Genetic evidence for a normal-weight "metabolically obese" phenotype linking insulin resistance, hypertension, coronary artery disease, and type 2 diabetes

The mechanisms that predispose to hypertension, coronary artery disease (CAD), and type 2 diabetes (T2D) in individuals of normal weight are poorly understood. In contrast, in monogenic primary lipodystrophy-a reduction in subcutaneous adipose tissue-it is clear that it is adipose dysfunction that c...

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Vydané v:	Diabetes (New York, N.Y.) Ročník 63; číslo 12; s. 4369
Hlavní autori:	Yaghootkar, Hanieh, Scott, Robert A, White, Charles C, Zhang, Weihua, Speliotes, Elizabeth, Munroe, Patricia B, Ehret, Georg B, Bis, Joshua C, Fox, Caroline S, Walker, Mark, Borecki, Ingrid B, Knowles, Joshua W, Yerges-Armstrong, Laura, Ohlsson, Claes, Perry, John R B, Chambers, John C, Kooner, Jaspal S, Franceschini, Nora, Langenberg, Claudia, Hivert, Marie-France, Dastani, Zari, Richards, J Brent, Semple, Robert K, Frayling, Timothy M
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.12.2014
Predmet:	Body Mass Index Coronary Artery Disease - genetics Diabetes Mellitus, Type 2 - genetics Genetic Predisposition to Disease Humans Hypertension - genetics Insulin Resistance - genetics Intra-Abdominal Fat Lipodystrophy - genetics Metabolic Syndrome - genetics Obesity - genetics Odds Ratio Phenotype Subcutaneous Fat
ISSN:	1939-327X, 1939-327X
On-line prístup:	Zistit podrobnosti o prístupe
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Abstract	The mechanisms that predispose to hypertension, coronary artery disease (CAD), and type 2 diabetes (T2D) in individuals of normal weight are poorly understood. In contrast, in monogenic primary lipodystrophy-a reduction in subcutaneous adipose tissue-it is clear that it is adipose dysfunction that causes severe insulin resistance (IR), hypertension, CAD, and T2D. We aimed to test the hypothesis that common alleles associated with IR also influence the wider clinical and biochemical profile of monogenic IR. We selected 19 common genetic variants associated with fasting insulin-based measures of IR. We used hierarchical clustering and results from genome-wide association studies of eight nondisease outcomes of monogenic IR to group these variants. We analyzed genetic risk scores against disease outcomes, including 12,171 T2D cases, 40,365 CAD cases, and 69,828 individuals with blood pressure measurements. Hierarchical clustering identified 11 variants associated with a metabolic profile consistent with a common, subtle form of lipodystrophy. A genetic risk score consisting of these 11 IR risk alleles was associated with higher triglycerides (β = 0.018; P = 4 × 10(-29)), lower HDL cholesterol (β = -0.020; P = 7 × 10(-37)), greater hepatic steatosis (β = 0.021; P = 3 × 10(-4)), higher alanine transaminase (β = 0.002; P = 3 × 10(-5)), lower sex-hormone-binding globulin (β = -0.010; P = 9 × 10(-13)), and lower adiponectin (β = -0.015; P = 2 × 10(-26)). The same risk alleles were associated with lower BMI (per-allele β = -0.008; P = 7 × 10(-8)) and increased visceral-to-subcutaneous adipose tissue ratio (β = -0.015; P = 6 × 10(-7)). Individuals carrying ≥17 fasting insulin-raising alleles (5.5% population) were slimmer (0.30 kg/m(2)) but at increased risk of T2D (odds ratio [OR] 1.46; per-allele P = 5 × 10(-13)), CAD (OR 1.12; per-allele P = 1 × 10(-5)), and increased blood pressure (systolic and diastolic blood pressure of 1.21 mmHg [per-allele P = 2 × 10(-5)] and 0.67 mmHg [per-allele P = 2 × 10(-4)], respectively) compared with individuals carrying ≤9 risk alleles (5.5% population). Our results provide genetic evidence for a link between the three diseases of the "metabolic syndrome" and point to reduced subcutaneous adiposity as a central mechanism.
