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ß2-adrenergic receptor Thr164Ile polymorphism, obesity, and diabetes: comparison with FTO, MC4R, and TMEM18 polymorphisms in more than 64,000 individuals.

https://arctichealth.org/en/permalink/ahliterature125626
Source
J Clin Endocrinol Metab. 2012 Jun;97(6):E1074-9
Publication Type
Article
Date
Jun-2012
Author
Mette Thomsen
Morten Dahl
Anne Tybjærg-Hansen
Børge G Nordestgaard
Author Affiliation
Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-2730 Herlev, Denmark.
Source
J Clin Endocrinol Metab. 2012 Jun;97(6):E1074-9
Date
Jun-2012
Language
English
Publication Type
Article
Keywords
Adult
Body mass index
Cohort Studies
Denmark - epidemiology
Diabetes Mellitus - epidemiology - genetics
Female
Genetic Predisposition to Disease - epidemiology - genetics
Genotype
Humans
Male
Membrane Proteins - genetics
Obesity - epidemiology - genetics
Polymorphism, Single Nucleotide - genetics
Proteins - genetics
Receptor, Melanocortin, Type 4 - genetics
Receptors, Adrenergic, beta-2 - genetics
Risk factors
Abstract
The ß(2)-adrenergic receptor (ADRB2) influences regulation of energy balance by stimulating catecholamine-induced lipolysis in adipose tissue. The rare functional ADRB2rs1800888(Thr164Ile) polymorphism could therefore influence risk of obesity and subsequently diabetes.
We tested the hypothesis that the ADRB2rs1800888(Thr164Ile) polymorphism associates with risk of obesity and diabetes and compared effect sizes with those of FTO(rs9939609), MC4R(rs17782313), and TMEM18(rs6548238).
We conducted a population-based cohort study in Copenhagen, Denmark.
We genotyped more than 64,000 individuals from the Danish general population.
We evaluated body mass index (BMI), obesity (BMI =30 kg/m(2)), and diabetes.
Rare allele frequencies were 0.02 for T for ADRB2rs1800888(Thr164Ile), 0.40 for A for FTOrs9939609, 0.25 for C for MC4Rrs17782313, and 0.20 for T for TMEM18rs6548238. For rare vs. common homozygotes, odds ratio for obesity was 3.32 (95% confidence interval = 1.08-10.19) for ADRB2rs1800888(Thr164Ile), 1.42 (1.35-1.52) for FTOrs9939609, 1.18 (1.06-1.30) for MC4Rrs17782313, and 1.28 (1.10-1.50) for TMEM18rs6548238 (common vs. rare). Corresponding odds ratios for diabetes were 1.85 (0.24-14.29), 1.22 (1.07-1.39), 0.96 (0.80-1.16), and 1.61 (1.17-2.22), respectively. After adjustment for BMI, only TMEM18rs6548238 remained associated with diabetes. BMI was increased in rare vs. common homozygotes in FTOrs9939609, MC4Rrs17782313, and TMEM18rs6548238 (common vs. rare) but not in ADRB2rs1800888(Thr164Ile).
Our results suggest that ADRB2rs1800888(Thr164Ile) rare vs. common homozygotes are not significantly associated with an increase in BMI measured continuously but may be associated with an increased risk of obesity. Also, TMEM18rs6548238 associated with risk of diabetes after adjustment for BMI. These findings need confirmation in other studies.
PubMed ID
22466342 View in PubMed
Less detail
Source
Nature. 2016 Sep 14;537(7620):S103-4
Publication Type
Article
Date
Sep-14-2016
Author
Jesse Emspak
Source
Nature. 2016 Sep 14;537(7620):S103-4
Date
Sep-14-2016
Language
English
Publication Type
Article
Keywords
Adult - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Age Factors - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Aged - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Alcohol Drinking - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Body Mass Index - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Continental Population Groups - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Diuretics - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Ethanol - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Female - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Gene-Environment Interaction - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Humans - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Hypertension - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Kidney Neoplasms - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Life Style - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Male - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Middle Aged - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Obesity - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Risk Factors - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Sex Factors - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Smoking - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
Sweden - epidemiology - genetics - statistics & numerical data - pharmacology - administration & dosage - pharmacology - epidemiology - classification - epidemiology - genetics - prevention & control - epidemiology - epidemiology - epidemiology
PubMed ID
27626777 View in PubMed
Less detail

