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1.  A Low‐Frequency Variant in MAPK14 Provides Mechanistic Evidence of a Link With Myeloperoxidase: A Prognostic Cardiovascular Risk Marker 
Background
Genetics can be used to predict drug effects and generate hypotheses around alternative indications. To support Losmapimod, a p38 mitogen‐activated protein kinase inhibitor in development for acute coronary syndrome, we characterized gene variation in MAPK11/14 genes by exome sequencing and follow‐up genotyping or imputation in participants well‐phenotyped for cardiovascular and metabolic traits.
Methods and Results
Investigation of genetic variation in MAPK11 and MAPK14 genes using additive genetic models in linear or logistic regression with cardiovascular, metabolic, and biomarker phenotypes highlighted an association of RS2859144 in MAPK14 with myeloperoxidase in a dyslipidemic population (Genetic Epidemiology of Metabolic Syndrome Study), P=2.3×10−6). This variant (or proxy) was consistently associated with myeloperoxidase in the Framingham Heart Study and Cardiovascular Health Study studies (replication meta‐P=0.003), leading to a meta‐P value of 9.96×10−7 in the 3 dyslipidemic groups. The variant or its proxy was then profiled in additional population‐based cohorts (up to a total of 58 930 subjects) including Cohorte Lausannoise, Ely, Fenland, European Prospective Investigation of Cancer, London Life Sciences Prospective Population Study, and the Genetics of Obesity Associations study obesity case–control for up to 40 cardiovascular and metabolic traits. Overall analysis identified the same single nucleotide polymorphisms to be nominally associated consistently with glomerular filtration rate (P=0.002) and risk of obesity (body mass index ≥30 kg/m2, P=0.004).
Conclusions
As myeloperoxidase is a prognostic marker of coronary events, the MAPK14 variant may provide a mechanistic link between p38 map kinase and these events, providing information consistent with current indication of Losmapimod for acute coronary syndrome. If replicated, the association with glomerular filtration rate, along with previous biological findings, also provides support for kidney diseases as alternative indications.
doi:10.1161/JAHA.114.001074
PMCID: PMC4310399  PMID: 25164947
acute coronary syndrome; drug target gene; exome sequencing; myeloperoxidase; rare variation
2.  Mendelian Randomization Studies Do Not Support a Causal Role for Reduced Circulating Adiponectin Levels in Insulin Resistance and Type 2 Diabetes 
Yaghootkar, Hanieh | Lamina, Claudia | Scott, Robert A. | Dastani, Zari | Hivert, Marie-France | Warren, Liling L. | Stancáková, Alena | Buxbaum, Sarah G. | Lyytikäinen, Leo-Pekka | Henneman, Peter | Wu, Ying | Cheung, Chloe Y.Y. | Pankow, James S. | Jackson, Anne U. | Gustafsson, Stefan | Zhao, Jing Hua | Ballantyne, Christie M. | Xie, Weijia | Bergman, Richard N. | Boehnke, Michael | el Bouazzaoui, Fatiha | Collins, Francis S. | Dunn, Sandra H. | Dupuis, Josee | Forouhi, Nita G. | Gillson, Christopher | Hattersley, Andrew T. | Hong, Jaeyoung | Kähönen, Mika | Kuusisto, Johanna | Kedenko, Lyudmyla | Kronenberg, Florian | Doria, Alessandro | Assimes, Themistocles L. | Ferrannini, Ele | Hansen, Torben | Hao, Ke | Häring, Hans | Knowles, Joshua W. | Lindgren, Cecilia M. | Nolan, John J. | Paananen, Jussi | Pedersen, Oluf | Quertermous, Thomas | Smith, Ulf | Lehtimäki, Terho | Liu, Ching-Ti | Loos, Ruth J.F. | McCarthy, Mark I. | Morris, Andrew D. | Vasan, Ramachandran S. | Spector, Tim D. | Teslovich, Tanya M. | Tuomilehto, Jaakko | van Dijk, Ko Willems | Viikari, Jorma S. | Zhu, Na | Langenberg, Claudia | Ingelsson, Erik | Semple, Robert K. | Sinaiko, Alan R. | Palmer, Colin N.A. | Walker, Mark | Lam, Karen S.L. | Paulweber, Bernhard | Mohlke, Karen L. | van Duijn, Cornelia | Raitakari, Olli T. | Bidulescu, Aurelian | Wareham, Nick J. | Laakso, Markku | Waterworth, Dawn M. | Lawlor, Debbie A. | Meigs, James B. | Richards, J. Brent | Frayling, Timothy M.
Diabetes  2013;62(10):3589-3598.
Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics–based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26–0.35) increase in fasting insulin, a 0.34-SD (0.30–0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47–2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI −0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (−0.20 SD; 95% CI −0.38 to −0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75–1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: −0.03 SD; 95% CI −0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95–1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.
doi:10.2337/db13-0128
PMCID: PMC3781444  PMID: 23835345
3.  Genome-wide Linkage and Association Analyses to Identify Genes Influencing Adiponectin Levels: The GEMS Study 
Obesity (Silver Spring, Md.)  2009;17(4):737-744.
Adiponectin has a variety of metabolic effects on obesity, insulin sensitivity, and atherosclerosis. To identify genes influencing variation in plasma adiponectin levels, we performed genome-wide linkage and association scans of adiponectin in two cohorts of subjects recruited in the Genetic Epidemiology of Metabolic Syndrome Study. The genome-wide linkage scan was conducted in families of Turkish and southern European (TSE, n = 789) and Northern and Western European (NWE, N = 2,280) origin. A whole genome association (WGA) analysis (500K Affymetrix platform) was carried out in a set of unrelated NWE subjects consisting of approximately 1,000 subjects with dyslipidemia and 1,000 overweight subjects with normal lipids. Peak evidence for linkage occurred at chromosome 8p23 in NWE subjects (lod = 3.10) and at chromosome 3q28 near ADIPOQ, the adiponectin structural gene, in TSE subjects (lod = 1.70). In the WGA analysis, the single-nucleotide polymorphisms (SNPs) most strongly associated with adiponectin were rs3774261 and rs6773957 (P < 10−7). These two SNPs were in high linkage disequilibrium (r2 = 0.98) and located within ADIPOQ. Interestingly, our fourth strongest region of association (P < 2 × 10−5) was to an SNP within CDH13, whose protein product is a newly identified receptor for high-molecular-weight species of adiponectin. Through WGA analysis, we confirmed previous studies showing SNPs within ADIPOQ to be strongly associated with variation in adiponectin levels and further observed these to have the strongest effects on adiponectin levels throughout the genome. We additionally identified a second gene (CDH13) possibly influencing variation in adiponectin levels. The impact of these SNPs on health and disease has yet to be determined.
doi:10.1038/oby.2008.625
PMCID: PMC4028785  PMID: 19165155
4.  Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links 
PLoS Genetics  2014;10(2):e1004132.
Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on 1H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10−8) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10−44) and lysine (rs8101881, P = 1.2×10−33), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.
Author Summary
The concentrations of small molecules known as metabolites, are subject to tight regulation in all organisms. Collectively, the metabolite concentrations make up the metabolome, which differs amongst individuals as a function of their environment and genetic makeup. In our study, we have further developed an untargeted approach to identify genetic factors affecting human metabolism. In this approach, we first identify all genetic variants that correlate with any of the measured metabolome features in a large set of individuals. For these variants, we then compute a profile of significance for association with all features, generating a signature that facilitates the expert or computational identification of the metabolite whose concentration is most likely affected by the genetic variant at hand. Our study replicated many of the previously reported genetically driven variations in human metabolism and revealed two new striking examples of genetic variations with a sizeable effect on the urine metabolome. Interestingly, in these two gene-metabolite pairs both the gene and the affected metabolite are related to human diseases – Crohn's disease in the first case, and kidney disease in the second. This highlights the connection between genetic predispositions, affected metabolites, and human health.
doi:10.1371/journal.pgen.1004132
PMCID: PMC3930510  PMID: 24586186
5.  Genetic variants influencing circulating lipid levels and risk of coronary artery disease 
Objectives
Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of LDL-c, HDL-c and triglycerides.
Methods and results
We combined genome-wide association data from eight studies, comprising up to 17,723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37,774 participants from eight populations and also in a population of Indian Asian descent. We also assessed the association between SNPs at lipid loci and risk of CAD in up to 9,633 cases and 38,684 controls.
We identified four novel genetic loci that showed reproducible associations with lipids (P values 1.6 × 10−8 to 3.1 × 10−10). These include a potentially functional SNP in the SLC39A8 gene for HDL-c, a SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-c and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with one or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (P values 1.1 × 10−3 to 1.2 × 10−9).
Conclusions
We have identified four novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-c, genetic loci mainly associated with circulating triglycerides and HDL-c are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.
doi:10.1161/ATVBAHA.109.201020
PMCID: PMC3891568  PMID: 20864672
lipids; lipoproteins; genetics; epidemiology
6.  Association of ABCB1 genetic variants with renal function in Africans and in Caucasians 
BMC Medical Genomics  2008;1:21.
Background
The P-glycoprotein, encoded by the ABCB1 gene, is expressed in human endothelial and mesangial cells, which contribute to control renal plasma flow and glomerular filtration rate. We investigated the association of ABCB1 variants with renal function in African and Caucasian subjects.
Methods
In Africans (290 subjects from 62 pedigrees), we genotyped the 2677G>T and 3435 C>T ABCB1 polymorphisms. Glomerular filtration rate (GFR) was measured using inulin clearance and effective renal plasma flow (ERPF) using para-aminohippurate clearance. In Caucasians (5382 unrelated subjects), we analyzed 30 SNPs located within and around ABCB1, using data from the Affymetrix 500 K chip. GFR was estimated using the simplified Modification of the Diet in Renal Disease (MDRD) and Cockcroft-Gault equations.
