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Chen X, Maldonado E, DeFronzo RA, Tripathy D. Impaired Suppression of Glucagon in Obese Subjects Parallels Decline in Insulin Sensitivity and Beta-Cell Function. J Clin Endocrinol Metab 2021; 106:1398-1409. [PMID: 33524152 PMCID: PMC8063259 DOI: 10.1210/clinem/dgab019] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Indexed: 12/23/2022]
Abstract
AIM To examine the relationship between plasma glucagon levels and insulin sensitivity and insulin secretion in obese subjects. METHODS Suppression of plasma glucagon was examined in 275 obese Hispanic Americans with varying glucose tolerance. All subjects received a 2-hour oral glucose tolerance test (OGTT) and a subset (n = 90) had euglycemic hyperinsulinemic clamp. During OGTT, we quantitated suppression of plasma glucagon concentration, Matsuda index of insulin sensitivity, and insulin secretion/insulin resistance (disposition) index. Plasma glucagon suppression was compared between quartiles of insulin sensitivity and beta-cell function. RESULTS Fasting plasma glucagon levels were similar in obese subjects with normal glucose tolerance (NGT), prediabetes, and type 2 diabetes (T2D), but the fasting glucagon/insulin ratio decreased progressively from NGT to prediabetes to T2D (9.28 ± 0.66 vs 6.84 ± 0.44 vs 5.84 ± 0.43; P < 0.001). Fasting and 2-hour plasma glucagon levels during OGTT progressively increased and correlated positively with severity of insulin resistance (both Matsuda index and euglycemic hyperinsulinemic clamp). The fasting glucagon/insulin ratio declined with worsening insulin sensitivity and beta-cell function, and correlated with whole-body insulin sensitivity (Matsuda index, r = 0.81; P < 0.001) and beta-cell function (r = 0.35; P < 0.001). The glucagon/insulin ratio also correlated and with beta-cell function during OGTT at 60 and 120 minutes (r = -0.47; P < 0.001 and r = -0.32; P < 0.001). CONCLUSION Insulin-mediated suppression of glucagon secretion in obese subjects is impaired with increasing severity of glucose intolerance and parallels the severity of insulin resistance and beta-cell dysfunction.
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Affiliation(s)
- Xi Chen
- Department of Medicine, Diabetes Division, University of Texas Health Science Center, San Antonio, TX, USA
| | - Enrique Maldonado
- Department of Medicine, Diabetes Division, University of Texas Health Science Center, San Antonio, TX, USA
| | - Ralph A DeFronzo
- Department of Medicine, Diabetes Division, University of Texas Health Science Center, San Antonio, TX, USA
- Audie L Murphy VA Hospital, South Texas Veterans Health Care System, San Antonio, TX, USA
| | - Devjit Tripathy
- Department of Medicine, Diabetes Division, University of Texas Health Science Center, San Antonio, TX, USA
- Audie L Murphy VA Hospital, South Texas Veterans Health Care System, San Antonio, TX, USA
- Correspondence: Devjit Tripathy, MD, PhD, Division of Diabetes, University of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA.
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Peralta JM, Blackburn NB, Porto A, Blangero J, Charlesworth J. Genome-wide linkage scan for loci influencing plasma triglyceride levels. BMC Proc 2018; 12:52. [PMID: 30275898 PMCID: PMC6157192 DOI: 10.1186/s12919-018-0137-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
We conducted a genome-wide linkage scan to detect loci that influence the levels of fasting triglycerides in plasma. Fasting triglyceride levels were available at 4 time points (visits), 2 pre- and 2 post-fenofibrate intervention. Multipoint identity-by-descent (MIBD) matrices were derived from genotypes using IBDLD. Variance-component linkage analyses were then conducted using SOLAR (Sequential Oligogenic Linkage Analysis Routines). We found evidence of linkage (logarithm of odds [LOD] ≥3) at 5 chromosomal regions with triglyceride levels in plasma. The highest LOD scores were observed for linkage to the estimated genetic value (additive genetic component) of the log-normalized triglyceride levels in plasma. Our results suggest that a chromosome 10 locus at 37 cM (LODpre = 3.01, LODpost = 3.72) influences fasting triglyceride levels in plasma regardless of the fenofibrate intervention, and that loci in chromosomes 1 at 170 cM and 4 at 24 cM ceases to affect the triglyceride levels when fenofibrate is present, while the regions in chromosomes 6 at 136 to 162 cM and 11 at 39 to 40 cM appear to influence triglyceride levels in response to fenofibrate.
