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8 results on '"Genetic Association Studies/methods"'

1. Digenic inheritance of human primary microcephaly delineates centrosomal and non-centrosomal pathways

Author

Cindy Badoer, Alain Verloes, Valérie Jacquemin, Camille Perazzolo, Marc Abramowicz, Judith Racapé, Isabelle Pirson, Marianne Rooman, Tom Lenaerts, Julie Soblet, Séverine Drunat, Sabine Costagliola, Frédérick Libert, Anne Lefort, Sarah Duerinckx, Sandrine Passemard, Laurence Desmyter, Viviane De Maertelaer, Yoann Vial, Annick Massart, Sofia Papadimitriou, Yann-Aël Le Borgne, Faculty of Sciences and Bioengineering Sciences, Electronics and Informatics, IR Academic Unit, Informatics and Applied Informatics, and Artificial Intelligence

Subjects
Primary microcephaly, Inheritance Patterns, Biology, digenic inheritance, ASPM, 03 medical and health sciences, Open Reading Frames, Animals, Centrosome/metabolism, Databases, Genetic, Genetic Association Studies/methods, Genetic Predisposition to Disease, Humans, Microcephaly/diagnosis, Microcephaly/genetics, Mutation, Phenotype, Signal Transduction, Exome Sequencing, Zebrafish, complex inheritance, exome sequencing, primary microcephaly, zebrafish, Genetics, Allele, Gene, Research Articles, Genetics (clinical), Exome sequencing, Genetic Association Studies, 030304 developmental biology, Centrosome, 0303 health sciences, 030305 genetics & heredity, biology.organism_classification, Digenic inheritance, Microcephaly, Research Article
Abstract

Primary microcephaly (PM) is characterized by a small head since birth and is vastly heterogeneous both genetically and phenotypically. While most cases are monogenic, genetic interactions between Aspm and Wdr62 have recently been described in a mouse model of PM. Here, we used two complementary, holistic in vivo approaches: high throughput DNA sequencing of multiple PM genes in human patients with PM, and genome‐edited zebrafish modeling for the digenic inheritance of PM. Exomes of patients with PM showed a significant burden of variants in 75 PM genes, that persisted after removing monogenic causes of PM (e.g., biallelic pathogenic variants in CEP152). This observation was replicated in an independent cohort of patients with PM, where a PM gene panel showed in addition that the burden was carried by six centrosomal genes. Allelic frequencies were consistent with digenic inheritance. In zebrafish, non‐centrosomal gene casc5 −/− produced a severe PM phenotype, that was not modified by centrosomal genes aspm or wdr62 invalidation. A digenic, quadriallelic PM phenotype was produced by aspm and wdr62. Our observations provide strong evidence for digenic inheritance of human PM, involving centrosomal genes. Absence of genetic interaction between casc5 and aspm or wdr62 further delineates centrosomal and non‐centrosomal pathways in PM., In a cohort of patients with primary microcephaly (PM), exome sequencing showed a significant burden of variants in PM genes, that persisted after removing monogenic causes of PM. The finding was confirmed in a replication cohort (not shown), and candidate centrosomal gene pairs were identified. Zebrafish genome editing produced a severe PM phenotype in casc5 −/− and no phenotype in aspm −/− or wdr62 −/− fishes. Zebrafish crosses displayed digenic interactions between centrosomal genes aspm and wdr62, and no interactions between non‐centrosomal gene casc5 and either aspm or wdr62, delineating centrosomal and non‐centrosomal pathways in PM. *p = .028.

