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1.  Meta-analysis of genome-wide association studies in five cohorts reveals common variants in RBFOX1, a regulator of tissue-specific splicing, associated with refractive error 
Human Molecular Genetics  2013;22(13):2754-2764.
Visual refractive errors (REs) are complex genetic traits with a largely unknown etiology. To date, genome-wide association studies (GWASs) of moderate size have identified several novel risk markers for RE, measured here as mean spherical equivalent (MSE). We performed a GWAS using a total of 7280 samples from five cohorts: the Age-Related Eye Disease Study (AREDS); the KORA study (‘Cooperative Health Research in the Region of Augsburg’); the Framingham Eye Study (FES); the Ogliastra Genetic Park-Talana (OGP-Talana) Study and the Multiethnic Study of Atherosclerosis (MESA). Genotyping was performed on Illumina and Affymetrix platforms with additional markers imputed to the HapMap II reference panel. We identified a new genome-wide significant locus on chromosome 16 (rs10500355, P = 3.9 × 10−9) in a combined discovery and replication set (26 953 samples). This single nucleotide polymorphism (SNP) is located within the RBFOX1 gene which is a neuron-specific splicing factor regulating a wide range of alternative splicing events implicated in neuronal development and maturation, including transcription factors, other splicing factors and synaptic proteins.
doi:10.1093/hmg/ddt116
PMCID: PMC3674806  PMID: 23474815
2.  Acute-Phase Serum Amyloid A Protein and Its Implication in the Development of Type 2 Diabetes in the KORA S4/F4 Study 
Diabetes Care  2013;36(5):1321-1326.
OBJECTIVE
We sought to investigate whether elevated levels of acute-phase serum amyloid A (A-SAA) protein precede the onset of type 2 diabetes independently of other risk factors, including parameters of glucose metabolism.
RESEARCH DESIGN AND METHODS
Within the population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 study, we measured A-SAA concentrations in 836 initially nondiabetic subjects (55–74 years of age) without clinically overt inflammation who participated in a 7-year follow-up examination including an oral glucose tolerance test.
RESULTS
A-SAA concentrations were significantly associated with incident type 2 diabetes (odds ratio [OR] for a one-SD increase of A-SAA adjusted for age and sex = 1.28 [95% CI 1.08–1.53], P = 0.005), particularly in younger subjects (P value for interaction = 0.047). The association attenuated when adjusting for parameters of glucose metabolism (fasting glucose, fasting insulin, HbA1c, and 2-h glucose; OR 1.16 [0.95–1.42], P = 0.15). Similar analyses for high-sensitive C-reactive protein (hs-CRP) yielded the following ORs: 1.39 (1.10–1.68, P = 0.0006) and 1.13 (0.88–1.45, P = 0.34), respectively. In contrast, A-SAA concentrations were significantly associated with 2-h glucose levels at follow-up even after adjustment for parameters of glucose metabolism (P = 0.008, n = 803).
CONCLUSIONS
Our findings indicate similarly strong prospective associations with type 2 diabetes for A-SAA and hs-CRP and suggest a potential causal link via postchallenge hyperglycemia.
doi:10.2337/dc12-1514
PMCID: PMC3631869  PMID: 23238662
3.  Identification of seven loci affecting mean telomere length and their association with disease 
Codd, Veryan | Nelson, Christopher P. | Albrecht, Eva | Mangino, Massimo | Deelen, Joris | Buxton, Jessica L. | Jan Hottenga, Jouke | Fischer, Krista | Esko, Tõnu | Surakka, Ida | Broer, Linda | Nyholt, Dale R. | Mateo Leach, Irene | Salo, Perttu | Hägg, Sara | Matthews, Mary K. | Palmen, Jutta | Norata, Giuseppe D. | O’Reilly, Paul F. | Saleheen, Danish | Amin, Najaf | Balmforth, Anthony J. | Beekman, Marian | de Boer, Rudolf A. | Böhringer, Stefan | Braund, Peter S. | Burton, Paul R. | de Craen, Anton J. M. | Denniff, Matthew | Dong, Yanbin | Douroudis, Konstantinos | Dubinina, Elena | Eriksson, Johan G. | Garlaschelli, Katia | Guo, Dehuang | Hartikainen, Anna-Liisa | Henders, Anjali K. | Houwing-Duistermaat, Jeanine J. | Kananen, Laura | Karssen, Lennart C. | Kettunen, Johannes | Klopp, Norman | Lagou, Vasiliki | van Leeuwen, Elisabeth M. | Madden, Pamela A. | Mägi, Reedik | Magnusson, Patrik K.E. | Männistö, Satu | McCarthy, Mark I. | Medland, Sarah E. | Mihailov, Evelin | Montgomery, Grant W. | Oostra, Ben A. | Palotie, Aarno | Peters, Annette | Pollard, Helen | Pouta, Anneli | Prokopenko, Inga | Ripatti, Samuli | Salomaa, Veikko | Suchiman, H. Eka D. | Valdes, Ana M. | Verweij, Niek | Viñuela, Ana | Wang, Xiaoling | Wichmann, H.-Erich | Widen, Elisabeth | Willemsen, Gonneke | Wright, Margaret J. | Xia, Kai | Xiao, Xiangjun | van Veldhuisen, Dirk J. | Catapano, Alberico L. | Tobin, Martin D. | Hall, Alistair S. | Blakemore, Alexandra I.F. | van Gilst, Wiek H. | Zhu, Haidong | Erdmann, Jeanette | Reilly, Muredach P. | Kathiresan, Sekar | Schunkert, Heribert | Talmud, Philippa J. | Pedersen, Nancy L. | Perola, Markus | Ouwehand, Willem | Kaprio, Jaakko | Martin, Nicholas G. | van Duijn, Cornelia M. | Hovatta, Iiris | Gieger, Christian | Metspalu, Andres | Boomsma, Dorret I. | Jarvelin, Marjo-Riitta | Slagboom, P. Eline | Thompson, John R. | Spector, Tim D. | van der Harst, Pim | Samani, Nilesh J.
Nature genetics  2013;45(4):422-427e2.
Inter-individual variation in mean leukocyte telomere length (LTL) is associated with cancer and several age-associated diseases. Here, in a genome-wide meta-analysis of 37,684 individuals with replication of selected variants in a further 10,739 individuals, we identified seven loci, including five novel loci, associated with mean LTL (P<5x10−8). Five of the loci contain genes (TERC, TERT, NAF1, OBFC1, RTEL1) that are known to be involved in telomere biology. Lead SNPs at two loci (TERC and TERT) associate with several cancers and other diseases, including idiopathic pulmonary fibrosis. Moreover, a genetic risk score analysis combining lead variants at all seven loci in 22,233 coronary artery disease cases and 64,762 controls showed an association of the alleles associated with shorter LTL with increased risk of CAD (21% (95% CI: 5–35%) per standard deviation in LTL, p=0.014). Our findings support a causal role of telomere length variation in some age-related diseases.
doi:10.1038/ng.2528
PMCID: PMC4006270  PMID: 23535734
4.  Dilution of candidates: the case of iron-related genes in restless legs syndrome 
Restless legs syndrome (RLS) is a common multifactorial disease. Some genetic risk factors have been identified. RLS susceptibility also has been related to iron. We therefore asked whether known iron-related genes are candidates for association with RLS and, vice versa, whether known RLS-associated loci influence iron parameters in serum. RLS/control samples (n=954/1814 in the discovery step, 735/736 in replication 1, and 736/735 in replication 2) were tested for association with SNPs located within 4 Mb intervals surrounding each gene from a list of 111 iron-related genes using a discovery threshold of P=5 × 10−4. Two population cohorts (KORA F3 and F4 with together n=3447) were tested for association of six known RLS loci with iron, ferritin, transferrin, transferrin-saturation, and soluble transferrin receptor. Results were negative. None of the candidate SNPs at the iron-related gene loci was confirmed significantly. An intronic SNP, rs2576036, of KATNAL2 at 18q21.1 was significant in the first (P=0.00085) but not in the second replication step (joint nominal P-value=0.044). Especially, rs1800652 (C282Y) in the HFE gene did not associate with RLS. Moreover, SNPs at the known RLS loci did not significantly affect serum iron parameters in the KORA cohorts. In conclusion, the correlation between RLS and iron parameters in serum may be weaker than assumed. Moreover, in a general power analysis, we show that genetic effects are diluted if they are transmitted via an intermediate trait to an end-phenotype. Sample size formulas are provided for small effect sizes.
