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Roumi Z, Salimi Z, Mahmoudi Z, Mobarakeh KA, Ladaninezhad M, Zeinalabedini M, Keshavarz Mohammadian M, Shamsi‐Goushki A, Saeedirad Z, Bahar B, Khoshdooz S, Kalantari N, Azizi Tabesh G, Doaei S, Gholamalizadeh M. Efficacy of a Comprehensive Weight Reduction Intervention in Male Adolescents With Different FTO Genotypes. Endocrinol Diabetes Metab 2024; 7:e00483. [PMID: 38556726 PMCID: PMC10982462 DOI: 10.1002/edm2.483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 02/29/2024] [Accepted: 03/07/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND The FTO gene polymorphisms may influence the effects of lifestyle interventions on obesity. The present study aimed to assess the influence of the rs9930506 FTO gene polymorphism on the success of a comprehensive weight loss intervention in male adolescents with overweight and obesity. METHODS This study was carried out on 96 adolescent boys with overweight and obesity who were randomly assigned to the intervention (n = 53) and control (n = 43) groups. The blood samples of the participants were collected, and the FTO gene was genotyped for the rs9930506 polymorphism. A comprehensive lifestyle intervention including changes in diet and physical activity was performed for 8 weeks in the intervention group. RESULTS Following the lifestyle intervention, BMI and fat mass decreased significantly in the intervention group compared with the control group (both p < 0.05), while no change was found in weight, height or body muscle percentage between the groups. The participants in the intervention group with the AA/AG genotype and not in carriers of the GG genotype had a significantly higher reduction in BMI (-1.21 vs. 1.87 kg/m2, F = 4.07, p < 0.05) compared with the control group. CONCLUSION The intervention in individuals with the AA/AG genotype has been significantly effective in weight loss compared with the control group. The intervention had no association effect on anthropometric indices in adolescents with the GG genotype of the FTO rs9930506 polymorphism. TRIAL REGISTRATION Name of the registry: National Nutrition and Food Technology Research Institute; Trial registration number: IRCT2016020925699N2; Date of registration: 24/04/2016; URL of trial registry record: https://www.irct.ir/trial/21447.
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Affiliation(s)
- Zahra Roumi
- Department of Nutrition, Science and Research BranchIslamic Azad UniversityTehranIran
| | - Zahra Salimi
- Nutrition and Metabolic Diseases Research CenterAhvaz Jundishapur University of Medical SciencesAhvazIran
| | - Zahra Mahmoudi
- Department of Nutrition, Science and Research BranchIslamic Azad UniversityTehranIran
| | - Khadijeh Abbasi Mobarakeh
- Food Security Research Center and Department of Community Nutrition, School of Nutrition and Food ScienceIsfahan University of Medical SciencesIsfahanIran
| | - Maryam Ladaninezhad
- School of Nutritional Sciences and DieteticsTehran University of Medical SciencesTehranIran
| | - Mobina Zeinalabedini
- Department of Cellular and Molecular Nutrition, School of Nutritional Sciences and DieteticsTehran University of Medical SciencesTehranIran
| | | | - Ali Shamsi‐Goushki
- Department of Nutrition, School of MedicineMashhad University of Medical SciencesMashhadIran
| | - Zahra Saeedirad
- Department of Clinical Nutrition and DieteticsTehran University of Medical SciencesTehranIran
| | - Bojlul Bahar
- Nutrition Sciences and Applied Food Safety Studies, Research Centre for Global Development, School of Sport & Health SciencesUniversity of Central LancashirePrestonUK
| | - Sara Khoshdooz
- Faculty of MedicineGuilan University of Medical ScienceRashtIran
| | - Naser Kalantari
- Department of Community Nutrition, Faculty of Nutrition and Food TechnologyNational Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical SciencesTehranIran
| | - Ghasem Azizi Tabesh
- Genomic Research CenterShahid Beheshti University of Medical SciencesTehranIran
| | - Saeid Doaei
- Department of Community Nutrition, Faculty of Nutrition and Food TechnologyNational Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical SciencesTehranIran
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Rasaei N, Daneshzad E, Khadem A, Gholami F, Samadi M, Mirzaei K. Investigation of the interaction between genetic risk score (GRS) and fatty acid quality indices on metabolic syndrome among overweight and obese women. BMC Med Genomics 2024; 17:113. [PMID: 38685080 PMCID: PMC11057091 DOI: 10.1186/s12920-024-01838-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 02/27/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND AND AIM Metabolic syndrome is one of the major public-health challenges, affecting one-quarter of the world population. Fatty acid quality indices are novel determinants of this disease and their interactions with genetic factors may have an impact on metabolic syndrome risk. Therefore, we aimed to investigate the interaction between genetic risk score (GRS) and fatty acid quality indices with metabolic syndrome (MetS) among overweight and obese women. METHODS In the present cross-sectional study, 279 overweight and obese women (18-48 years old) were included. Several anthropometric measurements such as weight, height, body mass index (BMI), waist circumference (WC), and body fat percent (BF%) were measured. Also, systolic and diastolic blood pressure (SBP and DBP) were measured. Biochemical determination was performed for fasting blood glucose (FBS), triglyceride (TG), and high-density lipoprotein (HDL). MetS was determined according to National Cholesterol Education Program (NCEP ATP III) criteria. Dietary intake was evaluated by a validated and reliable 147-item semi-quantitative food frequency