Published
2020

2. 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

3. A genome-wide approach to children's aggressive behavior: The EAGLE consortium

Author

Nicholas J. Timpson, Michel G. Nivard, Craig E. Pennell, Harold Snieder, Gareth E. Davies, Christel M. Middeldorp, Fernando Rivadeneira, Ilkka Seppälä, Carla M. T. Tiesler, Susan M. Ring, Marie Standl, James J. Hudziak, Kelly S. Benke, Viara R. Mileva-Seitz, Fleur P. Velders, George Davey Smith, Christine Power, Alina Rodriguez, John P. Kemp, René Veenstra, Beate St Pourcain, Harald Grallert, Liisa Keltikangas-Järvinen, Maria M. Groen-Blokhuis, Elina Hyppönen, Irene Pappa, David M. Evans, Marian J. Bakermans-Kranenburg, Joachim Heinrich, Marie-Claude Geoffroy, Christian Hakulinen, Albertine J. Oldehinkel, Dorret I. Boomsma, Elisabeth Thiering, Paul Scheet, George McMahon, Ilja M. Nolte, Henning Tiemeier, Alana Cavadino, Ehsan Motazedi, Terho Lehtimäki, Olli T. Raitakari, Andrew J. O. Whitehouse, Life Course Epidemiology (LCE), Sociology/ICS, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Biological Psychology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, EMGO+ - Mental Health, Child and Adolescent Psychiatry / Psychology, Erasmus MC other, Epidemiology, Internal Medicine, Psychiatry, Pappa, Irene, St, Pourcain Beate, Benke, Kelly, Cavadino, Alana, Hypponen, Elina, and Tiemeier, Henning

Subjects
0301 basic medicine, Male, Netherlands Twin Register (NTR), Receptors, Vasopressin, Poison control, Vasopressin/genetics, Genetics, Behavioral/methods, 0302 clinical medicine, Surveys and Questionnaires, Receptors, Psychology, Early childhood, genome-wide complex trait analysis (GCTA), Child, Genetics (clinical), education.field_of_study, HERITABILITY, Genetic Predisposition to Disease/genetics, aggression, Public Health, Global Health, Social Medicine and Epidemiology, ASSOCIATION, Polymorphism, Single Nucleotide/genetics, Justice and Strong Institutions, Aggression, Psychiatry and Mental health, Conduct disorder, DUTCH TWINS, ADOLESCENCE, Meta-analysis, Female, medicine.symptom, Single Nucleotide/genetics, Clinical psychology, SDG 16 - Peace, Adolescent, Population, Aggression/physiology, Single-nucleotide polymorphism, Genetics, Behavioral, Biology, Polymorphism, Single Nucleotide, GENETIC ARCHITECTURE, 03 medical and health sciences, Cellular and Molecular Neuroscience, medicine, Genetics, Humans, Genetic Predisposition to Disease, Polymorphism, EARLY-CHILDHOOD, education, Receptors, Vasopressin/genetics, Genetic Association Studies, childhood, Behavioral/methods, Behavior, Psykologi, STABILITY, ta1184, SDG 16 - Peace, Justice and Strong Institutions, Genetic Variation, ADULTS, medicine.disease, Genetic architecture, population-based, meta-analysis, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Genetic Association Studies/methods, 030104 developmental biology, TISSUE, CONDUCT DISORDER, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of aggressive behavior in children. We analyzed data from nine population-based studies and assessed aggressive behavior using well-validated parent-reported questionnaires. This is the largest sample exploring children's aggressive behavior to date (N = 18,988), with measures in two developmental stages (N = 15,668 early childhood and N = 16,311 middle childhood/early adolescence). First, we estimated the additive genetic variance of children's aggressive behavior based on genome-wide SNP information, using genome-wide complex trait analysis (GCTA). Second, genetic associations within each study were assessed using a quasi-Poisson regression approach, capturing the highly right-skewed distribution of aggressive behavior. Third, we performed meta-analyses of genome-wide associations for both the total age-mixed sample and the two developmental stages. Finally, we performed a gene-based test using the summary statistics of the total sample. GCTA quantified variance tagged by common SNPs (10-54%). The meta-analysis of the total sample identified one region in chromosome 2 (2p12) at near genome-wide significance (top SNP rs11126630, P = 5.30 x 10(-8)). The separate meta-analyses of the two developmental stages revealed suggestive evidence of association at the same locus. The gene-based analysis indicated association of variation within AVPR1A with aggressive behavior. We conclude that common variants at 2p12 show suggestive evidence for association with childhood aggression. Replication of these initial findings is needed, and further studies should clarify its biological meaning. (C) 2015 Wiley Periodicals, Inc.