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Affiliation(s)
- Juan M. Peralta
- South Texas Diabetes and Obesity Institute, University of Texas at the Rio Grande Valley, One West University Blvd, Brownsville, TX 78520 USA
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, TAS 7000 Australia
| | - Nicholas B. Blackburn
- South Texas Diabetes and Obesity Institute, University of Texas at the Rio Grande Valley, One West University Blvd, Brownsville, TX 78520 USA
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, TAS 7000 Australia
| | - Arthur Porto
- South Texas Diabetes and Obesity Institute, University of Texas at the Rio Grande Valley, One West University Blvd, Brownsville, TX 78520 USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas at the Rio Grande Valley, One West University Blvd, Brownsville, TX 78520 USA
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, TAS 7000 Australia
| | - Jac Charlesworth
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, TAS 7000 Australia
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3
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Wang WC, Chiu YF, Chung RH, Hwu CM, Lee IT, Lee CH, Chang YC, Hung KY, Quertermous T, Chen YDI, Hsiung CA. IGF1 Gene Is Associated With Triglyceride Levels In Subjects With Family History Of Hypertension From The SAPPHIRe And TWB Projects. Int J Med Sci 2018; 15:1035-1042. [PMID: 30013445 PMCID: PMC6036157 DOI: 10.7150/ijms.25742] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Accepted: 05/14/2018] [Indexed: 12/22/2022] Open
Abstract
Chromosome 12q23-q24 has been linked to triglyceride (TG) levels by previous linkage studies, and it contains the Insulin-like growth factor 1 (IGF1) gene. We investigated the association between IGF1 and TG levels using two independent samples collected in Taiwan. First, based on 954 siblings in 397 families from the Stanford Asian Pacific Program in Hypertension and Insulin Resistance (SAPPHIRe), we found that rs978458 was associated with TG levels (β = -0.049, p = 0.0043) under a recessive genetic model. Specifically, subjects carrying the homozygous genotype of the minor allele had lower TG levels, compared with other subjects. Then, a series of stratification analyses in a large sample of 13,193 unrelated subjects from the Taiwan biobank (TWB) project showed that this association appeared in subjects with a family history (FH) of hypertension (β = -0.045, p = 0.0000034), but not in subjects without such an FH. A re-examination of the SAPPHIRe sample confirmed that this association appeared in subjects with an FH of hypertension (β = -0.068, p = 0.0025), but not in subjects without an FH. The successful replication in two independent samples indicated that IGF1 is associated with TG levels in subjects with an FH of hypertension in Taiwan.
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Affiliation(s)
- Wen-Chang Wang
- The Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
| | - Yen-Feng Chiu
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
| | - Ren-Hua Chung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- Faculty of Medicine, National Yang-Ming University School of medicine, Taipei, Taiwan
| | - I-Te Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Chien-Hsing Lee
- Division of Endocrine and Metabolism, Tri-Service General Hospital, Taipei, Taiwan
- Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan
| | - Yi-Cheng Chang
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University, Taiwan
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Institute of Biomedical Science, Academia Sinica, Taipei, Taiwan
| | - Kuan-Yi Hung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
| | - Thomas Quertermous
- Division of Cardiovascular Medicine, Falk Cardiovascular Research Building, Stanford University School of Medicine, Stanford, CA, USA
| | - Yii-Der I. Chen
- Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Chao A. Hsiung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
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4
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Mercader JM, Liao RG, Bell AD, Dymek Z, Estrada K, Tukiainen T, Huerta-Chagoya A, Moreno-Macías H, Jablonski KA, Hanson RL, Walford GA, Moran I, Chen L, Agarwala V, Ordoñez-Sánchez ML, Rodríguez-Guillen R, Rodríguez-Torres M, Segura-Kato Y, García-Ortiz H, Centeno-Cruz F, Barajas-Olmos F, Caulkins L, Puppala S, Fontanillas P, Williams AL, Bonàs-Guarch S, Hartl C, Ripke S, Tooley K, Lane J, Zerrweck C, Martínez-Hernández A, Córdova EJ, Mendoza-Caamal E, Contreras-Cubas C, González-Villalpando ME, Cruz-Bautista I, Muñoz-Hernández L, Gómez-Velasco D, Alvirde U, Henderson BE, Wilkens LR, Le Marchand L, Arellano-Campos O, Riba L, Harden M, Gabriel S, Abboud HE, Cortes ML, Revilla-Monsalve C, Islas-Andrade S, Soberon X, Curran JE, Jenkinson CP, DeFronzo RA, Lehman DM, Hanis CL, Bell GI, Boehnke M, Blangero J, Duggirala R, Saxena R, MacArthur D, Ferrer J, McCarroll SA, Torrents D, Knowler WC, Baier LJ, Burtt N, González-Villalpando C, Haiman CA, Aguilar-Salinas CA, Tusié-Luna T, Flannick J, Jacobs SBR, Orozco L, Altshuler D, Florez JC. A Loss-of-Function Splice Acceptor Variant in IGF2 Is Protective for Type 2 Diabetes. Diabetes 2017; 66:2903-2914. [PMID: 28838971 PMCID: PMC5652606 DOI: 10.2337/db17-0187] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Accepted: 08/13/2017] [Indexed: 12/12/2022]
Abstract
Type 2 diabetes (T2D) affects more than 415 million people worldwide, and its costs to the health care system continue to rise. To identify common or rare genetic variation with potential therapeutic implications for T2D, we analyzed and replicated genome-wide protein coding variation in a total of 8,227 individuals with T2D and 12,966 individuals without T2D of Latino descent. We identified a novel genetic variant in the IGF2 gene associated with ∼20% reduced risk for T2D. This variant, which has an allele frequency of 17% in the Mexican population but is rare in Europe, prevents splicing between IGF2 exons 1 and 2. We show in vitro and in human liver and adipose tissue that the variant is associated with a specific, allele-dosage-dependent reduction in the expression of IGF2 isoform 2. In individuals who do not carry the protective allele, expression of IGF2 isoform 2 in adipose is positively correlated with both incidence of T2D and increased plasma glycated hemoglobin in individuals without T2D, providing support that the protective effects are mediated by reductions in IGF2 isoform 2. Broad phenotypic examination of carriers of the protective variant revealed no association with other disease states or impaired reproductive health. These findings suggest that reducing IGF2 isoform 2 expression in relevant tissues has potential as a new therapeutic strategy for T2D, even beyond the Latin American population, with no major adverse effects on health or reproduction.