questionnaire. Cholesterol-saturated fat index (CSI) and the ratio of omega-6/omega-3 (ω-6/ω-3) essential fatty acids were considered as fat quality indices. The salting-out method was used to extract the total DNA. The unweighted GRS was calculated using the risk alleles of the three single nucleotide polymorphisms. The total average GRS value was 2 and the sum of the risk alleles of the 3 polymorphisms was 6. RESULT The results of our analysis showed that after controlling for age, energy intake, BMI, and physical activity, there was a positive interaction between T2 of GRS and T2 of N6/N3 ratio on WC (β = 7.95, 95%CI = 0.83,15.08, P = 0.029), T3 of GRS and T2 of N6/N3 ratio on DBP (β = 5.93, 95%CI= -0.76,12.63, P = 0.083), and FBS (β = 6.47, 95%CI = 0.59,13.53, P = 0.073), T3 of GRS and T3 of N6/N3 ratio on TG (β = 54.42, 95%CI = 1.76,107.08, P = 0.043), and T3 of GRS and T3 of CSI on BF% (β = 3.55, 95%CI= -0.35,7.45, P = 0.075). Also T2 of GRS in the interaction with T3 of CSI leads to an decrease - 8.35 mg/dl in HDL level after adjustment in (β= -8.35, 95%CI= -17.34,0.62, P = 0.068). CONCLUSION It seems the interaction of GRS and fatty acid quality indices is positively associated with several components of metabolic syndrome such as WC, TG and BF%. Our findings are of importance to public health, considering the high consumption of foods that are high on fatty acids. Conflicting evidence of many previous studies regarding the effect of fat intake and obesity and cardiovascular diseases could be because of the gene-diet interactions and genetic heterogeneity across various ethnic groups. Hence, the synergism effect of genetic and dietay intakes should be considered in future studies.
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Affiliation(s)
- Niloufar Rasaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, P. O. Box: 14155-6117, Iran
| | - Elnaz Daneshzad
- Non-Communicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran
| | - Alireza Khadem
- Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Fatemeh Gholami
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, P. O. Box: 14155-6117, Iran
| | - Mahsa Samadi
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, P. O. Box: 14155-6117, Iran
| | - Khadijeh Mirzaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, P. O. Box: 14155-6117, Iran.
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Wan X, Ao Y, Liu X, Zhuang P, Huang Y, Shi H, Jiao J, Zhang Y. Fried food consumption, genetic risk, and incident obesity: a prospective study. Food Funct 2024; 15:2760-2771. [PMID: 38385219 DOI: 10.1039/d3fo02803h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Background and aims: Genetic and dietary factors contribute to adiposity risk, but little evidence supports genetic personalization of fried food intake recommendations for the management of obesity. This study aimed to assess the associations between fried food consumption and adiposity incidence and whether the associations were modified by an individual's genotype. Methods: We included 27 427 participants who had dietary data assessed by a validated 24 h dietary recall and available anthropometric information from the UK Biobank study. The genetic risk score (GRS) was calculated using 940 BMI associated variants. Results: With an average of 8.1 years of follow-up, 1472 and 2893 participants were defined as having overall obesity and abdominal obesity, respectively. Individuals in the highest categories of fried food consumption were positively associated with the risk of obesity (HR = 1.31; 95% CI 1.10-1.56) and abdominal obesity (HR = 1.27; 95% CI 1.12-1.45) compared with the lowest categories. Moreover, fried food consumption had a significant interatction with obesity GRS for abdominal obesity risk (P interaction = 0.016). Fried food intake was associated with a higher abdominal obesity risk (HR = 1.59, 95% CI: 1.25-2.00) among participants with a lower genetic risk. Conclusions: Our findings indicated that fried food consumption had a higher abdominal obesity risk among individuals with a lower genetic risk, suggesting the restriction of fried food intake for this group of people.
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Affiliation(s)
- Xuzhi Wan
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Department of Food Science and Nutrition, Zhejiang Key Laboratory for Agro-Food Processing, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Yang Ao
- Department of Endocrinology, The Second Affiliated Hospital, Department of Nutrition, School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiaohui Liu
- Department of Endocrinology, The Second Affiliated Hospital, Department of Nutrition, School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Pan Zhuang
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Department of Food Science and Nutrition, Zhejiang Key Laboratory for Agro-Food Processing, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Yingyu Huang
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Department of Food Science and Nutrition, Zhejiang Key Laboratory for Agro-Food Processing, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Hongbo Shi
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Department of Food Science and Nutrition, Zhejiang Key Laboratory for Agro-Food Processing, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Jingjing Jiao
- Department of Endocrinology, The Second Affiliated Hospital, Department of Nutrition, School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yu Zhang
- Department of Gastroenterology, The First Affiliated Hospital, Zhejiang University School of Medicine, Department of Food Science and Nutrition, Zhejiang Key Laboratory for Agro-Food Processing, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.