doi:10.1038/ejhg.2012.193
PMCID: PMC3598324  PMID: 22929029
restless legs syndrome; iron parameters; MEIS1 haplotype; power calculation; linear regression; logistic regression
5.  Contemporary paternal genetic landscape of Polish and German populations: from early medieval Slavic expansion to post-World War II resettlements 
Homogeneous Proto-Slavic genetic substrate and/or extensive mixing after World War II were suggested to explain homogeneity of contemporary Polish paternal lineages. Alternatively, Polish local populations might have displayed pre-war genetic heterogeneity owing to genetic drift and/or gene flow with neighbouring populations. Although sharp genetic discontinuity along the political border between Poland and Germany indisputably results from war-mediated resettlements and homogenisation, it remained unknown whether Y-chromosomal diversity in ethnically/linguistically defined populations was clinal or discontinuous before the war. In order to answer these questions and elucidate early Slavic migrations, 1156 individuals from several Slavic and German populations were analysed, including Polish pre-war regional populations and an autochthonous Slavic population from Germany. Y chromosomes were assigned to 39 haplogroups and genotyped for 19 STRs. Genetic distances revealed similar degree of differentiation of Slavic-speaking pre-war populations from German populations irrespective of duration and intensity of contacts with German speakers. Admixture estimates showed minor Slavic paternal ancestry (∼20%) in modern eastern Germans and hardly detectable German paternal ancestry in Slavs neighbouring German populations for centuries. BATWING analysis of isolated Slavic populations revealed that their divergence was preceded by rapid demographic growth, undermining theory that Slavic expansion was primarily linguistic rather than population spread. Polish pre-war regional populations showed within-group heterogeneity and lower STR variation within R-M17 subclades compared with modern populations, which might have been homogenised by war resettlements. Our results suggest that genetic studies on early human history in the Vistula and Oder basins should rely on reconstructed pre-war rather than modern populations.
doi:10.1038/ejhg.2012.190
PMCID: PMC3598329  PMID: 22968131
Y chromosome; demography; admixture; Slavs; Poland; Germany
6.  Interrogating causal pathways linking genetic variants, small molecule metabolites, and circulating lipids 
Genome Medicine  2014;6(3):25.
Background
Emerging technologies based on mass spectrometry or nuclear magnetic resonance enable the monitoring of hundreds of small metabolites from tissues or body fluids. Profiling of metabolites can help elucidate causal pathways linking established genetic variants to known disease risk factors such as blood lipid traits.
Methods
We applied statistical methodology to dissect causal relationships between single nucleotide polymorphisms, metabolite concentrations, and serum lipid traits, focusing on 95 genetic loci reproducibly associated with the four main serum lipids (total-, low-density lipoprotein-, and high-density lipoprotein- cholesterol and triglycerides). The dataset used included 2,973 individuals from two independent population-based cohorts with data for 151 small molecule metabolites and four main serum lipids. Three statistical approaches, namely conditional analysis, Mendelian randomization, and structural equation modeling, were compared to investigate causal relationship at sets of a single nucleotide polymorphism, a metabolite, and a lipid trait associated with one another.
Results
A subset of three lipid-associated loci (FADS1, GCKR, and LPA) have a statistically significant association with at least one main lipid and one metabolite concentration in our data, defining a total of 38 cross-associated sets of a single nucleotide polymorphism, a metabolite and a lipid trait. Structural equation modeling provided sufficient discrimination to indicate that the association of a single nucleotide polymorphism with a lipid trait was mediated through a metabolite at 15 of the 38 sets, and involving variants at the FADS1 and GCKR loci.
Conclusions
These data provide a framework for evaluating the causal role of components of the metabolome (or other intermediate factors) in mediating the association between established genetic variants and diseases or traits.
doi:10.1186/gm542
PMCID: PMC4062056  PMID: 24678845
7.  The procoagulant effects of fine particulate matter in vivo 
Inhalation of fine particulate matter (<2.5 μm; fine PM) has been shown to increase the risk for cardiovascular events. In this letter, we reappraise the role of tissue factor (TF) antigen and we also summarize changes in measured coagulation proteins in humans and rodents by other studies with fine PM. By considering all studies including ours, we conclude that monitoring the overall coagulation state by measuring capacity assays such as thrombin generation, and quantification of TF activity would be more suitable than determining single coagulation proteins (such as TF antigen) in order to better assess the systemic prothrombotic effects of fine PM.
doi:10.1186/1743-8977-8-12
PMCID: PMC3068090  PMID: 21406084
8.  Correction: Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease 
Jones, Lesley | Holmans, Peter A. | Hamshere, Marian L. | Harold, Denise | Moskvina, Valentina | Ivanov, Dobril | Pocklington, Andrew | Abraham, Richard | Hollingworth, Paul | Sims, Rebecca | Gerrish, Amy | Pahwa, Jaspreet Singh | Jones, Nicola | Stretton, Alexandra | Morgan, Angharad R. | Lovestone, Simon | Powell, John | Proitsi, Petroula | Lupton, Michelle K. | Brayne, Carol | Rubinsztein, David C. | Gill, Michael | Lawlor, Brian | Lynch, Aoibhinn | Morgan, Kevin | Brown, Kristelle S. | Passmore, Peter A. | Craig, David | McGuinness, Bernadette | Todd, Stephen | Holmes, Clive | Mann, David | Smith, A. David | Love, Seth | Kehoe, Patrick G. | Mead, Simon | Fox, Nick | Rossor, Martin | Collinge, John | Maier, Wolfgang | Jessen, Frank | Schürmann, Britta | van den Bussche, Hendrik | Heuser, Isabella | Peters, Oliver | Kornhuber, Johannes | Wiltfang, Jens | Dichgans, Martin | Frölich, Lutz | Hampel, Harald | Hüll, Michael | Rujescu, Dan | Goate, Alison M. | Kauwe, John S. K. | Cruchaga, Carlos | Nowotny, Petra | Morris, John C. | Mayo, Kevin | Livingston, Gill | Bass, Nicholas J. | Gurling, Hugh | McQuillin, Andrew | Gwilliam, Rhian | Deloukas, Panos | Al-Chalabi, Ammar | Shaw, Christopher E. | Singleton, Andrew B. | Guerreiro, Rita | Mühleisen, Thomas W. | Nöthen, Markus M. | Moebus, Susanne | Jöckel, Karl-Heinz | Klopp, Norman | Wichmann, H.-Erich | Rüther, Eckhard | Carrasquillo, Minerva M. | Pankratz, V. Shane | Younkin, Steven G. | Hardy, John | O'Donovan, Michael C. | Owen, Michael J. | Williams, Julie
PLoS ONE  2011;6(2):10.1371/annotation/a0bb886d-d345-4a20-a82e-adce9b047798.
doi:10.1371/annotation/a0bb886d-d345-4a20-a82e-adce9b047798
PMCID: PMC3039022
9.  Impact of Ambient Air Pollution on the Differential White Blood Cell Count in Patients with Chronic Pulmonary Disease 
Inhalation toxicology  2010;22(3):10.3109/08958370903207274.
Epidemiologic studies report associations between particulate air pollution and increased mortality from pulmonary diseases.To examine whether the exposure to ambient gaseous and particulate air pollution leads to an alteration of the differential white blood cell count in patients with chronic pulmonary diseases like chronic bronchitis, chronic obstructive pulmonary disease, and asthma.
A prospective panel study was conducted in Erfurt, Eastern Germany, with 12 repeated differential white blood cell counts in 38 males with chronic pulmonary diseases. Hourly particulate and gaseous air pollutants and meteorological data were acquired. Mixed models with a random intercept adjusting for trend, meteorology, weekday, and other risk variables were used.
In this explorative analysis we found an immediate decrease of polymorphonuclear leukocytes in response to an increase of most gaseous and particulate pollutants. Lymphocytes increased within 24 hours in association with all gaseous pollutants but showed no effect in regard to particulate air pollution. Monocytes showed an increase associated with ultrafine particles, and nitrogen monoxide. The effect had two peaks in time, one 0-23 hours before blood withdrawal and a second one with a time lag of 48-71 hours.
The increase of particulate and gaseous air pollution was associated with multiple changes in the differential white blood cell count in patients with chronic pulmonary diseases.
