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Showing papers by "Terho Lehtimäki published in 2012"


Journal ArticleDOI
TL;DR: Light is shed on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility and within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways.
Abstract: Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10(-8)). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10(-4), Bonferroni corrected), of which six reached P < 5 × 10(-8), including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.

1,076 citations


Journal ArticleDOI
TL;DR: A GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples identified significant associations at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder.
Abstract: Samuli Ripatti and colleagues report a genome-wide association study for human serum metabolites using NMR of serum samples from over 8,000 Finnish individuals. They identify 31 loci associated with at least one of 216 serum metabolic measures.

497 citations



Journal ArticleDOI
Zari Dastani1, Hivert M-F.2, Hivert M-F.3, N J Timpson4  +615 moreInstitutions (128)
TL;DR: A meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease identifies novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.
Abstract: Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

456 citations


Journal ArticleDOI
Jonathan P. Bradfield1, H R Taal2, Nicholas J. Timpson3, André Scherag4, C. Lecoeur5, Nicole M. Warrington6, Elina Hyppönen7, Claus Holst8, Beatriz Valcarcel9, Elisabeth Thiering, Rany M. Salem, Fredrick R. Schumacher10, Diana L. Cousminer11, Pma Sleiman1, Jianhua Zhao1, Robert I. Berkowitz1, Karani Santhanakrishnan Vimaleswaran7, Ivonne Jarick12, Craig E. Pennell6, David M. Evans3, B. St Pourcain, Diane J. Berry7, Dennis O. Mook-Kanamori, Albert Hofman2, Fernando Rivadeneira2, André G. Uitterlinden2, C M van Duijn2, Rjp van der Valk2, J. C. de Jongste2, D. S. Postma, Dorret I. Boomsma13, W. J. Gauderman10, Mohamed T. Hassanein10, Cecilia M. Lindgren14, Reedik Mägi15, Reedik Mägi14, Cag Boreham16, Charlotte E. Neville17, Luis A. Moreno18, Paul Elliott9, A Pouta, A.-L. Hartikainen19, Mingyao Li1, Olli T. Raitakari20, Terho Lehtimäki21, Johan G. Eriksson, Aarno Palotie, Jean Dallongeville5, Shikta Das9, Panagiotis Deloukas22, George McMahon3, Susan M. Ring3, John P. Kemp3, Jessica L. Buxton9, Aif Blakemore9, Mariona Bustamante, Mònica Guxens23, Joel N. Hirschhorn, Matthew W. Gillman24, Eskil Kreiner-Møller8, Hans Bisgaard8, Frank D. Gilliland10, Joachim Heinrich, Eleanor Wheeler22, Inês Barroso22, Inês Barroso25, Stephen O'Rahilly25, Aline Meirhaeghe5, Tia Sorensen3, Chris Power7, Lyle J. Palmer3, Anke Hinney4, E. Widen11, I. S. Farooqi25, Mark I. McCarthy14, Philippe Froguel5, Philippe Froguel9, David Meyre5, David Meyre26, Johannes Hebebrand4, M-R Jarvelin, Vwv Jaddoe2, George Davey Smith3, Hakon Hakonarson, Sfa Grant 
TL;DR: A North American, Australian and European collaborative meta-analysis of 14 studies consisting of 5,530 cases and 8,318 controls of European ancestry observed two loci that yielded genome-wide significant combined P values near OLFM4 at 13q14 and within HOXB5 at 17q21, which yielded directionally consistent associations.
Abstract: Multiple genetic variants have been associated with adult obesity and a few with severe obesity in childhood; however, less progress has been made in establishing genetic influences on common early-onset obesity. We performed a North American, Australian and European collaborative meta-analysis of 14 studies consisting of 5,530 cases (≥95th percentile of body mass index (BMI)) and 8,318 controls (<50th percentile of BMI) of European ancestry. Taking forward the eight newly discovered signals yielding association with P < 5 × 10(-6) in nine independent data sets (2,818 cases and 4,083 controls), we observed two loci that yielded genome-wide significant combined P values near OLFM4 at 13q14 (rs9568856; P = 1.82 × 10(-9); odds ratio (OR) = 1.22) and within HOXB5 at 17q21 (rs9299; P = 3.54 × 10(-9); OR = 1.14). Both loci continued to show association when two extreme childhood obesity cohorts were included (2,214 cases and 2,674 controls). These two loci also yielded directionally consistent associations in a previous meta-analysis of adult BMI(1).

