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Showing papers by "Nilesh J. Samani published in 2013"


Journal ArticleDOI
Cristen J. Willer1, Ellen M. Schmidt1, Sebanti Sengupta1, Gina M. Peloso2  +316 moreInstitutions (87)
TL;DR: It is found that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index.
Abstract: Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

2,585 citations


Journal ArticleDOI
TL;DR: An association analysis in CAD cases and controls identifies 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants strongly associated with CAD at a 5% false discovery rate (FDR).
Abstract: Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2) < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.

1,518 citations


Journal ArticleDOI
Ron Do1, Cristen J. Willer2, Ellen M. Schmidt2, Sebanti Sengupta2  +263 moreInstitutions (83)
TL;DR: It is suggested that triglyceride-rich lipoproteins causally influence risk for CAD, and the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk.
Abstract: Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

817 citations


Journal ArticleDOI
Veryan Codd1, Christopher P. Nelson1, Eva Albrecht, Massimo Mangino2, Joris Deelen3, Jessica L. Buxton4, Jouke-Jan Hottenga5, Krista Fischer6, Tõnu Esko6, Ida Surakka7, Linda Broer, Dale R. Nyholt8, Irene Mateo Leach9, Perttu Salo, Sara Hägg10, Mary K. Matthews1, Jutta Palmen11, Giuseppe Danilo Norata, Paul F. O'Reilly4, Danish Saleheen12, Najaf Amin13, Anthony J. Balmforth14, Marian Beekman3, Rudolf A. de Boer9, Stefan Böhringer3, Peter S. Braund1, Paul Burton1, Anton J. M. de Craen3, Matthew Denniff1, Yanbin Dong15, Konstantinos Douroudis6, Elena Dubinina1, Johan G. Eriksson, Katia Garlaschelli, Dehuang Guo15, Anna-Liisa Hartikainen16, Anjali K. Henders8, Jeanine J. Houwing-Duistermaat3, Laura Kananen7, Lennart C. Karssen13, Johannes Kettunen7, Norman Klopp, Vasiliki Lagou17, Elisabeth M. van Leeuwen13, Pamela A. F. Madden18, Reedik Mägi6, Patrik K. E. Magnusson10, Satu Männistö19, Satu Männistö20, Mark I. McCarthy21, Mark I. McCarthy17, Mark I. McCarthy22, Sarah E. Medland8, Evelin Mihailov6, Grant W. Montgomery8, Ben A. Oostra13, Aarno Palotie, Annette Peters, Helen Pollard1, Anneli Pouta16, Anneli Pouta20, Inga Prokopenko17, Samuli Ripatti, Veikko Salomaa19, Veikko Salomaa20, H. Eka D. Suchiman3, Ana M. Valdes2, Niek Verweij9, Ana Viñuela2, Xiaoling Wang23, Xiaoling Wang24, H-Erich Wichmann25, Elisabeth Widen7, Gonneke Willemsen5, Margaret J. Wright8, Kai Xia26, Xiangjun Xiao27, Dirk J. van Veldhuisen9, Alberico L. Catapano28, Martin D. Tobin1, Alistair S. Hall14, Alexandra I. F. Blakemore4, Wiek H. van Gilst9, Haidong Zhu24, Haidong Zhu23, Jeanette Erdmann, Muredach P. Reilly29, Sekar Kathiresan30, Sekar Kathiresan31, Heribert Schunkert, Philippa J. Talmud11, Nancy L. Pedersen10, Markus Perola6, Markus Perola7, Markus Perola20, Willem H. Ouwehand, Jaakko Kaprio, Nicholas G. Martin8, Cornelia M. van Duijn, Iiris Hovatta7, Iiris Hovatta20, Christian Gieger11, Andres Metspalu6, Dorret I. Boomsma5, Marjo-Riitta Järvelin, P. Eline Slagboom3, John R Thompson1, Tim D. Spector2, Pim van der Harst1, Nilesh J. Samani32, Nilesh J. Samani1 
TL;DR: In this paper, a genome-wide meta-analysis of 37,684 individuals with replication of selected variants in an additional 10,739 individuals was carried out to identify seven loci, including five new loci associated with mean leukocyte telomere length (LTL) (P < 5 × 10−8).
Abstract: Interindividual variation in mean leukocyte telomere length (LTL) is associated with cancer and several age-associated diseases. We report here a genome-wide meta-analysis of 37,684 individuals with replication of selected variants in an additional 10,739 individuals. We identified seven loci, including five new loci, associated with mean LTL (P < 5 × 10(-8)). Five of the loci contain candidate genes (TERC, TERT, NAF1, OBFC1 and 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 7 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 coronary artery disease (21% (95% confidence interval, 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.

703 citations


Journal ArticleDOI
Anna Köttgen1, Anna Köttgen2, Eva Albrecht, Alexander Teumer3  +247 moreInstitutions (64)
TL;DR: 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.
Abstract: 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.

