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Mollon J, Knowles EEM, Mathias SR, Rodrigue A, Moore TM, Calkins ME, Gur RC, Peralta JM, Weiner DJ, Robinson EB, Gur RE, Blangero J, Almasy L, Glahn DC. Genetic influences on externalizing psychopathology overlap with cognitive functioning and show developmental variation. Eur Psychiatry 2021; 64:e29. [PMID: 33785081 PMCID: PMC8080212 DOI: 10.1192/j.eurpsy.2021.21] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Questions remain regarding whether genetic influences on early life psychopathology overlap with cognition and show developmental variation. METHODS Using data from 9,421 individuals aged 8-21 from the Philadelphia Neurodevelopmental Cohort, factors of psychopathology were generated using a bifactor model of item-level data from a psychiatric interview. Five orthogonal factors were generated: anxious-misery (mood and anxiety), externalizing (attention deficit hyperactivity and conduct disorder), fear (phobias), psychosis-spectrum, and a general factor. Genetic analyses were conducted on a subsample of 4,662 individuals of European American ancestry. A genetic relatedness matrix was used to estimate heritability of these factors, and genetic correlations with executive function, episodic memory, complex reasoning, social cognition, motor speed, and general cognitive ability. Gene × Age analyses determined whether genetic influences on these factors show developmental variation. RESULTS Externalizing was heritable (h2 = 0.46, p = 1 × 10-6), but not anxious-misery (h2 = 0.09, p = 0.183), fear (h2 = 0.04, p = 0.337), psychosis-spectrum (h2 = 0.00, p = 0.494), or general psychopathology (h2 = 0.21, p = 0.040). Externalizing showed genetic overlap with face memory (ρg = -0.412, p = 0.004), verbal reasoning (ρg = -0.485, p = 0.001), spatial reasoning (ρg = -0.426, p = 0.010), motor speed (ρg = 0.659, p = 1x10-4), verbal knowledge (ρg = -0.314, p = 0.002), and general cognitive ability (g)(ρg = -0.394, p = 0.002). Gene × Age analyses revealed decreasing genetic variance (γg = -0.146, p = 0.004) and increasing environmental variance (γe = 0.059, p = 0.009) on externalizing. CONCLUSIONS Cognitive impairment may be a useful endophenotype of externalizing psychopathology and, therefore, help elucidate its pathophysiological underpinnings. Decreasing genetic variance suggests that gene discovery efforts may be more fruitful in children than adolescents or young adults.
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Affiliation(s)
- Josephine Mollon
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Emma E M Knowles
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Samuel R Mathias
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Amanda Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Tyler M Moore
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Monica E Calkins
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ruben C Gur
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Juan Manuel Peralta
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, Texas, USA
| | - Daniel J Weiner
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Elise B Robinson
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Raquel E Gur
- Brain Behavior Laboratory, Department of Psychiatry, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, Texas, USA
| | - Laura Almasy
- Department of Genetics, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.,Olin Neuropsychiatry Research Center, Institute of Living, Hartford, Connecticut, USA
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2
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Genetic influence on cognitive development between childhood and adulthood. Mol Psychiatry 2021; 26:656-665. [PMID: 30644433 PMCID: PMC6570578 DOI: 10.1038/s41380-018-0277-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 08/15/2018] [Accepted: 09/11/2018] [Indexed: 12/17/2022]
Abstract
Successful cognitive development between childhood and adulthood has important consequences for future mental and physical wellbeing, as well as occupational and financial success. Therefore, delineating the genetic influences underlying changes in cognitive abilities during this developmental period will provide important insights into the biological mechanisms that govern both typical and atypical maturation. Using data from the Philadelphia Neurodevelopmental Cohort (PNC), a large population-based sample of individuals aged 8 to 21 years old (n = 6634), we used an empirical relatedness matrix to establish the heritability of general and specific cognitive functions and determine if genetic factors influence cognitive maturation (i.e., Gene × Age interactions) between childhood and early adulthood. We found that neurocognitive measures across childhood and early adulthood were significantly heritable. Moreover, genetic variance on general cognitive ability, or g, increased significantly between childhood and early adulthood. Finally, we did not find evidence for decay in genetic correlation on neurocognition throughout childhood and adulthood, suggesting that the same genetic factors underlie cognition at different ages throughout this developmental period. Establishing significant Gene × Age interactions in neurocognitive functions across childhood and early adulthood is a necessary first step in identifying genes that influence cognitive development, rather than genes that influence cognition per se. Moreover, since aberrant cognitive development confers risk for several psychiatric disorders, further examination of these Gene × Age interactions may provide important insights into their etiology.
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Pizzagalli F, Auzias G, Yang Q, Mathias SR, Faskowitz J, Boyd JD, Amini A, Rivière D, McMahon KL, de Zubicaray GI, Martin NG, Mangin JF, Glahn DC, Blangero J, Wright MJ, Thompson PM, Kochunov P, Jahanshad N. The reliability and heritability of cortical folds and their genetic correlations across hemispheres. Commun Biol 2020; 3:510. [PMID: 32934300 PMCID: PMC7493906 DOI: 10.1038/s42003-020-01163-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 07/24/2020] [Indexed: 12/22/2022] Open
Abstract
Cortical folds help drive the parcellation of the human cortex into functionally specific regions. Variations in the length, depth, width, and surface area of these sulcal landmarks have been associated with disease, and may be genetically mediated. Before estimating the heritability of sulcal variation, the extent to which these metrics can be reliably extracted from in-vivo MRI must be established. Using four independent test-retest datasets, we found high reliability across the brain (intraclass correlation interquartile range: 0.65-0.85). Heritability estimates were derived for three family-based cohorts using variance components analysis and pooled (total N > 3000); the overall sulcal heritability pattern was correlated to that derived for a large population cohort (N > 9000) calculated using genomic complex trait analysis. Overall, sulcal width was the most heritable metric, and earlier forming sulci showed higher heritability. The inter-hemispheric genetic correlations were high, yet select sulci showed incomplete pleiotropy, suggesting hemisphere-specific genetic influences.
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Grants
- P41 EB015922 NIBIB NIH HHS
- R01 EB015611 NIBIB NIH HHS
- P01 AG026276 NIA NIH HHS
- R21 NS064534 NINDS NIH HHS
- R01 MH078111 NIMH NIH HHS
- R01 HD050735 NICHD NIH HHS
- R01 NS056307 NINDS NIH HHS
- R01 MH121246 NIMH NIH HHS
- P50 MH071616 NIMH NIH HHS
- R03 EB012461 NIBIB NIH HHS
- R01 AG059874 NIA NIH HHS
- U24 RR021382 NCRR NIH HHS
- P30 AG066444 NIA NIH HHS
- P01 AG003991 NIA NIH HHS
- P50 AG005681 NIA NIH HHS
- U54 EB020403 NIBIB NIH HHS
- R01 MH117601 NIMH NIH HHS
- U54 MH091657 NIMH NIH HHS
- R01 AG021910 NIA NIH HHS
- R01 MH078143 NIMH NIH HHS
- P41 RR015241 NCRR NIH HHS
- S10 OD023696 NIH HHS
- R01 MH083824 NIMH NIH HHS
- This research was funded in part by NIH ENIGMA Center grant U54 EB020403, supported by the Big Data to Knowledge (BD2K) Centers of Excellence program funded by a cross-NIH initiative. Additional grant support was provided by: R01 AG059874, R01 MH117601, R01 MH121246, and P41 EB015922. QTIM was supported by NIH R01 HD050735, and the NHMRC 486682, Australia; GOBS: Financial support for this study was provided by the National Institute of Mental Health grants MH078143 (PI: DC Glahn), MH078111 (PI: J Blangero), and MH083824 (PI: DC Glahn & J Blangero); HCP data were provided [in part] by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University; UK Biobank: This research was conducted using the UK Biobank Resource under Application Number ‘11559’; BrainVISA’s Morphologist software development received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Grant Agreement No 720270 & 785907 (Human Brain ProjectSGA1 & SGA2), and by the FRM DIC20161236445. OASIS: Cross-Sectional: Principal Investigators: D. Marcus, R. Buckner, J. Csernansky J. Morris; P50 AG05681, P01 AG03991, P01 AG026276, R01 AG021910, P20 MH071616, U24 RR021382. KKI was supported by NIH grants NCRR P41 RR015241 (Peter C.M. van Zijl), 1R01NS056307 (Jerry Prince), 1R21NS064534-01A109 (Bennett A. Landman/Jerry L. Prince), 1R03EB012461-01 (Bennett A. Landman). Neda Jahanshad and Paul Thompson are MPIs of a research project grant from Biogen, Inc. (PO 969323).
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Affiliation(s)
- Fabrizio Pizzagalli
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA.
| | - Guillaume Auzias
- Institut de Neurosciences de la Timone, UMR7289, Aix-Marseille Université & CNRS, Marseille, France
| | - Qifan Yang
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Samuel R Mathias
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Joshua Faskowitz
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Joshua D Boyd
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Armand Amini
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Denis Rivière
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, France
- CATI, Multicenter Neuroimaging Platform, Paris, France
| | - Katie L McMahon
- School of Clinical Sciences and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Greig I de Zubicaray
- Faculty of Health, Queensland University of Technology (QUT), Brisbane, QLD, 4000, Australia
| | | | - Jean-François Mangin
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, France
- CATI, Multicenter Neuroimaging Platform, Paris, France
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, 4072, Australia
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA.
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Johnson MP, Keyho R, Blackburn NB, Laston S, Kumar S, Peralta J, Thapa SS, Towne B, Subedi J, Blangero J, Williams-Blangero S. Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors. J Diabetes Res 2019; 2019:2310235. [PMID: 31089471 PMCID: PMC6476113 DOI: 10.1155/2019/2310235] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 12/20/2018] [Accepted: 01/12/2019] [Indexed: 01/08/2023] Open
Abstract
Measurements of fasting glucose (FG) or glycated hemoglobin A1c (HbA1c) are two clinically approved approaches commonly used to determine glycemia, both of which are influenced by genetic factors. Obtaining accurate measurements of FG or HbA1c is not without its challenges, though. Measuring glycated serum protein (GSP) offers an alternative approach for assessing glycemia. The aim of this study was to estimate the heritability of GSP and GSP expressed as a percentage of total serum albumin (%GA) using a variance component approach and localize genomic regions (QTLs) that harbor genes likely to influence GSP and %GA trait variation in a large extended multigenerational pedigree from Jiri, Nepal (n = 1,800). We also performed quantitative bivariate analyses to assess the relationship between GSP or %GA and several cardiometabolic traits. Additive genetic effects significantly influence variation in GSP and %GA levels (p values: 1.15 × 10-5 and 3.39 × 10-5, respectively). We localized a significant (LOD score = 3.18) and novel GSP QTL on chromosome 11q, which has been previously linked to type 2 diabetes. Two common (MAF > 0.4) SNPs within the chromosome 11 QTL were associated with GSP (adjusted pvalue < 5.87 × 10-5): an intronic variant (rs10790184) in the DSCAML1 gene and a 3'UTR variant (rs8258) in the CEP164 gene. Significant positive correlations were observed between GSP or %GA and blood pressure, and lipid traits (p values: 0.0062 to 1.78 × 10-9). A significant negative correlation was observed between %GA and HDL cholesterol (p = 1.12 × 10-5). GSP is influenced by genetic factors and can be used to assess glycemia and diabetes risk. Thus, GSP measurements can facilitate glycemic studies when accurate FG and/or HbA1c measurements are difficult to obtain. GSP can also be measured from frozen blood (serum) samples, which allows the prospect of retrospective glycemic studies using archived samples.
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Affiliation(s)
- Matthew P. Johnson
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Ryan Keyho
- The University of Texas at Austin, Austin, Texas 78705, USA
| | - Nicholas B. Blackburn
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Sandra Laston
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Satish Kumar
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Juan Peralta
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Menzies Institute for Medical Research, University of Tasmania, Hobart 7000, Australia
| | - Suman S. Thapa
- Tilganga Institute of Ophthalmology, Gaushala, Bagmati Bridge, P.O. Box 561, Kathmandu, Nepal
| | - Bradford Towne
- Department of Population Health and Public Health Sciences, Boonshoft School of Medicine, Wright State University, Kettering, Ohio 45435, USA
| | - Janardan Subedi
- Department of Sociology and Gerontology, College of Arts and Science, Miami University, Oxford, Ohio 45056, USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Sarah Williams-Blangero
- South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
- Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
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Scurrah KJ, Lamantia A, Ellis JA, Harrap SB. Familial Analysis of Epistatic and Sex-Dependent Association of Genes of the Renin-Angiotensin-Aldosterone System and Blood Pressure. ACTA ACUST UNITED AC 2018; 10:CIRCGENETICS.116.001595. [PMID: 28506960 DOI: 10.1161/circgenetics.116.001595] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Accepted: 03/02/2017] [Indexed: 01/11/2023]
Abstract
BACKGROUND Renin-angiotensin-aldosterone system genes have been inconsistently associated with blood pressure, possibly because of unrecognized influences of sex-dependent genetic effects or gene-gene interactions (epistasis). METHODS AND RESULTS We tested association of systolic blood pressure with single-nucleotide polymorphisms (SNPs) at renin (REN), angiotensinogen (AGT), angiotensin-converting enzyme (ACE), angiotensin II type 1 receptor (AGTR1), and aldosterone synthase (CYP11B2), including sex-SNP or SNP-SNP interactions. Eighty-eight tagSNPs were tested in 2872 white individuals in 809 pedigrees from the Victorian Family Heart Study using variance components models. Three SNPs (rs8075924 and rs4277404 at ACE and rs12721297 at AGTR1) were individually associated with lower systolic blood pressure with significant (P<0.00076) effect sizes ≈1.7 to 2.5 mm Hg. Sex-specific associations were seen for 3 SNPs in men (rs2468523 and rs2478544 at AGT and rs11658531 at ACE) and 1 SNP in women (rs12451328 at ACE). SNP-SNP interaction was suggested (P<0.005) for 14 SNP pairs, none of which had shown individual association with systolic blood pressure. Four SNP pairs were at the same gene (2 for REN, 1 for AGT, and 1 for AGTR1). The SNP rs3097 at CYP11B2 was represented in 5 separate pairs. CONCLUSIONS SNPs at key renin-angiotensin-aldosterone system genes associate with systolic blood pressure individually in both sexes, individually in one sex only and only when combined with another SNP. Analyses that incorporate sex-dependent and epistatic effects could reconcile past inconsistencies and account for some of the missing heritability of blood pressure and are generally relevant to SNP association studies for any phenotype.