347 citations


Journal ArticleDOI
Pim van der Harst1, Weihua Zhang2, Irene Mateo Leach1, Augusto Rendon  +191 moreInstitutions (54)
20 Dec 2012-Nature
TL;DR: A genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals identifies 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10−8, which together explain 4–9% of the phenotypic variance per trait.
Abstract: Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

306 citations


01 Jan 2012
TL;DR: In this article, the authors carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals and identified 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10−8, which together explain 4-9% of the phenotypic variance per trait.
Abstract: Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10−8, which together explain 4–9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

296 citations


Journal ArticleDOI
TL;DR: This study identifies the first susceptibility loci for migraine without aura, thereby expanding the knowledge of this debilitating neurological disorder.
Abstract: Migraine without aura is the most common form of migraine, characterized by recurrent disabling headache and associated autonomic symptoms. To identify common genetic variants associated with this migraine type, we analyzed genome-wide association data of 2,326 clinic-based German and Dutch individuals with migraine without aura and 4,580 population-matched controls. We selected SNPs from 12 loci with 2 or more SNPs associated with P values of <1 × 10(-5) for replication testing in 2,508 individuals with migraine without aura and 2,652 controls. SNPs at two of these loci showed convincing replication: at 1q22 (in MEF2D; replication P = 4.9 × 10(-4); combined P = 7.06 × 10(-11)) and at 3p24 (near TGFBR2; replication P = 1.0 × 10(-4); combined P = 1.17 × 10(-9)). In addition, SNPs at the PHACTR1 and ASTN2 loci showed suggestive evidence of replication (P = 0.01; combined P = 3.20 × 10(-8) and P = 0.02; combined P = 3.86 × 10(-8), respectively). We also replicated associations at two previously reported migraine loci in or near TRPM8 and LRP1. This study identifies the first susceptibility loci for migraine without aura, thereby expanding our knowledge of this debilitating neurological disorder.

295 citations


Jonathan P. Bradfield, H. Rob Taal, Nicholas J. Timpson, André Scherag, Cécile Lecoeur, Nicole M. Warrington, Elina Hyppönen, Claus Holst, Beatriz Valcarcel, Elisabeth Thiering, Rany M. Salem, Fredrick R. Schumacher, Diana L. Cousminer, Patrick M. A. Sleiman, Jianhua Zhao, Robert I. Berkowitz, Karani Santhanakrishnan Vimaleswaran, Ivonne Jarick, Craig E. Pennell, David M. Evans, Beate St Pourcain, Diane J. Berry, Dennis O. Mook-Kanamori, Albert Hofman, Fernando Rivadeneira, André G. Uitterlinden, Cornelia M. van Duijn, Ralf J. P. van der Valk, Johan C. de Jongste, Dirkje S. Postma, Dorret I. Boomsma, W. James Gauderman, Mohamed T. Hassanein, Cecilia M. Lindgren, Reedik Mägi, Colin Boreham, Charlotte E. Neville, Luis A. Moreno, Paul Elliott, Anneli Pouta, Anna-Liisa Hartikainen, Mingyao Li, Olli T. Raitakari, Terho Lehtimäki, Johan G. Eriksson, Aarno Palotie, Jean Dallongeville, Shikta Das, Panos Deloukas, George McMahon, Susan M. Ring, John P. Kemp, Jessica L. Buxton, Alexandra I. F. Blakemore, Mariona Bustamante, Mònica Guxens, Joel N. Hirschhorn, Matthew W. Gillman, Eskil Kreiner-Møller, Hans Bisgaard, Frank D. Gilliland, Joachim Heinrich, Eleanor Wheeler, Inês Barroso, Stephen O'Rahilly, Aline Meirhaeghe, Thorkild I. A. Sørensen, Chris Power, Lyle J. Palmer, Anke Hinney, Elisabeth Widen, I. Sadaf Farooqi, Mark I. McCarthy, Philippe Froguel, David Meyre, Johannes Hebebrand, Marjo-Riitta Järvelin, Vincent W. V. Jaddoe, George Davey Smith, Hakon Hakonarson, Struan F.A. Grant 
01 Jan 2012

