Person: Lyon, Helen N.
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Publication The Association of a SNP Upstream of INSIG2 with Body Mass Index is Reproduced in Several but Not All Cohorts
(Public Library of Science, 2007) Emilsson, Valur; Hinney, Anke; Heid, Iris M; Zhu, Xiaofeng; Thorleifsson, Gudmar; Gunnarsdottir, Steinunn; Walters, G. Bragi; Thorsteinsdottir, Unnur; Kong, Augustine; Gulcher, Jeffrey; Nguyen, Thuy Trang; Scherag, André; Pfeufer, Arne; Meitinger, Thomas; Brönner, Günter; Rief, Winfried; Soto-Quiros, Manuel E; Avila, Lydiana; Groop, Leif; Tuomi, Tiinamaija; Isomaa, Bo; Bengtsson, Kristina; Butler, Johannah L; Vollmert, Caren; Celedón, Juan C; Wichmann, H. Erich; Hebebrand, Johannes; Stefansson, Kari; Abecasis, Gonçalo; Lyon, Helen N.; Lasky-Su, Jessica; Klanderman, Barbara; Raby, Benjamin; Silverman, Edwin; Weiss, Scott; Laird, Nan; Ding, Xiao; Cooper, Richard S; Fox, Caroline; O'Donnell, Christopher; Lange, Christoph; Hirschhorn, JoelA SNP upstream of the INSIG2 gene, rs7566605, was recently found to be associated with obesity as measured by body mass index (BMI) by Herbert and colleagues. The association between increased BMI and homozygosity for the minor allele was first observed in data from a genome-wide association scan of 86,604 SNPs in 923 related individuals from the Framingham Heart Study offspring cohort. The association was reproduced in four additional cohorts, but was not seen in a fifth cohort. To further assess the general reproducibility of this association, we genotyped rs7566605 in nine large cohorts from eight populations across multiple ethnicities (total n = 16,969). We tested this variant for association with BMI in each sample under a recessive model using family-based, population-based, and case-control designs. We observed a significant (p < 0.05) association in five cohorts but saw no association in three other cohorts. There was variability in the strength of association evidence across examination cycles in longitudinal data from unrelated individuals in the Framingham Heart Study Offspring cohort. A combined analysis revealed significant independent validation of this association in both unrelated (p = 0.046) and family-based (p = 0.004) samples. The estimated risk conferred by this allele is small, and could easily be masked by small sample size, population stratification, or other confounders. These validation studies suggest that the original association is less likely to be spurious, but the failure to observe an association in every data set suggests that the effect of SNP rs7566605 on BMI may be heterogeneous across population samples.
Publication Meta-Analysis of the INSIG2 Association with Obesity Including 74,345 Individuals: Does Heterogeneity of Estimates Relate to Study Design?
(Public Library of Science, 2009) Heid, Iris M.; Huth, Cornelia; Loos, Ruth J. F.; Kronenberg, Florian; Adamkova, Vera; Anand, Sonia S.; Ardlie, Kristin; Biebermann, Heike; Bjerregaard, Peter; Boeing, Heiner; Bouchard, Claude; Ciullo, Marina; Cooper, Jackie A.; Corella, Dolores; Dina, Christian; Engert, James C.; Fisher, Eva; Francès, Francesc; Froguel, Philippe; Hebebrand, Johannes; Hegele, Robert A.; Hinney, Anke; Hoehe, Margret R.; Hubacek, Jaroslav A.; Humphries, Steve E.; Hunt, Steven C.; Illig, Thomas; Järvelin, Marjo-Riita; Kaakinen, Marika; Kollerits, Barbara; Krude, Heiko; Kumar, Jitender; Lange, Leslie A.; Langer, Birgit; Li, Shengxu; Luchner, Andreas; Meyre, David; Mohlke, Karen L.; Mooser, Vincent; Nebel, Almut; Nguyen, Thuy Trang; Paulweber, Bernhard; Perusse, Louis; Rankinen, Tuomo; Rosskopf, Dieter; Schreiber, Stefan; Sengupta, Shantanu; Sorice, Rossella; Suk, Anita; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Völzke, Henry; Vimaleswaran, Karani S.; Wareham, Nicholas J.; Waterworth, Dawn; Yusuf, Salim; Lindgren, Cecilia; McCarthy, Mark I.; Wichmann, H.-Erich; Allison, David B.; Hu, Frank; Qi, Lu; Lyon, Helen N.; Lange, Christoph; Hirschhorn, Joel; Laird, NanThe INSIG2 rs7566605 polymorphism was identified for obesity (BMI≥30 kg/m2) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies with subjects selected for conditions related to a better health status (‘healthy population’, HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-value = 0.27). The I2 measure of 41% (p-value = 0.015) indicated between-study heterogeneity. Restricting to GP studies resulted in a declined I2 measure of 11% (p-value = 0.33) and an OR of 1.10 (p-value = 0.015). Regarding the five hypotheses, our data showed (a) some difference between GP and HP studies (p-value = 0.012) and (b) an association in extreme comparisons (BMI≥32.5, 35.0, 37.5, 40.0 kg/m2 versus BMI less than;25 kg/m2) yielding ORs of 1.16, 1.18, 1.22, or 1.27 (p-values 0.001 to 0.003), which was also underscored by significantly increased CC-genotype frequencies across BMI categories (10.4% to 12.5%, p-value for trend = 0.0002). We did not find evidence for differential ORs (c) among studies with higher than average obesity prevalence compared to lower, (d) among studies with BMI assessment after the year 2000 compared to those before, or (e) among studies from older populations compared to younger. Analysis of non-Caucasian adults (n = 4889) or children (n = 3243) yielded ORs of 1.01 (p-value = 0.94) or 1.15 (p-value = 0.22), respectively. There was no evidence for overall association of the rs7566605 polymorphism with obesity. Our data suggested an association with extreme degrees of obesity, and consequently heterogeneous effects from different study designs may mask an underlying association when unaccounted for. The importance of study design might be under-recognized in gene discovery and association replication so far.