AbstractList	The mechanisms that predispose to hypertension, coronary artery disease (CAD), and type 2 diabetes (T2D) in individuals of normal weight are poorly understood. In contrast, in monogenic primary lipodystrophy-a reduction in subcutaneous adipose tissue-it is clear that it is adipose dysfunction that causes severe insulin resistance (IR), hypertension, CAD, and T2D. We aimed to test the hypothesis that common alleles associated with IR also influence the wider clinical and biochemical profile of monogenic IR. We selected 19 common genetic variants associated with fasting insulin-based measures of IR. We used hierarchical clustering and results from genome-wide association studies of eight nondisease outcomes of monogenic IR to group these variants. We analyzed genetic risk scores against disease outcomes, including 12,171 T2D cases, 40,365 CAD cases, and 69,828 individuals with blood pressure measurements. Hierarchical clustering identified 11 variants associated with a metabolic profile consistent with a common, subtle form of lipodystrophy. A genetic risk score consisting of these 11 IR risk alleles was associated with higher triglycerides (β = 0.018; P = 4 × 10(-29)), lower HDL cholesterol (β = -0.020; P = 7 × 10(-37)), greater hepatic steatosis (β = 0.021; P = 3 × 10(-4)), higher alanine transaminase (β = 0.002; P = 3 × 10(-5)), lower sex-hormone-binding globulin (β = -0.010; P = 9 × 10(-13)), and lower adiponectin (β = -0.015; P = 2 × 10(-26)). The same risk alleles were associated with lower BMI (per-allele β = -0.008; P = 7 × 10(-8)) and increased visceral-to-subcutaneous adipose tissue ratio (β = -0.015; P = 6 × 10(-7)). Individuals carrying ≥17 fasting insulin-raising alleles (5.5% population) were slimmer (0.30 kg/m(2)) but at increased risk of T2D (odds ratio [OR] 1.46; per-allele P = 5 × 10(-13)), CAD (OR 1.12; per-allele P = 1 × 10(-5)), and increased blood pressure (systolic and diastolic blood pressure of 1.21 mmHg [per-allele P = 2 × 10(-5)] and 0.67 mmHg [per-allele P = 2 × 10(-4)], respectively) compared with individuals carrying ≤9 risk alleles (5.5% population). Our results provide genetic evidence for a link between the three diseases of the "metabolic syndrome" and point to reduced subcutaneous adiposity as a central mechanism.The mechanisms that predispose to hypertension, coronary artery disease (CAD), and type 2 diabetes (T2D) in individuals of normal weight are poorly understood. In contrast, in monogenic primary lipodystrophy-a reduction in subcutaneous adipose tissue-it is clear that it is adipose dysfunction that causes severe insulin resistance (IR), hypertension, CAD, and T2D. We aimed to test the hypothesis that common alleles associated with IR also influence the wider clinical and biochemical profile of monogenic IR. We selected 19 common genetic variants associated with fasting insulin-based measures of IR. We used hierarchical clustering and results from genome-wide association studies of eight nondisease outcomes of monogenic IR to group these variants. We analyzed genetic risk scores against disease outcomes, including 12,171 T2D cases, 40,365 CAD cases, and 69,828 individuals with blood pressure measurements. Hierarchical clustering identified 11 variants associated with a metabolic profile consistent with a common, subtle form of lipodystrophy. A genetic risk score consisting of these 11 IR risk alleles was associated with higher triglycerides (β = 0.018; P = 4 × 10(-29)), lower HDL cholesterol (β = -0.020; P = 7 × 10(-37)), greater hepatic steatosis (β = 0.021; P = 3 × 10(-4)), higher alanine transaminase (β = 0.002; P = 3 × 10(-5)), lower sex-hormone-binding globulin (β = -0.010; P = 9 × 10(-13)), and lower adiponectin (β = -0.015; P = 2 × 10(-26)). The same risk alleles were associated with lower BMI (per-allele β = -0.008; P = 7 × 10(-8)) and increased visceral-to-subcutaneous adipose tissue ratio (β = -0.015; P = 6 × 10(-7)). Individuals carrying ≥17 fasting insulin-raising alleles (5.5% population) were slimmer (0.30 kg/m(2)) but at increased risk of T2D (odds ratio [OR] 1.46; per-allele P = 5 × 10(-13)), CAD (OR 1.12; per-allele P = 1 × 10(-5)), and increased blood pressure (systolic and diastolic blood pressure of 1.21 mmHg [per-allele P = 2 × 10(-5)] and 0.67 mmHg [per-allele P = 2 × 10(-4)], respectively) compared with individuals carrying ≤9 risk alleles (5.5% population). Our results provide genetic evidence for a link between the three diseases of the "metabolic syndrome" and point to reduced