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Dowaidar M. Gene-environment interactions that influence CVD, lipid traits, obesity, diabetes, and hypertension appear to be able to influence gene therapy. Mol Aspects Med 2023; 94:101213. [PMID: 37703607 DOI: 10.1016/j.mam.2023.101213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 09/06/2023] [Indexed: 09/15/2023]
Abstract
Most mind boggling diseases are accepted to be impacted by both genetic and environmental elements. As of late, there has been a flood in the improvement of different methodologies, concentrate on plans, and measurable and logical techniques to examine gene-environment cooperations (G × Es) in enormous scope studies including human populaces. The many-sided exchange between genetic elements and environmental openings has long charmed the consideration of clinicians and researchers looking to grasp the complicated starting points of diseases. While single variables can add to disease, the blend of genetic variations and environmental openings frequently decides disease risk. The fundamental point of this paper is to talk about the Gene-Environment Associations That Impact CVD, Lipid Characteristics, Obesity, Diabetes, and Hypertension Have all the earmarks of being Ready to Impact Gene Therapy. This survey paper investigates the meaning of gene-environment collaborations (G × E) in disease advancement. The intricacy of genetic and environmental communications in disease causation is explained, underlining the multifactorial idea of many circumstances. The job of gene-environment cooperations in cardiovascular disease, lipid digestion, diabetes, obesity, and hypertension is investigated. This audit fixates on Gene by Environment (G × E) collaborations, investigating their importance in disease etiology.
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Affiliation(s)
- Moataz Dowaidar
- Department of Bioengineering, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, 31261, Saudi Arabia; Interdisciplinary Research Center for Hydrogen and Energy Storage (IRC-HES), King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, 31261, Saudi Arabia; Interdisciplinary Research Center for Health & Biosciences, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, 31261, Saudi Arabia.
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Viljakainen H, Sorlí JV, Dahlström E, Agrawal N, Portolés O, Corella D. Interaction between genetic susceptibility to obesity and food intake on BMI in Finnish school-aged children. Sci Rep 2023; 13:15265. [PMID: 37709841 PMCID: PMC10502078 DOI: 10.1038/s41598-023-42430-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 09/10/2023] [Indexed: 09/16/2023] Open
Abstract
Diet modulates the genetic risk of obesity, but the modulation has been rarely studied using genetic risk scores (GRSs) in children. Our objectives were to identify single nucleotide polymorphisms (SNPs) that drive the interaction of specific foods with obesity and combine these into GRSs. Genetic and food frequency data from Finnish Health in Teens study was utilized. In total, 1142 11-year-old subjects were genotyped on the Metabochip array. BMI-GRS with 30 well-known SNPs was computed and the interaction of individual SNPs with food items and their summary dietary scores were examined in relation to age- and sex-specific BMI z-score (BMIz). The whole BMI-GRS interacted with several foods on BMIz. We identified 7-11 SNPs responsible for each interaction and these were combined into food-specific GRS. The most predominant interaction was witnessed for pizza (p < 0.001): the effect on BMIz was b - 0.130 (95% CI - 0.23; - 0.031) in those with low-risk, and 0.153 (95% CI 0.072; 0.234) in high-risk. Corresponding, but weaker interactions were verified for sweets and chocolate, sugary juice drink, and hamburger and hotdog. In total 5 SNPs close to genes NEGR1, SEC16B, TMEM18, GNPDA2, and FTO were shared between these interactions. Our results suggested that children genetically prone to obesity showed a stronger association of unhealthy foods with BMIz than those with lower genetic susceptibility. Shared SNPs of the interactions suggest common differences in metabolic gene-diet interactions, which warrants further investigation.
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Affiliation(s)
- Heli Viljakainen
- Folkhälsan Research Center, Topeliuksenkatu 20, 00250, Helsinki, Finland.
- Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| | - Jose V Sorlí
- Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición, Madrid, Spain
| | - Emma Dahlström
- Folkhälsan Research Center, Topeliuksenkatu 20, 00250, Helsinki, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290, Helsinki, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, 00290, Helsinki, Finland
| | - Nitin Agrawal
- Folkhälsan Research Center, Topeliuksenkatu 20, 00250, Helsinki, Finland
- Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Olga Portolés
- Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición, Madrid, Spain
| | - Dolores Corella
- Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición, Madrid, Spain
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Rasaei N, Samadi M, Khadem A, Fatemi SF, Gholami F, Mirzaei K. Investigation of the interaction between Genetic Risk Score (GRS) and fatty acid quality indices on mental health among overweight and obese women. BMC Womens Health 2023; 23:413. [PMID: 37542261 PMCID: PMC10403951 DOI: 10.1186/s12905-023-02491-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 06/19/2023] [Indexed: 08/06/2023] Open
Abstract
BACKGROUND & AIMS Mental disorders are associated with dietary fatty acids and genome-wide association studies have found multiple risk loci robustly related to depression, anxiety, and stress. The aim of this study is to investigate the interaction of genetic risk score (GRS) and dietary fat quality indices on mental health. METHODS This cross-sectional study included 279 overweight and obese women for N6/N3 ratio and 378 overweight and obese women for CSI aged 18-68 years. Using reliable and verified standard protocols, body composition, anthropometric indices, blood pressure, physical activity, and dietary fat quality were measured. Serum samples were used to determine biochemical tests. A genetic risk score (GRS) was calculated using the risk alleles of the three SNPs. A generalized linear model (GLM) was applied to assess the interactions between GRS and fat quality indices. Mental health was evaluated using Depression Anxiety Stress Scales (DASS-21). RESULTS The mean (± SD) age and BMI of our participants were 36.48 (8.45) and 30.73 (3.72) kg/m2 respectively. There was a marginally significant mean difference among tertiles of the CSI in terms of stress (P = 0.051), DASS-21 (P = 0.078) in the crude model. After adjusting for age, energy intake, physical activity and BMI in model 1, there was a positive interaction between GRS and T3 of N6/N3 ratio on anxiety (β = 0.91, CI = 0.08,1.75, P = 0.031), depression (β = 1.05, CI = 0.06,2.04, P = 0.037), DASS-21 (β = 2.22, CI= -0.31,4.75, P = 0.086). CONCLUSION Our findings indicate that higher ratio of N-6 to N-3 considering genetics were predictive of mental disorder in our population.
