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ABSTRACT: Background. Early diagnosis of acute coronary syndrome (ACS) is frequently a challenging task. Aims. To assess the role of novel biomarkers to identify ACS. Methods. Concentrations of lipids, lipoproteins, oxidized LDL (oxLDL), high-sensitivity C-reactive protein (hsCRP), paraoxonase-1 (PON1), secretory phospholipase A2 (sPLA2), and myeloperoxidase (MPO) were measured in 703 patients (mean age 65.5 ± 11.2 years; 422 men, 281 women) without diabetes mellitus assigned to coronary angiogram. The subjects were divided into three groups: ACS (n = 242), stable angina pectoris (SAP) (n = 242), and normal coronary artery (NCA) (n = 219). Results. HDL-cholesterol (HDL-C) (P < 0.001) and apolipoproteinA-I concentrations (P < 0.0001) were lowest in subjects with ACS. LDL-C (P = 0.008) and non-HDL (P < 0.0001) were higher in the ACS group than in the SAP group. Leukocyte count (P < 0.0001), oxLDL (P < 0.05), hsCRP (P < 0.001), sPLA2 (P < 0.05), and MPO (P < 0.0001) were highest in the ACS group. In multivariate models, comprising all biomarkers, elevated level of MPO had the best discriminatory power to identify patients with ACS. Receiver-operating characteristic curve with and without MPO comparison differed significantly (P = 0.03 for both ACS versus NCA and ACS versus SAP). Conclusion. Our study shows that ACS associates with low HDL-C and biomarkers of oxidative stress and inflammation. The addition of MPO in biomarker panels might improve diagnostic accuracy for ACS.
Annals of medicine 05/2013; · 3.52 Impact Factor
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ABSTRACT: OBJECTIVE: Genome-wide association studies have identified several genetic variants associated with coronary heart disease (CHD). The aim of this study was to evaluate the genetic risk discrimination and reclassification and apply the results for a 2-stage population risk screening strategy for CHD.Approach and Results-We genotyped 28 genetic variants in 24 124 participants in 4 Finnish population-based, prospective cohorts (recruitment years 1992-2002). We constructed a multilocus genetic risk score and evaluated its association with incident cardiovascular disease events. During the median follow-up time of 12 years (interquartile range 8.75-15.25 years), we observed 1093 CHD, 1552 cardiovascular disease, and 731 acute coronary syndrome events. Adding genetic information to conventional risk factors and family history improved risk discrimination of CHD (C-index 0.856 versus 0.851; P=0.0002) and other end points (cardiovascular disease: C-index 0.840 versus 0.837, P=0.0004; acute coronary syndrome: C-index 0.859 versus 0.855, P=0.001). In a standard population of 100 000 individuals, additional genetic screening of subjects at intermediate risk for CHD would reclassify 2144 subjects (12%) into high-risk category. Statin allocation for these subjects is estimated to prevent 135 CHD cases over 14 years. Similar results were obtained by external validation, where the effects were estimated from a training data set and applied for a test data set. CONCLUSIONS: Genetic risk score improves risk prediction of CHD and helps to identify individuals at high risk for the first CHD event. Genetic screening for individuals at intermediate cardiovascular risk could help to prevent future cases through better targeting of statins.
Arteriosclerosis Thrombosis and Vascular Biology 04/2013; · 6.37 Impact Factor
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Sonja I Berndt,
Stefan Gustafsson,
Reedik Mägi,
Andrea Ganna,
Eleanor Wheeler,
Mary F Feitosa,
Anne E Justice,
Keri L Monda,
Damien C Croteau-Chonka,
Felix R Day, [......],
Joel N Hirschhorn,
Cecilia M Lindgren,
Andrew P Morris,
David Meyre,
André Scherag,
Mark I McCarthy,
Elizabeth K Speliotes,
Kari E North,
Ruth J F Loos,
Erik Ingelsson
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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.