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Affiliation(s)
- Josep M Mercader
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Barcelona Supercomputing Center, Joint BSC-CRG-IRB Research Programme in Computational Biology, Barcelona, Spain
| | - Rachel G Liao
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Avery D Bell
- Department of Genetics, Harvard Medical School, Boston, MA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Zachary Dymek
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Karol Estrada
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Taru Tukiainen
- Department of Genetics, Harvard Medical School, Boston, MA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA
| | - Alicia Huerta-Chagoya
- Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Hortensia Moreno-Macías
- Unidad de Biología Molecular y Medicina Genómica, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México/Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
- Universidad Autónoma Metropolitana, Mexico City, Mexico
| | | | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Geoffrey A Walford
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Ignasi Moran
- Department of Medicine, Imperial College London, London, U.K
| | - Ling Chen
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Vineeta Agarwala
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - María Luisa Ordoñez-Sánchez
- Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Rosario Rodríguez-Guillen
- Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Maribel Rodríguez-Torres
- Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Yayoi Segura-Kato
- Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | | | | | | | - Lizz Caulkins
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Sobha Puppala
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX
| | - Pierre Fontanillas
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Amy L Williams
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY
| | - Sílvia Bonàs-Guarch
- Barcelona Supercomputing Center, Joint BSC-CRG-IRB Research Programme in Computational Biology, Barcelona, Spain
| | - Chris Hartl
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Stephan Ripke
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Katherine Tooley
- Department of Genetics, Harvard Medical School, Boston, MA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Jacqueline Lane
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Carlos Zerrweck
- Clínica Integral de Cirugía para la Obesidad y Enfermedades Metabólicas, Hospital General Tláhuac, Mexico City, Mexico
| | | | | | | | | | - María E González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Pública, Mexico City, Mexico
| | - Ivette Cruz-Bautista
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Liliana Muñoz-Hernández
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Donaji Gómez-Velasco
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Ulises Alvirde
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Brian E Henderson
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Lynne R Wilkens
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI
| | - Loic Le Marchand
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI
| | - Olimpia Arellano-Campos
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Laura Riba
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Maegan Harden
- The Genomics Platform, Broad Institute, Cambridge, MA
| | | | - Hanna E Abboud
- Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | | | - Cristina Revilla-Monsalve
- Unidad de Investigación Médica en Enfermedades Metabólicas, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Sergio Islas-Andrade
- Unidad de Investigación Médica en Enfermedades Metabólicas, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Xavier Soberon
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Joanne E Curran
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX
| | - Christopher P Jenkinson
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX
| | - Ralph A DeFronzo
- Division of Diabetes, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Donna M Lehman
- Departments of Medicine and Cellular & Structural Biology, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Craig L Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Graeme I Bell
- Department of Medicine, The University of Chicago, Chicago, IL
- Department of Human Genetics, The University of Chicago, Chicago, IL
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI
| | - John Blangero
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX
| | - Ravindranath Duggirala
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Edinburg, TX
| | - Richa Saxena
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Daniel MacArthur
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Jorge Ferrer
- Department of Medicine, Imperial College London, London, U.K
- Genomic Programming of Beta Cells and Diabetes, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
- CIBERDEM, Barcelona, Spain
| | - Steven A McCarroll
- Department of Genetics, Harvard Medical School, Boston, MA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - David Torrents
- Barcelona Supercomputing Center, Joint BSC-CRG-IRB Research Programme in Computational Biology, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
| | - William C Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ
| | - Noel Burtt
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Clicerio González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Pública, Mexico City, Mexico
| | | | - Carlos A Aguilar-Salinas
- Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Teresa Tusié-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México/Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Jason Flannick
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Molecular Biology, Harvard Medical School, Boston, MA
| | - Suzanne B R Jacobs
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - David Altshuler
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Genetics, Harvard Medical School, Boston, MA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Molecular Biology, Harvard Medical School, Boston, MA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA
| | - Jose C Florez
- Broad Metabolism Program and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
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5
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Blangero J, Teslovich TM, Sim X, Almeida MA, Jun G, Dyer TD, Johnson M, Peralta JM, Manning A, Wood AR, Fuchsberger C, Kent JW, Aguilar DA, Below JE, Farook VS, Arya R, Fowler S, Blackwell TW, Puppala S, Kumar S, Glahn DC, Moses EK, Curran JE, Thameem F, Jenkinson CP, DeFronzo RA, Lehman DM, Hanis C, Abecasis G, Boehnke M, Göring H, Duggirala R, Almasy L. Omics-squared: human genomic, transcriptomic and phenotypic data for genetic analysis workshop 19. BMC Proc 2016; 10:71-77. [PMID: 27980614 PMCID: PMC5133484 DOI: 10.1186/s12919-016-0008-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Background The Genetic Analysis Workshops (GAW) are a forum for development, testing, and comparison of statistical genetic methods and software. Each contribution to the workshop includes an application to a specified data set. Here we describe the data distributed for GAW19, which focused on analysis of human genomic and transcriptomic data. Methods GAW19 data were donated by the T2D-GENES Consortium and the San Antonio Family Heart Study and included whole genome and exome sequences for odd-numbered autosomes, measures of gene expression, systolic and diastolic blood pressures, and related covariates in two Mexican American samples. These two samples were a collection of 20 large families with whole genome sequence and transcriptomic data and a set of 1943 unrelated individuals with exome sequence. For each sample, simulated phenotypes were constructed based on the real sequence data. ‘Functional’ genes and variants for the simulations were chosen based on observed correlations between gene expression and blood pressure. The simulations focused primarily on additive genetic models but also included a genotype-by-medication interaction. A total of 245 genes were designated as ‘functional’ in the simulations with a few genes of large effect and most genes explaining < 1 % of the trait variation. An additional phenotype, Q1, was simulated to be correlated among related individuals, based on theoretical or empirical kinship matrices, but was not associated with any sequence variants. Two hundred replicates of the phenotypes were simulated. The GAW19 data are an expansion of the data used at GAW18, which included the family-based whole genome sequence, blood pressure, and simulated phenotypes, but not the gene expression data or the set of 1943 unrelated individuals with exome sequence.