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Affiliation(s)
- Niloufar Rasaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
- Network of Interdisciplinarity in Neonates and Infants (NINI), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Mahsa Samadi
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Alireza Khadem
- Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Seyedeh Fatemeh Fatemi
- Department of Nutrition, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Fatemeh Gholami
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Khadijeh Mirzaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
- Food Microbiology Research Center, Tehran University of Medical Sciences, Tehran, Iran
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Nikrad N, Shakarami A, Rahimi Z, Janghorbanian-Poodeh R, Farhangi MA, Hosseini B, Jafarzadeh F. Dietary pro-oxidant score (POS) and cardio-metabolic panel among obese individuals: a cross-sectional study. BMC Endocr Disord 2023; 23:144. [PMID: 37430312 PMCID: PMC10332071 DOI: 10.1186/s12902-023-01395-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 06/29/2023] [Indexed: 07/12/2023] Open
Abstract
BACKGROUND Oxidative stress is a disturbance in the natural balance between oxidative and anti-oxidative processes, which is the major effective factor in cardiovascular disorders and metabolic syndrome (MetS), due to the role of pro-oxidants in inducing oxidative stress, and as a result, the occurrence and exacerbation of components of metabolic syndrome and cardiovascular risk factors, this cross-sectional study was conducted with the aim of investigating the relationship between the status of dietary pro-oxidants score (POS) and metabolic parameters including serum lipids, glycemic markers and blood pressure among obese adults. METHODS 338 individuals with obesity (BMI ≥ 30 kg/m 2), aged between 20 and 50 years were recruited in the present cross-sectional study. A validated food frequency questionnaire (FFQ) was used to determine the dietary pro-oxidant score (POS). Analysis of variance (ANOVA) with Tukey's post-hoc comparisons after adjustment for confounders and multivariable logistic regression analysis were performed to determine the association of cardiometabolic risk factors among the tertiles of POS. RESULTS Participants with higher POS had lower levels of body mass index (BMI), weight and waist circumference (WC). There were no significant associations between metabolic parameters including glycemic markers and lipid profile in one-way ANOVA and multivariate multinomial logistic regression models. CONCLUSIONS The findings of this study revealed that greater dietary pro-oxidant intake might be associated with lower BMI, body weight, and WC in Iranian obese individuals. Further studies with interventional or longitudinal approaches will help to better elucidate the causality of the observed associations.
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Affiliation(s)
- Negin Nikrad
- Tabriz Health Services Management Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Amir Shakarami
- Department of Cardiovascular Medicine, Assistant Professor of Cardiology, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Zahra Rahimi
- Teaching Experimental Sciences Group, Teachers Training Center, Pardis Bahonar Faculty of Farhangian University, Isfahan, Iran
| | - Raheleh Janghorbanian-Poodeh
- Coronary Angiography Group, Heart Department of Chamran Sub-Speciality Heart Hospital, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mahdieh Abbasalizad Farhangi
- Tabriz Health Services Management Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Community Nutrition, Faculty of Nutrition, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Babak Hosseini
- Department of Surgery, School of Medicine, Laparoscopy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
| | - Faria Jafarzadeh
- Department of Internal Medicine, School of Medicine, North Khorasan University of Medical Sciences, Bojnourd, Iran.
