistry, Turku University Hospital (TYKS), Folkhälsan Research Centre, Department of Pediatrics, Haukeland University Hospital, University of Bergen (UiB)-University of Bergen (UiB), Center for Human Genetic Research and Diabetes Research Center, Massachusetts General Hospital [Boston], Harvard Medical School [Boston] (HMS), Program for Medical and Population Genetics, Broad Institute [Cambridge], Harvard University [Cambridge]-Massachusetts Institute of Technology (MIT)-Harvard University [Cambridge]-Massachusetts Institute of Technology (MIT), Center for Metabolic Disease Prevention, 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, School of Oral and Dental Sciences, University of Bristol [Bristol], National University of Singapore (NUS), Department of Genomics of Common Disease, Imperial College London, Department of Public Health and Primary Care, University of Cambridge [UK] (CAM), Department of Epidemiology and Biostatistics, Department of Life Course and Services, National Institute for Health and Welfare [Helsinki], Autard, Delphine, Lund University [Lund], Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université de Lausanne = University of Lausanne (UNIL), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), Universidad de Granada = University of Granada (UGR), University of Gothenburg (GU)-Institute of Medicine, University of California (UC)-University of California (UC)-David Geffen School of Medicine [Los Angeles], University of California (UC)-University of California (UC), Medical Research Council (MRC), Center for Liver, Digestive and Metabolic Diseases (CLDM), Brage, Soren [0000-0002-1265-7355], Sharp, Stephen [0000-0003-2375-1440], Sovio, Ulla [0000-0002-0799-1105], Khaw, Kay-Tee [0000-0002-8802-2903], Wareham, Nicholas [0000-0003-1422-2993], Apollo - University of Cambridge Repository, Hjelt Institute (-2014), Harvard University-Massachusetts Institute of Technology (MIT)-Harvard University-Massachusetts Institute of Technology (MIT), Kilpeläinen, Tuomas O, Qi, Lu, Brage, Soren, Sharp, Stephen J, Hypponen, Elina, and Loos, Ruth JF

Subjects
Male, Heredity, endocrine system diseases, Medical disciplines: 700::Basic medical, dental and veterinary science disciplines: 710::Medical genetics: 714 [VDP], Epidemiology, Social and Behavioral Sciences, no keywords, MESH: Genotype, 0302 clinical medicine, MESH: Child, GENETIC-VARIANTS, MESH: Proteins, 10. No inequality, Child, 0303 health sciences, Anthropometry, MESH: Polymorphism, Single Nucleotide, General Medicine, 11 Medical And Health Sciences, Genomics, MESH: Motor Activity, Adipose Tissue, Perspective, Medicine, Public Health, WAIST CIRCUMFERENCE, MESH: Adipose Tissue, medicine.medical_specialty, Genotype, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Endocrinology and Diabetes, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Genomic Medicine, Genetics, Humans, Genetic Testing, Gene Prediction, Biology, Adipose Tissue/metabolism, Adolescent, Adult, Aged, Female, Genetic Predisposition to Disease, Motor Activity, Obesity/genetics, Obesity/metabolism, Polymorphism, Single Nucleotide, Proteins/genetics, Risk Factors, MESH: Adolescent, Science & Technology, MESH: Humans, Computational Biology, nutritional and metabolic diseases, Proteins, MESH: Adult, Odds ratio, medicine.disease, Obesity, RS9939609 POLYMORPHISM, Endocrinology, Anthropology, Physiological Processes, Body mass index, MESH: Female, Population Genetics, obesity, Genetic Screens, Anatomy and Physiology, FTO gene, IDENTICAL-TWINS, MESH: Risk Factors, MESH: Obesity, adolescents, 030212 general & internal medicine, MESH: Aged, MESH: Genetic Predisposition to Disease, 3142 Public health care science, environmental and occupational health, ENVIRONMENT INTERACTION, Genetic Epidemiology, childhood obesity, Life Sciences & Biomedicine, Research Article, Clinical Research Design, UNITED-STATES, WEIGHT-LOSS, Childhood obesity, body weight, Medicine, General & Internal, Genome Analysis Tools, Internal medicine, General & Internal Medicine, medicine, Allele, Sports and Exercise Medicine, Genetic Association Studies, 030304 developmental biology, Nutrition, Clinical Genetics, Population Biology, business.industry, Human Genetics, MESH: Male, COMMON VARIANT, meta-analysis, Minor allele frequency, BODY-MASS INDEX, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Genetics of Disease, Genetic Polymorphism, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Meta-Analyses, business, Energy Metabolism, genetic predisposition, DIABETES PREVENTION
Abstract

