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Jung JH, Lee SM, Oh SH. A genome-wide association study on growth traits of Korean commercial pig breeds using Bayesian methods. Anim Biosci 2024; 37:807-816. [PMID: 38637973 PMCID: PMC11065719 DOI: 10.5713/ab.23.0443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 12/01/2023] [Accepted: 03/19/2024] [Indexed: 04/20/2024] Open
Abstract
OBJECTIVE This study aims to identify the significant regions and candidate genes of growth-related traits (adjusted backfat thickness [ABF], average daily gain [ADG], and days to 90 kg [DAYS90]) in Korean commercial GGP pig (Duroc, Landrace, and Yorkshire) populations. METHODS A genome-wide association study (GWAS) was performed using single-nucleotide polymorphism (SNP) markers for imputation to Illumina PorcineSNP60. The BayesB method was applied to calculate thresholds for the significance of SNP markers. The identified windows were considered significant if they explained ≥1% genetic variance. RESULTS A total of 28 window regions were related to genetic growth effects. Bayesian GWAS revealed 28 significant genetic regions including 52 informative SNPs associated with growth traits (ABF, ADG, DAYS90) in Duroc, Landrace, and Yorkshire pigs, with genetic variance ranging from 1.00% to 5.46%. Additionally, 14 candidate genes with previous functional validation were identified for these traits. CONCLUSION The identified SNPs within these regions hold potential value for future markerassisted or genomic selection in pig breeding programs. Consequently, they contribute to an improved understanding of genetic architecture and our ability to genetically enhance pigs. SNPs within the identified regions could prove valuable for future marker-assisted or genomic selection in pig breeding programs.
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Affiliation(s)
| | - Sang Min Lee
- National Institute of Animal Science, RDA, Cheonan, 31000,
Korea
| | - Sang-Hyon Oh
- Division of Animal Science, Gyeongsang National University, Jinju 52725,
Korea
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Carrasco-Luna J, Navarro-Solera M, Gombert M, Martín-Carbonell V, Carrasco-García Á, Del Castillo-Villaescusa C, García-Pérez MÁ, Codoñer-Franch P. Association of the rs17782313, rs17773430 and rs34114122 Polymorphisms of/near MC4R Gene with Obesity-Related Biomarkers in a Spanish Pediatric Cohort. CHILDREN (BASEL, SWITZERLAND) 2023; 10:1221. [PMID: 37508717 PMCID: PMC10378299 DOI: 10.3390/children10071221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 06/28/2023] [Accepted: 07/12/2023] [Indexed: 07/30/2023]
Abstract
Obesity is a multifactorial disease whose onset and development are shaped by the individual genetic background. The melanocortin 4 receptor gene (MC4R) is involved in the regulation of food intake and energy expenditure. Some of the single nucleotide polymorphisms (SNPs) of this gene are related to obesity and metabolic risk factors. The present study was undertaken to assess the relationship between three polymorphism SNPs, namely, rs17782313, rs17773430 and rs34114122, and obesity and metabolic risk factors. One hundred seventy-eight children with obesity aged between 7 and 16 years were studied to determine anthropometric variables and biochemical and inflammatory parameters. Our results highlight that metabolic risk factors, especially alterations in carbohydrate metabolism, were related to rs17782313. The presence of the minor C allele in the three variants (C-C-C) was significantly associated with anthropometric measures indicative of obesity, such as the body mass and fat mass indexes, and increased the values of insulinemia to 21.91 µIU/mL with respect to the wild type values. Our study suggests that the C-C-C haplotype of the SNPs rs17782313, rs17773430 and rs34114122 of the MC4R gene potentiates metabolic risk factors at early ages in children with obesity.
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Affiliation(s)
- Joaquín Carrasco-Luna
- Department of Pediatrics, Obstetrics and Gynecology, University of Valencia, 46010 Valencia, Spain
- Department for Biotechnology, Faculty of Experimental Science, Catholic University of Valencia, 46001 Valencia, Spain
| | - María Navarro-Solera
- Department of Pediatrics, Obstetrics and Gynecology, University of Valencia, 46010 Valencia, Spain
| | - Marie Gombert
- Biosciences Division, Center for Health Sciences, SRI International, Menlo Park, CA 94025, USA
| | - Vanessa Martín-Carbonell
- Department of Pediatrics, Obstetrics and Gynecology, University of Valencia, 46010 Valencia, Spain
| | - Álvaro Carrasco-García
- Department of Pediatrics, Obstetrics and Gynecology, University of Valencia, 46010 Valencia, Spain
| | - Cristina Del Castillo-Villaescusa
- Department of Pediatrics, University Hospital Doctor Peset, Foundation of Promotion of Health, Biomedical Research in the Valencian Region (FISABIO), 46020 Valencia, Spain
| | - Miguel Ángel García-Pérez
- Department of Genetics, Faculty of Biological Sciences, University of Valencia, INCLIVA, 46100 Valencia, Spain
| | - Pilar Codoñer-Franch
- Department of Pediatrics, Obstetrics and Gynecology, University of Valencia, 46010 Valencia, Spain
- Department of Pediatrics, University Hospital Doctor Peset, Foundation of Promotion of Health, Biomedical Research in the Valencian Region (FISABIO), 46020 Valencia, Spain
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3
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Pérez-Gimeno G, Seral-Cortes M, Sabroso-Lasa S, Esteban LM, Lurbe E, Béghin L, Gottrand F, Meirhaeghe A, Muntaner M, Kafatos A, Molnár D, Leclercq C, Widhalm K, Kersting M, Nova E, Salazar-Tortosa DF, Gonzalez-Gross M, Breidenassel C, Sinningen K, De Ruyter T, Labayen I, Rupérez AI, Bueno-Lozano G, Moreno LA. Development of a genetic risk score to predict the risk of hypertension in European adolescents from the HELENA study. Front Cardiovasc Med 2023; 10:1118919. [PMID: 37324619 PMCID: PMC10267871 DOI: 10.3389/fcvm.2023.1118919] [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: 12/08/2022] [Accepted: 05/11/2023] [Indexed: 06/17/2023] Open
Abstract
Introduction From genome wide association study (GWAS) a large number of single nucleotide polymorphisms (SNPs) have previously been associated with blood pressure (BP) levels. A combination of SNPs, forming a genetic risk score (GRS) could be considered as a useful genetic tool to identify individuals at risk of developing hypertension from early stages in life. Therefore, the aim of our study was to build a GRS being able to predict the genetic predisposition to hypertension (HTN) in European adolescents. Methods Data were extracted from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) cross-sectional study. A total of 869 adolescents (53% female), aged 12.5-17.5, with complete genetic and BP information were included. The sample was divided into altered (≥130 mmHg for systolic and/or ≥80 mmHg for diastolic) or normal BP. Based on the literature, a total of 1.534 SNPs from 57 candidate genes related with BP were selected from the HELENA GWAS database. Results From 1,534 SNPs available, An initial screening of SNPs univariately associated with HTN (p < 0.10) was established, to finally obtain a number of 16 SNPs significantly associated with HTN (p < 0.05) in the multivariate model. The unweighted GRS (uGRS) and weighted GRS (wGRS) were estimated. To validate the GRSs, the area under the curve (AUC) was explored using ten-fold internal cross-validation for uGRS (0.802) and wGRS (0.777). Further covariates of interest were added to the analyses, obtaining a higher predictive ability (AUC values of uGRS: 0.879; wGRS: 0.881 for BMI z-score). Furthermore, the differences between AUCs obtained with and without the addition of covariates were statistically significant (p < 0.05). Conclusions Both GRSs, the uGRS and wGRS, could be useful to evaluate the predisposition to hypertension in European adolescents.
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Affiliation(s)
- Gloria Pérez-Gimeno
- Growth, Exercise, NUtrition and Development (GENUD), Research Group, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria Aragón (IIS Aragón), Universidad de Zaragoza, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
| | - Miguel Seral-Cortes
- Growth, Exercise, NUtrition and Development (GENUD), Research Group, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria Aragón (IIS Aragón), Universidad de Zaragoza, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
| | - Sergio Sabroso-Lasa
- Genetic and Molecular Epidemiology Group (GMEG), Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | - Empar Lurbe
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
- INCLIVA Biomedical Research Institute, Pediatric Department, Consorcio Hospital General, University of Valencia, Valencia, Spain
| | - Laurent Béghin
- Université Lille, Inserm, CHU Lille, INFINITE—Institute for Translational Research in Inflammation, Lille, France
| | - Frederic Gottrand
- Université Lille, Inserm, CHU Lille, INFINITE—Institute for Translational Research in Inflammation, Lille, France
| | - Aline Meirhaeghe
- Risk Factors and Molecular Determinants of Aging-Related Diseases (RID-AGE), Centre Hosp. Univ Lille, Institut Pasteur de Lille, Université de Lille, Lille, France
| | - Manon Muntaner
- Risk Factors and Molecular Determinants of Aging-Related Diseases (RID-AGE), Centre Hosp. Univ Lille, Institut Pasteur de Lille, Université de Lille, Lille, France
| | - Anthony Kafatos
- Department of Social Medicine, Preventive Medicine and Nutrition Clinic, University of Crete School of Medicine, Heraklion, Greece
| | - Dénes Molnár
- Department of Pediatrics, University of Pecs, Pecs, Hungary
| | - Catherine Leclercq
- INRAN, National Research Institute for Food and Nutrition, Food and Nutrition Research Centre-Council for Agricultural Research and Economics, Rome, Italy
| | - Kurt Widhalm
- Division of Clinical Nutrition and Prevention, Department of Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Mathilde Kersting
- Departement of Nutrition—Human Nutrition, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Esther Nova
- Department of Metabolism and Nutrition, Institute of Food Science and Technology and Nutrition (ICTAN), CSIC, Madrid, Spain
| | - Diego F. Salazar-Tortosa
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, United States
- PROFITH ‘PROmoting FITness and Health Through Physical Activity’ Research Group, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain
| | - Marcela Gonzalez-Gross
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
- ImFine Research Group, Department of Health and Human Performance, Facultad de Ciencias de la Actividad Física y del Deporte-INEF, Universidad Politécnica de Madrid, Madrid, Spain
| | - Christina Breidenassel
- Departement of Nutrition—Human Nutrition, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
- ImFine Research Group, Department of Health and Human Performance, Facultad de Ciencias de la Actividad Física y del Deporte-INEF, Universidad Politécnica de Madrid, Madrid, Spain
| | - Kathrin Sinningen
- Research Department of Child Nutrition, University Hospital of Pediatrics and Adolescent Medicine, St. Josef-Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Thaïs De Ruyter
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Idoia Labayen
- Department of Health Sciences, Institute for Innovation & Sustainable Food Chain Development, Public University of Navarra, Pamplona, Spain
| | - Azahara I. Rupérez
- Growth, Exercise, NUtrition and Development (GENUD), Research Group, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria Aragón (IIS Aragón), Universidad de Zaragoza, Zaragoza, Spain
| | - Gloria Bueno-Lozano
- Growth, Exercise, NUtrition and Development (GENUD), Research Group, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria Aragón (IIS Aragón), Universidad de Zaragoza, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
| | - Luis A. Moreno
- Growth, Exercise, NUtrition and Development (GENUD), Research Group, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria Aragón (IIS Aragón), Universidad de Zaragoza, Zaragoza, Spain
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y la Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
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Gao F, Liang T, Lu YW, Fu X, Dong X, Pu L, Hong T, Zhou Y, Zhang Y, Liu N, Zhang F, Liu J, Malizia AP, Yu H, Zhu W, Cowan DB, Chen H, Hu X, Mably JD, Wang J, Wang DZ, Chen J. A defect in mitochondrial protein translation influences mitonuclear communication in the heart. Nat Commun 2023; 14:1595. [PMID: 36949106 PMCID: PMC10033703 DOI: 10.1038/s41467-023-37291-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 03/10/2023] [Indexed: 03/24/2023] Open
Abstract
The regulation of the informational flow from the mitochondria to the nucleus (mitonuclear communication) is not fully characterized in the heart. We have determined that mitochondrial ribosomal protein S5 (MRPS5/uS5m) can regulate cardiac function and key pathways to coordinate this process during cardiac stress. We demonstrate that loss of Mrps5 in the developing heart leads to cardiac defects and embryonic lethality while postnatal loss induces cardiac hypertrophy and heart failure. The structure and function of mitochondria is disrupted in Mrps5 mutant cardiomyocytes, impairing mitochondrial protein translation and OXPHOS. We identify Klf15 as a Mrps5 downstream target and demonstrate that exogenous Klf15 is able to rescue the overt defects and re-balance the cardiac metabolome. We further show that Mrps5 represses Klf15 expression through c-myc, together with the metabolite L-phenylalanine. This critical role for Mrps5 in cardiac metabolism and mitonuclear communication highlights its potential as a target for heart failure therapies.