doi:10.3109/08958370903207274
PMCID: PMC3877919  PMID: 20064088
air pollution; C-reactive protein; PM10; differential white blood cell count; ultrafine particles
10.  A genome-wide association study of anorexia nervosa 
Boraska, Vesna | Franklin, Christopher S | Floyd, James AB | Thornton, Laura M | Huckins, Laura M | Southam, Lorraine | Rayner, N William | Tachmazidou, Ioanna | Klump, Kelly L | Treasure, Janet | Lewis, Cathryn M | Schmidt, Ulrike | Tozzi, Federica | Kiezebrink, Kirsty | Hebebrand, Johannes | Gorwood, Philip | Adan, Roger AH | Kas, Martien JH | Favaro, Angela | Santonastaso, Paolo | Fernández-Aranda, Fernando | Gratacos, Monica | Rybakowski, Filip | Dmitrzak-Weglarz, Monika | Kaprio, Jaakko | Keski-Rahkonen, Anna | Raevuori, Anu | Van Furth, Eric F | Slof-Op t Landt, Margarita CT | Hudson, James I | Reichborn-Kjennerud, Ted | Knudsen, Gun Peggy S | Monteleone, Palmiero | Kaplan, Allan S | Karwautz, Andreas | Hakonarson, Hakon | Berrettini, Wade H | Guo, Yiran | Li, Dong | Schork, Nicholas J. | Komaki, Gen | Ando, Tetsuya | Inoko, Hidetoshi | Esko, Tõnu | Fischer, Krista | Männik, Katrin | Metspalu, Andres | Baker, Jessica H | Cone, Roger D | Dackor, Jennifer | DeSocio, Janiece E | Hilliard, Christopher E | O’Toole, Julie K | Pantel, Jacques | Szatkiewicz, Jin P | Taico, Chrysecolla | Zerwas, Stephanie | Trace, Sara E | Davis, Oliver SP | Helder, Sietske | Bühren, Katharina | Burghardt, Roland | de Zwaan, Martina | Egberts, Karin | Ehrlich, Stefan | Herpertz-Dahlmann, Beate | Herzog, Wolfgang | Imgart, Hartmut | Scherag, André | Scherag, Susann | Zipfel, Stephan | Boni, Claudette | Ramoz, Nicolas | Versini, Audrey | Brandys, Marek K | Danner, Unna N | de Kovel, Carolien | Hendriks, Judith | Koeleman, Bobby PC | Ophoff, Roel A | Strengman, Eric | van Elburg, Annemarie A | Bruson, Alice | Clementi, Maurizio | Degortes, Daniela | Forzan, Monica | Tenconi, Elena | Docampo, Elisa | Escaramís, Geòrgia | Jiménez-Murcia, Susana | Lissowska, Jolanta | Rajewski, Andrzej | Szeszenia-Dabrowska, Neonila | Slopien, Agnieszka | Hauser, Joanna | Karhunen, Leila | Meulenbelt, Ingrid | Slagboom, P Eline | Tortorella, Alfonso | Maj, Mario | Dedoussis, George | Dikeos, Dimitris | Gonidakis, Fragiskos | Tziouvas, Konstantinos | Tsitsika, Artemis | Papezova, Hana | Slachtova, Lenka | Martaskova, Debora | Kennedy, James L. | Levitan, Robert D. | Yilmaz, Zeynep | Huemer, Julia | Koubek, Doris | Merl, Elisabeth | Wagner, Gudrun | Lichtenstein, Paul | Breen, Gerome | Cohen-Woods, Sarah | Farmer, Anne | McGuffin, Peter | Cichon, Sven | Giegling, Ina | Herms, Stefan | Rujescu, Dan | Schreiber, Stefan | Wichmann, H-Erich | Dina, Christian | Sladek, Rob | Gambaro, Giovanni | Soranzo, Nicole | Julia, Antonio | Marsal, Sara | Rabionet, Raquel | Gaborieau, Valerie | Dick, Danielle M | Palotie, Aarno | Ripatti, Samuli | Widén, Elisabeth | Andreassen, Ole A | Espeseth, Thomas | Lundervold, Astri | Reinvang, Ivar | Steen, Vidar M | Le Hellard, Stephanie | Mattingsdal, Morten | Ntalla, Ioanna | Bencko, Vladimir | Foretova, Lenka | Janout, Vladimir | Navratilova, Marie | Gallinger, Steven | Pinto, Dalila | Scherer, Stephen | Aschauer, Harald | Carlberg, Laura | Schosser, Alexandra | Alfredsson, Lars | Ding, Bo | Klareskog, Lars | Padyukov, Leonid | Finan, Chris | Kalsi, Gursharan | Roberts, Marion | Logan, Darren W | Peltonen, Leena | Ritchie, Graham RS | Barrett, Jeffrey C | Estivill, Xavier | Hinney, Anke | Sullivan, Patrick F | Collier, David A | Zeggini, Eleftheria | Bulik, Cynthia M
Molecular psychiatry  2010;16(9):10.1038/mp.2010.107.
Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2,907 cases with AN from 14 countries (15 sites) and 14,860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery datasets. Seventy-six (72 independent) SNPs were taken forward for in silico (two datasets) or de novo (13 datasets) replication genotyping in 2,677 independent AN cases and 8,629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication datasets comprised 5,551 AN cases and 21,080 controls. AN subtype analyses (1,606 AN restricting; 1,445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01×10−7) in SOX2OT and rs17030795 (P=5.84×10−6) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76×10−6) between CUL3 and FAM124B and rs1886797 (P=8.05×10−6) near SPATA13. Comparing discovery to replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P= 4×10−6), strongly suggesting that true findings exist but that our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.
doi:10.1038/mp.2010.107
PMCID: PMC3859494  PMID: 21079607
anorexia nervosa; eating disorders; GWAS; genome-wide association study; body mass index; metabolic
11.  Human metabolic individuality in biomedical and pharmaceutical research 
Nature  2011;477(7362):10.1038/nature10354.
SUMMARY
Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 exhibit effect sizes that are unusually high for GWAS and account for 10-60% of metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism, and Crohn’s disease. Taken together our study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.
doi:10.1038/nature10354
PMCID: PMC3832838  PMID: 21886157
12.  Joint Analysis of Individual Participants’ Data from 17 Studies on the Association of the IL6 Variant -174G>C with Circulating Glucose Levels, Interleukin-6 Levels, and Body-Mass Index 
Annals of medicine  2009;41(2):128-138.
Background
Several studies have investigated associations between the -174G>C polymorphism (rs1800795) of the IL6-gene, but presented inconsistent results.
Aims
This joint analysis aimed to clarify whether IL6 -174G>C was associated with type 2 diabetes mellitus (T2DM) related quantitative phenotypes.
Methods
Individual-level data from all studies of the IL6-T2DM consortium on Caucasian subjects with available BMI were collected. As study-specific estimates did not show heterogeneity (P>0.1), they were combined by using the inverse-variance fixed-effect model.
Results
The main analysis included 9440, 7398, 24,117, or 5659 nondiabetic and manifest T2DM subjects for fasting glucose, 2-hour glucose, BMI or circulating interleukin-6 levels, respectively. IL6 -174 C-allele carriers had significantly lower fasting glucose (−0.091mmol/L, P=0.014). There was no evidence for association between IL6 -174G>C and BMI or interleukin-6. In an additional analysis of 641 subjects known to develop T2DM later on, the IL6 -174 CC-genotype was associated with higher baseline interleukin-6 (+0.75pg/mL, P=0.004), which was consistent with higher interleukin-6 in the 966 manifest T2DM subjects (+0.50pg/mL, P=0.044).
Conclusions
Our data suggest association between IL6 -174G>C and quantitative glucose, and exploratory analysis indicated modulated interleukin-6 levels in pre-diabetic subjects, being in-line with this SNP’s previously reported T2DM association and a role of circulating interleukin-6 as intermediate phenotype.
doi:10.1080/07853890802337037
PMCID: PMC3801210  PMID: 18752089
blood glucose; body mass index; diabetes mellitus; type 2; epidemiology; molecular; genes; inflammation mediators; interleukin-6; intermediate phenotype; meta-analysis; polymorphism; single nucleotide
13.  A Meta-Analysis of Genome-Wide Association Studies of the Electrocardiographic Early Repolarization Pattern 
Background
The early repolarization pattern (ERP) is common and associated with risk of sudden cardiac death. ERP is heritable and mutations have been described in syndromatic cases.
Objective
To conduct a meta-analysis of genome-wide association studies (GWAS) to identify common genetic variants influencing ERP.
Methods
We ascertained ERP based on electrocardiograms in three large community-based cohorts from Europe and the US: the Framingham Heart Study, the Health 2000 Study, and the KORA F4 Study. We analyzed GWAS in participants with and without ERP by logistic regression assuming an additive genetic model and meta-analyzed individual cohort results. We then sought to strengthen support for findings that reached p≤1×10−5 in independent individuals by direct genotyping or in-silico analysis of genome-wide data. We meta-analyzed the results from both stages.
Results
Of 7482 individuals in the discovery stage, 452 showed ERP (ERP positive: mean age 46.9±8.9 years, 30.3% women; ERP negative: 47.5±9.4 years, 54.2% women). After meta-analysis, eight single nucleotide polymorphisms reached p≤1×10−5: The most significant finding was intergenic rs11653989 (odds ratio 0.47; 95% confidence interval 0.36–0.61; p=6.9×10−9). The most biologically relevant finding was intronic to KCND3: rs17029069 (odds ratio 1.46; 95% confidence interval 1.25–1.69; p=8.5×10−7). In the replication step (7151 individuals), none of the eight variants replicated, and combined meta-analysis results failed to reach genome-wide significance.
Conclusions
In a GWAS, we were not able to reliably identify genetic variants predisposing to ERP, presumably due to insufficient statistical power and phenotype heterogeneity. The reported heritability of ERP warrants continued investigation in larger well-phenotyped populations.
doi:10.1016/j.hrthm.2012.06.008
PMCID: PMC3459269  PMID: 22683750
Early repolarization; Sudden cardiac death; Arrhythmia; GWAS; Meta-analysis; Electrocardiogram
14.  Previous Lung Diseases and Lung Cancer Risk: A Pooled Analysis From the International Lung Cancer Consortium 
American Journal of Epidemiology  2012;176(7):573-585.