293 citations


Journal ArticleDOI
Yukinori Okada, Xueling Sim1, Xueling Sim2, Min Jin Go  +411 moreInstitutions (19)
TL;DR: A meta-analysis of genome-wide association studies for kidney function–related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN), identified 17 loci newly associated with kidney function-related traits.
Abstract: Chronic kidney disease (CKD), impairment of kidney function, is a serious public health problem, and the assessment of genetic factors influencing kidney function has substantial clinical relevance. Here, we report a meta-analysis of genome-wide association studies for kidney function-related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN). Our meta-analysis identified 17 loci newly associated with kidney function-related traits, including the concentrations of blood urea nitrogen, uric acid and serum creatinine and estimated glomerular filtration rate based on serum creatinine levels (eGFRcrea) (P < 5.0 × 10(-8)). We further examined these loci with in silico replication in individuals of European ancestry from the KidneyGen, CKDGen and GUGC consortia, including a combined total of ∼110,347 individuals. We identify pleiotropic associations among these loci with kidney function-related traits and risk of CKD. These findings provide new insights into the genetics of kidney function.

271 citations


Journal ArticleDOI
TL;DR: In this article, the authors identify genetic variants associated with cortical bone thickness (CBT) and bone mineral density (BMD) by performing two separate genome-wide association study (GWAS) meta-analyses for CBT in 3 cohorts comprising 5,878 European subjects and for BMD in 5 cohorts consisting 5,672 individuals.
Abstract: We aimed to identify genetic variants associated with cortical bone thickness (CBT) and bone mineral density (BMD) by performing two separate genome-wide association study (GWAS) meta-analyses for CBT in 3 cohorts comprising 5,878 European subjects and for BMD in 5 cohorts comprising 5,672 individuals. We then assessed selected single-nucleotide polymorphisms (SNPs) for osteoporotic fracture in 2,023 cases and 3,740 controls. Association with CBT and forearm BMD was tested for ,2.5 million SNPs in each cohort separately, and results were meta-analyzed using fixed effect meta-analysis. We identified a missense SNP (Thr.Ile; rs2707466) located in the WNT16 gene (7q31), associated with CBT (effect size of 20.11 standard deviations [SD] per C allele, P = 6.2610 29 ). This SNP, as well as another nonsynonymous SNP rs2908004 (Gly.Arg), also had genome-wide significant association with forearm BMD (20.14 SD per C allele, P = 2.3610 212 , and 20.16 SD per G allele, P = 1.2610 215 , respectively). Four genome-wide significant SNPs arising from BMD meta-analysis were tested for association with forearm fracture. SNP rs7776725 in FAM3C, a gene adjacent to WNT16, was associated with a genome-wide significant increased risk of forearm fracture (OR = 1.33, P = 7.3610 29 ), with genome-wide suggestive signals from the two missense variants in WNT16 (rs2908004: OR = 1.22, P = 4.9610 26 and rs2707466: OR = 1.22, P = 7.2610 26 ). We next generated a homozygous mouse with targeted disruption of Wnt16. Female Wnt16 2/2 mice had 27% (P,0.001) thinner cortical bones at the femur midshaft, and bone strength measures were reduced between 43%–61% (6.5610 213 ,P,5.9610 24 ) at both femur and tibia, compared with their wild-type littermates. Natural variation in humans and targeted disruption in mice demonstrate that WNT16 is an important determinant of CBT, BMD, bone strength, and risk of fracture.

Journal ArticleDOI
01 Jun 2012-Diabetes
TL;DR: Metabolite associations with insulin resistance were studied in young Finns to elucidate underlying metabolic pathways and reflect the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints.
Abstract: Metabolite associations with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways. Insulin resistance was assessed by the homeostasis model (HOMA-IR) and circulating metabolites quantified by high-throughput nuclear magnetic resonance spectroscopy in two population-based cohorts. Associations were analyzed using regression models adjusted for age, waist, and standard lipids. Branched-chain and aromatic amino acids, gluconeogenesis intermediates, ketone bodies, and fatty acid composition and saturation were associated with HOMA-IR (P < 0.0005 for 20 metabolite measures). Leu, Ile, Val, and Tyr displayed sex- and obesity-dependent interactions, with associations being significant for women only if they were abdominally obese. Origins of fasting metabolite levels were studied with dietary and physical activity data. Here, protein energy intake was associated with Val, Phe, Tyr, and Gln but not insulin resistance index. We further tested if 12 genetic variants regulating the metabolites also contributed to insulin resistance. The genetic determinants of metabolite levels were not associated with HOMA-IR, with the exception of a variant in GCKR associated with 12 metabolites, including amino acids (P < 0.0005). Nonetheless, metabolic signatures extending beyond obesity and lipid abnormalities reflected the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints.