Appetitive traits as behavioural pathways in genetic susceptibility to obesity: a population-based cross-sectional study.

https://arctichealth.org/en/permalink/ahliterature275595
Source
Sci Rep. 2015;5:14726
Publication Type
Article
Date
2015
Author
Hanna Konttinen
Clare Llewellyn
Jane Wardle
Karri Silventoinen
Anni Joensuu
Satu Männistö
Veikko Salomaa
Pekka Jousilahti
Jaakko Kaprio
Markus Perola
Ari Haukkala
Source
Sci Rep. 2015;5:14726
Date
2015
Language
English
Publication Type
Article
Keywords
Adult
Aged
Anthropometry
Appetite
Body mass index
Cross-Sectional Studies
Feeding Behavior
Female
Finland - epidemiology
Genetic Predisposition to Disease
Humans
Male
Middle Aged
Models, Statistical
Multifactorial Inheritance
Obesity - epidemiology - genetics
Population Surveillance
Quantitative Trait, Heritable
Sex Factors
Young Adult
Abstract
The mechanisms through which genes influence body weight are not well understood, but appetite has been implicated as one mediating pathway. Here we use data from two independent population-based Finnish cohorts (4632 adults aged 25-74 years from the DILGOM study and 1231 twin individuals aged 21-26 years from the FinnTwin12 study) to investigate whether two appetitive traits mediate the associations between known obesity-related genetic variants and adiposity. The results from structural equation modelling indicate that the effects of a polygenic risk score (90 obesity-related loci) on measured body mass index and waist circumference are partly mediated through higher levels of uncontrolled eating (ßindirect = 0.030-0.032, P
Notes
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PubMed ID
26423639 View in PubMed
Less detail

The arrestin domain-containing 3 protein regulates body mass and energy expenditure.

https://arctichealth.org/en/permalink/ahliterature130643
Source
Cell Metab. 2011 Nov 2;14(5):671-83
Publication Type
Article
Date
Nov-2-2011
Author
Parth Patwari
Valur Emilsson
Eric E Schadt
William A Chutkow
Samuel Lee
Alessandro Marsili
Yongzhao Zhang
Radu Dobrin
David E Cohen
P Reed Larsen
Ann Marie Zavacki
Loren G Fong
Stephen G Young
Richard T Lee
Author Affiliation
Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. parth@alum.mit.edu
Source
Cell Metab. 2011 Nov 2;14(5):671-83
Date
Nov-2-2011
Language
English
Publication Type
Article
Keywords
Adipose Tissue, Brown - metabolism
Adipose Tissue, White - metabolism
Adrenergic beta-Agonists - pharmacology
Animals
Arrestins - genetics - metabolism
Body mass index
Chromosomes, Human, Pair 5
Cohort Studies
Energy Metabolism - genetics
Female
Genetic Loci
Humans
Iceland - epidemiology
Linkage Disequilibrium
Male
Mice
Mice, Knockout
Obesity - epidemiology - genetics - metabolism
Receptors, Adrenergic, beta - metabolism
Sequence Homology, Amino Acid
Sex Factors
Signal Transduction
Thermogenesis - genetics
Abstract
A human genome-wide linkage scan for obesity identified a linkage peak on chromosome 5q13-15. Positional cloning revealed an association of a rare haplotype to high body-mass index (BMI) in males but not females. The risk locus contains a single gene, "arrestin domain-containing 3" (ARRDC3), an uncharacterized a-arrestin. Inactivating Arrdc3 in mice led to a striking resistance to obesity, with greater impact on male mice. Mice with decreased ARRDC3 levels were protected from obesity due to increased energy expenditure through increased activity levels and increased thermogenesis of both brown and white adipose tissues. ARRDC3 interacted directly with ß-adrenergic receptors, and loss of ARRDC3 increased the response to ß-adrenergic stimulation in isolated adipose tissue. These results demonstrate that ARRDC3 is a gender-sensitive regulator of obesity and energy expenditure and reveal a surprising diversity for arrestin family protein functions.
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PubMed ID
21982743 View in PubMed
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Association between obesity and asthma in a twin cohort.