Results
In Africans, compared to the reference genotype (GG or CC), each copy of the 2677T and 3435T allele was associated, respectively, with: GFR higher by 10.6 ± 2.9 (P < 0.001) and 4.4 ± 2.3 (P = 0.06) mL/min; ERPF higher by 47.5 ± 11.6 (P < 0.001) and 28.1 ± 10.5 (P = 0.007) mL/min; and renal resistances lower by 0.016 ± 0.004 (P < 0.001) and 0.011 ± 0.004 (P = 0.004) mm Hg/mL/min. In Caucasians, we identified 3 polymorphisms in the ABCB1 gene that were strongly associated with all estimates of GFR (smallest P value = 0.0006, overall P = 0.014 after multiple testing correction).
Conclusion
Variants of the ABCB1 gene were associated with renal function in both Africans and Caucasians and may therefore confer susceptibility to nephropathy in humans. If confirmed in other studies, these results point toward a new candidate gene for nephropathy in humans.
doi:10.1186/1755-8794-1-21
PMCID: PMC2424071  PMID: 18518969
7.  Deep Resequencing Unveils Genetic Architecture of ADIPOQ and Identifies a Novel Low-Frequency Variant Strongly Associated With Adiponectin Variation 
Diabetes  2012;61(5):1297-1301.
Increased adiponectin levels have been shown to be associated with a lower risk of type 2 diabetes. To understand the relations between genetic variation at the adiponectin-encoding gene, ADIPOQ, and adiponectin levels, and subsequently its role in disease, we conducted a deep resequencing experiment of ADIPOQ in 14,002 subjects, including 12,514 Europeans, 594 African Americans, and 567 Indian Asians. We identified 296 single nucleotide polymorphisms (SNPs), including 30 amino acid changes, and carried out association analyses in a subset of 3,665 subjects from two independent studies. We confirmed multiple genome-wide association study findings and identified a novel association between a low-frequency SNP (rs17366653) and adiponectin levels (P = 2.2E–17). We show that seven SNPs exert independent effects on adiponectin levels. Together, they explained 6% of adiponectin variation in our samples. We subsequently assessed association between these SNPs and type 2 diabetes in the Genetics of Diabetes Audit and Research in Tayside Scotland (GO-DARTS) study, comprised of 5,145 case and 6,374 control subjects. No evidence of association with type 2 diabetes was found, but we were also unable to exclude the possibility of substantial effects (e.g., odds ratio 95% CI for rs7366653 [0.91–1.58]). Further investigation by large-scale and well-powered Mendelian randomization studies is warranted.
doi:10.2337/db11-0985
PMCID: PMC3331741  PMID: 22403302
8.  Meta-analysis and imputation refines the association of 15q25 with smoking quantity 
Liu, Jason Z. | Tozzi, Federica | Waterworth, Dawn M. | Pillai, Sreekumar G. | Muglia, Pierandrea | Middleton, Lefkos | Berrettini, Wade | Knouff, Christopher W. | Yuan, Xin | Waeber, Gérard | Vollenweider, Peter | Preisig, Martin | Wareham, Nicholas J | Zhao, Jing Hua | Loos, Ruth J.F. | Barroso, Inês | Khaw, Kay-Tee | Grundy, Scott | Barter, Philip | Mahley, Robert | Kesaniemi, Antero | McPherson, Ruth | Vincent, John B. | Strauss, John | Kennedy, James L. | Farmer, Anne | McGuffin, Peter | Day, Richard | Matthews, Keith | Bakke, Per | Gulsvik, Amund | Lucae, Susanne | Ising, Marcus | Brueckl, Tanja | Horstmann, Sonja | Wichmann, H.-Erich | Rawal, Rajesh | Dahmen, Norbert | Lamina, Claudia | Polasek, Ozren | Zgaga, Lina | Huffman, Jennifer | Campbell, Susan | Kooner, Jaspal | Chambers, John C | Burnett, Mary Susan | Devaney, Joseph M. | Pichard, Augusto D. | Kent, Kenneth M. | Satler, Lowell | Lindsay, Joseph M. | Waksman, Ron | Epstein, Stephen | Wilson, James F. | Wild, Sarah H. | Campbell, Harry | Vitart, Veronique | Reilly, Muredach P. | Li, Mingyao | Qu, Liming | Wilensky, Robert | Matthai, William | Hakonarson, Hakon H. | Rader, Daniel J. | Franke, Andre | Wittig, Michael | Schäfer, Arne | Uda, Manuela | Terracciano, Antonio | Xiao, Xiangjun | Busonero, Fabio | Scheet, Paul | Schlessinger, David | St Clair, David | Rujescu, Dan | Abecasis, Gonçalo R. | Grabe, Hans Jörgen | Teumer, Alexander | Völzke, Henry | Petersmann, Astrid | John, Ulrich | Rudan, Igor | Hayward, Caroline | Wright, Alan F. | Kolcic, Ivana | Wright, Benjamin J | Thompson, John R | Balmforth, Anthony J. | Hall, Alistair S. | Samani, Nilesh J. | Anderson, Carl A. | Ahmad, Tariq | Mathew, Christopher G. | Parkes, Miles | Satsangi, Jack | Caulfield, Mark | Munroe, Patricia B. | Farrall, Martin | Dominiczak, Anna | Worthington, Jane | Thomson, Wendy | Eyre, Steve | Barton, Anne | Mooser, Vincent | Francks, Clyde | Marchini, Jonathan
Nature genetics  2010;42(5):436-440.
Smoking is a leading global cause of disease and mortality1. We performed a genomewide meta-analytic association study of smoking-related behavioral traits in a total sample of 41,150 individuals drawn from 20 disease, population, and control cohorts. Our analysis confirmed an effect on smoking quantity (SQ) at a locus on 15q25 (P=9.45e-19) that includes three genes encoding neuronal nicotinic acetylcholine receptor subunits (CHRNA5, CHRNA3, CHRNB4). We used data from the 1000 Genomes project to investigate the region using imputation, which allowed analysis of virtually all common variants in the region and offered a five-fold increase in coverage over the HapMap. This increased the spectrum of potentially causal single nucleotide polymorphisms (SNPs), which included a novel SNP that showed the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.
doi:10.1038/ng.572
PMCID: PMC3612983  PMID: 20418889
9.  A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance 
Manning, Alisa K. | Hivert, Marie-France | Scott, Robert A. | Grimsby, Jonna L. | Bouatia-Naji, Nabila | Chen, Han | Rybin, Denis | Liu, Ching-Ti | Bielak, Lawrence F. | Prokopenko, Inga | Amin, Najaf | Barnes, Daniel | Cadby, Gemma | Hottenga, Jouke-Jan | Ingelsson, Erik | Jackson, Anne U. | Johnson, Toby | Kanoni, Stavroula | Ladenvall, Claes | Lagou, Vasiliki | Lahti, Jari | Lecoeur, Cecile | Liu, Yongmei | Martinez-Larrad, Maria Teresa | Montasser, May E. | Navarro, Pau | Perry, John R. B. | Rasmussen-Torvik, Laura J. | Salo, Perttu | Sattar, Naveed | Shungin, Dmitry | Strawbridge, Rona J. | Tanaka, Toshiko | van Duijn, Cornelia M. | An, Ping | de Andrade, Mariza | Andrews, Jeanette S. | Aspelund, Thor | Atalay, Mustafa | Aulchenko, Yurii | Balkau, Beverley | Bandinelli, Stefania | Beckmann, Jacques S. | Beilby, John P. | Bellis, Claire | Bergman, Richard N. | Blangero, John | Boban, Mladen | Boehnke, Michael | Boerwinkle, Eric | Bonnycastle, Lori L. | Boomsma, Dorret I. | Borecki, Ingrid B. | Böttcher, Yvonne | Bouchard, Claude | Brunner, Eric | Budimir, Danijela | Campbell, Harry | Carlson, Olga | Chines, Peter S. | Clarke, Robert | Collins, Francis S. | Corbatón-Anchuelo, Arturo | Couper, David | de Faire, Ulf | Dedoussis, George V | Deloukas, Panos | Dimitriou, Maria | Egan, Josephine M | Eiriksdottir, Gudny | Erdos, Michael R. | Eriksson, Johan G. | Eury, Elodie | Ferrucci, Luigi | Ford, Ian | Forouhi, Nita G. | Fox, Caroline S | Franzosi, Maria Grazia | Franks, Paul W | Frayling, Timothy M | Froguel, Philippe | Galan, Pilar | de Geus, Eco | Gigante, Bruna | Glazer, Nicole L. | Goel, Anuj | Groop, Leif | Gudnason, Vilmundur | Hallmans, Göran | Hamsten, Anders | Hansson, Ola | Harris, Tamara B. | Hayward, Caroline | Heath, Simon | Hercberg, Serge | Hicks, Andrew A. | Hingorani, Aroon | Hofman, Albert | Hui, Jennie | Hung, Joseph | Jarvelin, Marjo Riitta | Jhun, Min A. | Johnson, Paul C.D. | Jukema, J Wouter | Jula, Antti | Kao, W.H. | Kaprio, Jaakko | Kardia, Sharon L. R. | Keinanen-Kiukaanniemi, Sirkka | Kivimaki, Mika | Kolcic, Ivana | Kovacs, Peter | Kumari, Meena | Kuusisto, Johanna | Kyvik, Kirsten Ohm | Laakso, Markku | Lakka, Timo | Lannfelt, Lars | Lathrop, G Mark | Launer, Lenore J. | Leander, Karin | Li, Guo | Lind, Lars | Lindstrom, Jaana | Lobbens, Stéphane | Loos, Ruth J. F. | Luan, Jian’an | Lyssenko, Valeriya | Mägi, Reedik | Magnusson, Patrik K. E. | Marmot, Michael | Meneton, Pierre | Mohlke, Karen L. | Mooser, Vincent | Morken, Mario A. | Miljkovic, Iva | Narisu, Narisu | O’Connell, Jeff | Ong, Ken K. | Oostra, Ben A. | Palmer, Lyle J. | Palotie, Aarno | Pankow, James S. | Peden, John F. | Pedersen, Nancy L. | Pehlic, Marina | Peltonen, Leena | Penninx, Brenda | Pericic, Marijana | Perola, Markus | Perusse, Louis | Peyser, Patricia A | Polasek, Ozren | Pramstaller, Peter P. | Province, Michael A. | Räikkönen, Katri | Rauramaa, Rainer | Rehnberg, Emil | Rice, Ken | Rotter, Jerome I. | Rudan, Igor | Ruokonen, Aimo | Saaristo, Timo | Sabater-Lleal, Maria | Salomaa, Veikko | Savage, David B. | Saxena, Richa | Schwarz, Peter | Seedorf, Udo | Sennblad, Bengt | Serrano-Rios, Manuel | Shuldiner, Alan R. | Sijbrands, Eric J.G. | Siscovick, David S. | Smit, Johannes H. | Small, Kerrin S. | Smith, Nicholas L. | Smith, Albert Vernon | Stančáková, Alena | Stirrups, Kathleen | Stumvoll, Michael | Sun, Yan V. | Swift, Amy J. | Tönjes, Anke | Tuomilehto, Jaakko | Trompet, Stella | Uitterlinden, Andre G. | Uusitupa, Matti | Vikström, Max | Vitart, Veronique | Vohl, Marie-Claude | Voight, Benjamin F. | Vollenweider, Peter | Waeber, Gerard | Waterworth, Dawn M | Watkins, Hugh | Wheeler, Eleanor | Widen, Elisabeth | Wild, Sarah H. | Willems, Sara M. | Willemsen, Gonneke | Wilson, James F. | Witteman, Jacqueline C.M. | Wright, Alan F. | Yaghootkar, Hanieh | Zelenika, Diana | Zemunik, Tatijana | Zgaga, Lina | Wareham, Nicholas J. | McCarthy, Mark I. | Barroso, Ines | Watanabe, Richard M. | Florez, Jose C. | Dupuis, Josée | Meigs, James B. | Langenberg, Claudia
Nature genetics  2012;44(6):659-669.
Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and beta-cell dysfunction, but contributed little to our understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways may be uncovered by accounting for differences in body mass index (BMI) and potential interaction between BMI and genetic variants. We applied a novel joint meta-analytical approach to test associations with fasting insulin (FI) and glucose (FG) on a genome-wide scale. We present six previously unknown FI loci at P<5×10−8 in combined discovery and follow-up analyses of 52 studies comprising up to 96,496non-diabetic individuals. Risk variants were associated with higher triglyceride and lower HDL cholesterol levels, suggestive of a role for these FI loci in insulin resistance pathways. The localization of these additional loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.
doi:10.1038/ng.2274
PMCID: PMC3613127  PMID: 22581228
10.  Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways 
Scott, Robert A | Lagou, Vasiliki | Welch, Ryan P | Wheeler, Eleanor | Montasser, May E | Luan, Jian’an | Mägi, Reedik | Strawbridge, Rona J | Rehnberg, Emil | Gustafsson, Stefan | Kanoni, Stavroula | Rasmussen-Torvik, Laura J | Yengo, Loïc | Lecoeur, Cecile | Shungin, Dmitry | Sanna, Serena | Sidore, Carlo | Johnson, Paul C D | Jukema, J Wouter | Johnson, Toby | Mahajan, Anubha | Verweij, Niek | Thorleifsson, Gudmar | Hottenga, Jouke-Jan | Shah, Sonia | Smith, Albert V | Sennblad, Bengt | Gieger, Christian | Salo, Perttu | Perola, Markus | Timpson, Nicholas J | Evans, David M | Pourcain, Beate St | Wu, Ying | Andrews, Jeanette S | Hui, Jennie | Bielak, Lawrence F | Zhao, Wei | Horikoshi, Momoko | Navarro, Pau | Isaacs, Aaron | O’Connell, Jeffrey R | Stirrups, Kathleen | Vitart, Veronique | Hayward, Caroline | Esko, Tönu | Mihailov, Evelin | Fraser, Ross M | Fall, Tove | Voight, Benjamin F | Raychaudhuri, Soumya | Chen, Han | Lindgren, Cecilia M | Morris, Andrew P | Rayner, Nigel W | Robertson, Neil | Rybin, Denis | Liu, Ching-Ti | Beckmann, Jacques S | Willems, Sara M | Chines, Peter S | Jackson, Anne U | Kang, Hyun Min | Stringham, Heather M | Song, Kijoung | Tanaka, Toshiko | Peden, John F | Goel, Anuj | Hicks, Andrew A | An, Ping | Müller-Nurasyid, Martina | Franco-Cereceda, Anders | Folkersen, Lasse | Marullo, Letizia | Jansen, Hanneke | Oldehinkel, Albertine J | Bruinenberg, Marcel | Pankow, James S | North, Kari E | Forouhi, Nita G | Loos, Ruth J F | Edkins, Sarah | Varga, Tibor V | Hallmans, Göran | Oksa, Heikki | Antonella, Mulas | Nagaraja, Ramaiah | Trompet, Stella | Ford, Ian | Bakker, Stephan J L | Kong, Augustine | Kumari, Meena | Gigante, Bruna | Herder, Christian | Munroe, Patricia B | Caulfield, Mark | Antti, Jula | Mangino, Massimo | Small, Kerrin | Miljkovic, Iva | Liu, Yongmei | Atalay, Mustafa | Kiess, Wieland | James, Alan L | Rivadeneira, Fernando | Uitterlinden, Andre G | Palmer, Colin N A | Doney, Alex S F | Willemsen, Gonneke | Smit, Johannes H | Campbell, Susan | Polasek, Ozren | Bonnycastle, Lori L | Hercberg, Serge | Dimitriou, Maria | Bolton, Jennifer L | Fowkes, Gerard R | Kovacs, Peter | Lindström, Jaana | Zemunik, Tatijana | Bandinelli, Stefania | Wild, Sarah H | Basart, Hanneke V | Rathmann, Wolfgang | Grallert, Harald | Maerz, Winfried | Kleber, Marcus E | Boehm, Bernhard O | Peters, Annette | Pramstaller, Peter P | Province, Michael A | Borecki, Ingrid B | Hastie, Nicholas D | Rudan, Igor | Campbell, Harry | Watkins, Hugh | Farrall, Martin | Stumvoll, Michael | Ferrucci, Luigi | Waterworth, Dawn M | Bergman, Richard N | Collins, Francis S | Tuomilehto, Jaakko | Watanabe, Richard M | de Geus, Eco J C | Penninx, Brenda W | Hofman, Albert | Oostra, Ben A | Psaty, Bruce M | Vollenweider, Peter | Wilson, James F | Wright, Alan F | Hovingh, G Kees | Metspalu, Andres | Uusitupa, Matti | Magnusson, Patrik K E | Kyvik, Kirsten O | Kaprio, Jaakko | Price, Jackie F | Dedoussis, George V | Deloukas, Panos | Meneton, Pierre | Lind, Lars | Boehnke, Michael | Shuldiner, Alan R | van Duijn, Cornelia M | Morris, Andrew D | Toenjes, Anke | Peyser, Patricia A | Beilby, John P | Körner, Antje | Kuusisto, Johanna | Laakso, Markku | Bornstein, Stefan R | Schwarz, Peter E H | Lakka, Timo A | Rauramaa, Rainer | Adair, Linda S | Smith, George Davey | Spector, Tim D | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Gudnason, Vilmundur | Kivimaki, Mika | Hingorani, Aroon | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Boomsma, Dorret I | Stefansson, Kari | van der Harst, Pim | Dupuis, Josée | Pedersen, Nancy L | Sattar, Naveed | Harris, Tamara B | Cucca, Francesco | Ripatti, Samuli | Salomaa, Veikko | Mohlke, Karen L | Balkau, Beverley | Froguel, Philippe | Pouta, Anneli | Jarvelin, Marjo-Riitta | Wareham, Nicholas J | Bouatia-Naji, Nabila | McCarthy, Mark I | Franks, Paul W | Meigs, James B | Teslovich, Tanya M | Florez, Jose C | Langenberg, Claudia | Ingelsson, Erik | Prokopenko, Inga | Barroso, Inês
Nature genetics  2012;44(9):991-1005.
Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control.
