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Scott RA, Lagou V, Welch RP, Wheeler E, Montasser ME, Luan J, Mägi R, Strawbridge RJ, Rehnberg E, Gustafsson S, Kanoni S, Rasmussen-Torvik LJ, Yengo L, Lecoeur C, Shungin D, Sanna S, Sidore C, Johnson PCD, Jukema JW, Johnson T, Mahajan A, Verweij N, Thorleifsson G, Hottenga JJ, Shah S, Smith AV, Sennblad B, Gieger C, Salo P, Perola M, Timpson NJ, Evans DM, Pourcain BS, Wu Y, Andrews JS, Hui J, Bielak LF, Zhao W, Horikoshi M, Navarro P, Isaacs A, O'Connell JR, Stirrups K, Vitart V, Hayward C, Esko T, Mihailov E, Fraser RM, Fall T, Voight BF, Raychaudhuri S, Chen H, Lindgren CM, Morris AP, Rayner NW, Robertson N, Rybin D, Liu CT, Beckmann JS, Willems SM, Chines PS, Jackson AU, Kang HM, Stringham HM, Song K, Tanaka T, Peden JF, Goel A, Hicks AA, An P, Müller-Nurasyid M, Franco-Cereceda A, Folkersen L, Marullo L, Jansen H, Oldehinkel AJ, Bruinenberg M, Pankow JS, North KE, Forouhi NG, Loos RJF, Edkins S, Varga TV, Hallmans G, Oksa H, Antonella M, Nagaraja R, Trompet S, Ford I, Bakker SJL, Kong A, Kumari M, Gigante B, Herder C, Munroe PB, Caulfield M, Antti J, Mangino M, Small K, Miljkovic I, Liu Y, Atalay M, Kiess W, James AL, Rivadeneira F, Uitterlinden AG, Palmer CNA, Doney ASF, Willemsen G, Smit JH, Campbell S, Polasek O, Bonnycastle LL, Hercberg S, Dimitriou M, Bolton JL, Fowkes GR, Kovacs P, Lindström J, Zemunik T, Bandinelli S, Wild SH, Basart HV, Rathmann W, Grallert H, Maerz W, Kleber ME, Boehm BO, Peters A, Pramstaller PP, Province MA, Borecki IB, Hastie ND, Rudan I, Campbell H, Watkins H, Farrall M, Stumvoll M, Ferrucci L, Waterworth DM, Bergman RN, Collins FS, Tuomilehto J, Watanabe RM, de Geus EJC, Penninx BW, Hofman A, Oostra BA, Psaty BM, Vollenweider P, Wilson JF, Wright AF, Hovingh GK, Metspalu A, Uusitupa M, Magnusson PKE, Kyvik KO, Kaprio J, Price JF, Dedoussis GV, Deloukas P, Meneton P, Lind L, Boehnke M, Shuldiner AR, van Duijn CM, Morris AD, Toenjes A, Peyser PA, Beilby JP, Körner A, Kuusisto J, Laakso M, Bornstein SR, Schwarz PEH, Lakka TA, Rauramaa R, Adair LS, Smith GD, Spector TD, Illig T, de Faire U, Hamsten A, Gudnason V, Kivimaki M, Hingorani A, Keinanen-Kiukaanniemi SM, Saaristo TE, Boomsma DI, Stefansson K, van der Harst P, Dupuis J, Pedersen NL, Sattar N, Harris TB, Cucca F, Ripatti S, Salomaa V, Mohlke KL, Balkau B, Froguel P, Pouta A, Jarvelin MR, Wareham NJ, Bouatia-Naji N, McCarthy MI, Franks PW, Meigs JB, Teslovich TM, Florez JC, Langenberg C, Ingelsson E, Prokopenko I, Barroso I. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet 2012; 44:991-1005. [PMID: 22885924 PMCID: PMC3433394 DOI: 10.1038/ng.2385] [Citation(s) in RCA: 627] [Impact Index Per Article: 52.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2012] [Accepted: 07/20/2012] [Indexed: 12/16/2022]
Abstract
Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.
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Affiliation(s)
- Robert A Scott
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
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Valenti L, Rametta R, Ruscica M, Dongiovanni P, Steffani L, Motta BM, Canavesi E, Fracanzani AL, Mozzi E, Roviaro G, Magni P, Fargion S. The I148M PNPLA3 polymorphism influences serum adiponectin in patients with fatty liver and healthy controls. BMC Gastroenterol 2012; 12:111. [PMID: 22898488 PMCID: PMC3444917 DOI: 10.1186/1471-230x-12-111] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2012] [Accepted: 08/07/2012] [Indexed: 12/13/2022] Open
Abstract
Background Reduced adiponectin is implicated in the pathogenesis of nonalcoholic fatty liver disease (NAFLD) and steatohepatitis (NASH), and the I148M Patatin-like phospholipase domain-containing 3 (PNPLA3) polymorphism predisposes to NAFLD and liver damage progression in NASH and chronic hepatitis C (CHC) by still undefined mechanisms, possibly involving regulation of adipose tissue function. Aim of this study was to evaluate whether the I148M PNPLA3 polymorphism influences serum adiponectin in liver diseases and healthy controls. Methods To this end, we considered 144 consecutive Italian patients with NAFLD, 261 with CHC, 35 severely obese subjects, and 257 healthy controls with very low probability of steatosis, all with complete clinical and genetic characterization, including adiponectin (ADIPOQ) genotype. PNPLA3 rs738409 (I148M) and ADIPOQ genotypes were evaluated by Taqman assays, serum adiponectin by ELISA. Adiponectin mRNA levels were evaluated by quantitative real-time PCR in the visceral adipose tissue (VAT) of 35 obese subjects undergoing bariatric surgery. Results Adiponectin levels were independently associated with the risk of NAFLD and with the histological severity of the disease. Adiponectin levels decreased with the number of 148 M PNPLA3 alleles at risk of NASH both in patients with NAFLD (p = 0.03), and in healthy subjects (p = 0.04). At multivariate analysis, PNPLA3 148 M alleles were associated with low adiponectin levels (<6 mg/ml, median value) independently of NAFLD diagnosis, age, gender, BMI, and ADIPOQ genotype (OR 1.67, 95% c.i. 1.07-2.1 for each 148 M allele). The p.148 M PNPLA3 variant was associated with decreased adiponectin mRNA levels in the VAT of obese patients (p < 0.05) even in the absence of NASH. In contrast, in CHC, characterized by adiponectin resistance, low adiponectin was associated with male gender and steatosis, but not with PNPLA3 and ADIPOQ genotypes and viral features. Conclusions The I148M PNPLA3 variant is associated with adiponectin levels in patients with NAFLD and in healthy subjects, but in the presence of adiponectin resistance not in CHC patients. The I148M PNPLA3 genotype may represent a genetic determinant of serum adiponectin levels. Modulation of serum adiponectin might be involved in mediating the susceptibility to steatosis, NASH, and hepatocellular carcinoma in carriers of the 148 M PNPLA3 variant without CHC, with potential therapeutic implications.
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Affiliation(s)
- Luca Valenti
- Department of Internal Medicine, Università degli Studi Milano, UO Medicina Interna 1B, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
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103
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Mtiraoui N, Ezzidi I, Turki A, Chaieb A, Mahjoub T, Almawi WY. Single-nucleotide polymorphisms and haplotypes in the adiponectin gene contribute to the genetic risk for type 2 diabetes in Tunisian Arabs. Diabetes Res Clin Pract 2012; 97:290-7. [PMID: 22497971 DOI: 10.1016/j.diabres.2012.02.015] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2011] [Revised: 02/14/2012] [Accepted: 02/21/2012] [Indexed: 12/29/2022]
Abstract
Adiponectin is an adipocyte-produced protein involved in regulating glucose, lipid, and energy metabolism, and is encoded by ADIPOQ (APM1) gene. ADIPOQ polymorphisms were previously associated with type 2 diabetes (T2DM) in Caucasian and non-Caucasian populations. We investigated the contribution of 13 polymorphisms in the promoter, coding regions, and 3'untranslated region of ADIPOQ gene to T2DM in 917 patients and 748 normoglycemic control subjects. ADIPOQ genotyping was done by allelic discrimination method. Of the 13 ADIPOQ variants analyzed, higher minor allele frequency of rs16861194 (P<0.001), rs17300539 (P<0.001), rs266729 (P<0.001), rs822396 (P=0.02), rs2241767 (P=0.03), and rs1063538 (P=0.02) were seen in T2DM cases. Varied association of ADIPOQ genotypes with T2DM was seen according to the genetic model used: rs17300539 and rs266729 were significantly associated with T2DM under the three models, while rs16861194 was association with T2DM under additive and dominant models, and rs822396, rs2241766, and rs1063538 were associated with T2DM under the dominant models only. Haploview analysis revealed low linkage disequilibrium between the ADIPOQ variants, resulting in high haplotype diversity, and two blocks were identified, each differentially associated with T2DM. These results support a significant association of ADIPOQ gene polymorphism with T2DM in Tunisian Arabs.