subcutaneous adiposity as a central mechanism. The mechanisms that predispose to hypertension, coronary artery disease (CAD), and type 2 diabetes (T2D) in individuals of normal weight are poorly understood. In contrast, in monogenic primary lipodystrophy-a reduction in subcutaneous adipose tissue-it is clear that it is adipose dysfunction that causes severe insulin resistance (IR), hypertension, CAD, and T2D. We aimed to test the hypothesis that common alleles associated with IR also influence the wider clinical and biochemical profile of monogenic IR. We selected 19 common genetic variants associated with fasting insulin-based measures of IR. We used hierarchical clustering and results from genome-wide association studies of eight nondisease outcomes of monogenic IR to group these variants. We analyzed genetic risk scores against disease outcomes, including 12,171 T2D cases, 40,365 CAD cases, and 69,828 individuals with blood pressure measurements. Hierarchical clustering identified 11 variants associated with a metabolic profile consistent with a common, subtle form of lipodystrophy. A genetic risk score consisting of these 11 IR risk alleles was associated with higher triglycerides (β = 0.018; P = 4 × 10(-29)), lower HDL cholesterol (β = -0.020; P = 7 × 10(-37)), greater hepatic steatosis (β = 0.021; P = 3 × 10(-4)), higher alanine transaminase (β = 0.002; P = 3 × 10(-5)), lower sex-hormone-binding globulin (β = -0.010; P = 9 × 10(-13)), and lower adiponectin (β = -0.015; P = 2 × 10(-26)). The same risk alleles were associated with lower BMI (per-allele β = -0.008; P = 7 × 10(-8)) and increased visceral-to-subcutaneous adipose tissue ratio (β = -0.015; P = 6 × 10(-7)). Individuals carrying ≥17 fasting insulin-raising alleles (5.5% population) were slimmer (0.30 kg/m(2)) but at increased risk of T2D (odds ratio [OR] 1.46; per-allele P = 5 × 10(-13)), CAD (OR 1.12; per-allele P = 1 × 10(-5)), and increased blood pressure (systolic and diastolic blood pressure of 1.21 mmHg [per-allele P = 2 × 10(-5)] and 0.67 mmHg [per-allele P = 2 × 10(-4)], respectively) compared with individuals carrying ≤9 risk alleles (5.5% population). Our results provide genetic evidence for a link between the three diseases of the "metabolic syndrome" and point to reduced subcutaneous adiposity as a central mechanism.
Author	Walker, Mark White, Charles C Semple, Robert K Borecki, Ingrid B Hivert, Marie-France Knowles, Joshua W Kooner, Jaspal S Scott, Robert A Bis, Joshua C Langenberg, Claudia Dastani, Zari Frayling, Timothy M Zhang, Weihua Speliotes, Elizabeth Ohlsson, Claes Franceschini, Nora Chambers, John C Yaghootkar, Hanieh Munroe, Patricia B Ehret, Georg B Perry, John R B Richards, J Brent Yerges-Armstrong, Laura Fox, Caroline S
Author_xml	– sequence: 1 givenname: Hanieh surname: Yaghootkar fullname: Yaghootkar, Hanieh organization: Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, U.K – sequence: 2 givenname: Robert A surname: Scott fullname: Scott, Robert A organization: MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, U.K – sequence: 3 givenname: Charles C surname: White fullname: White, Charles C organization: Framingham Heart Study, National Heart, Lung, and Blood Institute, National Institutes of Health, Framingham, MA Department of Biostatistics, Boston University School of Public Health, Boston, MA – sequence: 4 givenname: Weihua surname: Zhang fullname: Zhang, Weihua organization: Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, U.K – sequence: 5 givenname: Elizabeth surname: Speliotes fullname: Speliotes, Elizabeth organization: Department of Internal Medicine, Division of Gastroenterology, and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI – sequence: 6 givenname: Patricia B surname: Munroe fullname: Munroe, Patricia B organization: Clinical Pharmacology and Barts and The London Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, U.K – sequence: 7 givenname: Georg B surname: Ehret fullname: Ehret, Georg B organization: Cardiology Center, Geneva University Hospital, Geneva, Switzerland Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD – sequence: 8 givenname: Joshua C surname: Bis fullname: Bis, Joshua C organization: Cardiovascular Health Research Unit and Department of Medicine, University of Washington, Seattle, WA – sequence: 9 givenname: Caroline S surname: Fox fullname: Fox, Caroline S organization: Framingham Heart Study, National Heart, Lung, and Blood Institute, National Institutes of Health, Framingham, MA Center for