Published
2016

4. Evaluation and application of summary statistic imputation to discover new height-associated loci

Author

Aaron McDaid, Zoltán Kutalik, and Sina Rüeger

Subjects
0301 basic medicine, Cancer Research, Linkage disequilibrium, Heredity, Genomics Statistics, Computer science, Algorithms, Biostatistics/methods, Exome/genetics, Gene Frequency, Genetic Association Studies/methods, Genome-Wide Association Study/methods, Genotype, Humans, Linkage Disequilibrium, Oligonucleotide Array Sequence Analysis, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci/genetics, Reproducibility of Results, Social Sciences, Genome-wide association study, QH426-470, computer.software_genre, Mathematical and Statistical Techniques, Sociology, Consortia, Statistics, Exome, Imputation (statistics), International HapMap Project, Genetics (clinical), Genomics, Genetic Mapping, Physical Sciences, Data mining, Statistics (Mathematics), Research Article, Genotyping, Quantitative Trait Loci, Correlation and dependence, Variant Genotypes, Biology, Biostatistics, Research and Analysis Methods, Statistical power, 03 medical and health sciences, Genome-Wide Association Studies, Genetics, Statistical Methods, Molecular Biology Techniques, Molecular Biology, Ecology, Evolution, Behavior and Systematics, Alleles, Genetic Association Studies, Biology and Life Sciences, Computational Biology, Human Genetics, Heritability, Genome Analysis, Summary statistics, Minor allele frequency, 030104 developmental biology, Sample size determination, Genetic Loci, computer, Imputation (genetics), Mathematics, Meta-Analysis, Genome-Wide Association Study
Abstract

As most of the heritability of complex traits is attributed to common and low frequency genetic variants, imputing them by combining genotyping chips and large sequenced reference panels is the most cost-effective approach to discover the genetic basis of these traits. Association summary statistics from genome-wide meta-analyses are available for hundreds of traits. Updating these to ever-increasing reference panels is very cumbersome as it requires reimputation of the genetic data, rerunning the association scan, and meta-analysing the results. A much more efficient method is to directly impute the summary statistics, termed as summary statistics imputation, which we improved to accommodate variable sample size across SNVs. Its performance relative to genotype imputation and practical utility has not yet been fully investigated. To this end, we compared the two approaches on real (genotyped and imputed) data from 120K samples from the UK Biobank and show that, genotype imputation boasts a 3- to 5-fold lower root-mean-square error, and better distinguishes true associations from null ones: We observed the largest differences in power for variants with low minor allele frequency and low imputation quality. For fixed false positive rates of 0.001, 0.01, 0.05, using summary statistics imputation yielded a decrease in statistical power by 9, 43 and 35%, respectively. To test its capacity to discover novel associations, we applied summary statistics imputation to the GIANT height meta-analysis summary statistics covering HapMap variants, and identified 34 novel loci, 19 of which replicated using data in the UK Biobank. Additionally, we successfully replicated 55 out of the 111 variants published in an exome chip study. Our study demonstrates that summary statistics imputation is a very efficient and cost-effective way to identify and fine-map trait-associated loci. Moreover, the ability to impute summary statistics is important for follow-up analyses, such as Mendelian randomisation or LD-score regression., Author summary Genome-wide association studies (GWASs) quantify the effect of genetic variants and traits, such as height. Such estimates are called association summary statistics and are typically publicly shared through publication. Typically, GWASs are carried out by genotyping ∼ 500′000 SNVs for each individual which are then combined with sequenced reference panels to infer untyped SNVs in each’ individuals genome. This process of genotype imputation is resource intensive and can therefore be a limitation when combining many GWASs. An alternative approach is to bypass the use of individual data and directly impute summary statistics. In our work we compare the performance of summary statistics imputation to genotype imputation. We observe that genotype imputation shows a 3- to 5-fold lower RMSE compared to summary statistics imputation, as well as a better capability to distinguish true associations from null results. Furthermore, we demonstrate the potential of summary statistics imputation by presenting 34 novel height-associated loci, 19 of which were confirmed in UK Biobank. Our study demonstrates that given current reference panels, summary statistics imputation is a very efficient and cost-effective way to identify common or low-frequency trait-associated loci.