Ruth Loos and colleagues report findings from a meta-analysis of multiple studies examining the extent to which physical activity attenuates effects of a specific gene variant, FTO, on obesity in adults and children. They report a fairly substantial attenuation by physical activity on the effects of this genetic variant on the risk of obesity in adults., Background The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n = 218,166) and nine studies of children and adolescents (n = 19,268). Methods and Findings All studies identified to have data on the FTO rs9939609 variant (or any proxy [r 2>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A−) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20–1.26), but PA attenuated this effect (p interaction = 0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio = 1.22/allele, 95% CI 1.19–1.25) than in the inactive group (odds ratio = 1.30/allele, 95% CI 1.24–1.36). No such interaction was found in children and adolescents. Conclusions The association of the FTO risk allele with the odds of obesity is attenuated by 27% in physically active adults, highlighting the importance of PA in particular in those genetically predisposed to obesity. Please see later in the article for the Editors' Summary, Editors’ Summary Background Two in three Americans are overweight, of whom half are obese, and the trend towards increasing obesity is now seen across developed and developing countries. There has long been interest in understanding the impact of genes and environment when it comes to apportioning responsibility for obesity. Carrying a change in the FTO gene is common (found in three-quarters of Europeans and North Americans) and is associated with a 20%–30% increased risk of obesity. Some overweight or obese individuals may feel that the dice are loaded and there is little point in fighting the fat; it has been reported that those made aware of their genetic susceptibility to obesity may still choose a poor diet. A similar fatalism may occur when overweight and obese people consider physical activity. But disentangling the influence of physical activity on those genetically susceptible to obesity from other factors that might impact weight is not straightforward, as it requires large sample sizes, could be subject to publication bias, and may rely on less than ideal self-reporting methods. Why Was This Study Done? The public health ramifications of understanding the interaction between genetic susceptibility to obesity and physical activity are considerable. Tackling the rising prevalence of obesity will inevitably include interventions principally aimed at changing dietary intake and/or increasing physical activity, but the evidence for these with regards to those genetically susceptible has been lacking to date. The authors of this paper set out to explore the interaction between the commonest genetic susceptibility trait and physical activity using a rigorous meta-analysis of a large number of studies. What Did the Researchers Do and Find? The authors were concerned that a meta-analysis of published studies would be limited both by the data available to them and by possible bias. Instead of this more widely used approach, they took the literature search as their starting point, identified other studies through their collaborators’ network, and then undertook a meta-analysis of all available studies using a new and standardized analysis plan. This entailed an extremely large number of authors mining their data afresh to extract the relevant data points to enable such a meta-analysis. Physical activity was identified in the original studies in many different ways, including by self-report or by using an external measure of activity or heart rate. In order to perform the meta-analysis, participants were labeled as physically active or inactive in each study. For studies that had used a continuous scale, the authors decided that the bottom 20% of the participants were inactive (10% for children and adolescents). Using data from over 218,000 adults, the authors found that carrying a copy of the susceptibility gene increased the odds of obesity by 1.23-fold. But the size of this influence was 27% less in the genetically susceptible adults who were physically active (1.22-fold) compared to those who were physically inactive (1.30-fold). In a smaller study of about 19,000 children, no such effect of physical activity was seen. What Do these Findings Mean? This study demonstrates that people who carry the susceptibility gene for obesity can benefit from physical activity. This should inform health care professionals and the wider public that the view of genetically determined obesity not being amenable to exercise is incorrect and should be challenged. Dissemination, implementation, and ensuring uptake of effective physical activity programs remains a challenge and deserves further consideration. That the researchers treated “physically active” as a yes/no category, and how they categorized individuals, could be criticized, but this was done for pragmatic reasons, as a variety of means of assessing physical activity were used across the studies. It is unlikely that the findings would have changed if the authors had used a different method of defining physically active. Most of the studies included in the meta-analysis looked at one time point only; information about the influence of physical activity on weight changes over time in genetically susceptible individuals is only beginning to emerge. Additional Information Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001116. This study is further discussed in a PLoS Medicine Perspective by Lennert Veerman The US Centers for Disease Control and Prevention provides obesity-related statistics, details of prevention programs, and an overview on public health strategy in the United States A more worldwide view is given by the World Health Organization The UK National Health Service website gives information on physical activity guidelines for different age groups, while similar information can also be found from US sources