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Affiliation(s)
- Nabil Mtiraoui
- Research Unit of Biology and Genetics of Cancer and Haematological and Autoimmune diseases, Faculty of Pharmacy of Monastir, University of Monastir, Monastir, Tunisia
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Dalamaga M, Diakopoulos KN, Mantzoros CS. The role of adiponectin in cancer: a review of current evidence. Endocr Rev 2012; 33:547-94. [PMID: 22547160 PMCID: PMC3410224 DOI: 10.1210/er.2011-1015] [Citation(s) in RCA: 441] [Impact Index Per Article: 36.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Excess body weight is associated not only with an increased risk of type 2 diabetes and cardiovascular disease (CVD) but also with various types of malignancies. Adiponectin, the most abundant protein secreted by adipose tissue, exhibits insulin-sensitizing, antiinflammatory, antiatherogenic, proapoptotic, and antiproliferative properties. Circulating adiponectin levels, which are determined predominantly by genetic factors, diet, physical activity, and abdominal adiposity, are decreased in patients with diabetes, CVD, and several obesity-associated cancers. Also, adiponectin levels are inversely associated with the risk of developing diabetes, CVD, and several malignancies later in life. Many cancer cell lines express adiponectin receptors, and adiponectin in vitro limits cell proliferation and induces apoptosis. Recent in vitro studies demonstrate the antiangiogenic and tumor growth-limiting properties of adiponectin. Studies in both animals and humans have investigated adiponectin and adiponectin receptor regulation and expression in several cancers. Current evidence supports a role of adiponectin as a novel risk factor and potential diagnostic and prognostic biomarker in cancer. In addition, either adiponectin per se or medications that increase adiponectin levels or up-regulate signaling pathways downstream of adiponectin may prove to be useful anticancer agents. This review presents the role of adiponectin in carcinogenesis and cancer progression and examines the pathophysiological mechanisms that underlie the association between adiponectin and malignancy in the context of a dysfunctional adipose tissue in obesity. Understanding of these mechanisms may be important for the development of preventive and therapeutic strategies against obesity-associated malignancies.
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Affiliation(s)
- Maria Dalamaga
- Laboratory of Clinical Biochemistry, Attikon General University Hospital, University of Athens, School of Medicine, 12462 Athens, Greece
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Abstract
Personalized nutrition has been traditionally based on the adjustment of food and diet according to individual needs and preferences. At present, this concept is being reinforced through the application of state-of-the-art high-throughput technologies to help understand the molecular mechanisms underlying a healthy state. This knowledge could enable the adjustment of general dietary recommendations to match the needs of specific population groups based on their molecular profiles. The optimal development of evidence-based nutritional guidance to promote health requires an adequate assessment of nutrient bioavailability, bioactivity, and bioefficacy. To achieve this, reliable information about exposure to nutrients, their intake, and functional effects is required; thus, the identification of valid biomarkers using standardized analytical procedures is necessary. Although some nutritional biomarkers are now successfully used (eg, serum retinol, zinc, ferritin, and folate), a comprehensive set to assess the nutritional status and metabolic conditions of nutritional relevance is not yet available. Also, there is very limited knowledge on how the extensive human genetic variability influences the interpretation of these biomarkers. In this context, nutrigenomics seems to be a promising approach to identify new biomarkers in nutrition, through an integrative application of transcriptomics, proteomics, metabolomics, epigenomics, and nutrigenetics in human nutritional research.
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106
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Zhang H, Mo X, Hao Y, Gu D. Association between polymorphisms in the adiponectin gene and cardiovascular disease: a meta-analysis. BMC MEDICAL GENETICS 2012; 13:40. [PMID: 22639977 PMCID: PMC3413575 DOI: 10.1186/1471-2350-13-40] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2012] [Accepted: 05/28/2012] [Indexed: 12/22/2022]
Abstract
Background Previous studies have examined the associations between polymorphisms of adiponectin gene (ADIPOQ) and cardiovascular disease (CVD), but those studies have been inconclusive. The aim of this study was to access the relationship between three single nucleotide polymorphisms (SNPs), +45 T > G (rs2241766), +276 G > T (rs1501299) and -11377 C > G (rs266729) in ADIPOQ and CVD. Methods A comprehensive search was conducted to identify all studies on the association of ADIPOQ gene polymorphisms with CVD risk. The fixed and random effect pooled measures (i.e. odds ratio (OR) and 95% confidence interval (CI)) were calculated in the meta-analysis. Heterogeneity among studies was evaluated using Q test and the I2. Publication bias was estimated using modified Egger’s linear regression test. Results Thirty-seven studies concerning the associations between the three polymorphisms of ADIPOQ gene and CVD risk were enrolled in this meta-analysis, including 6,398 cases and 10,829 controls for rs2241766, 8,392 cases and 18,730 controls for rs1501299 and 7,835 cases and 14,023 controls for rs266729. The three SNPs were significantly associated with CVD, yielding pooled ORs of 1.22 (95%CI: 1.07, 1.39; P = 0.004), 0.90 (95%CI: 0.83, 0.97; P = 0.007) and 1.09(95%CI: 1.01, 1.17; P = 0.032) for rs2241766, rs1501299 and rs266729, respectively. Rs2241766 and rs1501299 were significantly associated with coronary heart disease (CHD), yielding pooled ORs of 1.29 (95%CI: 1.09, 1.52; P = 0.004) and 0.89 (95%CI: 0.81, 0.99; P = 0.025), respectively. The pooled OR for rs266729 and CHD was 1.09 (95%CI: 0.99, 1.19; P = 0.090). Significant between-study heterogeneity was found in our meta-analysis. Evidence of publication bias was observed in the meta-analysis. Conclusions The present meta-analysis showed that the associations between rs2241766, rs1501299 and rs266729 in the ADIPOQ and CVD were significant but weak. High quality studies are still needed to confirm the associations, especially for rs2241766.
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Affiliation(s)
- Huan Zhang
- State Key Laboratory of Cardiovascular Disease, Department of Evidence Based Medicine and Division of Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
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Warren LL, Li L, Nelson MR, Ehm MG, Shen J, Fraser DJ, Aponte JL, Nangle KL, Slater AJ, Woollard PM, Hall MD, Topp SD, Yuan X, Cardon LR, Chissoe SL, Mooser V, Morris AD, Palmer CNA, Perry JR, Frayling TM, Whittaker JC, Waterworth DM. Deep resequencing unveils genetic architecture of ADIPOQ and identifies a novel low-frequency variant strongly associated with adiponectin variation. Diabetes 2012; 61:1297-301. [PMID: 22403302 PMCID: PMC3331741 DOI: 10.2337/db11-0985] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Increased adiponectin levels have been shown to be associated with a lower risk of type 2 diabetes. To understand the relations between genetic variation at the adiponectin-encoding gene, ADIPOQ, and adiponectin levels, and subsequently its role in disease, we conducted a deep resequencing experiment of ADIPOQ in 14,002 subjects, including 12,514 Europeans, 594 African Americans, and 567 Indian Asians. We identified 296 single nucleotide polymorphisms (SNPs), including 30 amino acid changes, and carried out association analyses in a subset of 3,665 subjects from two independent studies. We confirmed multiple genome-wide association study findings and identified a novel association between a low-frequency SNP (rs17366653) and adiponectin levels (P = 2.2E-17). We show that seven SNPs exert independent effects on adiponectin levels. Together, they explained 6% of adiponectin variation in our samples. We subsequently assessed association between these SNPs and type 2 diabetes in the Genetics of Diabetes Audit and Research in Tayside Scotland (GO-DARTS) study, comprised of 5,145 case and 6,374 control subjects. No evidence of association with type 2 diabetes was found, but we were also unable to exclude the possibility of substantial effects (e.g., odds ratio 95% CI for rs7366653 [0.91-1.58]). Further investigation by large-scale and well-powered Mendelian randomization studies is warranted.
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Affiliation(s)
- Liling L Warren
- Quantitative Sciences, GlaxoSmithKline, Research Triangle Park, North Carolina, USA.
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Dastani Z, Hivert MF, Timpson N, Perry JRB, Yuan X, Scott RA, Henneman P, Heid IM, Kizer JR, Lyytikäinen LP, Fuchsberger C, Tanaka T, Morris AP, Small K, Isaacs A, Beekman M, Coassin S, Lohman K, Qi L, Kanoni S, Pankow JS, Uh HW, Wu Y, Bidulescu A, Rasmussen-Torvik LJ, Greenwood CMT, Ladouceur M, Grimsby J, Manning AK, Liu CT, Kooner J, Mooser VE, Vollenweider P, Kapur KA, Chambers J, Wareham NJ, Langenberg C, Frants R, Willems-vanDijk K, Oostra BA, Willems SM, Lamina C, Winkler TW, Psaty BM, Tracy RP, Brody J, Chen I, Viikari J, Kähönen M, Pramstaller PP, Evans DM, St. Pourcain B, Sattar N, Wood AR, Bandinelli S, Carlson OD, Egan JM, Böhringer S, van Heemst D, Kedenko L, Kristiansson K, Nuotio ML, Loo BM, Harris T, Garcia M, Kanaya A, Haun M, Klopp N, Wichmann HE, Deloukas P, Katsareli E, Couper DJ, Duncan BB, Kloppenburg M, Adair LS, Borja JB, Wilson JG, Musani S, Guo X, Johnson T, Semple R, Teslovich TM, Allison MA, Redline S, Buxbaum SG, Mohlke KL, Meulenbelt I, Ballantyne CM, Dedoussis GV, Hu FB, Liu Y, Paulweber B, Spector TD, Slagboom PE, Ferrucci L, Jula A, Perola M, Raitakari O, Florez JC, Salomaa V, Eriksson JG, Frayling TM, Hicks AA, Lehtimäki T, Smith GD, Siscovick DS, Kronenberg F, van Duijn C, Loos RJF, Waterworth DM, Meigs JB, Dupuis J, Richards JB. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals. PLoS Genet 2012; 8:e1002607. [PMID: 22479202 PMCID: PMC3315470 DOI: 10.1371/journal.pgen.1002607] [Citation(s) in RCA: 360] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2011] [Accepted: 02/03/2012] [Indexed: 12/16/2022] Open
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.