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Affiliation(s)
- Feng Gao
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Tian Liang
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Yao Wei Lu
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Vascular Biology Program, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Xuyang Fu
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Xiaoxuan Dong
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Linbin Pu
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Tingting Hong
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Yuxia Zhou
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Yu Zhang
- Department of Clinical Pharmacy, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, China
| | - Ning Liu
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Feng Zhang
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Jianming Liu
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Vertex pharmaceuticals, VCGT, 316-318 Northern Ave, Boston, MA, 02210, USA
| | - Andrea P Malizia
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Hong Yu
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Wei Zhu
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Douglas B Cowan
- Vascular Biology Program, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Hong Chen
- Vascular Biology Program, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Xinyang Hu
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - John D Mably
- Center for Regenerative Medicine, University of South Florida Health Heart Institute, Morsani School of Medicine, University of South Florida, Tampa, FL, 33602, USA
| | - Jian'an Wang
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China.
| | - Da-Zhi Wang
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA.
- Center for Regenerative Medicine, University of South Florida Health Heart Institute, Morsani School of Medicine, University of South Florida, Tampa, FL, 33602, USA.
| | - Jinghai Chen
- Department of Cardiology, Provincial Key Lab of Cardiovascular Research, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China.
- Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou, 310029, China.
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El Meouchy P, Wahoud M, Allam S, Chedid R, Karam W, Karam S. Hypertension Related to Obesity: Pathogenesis, Characteristics and Factors for Control. Int J Mol Sci 2022; 23:ijms232012305. [PMID: 36293177 PMCID: PMC9604511 DOI: 10.3390/ijms232012305] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 10/01/2022] [Accepted: 10/07/2022] [Indexed: 11/16/2022] Open
Abstract
The World Health Organization (WHO) refers to obesity as abnormal or excessive fat accumulation that presents a health risk. Obesity was first designated as a disease in 2012 and since then the cost and the burden of the disease have witnessed a worrisome increase. Obesity and hypertension are closely interrelated as abdominal obesity interferes with the endocrine and immune systems and carries a greater risk for insulin resistance, diabetes, hypertension, and cardiovascular disease. Many factors are at the interplay between obesity and hypertension. They include hemodynamic alterations, oxidative stress, renal injury, hyperinsulinemia, and insulin resistance, sleep apnea syndrome and the leptin-melanocortin pathway. Genetics, epigenetics, and mitochondrial factors also play a major role. The measurement of blood pressure in obese patients requires an adapted cuff and the search for other secondary causes is necessary at higher thresholds than the general population. Lifestyle modifications such as diet and exercise are often not enough to control obesity, and so far, bariatric surgery constitutes the most reliable method to achieve weight loss. Nonetheless, the emergence of new agents such as Semaglutide and Tirzepatide offers promising alternatives. Finally, several molecular pathways are actively being explored, and they should significantly extend the treatment options available.
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Affiliation(s)
- Paul El Meouchy
- Department of Internal Medicine, MedStar Health, Baltimore, MD 21218, USA
| | - Mohamad Wahoud
- Department of Internal Medicine, Tufts Medical Center, Boston, MA 02111, USA
| | - Sabine Allam
- Faculty of Medicine and Medical Sciences, University of Balamand, El Koura P.O. Box 100, Lebanon
| | - Roy Chedid
- College of Osteopathic Medicine, William Carey University, Hattiesburg, MS 39401, USA
| | - Wissam Karam
- Department of Internal Medicine, University of Kansas School of Medicine, Wichita, KS 67214, USA
| | - Sabine Karam
- Division of Nephrology and Hypertension, University of Minnesota, Minneapolis, MN 55414, USA
- Correspondence:
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Močnik M, Zagradišnik B, Marčun Varda N. Assessing 48 SNPs in Hypertensive Paediatric Patients and Young Adults with Review of Genetic Background of Essential Hypertension. CHILDREN (BASEL, SWITZERLAND) 2022; 9:1262. [PMID: 36010152 PMCID: PMC9406300 DOI: 10.3390/children9081262] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/13/2022] [Accepted: 08/17/2022] [Indexed: 06/15/2023]
Abstract
Essential hypertension in paediatric patients and young adults is rising, mostly on account of obesity-related hypertension. Clinically, the difference between obese hypertensive and non-obese hypertensive individuals is evident; yet, the pathophysiology of essential and obesity-related hypertension is multifactorial, complex and not fully understood. The aim of our study was to obtain a comprehensive view of the clinical differences between obesity-related hypertension and hypertension in non-obese paediatric patients and young adults and to do genetic tests to possibly highlight some of the pathophysiological differences with a review of their genetic backgrounds. Four hundred and thirty-six hypertensive paediatric patients and young adults were included in the study, and a study of 48 single-nucleotide polymorphisms, using Kompetitive allele specific PCR, was conducted. The subjects were divided into 243 non-obese participants with hypertension and 193 obese participants with hypertension. The data for the clinical comparison of both groups were collected as well. The differences in some clinical and biochemical parameters were confirmed. Genetic tests showed a significant difference in one allele frequency between both groups in five SNPs: rs6232, rs6235, rs12145833, rs59744560 and rs9568856. In rs6235 and rs59744560, a direct effect of different allele states could be implied. Obesity-related hypertension at a young age differs from essential hypertension in those non-obese. The reported genetic differences could be important in understanding the complex pathophysiology of early-onset obesity-related hypertension and should be further evaluated.
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Affiliation(s)
- Mirjam Močnik
- Department of Paediatrics, University Medical Centre Maribor, Ljubljanska ulica 5, 2000 Maribor, Slovenia
| | - Boris Zagradišnik
- Laboratory of Medical Genetics, University Medical Centre Maribor, Ljubljanska ulica 5, 2000 Maribor, Slovenia
| | - Nataša Marčun Varda
- Department of Paediatrics, University Medical Centre Maribor, Ljubljanska ulica 5, 2000 Maribor, Slovenia
- Medical Faculty, University of Maribor, Taborska 8, 2000 Maribor, Slovenia
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7
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Goulet D, O'Loughlin J, Sylvestre MP. Association of Genetic Variants With Body-Mass Index and Blood Pressure in Adolescents: A Replication Study. Front Genet 2021; 12:690335. [PMID: 34539733 PMCID: PMC8440872 DOI: 10.3389/fgene.2021.690335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 08/05/2021] [Indexed: 11/13/2022] Open
Abstract
The strong correlation between adiposity and blood pressure (BP) might be explained in part by shared genetic risk factors. A recent study identified three nucleotide variants [rs16933812 (PAX5), rs7638110 (MRPS22), and rs9930333 (FTO)] associated with both body mass index (BMI) and systolic blood pressure (SBP) in adolescents age 12-18years. We attempted to replicate these findings in a sample of adolescents of similar age. A total of 713 adolescents were genotyped and had anthropometric indicators and blood pressure measured at age 13, 15, 17, and 24years. Using linear mixed models, we assessed associations of these variants with BMI and SBP. In our data, rs9930333 (FTO) was associated with body mass index, but not systolic blood pressure. Neither rs16933812 (PAX5) nor rs7638110 (MRPS22) were associated with body mass index or systolic blood pressure. Although, differences in phenotypic definitions and in genetic architecture across populations may explain some of the discrepancy across studies, nucleotide variant selection in the initial study may have led to false-positive results that could not be replicated.
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Affiliation(s)
- Danick Goulet
- École de santé publique, Université de Montréal, Montréal, QC, Canada
| | - Jennifer O'Loughlin
- École de santé publique, Université de Montréal, Montréal, QC, Canada.,Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Marie-Pierre Sylvestre
- École de santé publique, Université de Montréal, Montréal, QC, Canada.,Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
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8
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Wang T, Zhou M, Guo J, Guo YY, Ding K, Wang P, Wang ZP. Analysis of selection signatures on the Z chromosome of bidirectional selection broiler lines for the assessment of abdominal fat content. BMC Genom Data 2021; 22:18. [PMID: 34058970 PMCID: PMC8165782 DOI: 10.1186/s12863-021-00971-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 05/13/2021] [Indexed: 11/26/2022] Open
Abstract
Background The discovery of selection signatures has enabled the identification of genomics regions under selective pressure, enhancing knowledge of evolutionary genotype-phenotypes. Sex chromosomes play an important role in species formation and evolution. Therefore, the exploration of selection signatures on sex chromosomes has important biological significance. Results In this study, we used the Cross Population Extend Haplotype Homozygosity Test (XPEHH), F-statistics (FST) and EigenGWAS to assess selection signatures on the Z chromosome in 474 broiler chickens via Illumina chicken 60 K SNP chips. SNP genotype data were downloaded from publicly available resources. We identified 17 selection regions, amongst which 1, 11 and 12 were identified by XPEHH, FST, and EigenGWAS, respectively. Each end of the Z chromosome appeared to undergo the highest levels of selection pressure. A total of 215 candidate genes were located in 17 selection regions, some of which mediated lipogenesis, fatty acid production, fat metabolism, and fat decomposition, including FGF10, ELOVL7, and IL6ST. Using abdominal adipose tissue expression data of the chickens, 187 candidate genes were expressed with 15 differentially expressed genes (DEGs) in fat vs. lean lines identified. Amongst the DEGs, VCAN was related to fat metabolism. GO pathway enrichment analysis and QTL annotations were performed to fully characterize the selection mechanism(s) of chicken abdominal fat content. Conclusions We have found some selection regions and candidate genes involving in fat metabolism on the Z chromosome. These findings enhance our understanding of sex chromosome selection signatures. Supplementary Information The online version contains supplementary material available at 10.1186/s12863-021-00971-6.
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Affiliation(s)
- Tao Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, China.,Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin, China.,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China.,Bioinformatics Center, Northeast Agricultural University, Harbin, China
| | - Meng Zhou
- Bioinformatics Center, Northeast Agricultural University, Harbin, China.,Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture and Rural Affairs, Jimei University, Xiamen, China
| | - Jing Guo
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, China.,Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin, China.,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China.,Bioinformatics Center, Northeast Agricultural University, Harbin, China
| | - Yuan-Yuan Guo
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, China.,Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin, China.,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China.,Bioinformatics Center, Northeast Agricultural University, Harbin, China
| | - Kun Ding
- College of Computer Science and Technology, Inner Mongolia Normal University, Huhehot, China
| | - Peng Wang
- HeiLongJiang provincial Husbandry Department, Harbin, China
| | - Zhi-Peng Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Harbin, China. .,Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, Harbin, China. .,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China. .,Bioinformatics Center, Northeast Agricultural University, Harbin, China.
