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Loh M, Zhang W, Ng HK, Schmid K, Lamri A, Tong L, Ahmad M, Lee JJ, Ng MCY, Petty LE, Spracklen CN, Takeuchi F, Islam MT, Jasmine F, Kasturiratne A, Kibriya M, Mohlke KL, Paré G, Prasad G, Shahriar M, Chee ML, de Silva HJ, Engert JC, Gerstein HC, Mani KR, Sabanayagam C, Vujkovic M, Wickremasinghe AR, Wong TY, Yajnik CS, Yusuf S, Ahsan H, Bharadwaj D, Anand SS, Below JE, Boehnke M, Bowden DW, Chandak GR, Cheng CY, Kato N, Mahajan A, Sim X, McCarthy MI, Morris AP, Kooner JS, Saleheen D, Chambers JC. Identification of genetic effects underlying type 2 diabetes in South Asian and European populations. Commun Biol 2022; 5:329. [PMID: 35393509 PMCID: PMC8991226 DOI: 10.1038/s42003-022-03248-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 03/08/2022] [Indexed: 02/08/2023] Open
Abstract
South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10-8 to 5.2 × 10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations.
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Affiliation(s)
- Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Hong Kiat Ng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Katharina Schmid
- Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, 85764, Neuherberg, Germany
- Department of Informatics, Technical University of Munich, 85748, Garching bei München, Neuherberg, Germany
| | - Amel Lamri
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
| | - Lin Tong
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Meraj Ahmad
- Genomic Research on Complex diseases, CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Jung-Jin Lee
- Translational Medicine and Human Genetics, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Medicine, Mayo Hospital, Lahore, Pakistan
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, 37215, USA
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Cassandra N Spracklen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, 01003, USA
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Md Tariqul Islam
- U Chicago Research Bangladesh, House#4, Road#2b, Sector#4, Uttara, Dhaka, 1230, Bangladesh
| | - Farzana Jasmine
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Anuradhani Kasturiratne
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Kelaniya, Sri Lanka
| | - Muhammad Kibriya
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Guillaume Paré
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Gauri Prasad
- Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, 110020, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Mohammad Shahriar
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Miao Ling Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Kelaniya, Sri Lanka
| | - James C Engert
- Department of Medicine, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Hertzel C Gerstein
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - K Radha Mani
- Genomic Research on Complex diseases, CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Marijana Vujkovic
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Ananda R Wickremasinghe
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Kelaniya, Sri Lanka
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | - Salim Yusuf
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Habibul Ahsan
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Dwaipayan Bharadwaj
- Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, 110020, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Sonia S Anand
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, 48109, USA
| | - Donald W Bowden
- Department of Medicine, Mayo Hospital, Lahore, Pakistan
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, 37215, USA
| | - Giriraj R Chandak
- Genomic Research on Complex diseases, CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
- JSS Academy of Health Education of Research, Mysuru, India
- Science and Engineering Research Board, Department of Science and Technology, Ministry of Science and technology, Government of India, New Delhi, India
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Anubha Mahajan
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hosptial, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, L69 3GL, UK
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK.
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK.
- MRC-PHE Centre for Enviroment and Health, Imperial College London, London, W2 1PG, UK.
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK.
| | - Danish Saleheen
- Center for Non-Communicable Diseases, Karachi, Pakistan.
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, 10032, USA.
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK.
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK.
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK.
- MRC-PHE Centre for Enviroment and Health, Imperial College London, London, W2 1PG, UK.
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Shanaki M, Shabani P, Goudarzi A, Omidifar A, Bashash D, Emamgholipour S. The C1q/TNF-related proteins (CTRPs) in pathogenesis of obesity-related metabolic disorders: Focus on type 2 diabetes and cardiovascular diseases. Life Sci 2020; 256:117913. [DOI: 10.1016/j.lfs.2020.117913] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 05/28/2020] [Accepted: 06/01/2020] [Indexed: 02/07/2023]
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Jung TW, Hong HC, Hwang HJ, Yoo HJ, Baik SH, Choi KM. C1q/TNF-Related Protein 9 (CTRP9) attenuates hepatic steatosis via the autophagy-mediated inhibition of endoplasmic reticulum stress. Mol Cell Endocrinol 2015; 417:131-40. [PMID: 26419929 DOI: 10.1016/j.mce.2015.09.027] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2015] [Revised: 08/26/2015] [Accepted: 09/24/2015] [Indexed: 12/19/2022]
Abstract
C1q/TNF-Related Protein (CTRP) 9, the closest paralog of adiponectin, has been reported to protect against diet-induced obesity and non-alcoholic fatty liver disease (NAFLD). However, the underlying mechanism has not been fully elucidated. We explored the protective effect of CTRP9 against hepatic steatosis and apoptosis, and identified the mechanisms through autophagy and endoplasmic reticulum (ER) stress using in vitro and in vivo experiments. Treating HepG2 cells with human recombinant CTRP9 significantly ameliorated palmitate- or tunicamycin-induced dysregulation of lipid metabolism, caspase 3 activity and chromatin condensation, which lead to reduction of hepatic triglyceride (TG) accumulation. CTRP9 treatment induced autophagy markers including LC3 conversion, P62 degradation, Beclin1 and ATG7 through AMPK phosphorylation in human primary hepatocytes. Furthermore, CTRP9 decreased palmitate- or tunicamycin-induced ER stress markers, such as eIF2α, CHOP and IRE-1, in HepG2 cells. Compound C, an AMPK inhibitor, and 3 methyladenine (3 MA), an autophagy inhibitor, canceled the effects of CTRP9 on ER stress, apoptosis and hepatic steatosis. In the livers of HFD-fed mice, adenovirus-mediated CTRP9 overexpression significantly induced AMPK phosphorylation and autophagy, whereas suppressed ER stress markers. In addition, both SREBP1-mediated lipogenic gene expression and apoptosis were significantly attenuated, which result in improvement in hepatic steatosis by overexpression of CTRP9. These results demonstrate that CTRP9 alleviates hepatic steatosis through relief of ER stress via the AMPK-mediated induction of autophagy.
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Affiliation(s)
- Tae Woo Jung
- The Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Ho Cheol Hong
- The Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Hwan-Jin Hwang
- The Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Hye Jin Yoo
- The Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Sei Hyun Baik
- The Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea
| | - Kyung Mook Choi
- The Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Korea University, Seoul, Republic of Korea.
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Genetic polymorphisms of PCSK2 are associated with glucose homeostasis and progression to type 2 diabetes in a Chinese population. Sci Rep 2015; 5:14380. [PMID: 26607656 PMCID: PMC4660384 DOI: 10.1038/srep14380] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Accepted: 08/21/2015] [Indexed: 01/07/2023] Open
Abstract
Proprotein convertase subtilisin/kexin type 2 (PCSK2) is a prohormone processing enzyme involved in insulin and glucagon biosynthesis. We previously found the genetic polymorphism of PCSK2 on chromosome 20 was responsible for the linkage peak of several glucose homeostasis parameters. The aim of this study is to investigate the association between genetic variants of PCSK2 and glucose homeostasis parameters and incident diabetes. Total 1142 Chinese participants were recruited from the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) family study, and 759 participants were followed up for 5 years. Ten SNPs of the PCSK2 gene were genotyped. Variants of rs6044695 and rs2284912 were associated with fasting plasma glucose, and variants of rs2269023 were associated with fasting plasma glucose and 1-hour plasma glucose during OGTT. Haplotypes of rs4814605/rs1078199 were associated with fasting plasma insulin levels and HOMA-IR. Haplotypes of rs890609/rs2269023 were also associated with fasting plasma glucose, fasting insulin and HOMA-IR. In the longitudinal study, we found individuals carrying TA/AA genotypes of rs6044695 or TC/CC genotypes of rs2284912 had lower incidence of diabetes during the 5-year follow-up. Our results indicated that PCSK2 gene polymorphisms are associated with pleiotropic effects on various traits of glucose homeostasis and incident diabetes.
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Babaya N, Ueda H, Noso S, Hiromine Y, Itoi-Babaya M, Kobayashi M, Fujisawa T, Ikegami H. Genetic dissection of susceptibility genes for diabetes and related phenotypes on mouse chromosome 14 by means of congenic strains. BMC Genet 2014; 15:93. [PMID: 25167881 PMCID: PMC4152764 DOI: 10.1186/s12863-014-0093-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2014] [Accepted: 08/14/2014] [Indexed: 11/13/2022] Open
Abstract
Background A susceptibility locus, Nidd2n, for type 2 diabetes has been mapped to mouse chromosome 14 (Chr 14) and confirmed using the consomic strain (C3H-Chr 14NSY) of the Nagoya-Shibata-Yasuda (NSY) mouse, an animal model of spontaneous type 2 diabetes. The aim of this study was to localize and characterize Nidd2n. Results We constructed two novel congenic strains homozygous for different segments of NSY-Chr 14 on the control C3H/HeNcrj (C3H) background: R1 (C3H.NSY-(D14Mit206-D14Mit5)) possesses the proximal and middle segment, and R2 (C3H.NSY-(D14Mit206-D14Mit186)) possesses the most proximal segment of NSY-Chr 14. Diabetes-related phenotypes were studied in comparison with those of consomic C3H-Chr 14NSY (R0) and parental NSY and C3H strains. Congenic R1 and R2 showed significantly higher post-challenge glucose than that in C3H mice. Fasting glucose, in contrast, was significantly lower in R1 and R2 than in C3H mice. Insulin sensitivity was significantly impaired in R1 and R2 compared to C3H mice. R2 showed significantly higher body weight and fat-pad weight than those in C3H and R1. Leptin level was significantly higher in R0, R1 and R2 than in C3H mice, with R2 showing the highest level, similar to that in NSY mice. Serum adiponectin level was significantly lower in R0, R1 and R2 than in C3H mice, while it was significantly higher in NSY than in C3H mice. Conclusions These data indicate that Chr 14 harbors multiple genes for diabetes-related phenotypes. The original Nidd2n, which is located in the middle region of Chr 14, was divided into two segments; Nidd2.1n in proximal Chr 14 and Nidd2.2n in distal Chr 14. Nidd2.1n contributes to post-challenge hyperglycemia, insulin resistance and adiposity. Nidd2.2n contributes to fasting as well as post-challenge hyperglycemia and insulin resistance. Adp1n, which contributes to decreased adiposity and increased insulin sensitivity, rather than a diabetogenic gene, was mapped in the middle segment.
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Affiliation(s)
| | | | | | | | | | | | | | - Hiroshi Ikegami
- Department of Endocrinology, Metabolism and Diabetes, Kinki University School of Medicine, 377-2 Ohno-higashi, Osaka-sayama 589-8511, Osaka, Japan.
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Marullo L, El-Sayed Moustafa JS, Prokopenko I. Insights into the genetic susceptibility to type 2 diabetes from genome-wide association studies of glycaemic traits. Curr Diab Rep 2014; 14:551. [PMID: 25344220 DOI: 10.1007/s11892-014-0551-8] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Over the past 8 years, the genetics of complex traits have benefited from an unprecedented advancement in the identification of common variant loci for diseases such as type 2 diabetes (T2D). The ability to undertake genome-wide association studies in large population-based samples for quantitative glycaemic traits has permitted us to explore the hypothesis that models arising from studies in non-diabetic individuals may reflect mechanisms involved in the pathogenesis of diabetes. Amongst 88 T2D risk and 72 glycaemic trait loci, only 29 are shared and show disproportionate magnitudes of phenotypic effects. Important mechanistic insights have been gained regarding the physiological role of T2D loci in disease predisposition through the elucidation of their contribution to glycaemic trait variability. Further investigation is warranted to define causal variants within these loci, including functional characterisation of associated variants, to dissect their role in disease mechanisms and to enable clinical translation.
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Affiliation(s)
- Letizia Marullo
- Department of Life Sciences and Biotechnology, Genetic Section, University of Ferrara, Via L. Borsari 46, 44121, Ferrara, Italy
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Weir JM, Wong G, Barlow CK, Greeve MA, Kowalczyk A, Almasy L, Comuzzie AG, Mahaney MC, Jowett JBM, Shaw J, Curran JE, Blangero J, Meikle PJ. Plasma lipid profiling in a large population-based cohort. J Lipid Res 2013; 54:2898-908. [PMID: 23868910 DOI: 10.1194/jlr.p035808] [Citation(s) in RCA: 277] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
We have performed plasma lipid profiling using liquid chromatography electrospray ionization tandem mass spectrometry on a population cohort of more than 1,000 individuals. From 10 μl of plasma we were able to acquire comparative measures of 312 lipids across 23 lipid classes and subclasses including sphingolipids, phospholipids, glycerolipids, and cholesterol esters (CEs) in 20 min. Using linear and logistic regression, we identified statistically significant associations of lipid classes, subclasses, and individual lipid species with anthropometric and physiological measures. In addition to the expected associations of CEs and triacylglycerol with age, sex, and body mass index (BMI), ceramide was significantly higher in males and was independently associated with age and BMI. Associations were also observed for sphingomyelin with age but this lipid subclass was lower in males. Lysophospholipids were associated with age and higher in males, but showed a strong negative association with BMI. Many of these lipids have previously been associated with chronic diseases including cardiovascular disease and may mediate the interactions of age, sex, and obesity with disease risk.
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Comuzzie AG, Cole SA, Laston SL, Voruganti VS, Haack K, Gibbs RA, Butte NF. Novel genetic loci identified for the pathophysiology of childhood obesity in the Hispanic population. PLoS One 2012; 7:e51954. [PMID: 23251661 PMCID: PMC3522587 DOI: 10.1371/journal.pone.0051954] [Citation(s) in RCA: 274] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2012] [Accepted: 11/07/2012] [Indexed: 12/14/2022] Open
Abstract
Genetic variants responsible for susceptibility to obesity and its comorbidities among Hispanic children have not been identified. The VIVA LA FAMILIA Study was designed to genetically map childhood obesity and associated biological processes in the Hispanic population. A genome-wide association study (GWAS) entailed genotyping 1.1 million single nucleotide polymorphisms (SNPs) using the Illumina Infinium technology in 815 children. Measured genotype analysis was performed between genetic markers and obesity-related traits i.e., anthropometry, body composition, growth, metabolites, hormones, inflammation, diet, energy expenditure, substrate utilization and physical activity. Identified genome-wide significant loci: 1) corroborated genes implicated in other studies (MTNR1B, ZNF259/APOA5, XPA/FOXE1 (TTF-2), DARC, CCR3, ABO); 2) localized novel genes in plausible biological pathways (PCSK2, ARHGAP11A, CHRNA3); and 3) revealed novel genes with unknown function in obesity pathogenesis (MATK, COL4A1). Salient findings include a nonsynonymous SNP (rs1056513) in INADL (p = 1.2E-07) for weight; an intronic variant in MTNR1B associated with fasting glucose (p = 3.7E-08); variants in the APOA5-ZNF259 region associated with triglycerides (p = 2.5-4.8E-08); an intronic variant in PCSK2 associated with total antioxidants (p = 7.6E-08); a block of 23 SNPs in XPA/FOXE1 (TTF-2) associated with serum TSH (p = 5.5E-08 to 1.0E-09); a nonsynonymous SNP (p = 1.3E-21), an intronic SNP (p = 3.6E-13) in DARC identified for MCP-1; an intronic variant in ARHGAP11A associated with sleep duration (p = 5.0E-08); and, after adjusting for body weight, variants in MATK for total energy expenditure (p = 2.7E-08) and in CHRNA3 for sleeping energy expenditure (p = 6.0E-08). Unprecedented phenotyping and high-density SNP genotyping enabled localization of novel genetic loci associated with the pathophysiology of childhood obesity.
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Affiliation(s)
- Anthony G. Comuzzie
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Shelley A. Cole
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Sandra L. Laston
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - V. Saroja Voruganti
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Karin Haack
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Department of Molecular & Human Genetics, Baylor College of Medicine, Houston, Texas, United States of America
| | - Nancy F. Butte
- USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, United States of America
- * E-mail:
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Glahn DC, Curran JE, Winkler AM, Carless MA, Kent JW, Charlesworth JC, Johnson MP, Göring HHH, Cole SA, Dyer TD, Moses EK, Olvera RL, Kochunov P, Duggirala R, Fox PT, Almasy L, Blangero J. High dimensional endophenotype ranking in the search for major depression risk genes. Biol Psychiatry 2012; 71:6-14. [PMID: 21982424 PMCID: PMC3230692 DOI: 10.1016/j.biopsych.2011.08.022] [Citation(s) in RCA: 135] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2010] [Revised: 08/24/2011] [Accepted: 08/25/2011] [Indexed: 11/26/2022]
Abstract
BACKGROUND Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently no empirically derived statistically rigorous method for selecting optimal endophentypes for mental illnesses. Here, we describe the endophenotype ranking value, a new objective index of the genetic utility of endophenotypes for any heritable illness. METHODS Applying endophenotype ranking value analysis to a high-dimensional set of over 11,000 traits drawn from behavioral/neurocognitive, neuroanatomic, and transcriptomic phenotypic domains, we identified a set of objective endophenotypes for recurrent major depression in a sample of Mexican American individuals (n = 1122) from large randomly selected extended pedigrees. RESULTS Top-ranked endophenotypes included the Beck Depression Inventory, bilateral ventral diencephalon volume, and expression levels of the RNF123 transcript. To illustrate the utility of endophentypes in this context, each of these traits were utlized along with disease status in bivariate linkage analysis. A genome-wide significant quantitative trait locus was localized on chromsome 4p15 (logarithm of odds = 3.5) exhibiting pleiotropic effects on both the endophenotype (lymphocyte-derived expression levels of the RNF123 gene) and disease risk. CONCLUSIONS The wider use of quantitative endophenotypes, combined with unbiased methods for selecting among these measures, should spur new insights into the biological mechanisms that influence mental illnesses like major depression.
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Affiliation(s)
- David C Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, 200 Retreat Avenue, Hartford, CT 06106, USA.
| | - Joanne E Curran
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Anderson M Winkler
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, 200 Retreat Avenue, CT, 06106, USA,Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT, 06511, USA
| | - Melanie A Carless
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Jack W Kent
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Jac C Charlesworth
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Matthew P Johnson
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Harald HH Göring
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Shelley A Cole
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Thomas D Dyer
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Eric K Moses
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Rene L Olvera
- Department of Psychiatry, University of Texas Health Science Center San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78229, USA
| | - Peter Kochunov
- Research Imaging Institute, University of Texas Health Science Center San Antonio, 8403 Floyd Curl Dr, San Antonio, TX, 78229, USA
| | - Ravi Duggirala
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center San Antonio, 8403 Floyd Curl Dr, San Antonio, TX, 78229, USA
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, PO Box 760549, San Antonio, TX, 78245 USA
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10
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Babaya N, Fujisawa T, Nojima K, Itoi-Babaya M, Yamaji K, Yamada K, Kobayashi M, Ueda H, Hiromine Y, Noso S, Ikegami H. Direct evidence for susceptibility genes for type 2 diabetes on mouse chromosomes 11 and 14. Diabetologia 2010; 53:1362-71. [PMID: 20390404 DOI: 10.1007/s00125-010-1737-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2009] [Accepted: 03/01/2010] [Indexed: 10/19/2022]
Abstract
AIMS/HYPOTHESIS Diabetogenic loci for type 2 diabetes have been mapped to mouse chromosome (Chr) 11 and 14 in the Nagoya-Shibata-Yasuda (NSY) mouse, an animal model of type 2 diabetes. We aimed to obtain direct evidence of these genes on each chromosome and to clarify their function and interaction in conferring susceptibility to type 2 diabetes. METHODS We established three consomic strains homozygous for diabetogenic NSY-Chr11, NSY-Chr14 or both on the control C3H background (C3H-11(NSY), C3H-14(NSY) and C3H-11(NSY)14(NSY), respectively), and monitored diabetes-related phenotypes longitudinally. The glucokinase gene was sequenced as a positional candidate gene on Chr11. RESULTS C3H-11(NSY) mice showed hyperglycaemia associated with impaired insulin secretion and age-dependent insulin resistance without obesity. C3H-14(NSY) mice exhibited hyperglycaemia mainly due to insulin resistance, with a slight increase in percentage body fat. C3H-11(NSY)14(NSY) double consomic mice showed marked hyperglycaemia and obesity, which was not observed in single consomic strains. Sequences of the glucokinase gene were allelically variant between NSY and C3H mice. CONCLUSIONS/INTERPRETATION These data provide direct evidence that Chr11 and Chr14 harbour major susceptibility genes for type 2 diabetes. These two chromosomes interact to cause more severe hyperglycaemia and obesity, which was not observed with the presence of either single chromosome, indicating different modes of gene-gene interaction depending on the phenotype. Marked changes in the phenotypes retained in the consomic strains will facilitate fine mapping and the identification of the responsible genes and their interaction with each other, other genes and environmental factors.
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Affiliation(s)
- N Babaya
- Department of Endocrinology, Metabolism and Diabetes, Kinki University School of Medicine, 377-2 Ohno-higashi, Osaka-sayama, Osaka 589-8511, Japan
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11
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Lillioja S, Wilton A. Agreement among type 2 diabetes linkage studies but a poor correlation with results from genome-wide association studies. Diabetologia 2009; 52:1061-74. [PMID: 19296077 DOI: 10.1007/s00125-009-1324-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2008] [Accepted: 02/13/2009] [Indexed: 12/22/2022]
Abstract
AIMS/HYPOTHESIS Little of the genetic basis for type 2 diabetes has been explained, despite numerous genetic linkage studies and the discovery of multiple genes in genome-wide association (GWA) studies. To begin to resolve the genetic component of this disease, we searched for sites at which genetic results had been corroborated in different studies, in the expectation that replication among studies should direct us to the genomic locations of causative genes with more confidence than the results of individual studies. METHODS We have mapped the physical location of results from 83 linkage reports (for type 2 diabetes and diabetes precursor quantitative traits [QTs, e.g. plasma insulin levels]) and recent large GWA reports (for type 2 diabetes) onto the same human genome sequence to identify replicated results in diabetes genetic 'hot spots'. RESULTS Genetic linkage has been found at least ten times at 18 different locations, and at least five times in 56 locations. All replication clusters contained study populations from more than one ethnic background and most contained results for both diabetes and QTs. There is no close relationship between the GWA results and linkage clusters, and the nine best replication clusters have no nearby GWA result. CONCLUSIONS/INTERPRETATION Many of the genes for type 2 diabetes remain unidentified. This analysis identifies the broad location of yet to be identified genes on 6q, 1q, 18p, 2q, 20q, 17pq, 8p, 19q and 9q. The discrepancy between the linkage and GWA studies may be explained by the presence of multiple, uncommon, mildly deleterious polymorphisms scattered throughout the regulatory and coding regions of genes for type 2 diabetes.
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Affiliation(s)
- S Lillioja
- Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia.
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12
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Wong GW, Krawczyk SA, Kitidis-Mitrokostas C, Ge G, Spooner E, Hug C, Gimeno R, Lodish HF. Identification and characterization of CTRP9, a novel secreted glycoprotein, from adipose tissue that reduces serum glucose in mice and forms heterotrimers with adiponectin. FASEB J 2008; 23:241-58. [PMID: 18787108 DOI: 10.1096/fj.08-114991] [Citation(s) in RCA: 229] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Adiponectin is a major insulin-sensitizing, multimeric hormone derived from adipose tissue that acts on muscle and liver to regulate whole-body glucose and lipid metabolism. Here, we describe a novel and highly conserved paralog of adiponectin designated as C1q/TNF-related protein (CTRP) 9. Of all the CTRP paralogs, CTRP9 shows the highest degree of amino acid identity to adiponectin in its globular C1q domain. CTRP9 is expressed predominantly in adipose tissue and females expresses higher levels of the transcript than males. Moreover, its expression levels in ob/ob mice changed in an age-dependent manner, with significant up-regulation in younger mice. CTRP9 is a secreted glycoprotein with multiple post-translational modifications in its collagen domain that include hydroxylated prolines and hydroxylated and glycosylated lysines. It is secreted as multimers (predominantly trimers) from transfected cells and circulates in the mouse serum with levels varying according to sex and metabolic state of mice. Furthermore, CTRP9 and adiponectin can be secreted as heterooligomers when cotransfected into mammalian cells, and in vivo, adiponectin/CTRP9 complexes can be reciprocally coimmunoprecipitated from the serum of adiponectin and CTRP9 transgenic mice. Biochemical analysis demonstrates that adiponectin and CTRP9 associate via their globular C1q domain, and this interaction does not require their conserved N-terminal cysteines or their collagen domains. Furthermore, we show that adiponectin and CTRP9 form heterotrimers. In cultured myotubes, CTRP9 specifically activates AMPK, Akt, and p44/42 MAPK signaling pathways. Adenovirus-mediated overexpression of CTRP9 in obese (ob/ob) mice significantly lowered serum glucose levels. Collectively, these results suggest that CTRP9 is a novel adipokine, and further study of CTRP9 will yield novel mechanistic insights into its physiological and metabolic function.
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Affiliation(s)
- G William Wong
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
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13
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van Greevenbroek MMJ, Zhang J, Kallen CJHVD, Schiffers PMH, Feskens EJM, de Bruin TWA. Effects of interacting networks of cardiovascular risk genes on the risk of type 2 diabetes mellitus (the CODAM study). BMC MEDICAL GENETICS 2008; 9:36. [PMID: 18433508 PMCID: PMC2391157 DOI: 10.1186/1471-2350-9-36] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/12/2007] [Accepted: 04/24/2008] [Indexed: 01/22/2023]
Abstract
BACKGROUND Genetic dissection of complex diseases requires innovative approaches for identification of disease-predisposing genes. A well-known example of a human complex disease with a strong genetic component is Type 2 Diabetes Mellitus (T2DM). METHODS We genotyped normal-glucose-tolerant subjects (NGT; n = 54), subjects with an impaired glucose metabolism (IGM; n = 111) and T2DM (n = 142) subjects, in an assay (designed by Roche Molecular Systems) for detection of 68 polymorphisms in 36 cardiovascular risk genes. Using the single-locus logistic regression and the so-called haplotype entropy, we explored the possibility that (1) common pathways underlie development of T2DM and cardiovascular disease -which would imply enrichment of cardiovascular risk polymorphisms in "pre-diabetic" (IGM) and diabetic (T2DM) populations- and (2) that gene-gene interactions are relevant for the effects of risk polymorphisms. RESULTS In single-locus analyses, we showed suggestive association with disturbed glucose metabolism (i.e. subjects who were either IGM or had T2DM), or with T2DM only. Moreover, in the haplotype entropy analysis, we identified a total of 14 pairs of polymorphisms (with a false discovery rate of 0.125) that may confer risk of disturbed glucose metabolism, or T2DM only, as members of interacting networks of genes. We substantiated gene-gene interactions by showing that these interacting networks can indeed identify potential "disease-predisposing allele-combinations". CONCLUSION Gene-gene interactions of cardiovascular risk polymorphisms can be detected in prediabetes and T2DM, supporting the hypothesis that common pathways may underlie development of T2DM and cardiovascular disease. Thus, a specific set of risk polymorphisms, when simultaneously present, increases the risk of disease and hence is indeed relevant in the transfer of risk.
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Affiliation(s)
- Marleen M J van Greevenbroek
- Laboratory for Metabolism and Vascular Medicine, Department of Internal Medicine/Cardiovascular Research Institute (CARIM), Maastricht University, Maastricht, The Netherlands.
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14
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Voruganti VS, Lopez-Alvarenga JC, Nath SD, Rainwater DL, Bauer R, Cole SA, Maccluer JW, Blangero J, Comuzzie AG. Genetics of variation in HOMA-IR and cardiovascular risk factors in Mexican-Americans. J Mol Med (Berl) 2008; 86:303-11. [PMID: 18204828 DOI: 10.1007/s00109-007-0273-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2007] [Revised: 08/31/2007] [Accepted: 09/24/2007] [Indexed: 12/15/2022]
Abstract
Insulin resistance is a major biochemical defect underlying the pathogenesis of cardiovascular disease (CVD). Mexican-Americans are known to have an unfavorable cardiovascular profile. Thus, the aim of this study was to investigate the genetic effect on variation in HOMA-IR and to evaluate its genetic correlations with other phenotypes related to risk of CVD in Mexican-Americans. The homeostatic model assessment method (HOMA-IR) is one of several approaches that are used to measure insulin resistance and was used here to generate a quantitative phenotype for genetic analysis. For 644 adults who had participated in the San Antonio Family Heart Study (SAFHS), estimates of genetic contribution were computed using a variance components method implemented in SOLAR. Traits that exhibited significant heritabilities were body mass index (BMI) (h (2) = 0.43), waist circumference (h (2) = 0.48), systolic blood pressure (h (2) = 0.30), diastolic blood pressure (h (2) = 0.21), pulse pressure (h (2) = 0.32), triglycerides (h (2) = 0.51), LDL cholesterol (h (2) = 0.31), HDL cholesterol (h (2) = 0.24), C-reactive protein (h (2) = 0.17), and HOMA-IR (h (2) = 0.33). A genome-wide scan for HOMA-IR revealed significant evidence of linkage on chromosome 12q24 (close to PAH (phenylalanine hydroxylase), LOD = 3.01, p < 0.001). Bivariate analyses demonstrated significant genetic correlations (p < 0.05) of HOMA-IR with BMI (rho (G) = 0.36), waist circumference (rho (G) = 0.47), pulse pressure (rho (G) = 0.39), and HDL cholesterol (rho (G) = -0.18). Identification of significant linkage for HOMA-IR on chromosome 12q replicates previous family-based studies reporting linkage of phenotypes associated with type 2 diabetes in the same chromosomal region. Significant genetic correlations between HOMA-IR and phenotypes related to CVD risk factors suggest that a common set of gene(s) influence the regulation of these phenotypes.
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Affiliation(s)
- V Saroja Voruganti
- Southwest Foundation for Biomedical Research, San Antonio, TX 78245-0549, USA.
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15
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Cai G, Cole SA, Butte NF, Voruganti VS, Comuzzie AG. A quantitative trait locus on chromosome 13q affects fasting glucose levels in Hispanic children. J Clin Endocrinol Metab 2007; 92:4893-6. [PMID: 17925332 DOI: 10.1210/jc.2007-1695] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
OBJECTIVE The prevalence of childhood obesity has increased dramatically in the United States. Early presentation of type 2 diabetes has been observed in children and adolescents, especially in the Hispanic population. The genetic contribution of glucose homeostasis related to childhood obesity is poorly understood. The objective of this study was to localize quantitative trait loci influencing fasting serum glucose levels in Hispanic children participating in the Viva La Familia Study. DESIGN Subjects were 1030 children ascertained through an overweight child from 319 Hispanic families. Fasting serum glucose levels were measured enzymatically, and genetic linkage analyses were conducted using SOLAR software. RESULTS Fasting glucose was heritable, with a heritability of 0.62 +/- 0.08 (P < 0.01). Genome-wide scan mapped fasting serum glucose to markers D13S158-D13S173 on chromosome 13q (LOD score of 4.6). A strong positional candidate gene is insulin receptor substrate 2, regulator of glucose homeostasis and a candidate gene for obesity. This region was reported previously to be linked to obesity- and diabetes-related phenotypes. CONCLUSIONS A quantitative trait locus on chromosome 13q contributes to the variation in fasting serum glucose levels in Hispanic children at high risk for obesity.
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Affiliation(s)
- Guowen Cai
- United States Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, Texas 77030, USA
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16
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Puppala S, Arya R, Thameem F, Arar NH, Bhandari K, Lehman DM, Schneider J, Fowler S, Farook VS, Diego VP, Almasy L, Blangero J, Stern MP, Duggirala R, Abboud HE. Genotype by diabetes interaction effects on the detection of linkage of glomerular filtration rate to a region on chromosome 2q in Mexican Americans. Diabetes 2007; 56:2818-28. [PMID: 17698600 DOI: 10.2337/db06-0984] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVE Glomerular filtration rate (GFR) is used to assess the progression of renal disease. We performed linkage analysis to localize genes that influence GFR using estimated GFR data from the San Antonio Family Diabetes/Gallbladder Study. We also examined the effect of genotype by diabetes interaction (G x DM) on the detection of linkage to address whether genetic effects on GFR differ in diabetic and nondiabetic subjects. RESEARCH DESIGN AND METHODS GFR (N = 453) was estimated using the recently recalculated Cockcroft-Gault (GFR-CGc) and the simplified Modification of Diet in Renal Disease (GFR-4VMDRD) formulae. Both estimates of GFR exhibited significant heritabilities, but only GFR-CGc showed significant G x DM interaction. We therefore performed multipoint linkage analyses on both GFR measures using models that did not include G x DM interaction effects (Model 1) and that included G x DM interaction effects (Model 2, in the case of GFR-CGc). RESULTS The strongest evidence for linkage (Model 1) of both GFR-CGc (logarithm of odds [LOD] 2.9) and GFR-4VMDRD (LOD 2.6) occurred between markers D9S922 and D9S1120 on chromosome 9q. However, using Model 2, the strongest evidence for linkage of GFR-CGc on chromosome 2q was found near marker D2S427 (corrected LOD score [LOD(C)] 3.3) compared with the LOD score of 2.7 based on Model 1. Potential linkages (LOD or LOD(C) >or=1.2) were found only for GFR-CGc on chromosomes 3p, 3q, 4p, 8q, 11q, and 14q. CONCLUSIONS We found a major locus on chromosome 2q that differentially influences GFR in diabetic and nondiabetic environments in the Mexican-American population.
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Affiliation(s)
- Sobha Puppala
- Southwest Foundation for Biomedical Research, Department of Genetics, P.O. Box 760549, San Antonio, TX 78254, USA.
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17
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Engert JC, Lemire M, Faith J, Brisson D, Fujiwara TM, Roslin NM, Brewer CG, Montpetit A, Darmond-Zwaig C, Renaud Y, Doré C, Bailey SD, Verner A, Tremblay G, St-Pierre J, Bétard C, Platko J, Rioux JD, Morgan K, Hudson TJ, Gaudet D. Identification of a chromosome 8p locus for early-onset coronary heart disease in a French Canadian population. Eur J Hum Genet 2007; 16:105-14. [PMID: 17805225 DOI: 10.1038/sj.ejhg.5201920] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Susceptibility to coronary heart disease (CHD) has long been known to exhibit familial aggregation, with heritability estimated to be greater than 50%. The French Canadian population of the Saguenay-Lac Saint-Jean region of Quebec, Canada is descended from a founder population that settled this region 300-400 years ago and this may provide increased power to detect genes contributing to complex traits such as CHD. Probands with early-onset CHD, defined by angiographically determined coronary stenosis, and their relatives were recruited from this population (average sibship size of 6.4). Linkage analysis was performed following a genome-wide microsatellite marker scan on 42 families with 284 individuals. Nonparametric linkage (NPL) analysis provided suggestive evidence for a CHD susceptibility locus on chromosome 8 with an NPL score of 3.14 (P=0.001) at D8S1106. Linkage to this locus was verified by fine mapping in an enlarged sample of 50 families with 320 individuals. This analysis provided evidence of linkage at D8S552 (NPL score=3.53, P=0.0003), a marker that maps to the same location as D8S1106. Candidate genes in this region, including macrophage scavenger receptor 1, farnesyl-diphosphate farnesyltransferase 1, fibrinogen-like 1, and GATA-binding protein 4, were resequenced in all coding exons in both affected and unaffected individuals. Association studies with variants in these and five other genes did not identify a disease-associated mutation. In conclusion, a genome-wide scan and additional fine mapping provide evidence for a locus on chromosome 8 that contributes to CHD in a French Canadian population.
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Affiliation(s)
- James C Engert
- McGill University Health Centre, Montréal, Québec, Canada.
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Abstract
Inbred mouse strains provide genetic diversity comparable to that of the human population. Like humans, mice have a wide range of diabetes-related phenotypes. The inbred mouse strains differ in the response of their critical physiological functions, such as insulin sensitivity, insulin secretion, beta-cell proliferation and survival, and fuel partitioning, to diet and obesity. Most of the critical genes underlying these differences have not been identified, although many loci have been mapped. The dramatic improvements in genomic and bioinformatics resources are accelerating the pace of gene discovery. This review describes how mouse genetics can be used to discover diabetes-related genes, summarizes how the mouse strains differ in their diabetes-related phenotypes, and describes several examples of how loci identified in the mouse may directly relate to human diabetes.
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Affiliation(s)
- Susanne M Clee
- Department of Biochemistry, University of Wisconsin-Madison, 433 Babcock Drive, Madison, Wisconsin 53706-1544, USA
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