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Find video protocols related to scientific articles indexed in Pubmed.
Quantification of HDL Particle Concentration by Calibrated Ion Mobility Analysis.
Clin. Chem.
PUBLISHED: 09-15-2014
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It is critical to develop new metrics to determine whether HDL is cardioprotective in humans. One promising approach is HDL particle concentration (HDL-P), the size and concentration of HDL in plasma. However, the 2 methods currently used to determine HDL-P yield concentrations that differ >5-fold. We therefore developed and validated an improved approach to quantify HDL-P, termed calibrated ion mobility analysis (calibrated IMA).
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HDL-3 is a superior predictor of carotid artery disease in a case-control cohort of 1725 participants.
J Am Heart Assoc
PUBLISHED: 06-27-2014
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Recent data suggest that high-density lipoprotein cholesterol (HDL-C) levels are likely not in the causative pathway of atheroprotection, shifting focus from HDL-C to its subfractions and associated proteins. This study's goal was to determine which HDL phenotype was the better predictor of carotid artery disease (CAAD).
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Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci.
Vinicius Tragante, Michael R Barnes, Santhi K Ganesh, Matthew B Lanktree, Wei Guo, Nora Franceschini, Erin N Smith, Toby Johnson, Michael V Holmes, Sandosh Padmanabhan, Konrad J Karczewski, Berta Almoguera, John Barnard, Jens Baumert, Yen-Pei Christy Chang, Clara C Elbers, Martin Farrall, Mary E Fischer, Tom R Gaunt, Johannes M I H Gho, Christian Gieger, Anuj Goel, Yan Gong, Aaron Isaacs, Marcus E Kleber, Irene Mateo Leach, Caitrin W McDonough, Matthijs F L Meijs, Olle Melander, Christopher P Nelson, Ilja M Nolte, Nathan Pankratz, Tom S Price, Jonathan Shaffer, Sonia Shah, Maciej Tomaszewski, Peter J van der Most, Erik P A van Iperen, Judith M Vonk, Kate Witkowska, Caroline O L Wong, Li Zhang, Amber L Beitelshees, Gerald S Berenson, Deepak L Bhatt, Morris Brown, Amber Burt, Rhonda M Cooper-DeHoff, John M Connell, Karen J Cruickshanks, Sean P Curtis, George Davey-Smith, Christian Delles, Ron T Gansevoort, Xiuqing Guo, Shen Haiqing, Claire E Hastie, Marten H Hofker, G Kees Hovingh, Daniel S Kim, Susan A Kirkland, Barbara E Klein, Ronald Klein, Yun R Li, Steffi Maiwald, Christopher Newton-Cheh, Eoin T O'Brien, N Charlotte Onland-Moret, Walter Palmas, Afshin Parsa, Brenda W Penninx, Mary Pettinger, Ramachandran S Vasan, Jane E Ranchalis, Paul M Ridker, Lynda M Rose, Peter Sever, Daichi Shimbo, Laura Steele, Ronald P Stolk, Barbara Thorand, Mieke D Trip, Cornelia M van Duijn, W Monique Verschuren, Cisca Wijmenga, Sharon Wyatt, J Hunter Young, Aeilko H Zwinderman, Connie R Bezzina, Eric Boerwinkle, Juan P Casas, Mark J Caulfield, Aravinda Chakravarti, Daniel I Chasman, Karina W Davidson, Pieter A Doevendans, Anna F Dominiczak, Garret A FitzGerald, John G Gums, Myriam Fornage, Hakon Hakonarson, Indrani Halder, Hans L Hillege, Thomas Illig, Gail P Jarvik, Julie A Johnson, John J P Kastelein, Wolfgang Koenig, Meena Kumari, Winfried März, Sarah S Murray, Jeffery R O'Connell, Albertine J Oldehinkel, James S Pankow, Daniel J Rader, Susan Redline, Muredach P Reilly, Eric E Schadt, Kandice Kottke-Marchant, Harold Snieder, Michael Snyder, Alice V Stanton, Martin D Tobin, André G Uitterlinden, Pim van der Harst, Yvonne T van der Schouw, Nilesh J Samani, Hugh Watkins, Andrew D Johnson, Alex P Reiner, Xiaofeng Zhu, Paul I W de Bakker, Daniel Levy, Folkert W Asselbergs, Patricia B Munroe, Brendan J Keating.