Published
2011

76. Personality, a key factor in personalized medicine?

Author

Anton J.W. Scheurink, André P van Beek, Gertjan van Dijk, Lambertus Benthem, Gretha J. Boersma, Groningen Kidney Center (GKC), Scheurink lab, Van Dijk lab, and Center for Liver, Digestive and Metabolic Diseases (CLDM)

Subjects
Coping (psychology), ROMAN HIGH-AVOIDANCE, media_common.quotation_subject, Psychological intervention, EXERCISE, Type 2 diabetes, RATS, Health problems, Medicine, Personality, Animals, Humans, Precision Medicine, INCREASED RISK, media_common, Pharmacology, INSULIN-RESISTANCE, business.industry, FRAMESHIFT MUTATION, medicine.disease, Personalized medicine, Obesity, Coping style, RANDOMIZED-TRIAL, COMMON VARIANT, Treatment, Increased risk, OBESITY, Disease Susceptibility, Insulin Resistance, business, Clinical psychology
Abstract

The incidence of health problems resulting from obesity is growing and obesity and its related diseases has become one of the main causes in death in industrialized societies. Environmental influences are crucial for the interactions between genetic, neurohormonal and metabolic factors that may be important in understanding individual differences in the development of obesity and metabolic diseases like type 2 diabetes. In particular the interactions between the personality of an individual and the environment play a key role in predicting the chance for successful treatment. Our experimental data clearly point out that the success of interventions designed to prevent or treat metabolic diseases could be considerably improved by adjusting the intervention to the personality of the individual. Furthermore, certain physiological and neuroendocrine characteristics of a personality are strong indicators for pathology development, both in experimental animals and humans. Future research should focus on the identification of easily measurable physiological and neuroendocrine markers indicative of the coping style or personality in humans. (C) 2011 Elsevier B.V. All rights reserved.

Published
2011

77. Obesity-susceptibility loci have a limited influence on birth weight: a meta-analysis of up to 28,219 individuals

Author

Marcel Den Hoed, Ruth Loos, Eco De Geus, Marjo-Riitta Jarvelin, Elina Hypponen, Amanda Bennett, Yurii Aulchenko, Andrew Hattersley, Craig Pennell, Gerard Koppelman, David Evans, Soren Brage, Rachel Freathy, Stavroula Kanoni, Lachlan Coin, George Davey Smith, Inga Prokopenko, Tuomas Kilpeläinen, Philippe Froguel, Cornelia Van Duijn, Anders Grøntved, Struan Grant, Reedik Mägi, Lyle John Palmer, Paul O'Reilly, Julie Marsh, Fernando Rivadeneira, Paul Elliott, Adaikalavan Ramasamy, Gonneke Willemsen, Mark McCarthy, Cecilia Lindgren, Nicole Warrington, Faculty of Behavioural and Movement Sciences, Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, University of Groningen, Kilpeläinen, Tuomas O, den Hoed, Marcel, Ong, Ken K, Grøntved, Anders, Hypponen, Elina, and Loos, Ruth JF

Subjects
Male, Netherlands Twin Register (NTR), obesity, Medicine (miscellaneous), Genome-wide association study, MC4R, Mitochondrial Membrane Transport Proteins, FTO gene, Body Mass Index, ADULT OBESITY, Birth Weight, body mass index (BMI), GESTATIONAL-AGE, Aged, 80 and over, Genetics, Nutrition and Dietetics, Middle Aged, European Prospective Investigation into Cancer and Nutrition, FAT MASS, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, loci, Genome-wide association, Body-mass index, Gestational-age, Common variant, Adult obesity, Fetal-growth, Fat mass, Adiposity, Female, Adult, medicine.medical_specialty, Birth weight, Biology, Mitochondrial Proteins, Young Adult, SDG 3 - Good Health and Well-being, Internal medicine, medicine, Humans, COHORT, Obesity, GENOME-WIDE ASSOCIATION, Allele, FTO GENE, Alleles, Aged, Membrane Transport Proteins, Proteins, birth weight, medicine.disease, COMMON VARIANT, BODY-MASS INDEX, Endocrinology, Genetic Loci, FETAL-GROWTH, Body mass index, Genome-Wide Association Study
Abstract