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Fernández-Rhodes L, McArdle CE, Rao H, Wang Y, Martinez-Miller EE, Ward JB, Cai J, Sofer T, Isasi CR, North KE. A Gene-Acculturation Study of Obesity Among US Hispanic/Latinos: The Hispanic Community Health Study/Study of Latinos. Psychosom Med 2023; 85:358-365. [PMID: 36917487 PMCID: PMC10159946 DOI: 10.1097/psy.0000000000001193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
OBJECTIVE In the United States, Hispanic/Latino adults face a high burden of obesity; yet, not all individuals are equally affected, partly due in part to this ethnic group's marked sociocultural diversity. We sought to analyze the modification of body mass index (BMI) genetic effects in Hispanic/Latino adults by their level of acculturation, a complex biosocial phenomenon that remains understudied. METHODS Among 11,747 Hispanic/Latinos adults in the Hispanic Community Health Study/Study of Latinos aged 18 to 76 years from four urban communities (2008-2011), we a) tested our hypothesis that the effect of a genetic risk score (GRS) for increased BMI may be exacerbated by higher levels of acculturation and b) examined if GRS acculturation interactions varied by gender or Hispanic/Latino background group. All genetic modeling controlled for relatedness, age, gender, principal components of ancestry, center, and complex study design within a generalized estimated equation framework. RESULTS We observed a GRS increase of 0.34 kg/m 2 per risk allele in weighted mean BMI. The estimated main effect of GRS on BMI varied both across acculturation level and across gender. The difference between high and low acculturation ranged from 0.03 to 0.23 kg/m 2 per risk allele, but varied across acculturation measure and gender. CONCLUSIONS These results suggest the presence of effect modification by acculturation, with stronger effects on BMI among highly acculturated individuals and female immigrants. Future studies of obesity in the Hispanic/Latino community should account for sociocultural environments and consider their intersection with gender to better target obesity interventions.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Cristin E. McArdle
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA
| | - Hridya Rao
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA
| | - Yujie Wang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Erline E. Martinez-Miller
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX
| | - Julia B. Ward
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Social & Scientific Systems, a DLH Holdings Company, Durham, NC
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Tamar Sofer
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Carmen R. Isasi
- Departments of Epidemiology & Population Health and Pediatrics, Albert Einstein College of Medicine, Bronx, NY
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC
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Voruganti VS. Precision Nutrition: Recent Advances in Obesity. Physiology (Bethesda) 2023; 38:0. [PMID: 36125787 PMCID: PMC9705019 DOI: 10.1152/physiol.00014.2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/15/2022] [Accepted: 09/19/2022] [Indexed: 11/22/2022] Open
Abstract
"Precision nutrition" is an emerging area of nutrition research that focuses on understanding metabolic variability within and between individuals and helps develop customized dietary plans and interventions to maintain optimal individual health. It encompasses nutritional genomic (gene-nutrient interactions), epigenetic, microbiome, and environmental factors. Obesity is a complex disease that is affected by genetic and environmental factors and thus a relevant target of precision nutrition-based approaches. Recent studies have shown significant associations between obesity phenotypes (body weight, body mass index, waist circumference, and central and regional adiposity) and genetic variants, epigenetic factors (DNA methylation and noncoding RNA), microbial species, and environment (sociodemographics and physical activity). Additionally, studies have also shown that the interactions between genetic variants, microbial metabolites, and epigenetic factors affect energy balance and adiposity. These include variants in FTO, MC4R, PPAR, APOA, and FADS genes, DNA methylation in CpG island regions, and specific miRNAs and microbial species such as Firmicutes, Bacteriodes, Clostridiales, etc. Similarly, studies have shown that microbial metabolites, folate, B-vitamins, and short-chain fatty acids interact with miRNAs to influence obesity phenotypes. With the advent of next-generation sequencing and analytical approaches, the advances in precision nutrition have the potential to lead to new paradigms, which can further lead to interventions or customized treatments specific to individuals or susceptible groups of individuals. This review highlights the recent advances in precision nutrition as applied to obesity and projects the importance of precision nutrition in obesity and weight management.
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Affiliation(s)
- V Saroja Voruganti
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina
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10
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Goh Y, Choi JH. Genetic variation rs1121980 in the fat mass and obesity-associated gene ( FTO) is associated with dietary intake in Koreans. Food Nutr Res 2022; 66:8059. [PMID: 36590860 PMCID: PMC9793768 DOI: 10.29219/fnr.v66.8059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 08/11/2022] [Accepted: 08/16/2022] [Indexed: 11/16/2022] Open
Abstract
Background Fat mass and obesity-associated gene (FTO) is a well-known gene associated with body weight and obesity risk. Recent studies have suggested that genetic variations in FTO may play a role in the regulation of food preference and consumption. However, little is known with respect to Asian populations. Objective This study examined whether rs1121980 C > T in FTO is associated with food intake in Koreans. Design This study was performed using data from the Korean Genome and Epidemiology Study (Ansan/Ansung cohort). Dietary intake was determined using the semi-food frequency questionnaire, and the FTO rs1121980 genotypes of 6,262 individuals (3,049 males and 3,213 females) were analyzed along with sex and body mass index (BMI). Result Genetic variation did not show a significant association with the population's energy-nutrient intake. However, female T allele carriers with BMI ≥ 25 consumed more blue fish and coffee, and their coffee creamer consumption was decisively higher than that of T allele non-carriers (P adjusted = 0.004). In males, the presence of the T allele showed a putative association with the consumption of sweets, snacks, and coffee creamer by the BMI level. Conclusion The FTO rs1121980 variation was associated with a preference for foods particularly high in fat (e.g. coffee creamer, blue fish, sweets, and snacks) in Koreans; these preferences varied by sex and BMI.
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Affiliation(s)
| | - Jeong-Hwa Choi
- Jeong-Hwa Choi, Department of Food Science and Nutrition, Keimyung University, 1095 Dalgubeol-daero, Dalseogu, Daegu 42601, Korea. Tel: +82-53-580-5913, Fax: +82-53-580-6286.