To clarify the role of previous lung diseases (chronic bronchitis, emphysema, pneumonia, and tuberculosis) in the development of lung cancer, the authors conducted a pooled analysis of studies in the International Lung Cancer Consortium. Seventeen studies including 24,607 cases and 81,829 controls (noncases), mainly conducted in Europe and North America, were included (1984–2011). Using self-reported data on previous diagnoses of lung diseases, the authors derived study-specific effect estimates by means of logistic regression models or Cox proportional hazards models adjusted for age, sex, and cumulative tobacco smoking. Estimates were pooled using random-effects models. Analyses stratified by smoking status and histology were also conducted. A history of emphysema conferred a 2.44-fold increased risk of lung cancer (95% confidence interval (CI): 1.64, 3.62 (16 studies)). A history of chronic bronchitis conferred a relative risk of 1.47 (95% CI: 1.29, 1.68 (13 studies)). Tuberculosis (relative risk = 1.48, 95% CI: 1.17, 1.87 (16 studies)) and pneumonia (relative risk = 1.57, 95% CI: 1.22, 2.01 (12 studies)) were also associated with lung cancer risk. Among never smokers, elevated risks were observed for emphysema, pneumonia, and tuberculosis. These results suggest that previous lung diseases influence lung cancer risk independently of tobacco use and that these diseases are important for assessing individual risk.
doi:10.1093/aje/kws151
PMCID: PMC3530374  PMID: 22986146
bronchitis; chronic; emphysema; lung diseases; lung neoplasms; meta-analysis; pneumonia; pulmonary disease; chronic obstructive; tuberculosis
15.  A genomewide perspective of genetic variation in human metabolism 
Nature genetics  2009;42(2):137-141.
Serum metabolite concentrations provide a direct readout of biological processes in the human body, and are associated with disorders such as cardiovascular and metabolic diseases. Here we present a genome-wide association study with 163 metabolic traits using 1809 participants from the KORA population, followed up in the TwinsUK cohort with 422 participants. In eight out of nine replicated loci (FADS1, ELOVL2, ACADS, ACADM, ACADL, SPTLC3, ETFDH, SLC16A9) the genetic variant is located in or near enzyme or solute carrier coding genes, where the associating metabolic traits match the proteins’ function. Many of these loci are located in rate limiting steps of important enzymatic reactions. Use of metabolite concentration ratios as proxies for enzymatic reaction rates reduces the variance and yields robust statistical associations with p-values between 3×10−24 and 6.5×10−179. These loci explained 5.6% to 36.3% of the observed variance. For several loci, associations with clinically relevant parameters have previously been reported.
doi:10.1038/ng.507
PMCID: PMC3773904  PMID: 20037589
16.  Common variants at 12q15 and 12q24 are associated with infant head circumference 
Taal, H Rob | Pourcain, Beate St | Thiering, Elisabeth | Das, Shikta | Mook-Kanamori, Dennis O | Warrington, Nicole M | Kaakinen, Marika | Kreiner-Møller, Eskil | Bradfield, Jonathan P | Freathy, Rachel M | Geller, Frank | Guxens, Mònica | Cousminer, Diana L | Kerkhof, Marjan | Timpson, Nicholas J | Ikram, M Arfan | Beilin, Lawrence J | Bønnelykke, Klaus | Buxton, Jessica L | Charoen, Pimphen | Chawes, Bo Lund Krogsgaard | Eriksson, Johan | Evans, David M | Hofman, Albert | Kemp, John P | Kim, Cecilia E | Klopp, Norman | Lahti, Jari | Lye, Stephen J | McMahon, George | Mentch, Frank D | Müller, Martina | O’Reilly, Paul F | Prokopenko, Inga | Rivadeneira, Fernando | Steegers, Eric A P | Sunyer, Jordi | Tiesler, Carla | Yaghootkar, Hanieh | Breteler, Monique M B | Debette, Stephanie | Fornage, Myriam | Gudnason, Vilmundur | Launer, Lenore J | van der Lugt, Aad | Mosley, Thomas H | Seshadri, Sudha | Smith, Albert V | Vernooij, Meike W | Blakemore, Alexandra IF | Chiavacci, Rosetta M | Feenstra, Bjarke | Fernandez-Benet, Julio | Grant, Struan F A | Hartikainen, Anna-Liisa | van der Heijden, Albert J | Iñiguez, Carmen | Lathrop, Mark | McArdle, Wendy L | Mølgaard, Anne | Newnham, John P | Palmer, Lyle J | Palotie, Aarno | Pouta, Annneli | Ring, Susan M | Sovio, Ulla | Standl, Marie | Uitterlinden, Andre G | Wichmann, H-Erich | Vissing, Nadja Hawwa | DeCarli, Charles | van Duijn, Cornelia M | McCarthy, Mark I | Koppelman, Gerard H. | Estivill, Xavier | Hattersley, Andrew T | Melbye, Mads | Bisgaard, Hans | Pennell, Craig E | Widen, Elisabeth | Hakonarson, Hakon | Smith, George Davey | Heinrich, Joachim | Jarvelin, Marjo-Riitta | Jaddoe, Vincent W V
Nature genetics  2012;44(5):532-538.
To identify genetic variants associated with head circumference in infancy, we performed a meta-analysis of seven genome-wide association (GWA) studies (N=10,768 from European ancestry enrolled in pregnancy/birth cohorts) and followed up three lead signals in six replication studies (combined N=19,089). Rs7980687 on chromosome 12q24 (P=8.1×10−9), and rs1042725 on chromosome 12q15 (P=2.8×10−10) were robustly associated with head circumference in infancy. Although these loci have previously been associated with adult height1, their effects on infant head circumference were largely independent of height (P=3.8×10−7 for rs7980687, P=1.3×10−7 for rs1042725 after adjustment for infant height). A third signal, rs11655470 on chromosome 17q21, showed suggestive evidence of association with head circumference (P=3.9×10−6). SNPs correlated to the 17q21 signal show genome-wide association with adult intra cranial volume2, Parkinson’s disease and other neurodegenerative diseases3-5, indicating that a common genetic variant in this region might link early brain growth with neurological disease in later life.
doi:10.1038/ng.2238
PMCID: PMC3773913  PMID: 22504419
17.  GWAS of 126,559 Individuals Identifies Genetic Variants Associated with Educational Attainment 
Rietveld, Cornelius A. | Medland, Sarah E. | Derringer, Jaime | Yang, Jian | Esko, Tõnu | Martin, Nicolas W. | Westra, Harm-Jan | Shakhbazov, Konstantin | Abdellaoui, Abdel | Agrawal, Arpana | Albrecht, Eva | Alizadeh, Behrooz Z. | Amin, Najaf | Barnard, John | Baumeister, Sebastian E. | Benke, Kelly S. | Bielak, Lawrence F. | Boatman, Jeffrey A. | Boyle, Patricia A. | Davies, Gail | de Leeuw, Christiaan | Eklund, Niina | Evans, Daniel S. | Ferhmann, Rudolf | Fischer, Krista | Gieger, Christian | Gjessing, Håkon K. | Hägg, Sara | Harris, Jennifer R. | Hayward, Caroline | Holzapfel, Christina | Ibrahim-Verbaas, Carla A. | Ingelsson, Erik | Jacobsson, Bo | Joshi, Peter K. | Jugessur, Astanand | Kaakinen, Marika | Kanoni, Stavroula | Karjalainen, Juha | Kolcic, Ivana | Kristiansson, Kati | Kutalik, Zoltán | Lahti, Jari | Lee, Sang H. | Lin, Peng | Lind, Penelope A. | Liu, Yongmei | Lohman, Kurt | Loitfelder, Marisa | McMahon, George | Vidal, Pedro Marques | Meirelles, Osorio | Milani, Lili | Myhre, Ronny | Nuotio, Marja-Liisa | Oldmeadow, Christopher J. | Petrovic, Katja E. | Peyrot, Wouter J. | Polašek, Ozren | Quaye, Lydia | Reinmaa, Eva | Rice, John P. | Rizzi, Thais S. | Schmidt, Helena | Schmidt, Reinhold | Smith, Albert V. | Smith, Jennifer A. | Tanaka, Toshiko | Terracciano, Antonio | van der Loos, Matthijs J.H.M. | Vitart, Veronique | Völzke, Henry | Wellmann, Jürgen | Yu, Lei | Zhao, Wei | Allik, Jüri | Attia, John R. | Bandinelli, Stefania | Bastardot, François | Beauchamp, Jonathan | Bennett, David A. | Berger, Klaus | Bierut, Laura J. | Boomsma, Dorret I. | Bültmann, Ute | Campbell, Harry | Chabris, Christopher F. | Cherkas, Lynn | Chung, Mina K. | Cucca, Francesco | de Andrade, Mariza | De Jager, Philip L. | De Neve, Jan-Emmanuel | Deary, Ian J. | Dedoussis, George V. | Deloukas, Panos | Dimitriou, Maria | Eiriksdottir, Gudny | Elderson, Martin F. | Eriksson, Johan G. | Evans, David M. | Faul, Jessica D. | Ferrucci, Luigi | Garcia, Melissa E. | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Per | Harris, Juliette M. | Harris, Tamara B. | Hastie, Nicholas D. | Heath, Andrew C. | Hernandez, Dena G. | Hoffmann, Wolfgang | Hofman, Adriaan | Holle, Rolf | Holliday, Elizabeth G. | Hottenga, Jouke-Jan | Iacono, William G. | Illig, Thomas | Järvelin, Marjo-Riitta | Kähönen, Mika | Kaprio, Jaakko | Kirkpatrick, Robert M. | Kowgier, Matthew | Latvala, Antti | Launer, Lenore J. | Lawlor, Debbie A. | Lehtimäki, Terho | Li, Jingmei | Lichtenstein, Paul | Lichtner, Peter | Liewald, David C. | Madden, Pamela A. | Magnusson, Patrik K. E. | Mäkinen, Tomi E. | Masala, Marco | McGue, Matt | Metspalu, Andres | Mielck, Andreas | Miller, Michael B. | Montgomery, Grant W. | Mukherjee, Sutapa | Nyholt, Dale R. | Oostra, Ben A. | Palmer, Lyle J. | Palotie, Aarno | Penninx, Brenda | Perola, Markus | Peyser, Patricia A. | Preisig, Martin | Räikkönen, Katri | Raitakari, Olli T. | Realo, Anu | Ring, Susan M. | Ripatti, Samuli | Rivadeneira, Fernando | Rudan, Igor | Rustichini, Aldo | Salomaa, Veikko | Sarin, Antti-Pekka | Schlessinger, David | Scott, Rodney J. | Snieder, Harold | Pourcain, Beate St | Starr, John M. | Sul, Jae Hoon | Surakka, Ida | Svento, Rauli | Teumer, Alexander | Tiemeier, Henning | Rooij, Frank JAan | Van Wagoner, David R. | Vartiainen, Erkki | Viikari, Jorma | Vollenweider, Peter | Vonk, Judith M. | Waeber, Gérard | Weir, David R. | Wichmann, H.-Erich | Widen, Elisabeth | Willemsen, Gonneke | Wilson, James F. | Wright, Alan F. | Conley, Dalton | Davey-Smith, George | Franke, Lude | Groenen, Patrick J. F. | Hofman, Albert | Johannesson, Magnus | Kardia, Sharon L.R. | Krueger, Robert F. | Laibson, David | Martin, Nicholas G. | Meyer, Michelle N. | Posthuma, Danielle | Thurik, A. Roy | Timpson, Nicholas J. | Uitterlinden, André G. | van Duijn, Cornelia M. | Visscher, Peter M. | Benjamin, Daniel J. | Cesarini, David | Koellinger, Philipp D.