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Affiliation(s)
- John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Tanya M Teslovich
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Xueling Sim
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Marcio A Almeida
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Goo Jun
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA ; Department of Epidemiology, Human Genetics and Environmenal Sciences, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Thomas D Dyer
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Matthew Johnson
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Juan M Peralta
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Alisa Manning
- Department of Genetics, Massachusetts General Hospital, Boston, MA 02114 USA
| | - Andrew R Wood
- Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK
| | - Christian Fuchsberger
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Jack W Kent
- Department of Genetics, Texas Biomedical Research Institute, 7620 NW Loop 410, San Antonio, TX 78227 USA
| | - David A Aguilar
- Cardiovascular Division, Baylor College of Medicine, Houston, TX 77030 USA
| | - Jennifer E Below
- Department of Epidemiology, Human Genetics and Environmenal Sciences, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Vidya S Farook
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Rector Arya
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Sharon Fowler
- Division of Clinical Epidemiology, Department of Medicine, University of San Antonio Health Science Center at San Antonio, San Antonio, TX 78229 USA
| | - Tom W Blackwell
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Sobha Puppala
- Department of Genetics, Texas Biomedical Research Institute, 7620 NW Loop 410, San Antonio, TX 78227 USA
| | - Satish Kumar
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - David C Glahn
- Department of Psychiatry, Yale University, New Haven, CT 06106 USA
| | - Eric K Moses
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Australia
| | - Joanne E Curran
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Farook Thameem
- Department of Biochemistry, Faculty of Medicine, Kuwait University, Safat, Kuwait City, 13110 Kuwait
| | - Christopher P Jenkinson
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Ralph A DeFronzo
- Texas Diabetes Institute, University of San Antonio Health Science Center at San Antonio, San Antonio, TX 78229 USA
| | - Donna M Lehman
- Division of Clinical Epidemiology, Department of Medicine, University of San Antonio Health Science Center at San Antonio, San Antonio, TX 78229 USA
| | - Craig Hanis
- Department of Epidemiology, Human Genetics and Environmenal Sciences, University of Texas Health Science Center at Houston, Houston, TX 77030 USA
| | - Goncalo Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Harald Göring
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Ravindranath Duggirala
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA
| | - Laura Almasy
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Harlingen, TX 78550 USA ; Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104 USA
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Tayo BO, Tong L, Cooper RS. Association of polymorphisms in the aldosterone-regulated sodium reabsorption pathway with blood pressure among Hispanics. BMC Proc 2016; 10:343-348. [PMID: 27980660 PMCID: PMC5133472 DOI: 10.1186/s12919-016-0054-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Whereas genome-wide association study (GWAS) has proven to be an important tool for discovery of variants influencing many human diseases and traits, unfortunately its performance has not been much of all-around success for some complex conditions, for example, hypertension. Because some of the existing effective pharmacotherapeutic agents act by targeting known biological pathways, pathway-based analytical approaches could lead to more success in discovery of disease-associated variants. The objective of the present study was to identify functional variants associated with blood pressure in the aldosterone-regulated sodium reabsorption pathway using the simulated and real blood pressure phenotypes provided for Genetic Analysis Workshop 19. METHODS The present analysis included 1942 samples with exome sequencing data and for whom blood pressure phenotypes were available. Because only odd-numbered autosomes were available, we restricted analysis to 127 quality-controlled single-nucleotide polymorphisms from the aldosterone-regulated sodium reabsorption pathway. We performed pathway-based association analysis using appropriate regression models for single variant, haplotype and epistasis association analyses. To account for multiple comparisons, statistical significance was empirically derived by permutation procedure and Bonferroni correction. RESULTS The topmost pathway-based association signals were observed in PRKCA gene for diastolic blood pressure (DBP), systolic blood pressure (SBP), and mean arterial pressure (MAP) in both real and simulated data. The associations remained significant (P <0.05) after multiple testing corrections for the number of genes. Similarly, the pathway-based 2-locus epistasis analysis indicated significant interactions between INSR and PRKCG for SBP and MAP; INS and PIK3R2 for DBP; PIK3CD and ATP1B2 for hypertension in the real data set. We also observed significant within-gene interactions in INSR for SBP, DBP, and hypertension in the simulated data set. CONCLUSION The findings from this study show that pathway-based analytical approach targeting known biological pathways can be useful in identification of disease-associated variants that are otherwise undetectable by GWAS. The approach takes advantage of the assumption of nonindependence of variants within and across pathway genes which leads to reduced penalty of multiple testing and thus less-stringent statistical significance threshold.