Nature Genetics 04/2013; · 35.53 Impact Factor
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Sonja I Berndt,
Stefan Gustafsson,
Reedik Magi,
Andrea Ganna,
Eleanor Wheeler,
Mary F Feitosa,
Anne E Justice,
Keri L Monda,
Damien C Croteau-Chonka,
Felix R Day, [......],
Joel N Hirschhorn,
Cecilia M Lindgren,
Andrew P Morris,
David Meyre,
Andre Scherag,
Mark I McCarthy,
Elizabeth K Speliotes,
Kari E North,
Ruth J F Loos,
Erik Ingelsson
[show abstract]
[hide abstract]
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.
Nature Genetics 04/2013; · 35.53 Impact Factor
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Veryan Codd,
Christopher P Nelson,
Eva Albrecht,
Massimo Mangino,
Joris Deelen,
Jessica L Buxton,
Jouke Jan Hottenga,
Krista Fischer,
Tõnu Esko,
Ida Surakka, [......],
Iiris Hovatta,
Christian Gieger,
Andres Metspalu,
Dorret I Boomsma,
Marjo-Riitta Jarvelin,
P Eline Slagboom,
John R Thompson,
Tim D Spector,
Pim van der Harst,
Nilesh J Samani
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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.
Nature Genetics 03/2013; 45(4):422-427. · 35.53 Impact Factor
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Diana L Cousminer,
Diane J Berry,
Nicholas J Timpson,
Wei Ang,
Elisabeth Thiering,
Enda Byrne,
H Rob Taal,
Ville Huikari,
Jonathan P Bradfield,
Marjan Kerkhof, [......],
Joachim Heinrich,
Craig E Pennell,
Olli Raitakari,
Johan G Eriksson,
George Davey Smith,
Elina Hyppönen,
Marjo-Riitta Järvelin,
Mark I McCarthy, Samuli Ripatti,
Elisabeth Widén
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ABSTRACT: The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. While little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty, and cancer progression, pointing to shared underlying mechanisms.To discover genetic loci influencing pubertal height and growth and place them in context of overall growth and maturation, we performed genome-wide association (GWA) meta-analyses in up to 18,737 European samples utilizing longitudinally collected height measurements. We found significant associations (P<1.67 x 10-8) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased BMI, reduced pubertal growth, and earlier puberty.While epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty, and childhood obesity, and provides new information to pinpoint processes linking these traits.
Human Molecular Genetics 02/2013; · 7.64 Impact Factor
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Pirkka-Pekka Laurila,
Ida Surakka,
Antti-Pekka Sarin,
Laxman Yetukuri,
Tuulia Hyötyläinen,
Sanni Söderlund,
Jussi Naukkarinen,
Jing Tang,
Johannes Kettunen,
Daniel B Mirel, [......],
Veikko Salomaa,
Antti Jula,
Olli T Raitakari,
Marjo-Riitta Järvelin,
Aarno Palotie,
Leena Peltonen,
Matej Oresic,
Matti Jauhiainen,
Marja-Riitta Taskinen, Samuli Ripatti
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ABSTRACT: OBJECTIVE: Low high-density lipoprotein cholesterol (HDL-C) is associated with cardiometabolic pathologies. In this study, we investigate the biological pathways and individual genes behind low HDL-C by integrating results from 3 high-throughput data sources: adipose tissue transcriptomics, HDL lipidomics, and dense marker genotypes from Finnish individuals with low or high HDL-C (n=450).Approach and Results-In the pathway analysis of genetic data, we demonstrate that genetic variants within inflammatory pathways were enriched among low HDL-C associated single-nucleotide polymorphisms, and the expression of these pathways upregulated in the adipose tissue of low HDL-C subjects. The lipidomic analysis highlighted the change in HDL particle quality toward putatively more inflammatory and less vasoprotective state in subjects with low HDL-C, as evidenced by their decreased antioxidative plasmalogen contents. We show that the focal point of these inflammatory pathways seems to be the human leukocyte antigen region with its low HDL-associated alleles also associating with more abundant local transcript levels in adipose tissue, increased plasma vascular cell adhesion molecule 1 levels, and decreased HDL particle plasmalogen contents, markers of adipose tissue inflammation, vascular inflammation, and HDL antioxidative potential, respectively. In a population-based look-up of the inflammatory pathway single-nucleotide polymorphisms in a large Finnish cohorts (n=11 211), no association of the human leukocyte antigen region was detected for HDL-C as quantitative trait, but with extreme HDL-C phenotypes, implying the presence of low or high HDL genes in addition to the population-genomewide association studies-identified HDL genes. CONCLUSIONS: Our study highlights the role of inflammation with a genetic component in subjects with low HDL-C and identifies novel cis-expression quantitative trait loci variants in human leukocyte antigen region to be associated with low HDL-C.