https://arctichealth.org/en/permalink/ahliterature87548
Source
Allergy. 2007 Oct;62(10):1199-204
Publication Type
Article
Date
Oct-2007
Author
Thomsen S F
Ulrik C S
Kyvik K O
Sørensen T I A
Posthuma D.
Skadhauge L R
Steffensen I.
Backer V.
Author Affiliation
Department of Respiratory Medicine, Bispebjerg Hospital, Copenhagen, Denmark.
Source
Allergy. 2007 Oct;62(10):1199-204
Date
Oct-2007
Language
English
Publication Type
Article
Keywords
Adult
Age Distribution
Asthma - epidemiology - genetics
Body mass index
Cohort Studies
Comorbidity
Denmark - epidemiology
Diseases in Twins - epidemiology - genetics
Female
Genetic Predisposition to Disease - genetics
Humans
Male
Obesity - epidemiology - genetics
Population Surveillance - methods
Prevalence
Questionnaires
Risk factors
Sex Factors
Twins, Dizygotic
Twins, Monozygotic
Abstract
BACKGROUND: Obesity is linked to asthma in a yet poorly understood manner. We examined the relationship between obesity and asthma in a population-based sample of twins. METHODS: From the cohorts born between 1953 and 1982, who were enrolled in The Danish Twin Registry, a total of 29 183 twin individuals participated in a nationwide questionnaire study, where data on height, weight and asthma were collected. Latent factor models of genetic and environmental effects were fitted using maximum likelihood methods. RESULTS: The age-adjusted risk of asthma was increased both in obese females, OR = 1.96 (1.45-2.64), P
PubMed ID
17845591 View in PubMed
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Association of 18 confirmed susceptibility loci for type 2 diabetes with indices of insulin release, proinsulin conversion, and insulin sensitivity in 5,327 nondiabetic Finnish men.

https://arctichealth.org/en/permalink/ahliterature150518
Source
Diabetes. 2009 Sep;58(9):2129-36
Publication Type
Article
Date
Sep-2009
Author
Alena Stancáková
Teemu Kuulasmaa
Jussi Paananen
Anne U Jackson
Lori L Bonnycastle
Francis S Collins
Michael Boehnke
Johanna Kuusisto
Markku Laakso
Author Affiliation
Department of Medicine, University of Kuopio and Kuopio University Hospital, Kuopio, Finland.
Source
Diabetes. 2009 Sep;58(9):2129-36
Date
Sep-2009
Language
English
Publication Type
Article
Keywords
Aged
Diabetes Mellitus, Type 2 - epidemiology - genetics - metabolism
Finland - epidemiology
Gene Expression Profiling
Genetic Predisposition to Disease - epidemiology
Genotype
Glucose Tolerance Test
Humans
Insulin - metabolism
Insulin Resistance - genetics
Male
Middle Aged
Obesity - epidemiology - genetics - metabolism
Polymorphism, Single Nucleotide
Proinsulin - metabolism
Risk factors
Abstract
We investigated the effects of 18 confirmed type 2 diabetes risk single nucleotide polymorphisms (SNPs) on insulin sensitivity, insulin secretion, and conversion of proinsulin to insulin.
A total of 5,327 nondiabetic men (age 58 +/- 7 years, BMI 27.0 +/- 3.8 kg/m(2)) from a large population-based cohort were included. Oral glucose tolerance tests and genotyping of SNPs in or near PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, LOC387761, CDKN2B, IGF2BP2, CDKAL1, HNF1B, WFS1, JAZF1, CDC123, TSPAN8, THADA, ADAMTS9, NOTCH2, KCNQ1, and MTNR1B were performed. HNF1B rs757210 was excluded because of failure to achieve Hardy-Weinberg equilibrium.
Six SNPs (TCF7L2, SLC30A8, HHEX, CDKN2B, CDKAL1, and MTNR1B) were significantly (P or=11 vs.
Notes
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PubMed ID
19502414 View in PubMed
Less detail