Published
2018

5. Evaluating the causal relation of ApoA-IV with disease-related traits - A bidirectional two-sample mendelian randomization study

Author

Mack, S., Coassin, S., Vaucher, J., Kronenberg, F., Lamina, C., Rueedi, R., Yousri, N.A., Seppälä, I., ApoA-IV-GWAS Constortium (Gieger, C.), Schönherr, S., Forer, L., Erhart, G., Kollerits, B., Marques-Vidal, P., ApoA-IV-GWAS Constortium (Müller-Nurasyid, M.), Waeber, G., Bergmann, S., Dähnhardt, D., Stöckl, A., Kiechl, S., Raitakari, O.T., Kähönen, M., Willeit, J., Kedenko, L., Paulweber, B., ApoA-IV-GWAS Constortium (Peters, A.), ApoA-IV-GWAS Constortium (Meitinger, T.), ApoA-IV-GWAS Constortium (Strauch, K.), Lehtimäki, T., Hunt, S.C., Vollenweider, P., ApoA-IV-GWAS Consortium, Rueedi, R., Yousri, N.A., Seppälä, I., Gieger, C., Schönherr, S., Forer, L., Erhart, G., Kollerits, B., Marques-Vidal, P., Müller-Nurasyid, M., Waeber, G., Bergmann, S., Dähnhardt, D., Stöckl, A., Kiechl, S., Raitakari, O.T., Kähönen, M., Willeit, J., Kedenko, L., Paulweber, B., Peters, A., Meitinger, T., Strauch, K., Lehtimäki, T., Hunt, S.C., and Vollenweider, P.

Subjects
Blood Glucose, Fasting, Mendelian Randomization Analysis, Lipids, Polymorphism, Single Nucleotide, Article, Phenotype, Quantitative Trait, Heritable, Humans, Genetic Predisposition to Disease, lipids (amino acids, peptides, and proteins), Adiposity, Apolipoproteins A/genetics, Apolipoproteins A/metabolism, Biomarkers, Genetic Association Studies/methods, Glomerular Filtration Rate, Lipids/blood, Apolipoproteins A, Genetic Association Studies
Abstract

Apolipoprotein A-IV (apoA-IV) has been observed to be associated with lipids, kidney function, adiposity- and diabetes-related parameters. To assess the causal relationship of apoA-IV with these phenotypes, we conducted bidirectional Mendelian randomization (MR) analyses using publicly available summary-level datasets from GWAS consortia on apoA-IV concentrations (n = 13,813), kidney function (estimated glomerular filtration rate (eGFR), n = 133,413), lipid traits (HDL cholesterol, LDL cholesterol, triglycerides, n = 188,577), adiposity-related traits (body-mass-index (n = 322,206), waist-hip-ratio (n = 210,088)) and fasting glucose (n = 133,010). Main analyses consisted in inverse-variance weighted and multivariable MR, whereas MR-Egger regression and weighted median estimation were used as sensitivity analyses. We found that eGFR is likely to be causal on apoA-IV concentrations (53 SNPs; causal effect estimate per 1-SD increase in eGFR = -0.39; 95% CI = [-0.54, -0.24]; p-value = 2.4e-07). Triglyceride concentrations were also causally associated with apoA-IV concentrations (40 SNPs; causal effect estimate per 1-SD increase in triglycerides = -0.06; 95% CI = [-0.08, -0.04] ; p-value = 4.8e-07), independently of HDL-C and LDL-C concentrations (causal effect estimate from multivariable MR = -0.06; 95% CI = [-0.10, -0.02]; p-value = 0.0014). Evaluating the inverse direction of causality revealed a possible causal association of apoA-IV on HDL-cholesterol (2 SNPs; causal effect estimate per one percent increase in apoA-IV = -0.40; 95% CI = [-0.60, -0.21] ; p-value = 5.5e-05).