Journal ArticleDOI
Andrea D. Coviello1, Robin Haring2, Melissa Wellons3, Dhananjay Vaidya4, Terho Lehtimäki, Sarah Keildson5, Kathryn L. Lunetta1, Chunyan He6, Myriam Fornage7, Vasiliki Lagou5, Massimo Mangino8, N. Charlotte Onland-Moret9, Brian H. Chen10, Joel Eriksson11, Melissa Garcia12, Yongmei Liu13, Annemarie Koster12, Kurt Lohman13, Leo-Pekka Lyytikäinen, Ann-Kristin Petersen12, Jennifer Prescott14, Lisette Stolk14, Liesbeth Vandenput11, Andrew R. Wood, Wei Vivian Zhuang1, Aimo Ruokonen15, Anna-Liisa Hartikainen16, Anneli Pouta16, Stefania Bandinelli16, Reiner Biffar, Georg Brabant2, David G. Cox17, David G. Cox18, Yuhui Chen5, Steven R. Cummings19, Luigi Ferrucci12, Marc J. Gunter20, Susan E. Hankinson14, Susan E. Hankinson21, Hannu Martikainen16, Albert Hofman22, Georg Homuth2, Thomas Illig23, John-Olov Jansson11, Andrew D. Johnson1, David Karasik14, Magnus Karlsson24, Johannes Kettunen25, Johannes Kettunen26, Douglas P. Kiel23, Peter Kraft, Jingmin Liu25, Östen Ljunggren14, Mattias Lorentzon11, M. Maggio27, Marcello Ricardo Paulista Markus28, Dan Mellström11, Iva Miljkovic29, Daniel B. Mirel2, Sarah C. Nelson30, Laure Morin Papunen16, Petra H.M. Peeters9, Inga Prokopenko5, Leslie J. Raffel31, Martin Reincke32, Alexander P. Reiner33, Kathryn M. Rexrode14, Fernando Rivadeneira14, Stephen M. Schwartz34, David S. Siscovick27, Nicole Soranzo35, Nicole Soranzo8, Doris Stöckl32, Shelley S. Tworoger14, André G. Uitterlinden22, André G. Uitterlinden14, Carla H. van Gils9, Ramachandran S. Vasan1, H.-Erich Wichmann32, Guangju Zhai36, Guangju Zhai8, Shalender Bhasin1, Martin Bidlingmaier34, Stephen J. Chanock12, Immaculata De Vivo14, Tamara B. Harris12, David J. Hunter14, Mika Kähönen, Simin Liu10, Pamela Ouyang4, Tim D. Spector8, Yvonne T. van der Schouw9, Jorma Viikari37, Henri Wallaschofski2, Mark I. McCarthy5, Timothy M. Frayling, Anna Murray, Steve Franks17, Marjo-Riitta Järvelin17, Marjo-Riitta Järvelin16, Frank De Jong14, Olli T. Raitakari37, Alexander Teumer22, Claes Ohlsson11, Joanne M. Murabito1, John R. B. Perry8, John R. B. Perry5, John R. B. Perry15 
TL;DR: Evidence of sex-differentiated genetic influences on sex steroid hormone-binding globulin is found and the importance of considering these features when estimating complex trait variance is highlighted.
Abstract: Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8x10(-106)), PRMT6 (rs17496332, 1p13.3, p=1.4x10(-11)), GCKR (rs780093, 2p23.3, p=2.2x10(-16)), ZBTB10 (rs440837, 8q21.13, p=3.4x10(-09)), JMJD1C (rs7910927, 10q21.3, p=6.1x10(-35)), SLCO1B1 (rs4149056, 12p12.1, p=1.9x10(-08)), NR2F2 (rs8023580, 15q26.2, p=8.3x10(-12)), ZNF652 (rs2411984, 17q21.32, p=3.5x10(-14)), TDGF3 (rs1573036, Xq22.3, p=4.1x10(-14)), LHCGR (rs10454142, 2p16.3, p=1.3x10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p=2.7x10(-08)), and UGT2B15 (rs293428, 4q13.2, p=5.5x10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5x10(-08), women p=0.66, heterogeneity p=0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained similar to 15.6% and similar to 8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.