633 citations


Veryan Codd, Christopher P. Nelson, Eva Albrecht, Massimo Mangino, Joris Deelen, Jessica L. Buxton, Jouke-Jan Hottenga, Krista Fischer, Tõnu Esko, Ida Surakka, Linda Broer, Dale R. Nyholt, Irene Mateo Leach, Perttu Salo, Sara Hägg, Mary K. Matthews, Jutta Palmen, Giuseppe Danilo Norata, Paul F. O'Reilly, Danish Saleheen, Najaf Amin, Anthony J. Balmforth, Marian Beekman, Rudolf A. de Boer, Stefan Böhringer, Peter S. Braund, Paul Burton, Anton J. M. de Craen, Matthew Denniff, Yanbin Dong, Konstantinos Douroudis, Elena Dubinina, Johan G. Eriksson, Katia Garlaschelli, Dehuang Guo, Anna-Liisa Hartikainen, Anjali K. Henders, Jeanine J. Houwing-Duistermaat, Laura Kananen, Lennart C. Karssen, Johannes Kettunen, Norman Klopp, Vasiliki Lagou, Elisabeth M. van Leeuwen, Pamela A. F. Madden, Reedik Maegi, Patrik K. E. Magnusson, Satu Männistö, Mark I. McCarthy, Sarah E. Medland, Evelin Mihailov, Grant W. Montgomery, Ben A. Oostra, Aarno Palotie, Annette Peters, Helen Pollard, Anneli Pouta, Inga Prokopenko, Samuli Ripatti, Veikko Salomaa, H. Eka D. Suchiman, Ana M. Valdes, Niek Verweij, Ana Viñuela, Xiaoling Wang, H-Erich Wichmann, Elisabeth Widen, Gonneke Willemsen, Margaret J. Wright, Kai Xia, Xiangjun Xiao, Dirk J. van Veldhuisen, Alberico L. Catapano, Martin D. Tobin, Alistair S. Hall, Alexandra I. F. Blakemore, Wiek H. van Gilst, Haidong Zhu, Jeanette Erdmann, Muredach P. Reilly, Sekar Kathiresan, Heribert Schunkert, Philippa J. Talmud, Nancy L. Pedersen, Markus Perola, Willem H. Ouwehand, Jaakko Kaprio, Nicholas G. Martin, Cornelia M. van Duijn, Iris Hovatta, Christian Gieger, Andres Metspalu, Dorret I. Boomsma, Marjo-Riitta Järvelin, P. Eline Slagboom, John R Thompson, Tim D. Spector, Pim van der Harst, Nilesh J. Samani 
01 Jan 2013
TL;DR: In this article, a genome-wide meta-analysis of 37,684 individuals with replication of selected variants in an additional 10,739 individuals was carried out to identify seven loci, including five new loci associated with mean leukocyte telomere length (LTL).
Abstract: Interindividual variation in mean leukocyte telomere length (LTL) is associated with cancer and several age-associated diseases. We report here a genome-wide meta-analysis of 37,684 individuals with replication of selected variants in an additional 10,739 individuals. We identified seven loci, including five new loci, associated with mean LTL (P < 5 × 10−8). Five of the loci contain candidate genes (TERC, TERT, NAF1, OBFC1 and 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 7 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 coronary artery disease (21% (95% confidence interval, 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.

604 citations


Journal ArticleDOI
Sonja I. Berndt1, Stefan Gustafsson2, Stefan Gustafsson3, Reedik Mägi4  +382 moreInstitutions (117)
TL;DR: A genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry finds a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
Abstract: Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

576 citations


01 Jan 2013
TL;DR: In this article, the authors 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).
Abstract: 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.

494 citations



Journal ArticleDOI
TL;DR: The value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits is demonstrated, with no evidence for genetic effects with opposite directions in men versus women.
Abstract: 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.

402 citations


Journal ArticleDOI
TL;DR: A high and very consistent heritability estimate for TL is found, evidence for a maternal inheritance component and the influence of parental age at birth on TL is investigated, and a positive association with paternal age is found.
Abstract: Telomere length (TL) has been associated with aging and mortality, but individual differences are also influenced by genetic factors, with previous studies reporting heritability estimates ranging from 34 to 82%. Here we investigate the heritability, mode of inheritance and the influence of parental age at birth on TL in six large, independent cohort studies with a total of 19,713 participants. The meta-analysis estimate of TL heritability was 0.70 (95% CI 0.64-0.76) and is based on a pattern of results that is highly similar for twins and other family members. We observed a stronger mother-offspring (r=0.42; P-value=3.60 × 10(-61)) than father-offspring correlation (r=0.33; P-value=7.01 × 10(-5)), and a significant positive association with paternal age at offspring birth (β=0.005; P-value=7.01 × 10(-5)). Interestingly, a significant and quite substantial correlation in TL between spouses (r=0.25; P-value=2.82 × 10(-30)) was seen, which appeared stronger in older spouse pairs (mean age ≥55 years; r=0.31; P-value=4.27 × 10(-23)) than in younger pairs (mean age<55 years; r=0.20; P-value=3.24 × 10(-10)). In summary, we find a high and very consistent heritability estimate for TL, evidence for a maternal inheritance component and a positive association with paternal age.

Journal ArticleDOI
TL;DR: A 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci, providing fresh insights into the mechanisms regulating heart rate.
Abstract: Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate-increasing and heart rate-decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.

Journal ArticleDOI
19 Dec 2013-Nature
TL;DR: Starting with a severely affected family, this work has identified a link between impaired soluble-guanylyl-cyclase-dependent nitric oxide signalling and myocardial infarction risk, possibly through accelerated thrombus formation, and demonstrated in vitro that mutations in both GUCY1A3 and CCT7 severely reduce α1-sGC as well as β1- sGC protein content, and impair soluble guanyly l cyclase activity.
Abstract: Myocardial infarction, a leading cause of death intheWesternworld(1), usually occurs when the fibrous cap overlying an atherosclerotic plaque in a coronary artery ruptures. The resulting exposure of blood to the atherosclerotic material then triggers thrombus formation, which occludes the artery(2). The importance of genetic predisposition to coronary artery disease and myocardial infarction is best documented by the predictive value of a positive family history(3). Nextgeneration sequencing in families with several affected individuals has revolutionized mutation identification(4). Here we report the segregation of two private, heterozygous mutations in two functionally relatedgenes, GUCY1A3 (p.Leu163Phefs*24) andCCT7 (p.Ser525Leu), in an extended myocardial infarction family. GUCY1A3 encodes the alpha 1 subunit of soluble guanylyl cyclase (alpha 1-sGC)(5), and CCT7 encodes CCT eta, a member of the tailless complex polypeptide 1 ring complex(6), which, among other functions, stabilizes soluble guanylyl cyclase. After stimulation with nitric oxide, soluble guanylyl cyclase generates cGMP, which induces vasodilation and inhibits platelet activation(7). Wedemonstratein vitro that mutations inbothGUCY1A3 and CCT7 severely reduce alpha 1-sGC as well as beta 1-sGC protein content, and impair soluble guanylyl cyclase activity. Moreover, platelets from digenic mutation carriers contained less soluble guanylyl cyclase protein and consequently displayed reduced nitric-oxideinduced cGMP formation. Mice deficient in alpha 1-sGC protein displayed accelerated thrombus formation in themicrocirculation after local trauma. Starting with a severely affected family, we have identified a link between impaired soluble-guanylyl-cyclase-dependent nitric oxide signalling and myocardial infarction risk, possibly through accelerated thrombus formation. Reversing this defect may provide a new therapeutic target for reducing the risk of myocardial infarction.