Am. J. Hum. Genet.
PUBLISHED: 02-20-2014
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Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ~50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.
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Effects of dietary components on high-density lipoprotein measures in a cohort of 1,566 participants.
Nutr Metab (Lond)
PUBLISHED: 01-01-2014
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Recent data suggest that an increased level of high-density lipoprotein cholesterol (HDL-C) is not causally protective against heart disease, shifting focus to other sub-phenotypes of HDL. Prior work on the effects of dietary intakes has focused largely on HDL-C. The goal of this study was to identify the dietary intakes that affect HDL-related measures: HDL-C, HDL-2, HDL-3, and apoA1 using data from a carotid artery disease case-control cohort.
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Dietary fatty acid intake is associated with paraoxonase 1 activity in a cohort-based analysis of 1,548 subjects.
Lipids Health Dis
PUBLISHED: 09-23-2013
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Paraoxonase 1 (PON1) is a cardioprotective, HDL-associated glycoprotein enzyme with broad substrate specificity. Our previous work found associations between dietary cholesterol and vitamin C with PON1 activity. The goal of this study was to determine the effect of specific dietary fatty acid (DFA) intake on PON1 activity.
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Joint Linkage and Association Analysis with Exome Sequence Data Implicates SLC25A40 in Hypertriglyceridemia.
Am. J. Hum. Genet.
PUBLISHED: 07-25-2013
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Hypertriglyceridemia (HTG) is a heritable risk factor for cardiovascular disease. Investigating the genetics of HTG may identify new drug targets. There are ?35 known single-nucleotide variants (SNVs) that explain only ?10% of variation in triglyceride (TG) level. Because of the genetic heterogeneity of HTG, a family study design is optimal for identification of rare genetic variants with large effect size because the same mutation can be observed in many relatives and cosegregation with TG can be tested. We considered HTG in a five-generation family of European American descent (n = 121), ascertained for familial combined hyperlipidemia. By using Bayesian Markov chain Monte Carlo joint oligogenic linkage and association analysis, we detected linkage to chromosomes 7 and 17. Whole-exome sequence data revealed shared, highly conserved, private missense SNVs in both SLC25A40 on chr7 and PLD2 on chr17. Jointly, these SNVs explained 49% of the genetic variance in TG; however, only the SLC25A40 SNV was significantly associated with TG (p = 0.0001). This SNV, c.374A>G, causes a highly disruptive p.Tyr125Cys substitution just outside the second helical transmembrane region of the SLC25A40 inner mitochondrial membrane transport protein. Whole-gene testing in subjects from the Exome Sequencing Project confirmed the association between TG and SLC25A40 rare, highly conserved, coding variants (p = 0.03). These results suggest a previously undescribed pathway for HTG and illustrate the power of large pedigrees in the search for rare, causal variants.
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Novel gene-by-environment interactions: APOB and NPC1L1 variants affect the relationship between dietary and total plasma cholesterol.
J. Lipid Res.
PUBLISHED: 03-11-2013
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Cardiovascular disease (CVD) is the leading cause of death in developed countries. Plasma cholesterol level is a key risk factor in CVD pathogenesis. Genetic and dietary variation both influence plasma cholesterol; however, little is known about dietary interactions with genetic variants influencing the absorption and transport of dietary cholesterol. We sought to determine whether gut expressed variants predicting plasma cholesterol differentially affected the relationship between dietary and plasma cholesterol levels in 1,128 subjects (772/356 in the discovery/replication cohorts, respectively). Four single nucleotide polymorphisms (SNPs) within three genes (APOB, CETP, and NPC1L1) were significantly associated with plasma cholesterol in the discovery cohort. These were subsequently evaluated for gene-by-environment (GxE) interactions with dietary cholesterol for the prediction of plasma cholesterol, with significant findings tested for replication. Novel GxE interactions were identified and replicated for two variants: rs1042034, an APOB Ser4338Asn missense SNP and rs2072183 (in males only), a synonymous NPC1L1 SNP in linkage disequilibrium with SNPs 5 of NPC1L1. This study identifies the presence of novel GxE and gender interactions implying that differential gut absorption is the basis for the variant associations with plasma cholesterol. These GxE interactions may account for part of the "missing heritability" not accounted for by genetic associations.
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Loci influencing blood pressure identified using a cardiovascular gene-centric array.