01 Jan 2012
TL;DR: In this article, the associations of metabolites with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways, using regression models adjusted for age, waist, and standard lipids.
Abstract: Metabolite associations with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways. Insulin resistance was assessed by the homeostasis model (HOMA-IR) and circulating metabolites quantified by high-throughput nuclear magnetic resonance spectroscopy in two population-based cohorts. Associations were analyzed using regression models adjusted for age, waist, and standard lipids. Branched-chain and aromatic amino acids, gluconeogenesis intermediates, ketone bodies, and fatty acid composition and saturation were associated with HOMA-IR (P < 0.0005 for 20 metabolite measures). Leu, Ile, Val, and Tyr displayed sex- and obesity-dependent interactions, with associations being significant for women only if they were abdominally obese. Origins of fasting metabolite levels were studied with dietary and physical activity data. Here, protein energy intake was associated with Val, Phe, Tyr, and Gln but not insulin resistance index. We further tested if 12 genetic variants regulating the metabolites also contributed to insulin resistance. The genetic determinants of metabolite levels were not associated with HOMA-IR, with the exception of a variant in GCKR associated with 12 metabolites, including amino acids (P < 0.0005). Nonetheless, metabolic signatures extending beyond obesity and lipid abnormalities reflected the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints.

Journal ArticleDOI
TL;DR: The American Heart Association defined a new concept, cardiovascular health, and determined metrics needed to monitor it over time as part of its 2020 Impact Goal definition as discussed by the authors, which was defined by the AHA.
Abstract: Background—The American Heart Association (AHA) defined a new concept, cardiovascular health, and determined metrics needed to monitor it over time as part of its 2020 Impact Goal definition. Ideal...

Journal ArticleDOI
TL;DR: Genes from lipid metabolism pathways have the key role in the genetic background of MetS, and a genetic risk score, calculated as the number of risk alleles in loci associated with individual MetS traits, was strongly associated with MetS status.
Abstract: Background—Genome-wide association (GWA) studies have identified several susceptibility loci for metabolic syndrome (MetS) component traits, but have had variable success in identifying susceptibil...

Journal ArticleDOI
28 Sep 2012-PLOS ONE
TL;DR: In this paper, the identification of genetic risk factors is limited by availability of suitable studies, and the authors propose a method to identify the genetic component of Asthma with a strong genetic component.
Abstract: Rationale: Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives: To t ...

01 Jan 2012
TL;DR: The analysis in population-based cohorts of Asthma Traits (APCAT) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population based cohorts.
Abstract: Rationale Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. Methods The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant ( P −8 ) and three variants reported as suggestive ( P −7 ). We also searched for novel associations in APCAT ( Stage 1 ) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls ( Stage 2 ). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. Main Results We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA , now reaches genome-wide significance when combined with our data ( P = 2.4×10 −9 ). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 ( P Stage1+Stage2 = 1.1x10 −9 ), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region ( P Stage1+Stage2 = 1.1x10 −8 ), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. Conclusions Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma.

Journal ArticleDOI
TL;DR: In this paper, the authors performed a multivariate genome-wide association analysis and identified 34 genomic loci at genomewide significance, of which 7 are novel. But the results of the analysis were limited to two population-based cohorts with both genomewide SNP data and serum metabolomic profiles.
Abstract: Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.

Journal ArticleDOI
Cristian Pattaro, Anna Köttgen1, Anna Köttgen2, Alexander Teumer3  +171 moreInstitutions (50)
TL;DR: In this article, the authors performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors, uncovering 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80.
Abstract: Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD.