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Affiliation(s)
- Bamidele O. Tayo
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153 USA
| | - Liping Tong
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153 USA
| | - Richard S. Cooper
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153 USA
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Abstract
Although disproportionately affected by increasing rates of type 2 diabetes and dyslipidemias, Hispanic populations are underrepresented in efforts to understand genetic susceptibility to these disorders. Where research has been undertaken, these populations have provided substantial insight into identification of novel risk-associated genes and have aided in the ability to fine map previously described risk loci. Genome-wide analyses in Hispanic and trans-ethnic populations have resulted in identification of more than 40 replicated or novel genes with significant effects for type 2 diabetes or lipid traits. Initial investigations into rare variant effects have identified new risk-associated variants private to Hispanic populations, and preliminary results suggest metagenomic approaches in Hispanic populations, such as characterizing the gut microbiome, will enable the development of new predictive tools and therapeutic targets for type 2 diabetes. Future genome-wide studies in expanded cohorts of Hispanics are likely to result in new insights into the genetic etiology of metabolic health.
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Affiliation(s)
- Jennifer E Below
- The Human Genetics Center, University of Texas School of Public Health, Houston, TX, USA.
| | - Esteban J Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada
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Yamauchi T, Iwabu M, Okada-Iwabu M, Kadowaki T. Adiponectin receptors: a review of their structure, function and how they work. Best Pract Res Clin Endocrinol Metab 2014; 28:15-23. [PMID: 24417942 DOI: 10.1016/j.beem.2013.09.003] [Citation(s) in RCA: 241] [Impact Index Per Article: 21.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The discovery of adiponectin and subsequently the receptors it acts upon have lead to a great surge forward in the understanding of the development of insulin resistance and obesity-linked diseases. Adiponectin is a hormone that is derived from adipose tissue and is reduced in obesity-linked diseases including insulin resistance/type 2 diabetes and atherosclerosis. Adiponectin exerts its effects by binding to adiponectin receptors, two of which, AdipoR1 and AdipoR2, have been cloned. This has enabled researchers to carry out detailed studies elucidating the role played by these receptors and the metabolic pathways that are involved following their activation. Such studies have clearly shown that the stimulation of these receptors is associated with glucose homeostasis and ongoing research into their role will clarify the underlying molecular mechanisms of adiponectin. Such knowledge can then be used to provide therapeutic targets aimed at managing obesity-linked diseases including type 2 diabetes and metabolic syndrome.
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Affiliation(s)
- Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
| | - Masato Iwabu
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
| | - Miki Okada-Iwabu
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
| | - Takashi Kadowaki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
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10
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Farook VS, Coletta DK, Puppala S, Schneider J, Chittoor G, Hu SL, Winnier DA, Norton L, Dyer TD, Arya R, Cole SA, Carless M, Göring HH, Almasy L, Mahaney MC, Comuzzie AG, Curran JE, Blangero J, Duggirala R, Lehman DM, Jenkinson CP, Defronzo RA. Linkage of type 2 diabetes on chromosome 9p24 in Mexican Americans: additional evidence from the Veterans Administration Genetic Epidemiology Study (VAGES). Hum Hered 2013; 76:36-46. [PMID: 24060607 DOI: 10.1159/000354849] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2011] [Accepted: 08/02/2013] [Indexed: 01/21/2023] Open
Abstract
OBJECTIVE Type 2 diabetes (T2DM) is a complex metabolic disease and is more prevalent in certain ethnic groups such as the Mexican Americans. The goal of our study was to perform a genome-wide linkage (GWL) analysis to localize T2DM susceptibility loci in Mexican Americans. METHODS We used the phenotypic and genotypic data from 1,122 Mexican-American individuals (307 families) who participated in the Veterans Administration Genetic Epidemiology Study (VAGES). GWL analysis was performed using the variance components approach. Data from 2 additional Mexican-American family studies, the San Antonio Family Heart Study (SAFHS) and the San Antonio Family Diabetes/Gallbladder Study (SAFDGS), were combined with the VAGES data to test for improved linkage evidence. RESULTS After adjusting for covariate effects, T2DM was found to be under significant genetic influences (h2 = 0.62, p = 2.7 × 10(-6)). The strongest evidence for linkage of T2DM occurred between markers D9S1871 and D9S2169 on chromosome 9p24.2-p24.1 (LOD = 1.8). Given that we previously reported suggestive evidence for linkage of T2DM at this region also in SAFDGS, we found the significant and increased linkage evidence (LOD = 4.3, empirical p = 1.0 × 10(-5), genome-wide p = 1.6 × 10(-3)) for T2DM at the same chromosomal region, when we performed a GWL analysis of the VAGES data combined with the SAFHS and SAFDGS data. CONCLUSION Significant T2DM linkage evidence was found on chromosome 9p24 in Mexican Americans. Importantly, the chromosomal region of interest in this study overlaps with several recent genome-wide association studies involving T2DM-related traits. Given its overlap with such findings and our own initial T2DM association findings in the 9p24 chromosomal region, high throughput sequencing of the linked chromosomal region could identify the potential causal T2DM genes.