Background: High birth weight is associated with adult body mass index (BMI). We hypothesized that birth weight and BMI may partly share a common genetic background. Objective: The objective was to examine the associations of 12 established BMI variants in or near the NEGR1, SEC16B, TMEM18, ETV5, GNPDA2, BDNF, MTCH2, BCDIN3D, SH2B1, FTO, MC4R, and KCTD15 genes and their additive score with birth weight. Design: A meta-analysis was conducted with the use of 1) the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk, Hertfordshire, Fenland, and European Youth Heart Study cohorts (n(max) = 14,060); 2) data extracted from the Early Growth Genetics Consortium meta-analysis of 6 genome-wide association studies for birth weight (n(max) = 10,623); and 3) all published data (n(max) = 14,837). Results: Only the MTCH2 and FTO loci showed a nominally significant association with birth weight. The BMI-increasing allele of the MTCH2 variant (rs10838738) was associated with a lower birth weight (beta +/- SE: 213 +/- 5 g/allele; P = 0.012; n = 23,680), and the BMI-increasing allele of the FTO variant (rs1121980) was associated with a higher birth weight (beta +/- SE: 11 +/- 4 g/allele; P = 0.013; n = 28,219). These results were not significant after correction for multiple testing. Conclusions: Obesity-susceptibility loci have a small or no effect on weight at birth. Some evidence of an association was found for the MTCH2 and FTO loci, ie, lower and higher birth weight, respectively. These findings may provide new insights into the underlying mechanisms by which these loci confer an increased risk of obesity. Am J Clin Nutr 2011;93:851-60.

Published
2011

78. Genetics in schizophrenia: where are we and what next?

Author

Arun K, Tiwari, Clement C, Zai, Daniel J, Müller, and James L, Kennedy

Subjects
DNA Copy Number Variations, Receptors, Notch, whole genome association study, GWAS, CNV, copy number variation, candidate gene, schizophrenia, Proto-Oncogene Proteins, common variant, mental disorders, Translational Research, Genetics, Humans, Receptor, Notch4, linkage, rare variant, Genome-Wide Association Study
Abstract

Understanding the genetic basis of schizophrenia continues to be major challenge. The research done during the last two decades has provided several candidate genes which unfortunately have not been consistently replicated across or within a population. The recent genome-wide association studies (GWAS) and copy number variation (CNV) studies have provided important evidence suggesting a role of both common and rare large CNVs in schizophrenia genesis. The burden of rare copy number variations appears to be increased in schizophrenia patients. A consistent observation among the GWAS studies is the association with schizophrenia of genetic markers in the major histocompatibility complex (6p22.1)-containing genes including NOTCH4 and histone protein loci. Molecular genetic studies are also demonstrating that there is more overlap between the susceptibility genes for schizophrenia and bipolar disorder than previously suspected. In this review we summarize the major findings of the past decade and suggest areas of future research.

Published
2010

79. Genome-wide meta-analysis for serum calcium identifies significantly associated SNPs near the calcium-sensing receptor (CASR) gene

Author

Gérard Waeber, Andrew B. Singleton, Toby Johnson, Daniel F. Gudbjartsson, Gudmundur I. Eyjolfsson, Peter Vollenweider, Yuri Milaneschi, Vincent Mooser, Diana Marek, Jacques S. Beckmann, Noam D. Beckmann, John C. Chambers, Unnur Styrkarsdottir, Kari Stefansson, Hilma Holm, Gunnar Sigurdsson, Stefania Bandinelli, Toshiko Tanaka, Joban Sehmi, Yun Li, Sven Bergmann, Dawn M. Waterworth, Murielle Bochud, Jack M. Guralnik, Paul Elliott, Unnur Thorsteinsdottir, Karen Kapur, Ranil DeSilva, Jaspal S. Kooner, James Scott, Weihua Zhang, Zoltán Kutalik, Unnur S. Bjornsdottir, Angelo DiIorio, Dena G. Hernandez, Luigi Ferrucci, and Medical Research Council (MRC)