Journal ArticleDOI
TL;DR: Alanine, lactate, and pyruvate were predictive of postchallenge glucose exclusively and gluconeogenic precursors are potential markers of long-term impaired insulin sensitivity that may relate to attenuated glucose tolerance later in life.
Abstract: OBJECTIVE Metabolite predictors of deteriorating glucose tolerance may elucidate the pathogenesis of type 2 diabetes. We investigated associations of circulating metabolites from high-throughput profiling with fasting and postload glycemia cross-sectionally and prospectively on the population level. RESEARCH DESIGN AND METHODS Oral glucose tolerance was assessed in two Finnish, population-based studies consisting of 1,873 individuals (mean age 52 years, 58% women) and reexamined after 6.5 years for 618 individuals in one of the cohorts. Metabolites were quantified by nuclear magnetic resonance spectroscopy from fasting serum samples. Associations were studied by linear regression models adjusted for established risk factors. RESULTS Nineteen circulating metabolites, including amino acids, gluconeogenic substrates, and fatty acid measures, were cross-sectionally associated with fasting and/or postload glucose ( P P P = 0.003–0.04). None of the fatty acid measures were prospectively associated with glycemia. Changes in fatty acid concentrations were associated with changes in fasting and postload glycemia during follow-up; however, changes in branched-chain amino acids did not follow glucose dynamics, and gluconeogenic substrates only paralleled changes in fasting glucose. CONCLUSIONS Alterations in branched-chain and aromatic amino acid metabolism precede hyperglycemia in the general population. Further, alanine, lactate, and pyruvate were predictive of postchallenge glucose exclusively. These gluconeogenic precursors are potential markers of long-term impaired insulin sensitivity that may relate to attenuated glucose tolerance later in life.

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TL;DR: High-throughput metabolite quantification, with new systemic biomarkers, improved risk stratification for subclinical atherosclerosis in comparison to conventional lipids and could potentially be useful for early cardiovascular risk assessment.
Abstract: Aims High-throughput metabolite quantification holds promise for cardiovascular risk assessment. Here, we evaluated whether metabolite quantification by nuclear magnetic resonance (NMR) improves prediction of subclinical atherosclerosis in comparison to conventional lipid testing. Methods and results Circulating lipids, lipoprotein subclasses, and small molecules were assayed by NMR for 1595 individuals aged 24–39 years from the population-based Cardiovascular Risk in Young Finns Study. Carotid intima–media thickness (IMT), a marker of subclinical atherosclerosis, was measured in 2001 and 2007. Baseline conventional risk factors and systemic metabolites were used to predict 6-year incidence of high IMT (≥90th percentile) or plaque. The best prediction of high intima–media thickness was achieved when total and HDL cholesterol were replaced by NMR-determined LDL cholesterol and medium HDL, docosahexaenoic acid, and tyrosine in prediction models with risk factors from the Framingham risk score. The extended prediction model improved risk stratification beyond established risk factors alone; area under the receiver operating characteristic curve 0.764 vs. 0.737, P = 0.02, and net reclassification index 17.6%, P = 0.0008. Higher docosahexaenoic acid levels were associated with decreased risk for incident high IMT (odds ratio: 0.74; 95% confidence interval: 0.67–0.98; P = 0.007). Tyrosine (1.33; 1.10–1.60; P = 0.003) and glutamine (1.38; 1.13–1.68; P = 0.001) levels were associated with 6-year incident high IMT independent of lipid measures. Furthermore, these amino acids were cross-sectionally associated with carotid IMT and the presence of angiographically ascertained coronary artery disease in independent populations. Conclusion High-throughput metabolite quantification, with new systemic biomarkers, improved risk stratification for subclinical atherosclerosis in comparison to conventional lipids and could potentially be useful for early cardiovascular risk assessment.

Journal ArticleDOI
TL;DR: Using genome‐wide single nucleotide polymorphism (SNP) data from > 8000 individuals, it is estimated that little variation in the Cloninger personality dimensions (7.2% on average) is due to the combined effect of common, additive genetic variants across the genome, suggesting that most heritable variation in personality isDue to rare variant effects and/or a combination of dominance and epistasis.
Abstract: Personality traits are basic dimensions of behavioral variation, and twin, family, and adoption studies show that around 30% of the between-individual variation is due to genetic variation. There is rapidly growing interest in understanding the evolutionary basis of this genetic variation. Several evolutionary mechanisms could explain how genetic variation is maintained in traits, and each of these makes predictions in terms of the relative contribution of rare and common genetic variants to personality variation, the magnitude of nonadditive genetic influences, and whether personality is affected by inbreeding. Using genome-wide single nucleotide polymorphism (SNP) data from > 8000 individuals, we estimated that little variation in the Cloninger personality dimensions (7.2% on average) is due to the combined effect of common, additive genetic variants across the genome, suggesting that most heritable variation in personality is due to rare variant effects and/or a combination of dominance and epistasis. Furthermore, higher levels of inbreeding were associated with less socially desirable personality trait levels in three of the four personality dimensions. These findings are consistent with genetic variation in personality traits having been maintained by mutation–selection balance.