Association of RBP4 gene variants and serum HDL cholesterol levels in the Newfoundland population.

https://arctichealth.org/en/permalink/ahliterature147534
Source
Obesity (Silver Spring). 2010 Jul;18(7):1393-7
Publication Type
Article
Date
Jul-2010
Author
Jennifer L Shea
J Concepción Loredo-Osti
Guang Sun
Author Affiliation
Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St John's, Newfoundland and Labrador, Canada.
Source
Obesity (Silver Spring). 2010 Jul;18(7):1393-7
Date
Jul-2010
Language
English
Publication Type
Article
Keywords
Adult
Cholesterol, HDL - blood
Female
Gene Frequency
Genetic Predisposition to Disease - epidemiology
Genetic Variation
Genotype
Glucose Intolerance - epidemiology - genetics
Homeostasis - genetics
Humans
Hyperlipidemias - epidemiology - genetics
Insulin Resistance - genetics
Lipid Metabolism - genetics
Male
Middle Aged
Newfoundland and Labrador - epidemiology
Obesity - epidemiology - genetics
Polymorphism, Single Nucleotide
Retinol-Binding Proteins, Plasma - genetics
Risk factors
Abstract
Retinol-binding protein 4 (RBP4) is a novel adipokine that likely contributes to systemic insulin resistance and dyslipidemia. The role of genetic variations in RBP4 on phenotypes of glucose and lipid metabolism is not clear in humans. The purpose of this study was to examine five single-nucleotide polymorphisms (SNPs) in the RBP4 gene to determine their relationship with markers of insulin resistance and serum lipids in the CODING Study. The CODING Study consists of 1,836 subjects recruited from the genetically homogeneous population of Newfoundland and Labrador (NL), Canada. Serum glucose, insulin, homeostasis model assessment of insulin resistance (HOMA(IR)), HOMA for beta cell function (HOMA(beta)), total cholesterol (Chol), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides were determined after a 12-h fast. Five SNPs within RBP4 (rs3758539, G/A 5' flanking region; rs61461737, A/G intron; rs10882280, C/A intron; rs11187545, A/G intron; and rs12265684, C/G intron) were genotyped using TaqMan validated or functionally tested SNP genotyping assays. After correcting for multiple testing, we observed a significant association between the minor allele of two noncoding SNPs (rs10882280 and rs11187545) and higher serum HDL-C (P = 0.043 and 0.042, respectively). No significant associations were observed with any other parameter related to lipid metabolism. We also found no significant association between any variant sites and markers of insulin resistance. Our results suggest that genetic variations in RBP4 may play a role in the differences in serum HDL-C levels in the NL population.
PubMed ID
19893506 View in PubMed
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Association of variants in the fat mass and obesity associated (FTO) gene with polycystic ovary syndrome.