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Affiliation(s)
- Zari Dastani
- Department of Epidemiology, Biostatistics, and Occupational Health, Jewish General Hospital, Lady Davis Institute, McGill University, Montreal, Canada
| | - Marie-France Hivert
- Department of Medicine, Université de Sherbrooke, Sherbrooke, Canada
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Nicholas Timpson
- MRC CAiTE Centre and School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - John R. B. Perry
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, United Kingdom
| | - Xin Yuan
- Genetics, GlaxoSmithKline, King of Prussia, Pennsylvania, United States of America
| | - Robert A. Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Peter Henneman
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Iris M. Heid
- Department of Epidemiology and Preventive Medicine, Regensburg University Medical Center, Regensburg, Germany
| | - Jorge R. Kizer
- Departments of Medicine and Public Health, Weill Cornell Medical College, New York, New York, United States of America
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Christian Fuchsberger
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Toshiko Tanaka
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Andrew P. Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Kerrin Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Centre for Medical Systems Biology, Leiden, The Netherlands
| | - Marian Beekman
- Section of Molecular Epidemiology, Leiden University Medical Center and The Netherlands Genomics Initiative, The Netherlands Consortium for Healthy Aging, Leiden, The Netherlands
| | - Stefan Coassin
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Kurt Lohman
- Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Lu Qi
- Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Stavroula Kanoni
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Hae-Won Uh
- Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Aurelian Bidulescu
- Cardiovascular Research Institute, Morehouse School of Medicine, Atlanta, Georgia, United States of America
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Celia M. T. Greenwood
- Lady Davis Institute for Medical Research, Department of Oncology, McGill University, Montreal, Canada
| | - Martin Ladouceur
- Department of Human Genetics McGill University, Montreal, Canada
| | - Jonna Grimsby
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Alisa K. Manning
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Jaspal Kooner
- Cardiology, Ealing Hospital National Health Service (NHS) Trust, London, United Kingdom
| | - Vincent E. Mooser
- Genetics, GlaxoSmithKline, King of Prussia, Pennsylvania, United States of America
| | - Peter Vollenweider
- Department of Internal Medicine, University of Lausanne, Lausanne, Switzerland
| | - Karen A. Kapur
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - John Chambers
- Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Rune Frants
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Ko Willems-vanDijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Ben A. Oostra
- Centre for Medical Systems Biology, Leiden, The Netherlands
- Deptartment of Clinical Genetics and Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Sara M. Willems
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Claudia Lamina
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Thomas W. Winkler
- Department of Epidemiology and Preventive Medicine, Regensburg University Medical Center, Regensburg, Germany
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, Washington, United States of America
- Group Health Research Institute, Group Health Cooperative, Seattle, Washington, United States of America
| | - Russell P. Tracy
- Departments of Pathology and Biochemistry, University of Vermont, Burlington, Vermont, United States of America
| | - Jennifer Brody
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
| | - Ida Chen
- Medical Genetics Research Institute, Cedars Sinai Medical Center, Los Angeles, California, United States of America
| | - Jorma Viikari
- Department of Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Peter P. Pramstaller
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC) (Affiliated Institute of the University of Lübeck, Lübeck, Germany), Bolzano, Italy
- Department of Neurology, General Central Hospital, Bolzano, Italy
- Department of Neurology, University of Lübeck, Lübeck, Germany
| | - David M. Evans
- MRC CAiTE Centre and School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Beate St. Pourcain
- School of Social and community medicine, University of Bristol, Bristol, United Kingdom
| | - Naveed Sattar
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom
| | - Andrew R. Wood
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, United Kingdom
| | | | - Olga D. Carlson
- Laboratory of Clinical Investigation, National Institute of Aging, Baltimore, Maryland, United States of America
| | - Josephine M. Egan
- Laboratory of Clinical Investigation, National Institute of Aging, Baltimore, Maryland, United States of America
| | - Stefan Böhringer
- Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Diana van Heemst
- Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Lyudmyla Kedenko
- First Department of Internal Medicine, St. Johann Spital, Paracelsus Private Medical University Salzburg, Salzburg, Austria
| | - Kati Kristiansson
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, and Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Marja-Liisa Nuotio
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, and Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Britt-Marie Loo
- Population Studies Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Turku, Finland
| | - Tamara Harris
- Intramural Research Program, Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Melissa Garcia
- Intramural Research Program, Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Alka Kanaya
- Division of General Internal Medicine, Women's Health Clinical Research Center, University of California San Francisco, San Francisco, California, United States of America
| | - Margot Haun
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Norman Klopp
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - H.-Erich Wichmann
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- Klinikum Großhadern, Munich, Germany
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | | | - David J. Couper
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Bruce B. Duncan
- School of Medicine, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Margreet Kloppenburg
- Department of Rheumatology and Department of Clinical Epidemiology, Leiden, The Netherlands
| | - Linda S. Adair
- Department of Nutrition, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Judith B. Borja
- Office of Population Studies Foundation, University of San Carlos, Cebu City, Philippines
| | | | | | | | | | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Solomon Musani
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Xiuqing Guo
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Toby Johnson
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- University Institute of Social and Preventative Medicine, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Robert Semple
- Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Tanya M. Teslovich
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Matthew A. Allison
- Department of Family and Preventive Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Susan Redline
- Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Sarah G. Buxbaum
- Jackson Heart Study Coordinating Center, Jackson State University, Jackson, Mississippi, United States of America
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Ingrid Meulenbelt
- Section of Molecular Epidemiology, Leiden University Medical Center and The Netherlands Genomics Initiative, The Netherlands Consortium for Healthy Aging, Leiden, The Netherlands
| | - Christie M. Ballantyne
- Baylor College of Medicine and Methodist DeBakey Heart and Vascular Center, Houston, Texas, United States of America
| | | | - Frank B. Hu
- Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Yongmei Liu
- Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Bernhard Paulweber
- First Department of Internal Medicine, St. Johann Spital, Paracelsus Private Medical University Salzburg, Salzburg, Austria
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - P. Eline Slagboom
- Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Luigi Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Antti Jula
- Population Studies Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Turku, Finland
| | - Markus Perola
- Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, and Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and the Department of Clinical Physiology, Turku University Hospital, Turku, Finland
| | - Jose C. Florez
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Diabetes Research Center, Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Veikko Salomaa
- Chronic Disease Epidemiology and Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Johan G. Eriksson
- Diabetes Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Unit of General Practice, Helsinki University Central Hospital, Helsinki, Finland
- Folkhalsan Research Centre, Helsinki, Finland
- Vaasa Central Hospital, Vaasa, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
| | - Timothy M. Frayling
- Genetics of Complex Traits, Peninsula Medical School, University of Exeter, Exeter, United Kingdom
| | - Andrew A. Hicks
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC) (Affiliated Institute of the University of Lübeck, Lübeck, Germany), Bolzano, Italy
| | - Terho Lehtimäki
- Department of Clinical Chemistry, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - George Davey Smith
- MRC CAiTE Centre and School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | | | - Florian Kronenberg
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Cornelia van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Centre for Medical Systems Biology, Leiden, The Netherlands
| | - Ruth J. F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Dawn M. Waterworth
- Genetics, GlaxoSmithKline, King of Prussia, Pennsylvania, United States of America
| | - James B. Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Josee Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - J. Brent Richards
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
- Departments of Medicine, Human Genetics, Epidemiology, and Biostatistics, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Canada
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109
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Yang Y, Zhang F, Ding R, Wang Y, Lei H, Hu D. Association of ADIPOQ gene polymorphisms and coronary artery disease risk: a meta-analysis based on 12 465 subjects. Thromb Res 2012; 130:58-64. [PMID: 22386722 DOI: 10.1016/j.thromres.2012.01.018] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2011] [Revised: 01/02/2012] [Accepted: 01/04/2012] [Indexed: 01/09/2023]
Abstract
INTRODUCTION Coronary artery disease (CAD) is one of the most common cardiovascular diseases and is a major cause of morbidity and mortality worldwide. Various researchers have investigated the role of ADIPOQ gene in the risk of CAD, yet their results have been inconsistent. METHODS To evaluate the association between ADIPOQ genetic polymorphisms and CAD risk, relevant studies published before October 2011 were identified by searching PubMed and EMBASE. Studies were selected using previously defined criteria. The strength of the relationship between the four single nucleotide polymorphisms (SNPs) of the ADIPOQ gene and CAD risk was assessed using odds ratios (ORs). RESULTS A total of 12 465 subjects from 17 case-control studies were identified in the present study. Based on the relevant studies, it was determined that the risk of CAD was not associated with rs2241766 in any genetic model. Increased risk of CAD was associated with rs266729 in allele contrast (1.11, [1.03, 1.20]) and dominant genetic model (1.15, 95%CI: [1.05, 1.27]); increased risk of CAD was also associated with rs822395 in additive (1.63, 95%CI: [1.19, 2.22]) and recessive genetic model (1.71, 95%CI: [1.27, 2.30]). It was further determined that the rs1501299 polymorphism reduced the risk of CAD in the additive (0.80, 95%CI: [0.67, 0.94]) and recessive genetic model (0.81, 95%CI: [0.68, 0.95]). In the stratified analysis, significant associations were found in Asian subjects for rs266729 and in Caucasian subjects for rs1501299. CONCLUSION There is an association between ADIPOQ gene polymorphisms and CAD risk. Different SNPs of the ADIPOQ gene have different associations with CAD risk, and appear to increase risk in individuals of Asian ethnicity while decrease the CAD risk in Caucasians. However, the overall strength of association was mild to moderate.