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11
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Tan PY, Moore JB, Bai L, Tang G, Gong YY. In the context of the triple burden of malnutrition: A systematic review of gene-diet interactions and nutritional status. Crit Rev Food Sci Nutr 2022; 64:3235-3263. [PMID: 36222100 PMCID: PMC11000749 DOI: 10.1080/10408398.2022.2131727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Genetic background interacts with dietary components to modulate nutritional health status. This study aimed to review the evidence for gene-diet interactions in all forms of malnutrition. A comprehensive systematic literature search was conducted through April 2021 to identify observational and intervention studies reporting the effects of gene-diet interactions in over-nutrition, under-nutrition and micronutrient status. Risk of publication bias was assessed using the Quality Criteria Checklist and a tool specifically designed for gene-diet interaction research. 167 studies from 27 populations were included. The majority of studies investigated single nucleotide polymorphisms (SNPs) in overnutrition (n = 158). Diets rich in whole grains, vegetables, fruits and low in total and saturated fats, such as Mediterranean and DASH diets, showed promising effects for reducing obesity risk among individuals who had higher genetic risk scores for obesity, particularly the risk alleles carriers of FTO rs9939609, rs1121980 and rs1421085. Other SNPs in MC4R, PPARG and APOA5 genes were also commonly studied for interaction with diet on overnutrition though findings were inconclusive. Only limited data were found related to undernutrition (n = 1) and micronutrient status (n = 9). The findings on gene-diet interactions in this review highlight the importance of personalized nutrition, and more research on undernutrition and micronutrient status is warranted.
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Affiliation(s)
- Pui Yee Tan
- School of Food Science and Nutrition, Faculty of Environment, University of Leeds, Leeds, United Kingdom
| | - J. Bernadette Moore
- School of Food Science and Nutrition, Faculty of Environment, University of Leeds, Leeds, United Kingdom
| | - Ling Bai
- School of Food Science and Nutrition, Faculty of Environment, University of Leeds, Leeds, United Kingdom
- School of Psychology, University of East Anglia, Norwich, United Kingdom
| | - GuYuan Tang
- School of Food Science and Nutrition, Faculty of Environment, University of Leeds, Leeds, United Kingdom
| | - Yun Yun Gong
- School of Food Science and Nutrition, Faculty of Environment, University of Leeds, Leeds, United Kingdom
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12
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Vesnina A, Prosekov A, Atuchin V, Minina V, Ponasenko A. Tackling Atherosclerosis via Selected Nutrition. Int J Mol Sci 2022; 23:8233. [PMID: 35897799 PMCID: PMC9368664 DOI: 10.3390/ijms23158233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 07/22/2022] [Accepted: 07/23/2022] [Indexed: 12/02/2022] Open
Abstract
The development and pathogenesis of atherosclerosis are significantly influenced by lifestyle, particularly nutrition. The modern level of science and technology development promote personalized nutrition as an efficient preventive measure against atherosclerosis. In this survey, the factors were revealed that contribute to the formation of an individual approach to nutrition: genetic characteristics, the state of the microbiota of the gastrointestinal tract (GIT) and environmental factors (diets, bioactive components, cardioprotectors, etc.). In the course of the work, it was found that in order to analyze the predisposition to atherosclerosis associated with nutrition, genetic features affecting the metabolism of nutrients are significant. The genetic features include the presence of single nucleotide polymorphisms (SNP) of genes and epigenetic factors. The influence of telomere length on the pathogenesis of atherosclerosis and circadian rhythms was also considered. Relatively new is the study of the relationship between chrono-nutrition and the development of metabolic diseases. That is, to obtain the relationship between nutrition and atherosclerosis, a large number of genetic markers should be considered. In this relation, the question arises: "How many genetic features need to be analyzed in order to form a personalized diet for the consumer?" Basically, companies engaged in nutrigenetic research and choosing a diet for the prevention of a number of metabolic diseases use SNP analysis of genes that accounts for lipid metabolism, vitamins, the body's antioxidant defense system, taste characteristics, etc. There is no set number of genetic markers. The main diets effective against the development of atherosclerosis were considered, and the most popular were the ketogenic, Mediterranean, and DASH-diets. The advantage of these diets is the content of foods with a low amount of carbohydrates, a high amount of vegetables, fruits and berries, as well as foods rich in antioxidants. However, due to the restrictions associated with climatic, geographical, material features, these diets are not available for a number of consumers. The way out is the use of functional products, dietary supplements. In this approach, the promising biologically active substances (BAS) that exhibit anti-atherosclerotic potential are: baicalin, resveratrol, curcumin, quercetin and other plant metabolites. Among the substances, those of animal origin are popular: squalene, coenzyme Q10, omega-3. For the prevention of atherosclerosis through personalized nutrition, it is necessary to analyze the genetic characteristics (SNP) associated with the metabolism of nutrients, to assess the state of the microbiota of the GIT. Based on the data obtained and food preferences, as well as the individual capabilities of the consumer, the optimal diet can be selected. It is topical to exclude nutrients of which their excess consumption stimulates the occurrence and pathogenesis of atherosclerosis and to enrich the diet with functional foods (FF), BAS containing the necessary anti-atherosclerotic, and stimulating microbiota of the GIT nutrients. Personalized nutrition is a topical preventive measure and there are a number of problems hindering the active use of this approach among consumers. The key factors include weak evidence of the influence of a number of genetic features, the high cost of the approach, and difficulties in the interpretation of the results. Eliminating these deficiencies will contribute to the maintenance of a healthy state of the population through nutrition.