Santhi K Ganesh, Vinicius Tragante, Wei Guo, Yiran Guo, Matthew B Lanktree, Erin N Smith, Toby Johnson, Berta Almoguera Castillo, John Barnard, Jens Baumert, Yen-Pei Christy Chang, Clara C Elbers, Martin Farrall, Mary E Fischer, Nora Franceschini, Tom R Gaunt, Johannes M I H Gho, Christian Gieger, Yan Gong, Aaron Isaacs, Marcus E Kleber, Irene Mateo Leach, Caitrin W McDonough, Matthijs F L Meijs, Olle Mellander, Cliona M Molony, Ilja M Nolte, Sandosh Padmanabhan, Tom S Price, Ramakrishnan Rajagopalan, Jonathan Shaffer, Sonia Shah, Haiqing Shen, Nicole Soranzo, Peter J van der Most, Erik P A van Iperen, Jessica van Setten, Jessic A Van Setten, Judith M Vonk, Li Zhang, Amber L Beitelshees, Gerald S Berenson, Deepak L Bhatt, Jolanda M A Boer, Eric Boerwinkle, Ben Burkley, Amber Burt, Aravinda Chakravarti, Wei Chen, Rhonda M Cooper-DeHoff, Sean P Curtis, Albert Dreisbach, David Duggan, Georg B Ehret, Richard R Fabsitz, Myriam Fornage, Ervin Fox, Clement E Furlong, Ron T Gansevoort, Marten H Hofker, G Kees Hovingh, Susan A Kirkland, Kandice Kottke-Marchant, Abdullah Kutlar, Andrea Z LaCroix, Taimour Y Langaee, Yun R Li, Honghuang Lin, Kiang Liu, Steffi Maiwald, Rainer Malik, , Gurunathan Murugesan, Christopher Newton-Cheh, Jeffery R O'Connell, N Charlotte Onland-Moret, Willem H Ouwehand, Walter Palmas, Brenda W Penninx, Carl J Pepine, Mary Pettinger, Joseph F Polak, Vasan S Ramachandran, Jane Ranchalis, Susan Redline, Paul M Ridker, Lynda M Rose, Hubert Scharnag, Nicholas J Schork, Daichi Shimbo, Alan R Shuldiner, Sathanur R Srinivasan, Ronald P Stolk, Herman A Taylor, Barbara Thorand, Mieke D Trip, Cornelia M van Duijn, W Monique Verschuren, Cisca Wijmenga, Bernhard R Winkelmann, Sharon Wyatt, J Hunter Young, Bernhard O Boehm, Mark J Caulfield, Daniel I Chasman, Karina W Davidson, Pieter A Doevendans, Garret A FitzGerald, John G Gums, Hakon Hakonarson, Hans L Hillege, Thomas Illig, Gail P Jarvik, Julie A Johnson, John J P Kastelein, Wolfgang Koenig, Winfried März, Braxton D Mitchell, Sarah S Murray, Albertine J Oldehinkel, Daniel J Rader, Muredach P Reilly, Alex P Reiner, Eric E Schadt, Roy L Silverstein, Harold Snieder, Alice V Stanton, André G Uitterlinden, Pim van der Harst, Yvonne T van der Schouw, Nilesh J Samani, Andrew D Johnson, Patricia B Munroe, Paul I W de Bakker, Xiaofeng Zhu, Daniel Levy, Brendan J Keating, Folkert W Asselbergs.
Hum. Mol. Genet.
PUBLISHED: 01-08-2013
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Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ?50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ?2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10(-6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.
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Linkage and association of phospholipid transfer protein activity to LASS4.
J. Lipid Res.
PUBLISHED: 07-13-2011
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Phospholipid transfer protein activity (PLTPa) is associated with insulin levels and has been implicated in atherosclerotic disease in both mice and humans. Variation at the PLTP structural locus on chromosome 20 explains some, but not all, heritable variation in PLTPa. In order to detect quantitative trait loci (QTLs) elsewhere in the genome that affect PLTPa, we performed both oligogenic and single QTL linkage analysis on four large families (n = 227 with phenotype, n = 330 with genotype, n = 462 total), ascertained for familial combined hyperlipidemia. We detected evidence of linkage between PLTPa and chromosome 19p (lod = 3.2) for a single family and chromosome 2q (lod = 2.8) for all families. Inclusion of additional marker and exome sequence data in the analysis refined the linkage signal on chromosome 19 and implicated coding variation in LASS4, a gene regulated by leptin that is involved in ceramide synthesis. Association between PLTPa and LASS4 variation was replicated in the other three families (P = 0.02), adjusting for pedigree structure. To our knowledge, this is the first example for which exome data was used in families to identify a complex QTL that is not the structural locus.