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Affiliation(s)
- Yuan Yang
- Department of Cardiology, First Affiliated Hospital, Chongqing Medical University, Chongqing, 400016, China
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110
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Tabassum R, Mahendran Y, Dwivedi OP, Chauhan G, Ghosh S, Marwaha RK, Tandon N, Bharadwaj D. Common variants of IL6, LEPR, and PBEF1 are associated with obesity in Indian children. Diabetes 2012; 61:626-31. [PMID: 22228719 PMCID: PMC3282821 DOI: 10.2337/db11-1501] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The increasing prevalence of obesity in urban Indian children is indicative of an impending crisis of metabolic disorders. Although perturbations in the secretion of adipokines and inflammatory molecules in childhood obesity are well documented, the contribution of common variants of genes encoding them is not well investigated. We assessed the association of 125 common variants from 21 genes, encoding adipocytokines and inflammatory markers in 1,325 urban Indian children (862 normal weight [NW group] and 463 overweight/obese [OW/OB group]) and replicated top loci in 1,843 Indian children (1,399 NW children and 444 OW/OB children). Variants of four genes (PBEF1 [rs3801266] [P = 4.5 × 10(-4)], IL6 [rs2069845] [P = 8.7 × 10(-4)], LEPR [rs1137100] [P = 1.8 × 10(-3)], and IL6R [rs7514452] [P = 2.1 × 10(-3)]) were top signals in the discovery sample. Associations of rs2069845, rs1137100, and rs3801266 were replicated (P = 7.9 × 10(-4), 8.3 × 10(-3), and 0.036, respectively) and corroborated in meta-analysis (P = 2.3 × 10(-6), 3.9 × 10(-5), and 4.3 × 10(-4), respectively) that remained significant after multiple testing corrections. These variants also were associated with quantitative measures of adiposity (weight, BMI, and waist and hip circumferences). Allele dosage analysis of rs2069845, rs1137100, and rs3801266 revealed that children with five to six risk alleles had an approximately four times increased risk of obesity than children with less than two risk alleles (P = 1.2 × 10(-7)). In conclusion, our results demonstrate the association of the common variants of IL6, LEPR, and PBEF1 with obesity in Indian children.
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Affiliation(s)
- Rubina Tabassum
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, Delhi, India
| | - Yuvaraj Mahendran
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, Delhi, India
| | - Om Prakash Dwivedi
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, Delhi, India
| | - Ganesh Chauhan
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, Delhi, India
| | - Saurabh Ghosh
- Human Genetics Unit, Indian Statistical Institute, Kolkata, India
| | - Raman K. Marwaha
- Department of Endocrinology and Thyroid Research, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Nikhil Tandon
- Department of Endocrinology, All India Institute of Medical Sciences, New Delhi, India
- Corresponding authors: Nikhil Tandon, , and Dwaipayan Bharadwaj,
| | - Dwaipayan Bharadwaj
- Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, Delhi, India
- Corresponding authors: Nikhil Tandon, , and Dwaipayan Bharadwaj,
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111
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Ladouceur M, Dastani Z, Aulchenko YS, Greenwood CMT, Richards JB. The empirical power of rare variant association methods: results from sanger sequencing in 1,998 individuals. PLoS Genet 2012; 8:e1002496. [PMID: 22319458 PMCID: PMC3271058 DOI: 10.1371/journal.pgen.1002496] [Citation(s) in RCA: 88] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2011] [Accepted: 12/08/2011] [Indexed: 01/09/2023] Open
Abstract
The role of rare genetic variation in the etiology of complex disease remains unclear. However, the development of next-generation sequencing technologies offers the experimental opportunity to address this question. Several novel statistical methodologies have been recently proposed to assess the contribution of rare variation to complex disease etiology. Nevertheless, no empirical estimates comparing their relative power are available. We therefore assessed the parameters that influence their statistical power in 1,998 individuals Sanger-sequenced at seven genes by modeling different distributions of effect, proportions of causal variants, and direction of the associations (deleterious, protective, or both) in simulated continuous trait and case/control phenotypes. Our results demonstrate that the power of recently proposed statistical methods depend strongly on the underlying hypotheses concerning the relationship of phenotypes with each of these three factors. No method demonstrates consistently acceptable power despite this large sample size, and the performance of each method depends upon the underlying assumption of the relationship between rare variants and complex traits. Sensitivity analyses are therefore recommended to compare the stability of the results arising from different methods, and promising results should be replicated using the same method in an independent sample. These findings provide guidance in the analysis and interpretation of the role of rare base-pair variation in the etiology of complex traits and diseases.
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Affiliation(s)
- Martin Ladouceur
- Department of Human Genetics, McGill University, Montreal, Canada
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada
| | - Zari Dastani
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
| | - Yurii S. Aulchenko
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Institute of Cytology and Genetics SD RAS, Novosibirsk, Russia
| | - Celia M. T. Greenwood
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
- Department of Oncology, McGill University, Montreal, Canada
| | - J. Brent Richards
- Department of Human Genetics, McGill University, Montreal, Canada
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada
- Department of Medicine, Jewish General Hospital, McGill University, Montreal, Canada
- Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
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Moayyeri A, Hammond CJ, Valdes AM, Spector TD. Cohort Profile: TwinsUK and healthy ageing twin study. Int J Epidemiol 2012; 42:76-85. [PMID: 22253318 DOI: 10.1093/ije/dyr207] [Citation(s) in RCA: 189] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
The UK's largest registry of adult twins, or TwinsUK Registry, started in 1992 and encompasses about 12000 volunteer twins from all over the United Kingdom. More than 70% of the registered twins have filled at least one detailed health questionnaire and about half of them undergone a baseline comprehensive assessment and two follow-up clinical evaluations. The most recent follow-up visit, known as Healthy Ageing Twin Study (HATS), involved 3125 female twins aged >40 years with at least one previous clinical assessment to enable inspection of longitudinal changes in ageing traits and their genetic and environmental components. The study benefits from several state-of-the-art OMICs studies including genome-wide association, next-generation genome and transcriptome sequencing, and epigenetic and metabolomic profiles. This makes our cohort as one of the most deeply phenotyped and genotyped in the world. Several collaborative projects in the field of epidemiology of complex disorders are ongoing in our cohort and interested researchers are encouraged to get in contact for future collaborations.
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Affiliation(s)
- Alireza Moayyeri
- Department of Twin Research and Genetic Epidemiology, King's College London, St Thomas' Hospital, London, UK
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113
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Morisaki H, Yamanaka I, Iwai N, Miyamoto Y, Kokubo Y, Okamura T, Okayama A, Morisaki T. CDH13
gene coding t-cadherin influences variations in plasma adiponectin levels in the Japanese population. Hum Mutat 2011; 33:402-10. [DOI: 10.1002/humu.21652] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2011] [Accepted: 10/24/2011] [Indexed: 01/09/2023]
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Povel CM, Boer JMA, Feskens EJM. Shared genetic variance between the features of the metabolic syndrome: heritability studies. Mol Genet Metab 2011; 104:666-9. [PMID: 21963081 DOI: 10.1016/j.ymgme.2011.08.035] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2011] [Revised: 08/31/2011] [Accepted: 08/31/2011] [Indexed: 12/27/2022]
Abstract
Heritability estimates of MetS range from approximately 10%-30%. The genetic variation that is shared among MetS features can be calculated by genetic correlation coefficients. The objective of this paper is to identify MetS feature as well as MetS related features which have much genetic variation in common, by reviewing the literature regarding genetic correlation coefficients. Identification of features, that have much genetic variation in common, may eventually facilitate the search for pleitropic genetic variants that may explain the clustering of MetS features. A PubMed search with the search terms "(metabolic syndrome OR insulin resistance syndrome) and (heritability OR genetic correlation OR pleiotropy)" was performed. Studies published before 7th July 2011, which presented genetic correlation coefficients between the different MetS features and genetic correlation coefficients of MetS and its features with adipose tissue-, pro-inflammatory and pro-thrombotic biomarkers were included. Nine twin and 19 family studies were included in the review. Genetic correlations varied, but were strongest between waist circumference and HOMA-IR (r(2): 0.36 to 0.79, median: 0.50), HDL cholesterol and triglycerides (r(2): -0.05 to -0.59, median -0.45), adiponectin and MetS (r(2): -0.32 to -0.43; median -0.38), adiponectin and insulin (r(2): -0.10 to -0.60; median -0.30) and between adiponectin and HDL-cholesterol (r(2): -0.22 to -0.51, median -0.29). In conclusion, heritability studies suggest that genetic pleiotropy exist especially between certain MetS features, as well as between MetS and adiponectin. Further research on actual genetic variants responsible for the genetic pleiotropy of these combinations will provide more insight into the etiology of MetS.