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Affiliation(s)
- Katrina J Scurrah
- From the Department of Physiology (K.J.S., A.L., S.B.H.), Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health (K.J.S.), and Department of Paediatrics (J.A.E.), The University of Melbourne, Australia; Genes, Environment & Complex Disease Unit, Murdoch Children's Research Institute, Parkville, Victoria, Australia (J.A.E.); and Centre for Social and Early Emotional Development, Faculty of Health, Deakin University, Victoria, Australia (J.A.E.)
| | - Angela Lamantia
- From the Department of Physiology (K.J.S., A.L., S.B.H.), Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health (K.J.S.), and Department of Paediatrics (J.A.E.), The University of Melbourne, Australia; Genes, Environment & Complex Disease Unit, Murdoch Children's Research Institute, Parkville, Victoria, Australia (J.A.E.); and Centre for Social and Early Emotional Development, Faculty of Health, Deakin University, Victoria, Australia (J.A.E.)
| | - Justine A Ellis
- From the Department of Physiology (K.J.S., A.L., S.B.H.), Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health (K.J.S.), and Department of Paediatrics (J.A.E.), The University of Melbourne, Australia; Genes, Environment & Complex Disease Unit, Murdoch Children's Research Institute, Parkville, Victoria, Australia (J.A.E.); and Centre for Social and Early Emotional Development, Faculty of Health, Deakin University, Victoria, Australia (J.A.E.)
| | - Stephen B Harrap
- From the Department of Physiology (K.J.S., A.L., S.B.H.), Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health (K.J.S.), and Department of Paediatrics (J.A.E.), The University of Melbourne, Australia; Genes, Environment & Complex Disease Unit, Murdoch Children's Research Institute, Parkville, Victoria, Australia (J.A.E.); and Centre for Social and Early Emotional Development, Faculty of Health, Deakin University, Victoria, Australia (J.A.E.).
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6
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Bearden CE, Glahn DC. Cognitive genomics: Searching for the genetic roots of neuropsychological functioning. Neuropsychology 2017; 31:1003-1019. [PMID: 29376674 PMCID: PMC5791763 DOI: 10.1037/neu0000412] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVE Human cognition has long been known to be under substantial genetic control. With the complete mapping of the human genome, genome-wide association studies for many complex traits have proliferated; however, the highly polygenic nature of intelligence has made the identification of the precise genes that influence both global and specific cognitive abilities more difficult than anticipated. METHOD Here, we review the latest developments in the genomics of cognition, including a discussion of methodological advances in the genetic analysis of complex traits, and shared genetic contributions to cognitive abilities and neuropsychiatric disorders. RESULTS A wealth of twin and family studies have provided compelling evidence for a strong heritable component of both global and specific cognitive abilities, and for the existence of "generalist genes" responsible for a large portion of the variance in diverse cognitive abilities. Increasingly sophisticated analytic tools and ever-larger sample sizes are now facilitating the identification of specific genetic and molecular underpinnings of cognitive abilities, leading to optimism regarding possibilities for novel treatments for illnesses related to cognitive function. CONCLUSIONS We conclude with a set of future directions for the field, which will further accelerate discoveries regarding the biological pathways relevant to cognitive abilities. These, in turn, may be further interrogated in order to link biological mechanisms to behavior. (PsycINFO Database Record
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Affiliation(s)
- Carrie E Bearden
- Department of Psychiatry, University of California at Los Angeles
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7
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Runge CL, Indap A, Zhou Y, Kent JW, King E, Erbe CB, Cole R, Littrell J, Merath K, James R, Rüschendorf F, Kerschner JE, Marth G, Hübner N, Göring HHH, Friedland DR, Kwok WM, Olivier M. Association of TMTC2 With Human Nonsyndromic Sensorineural Hearing Loss. JAMA Otolaryngol Head Neck Surg 2017; 142:866-72. [PMID: 27311106 DOI: 10.1001/jamaoto.2016.1444] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
IMPORTANCE Sensorineural hearing loss (SNHL) is commonly caused by conditions that affect cochlear structures or the auditory nerve, and the genes identified as causing SNHL to date only explain a fraction of the overall genetic risk for this debilitating disorder. It is likely that other genes and mutations also cause SNHL. OBJECTIVE To identify a candidate gene that causes bilateral, symmetric, progressive SNHL in a large multigeneration family of Northern European descent. DESIGN, SETTING, AND PARTICIPANTS In this prospective genotype and phenotype study performed from January 1, 2006, through April 1, 2016, a 6-generation family of Northern European descent with 19 individuals having reported early-onset hearing loss suggestive of an autosomal dominant inheritance were studied at a tertiary academic medical center. In addition, 179 unrelated adult individuals with SNHL and 186 adult individuals reporting nondeafness were examined. MAIN OUTCOMES AND MEASURES Sensorineural hearing loss. RESULTS Nine family members (5 women [55.6%]) provided clinical audiometric and medical records that documented hearing loss. The hearing loss is characterized as bilateral, symmetric, progressive SNHL that reached severe to profound loss in childhood. Audiometric configurations demonstrated a characteristic dip at 1000 to 2000 Hz. All affected family members wear hearing aids or have undergone cochlear implantation. Exome sequencing and linkage and association analyses identified a fully penetrant sequence variant (rs35725509) on chromosome 12q21 (logarithm of odds, 3.3) in the TMTC2 gene region that segregates with SNHL in this family. This gene explains the SNHL occurrence in this family. The variant is also associated with SNHL in a cohort of 363 unrelated individuals (179 patients with confirmed SNHL and 184 controls, P = 7 × 10-4). CONCLUSIONS AND RELEVANCE A previously uncharacterized gene, TMTC2, has been identified as a candidate for causing progressive SNHL in humans. This finding identifies a novel locus that causes autosomal dominant SNHL and therefore a more detailed understanding of the genetic basis of SNHL. Because TMTC2 has not been previously reported to regulate auditory function, the discovery reveals a potentially new, uncharacterized mechanism of hearing loss.
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Affiliation(s)
- Christina L Runge
- Department of Otolaryngology and Communication Sciences, Medical College of Wisconsin, Milwaukee
| | - Amit Indap
- Department of Biology, Boston College, Chestnut Hill, Massachusetts
| | - Yifan Zhou
- Department of Pharmacology and Toxicology, Medical College of Wisconsin, Milwaukee
| | - Jack W Kent
- Department of Genetics, Texas Biomedical Research Institute, San Antonio
| | - Ericka King
- Department of Otolaryngology and Communication Sciences, Medical College of Wisconsin, Milwaukee
| | - Christy B Erbe
- Department of Otolaryngology and Communication Sciences, Medical College of Wisconsin, Milwaukee
| | - Regina Cole
- Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee
| | - Jack Littrell
- Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee
| | - Kate Merath
- Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee
| | - Roland James
- Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee
| | | | - Joseph E Kerschner
- Department of Otolaryngology and Communication Sciences, Medical College of Wisconsin, Milwaukee
| | - Gabor Marth
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City
| | - Norbert Hübner
- Max Delbrück Center for Molecular Medicine, Berlin-Buch, Germany
| | - Harald H H Göring
- Department of Genetics, Texas Biomedical Research Institute, San Antonio
| | - David R Friedland
- Department of Otolaryngology and Communication Sciences, Medical College of Wisconsin, Milwaukee
| | - Wai-Meng Kwok
- Department of Pharmacology and Toxicology, Medical College of Wisconsin, Milwaukee8Department of Anesthesiology, Medical College of Wisconsin, Milwaukee
| | - Michael Olivier
- Department of Genetics, Texas Biomedical Research Institute, San Antonio5Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee
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8
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Mahaney MC, Karere GM, Rainwater DL, Voruganti VS, Dick EJ, Owston MA, Rice KS, Cox LA, Comuzzie AG, VandeBerg JL. Diet-induced early-stage atherosclerosis in baboons: Lipoproteins, atherogenesis, and arterial compliance. J Med Primatol 2017. [PMID: 28620920 DOI: 10.1111/jmp.12283] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND The purpose of this study was to determine whether dietary manipulation can reliably induce early-stage atherosclerosis and clinically relevant changes in vascular function in an established, well-characterized non-human primate model. METHODS We fed 112 baboons a high-cholesterol, high-fat challenge diet for two years. We assayed circulating biomarkers of cardiovascular disease (CVD) risk, at 0, 7, and 104 weeks into the challenge; assessed arterial compliance noninvasively at 104 weeks; and measured atherosclerotic lesions in three major arteries at necropsy. RESULTS We observed evidence of atherosclerosis in all but one baboon fed the two-year challenge diet. CVD risk biomarkers, the prevalence, size, and complexity of arterial lesions, plus consequent arterial stiffness, were increased in comparison with dietary control animals. CONCLUSIONS Feeding baboons a high-cholesterol, high-fat diet for two years reliably induces atherosclerosis, with risk factor profiles, arterial lesions, and changes in vascular function also seen in humans.
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Affiliation(s)
- Michael C Mahaney
- South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Genesio M Karere
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - David L Rainwater
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Venkata S Voruganti
- Department of Nutrition and UNC Nutrition Research Institute, University of North Carolina, Kannapolis, NC, USA
| | - Edward J Dick
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Michael A Owston
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Karen S Rice
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Laura A Cox
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA.,Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Anthony G Comuzzie
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA.,Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - John L VandeBerg
- South Texas Diabetes and Obesity Institute, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, USA
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9
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Manousaki D, Kent JW, Haack K, Zhou S, Xie P, Greenwood CM, Brassard P, Newman DE, Cole S, Umans JG, Rouleau G, Comuzzie AG, Richards JB. Toward Precision Medicine: TBC1D4 Disruption Is Common Among the Inuit and Leads to Underdiagnosis of Type 2 Diabetes. Diabetes Care 2016; 39:1889-1895. [PMID: 27561922 DOI: 10.2337/dc16-0769] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Accepted: 08/09/2016] [Indexed: 02/03/2023]
Abstract
OBJECTIVE A common nonsense mutation in TBC1D4 was recently found to substantially increase the odds of type 2 diabetes in Greenlandic Inuit, leading to exclusively increased postprandial glucose. We investigated the frequency and effect of the TBC1D4 mutation on glucose metabolism and type 2 diabetes diagnosis among Canadian and Alaskan Inuit. RESEARCH DESIGN AND METHODS Exome sequencing of the TBC1D4 variant was performed in 114 Inuit from Nunavik, Canada, and Sanger sequencing was undertaken in 1,027 Alaskan Inuit from the Genetics of Coronary Artery Disease in Alaskan Natives (GOCADAN) Study. Association testing evaluated the effect of the TBC1D4 variant on diabetes-related metabolic traits and diagnosis. RESULTS The TBC1D4 mutation was present in 27% of Canadian and Alaskan Inuit. It was strongly associated with higher glucose (effect size +3.3 mmol/L; P = 2.5 x 10-6) and insulin (effect size +175 pmol/L; P = 0.04) 2 h after an oral glucose load in homozygote carriers. TBC1D4 carriers with prediabetes and type 2 diabetes had an increased risk of remaining undiagnosed unless postprandial glucose values were tested (odds ratio 5.4 [95% CI 2.5-12]) compared with noncarriers. Of carriers with prediabetes or type 2 diabetes, 32% would remain undiagnosed without an oral glucose tolerance test (OGTT). CONCLUSIONS Disruption of TBC1D4 is common among North American Inuit, resulting in exclusively elevated postprandial glucose. This leads to underdiagnosis of type 2 diabetes, unless an OGTT is performed. Accounting for genetic factors in the care of Inuit with diabetes provides an opportunity to implement precision medicine in this population.