Science (New York, N.Y.)  2013;340(6139):1467-1471.
A genome-wide association study of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent SNPs are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (R2 ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈ 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.
doi:10.1126/science.1235488
PMCID: PMC3751588  PMID: 23722424
18.  Increased Genetic Vulnerability to Smoking at CHRNA5 in Early-Onset Smokers 
Hartz, Sarah M. | Short, Susan E. | Saccone, Nancy L. | Culverhouse, Robert | Chen, LiShiun | Schwantes-An, Tae-Hwi | Coon, Hilary | Han, Younghun | Stephens, Sarah H. | Sun, Juzhong | Chen, Xiangning | Ducci, Francesca | Dueker, Nicole | Franceschini, Nora | Frank, Josef | Geller, Frank | Guđbjartsson, Daniel | Hansel, Nadia N. | Jiang, Chenhui | Keskitalo-Vuokko, Kaisu | Liu, Zhen | Lyytikäinen, Leo-Pekka | Michel, Martha | Rawal, Rajesh | Hum, Sc | Rosenberger, Albert | Scheet, Paul | Shaffer, John R. | Teumer, Alexander | Thompson, John R. | Vink, Jacqueline M. | Vogelzangs, Nicole | Wenzlaff, Angela S. | Wheeler, William | Xiao, Xiangjun | Yang, Bao-Zhu | Aggen, Steven H. | Balmforth, Anthony J. | Baumeister, Sebastian E. | Beaty, Terri | Bennett, Siiri | Bergen, Andrew W. | Boyd, Heather A. | Broms, Ulla | Campbell, Harry | Chatterjee, Nilanjan | Chen, Jingchun | Cheng, Yu-Ching | Cichon, Sven | Couper, David | Cucca, Francesco | Dick, Danielle M. | Foroud, Tatiana | Furberg, Helena | Giegling, Ina | Gu, Fangyi | Hall, Alistair S. | Hällfors, Jenni | Han, Shizhong | Hartmann, Annette M. | Hayward, Caroline | Heikkilä, Kauko | Lic, Phil | Hewitt, John K. | Hottenga, Jouke Jan | Jensen, Majken K. | Jousilahti, Pekka | Kaakinen, Marika | Kittner, Steven J. | Konte, Bettina | Korhonen, Tellervo | Landi, Maria-Teresa | Laatikainen, Tiina | Leppert, Mark | Levy, Steven M. | Mathias, Rasika A. | McNeil, Daniel W. | Medland, Sarah E. | Montgomery, Grant W. | Muley, Thomas | Murray, Tanda | Nauck, Matthias | North, Kari | Pergadia, Michele | Polasek, Ozren | Ramos, Erin M. | Ripatti, Samuli | Risch, Angela | Ruczinski, Ingo | Rudan, Igor | Salomaa, Veikko | Schlessinger, David | Styrkársdóttir, Unnur | Terracciano, Antonio | Uda, Manuela | Willemsen, Gonneke | Wu, Xifeng | Abecasis, Goncalo | Barnes, Kathleen | Bickeböller, Heike | Boerwinkle, Eric | Boomsma, Dorret I. | Caporaso, Neil | Duan, Jubao | Edenberg, Howard J. | Francks, Clyde | Gejman, Pablo V. | Gelernter, Joel | Grabe, Hans Jörgen | Hops, Hyman | Jarvelin, Marjo-Riitta | Viikari, Jorma | Kähönen, Mika | Kendler, Kenneth S. | Lehtimäki, Terho | Levinson, Douglas F. | Marazita, Mary L. | Marchini, Jonathan | Melbye, Mads | Mitchell, Braxton D. | Murray, Jeffrey C. | Nöthen, Markus M. | Penninx, Brenda W. | Raitakari, Olli | Rietschel, Marcella | Rujescu, Dan | Samani, Nilesh J. | Sanders, Alan R. | Schwartz, Ann G. | Shete, Sanjay | Shi, Jianxin | Spitz, Margaret | Stefansson, Kari | Swan, Gary E. | Thorgeirsson, Thorgeir | Völzke, Henry | Wei, Qingyi | Wichmann, H.-Erich | Amos, Christopher I. | Breslau, Naomi | Cannon, Dale S. | Ehringer, Marissa | Grucza, Richard | Hatsukami, Dorothy | Heath, Andrew | Johnson, Eric O. | Kaprio, Jaakko | Madden, Pamela | Martin, Nicholas G. | Stevens, Victoria L. | Stitzel, Jerry A. | Weiss, Robert B. | Kraft, Peter | Bierut, Laura J.
Archives of general psychiatry  2012;69(8):854-860.
Context
Recent studies have shown an association between cigarettes per day (CPD) and a nonsynonymous single-nucleotide polymorphism in CHRNA5, rs16969968.
Objective
To determine whether the association between rs16969968 and smoking is modified by age at onset of regular smoking.
Data Sources
Primary data.
Study Selection
Available genetic studies containing measures of CPD and the genotype of rs16969968 or its proxy.
Data Extraction
Uniform statistical analysis scripts were run locally. Starting with 94 050 ever-smokers from 43 studies, we extracted the heavy smokers (CPD >20) and light smokers (CPD ≤10) with age-at-onset information, reducing the sample size to 33 348. Each study was stratified into early-onset smokers (age at onset ≤16 years) and late-onset smokers (age at onset >16 years), and a logistic regression of heavy vs light smoking with the rs16969968 genotype was computed for each stratum. Meta-analysis was performed within each age-at-onset stratum.
Data Synthesis
Individuals with 1 risk allele at rs16969968 who were early-onset smokers were significantly more likely to be heavy smokers in adulthood (odds ratio [OR]=1.45; 95% CI, 1.36–1.55; n=13 843) than were carriers of the risk allele who were late-onset smokers (OR = 1.27; 95% CI, 1.21–1.33, n = 19 505) (P = .01).