Population Studies, National Heart, Lung, and Blood Institute, National Institutes of Health, Framingham, MA Division of Endocrinology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA – sequence: 10 givenname: Mark surname: Walker fullname: Walker, Mark organization: Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, U.K – sequence: 11 givenname: Ingrid B surname: Borecki fullname: Borecki, Ingrid B organization: Department of Genetics, Washington University School of Medicine, St. Louis, MO – sequence: 12 givenname: Joshua W surname: Knowles fullname: Knowles, Joshua W organization: Department of Medicine and Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA – sequence: 13 givenname: Laura surname: Yerges-Armstrong fullname: Yerges-Armstrong, Laura organization: University of Maryland School of Medicine, Division of Endocrinology, Baltimore, MA – sequence: 14 givenname: Claes surname: Ohlsson fullname: Ohlsson, Claes organization: Center for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden – sequence: 15 givenname: John R B surname: Perry fullname: Perry, John R B organization: MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, U.K – sequence: 16 givenname: John C surname: Chambers fullname: Chambers, John C organization: Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, U.K – sequence: 17 givenname: Jaspal S surname: Kooner fullname: Kooner, Jaspal S organization: Cardiovascular Science, National Heart and Lung Institute, Imperial College London, London, U.K – sequence: 18 givenname: Nora surname: Franceschini fullname: Franceschini, Nora organization: Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC – sequence: 19 givenname: Claudia surname: Langenberg fullname: Langenberg, Claudia organization: MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, U.K. Department of Epidemiology and Public Health, University College London, London, U.K – sequence: 20 givenname: Marie-France surname: Hivert fullname: Hivert, Marie-France organization: Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA General Medicine Division, Massachusetts General Hospital, Boston, MA – sequence: 21 givenname: Zari surname: Dastani fullname: Dastani, Zari organization: Departments of Human Genetics and Epidemiology and Biostatistics, McGill University, Montreal, Quebec, Canada – sequence: 22 givenname: J Brent surname: Richards fullname: Richards, J Brent organization: Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K. Department of Medicine, Human Genetics, Epidemiology, and Biostatistics, McGill University, Montreal, Quebec, Canada – sequence: 23 givenname: Robert K surname: Semple fullname: Semple, Robert K organization: The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, U.K. The University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Cambridge, U.K – sequence: 24 givenname: Timothy M surname: Frayling fullname: Frayling, Timothy M email: t.m.frayling@ex.ac.uk organization: Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, U.K. t.m.frayling@ex.ac.uk
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/25048195$$D View this record in MEDLINE/PubMed
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ContentType	Journal Article
Copyright	2014 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
Copyright_xml	– notice: 2014 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
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License	2014 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
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PublicationTitle	Diabetes (New York, N.Y.)
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References	25414016 - Diabetes. 2014 Dec;63(12):4004-7. doi: 10.2337/db14-1358.
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Snippet	The mechanisms that predispose to hypertension, coronary artery disease (CAD), and type 2 diabetes (T2D) in individuals of normal weight are poorly understood....
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SubjectTerms	Body Mass Index Coronary Artery Disease - genetics Diabetes Mellitus, Type 2 - genetics Genetic Predisposition to Disease Humans Hypertension - genetics Insulin Resistance - genetics Intra-Abdominal Fat Lipodystrophy - genetics Metabolic Syndrome - genetics Obesity - genetics Odds Ratio Phenotype Subcutaneous Fat
Title	Genetic evidence for a normal-weight "metabolically obese" phenotype linking insulin resistance, hypertension, coronary artery disease, and type 2 diabetes
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