Published
2017

6. Exome-wide association study of plasma lipids in >300,000 individuals

Author

Asif Rasheed, Mary F. Feitosa, Ian J. Deary, Melissa E. Garcia, Danish Saleheen, Christian Gieger, Andrea Maschio, Lia E. Bang, Cliona Molony, Ivan Brandslund, Dan M. Roden, Ian Ford, Paul M. Ridker, Alisa K. Manning, Giorgio Pistis, Anette Varbo, Alexander P. Reiner, Kathleen Stirrups, David C. Liewald, Tim D. Spector, Paul W. Franks, Cristen J. Willer, Daniel I. Chasman, Jean Ferrières, Vilmundur Gudnason, Tapani Ebeling, Neil Poulter, Magdalena Zoledziewska, Elizabeth K. Speliotes, Eleftheria Zeggini, Megan L. Grove, Hua Tang, Stavroula Kanoni, Peter Weeke, Panos Deloukas, Daniel J. Rader, Amit Khera, Serena Sanna, Dorota Pasko, Gina M. Peloso, Charles Kooperberg, Suthesh Sivapalaratnam, Natalie R. van Zuydam, Christian M. Shaffer, Fredrik Karpe, Naveed Sattar, Pieter Muntendam, Ruth J. F. Loos, Eric Boerwinkle, Wei Gao, Mark J. Caulfield, Matt Neville, Sangeetha Somayajula, Olle Melander, Hayato Tada, Jose M. Ordovas, He Zhang, John D. Rioux, Michael Boehnke, Erwin P. Bottinger, Franco Giulianini, Martina Müller-Nurasyid, Stella Trompet, Connor A. Emdin, Andrew P. Morris, Johanne Marie Justesen, Alan R. Tall, Kari Kuulasmaa, Adam S. Butterworth, Marie-Pierre Dubé, Dajiang J. Liu, Paul L. Auer, Jennifer E. Huffman, Usman Baber, John Danesh, Xiao Wang, Anna F. Dominiczak, Jarmo Virtamo, John M. Starr, Ozren Polasek, Gonçalo R. Abecasis, Timo A. Lakka, Stephen S. Rich, Marco M Ferrario, Marju Orho-Melander, Xueling Sim, Dominique Arveiler, Dermot F. Reilly, Torsten Lauritzen, Gudny Eiriksdottir, Marit E. Jørgensen, Anubha Mahajan, Colin N. A. Palmer, Veikko Salomaa, Nicholas J. Wareham, Dewan S. Alam, Anne Tybjærg-Hansen, Ellen M. Schmidt, Y. Eugene Chen, Heather M. Stringham, Bruce M. Psaty, Christie M. Ballantyne, Nan Wang, Joshua C. Bis, Myriam Fornage, Neil S Zheng, Kristian Hveem, Praveen Surendran, Yingchang Lu, Peter S. Sever, James B. Meigs, Heikki A. Koistinen, Charlotta Pisinger, Tibor V. Varga, Yii-Der Ida Chen, Konstantin Strauch, Timothy M. Frayling, Patricia B. Munroe, Albert V. Smith, Ruth Frikke-Schmidt, Lorraine Southam, Frida Renström, Philippe Amouyel, Nicholas G. D. Masca, Alexessander Couto Alves, Xiangfeng Lu, Andres Metspalu, Anne Langsted, Joanna M. M. Howson, Tamara B. Harris, Leif Groop, Chad A. Cowan, Cramer Christensen, Audrey Y. Chu, Markku Laakso, Torben Hansen, Li-An Lin, John C. Chambers, Jonas B. Nielsen, Niels Grarup, Neil R. Robertson, Kiran Musunuru, Joshua S. Weinstock, Morris J. Brown, Jean-Claude Tardif, Gorm B. Jensen, Jerome I. Rotter, Harald Grallert, Yan Zhang, Kerrin S. Small, Nathan O. Stitziel, Fabio Busonero, Jennifer Wessel, Themistocles L. Assimes, Lenore J. Launer, Lars G. Fritsche, Mark O. Goodarzi, Peter W.F. Wilson, Sekar Kathiresan, Philippe M. Frossard, Emanuele Di Angelantonio, Yanhua Zhou, James G. Wilson, Frank Kee, Scott M. Damrauer, Weihua Zhang, Gail Davies, Oluf Pedersen, Sune F. Nielsen, Alanna C. Morrison, Raquel S. Sevilla, Helen R. Warren, Johanna Kuusisto, Hanieh Yaghootkar, Sandosh Padmanabhan, Philip S. Tsao, Caroline Hayward, Tõnu Esko, Ming Xu, Anders Mälarstig, Anne U. Jackson, Eirini Marouli, Jette Bork-Jensen, Robin Young, C.J. O'Donnell, Yong Huo, Melanie Waldenberger, Jaspal S. Kooner, Pekka Mäntyselkä, Marjo-Riitta Järvelin, Santhi K. Ganesh, Annette Peters, L. Adrienne Cupples, Wei Zhou, Derek Klarin, Markus Perola, Francesco Cucca, Allan Linneberg, Mark I. McCarthy, Joel N. Hirschhorn, Pia R. Kamstrup, Nilesh J. Samani, J. Wouter Jukema, Valentin Fuster, Claudia Langenberg, Roxana Mehran, Børge G. Nordestgaard, Jaakko Tuomilehto, Reedik Mägi, Blair H. Smith, Johanna Jakobsdottir, Marianne Benn, Kent D. Taylor, Ani Manichaikul, Igor Rudan, Aniruddh P. Patel, Joshua C. Denny, Oddgeir L. Holmen, John M. C. Connell, Robert A. Scott, Haojie Yu, Rajiv Chowdhury, Sehrish Jabeen, Antonella Mulas, Aliki-Eleni Farmaki, Rainer Rauramaa, George Dedoussis, Vascular Medicine, Nielsen, Jonas B [0000-0002-6654-2852], Kathiresan, Sekar [0000-0002-6724-032X], Apollo - University of Cambridge Repository, and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)