https://arctichealth.org/en/permalink/ahliterature157193
Source
Diabetologia. 2008 Jul;51(7):1153-8
Publication Type
Article
Date
Jul-2008
Author
T M Barber
A J Bennett
C J Groves
U. Sovio
A. Ruokonen
H. Martikainen
A. Pouta
A-L Hartikainen
P. Elliott
C M Lindgren
R M Freathy
K. Koch
W H Ouwehand
F. Karpe
G S Conway
J A H Wass
M-R Järvelin
S. Franks
M I McCarthy
Author Affiliation
Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford, OX3 7LJ, UK. tom.barber@drl.ox.ac.uk
Source
Diabetologia. 2008 Jul;51(7):1153-8
Date
Jul-2008
Language
English
Publication Type
Article
Keywords
Adipose Tissue - pathology
Adult
Case-Control Studies
Diabetes Mellitus, Type 2 - epidemiology - genetics - pathology
Female
Finland - epidemiology
Gene Frequency
Genetic Predisposition to Disease - epidemiology
Genetic Variation
Genotype
Great Britain - epidemiology
Humans
Middle Aged
Obesity - epidemiology - genetics - pathology
Polycystic Ovary Syndrome - epidemiology - genetics - pathology
Proteins - genetics
Risk factors
Abstract
Variants in the fat-mass and obesity-associated gene (FTO) influence susceptibility to type 2 diabetes via an effect on adiposity/obesity. Given the important role of obesity in the aetiology of both polycystic ovary syndrome (PCOS) and type 2 diabetes mellitus, our aim was to establish whether FTO variants are also implicated in PCOS susceptibility.
We performed a genetic association study of FTO variant rs9939609 using case-control analyses, conducted in 463 PCOS patients (geometric mean BMI 27.5 kg/m(2)) and 1,336 female controls (geometric mean BMI 25.3 kg/m(2)) of UK British/Irish origin. We also sought evidence for associations between FTO variation and circulating testosterone levels in 324 UK PCOS patients and 1,000 women from the Northern Finland Birth Cohort of 1966. Outcome measures included FTO rs9939609 genotype frequencies by participant group and androgen measures (testosterone, free androgen index) by genotype.
There was a significant association between FTO genotype and PCOS status in the UK case-control analysis, which was attenuated by adjustment for BMI (Cochran-Armitage test, odds ratio [per minor allele copy] 1.30 [95% CI 1.12, 1.51], p = 7.2 x 10(-4) [unadjusted], p = 2.9 x 10(-3) [adjusted]). This association was most evident in obese PCOS patients (PCOS patients below median BMI vs UK controls, p = 0.11; above median BMI vs controls, p = 2.9 x 10(-4)). No relationship between FTO genotype and androgen levels was seen.
We provide the first evidence that variants that predispose to common obesity also result in altered susceptibility to PCOS, confirming the mechanistic link between these conditions. The predominant effect of FTO variants on PCOS susceptibility is probably mediated through adiposity.
PubMed ID
18478198 View in PubMed
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Associations between dietary patterns and obesity phenotypes.

https://arctichealth.org/en/permalink/ahliterature148666
Source
Int J Obes (Lond). 2009 Dec;33(12):1419-26
Publication Type
Article
Date
Dec-2009
Author
A-M Paradis
G. Godin
L. Pérusse
M-C Vohl
Author Affiliation
Department of Food Science and Nutrition, Laval University, Québec, Canada. marie-claude.vohl@crchul.ulaval.ca
Source
Int J Obes (Lond). 2009 Dec;33(12):1419-26
Date
Dec-2009
Language
English
Publication Type
Article
Keywords
Adolescent
Adult
Analysis of Variance
Body mass index
Cross-Sectional Studies
Diet
Diet Records
Dietary Fats - adverse effects
Female
Food Habits - psychology
Humans
Male
Middle Aged
Obesity - epidemiology - genetics
Phenotype
Quebec - epidemiology
Questionnaires
Risk factors
Waist Circumference
Young Adult
Abstract
To examine whether dietary patterns are associated with obesity phenotypes.
Cross-sectional study.
We recruited 664 participants aged between 18 and 55 years. Dietary data were collected from a food frequency questionnaire. A factor analysis was performed to derive dietary patterns. Body mass index (BMI), weight and waist girth were recorded using standard procedures. Fat mass and fat-free mass were assessed by electrical bioimpedance. Obesity was defined as having a BMI> or =30 kg m(-2) and a positive FHO (FHO+) as having at least one obese first-degree relative.
Two dietary patterns were identified; Western and Prudent. The Western pattern was mainly characterized by a higher consumption of refined grains, French fries, red meats, condiments, processed meats and regular soft drinks whereas the Prudent pattern was mainly characterized by a higher consumption of non-hydrogenated fat, vegetables, eggs and fish and seafood. Subjects in the top tertile of the Western pattern had higher BMI, weight, waist girth, waist-to-hip ratio and fat mass than those in the lower tertile. In contrast, subjects in the top tertile of the Prudent pattern had lower BMI, weight, waist girth, fat mass, HDL-cholesterol levels, and lower triglyceride levels than those in the lowest tertile. Individuals in the upper tertile of the Western pattern were more likely to be obese (obesity was defined as having a BMI> or =30 kg m(-2)) (OR=1.82, 95% CI 1.16-2.87) whereas those in the upper tertile of the Prudent pattern were less likely to be obese (OR=0.62, 95% CI 0.40-0.96). These latter significant associations were only observed among those with FHO+. No such association was observed among FHO- individuals.
Individuals having a high score of Western pattern were more likely to be obese and those having a high score of the Prudent pattern were less likely to be obese, and this is particularly among individuals with an FHO+.
PubMed ID
19736556 View in PubMed
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Association testing of novel type 2 diabetes risk alleles in the JAZF1, CDC123/CAMK1D, TSPAN8, THADA, ADAMTS9, and NOTCH2 loci with insulin release, insulin sensitivity, and obesity in a population-based sample of 4,516 glucose-tolerant middle-aged Danes.