Journal ArticleDOI
M. Arfan Ikram1, M. Arfan Ikram2, Myriam Fornage2, Myriam Fornage3  +165 moreInstitutions (48)
TL;DR: The data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size.
Abstract: During aging, intracranial volume remains unchanged and represents maximally attained brain size, while various interacting biological phenomena lead to brain volume loss. Consequently, intracranial volume and brain volume in late life reflect different genetic influences. Our genome-wide association study (GWAS) in 8,175 community-dwelling elderly persons did not reveal any associations at genome-wide significance (P < 5 × 10(-8)) for brain volume. In contrast, intracranial volume was significantly associated with two loci: rs4273712 (P = 3.4 × 10(-11)), a known height-associated locus on chromosome 6q22, and rs9915547 (P = 1.5 × 10(-12)), localized to the inversion on chromosome 17q21. We replicated the associations of these loci with intracranial volume in a separate sample of 1,752 elderly persons (P = 1.1 × 10(-3) for 6q22 and 1.2 × 10(-3) for 17q21). Furthermore, we also found suggestive associations of the 17q21 locus with head circumference in 10,768 children (mean age of 14.5 months). Our data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size.

Journal ArticleDOI
H. Rob Taal1, Beate St Pourcain2, Elisabeth Thiering, Shikta Das3  +227 moreInstitutions (60)
TL;DR: This article performed a meta-analysis of seven genome-wide association studies (GWAS) (N = 10,768 individuals of European ancestry enrolled in pregnancy and/or birth cohorts) and followed up three lead signals in six replication studies (combined N = 19,089).
Abstract: To identify genetic variants associated with head circumference in infancy, we performed a meta-analysis of seven genome-wide association studies (GWAS) (N = 10,768 individuals of European ancestry enrolled in pregnancy and/or 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 height, their effects on infant head circumference were largely independent of height (P = 3.8 × 10(-7) for rs7980687 and 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 have shown genome-wide association with adult intracranial volume, Parkinson's disease and other neurodegenerative diseases, indicating that a common genetic variant in this region might link early brain growth with neurological disease in later life.

Journal ArticleDOI
TL;DR: In this article, a longitudinal study aimed to examine the best combination of childhood physical and environmental factors to predict adult hypertension and furthermore whether newly identified genetic variants for blood pressure increase the prediction of adult hypertension.
Abstract: Background—Hypertension is a major modifiable cardiovascular risk factor. The present longitudinal study aimed to examine the best combination of childhood physical and environmental factors to predict adult hypertension and furthermore whether newly identified genetic variants for blood pressure increase the prediction of adult hypertension. Methods and Results—The study cohort included 2625 individuals from the Cardiovascular Risk in Young Finns Study who were followed up for 21 to 27 years since baseline (1980; age, 3–18 years). In addition to dietary factors and biomarkers related to blood pressure, we examined whether a genetic risk score based on 29 newly identified single-nucleotide polymorphisms enhances the prediction of adult hypertension. Hypertension in adulthood was defined as systolic blood pressure ≥130 mm Hg and/or diastolic blood pressure ≥85 mm Hg or medication for the condition. Independent childhood risk factors for adult hypertension included the individual's own blood pressure (P<0.0...


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TL;DR: The current findings suggest that PWV reflects a different aspect of vascular damage than FMD or IMT in young adults, whereas in older adults the information provided by PWV and IMT may be, to some extent, similar as regards subclinical vascular damage.

01 Jan 2012
TL;DR: A meta-analysis of genome-wide association studies and lead signals showed suggestive evidence of association with head circumference in infancy, indicating that a common genetic variant in this region might link early brain growth with neurological disease in later life.