Subjects
0301 basic medicine, Exome/genetics, Genome-wide association study, Type 2 diabetes, Coronary Artery Disease, 030204 cardiovascular system & hematology, Bioinformatics, Charge Diabetes Working Group, Macular Degeneration, chemistry.chemical_compound, 0302 clinical medicine, Risk Factors, Exome, Macular Degeneration/blood, Genetics & Heredity, Genetic Predisposition to Disease/genetics, CLONAL HEMATOPOIESIS, 11 Medical And Health Sciences, CODING-SEQUENCE VARIANTS, Lipids, Phenotype, CARDIOVASCULAR-DISEASE, VA Million Veteran Program, lipids (amino acids, peptides, and proteins), GOLD Consortium, LOW-FREQUENCY, EPIC-InterAct Consortium, Diabetes Mellitus, Type 2/blood, Life Sciences & Biomedicine, Type 2, medicine.medical_specialty, Genotype, APOBEC-1 COMPLEMENTATION FACTOR, Biology, Lower risk, Article, EPIC-CVD Consortium, GENETIC ARCHITECTURE, 03 medical and health sciences, Coronary Artery Disease/blood, Diabetes mellitus, Internal medicine, Genetics, medicine, Diabetes Mellitus, Journal Article, Lipolysis, Humans, Genetic Predisposition to Disease, Allele, TYROSINE KINASE JAK2, Genetic Association Studies, B MESSENGER-RNA, Science & Technology, MACULAR DEGENERATION, MYELOPROLIFERATIVE DISORDERS, Cholesterol, Lipids/blood, Genetic Variation, 06 Biological Sciences, medicine.disease, cardiovascular diseases, genome wide association studies, Genetic Association Studies/methods, 030104 developmental biology, Endocrinology, chemistry, Diabetes Mellitus, Type 2, TM6SF2, Developmental Biology
Abstract

We screened DNA sequence variants on an exome-focused genotyping array in >300,000 participants with replication in >280,000 participants and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice revealed lipid changes consistent with the human data. We utilized mapped variants to address four clinically relevant questions and found the following: (1) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease; (2) outside of the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (3) only some mechanisms of lowering LDL-C seemed to increase risk for type 2 diabetes; and (4) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (e.g., TM6SF2, PNPLA3) tracked with higher liver fat, higher risk for type 2 diabetes, and lower risk for coronary artery disease whereas TG-lowering alleles involved in peripheral lipolysis (e.g., LPL, ANGPTL4) had no effect on liver fat but lowered risks for both type 2 diabetes and coronary artery disease.

