Showing papers by "Terho Lehtimäki published in 2012"
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Karol Estrada1, Unnur Styrkarsdottir, Evangelos Evangelou2, Yi-Hsiang Hsu3 +187 more•Institutions (69)
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
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National Institutes of Health1, University of Helsinki2, University of Tampere3, University of Oulu4, University of Eastern Finland5, Imperial College London6, Virginia Commonwealth University7, Indiana University8, Turku University Hospital9, Helsinki University Central Hospital10, Walter and Eliza Hall Institute of Medical Research11, University of Melbourne12, Churchill Hospital13, Wellcome Trust Centre for Human Genetics14, University of Turku15, University of Tartu16, Semel Institute for Neuroscience and Human Behavior17, Wellcome Trust Sanger Institute18
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
01 Jan 2012
459 citations
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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
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University of Pennsylvania1, Erasmus University Rotterdam2, University of Bristol3, University of Duisburg-Essen4, Pasteur Institute5, University of Western Australia6, University College London7, University of Copenhagen8, Imperial College London9, University of Southern California10, University of Helsinki11, University of Marburg12, VU University Amsterdam13, University of Oxford14, University of Tartu15, University College Dublin16, Queen's University Belfast17, University of Zaragoza18, University of Oulu19, University of Turku20, University of Tampere21, Wellcome Trust Sanger Institute22, Pompeu Fabra University23, Harvard University24, University of Cambridge25, McMaster University26
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
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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
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Ludwig Maximilian University of Munich1, Wellcome Trust Sanger Institute2, University of Helsinki3, Leiden University4, Helsinki University Central Hospital5, Autonomous University of Barcelona6, Oslo University Hospital7, QIMR Berghofer Medical Research Institute8, University of Ulm9, University of Turku10, University of Tampere11, University of Barcelona12, Erasmus University Rotterdam13, Erasmus University Medical Center14, Norwegian University of Science and Technology15, National Institutes of Health16, Technische Universität München17, Max Planck Society18
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
01 Jan 2012
293 citations
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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
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McGill University1, University of Bristol2, University of Queensland3, Royal Brisbane and Women's Hospital4, University of Gothenburg5, University of Maryland, Baltimore6, University of Tampere7, Umeå University8, Turku University Hospital9, University of Helsinki10, Montreal Heart Institute11, Erasmus University Medical Center12, University of Western Australia13, Sir Charles Gairdner Hospital14, University of Manitoba15, Garvan Institute of Medical Research16, University of Calgary17, Menzies Research Institute18, University of Auckland19, Royal North Shore Hospital20, Lund University21, University of Southampton22, King's College London23, University of Sheffield24, Lexicon Pharmaceuticals25, United States Department of Veterans Affairs26, Jewish General Hospital27
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.
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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.
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Boston University1, University of Greifswald2, University of Alabama at Birmingham3, Johns Hopkins University4, University of Oxford5, Indiana University6, University of Texas Health Science Center at Houston7, King's College London8, Utrecht University9, University of California, Los Angeles10, University of Gothenburg11, National Institutes of Health12, Wake Forest University13, Harvard University14, University of Exeter15, University of Oulu16, Imperial College London17, University of Lübeck18, California Pacific Medical Center19, French Institute of Health and Medical Research20, University of Massachusetts Amherst21, Erasmus University Rotterdam22, Hannover Medical School23, Lund University24, National Institute for Health and Welfare25, University of Helsinki26, Fred Hutchinson Cancer Research Center27, Uppsala University28, University of Parma29, University of Pittsburgh30, Broad Institute31, Ludwig Maximilian University of Munich32, Cedars-Sinai Medical Center33, University of Washington34, Wellcome Trust Sanger Institute35, Memorial University of Newfoundland36, University of Turku37
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.
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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...
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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...
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Imperial College London1, National Institutes of Health2, Broad Institute3, Boston Children's Hospital4, QIMR Berghofer Medical Research Institute5, St George's, University of London6, Monash University7, Princess Alexandra Hospital8, University of Melbourne9, University of Helsinki10, Washington University in St. Louis11, Uppsala University12, University of Tampere13, Finnish Institute of Occupational Health14, Princess Margaret Hospital for Children15, University of Sydney16, University of Oulu17, University of Turku18, University of Western Australia19, Turku University Hospital20, University of Eastern Finland21, Boston University22, Harvard University23
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.
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Walter and Eliza Hall Institute of Medical Research1, University of Melbourne2, Wellcome Trust Sanger Institute3, National Institutes of Health4, University of Helsinki5, University of Tampere6, University of Oulu7, University of Eastern Finland8, Turku University Hospital9, Imperial College London10
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.
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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.
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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.
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QIMR Berghofer Medical Research Institute1, University of Helsinki2, University of Oulu3, National Institutes of Health4, Wellcome Trust Sanger Institute5, University of Edinburgh6, Washington University in St. Louis7, Turku University Hospital8, University of Tampere9, University of Colorado Boulder10
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.
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TL;DR: Elevated adolescence LDL-C and systolic BP levels are independent predictors of adulthood CAC, indicating that adolescence risk factor levels play an important role in the pathogenesis of coronary heart disease.
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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.
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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.
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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: Although youth with MetS are at increased risk of adult high IMT and T2DM, these data indicate that the resolution of youth MetS by adulthood can go some way to normalize this risk to levels seen in those who have never had MetS.
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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.