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Affiliation(s)
- Anna Vesnina
- Laboratory of Natural Nutraceuticals Biotesting, Research Department, Kemerovo State University, 650043 Kemerovo, Russia;
| | - Alexander Prosekov
- Laboratory of Biocatalysis, Kemerovo State University, 650043 Kemerovo, Russia;
| | - Victor Atuchin
- Laboratory of Optical Materials and Structures, Institute of Semiconductor Physics, 630090 Novosibirsk, Russia
- Research and Development Department, Kemerovo State University, 650000 Kemerovo, Russia
- Laboratory of Applied Physics, Novosibirsk State University, 630090 Novosibirsk, Russia
- Department of Industrial Machinery Design, Novosibirsk State Technical University, 630073 Novosibirsk, Russia
- R&D Center “Advanced Electronic Technologies”, Tomsk State University, 634034 Tomsk, Russia
| | - Varvara Minina
- Department of Genetic and Fundamental Medicine, Kemerovo State University, 650000 Kemerovo, Russia;
| | - Anastasia Ponasenko
- Laboratory of Genome Medicine, Research Institute for Complex Issues of Cardiovascular Diseases, 650002 Kemerovo, Russia;
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13
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Yuzbashian E, Asghari G, Chan CB, Hedayati M, Safarian M, Zarkesh M, Mirmiran P, Khalaj A. The association of dietary and plasma fatty acid composition with FTO gene expression in human visceral and subcutaneous adipose tissues. Eur J Nutr 2021; 60:2485-2494. [PMID: 33159224 DOI: 10.1007/s00394-020-02422-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 10/19/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE The human obesity susceptibility gene, FTO, associates with body mass and obesity in humans through regulation of energy expenditure and intake. We aimed to determine how fatty acids in plasma and in diet associate with FTO gene expression in subcutaneous and visceral adipose tissues. METHODS In this study, 97 participants aged ≥ 18 years were selected from patients admitted to the hospital for abdominal surgeries. Habitual dietary intake of participants was collected using a valid and reliable food frequency questionnaire (FFQ), from which the intake of fatty acids was quantified. Plasma fatty acids were assessed by gas-liquid chromatography. The mRNA expression of the FTO gene in visceral and subcutaneous adipose tissues obtained by biopsy was measured by Real-Time Quantitative Reverse Transcription PCR. Standardized β-coefficients were calculated by multivariable linear regression. RESULTS After adjusting for age, homeostasis model insulin resistance index (HOMA-IR), and body mass index, total fatty acid intake was significantly associated with FTO gene expression in visceral (STZβ = 0.208, P = 0.037) and subcutaneous (STZβ = 0.236, P = 0.020) adipose tissues. Dietary intake of monounsaturated fatty acid (MUFA) and polyunsaturated fatty acids (PUFA) had positive significant associations with the expression of FTO in visceral (STZβ = 0.227, P = 0.023; STZβ = 0.346, P < 0.001, respectively) and subcutaneous (STZβ = 0.227, P = 0.026; STZβ = 0.274, P = 0.006, respectively) adipose tissues. There were no associations between plasma fatty acids and FTO mRNA expression in either subcutaneous or visceral adipose tissues. CONCLUSION The weak association of dietary total fatty acids, MUFA, and PUFA with FTO gene expression in both adipose tissues may highlight the importance of dietary fatty acids composition along with total fat intake in relation to FTO gene expression.
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Affiliation(s)
- Emad Yuzbashian
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Golaleh Asghari
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Department of Clinical Nutrition and Dietetics, Faculty of Nutrition Sciences and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, P.O. Box: 19395-4763, Tehran, Iran
| | - Catherine B Chan
- Department of Agricultural, Food and Nutritional Science and Department of Physiology, University of Alberta, Edmonton, AB, Canada
| | - Mehdi Hedayati
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box: 19395-4763, Tehran, Iran
| | - Mohammad Safarian
- Department of Nutrition, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Maryam Zarkesh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box: 19395-4763, Tehran, Iran
| | - Parvin Mirmiran
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
- Department of Clinical Nutrition and Dietetics, Faculty of Nutrition Sciences and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, P.O. Box: 19395-4763, Tehran, Iran.
| | - Alireza Khalaj
- Department of Surgery, Tehran Obesity Treatment Center, Shahed University, Tehran, Iran
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14
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McDaniel T, Wilson DK, Coulon MS, Sweeney AM, Van Horn ML. Interaction of Neighborhood and Genetic Risk on Waist Circumference in African-American Adults: A Longitudinal Study. Ann Behav Med 2021; 55:708-719. [PMID: 32914830 DOI: 10.1093/abm/kaaa063] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Understanding determinants of metabolic risk has become a national priority given the increasingly high prevalence rate of this condition among U.S. adults. PURPOSE This study's aim was to assess the impact of gene-by-neighborhood social environment interactions on waist circumference (WC) as a primary marker of metabolic risk in underserved African-American adults. Based on a dual-risk model, it was hypothesized that those with the highest genetic risk and who experienced negative neighborhood environment conditions would demonstrate higher WC than those with fewer risk factors. METHODS This study utilized a subsample of participants from the Positive Action for Today's Health environmental intervention to improve access and safety for walking in higher-crime neighborhoods, who were willing to provide buccal swab samples for genotyping stress-related genetic pathways. Assessments were conducted with 228 African-American adults at baseline, 12, 18, and 24 months. RESULTS Analyses indicated three significant gene-by-environment interactions on WC outcomes within the sympathetic nervous system (SNS) genetic pathway. Two interactions supported the dual-risk hypotheses, including the SNS genetic risk-by-neighborhood social life interaction (b = -0.11, t(618) = -2.02, p = .04), and SNS genetic risk-by-informal social control interaction (b = -0.51, t(618) = -1.95, p = .05) on WC outcomes. These interactions indicated that higher genetic risk and lower social-environmental supports were associated with higher WC. There was also one significant SNS genetic risk-by-neighborhood satisfaction interaction (b = 1.48, t(618) = 2.23, p = .02) on WC that was inconsistent with the dual-risk pattern. CONCLUSIONS Findings indicate that neighborhood and genetic factors dually influence metabolic risk and that these relations may be complex and warrant further study. TRIAL REGISTRATION NCT01025726.