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Affiliation(s)
- Despoina Manousaki
- Centre for Clinical Epidemiology, Department of Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada.,Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Jack W Kent
- Texas Biomedical Research Institute, San Antonio, TX
| | - Karin Haack
- Texas Biomedical Research Institute, San Antonio, TX
| | - Sirui Zhou
- Department of Medicine, McGill University, Montreal, Quebec, Canada.,Department of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Pingxing Xie
- Department of Medicine, McGill University, Montreal, Quebec, Canada.,Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
| | - Celia M Greenwood
- Centre for Clinical Epidemiology, Department of Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada.,Department of Human Genetics, McGill University, Montreal, Quebec, Canada.,Department of Oncology, McGill University, Montreal, Quebec, Canada
| | - Paul Brassard
- Centre for Clinical Epidemiology, Department of Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada.,Department of Medicine, McGill University, Montreal, Quebec, Canada
| | | | - Shelley Cole
- Texas Biomedical Research Institute, San Antonio, TX
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD.,Georgetown-Howard Universities Center for Clinical and Translational Science, Washington
| | - Guy Rouleau
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada.,Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | | | - J Brent Richards
- Centre for Clinical Epidemiology, Department of Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada .,Department of Human Genetics, McGill University, Montreal, Quebec, Canada.,Department of Medicine, McGill University, Montreal, Quebec, Canada.,Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K
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10
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Kulkarni H, Mamtani M, Peralta JM, Diego V, Dyer TD, Goring H, Almasy L, Mahaney MC, Williams-Blangero S, Duggirala R, Curran JE, Blangero J. Lack of Association between SLC30A8 Variants and Type 2 Diabetes in Mexican American Families. J Diabetes Res 2016; 2016:6463214. [PMID: 27896278 PMCID: PMC5118530 DOI: 10.1155/2016/6463214] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Accepted: 10/11/2016] [Indexed: 12/15/2022] Open
Abstract
SLC30A8 encodes zinc transporter 8 which is involved in packaging and release of insulin. Evidence for the association of SLC30A8 variants with type 2 diabetes (T2D) is inconclusive. We interrogated single nucleotide polymorphisms (SNPs) around SLC30A8 for association with T2D in high-risk, pedigreed individuals from extended Mexican American families. This study of 118 SNPs within 50 kb of the SLC30A8 locus tested the association with eight T2D-related traits at four levels: (i) each SNP using measured genotype approach (MGA); (ii) interaction of SNPs with age and sex; (iii) combinations of SNPs using Bayesian Quantitative Trait Nucleotide (BQTN) analyses; and (iv) entire gene locus using the gene burden test. Only one SNP (rs7817754) was significantly associated with incident T2D but a summary statistic based on all T2D-related traits identified 11 novel SNPs. Three SNPs and one SNP were weakly but interactively associated with age and sex, respectively. BQTN analyses could not demonstrate any informative combination of SNPs over MGA. Lastly, gene burden test results showed that at best the SLC30A8 locus could account for only 1-2% of the variability in T2D-related traits. Our results indicate a lack of association of the SLC30A8 SNPs with T2D in Mexican American families.
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Affiliation(s)
- Hemant Kulkarni
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
- *Hemant Kulkarni:
| | - Manju Mamtani
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Juan Manuel Peralta
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Vincent Diego
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Thomas D. Dyer
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Harald Goring
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Laura Almasy
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Michael C. Mahaney
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Sarah Williams-Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Ravindranath Duggirala
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Joanne E. Curran
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
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11
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Franceschini N, Tao R, Liu L, Rutherford S, Haack K, Almasy L, Göring HH, Laston S, Lee ET, Best LG, Fabsitz R, Cole SA, North KE. Mapping of a blood pressure QTL on chromosome 17 in American Indians of the strong heart family study. BMC Cardiovasc Disord 2014; 14:158. [PMID: 25387527 PMCID: PMC4246441 DOI: 10.1186/1471-2261-14-158] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Accepted: 09/18/2014] [Indexed: 01/11/2023] Open
Abstract
Background Blood pressure (BP) is a complex trait, with a heritability of 30 to 40%. Several genome wide associated BP loci explain only a small fraction of the phenotypic variation. Family studies can provide an important tool for gene discovery by utilizing trait and genetic transmission information among relative-pairs. We have previously described a quantitative trait locus at chromosome 17q25.3 influencing systolic BP in American Indians of the Strong Heart Family Study (SHFS). This locus has been reported to associate with variation in BP traits in family studies of Europeans, African Americans and Hispanics. Methods To follow-up persuasive linkage findings at this locus, we performed comprehensive genotyping in the 1-LOD unit support interval region surrounding this QTL using a multi-step strategy. We first genotyped 1,334 single nucleotide polymorphisms (SNPs) in 928 individuals from families that showed evidence of linkage for BP. We then genotyped a second panel of 306 SNPs in all SHFS participants (N = 3,807) for genes that displayed the strongest evidence of association in the region, and, in a third step, included additional genotyping to better cover the genes of interest and to interrogate plausible candidate genes in the region. Results Three genes had multiple SNPs marginally associated with systolic BP (TBC1D16, HRNBP3 and AZI1). In BQTN analysis, used to estimate the posterior probability that any variant in each gene had an effect on the phenotype, AZI1 showed the most prominent findings (posterior probability of 0.66). Importantly, upon correction for multiple testing, none of our study findings could be distinguished from chance. Conclusion Our findings demonstrate the difficulty of follow-up studies of linkage studies for complex traits, particularly in the context of low powered studies and rare variants underlying linkage peaks. Electronic supplementary material The online version of this article (doi:10.1186/1471-2261-14-158) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA.
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12
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Bozaoglu K, Attard C, Kulkarni H, Cummings N, Diego VP, Carless MA, Shields KA, Johnson MP, Kowlessur S, Dyer TD, Comuzzie AG, Almasy L, Zimmet P, Moses EK, Göring HHH, Curran JE, Blangero J, Jowett JBM. Plasma levels of soluble interleukin 1 receptor accessory protein are reduced in obesity. J Clin Endocrinol Metab 2014; 99:3435-43. [PMID: 24915116 PMCID: PMC4154095 DOI: 10.1210/jc.2013-4475] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
CONTEXT Adipokines actuate chronic, low-grade inflammation through a complex network of immune markers, but the current understanding of these networks is incomplete. The soluble isoform of the IL-1 receptor accessory protein (sIL1RAP) occupies an important position in the inflammatory pathways involved in obesity. The pathogenetic and clinical influences of sIL1RAP are unknown. OBJECTIVE The objective of the study was to elucidate whether plasma levels of sIL1RAP are reduced in obesity, using affluent clinical, biochemical, and genetic data from two diverse cohorts. DESIGN, SETTING, AND PARTICIPANTS The study was conducted in two cohorts: the San Antonio Family Heart Study (n = 1397 individuals from 42 families) and South Asians living in Mauritius, n = 230). MAIN OUTCOME MEASURES Plasma sIL1RAP levels were measured using an ELISA. The genetic basis of sIL1RAP levels were investigated using both a large-scale gene expression profiling study and a genome-wide association study. RESULTS A significant decrease in plasma sIL1RAP levels were observed in obese subjects, even after adjustment for age and sex. The sIL1RAP levels demonstrated a strong inverse association with obesity measures in both populations. All associations were more significant in females. Plasma sIL1RAP levels were significantly heritable, correlated with IL1RAP transcript levels (NM_134470), showed evidence for shared genetic influences with obesity measures and were significantly associated with the rs2885373 single-nucleotide polymorphism (P = 6.7 × 10(-23)) within the IL1RAP gene. CONCLUSIONS Plasma sIL1RAP levels are reduced in obesity and can potentially act as biomarkers of obesity. Mechanistic studies are required to understand the exact contribution of sIL1RAP to the pathogenesis of obesity.
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13
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Abstract
Statistical genetic methods incorporating temporal variation allow for greater understanding of genetic architecture and consistency of biological variation influencing development of complex diseases. This study proposes a bivariate association method jointly testing association of two quantitative phenotypic measures from different time points. Measured genotype association was analyzed for single-nucleotide polymorphisms (SNPs) for systolic blood pressure (SBP) from the first and third visits using 200 simulated Genetic Analysis Workshop 18 (GAW18) replicates. Bivariate association, in which the effect of an SNP on the mean trait values of the two phenotypes is constrained to be equal for both measures and is included as a covariate in the analysis, was compared with a bivariate analysis in which the effect of an SNP was estimated separately for the two measures and univariate association analyses in 9 SNPs that explained greater than 0.001% SBP variance over all 200 GAW18 replicates.The SNP 3_48040283 was significantly associated with SBP in all 200 replicates with the constrained bivariate method providing increased signal over the unconstrained bivariate method. This method improved signal in all 9 SNPs with simulated effects on SBP for nominal significance (p-value <0.05). However, this appears to be determined by the effect size of the SNP on the phenotype. This bivariate association method applied to longitudinal data improves genetic signal for quantitative traits when the effect size of the variant is moderate to large.
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Affiliation(s)
- Phillip E Melton
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Australia
| | - Laura A Almasy
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, USA
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14
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Kochunov P, Jahanshad N, Sprooten E, Nichols TE, Mandl RC, Almasy L, Booth T, Brouwer RM, Curran JE, de Zubicaray GI, Dimitrova R, Duggirala R, Fox PT, Hong LE, Landman BA, Lemaitre H, Lopez LM, Martin NG, McMahon KL, Mitchell BD, Olvera RL, Peterson CP, Starr JM, Sussmann JE, Toga AW, Wardlaw JM, Wright MJ, Wright SN, Bastin ME, McIntosh AM, Boomsma DI, Kahn RS, den Braber A, de Geus EJC, Deary IJ, Hulshoff Pol HE, Williamson DE, Blangero J, van 't Ent D, Thompson PM, Glahn DC. Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling. Neuroimage 2014; 95:136-50. [PMID: 24657781 DOI: 10.1016/j.neuroimage.2014.03.033] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2013] [Revised: 02/21/2014] [Accepted: 03/04/2014] [Indexed: 01/25/2023] Open
Abstract
Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Neda Jahanshad
- Imaging Genetics Center, Institute of Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Emma Sprooten
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA
| | - Thomas E Nichols
- Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK; Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Oxford University, UK
| | - René C Mandl
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Tom Booth
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Rachel M Brouwer
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Joanne E Curran
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | | | - Rali Dimitrova
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Ravi Duggirala
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Bennett A Landman
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Hervé Lemaitre
- U1000 Research Unit Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris-Sud, Orsay, France
| | - Lorna M Lopez
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | | | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Rene L Olvera
- Department of Psychiatry, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - Charles P Peterson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Jessika E Sussmann
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Arthur W Toga
- Imaging Genetics Center, Institute of Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | | | - Susan N Wright
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - René S Kahn
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anouk den Braber
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Hilleke E Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Douglas E Williamson
- Department of Psychiatry, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Dennis van 't Ent
- Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Institute of Neuroimaging and Informatics, Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA; Department of Neurology, Pediatrics, Engineering, Psychiatry, Radiology, & Ophthalmology, University of Southern California, Los Angeles, CA, USA
| | - David C Glahn
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA
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15
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Voruganti VS, Franceschini N, Haack K, Laston S, MacCluer JW, Umans JG, Comuzzie AG, North KE, Cole SA. Replication of the effect of SLC2A9 genetic variation on serum uric acid levels in American Indians. Eur J Hum Genet 2013; 22:938-43. [PMID: 24301058 DOI: 10.1038/ejhg.2013.264] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2013] [Revised: 10/08/2013] [Accepted: 10/18/2013] [Indexed: 12/21/2022] Open
Abstract
Increased serum uric acid (SUA) or hyperuricemia, a risk factor for gout, renal and cardiovascular diseases, is caused by either increased production or decreased excretion of uric acid or a mix of both. The solute carrier protein 2 family, member 9 (SLC2A9) gene encodes a transporter that mediates urate flux across the renal proximal tubule. Genome-wide association studies have consistently shown the association of single-nucleotide polymorphisms in this gene with SUA in majority populations. American Indian participants of the Strong Heart Family Study, belonging to multigenerational families, have high prevalence of hyperuricemia. We conducted measured genotype analyses, based on variance components decomposition method and accounting for family relationships, to assess whether the association between SUA and SLC2A9 gene polymorphisms generalized to American Indians (n=3604) of this study. Seven polymorphisms were selected for genotyping based on their association with SUA levels in other populations. A strong association was found between SLC2A9 gene polymorphisms and SUA in all centers combined (P-values: 1.3 × 10(-31)-5.1 × 10(-23)) and also when stratified by recruitment center; P-values: 1.2 × 10(-14)-1.0 × 10(-5). These polymorphisms were also associated with the estimated glomerular filtration rate and serum creatinine but not albumin-creatinine ratio. In summary, the association of polymorphisms in the uric acid transporter gene with SUA levels extends to a new population of American Indians.