Published
2017

7. A Comprehensive Analysis of Choroideremia: From Genetic Characterization to Clinical Practice

Author

María José Trujillo-Tiebas, Blanca Garcia-Sandoval, Luciana Rodrigues-Jacy da Silva, Cristina Villaverde, Simona Torriano, Carlo Rivolta, Almudena Avila-Fernandez, Maria Isabel Lopez-Molina, Olga Zurita, Marta Corton, Noelia Sanchez-Bolivar, Raquel Perez-Carro, Isabel Lorda, Rocío Sánchez-Alcudia, Ascension Gimenez, Miguel Angel Lopez-Martinez, Maria Garcia-Hoyos, Fiona Blanco-Kelly, Carmen Ayuso, Vasiliki Kalatzis, and Rosa Riveiro-Alvarez

Subjects
0301 basic medicine, Male, Pigments, DNA Mutational Analysis, lcsh:Medicine, medicine.disease_cause, Pathology and Laboratory Medicine, Choroideremia, Exon, 0302 clinical medicine, Genotype, Medicine and Health Sciences, Deletions, Frameshift Mutation, lcsh:Science, Genetics, Mutation, Multidisciplinary, Chromosome Biology, Nonsense Mutation, Exons, Phenotype, 3. Good health, Pedigree, Chromosomal Aberrations, Deletion Mutation, Physical Sciences, Female, Research Article, Nonsense mutation, Materials Science, Biology, Research and Analysis Methods, Frameshift mutation, 03 medical and health sciences, Signs and Symptoms, Diagnostic Medicine, medicine, Humans, Molecular Biology Techniques, Sequencing Techniques, Molecular Biology, Genetic Association Studies, Materials by Attribute, Adaptor Proteins, Signal Transducing, Evolutionary Biology, Alkyl and Aryl Transferases, Population Biology, Haplotype, lcsh:R, Biology and Life Sciences, Cell Biology, medicine.disease, Direct Sequencing, 030104 developmental biology, Haplotypes, 030221 ophthalmology & optometry, lcsh:Q, Atrophy, Adaptor Proteins, Signal Transducing/genetics, Alkyl and Aryl Transferases/genetics, Choroideremia/genetics, DNA Mutational Analysis/methods, Exons/genetics, Genetic Association Studies/methods, Haplotypes/genetics, Mutation/genetics, Population Genetics
Abstract

Choroideremia (CHM) is a rare X-linked disease leading to progressive retinal degeneration resulting in blindness. The disorder is caused by mutations in the CHM gene encoding REP-1 protein, an essential component of the Rab geranylgeranyltransferase (GGTase) complex. In the present study, we evaluated a multi-technique analysis algorithm to describe the mutational spectrum identified in a large cohort of cases and further correlate CHM variants with phenotypic characteristics and biochemical defects of choroideremia patients. Molecular genetic testing led to the characterization of 36 out of 45 unrelated CHM families (80%), allowing the clinical reclassification of four CHM families. Haplotype reconstruction showed independent origins for the recurrent p.Arg293* and p.Lys178Argfs*5 mutations, suggesting the presence of hotspots in CHM, as well as the identification of two different unrelated events involving exon 9 deletion. No certain genotype-phenotype correlation could be established. Furthermore, all the patients´ fibroblasts analyzed presented significantly increased levels of unprenylated Rabs proteins compared to control cells; however, this was not related to the genotype. This research demonstrates the major potential of the algorithm proposed for diagnosis. Our data enhance the importance of establish a differential diagnosis with other retinal dystrophies, supporting the idea of an underestimated prevalence of choroideremia. Moreover, they suggested that the severity of the disorder cannot be exclusively explained by the genotype.