Arteriosclerosis Thrombosis and Vascular Biology 02/2013; · 6.37 Impact Factor
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Andrey V Khrunin,
Denis V Khokhrin,
Irina N Filippova,
Tõnu Esko,
Mari Nelis,
Natalia A Bebyakova,
Natalia L Bolotova,
Janis Klovins,
Liene Nikitina-Zake,
Karola Rehnström, Samuli Ripatti,
Stefan Schreiber,
Andre Franke,
Milan Macek,
Veronika Krulišová,
Jan Lubinski,
Andres Metspalu,
Svetlana A Limborska
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ABSTRACT: Several studies examined the fine-scale structure of human genetic variation in Europe. However, the European sets analyzed represent mainly northern, western, central, and southern Europe. Here, we report an analysis of approximately 166,000 single nucleotide polymorphisms in populations from eastern (northeastern) Europe: four Russian populations from European Russia, and three populations from the northernmost Finno-Ugric ethnicities (Veps and two contrast groups of Komi people). These were compared with several reference European samples, including Finns, Estonians, Latvians, Poles, Czechs, Germans, and Italians. The results obtained demonstrated genetic heterogeneity of populations living in the region studied. Russians from the central part of European Russia (Tver, Murom, and Kursk) exhibited similarities with populations from central-eastern Europe, and were distant from Russian sample from the northern Russia (Mezen district, Archangelsk region). Komi samples, especially Izhemski Komi, were significantly different from all other populations studied. These can be considered as a second pole of genetic diversity in northern Europe (in addition to the pole, occupied by Finns), as they had a distinct ancestry component. Russians from Mezen and the Finnic-speaking Veps were positioned between the two poles, but differed from each other in the proportions of Komi and Finnic ancestries. In general, our data provides a more complete genetic map of Europe accounting for the diversity in its most eastern (northeastern) populations.
PLoS ONE 01/2013; 8(3):e58552. · 4.09 Impact Factor
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Matthijs J H M van der Loos,
Cornelius A Rietveld,
Niina Eklund,
Philipp D Koellinger,
Fernando Rivadeneira,
Gonçalo R Abecasis,
Georgina A Ankra-Badu,
Sebastian E Baumeister,
Daniel J Benjamin,
Reiner Biffar, [......],
Henry Völzke,
H-Erich Wichmann,
Philipp S Wild,
Sara M Willems,
Gonneke Willemsen,
Frank J A van Rooij,
Patrick J F Groenen,
André G Uitterlinden,
Albert Hofman,
A Roy Thurik
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ABSTRACT: Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg (2)/σP (2) = 25%, h (2) = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10(-5) were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.
PLoS ONE 01/2013; 8(4):e60542. · 4.09 Impact Factor
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Anna Köttgen,
Eva Albrecht,
Alexander Teumer,
Veronique Vitart,
Jan Krumsiek,
Claudia Hundertmark,
Giorgio Pistis,
Daniela Ruggiero,
Conall M O'Seaghdha,
Toomas Haller, [......],
Nicole Soranzo,
Daniela Toniolo,
Daniel I Chasman,
Olli Raitakari,
W H Linda Kao,
Marina Ciullo,
Caroline S Fox,
Mark Caulfield,
Murielle Bochud,
Christian Gieger
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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.
Nature genetics. 01/2013; 45(2):145-54.