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Affiliation(s)
- C M Povel
- Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands.
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115
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Croteau-Chonka DC, Wu Y, Li Y, Fogarty MP, Lange LA, Kuzawa CW, McDade TW, Borja JB, Luo J, AbdelBaky O, Combs TP, Adair LS, Lange EM, Mohlke KL. Population-specific coding variant underlies genome-wide association with adiponectin level. Hum Mol Genet 2011; 21:463-71. [PMID: 22010046 DOI: 10.1093/hmg/ddr480] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Adiponectin is a protein hormone that can affect major metabolic processes including glucose regulation and fat metabolism. Our previous genome-wide association (GWA) study of circulating plasma adiponectin levels in Filipino women from the Cebu Longitudinal Health and Nutrition Survey (CLHNS) detected a 100 kb two-SNP haplotype at KNG1-ADIPOQ associated with reduced adiponectin (frequency = 0.050, P = 1.8 × 10(-25)). Subsequent genotyping of CLHNS young adult offspring detected an uncommon variant [minor allele frequency (MAF) = 0.025] located ~800 kb from ADIPOQ that showed strong association with lower adiponectin levels (P = 2.7 × 10(-15), n = 1695) and tagged a subset of KNG1-ADIPOQ haplotype carriers with even lower adiponectin levels. Sequencing of the ADIPOQ-coding region detected variant R221S (MAF = 0.015, P = 2.9 × 10(-69)), which explained 17.1% of the variance in adiponectin levels and largely accounted for the initial GWA signal in Filipinos. R221S was not present in 12 514 Europeans with previously sequenced exons. To explore the mechanism of this substitution, we re-measured adiponectin level in 20 R221S offspring carriers and 20 non-carriers using two alternative antibodies and determined that the presence of R221S resulted in artificially low quantification of adiponectin level using the original immunoassay. These data provide an example of an uncommon variant responsible for a GWA signal and demonstrate that genetic associations with phenotypes measured by antibody-based quantification methods can be affected by uncommon coding SNPs residing in the antibody target region.
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Cohen SS, Gammon MD, North KE, Millikan RC, Lange EM, Williams SM, Zheng W, Cai Q, Long J, Smith JR, Signorello LB, Blot WJ, Matthews CE. ADIPOQ, ADIPOR1, and ADIPOR2 polymorphisms in relation to serum adiponectin levels and BMI in black and white women. Obesity (Silver Spring) 2011; 19:2053-62. [PMID: 21273992 PMCID: PMC3474141 DOI: 10.1038/oby.2010.346] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Adiponectin is an adipose-secreted protein with influence on several physiologic pathways including those related to insulin sensitivity, inflammation, and atherogenesis. Adiponectin levels are highly heritable and several single-nucleotide polymorphisms (SNPs) in adiponectin-related genes (ADIPOQ, ADIPOR1, ADIPOR2) have been examined in relation to circulating adiponectin levels and obesity phenotypes, but despite differences in adiponectin levels and obesity prevalence by race, few studies have included black participants. Using cross-sectional interview data and blood samples collected from 990 black and 977 white women enrolled in the Southern Community Cohort Study (SCCS) from 2002 to 2006, we examined 25 SNPs in ADIPOQ, 19 in ADIPOR1, and 27 in ADIPOR2 in relation to serum adiponectin levels and BMI using race-stratified linear regression models adjusted for age and percentage African ancestry. SNP rs17366568 in ADIPOQ was significantly associated with serum adiponectin levels in white women only (adjusted mean adiponectin levels = 15.9 for G/G genotype, 13.7 for A/G, and 9.3 for A/A, P = 0.00036). No other SNPs were associated with adiponectin or BMI among blacks or whites. Because adiponectin levels as well as obesity are highly heritable and vary by race but associations with polymorphisms in the ADIPOQ, ADIPOR1, and ADIPOR2 genes have been few in this and other studies, future work including large populations from diverse racial groups is needed to detect additional genetic variants that influence adiponectin and BMI.
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Affiliation(s)
- Sarah S Cohen
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA.
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117
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Oliveira CSV, Giuffrida FMA, Crispim F, Saddi-Rosa P, Reis AF. ADIPOQ and adiponectin: the common ground of hyperglycemia and coronary artery disease? ACTA ACUST UNITED AC 2011; 55:446-54. [DOI: 10.1590/s0004-27302011000700003] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2011] [Accepted: 10/30/2011] [Indexed: 01/02/2023]
Abstract
Plasma adiponectin and the coding gene for adiponectin, ADIPOQ, are thought to explain part of the interaction between obesity, insulin resistance, type 2 diabetes (T2DM) and coronary artery disease (CAD). Here, we illustrate the role that adiponectin and ADIPOQ variants might play in the modulation of CAD, especially in the occurrence of hyperglycemia. Recent evidence suggests that total and high molecular weight (HMW) adiponectin levels are apparent markers of better cardiovascular prognosis in patients with low risk of CAD. However, in subjects with established or high risk of CAD, these levels are associated with poorer prognosis. We also provide recent evidences relating to the genetic control of total and HMW adiponectin levels, especially evidence regarding ADIPOQ. Accumulated data suggest that both adiponectin levels and polymorphisms in the ADIPOQ gene are linked to the risk of CAD in patients with hyperglycemia, and that these associations seem to be independent from each other, even if adiponectin levels are partly dependent on ADIPOQ.
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Chung CM, Lin TH, Chen JW, Leu HB, Yang HC, Ho HY, Ting CT, Sheu SH, Tsai WC, Chen JH, Lin SJ, Chen YT, Pan WH. A genome-wide association study reveals a quantitative trait locus of adiponectin on CDH13 that predicts cardiometabolic outcomes. Diabetes 2011; 60:2417-23. [PMID: 21771975 PMCID: PMC3161336 DOI: 10.2337/db10-1321] [Citation(s) in RCA: 96] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
OBJECTIVE The plasma adiponectin level, a potential upstream and internal facet of metabolic and cardiovascular diseases, has a reasonably high heritability. Whether other novel genes influence the variation in adiponectin level and the roles of these genetic variants on subsequent clinical outcomes has not been thoroughly investigated. Therefore, we aimed not only to identify genetic variants modulating plasma adiponectin levels but also to investigate whether these variants are associated with adiponectin-related metabolic traits and cardiovascular diseases. RESEARCH DESIGN AND METHODS We conducted a genome-wide association study (GWAS) to identify quantitative trait loci (QTL) associated with high molecular weight forms of adiponectin levels by genotyping 382 young-onset hypertensive (YOH) subjects with Illumina HumanHap550 SNP chips. The culpable single nucleotide polymorphism (SNP) variants responsible for lowered adiponectin were then confirmed in another 559 YOH subjects, and the association of these SNP variants with the risk of metabolic syndrome (MS), type 2 diabetes mellitus (T2DM), and ischemic stroke was examined in an independent community-based prospective cohort, the CardioVascular Disease risk FACtors Two-township Study (CVDFACTS, n = 3,350). RESULTS The SNP (rs4783244) most significantly associated with adiponectin levels was located in intron 1 of the T-cadherin (CDH13) gene in the first stage (P = 7.57 × 10(-9)). We replicated and confirmed the association between rs4783244 and plasma adiponectin levels in an additional 559 YOH subjects (P = 5.70 × 10(-17)). This SNP was further associated with the risk of MS (odds ratio [OR] = 1.42, P = 0.027), T2DM in men (OR = 3.25, P = 0.026), and ischemic stroke (OR = 2.13, P = 0.002) in the CVDFACTS. CONCLUSIONS These findings indicated the role of T-cadherin in modulating adiponectin levels and the involvement of CDH13 or adiponectin in the development of cardiometabolic diseases.