Conclusion
These results highlight an increased genetic vulnerability to smoking in early-onset smokers.
doi:10.1001/archgenpsychiatry.2012.124
PMCID: PMC3482121  PMID: 22868939
19.  Genome-wide association analyses identify 18 new loci associated with serum urate concentrations 
Köttgen, Anna | Albrecht, Eva | Teumer, Alexander | Vitart, Veronique | Krumsiek, Jan | Hundertmark, Claudia | Pistis, Giorgio | Ruggiero, Daniela | O’Seaghdha, Conall M | Haller, Toomas | Yang, Qiong | Tanaka, Toshiko | Johnson, Andrew D | Kutalik, Zoltán | Smith, Albert V | Shi, Julia | Struchalin, Maksim | Middelberg, Rita P S | Brown, Morris J | Gaffo, Angelo L | Pirastu, Nicola | Li, Guo | Hayward, Caroline | Zemunik, Tatijana | Huffman, Jennifer | Yengo, Loic | Zhao, Jing Hua | Demirkan, Ayse | Feitosa, Mary F | Liu, Xuan | Malerba, Giovanni | Lopez, Lorna M | van der Harst, Pim | Li, Xinzhong | Kleber, Marcus E | Hicks, Andrew A | Nolte, Ilja M | Johansson, Asa | Murgia, Federico | Wild, Sarah H | Bakker, Stephan J L | Peden, John F | Dehghan, Abbas | Steri, Maristella | Tenesa, Albert | Lagou, Vasiliki | Salo, Perttu | Mangino, Massimo | Rose, Lynda M | Lehtimäki, Terho | Woodward, Owen M | Okada, Yukinori | Tin, Adrienne | Müller, Christian | Oldmeadow, Christopher | Putku, Margus | Czamara, Darina | Kraft, Peter | Frogheri, Laura | Thun, Gian Andri | Grotevendt, Anne | Gislason, Gauti Kjartan | Harris, Tamara B | Launer, Lenore J | McArdle, Patrick | Shuldiner, Alan R | Boerwinkle, Eric | Coresh, Josef | Schmidt, Helena | Schallert, Michael | Martin, Nicholas G | Montgomery, Grant W | Kubo, Michiaki | Nakamura, Yusuke | Tanaka, Toshihiro | Munroe, Patricia B | Samani, Nilesh J | Jacobs, David R | Liu, Kiang | D’Adamo, Pio | Ulivi, Sheila | Rotter, Jerome I | Psaty, Bruce M | Vollenweider, Peter | Waeber, Gerard | Campbell, Susan | Devuyst, Olivier | Navarro, Pau | Kolcic, Ivana | Hastie, Nicholas | Balkau, Beverley | Froguel, Philippe | Esko, Tõnu | Salumets, Andres | Khaw, Kay Tee | Langenberg, Claudia | Wareham, Nicholas J | Isaacs, Aaron | Kraja, Aldi | Zhang, Qunyuan | Wild, Philipp S | Scott, Rodney J | Holliday, Elizabeth G | Org, Elin | Viigimaa, Margus | Bandinelli, Stefania | Metter, Jeffrey E | Lupo, Antonio | Trabetti, Elisabetta | Sorice, Rossella | Döring, Angela | Lattka, Eva | Strauch, Konstantin | Theis, Fabian | Waldenberger, Melanie | Wichmann, H-Erich | Davies, Gail | Gow, Alan J | Bruinenberg, Marcel | Study, LifeLines Cohort | Stolk, Ronald P | Kooner, Jaspal S | Zhang, Weihua | Winkelmann, Bernhard R | Boehm, Bernhard O | Lucae, Susanne | Penninx, Brenda W | Smit, Johannes H | Curhan, Gary | Mudgal, Poorva | Plenge, Robert M | Portas, Laura | Persico, Ivana | Kirin, Mirna | Wilson, James F | Leach, Irene Mateo | van Gilst, Wiek H | Goel, Anuj | Ongen, Halit | Hofman, Albert | Rivadeneira, Fernando | Uitterlinden, Andre G | Imboden, Medea | von Eckardstein, Arnold | Cucca, Francesco | Nagaraja, Ramaiah | Piras, Maria Grazia | Nauck, Matthias | Schurmann, Claudia | Budde, Kathrin | Ernst, Florian | Farrington, Susan M | Theodoratou, Evropi | Prokopenko, Inga | Stumvoll, Michael | Jula, Antti | Perola, Markus | Salomaa, Veikko | Shin, So-Youn | Spector, Tim D | Sala, Cinzia | Ridker, Paul M | Kähönen, Mika | Viikari, Jorma | Hengstenberg, Christian | Nelson, Christopher P | Consortium, CARDIoGRAM | Consortium, DIAGRAM | Consortium, ICBP | Consortium, MAGIC | Meschia, James F | Nalls, Michael A | Sharma, Pankaj | Singleton, Andrew B | Kamatani, Naoyuki | Zeller, Tanja | Burnier, Michel | Attia, John | Laan, Maris | Klopp, Norman | Hillege, Hans L | Kloiber, Stefan | Choi, Hyon | Pirastu, Mario | Tore, Silvia | Probst-Hensch, Nicole M | Völzke, Henry | Gudnason, Vilmundur | Parsa, Afshin | Schmidt, Reinhold | Whitfield, John B | Fornage, Myriam | Gasparini, Paolo | Siscovick, David S | Polašek, Ozren | Campbell, Harry | Rudan, Igor | Bouatia-Naji, Nabila | Metspalu, Andres | Loos, Ruth J F | van Duijn, Cornelia M | Borecki, Ingrid B | Ferrucci, Luigi | Gambaro, Giovanni | Deary, Ian J | Wolffenbuttel, Bruce H R | Chambers, John C | März, Winfried | Pramstaller, Peter P | Snieder, Harold | Gyllensten, Ulf | Wright, Alan F | Navis, Gerjan | Watkins, Hugh | Witteman, Jacqueline C M | Sanna, Serena | Schipf, Sabine | Dunlop, Malcolm G | Tönjes, Anke | Ripatti, Samuli | Soranzo, Nicole | Toniolo, Daniela | Chasman, Daniel I | Raitakari, Olli | Kao, W H Linda | Ciullo, Marina | Fox, Caroline S | Caulfield, Mark | Bochud, Murielle | Gieger, Christian
Nature genetics  2012;45(2):145-154.
Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.
doi:10.1038/ng.2500
PMCID: PMC3663712  PMID: 23263486
20.  Metabolite profiling reveals new insights into the regulation of serum urate in humans 
Metabolomics  2013;10:141-151.
Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia.
Electronic supplementary material
The online version of this article (doi:10.1007/s11306-013-0565-2) contains supplementary material, which is available to authorized users.
doi:10.1007/s11306-013-0565-2
PMCID: PMC3890072  PMID: 24482632
Gaussian Graphical Modeling; Metabolite network; Pathway reconstruction; Allopurinol; Uric acid; Purine metabolism
21.  Associations between thyroid hormones and serum metabolite profiles in an euthyroid population 
Metabolomics  2013;10:152-164.
The aim was to characterise associations between circulating thyroid hormones—free thyroxine (FT4) and thyrotropin (TSH)—and the metabolite profiles in serum samples from participants of the German population-based KORA F4 study. Analyses were based on the metabolite profile of 1463 euthyroid subjects. In serum samples, obtained after overnight fasting (≥8), 151 different metabolites were quantified in a targeted approach including amino acids, acylcarnitines (ACs), and phosphatidylcholines (PCs). Associations between metabolites and thyroid hormone concentrations were analysed using adjusted linear regression models. To draw conclusions on thyroid hormone related pathways, intra-class metabolite ratios were additionally explored. We discovered 154 significant associations (Bonferroni p < 1.75 × 10−04) between FT4 and various metabolites and metabolite ratios belonging to AC and PC groups. Significant associations with TSH were lacking. High FT4 levels were associated with increased concentrations of many ACs and various sums of ACs of different chain length, and the ratio of C2 by C0. The inverse associations observed between FT4 and many serum PCs reflected the general decrease in PC concentrations. Similar results were found in subgroup analyses, e.g., in weight-stable subjects or in obese subjects. Further, results were independent of different parameters for liver or kidney function, or inflammation, which supports the notion of an independent FT4 effect. In fasting euthyroid adults, higher serum FT4 levels are associated with increased serum AC concentrations and an increased ratio of C2 by C0 which is indicative of an overall enhanced fatty acyl mitochondrial transport and β-oxidation of fatty acids.
Electronic supplementary material
The online version of this article (doi:10.1007/s11306-013-0563-4) contains supplementary material, which is available to authorized users.
doi:10.1007/s11306-013-0563-4
PMCID: PMC4042025  PMID: 24955082
Targeted metabolomics; Serum metabolites; Free thyroxine; Thyrotropin; Thyroid hormones; Epidemiology
22.  Posttraumatic Stress Disorder and Not Depression Is Associated with Shorter Leukocyte Telomere Length: Findings from 3,000 Participants in the Population-Based KORA F4 Study 
PLoS ONE  2013;8(7):e64762.
Background
A link between severe mental stress and shorter telomere length (TL) has been suggested. We analysed the impact of Posttraumatic Stress Disorder (PTSD) on TL in the general population and postulated a dose-dependent TL association in subjects suffering from partial PTSD compared to full PTSD.
Methods
Data are derived from the population-based KORA F4 study (2006–2008), located in southern Germany including 3,000 individuals (1,449 men and 1,551 women) with valid and complete TL data. Leukocyte TL was measured using a quantitative PCR-based technique. PTSD was assessed in a structured interview and by applying the Posttraumatic Diagnostic Scale (PDS) and the Impact of Event Scale (IES). A total of 262 (8.7%) subjects qualified for having partial PTSD and 51 (1.7%) for full PTSD. To assess the association of PTSD with the average TL, linear regression analyses with adjustments for potential confounding factors were performed.
Results
The multiple model revealed a significant association between partial PTSD and TL (beta = −0.051, p = 0.009) as well as between full PTSD and shorter TL (beta = −0.103, p = 0.014) indicating shorter TL on average for partial and full PTSD. An additional adjustment for depression and depressed mood/exhaustion gave comparable beta estimations.