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Affiliation(s)
- Vidya S Farook
- Southwest Foundation for Biomedical Research, San Antonio, Tex., USA
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11
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Genetic epidemiology of cardiometabolic risk factors and their clustering patterns in Mexican American children and adolescents: the SAFARI Study. Hum Genet 2013; 132:1059-71. [PMID: 23736306 DOI: 10.1007/s00439-013-1315-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2013] [Accepted: 05/14/2013] [Indexed: 10/26/2022]
Abstract
Pediatric metabolic syndrome (MS) and its cardiometabolic components (MSCs) have become increasingly prevalent, yet little is known about the genetics underlying MS risk in children. We examined the prevalence and genetics of MS-related traits among 670 non-diabetic Mexican American (MA) children and adolescents, aged 6-17 years (49 % female), who were participants in the San Antonio Family Assessment of Metabolic Risk Indicators in Youth study. These children are offspring or biological relatives of adult participants from three well-established Mexican American family studies in San Antonio, TX, at increased risk of type 2 diabetes. MS was defined as ≥3 abnormalities among 6 MSC measures: waist circumference, systolic and/or diastolic blood pressure, fasting insulin, triglycerides, HDL-cholesterol, and fasting and/or 2-h OGTT glucose. Genetic analyses of MS, number of MSCs (MSC-N), MS factors, and bivariate MS traits were performed. Overweight/obesity (53 %), pre-diabetes (13 %), acanthosis nigricans (33 %), and MS (19 %) were strikingly prevalent, as were MS components, including abdominal adiposity (32 %) and low HDL-cholesterol (32 %). Factor analysis of MS traits yielded three constructs: adipo-insulin-lipid, blood pressure, and glucose factors, and their factor scores were highly heritable. MS itself exhibited 68 % heritability. MSC-N showed strong positive genetic correlations with obesity, insulin resistance, inflammation, and acanthosis nigricans, and negative genetic correlation with physical fitness. MS trait pairs exhibited strong genetic and/or environmental correlations. These findings highlight the complex genetic architecture of MS/MSCs in MA children, and underscore the need for early screening and intervention to prevent chronic sequelae in this vulnerable pediatric population.
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Chittoor G, Farook VS, Puppala S, Fowler SP, Schneider J, Dyer TD, Cole SA, Lynch JL, Curran JE, Almasy L, Maccluer JW, Comuzzie AG, Hale DE, Ramamurthy RS, Dudley DJ, Moses EK, Arya R, Lehman DM, Jenkinson CP, Bradshaw BS, Defronzo RA, Blangero J, Duggirala R. Localization of a major susceptibility locus influencing preterm birth. Mol Hum Reprod 2013; 19:687-96. [PMID: 23689979 DOI: 10.1093/molehr/gat036] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Preterm birth (PTB) is a complex trait, but little is known regarding its major genetic determinants. The objective of this study is to localize genes that influence susceptibility to PTB in Mexican Americans (MAs), a minority population in the USA, using predominantly microfilmed birth certificate-based data obtained from the San Antonio Family Birth Weight Study. Only 1302 singleton births from 288 families with information on PTB and significant covariates were considered for genetic analysis. PTB is defined as a childbirth that occurs at <37 completed weeks of gestation, and the prevalence of PTB in this sample was 6.4%. An ∼10 cM genetic map was used to conduct a genome-wide linkage analysis using the program SOLAR. The heritability of PTB was high (h(2) ± SE: 0.75 ± 0.20) and significant (P = 4.5 × 10(-5)), after adjusting for the significant effects of birthweight and birth order. We found significant evidence for linkage of PTB (LOD = 3.6; nominal P = 2.3 × 10(-5); empirical P = 1.0 × 10(-5)) on chromosome 18q between markers D18S1364 and D18S541. Several other chromosomal regions (2q, 9p, 16q and 20q) were also potentially linked with PTB. A strong positional candidate gene in the 18q linked region is SERPINB2 or PAI-2, a member of the plasminogen activator system that is associated with various reproductive processes. In conclusion, to our knowledge, perhaps for the first time in MAs or US populations, we have localized a major susceptibility locus for PTB on chromosome 18q21.33-q23.