Journal ArticleDOI
Tove Fall1, Sara Hägg2, Sara Hägg1, Reedik Mägi3  +147 moreInstitutions (41)
TL;DR: 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.
Abstract: 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 ...

Journal ArticleDOI
TL;DR: Overall, common genetic variants that influence plasma tHcy concentrations are not associated with risk of CAD in white populations, which further refutes the causal relevance of moderately elevated tH Cy concentrations and tHCy-related pathways for CAD.

Journal ArticleDOI
TL;DR: A network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk.
Abstract: Objective— Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene–disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results— We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. Twenty-four coexpression modules were identified, including 1 case-specific and 1 control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with gene expression–associated single-nucleotide polymorphisms and with results of genome-wide association studies of CHD and its risk factors, the control-specific DM was implicated as CHD causal based on its significant enrichment for both CHD and lipid expression–associated single-nucleotide polymorphisms. This causal DM was further integrated with tissue-specific Bayesian networks and protein–protein interaction networks to identify regulatory key driver genes. Multitissue key drivers ( SPIB and TNFRSF13C ) and tissue-specific key drivers (eg, EBF1 ) were identified. Conclusions— Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk.

Journal ArticleDOI
Santhi K. Ganesh1, Vinicius Tragante2, Wei Guo3, Yiran Guo4, Matthew B. Lanktree5, Erin N. Smith6, Toby Johnson7, Berta Almoguera Castillo4, John Barnard8, Jens Baumert, Yen Pei C. Chang9, Clara C. Elbers2, Martin Farrall10, Mary E. Fischer11, Nora Franceschini12, Tom R. Gaunt13, Johannes M.I.H. Gho2, Christian Gieger, Yan Gong14, Aaron Isaacs15, Marcus E. Kleber16, Irene Mateo Leach17, Caitrin W. McDonough14, Matthijs F.L. Meijs2, Olle Mellander18, Cliona Molony, Ilja M. Nolte17, Sandosh Padmanabhan19, Tom S. Price20, Ramakrishnan Rajagopalan21, Jonathan A. Shaffer22, Sonia Shah23, Haiqing Shen9, Nicole Soranzo24, Peter J. van der Most17, Erik P A Van Iperen, Jessica van Setten2, Judith M. Vonk17, Li Zhang8, Amber L. Beitelshees8, Gerald S. Berenson25, Deepak L. Bhatt26, Jolanda M. A. Boer, Eric Boerwinkle27, Ben Burkley14, Amber A. Burt21, Aravinda Chakravarti, Wei Chen25, Rhonda M. Cooper-DeHoff14, Sean P. Curtis28, Albert W. Dreisbach29, David Duggan30, Georg Ehret, Richard R. Fabsitz31, Myriam Fornage27, Ervin R. Fox29, Clement E. Furlong21, Ron T. Gansevoort17, Marten H. Hofker17, G. Kees Hovingh, Susan Kirkland32, Kandice Kottke-Marchant8, Abdullah Kutlar33, Andrea Z. LaCroix34, Taimour Y. Langaee14, Yun Li4, Honghuang Lin35, Kiang Liu36, Steffi Maiwald37, Rainer Malik38, Gurunathan Murugesan8, Christopher Newton-Cheh39, Christopher Newton-Cheh26, Jeffery R. O'Connell9, N. Charlotte Onland-Moret2, Willem H. Ouwehand24, Walter Palmas22, Brenda W.J.H. Penninx40, Carl J. Pepine14, Mary Pettinger31, Joseph F. Polak26, Vasan S. Ramachandran31, Vasan S. Ramachandran35, Jane E. Ranchalis21, Susan Redline26, Paul M. Ridker26, Lynda M. Rose26, Hubert Scharnag41, Hubert Scharnag1, Nicholas J. Schork42, Daichi Shimbo22, Alan R. Shuldiner43, Alan R. Shuldiner9, Sathanur R. Srinivasan25, Ronald P. Stolk17, Herman A. Taylor29, Barbara Thorand, Mieke D. Trip37, Cornelia M. van Duijn15, W. M. Monique Verschuren, Cisca Wijmenga17, Bernhard R. Winkelmann, Sharon B. Wyatt29, J. Hunter Young44, Bernhard O. Boehm45, Mark J. Caulfield7, Daniel I. Chasman26, Karina W. Davidson22, Pieter A. Doevendans2, Garret A. FitzGerald4, John G. Gums14, Hakon Hakonarson4, Hans L. Hillege17, Thomas Illig46, Gail P. Jarvik21, Julie A. Johnson14, John J.P. Kastelein, Wolfgang Koenig45, Winfried März16, Winfried März47, Braxton D. Mitchell9, Sarah S. Murray48, Albertine J. Oldehinkel17, Daniel J. Rader4, Muredach P. Reilly4, Alexander P. Reiner34, Eric E. Schadt49, Roy L. Silverstein3, Roy L. Silverstein50, Harold Snieder17, Alice Stanton51, André G. Uitterlinden15, Pim van der Harst17, Yvonne T. van der Schouw2, Nilesh J. Samani52, Nilesh J. Samani53, Andrew D. Johnson31, Patricia B. Munroe7, Paul I.W. de Bakker39, Paul I.W. de Bakker26, Paul I.W. de Bakker2, Xiaofeng Zhu3, Daniel Levy, Brendan J. Keating4, Folkert W. Asselbergs2 
University of Michigan1, Utrecht University2, Case Western Reserve University3, University of Pennsylvania4, University of Western Ontario5, University of California, San Diego6, Queen Mary University of London7, Cleveland Clinic8, University of Maryland, Baltimore9, University of Oxford10, University of Wisconsin-Madison11, University of North Carolina at Chapel Hill12, University of Bristol13, University of Florida14, Erasmus University Rotterdam15, Heidelberg University16, University of Groningen17, Lund University18, University of Glasgow19, Medical Research Council20, University of Washington21, Columbia University22, University College London23, NHS Blood and Transplant24, Tulane University25, Harvard University26, University of Texas Health Science Center at Houston27, Merck & Co.28, University of Mississippi29, Translational Genomics Research Institute30, National Institutes of Health31, Dalhousie University32, Georgia Regents University33, Fred Hutchinson Cancer Research Center34, Boston University35, Northwestern University36, University of Amsterdam37, Ludwig Maximilian University of Munich38, Broad Institute39, VU University Amsterdam40, Medical University of Graz41, Scripps Research Institute42, Veterans Health Administration43, Johns Hopkins University44, University of Ulm45, Hannover Medical School46, Synlab Group47, Scripps Health48, Icahn School of Medicine at Mount Sinai49, Cleveland Clinic Lerner Research Institute50, Royal College of Surgeons in Ireland51, University of Leicester52, Glenfield Hospital53
TL;DR: Two novel loci associated with BP are identified and multiple previously reported associations are confirmed, extending the understanding of genes involved in BP regulation and some of which may eventually provide new targets for therapeutic intervention.
Abstract: Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10(-6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.