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9
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Walia GK, Saini S, Vimal P, Bhatia K, Kumar A, Singh R, Prabhakaran D, Gupta V. Association of MC4R (rs17782313) gene polymorphism with obesity measures in Western India. Diabetes Metab Syndr 2021; 15:661-665. [PMID: 33813238 DOI: 10.1016/j.dsx.2021.03.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 03/08/2021] [Accepted: 03/15/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND AND AIMS The association of melanocortin receptor 4 (MC4R) gene with adiposity measures is widely studied in European populations. Only six studies have investigated the role of MC4R gene with adiposity measures among Indian populations. We have evaluated the role of MC4R (rs17782313) gene polymorphism in influencing adiposity measures in India among children and adults. MATERIALS AND METHODS The present population based cross sectional study was conducted among 303 individuals (208 children and 95 adults) of age group 10-30 years, belonging to Rajasthan. Somatometric measurements (standing height, weight, and waist and hip girths) and blood samples were taken after obtaining written informed consent. Genotyping of MC4R rs17782313 single nucleotide polymorphism was done using restriction fragment length polymorphism method for polymerase chain reaction amplified fragments. We examined association between rs17782313 and different adiposity measures (height, weight, BMI, WHR, and waist and hip girths) using linear regression models. RESULTS The MC4R variant (rs17782313) predicted increased body weight (0.15 kg, S.E ± 0.076, P = 0.043) among children. In combined population, the rs17782313 variant was moderately associated with body weight (0.13 kg, S.E ± 0.070, P = 0.057). This variant was not found to be associated with any other adiposity measure. CONCLUSION Further studies are needed to evaluate the association of MC4R variants through sequencing and functional genomics with different adiposity measures in Indian populations for understanding the genetic underpinnings of adiposity in India.
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Affiliation(s)
| | - Simmi Saini
- Department of Anthropology, University of Delhi, India.
| | - Pradeep Vimal
- Indian Institute of Public Health- Delhi, Public Health Foundation of India, Gurugram, India.
| | | | - Arun Kumar
- Department of Anthropology, University of Delhi, India.
| | - Ranjana Singh
- Indian Institute of Public Health- Delhi, Public Health Foundation of India, Gurugram, India.
| | | | - Vipin Gupta
- Department of Anthropology, University of Delhi, India.
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10
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Javanrouh N, Khalaj A, Guity K, Sedaghati-Khayat B, Valizadeh M, Barzin M, Daneshpour MS. Presence of CC Genotype for rs17773430 Could Affect the Percentage of Excess Weight Loss 1 Year After Bariatric Surgery: Tehran Obesity Treatment Study (TOTS). Obes Surg 2021; 30:537-544. [PMID: 31637671 DOI: 10.1007/s11695-019-04211-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Morbid obesity could last for a long period of life and increase the risk of morbidity as well as premature mortality. Although bariatric surgery benefits patients by quick weight loss, not all bariatric patients lose the same percentage of weight after a long time from surgery, which may be the result of diet, physical activity, and genetic components. OBJECTIVES In this study, we evaluated the association between the MC4R gene and both excess weight loss percentage (EWL%) and excess BMI loss percentage (EBMIL%) in a cohort of bariatric surgery patients after 6 and 12 months from surgery. METHODS A total of 424 bariatric surgery patients who had participated in the Tehran Obesity Treatment Study and had weight measurements after 6 and 12 months from surgery were included in the study. Four SNPs in the MC4R gene were selected for evaluating the associations. RESULTS We found that rs17773430 had a significant effect on both EWL% and EBMIL%, especially after 12 months of bariatric surgery. Furthermore, three other SNPs, rs17782313, rs476828, and rs11152213, did not show any significant association with EWL% and EBMIL%. CONCLUSION This study was the first to report on the association of rs17773430 with both EWL% and EBMIL% in a cohort of patients after bariatric surgery. We found that weight loss after surgery is influenced by genetic factors, and there were significant differences between the distribution of EWL% and EBMIL% in morbid obese bariatric patients who have two minor alleles of the rs17773430 and other SNPs.
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Affiliation(s)
- Niloufar Javanrouh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, PO Box 19195-4763, Tehran, Iran
| | - Alireza Khalaj
- Tehran Obesity Treatment Center, Department of Surgery, Faculty of Medicine, Shahed University, Tehran, Iran
| | - Kamran Guity
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, PO Box 19195-4763, Tehran, Iran
| | - Bahareh Sedaghati-Khayat
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, PO Box 19195-4763, Tehran, Iran
| | - Majid Valizadeh
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Barzin
- Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - Maryam S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, PO Box 19195-4763, Tehran, Iran.
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11
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Yılmaz B, Gezmen Karadağ M. The current review of adolescent obesity: the role of genetic factors. J Pediatr Endocrinol Metab 2021; 34:151-162. [PMID: 33185580 DOI: 10.1515/jpem-2020-0480] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 10/20/2020] [Indexed: 11/15/2022]
Abstract
Obesity, a complex, multi-factor and heterogeneous condition, is thought to result from the interaction of environmental and genetic factors. Considering the result of adolescence obesity in adulthood, the role of genetic factors comes to the fore. Recently, many genome-wide association studies (GWAS) have been conducted and many loci associated with adiposity have been identified. In adolescents, the strongest association with obesity has been found in single nucleotide polymorphisms (SNP) in the FTO gene. Besides FTO, GWAS showed consistent effects between variants in MC4R, TMEM18, TNNI3K, SEC16B, GNPDA2, POMC and obesity. However, these variants may not have similar effects for all ethnic groups. Although recently genetic factors are considered to contribute to obesity, relatively little is known about the specific loci related to obesity and the mechanisms by which they cause obesity.
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Affiliation(s)
- Birsen Yılmaz
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Gazi University, Çankaya, Ankara, Turkey.,Department of Nutrition and Dietetics, Faculty of Health Sciences, Çukurova University, Adana, Turkey
| | - Makbule Gezmen Karadağ
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Gazi University, Çankaya, Ankara, Turkey
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12
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Sun C, Kovacs P, Guiu-Jurado E. Genetics of Obesity in East Asians. Front Genet 2020; 11:575049. [PMID: 33193685 PMCID: PMC7606890 DOI: 10.3389/fgene.2020.575049] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 09/17/2020] [Indexed: 12/31/2022] Open
Abstract
Obesity has become a public health problem worldwide. Compared with Europe, people in Asia tend to suffer from type 2 diabetes with a lower body mass index (BMI). Genome-wide association studies (GWASs) have identified over 750 loci associated with obesity. Although the majority of GWAS results were conducted in individuals of European ancestry, a recent GWAS in individuals of Asian ancestry has made a significant contribution to the identification of obesity susceptibility loci. Indeed, owing to the multifactorial character of obesity with a strong environmental component, the revealed loci may have distinct contributions in different ancestral genetic backgrounds and in different environments as presented through diet and exercise among other factors. Uncovering novel, yet unrevealed genes in non-European ancestries may further contribute to explaining the missing heritability for BMI. In this review, we aimed to summarize recent advances in obesity genetics in individuals of Asian ancestry. We therefore compared proposed mechanisms underlying susceptibility loci for obesity associated with individuals of European and Asian ancestries and discussed whether known genetic variants might explain ethnic differences in obesity risk. We further acknowledged that GWAS implemented in individuals of Asian ancestries have not only validated the potential role of previously specified obesity susceptibility loci but also exposed novel ones, which have been missed in the initial genetic studies in individuals of European ancestries. Thus, multi-ethnic studies have a great potential not only to contribute to a better understanding of the complex etiology of human obesity but also potentially of ethnic differences in the prevalence of obesity, which may ultimately pave new avenues in more targeted and personalized obesity treatments.
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Affiliation(s)
| | - Peter Kovacs
- Medical Department III – Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
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13
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Corrigan JK, Ramachandran D, He Y, Palmer CJ, Jurczak MJ, Chen R, Li B, Friedline RH, Kim JK, Ramsey JJ, Lantier L, McGuinness OP, Banks AS. A big-data approach to understanding metabolic rate and response to obesity in laboratory mice. eLife 2020; 9:e53560. [PMID: 32356724 PMCID: PMC7274785 DOI: 10.7554/elife.53560] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 04/30/2020] [Indexed: 12/21/2022] Open
Abstract
Maintaining a healthy body weight requires an exquisite balance between energy intake and energy expenditure. To understand the genetic and environmental factors that contribute to the regulation of body weight, an important first step is to establish the normal range of metabolic values and primary sources contributing to variability. Energy metabolism is measured by powerful and sensitive indirect calorimetry devices. Analysis of nearly 10,000 wild-type mice from two large-scale experiments revealed that the largest variation in energy expenditure is due to body composition, ambient temperature, and institutional site of experimentation. We also analyze variation in 2329 knockout strains and establish a reference for the magnitude of metabolic changes. Based on these findings, we provide suggestions for how best to design and conduct energy balance experiments in rodents. These recommendations will move us closer to the goal of a centralized physiological repository to foster transparency, rigor and reproducibility in metabolic physiology experimentation.
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Affiliation(s)
- June K Corrigan
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical SchoolBostonUnited States
| | - Deepti Ramachandran
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical SchoolBostonUnited States
| | - Yuchen He
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical SchoolBostonUnited States
| | - Colin J Palmer
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical SchoolBostonUnited States
| | - Michael J Jurczak
- Division of Endocrinology, Yale University School of MedicineNew HavenUnited States
| | - Rui Chen
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of MedicineNashvilleUnited States
| | - Bingshan Li
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of MedicineNashvilleUnited States
| | - Randall H Friedline
- Program in Molecular Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
| | - Jason K Kim
- Program in Molecular Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
- Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
| | - Jon J Ramsey
- Department of Molecular Biosciences, School of Veterinary Medicine, University of California, DavisDavisUnited States
| | - Louise Lantier
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of MedicineNashvilleUnited States
| | - Owen P McGuinness
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of MedicineNashvilleUnited States
| | - Mouse Metabolic Phenotyping Center Energy Balance Working Group
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical SchoolBostonUnited States
- Division of Endocrinology, Yale University School of MedicineNew HavenUnited States
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of MedicineNashvilleUnited States
- Program in Molecular Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
- Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, University of Massachusetts Medical SchoolWorcesterUnited States
- Department of Molecular Biosciences, School of Veterinary Medicine, University of California, DavisDavisUnited States
| | - Alexander S Banks
- Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical SchoolBostonUnited States
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14
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Dlamini Z, Hull R, Makhafola TJ, Mbele M. Regulation of alternative splicing in obesity-induced hypertension. Diabetes Metab Syndr Obes 2019; 12:1597-1615. [PMID: 31695458 PMCID: PMC6718130 DOI: 10.2147/dmso.s188680] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 02/11/2019] [Indexed: 12/26/2022] Open
Abstract
Obesity is the result of genetics which predisposes an individual to obesity and environmental factors, resulting in excessive weight gain. A well-established linear relationship exists between hypertension and obesity. The combined burden of hypertension and obesity poses significant health and economic challenges. Many environmental factors and genetic traits interact to contribute to obesity-linked hypertension. These include excess sodium re-absorption or secretion by the kidneys, a hypertensive shift of renal-pressure and activation of the sympathetic nervous system. Most individuals suffering from hypertension need drugs in order to treat their raised blood pressure, and while a number of antihypertensive therapeutic agents are currently available, 50% of cases remain uncontrolled. In order to develop new and effective therapeutic agents combating obesity-induced hypertension, a thorough understanding of the molecular events leading to adipogenesis is critical. With the advent of whole genome and exome sequencing techniques, new genes and variants which can be used as markers for obesity and hypertension are being identified. This review examines the role played by alternative splicing (AS) as a contributing factor to the metabolic regulation of obesity-induced hypertension. Splicing mutations constitute at least 14% of the disease-causing mutations, thus implicating polymorphisms that effect splicing as indicators of disease susceptibility. The unique transcripts resulting from the alternate splicing of mRNA encoding proteins that play a key role in contributing to obesity would be vital to gain a proper understanding of the genetic causes of obesity. A greater knowledge of the genetic basis for obesity-linked hypertension will assist in the development of appropriate diagnostic tests as well as the identification of new personalized therapeutic targets against obesity-induced hypertension.