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Affiliation(s)
- V Saroja Voruganti
- 1] Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA [2] Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Karin Haack
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Sandra Laston
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Jean W MacCluer
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Jason G Umans
- 1] Medstar Health Research Institute, Hyattsville, MD, USA [2] Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Anthony G Comuzzie
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Kari E North
- 1] Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA [2] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Shelley A Cole
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
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16
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Genetic effects on DNA methylation and its potential relevance for obesity in Mexican Americans. PLoS One 2013; 8:e73950. [PMID: 24058506 PMCID: PMC3772804 DOI: 10.1371/journal.pone.0073950] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2013] [Accepted: 07/23/2013] [Indexed: 12/22/2022] Open
Abstract
Several studies have identified effects of genetic variation on DNA methylation patterns and associated heritability, with research primarily focused on Caucasian individuals. In this paper, we examine the evidence for genetic effects on DNA methylation in a Mexican American cohort, a population burdened by a high prevalence of obesity. Using an Illumina-based platform and following stringent quality control procedures, we assessed a total of 395 CpG sites in peripheral blood samples obtained from 183 Mexican American individuals for evidence of heritability, proximal genetic regulation and association with age, sex and obesity measures (i.e. waist circumference and body mass index). We identified 16 CpG sites (∼4%) that were significantly heritable after Bonferroni correction for multiple testing and 27 CpG sites (∼6.9%) that showed evidence of genetic effects. Six CpG sites (∼2%) were associated with age, primarily exhibiting positive relationships, including CpG sites in two genes that have been implicated in previous genome-wide methylation studies of age (FZD9 and MYOD1). In addition, we identified significant associations between three CpG sites (∼1%) and sex, including DNA methylation in CASP6, a gene that may respond to estradiol treatment, and in HSD17B12, which encodes a sex steroid hormone. Although we did not identify any significant associations between DNA methylation and the obesity measures, several nominally significant results were observed in genes related to adipogenesis, obesity, energy homeostasis and glucose homeostasis (ARHGAP9, CDKN2A, FRZB, HOXA5, JAK3, MEST, NPY, PEG3 and SMARCB1). In conclusion, we were able to replicate several findings from previous studies in our Mexican American cohort, supporting an important role for genetic effects on DNA methylation. In addition, we found a significant influence of age and sex on DNA methylation, and report on trend-level, novel associations between DNA methylation and measures of obesity.
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17
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Jahanshad N, Kochunov PV, Sprooten E, Mandl RC, Nichols TE, Almasy L, Blangero J, Brouwer RM, Curran JE, de Zubicaray GI, Duggirala R, Fox PT, Hong LE, Landman BA, Martin NG, McMahon KL, Medland SE, Mitchell BD, Olvera RL, Peterson CP, Starr JM, Sussmann JE, Toga AW, Wardlaw JM, Wright MJ, Hulshoff Pol HE, Bastin ME, McIntosh AM, Deary IJ, Thompson PM, Glahn DC. Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group. Neuroimage 2013; 81:455-469. [PMID: 23629049 DOI: 10.1016/j.neuroimage.2013.04.061] [Citation(s) in RCA: 283] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2013] [Revised: 03/28/2013] [Accepted: 04/10/2013] [Indexed: 10/26/2022] Open
Abstract
The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).
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Affiliation(s)
- Neda Jahanshad
- Imaging Genetics Center, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA
| | - Peter V Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Emma Sprooten
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - René C Mandl
- Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Thomas E Nichols
- Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK; Oxford Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Oxford University, UK
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Rachel M Brouwer
- Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Joanne E Curran
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | | | - Ravi Duggirala
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, TX, USA; South Texas Veterans Administration Medical Center, San Antonio, TX, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | | | - Katie L McMahon
- University of Queensland, Center for Advanced Imaging, Brisbane, Australia
| | - Sarah E Medland
- Queensland Institute of Medical Research, Brisbane, Australia
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Rene L Olvera
- Research Imaging Institute, University of Texas Health Science Center San Antonio, San Antonio, TX, USA
| | - Charles P Peterson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Jessika E Sussmann
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Arthur W Toga
- Imaging Genetics Center, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Hilleke E Hulshoff Pol
- Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Brain Research Imaging Centre, Division of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Paul M Thompson
- Imaging Genetics Center, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA.
| | - David C Glahn
- Olin Neuropsychiatry Research Center in the Institute of Living, Yale University School of Medicine, New Haven, CT, USA
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18
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Johnson MP, Brennecke SP, East CE, Dyer TD, Roten LT, Proffitt JM, Melton PE, Fenstad MH, Aalto-Viljakainen T, Mäkikallio K, Heinonen S, Kajantie E, Kere J, Laivuori H, Austgulen R, Blangero J, Moses EK. Genetic dissection of the pre-eclampsia susceptibility locus on chromosome 2q22 reveals shared novel risk factors for cardiovascular disease. Mol Hum Reprod 2013; 19:423-37. [PMID: 23420841 DOI: 10.1093/molehr/gat011] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Pre-eclampsia is an idiopathic pregnancy disorder promoting morbidity and mortality to both mother and child. Delivery of the fetus is the only means to resolve severe symptoms. Women with pre-eclamptic pregnancies demonstrate increased risk for later life cardiovascular disease (CVD) and good evidence suggests these two syndromes share several risk factors and pathophysiological mechanisms. To elucidate the genetic architecture of pre-eclampsia we have dissected our chromosome 2q22 susceptibility locus in an extended Australian and New Zealand familial cohort. Positional candidate genes were prioritized for exon-centric sequencing using bioinformatics, SNPing, transcriptional profiling and QTL-walking. In total, we interrogated 1598 variants from 52 genes. Four independent SNP associations satisfied our gene-centric multiple testing correction criteria: a missense LCT SNP (rs2322659, P = 0.0027), a synonymous LRP1B SNP (rs35821928, P = 0.0001), an UTR-3 RND3 SNP (rs115015150, P = 0.0024) and a missense GCA SNP (rs17783344, P = 0.0020). We replicated the LCT SNP association (P = 0.02) and observed a borderline association for the GCA SNP (P = 0.07) in an independent Australian case-control population. The LRP1B and RND3 SNP associations were not replicated in this same Australian singleton cohort. Moreover, these four SNP associations could not be replicated in two additional case-control populations from Norway and Finland. These four SNPs, however, exhibit pleiotropic effects with several quantitative CVD-related traits. Our results underscore the genetic complexity of pre-eclampsia and present novel empirical evidence of possible shared genetic mechanisms underlying both pre-eclampsia and other CVD-related risk factors.
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Affiliation(s)
- Matthew P Johnson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
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19
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Blangero J, Diego VP, Dyer TD, Almeida M, Peralta J, Kent JW, Williams JT, Almasy L, Göring HHH. A kernel of truth: statistical advances in polygenic variance component models for complex human pedigrees. ADVANCES IN GENETICS 2013; 81:1-31. [PMID: 23419715 PMCID: PMC4019427 DOI: 10.1016/b978-0-12-407677-8.00001-4] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Statistical genetic analysis of quantitative traits in large pedigrees is a formidable computational task due to the necessity of taking the nonindependence among relatives into account. With the growing awareness that rare sequence variants may be important in human quantitative variation, heritability and association study designs involving large pedigrees will increase in frequency due to the greater chance of observing multiple copies of rare variants among related individuals. Therefore, it is important to have statistical genetic test procedures that utilize all available information for extracting evidence regarding genetic association. Optimal testing for marker/phenotype association involves the exact calculation of the likelihood ratio statistic which requires the repeated inversion of potentially large matrices. In a whole genome sequence association context, such computation may be prohibitive. Toward this end, we have developed a rapid and efficient eigen simplification of the likelihood that makes analysis of family data commensurate with the analysis of a comparable sample of unrelated individuals. Our theoretical results which are based on a spectral representation of the likelihood yield simple exact expressions for the expected likelihood ratio test statistic (ELRT) for pedigrees of arbitrary size and complexity. For heritability, the ELRT is where h2 and λgi are, respectively, the heritability and eigenvalues of the pedigree-derived genetic relationship kernel (GRK). For association analysis of sequence variants, the ELRT is given by where ht2, hq2, and hr2 are the total, quantitative trait nucleotide, and residual heritabilities, respectively. Using these results, fast and accurate analytical power analyses are possible, eliminating the need for computer simulation. Additional benefits of eigen simplification include a simple method for calculation of the exact distribution of the ELRT under the null hypothesis which turns out to differ from that expected under the usual asymptotic theory. Further, when combined with the use of empirical GRKs-estimated over a large number of genetic markers-our theory reveals potential problems associated with nonpositive semidefinite kernels. These procedures are being added to our general statistical genetic computer package, SOLAR.
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Affiliation(s)
- John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, USA.
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20
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Farook VS, Puppala S, Schneider J, Fowler SP, Chittoor G, Dyer TD, Allayee H, Cole SA, Arya R, Black MH, Curran JE, Almasy L, Buchanan TA, Jenkinson CP, Lehman DM, Watanabe RM, Blangero J, Duggirala R. Metabolic syndrome is linked to chromosome 7q21 and associated with genetic variants in CD36 and GNAT3 in Mexican Americans. Obesity (Silver Spring) 2012; 20:2083-92. [PMID: 22456541 PMCID: PMC4287372 DOI: 10.1038/oby.2012.74] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The prevalence of metabolic syndrome (MS) has been rising alarmingly worldwide, including in the United States, but knowledge on specific genetic determinants of MS is very limited. Therefore, we planned to identify the genetic determinants of MS as defined by National Cholesterol Education Program/Adult Treatment Panel III (NCEP/ATPIII) criteria. We performed linkage screen for MS using data from 692 Mexican Americans, who participated in the San Antonio Family Diabetes/Gallbladder Study (SAFDGS). We found strong evidence for linkage of MS on chromosome 7q (LOD = 3.6, empirical P = 6.0 × 10(-5)), between markers D7S2212 and D7S821. In addition, six chromosomal regions exhibited potential evidence for linkage (LOD ≥1.2) with MS. Furthermore, we examined 29 single-nucleotide polymorphisms (SNPs) from the fatty acid translocase (FAT or CD36, 18 SNPs) gene and guanine nucleotide binding protein, α transducing 3 (GNAT3, 11 SNPs) gene, located within the 1-LOD support interval region for their association with MS and its related traits. Several SNPs were associated with MS and its related traits. Remarkably, rs11760281 in GNAT3 and rs1194197 near CD36 exhibited the strongest associations with MS (P = 0.0003, relative risk (RR) = 1.6 and P = 0.004, RR = 1.7, respectively) and several other related traits. These two variants explained ~18% of the MS linkage evidence on chromosome 7q21, and together conferred approximately threefold increase in MS risk (RR = 2.7). In conclusion, our linkage and subsequent association studies implicate a region on chromosome 7q21 to influence MS in Mexican Americans.
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Affiliation(s)
- Vidya S Farook
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas, USA.
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21
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Thameem F, Puppala S, Schneider J, Bhandari B, Arya R, Arar NH, Vasylyeva TL, Farook VS, Fowler S, Almasy L, Blangero J, Duggirala R, Abboud HE. The Gly(972)Arg variant of human IRS1 gene is associated with variation in glomerular filtration rate likely through impaired insulin receptor signaling. Diabetes 2012; 61:2385-93. [PMID: 22617042 PMCID: PMC3425400 DOI: 10.2337/db11-1078] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
The objective of this study is to identify and characterize the genetic variants related to the glomerular filtration rate (GFR) linkage on 2q37. Of the positional candidate genes, we selected IRS1 and resequenced its 2-kb promoter region and exons for sequence variants in 32 subjects. A total of 11 single nucleotide polymorphisms (SNPs) were identified. To comprehensively cover the 59-kb-long intron-1, eight additional tagging SNPs were selected from the HapMap. All the 19 SNPs were genotyped by TaqMan Assay in the entire data set (N = 670; 39 families). Association analyses between the SNPs and GFR and type 2 diabetes-related traits were performed using the measured genotype approach. Of the SNPs examined for association, only the Gly(972)Arg variant of IRS1 exhibited a significant association with GFR (P = 0.0006) and serum triglycerides levels (P = 0.003), after accounting for trait-specific covariate effects. Carriers of Arg972 had significantly decreased GFR values. Gly(972)Arg contributed to 26% of the linkage signal on 2q. Expression of IRS1 mutant Arg972 in human mesangial cells significantly reduced the insulin-stimulated phosphorylation of IRS1 and Akt kinase. Taken together, the data provide the first evidence that genetic variation in IRS1 may influence variation in GFR probably through impaired insulin receptor signaling.
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Affiliation(s)
- Farook Thameem
- Division of Nephrology, The University of Texas Health Science Center, San Antonio, Texas, USA.
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22
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Voruganti VS, Higgins PB, Ebbesson SOE, Kennish J, Göring HHH, Haack K, Laston S, Drigalenko E, Wenger CR, Harris WS, Fabsitz RR, Devereux RB, Maccluer JW, Curran JE, Carless MA, Johnson MP, Moses EK, Blangero J, Umans JG, Howard BV, Cole SA, Comuzzie AG. Variants in CPT1A, FADS1, and FADS2 are Associated with Higher Levels of Estimated Plasma and Erythrocyte Delta-5 Desaturases in Alaskan Eskimos. Front Genet 2012; 3:86. [PMID: 22701466 PMCID: PMC3371589 DOI: 10.3389/fgene.2012.00086] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2012] [Accepted: 04/30/2012] [Indexed: 12/15/2022] Open
Abstract
The delta-5 and delta-6 desaturases (D5D and D6D), encoded by fatty acid desaturase 1 (FADS1) and 2 (FADS2) genes, respectively, are rate-limiting enzymes in the metabolism of ω-3 and ω-6 fatty acids. The objective of this study was to identify genes influencing variation in estimated D5D and D6D activities in plasma and erythrocytes in Alaskan Eskimos (n = 761) participating in the genetics of coronary artery disease in Alaska Natives (GOCADAN) study. Desaturase activity was estimated by product: precursor ratio of polyunsaturated fatty acids. We found evidence of linkage for estimated erythrocyte D5D (eD5D) on chromosome 11q12-q13 (logarithm of odds score = 3.5). The confidence interval contains candidate genes FADS1, FADS2, 7-dehydrocholesterol reductase (DHCR7), and carnitine palmitoyl transferase 1A, liver (CPT1A). Measured genotype analysis found association between CPT1A, FADS1, and FADS2 single-nucleotide polymorphisms (SNPs) and estimated eD5D activity (p-values between 10−28 and 10−5). A Bayesian quantitative trait nucleotide analysis showed that rs3019594 in CPT1A, rs174541 in FADS1, and rs174568 in FADS2 had posterior probabilities > 0.8, thereby demonstrating significant statistical support for a functional effect on eD5D activity. Highly significant associations of FADS1, FADS2, and CPT1A transcripts with their respective SNPs (p-values between 10−75 and 10−7) in Mexican Americans of the San Antonio Family Heart Study corroborated our results. These findings strongly suggest a functional role for FADS1, FADS2, and CPT1A SNPs in the variation in eD5D activity.