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Analysis of recently identified dyslipidemia alleles reveals two loci that contribute to risk for carotid artery disease.
Lipids Health Dis
PUBLISHED: 10-16-2009
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Genome-wide association studies have identified numerous single nucleotide polymorphisms (SNPs) affecting high density lipoprotein (HDL) or low density lipoprotein (LDL) cholesterol levels; these SNPs may contribute to the genetic basis of vascular diseases.
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Novel common and rare genetic determinants of paraoxonase activity: FTO, SERPINA12, and ITGAL.
J. Lipid Res.
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HDL-associated paraoxonase 1 (PON1) activity is associated with cardiovascular and other human diseases. As the role of genetic variants outside of the PON gene cluster on PON1 activity is unknown, we sought to identify common and rare variants in such loci. We typed 33,057 variants on the CVD chip in 1,362 subjects to test for their effects on adjusted-PON1 activity. Three novel genes (FTO, ITGAL, and SERPINA12) and the PON gene cluster had SNPs associated with PON1 arylesterase (AREase) activity. These loci were carried forward for rare-variant analysis using Exome chip genotypes in an overlapping subset of 1,051 subjects using sequence kernel association testing. PON1 (P = 2.24 × 10(-4)), PON3 (P = 0.022), FTO (P = 0.019), and SERPINA12 (P = 0.039) had both common and rare variants associated with PON1 AREase. ITGAL variants were associated with PON1 activity when using weighted sequence kernel association testing (SKAT) analysis (P = 2.63 × 10(-3)). When adjusting for the initial common variants, SERPINA12 became marginally significant (P = 0.09), whereas all other findings remained significant (P < 0.05), suggesting independent rare-variant effects. We present novel findings that common and rare variants in FTO, SERPINA12, and ITGAL predict PON1 activity. These results further link PON1 to diabetes and inflammation and may inform the role of HDL in human disease.
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Dietary cholesterol increases paraoxonase 1 enzyme activity.
J. Lipid Res.
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HDL-associated paraoxonase 1 (PON1) activity has been consistently associated with cardiovascular and other diseases. Vitamins C and E intake have previously been positively associated with PON1 in a subset of the Carotid Lesion Epidemiology and Risk (CLEAR) cohort. The goal of this study was to replicate these findings and determine whether other nutrient intake affected PON1 activity. To predict nutrient and mineral intake values, 1,402 subjects completed a standardized food frequency survey of their dietary habits over the past year. Stepwise regression was used to evaluate dietary and covariate effects on PON1 arylesterase activity. Five dietary components, cholesterol (P < 2.0 × 10(-16)), alcohol (P = 8.51 × 10(-8)), vitamin C (P = 7.97 × 10(-5)), iron (P = 0.0026), and folic acid (0.037) were independently predictive of PON1 activity. Dietary cholesterol was positively associated and predicted 5.5% of PON1 activity, second in variance explained. This study presents a novel finding of dietary cholesterol, iron, and folic acid predicting PON1 activity in humans and confirms prior reported associations, including that with vitamin C. Identifying and understanding environmental factors that affect PON1 activity is necessary to understand its role and that of HDL in human disease.
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Additional Common Polymorphisms in the PON Gene Cluster Predict PON1 Activity but Not Vascular Disease.
J Lipids
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Background. Paraoxonase 1 (PON1) enzymatic activity has been consistently predictive of cardiovascular disease, while the genotypes at the four functional polymorphisms at PON1 have not. The goal of this study was to identify additional variation at the PON gene cluster that improved prediction of PON1 activity and determine if these variants predict carotid artery disease (CAAD). Methods. We considered 1,328 males in a CAAD cohort. 51 tagging single-nucleotide polymorphisms (tag SNPs) across the PON cluster were evaluated to determine their effects on PON1 activity and CAAD status. Results. Six SNPs (four in PON1 and one each in PON2/3) predicted PON1 arylesterase (AREase) activity, in addition to the four previously known functional SNPs. In total, the 10 SNPs explained 30.1% of AREase activity, 5% of which was attributable to the six identified predictive SNPs. We replicate rs854567 prediction of 2.3% of AREase variance, the effects of rs3917510, and a PON3 haplotype that includes rs2375005. While AREase activity strongly predicted CAAD, none of the 10 SNPs predicting AREase predicted CAAD. Conclusions. This study identifies new genetic variants that predict additional PON1 AREase activity. Identification of SNPs associated with PON1 activity is required when evaluating the many phenotypes associated with genetic variation near PON1.