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Affiliation(s)
- Zodwa Dlamini
- South African Medical Research Council/University of Pretoria Precision Prevention & Novel Drug Targets for HIV-Associated Cancers (PPNDTHAC) Extramural Unit, Pan African Cancer Research Institute (PACRI), Faculty of Health Sciences, University of Pretoria, Hatfield0028, South Africa
- Correspondence: Zodwa Dlamini South African Medical Research Council/University of Pretoria Precision Prevention & Novel Drug Targets for HIV-Associated Cancers (PPNDTHAC) Extramural Unit, Pan African Cancer Research Institute (PACRI), Faculty of Health Sciences, University of Pretoria, South AfricaTel +27 3 18 199 334/5Email
| | - Rodney Hull
- South African Medical Research Council/University of Pretoria Precision Prevention & Novel Drug Targets for HIV-Associated Cancers (PPNDTHAC) Extramural Unit, Pan African Cancer Research Institute (PACRI), Faculty of Health Sciences, University of Pretoria, Hatfield0028, South Africa
| | - Tshepiso J Makhafola
- South African Medical Research Council/University of Pretoria Precision Prevention & Novel Drug Targets for HIV-Associated Cancers (PPNDTHAC) Extramural Unit, Pan African Cancer Research Institute (PACRI), Faculty of Health Sciences, University of Pretoria, Hatfield0028, South Africa
| | - Mzwandile Mbele
- South African Medical Research Council/University of Pretoria Precision Prevention & Novel Drug Targets for HIV-Associated Cancers (PPNDTHAC) Extramural Unit, Pan African Cancer Research Institute (PACRI), Faculty of Health Sciences, University of Pretoria, Hatfield0028, South Africa
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15
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Saini S, Walia GK, Sachdeva MP, Gupta V. Genetics of obesity and its measures in India. J Genet 2018. [DOI: 10.1007/s12041-018-0987-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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16
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A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci. Genetics 2018; 210:499-515. [PMID: 30108127 DOI: 10.1534/genetics.118.301479] [Citation(s) in RCA: 96] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Accepted: 08/08/2018] [Indexed: 12/31/2022] Open
Abstract
Body mass index (BMI), a proxy measure for obesity, is determined by both environmental (including ethnicity, age, and sex) and genetic factors, with > 400 BMI-associated loci identified to date. However, the impact, interplay, and underlying biological mechanisms among BMI, environment, genetics, and ancestry are not completely understood. To further examine these relationships, we utilized 427,509 calendar year-averaged BMI measurements from 100,418 adults from the single large multiethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We observed substantial independent ancestry and nationality differences, including ancestry principal component interactions and nonlinear effects. To increase the list of BMI-associated variants before assessing other differences, we conducted a genome-wide association study (GWAS) in GERA, with replication in the Genetic Investigation of Anthropomorphic Traits (GIANT) consortium combined with the UK Biobank (UKB), followed by GWAS in GERA combined with GIANT, with replication in the UKB. We discovered 30 novel independent BMI loci (P < 5.0 × 10-8) that replicated. We then assessed the proportion of BMI variance explained by sex in the UKB using previously identified loci compared to previously and newly identified loci and found slight increases: from 3.0 to 3.3% for males and from 2.7 to 3.0% for females. Further, the variance explained by previously and newly identified variants decreased with increasing age in the GERA and UKB cohorts, echoed in the variance explained by the entire genome, which also showed gene-age interaction effects. Finally, we conducted a tissue expression QTL enrichment analysis, which revealed that GWAS BMI-associated variants were enriched in the cerebellum, consistent with prior work in humans and mice.
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AMPK activation negatively regulates GDAP1, which influences metabolic processes and circadian gene expression in skeletal muscle. Mol Metab 2018; 16:12-23. [PMID: 30093355 PMCID: PMC6157647 DOI: 10.1016/j.molmet.2018.07.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2018] [Revised: 06/26/2018] [Accepted: 07/01/2018] [Indexed: 12/31/2022] Open
Abstract
Objective We sought to identify AMPK-regulated genes via bioinformatic analysis of microarray data generated from skeletal muscle of animal models with genetically altered AMPK activity. We hypothesized that such genes would play a role in metabolism. Ganglioside-induced differentiation-associated protein 1 (GDAP1), a gene which plays a role in mitochondrial fission and peroxisomal function in neuronal cells but whose function in skeletal muscle is undescribed, was identified and further validated. AMPK activation reduced GDAP1 expression in skeletal muscle. GDAP1 expression was elevated in skeletal muscle from type 2 diabetic patients but decreased after acute exercise. Methods The metabolic impact of GDAP1 silencing was determined in primary skeletal muscle cells via siRNA-transfections. Confocal microscopy was used to visualize whether silencing GDAP1 impacted mitochondrial network morphology and membrane potential. Results GDAP1 silencing increased mitochondrial protein abundance, decreased palmitate oxidation, and decreased non-mitochondrial respiration. Mitochondrial morphology was unaltered by GDAP1 silencing. GDAP1 silencing and treatment of cells with AMPK agonists altered several genes in the core molecular clock machinery. Conclusion We describe a role for GDAP1 in regulating mitochondrial proteins, circadian genes, and metabolic flux in skeletal muscle. Collectively, our results implicate GDAP1 in the circadian control of metabolism. Transcriptomic studies reveal GDAP1 mRNA is inversely associated with AMPK activity. GDAP1 silencing increases mitochondrial protein abundance in skeletal muscle. GDAP1 silencing influences expression of core molecular clock machinery. GDAP1 is a AMPK target involved in metabolism and circadian gene expression.
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18
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The antihypertensive MTHFR gene polymorphism rs17367504-G is a possible novel protective locus for preeclampsia. J Hypertens 2017; 35:132-139. [PMID: 27755385 PMCID: PMC5131692 DOI: 10.1097/hjh.0000000000001131] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Preeclampsia is a complex heterogeneous disease commonly defined by new-onset hypertension and proteinuria in pregnancy. Women experiencing preeclampsia have increased risk for cardiovascular diseases (CVD) later in life. Preeclampsia and CVD share risk factors and pathophysiologic mechanisms, including dysregulated inflammation and raised blood pressure. Despite commonalities, little is known about the contribution of shared genes (pleiotropy) to these diseases. This study aimed to investigate whether genetic risk factors for hypertension or inflammation are pleiotropic by also being associated with preeclampsia. METHODS We genotyped 122 single nucleotide polymorphisms (SNPs) in women with preeclampsia (n = 1006) and nonpreeclamptic controls (n = 816) from the Norwegian HUNT Study. SNPs were chosen on the basis of previously reported associations with either nongestational hypertension or inflammation in genome-wide association studies. The SNPs were tested for association with preeclampsia in a multiple logistic regression model. RESULTS The minor (G) allele of the intronic SNP rs17367504 in the gene methylenetetrahydrofolate reductase (MTHFR) was associated with a protective effect on preeclampsia (odds ratio 0.65, 95% confidence interval 0.53-0.80) in the Norwegian cohort. This association did not replicate in an Australian preeclampsia case-control cohort (P = 0.68, odds ratio 1.05, 95% confidence interval 0.83-1.32, minor allele frequency = 0.15). CONCLUSION MTHFR is important for regulating transmethylation processes and is involved in regulation of folate metabolism. The G allele of rs17367504 has previously been shown to protect against nongestational hypertension. Our study suggests a novel association between this allele and reduced risk for preeclampsia. This is the first study associating the minor (G) allele of a SNP within the MTHFR gene with a protective effect on preeclampsia, and in doing so identifying a possible pleiotropic protective effect on preeclampsia and hypertension.
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Pausova Z, Paus T, Abrahamowicz M, Bernard M, Gaudet D, Leonard G, Peron M, Pike GB, Richer L, Séguin JR, Veillette S. Cohort Profile: The Saguenay Youth Study (SYS). Int J Epidemiol 2017; 46:e19. [PMID: 27018016 PMCID: PMC5837575 DOI: 10.1093/ije/dyw023] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/20/2016] [Indexed: 01/15/2023] Open
Abstract
The Saguenay Youth Study (SYS) is a two-generational study of adolescents and their parents (n = 1029 adolescents and 962 parents) aimed at investigating the aetiology, early stages and trans-generational trajectories of common cardiometabolic and brain diseases. The ultimate goal of this study is to identify effective means for increasing healthy life expectancy. The cohort was recruited from the genetic founder population of the Saguenay Lac St Jean region of Quebec, Canada. The participants underwent extensive (15-h) phenotyping, including an hour-long recording of beat-by-beat blood pressure, magnetic resonance imaging of the brain and abdomen, and serum lipidomic profiling with LC-ESI-MS. All participants have been genome-wide genotyped (with ∼ 8 M imputed single nucleotide polymorphisms) and a subset of them (144 adolescents and their 288 parents) has been genome-wide epityped (whole blood DNA, Infinium HumanMethylation450K BeadChip). These assessments are complemented by a detailed evaluation of each participant in a number of domains, including cognition, mental health and substance use, diet, physical activity and sleep, and family environment. The data collection took place during 2003-12 in adolescents (full) and their parents (partial), and during 2012-15 in parents (full). All data are available upon request.
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Affiliation(s)
- Zdenka Pausova
- Hospital for Sick Children and Departments of Physiology and Nutritional Science
| | - Tomas Paus
- Rotman Research Institute and Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
- Child Mind Institute, New York, NY, USA
| | - Michal Abrahamowicz
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Manon Bernard
- Hospital for Sick Children and Departments of Physiology and Nutritional Science
| | - Daniel Gaudet
- Community Genomic Centre, Université de Montréal, Chicoutimi, QC, Canada
| | - Gabriel Leonard
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Michel Peron
- Department of Human Sciences, Université du Québec à Chicoutimi, Chicoutimi, QC, Canada
| | - G Bruce Pike
- Hotchkiss Brain Institute, University of Calgary, Calgary, BC, Canada
| | - Louis Richer
- Department of Health Sciences, Université du Québec à Chicoutimi, Chicoutimi, QC, Canada and
| | - Jean R Séguin
- Sainte-Justine Hospital Research Center and Department of Psychiatry, Université de Montréal, Montreal, QC, Canada
| | - Suzanne Veillette
- Department of Human Sciences, Université du Québec à Chicoutimi, Chicoutimi, QC, Canada
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20
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Dumitrescu L, Ritchie MD, Denny JC, El Rouby NM, McDonough CW, Bradford Y, Ramirez AH, Bielinski SJ, Basford MA, Chai HS, Peissig P, Carrell D, Pathak J, Rasmussen LV, Wang X, Pacheco JA, Kho AN, Hayes MG, Matsumoto M, Smith ME, Li R, Cooper-DeHoff RM, Kullo IJ, Chute CG, Chisholm RL, Jarvik GP, Larson EB, Carey D, McCarty CA, Williams MS, Roden DM, Bottinger E, Johnson JA, de Andrade M, Crawford DC. Genome-wide study of resistant hypertension identified from electronic health records. PLoS One 2017; 12:e0171745. [PMID: 28222112 PMCID: PMC5319785 DOI: 10.1371/journal.pone.0171745] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2016] [Accepted: 01/25/2017] [Indexed: 12/11/2022] Open
Abstract
Resistant hypertension is defined as high blood pressure that remains above treatment goals in spite of the concurrent use of three antihypertensive agents from different classes. Despite the important health consequences of resistant hypertension, few studies of resistant hypertension have been conducted. To perform a genome-wide association study for resistant hypertension, we defined and identified cases of resistant hypertension and hypertensives with treated, controlled hypertension among >47,500 adults residing in the US linked to electronic health records (EHRs) and genotyped as part of the electronic MEdical Records & GEnomics (eMERGE) Network. Electronic selection logic using billing codes, laboratory values, text queries, and medication records was used to identify resistant hypertension cases and controls at each site, and a total of 3,006 cases of resistant hypertension and 876 controlled hypertensives were identified among eMERGE Phase I and II sites. After imputation and quality control, a total of 2,530,150 SNPs were tested for an association among 2,830 multi-ethnic cases of resistant hypertension and 876 controlled hypertensives. No test of association was genome-wide significant in the full dataset or in the dataset limited to European American cases (n = 1,719) and controls (n = 708). The most significant finding was CLNK rs13144136 at p = 1.00x10-6 (odds ratio = 0.68; 95% CI = 0.58–0.80) in the full dataset with similar results in the European American only dataset. We also examined whether SNPs known to influence blood pressure or hypertension also influenced resistant hypertension. None was significant after correction for multiple testing. These data highlight both the difficulties and the potential utility of EHR-linked genomic data to study clinically-relevant traits such as resistant hypertension.