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Affiliation(s)
- V Saroja Voruganti
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
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24
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Abstract
Although disrupted in schizophrenia 1 (DISC1) has been implicated in many psychiatric disorders, including schizophrenia, bipolar disorder, schizoaffective disorder and major depression, its biological role in these disorders is unclear. To better understand this gene and its role in psychiatric disease, we conducted transcriptional profiling and genome-wide association analysis in 1232 pedigreed Mexican-American individuals for whom we have neuroanatomic images, neurocognitive assessments and neuropsychiatric diagnoses. SOLAR was used to determine heritability, identify gene expression patterns and perform association analyses on 188 quantitative brain-related phenotypes. We found that the DISC1 transcript is highly heritable (h(2)=0.50; P=1.97 × 10(-22)), and that gene expression is strongly cis-regulated (cis-LOD=3.89) but is also influenced by trans-effects. We identified several DISC1 polymorphisms that were associated with cortical gray matter thickness within the parietal, temporal and frontal lobes. Associated regions affiliated with memory included the entorhinal cortex (rs821639, P=4.11 × 10(-5); rs2356606, P=4.71 × 10(-4)), cingulate cortex (rs16856322, P=2.88 × 10(-4)) and parahippocampal gyrus (rs821639, P=4.95 × 10(-4)); those affiliated with executive and other cognitive processing included the transverse temporal gyrus (rs9661837, P=5.21 × 10(-4); rs17773946, P=6.23 × 10(-4)), anterior cingulate cortex (rs2487453, P=4.79 × 10(-4); rs3738401, P=5.43 × 10(-4)) and medial orbitofrontal cortex (rs9661837; P=7.40 × 10(-4)). Cognitive measures of working memory (rs2793094, P=3.38 × 10(-4)), as well as lifetime history of depression (rs4658966, P=4.33 × 10(-4); rs12137417, P=4.93 × 10(-4)) and panic (rs12137417, P=7.41 × 10(-4)) were associated with DISC1 sequence variation. DISC1 has well-defined genetic regulation and clearly influences important phenotypes related to psychiatric disease.
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25
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Cox HC, Lea RA, Bellis C, Carless M, Dyer T, Blangero J, Griffiths LR. Variants in the human potassium channel gene (KCNN3) are associated with migraine in a high risk genetic isolate. J Headache Pain 2011; 12:603-8. [PMID: 22030984 PMCID: PMC3208049 DOI: 10.1007/s10194-011-0392-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2010] [Accepted: 11/14/2010] [Indexed: 11/30/2022] Open
Abstract
The calcium-activated potassium ion channel gene (KCNN3) is located in the vicinity of the familial hemiplegic migraine type 2 locus on chromosome 1q21.3. This gene is expressed in the central nervous system and plays a role in neural excitability. Previous association studies have provided some, although not conclusive, evidence for involvement of this gene in migraine susceptibility. To elucidate KCNN3 involvement in migraine, we performed gene-wide SNP genotyping in a high-risk genetic isolate from Norfolk Island, a population descended from a small number of eighteenth century Isle of Man ‘Bounty Mutineer’ and Tahitian founders. Phenotype information was available for 377 individuals who are related through the single, well-defined Norfolk pedigree (96 were affected: 64 MA, 32 MO). A total of 85 SNPs spanning the KCNN3 gene were genotyped in a sub-sample of 285 related individuals (76 affected), all core members of the extensive Norfolk Island ‘Bounty Mutineer’ genealogy. All genotyping was performed using the Illumina BeadArray platform. The analysis was performed using the statistical program SOLAR v4.0.6 assuming an additive model of allelic effect adjusted for the effects of age and sex. Haplotype analysis was undertaken using the program HAPLOVIEW v4.0. A total of four intronic SNPs in the KCNN3 gene displayed significant association (P < 0.05) with migraine. Two SNPs, rs73532286 and rs6426929, separated by approximately 0.1 kb, displayed complete LD (r2 = 1.00, D′ = 1.00, D′ 95% CI = 0.96–1.00). In all cases, the minor allele led to a decrease in migraine risk (beta coefficient = 0.286–0.315), suggesting that common gene variants confer an increased risk of migraine in the Norfolk pedigree. This effect may be explained by founder effect in this genetic isolate. This study provides evidence for association of variants in the KCNN3 ion channel gene with migraine susceptibility in the Norfolk genetic isolate with the rarer allelic variants conferring a possible protective role. This the first comprehensive analysis of this potential candidate gene in migraine and also the first study that has utilised the unique Norfolk Island large pedigree isolate to implicate a specific migraine gene. Studies of additional variants in KCNN3 in the Norfolk pedigree are now required (e.g. polyglutamine variants) and further analyses in other population data sets are required to clarify the association of the KCNN3 gene and migraine risk in the general outbred population.
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Affiliation(s)
- Hannah C Cox
- Genomics Research Centre, Griffith Health Institute, Gold Coast Campus, Griffith University, Southport, QLD, 4222, Australia
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26
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Butte NF, Voruganti VS, Cole SA, Haack K, Comuzzie AG, Muzny DM, Wheeler DA, Chang K, Hawes A, Gibbs RA. Resequencing of IRS2 reveals rare variants for obesity but not fasting glucose homeostasis in Hispanic children. Physiol Genomics 2011; 43:1029-37. [PMID: 21771880 DOI: 10.1152/physiolgenomics.00019.2011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Our objective was to resequence insulin receptor substrate 2 (IRS2) to identify variants associated with obesity- and diabetes-related traits in Hispanic children. Exonic and intronic segments, 5' and 3' flanking regions of IRS2 (∼14.5 kb), were bidirectionally sequenced for single nucleotide polymorphism (SNP) discovery in 934 Hispanic children using 3730XL DNA Sequencers. Additionally, 15 SNPs derived from Illumina HumanOmni1-Quad BeadChips were analyzed. Measured genotype analysis tested associations between SNPs and obesity and diabetes-related traits. Bayesian quantitative trait nucleotide analysis was used to statistically infer the most likely functional polymorphisms. A total of 140 SNPs were identified with minor allele frequencies (MAF) ranging from 0.001 to 0.47. Forty-two of the 70 coding SNPs result in nonsynonymous amino acid substitutions relative to the consensus sequence; 28 SNPs were detected in the promoter, 12 in introns, 28 in the 3'-UTR, and 2 in the 5'-UTR. Two insertion/deletions (indels) were detected. Ten independent rare SNPs (MAF = 0.001-0.009) were associated with obesity-related traits (P = 0.01-0.00002). SNP 10510452_139 in the promoter region was shown to have a high posterior probability (P = 0.77-0.86) of influencing BMI, fat mass, and waist circumference in Hispanic children. SNP 10510452_139 contributed between 2 and 4% of the population variance in body weight and composition. None of the SNPs or indels were associated with diabetes-related traits or accounted for a previously identified quantitative trait locus on chromosome 13 for fasting serum glucose. Rare but not common IRS2 variants may play a role in the regulation of body weight but not an essential role in fasting glucose homeostasis in Hispanic children.
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Affiliation(s)
- Nancy F Butte
- Department of Pediatrics, Baylor College of Medicine, US Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Houston, TX, USA.
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27
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Lehtinen AB, Cox AJ, Ziegler JT, Voruganti VS, Xu J, Freedman BI, Carr JJ, Comuzzie AG, Langefeld CD, Bowden DW. Genetic mapping of vascular calcified plaque loci on chromosome 16p in European Americans from the diabetes heart study. Ann Hum Genet 2011; 75:222-35. [PMID: 21309755 DOI: 10.1111/j.1469-1809.2010.00632.x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A linkage peak for carotid artery calcified plaque (CarCP) on chromosome 16p (LOD 4.39 at 8.4 cM) in families with type 2 diabetes mellitus (T2DM) from the Diabetes Heart Study (DHS) has been refined. Fine mapping encompassed 104 single-nucleotide polymorphisms (SNPs) in 937 subjects from 315 families; including 45 SNPs in six candidate genes (CACNA1H, SEPX1, ABCA3, IL32, SOCS1, CLEC16A). Linkage and association analyses using variance components analysis adjusting for age, gender, body mass index (BMI), and diabetes status refined the CarCP linkage into two distinct peaks (LODs: 3.89 at 6.9 cM and 4.86 at 16.0 cM). Evidence of linkage for coronary calcified plaque (LOD: 2.27 at 19 cM) and a vascular calcification principle component (LOD: 3.71 at 16.0 cM) was also observed. The strongest evidence for association with CarCP was observed with SNPs in the A2BP1 gene region (rs4337300 P= 0.005) with modest evidence of association with SNPs in CACNA1H (P= 0.010-0.033). Bayesian quantitative trait nucleotide (BQTN) analysis identified a SNP, rs1358489, with either a functional effect on CarCP or in linkage disequilibrium (LD) with a functional SNP. This study refined the 16p region contributing to vascular calcification. The causal variants remain to be identified, but results are consistent with a linkage peak that is due to multiple common variants, though rare variants cannot be excluded.
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Affiliation(s)
- Allison B Lehtinen
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
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28
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Cummings N, Shields KA, Curran JE, Bozaoglu K, Trevaskis J, Gluschenko K, Cai G, Comuzzie AG, Dyer TD, Walder KR, Zimmet P, Collier GR, Blangero J, Jowett JBM. Genetic variation in SH3-domain GRB2-like (endophilin)-interacting protein 1 has a major impact on fat mass. Int J Obes (Lond) 2011; 36:201-6. [PMID: 21407171 DOI: 10.1038/ijo.2011.67] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE The SH3-domain GRB2-like (endophilin)-interacting protein 1 (SGIP1) gene has been shown to be differentially expressed in the hypothalamus of lean versus obese Israeli sand rats (Psammomys obesus), and is suspected of having a role in regulating food intake. The purpose of this study was to assess the role of genetic variation in SGIP1 in human disease. SUBJECTS We performed single-nucleotide polymorphism (SNP) genotyping in a large family pedigree cohort from the island of Mauritius. The Mauritius Family Study (MFS) consists of 400 individuals from 24 Indo-Mauritian families recruited from the genetically homogeneous population of Mauritius. We measured markers of the metabolic syndrome, including diabetes and obesity-related phenotypes such as fasting plasma glucose, waist:hip ratio, body mass index and fat mass. RESULTS Statistical genetic analysis revealed associations between SGIP1 polymorphisms and fat mass (in kilograms) as measured by bioimpedance. SNP genotyping identified associations between several genetic variants and fat mass, with the strongest association for rs2146905 (P=4.7 × 10(-5)). A strong allelic effect was noted for several SNPs where fat mass was reduced by up to 9.4% for individuals homozygous for the minor allele. CONCLUSIONS Our results show association between genetic variants in SGIP1 and fat mass. We provide evidence that variation in SGIP1 is a potentially important determinant of obesity-related traits in humans.
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Affiliation(s)
- N Cummings
- Genomics and Systems Biology, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, Australia
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Konstantopoulos N, Foletta VC, Segal DH, Shields KA, Sanigorski A, Windmill K, Swinton C, Connor T, Wanyonyi S, Dyer TD, Fahey RP, Watt RA, Curran JE, Molero JC, Krippner G, Collier GR, James DE, Blangero J, Jowett JB, Walder KR. A gene expression signature for insulin resistance. Physiol Genomics 2011; 43:110-20. [DOI: 10.1152/physiolgenomics.00115.2010] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Insulin resistance is a heterogeneous disorder caused by a range of genetic and environmental factors, and we hypothesize that its etiology varies considerably between individuals. This heterogeneity provides significant challenges to the development of effective therapeutic regimes for long-term management of type 2 diabetes. We describe a novel strategy, using large-scale gene expression profiling, to develop a gene expression signature (GES) that reflects the overall state of insulin resistance in cells and patients. The GES was developed from 3T3-L1 adipocytes that were made “insulin resistant” by treatment with tumor necrosis factor-α (TNF-α) and then reversed with aspirin and troglitazone (“resensitized”). The GES consisted of five genes whose expression levels best discriminated between the insulin-resistant and insulin-resensitized states. We then used this GES to screen a compound library for agents that affected the GES genes in 3T3-L1 adipocytes in a way that most closely resembled the changes seen when insulin resistance was successfully reversed with aspirin and troglitazone. This screen identified both known and new insulin-sensitizing compounds including nonsteroidal anti-inflammatory agents, β-adrenergic antagonists, β-lactams, and sodium channel blockers. We tested the biological relevance of this GES in participants in the San Antonio Family Heart Study ( n = 1,240) and showed that patients with the lowest GES scores were more insulin resistant (according to HOMA_IR and fasting plasma insulin levels; P < 0.001). These findings show that GES technology can be used for both the discovery of insulin-sensitizing compounds and the characterization of patients into subtypes of insulin resistance according to GES scores, opening the possibility of developing a personalized medicine approach to type 2 diabetes.