Publication Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution
(Public Library of Science, 2009) Lindgren, Cecilia M.; Heid, Iris M.; Randall, Joshua C.; Lamina, Claudia; Steinthorsdottir, Valgerdur; Speliotes, Elizabeth K.; Thorleifsson, Gudmar; Willer, Cristen J.; Herrera, Blanca M.; Jackson, Anne U.; Lim, Noha; Scheet, Paul; Soranzo, Nicole; Amin, Najaf; Aulchenko, Yurii S.; Chambers, John C.; Drong, Alexander; Luan, Jian'an; Rivadeneira, Fernando; Sanna, Serena; Timpson, Nicholas J.; Zillikens, M. Carola; Almgren, Peter; Bandinelli, Stefania; Bennett, Amanda J.; Bergman, Richard N.; Bonnycastle, Lori L.; Bumpstead, Suzannah J.; Chanock, Stephen J.; Cherkas, Lynn; Chines, Peter; Coin, Lachlan; Cooper, Cyrus; Crawford, Gabriel; Doering, Angela; Dominiczak, Anna; Doney, Alex S. F.; Ebrahim, Shah; Elliott, Paul; Erdos, Michael R.; Estrada, Karol; Ferrucci, Luigi; Fischer, Guido; Forouhi, Nita G.; Gieger, Christian; Grallert, Harald; Groves, Christopher J.; Grundy, Scott; Guiducci, Candace; Hadley, David; Hamsten, Anders; Havulinna, Aki S.; Holle, Rolf; Holloway, John W.; Illig, Thomas; Isomaa, Bo; Jacobs, Leonie C.; Jameson, Karen; Jousilahti, Pekka; Karpe, Fredrik; Kuusisto, Johanna; Laitinen, Jaana; Lathrop, G. Mark; Lawlor, Debbie A.; Mangino, Massimo; McArdle, Wendy L.; Meitinger, Thomas; Morken, Mario A.; Morris, Andrew P.; Munroe, Patricia; Narisu, Narisu; Nordström, Anna; Nordström, Peter; Oostra, Ben A.; Palmer, Colin N. A.; Payne, Felicity; Peden, John F.; Prokopenko, Inga; Renström, Frida; Ruokonen, Aimo; Salomaa, Veikko; Sandhu, Manjinder S.; Scuteri, Angelo; Silander, Kaisa; Song, Kijoung; Stringham, Heather M.; Swift, Amy J.; Tuomi, Tiinamaija; Uda, Manuela; Vollenweider, Peter; Waeber, Gerard; Wallace, Chris; Walters, G. Bragi; Weedon, Michael N.; Witteman, Jacqueline C. M.; Zhang, Cuilin; Zhang, Weihua; Caulfield, Mark J.; Collins, Francis S.; Davey Smith, George; Day, Ian N. M.; Franks, Paul W.; Hattersley, Andrew T.; Jarvelin, Marjo-Riitta; Kong, Augustine; Kooner, Jaspal S.; Laakso, Markku; Lakatta, Edward; Mooser, Vincent; Morris, Andrew D.; Peltonen, Leena; Samani, Nilesh J.; Spector, Timothy D.; Strachan, David P.; Tanaka, Toshiko; Tuomilehto, Jaakko; Uitterlinden, André G.; van Duijn, Cornelia M.; Wareham, Nicholas J.; Waterworth, Dawn M.; Boehnke, Michael; Deloukas, Panos; Groop, Leif; Thorsteinsdottir, Unnur; Schlessinger, David; Wichmann, H.-Erich; Frayling, Timothy M.; Abecasis, Gonçalo R.; Loos, Ruth J. F.; Stefansson, Kari; Mohlke, Karen L.; Barroso, Inês; Hirschhorn, Joel; McCarthy, Mark I.; Watkins, Hugh; The Wellcome Trust Case Control Consortium; Hunter, David; Hu, Frank; Yuan, Xin; Scott, Laura J.; Hofman, Albert; Zhao, Jing Hua; Lyon, Helen N.; Qi, LuTo identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist–hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9×(10^{-11})) and MSRA (WC, P = 8.9×(10^{-9})). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6×(10^{-8})). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.