https://arctichealth.org/en/permalink/ahliterature92941
Source
Diabetes. 2008 Sep;57(9):2534-40
Publication Type
Article
Date
Sep-2008
Author
Grarup Niels
Andersen Gitte
Krarup Nikolaj T
Albrechtsen Anders
Schmitz Ole
Jørgensen Torben
Borch-Johnsen Knut
Hansen Torben
Pedersen Oluf
Author Affiliation
Steno Diabetes Center, Copenhagen, Denmark. ngrp@steno.dk
Source
Diabetes. 2008 Sep;57(9):2534-40
Date
Sep-2008
Language
English
Publication Type
Article
Keywords
ADAM Proteins - genetics
Adult
Antigens, Neoplasm - genetics
Calcium-Calmodulin-Dependent Protein Kinase Type 1 - genetics
Cell Cycle Proteins - genetics
Cohort Studies
Denmark - epidemiology
Diabetes Mellitus, Type 2 - diagnosis - epidemiology - genetics
Female
Genomics
Glucose Tolerance Test
Humans
Insulin Resistance - genetics
Male
Membrane Glycoproteins - genetics
Middle Aged
Neoplasm Proteins - genetics
Obesity - epidemiology - genetics
Risk factors
Abstract
OBJECTIVE: We evaluated the impact on diabetes-related intermediary traits of common novel type 2 diabetes-associated variants in the JAZF1 (rs864745), CDC123/CAMK1D (rs12779790), TSPAN8 (rs7961581), THADA (rs7578597), ADAMTS9 (rs4607103), and NOTCH2 (rs10923931) loci, which were recently identified by meta-analysis of genome-wide association data. RESEARCH DESIGN AND METHODS: We genotyped the six variants in 4,516 middle-aged glucose-tolerant individuals of the population-based Inter99 cohort who were all characterized by an oral glucose tolerance test (OGTT). RESULTS: Homozygous carriers of the minor diabetes risk G-allele of the CDC123/CAMK1D rs12779790 showed an 18% decrease in insulinogenic index (95% CI 10-27%; P = 4 x 10(-5)), an 18% decrease in corrected insulin response (CIR) (8.1-29%; P = 4 x 10(-4)), and a 13% decrease in the ratio of area under the serum-insulin and plasma-glucose curves during an OGTT (AUC-insulin/AUC-glucose) (5.8-20%; P = 4 x 10(-4)). Carriers of the diabetes-associated T-allele of JAZF1 rs864745 had an allele-dependent 3% decrease in BIGTT-AIR (0.9-4.3%; P = 0.003). Furthermore, the diabetes-associated C-allele of TSPAN8 rs7961581 associated with decreased levels of CIR (4.5% [0.5-8.4]; P = 0.03), of AUC-insulin/AUC-glucose ratio (3.9% [1.2-6.7]; P = 0.005), and of the insulinogenic index (5.2% [1.9-8.6]; P = 0.002). No association with traits of insulin release or insulin action was observed for the THADA, ADAMTS9, or NOTCH2 variants. CONCLUSIONS: If replicated, our data suggest that type 2 diabetes at-risk alleles in the JAZF1, CDC123/CAMK1D, and TSPAN8 loci associate with various OGTT-based surrogate measures of insulin release, emphasizing the contribution of abnormal pancreatic beta-cell function in the pathogenesis of type 2 diabetes.
PubMed ID
18567820 View in PubMed
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