Published
2016

8. A multicenter study of glucocerebrosidase mutations in dementia with Lewy bodies

Author

Tatiana Foroud, Alexandra Durr, Andrew B. Singleton, Melanie A. Knight, Karen Marder, Bernardino Ghetti, Ian G. McKeith, Elvira Valeria De Marco, Sandra E. Black, Patrick Cras, Tyra G. Wolfsberg, Benoit I. Giasson, Claudia Landazabal, William C. Nichols, Jessie Theuns, Jose Bras, Grazia Annesi, Ellen Sidransky, John Hardy, Jenny Harris, Stephan Klebe, Nahid Tayebi, Una-Marie Sheerin, Nicola Halliwell, Glenda M. Halliday, Howard I. Hurtig, John Q. Trojanowski, Lawrence S. Honig, Yvonne S Davidson, Suzanne Lesage, Daniela Berg, Aldo Quattrone, Christine Van Broeckhoven, Kathrin Brockmann, Alexis Brice, David M. A. Mann, Thomas Gasser, Patrick F. Chinnery, Julie S. Snowden, David Crosiers, Walter Maetzler, Linda Gibbons, Mario Masellis, Marzena Kurzawa-Akanbi, Fabiana Novellino, Ekaterina Rogaeva, Mike A. Nalls, Stuart Pickering-Brown, Charles Duyckaerts, Lorraine N. Clark, Nathan Pankratz, Margaux F. Keller, Christopher Morris, Peter Paul De Deyn, Grisel Lopez, Raquel Duran, Sebastiaan Engelborghs, Juan M. Bilbao, Physiotherapy, Human Physiology and Anatomy, Clinical sciences, Neurology, Faculteit Medische Wetenschappen/UMCG, and Molecular Neuroscience and Ageing Research (MOLAR)

Subjects
Male, Pathology, ALPHA-SYNUCLEIN, mutations in glucocerebrosidase (GBA1), methods [Genetic Association Studies], SUSCEPTIBILITY, genetics [Glucosylceramidase], GAUCHER-DISEASE, 0302 clinical medicine, PARKINSONS-DISEASE, genetics [Lewy Body Disease], BODY DISORDERS, Risk Factors, risk factors, Lewy Body Disease/diagnosis, Aged, 80 and over, Medicine(all), 0303 health sciences, Middle Aged, 3. Good health, epidemiology [Lewy Body Disease], CONFER, Meta-analysis, Glucosylceramidase/genetics, Glucosylceramidase, Female, diagnosis [Lewy Body Disease], Lewy Body Disease, medicine.medical_specialty, Genotype, Mutation/genetics, genetics [Mutation], Case-control studies, Lewy body disorders, 03 medical and health sciences, RISK-FACTOR, Internal medicine, mental disorders, medicine, Dementia, Humans, ddc:610, Risk factor, Biology, Genetic Association Studies, 030304 developmental biology, Aged, risk for Parkinson disease (PD), Lewy body, business.industry, Dementia with Lewy bodies, Case-control study, Odds ratio, medicine.disease, GENE, PATHOLOGY, Genetic Association Studies/methods, GBA MUTATIONS, Case-Control Studies, Mutation, Human medicine, Neurology (clinical), business, aged, 80 and over, Glucocerebrosidase, 030217 neurology & neurosurgery
Abstract

Importance: While mutations in glucocerebrosidase (GBA1) are associated with an increased risk for Parkinson disease (PD), it is important to establish whether such mutations are also a common risk factor for other Lewy body disorders.Objective: To establish whether GBA1 mutations are a risk factor for dementia with Lewy bodies (DLB).Design: We compared genotype data on patients and controls from 11 centers. Data concerning demographics, age at onset, disease duration, and clinical and pathological features were collected when available. We conducted pooled analyses using logistic regression to investigate GBA1 mutation carrier status as predicting DLB or PD with dementia status, using common control subjects as a reference group. Random-effects meta-analyses were conducted to account for additional heterogeneity.Setting: Eleven centers from sites around the world performing genotyping.Participants: Seven hundred twenty-one cases met diagnostic criteria for DLB and 151 had PD with dementia. We compared these cases with 1962 controls from the same centers matched for age, sex, and ethnicity.Main Outcome Measures: Frequency of GBA1 mutations in cases and controls.Results: We found a significant association between GBA1 mutation carrier status and DLB, with an odds ratio of 8.28 (95% CI, 4.78-14.88). The odds ratio for PD with dementia was 6.48 (95% CI, 2.53-15.37). The mean age at diagnosis of DLB was earlier in GBA1 mutation carriers than in noncarriers (63.5 vs 68.9 years; P Conclusions and Relevance: Mutations in GBA1 are a significant risk factor for DLB. GBA1 mutations likely play an even larger role in the genetic etiology of DLB than in PD, providing insight into the role of glucocerebrosidase in Lewy body disease.

Published
2013

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