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Anna Köttgen,
Eva Albrecht,
Alexander Teumer,
Veronique Vitart,
Jan Krumsiek,
Claudia Hundertmark,
Giorgio Pistis,
Daniela Ruggiero,
Conall M O'Seaghdha,
Toomas Haller, [......],
Nicole Soranzo,
Daniela Toniolo,
Daniel I Chasman,
Olli Raitakari,
W H Linda Kao,
Marina Ciullo,
Caroline S Fox,
Mark Caulfield,
Murielle Bochud,
Christian Gieger
[show abstract]
[hide abstract]
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.
Nature Genetics 12/2012; · 35.53 Impact Factor
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The CARDIoGRAMplusC4D Consortium,
Panos Deloukas,
Stavroula Kanoni,
Christina Willenborg,
Martin Farrall,
Themistocles L Assimes,
John R Thompson,
Erik Ingelsson,
Danish Saleheen,
Jeanette Erdmann, [......],
Anders Hamsten,
Jaspal S Kooner,
Unnur Thorsteinsdottir,
John Danesh,
Colin N A Palmer,
Robert Roberts,
Hugh Watkins,
Heribert Schunkert,
Nilesh J Samani,
Klaus Stark
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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 (r2 < 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.
Nature Genetics 12/2012; 45(1):25. · 35.53 Impact Factor
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The CARDIoGRAMplusC4D Consortium,
Panos Deloukas,
Stavroula Kanoni,
Christina Willenborg,
Martin Farrall,
Themistocles L Assimes,
John R Thompson,
Erik Ingelsson,
Danish Saleheen,
Jeanette Erdmann, [......],
Sekar Kathiresan,
Anders Hamsten,
Jaspal S Kooner,
Unnur Thorsteinsdottir,
John Danesh,
Colin N A Palmer,
Robert Roberts,
Hugh Watkins,
Heribert Schunkert,
Nilesh J Samani
[show abstract]
[hide abstract]
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.
Nature Genetics 12/2012; 45(1):25. · 35.53 Impact Factor
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The CARDIoGRAMplusC4D Consortium,
Panos Deloukas,
Stavroula Kanoni,
Christina Willenborg,
Martin Farrall,
Themistocles L Assimes,
John R Thompson,
Erik Ingelsson,
Danish Saleheen,
Jeanette Erdmann, [......],
Sekar Kathiresan,
Anders Hamsten,
Jaspal S Kooner,
Unnur Thorsteinsdottir,
John Danesh,
Colin N A Palmer,
Robert Roberts,
Hugh Watkins,
Heribert Schunkert,
Nilesh J Samani
[show abstract]
[hide abstract]
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 (r2 < 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.
Nature Genetics 12/2012; 45(1):25. · 35.53 Impact Factor
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[show abstract]
[hide abstract]
ABSTRACT: During the past ten years the field of human disease genetics has made major leaps, including the completion of the Human Genome Project, the HapMap Project, the development of the genome-wide association (GWA) studies to identify common disease-predisposing variants, and the introduction of large- scale whole-genome and whole-exome sequencing studies. The introduction of new technologies has enabled researchers to utilize novel study designs to tackle previously unexplored research questions in human genomics. These new types of studies typically need large sample sizes to overcome the multiple testing challenges caused by the huge number of interrogated genetic variants. As a consequence, large consortia-studies are at present the default in disease genetics research. The systematic planning of the GWA-studies was a key element in the success of the approach. Similar planning and rigor in statistical inferences will likely be beneficial also to future sequencing studies. Already today, the next-generation exome sequencing has lead to the identification of a number of genes underlying Mendelian diseases. In spite of the clear benefits, the method has proven more challenging than anticipated. In the case of complex diseases, next-generation sequencing aims to identify disease-associated low-frequency alleles. However, their robust detection will require very large study samples, even larger than in the case of the GWA-studies. This has stimulated study designs that capitalize on enriching sets of low-frequency alleles, e.g studies focusing on population isolates such as Finland or Iceland. One example is the collaborative SISu Project (Sequencing Initiative Suomi) that aims to provide near complete genome variation information from Finnish study samples and pave the way for large, nationwide genome health initiative studies.