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Affiliation(s)
| | | | - David H. Segal
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
| | | | - Andrew Sanigorski
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
| | - Kelly Windmill
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
| | - Courtney Swinton
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
| | - Tim Connor
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
| | - Stephen Wanyonyi
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
| | - Thomas D. Dyer
- Southwest Foundation for Biomedical Research, San Antonio, Texas; and
| | - Richard P. Fahey
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
| | - Rose A. Watt
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
| | - Joanne E. Curran
- Southwest Foundation for Biomedical Research, San Antonio, Texas; and
| | - Juan-Carlos Molero
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
| | | | | | - David E. James
- Diabetes and Obesity Research Program, Garvan Institute, Sydney; and
| | - John Blangero
- Southwest Foundation for Biomedical Research, San Antonio, Texas; and
| | | | - Ken R. Walder
- Metabolic Research Unit, School of Medicine, Deakin University, Geelong and
- Institute of Technology and Research Innovation, Deakin University, Geelong, Australia
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30
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Fenstad MH, Johnson MP, Roten LT, Aas PA, Forsmo S, Klepper K, East CE, Abraham LJ, Blangero J, Brennecke SP, Austgulen R, Moses EK. Genetic and molecular functional characterization of variants within TNFSF13B, a positional candidate preeclampsia susceptibility gene on 13q. PLoS One 2010; 5:e12993. [PMID: 20927378 PMCID: PMC2947510 DOI: 10.1371/journal.pone.0012993] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2010] [Accepted: 09/03/2010] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Preeclampsia is a serious pregnancy complication, demonstrating a complex pattern of inheritance. The elucidation of genetic liability to preeclampsia remains a major challenge in obstetric medicine. We have adopted a positional cloning approach to identify maternal genetic components, with linkages previously demonstrated to chromosomes 2q, 5q and 13q in an Australian/New Zealand familial cohort. The current study aimed to identify potential functional and structural variants in the positional candidate gene TNFSF13B under the 13q linkage peak and assess their association status with maternal preeclampsia genetic susceptibility. METHODOLOGY/PRINCIPAL FINDINGS The proximal promoter and coding regions of the positional candidate gene TNFSF13B residing within the 13q linkage region was sequenced using 48 proband or founder individuals from Australian/New Zealand families. Ten sequence variants (nine SNPs and one single base insertion) were identified and seven SNPs were successfully genotyped in the total Australian/New Zealand family cohort (74 families/480 individuals). Borderline association to preeclampsia (p = 0.0153) was observed for three rare SNPs (rs16972194, rs16972197 and rs56124946) in strong linkage disequilibrium with each other. Functional evaluation by electrophoretic mobility shift assays showed differential nuclear factor binding to the minor allele of the rs16972194 SNP, residing upstream of the translation start site, making this a putative functional variant. The observed genetic associations were not replicated in a Norwegian case/control cohort (The Nord-Trøndelag Health Study (HUNT2), 851 preeclamptic and 1,440 non-preeclamptic women). CONCLUSION/SIGNIFICANCE TNFSF13B has previously been suggested to contribute to the normal immunological adaption crucial for a successful pregnancy. Our observations support TNFSF13B as a potential novel preeclampsia susceptibility gene. We discuss a possible role for TNFSF13B in preeclampsia pathogenesis, and propose the rs16972194 variant as a candidate for further functional evaluation.
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Affiliation(s)
- Mona H. Fenstad
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Matthew P. Johnson
- Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas, United States of America
| | - Linda T. Roten
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Per A. Aas
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Siri Forsmo
- Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kjetil Klepper
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Christine E. East
- Department of Perinatal Medicine/Department of Obstetrics and Gynaecology, Royal Women's Hospital and University of Melbourne, Parkville, Australia
| | - Lawrence J. Abraham
- The School of Biomedical Biomolecular and Chemical Sciences, The University of Western Australia Crawley, Perth, Australia
| | - John Blangero
- Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas, United States of America
| | - Shaun P. Brennecke
- Department of Perinatal Medicine/Department of Obstetrics and Gynaecology, Royal Women's Hospital and University of Melbourne, Parkville, Australia
| | - Rigmor Austgulen
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Eric K. Moses
- Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas, United States of America
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31
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Almasy L, Blangero J. Variance component methods for analysis of complex phenotypes. Cold Spring Harb Protoc 2010; 2010:pdb.top77. [PMID: 20439422 DOI: 10.1101/pdb.top77] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Variance component methods have a long history in human quantitative genetics as well as in agricultural genetics and animal breeding. They are designed for genetic analysis of continuously varying quantitative traits such as body mass index (BMI), cholesterol levels, or intelligence quotient. They can be used to assess the strength of genetic effects on a trait, to localize genes influencing a trait through either linkage or association methods, to assess whether associated variants are likely to be the functional variants behind a given localization signal, to explore whether related traits have shared genetic influences in multivariate analyses, and to characterize the genetic effects on a trait through analyses of gene-gene and gene-environment interactions.
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32
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Prior MJ, Foletta VC, Jowett JB, Segal DH, Carless MA, Curran JE, Dyer TD, Moses EK, McAinch AJ, Konstantopoulos N, Bozaoglu K, Collier GR, Cameron-Smith D, Blangero J, Walder KR. The characterization of Abelson helper integration site-1 in skeletal muscle and its links to the metabolic syndrome. Metabolism 2010; 59:1057-64. [PMID: 20045148 PMCID: PMC3249385 DOI: 10.1016/j.metabol.2009.11.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2009] [Revised: 10/17/2009] [Accepted: 11/02/2009] [Indexed: 10/20/2022]
Abstract
The human Abelson helper integration site-1 (AHI1) gene is associated with both neurologic and hematologic disorders; however, it is also located in a chromosomal region linked to metabolic syndrome phenotypes and was identified as a type 2 diabetes mellitus susceptibility gene from a genomewide association study. To further define a possible role in type 2 diabetes mellitus development, AHI1 messenger RNA expression levels were investigated in a range of tissues and found to be highly expressed in skeletal muscle as well as displaying elevated levels in brain regions and gonad tissues. Further analysis in a rodent polygenic animal model of obesity and type 2 diabetes mellitus identified increased Ahi-1 messenger RNA levels in red gastrocnemius muscle from fasted impaired glucose-tolerant and diabetic rodents compared with healthy animals (P < .002). Moreover, elevated gene expression levels were confirmed in skeletal muscle from fasted obese and type 2 diabetes mellitus human subjects (P < .02). RNAi-mediated suppression of Ahi-1 resulted in increased glucose transport in rat L6 myotubes in both the basal and insulin-stimulated states (P < .01). Finally, single nucleotide polymorphism association studies identified 2 novel AHI1 genetic variants linked with fasting blood glucose levels in Mexican American subjects (P < .037). These findings indicate a novel role for AHI1 in skeletal muscle and identify additional genetic links with metabolic syndrome phenotypes suggesting an involvement of AHI1 in the maintenance of glucose homeostasis and type 2 diabetes mellitus progression.
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MESH Headings
- Adaptor Proteins, Signal Transducing/genetics
- Adaptor Proteins, Signal Transducing/metabolism
- Adaptor Proteins, Vesicular Transport
- Animals
- Blood Glucose/metabolism
- Blotting, Western
- Body Weight/physiology
- Cells, Cultured
- Cohort Studies
- Deoxyglucose/metabolism
- Diabetes Mellitus, Type 2/genetics
- Diabetes Mellitus, Type 2/metabolism
- Genotype
- Glucose/metabolism
- Humans
- Insulin/blood
- Insulin Resistance/genetics
- Metabolic Syndrome/genetics
- Metabolic Syndrome/metabolism
- Mexican Americans
- Muscle Fibers, Skeletal/metabolism
- Muscle, Skeletal/metabolism
- Myoblasts/drug effects
- Myoblasts/metabolism
- Obesity/metabolism
- RNA, Messenger/biosynthesis
- RNA, Messenger/genetics
- Rats
- Reverse Transcriptase Polymerase Chain Reaction
- Transfection
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Affiliation(s)
- Matthew J. Prior
- School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Victoria C. Foletta
- School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Jeremy B. Jowett
- The Baker IDI Heart and Diabetes Institute, Melbourne, Australia
| | - David H. Segal
- School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | | | | | - Tom D. Dyer
- Southwest Foundation for Biomedical Research, San Antonio, USA
| | - Eric K. Moses
- Southwest Foundation for Biomedical Research, San Antonio, USA
| | - Andrew J. McAinch
- School of Biomedical and Health Sciences, Victoria University, Melbourne, 8001, Australia
| | | | - Kiymet Bozaoglu
- School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | | | - David Cameron-Smith
- School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - John Blangero
- Southwest Foundation for Biomedical Research, San Antonio, USA
| | - Ken R. Walder
- School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
- Verva Pharmaceuticals Ltd, Geelong, Australia
- Corresponding author. , Telephone: + 61-3-5227 2883, Facsimilie: + 61-3-5227 2170
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Genome-wide scan identifies a quantitative trait locus at 4p15.3 for serum urate. Eur J Hum Genet 2010; 18:1243-7. [PMID: 20588307 DOI: 10.1038/ejhg.2010.97] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Elevated serum urate levels lead to gout and are associated with hypertension, metabolic syndrome, type 2 diabetes and cardiovascular diseases. The purpose of this study was to identify evidence for genetic linkage with serum urate and to determine whether variation within positional candidate genes is associated with serum urate levels in a non-European population. Genetic linkage analysis and single nucleotide polymorphism (SNP) genotyping was performed in a large family pedigree cohort from Mauritius. We assessed associations between serum urate levels and 97 SNPs in a positional candidate gene, SLC2A9. A genome-wide scan identified a new region with evidence for linkage for serum urate at 4p15.3. SNP genotyping identified significant association between six SNP variants in SLC2A9 and serum urate levels. Allelic and gender-based effects were noted for several SNPs. Significant correlations were also observed between serum urate levels and individual components of metabolic syndrome. Our study results implicate genetic variation in SLC2A9 in influencing levels of serum urate over a broad range of values in a large Mauritian family cohort.
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34
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Genetic variation in APOJ, LPL, and TNFRSF10B affects plasma fatty acid distribution in Alaskan Eskimos. Am J Clin Nutr 2010; 91:1574-83. [PMID: 20410100 PMCID: PMC2869509 DOI: 10.3945/ajcn.2009.28927] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Alterations in plasma fatty acid distribution are linked to metabolic abnormalities related to type 2 diabetes and cardiovascular disease. OBJECTIVE The aim of this study was to investigate genetic factors influencing plasma fatty acid distribution in Alaskan Eskimos from the Genetics of Coronary Artery Disease in Alaska Natives (GOCADAN) study. DESIGN Fatty acids in plasma were measured by gas chromatography in 761 related individuals (>35 y of age). RESULTS Quantitative genetic analyses showed that fatty acid distribution is significantly heritable (P < 0.001), with heritabilities ranging from 0.33 to 0.55. A genome-wide scan for plasma fatty acids identified a 20-cM region on chromosome 8 (p12-p21) with a quantitative trait locus for monounsaturated fatty acids (logarithm of odds score = 3.8). The same region had a quantitative trait locus for polyunsaturated fatty acids (logarithm of odds score = 2.6). We genotyped single nucleotide polymorphisms (SNPs) in candidate genes in 8p12-p21 and found a significant association between fatty acids and SNPs in apolipoprotein J (APOJ), lipoprotein lipase (LPL), macrophage scavenger receptor 1 (MSR1), and tumor necrosis factor receptor superfamily member 10b (TNFRSF10B). A Bayesian quantitative trait nucleotide analysis based on a measured genotype model showed that SNPs in LPL, TNFRSF10B, and APOJ had strong statistical evidence of a functional effect (posterior probability > or =75%) on plasma fatty acid distribution. CONCLUSIONS The results indicate that there is strong genetic influence on plasma fatty acid distribution and that genetic variation in APOJ, LPL, and TNFRSF10B may play a role. The GOCADAN study was registered at www.clinicaltrials.gov as NCT00006192.