doi:10.1038/ng.2385
PMCID: PMC3433394  PMID: 22885924
11.  Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma 
Chambers, John C | Zhang, Weihua | Sehmi, Joban | Li, Xinzhong | Wass, Mark N | Van der Harst, Pim | Holm, Hilma | Sanna, Serena | Kavousi, Maryam | Baumeister, Sebastian E | Coin, Lachlan J | Deng, Guohong | Gieger, Christian | Heard-Costa, Nancy L | Hottenga, Jouke-Jan | Kühnel, Brigitte | Kumar, Vinod | Lagou, Vasiliki | Liang, Liming | Luan, Jian’an | Vidal, Pedro Marques | Leach, Irene Mateo | O’Reilly, Paul F | Peden, John F | Rahmioglu, Nilufer | Soininen, Pasi | Speliotes, Elizabeth K | Yuan, Xin | Thorleifsson, Gudmar | Alizadeh, Behrooz Z | Atwood, Larry D | Borecki, Ingrid B | Brown, Morris J | Charoen, Pimphen | Cucca, Francesco | Das, Debashish | de Geus, Eco J C | Dixon, Anna L | Döring, Angela | Ehret, Georg | Eyjolfsson, Gudmundur I | Farrall, Martin | Forouhi, Nita G | Friedrich, Nele | Goessling, Wolfram | Gudbjartsson, Daniel F | Harris, Tamara B | Hartikainen, Anna-Liisa | Heath, Simon | Hirschfield, Gideon M | Hofman, Albert | Homuth, Georg | Hyppönen, Elina | Janssen, Harry L A | Johnson, Toby | Kangas, Antti J | Kema, Ido P | Kühn, Jens P | Lai, Sandra | Lathrop, Mark | Lerch, Markus M | Li, Yun | Liang, T Jake | Lin, Jing-Ping | Loos, Ruth J F | Martin, Nicholas G | Moffatt, Miriam F | Montgomery, Grant W | Munroe, Patricia B | Musunuru, Kiran | Nakamura, Yusuke | O’Donnell, Christopher J | Olafsson, Isleifur | Penninx, Brenda W | Pouta, Anneli | Prins, Bram P | Prokopenko, Inga | Puls, Ralf | Ruokonen, Aimo | Savolainen, Markku J | Schlessinger, David | Schouten, Jeoffrey N L | Seedorf, Udo | Sen-Chowdhry, Srijita | Siminovitch, Katherine A | Smit, Johannes H | Spector, Timothy D | Tan, Wenting | Teslovich, Tanya M | Tukiainen, Taru | Uitterlinden, Andre G | Van der Klauw, Melanie M | Vasan, Ramachandran S | Wallace, Chris | Wallaschofski, Henri | Wichmann, H-Erich | Willemsen, Gonneke | Würtz, Peter | Xu, Chun | Yerges-Armstrong, Laura M | Abecasis, Goncalo R | Ahmadi, Kourosh R | Boomsma, Dorret I | Caulfield, Mark | Cookson, William O | van Duijn, Cornelia M | Froguel, Philippe | Matsuda, Koichi | McCarthy, Mark I | Meisinger, Christa | Mooser, Vincent | Pietiläinen, Kirsi H | Schumann, Gunter | Snieder, Harold | Sternberg, Michael J E | Stolk, Ronald P | Thomas, Howard C | Thorsteinsdottir, Unnur | Uda, Manuela | Waeber, Gérard | Wareham, Nicholas J | Waterworth, Dawn M | Watkins, Hugh | Whitfield, John B | Witteman, Jacqueline C M | Wolffenbuttel, Bruce H R | Fox, Caroline S | Ala-Korpela, Mika | Stefansson, Kari | Vollenweider, Peter | Völzke, Henry | Schadt, Eric E | Scott, James | Järvelin, Marjo-Riitta | Elliott, Paul | Kooner, Jaspal S
Nature genetics  2011;43(11):1131-1138.
Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10−8 to P = 10−190). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.
doi:10.1038/ng.970
PMCID: PMC3482372  PMID: 22001757
12.  Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals 
Dastani, Zari | Hivert, Marie-France | Timpson, Nicholas | Perry, John R. B. | Yuan, Xin | Scott, Robert A. | Henneman, Peter | Heid, Iris M. | Kizer, Jorge R. | Lyytikäinen, Leo-Pekka | Fuchsberger, Christian | Tanaka, Toshiko | Morris, Andrew P. | Small, Kerrin | Isaacs, Aaron | Beekman, Marian | Coassin, Stefan | Lohman, Kurt | Qi, Lu | Kanoni, Stavroula | Pankow, James S. | Uh, Hae-Won | Wu, Ying | Bidulescu, Aurelian | Rasmussen-Torvik, Laura J. | Greenwood, Celia M. T. | Ladouceur, Martin | Grimsby, Jonna | Manning, Alisa K. | Liu, Ching-Ti | Kooner, Jaspal | Mooser, Vincent E. | Vollenweider, Peter | Kapur, Karen A. | Chambers, John | Wareham, Nicholas J. | Langenberg, Claudia | Frants, Rune | Willems-vanDijk, Ko | Oostra, Ben A. | Willems, Sara M. | Lamina, Claudia | Winkler, Thomas W. | Psaty, Bruce M. | Tracy, Russell P. | Brody, Jennifer | Chen, Ida | Viikari, Jorma | Kähönen, Mika | Pramstaller, Peter P. | Evans, David M. | St. Pourcain, Beate | Sattar, Naveed | Wood, Andrew R. | Bandinelli, Stefania | Carlson, Olga D. | Egan, Josephine M. | Böhringer, Stefan | van Heemst, Diana | Kedenko, Lyudmyla | Kristiansson, Kati | Nuotio, Marja-Liisa | Loo, Britt-Marie | Harris, Tamara | Garcia, Melissa | Kanaya, Alka | Haun, Margot | Klopp, Norman | Wichmann, H.-Erich | Deloukas, Panos | Katsareli, Efi | Couper, David J. | Duncan, Bruce B. | Kloppenburg, Margreet | Adair, Linda S. | Borja, Judith B. | Wilson, James G. | Musani, Solomon | Guo, Xiuqing | Johnson, Toby | Semple, Robert | Teslovich, Tanya M. | Allison, Matthew A. | Redline, Susan | Buxbaum, Sarah G. | Mohlke, Karen L. | Meulenbelt, Ingrid | Ballantyne, Christie M. | Dedoussis, George V. | Hu, Frank B. | Liu, Yongmei | Paulweber, Bernhard | Spector, Timothy D. | Slagboom, P. Eline | Ferrucci, Luigi | Jula, Antti | Perola, Markus | Raitakari, Olli | Florez, Jose C. | Salomaa, Veikko | Eriksson, Johan G. | Frayling, Timothy M. | Hicks, Andrew A. | Lehtimäki, Terho | Smith, George Davey | Siscovick, David S. | Kronenberg, Florian | van Duijn, Cornelia | Loos, Ruth J. F. | Waterworth, Dawn M. | Meigs, James B. | Dupuis, Josee | Richards, J. Brent
PLoS Genetics  2012;8(3):e1002607.
Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10−8–1.2×10−43). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10−4). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10−3, n = 22,044), increased triglycerides (p = 2.6×10−14, n = 93,440), increased waist-to-hip ratio (p = 1.8×10−5, n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10−3, n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10−13, n = 96,748) and decreased BMI (p = 1.4×10−4, n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
Author Summary
Serum adiponectin levels are highly heritable and are inversely correlated with the risk of type 2 diabetes (T2D), coronary artery disease, stroke, and several metabolic traits. To identify common genetic variants associated with adiponectin levels and risk of T2D and metabolic traits, we conducted a meta-analysis of genome-wide association studies of 45,891 multi-ethnic individuals. In addition to confirming that variants at the ADIPOQ and CDH13 loci influence adiponectin levels, our analyses revealed that 10 new loci also affecting circulating adiponectin levels. We demonstrated that expression levels of several genes in these candidate regions are associated with serum adiponectin levels. Using a powerful novel method to assess the contribution of the identified variants with other traits using summary-level results from large-scale GWAS consortia, we provide evidence that the risk alleles for adiponectin are associated with deleterious changes in T2D risk and metabolic syndrome traits (triglycerides, HDL, post-prandial glucose, insulin, and waist-to-hip ratio), demonstrating that the identified loci, taken together, impact upon metabolic disease.
doi:10.1371/journal.pgen.1002607
PMCID: PMC3315470  PMID: 22479202
13.  Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies 
Elks, Cathy E. | Perry, John R.B. | Sulem, Patrick | Chasman, Daniel I. | Franceschini, Nora | He, Chunyan | Lunetta, Kathryn L. | Visser, Jenny A. | Byrne, Enda M. | Cousminer, Diana L. | Gudbjartsson, Daniel F. | Esko, Tõnu | Feenstra, Bjarke | Hottenga, Jouke-Jan | Koller, Daniel L. | Kutalik, Zoltán | Lin, Peng | Mangino, Massimo | Marongiu, Mara | McArdle, Patrick F. | Smith, Albert V. | Stolk, Lisette | van Wingerden, Sophie W. | Zhao, Jing Hua | Albrecht, Eva | Corre, Tanguy | Ingelsson, Erik | Hayward, Caroline | Magnusson, Patrik K.E. | Smith, Erin N. | Ulivi, Shelia | Warrington, Nicole M. | Zgaga, Lina | Alavere, Helen | Amin, Najaf | Aspelund, Thor | Bandinelli, Stefania | Barroso, Ines | Berenson, Gerald S. | Bergmann, Sven | Blackburn, Hannah | Boerwinkle, Eric | Buring, Julie E. | Busonero, Fabio | Campbell, Harry | Chanock, Stephen J. | Chen, Wei | Cornelis, Marilyn C. | Couper, David | Coviello, Andrea D. | d’Adamo, Pio | de Faire, Ulf | de Geus, Eco J.C. | Deloukas, Panos | Döring, Angela | Smith, George Davey | Easton, Douglas F. | Eiriksdottir, Gudny | Emilsson, Valur | Eriksson, Johan | Ferrucci, Luigi | Folsom, Aaron R. | Foroud, Tatiana | Garcia, Melissa | Gasparini, Paolo | Geller, Frank | Gieger, Christian | Gudnason, Vilmundur | Hall, Per | Hankinson, Susan E. | Ferreli, Liana | Heath, Andrew C. | Hernandez, Dena G. | Hofman, Albert | Hu, Frank B. | Illig, Thomas | Järvelin, Marjo-Riitta | Johnson, Andrew D. | Karasik, David | Khaw, Kay-Tee | Kiel, Douglas P. | Kilpeläinen, Tuomas O. | Kolcic, Ivana | Kraft, Peter | Launer, Lenore J. | Laven, Joop S.E. | Li, Shengxu | Liu, Jianjun | Levy, Daniel | Martin, Nicholas G. | McArdle, Wendy L. | Melbye, Mads | Mooser, Vincent | Murray, Jeffrey C. | Murray, Sarah S. | Nalls, Michael A. | Navarro, Pau | Nelis, Mari | Ness, Andrew R. | Northstone, Kate | Oostra, Ben A. | Peacock, Munro | Palmer, Lyle J. | Palotie, Aarno | Paré, Guillaume | Parker, Alex N. | Pedersen, Nancy L. | Peltonen, Leena | Pennell, Craig E. | Pharoah, Paul | Polasek, Ozren | Plump, Andrew S. | Pouta, Anneli | Porcu, Eleonora | Rafnar, Thorunn | Rice, John P. | Ring, Susan M. | Rivadeneira, Fernando | Rudan, Igor | Sala, Cinzia | Salomaa, Veikko | Sanna, Serena | Schlessinger, David | Schork, Nicholas J. | Scuteri, Angelo | Segrè, Ayellet V. | Shuldiner, Alan R. | Soranzo, Nicole | Sovio, Ulla | Srinivasan, Sathanur R. | Strachan, David P. | Tammesoo, Mar-Liis | Tikkanen, Emmi | Toniolo, Daniela | Tsui, Kim | Tryggvadottir, Laufey | Tyrer, Jonathon | Uda, Manuela | van Dam, Rob M. | van Meurs, Joyve B.J. | Vollenweider, Peter | Waeber, Gerard | Wareham, Nicholas J. | Waterworth, Dawn M. | Weedon, Michael N. | Wichmann, H. Erich | Willemsen, Gonneke | Wilson, James F. | Wright, Alan F. | Young, Lauren | Zhai, Guangju | Zhuang, Wei Vivian | Bierut, Laura J. | Boomsma, Dorret I. | Boyd, Heather A. | Crisponi, Laura | Demerath, Ellen W. | van Duijn, Cornelia M. | Econs, Michael J. | Harris, Tamara B. | Hunter, David J. | Loos, Ruth J.F. | Metspalu, Andres | Montgomery, Grant W. | Ridker, Paul M. | Spector, Tim D. | Streeten, Elizabeth A. | Stefansson, Kari | Thorsteinsdottir, Unnur | Uitterlinden, André G. | Widen, Elisabeth | Murabito, Joanne M. | Ong, Ken K. | Murray, Anna
Nature genetics  2010;42(12):1077-1085.