Journal ArticleDOI
Maria Sabater-Lleal1, Jie Huang, Daniel I. Chasman2, Silvia Naitza, Abbas Dehghan3, Andrew D. Johnson, Alexander Teumer4, Alexander P. Reiner5, Lasse Folkersen1, Saonli Basu6, Alicja R. Rudnicka7, Stella Trompet8, Anders Mälarstig1, Jens Baumert, Joshua C. Bis9, Xiuqing Guo10, Jouke J. Hottenga11, So-Youn Shin12, Lorna M. Lopez13, Jari Lahti14, Toshiko Tanaka15, Lisa R. Yanek16, Tiphaine Oudot-Mellakh17, James F. Wilson13, Pau Navarro13, Jennifer E. Huffman18, Tatijana Zemunik19, Susan Redline20, Reena Mehra, Drazen Pulanic21, Igor Rudan13, Alan F. Wright18, Ivana Kolcic19, Ozren Polasek19, Sarah H. Wild13, Harry Campbell13, J. David Curb22, Robert B. Wallace23, Simin Liu24, Charles B. Eaton25, Diane M. Becker16, Lewis C. Becker16, Stefania Bandinelli, Katri Räikkönen14, Elisabeth Widen14, Aarno Palotie14, Myriam Fornage26, David Green27, Myron D. Gross6, Gail Davies13, Sarah E. Harris18, David C. Liewald13, John M. Starr18, Frances M K Williams28, Peter J. Grant29, Tim D. Spector28, Rona J. Strawbridge1, Angela Silveira1, Bengt Sennblad1, Fernando Rivadeneira3, André G. Uitterlinden3, Oscar H. Franco3, Albert Hofman3, Jenny van Dongen11, Gonneke Willemsen11, Dorret I. Boomsma11, Jie Yao10, Nancy S. Jenny30, Talin Haritunians10, Barbara McKnight9, Thomas Lumley9, Kent D. Taylor10, Jerome I. Rotter10, Bruce M. Psaty9, Annette Peters, Christian Gieger, Thomas Illig31, Anne Grotevendt4, Georg Homuth, Henry Völzke, Thomas D. Kocher, Anuj Goel32, Maria Grazia Franzosi33, Udo Seedorf34, Robert Clarke35, Maristella Steri, Kirill V. Tarasov15, Serena Sanna, David Schlessinger15, David J. Stott36, Naveed Sattar, Brendan M. Buckley37, Ann Rumley36, Gordon D.O. Lowe36, Wendy L. McArdle12, Ming-Huei Chen38, Geoffrey H. Tofler39, Jaejoon Song6, Eric Boerwinkle26, Aaron R. Folsom6, Lynda M. Rose2, Anders Franco-Cereceda40, Martina Teichert3, M. Arfan Ikram3, Thomas H. Mosley41, Steve Bevan7, Martin Dichgans42, Peter M. Rothwell35, Cathie Sudlow13, Jemma C. Hopewell35, John C. Chambers43, Danish Saleheen44, Jaspal S. Kooner15, John Danesh45, Christopher P. Nelson46, Jeanette Erdmann47, Muredach P. Reilly15, Sekar Kathiresan48, Heribert Schunkert47, Pierre-Emmanuel Morange49, Luigi Ferrucci15, Johan G. Eriksson50, David R. Jacobs6, Ian J. Deary13, Nicole Soranzo51, Jacqueline C.M. Witteman3, Eco J. C. de Geus11, Russell P. Tracy30, Caroline Hayward18, Wolfgang Koenig52, Francesco Cucca, J. Wouter Jukema8, Per Eriksson1, Sudha Seshadri38, Hugh S. Markus7, Hugh Watkins32, Nilesh J. Samani46, Henri Wallaschofski4, Nicholas L. Smith9, David-Alexandre Trégouët53, Paul M. Ridker2, Weihong Tang6, David P. Strachan7, Anders Hamsten40, Christopher J. O'Donnell15 
Karolinska University Hospital1, Brigham and Women's Hospital2, Erasmus University Rotterdam3, Greifswald University Hospital4, Fred Hutchinson Cancer Research Center5, University of Minnesota6, St George's, University of London7, Leiden University Medical Center8, University of Washington9, Cedars-Sinai Medical Center10, VU University Amsterdam11, University of Bristol12, University of Edinburgh13, University of Helsinki14, National Institutes of Health15, Johns Hopkins University School of Medicine16, French Institute of Health and Medical Research17, Western General Hospital18, University of Split19, Beth Israel Deaconess Medical Center20, Josip Juraj Strossmayer University of Osijek21, University of Hawaii22, University of Iowa23, University of California, Los Angeles24, Brown University25, University of Texas Health Science Center at Houston26, Northwestern University27, King's College London28, University of Leeds29, University of Vermont30, Hannover Medical School31, Wellcome Trust Centre for Human Genetics32, Mario Negri Institute for Pharmacological Research33, University of Münster34, University of Oxford35, University of Glasgow36, University College Cork37, Boston University38, University of Sydney39, Karolinska Institutet40, University of Mississippi Medical Center41, Ludwig Maximilian University of Munich42, Imperial College London43, University of Pennsylvania44, University of Cambridge45, University of Leicester46, University of Lübeck47, Harvard University48, Aix-Marseille University49, Helsinki University Central Hospital50, Wellcome Trust51, University of Ulm52, Pierre-and-Marie-Curie University53
TL;DR: Clinical outcome analysis of these loci does not support a causal relationship between circulating levels of fibrinogen and coronary artery disease, stroke, or venous thromboembolism.
Abstract: Background—Estimates of the heritability of plasma fibrinogen concentration, an established predictor of cardiovascular disease, range from 34% to 50%. Genetic variants so far identified by genome-...