Conclusions
Participants with partial and full PTSD had significantly shorter leukocyte TL than participants without PTSD. The dose-dependent variation in TL of subjects with partial and full PTSD exceeded the chronological age effect, and was equivalent to an estimated 5 years in partial and 10 years in full PTSD of premature aging.
doi:10.1371/journal.pone.0064762
PMCID: PMC3700974  PMID: 23843935
23.  The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis 
Fall, Tove | Hägg, Sara | Mägi, Reedik | Ploner, Alexander | Fischer, Krista | Horikoshi, Momoko | Sarin, Antti-Pekka | Thorleifsson, Gudmar | Ladenvall, Claes | Kals, Mart | Kuningas, Maris | Draisma, Harmen H. M. | Ried, Janina S. | van Zuydam, Natalie R. | Huikari, Ville | Mangino, Massimo | Sonestedt, Emily | Benyamin, Beben | Nelson, Christopher P. | Rivera, Natalia V. | Kristiansson, Kati | Shen, Huei-yi | Havulinna, Aki S. | Dehghan, Abbas | Donnelly, Louise A. | Kaakinen, Marika | Nuotio, Marja-Liisa | Robertson, Neil | de Bruijn, Renée F. A. G. | Ikram, M. Arfan | Amin, Najaf | Balmforth, Anthony J. | Braund, Peter S. | Doney, Alexander S. F. | Döring, Angela | Elliott, Paul | Esko, Tõnu | Franco, Oscar H. | Gretarsdottir, Solveig | Hartikainen, Anna-Liisa | Heikkilä, Kauko | Herzig, Karl-Heinz | Holm, Hilma | Hottenga, Jouke Jan | Hyppönen, Elina | Illig, Thomas | Isaacs, Aaron | Isomaa, Bo | Karssen, Lennart C. | Kettunen, Johannes | Koenig, Wolfgang | Kuulasmaa, Kari | Laatikainen, Tiina | Laitinen, Jaana | Lindgren, Cecilia | Lyssenko, Valeriya | Läärä, Esa | Rayner, Nigel W. | Männistö, Satu | Pouta, Anneli | Rathmann, Wolfgang | Rivadeneira, Fernando | Ruokonen, Aimo | Savolainen, Markku J. | Sijbrands, Eric J. G. | Small, Kerrin S. | Smit, Jan H. | Steinthorsdottir, Valgerdur | Syvänen, Ann-Christine | Taanila, Anja | Tobin, Martin D. | Uitterlinden, Andre G. | Willems, Sara M. | Willemsen, Gonneke | Witteman, Jacqueline | Perola, Markus | Evans, Alun | Ferrières, Jean | Virtamo, Jarmo | Kee, Frank | Tregouet, David-Alexandre | Arveiler, Dominique | Amouyel, Philippe | Ferrario, Marco M. | Brambilla, Paolo | Hall, Alistair S. | Heath, Andrew C. | Madden, Pamela A. F. | Martin, Nicholas G. | Montgomery, Grant W. | Whitfield, John B. | Jula, Antti | Knekt, Paul | Oostra, Ben | van Duijn, Cornelia M. | Penninx, Brenda W. J. H. | Davey Smith, George | Kaprio, Jaakko | Samani, Nilesh J. | Gieger, Christian | Peters, Annette | Wichmann, H.-Erich | Boomsma, Dorret I. | de Geus, Eco J. C. | Tuomi, TiinaMaija | Power, Chris | Hammond, Christopher J. | Spector, Tim D. | Lind, Lars | Orho-Melander, Marju | Palmer, Colin Neil Alexander | Morris, Andrew D. | Groop, Leif | Järvelin, Marjo-Riitta | Salomaa, Veikko | Vartiainen, Erkki | Hofman, Albert | Ripatti, Samuli | Metspalu, Andres | Thorsteinsdottir, Unnur | Stefansson, Kari | Pedersen, Nancy L. | McCarthy, Mark I. | Ingelsson, Erik | Prokopenko, Inga
PLoS Medicine  2013;10(6):e1001474.
In this study, Prokopenko and colleagues provide novel evidence for causal relationship between adiposity and heart failure and increased liver enzymes using a Mendelian randomization study design.
Please see later in the article for the Editors' Summary
Background
The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
Methods and Findings
We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.
Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).
Conclusions
We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.
Please see later in the article for the Editors' Summary
Editors' Summary
Cardiovascular disease (CVD)—disease that affects the heart and/or the blood vessels—is a major cause of illness and death worldwide. In the US, for example, coronary heart disease—a CVD in which narrowing of the heart's blood vessels by fatty deposits slows the blood supply to the heart and may eventually cause a heart attack—is the leading cause of death, and stroke—a CVD in which the brain's blood supply is interrupted—is the fourth leading cause of death. Globally, both the incidence of CVD (the number of new cases in a population every year) and its prevalence (the proportion of the population with CVD) are increasing, particularly in low- and middle-income countries. This increasing burden of CVD is occurring in parallel with a global increase in the incidence and prevalence of obesity—having an unhealthy amount of body fat (adiposity)—and of metabolic diseases—conditions such as diabetes in which metabolism (the processes that the body uses to make energy from food) is disrupted, with resulting high blood sugar and damage to the blood vessels.
Why Was This Study Done?
Epidemiological studies—investigations that record the patterns and causes of disease in populations—have reported an association between adiposity (indicated by an increased body mass index [BMI], which is calculated by dividing body weight in kilograms by height in meters squared) and cardiometabolic traits such as coronary heart disease, stroke, heart failure (a condition in which the heart is incapable of pumping sufficient amounts of blood around the body), diabetes, high blood pressure (hypertension), and high blood cholesterol (dyslipidemia). However, observational studies cannot prove that adiposity causes any particular cardiometabolic trait because overweight individuals may share other characteristics (confounding factors) that are the real causes of both obesity and the cardiometabolic disease. Moreover, it is possible that having CVD or a metabolic disease causes obesity (reverse causation). For example, individuals with heart failure cannot do much exercise, so heart failure may cause obesity rather than vice versa. Here, the researchers use “Mendelian randomization” to examine whether adiposity is causally related to various cardiometabolic traits. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. It is known that a genetic variant (rs9939609) within the genome region that encodes the fat-mass- and obesity-associated gene (FTO) is associated with increased BMI. Thus, an investigation of the associations between rs9939609 and cardiometabolic traits can indicate whether obesity is causally related to these traits.
What Did the Researchers Do and Find?
The researchers analyzed the association between rs9939609 (the “instrumental variable,” or IV) and BMI, between rs9939609 and 24 cardiometabolic traits, and between BMI and the same traits using genetic and health data collected in 36 population-based studies of nearly 200,000 individuals of European descent. They then quantified the strength of the causal association between BMI and the cardiometabolic traits by calculating “IV estimators.” Higher BMI showed a causal relationship with heart failure, metabolic syndrome (a combination of medical disorders that increases the risk of developing CVD), type 2 diabetes, dyslipidemia, hypertension, increased blood levels of liver enzymes (an indicator of liver damage; some metabolic disorders involve liver damage), and several other cardiometabolic traits. All the IV estimators were similar to the BMI–cardiovascular trait associations (observational estimates) derived from the same individuals, with the exception of diabetes, where the causal estimate was higher than the observational estimate, probably because the observational estimate is based on a single BMI measurement, whereas the causal estimate considers lifetime changes in BMI.
What Do These Findings Mean?
Like all Mendelian randomization studies, the reliability of the causal associations reported here depends on several assumptions made by the researchers. Nevertheless, these findings provide support for many previously suspected and biologically plausible causal relationships, such as that between adiposity and hypertension. They also provide new insights into the causal effect of obesity on liver enzyme levels and on heart failure. In the latter case, these findings suggest that a one-unit increase in BMI might increase the incidence of heart failure by 17%. In the US, this corresponds to 113,000 additional cases of heart failure for every unit increase in BMI at the population level. Although additional studies are needed to confirm and extend these findings, these results suggest that global efforts to reduce the burden of obesity will likely also reduce the occurrence of CVD and metabolic disorders.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001474.