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Affiliation(s)
- Logan Dumitrescu
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Marylyn D. Ritchie
- Biomedical and Translational Informatics, Geisinger Health System, Danville, Pennsylvania, United States of America
| | - Joshua C. Denny
- Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Medicine, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Nihal M. El Rouby
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, Florida, United States of America
| | - Caitrin W. McDonough
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, Florida, United States of America
| | - Yuki Bradford
- Biomedical and Translational Informatics, Geisinger Health System, Danville, Pennsylvania, United States of America
| | - Andrea H. Ramirez
- Department of Medicine, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Suzette J. Bielinski
- Division of Epidemiology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Melissa A. Basford
- Office of Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - High Seng Chai
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Peggy Peissig
- Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, United States of America
| | - David Carrell
- Group Health Research Institute, Seattle, Washington, United States of America
| | - Jyotishman Pathak
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Luke V. Rasmussen
- Department of Preventive Medicine, Division of Health and Biomedical Informatics, Northwestern University, Chicago, Illinois, United States of America
| | - Xiaoming Wang
- Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Jennifer A. Pacheco
- Center for Genetic Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Abel N. Kho
- Department Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - M. Geoffrey Hayes
- Department Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Martha Matsumoto
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Maureen E. Smith
- Center for Genetic Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Rongling Li
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, Florida, United States of America
- Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Iftikhar J. Kullo
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Christopher G. Chute
- Division of General Internal Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Rex L. Chisholm
- Center for Genetic Medicine, Northwestern University, Chicago, Illinois, United States of America
| | - Gail P. Jarvik
- Department of Medicine, University of Washington Medical Center, Seattle, Washington, United States of America
| | - Eric B. Larson
- Group Health Research Institute, Seattle, Washington, United States of America
| | - David Carey
- Weis Center for Research, Geisinger Health System, Danville, Pennsylvania, United States of America
| | | | - Marc S. Williams
- Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, United States of America
| | - Dan M. Roden
- Department of Medicine, Vanderbilt University, Nashville, Tennessee, United States of America
- Department of Pharmacology, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Erwin Bottinger
- Charles R. Bronfman Institute for Personalized Medicine, Mount Sinai, New York, New York, United States of America
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, Florida, United States of America
- Division of Cardiovascular Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Mariza de Andrade
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Dana C. Crawford
- Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail:
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21
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Dalle Molle R, Fatemi H, Dagher A, Levitan RD, Silveira PP, Dubé L. Gene and environment interaction: Is the differential susceptibility hypothesis relevant for obesity? Neurosci Biobehav Rev 2016; 73:326-339. [PMID: 28024828 DOI: 10.1016/j.neubiorev.2016.12.028] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Revised: 12/09/2016] [Accepted: 12/20/2016] [Indexed: 02/04/2023]
Abstract
The differential susceptibility model states that a given genetic variant is associated with an increased risk of pathology in negative environments but greater than average resilience in enriched ones. While this theory was first implemented in psychiatric-genetic research, it may also help us to unravel the complex ways that genes and environments interact to influence feeding behavior and obesity. We reviewed evidence on gene vs. environment interactions that influence obesity development, aiming to support the applicability of the differential susceptibility model for this condition, and propose that various environmental "layers" relevant for human development should be considered when bearing the differential susceptibility model in mind. Mother-child relationship, socioeconomic status and individual's response are important modifiers of BMI and food intake when interacting with gene variants, "for better and for worse". While only a few studies to date have investigated obesity outcomes using this approach, we propose that the differential susceptibility hypothesis is in fact highly applicable to the study of genetic and environmental influences on feeding behavior and obesity risk.
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Affiliation(s)
- Roberta Dalle Molle
- Desautels Faculty of Management, McGill Center for the Convergence of Health and Economics, McGill University, Bronfman Building, 1001 Sherbrooke St. W., Montreal, QC H3A 1G5, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada.
| | - Hajar Fatemi
- Desautels Faculty of Management, McGill Center for the Convergence of Health and Economics, McGill University, Bronfman Building, 1001 Sherbrooke St. W., Montreal, QC H3A 1G5, Canada
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, QC H3A 2B4, Canada
| | - Robert D Levitan
- Department of Psychiatry, University of Toronto and Centre for Addiction and Mental Health, 100 Stokes Street, Toronto, ON M6J 1H4, Canada
| | - Patricia P Silveira
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Douglas Institute, Perry Pavilion, 6875 Boulevard LaSalle, Montreal, QC H4H 1R3, Canada
| | - Laurette Dubé
- Desautels Faculty of Management, McGill Center for the Convergence of Health and Economics, McGill University, Bronfman Building, 1001 Sherbrooke St. W., Montreal, QC H3A 1G5, Canada
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22
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Kim SK, Avila JJ, Massett MP. Strain survey and genetic analysis of vasoreactivity in mouse aorta. Physiol Genomics 2016; 48:861-873. [PMID: 27764765 DOI: 10.1152/physiolgenomics.00054.2016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 09/25/2016] [Indexed: 11/22/2022] Open
Abstract
Understanding the genetic influence on vascular reactivity is important for identifying genes underlying impaired vascular function. The purpose of this study was to characterize the genetic contribution to intrinsic vascular function and to identify loci associated with phenotypic variation in vascular reactivity in mice. Concentration response curves to phenylephrine (PE), potassium chloride (KCl), acetylcholine (ACh), and sodium nitroprusside (SNP) were generated in aortic rings from male mice (12 wk old) from 27 inbred mouse strains. Significant strain-dependent differences were found for both maximal responses and sensitivity for each agent, except for SNP Max (%). Strain differences for maximal responses to ACh, PE, and KCl varied by two- to fivefold. On the basis of these large strain differences, we performed genome-wide association mapping (GWAS) to identify loci associated with variation in responses to these agents. GWAS for responses to ACh identified four significant and 19 suggestive loci. Several suggestive loci for responses to SNP, PE, and KCl (including one significant locus for KCl EC50) were also identified. These results demonstrate that intrinsic endothelial function, and more generally vascular function, is genetically determined and associated with multiple genomic loci. Furthermore, these results are supported by the finding that several genes residing in significant and suggestive loci for responses to ACh were previously identified in rat and/or human quantitative trait loci/GWAS for cardiovascular disease. This study represents the first step toward the unbiased comprehensive discovery of genetic determinants that regulate intrinsic vascular function, particularly endothelial function.
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Affiliation(s)
- Seung Kyum Kim
- Department of Health and Kinesiology, Texas A&M University, College Station, Texas
| | - Joshua J Avila
- Department of Health and Kinesiology, Texas A&M University, College Station, Texas
| | - Michael P Massett
- Department of Health and Kinesiology, Texas A&M University, College Station, Texas
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23
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A GWA study reveals genetic loci for body conformation traits in Chinese Laiwu pigs and its implications for human BMI. Mamm Genome 2016; 27:610-621. [PMID: 27473603 DOI: 10.1007/s00335-016-9657-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 07/06/2016] [Indexed: 12/20/2022]
Abstract
Pigs share numerous physiological and phenotypic similarities with human and thus have been considered as a good model in nonrodent mammals for the study of genetic basis of human obesity. Researches on candidate genes for obesity traits have successfully identified some common genes between humans and pigs. However, few studies have assessed how many similarities exist between the genetic architecture of obesity in pigs and humans by large-scale comparative genomics. Here, we performed a genome-wide association study (GWAS) using the porcine 60 K SNP Beadchip for BMI and other four conformation traits at three different ages in a Chinese Laiwu pig population, which shows a large variability in fat deposition. In total, 35 SNPs were found to be significant at Bonferroni-corrected 5 % chromosome-wise level (P = 2.13 × 10-5) and 88 SNPs had suggestive (P < 10-4) association with the conformation traits. Some SNPs showed age-dependent association. Intriguingly, out of 32 regions associated with BMI in pigs, 18 were homologous with the loci for BMI in humans. Furthermore, five closest genes to GWAS peaks including HIF1AN, SMYD3, COX10, SLMAP, and GBE1 have been already associated with BMI in humans, which makes them very promising candidates for these QTLs. The result of GO analysis provided strong support to the fact that mitochondria and synapse play important roles in obesity susceptibility, which is consistent with previous findings on human obesity, and it also implicated new gene sets related to chromatin modification and Ig-like C2-type 5 domain. Therefore, these results not only provide new insights into the genetic architecture of BMI in pigs but also highlight that humans and pigs share the significant overlap of obesity-related genes.
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24
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Parmar PG, Taal HR, Timpson NJ, Thiering E, Lehtimäki T, Marinelli M, Lind PA, Howe LD, Verwoert G, Aalto V, Uitterlinden AG, Briollais L, Evans DM, Wright MJ, Newnham JP, Whitfield JB, Lyytikäinen LP, Rivadeneira F, Boomsma DI, Viikari J, Gillman MW, St Pourcain B, Hottenga JJ, Montgomery GW, Hofman A, Kähönen M, Martin NG, Tobin MD, Raitakari O, Vioque J, Jaddoe VW, Jarvelin MR, Beilin LJ, Heinrich J, van Duijn CM, Pennell CE, Lawlor DA, Palmer LJ. International Genome-Wide Association Study Consortium Identifies Novel Loci Associated With Blood Pressure in Children and Adolescents. CIRCULATION. CARDIOVASCULAR GENETICS 2016; 9:266-278. [PMID: 26969751 PMCID: PMC5279885 DOI: 10.1161/circgenetics.115.001190] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2015] [Accepted: 02/25/2016] [Indexed: 01/11/2023]
Abstract
BACKGROUND Our aim was to identify genetic variants associated with blood pressure (BP) in childhood and adolescence. METHODS AND RESULTS Genome-wide association study data from participating European ancestry cohorts of the Early Genetics and Lifecourse Epidemiology (EAGLE) Consortium was meta-analyzed across 3 epochs; prepuberty (4-7 years), puberty (8-12 years), and postpuberty (13-20 years). Two novel loci were identified as having genome-wide associations with systolic BP across specific age epochs: rs1563894 (ITGA11, located in active H3K27Ac mark and transcription factor chromatin immunoprecipitation and 5'-C-phosphate-G-3' methylation site) during prepuberty (P=2.86×10(-8)) and rs872256 during puberty (P=8.67×10(-9)). Several single-nucleotide polymorphism clusters were also associated with childhood BP at P<5×10(-3). Using a P value threshold of <5×10(-3), we found some overlap in variants across the different age epochs within our study and between several single-nucleotide polymorphisms in any of the 3 epochs and adult BP-related single-nucleotide polymorphisms. CONCLUSIONS Our results suggest that genetic determinants of BP act from childhood, develop over the lifecourse, and show some evidence of age-specific effects.