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Michael V. Holmes1, Tabassome Simon2, Tabassome Simon3, Holly J. Exeter1, Lasse Folkersen4, Folkert W. Asselbergs5, Montse Guardiola, Jackie A. Cooper1, Jutta Palmen1, Jaroslav A. Hubacek, Kathryn F. Carruthers6, Benjamin D. Horne7, Kimberly D. Brunisholz, Jessica L. Mega8, Erik P A Van Iperen9, Mingyao Li10, Maarten Leusink5, Stella Trompet11, Jeffrey J. W. Verschuren11, G. Kees Hovingh9, Abbas Dehghan12, Christopher P. Nelson13, Salma Kotti, Nicolas Danchin14, Nicolas Danchin15, Markus Scholz16, Christiane L Haase17, Dietrich Rothenbacher14, Dietrich Rothenbacher15, Daniel I. Swerdlow1, Karoline Kuchenbaecker18, Eleonora Staines-Urias19, Anuj Goel20, Ferdinand Van 'T Hooft4, Karl Gertow4, Ulf de Faire4, Andrie G. Panayiotou21, Elena Tremoli22, Damiano Baldassarre22, Fabrizio Veglia, Lesca M. Holdt23, Lesca M. Holdt16, Frank Beutner16, Ron T. Gansevoort24, Gerjan Navis24, Irene Mateo Leach24, Lutz P. Breitling14, Hermann Brenner14, Joachim Thiery16, Dhayana Dallmeier15, Anders Franco-Cereceda4, Jolanda M. A. Boer, Jeffrey W. Stephens25, Marten H. Hofker24, Alain Tedgui2, Albert Hofman12, André G. Uitterlinden12, Vera Adamkova, Jan Pitha, N. Charlotte Onland-Moret5, Maarten J. Cramer5, Hendrik M. Nathoe5, Wilko Spiering5, Olaf H. Klungel5, Meena Kumari1, Peter H. Whincup19, David A. Morrow8, Peter S. Braund13, Alistair S. Hall26, Anders G. Olsson27, Pieter A. Doevendans5, Mieke D. Trip9, Martin D. Tobin13, Anders Hamsten4, Hugh Watkins20, Wolfgang Koenig15, Andrew N. Nicolaides28, Daniel Teupser16, Daniel Teupser23, Ian N.M. Day, John F. Carlquist7, Tom R. Gaunt29, Ian Ford30, Naveed Sattar30, Sotirios Tsimikas31, Gregory G. Schwartz32, Debbie A Lawlor29, Richard W Morris1, Manjinder S. Sandhu32, Rudolf Poledne, Anke H. Maitland-van der Zee5, Kay-Tee Khaw18, Brendan J. Keating33, Pim van der Harst24, Jackie F. Price6, Shamir R. Mehta, Salim Yusuf34, Jaqueline C M Witteman12, Oscar H. Franco12, J. Wouter Jukema11, Peter de Knijff11, Anne Tybjærg-Hansen17, Daniel J. Rader10, Martin Farrall20, Nilesh J. Samani13, Mika Kivimäki1, Keith A.A. Fox6, Steve E. Humphries1, Jeffrey L. Anderson7, S. Matthijs Boekholdt9, Tom Palmer35, Per Eriksson4, Guillaume Paré, Aroon D. Hingorani1, Marc S. Sabatine8, Ziad Mallat2, Ziad Mallat18, Juan P. Casas19, Juan P. Casas1, Philippa J. Talmud1 
TL;DR: In this paper, the role of secretory phospholipase A2 (sPLA2)-IIA in cardiovascular disease was investigated by using a Mendelian randomization meta-analysis of 19 general population studies and 10 acute coronary syndrome (ACS) cohorts.