Subjects
Cancer Research, Candidate gene, Linkage disequilibrium, CARDIOVASCULAR MORTALITY, LOCI, Genome-wide association study, 0302 clinical medicine, PRIMARY HYPERPARATHYROIDISM, Genetics (clinical), Genetics, Genetics & Heredity, 0303 health sciences, education.field_of_study, A986S POLYMORPHISM, 030220 oncology & carcinogenesis, Calcium-sensing receptor, BONE-MINERAL DENSITY, Life Sciences & Biomedicine, Research Article, medicine.medical_specialty, lcsh:QH426-470, Population, European Continental Ancestry Group, Public Health and Epidemiology, chemistry.chemical_element, Single-nucleotide polymorphism, Biology, Calcium, HYPOCALCIURIC HYPERCALCEMIA, Polymorphism, Single Nucleotide, White People, 03 medical and health sciences, ADULT, Internal medicine, medicine, Humans, CORONARY-HEART-DISEASE, education, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, Calcium metabolism, 0604 Genetics, Science & Technology, Genome, Human, Genetics and Genomics, Calcium/blood, European Continental Ancestry Group/statistics & numerical data, Genome-Wide Association Study/statistics & numerical data, Receptors, Calcium-Sensing/genetics, COMMON VARIANT, lcsh:Genetics, Endocrinology, chemistry, MYOCARDIAL-INFARCTION, Computational Biology/Population Genetics, Receptors, Calcium-Sensing, Computational Biology/Genomics, Genome-Wide Association Study, Developmental Biology
Abstract

Calcium has a pivotal role in biological functions, and serum calcium levels have been associated with numerous disorders of bone and mineral metabolism, as well as with cardiovascular mortality. Here we report results from a genome-wide association study of serum calcium, integrating data from four independent cohorts including a total of 12,865 individuals of European and Indian Asian descent. Our meta-analysis shows that serum calcium is associated with SNPs in or near the calcium-sensing receptor (CASR) gene on 3q13. The top hit with a p-value of 6.3×10-37 is rs1801725, a missense variant, explaining 1.26% of the variance in serum calcium. This SNP had the strongest association in individuals of European descent, while for individuals of Indian Asian descent the top hit was rs17251221 (p = 1.1×10-21), a SNP in strong linkage disequilibrium with rs1801725. The strongest locus in CASR was shown to replicate in an independent Icelandic cohort of 4,126 individuals (p = 1.02×10-4). This genome-wide meta-analysis shows that common CASR variants modulate serum calcium levels in the adult general population, which confirms previous results in some candidate gene studies of the CASR locus. This study highlights the key role of CASR in calcium regulation., Author Summary Calcium levels in blood serum play an important role in many biological processes. The regulation of serum calcium is under strong genetic control. This study describes the first meta-analysis of a genome-wide association study from four cohorts totaling 12,865 participants of European and Indian Asian descent. Confirming previous results in some candidate gene studies, we find that common polymorphisms at the calcium-sensing receptor (CASR) gene locus are associated with serum calcium concentrations. We show that CASR variants give rise to the strongest signals associated with serum calcium levels in both European and Indian Asian populations, while no other locus reaches genome-wide significance. Our results show that CASR is a key player in genetic regulation of serum calcium in the adult general population.

Published
2010
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80. A genome-wide association study identifies protein quantitative trait loci (pQTLs)

Author

Luigi Ferrucci, J. Raphael Gibbs, Michael N. Weedon, Tamara B. Harris, Alison J. Hurst, William Henley, Annamaria Corsi, Vijay Panicker, Colin M. Dayan, Amanda J. Bennett, Nicole Washecka, Kara Stevens, Stefania Bandinelli, Jack M. Guralnik, Giuseppe Paolisso, Sampath Arepalli, Marjo-Riitta Järvelin, Ian Rafferty, Joyce van de Leemput, John R. B. Perry, Sonja W. Scholz, Mark I. McCarthy, Gregory J. Tranah, Hana Lango, Javier Simón-Sánchez, Rongling Li, Aimo Ruokonen, Andrew B. Singleton, Anne B. Newman, Timothy M. Frayling, Fulvio Lauretani, Dena G. Hernandez, Neil Rice, Anna Murray, David Melzer, Sajjad Rafiq, Angela Britton, Melzer, D., Perry, J., Hernandez, D., Corsi, A., Stevens, K., Rafferty, I., Murray, A., Gibbs, J., Paolisso, Giuseppe, Rafiq, S., SIMON SANCHEZ, J., Lango, H., Sholz, S., Weedon, M., Arepalli, S., Rice, N., Washecka, N., Hurst, A., Britton, A., Henley, W., VAN DE LEEMPUT, J., Li, R., Newman, A., Tranah, G., Harris, T., Panicker, V., Dayan, C., Bennet, A., Mccarthy, M., Ruokonen, A., Jarvelin, M., Guralnik, J., Bandinelli, S., Frayling, T., Singleton, A., and Ferrucci, L.