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Affiliation(s)
- Chia-Min Chung
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Tsung-Hsien Lin
- Division of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
- Department of Internal Medicine, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Jaw-Wen Chen
- Cardiovascular Research Center, National Yang-Ming University, Taipei, Taiwan
- Department of Medical Research and Education, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Hsin-Bang Leu
- Cardiovascular Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Hsin-Chou Yang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Hung-Yun Ho
- Taichung Veterans General Hospital, Taichung, Taiwan
| | - Chih-Tai Ting
- Taichung Veterans General Hospital, Taichung, Taiwan
| | - Sheng-Hsiung Sheu
- Division of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
- Department of Internal Medicine, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Wei-Chuan Tsai
- College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Jyh-Hong Chen
- College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Shing-Jong Lin
- Department of Medical Research and Education, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yuan-Tsong Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Wen-Harn Pan
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
- Division of Preventive Medicine and Health Service Research, National Health Research Institutes, Miaoli, Taiwan
- Corresponding author: Wen-Harn Pan,
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Han LY, Wu QH, Jiao ML, Hao YH, Liang LB, Gao LJ, Legge DG, Quan H, Zhao MM, Ning N, Kang Z, Sun H. Associations between single-nucleotide polymorphisms (+45T>G, +276G>T, -11377C>G, -11391G>A) of adiponectin gene and type 2 diabetes mellitus: a systematic review and meta-analysis. Diabetologia 2011; 54:2303-14. [PMID: 21638131 DOI: 10.1007/s00125-011-2202-9] [Citation(s) in RCA: 70] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2010] [Accepted: 04/27/2011] [Indexed: 02/07/2023]
Abstract
AIMS/HYPOTHESIS The associations between adiponectin polymorphisms and type 2 diabetes have been studied widely; however, results are inconsistent. METHODS We searched electronic literature databases and reference lists of relevant articles. A fixed or random effects model was used on the basis of heterogeneity. Sub-group and meta-regression analyses were conducted to explore the sources of heterogeneity. RESULTS There were no statistically significant associations between +45T>G (rs2241766), +276G>T (rs1501299), -11391G>A (rs17300539) and type 2 diabetes risk. However, for -11377C>G (rs266729), the pooled OR (95% CI) for G vs C allele was 1.07 (1.03-1.11, p = 0.001). Subgroup analysis by study design revealed that -11377C>G (rs266729) dominant model (CG+GG vs CC, p = 0.0008) and G vs C allele (p = 0.0004) might be associated with type 2 diabetes risk in population-based case-control studies. After stratification by ethnicity, we found that -11377C>G (rs266729) dominant model (CG+GG vs CC, p = 0.004) and G vs C allele (p = 0.001) might be associated with type 2 diabetes risk in white individuals. In individuals with a family history of diabetes, the presence of -11391G>A (rs17300539) dominant model (GA+AA vs GG) and A vs G allele might be associated with increased risk of type 2 diabetes. CONCLUSIONS/INTERPRETATION The presence of +45T>G (rs2241766), +276G>T (rs1501299) and -11391G>A (rs17300539) do not appear to influence the development of type 2 diabetes. However, G vs C allele of -11377C>G (rs266729) might be a risk factor for type 2 diabetes.
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Affiliation(s)
- L Y Han
- Department of Social Medicine, School of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, Heilongjiang 150081, People's Republic of China
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Qi L, Menzaghi C, Salvemini L, De Bonis C, Trischitta V, Hu FB. Novel locus FER is associated with serum HMW adiponectin levels. Diabetes 2011; 60:2197-201. [PMID: 21700879 PMCID: PMC3142072 DOI: 10.2337/db10-1645] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
OBJECTIVE High molecular weight (HMW) adiponectin is a predominant isoform of circulating adiponectin and has been related to type 2 diabetes. Previous linkage studies suggest that different genetic components might be involved in determining HMW and total adiponectin levels. RESEARCH DESIGN AND METHODS We performed a genome-wide association study (GWAS) of serum HMW adiponectin levels in individuals of European ancestry drawn from the Nurses' Health Study (NHS) (N = 1,591). The single nucleotide polymorphisms (SNPs) identified in the GWAS analysis were replicated in an independent cohort of Europeans (N = 626). We examined the associations of the identified variations with diabetes risk and metabolic syndrome. RESULTS We identified a novel locus near the FER gene (5q21) at a genome-wide significance level, best represented by SNP rs10447248 (P = 4.69 × 10(-8)). We also confirmed that variations near the adiponectin-encoding ADIPOQ locus (3q27) were related to serum HMW adiponectin levels. In addition, we found that FER SNP rs10447248 was related to HDL cholesterol levels (P = 0.009); ADIPOQ variation was associated with fasting glucose (P = 0.04), HDL cholesterol (P = 0.04), and a metabolic syndrome score (P = 0.002). CONCLUSIONS Our results suggest that different loci may be involved in regulation of circulating HMW adiponectin levels and provide novel insight into the mechanisms that affect HMW adiponectin homeostasis.
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Affiliation(s)
- Lu Qi
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA.
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121
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Dahlman I, Arner P. Genetics of adipose tissue biology. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2011; 94:39-74. [PMID: 21036322 DOI: 10.1016/b978-0-12-375003-7.00003-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Adipose tissue morphology and release of free fatty acids, as well as peptide hormones, are believed to contribute to obesity and related metabolic disorders. These adipose tissue phenotypes are influenced by adiposity, but there is also a strong hereditary impact. Polymorphisms in numerous adipose-expressed genes have been evaluated for association with adipocyte and clinical phenotypes. In our opinion, some results are convincing. Thus ADRB2 and GPR74 genes are associated with adipocyte lipolysis, GPR74 also with BMI; PPARG and SREBP1, which promote adipogenesis and lipid storage, are associated with T2D and possible adiposity; ADIPOQ and ARL15 are associated with circulating levels of adiponectin, ARL15 also with coronary heart disease. We anticipate that the use of complementary approaches such as expression profiling and RNAi screening, and studies of additional levels of gene regulation, that is, miRNA and epigenetics, will be important to unravel the genetics of adipose tissue function.
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122
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Menzaghi C, De Cosmo S, Copetti M, Salvemini L, De Bonis C, Mangiacotti D, Fini G, Pellegrini F, Trischitta V. Relationship between ADIPOQ gene, circulating high molecular weight adiponectin and albuminuria in individuals with normal kidney function: evidence from a family-based study. Diabetologia 2011; 54:812-8. [PMID: 21229348 DOI: 10.1007/s00125-010-2037-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2010] [Accepted: 12/14/2010] [Indexed: 12/26/2022]
Abstract
AIMS/HYPOTHESIS Insulin resistance is associated with reduced serum adiponectin and increased albuminuria levels. Thus, one would anticipate an inverse relationship between circulating adiponectin and albuminuria. However, several studies have described a 'paradoxical' elevation of serum adiponectin in patients with elevated albuminuria. These findings may have been confounded by the presence of diseases and related treatments known to affect circulating adiponectin and albuminuria. We therefore studied the relationship between circulating adiponectin and albuminuria in the absence of such confounders. METHODS To this purpose, the relationship between adiponectin isoforms and albumin:creatinine ratio (ACR) was investigated in a family-based sample of 634 non-diabetic untreated white individuals with normal kidney function. We also investigated whether the two variables share a common genetic background and addressed the specific role of the gene encoding adiponectin on that background by genotyping several ADIPOQ single nucleotide polymorphisms (SNPs). RESULTS ACR was directly associated with high molecular weight (HMW) adiponectin isoform (p = 0.024). The two variables shared some genetic correlation (ρ(g) = 0.38, p = 0.04). ADIPOQ promoter SNP rs17300539 was associated with HMW adiponectin (p = 4.8 × 10(-5)) and ACR (p =0.0027). The genetic correlation between HMW adiponectin and ACR was no longer significant when SNP rs17300539 was added to the model, thus reinforcing the role of this SNP in determining both traits. CONCLUSIONS/INTERPRETATION Our study shows a positive, independent correlation between HWM adiponectin and ACR. ADIPOQ variability is associated with HMW adiponectin and ACR, and explains some of the common genetic background shared by these traits, thus suggesting that ADIPOQ and HMW adiponectin modulate albuminuria levels.
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Affiliation(s)
- C Menzaghi
- Research Unit of Diabetes and Endocrine Disease, IRCCS Casa Sollievo della Sofferenza, Viale Padre Pio, 71013 San Giovanni Rotondo, Italy
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Adiponectin and Resistin Gene Polymorphisms in Association with Their Respective Adipokine Levels. Ann Hum Genet 2011; 75:370-82. [DOI: 10.1111/j.1469-1809.2010.00635.x] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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124
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Monda KL, North KE, Hunt SC, Rao DC, Province MA, Kraja AT. The genetics of obesity and the metabolic syndrome. Endocr Metab Immune Disord Drug Targets 2011; 10:86-108. [PMID: 20406164 DOI: 10.2174/187153010791213100] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2010] [Accepted: 04/04/2010] [Indexed: 12/19/2022]
Abstract
In this review, we discuss the genetic architecture of obesity and the metabolic syndrome, highlighting recent advances in identifying genetic variants and loci responsible for a portion of the variation in components of the metabolic syndrome, namely, adiposity traits, serum HDL and triglycerides, blood pressure, and glycemic traits. We focus particularly on recent progress from large-scale genome-wide association studies (GWAS), by detailing their successes and how lessons learned can pave the way for future discovery. Results from recent GWAS coalesce with earlier work suggesting numerous interconnections between obesity and the metabolic syndrome, developed through several potentially pleiotropic effects. We detail recent work by way of a case study on the cadherin 13 gene and its relation with adiponectin in the HyperGEN and the Framingham Heart Studies, and its association with obesity and the metabolic syndrome. We provide also a gene network analysis of recent variants related to obesity and metabolic syndrome discovered through genome-wide association studies, and 4 gene networks based on searching the NCBI database.
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Affiliation(s)
- Keri L Monda
- Department of Epidemiology, University of North Carolina at Chapel Hill, USA.