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31 Jul 2013-PLOS ONE
TL;DR: Data suggest that regular engagement in ultra-endurance aerobic exercise attenuates cellular aging and is associated with shorter mean leukocyte telomere length.
Abstract: Telomere length is recognized as a marker of biological age, and shorter mean leukocyte telomere length is associated with increased risk of cardiovascular disease. It is unclear whether repeated exposure to ultra-endurance aerobic exercise is beneficial or detrimental in the long-term and whether it attenuates biological aging. We quantified 67 ultra-marathon runners' and 56 apparently healthy males' leukocyte telomere length (T/S ratio) using real-time quantitative PCR. The ultra-marathon runners had 11% longer telomeres (T/S ratio) than controls (ultra-marathon runners: T/S ratio = 3.5 +/- 0.68, controls: T/S ratio = 3.1 +/- 0.41; beta = 0.40, SE = 0.10, P = 1.4x10(-4)) in age-adjusted analysis. The difference remained statistically significant after adjustment for cardiovascular risk factors (P = 2.2x10(-4)). The magnitude of this association translates into 16.2 +/- 0.26 years difference in biological age and approximately 324-648bp difference in leukocyte telomere length between ultra-marathon runners and healthy controls. Neither traditional cardiovascular risk factors nor markers of inflammation/adhesion molecules explained the difference in leukocyte telomere length between ultra-marathon runners and controls. Taken together these data suggest that regular engagement in ultra-endurance aerobic exercise attenuates cellular aging.

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TL;DR: This study diagnosed clinically unapparent cholesterol ester storage disease in the affected individuals from this kindred and addressed an outstanding question about risk of cardiovascular disease in LIPA E8SJM heterozygous carriers.
Abstract: Objective— Autosomal recessive hypercholesterolemia is a rare inherited disorder, characterized by extremely high total and low-density lipoprotein cholesterol levels, that has been previously linked to mutations in LDLRAP1 . We identified a family with autosomal recessive hypercholesterolemia not explained by mutations in LDLRAP1 or other genes known to cause monogenic hypercholesterolemia. The aim of this study was to identify the molecular pathogenesis of autosomal recessive hypercholesterolemia in this family. Approach and Results— We used exome sequencing to assess all protein-coding regions of the genome in 3 family members and identified a homozygous exon 8 splice junction mutation (c.894G>A, also known as E8SJM) in LIPA that segregated with the diagnosis of hypercholesterolemia. Because homozygosity for mutations in LIPA is known to cause cholesterol ester storage disease, we performed directed follow-up phenotyping by noninvasively measuring hepatic cholesterol content. We observed abnormal hepatic accumulation of cholesterol in the homozygote individuals, supporting the diagnosis of cholesterol ester storage disease. Given previous suggestions of cardiovascular disease risk in heterozygous LIPA mutation carriers, we genotyped E8SJM in >27 000 individuals and found no association with plasma lipid levels or risk of myocardial infarction, confirming a true recessive mode of inheritance. Conclusions— By integrating observations from Mendelian and population genetics along with directed clinical phenotyping, we diagnosed clinically unapparent cholesterol ester storage disease in the affected individuals from this kindred and addressed an outstanding question about risk of cardiovascular disease in LIPA E8SJM heterozygous carriers.

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TL;DR: A genetic marker associated with cardiovascular risk factors, and in particular concurrent vascular disease, appeared to independently contribute to susceptibility for AAA, given the potential genetic overlap between risk factor and disease phenotypes.
Abstract: Abdominal aortic aneurysm (AAA) is a common human disease with a high estimated heritability (0.7); however, only a small number of associated genetic loci have been reported to date. In contrast, over 100 loci have now been reproducibly associated with either blood lipid profile and/or coronary artery disease (CAD) (both risk factors for AAA) in large-scale meta-analyses. This study employed a staged design to investigate whether the loci for these two phenotypes are also associated with AAA. Validated CAD and dyslipidaemia loci underwent screening using the Otago AAA genome-wide association data set. Putative associations underwent staged secondary validation in 10 additional cohorts. A novel association between the SORT1 (1p13.3) locus and AAA was identified. The rs599839 G allele, which has been previously associated with both dyslipidaemia and CAD, reached genome-wide significance in 11 combined independent cohorts (meta-analysis with 7048 AAA cases and 75 976 controls: G allele OR 0.81, 95% CI 0.76–0.85, P = 7.2 × 10⁻¹⁴). Modelling for confounding interactions of concurrent dyslipidaemia, heart disease and other risk factors suggested that this marker is an independent predictor of AAA susceptibility. In conclusion, a genetic marker associated with cardiovascular risk factors, and in particular concurrent vascular disease, appeared to independently contribute to susceptibility for AAA. Given the potential genetic overlap between risk factor and disease phenotypes, the use of well-characterized case–control cohorts allowing for modelling of cardiovascular disease risk confounders will be an important component in the future discovery of genetic markers for conditions such as AAA.