Subjects
Male, Cancer Research, Transcription, Genetic, Genetic Linkage, Gene Dosage, Genome-wide association study, DISEASE, 0302 clinical medicine, Biochemistry/Protein Chemistry, Copy-number variation, Genetics and Genomics/Genetics of Disease, Genetics (clinical), Genetics & Heredity, RISK, Aged, 80 and over, Genetics, 0303 health sciences, BIRTH COHORT, interleukin, Genetics and Genomics/Functional Genomics, Genetics and Genomics/Gene Expression, Blood Proteins, Genetics and Genomics/Physiogenomics, Middle Aged, CANCER, Diabetes and Endocrinology, InCHIANTI study, 030220 oncology & carcinogenesis, MENDELIAN RANDOMIZATION, Female, Life Sciences & Biomedicine, Biochemistry/Transcription and Translation, Research Article, Adult, liver function markers, lcsh:QH426-470, Genotype, Cardiovascular Disorders, Quantitative Trait Loci, Single-nucleotide polymorphism, Genetics and Genomics/Complex Traits, Biology, Quantitative trait locus, Polymorphism, Single Nucleotide, 03 medical and health sciences, Genetic variation, Humans, YEAST, Allele, Molecular Biology, QH426, POLYMORPHISMS, Ecology, Evolution, Behavior and Systematics, Aged, 030304 developmental biology, 0604 Genetics, Science & Technology, HUMAN GENE-EXPRESSION, RECEPTOR, Genome, Human, Genetic Variation, Molecular biology, R1, COMMON VARIANT, lcsh:Genetics, Genetics and Genomics/Genome Projects, Expression quantitative trait loci, Liver function, Developmental Biology, Genome-Wide Association Study
Abstract

There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts – cis effects, and elsewhere in the genome – trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10−57), CCL4L1 (p = 3.9×10−21), IL18 (p = 6.8×10−13), LPA (p = 4.4×10−10), GGT1 (p = 1.5×10−7), SHBG (p = 3.1×10−7), CRP (p = 6.4×10−6) and IL1RN (p = 7.3×10−6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10−40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways., Author Summary One of the central dogmas of molecular genetics is that DNA is transcribed to RNA which is translated to protein and alterations to proteins can influence human diseases. Genome-wide association studies have recently revealed many new DNA variants that influence human diseases. To complement these efforts, several genome-wide studies have established that DNA variation influences mRNA expression levels. Loci influencing mRNA levels have been termed “eQTLs”. In this study we have performed the first genome-wide association study of the third piece in this jigsaw – the role of DNA variation in relation to protein levels, or “pQTLs”. We analysed 42 proteins measured in blood fractions from the InCHIANTI study. We identified eight cis effects including common variants in or near the IL6R, CCL4, IL18, LPA, GGT1, SHBG, CRP and IL1RN genes, all associated with blood levels of their respective protein products. Mechanisms implicated included altered transcription (GGT1) but also rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA) and variation in gene copy number (CCL4). Blood levels of many of these proteins are correlated with human diseases and the identification of “pQTLs” may in turn help our understanding of disease.

Published
2008

81. Genome-wide association and functional studies identify the DOT1L gene to be involved in cartilage thickness and hip osteoarthritis

Abstract

Hip osteoarthritis (HOA) is one of the most disabling and common joint disorders with a large genetic component that is, however, still ill-defined. To date, genome-wide association studies (GWAS) in osteoarthritis (OA) and specifically in HOA have yielded only few loci, which is partly explained by heterogeneity in the OA definition. Therefore, we here focused on radiographically measured joint-space width (JSW), a proxy for cartilage thickness and an important underlying intermediate trait for HOA. In a GWAS of 6,523 individuals on hip-JSW, we identified the G allele of rs12982744 on chromosome 19p13.3 to be associated with a 5% larger JSW (P = 4.8 × 10-10). The association was replicated in 4,442 individuals from three United Kingdom cohorts with an overall meta-analysis P value of 1.1 × 10-11. The SNP was also strongly associated with a 12% reduced risk for HOA (P = 1 × 10-4). The SNP is located in the DOT1L gene, which is an evolutionarily conserved histone methyltransferase, recently identified as a potentially dedicated enzyme for Wnt target-gene activation in leukemia. Immunohistochemical staining of the DOT1L prote

Published
2012
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82. VNTR polymorphism of the insulin gene and childhood overweight in a general population