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25
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Gopisetty G, Thangarajan R. Mammalian mitochondrial ribosomal small subunit (MRPS) genes: A putative role in human disease. Gene 2016; 589:27-35. [PMID: 27170550 DOI: 10.1016/j.gene.2016.05.008] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2016] [Accepted: 05/06/2016] [Indexed: 12/25/2022]
Abstract
Mitochondria are prominently understood as power houses producing ATP the primary energy currency of the cell. However, mitochondria are also known to play an important role in apoptosis and autophagy, and mitochondrial dysregulation can lead to pathological outcomes. Mitochondria are known to contain 1500 proteins of which only 13 are coded by mitochondrial DNA and the rest are coded by nuclear genes. Protein synthesis in mitochondria involves mitochondrial ribosomes which are 55-60S particles and are composed of small 28S and large 39S subunits. A feature of mammalian mitoribosome which differentiate it from bacterial ribosomes is the increased protein content. The human mitochondrial ribosomal protein (MRP) gene family comprises of 30 genes which code for mitochondrial ribosomal small subunit and 50 genes for the large subunit. The present review focuses on the mitochondrial ribosomal small subunit genes (MRPS), presents an overview of the literature and data gleaned from publicly available gene and protein expression databases. The survey revealed aberrations in MRPS gene expression patterns in varied human diseases indicating a putative role in their etiology.
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Affiliation(s)
- Gopal Gopisetty
- Department of Molecular Oncology, Cancer Institute (WIA), Chennai, India
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26
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Pant SD, Karlskov-Mortensen P, Jacobsen MJ, Cirera S, Kogelman LJA, Bruun CS, Mark T, Jørgensen CB, Grarup N, Appel EVR, Galjatovic EAA, Hansen T, Pedersen O, Guerin M, Huby T, Lesnik P, Meuwissen THE, Kadarmideen HN, Fredholm M. Comparative Analyses of QTLs Influencing Obesity and Metabolic Phenotypes in Pigs and Humans. PLoS One 2015; 10:e0137356. [PMID: 26348622 PMCID: PMC4562524 DOI: 10.1371/journal.pone.0137356] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2015] [Accepted: 08/14/2015] [Indexed: 12/31/2022] Open
Abstract
The pig is a well-known animal model used to investigate genetic and mechanistic aspects of human disease biology. They are particularly useful in the context of obesity and metabolic diseases because other widely used models (e.g. mice) do not completely recapitulate key pathophysiological features associated with these diseases in humans. Therefore, we established a F2 pig resource population (n = 564) designed to elucidate the genetics underlying obesity and metabolic phenotypes. Segregation of obesity traits was ensured by using breeds highly divergent with respect to obesity traits in the parental generation. Several obesity and metabolic phenotypes were recorded (n = 35) from birth to slaughter (242 ± 48 days), including body composition determined at about two months of age (63 ± 10 days) via dual-energy x-ray absorptiometry (DXA) scanning. All pigs were genotyped using Illumina Porcine 60k SNP Beadchip and a combined linkage disequilibrium-linkage analysis was used to identify genome-wide significant associations for collected phenotypes. We identified 229 QTLs which associated with adiposity- and metabolic phenotypes at genome-wide significant levels. Subsequently comparative analyses were performed to identify the extent of overlap between previously identified QTLs in both humans and pigs. The combined analysis of a large number of obesity phenotypes has provided insight in the genetic architecture of the molecular mechanisms underlying these traits indicating that QTLs underlying similar phenotypes are clustered in the genome. Our analyses have further confirmed that genetic heterogeneity is an inherent characteristic of obesity traits most likely caused by segregation or fixation of different variants of the individual components belonging to cellular pathways in different populations. Several important genes previously associated to obesity in human studies, along with novel genes were identified. Altogether, this study provides novel insight that may further the current understanding of the molecular mechanisms underlying human obesity.
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Affiliation(s)
- Sameer D. Pant
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter Karlskov-Mortensen
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mette J. Jacobsen
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Susanna Cirera
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lisette J. A. Kogelman
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Camilla S. Bruun
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Mark
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Claus B. Jørgensen
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Emil V. R. Appel
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ehm A. A. Galjatovic
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maryse Guerin
- INSERM UMR_S 1166, Integrative Biology of Atherosclerosis Team, F-75013, Paris, France
- Sorbonne Universités UPMC Univ Paris 06 UMR_S 1166, Integrative Biology of Atherosclerosis Team, F-75013, Paris, France
- Institute of Cardiometabolism and Nutrition (ICAN), Pitié-Salpêtrière Hospital, 75013, Paris, France
| | - Thierry Huby
- INSERM UMR_S 1166, Integrative Biology of Atherosclerosis Team, F-75013, Paris, France
- Sorbonne Universités UPMC Univ Paris 06 UMR_S 1166, Integrative Biology of Atherosclerosis Team, F-75013, Paris, France
- Institute of Cardiometabolism and Nutrition (ICAN), Pitié-Salpêtrière Hospital, 75013, Paris, France
| | - Philipppe Lesnik
- INSERM UMR_S 1166, Integrative Biology of Atherosclerosis Team, F-75013, Paris, France
- Sorbonne Universités UPMC Univ Paris 06 UMR_S 1166, Integrative Biology of Atherosclerosis Team, F-75013, Paris, France
- Institute of Cardiometabolism and Nutrition (ICAN), Pitié-Salpêtrière Hospital, 75013, Paris, France
| | - Theo H. E. Meuwissen
- Institute of Animal and Agricultural Sciences, Norwegian University of Life Sciences, Ås, Norway
| | - Haja N. Kadarmideen
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- * E-mail: (MF); (HNK)
| | - Merete Fredholm
- Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- * E-mail: (MF); (HNK)
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Abstract
There is growing concern about elevated blood pressure (BP) in children. The evidence for familial aggregation of childhood BP is substantial. Twin studies have shown that a large part of the familial aggregation of childhood BP is due to genes. The first part of this review provides the latest progress in gene finding for childhood BP, focusing on the combined effects of multiple loci identified from the genome-wide association studies on adult BP. We further review the evidence on the contribution of the genetic components of other family risk factors to the familial aggregation of childhood BP including obesity, birth weight, sleep quality, sodium intake, parental smoking, and socioeconomic status. At the end, we emphasize the promise of using genomic-relatedness-matrix restricted maximum likelihood (GREML) analysis, a method that uses genome-wide data from unrelated individuals, in answering a number of unsolved questions in the familial aggregation of childhood BP.
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Affiliation(s)
- Xiaoling Wang
- Georgia Prevention Center, Medical College of Georgia, Georgia Regents University, HS-1640, Augusta, GA, 30912, USA,
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28
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Paus T, Pausova Z, Abrahamowicz M, Gaudet D, Leonard G, Pike GB, Richer L. Saguenay Youth Study: a multi-generational approach to studying virtual trajectories of the brain and cardio-metabolic health. Dev Cogn Neurosci 2015; 11:129-44. [PMID: 25454417 PMCID: PMC6989769 DOI: 10.1016/j.dcn.2014.10.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2014] [Revised: 10/03/2014] [Accepted: 10/10/2014] [Indexed: 01/06/2023] Open
Abstract
This paper provides an overview of the Saguenay Youth Study (SYS) and its parental arm. The overarching goal of this effort is to develop trans-generational models of developmental cascades contributing to the emergence of common chronic disorders, such as depression, addictions, dementia and cardio-metabolic diseases. Over the past 10 years, we have acquired detailed brain and cardio-metabolic phenotypes, and genome-wide genotypes, in 1029 adolescents recruited in a population with a known genetic founder effect. At present, we are extending this dataset to acquire comparable phenotypes and genotypes in the biological parents of these individuals. After providing conceptual background for this work (transactions across time, systems and organs), we describe briefly the tools employed in the adolescent arm of this cohort and highlight some of the initial accomplishments. We then outline in detail the phenotyping protocol used to acquire comparable data in the parents.
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Affiliation(s)
- T Paus
- Rotman Research Institute, University of Toronto, Toronto, Canada.
| | - Z Pausova
- Hospital for Sick Children, University of Toronto, Toronto, Canada.
| | - M Abrahamowicz
- McGill University Health Centre, McGill University, Montreal, Canada
| | - D Gaudet
- Community Genomic Medicine Centre, Department of Medicine, Université de Montréal, Chicoutimi, Canada
| | - G Leonard
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - G B Pike
- Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - L Richer
- Department of Health Sciences, University of Quebec in Chicoutimi, Chicoutimi, Canada
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29
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Wen W, Zheng W, Okada Y, Takeuchi F, Tabara Y, Hwang JY, Dorajoo R, Li H, Tsai FJ, Yang X, He J, Wu Y, He M, Zhang Y, Liang J, Guo X, Sheu WHH, Delahanty R, Guo X, Kubo M, Yamamoto K, Ohkubo T, Go MJ, Liu JJ, Gan W, Chen CC, Gao Y, Li S, Lee NR, Wu C, Zhou X, Song H, Yao J, Lee IT, Long J, Tsunoda T, Akiyama K, Takashima N, Cho YS, Ong RT, Lu L, Chen CH, Tan A, Rice TK, Adair LS, Gui L, Allison M, Lee WJ, Cai Q, Isomura M, Umemura S, Kim YJ, Seielstad M, Hixson J, Xiang YB, Isono M, Kim BJ, Sim X, Lu W, Nabika T, Lee J, Lim WY, Gao YT, Takayanagi R, Kang DH, Wong TY, Hsiung CA, Wu IC, Juang JMJ, Shi J, Choi BY, Aung T, Hu F, Kim MK, Lim WY, Wang TD, Shin MH, Lee J, Ji BT, Lee YH, Young TL, Shin DH, Chun BY, Cho MC, Han BG, Hwu CM, Assimes TL, Absher D, Yan X, Kim E, Kuo JZ, Kwon S, Taylor KD, Chen YDI, Rotter JI, Qi L, Zhu D, Wu T, Mohlke KL, Gu D, Mo Z, Wu JY, Lin X, Miki T, Tai ES, Lee JY, Kato N, Shu XO, Tanaka T. Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index. Hum Mol Genet 2014; 23:5492-504. [PMID: 24861553 PMCID: PMC4168820 DOI: 10.1093/hmg/ddu248] [Citation(s) in RCA: 148] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2013] [Revised: 03/22/2014] [Accepted: 05/19/2014] [Indexed: 12/28/2022] Open
Abstract
Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488-47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10(-13)), ALDH2/MYL2 (rs671, P = 3.40 × 10(-11); rs12229654, P = 4.56 × 10(-9)), ITIH4 (rs2535633, P = 1.77 × 10(-10)) and NT5C2 (rs11191580, P = 3.83 × 10(-8)) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10(-8)) and an additional 14 at P < 1.0 × 10(-3) with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity.