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125
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Karg K, Burmeister M, Shedden K, Sen S. The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: evidence of genetic moderation. ACTA ACUST UNITED AC 2011; 68:444-54. [PMID: 21199959 DOI: 10.1001/archgenpsychiatry.2010.189] [Citation(s) in RCA: 932] [Impact Index Per Article: 71.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
CONTEXT Two recent meta-analyses assessed the set of studies exploring the interaction between a serotonin transporter promoter polymorphism (5-HTTLPR) and stress in the development of depression and concluded that the evidence did not support the presence of the interaction. However, even the larger of the meta-analyses included only 14 of the 56 studies that have assessed the relationship between 5-HTTLPR, stress, and depression. OBJECTIVE To perform a meta-analysis including all relevant studies exploring the interaction. DATA SOURCES We identified studies published through November 2009 in PubMed. STUDY SELECTION We excluded 2 studies presenting data that were included in other larger studies. DATA EXTRACTION To perform a more inclusive meta-analysis, we used the Liptak-Stouffer z score method to combine findings of primary studies at the level of significance tests rather than the level of raw data. DATA SYNTHESIS We included 54 studies and found strong evidence that 5-HTTLPR moderates the relationship between stress and depression, with the 5-HTTLPR s allele associated with an increased risk of developing depression under stress (P = .00002). When stratifying our analysis by the type of stressor studied, we found strong evidence for an association between the s allele and increased stress sensitivity in the childhood maltreatment (P = .00007) and the specific medical condition (P = .0004) groups of studies but only marginal evidence for an association in the stressful life events group (P = .03). When restricting our analysis to the studies included in the previous meta-analyses, we found no evidence of association (Munafò et al studies, P = .16; Risch et al studies, P = .11). This suggests that the difference in results between meta-analyses was due to the different set of included studies rather than the meta-analytic technique. CONCLUSION Contrary to the results of the smaller earlier meta-analyses, we find strong evidence that the studies published to date support the hypothesis that 5-HTTLPR moderates the relationship between stress and depression.
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Affiliation(s)
- Katja Karg
- Department of Human Genetics, University of Wuerzburg, Wuerzburg, Germany
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126
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Abstract
Obesity is a major health problem and an immense economic burden on the health care systems both in the United States and the rest of the world. The prevalence of obesity in children and adults in the United States has increased dramatically over the past decade. Besides environmental factors, genetic factors are known to play an important role in the pathogenesis of obesity. Genome-wide association studies (GWAS) have revealed strongly associated genomic variants associated with most common disorders; indeed there is general consensus on these findings from generally positive replication outcomes by independent groups. To date, there have been only a few GWAS-related reports for childhood obesity specifically, with studies primarily uncovering loci in the adult setting instead. It is clear that a number of loci previously reported from GWAS analyses of adult BMI and/or obesity also play a role in childhood obesity.
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Affiliation(s)
- Jianhua Zhao
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Struan F. A. Grant
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia Research Institute, 34th and Civic Center Boulevard, Philadelphia, PA 19104, USA
- *Struan F. A. Grant:
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127
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Shim SM, Kim JH, Jung SE, Kim DJ, Oh JH, Han BG, Jeon JP. Multilaboratory Assessment of Variations in Spectrophotometry-Based DNA Quantity and Purity Indexes. Biopreserv Biobank 2010; 8:187-92. [DOI: 10.1089/bio.2010.0016] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Affiliation(s)
- Sung-Mi Shim
- Division of Biobank for Health Sciences, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Seoul, Korea
| | - Ji-Hyun Kim
- Division of Biobank for Health Sciences, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Seoul, Korea
| | - Seung-Eun Jung
- Division of Biobank for Health Sciences, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Seoul, Korea
| | - Dong-Joon Kim
- Center for Genome Science, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Seoul, Korea
| | - Ji-Hee Oh
- Center for Genome Science, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Seoul, Korea
| | - Bok-Ghee Han
- Center for Genome Science, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Seoul, Korea
| | - Jae-Pil Jeon
- Division of Biobank for Health Sciences, Korea National Institute of Health, Korea Centers for Disease Control and Prevention, Seoul, Korea
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128
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Rodríguez-Rodríguez L, García-Bermúdez M, González-Juanatey C, Vazquez-Rodriguez TR, Miranda-Filloy JA, Fernandez-Gutierrez B, Llorca J, Martin J, González-Gay MA. Lack of association between ADIPOQ rs266729 and ADIPOQ rs1501299 polymorphisms and cardiovascular disease in rheumatoid arthritis patients. ACTA ACUST UNITED AC 2010; 77:74-8. [DOI: 10.1111/j.1399-0039.2010.01580.x] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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129
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Glessner JT, Bradfield JP, Wang K, Takahashi N, Zhang H, Sleiman PM, Mentch FD, Kim CE, Hou C, Thomas KA, Garris ML, Deliard S, Frackelton EC, Otieno FG, Zhao J, Chiavacci RM, Li M, Buxbaum JD, Berkowitz RI, Hakonarson H, Grant SF. A genome-wide study reveals copy number variants exclusive to childhood obesity cases. Am J Hum Genet 2010; 87:661-6. [PMID: 20950786 PMCID: PMC2978976 DOI: 10.1016/j.ajhg.2010.09.014] [Citation(s) in RCA: 85] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2010] [Revised: 09/10/2010] [Accepted: 09/24/2010] [Indexed: 01/06/2023] Open
Abstract
The prevalence of obesity in children and adults in the United States has increased dramatically over the past decade. Genomic copy number variations (CNVs) have been strongly implicated in subjects with extreme obesity and coexisting developmental delay. To complement these previous studies, we addressed CNVs in common childhood obesity by examining children with a BMI in the upper 5(th) percentile but excluding any subject greater than three standard deviations from the mean in order to reduce severe cases in the cohort. We performed a whole-genome CNV survey of our cohort of 1080 defined European American (EA) childhood obesity cases and 2500 lean controls (< 50(th) percentile BMI) who were genotyped with 550,000 SNP markers. Positive findings were evaluated in an independent African American (AA) cohort of 1479 childhood obesity cases and 1575 lean controls. We identified 17 CNV loci that were unique to at least three EA cases and were both previously unreported in the public domain and validated via quantitative PCR. Eight of these loci (47.1%) also replicated exclusively in AA cases (six deletions and two duplications). Replicated deletion loci consisted of EDIL3, S1PR5, FOXP2, TBCA, ABCB5, and ZPLD1, whereas replicated duplication loci consisted of KIF2B and ARL15. We also observed evidence for a deletion at the EPHA6-UNQ6114 locus when the AA cohort was investigated as a discovery set. Although these variants may be individually rare, our results indicate that CNVs contribute to the genetic susceptibility of common childhood obesity in subjects of both European and African ancestry.
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Affiliation(s)
- Joseph T. Glessner
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Jonathan P. Bradfield
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kai Wang
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Nagahide Takahashi
- Laboratory of Molecular Neuropsychiatry, Department of Psychiatry, Mount Sinai School of Medicine, New York, NY 10029 USA
| | - Haitao Zhang
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Patrick M. Sleiman
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Frank D. Mentch
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Cecilia E. Kim
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Cuiping Hou
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kelly A. Thomas
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Maria L. Garris
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Sandra Deliard
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Edward C. Frackelton
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - F. George Otieno
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Jianhua Zhao
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Rosetta M. Chiavacci
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Mingyao Li
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Joseph D. Buxbaum
- Laboratory of Molecular Neuropsychiatry, Department of Psychiatry, Mount Sinai School of Medicine, New York, NY 10029 USA
| | - Robert I. Berkowitz
- Behavioral Health Center and Department of Child and Adolescent Psychiatry, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Center for Weight and Eating Disorders, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Laboratory of Molecular Neuropsychiatry, Department of Psychiatry, Mount Sinai School of Medicine, New York, NY 10029 USA
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Struan F.A. Grant
- Center for Applied Genomics, Abramson Research Center, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Laboratory of Molecular Neuropsychiatry, Department of Psychiatry, Mount Sinai School of Medicine, New York, NY 10029 USA
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
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130
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Jee SH, Sull JW, Lee JE, Shin C, Park J, Kimm H, Cho EY, Shin ES, Yun JE, Park JW, Kim SY, Lee SJ, Jee EJ, Baik I, Kao L, Yoon SK, Jang Y, Beaty TH. Adiponectin concentrations: a genome-wide association study. Am J Hum Genet 2010; 87:545-52. [PMID: 20887962 PMCID: PMC2948810 DOI: 10.1016/j.ajhg.2010.09.004] [Citation(s) in RCA: 127] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2010] [Revised: 08/18/2010] [Accepted: 09/08/2010] [Indexed: 12/31/2022] Open
Abstract
Adiponectin is associated with obesity and insulin resistance. To date, there has been no genome-wide association study (GWAS) of adiponectin levels in Asians. Here we present a GWAS of a cohort of Korean volunteers. A total of 4,001 subjects were genotyped by using a genome-wide marker panel in a two-stage design (979 subjects initially and 3,022 in a second stage). Another 2,304 subjects were used for follow-up replication studies with selected markers. In the discovery phase, the top SNP associated with mean log adiponectin was rs3865188 in CDH13 on chromosome 16 (p = 1.69 × 10(-15) in the initial sample, p = 6.58 × 10(-39) in the second genome-wide sample, and p = 2.12 × 10(-32) in the replication sample). The meta-analysis p value for rs3865188 in all 6,305 individuals was 2.82 × 10(-83). The association of rs3865188 with high-molecular-weight adiponectin (p = 7.36 × 10(-58)) was even stronger in the third sample. A reporter assay that evaluated the effects of a CDH13 promoter SNP in complete linkage disequilibrium with rs3865188 revealed that the major allele increased expression 2.2-fold. This study clearly shows that genetic variants in CDH13 influence adiponectin levels in Korean adults.