Abstract

Objective: The VNTR polymorphism 5' of the insulin gene has been related to obesity in a previous study on children with early onset of severe obesity. Our purpose was to analyze the association between this polymorphism and adiposity variability in an unselected population of children and adolescents in northern France. Research Methods and Procedures: In 293 nuclear families from the Fleurbaix Laventie Ville Santé study, we genotyped the INS VNTR polymorphism in 431 children and adolescents (8 to 18 years of age) and their parents. Overweight was defined according to the international definition in both children and adults. A transmission disequilibrium test in families with an overweight offspring was performed. The prevalence of overweight was compared according to genotype. The effect of the genotype on BMI and waist circumference was tested with a linear regression model, adjusting for age, gender, and Tanner stage. Results: There was an undertransmission of class III alleles from heterozygous parents to their overweight offspring (p < 0.002). Overweight was associated with class I alleles in children and adolescents (12% I/I, I/III vs. 3% III/III; p < 0.08). Those with a class III/III genotype had a 1 kg/m2 lower mean BMI (p = 0.04) and 3 cm lower waist circumference (p = 0.02) than those bearing one or two class I alleles. No association of adiposity or obesity with class I alleles was found in parents. Discussion: INS VNTR polymorphism seems to contribute to differences in adiposity level in the general population of children and adolescents.

Published
2004

83. PhredEM: a phred-score-informed genotype-calling approach for next-generation sequencing studies.

Author

Liao P, Satten GA, and Hu YJ

Subjects
Algorithms, Databases, Genetic, Humans, Models, Genetic, Genomics methods, Genotype, High-Throughput Nucleotide Sequencing methods, Polymorphism, Single Nucleotide genetics, Sequence Analysis, DNA methods, Software
Abstract

A fundamental challenge in analyzing next-generation sequencing (NGS) data is to determine an individual's genotype accurately, as the accuracy of the inferred genotype is essential to downstream analyses. Correctly estimating the base-calling error rate is critical to accurate genotype calls. Phred scores that accompany each call can be used to decide which calls are reliable. Some genotype callers, such as GATK and SAMtools, directly calculate the base-calling error rates from phred scores or recalibrated base quality scores. Others, such as SeqEM, estimate error rates from the read data without using any quality scores. It is also a common quality control procedure to filter out reads with low phred scores. However, choosing an appropriate phred score threshold is problematic as a too high threshold may lose data, while a too low threshold may introduce errors. We propose a new likelihood-based genotype-calling approach that exploits all reads and estimates the per-base error rates by incorporating phred scores through a logistic regression model. The approach, which we call PhredEM, uses the expectation-maximization (EM) algorithm to obtain consistent estimates of genotype frequencies and logistic regression parameters. It also includes a simple, computationally efficient screening algorithm to identify loci that are estimated to be monomorphic, so that only loci estimated to be nonmonomorphic require application of the EM algorithm. Like GATK, PhredEM can be used together with a linkage-disequilibrium-based method such as Beagle, which can further improve genotype calling as a refinement step. We evaluate the performance of PhredEM using both simulated data and real sequencing data from the UK10K project and the 1000 Genomes project. The results demonstrate that PhredEM performs better than either GATK or SeqEM, and that PhredEM is an improved, robust, and widely applicable genotype-calling approach for NGS studies. The relevant software is freely available., (© 2017 WILEY PERIODICALS, INC.)

Published
2017
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84. A Common Variant in the MC1R Gene (p.V92M) is associated with Alzheimer's Disease Risk.

Author

Tell-Marti G, Puig-Butille JA, Potrony M, Plana E, Badenas C, Antonell A, Sanchez-Valle R, Molinuevo JL, Lleó A, Alcolea D, Fortea J, Fernández-Santiago R, Clarimón J, Lladó A, and Puig S

Subjects
Age of Onset, Aged, Alzheimer Disease cerebrospinal fluid, Apolipoprotein E4 genetics, Biomarkers cerebrospinal fluid, Case-Control Studies, Female, Genetic Association Studies, Humans, Male, Alzheimer Disease genetics, Genetic Predisposition to Disease, Receptor, Melanocortin, Type 1 genetics
Abstract

Despite the recent identification of some novel risk genes for Alzheimer's disease (AD), the genetic etiology of late-onset Alzheimer's disease (LOAD) remains largely unknown. The inclusion of these novel risk genes to the risk attributable to the APOE gene accounts for roughly half of the total genetic variance in LOAD. The evidence indicates that undiscovered genetic factors may contribute to AD susceptibility. In the present study, we sequenced the MC1R gene in 525 Spanish LOAD patients and in 160 controls. We observed that a common MC1R variant p.V92M (rs2228479), not related to pigmentation traits, was present in 72 (14%) patients and 15 (9%) controls and confers increased risk of developing LOAD (OR: 1.99, 95% CI: 1.08-3.64, p = 0.026), especially in those patients whose genetic risk could not be explained by APOE genotype. This association remains and even increased in the subset of 69 patients with typical AD cerebrospinal fluid profile (OR: 3.40 95% CI: 1.40-8.27, p = 0.007). We did not find an association between p.V92M and age of onset of AD. Further studies are necessary to elucidate the role of MC1R in brain cells through the different MC1R pathways.