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Affiliation(s)
- Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Yukinori Okada
- Laboratory for Statistical Analysis, Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Joo-Yeon Hwang
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore, Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK
| | - Huaixing Li
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai 200031, China
| | - Fuu-Jen Tsai
- School of Chinese Medicine, Department of Medical Genetics, Department of Health and Nutrition Biotechnology, Asia University, Taichung, Taiwan
| | - Xiaobo Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Meian He
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yi Zhang
- State Key Laboratory of Medical Genetics, Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, Shanghai Institute of Hypertension, Shanghai, China
| | - Jun Liang
- Department of Endocrinology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical College, Affiliated Hospital of Southeast University, Xuzhou, Jiangsu 221009, China
| | - Xiuqing Guo
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Institute for Translational Genomics and Populations Sciences, Torrance, CA, USA
| | - Wayne Huey-Herng Sheu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan, National Defense Medical Center, College of Medicine, Taipei, Taiwan, School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Ryan Delahanty
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | | | - Ken Yamamoto
- Department of Molecular Genetics, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
| | - Takayoshi Ohkubo
- Department of Planning for Drug Development and Clinical Evaluation, Tohoku University Graduate School of Pharmaceutical Sciences, Sendai, Japan, Department of Health Science, Shiga University of Medical Science, Otsu, Japan
| | - Min Jin Go
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Jian Jun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Wei Gan
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai 200031, China
| | - Ching-Chu Chen
- School of Chinese Medicine, Division of Endocrinology and Metabolism, Department of Medicine, China Medical University Hospital, Taichung, Taiwan
| | - Yong Gao
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China, College of General Practice, Guangxi Medical University, Nanning, Guangxi, China
| | - Shengxu Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu, Philippines
| | - Chen Wu
- State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xueya Zhou
- Bioinformatics Division, Tsinghua National Laboratory of Information Science and Technology, Beijing, China
| | - Huaidong Song
- State Key Laboratory of Medical Genomics, Ruijin Hospital, Molecular Medical Center, Shanghai Institute of Endocrinology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Yao
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Institute for Translational Genomics and Populations Sciences, Torrance, CA, USA
| | - I-Te Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan, Department of Medicine, Chung-Shan Medical University, Taichung, Taiwan
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | | | - Koichi Akiyama
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Naoyuki Takashima
- Department of Health Science, Shiga University of Medical Science, Otsu, Japan
| | - Yoon Shin Cho
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea, Department of Biomedical Science, Hallym University, Gangwon-do, Republic of Korea
| | - Rick Th Ong
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, Centre for Molecular Epidemiology, National University of Singapore, Singapore, Singapore
| | - Ling Lu
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai 200031, China
| | - Chien-Hsiun Chen
- School of Chinese Medicine, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Aihua Tan
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Treva K Rice
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Linda S Adair
- Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA
| | - Lixuan Gui
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | | | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan, Department of Social Work, Tunghai University, Taichung, Taiwan
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Minoru Isomura
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, Japan
| | - Satoshi Umemura
- Department of Medical Science and Cardiorenal Medicine, Yokohama City University School of Medicine, Yokohama, Japan
| | - Young Jin Kim
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Mark Seielstad
- Institute of Human Genetics, University of California, San Francisco, USA
| | - James Hixson
- Human Genetics Center, University of Texas School of Public Health, Houston, TX, USA
| | - Yong-Bing Xiang
- Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Bong-Jo Kim
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Xueling Sim
- Centre for Molecular Epidemiology, National University of Singapore, Singapore, Singapore
| | - Wei Lu
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Toru Nabika
- Department of Functional Pathology, Shimane University School of Medicine, Izumo, Japan
| | - Juyoung Lee
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | | | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Ryoichi Takayanagi
- Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Dae-Hee Kang
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, Department of Ophthalmology, Yong Loo Lin School of Medicine
| | - Chao Agnes Hsiung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - I-Chien Wu
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Jyh-Ming Jimmy Juang
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Jiajun Shi
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Bo Youl Choi
- Department of Preventive Medicine, College of Medicine, Hanyang University, Seoul, Republic of Korea
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore, Department of Ophthalmology, Yong Loo Lin School of Medicine
| | - Frank Hu
- Department of Epidemiology, Department of Nutrition, Harvard University School of Public Health, Boston, MA, USA
| | - Mi Kyung Kim
- Department of Preventive Medicine, College of Medicine, Hanyang University, Seoul, Republic of Korea
| | | | - Tzung-Dao Wang
- Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Min-Ho Shin
- Department of Preventive Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea
| | | | - Bu-Tian Ji
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Young-Hoon Lee
- Department of Preventive Medicine & Institute of Wonkwang Medical Science, Wonkwang University College of Medicine, Iksan, Republic of Korea
| | - Terri L Young
- Department of Ophthalmology, Duke University Medical Center, Durham, NC, USA, Division of Neuroscience, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Dong Hoon Shin
- Department of Preventive Medicine, Keimyung University School of Medicine, Daegu, Republic of Korea
| | - Byung-Yeol Chun
- Department of Preventive Medicine, School of Medicine, and Health Promotion Research Center, Kyungpook National University, Daegu, Republic of Korea
| | - Myeong-Chan Cho
- National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Bok-Ghee Han
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Chii-Min Hwu
- School of Medicine, National Yang-Ming University, Taipei, Taiwan, Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | | | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Xiaofei Yan
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Institute for Translational Genomics and Populations Sciences, Torrance, CA, USA
| | - Eric Kim
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Institute for Translational Genomics and Populations Sciences, Torrance, CA, USA
| | - Jane Z Kuo
- NShiley Eye Center, Department of Ophthalmology, University of California at San Diego, La Jolla, CA, USA
| | - Soonil Kwon
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Institute for Translational Genomics and Populations Sciences, Torrance, CA, USA
| | - Kent D Taylor
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Institute for Translational Genomics and Populations Sciences, Torrance, CA, USA
| | - Yii-Der I Chen
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Institute for Translational Genomics and Populations Sciences, Torrance, CA, USA
| | - Jerome I Rotter
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Institute for Translational Genomics and Populations Sciences, Torrance, CA, USA
| | - Lu Qi
- Department of Nutrition, Harvard University School of Public Health, Boston, MA, USA, Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, USA
| | - Dingliang Zhu
- State Key Laboratory of Medical Genetics, Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, Shanghai Institute of Hypertension, Shanghai, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Dongfeng Gu
- Department of Evidence Based Medicine, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, and National Center for Cardiovascular Diseases, Beijing, China
| | - Zengnan Mo
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China, Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Jer-Yuarn Wu
- School of Chinese Medicine, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Xu Lin
- Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Shanghai 200031, China
| | - Tetsuro Miki
- Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Toon, Japan
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, and National University Health System, Singapore, Singapore Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Jong-Young Lee
- Center for Genome Science, National Institute of Health, Osong Health Technology Administration Complex, Chungcheongbuk-do, Republic of Korea
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA,
| | - Toshihiro Tanaka
- Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan, Laboratory for Cardiovascular Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan, Division of Disease Diversity, Bioresource Research Center, Tokyo Medical and Dental University, Tokyo, Japan
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Souto JC, Pena G, Ziyatdinov A, Buil A, López S, Fontcuberta J, Soria JM. A genomewide study of body mass index and its genetic correlation with thromboembolic risk. Results from the GAIT project. Thromb Haemost 2014; 112:1036-43. [PMID: 25118907 DOI: 10.1160/th14-03-0275] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2014] [Accepted: 06/13/2014] [Indexed: 11/05/2022]
Abstract
Thrombosis and obesity are complex epidemiologically associated diseases. The mechanism of this association is not yet understood. It was the objective of this study to identify genetic components of body mass index (BMI) and their possible role in the risk of thromboembolic disease. With the self-reported BMI of 397 individuals from 21 extended families enrolled in the GAIT (Genetic Analysis of Idiopathic Thrombophilia) Project, we estimated the heritability of BMI and the genetic correlation with the risk of thrombosis. Subjects were genotyped for an autosomal genome-wide scan with 363 highly-informative DNA markers. Univariate and bivariate multipoint linkage analyses were performed. The heritability for BMI was 0.31 (p=2.9×10⁻⁵). Thromboembolic disease (including venous and arterial) and BMI had a significant genetic correlation (ρG=0.54, p=0.005). Two linkage signals for BMI were obtained, one at 13q34 (LOD=3.36, p=0.0004) and other at 2q34, highly suggestive of linkage (LOD=1.95). Bivariate linkage analysis with BMI and thrombosis risk also showed a significant signal at 13q34 (LOD=3), indicating that this locus influences at the same time normal variation in the BMI phenotype as well as susceptibility to thrombosis. In conclusion, BMI and thrombosis are genetically correlated. The locus 13q34, which showed pleiotropy with both phenotypes, contains two candidate genes, which may explain our linkage pleiotropic signal and deserve further investigation as possible risk factors for obesity and thrombosis.
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Affiliation(s)
- Juan Carlos Souto
- Juan Carlos Souto, MD, PhD, Unitat d'Hemostàsia i Trombosi, Hospital de la Santa Creu i Sant Pau, Sant Antoni Maria Claret 167, 08025, Barcelona, Spain, Tel.: +34 93 5537151, Fax: +34 93 5537153, E-mail:
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Abstract
Obesity is a highly heritable trait. While acute and chronic changes in body weight or obesity-related comorbidities are heavily influenced by environmental factors, there are still strong genomic modifiers that help account for inter-subject variability in baseline traits and in response to interventions. This review is intended to provide an up-to-date overview of our current understanding of genetic influences on obesity, with emphasis on genetic modifiers of baseline traits and responses to intervention. We begin by reviewing how genetic variants can influence obesity. We then examine genetic modifiers of weight loss via different intervention strategies, focusing on known and potential modifiers of surgical weight loss outcomes. We will pay particular attention to the effects of patient age on outcomes, addressing the risks and benefits of adopting early intervention strategies. Finally, we will discuss how the field of bariatric surgery can leverage knowledge of genetic modifiers to adopt a personalized medicine approach for optimal outcomes across this widespread and diverse patient population.
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Affiliation(s)
- Samantha Sevilla
- Research Center for Genetic Medicine, Children's National Medical Center, 111 Michigan Ave NW, Washington, DC 20010
| | - Monica J Hubal
- Research Center for Genetic Medicine, Children's National Medical Center, 111 Michigan Ave NW, Washington, DC 20010.
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Influence of FTO variants on obesity, inflammation and cardiovascular disease risk biomarkers in Spanish children: a case-control multicentre study. BMC MEDICAL GENETICS 2013; 14:123. [PMID: 24289790 PMCID: PMC3866940 DOI: 10.1186/1471-2350-14-123] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2013] [Accepted: 11/25/2013] [Indexed: 11/25/2022]
Abstract
Background Variants in the FTO gene have been associated with obesity in children, but this association has not been shown with other biomarkers. We assessed the association of 52 FTO polymorphisms, spanning the whole gene, with obesity and estimated the influence of these polymorphisms on anthropometric, clinical and metabolic parameters as well as inflammation and cardiovascular disease (CVD) risk biomarkers among Spanish children. Methods A multicentre case–control study was conducted in 534 children (292 obese and 242 with normal-BMI). Anthropometric, clinical, metabolic, inflammation and CVD risk markers were compared using the Student’s t-test for unpaired samples. The genotype relative risk was assessed by comparing the obese and normal-BMI group, calculating the odds ratio. The association of each SNP with phenotypic parameters was analysed using either logistic or linear regression analysis. Results All anthropometric, clinical and metabolic factors as well as inflammatory and CVD risk biomarkers were higher in the obese than in the normal-BMI group, except adiponectin and HDL-c that were lower, and glucose, LDL-c, and metalloproteinase-9 that did not show difference. Four polymorphisms (rs9935401, rs9939609, rs9928094 and rs9930333) were positively associated with obesity and in linkage disequilibrium between each other; the haplotype including the risk alleles of these polymorphisms showed a high risk for obesity. The rs8061518 was negatively associated with obesity and the haplotype including this SNP and rs3826169, rs17818902 and rs7190053 showed a decreased risk for obesity. Additionally, the rs8061518 was associated with weight, diastolic blood pressure, insulin, homeostatic model assessment of insulin resistance, leptin, and active plasminogen inhibitor activator-1 after sex and age adjustment; however, after an additional BMI adjustment, this polymorphism remained associated only with leptin. Conclusions We validated the previous reported association of genetic variability in intron 1 of the FTO gene with the risk of obesity and found no association with other related traits in this region of the gene. We have observed strong statistical evidence for an association of rs8061518 in intron 3 of the gene with decreased risk of obesity and low concentration of leptin.