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Affiliation(s)
- G Chittoor
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78245-0549, USA
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Long J, Edwards T, Signorello LB, Cai Q, Zheng W, Shu XO, Blot WJ. Evaluation of genome-wide association study-identified type 2 diabetes loci in African Americans. Am J Epidemiol 2012; 176:995-1001. [PMID: 23144361 DOI: 10.1093/aje/kws176] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Type 2 diabetes (T2D) is up to twice as prevalent among African Americans as Caucasians. Recent genome-wide association studies (GWAS) have identified multiple common genetic risk variants for T2D; however, none of these studies were conducted exclusively among subjects of African ancestry. Investigating these known loci in other populations would be an expedient way to evaluate the generalizability of the current findings. The authors evaluated 29 known T2D loci in a large southeastern US cohort study including 4,288 African Americans (1,554 cases and 2,734 controls) enrolled during 2002-2009. Seven of the 29 single nucleotide polymorphisms (SNPs) examined were found to be associated with T2D risk at P ≤ 0.05, including rs6769511 (IGF2BP2), 2 SNPs in the WFS1 gene (rs4689388 and rs1801214), rs7903146 (TCF7L2), and 3 SNPs in the KCNQ1 gene (rs231362, rs2237892, and rs2237897). Notably, the association for rs7903146 reached the GWAS significance level (P = 3.6 × 10(-8)), with an odds ratio per T allele of 1.32 (95% confidence interval: 1.20, 1.46). Regional analyses using GWAS data from Vanderbilt University's BioVU DNA biobank showed significant associations (P < 0.05) with 9 loci, though no association was observed for the index SNPs reported in European- or Asian-ancestry populations. These results extend some of the recent GWAS findings to African Americans and may guide future efforts to identify causal variants for T2D.
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Affiliation(s)
- Jirong Long
- Division of Epidemiology, Departmentof Medicine, School of Medicine, Vanderbilt University, Nashville, Tennessee 37203-1738, USA.
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Yan TT, Yin RX, Li Q, Huang P, Zeng XN, Huang KK, Aung LHH, Wu DF, Liu CW, Pan SL. Sex-specific association of rs16996148 SNP in the NCAN/CILP2/PBX4 and serum lipid levels in the Mulao and Han populations. Lipids Health Dis 2011; 10:248. [PMID: 22208664 PMCID: PMC3274493 DOI: 10.1186/1476-511x-10-248] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2011] [Accepted: 12/31/2011] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The association of rs16996148 single nucleotide polymorphism (SNP) in NCAN/CILP2/PBX4 and serum lipid levels is inconsistent. Furthermore, little is known about the association of rs16996148 SNP and serum lipid levels in the Chinese population. We therefore aimed to detect the association of rs16996148 SNP and several environmental factors with serum lipid levels in the Guangxi Mulao and Han populations. METHOD A total of 712 subjects of Mulao nationality and 736 participants of Han nationality were randomly selected from our stratified randomized cluster samples. Genotyping of the rs16996148 SNP was performed by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and then confirmed by direct sequencing. RESULTS The levels of apolipoprotein (Apo) B were higher in Mulao than in Han (P < 0.001). The frequencies of G and T alleles were 87.2% and 12.8% in Mulao, and 89.9% and 10.1% in Han (P <0.05); respectively. The frequencies of GG, GT and TT genotypes were 76.0%, 22.5% and 1.5% in Mulao, and 81.2%, 17.4% and 1.4% in Han (P <0.05); respectively. There were no significant differences in the genotypic and allelic frequencies between males and females in both ethnic groups. The levels of HDL-C, ApoAI, and the ratio of ApoAI to ApoB in Mulao were different between the GG and GT/TT genotypes in males but not in females (P < 0.01 for all), the subjects with GT/TT genotypes had higher serum levels of HDL-C, ApoAI, and the ratio of ApoAI to ApoB than the subjects with GG genotype. The levels of TC, TG, LDL-C, ApoAI, and ApoB in Han were different between the GG and GT/TT genotypes in males but not in females (P < 0.05-0.001), the T allele carriers had higher serum levels of TC, TG, LDL-C, ApoAI, and ApoB than the T allele noncarriers. The levels of HDL-C, ApoAI, and the ratio of ApoAI to ApoB in Mulao were correlated with the genotypes in males (P < 0.05-0.01) but not in females. The levels of TC, TG, HDL-C, LDL-C, ApoAI and ApoB in Han were associated with the genotypes in males (P < 0.05-0.001) but not in females. Serum lipid parameters were also correlated with several enviromental factors in both ethnic groups (P < 0.05-0.001). CONCLUSIONS The genotypic and allelic frequencies of rs16996148 SNP and the associations of the SNP and serum lipid levels are different in the Mulao and Han populations. Sex (male)-specific association of rs16996148 SNP in the NCAN/CILP2/PBX4 and serum lipid levels is also observed in the both ethnic groups.