The American Heart Association provides information on all aspects of cardiovascular disease and tips on keeping the heart healthy, including weight management (in several languages); its website includes personal stories about stroke and heart attacks
The US Centers for Disease Control and Prevention has information on heart disease, stroke, and all aspects of overweight and obesity (in English and Spanish)
The UK National Health Service Choices website provides information about cardiovascular disease and obesity, including a personal story about losing weight
The World Health Organization provides information on obesity (in several languages)
The International Obesity Taskforce provides information about the global obesity epidemic
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
MedlinePlus provides links to other sources of information on heart disease, on vascular disease, on obesity, and on metabolic disorders (in English and Spanish)
The International Association for the Study of Obesity provides maps and information about obesity worldwide
The International Diabetes Federation has a web page that describes types, complications, and risk factors of diabetes
doi:10.1371/journal.pmed.1001474
PMCID: PMC3692470  PMID: 23824655
24.  Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits 
Randall, Joshua C. | Winkler, Thomas W. | Kutalik, Zoltán | Berndt, Sonja I. | Jackson, Anne U. | Monda, Keri L. | Kilpeläinen, Tuomas O. | Esko, Tõnu | Mägi, Reedik | Li, Shengxu | Workalemahu, Tsegaselassie | Feitosa, Mary F. | Croteau-Chonka, Damien C. | Day, Felix R. | Fall, Tove | Ferreira, Teresa | Gustafsson, Stefan | Locke, Adam E. | Mathieson, Iain | Scherag, Andre | Vedantam, Sailaja | Wood, Andrew R. | Liang, Liming | Steinthorsdottir, Valgerdur | Thorleifsson, Gudmar | Dermitzakis, Emmanouil T. | Dimas, Antigone S. | Karpe, Fredrik | Min, Josine L. | Nicholson, George | Clegg, Deborah J. | Person, Thomas | Krohn, Jon P. | Bauer, Sabrina | Buechler, Christa | Eisinger, Kristina | Bonnefond, Amélie | Froguel, Philippe | Hottenga, Jouke-Jan | Prokopenko, Inga | Waite, Lindsay L. | Harris, Tamara B. | Smith, Albert Vernon | Shuldiner, Alan R. | McArdle, Wendy L. | Caulfield, Mark J. | Munroe, Patricia B. | Grönberg, Henrik | Chen, Yii-Der Ida | Li, Guo | Beckmann, Jacques S. | Johnson, Toby | Thorsteinsdottir, Unnur | Teder-Laving, Maris | Khaw, Kay-Tee | Wareham, Nicholas J. | Zhao, Jing Hua | Amin, Najaf | Oostra, Ben A. | Kraja, Aldi T. | Province, Michael A. | Cupples, L. Adrienne | Heard-Costa, Nancy L. | Kaprio, Jaakko | Ripatti, Samuli | Surakka, Ida | Collins, Francis S. | Saramies, Jouko | Tuomilehto, Jaakko | Jula, Antti | Salomaa, Veikko | Erdmann, Jeanette | Hengstenberg, Christian | Loley, Christina | Schunkert, Heribert | Lamina, Claudia | Wichmann, H. Erich | Albrecht, Eva | Gieger, Christian | Hicks, Andrew A. | Johansson, Åsa | Pramstaller, Peter P. | Kathiresan, Sekar | Speliotes, Elizabeth K. | Penninx, Brenda | Hartikainen, Anna-Liisa | Jarvelin, Marjo-Riitta | Gyllensten, Ulf | Boomsma, Dorret I. | Campbell, Harry | Wilson, James F. | Chanock, Stephen J. | Farrall, Martin | Goel, Anuj | Medina-Gomez, Carolina | Rivadeneira, Fernando | Estrada, Karol | Uitterlinden, André G. | Hofman, Albert | Zillikens, M. Carola | den Heijer, Martin | Kiemeney, Lambertus A. | Maschio, Andrea | Hall, Per | Tyrer, Jonathan | Teumer, Alexander | Völzke, Henry | Kovacs, Peter | Tönjes, Anke | Mangino, Massimo | Spector, Tim D. | Hayward, Caroline | Rudan, Igor | Hall, Alistair S. | Samani, Nilesh J. | Attwood, Antony Paul | Sambrook, Jennifer G. | Hung, Joseph | Palmer, Lyle J. | Lokki, Marja-Liisa | Sinisalo, Juha | Boucher, Gabrielle | Huikuri, Heikki | Lorentzon, Mattias | Ohlsson, Claes | Eklund, Niina | Eriksson, Johan G. | Barlassina, Cristina | Rivolta, Carlo | Nolte, Ilja M. | Snieder, Harold | Van der Klauw, Melanie M. | Van Vliet-Ostaptchouk, Jana V. | Gejman, Pablo V. | Shi, Jianxin | Jacobs, Kevin B. | Wang, Zhaoming | Bakker, Stephan J. L. | Mateo Leach, Irene | Navis, Gerjan | van der Harst, Pim | Martin, Nicholas G. | Medland, Sarah E. | Montgomery, Grant W. | Yang, Jian | Chasman, Daniel I. | Ridker, Paul M. | Rose, Lynda M. | Lehtimäki, Terho | Raitakari, Olli | Absher, Devin | Iribarren, Carlos | Basart, Hanneke | Hovingh, Kees G. | Hyppönen, Elina | Power, Chris | Anderson, Denise | Beilby, John P. | Hui, Jennie | Jolley, Jennifer | Sager, Hendrik | Bornstein, Stefan R. | Schwarz, Peter E. H. | Kristiansson, Kati | Perola, Markus | Lindström, Jaana | Swift, Amy J. | Uusitupa, Matti | Atalay, Mustafa | Lakka, Timo A. | Rauramaa, Rainer | Bolton, Jennifer L. | Fowkes, Gerry | Fraser, Ross M. | Price, Jackie F. | Fischer, Krista | KrjutÅ¡kov, Kaarel | Metspalu, Andres | Mihailov, Evelin | Langenberg, Claudia | Luan, Jian'an | Ong, Ken K. | Chines, Peter S. | Keinanen-Kiukaanniemi, Sirkka M. | Saaristo, Timo E. | Edkins, Sarah | Franks, Paul W. | Hallmans, Göran | Shungin, Dmitry | Morris, Andrew David | Palmer, Colin N. A. | Erbel, Raimund | Moebus, Susanne | Nöthen, Markus M. | Pechlivanis, Sonali | Hveem, Kristian | Narisu, Narisu | Hamsten, Anders | Humphries, Steve E. | Strawbridge, Rona J. | Tremoli, Elena | Grallert, Harald | Thorand, Barbara | Illig, Thomas | Koenig, Wolfgang | Müller-Nurasyid, Martina | Peters, Annette | Boehm, Bernhard O. | Kleber, Marcus E. | März, Winfried | Winkelmann, Bernhard R. | Kuusisto, Johanna | Laakso, Markku | Arveiler, Dominique | Cesana, Giancarlo | Kuulasmaa, Kari | Virtamo, Jarmo | Yarnell, John W. G. | Kuh, Diana | Wong, Andrew | Lind, Lars | de Faire, Ulf | Gigante, Bruna | Magnusson, Patrik K. E. | Pedersen, Nancy L. | Dedoussis, George | Dimitriou, Maria | Kolovou, Genovefa | Kanoni, Stavroula | Stirrups, Kathleen | Bonnycastle, Lori L. | Njølstad, Inger | Wilsgaard, Tom | Ganna, Andrea | Rehnberg, Emil | Hingorani, Aroon | Kivimaki, Mika | Kumari, Meena | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunians, Talin | Hunter, David | Ingelsson, Erik | Kaplan, Robert | Mohlke, Karen L. | O'Connell, Jeffrey R. | Schlessinger, David | Strachan, David P. | Stefansson, Kari | van Duijn, Cornelia M. | Abecasis, Gonçalo R. | McCarthy, Mark I. | Hirschhorn, Joel N. | Qi, Lu | Loos, Ruth J. F. | Lindgren, Cecilia M. | North, Kari E. | Heid, Iris M.
PLoS Genetics  2013;9(6):e1003500.
Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
Author Summary
Men and women differ substantially regarding height, weight, and body fat. Interestingly, previous work detecting genetic effects for waist-to-hip ratio, to assess body fat distribution, has found that many of these showed sex-differences. However, systematic searches for sex-differences in genetic effects have not yet been conducted. Therefore, we undertook a genome-wide search for sexually dimorphic genetic effects for anthropometric traits including 133,723 individuals in a large meta-analysis and followed promising variants in further 137,052 individuals, including a total of 94 studies. We identified seven loci with significant sex-difference including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were significant in women, but not in men. Of interest is that sex-difference was only observed for waist phenotypes, but not for height or body-mass-index. We found no evidence for sex-differences with opposite effect direction for men and women. The PPARG locus is of specific interest due to its link to diabetes genetics and therapy. Our findings demonstrate the importance of investigating sex differences, which may lead to a better understanding of disease mechanisms with a potential relevance to treatment options.
doi:10.1371/journal.pgen.1003500
PMCID: PMC3674993  PMID: 23754948
25.  Identification of fifteen new psoriasis susceptibility loci highlights the role of innate immunity 
Nature genetics  2012;44(12):1341-1348.
Summary
To gain further insight into the genetic architecture of psoriasis, we conducted a meta-analysis of three genome-wide association studies (GWAS) and two independent datasets genotyped on the Immunochip, involving 10,588 cases and 22,806 controls in total. We identified 15 new disease susceptibility regions, increasing the number of psoriasis-associated loci to 36 for Caucasians. Conditional analyses identified five independent signals within previously known loci. The newly identified shared disease regions encompassed a number of genes whose products regulate T-cell function (e.g. RUNX3, TAGAP and STAT3). The new psoriasis-specific regions were notable for candidate genes whose products are involved in innate host defense, encoding proteins with roles in interferon-mediated antiviral responses (DDX58), macrophage activation (ZC3H12C), and NF-κB signaling (CARD14 and CARM1). These results portend a better understanding of shared and distinctive genetic determinants of immune-mediated inflammatory disorders and emphasize the importance of the skin in innate and acquired host defense.
doi:10.1038/ng.2467
PMCID: PMC3510312  PMID: 23143594

Results 1-25 (184)