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TL;DR: Low-density lipoprotein receptor (LDLR) rs6511720 A was significantly associated overall and in 3 of 5 individual replication studies, consistent with established effects of this variant on coronary artery disease.
Abstract: Background— Abdominal aortic aneurysm (AAA) is a common cardiovascular disease among older people and demonstrates significant heritability. In contrast to similar complex diseases, relatively few genetic associations with AAA have been confirmed. We reanalyzed our genome-wide study and carried through to replication suggestive discovery associations at a lower level of significance. Methods and Results— A genome-wide association study was conducted using 1830 cases from the United Kingdom, New Zealand, and Australia with infrarenal aorta diameter ≥30 mm or ruptured AAA and 5435 unscreened controls from the 1958 Birth Cohort and National Blood Service cohort from the Wellcome Trust Case Control Consortium. Eight suggestive associations with P <1×10−4 were carried through to in silico replication in 1292 AAA cases and 30 503 controls. One single-nucleotide polymorphism associated with P <0.05 after Bonferroni correction in the in silico study underwent further replication (706 AAA cases and 1063 controls from the United Kingdom, 507 AAA cases and 199 controls from Denmark, and 885 AAA cases and 1000 controls from New Zealand). Low-density lipoprotein receptor ( LDLR ) rs6511720 A was significantly associated overall and in 3 of 5 individual replication studies. The full study showed an association that reached genome-wide significance (odds ratio, 0.76; 95% confidence interval, 0.70–0.83; P =2.08×10−10). Conclusions— LDLR rs6511720 is associated with AAA. This finding is consistent with established effects of this variant on coronary artery disease. Shared causal pathways with other cardiovascular diseases may present novel opportunities for preventative and therapeutic strategies for AAA.

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TL;DR: Most blood pressure–associated polymorphisms also confer an increased risk for coronary artery disease, consistent with a causal relationship of increasing blood pressure to coronary artery Disease.
Abstract: Hypertension is a risk factor for coronary artery disease. Recent genome-wide association studies have identified 30 genetic variants associated with higher blood pressure at genome-wide significance (P 1 for coronary artery disease, a proportion much higher than expected by chance (P=4 × 10(-5)). The average relative coronary artery disease risk increase per each of the multiple blood pressure-raising alleles observed in the consortium was 3.0% for systolic blood pressure-associated polymorphisms (95% confidence interval, 1.8%-4.3%) and 2.9% for diastolic blood pressure-associated polymorphisms (95% confidence interval, 1.7%-4.1%). In substudies, individuals carrying most systolic blood pressure- and diastolic blood pressure-related risk alleles (top quintile of a genetic risk score distribution) had 70% (95% confidence interval, 50%-94%) and 59% (95% confidence interval, 40%-81%) higher odds of having coronary artery disease, respectively, as compared with individuals in the bottom quintile. In conclusion, most blood pressure-associated polymorphisms also confer an increased risk for coronary artery disease. These findings are consistent with a causal relationship of increasing blood pressure to coronary artery disease. Genetic variants primarily affecting blood pressure contribute to the genetic basis of coronary artery disease.

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TL;DR: The 9p21 locus shows convincing association with greater burden of CAD but not with MI in the presence of underlying CAD, adding further weight to the hypothesis that 9p 21 locus primarily mediates an atherosclerotic phenotype.

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TL;DR: The results strongly point to a common biological basis of the regulation of theregulation of the authors' appetite for tobacco and food, and thus the vulnerability to nicotine addiction and obesity, and the effect of single-nucleotide polymorphisms affecting body mass index (BMI).
Abstract: Smoking influences body weight such that smokers weigh less than non-smokers and smoking cessation often leads to weight increase. The relationship between body weight and smoking is partly explained by the effect of nicotine on appetite and metabolism. However, the brain reward system is involved in the control of the intake of both food and tobacco. We evaluated the effect of single-nucleotide polymorphisms (SNPs) affecting body mass index (BMI) on smoking behavior, and tested the 32 SNPs identified in a meta-analysis for association with two smoking phenotypes, smoking initiation (SI) and the number of cigarettes smoked per day (CPD) in an Icelandic sample (N=34 216 smokers). Combined according to their effect on BMI, the SNPs correlate with both SI (r=0.019, P=0.00054) and CPD (r=0.032, P=8.0 × 10−7). These findings replicate in a second large data set (N=127 274, thereof 76 242 smokers) for both SI (P=1.2 × 10−5) and CPD (P=9.3 × 10−5). Notably, the variant most strongly associated with BMI (rs1558902-A in FTO) did not associate with smoking behavior. The association with smoking behavior is not due to the effect of the SNPs on BMI. Our results strongly point to a common biological basis of the regulation of our appetite for tobacco and food, and thus the vulnerability to nicotine addiction and obesity.

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TL;DR: In-depth analysis of these 105 cis eQTL revealed that at 76 loci genetic associations were compatible with additive effects of several SNPs, while for the 29 remaining regions data could be compatible with a more complex haplotypic pattern.
Abstract: In order to assess whether gene expression variability could be influenced by several SNPs acting in cis, either throughadditive or more complex haplotype effects, a systematic genome-wide search for cis haplotype expression quantitativetrait loci (eQTL) was conducted in a sample of 758 individuals, part of the Cardiogenics Transcriptomic Study, for whichgenome-wide monocyte expression and GWAS data were available. 19,805 RNA probes were assessed for cis haplotypicregulation through investigation of ,2,1610 9 haplotypic combinations. 2,650 probes demonstrated haplotypic p-values .10 4 -fold smaller than the best single SNP p-value. Replication of significant haplotype effects were tested for 412probes for which SNPs (or proxies) that defined the detected haplotypes were available in the Gutenberg Health Studycomposed of 1,374 individuals. At the Bonferroni correction level of 1.2610 24 (,0.05/412), 193 haplotypic signalsreplicated. 1000G imputation was then conducted, and 105 haplotypic signals still remained more informative than imputedSNPs. In-depth analysis of these 105 cis eQTL revealed that at 76 loci genetic associations were compatible with additiveeffects of several SNPs, while for the 29 remaining regions data could be compatible with a more complex haplotypicpattern. As 24 of the 105 cis eQTL have previously been reported to be disease-associated loci, this work highlights the needfor conducting haplotype-based and 1000G imputed cis eQTL analysis before commencing functional studies at disease-associated loci.