Published
2017
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86. Tourette Syndrome: Bridging the Gap between Genetics and Biology.

Author

Richer P and Fernandez TV

Abstract

Tourette syndrome is a childhood neuropsychiatric disorder, which presents with disruptive motor and vocal tics. The disease also has a high comorbidity with obsessive-compulsive disorder and attention deficit hyperactivity disorder, which may further increase the distress experienced by patients. Current treatments act with varying efficacies in alleviating symptoms, as the underlying biology of the disease is not fully understood to provide precise therapeutic targets. Moreover, the genetic complexity of the disorder presents a substantial challenge to the identification of genetic alterations that contribute to the Tourette's phenotype. Nevertheless, genetic studies have suggested involvement of dopaminergic, serotonergic, glutamatergic, and histaminergic pathways in the pathophysiology of at least some cases. In addition, genetic overlaps with other neuropsychiatric disorders may point toward a shared biology. The findings that are emerging from genetic studies will allow researchers to piece together the underlying components of the disease, in the hopes that a deeper understanding of Tourette's can lead to improved treatments for those affected by it.

Published
2015
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87. A Novel Statistic for Global Association Testing Based on Penalized Regression.

Author

Austin E, Shen X, and Pan W

Subjects
Genetic Variation, Genotype, Humans, Hypertension diagnosis, Hypertension genetics, Linkage Disequilibrium, Logistic Models, Models, Genetic, Phenotype, Genetic Association Studies
Abstract

Natural genetic structures like genes may contain multiple variants that work as a group to determine a biologic outcome. The effect of rare variants, mutations occurring in less than 5% of samples, is hypothesized to be explained best as groups collectively associated with a biologic function. Therefore, it is important to develop powerful association tests to identify a true association between an outcome of interest and a group of variants, in particular a group with many rare variants. In this article we first delineate a novel penalized regression-based global test for the association between sets of variants and a disease phenotype. Next, we use Genetic Analysis Workshop 18 (GAW18) data to assess the power of the new global association test to capture a relationship between an aggregated group of variants and a simulated hypertension status. Rare variant only, common variant only, and combined variant groups are studied. The power values are compared to those obtained from eight well-regarded global tests (Score, Sum, SSU, SSUw, UminP, aSPU, aSPUw, and sequence kernel association test (SKAT)) that do not use penalized regression and a set of tests using either the SSU or score statistics and least absolute shrinkage and selection operator penalty (LASSO) logistic regression. Association testing of rare variants with our method was the top performer when there was low linkage disequilibrium (LD) between and within causal variants. This was similarly true when simultaneously testing rare and common variants in low LD scenarios. Finally, our method was able to provide meaningful variant-specific association information., (© 2015 WILEY PERIODICALS, INC.)

Published
2015
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88. A novel approach for the simultaneous analysis of common and rare variants in complex traits.

Author

Yuan A, Chen G, Zhou Y, Bentley A, and Rotimi C

Abstract

Genome-wide association studies (GWAS) have been successful in detecting common genetic variants underlying common traits and diseases. Despite the GWAS success stories, the percent trait variance explained by GWAS signals, the so called "missing heritability" has been, at best, modest. Also, the predictive power of common variants identified by GWAS has not been encouraging. Given these observations along with the fact that the effects of rare variants are often, by design, unaccounted for by GWAS and the availability of sequence data, there is a growing need for robust analytic approaches to evaluate the contribution of rare variants to common complex diseases. Here we propose a new method that enables the simultaneous analysis of the association between rare and common variants in disease etiology. We refer to this method as SCARVA (simultaneous common and rare variants analysis). SCARVA is simple to use and is efficient. We used SCARVA to analyze two independent real datasets to identify rare and common variants underlying variation in obesity among participants in the Africa America Diabetes Mellitus (AADM) study and plasma triglyceride levels in the Dallas Heart Study (DHS). We found common and rare variants associated with both traits, consistent with published results.

Published
2012
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