New Biotechnology 11/2012; · 2.76 Impact Factor
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Ida Surakka,
John B Whitfield,
Markus Perola,
Peter M Visscher,
Grant W Montgomery,
Mario Falchi,
Gonneke Willemsen,
Eco J C de Geus,
Patrik K E Magnusson,
Kaare Christensen, [......],
Ann-Christine Syvänen,
Aarno Palotie,
Jaakko Kaprio,
Kirsten O Kyvik,
Nancy L Pedersen,
Dorret I Boomsma,
Tim Spector,
Nicholas G Martin, Samuli Ripatti,
Leena Peltonen
[show abstract]
[hide abstract]
ABSTRACT: Genome-wide association analysis on monozygotic twin-pairs offers a route to discovery of gene-environment interactions through testing for variability loci associated with sensitivity to individual environment/lifestyle. We present a genome-wide scan of loci associated with intra-pair differences in serum lipid and apolipoprotein levels. We report data for 1,720 monozygotic female twin-pairs from GenomEUtwin project with 2.5 million SNPs, imputed or genotyped, and measured serum lipid fractions for both twins. We found one locus associated with intra-pair differences in high-density lipoprotein cholesterol, rs2483058 in an intron of SRGAP2, where twins carrying the C allele are more sensitive to environmental factors (P = 3.98 × 10-8). We followed up the association in further genotyped monozygotic twins (N = 1,261), which showed a moderate association for the variant (P = 0.200, same direction of an effect). In addition, we report a new association on the level of apolipoprotein A-II (P = 4.03 × 10-8).
Twin Research and Human Genetics 10/2012; · 1.70 Impact Factor
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Jian Yang,
Ruth J F Loos,
Joseph E Powell,
Sarah E Medland,
Elizabeth K Speliotes,
Daniel I Chasman,
Lynda M Rose,
Gudmar Thorleifsson,
Valgerdur Steinthorsdottir,
Reedik Mägi, [......],
David P Strachan,
William G Hill,
Harold Snieder,
Paul M Ridker,
Unnur Thorsteinsdottir,
Kari Stefansson,
Timothy M Frayling,
Joel N Hirschhorn,
Michael E Goddard,
Peter M Visscher
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ABSTRACT: There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
Nature 09/2012; 490(7419):267-72. · 36.28 Impact Factor
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Andrew P Morris,
Benjamin F Voight,
Tanya M Teslovich,
Teresa Ferreira,
Ayellet V Segrè,
Valgerdur Steinthorsdottir,
Rona J Strawbridge,
Hassan Khan,
Harald Grallert,
Anubha Mahajan, [......],
Unnur Thorsteinsdottir,
Leif C Groop,
Kari Stefansson,
Frank Hu,
James S Pankow,
Josée Dupuis,
James B Meigs,
David Altshuler,
Michael Boehnke,
Mark I McCarthy
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Tanya M Teslovich,
Kiran Musunuru,
Albert V Smith,
Andrew C Edmondson,
Ioannis M Stylianou,
Masahiro Koseki,
James P Pirruccello, Samuli Ripatti,
Daniel I Chasman,
Cristen J Willer, [......],
Heribert Schunkert,
L Adrienne Cupples,
Manjinder S Sandhu,
Paul M Ridker,
Daniel J Rader,
Cornelia M van Duijn,
Leena Peltonen,
Gonçalo R Abecasis,
Michael Boehnke,
Sekar Kathiresan
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Tanya M Teslovich,
Kiran Musunuru,
Albert V Smith,
Andrew C Edmondson,
Ioannis M Stylianou,
Masahiro Koseki,
James P Pirruccello, Samuli Ripatti,
Daniel I Chasman,
Cristen J Willer, [......],
Heribert Schunkert,
L Adrienne Cupples,
Manjinder S Sandhu,
Paul M Ridker,
Daniel J Rader,
Cornelia M van Duijn,
Leena Peltonen,
Gonçalo R Abecasis,
Michael Boehnke,
Sekar Kathiresan