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TL;DR: Coronary artery disease predisposing haplogroup I of the Y chromosome is associated with downregulation of UTY and PRKY genes in macrophages but not with conventional cardiovascular risk factors.
Abstract: Objective— Haplogroup I of male-specific region of the human Y chromosome is associated with 50% increased risk of coronary artery disease. It is not clear to what extent conventional cardiovascular risk factors and genes of the male-specific region may explain this association. Approach and Results— A total of 1988 biologically unrelated men from 4 white European populations were genotyped using 11 Y chromosome single nucleotide polymorphisms and classified into 13 most common European haplogroups. Approximately 75% to 93% of the haplotypic variation of the Y chromosome in all cohorts was attributable to I, R1a, and R1b1b2 lineages. None of traditional cardiovascular risk factors, including body mass index, blood pressures, lipids, glucose, C-reactive protein, creatinine, and insulin resistance, was associated with haplogroup I of the Y chromosome in the joint inverse variance meta-analysis. Fourteen of 15 ubiquitous single-copy genes of the male-specific region were expressed in human macrophages. When compared with men with other haplogroups, carriers of haplogroup I had ≈0.61- and 0.64-fold lower expression of ubiquitously transcribed tetratricopeptide repeat, Y-linked gene ( UTY ) and protein kinase, Y-linked, pseudogene ( PRKY ) in macrophages ( P =0.0001 and P =0.002, respectively). Conclusions— Coronary artery disease predisposing haplogroup I of the Y chromosome is associated with downregulation of UTY and PRKY genes in macrophages but not with conventional cardiovascular risk factors.

Journal ArticleDOI
03 Jul 2013-PLOS ONE
TL;DR: 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.
Abstract: 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= 20.051, p=0.009) as well as between full PTSD and shorter TL (beta= 20.103, 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.

Journal ArticleDOI
Sarah H. Stephens1, Sarah M. Hartz2, Nicole R. Hoft3, Nancy L. Saccone2, Robin C. Corley3, John K. Hewitt3, Christian J. Hopfer3, Naomi Breslau4, Hilary Coon5, Xiangning Chen6, Francesca Ducci7, Francesca Ducci8, Nicole Dueker1, Nora Franceschini9, Josef Frank10, Younghun Han11, Nadia N. Hansel12, Chenhui Jiang13, Tellervo Korhonen14, Penelope A. Lind15, Jason Z. Liu16, Leo-Pekka Lyytikäinen, Martha Michel17, John R. Shaffer18, Susan E. Short19, Juzhong Sun20, Alexander Teumer21, John R. Thompson22, Nicole Vogelzangs23, Jacqueline M. Vink23, Angela S. Wenzlaff24, William Wheeler25, Bao-Zhu Yang13, Steven H. Aggen6, Anthony J. Balmforth26, Sebastian E. Baumeister21, Terri H. Beaty12, Daniel J. Benjamin27, Andrew W. Bergen17, Ulla Broms14, David Cesarini28, Nilanjan Chatterjee25, Jingchun Chen6, Yu-Ching Cheng1, Sven Cichon29, David J Couper8, Francesco Cucca, Danielle M. Dick6, Tatiana Foroud30, Helena Furberg31, Ina Giegling32, Nathan A. Gillespie6, Fangyi Gu25, Alistair S. Hall26, Jenni Hällfors14, Shizhong Han13, Annette M. Hartmann32, Kauko Heikkilä14, Ian B. Hickie33, Jouke-Jan Hottenga23, Pekka Jousilahti34, Marika Kaakinen35, Mika Kähönen, Philipp Koellinger36, Stephen Kittner1, Bettina Konte32, Maria Teresa Landi25, Tiina Laatikainen34, Mark Leppert5, Steven M. Levy37, Rasika A. Mathias12, Daniel W. McNeil38, Sarah E. Medland15, Grant W. Montgomery15, Tanda Murray12, Matthias Nauck21, Kari E. North9, Peter D. Paré39, Michele L. Pergadia2, Ingo Ruczinski12, Veikko Salomaa34, Jorma Viikari40, Gonneke Willemsen23, Kathleen C. Barnes12, Eric Boerwinkle41, Dorret I. Boomsma23, Neil E. Caporaso25, Howard J. Edenberg30, Clyde Francks42, Joel Gelernter13, Hans J. Grabe21, Hyman Hops43, Marjo-Riitta Järvelin44, Marjo-Riitta Järvelin35, Marjo-Riitta Järvelin34, Magnus Johannesson45, Kenneth S. Kendler6, Terho Lehtimäki, Patrik K. E. Magnusson46, Mary L. Marazita18, Jonathan Marchini16, Braxton D. Mitchell1, Markus M. Nöthen29, Brenda W.J.H. Penninx23, Olli T. Raitakari40, Marcella Rietschel10, Dan Rujescu32, Nilesh J. Samani22, Ann G. Schwartz24, Sanjay Shete11, Margaret R. Spitz11, Gary E. Swan17, Henry Völzke21, Juha Veijola35, Qingyi Wei11, Christopher I. Amos11, Dale S. Cannon5, Richard A. Grucza2, Dorothy K. Hatsukami47, Andrew C. Heath2, Eric O. Johnson48, Jaakko Kaprio14, Pamela A. F. Madden2, Nicholas G. Martin15, Victoria L. Stevens20, Robert B. Weiss5, Peter Kraft49, Laura J. Bierut2, Marissa A. Ehringer3 
TL;DR: The results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotype.
Abstract: Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotype.