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Wuni R, Ventura EF, Curi-Quinto K, Murray C, Nunes R, Lovegrove JA, Penny M, Favara M, Sanchez A, Vimaleswaran KS. Interactions between genetic and lifestyle factors on cardiometabolic disease-related outcomes in Latin American and Caribbean populations: A systematic review. Front Nutr 2023; 10:1067033. [PMID: 36776603 PMCID: PMC9909204 DOI: 10.3389/fnut.2023.1067033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 01/09/2023] [Indexed: 01/27/2023] Open
Abstract
Introduction The prevalence of cardiometabolic diseases has increased in Latin American and the Caribbean populations (LACP). To identify gene-lifestyle interactions that modify the risk of cardiometabolic diseases in LACP, a systematic search using 11 search engines was conducted up to May 2022. Methods Eligible studies were observational and interventional studies in either English, Spanish, or Portuguese. A total of 26,171 publications were screened for title and abstract; of these, 101 potential studies were evaluated for eligibility, and 74 articles were included in this study following full-text screening and risk of bias assessment. The Appraisal tool for Cross-Sectional Studies (AXIS) and the Risk Of Bias In Non-Randomized Studies-of Interventions (ROBINS-I) assessment tool were used to assess the methodological quality and risk of bias of the included studies. Results We identified 122 significant interactions between genetic and lifestyle factors on cardiometabolic traits and the vast majority of studies come from Brazil (29), Mexico (15) and Costa Rica (12) with FTO, APOE, and TCF7L2 being the most studied genes. The results of the gene-lifestyle interactions suggest effects which are population-, gender-, and ethnic-specific. Most of the gene-lifestyle interactions were conducted once, necessitating replication to reinforce these results. Discussion The findings of this review indicate that 27 out of 33 LACP have not conducted gene-lifestyle interaction studies and only five studies have been undertaken in low-socioeconomic settings. Most of the studies were cross-sectional, indicating a need for longitudinal/prospective studies. Future gene-lifestyle interaction studies will need to replicate primary research of already studied genetic variants to enable comparison, and to explore the interactions between genetic and other lifestyle factors such as those conditioned by socioeconomic factors and the built environment. The protocol has been registered on PROSPERO, number CRD42022308488. Systematic review registration https://clinicaltrials.gov, identifier CRD420223 08488.
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Affiliation(s)
- Ramatu Wuni
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, United Kingdom
| | - Eduard F Ventura
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, United Kingdom
| | | | - Claudia Murray
- Department of Real Estate and Planning, University of Reading, Reading, United Kingdom
| | - Richard Nunes
- Department of Real Estate and Planning, University of Reading, Reading, United Kingdom
| | - Julie A Lovegrove
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, United Kingdom
| | - Mary Penny
- Instituto de Investigación Nutricional, Lima, Peru
| | - Marta Favara
- Oxford Department of International Development, University of Oxford, Oxford, United Kingdom
| | - Alan Sanchez
- Grupo de Análisis para el Desarrollo (GRADE), Lima, Peru
| | - Karani Santhanakrishnan Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, United Kingdom.,Institute for Food, Nutrition and Health (IFNH), University of Reading, Reading, United Kingdom
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Carvalho LSF, Benseñor IM, Nogueira ACC, Duncan BB, Schmidt MI, Blaha MJ, Toth PP, Jones SR, Santos RD, Lotufo PA, Sposito AC. Increased particle size of triacylglycerol-enriched remnant lipoproteins, but not their plasma concentration or lipid content, augments risk prediction of incident type 2 diabetes. Diabetologia 2021; 64:385-396. [PMID: 33159534 DOI: 10.1007/s00125-020-05322-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 09/21/2020] [Indexed: 12/11/2022]
Abstract
AIMS/HYPOTHESIS Type 2 diabetes prevention requires the accurate identification of those at high risk. Beyond the association of fasting serum triacylglycerols with diabetes, triacylglycerol-enriched remnant lipoproteins (TRLs) more accurately reflect pathophysiological changes that underlie progression to diabetes, such as hepatic insulin resistance, pancreatic steatosis and systemic inflammation. We hypothesised that TRL-related factors could improve risk prediction for incident diabetes. METHODS We included individuals from the Brazilian Longitudinal Study of Adult Health cohort. We trained a logistic regression model for the risk of incident diabetes in 80% of the cohort using tenfold cross-validation, and tested the model in the remaining 20% of the cohort (test set). Variables included medical history and traits of the metabolic syndrome, followed by TRL-related measurements (plasma concentration, TRL particle diameter, cholesterol and triacylglycerol content). TRL features were measured using NMR spectroscopy. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). RESULTS Among 4463 at-risk individuals, there were 366 new cases of diabetes after a mean (±SD) of 3.7 (±0.63) years of follow-up. We derived an 18-variable model with a global AUROC of 0.846 (95% CI: 0.829, 0.869). Overall TRL-related markers were not associated with diabetes. However, TRL particle diameter increased the AUROC, particularly in individuals with HbA1c <39 mmol/mol (5.7%) (hold-out test set [n = 659]; training-validation set [n = 2638]), but not in individuals with baseline HbA1c 39-46 mmol/mol (5.7-6.4%) (hold-out test set [n = 233]; training-validation set [n = 933]). In the subgroup with baseline HbA1c <39 mmol/mol (5.7%), AUROC in the test set increased from 0.717 (95% CI 0.603, 0.818) to 0.794 (95% CI 0.731, 0.862), and AUPRC in the test set rose from 0.582 to 0.701 when using the baseline model and the baseline model plus TRL particle diameter, respectively. TRL particle diameter was highly correlated with obesity, insulin resistance and inflammation in those with impaired fasting glucose at baseline, but less so in those with HbA1c <39 mmol/mol (5.7%). CONCLUSIONS/INTERPRETATION TRL particle diameter improves the prediction of diabetes, but only in individuals with HbA1c <39 mmol/mol (5.7%) at baseline. These data support TRL particle diameter as a risk factor that is changed early in the course of the pathophysiological processes that lead to the development of type 2 diabetes, even before glucose abnormalities are established. Graphical abstract.
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Affiliation(s)
- Luiz Sérgio F Carvalho
- Data Lab, Clarity Healthcare Intelligence, Jundiaí, SP, Brazil.
- Cardiology Division, Faculty of Medical Sciences, State University of Campinas (Unicamp), Campinas, SP, Brazil.
- Laboratory of Data for Quality of Care and Outcomes Research, Institute for Strategic Management in Healthcare DF (IGESDF), Brasília, DF, Brazil.
| | - Isabela M Benseñor
- Center for Clinical and Epidemiological Research, University Hospital, University of São Paulo, São Paulo, SP, Brazil
| | - Ana C C Nogueira
- Laboratory of Data for Quality of Care and Outcomes Research, Institute for Strategic Management in Healthcare DF (IGESDF), Brasília, DF, Brazil
| | - Bruce B Duncan
- Postgraduate Studies Program in Epidemiology, School of Medicine and Hospital de Clínicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Maria I Schmidt
- Postgraduate Studies Program in Epidemiology, School of Medicine and Hospital de Clínicas, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Michael J Blaha
- The Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, MD, USA
| | - Peter P Toth
- The Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, MD, USA
- Preventive Cardiology, CGH Medical Center, Sterling, IL, USA
| | - Steven R Jones
- The Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Baltimore, MD, USA
| | - Raul D Santos
- Center for Clinical and Epidemiological Research, University Hospital, University of São Paulo, São Paulo, SP, Brazil
- Lipid Clinic Heart Institute (InCor), University of São Paulo, Medical School Hospital, São Paulo, SP, Brazil
| | - Paulo A Lotufo
- Center for Clinical and Epidemiological Research, University Hospital, University of São Paulo, São Paulo, SP, Brazil
| | - Andrei C Sposito
- Cardiology Division, Faculty of Medical Sciences, State University of Campinas (Unicamp), Campinas, SP, Brazil
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Wu P, Rybin D, Bielak LF, Feitosa MF, Franceschini N, Li Y, Lu Y, Marten J, Musani SK, Noordam R, Raghavan S, Rose LM, Schwander K, Smith AV, Tajuddin SM, Vojinovic D, Amin N, Arnett DK, Bottinger EP, Demirkan A, Florez JC, Ghanbari M, Harris TB, Launer LJ, Liu J, Liu J, Mook-Kanamori DO, Murray AD, Nalls MA, Peyser PA, Uitterlinden AG, Voortman T, Bouchard C, Chasman D, Correa A, de Mutsert R, Evans MK, Gudnason V, Hayward C, Kao L, Kardia SLR, Kooperberg C, Loos RJF, Province MM, Rankinen T, Redline S, Ridker PM, Rotter JI, Siscovick D, Smith BH, van Duijn C, Zonderman AB, Rao DC, Wilson JG, Dupuis J, Meigs JB, Liu CT, Vassy JL. Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose. PLoS One 2020; 15:e0230815. [PMID: 32379818 PMCID: PMC7205201 DOI: 10.1371/journal.pone.0230815] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 03/09/2020] [Indexed: 02/07/2023] Open
Abstract
Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.
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Affiliation(s)
- Peitao Wu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, United States of America
| | - Denis Rybin
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, United States of America
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America
| | - Mary F. Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Nora Franceschini
- University of North Carolina, Chapel Hill, NC, United States of America
| | - Yize Li
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Jonathan Marten
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Solomon K. Musani
- Jackson Heart Study, University of Mississippi Medical Center, MS, United States of America
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Sridharan Raghavan
- Section of Hospital Medicine, Veterans Affairs Eastern Colorado Healthcare System, Denver, CO, United States of America
- Division of General Internal Medicine, University of Colorado School of Medicine, Aurora, CO, United States of America
- Colorado Cardiovascular Outcomes Research Consortium, Aurora, CO, United States of America
| | - Lynda M. Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
| | - Karen Schwander
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Albert V. Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Salman M. Tajuddin
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Donna K. Arnett
- Dean's Office, University of Kentucky College of Public Health, Lexington, Kentucky, United States of America
| | - Erwin P. Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Ayse Demirkan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jose C. Florez
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Massachusetts General Hospital, Boston, MA, United States of America
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Tamara B. Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, United States of America
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, United States of America
| | - Jingmin Liu
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Jun Liu
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Dennis O. Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Alison D. Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, United Kingdom
| | - Mike A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States of America
- Data Tecnica International LLC, Glen Echo, MD, United States of America
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America
| | - André G. Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Trudy Voortman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States of America
| | - Daniel Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States of America
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Michele K. Evans
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Linda Kao
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, United States of America
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, United States of America
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Michael M. Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States of America
| | - Susan Redline
- Harvard Medical School, Boston, MA, United States of America
- Departments of Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
- Beth Israel Deaconess Medical Center, Boston, MA, United States of America
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - David Siscovick
- The New York Academy of Medicine, New York, NY, United States of America
| | - Blair H. Smith
- Division of Population Health and Genomics, University of Dundee, Dundee, United Kingdom
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Alan B. Zonderman
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - D. C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - James G. Wilson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States of America
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, United States of America
- The National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, United States of America
| | - James B. Meigs
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Division of General Internal Medicine Division, Massachusetts General Hospital, Boston, MA, United States of America
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, United States of America
| | - Jason L. Vassy
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
- VA Boston Healthcare System, Boston, MA, United States of America
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APOC3 promotes TNF-α-induced expression of JAM-1 in endothelial cell via PI3K-IKK2-p65 pathway. Cardiovasc Pathol 2019; 41:11-17. [DOI: 10.1016/j.carpath.2019.02.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 01/27/2019] [Accepted: 02/24/2019] [Indexed: 02/06/2023] Open
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Association between Genetic Variant of Apolipoprotein C3 and Incident Hypertension Stratified by Obesity and Physical Activity in Korea. Nutrients 2018; 10:nu10111595. [PMID: 30380775 PMCID: PMC6267455 DOI: 10.3390/nu10111595] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 10/21/2018] [Accepted: 10/25/2018] [Indexed: 01/18/2023] Open
Abstract
Apolipoprotein C3 (APOC3) is an important regulator of lipoprotein metabolism, and has been shown to be strongly associated with hypertriglyceridemia. We tested whether triglyceride-influencing genetic variants at APOC3 (T-455C, C-482T, C1100T, and SstI) are associated with the onset of hypertension (HTN) among Korean adults stratified by lifestyle-related factors in the Ansung–Ansan cohort within the Korean Genome and Epidemiology Study. After excluding participants with preexisting cancer, cardiovascular diseases, diabetes, and HTN, a total of 5239 men and women were included at baseline (2001–2002), and followed up for a median of 9.8 years. Carriers of the C allele of C1100T with body mass index <25 kg/m2 showed a significantly lower HTN risk (hazard ratio (HR) than non-carriers: 0.87, 95% confidence interval (CI): 0.77–0.98) after adjusting for covariates. In addition, carriers of the C allele of T-455C and the T allele of C-482T with low physical activity had lower incident HTN than non-carriers (HR: 1.14, 95% CI: 1.03–1.26; HR: 1.13, 95% CI: 1.02–1.25). Our results suggest that genotype effects in APOC3 on HTN risk have been shown in lean carriers of the C allele of C1100T and in less active people having the C allele of T-455C and T allele of C-482T in a large sample of the Korean population.
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Zhang P, Gao J, Pu C, Zhang Y. Apolipoprotein status in type 2 diabetes mellitus and its complications (Review). Mol Med Rep 2017; 16:9279-9286. [PMID: 29152661 DOI: 10.3892/mmr.2017.7831] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2016] [Accepted: 08/22/2017] [Indexed: 11/06/2022] Open
Abstract
Dyslipidaemia in type 2 diabetes mellitus (T2DM) is characterized by high plasma triglyceride concentrations, reduced high‑density lipoprotein concentrations and increased small density low‑density lipoprotein concentrations. Dyslipidaemia may lead to cardiovascular disease (CVD) and other complications. Apolipoproteins mainly comprise six species, apolipoprotein (apo)A, apoB, apoC, apoD, apoE and apoM, which are important components of plasma lipoproteins that carry lipids and stabilize the structure of lipoproteins. Complex metabolic disorders of apolipoproteins are present in T2DM, such as high plasma apoB, apoC‑II, apoC‑III and apoE concentrations, and low plasma apoA‑I and apoM concentrations, which are associated with dyslipidaemia and interrelated complications. Plasma concentrations of some apolipoproteins are also altered in T2DM with CVD or other complications. Several apolipoprotein polymorphisms are associated with diabetes susceptibility and/or lipid metabolism. The present review described the metabolic disorders of apolipoproteins in T2DM and its complications, and the relationship between each major apolipoprotein and T2DM, as well as the effects of apolipoprotein polymorphisms on diabetic susceptibility.
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Affiliation(s)
- Puhong Zhang
- Anhui Province Key Laboratory of Biological Macromolecules Research, Wannan Medical College, Wuhu, Anhui 241002, P.R. China
| | - Jialin Gao
- Department of Endocrinology and Genetic Metabolism, Yijishan Hospital of Wannan Medical College, Wuhu, Anhui 241002, P.R. China
| | - Chun Pu
- Clinical Laboratory, Yijishan Hospital of Wannan Medical College, Wuhu, Anhui 241002, P.R. China
| | - Yao Zhang
- Anhui Province Key Laboratory of Biological Macromolecules Research, Wannan Medical College, Wuhu, Anhui 241002, P.R. China
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Abstract
Genome-wide association studies have identified many genes associated with digestive tract neoplasms. However, the published findings have been conflicting. The aim of our study was to evaluate the involvement of two polymorphisms (miR-146a rs2910164, miR-196a2 rs11614913) in digestive tract neoplasms risk and explore how miR-146a and miR-196a2 influence this risk. Systemic research of the PubMed, EBSCO, CBM and VIP databases was performed. The software STATA 12.0 was used to calculate odd ratios and 95% confidence intervals. There were 14 studies (6,053 cases and 6,527 controls) available for rs2910164 and 15 studies (5,648 cases and 6,607 controls) involved in rs11614913. Rs2910164G>C was statistically significantly associated with digestive tract neoplasms (OR 1.134, 95% CI 1.076-1.194, P < 0.001). In the subgroup analysis by ethnicity, significant association was observed in Asian individuals (OR 1.145, 95% CI 1.084-1.209, P < 0.001). We found a correlation between rs11614913 and only colorectal cancer (OR 1.325, 95% CI 1.102-1.594, P = 0.003). This study suggested that digestive tract neoplasms might associate with miR-146a variants, but not miR-196a2 variants.
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Apolipoprotein C3 Gene Variants and Risk of Developing Type 2 Diabetes in Saudi Subjects. Metab Syndr Relat Disord 2015; 13:298-303. [DOI: 10.1089/met.2015.0022] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Onat A, Dönmez I, Karadeniz Y, Cakır H, Kaya A. Type-2 diabetes and coronary heart disease: common physiopathology, viewed from autoimmunity. Expert Rev Cardiovasc Ther 2015; 12:667-79. [PMID: 24846677 DOI: 10.1586/14779072.2014.910114] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Two highly prevalent diseases, Type-2 diabetes mellitus and coronary heart disease (CHD), share risk factors. Excess levels of LDL-cholesterol have been overemphasized to uniformly encompass the development of CHD, and the origin of insulin resistance underlying Type-2 diabetes has not been fully elucidated. Autoimmune response has been recognized to be responsible only of a small minority of diabetes. The increasing trend in the worldwide prevalence of diabetes and the risk factors for both diseases are reviewed, the independent mediation for CHD of (central) adiposity in both diseases and the 'hypertriglyceridemic waist' phenotype are outlined. Evidence is described that serum lipoprotein (Lp)(a) concentrations, not only in excess, but also in apparently 'reduced' levels, as a result of autoimmune response, underlie both disorders and are closely related to insulin resistance.
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Affiliation(s)
- Altan Onat
- Department of Cardiology, Cerrahpaşa Medical Faculty, Istanbul University, Istanbul, Turkey
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Lin B, Huang Y, Zhang M, Wang J, Wu Y. Association between apolipoprotein C3 Sst I, T-455C, C-482T and C1100T polymorphisms and risk of coronary heart disease. BMJ Open 2014; 4:e004156. [PMID: 24430880 PMCID: PMC3902403 DOI: 10.1136/bmjopen-2013-004156] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVES Apolipoprotein C3 (ApoC3) polymorphisms have been suggested to be associated with risk of coronary heart disease (CHD). However, the results of relevant studies were inconsistent. We aimed to systematically evaluate this issue. DESIGN PubMed, EMBASE and Cochrane library databases (up to March 2013) were systematically searched to identify studies evaluating the association between ApoC3 polymorphisms and CHD risk. Two reviewers independently identified studies, extracted and analysed the data. Either a fixed-effects or a random-effects model was adopted to estimate overall ORs. STUDIES REVIEWED Finally, 20 studies comprising 15 591 participants were included in this systematic review. Fifteen studies with 11 539 individuals were included in the meta-analysis of Sst I polymorphism, four studies comprising 3378 individuals assessed T-455C polymorphism, four studies with 3070 participants evaluated C-482T polymorphism and C1100T polymorphism was assessed by three studies comprising 4662 participants. RESULTS Under dominant model, Sst I polymorphism was borderline significantly associated with CHD risk (S1S2+S2S2 vs S1S1, pooled OR=1.19, 95% CI 1.00 to 1.42). Subgroup analyses suggested that Sst I polymorphism was significantly associated with myocardial infarction (MI) risk (pooled OR=1.42, 95% CI 1.06 to 1.91), and Sst I polymorphism was statistically associated with CHD risk among Asian population (pooled OR=1.35, 95% CI 1.08 to 1.69) and in retrospective studies (pooled OR=1.30, 95% CI 1.04 to 1.61). A significant association was observed between T-455C polymorphism and CHD risk (TC+CC vs TT, pooled OR=1.22, 95% CI 1.06 to 1.42). A borderline significant association was suggested between T-455C polymorphism and MI risk (pooled OR=1.21, 95% CI 1.00 to 1.46). C-482T and C1100T polymorphisms were not indicated to be associated with CHD risk or MI risk. CONCLUSIONS ApoC3 Sst I and T-455C polymorphisms might be associated with CHD risk.
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Affiliation(s)
- Bin Lin
- Department of Cardiology, Wenzhou Central Hospital, Wenzhou, China
| | - Yiwei Huang
- Department of Cardiology, Wenzhou Central Hospital, Wenzhou, China
| | - Mingying Zhang
- Department of Cardiology, Wenzhou Central Hospital, Wenzhou, China
| | - Jun Wang
- Department of Cardiology, Wenzhou Central Hospital, Wenzhou, China
| | - Yihua Wu
- Department of Epidemiology and Health Statistics, Zhejiang University School of Public Health, Hangzhou, China
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Larach DB, Cuchel M, Rader DJ. Monogenic causes of elevated HDL cholesterol and implications for development of new therapeutics. CLINICAL LIPIDOLOGY 2013; 8:635-648. [PMID: 25374625 PMCID: PMC4217288 DOI: 10.2217/clp.13.73] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Identification of the CETP, LIPG (encoding endothelial lipase) and APOC3 genes, and ana lysis of rare genetic variants in them, have allowed researchers to increase understanding of HDL metabolism significantly. However, development of cardiovascular risk-reducing therapeutics targeting the proteins encoded by these genes has been less straightforward. The failure of two CETP inhibitors is complex but illustrates a possible over-reliance on HDL cholesterol as a marker of therapeutic efficacy. The case of endothelial lipase exemplifies the importance of utilizing population-wide genetic studies of rare variants in potential therapeutic targets to gain information on cardiovascular disease end points. Similar population-wide studies of cardiovascular end points make apoC-III a potentially attractive target for lipid-related drug discovery. These three cases illustrate the positives and negatives of single-gene studies relating to HDL-related cardiovascular drug discovery; such studies should focus not only on HDL cholesterol and other components of the lipid profile, but also on the effect genetic variants have on cardiovascular end points.
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Affiliation(s)
- Daniel B Larach
- Division of Translational Medicine & Human Genetics, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, PA, USA
| | - Marina Cuchel
- Division of Translational Medicine & Human Genetics, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, PA, USA
| | - Daniel J Rader
- Division of Translational Medicine & Human Genetics, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, PA, USA
- 11–125 Smilow Center for Translational Research, 3400 Civic Center Boulevard, Building 421, PA 19104–5158, USA
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Rasouli B, Grill V, Midthjell K, Ahlbom A, Andersson T, Carlsson S. Smoking is associated with reduced risk of autoimmune diabetes in adults contrasting with increased risk in overweight men with type 2 diabetes: a 22-year follow-up of the HUNT study. Diabetes Care 2013; 36:604-10. [PMID: 23172971 PMCID: PMC3579345 DOI: 10.2337/dc12-0913] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To investigate the association between smoking habits and risk of autoimmune diabetes in adults and of type 2 diabetes. RESEARCH DESIGN AND METHODS We used data from the three surveys of the Nord-Trøndelag Health Study, spanning 1984-2008 and including a cohort of 90,819 Norwegian men (48%) and women (52%) aged ≥20 years. Incident cases of diabetes were identified by questionnaire and classified as type 2 diabetes (n = 1,860) and autoimmune diabetes (n = 140) based on antibodies to glutamic decarboxylase (GADA) and age at onset of diabetes. Hazard ratios (HRs) adjusted for confounders were estimated by Cox proportional hazards regression models. RESULTS The risk of autoimmune diabetes was reduced by 48% (HR 0.52 [95% CI 0.30-0.89]) in current smokers and 58% in heavy smokers (0.42 [0.18-0.98]). The reduced risk was positively associated with number of pack-years. Heavy smoking was associated with lower levels of GADA (P = 0.001) and higher levels of C-peptide (964 vs. 886 pmol/L; P = 0.03). In contrast, smoking was associated with an increased risk of type 2 diabetes, restricted to overweight men (1.33 [1.10-1.61]). Attributable proportion due to an interaction between overweight and heavy smoking was estimated to 0.40 (95% CI 0.23-0.57). CONCLUSIONS In this epidemiological study, smoking is associated with a reduced risk of autoimmune diabetes, possibly linked to an inhibitory effect on the autoimmune process. An increased risk of type 2 diabetes was restricted to overweight men.
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Affiliation(s)
- Bahareh Rasouli
- Department of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
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Zhang Z, Rowlan JS, Wang Q, Shi W. Genetic analysis of atherosclerosis and glucose homeostasis in an intercross between C57BL/6 and BALB/cJ apolipoprotein E-deficient mice. ACTA ACUST UNITED AC 2012; 5:190-201. [PMID: 22294616 DOI: 10.1161/circgenetics.111.961649] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Diabetic patients have an increased risk of developing atherosclerosis and related complications compared with nondiabetic individuals. The increased cardiovascular risk associated with diabetes is due in part to genetic variations that influence both glucose homeostasis and atherosclerotic lesion growth. Mouse strains C57BL/6J (B6) and BALB/cJ (BALB) exhibit distinct differences in fasting plasma glucose and atherosclerotic lesion size when deficient in apolipoprotein E (Apoe(-/-)). Quantitative trait locus (QTL) analysis was performed to determine genetic factors influencing the 2 phenotypes. METHODS AND RESULTS Female F(2) mice (n=266) were generated from an intercross between B6.Apoe(-/-) and BALB.Apoe(-/-) mice and fed a Western diet for 12 weeks. Atherosclerotic lesions in the aortic root, fasting plasma glucose, and body weight were measured. 130 microsatellite markers across the entire genome were genotyped. Four significant QTLs, Ath1 on chromosome (Chr) 1, Ath41 on Chr2, Ath42 on Chr5, and Ath29 on Chr9, and 1 suggestive QTL on Chr4, were identified for atherosclerotic lesion size. Four significant QTLs, Bglu3 and Bglu12 on Chr1, Bglu13 on Chr5, Bglu15 on Chr12, and 2 suggestive QTLs on Chr9 and Chr15 were identified for fasting glucose levels on the chow diet. Two significant QTLs, Bglu3 and Bglu13, and 1 suggestive locus on Chr8 were identified for fasting glucose on the Western diet. One significant locus on Chr1 and 2 suggestive loci on Chr9 and Chr19 were identified for body weight. Ath1 and Ath42 coincided with Bglu3 and Bglu13, respectively, in the confidence interval. CONCLUSIONS We have identified novel QTLs that have major influences on atherosclerotic lesion size and glucose homeostasis. The colocalization of QTLs for atherosclerosis and diabetes suggests possible genetic connections between the 2 diseases.
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Affiliation(s)
- Zhimin Zhang
- Departments of Radiology and Medical Imaging and of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA
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Coban N, Onat A, Guclu-Geyik F, Komurcu-Bayrak E, Sansoy V, Hergenc G, Can G, Erginel-Unaltuna N. Gender- and obesity-specific effect of apolipoprotein C3 gene (APOC3) -482C>T polymorphism on triglyceride concentration in Turkish adults. Clin Chem Lab Med 2011; 50:285-92. [PMID: 22004016 DOI: 10.1515/cclm.2011.747] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2011] [Accepted: 09/14/2011] [Indexed: 11/15/2022]
Abstract
BACKGROUND Apolipoprotein C3 (APOC3) gene polymorphisms are associated with cardiometabolic risk factors, varying in ethnicities. This study aimed to investigate such association between the APOC3 -482C>T polymorphism and cardiometabolic risk factors in the turkish adult risk factor (TARF) study cohort, stratifying by gender and obesity. METHODS Randomly selected 1548 individuals (757 male and 791 female, mean age 49.9±11.8 years) were genotyped for -482C>T polymorphism using hybridization probes in a Real-Time PCR LC480 device. RESULTS The -482TT genotype prevailed 9.9% in men and 11.5% in women. Association between 482C>T polymorphism and dyslipidemia (p=0.036, OR=1.42, 95%Cl=1.02-1.97) was found only in men. Analysis of variance showed that anthropometric and metabolic variables were not differently distributed in APOC3 -482C>T genotypes in the study population. In relation to dyslipidemia and obesity, the -482C>T polymorphism showed significant gender-by-genotype interactions (p<0.01). When the study population was stratified according to gender and obesity, homozygotes for the T allele were associated strongly with (by 45%) elevated fasting triglyceride concentrations in obese men (p=0.009) and homeostatic model assessment (HOMA) index in non-obese women (p=0.013). Furthermore, in the same subgroups, the associations of the fasting triglyceride concentrations and HOMA index with the TT genotype remained after adjustment for risk factors (p<0.05). CONCLUSIONS APOC3 -482TT genotype is independently associated with elevated fasting triglyceride concentrations in obese men. Presence of obesity seems to be required for this genotype to induce markedly elevated triglycerides. Furthermore, it is associated with the dyslipidemia in men, without requirement of obesity.
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Affiliation(s)
- Neslihan Coban
- Department of Genetics, Institute for Experimental Medical Research, Istanbul University, Vakif Gureba Cad. Sehremini, Istanbul, Turkey
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