To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P=5.4×10−60) and 9q31.2 (P=2.2×10−33), we identified 30 novel menarche loci (all P<5×10−8) and found suggestive evidence for a further 10 loci (P<1.9×10−6). New loci included four previously associated with BMI (in/near FTO, SEC16B, TRA2B and TMEM18), three in/near other genes implicated in energy homeostasis (BSX, CRTC1, and MCHR2), and three in/near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and MAGENTA pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing.
doi:10.1038/ng.714
PMCID: PMC3140055  PMID: 21102462
14.  Lack of association between the Trp719Arg polymorphism in kinesin-like protein 6 and coronary artery disease in 19 case-control studies 
Assimes, Themistocles L | Hólm, Hilma | Kathiresan, Sekar | Reilly, Muredach P | Thorleifsson, Gudmar | Voight, Benjamin F | Erdmann, Jeanette | Willenborg, Christina | Vaidya, Dhananjay | Xie, Changchun | Patterson, Chris C | Morgan, Thomas M | Burnett, Mary Susan | Li, Mingyao | Hlatky, Mark A | Knowles, Joshua W | Thompson, John R | Absher, Devin | Iribarren, Carlos | Go, Alan | Fortmann, Stephen P | Sidney, Stephen | Risch, Neil | Tang, Hua | Myers, Richard M | Berger, Klaus | Stoll, Monika | Shah, Svati H. | Thorgeirsson, Gudmundur | Andersen, Karl | Havulinna, Aki S | Herrera, J. Enrique | Faraday, Nauder | Kim, Yoonhee | Kral, Brian G. | Mathias, Rasika | Ruczinski, Ingo | Suktitipat, Bhoom | Wilson, Alexander F | Yanek, Lisa R. | Becker, Lewis C | Linsel-Nitschke, Patrick | Lieb, Wolfgang | König, Inke R | Hengstenberg, Christian | Fischer, Marcus | Stark, Klaus | Reinhard, Wibke | Winogradow, Janina | Grassl, Martina | Grosshennig, Anika | Preuss, Michael | Eifert, Sandra | Schreiber, Stefan | Wichmann, H-Erich | Meisinger, Christa | Yee, Jean | Friedlander, Yechiel | Do, Ron | Meigs, James B | Williams, Gordon | Nathan, David M | MacRae, Calum A | Qu, Liming | Wilensky, Robert L | Matthai, William H. | Qasim, Atif N | Hakonarson, Hakon | Pichard, Augusto D | Kent, Kenneth M | Satler, Lowell | Lindsay, Joseph M | Waksman, Ron | Knouff, Christopher W | Waterworth, Dawn M | Walker, Max C | Mooser, Vincent | Marrugat, Jaume | Lucas, Gavin | Subirana, Isaac | Sala, Joan | Ramos, Rafael | Martinelli, Nicola | Olivieri, Oliviero | Trabetti, Elisabetta | Malerba, Giovanni | Pignatti, Pier Franco | Guiducci, Candace | Mirel, Daniel | Parkin, Melissa | Hirschhorn, Joel N | Asselta, Rosanna | Duga, Stefano | Musunuru, Kiran | Daly, Mark J | Purcell, Shaun | Braund, Peter S | Wright, Benjamin J | Balmforth, Anthony J | Ball, Stephen G | Ouwehand, Willem H | Deloukas, Panos | Scholz, Michael | Cambien, Francois | Huge, Andreas | Scheffold, Thomas | Salomaa, Veikko | Girelli, Domenico | Granger, Christopher B. | Peltonen, Leena | McKeown, Pascal P | Altshuler, David | Melander, Olle | Devaney, Joseph M | Epstein, Stephen E | Rader, Daniel J | Elosua, Roberto | Engert, James C | Anand, Sonia S | Hall, Alistair S | Ziegler, Andreas | O’Donnell, Christopher J | Spertus, John A | Siscovick, David | Schwartz, Stephen M | Becker, Diane | Thorsteinsdottir, Unnur | Stefansson, Kari | Schunkert, Heribert | Samani, Nilesh J | Quertermous, Thomas
Objectives
We sought to replicate the association between the kinesin-like protein 6 (KIF6) Trp719Arg polymorphism (rs20455) and clinical coronary artery disease (CAD).
Background
Recent prospective studies suggest that carriers of the 719Arg allele in KIF6 are at increased risk of clinical CAD compared with non-carriers.
Methods
The KIF6 Trp719Arg polymorphism (rs20455) was genotyped in nineteen case-control studies of non-fatal CAD either as part of a genome-wide association study or in a formal attempt to replicate the initial positive reports.
Results
Over 17 000 cases and 39 000 controls of European descent as well as a modest number of South Asians, African Americans, Hispanics, East Asians, and admixed cases and controls were successfully genotyped. None of the nineteen studies demonstrated an increased risk of CAD in carriers of the 719Arg allele compared with non-carriers. Regression analyses and fixed effect meta-analyses ruled out with high degree of confidence an increase of ≥2% in the risk of CAD among European 719Arg carriers. We also observed no increase in the risk of CAD among 719Arg carriers in the subset of Europeans with early onset disease (<50 years of age for males and <60 years for females) compared with similarly aged controls as well as all non-European subgroups.
Conclusions
The KIF6 Trp719Arg polymorphism was not associated with the risk of clinical CAD in this large replication study.
doi:10.1016/j.jacc.2010.06.022
PMCID: PMC3084526  PMID: 20933357
kinesin-like protein 6; KIF6; coronary artery disease; myocardial infarction; polymorphism
15.  A Genome-Wide Screen for Interactions Reveals a New Locus on 4p15 Modifying the Effect of Waist-to-Hip Ratio on Total Cholesterol 
Surakka, Ida | Isaacs, Aaron | Karssen, Lennart C. | Laurila, Pirkka-Pekka P. | Middelberg, Rita P. S. | Tikkanen, Emmi | Ried, Janina S. | Lamina, Claudia | Mangino, Massimo | Igl, Wilmar | Hottenga, Jouke-Jan | Lagou, Vasiliki | van der Harst, Pim | Mateo Leach, Irene | Esko, Tõnu | Kutalik, Zoltán | Wainwright, Nicholas W. | Struchalin, Maksim V. | Sarin, Antti-Pekka | Kangas, Antti J. | Viikari, Jorma S. | Perola, Markus | Rantanen, Taina | Petersen, Ann-Kristin | Soininen, Pasi | Johansson, Åsa | Soranzo, Nicole | Heath, Andrew C. | Papamarkou, Theodore | Prokopenko, Inga | Tönjes, Anke | Kronenberg, Florian | Döring, Angela | Rivadeneira, Fernando | Montgomery, Grant W. | Whitfield, John B. | Kähönen, Mika | Lehtimäki, Terho | Freimer, Nelson B. | Willemsen, Gonneke | de Geus, Eco J. C. | Palotie, Aarno | Sandhu, Manj S. | Waterworth, Dawn M. | Metspalu, Andres | Stumvoll, Michael | Uitterlinden, André G. | Jula, Antti | Navis, Gerjan | Wijmenga, Cisca | Wolffenbuttel, Bruce H. R. | Taskinen, Marja-Riitta | Ala-Korpela, Mika | Kaprio, Jaakko | Kyvik, Kirsten O. | Boomsma, Dorret I. | Pedersen, Nancy L. | Gyllensten, Ulf | Wilson, James F. | Rudan, Igor | Campbell, Harry | Pramstaller, Peter P. | Spector, Tim D. | Witteman, Jacqueline C. M. | Eriksson, Johan G. | Salomaa, Veikko | Oostra, Ben A. | Raitakari, Olli T. | Wichmann, H.-Erich | Gieger, Christian | Järvelin, Marjo-Riitta | Martin, Nicholas G. | Hofman, Albert | McCarthy, Mark I. | Peltonen, Leena | van Duijn, Cornelia M. | Aulchenko, Yurii S. | Ripatti, Samuli
PLoS Genetics  2011;7(10):e1002333.
Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene–environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10−9. There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.