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Bozaoglu K, Curran JE, Stocker CJ, Zaibi MS, Segal D, Konstantopoulos N, Morrison S, Carless M, Dyer TD, Cole SA, Goring HHH, Moses EK, Walder K, Cawthorne MA, Blangero J, Jowett JBM. Chemerin, a novel adipokine in the regulation of angiogenesis. J Clin Endocrinol Metab 2010; 95:2476-85. [PMID: 20237162 PMCID: PMC2869547 DOI: 10.1210/jc.2010-0042] [Citation(s) in RCA: 163] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
CONTEXT Chemerin is a new adipokine associated with obesity and the metabolic syndrome. Gene expression levels of chemerin were elevated in the adipose depots of obese compared with lean animals and was markedly elevated during differentiation of fibroblasts into mature adipocytes. OBJECTIVE The objective of the study was to identify factors that affect the regulation and potential function of chemerin using a genetics approach. DESIGN, SETTING, PATIENTS, AND INTERVENTION Plasma chemerin levels were measured in subjects from the San Antonio Family Heart Study, a large family-based genetic epidemiological study including 1354 Mexican-American individuals. Individuals were randomly sampled without regard to phenotype or disease status. MAIN OUTCOME MEASURES A genome-wide association analysis using 542,944 single-nucleotide polymorphisms in a subset of 523 of the same subjects was undertaken. The effect of chemerin on angiogenesis was measured using human endothelial cells and interstitial cells in coculture in a specially formulated medium. RESULTS Serum chemerin levels were found to be highly heritable (h(2) = 0.25; P = 1.4 x 10(-9)). The single-nucleotide polymorphism showing strongest evidence of association (rs347344; P = 1.4 x 10(-6)) was located within the gene encoding epithelial growth factor-like repeats and discoidin I-like domains 3, which has a known role in angiogenesis. Functional angiogenesis assays in human endothelial cells confirmed that chemerin significantly mediated the formation of blood vessels to a similar extent as vascular endothelial growth factor. CONCLUSION Here we demonstrate for the first time that plasma chemerin levels are significantly heritable and identified a novel role for chemerin as a stimulator of angiogenesis.
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Affiliation(s)
- Kiymet Bozaoglu
- Metabolic Research Unit, Deakin University, Geelong 3217, Australia
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36
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Zhang Y, Smith EM, Baye TM, Eckert JV, Abraham LJ, Moses EK, Kissebah AH, Martin LJ, Olivier M. Serotonin (5-HT) receptor 5A sequence variants affect human plasma triglyceride levels. Physiol Genomics 2010; 42:168-76. [PMID: 20388841 DOI: 10.1152/physiolgenomics.00038.2010] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Neurotransmitters such as serotonin (5-hydroxytryptamine, 5-HT) work closely with leptin and insulin to fine-tune the metabolic and neuroendocrine responses to dietary intake. Losing the sensitivity to excess food intake can lead to obesity, diabetes, and a multitude of behavioral disorders. It is largely unclear how different serotonin receptor subtypes respond to and integrate metabolic signals and which genetic variations in these receptor genes lead to individual differences in susceptibility to metabolic disorders. In an obese cohort of families of Northern European descent (n = 2,209), the serotonin type 5A receptor gene, HTR5A, was identified as a prominent factor affecting plasma levels of triglycerides (TG), supported by our data from both genome-wide linkage and targeted association analyses using 28 publicly available and 12 newly discovered single nucleotide polymorphisms (SNPs), of which 3 were strongly associated with plasma TG levels (P < 0.00125). Bayesian quantitative trait nucleotide (BQTN) analysis identified a putative causal promoter SNP (rs3734967) with substantial posterior probability (P = 0.59). Functional analysis of rs3734967 by electrophoretic mobility shift assay (EMSA) showed distinct binding patterns of the two alleles of this SNP with nuclear proteins from glioma cell lines. In conclusion, sequence variants in HTR5A are strongly associated with high plasma levels of TG in a Northern European population, suggesting a novel role of the serotonin receptor system in humans. This suggests a potential brain-specific regulation of plasma TG levels, possibly by alteration of the expression of HTR5A.
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Affiliation(s)
- Y Zhang
- Human and Molecular Genetics Center, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA
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Jowett JBM, Curran JE, Johnson MP, Carless MA, Göring HHH, Dyer TD, Cole SA, Comuzzie AG, MacCluer JW, Moses EK, Blangero J. Genetic variation at the FTO locus influences RBL2 gene expression. Diabetes 2010; 59:726-32. [PMID: 20009087 PMCID: PMC2828652 DOI: 10.2337/db09-1277] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVE Genome-wide association studies that compare the statistical association between thousands of DNA variations and a human trait have detected 958 loci across 127 different diseases and traits. However, these statistical associations only provide evidence for genomic regions likely to harbor a causal gene(s) and do not directly identify such genes. We combined gene variation and expression data in a human cohort to identify causal genes. RESEARCH DESIGN AND METHODS Global gene transcription activity was obtained for each individual in a large human cohort (n = 1,240). These quantitative transcript data were tested for correlation with genotype data generated from the same individuals to identify gene expression patterns influenced by the variants. RESULTS Variant rs8050136 lies within intron 1 of the FTO gene on chromosome 16 and marks a locus strongly associated with type 2 diabetes and obesity and widely replicated across many populations. We report that genetic variation at this locus does not influence FTO gene expression levels (P = 0.38), but is strongly correlated with expression of RBL2 (P = 2.7 x 10(-5)), approximately 270,000 base pairs distant to FTO. CONCLUSIONS These data suggest that variants at FTO influence RBL2 gene expression at large genetic distances. This observation underscores the complexity of human transcriptional regulation and highlights the utility of large human cohorts in which both genetic variation and global gene expression data are available to identify disease genes. Expedient identification of genes mediating the effects of genome-wide association study-identified loci will enable mechanism-of-action studies and accelerate understanding of human disease processes under genetic influence.
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Affiliation(s)
- Jeremy B M Jowett
- Department of Genomics and Systems Biology, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, Australia.
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38
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Cole SA, Butte NF, Voruganti VS, Cai G, Haack K, Kent JW, Blangero J, Comuzzie AG, McPherson JD, Gibbs RA. Evidence that multiple genetic variants of MC4R play a functional role in the regulation of energy expenditure and appetite in Hispanic children. Am J Clin Nutr 2010; 91:191-9. [PMID: 19889825 PMCID: PMC2793108 DOI: 10.3945/ajcn.2009.28514] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2009] [Accepted: 10/12/2009] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Melanocortin-4-receptor (MC4R) haploinsufficiency is the most common form of monogenic obesity; however, the frequency of MC4R variants and their functional effects in general populations remain uncertain. OBJECTIVE The aim was to identify and characterize the effects of MC4R variants in Hispanic children. DESIGN MC4R was resequenced in 376 parents, and the identified single nucleotide polymorphisms (SNPs) were genotyped in 613 parents and 1016 children from the Viva la Familia cohort. Measured genotype analysis (MGA) tested associations between SNPs and phenotypes. Bayesian quantitative trait nucleotide (BQTN) analysis was used to infer the most likely functional polymorphisms influencing obesity-related traits. RESULTS Seven rare SNPs in coding and 18 SNPs in flanking regions of MC4R were identified. MGA showed suggestive associations between MC4R variants and body size, adiposity, glucose, insulin, leptin, ghrelin, energy expenditure, physical activity, and food intake. BQTN analysis identified SNP 1704 in a predicted micro-RNA target sequence in the downstream flanking region of MC4R as a strong, probable functional variant influencing total, sedentary, and moderate activities with posterior probabilities of 1.0. SNP 2132 was identified as a variant with a high probability (1.0) of exerting a functional effect on total energy expenditure and sleeping metabolic rate. SNP rs34114122 was selected as having likely functional effects on the appetite hormone ghrelin, with a posterior probability of 0.81. CONCLUSION This comprehensive investigation provides strong evidence that MC4R genetic variants are likely to play a functional role in the regulation of weight, not only through energy intake but through energy expenditure.
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Affiliation(s)
- Shelley A Cole
- Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX, USA
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39
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Li X, Mei L, Yang K, Rotter JI, Guo X. Identifying association under a previous linkage peak on chromosome 16 for body mass index using cross-sectional and longitudinal data of the Framingham Heart Study. BMC Proc 2009; 3 Suppl 7:S101. [PMID: 20017965 PMCID: PMC2795872 DOI: 10.1186/1753-6561-3-s7-s101] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
We performed association analysis under a previous linkage peak on chromosome 16 with genome-wide single-nucleotide polymorphism (SNP) data to identify genetic variants underlying body mass index (BMI). Data from all subjects with baseline measures and a subgroup who had complete data at four selected time points from the Framingham Heart Study were analyzed. The cross-sectional measures include BMI at baseline for all subjects, as well as BMI at selected time points for the subgroup. The longitudinal measure is the within-subject mean of BMI for the subgroup at the four time points. Association analysis was first performed using PLINK after dividing large pedigrees into nuclear families. We then followed up the identified regions by variance-components methods as implemented in SOLAR using the extended pedigrees. The strongest evidence for associations were observed at 52.3 Mbp (PLINK p = 0.00002, QTLD p = 0.005), on the FTO gene, and at 48.1 Mbp (PLINK p = 0.002, QTLD p = 0.0006) on chromosome 16, which are directly under the previous identified linkage peak. This association was consistently observed for all samples at baseline, and for the subgroup at time point 2, 3, 4 and MEAN, both by PLINK and SOLAR. In addition, another SNP/region at 46.7 Mbp on same chromosome was found to be associated with several BMI measures in the subgroup. Fine-mapping with more markers provided further evidence for SNP association with BMI in the same region (at 52.4 Mbp, QTLD p = 0.0003). These results suggest the existence of genes/DNA variations in these regions that contribute to BMI variation.
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Affiliation(s)
- Xiaohui Li
- Medical Genetics Institute, Cedars-Sinai Medical Center, 8635 West Third Street, Suite 1150, Los Angeles, California 90048 USA.
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40
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Kent JW, Peterson CP, Dyer TD, Almasy L, Blangero J. Genome-wide discovery of maternal effect variants. BMC Proc 2009; 3 Suppl 7:S19. [PMID: 20018008 PMCID: PMC2795915 DOI: 10.1186/1753-6561-3-s7-s19] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Many phenotypes may be influenced by the prenatal environment of the mother and/or maternal care, and these maternal effects may have a heritable component. We have implemented in the computer program SOLAR a variance components-based method for detecting indirect effects of maternal genotype on offspring phenotype. Of six phenotypes measured in three generations of the Framingham Heart Study, height showed the strongest evidence (P = 0.02) of maternal effect. We conducted a genome-wide association analysis for height, testing both the direct effect of the focal individual's genotype and the indirect effect of the maternal genotype. Offspring height showed suggestive evidence of association with maternal genotype for two single-nucleotide polymorphisms in the trafficking protein particle complex 9 gene TRAPPC9 (NIBP), which plays a role in neuronal NF-κB signalling. This work establishes a methodological framework for identifying genetic variants that may influence the contribution of the maternal environment to offspring phenotypes.
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Affiliation(s)
- Jack W Kent
- Department of Genetics, Southwest Foundation for Biomedical Research, 7620 NW Loop 410, San Antonio, TX 78227, USA.
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41
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Calafell F, Almasy L, Sabater-Lleal M, Buil A, Mordillo C, Ramírez-Soriano A, Sikora M, Souto JC, Blangero J, Fontcuberta J, Soria JM. Sequence variation and genetic evolution at the human F12 locus: mapping quantitative trait nucleotides that influence FXII plasma levels. Hum Mol Genet 2009; 19:517-25. [PMID: 19933701 DOI: 10.1093/hmg/ddp517] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The level of Factor XII (FXII) is an important phenotype that exhibits a high genetic component and is associated with thrombotic disease. In a genome-wide linkage scan, we demonstrated that the F12 gene represents a quantitative trait locus (QTL) that influences FXII levels. The current study investigated the genetic architecture of the F12 gene to locate polymorphism(s) responsible for the variation of FXII levels. Re-sequencing of the F12 gene in 40 unrelated individuals (selected from the tails of normal distribution of FXII levels) identified 26 polymorphisms which were genotyped in 398 individuals belonging to 21 families from the GAIT Project. By a measured genotype association analysis, eight of 26 SNPs showed significant P-values less than 10(-5) (after multiple test correction) with FXII levels. In addition, the Bayesian Quantitative Trait Nucleotide method, which infers those polymorphisms most likely to have a direct influence on the trait under study, provided evidence that only rs1801020 variation accounted for the variance attributed to this QTL. Moreover, we have analyzed the evolutionary processes that produced the variation in F12 gene and concluded that is evolutionarily neutral and that the T allele of the rs1801020 appeared approximately 100 000 years ago and spread to most human populations rising to high frequencies by genetic drift. Our study provides a template for future genetic studies of human quantitative traits, as we move beyond QTL localization to the polymorphisms responsible for the variation of important biomedical phenotypes.
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Affiliation(s)
- Francesc Calafell
- Departament de Ciències Experimentals i de la Salut, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
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42
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Genetic variation in PARL influences mitochondrial content. Hum Genet 2009; 127:183-90. [PMID: 19862556 DOI: 10.1007/s00439-009-0756-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2009] [Accepted: 10/13/2009] [Indexed: 12/19/2022]
Abstract
Given their involvement in processes necessary for life, mitochondrial damage and subsequent dysfunction can lead to a wide range of human diseases. Previous studies of both animal models and humans have suggested that presenilins-associated rhomboid-like protein (PARL) is a key regulator of mitochondrial integrity and function, and plays a role in cellular apoptosis. As a surrogate measure of mitochondrial integrity, we previously measured mitochondrial content in a Caucasian population consisting of large extended pedigrees, with results highlighting a substantial genetic component to this trait. To assess the influence of variation in the PARL gene on mitochondrial content, we re-sequenced 6.5 kb of the gene, identifying 16 SNPs and genotyped these in 1,086 Caucasian individuals, distributed across 170 families. Statistical genetic analysis revealed that one promoter variant, T-191C, exhibited significant effects (after correction for multiple testing) on mitochondrial content levels. Comparison of the transcription factor binding characteristics of the T-191C promoter SNP by EMSA indicates preferential binding of nuclear factors to the T allele, suggesting functional variation in PARL expression. These results suggest that genetic variation within PARL influences mitochondrial abundance and integrity.