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Affiliation(s)
- Ting-Ting Yan
- Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Rui-Xing Yin
- Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Qing Li
- Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Ping Huang
- Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Xiao-Na Zeng
- Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Ke-Ke Huang
- Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Lynn Htet Htet Aung
- Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Dong-Feng Wu
- Department of Cardiology, Institute of Cardiovascular Diseases, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, People's Republic of China
| | - Cheng-Wu Liu
- Department of Pathophysiology, School of Premedical Sciences, Guangxi Medical University, Nanning 530021, Guangxi, People's Republic of China
| | - Shang-Ling Pan
- Department of Pathophysiology, School of Premedical Sciences, Guangxi Medical University, Nanning 530021, Guangxi, People's Republic of China
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Puppala S, Coletta DK, Schneider J, Hu SL, Farook VS, Dyer TD, Arya R, Blangero J, Duggirala R, DeFronzo RA, Jenkinson CP. Genome-Wide Linkage Screen for Systolic Blood Pressure in the Veterans Administration Genetic Epidemiology Study (VAGES) of Mexican-Americans and Confirmation of a Major Susceptibility Locus on Chromosome 6q14.1. Hum Hered 2011; 71:1-10. [DOI: 10.1159/000323143] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2010] [Accepted: 11/22/2010] [Indexed: 01/11/2023] Open
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Nanni L, Quagliarini F, Megiorni F, Montali A, Minicocci I, Campagna F, Pizzuti A, Arca M. Genetic variants in adipose triglyceride lipase influence lipid levels in familial combined hyperlipidemia. Atherosclerosis 2010; 213:206-11. [PMID: 20832801 DOI: 10.1016/j.atherosclerosis.2010.08.055] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2010] [Revised: 07/12/2010] [Accepted: 08/10/2010] [Indexed: 01/01/2023]
Abstract
OBJECTIVE Familial combined hyperlipidemia (FCHL) has been associated with abnormalities in fatty acid metabolism. The adipose triglyceride lipase (PNPLA2) plays a pivotal role in the turnover of fatty acids in adipose tissue and liver. This study was designed to evaluate whether selected PNPLA2 variants may influence the susceptibility to FCHL or its lipid-related traits. METHODS Four SNPs within the PNPLA2 gene (rs7925131, rs7942159, rs66460720 and the nonsynonymous P481L) were selected based on previous association with decreased plasma levels of free fatty acids (FFA) and total triglycerides (TG) and their high frequency (MAF>0.25). These SNPs were genotyped in 214 FCHL individuals from 83 families and in 103 controls and the corresponding haplotypes were reconstructed. RESULTS No association between individual SNPs and the FCHL trait was observed. However, two PNPLA2 haplotypes were associated with lower risk of FCHL (P<0.004 after Bonferroni's correction). Compared to the others, these haplotypes were related to lower TG (118.9 ± 66.8 vs. 197.1 ± 114.7 mg/dl; P=0.001) and higher HDL-C (62.3 ± 15.8 vs. 51.0 ± 15.0 mg/dl; P<0.005). In a subgroup of studied subjects (n=63) protective haplotypes were also associated with lower FFA levels (0.33 ± 0.11 vs. 0.46 ± 0.18 mEq/L; P<0.05). These effects were independent from age, BMI and HOMA(IR). CONCLUSION These data demonstrate that variants within PNPLA2 may modulate the TG component of FCHL trait, thus implicating PNPLA2 as modifier gene in this lipid disorder. They also suggest a potential role of PNPLA2 in the metabolism of TG-rich lipoproteins.
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Affiliation(s)
- Luisa Nanni
- Department of Clinical and Medical Therapy, Unit of Atherosclerosis, University of Rome La Sapienza, Italy
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Fisher E, Grallert H, Klapper M, Pfäfflin A, Schrezenmeir J, Illig T, Boeing H, Döring F. Evidence for the Thr79Met polymorphism of the ileal fatty acid binding protein (FABP6) to be associated with type 2 diabetes in obese individuals. Mol Genet Metab 2009; 98:400-5. [PMID: 19744871 DOI: 10.1016/j.ymgme.2009.08.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2009] [Revised: 08/05/2009] [Accepted: 08/05/2009] [Indexed: 11/23/2022]
Abstract
The ileal fatty acid binding protein (FABP6) is known to be involved in enterohepatic bile acid metabolism. We have previously found a significant association between the rare allele of the FABP6 Thr79Met polymorphism and lower type 2 diabetes risk in a small case-control study (192 cases and 384 controls) embedded in the large EPIC-Potsdam cohort. A priori functional implication of the amino acid change was gained from in-silico analysis. In this study, we analysed an independent nested case-cohort including 543 incident type 2 diabetes cases from the EPIC-Potsdam cohort and a case-control study including 939 type 2 diabetes cases from KORA to confirm the association with type 2 diabetes and performed association analyses with quantitative disease-related measures in 2112 non-diabetic individuals. Homozygosity for the Met-allele was associated with lower risk of type 2 diabetes (EPIC-Potsdam: 0.70, P=0.04; KORA: 0.79, P=0.06) if adjusted for age, sex, body mass index (BMI), and waist circumference. The homozygous rare variant showed a significant interaction (P=0.006) with BMI. Relative risks in different categories (BMI <25, 25-30, and >30 kg/m(2)) showed an association exclusively in obese (BMI >30 kg/m(2)) individuals (combined risk ratio: 0.62, 95% CI 0.45-0.86). In non-diabetic individuals from the general adult population, no significant associations were observed with plasma total cholesterol, LDL-, and HDL-cholesterol, triglyceride, insulin and glucose concentration. In summary, we found evidence that the-putative functional-Thr79Met substitution of FABP6 confers a protective effect on type 2 diabetes in obese individuals.
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Affiliation(s)
- Eva Fisher
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany.
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Morris A, Ferdinand KC. Hyperlipidemia in racial/ethnic minorities: differences in lipid profiles and the impact of statin therapy. ACTA ACUST UNITED AC 2009. [DOI: 10.2217/clp.09.70] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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