Author Summary
Circulating serum lipids contribute greatly to the global health by affecting the risk for cardiovascular diseases. Serum lipid levels are partly inherited, and already 95 loci affecting high- and low-density lipoprotein cholesterol, total cholesterol, and triglycerides have been found. Serum lipids are also known to be affected by multiple epidemiological risk factors like body composition, lifestyle, and sex. It has been hypothesized that there are loci modifying the effects between risk factors and serum lipids, but to date only candidate gene studies for interactions have been reported. We conducted a genome-wide screen with meta-analysis approach to identify loci having interactions with epidemiological risk factors on serum lipids with over 30,000 population-based samples. When combining results from our initial datasets and 8 additional replication cohorts (maximum N = 17,102), we found a genome-wide significant locus in chromosome 4p15 with a joint P-value of 4.79×10−9 modifying the effect of waist-to-hip ratio on total cholesterol. In the area surrounding this genetic variant, there were two genes having association between the genotypes and the gene expression in adipose tissue, and we also found enrichment of association in genes belonging to lipid metabolism related functions.
doi:10.1371/journal.pgen.1002333
PMCID: PMC3197672  PMID: 22028671
16.  Genetic Insights into Schizophrenia 
Objective
To outline new insights into the genetic etiology of schizophrenia.
Methods
We discuss several commonly held beliefs about the genetic issues in schizophrenia.
Results
The complex genetic nature of the illness poses a challenge for investigators seeking causative genetic mutations. Multiple independent research findings are, however converging to identify a relatively small number of chromosomal locations that appear to contain schizophrenia susceptibility genes. Also, a clinically relevant genetic subtype of schizophrenia (22qDS) has been identified. We are developing a better understanding of how schizophrenia relates to other psychiatric disorders. While investigations into the possible roles of dopaminergic and serotonergic systems continue, other approaches that do not require theories of the mechanism of illness are also being used to identify candidate susceptibility genes.
Conclusions
Research to date suggests that our understanding of the pathophysiology of schizophrenia will soon be fundamentally altered by genetic approaches to this complex disease.
PMCID: PMC3188301  PMID: 11280081 CAMSID: cams1940
genetics; schizophrenia; linkage; 22q deletion syndrome; psychiatric genetics
17.  Prospective study of insulin-like growth factor-I, insulin-like growth factor-binding protein 3, genetic variants in the IGF1 and IGFBP3 genes and risk of coronary artery disease 
Although experimental studies have suggested that insulin-like growth factor I (IGF-I) and its binding protein IGFBP-3 might have a role in the aetiology of coronary artery disease (CAD), the relevance of circulating IGFs and their binding proteins in the development of CAD in human populations is unclear. We conducted a nested case-control study, with a mean follow-up of six years, within the EPIC-Norfolk cohort to assess the association between circulating levels of IGF-I and IGFBP-3 and risk of CAD in up to 1,013 cases and 2,055 controls matched for age, sex and study enrolment date. After adjustment for cardiovascular risk factors, we found no association between circulating levels of IGF-I or IGFBP-3 and risk of CAD (odds ratio: 0.98 (95% Cl 0.90-1.06) per 1 SD increase in circulating IGF-I; odds ratio: 1.02 (95% Cl 0.94-1.12) for IGFBP-3). We examined associations between tagging single nucleotide polymorphisms (tSNPs) at the IGF1 and IGFBP3 loci and circulating IGF-I and IGFBP-3 levels in up to 1,133 cases and 2,223 controls and identified three tSNPs (rs1520220, rs3730204, rs2132571) that showed independent association with either circulating IGF-I or IGFBP-3 levels. In an assessment of 31 SNPs spanning the IGF1 or IGFBP3 loci, none were associated with risk of CAD in a meta-analysis that included EPIC-Norfolk and eight additional studies comprising up to 9,319 cases and 19,964 controls. Our results indicate that IGF-I and IGFBP-3 are unlikely to be importantly involved in the aetiology of CAD in human populations.
PMCID: PMC3166154  PMID: 21915365
Epidemiology; Genetics of cardiovascular disease; Risk factors; IGF1; IGFBP3
18.  Pathway-Wide Association Study Implicates Multiple Sterol Transport and Metabolism Genes in HDL Cholesterol Regulation 
Pathway-based association methods have been proposed to be an effective approach in identifying disease genes, when single-marker association tests do not have sufficient power. The analysis of quantitative traits may be benefited from these approaches, by sampling from two extreme tails of the distribution. Here we tested a pathway association approach on a small genome-wide association study (GWAS) on 653 subjects with extremely high high-density lipoprotein cholesterol (HDL-C) levels and 784 subjects with low HDL-C levels. We identified 102 genes in the sterol transport and metabolism pathways that collectively associate with HDL-C levels, and replicated these association signals in an independent GWAS. Interestingly, the pathways include 18 genes implicated in previous GWAS on lipid traits, suggesting that genuine HDL-C genes are highly enriched in these pathways. Additionally, multiple biologically relevant loci in the pathways were not detected by previous GWAS, including genes implicated in previous candidate gene association studies (such as LEPR, APOA2, HDLBP, SOAT2), genes that cause Mendelian forms of lipid disorders (such as DHCR24), and genes expressing dyslipidemia phenotypes in knockout mice (such as SOAT1, PON1). Our study suggests that sampling from two extreme tails of a quantitative trait and examining genetic pathways may yield biological insights from smaller samples than are generally required using single-marker analysis in large-scale GWAS. Our results also implicate that functionally related genes work together to regulate complex quantitative traits, and that future large-scale studies may benefit from pathway-association approaches to identify novel pathways regulating HDL-C levels.
doi:10.3389/fgene.2011.00041
PMCID: PMC3268595  PMID: 22303337
GWAS; lipid; HDL-C; pathway analysis; cholesterol; sterol transport; sterol metabolism; genetic association
19.  Biological, Clinical, and Population Relevance of 95 Loci for Blood Lipids 
Teslovich, Tanya M. | Musunuru, Kiran | Smith, Albert V. | Edmondson, Andrew C. | Stylianou, Ioannis M. | Koseki, Masahiro | Pirruccello, James P. | Ripatti, Samuli | Chasman, Daniel I. | Willer, Cristen J. | Johansen, Christopher T. | Fouchier, Sigrid W. | Isaacs, Aaron | Peloso, Gina M. | Barbalic, Maja | Ricketts, Sally L. | Bis, Joshua C. | Aulchenko, Yurii S. | Thorleifsson, Gudmar | Feitosa, Mary F. | Chambers, John | Orho-Melander, Marju | Melander, Olle | Johnson, Toby | Li, Xiaohui | Guo, Xiuqing | Li, Mingyao | Cho, Yoon Shin | Go, Min Jin | Kim, Young Jin | Lee, Jong-Young | Park, Taesung | Kim, Kyunga | Sim, Xueling | Ong, Rick Twee-Hee | Croteau-Chonka, Damien C. | Lange, Leslie A. | Smith, Joshua D. | Song, Kijoung | Zhao, Jing Hua | Yuan, Xin | Luan, Jian'an | Lamina, Claudia | Ziegler, Andreas | Zhang, Weihua | Zee, Robert Y.L. | Wright, Alan F. | Witteman, Jacqueline C.M. | Wilson, James F. | Willemsen, Gonneke | Wichmann, H-Erich | Whitfield, John B. | Waterworth, Dawn M. | Wareham, Nicholas J. | Waeber, Gérard | Vollenweider, Peter | Voight, Benjamin F. | Vitart, Veronique | Uitterlinden, Andre G. | Uda, Manuela | Tuomilehto, Jaakko | Thompson, John R. | Tanaka, Toshiko | Surakka, Ida | Stringham, Heather M. | Spector, Tim D. | Soranzo, Nicole | Smit, Johannes H. | Sinisalo, Juha | Silander, Kaisa | Sijbrands, Eric J.G. | Scuteri, Angelo | Scott, James | Schlessinger, David | Sanna, Serena | Salomaa, Veikko | Saharinen, Juha | Sabatti, Chiara | Ruokonen, Aimo | Rudan, Igor | Rose, Lynda M. | Roberts, Robert | Rieder, Mark | Psaty, Bruce M. | Pramstaller, Peter P. | Pichler, Irene | Perola, Markus | Penninx, Brenda W.J.H. | Pedersen, Nancy L. | Pattaro, Cristian | Parker, Alex N. | Pare, Guillaume | Oostra, Ben A. | O'Donnell, Christopher J. | Nieminen, Markku S. | Nickerson, Deborah A. | Montgomery, Grant W. | Meitinger, Thomas | McPherson, Ruth | McCarthy, Mark I. | McArdle, Wendy | Masson, David | Martin, Nicholas G. | Marroni, Fabio | Mangino, Massimo | Magnusson, Patrik K.E. | Lucas, Gavin | Luben, Robert | Loos, Ruth J. F. | Lokki, Maisa | Lettre, Guillaume | Langenberg, Claudia | Launer, Lenore J. | Lakatta, Edward G. | Laaksonen, Reijo | Kyvik, Kirsten O. | Kronenberg, Florian | König, Inke R. | Khaw, Kay-Tee | Kaprio, Jaakko | Kaplan, Lee M. | Johansson, Åsa | Jarvelin, Marjo-Riitta | Janssens, A. Cecile J.W. | Ingelsson, Erik | Igl, Wilmar | Hovingh, G. Kees | Hottenga, Jouke-Jan | Hofman, Albert | Hicks, Andrew A. | Hengstenberg, Christian | Heid, Iris M. | Hayward, Caroline | Havulinna, Aki S. | Hastie, Nicholas D. | Harris, Tamara B. | Haritunians, Talin | Hall, Alistair S. | Gyllensten, Ulf | Guiducci, Candace | Groop, Leif C. | Gonzalez, Elena | Gieger, Christian | Freimer, Nelson B. | Ferrucci, Luigi | Erdmann, Jeanette | Elliott, Paul | Ejebe, Kenechi G. | Döring, Angela | Dominiczak, Anna F. | Demissie, Serkalem | Deloukas, Panagiotis | de Geus, Eco J.C. | de Faire, Ulf | Crawford, Gabriel | Collins, Francis S. | Chen, Yii-der I. | Caulfield, Mark J. | Campbell, Harry | Burtt, Noel P. | Bonnycastle, Lori L. | Boomsma, Dorret I. | Boekholdt, S. Matthijs | Bergman, Richard N. | Barroso, Inês | Bandinelli, Stefania | Ballantyne, Christie M. | Assimes, Themistocles L. | Quertermous, Thomas | Altshuler, David | Seielstad, Mark | Wong, Tien Y. | Tai, E-Shyong | Feranil, Alan B. | Kuzawa, Christopher W. | Adair, Linda S. | Taylor, Herman A. | Borecki, Ingrid B. | Gabriel, Stacey B. | Wilson, James G. | Stefansson, Kari | Thorsteinsdottir, Unnur | Gudnason, Vilmundur | Krauss, Ronald M. | Mohlke, Karen L. | Ordovas, Jose M. | Munroe, Patricia B. | Kooner, Jaspal S. | Tall, Alan R. | Hegele, Robert A. | Kastelein, John J.P. | Schadt, Eric E. | Rotter, Jerome I. | Boerwinkle, Eric | Strachan, David P. | Mooser, Vincent | Holm, Hilma | Reilly, Muredach P. | Samani, Nilesh J | Schunkert, Heribert | Cupples, L. Adrienne | Sandhu, Manjinder S. | Ridker, Paul M | Rader, Daniel J. | van Duijn, Cornelia M. | Peltonen, Leena | Abecasis, Gonçalo R. | Boehnke, Michael | Kathiresan, Sekar
Nature  2010;466(7307):707-713.
Serum concentrations of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with serum lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 × 10-8), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (e.g., CYP7A1, NPC1L1, and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and impact lipid traits in three non-European populations (East Asians, South Asians, and African Americans). Our results identify several novel loci associated with serum lipids that are also associated with CAD. Finally, we validated three of the novel genes—GALNT2, PPP1R3B, and TTC39B—with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
doi:10.1038/nature09270
PMCID: PMC3039276  PMID: 20686565
20.  Clear detection of ADIPOQ locus as the major gene for plasma adiponectin: results of genome-wide association analyses including 4659 European individuals 
Atherosclerosis  2009;208(2):412-420.
Objective
Plasma adiponectin is strongly associated with various components of metabolic syndrome, type 2 diabetes and cardiovascular outcomes. Concentrations are highly heritable and differ between men and women. We therefore aimed to investigate the genetics of plasma adiponectin in men and women.
Methods
We combined genome-wide association scans of three population-based studies including 4659 persons. For the replication stage in 13795 subjects, we selected the 20 top signals of the combined analysis, as well as the 10 top signals with p-values less than 1.0*10-4 for each the men- and the women-specific analyses. We further selected 73 SNPs that were consistently associated with metabolic syndrome parameters in previous genome-wide association studies to check for their association with plasma adiponectin.
Results
The ADIPOQ locus showed genome-wide significant p-values in the combined (p=4.3*10-24) as well as in both women- and men-specific analyses (p=8.7*10-17 and p=2.5*10-11, respectively). None of the other 39 top signal SNPs showed evidence for association in the replication analysis. None of 73 SNPs from metabolic syndrome loci exhibited association with plasma adiponectin (p>0.01).
Conclusions
We demonstrated the ADIPOQ gene as the only major gene for plasma adiponectin, which explains 6.7% of the phenotypic variance. We further found that neither this gene nor any of the metabolic syndrome loci explained the sex differences observed for plasma adiponectin. Larger studies are needed to identify more moderate genetic determinants of plasma adiponectin.
doi:10.1016/j.atherosclerosis.2009.11.035
PMCID: PMC2845297  PMID: 20018283
adiponectin; genome-wide association study; polymorphism; cardiovascular disease; metabolic syndrome
21.  Genetic variation in LIN28B is associated with the timing of puberty 
Nature genetics  2009;41(6):729-733.
The timing of puberty is highly variable1. We carried out a genome-wide association study for age at menarche in 4,714 women and report an association in LIN28B on chromosome 6 (rs314276, minor allele frequency (MAF) = 0.33, P = 1.5 × 10−8). In independent replication studies in 16,373 women, each major allele was associated with 0.12 years earlier menarche (95% CI = 0.08–0.16; P = 2.8 × 10−10; combined P = 3.6 × 10−16). This allele was also associated with earlier breast development in girls (P = 0.001; N = 4,271); earlier voice breaking (P = 0.006, N = 1,026) and more advanced pubic hair development in boys (P = 0.01; N = 4,588); a faster tempo of height growth in girls (P = 0.00008; N = 4,271) and boys (P = 0.03; N = 4,588); and shorter adult height in women (P = 3.6 × 10−7; N = 17,274) and men (P = 0.006; N = 9,840) in keeping with earlier growth cessation. These studies identify variation in LIN28B, a potent and specific regulator of microRNA processing2, as the first genetic determinant regulating the timing of human pubertal growth and development.
doi:10.1038/ng.382
PMCID: PMC3000552  PMID: 19448623
22.  Eight blood pressure loci identified by genome-wide association study of 34,433 people of European ancestry 
Newton-Cheh, Christopher | Johnson, Toby | Gateva, Vesela | Tobin, Martin D | Bochud, Murielle | Coin, Lachlan | Najjar, Samer S | Zhao, Jing Hua | Heath, Simon C | Eyheramendy, Susana | Papadakis, Konstantinos | Voight, Benjamin F | Scott, Laura J | Zhang, Feng | Farrall, Martin | Tanaka, Toshiko | Wallace, Chris | Chambers, John C | Khaw, Kay-Tee | Nilsson, Peter | van der Harst, Pim | Polidoro, Silvia | Grobbee, Diederick E | Onland-Moret, N Charlotte | Bots, Michiel L | Wain, Louise V | Elliott, Katherine S | Teumer, Alexander | Luan, Jian’an | Lucas, Gavin | Kuusisto, Johanna | Burton, Paul R | Hadley, David | McArdle, Wendy L | Brown, Morris | Dominiczak, Anna | Newhouse, Stephen J | Samani, Nilesh J | Webster, John | Zeggini, Eleftheria | Beckmann, Jacques S | Bergmann, Sven | Lim, Noha | Song, Kijoung | Vollenweider, Peter | Waeber, Gerard | Waterworth, Dawn M | Yuan, Xin | Groop, Leif | Orho-Melander, Marju | Allione, Alessandra | Di Gregorio, Alessandra | Guarrera, Simonetta | Panico, Salvatore | Ricceri, Fulvio | Romanazzi, Valeria | Sacerdote, Carlotta | Vineis, Paolo | Barroso, Inês | Sandhu, Manjinder S | Luben, Robert N | Crawford, Gabriel J. | Jousilahti, Pekka | Perola, Markus | Boehnke, Michael | Bonnycastle, Lori L | Collins, Francis S | Jackson, Anne U | Mohlke, Karen L | Stringham, Heather M | Valle, Timo T | Willer, Cristen J | Bergman, Richard N | Morken, Mario A | Döring, Angela | Gieger, Christian | Illig, Thomas | Meitinger, Thomas | Org, Elin | Pfeufer, Arne | Wichmann, H Erich | Kathiresan, Sekar | Marrugat, Jaume | O’Donnell, Christopher J | Schwartz, Stephen M | Siscovick, David S | Subirana, Isaac | Freimer, Nelson B | Hartikainen, Anna-Liisa | McCarthy, Mark I | O’Reilly, Paul F | Peltonen, Leena | Pouta, Anneli | de Jong, Paul E | Snieder, Harold | van Gilst, Wiek H | Clarke, Robert | Goel, Anuj | Hamsten, Anders | Peden, John F | Seedorf, Udo | Syvänen, Ann-Christine | Tognoni, Giovanni | Lakatta, Edward G | Sanna, Serena | Scheet, Paul | Schlessinger, David | Scuteri, Angelo | Dörr, Marcus | Ernst, Florian | Felix, Stephan B | Homuth, Georg | Lorbeer, Roberto | Reffelmann, Thorsten | Rettig, Rainer | Völker, Uwe | Galan, Pilar | Gut, Ivo G | Hercberg, Serge | Lathrop, G Mark | Zeleneka, Diana | Deloukas, Panos | Soranzo, Nicole | Williams, Frances M | Zhai, Guangju | Salomaa, Veikko | Laakso, Markku | Elosua, Roberto | Forouhi, Nita G | Völzke, Henry | Uiterwaal, Cuno S | van der Schouw, Yvonne T | Numans, Mattijs E | Matullo, Giuseppe | Navis, Gerjan | Berglund, Göran | Bingham, Sheila A | Kooner, Jaspal S | Paterson, Andrew D | Connell, John M | Bandinelli, Stefania | Ferrucci, Luigi | Watkins, Hugh | Spector, Tim D | Tuomilehto, Jaakko | Altshuler, David | Strachan, David P | Laan, Maris | Meneton, Pierre | Wareham, Nicholas J | Uda, Manuela | Jarvelin, Marjo-Riitta | Mooser, Vincent | Melander, Olle | Loos, Ruth JF | Elliott, Paul | Abecasis, Goncalo R | Caulfield, Mark | Munroe, Patricia B
Nature genetics  2009;41(6):666-676.
Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5m genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N≤71,225 European ancestry, N=12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N=29,136). We identified association between systolic or diastolic blood pressure and common variants in 8 regions near the CYP17A1 (P=7×10−24), CYP1A2 (P=1×10−23), FGF5 (P=1×10−21), SH2B3 (P=3×10−18), MTHFR (P=2×10−13), c10orf107 (P=1×10−9), ZNF652 (P=5×10−9) and PLCD3 (P=1×10−8) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.
doi:10.1038/ng.361
PMCID: PMC2891673  PMID: 19430483
23.  Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge 
Saxena, Richa | Hivert, Marie-France | Langenberg, Claudia | Tanaka, Toshiko | Pankow, James S | Vollenweider, Peter | Lyssenko, Valeriya | Bouatia-Naji, Nabila | Dupuis, Josée | Jackson, Anne U | Kao, W H Linda | Li, Man | Glazer, Nicole L | Manning, Alisa K | Luan, Jian’an | Stringham, Heather M | Prokopenko, Inga | Johnson, Toby | Grarup, Niels | Boesgaard, Trine W | Lecoeur, Cécile | Shrader, Peter | O’Connell, Jeffrey | Ingelsson, Erik | Couper, David J | Rice, Kenneth | Song, Kijoung | Andreasen, Camilla H | Dina, Christian | Köttgen, Anna | Le Bacquer, Olivier | Pattou, François | Taneera, Jalal | Steinthorsdottir, Valgerdur | Rybin, Denis | Ardlie, Kristin | Sampson, Michael | Qi, Lu | van Hoek, Mandy | Weedon, Michael N | Aulchenko, Yurii S | Voight, Benjamin F | Grallert, Harald | Balkau, Beverley | Bergman, Richard N | Bielinski, Suzette J | Bonnefond, Amelie | Bonnycastle, Lori L | Borch-Johnsen, Knut | Böttcher, Yvonne | Brunner, Eric | Buchanan, Thomas A | Bumpstead, Suzannah J | Cavalcanti-Proença, Christine | Charpentier, Guillaume | Chen, Yii-Der Ida | Chines, Peter S | Collins, Francis S | Cornelis, Marilyn | Crawford, Gabriel J | Delplanque, Jerome | Doney, Alex | Egan, Josephine M | Erdos, Michael R | Firmann, Mathieu | Forouhi, Nita G | Fox, Caroline S | Goodarzi, Mark O | Graessler, Jürgen | Hingorani, Aroon | Isomaa, Bo | Jørgensen, Torben | Kivimaki, Mika | Kovacs, Peter | Krohn, Knut | Kumari, Meena | Lauritzen, Torsten | Lévy-Marchal, Claire | Mayor, Vladimir | McAteer, Jarred B | Meyre, David | Mitchell, Braxton D | Mohlke, Karen L | Morken, Mario A | Narisu, Narisu | Palmer, Colin N A | Pakyz, Ruth | Pascoe, Laura | Payne, Felicity | Pearson, Daniel | Rathmann, Wolfgang | Sandbaek, Annelli | Sayer, Avan Aihie | Scott, Laura J | Sharp, Stephen J | Sijbrands, Eric | Singleton, Andrew | Siscovick, David S | Smith, Nicholas L | Sparsø, Thomas | Swift, Amy J | Syddall, Holly | Thorleifsson, Gudmar | Tönjes, Anke | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Valle, Timo T | Waeber, Gérard | Walley, Andrew | Waterworth, Dawn M | Zeggini, Eleftheria | Zhao, Jing Hua | Illig, Thomas | Wichmann, H Erich | Wilson, James F | van Duijn, Cornelia | Hu, Frank B | Morris, Andrew D | Frayling, Timothy M | Hattersley, Andrew T | Thorsteinsdottir, Unnur | Stefansson, Kari | Nilsson, Peter | Syvänen, Ann-Christine | Shuldiner, Alan R | Walker, Mark | Bornstein, Stefan R | Schwarz, Peter | Williams, Gordon H | Nathan, David M | Kuusisto, Johanna | Laakso, Markku | Cooper, Cyrus | Marmot, Michael | Ferrucci, Luigi | Mooser, Vincent | Stumvoll, Michael | Loos, Ruth J F | Altshuler, David | Psaty, Bruce M | Rotter, Jerome I | Boerwinkle, Eric | Hansen, Torben | Pedersen, Oluf | Florez, Jose C | McCarthy, Mark I | Boehnke, Michael | Barroso, Inês | Sladek, Robert | Froguel, Philippe | Meigs, James B | Groop, Leif | Wareham, Nicholas J | Watanabe, Richard M
Nature genetics  2010;42(2):142-148.
Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studies (n = 15,234 nondiabetic individuals) and a follow-up of 29 independent loci (n = 6,958–30,620). We identify variants at the GIPR locus associated with 2-h glucose level (rs10423928, β (s.e.m.) = 0.09 (0.01) mmol/l per A allele, P = 2.0 × 10−15). The GIPR A-allele carriers also showed decreased insulin secretion (n = 22,492; insulinogenic index, P = 1.0 × 10−17; ratio of insulin to glucose area under the curve, P = 1.3 × 10−16) and diminished incretin effect (n = 804; P = 4.3 × 10−4). We also identified variants at ADCY5 (rs2877716, P = 4.2 × 10−16), VPS13C (rs17271305, P = 4.1 × 10−8), GCKR (rs1260326, P = 7.1 × 10−11) and TCF7L2 (rs7903146, P = 4.2 × 10−10) associated with 2-h glucose. Of the three newly implicated loci (GIPR, ADCY5 and VPS13C), only ADCY5 was found to be associated with type 2 diabetes in collaborating studies (n = 35,869 cases, 89,798 controls, OR = 1.12, 95% CI 1.09–1.15, P = 4.8 × 10−18).
doi:10.1038/ng.521
PMCID: PMC2922003  PMID: 20081857
24.  Genetic Loci Influencing C-reactive Protein Levels and Risk of Coronary Heart Disease 
Context:
Plasma levels of C-reactive protein (CRP) are independently associated with risk of coronary heart disease, but whether CRP is causally associated with coronary heart disease or merely a marker of underlying atherosclerosis is uncertain.
Objective:
To investigate association of genetic loci with CRP levels and risk of coronary heart disease.
Design, setting and participants:
We first carried out a genome-wide association (n=17,967) and replication study (n=14,747) to identify genetic loci associated with plasma CRP concentrations. Data collection took place between 1989 and 2008 and genotyping between 2003 and 2008. We carried out a Mendelian randomisation study of the most closely associated SNP in the CRP locus and published data on other CRP variants involving a total of 28,112 cases and 100,823 controls, to investigate the association of CRP variants with coronary heart disease. We compared our finding with that predicted from meta-analysis of observational studies of CRP levels and risk of coronary heart disease. For the other loci associated with CRP levels, we selected the most closely associated SNP for testing against coronary heart disease among 14,365 cases and 32,069 controls.
Main outcome measure:
Risk of coronary heart disease.
Results:
Polymorphisms in five genetic loci were strongly associated with CRP levels (% difference per minor allele): SNP rs6700896 in LEPR (−14.7% [95% Confidence Interval {CI}], −17.5 – −11.9, P=1.6×10−21), rs4537545 in IL6R (−10.8% [95% CI, −13.8 – −7.7], P=5.1×10−11), rs7553007 in CRP locus (−20.7% [95% CI, −23.5 – −17.9], P=3.3×10−38), rs1183910 in HNF1A (−13.6% [95% CI, −16.4 – −10.6], P=1.2×10−17) and rs4420638 in APOE-CI-CII (−21.8% [95% CI, −25.4 – −18.1], P=2.1×10−25). Association of SNP rs7553007 in the CRP locus with coronary heart disease gave odds ratio (OR) 0.98 (95% CI, 0.94 – 1.01) per 20% lower CRP. Our Mendelian randomisation study of variants in the CRP locus showed no association with coronary heart disease: OR 1.00 (95% CI, 0.97 – 1.02) per 20% lower CRP, compared with OR 0.94 (95% CI, 0.94 – 0.95) predicted from meta-analysis of the observational studies of CRP levels and coronary heart disease (Z-score −3.45, P<.001). SNPs rs6700896 in LEPR (OR 1.06 [95% CI, 1.02 – 1.09] per minor allele), rs4537545 in IL6R (OR 0.94 [95% CI, 0.91 – 0.97]) and rs4420638 in the APOE-CI-CII cluster (OR 1.16 [95% CI, 1.12 – 1.21]) were all associated with risk of coronary heart disease.
Conclusions:
The lack of concordance between the effect on coronary heart disease risk of CRP genotypes and CRP levels argues against a causal association of CRP with coronary heart disease.
doi:10.1001/jama.2009.954
PMCID: PMC2803020  PMID: 19567438
25.  Correction: Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution 
Lindgren, Cecilia M. | Heid, Iris M. | Randall, Joshua C. | Lamina, Claudia | Steinthorsdottir, Valgerdur | Qi, Lu | 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 | Lyon, Helen N. | Rivadeneira, Fernando | Sanna, Serena | Timpson, Nicholas J. | Zillikens, M. Carola | Zhao, Jing Hua | 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. | Hofman, Albert | 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. | Scott, Laura J. | Scuteri, Angelo | Silander, Kaisa | Song, Kijoung | Yuan, Xin | 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. | Hu, Frank B. | 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. | Watkins for the PROCARDIS consortia, Hugh | Waterworth, Dawn M. | Boehnke, Michael | Deloukas, Panos | Groop, Leif | Hunter, David J. | Thorsteinsdottir, Unnur | Schlessinger, David | Wichmann, H.-Erich | Frayling, Timothy M. | Abecasis, Gonçalo R. | Hirschhorn, Joel N. | Loos, Ruth J. F. | Stefansson, Kari | Mohlke, Karen L. | Barroso, Inês | McCarthy for the GIANT consortium, Mark I.
PLoS Genetics  2009;5(7):10.1371/annotation/b6e8f9f6-2496-4a40-b0e3-e1d1390c1928.
doi:10.1371/annotation/b6e8f9f6-2496-4a40-b0e3-e1d1390c1928
PMCID: PMC2722420

Results 1-25 (31)