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Fridley BL. Bayesian variable and model selection methods for genetic association studies. Genet Epidemiol 2009; 33:27-37. [PMID: 18618760 DOI: 10.1002/gepi.20353] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Variable selection is growing in importance with the advent of high throughput genotyping methods requiring analysis of hundreds to thousands of single nucleotide polymorphisms (SNPs) and the increased interest in using these genetic studies to better understand common, complex diseases. Up to now, the standard approach has been to analyze the genotypes for each SNP individually to look for an association with a disease. Alternatively, combinations of SNPs or haplotypes are analyzed for association. Another added complication in studying complex diseases or phenotypes is that genetic risk for the disease is often due to multiple SNPs in various locations on the chromosome with small individual effects that may have a collectively large effect on the phenotype. Hence, multi-locus SNP models, as opposed to single SNP models, may better capture the true underlying genotypic-phenotypic relationship. Thus, innovative methods for determining which SNPs to include in the model are needed. The goal of this article is to describe several methods currently available for variable and model selection using Bayesian approaches and to illustrate their application for genetic association studies using both real and simulated candidate gene data for a complex disease. In particular, Bayesian model averaging (BMA), stochastic search variable selection (SSVS), and Bayesian variable selection (BVS) using a reversible jump Markov chain Monte Carlo (MCMC) for candidate gene association studies are illustrated using a study of age-related macular degeneration (AMD) and simulated data.
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Affiliation(s)
- Brooke L Fridley
- Division of Biostatistics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota 55905, USA.
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The ERAP2 gene is associated with preeclampsia in Australian and Norwegian populations. Hum Genet 2009; 126:655-66. [PMID: 19578876 DOI: 10.1007/s00439-009-0714-x] [Citation(s) in RCA: 82] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2009] [Accepted: 06/22/2009] [Indexed: 01/07/2023]
Abstract
Preeclampsia is a heritable pregnancy disorder that presents new onset hypertension and proteinuria. We have previously reported genetic linkage to preeclampsia on chromosomes 2q, 5q and 13q in an Australian/New Zealand (Aust/NZ) familial cohort. This current study centered on identifying the susceptibility gene(s) at the 5q locus. We first prioritized candidate genes using a bioinformatic tool designed for this purpose. We then selected a panel of known SNPs within ten prioritized genes and genotyped them in an extended set of the Aust/NZ families and in a very large, independent Norwegian case/control cohort (1,139 cases, 2,269 controls). In the Aust/NZ cohort we identified evidence of a genetic association for the endoplasmic reticulum aminopeptidase 1 (ERAP1) gene (rs3734016, P (uncorr) = 0.009) and for the endoplasmic reticulum aminopeptidase 2 (ERAP2) gene (rs2549782, P (uncorr) = 0.004). In the Norwegian cohort we identified evidence of a genetic association for ERAP1 (rs34750, P (uncorr) = 0.011) and for ERAP2 (rs17408150, P (uncorr) = 0.009). The ERAP2 SNPs in both cohorts remained statistically significant (rs2549782, P (corr) = 0.018; rs17408150, P (corr) = 0.039) after corrections at an experiment-wide level. The ERAP1 and ERAP2 genes encode enzymes that are reported to play a role in blood pressure regulation and essential hypertension in addition to innate immune and inflammatory responses. Perturbations within vascular, immunological and inflammatory pathways constitute important physiological mechanisms in preeclampsia pathogenesis. We herein report a novel preeclampsia risk locus, ERAP2, in a region of known genetic linkage to this pregnancy-specific disorder.
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A critical assessment of the factors affecting reporter gene assays for promoter SNP function: a reassessment of -308 TNF polymorphism function using a novel integrated reporter system. Eur J Hum Genet 2009; 17:1454-62. [PMID: 19471307 DOI: 10.1038/ejhg.2009.80] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
One of the greatest challenges facing genetics is the development of strategies to identify functionally relevant genetic variation. The most common test of function is the reporter gene assay, in which allelic regulatory regions are used to drive the expression of a reporter gene, and differences in expression in a cell line after transient transfection are taken to be a reflection of the polymorphism. Many studies have reported small differences in single nucleotide polymorphism (SNP)-specific reporter activity, including the tumor necrosis factor (TNF) G-308A polymorphism. However, we have established that many variables inherent in the reporter gene approach can account for the reported allelic differences. Variables, such as the amount of DNA used in transfection, the amount of transfection control vector used, the method of transfection, the growth history of the host cells, and the quality and purity of DNA used, all influence TNF -308 SNP-specific transient reporter gene assays and serve as a caution for those researchers who apply this method to the functional assessment of polymorphic promoter sequences. We have developed an integrated reporter system that obviates some of these problems and shows that the TNF G-308A polymorphism is functionally relevant in this improved assay, thus confirming that the -308A allele expresses at a higher level compared with the -308G allele.
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Montasser ME, Shimmin LC, Hanis CL, Boerwinkle E, Hixson JE. Gene by smoking interaction in hypertension: identification of a major quantitative trait locus on chromosome 15q for systolic blood pressure in Mexican–Americans. J Hypertens 2009; 27:491-501. [DOI: 10.1097/hjh.0b013e32831ef54f] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Roten LT, Johnson MP, Forsmo S, Fitzpatrick E, Dyer TD, Brennecke SP, Blangero J, Moses EK, Austgulen R. Association between the candidate susceptibility gene ACVR2A on chromosome 2q22 and pre-eclampsia in a large Norwegian population-based study (the HUNT study). Eur J Hum Genet 2008; 17:250-7. [PMID: 18781190 DOI: 10.1038/ejhg.2008.158] [Citation(s) in RCA: 46] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Genome-wide scans in Icelandic, Australian/New Zealand and Finnish pedigrees have provided evidence for maternal susceptibility loci for pre-eclampsia on chromosome 2, although at different positions (Iceland: 2p13 and 2q23, Australia/New Zealand: 2p11-12 and 2q22, Finland: 2p25). In this project, a large population-based (n=65 000) nested case-control study was performed in Norway to further explore the association between positional candidate genes on chromosome 2q and pre-eclampsia, using single-nucleotide polymorphisms (SNPs). DNA samples from 1139 cases (women with one or more pre-eclamptic pregnancies) and 2269 controls (women with normal pregnancies) were genotyped using the Applied Biosystems SNPlex high-throughput genotyping assay. In total, 71 SNPs within positional candidate genes at 2q22-23 locus on chromosome 2 were genotyped in each individual. Genotype data were statistically analysed with the sequential oligogenic linkage analysis routines (SOLAR) computer package. Nominal evidence of association was found for six SNPs (rs1014064, rs17742134, rs1424941, rs2161983, rs3768687 and rs3764955) within the activin receptor type 2 gene (ACVR2A) (all P-values <0.05). The non-independence of statistical tests due to linkage disequilibrium between SNPs at a false discovery rate of 5% identifies our four best SNPs (rs1424941, rs1014064, rs2161983 and rs3768687) to remain statistically significant. The fact that populations with different ancestors (Iceland/Norway-Australia/New Zealand) demonstrate a common maternal pre-eclampsia susceptibility locus on chromosome 2q22-23, may suggest a general role of this locus, and possibly the ACVR2A gene, in pre-eclampsia pathogenesis.
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Affiliation(s)
- Linda T Roten
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
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Jenkinson CP, Coletta DK, Flechtner-Mors M, Hu SL, Fourcaudot MJ, Rodriguez LM, Schneider J, Arya R, Stern MP, Blangero J, Duggirala R, DeFronzo RA. Association of genetic variation in ENPP1 with obesity-related phenotypes. Obesity (Silver Spring) 2008; 16:1708-13. [PMID: 18464750 PMCID: PMC4889449 DOI: 10.1038/oby.2008.262] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Ectonucleotide pyrophosphatase phosphodiesterase (ENPP1) is a positional candidate gene at chromosome 6q23 where we previously detected strong linkage with fasting-specific plasma insulin and obesity in Mexican Americans from the San Antonio Family Diabetes Study (SAFDS). We genotyped 106 single-nucleotide polymorphisms (SNPs) within ENPP1 in all 439 subjects from the linkage study, and measured association with obesity and metabolic syndrome (MS)-related traits. Of 72 polymorphic SNPs, 24 were associated, using an additive model, with at least one of eight key metabolic traits. Three traits were associated with at least four SNPs. They were high-density lipoprotein cholesterol (HDL-C), leptin, and fasting plasma glucose (FPG). HDL-C was associated with seven SNPs, of which the two most significant P values were 0.0068 and 0.0096. All SNPs and SNP combinations were analyzed for functional contribution to the traits using the Bayesian quantitative-trait nucleotide (BQTN) approach. With this SNP-prioritization analysis, HDL-C was the most strongly associated trait in a four-SNP model (P=0.00008). After accounting for multiple testing, we conclude that ENPP1 is not a major contributor to our previous linkage peak with MS-related traits in Mexican Americans. However, these results indicate that ENPP1 is a genetic determinant of these traits in this population, and are consistent with multiple positive association findings in independent studies in diverse human populations.
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Affiliation(s)
- Christopher P Jenkinson
- Division of Diabetes, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
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Williams-Blangero S, Vandeberg JL, Subedi J, Jha B, Dyer TD, Blangero J. Two quantitative trait loci influence whipworm (Trichuris trichiura) infection in a Nepalese population. J Infect Dis 2008; 197:1198-203. [PMID: 18462166 DOI: 10.1086/533493] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND Whipworm (Trichuris trichiura) infection is a soil-transmitted helminth infection that affects >1 billion people. It is a serious public health problem in many developing countries and can result in deficits in growth and cognitive development. In a follow-up study of significant heritability for whipworm infection, we conducted the first genome scan for quantitative trait loci (QTL) influencing the heritability of susceptibility to this important parasitic disease. METHODS Whipworm egg counts were determined for 1,253 members of the Jirel population of eastern Nepal. All individuals in the study sample belonged to a single pedigree including >26,000 pairs of relatives that are informative for genetic analysis. RESULTS Linkage analysis of genome scan data generated for the pedigree provided unambiguous evidence for 2 QTL influencing susceptibility to whipworm infection, one located on chromosome 9 (logarithm of the odds ratio [LOD] score, 3.35; genomewide P = .0138) and the other located on chromosome 18 (LOD score, 3.29; genomewide P = .0159). There was also suggestive evidence that 2 loci located on chromosomes 12 and 13 influenced whipworm infection. CONCLUSION The results of this first genome scan for T. trichiura egg counts provides new information on the determinants of genetic predisposition to whipworm infection.
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Affiliation(s)
- Sarah Williams-Blangero
- Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas 78245-0549, USA.
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50
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Huertas-Vazquez A, Plaisier C, Weissglas-Volkov D, Sinsheimer J, Canizales-Quinteros S, Cruz-Bautista I, Nikkola E, Herrera-Hernandez M, Davila-Cervantes A, Tusie-Luna T, Taskinen MR, Aguilar-Salinas C, Pajukanta P. TCF7L2 is associated with high serum triacylglycerol and differentially expressed in adipose tissue in families with familial combined hyperlipidaemia. Diabetologia 2008; 51:62-9. [PMID: 17972059 DOI: 10.1007/s00125-007-0850-6] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2007] [Accepted: 09/19/2007] [Indexed: 10/22/2022]
Abstract
AIMS/HYPOTHESIS Common DNA variants of the transcription factor 7-like 2 gene (TCF7L2) are associated with type 2 diabetes. Familial combined hyperlipidaemia (FCHL) is characterised by hypertriacylglycerolaemia, hypercholesterolaemia, or both. Additionally, disturbances in glucose metabolism are commonly seen in FCHL. Therefore, we hypothesised that TCF7L2 may contribute to the genetic susceptibility for this common dyslipidaemia. METHODS We investigated the effect of the TCF7L2 variants, rs7903146 and rs12255372, on FCHL and its component traits triacylglycerol (TG), total cholesterol (TC) and apolipoprotein B (ApoB) in 759 individuals from 55 Mexican families. As a replication sample, 719 individuals from 60 Finnish FCHL families were analysed. We also used quantitative RT-PCR to evaluate the transcript levels of TCF7L2 in 47 subcutaneous fat biopsies from unrelated Mexican FCHL and normolipidaemic participants. RESULTS Significant evidence for association was observed for high TG for the T alleles of rs7903146 and rs12255372 (p = 0.005 and p = 0.01) in Mexican FCHL families. No evidence for association was observed for FCHL, TC, ApoB or glucose in Mexicans. When testing rs7903146 and rs12255372 for replication in Finnish FCHL families, these single nucleotide polymorphisms were associated with TG (p = 0.01 and p = 0.007). Furthermore, we observed statistically significant decreases in the mRNA levels (p = 0.0002) of TCF7L2 in FCHL- and TG-affected individuals. TCF7L2 expression was not altered by the SNP genotypes. CONCLUSIONS/INTERPRETATION These data show that rs7903146 and rs12255372 are significantly associated with high TG in FCHL families from two different populations. In addition, significantly decreased expression of TCF7L2 was observed in TG- and FCHL-affected individuals.
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Affiliation(s)
- A Huertas-Vazquez
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA
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