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Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.
Richa Saxena, Clara C Elbers, Yiran Guo, Inga Peter, Tom R Gaunt, Jessica L Mega, Matthew B Lanktree, Archana Tare, Berta Almoguera Castillo, Yun R Li, Toby Johnson, Marcel Bruinenberg, Diane Gilbert-Diamond, Ramakrishnan Rajagopalan, Benjamin F Voight, Ashok Balasubramanyam, John Barnard, Florianne Bauer, Jens Baumert, Tushar Bhangale, Bernhard O Böhm, Peter S Braund, Paul R Burton, Hareesh R Chandrupatla, Robert Clarke, Rhonda M Cooper-DeHoff, Errol D Crook, George Davey-Smith, Ian N Day, Anthonius de Boer, Mark C H de Groot, Fotios Drenos, Jane Ferguson, Caroline S Fox, Clement E Furlong, Quince Gibson, Christian Gieger, Lisa A Gilhuijs-Pederson, Joseph T Glessner, Anuj Goel, Yan Gong, Struan F A Grant, Diederick E Grobbee, Claire Hastie, Steve E Humphries, Cecilia E Kim, Mika Kivimäki, Marcus Kleber, Christa Meisinger, Meena Kumari, Taimour Y Langaee, Debbie A Lawlor, Mingyao Li, Maximilian T Lobmeyer, Anke-Hilse Maitland-van der Zee, Matthijs F L Meijs, Cliona M Molony, David A Morrow, Gurunathan Murugesan, Solomon K Musani, Christopher P Nelson, Stephen J Newhouse, Jeffery R O'Connell, Sandosh Padmanabhan, Jutta Palmen, Sanjey R Patel, Carl J Pepine, Mary Pettinger, Thomas S Price, Suzanne Rafelt, Jane Ranchalis, Asif Rasheed, Elisabeth Rosenthal, Ingo Ruczinski, Sonia Shah, Haiqing Shen, Günther Silbernagel, Erin N Smith, Annemieke W M Spijkerman, Alice Stanton, Michael W Steffes, Barbara Thorand, Mieke Trip, Pim van der Harst, Daphne L van der A, Erik P A van Iperen, Jessica van Setten, Jana V van Vliet-Ostaptchouk, Niek Verweij, Bruce H R Wolffenbuttel, Taylor Young, M Hadi Zafarmand, Joseph M Zmuda, , Michael Boehnke, David Altshuler, Mark McCarthy, W H Linda Kao, James S Pankow, Thomas P Cappola, Peter Sever, Neil Poulter, Mark Caulfield, Anna Dominiczak, Denis C Shields, Deepak L Bhatt, Deepak Bhatt, Li Zhang, Sean P Curtis, John Danesh, Juan P Casas, Yvonne T van der Schouw, N Charlotte Onland-Moret, Pieter A Doevendans, Gerald W Dorn, Martin Farrall, Garret A FitzGerald, Anders Hamsten, Robert Hegele, Aroon D Hingorani, Marten H Hofker, Gordon S Huggins, Thomas Illig, Gail P Jarvik, Julie A Johnson, Olaf H Klungel, William C Knowler, Wolfgang Koenig, Winfried März, James B Meigs, Olle Melander, Patricia B Munroe, Braxton D Mitchell, Susan J Bielinski, Daniel J Rader, Muredach P Reilly, Stephen S Rich, Jerome I Rotter, Danish Saleheen, Nilesh J Samani, Eric E Schadt, Alan R Shuldiner, Roy Silverstein, Kandice Kottke-Marchant, Philippa J Talmud, Hugh Watkins, Folkert W Asselbergs, Folkert Asselbergs, Paul I W de Bakker, Jeanne McCaffery, Cisca Wijmenga, Marc S Sabatine, James G Wilson, Alex Reiner, Donald W Bowden, Hakon Hakonarson, David S Siscovick, Brendan J Keating.
Am. J. Hum. Genet.
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To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ?50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ?2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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