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Pei YF, Zhang L, Liu Y, Li J, Shen H, Liu YZ, Tian Q, He H, Wu S, Ran S, Han Y, Hai R, Lin Y, Zhu J, Zhu XZ, Papasian CJ, Deng HW. Meta-analysis of genome-wide association data identifies novel susceptibility loci for obesity. Hum Mol Genet 2013; 23:820-30. [PMID: 24064335 DOI: 10.1093/hmg/ddt464] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Obesity is a major public health problem with strong genetic determination. Multiple genetic variants have been implicated for obesity by conducting genome-wide association (GWA) studies, primarily focused on body mass index (BMI). Fat body mass (FBM) is phenotypically more homogeneous than BMI and is more appropriate for obesity research; however, relatively few studies have been conducted on FBM. Aiming to identify variants associated with obesity, we carried out meta-analyses of seven GWA studies for BMI-related traits including FBM, and followed these analyses by de novo replication. The discovery cohorts consisted of 21 969 individuals from diverse ethnic populations and a total of over 4 million genotyped or imputed SNPs. The de novo replication cohorts consisted of 6663 subjects from two independent samples. To complement individual SNP-based association analyses, we also carried out gene-based GWA analyses in which all variations within a gene were considered jointly. Individual SNP-based association analyses identified a novel locus 1q21 [rs2230061, CTSS (Cathepsin S)] that was associated with FBM after the adjustment of lean body mass (LBM) (P = 3.57 × 10(-8)) at the genome-wide significance level. Gene-based association analyses identified a novel gene NLK (nemo-like kinase) in 17q11 that was significantly associated with FBM adjusted by LBM. In addition, we confirmed three previously reported obesity susceptibility loci: 16q12 [rs62033400, P = 1.97 × 10(-14), FTO (fat mass and obesity associated)], 18q22 [rs6567160, P = 8.09 × 10(-19), MC4R (melanocortin 4 receptor)] and 2p25 [rs939583, P = 1.07 × 10(-7), TMEM18 (transmembrane protein 18)]. We also found that rs6567160 may exert pleiotropic effects to both FBM and LBM. Our results provide additional insights into the molecular genetic basis of obesity and may provide future targets for effective prevention and therapeutic intervention.
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Affiliation(s)
- Yu-Fang Pei
- Center of System Biomedical Sciences, University of Shanghai for Science and Technology, Shanghai 200093, P R China
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Patton IT, McPherson AC. Anthropometric measurements in Canadian children: a scoping review. Canadian Journal of Public Health 2013; 104:e369-74. [PMID: 24183177 DOI: 10.17269/cjph.104.4032] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2013] [Revised: 09/18/2013] [Accepted: 09/17/2013] [Indexed: 01/02/2023]
Abstract
OBJECTIVE The objective of the current study was to identify what forms of anthropometric measurement are currently being utilized with Canadian children and youth and what are the gaps in the literature on this topic. METHODS The current study utilized a scoping review methodology in order to achieve the study objectives. Online databases Medline and PubMed and CINAHL were used to search articles from the last decade (2002-2012) that addressed Canadian children aged 2-18 years. SYNTHESIS 50 studies were included in this review. A variety of anthropometric measurements were identified, including body mass index, waist circumference, hip-to-waist ratio, among others. Six of the included studies (12%) utilized nationally representative data from large-scale studies. BMI was the most reported form of measurement with 88% of studies collecting it. Waist circumference was a distant second with 20% of studies reporting it. Several gaps in the literature exist with regards to First Nations (FN) research; many of the measurement methods were not used. Additionally, FN accounted for only 2.5% of the study's sample. The majority of studies took place in Quebec (29%) and Ontario (27%). CONCLUSION Body mass index is the most reported method of anthropometric measurement used for children. Efforts should be taken by health care practitioners and researchers to collect other forms of measurement in order to assist in understanding the validity of other measures and their value when used with children. Furthermore, attention needs to be focused on utilizing and studying various forms of anthropometric measurement across all Canadian regions and populations.
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Vasan SK, Fall T, Job V, Gu HF, Ingelsson E, Brismar K, Karpe F, Thomas N. A common variant in the FTO locus is associated with waist-hip ratio in Indian adolescents. Pediatr Obes 2013; 8:e45-9. [PMID: 23447422 DOI: 10.1111/j.2047-6310.2013.00118.x] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2012] [Revised: 10/04/2012] [Accepted: 10/15/2012] [Indexed: 12/01/2022]
Abstract
BACKGROUND Common variants in the FTO locus, and near MC4R locus, have been shown to have a robust association with obesity in children and adults among various ethnic groups. Associations with obesity traits among Indian adolescents have not been determined. OBJECTIVE To study the association of rs9939609 (FTO) and rs17782313 (MC4R) to obesity related anthropometric traits in Indian adolescents. METHODS Subjects for the current study were recruited from a cross-sectional cohort of 1,230 adolescents (age mean ± SD: 17.1 ± 1.9 years) from South India. RESULTS The variant at the FTO locus was found to be associated with waist-hip ratio (WHR) but not with overall obesity in this population. No significant association was observed for obesity-traits and Mc4R variant rs17782313. CONCLUSION The common variant of FTO (rs9939609) is associated with body fat distribution during early growth in Indian adolescents and may predispose to obesity and metabolic consequences in adulthood.
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Affiliation(s)
- S K Vasan
- Rolf Luft Research Center for Diabetes and Endocrinology, Department of Molecular Medicine & Surgery, Karolinska Institutet, Stockholm, Sweden.
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Searching for genes involved in hypertension development in special populations: children and pre-eclamptic women. Where are we standing now? Clin Chem Lab Med 2013; 51:2253-69. [DOI: 10.1515/cclm-2013-0405] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2013] [Accepted: 07/23/2013] [Indexed: 01/02/2023]
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Melanocortin-4 Receptor in Energy Homeostasis and Obesity Pathogenesis. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2013; 114:147-91. [DOI: 10.1016/b978-0-12-386933-3.00005-4] [Citation(s) in RCA: 115] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Melka MG, Gillis J, Bernard M, Abrahamowicz M, Chakravarty MM, Leonard GT, Perron M, Richer L, Veillette S, Banaschewski T, Barker GJ, Büchel C, Conrod P, Flor H, Heinz A, Garavan H, Brühl R, Mann K, Artiges E, Lourdusamy A, Lathrop M, Loth E, Schwartz Y, Frouin V, Rietschel M, Smolka MN, Ströhle A, Gallinat J, Struve M, Lattka E, Waldenberger M, Schumann G, Pavlidis P, Gaudet D, Paus T, Pausova Z. FTO, obesity and the adolescent brain. Hum Mol Genet 2012. [PMID: 23201753 DOI: 10.1093/hmg/dds504] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Genetic variations in fat mass- and obesity (FTO)-associated gene, a well-replicated gene locus of obesity, appear to be associated also with reduced regional brain volumes in elderly. Here, we examined whether FTO is associated with total brain volume in adolescence, thus exploring possible developmental effects of FTO. We studied a population-based sample of 598 adolescents recruited from the French Canadian founder population in whom we measured brain volume by magnetic resonance imaging. Total fat mass was assessed with bioimpedance and body mass index was determined with anthropometry. Genotype-phenotype associations were tested with Merlin under an additive model. We found that the G allele of FTO (rs9930333) was associated with higher total body fat [TBF (P = 0.002) and lower brain volume (P = 0.005)]. The same allele was also associated with higher lean body mass (P = 0.03) and no difference in height (P = 0.99). Principal component analysis identified a shared inverse variance between the brain volume and TBF, which was associated with FTO at P = 5.5 × 10(-6). These results were replicated in two independent samples of 413 and 718 adolescents, and in a meta-analysis of all three samples (n = 1729 adolescents), FTO was associated with this shared inverse variance at P = 1.3 × 10(-9). Co-expression networks analysis supported the possibility that the underlying FTO effects may occur during embryogenesis. In conclusion, FTO is associated with shared inverse variance between body adiposity and brain volume, suggesting that this gene may exert inverse effects on adipose and brain tissues. Given the completion of the overall brain growth in early childhood, these effects may have their origins during early development.
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Affiliation(s)
- Melkaye G Melka
- The Hospital for Sick Children, University of Toronto, Toronto, Canada
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Xi B, Zhang M, Wang C, Shen Y, Zhao X, Wang X, Mi J. The common SNP (rs9939609) in the FTO gene modifies the association between obesity and high blood pressure in Chinese children. Mol Biol Rep 2012; 40:773-8. [PMID: 23111453 DOI: 10.1007/s11033-012-2113-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2012] [Accepted: 10/03/2012] [Indexed: 02/02/2023]
Abstract
Previous studies have suggested that common variants in fat mass- and obesity-associated (FTO) gene are associated with body mass index (BMI) and the risk of obesity. Since obesity plays an important role in the etiology of high blood pressure (HBP), we aim to investigate the association between obesity and HBP in a population with different variants of the FTO gene. A total of 3,494 children (1,775 boys, 50.8 %) aged 6-18 years were recruited for measuring pubertal status, BMI and systolic and diastolic blood pressure. The single nucleotide polymorphism rs9939609 of the FTO gene was genotyped. The blood pressure levels increased by 1.4, 1.5 and 1.8 mmHg for systolic blood pressure and 0.8, 0.9 and 1.2 mmHg for diastolic blood pressure per 1-unit BMI increase in subjects carrying TT, TA and AA genotypes, respectively. After stratifying for FTO rs9939609 genotypes (TT, TA and AA), the odds ratios (95 % confidence intervals) of HBP in obese versus non-obese children were 4.26 (3.18-5.71), 5.13 (2.96-8.90) and 10.37 (1.59-67.43), respectively, with adjustment for age, gender and pubertal status. The FTO rs9939609 SNP modifies the effect of obesity on HBP in Chinese children, with obese ones carrying the AA homozygous genotype of the FTO rs9939609 having the highest risk of developing HBP.
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Affiliation(s)
- Bo Xi
- Department of Maternal and Child Health Care, School of Public Health, Shandong University, Jinan, 250012, China
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Liu F, van der Lijn F, Schurmann C, Zhu G, Chakravarty MM, Hysi PG, Wollstein A, Lao O, de Bruijne M, Ikram MA, van der Lugt A, Rivadeneira F, Uitterlinden AG, Hofman A, Niessen WJ, Homuth G, de Zubicaray G, McMahon KL, Thompson PM, Daboul A, Puls R, Hegenscheid K, Bevan L, Pausova Z, Medland SE, Montgomery GW, Wright MJ, Wicking C, Boehringer S, Spector TD, Paus T, Martin NG, Biffar R, Kayser M. A genome-wide association study identifies five loci influencing facial morphology in Europeans. PLoS Genet 2012; 8:e1002932. [PMID: 23028347 PMCID: PMC3441666 DOI: 10.1371/journal.pgen.1002932] [Citation(s) in RCA: 196] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2012] [Accepted: 07/13/2012] [Indexed: 12/11/2022] Open
Abstract
Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes--PRDM16, PAX3, TP63, C5orf50, and COL17A1--in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.
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Affiliation(s)
- Fan Liu
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Fedde van der Lijn
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Medical Informatics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Claudia Schurmann
- Interfaculty Institute for Genetics and Functional Genomics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
| | - Gu Zhu
- Queensland Institute of Medical Research, Brisbane, Australia
| | - M. Mallar Chakravarty
- Rotman Research Institute, University of Toronto, Toronto, Canada
- Centre for Addiction and Mental Health, University of Toronto, Toronto, Canada
| | - Pirro G. Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Andreas Wollstein
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Oscar Lao
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marleen de Bruijne
- Department of Medical Informatics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M. Arfan Ikram
- Department of Radiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Aad van der Lugt
- Department of Radiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Wiro J. Niessen
- Department of Medical Informatics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Imaging Science and Technology, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
| | - Greig de Zubicaray
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Katie L. McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Paul M. Thompson
- Laboratory of Neuroimaging, School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America
| | - Amro Daboul
- Center of Oral Health, Department of Prosthodontics, Gerostomatology, and Dental Materials, University Medicine Greifswald, Greifswald, Germany
| | - Ralf Puls
- Department of Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Katrin Hegenscheid
- Department of Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Liisa Bevan
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Zdenka Pausova
- The Hospital of Sick Children, University of Toronto, Toronto, Canada
| | | | | | | | - Carol Wicking
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
| | - Stefan Boehringer
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Tomáš Paus
- Rotman Research Institute, University of Toronto, Toronto, Canada
- Montréal Neurological Institute, McGill University, Montréal, Canada
| | | | - Reiner Biffar
- Center of Oral Health, Department of Prosthodontics, Gerostomatology, and Dental Materials, University Medicine Greifswald, Greifswald, Germany
| | - Manfred Kayser
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
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