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Affiliation(s)
- Sun Ha Jee
- Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul 102-752, South Korea
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Jae Woong Sull
- Department of Biomedical Laboratory Science, College of Health Sciences, Eulji University, Seongnam 461-713, South Korea
| | | | - Chol Shin
- Department of Internal Medicine, Korea University Ansan Hospital, Ansan 425-707, South Korea
| | - Jongkeun Park
- Research Institute of Molecular Genetics, The Catholic University of Korea, Seoul 137-701, South Korea
- Department of Biomedical Sciences, The Catholic University of Korea, Seoul 137-701, South Korea
| | - Heejin Kimm
- Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul 102-752, South Korea
| | | | | | - Ji Eun Yun
- Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul 102-752, South Korea
| | - Ji Wan Park
- Department of Medical Genetics, College of Medicine, Hallym University, Chuncheon 200-702, South Korea
| | - Sang Yeun Kim
- Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul 102-752, South Korea
| | - Sun Ju Lee
- Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul 102-752, South Korea
| | - Eun Jung Jee
- Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul 102-752, South Korea
| | - Inkyung Baik
- Department of Foods and Nutrition, College of Natural Sciences, Kookmin University, Seoul 136-702, South Korea
| | - Linda Kao
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Sungjoo Kim Yoon
- Research Institute of Molecular Genetics, The Catholic University of Korea, Seoul 137-701, South Korea
- Department of Biomedical Sciences, The Catholic University of Korea, Seoul 137-701, South Korea
| | - Yangsoo Jang
- Cardiology Division and Cardiovascular Research Institute, Yonsei University College of Medicine, Seoul 102-752, South Korea
| | - Terri H. Beaty
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
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Wu Y, Li Y, Lange EM, Croteau-Chonka DC, Kuzawa CW, McDade TW, Qin L, Curocichin G, Borja JB, Lange LA, Adair LS, Mohlke KL. Genome-wide association study for adiponectin levels in Filipino women identifies CDH13 and a novel uncommon haplotype at KNG1-ADIPOQ. Hum Mol Genet 2010; 19:4955-64. [PMID: 20876611 DOI: 10.1093/hmg/ddq423] [Citation(s) in RCA: 88] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Adiponectin is an adipocyte-secreted protein involved in a variety of metabolic processes, including glucose regulation and fatty acid catabolism. We conducted a genome-wide association study to investigate the genetic loci associated with plasma adiponectin in 1776 unrelated Filipino women from the Cebu Longitudinal Health and Nutrition Survey (CLHNS). Our strongest signal for adiponectin mapped to the gene CDH13 (rs3865188, P ≤ 7.2 × 10(-16)), which encodes a receptor for high-molecular-weight forms of adiponectin. Strong association was also detected near the ADIPOQ gene (rs864265, P = 3.8 × 10(-9)) and at a novel signal 100 kb upstream near KNG1 (rs11924390, P = 7.6 × 10(-7)). All three signals were also observed in 1774 young adult CLHNS offspring and in combined analysis including all 3550 mothers and offspring samples (all P ≤ 1.6 × 10(-9)). An uncommon haplotype of rs11924390 and rs864265 (haplotype frequency = 0.050) was strongly associated with lower adiponectin compared with the most common C-G haplotype in both CLHNS mothers (P = 1.8 × 10(-25)) and offspring (P = 8.7 × 10(-32)). Comprehensive imputation of 2653 SNPs in a 2 Mb region using as reference combined CHB, JPT and CEU haplotypes from the 1000 Genomes Project revealed no variants that perfectly tagged this haplotype. Our findings provide the first genome-wide significant evidence of association with plasma adiponectin at the CDH13 locus and identify a novel uncommon KNG1-ADIPOQ haplotype strongly associated with adiponectin levels in Filipinos.
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Affiliation(s)
- Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599-7264, USA
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Bowden DW, An SS, Palmer ND, Brown WM, Norris JM, Haffner SM, Hawkins GA, Guo X, Rotter JI, Chen YDI, Wagenknecht LE, Langefeld CD. Molecular basis of a linkage peak: exome sequencing and family-based analysis identify a rare genetic variant in the ADIPOQ gene in the IRAS Family Study. Hum Mol Genet 2010; 19:4112-20. [PMID: 20688759 DOI: 10.1093/hmg/ddq327] [Citation(s) in RCA: 75] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Family-based linkage analysis has been a powerful tool for identification of genes contributing to traits with monogenic patterns of inheritance. These approaches have been of limited utility in identification of genes underlying complex traits. In contrast, searches for common genetic variants associated with complex traits have been highly successful. It is now widely recognized that common variations frequently explain only part of the inter-individual variation in populations. 'Rare' genetic variants have been hypothesized to contribute significantly to phenotypic variation in the population. We have developed a combination of family-based linkage, whole-exome sequencing, direct sequencing and association methods to efficiently identify rare variants of large effect. Key to the successful application of the method was the recognition that only a few families in a sample contribute significantly to a linkage signal. Thus, a search for mutations can be targeted to a small number of families in a chromosome interval restricted to the linkage peak. This approach has been used to identify a rare (1.1%) G45R mutation in the gene encoding adiponectin, ADIPOQ. This variant explains a strong linkage signal (LOD > 8.0) and accounts for ∼17% of the variance in plasma adiponectin levels in a sample of 1240 Hispanic Americans and 63% of the variance in families carrying the mutation. Individuals carrying the G45R mutation have mean adiponectin levels that are 19% of non-carriers. We propose that rare variants may be a common explanation for linkage peaks observed in complex trait genetics. This approach is applicable to a wide range of family studies and has potential to be a discovery tool for identification of novel genes influencing complex traits.
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Affiliation(s)
- Donald W Bowden
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA.
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Increased cardiometabolic traits in pediatric survivors of acute lymphoblastic leukemia treated with total body irradiation. Biol Blood Marrow Transplant 2010; 16:1674-81. [PMID: 20685399 DOI: 10.1016/j.bbmt.2010.05.016] [Citation(s) in RCA: 80] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2010] [Accepted: 05/24/2010] [Indexed: 11/22/2022]
Abstract
Survivors of childhood acute lymphoblastic leukemia (ALL) may face an increased risk of metabolic and cardiovascular late effects. To determine the prevalence of and risk factors for adverse cardiometabolic traits in a contemporary cohort of pediatric ALL survivors, we recruited 48 off-therapy patients in remission treated with conventional chemotherapy and 26 treated with total body irradiation (TBI)-based hematopoietic cell transplantation (HCT) in this cross-sectional pilot study. At a median age of 15 years (range, 8-21 years), HCT survivors were significantly more likely than non-HCT survivors to manifest multiple cardiometabolic traits, including central adiposity, hypertension, insulin resistance, and dyslipidemia. Overall, 23.1% of HCT survivors met the criteria for metabolic syndrome (≥ 3 traits), compared with 4.2% of non-HCT survivors (P = .02). HCT survivors also had increased C-reactive protein and leptin levels and decreased adiponectin, suggestive of underlying inflammation and increased visceral fat. In multivariate analyses, history of HCT remained associated with ≥ 2 traits (odds ratio [OR]. 5.13; 95% confidence interval [CI], 1.54-17.15) as well as with ≥ 3 traits (OR, 16.72; 95% CI, 1.66-168.80). Other risk factors included any cranial radiation exposure and family history of cardiometabolic disease. In summary, pediatric ALL survivors exposed to TBI-based HCT as well as to any cranial radiation may manifest cardiometabolic traits at an early age and should be screened accordingly.
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Abstract
CONTEXT Adiponectin is a highly abundant plasma protein synthesized nearly exclusively in adipose tissue from the ADIPOQ gene. It has excited intense interest because of robust correlation of its circulating levels with indices of insulin resistance (IR) and risk of type 2 diabetes, and their unusual inverse relationship with fat mass. It has been suggested that pharmacological strategies aimed at augmenting adiponectin levels or action may generate novel insulin-sensitizing drugs. EVIDENCE ACQUISITION Relevant publications were identified by searching PubMed, with secondary searches of their bibliographies. EVIDENCE SYNTHESIS Rodent studies suggest that adiponectin exerts a direct insulin-sensitizing effect on the liver, consistent with a role in the pathogenesis of prevalent forms of IR and its sequelae. However, the complex higher-order structure of adiponectin and inconsistent reports regarding its putative receptors have complicated efforts to understand the mechanistic basis of this. No proof yet exists that adiponectin modulates insulin sensitivity in humans, and genetic, biochemical, and physiological evidence suggests that low adiponectin levels may be a consequence of IR with compensatory hyperinsulinemia. This suggests that there may be a bidirectional relationship between IR and hypoadiponectinemia in humans. CONCLUSIONS The relationship between adiponectin and insulin action in humans is more complex than often suggested. Further investigation of the direction of causality in this relationship, allied to studies of the cellular mechanisms involved, will be central to improving understanding of the physiological role of this enigmatic protein, and to efforts to exploit it for therapeutic benefit.
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Affiliation(s)
- Joshua R Cook
- University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Hills Road, Cambridge CB2 OQQ, United Kingdom
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