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Affiliation(s)
- Tyler McDaniel
- Department of Psychology, Barnwell College, University of South Carolina, Columbia, SC, USA
| | - Dawn K Wilson
- Department of Psychology, Barnwell College, University of South Carolina, Columbia, SC, USA
| | - M Sandra Coulon
- Department of Mental Health, Ralph H. Johnson VA Medical Center, Charleston, SC, USA
| | - Allison M Sweeney
- Department of Psychology, Barnwell College, University of South Carolina, Columbia, SC, USA
| | - M Lee Van Horn
- Department of Educational Psychology, University of New Mexico, Albuquerque, NM, USA
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15
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de Souza DMS, Silva MC, Farias SEB, Menezes APDJ, Milanezi CM, Lúcio KDP, Paiva NCN, de Abreu PM, Costa DC, Pinto KMDC, Costa GDP, Silva JS, Talvani A. Diet Rich in Lard Promotes a Metabolic Environment Favorable to Trypanosoma cruzi Growth. Front Cardiovasc Med 2021; 8:667580. [PMID: 34113663 PMCID: PMC8185140 DOI: 10.3389/fcvm.2021.667580] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Accepted: 04/15/2021] [Indexed: 01/24/2023] Open
Abstract
Background: Trypanosoma cruzi is a protozoan parasite that causes Chagas disease and affects 6-7 million people mainly in Latin America and worldwide. Here, we investigated the effects of hyperlipidic diets, mainly composed of olive oil or lard on experimental T. cruzi infection. C57BL/6 mice were fed two different dietary types in which the main sources of fatty acids were either monounsaturated (olive oil diet) or saturated (lard diet). Methods: After 60 days on the diet, mice were infected with 50 trypomastigote forms of T. cruzi Colombian strain. We evaluated the systemic and tissue parasitism, tissue inflammation, and the redox status of mice after 30 days of infection. Results: Lipid levels in the liver of mice fed with the lard diet increased compared with that of the mice fed with olive oil or normolipidic diets. The lard diet group presented with an increased parasitic load in the heart and adipose tissues following infection as well as an increased expression of Tlr2 and Tlr9 in the heart. However, no changes were seen in the survival rates across the dietary groups. Infected mice receiving all diets presented comparable levels of recruited inflammatory cells at 30 days post-infection but, at this time, we observed lard diet inducing an overproduction of CCL2 in the cardiac tissue and its inhibition in the adipose tissue. T. cruzi infection altered liver antioxidant levels in mice, with the lard diet group demonstrating decreased catalase (CAT) activity compared with that of other dietary groups. Conclusions: Our data demonstrated that T. cruzi growth is more favorable on tissue of mice subjected to the lard diet. Our findings supported our hypothesis of a relationship between the source of dietary lipids and parasite-induced immunopathology.
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Affiliation(s)
- Débora Maria Soares de Souza
- Laboratory of Immunobiology of Inflammation, Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil.,Biological Science Post-graduate Program, Federal University of Ouro Preto, Ouro Preto, Brazil.,Health and Nutrition Post-graduate Program, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Maria Cláudia Silva
- Department of Biochemistry and Immunology, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Silvia Elvira Barros Farias
- Laboratory of Immunobiology of Inflammation, Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Ana Paula de J Menezes
- Laboratory of Immunobiology of Inflammation, Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Cristiane Maria Milanezi
- Department of Biochemistry and Immunology, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Karine de P Lúcio
- Laboratory of Metabolic Biochemistry, Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Nívia Carolina N Paiva
- Center of Research in Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Paula Melo de Abreu
- Biological Science Post-graduate Program, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Daniela Caldeira Costa
- Health and Nutrition Post-graduate Program, Federal University of Ouro Preto, Ouro Preto, Brazil.,Laboratory of Metabolic Biochemistry, Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Kelerson Mauro de Castro Pinto
- Laboratory of Immunobiology of Inflammation, Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil.,School of Physical Education, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Guilherme de Paula Costa
- Laboratory of Immunobiology of Inflammation, Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil.,Health and Nutrition Post-graduate Program, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - João Santana Silva
- Department of Biochemistry and Immunology, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil.,Fiocruz-Bi-Institutional Translational Medicine Plataform, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - André Talvani
- Laboratory of Immunobiology of Inflammation, Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil.,Health and Nutrition Post-graduate Program, Federal University of Ouro Preto, Ouro Preto, Brazil.,Health Science, Infectology and Tropical Medicine Post-graduate Program, Federal University of Minas Gerais, Belo Horizonte, Brazil
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16
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Isgin-Atici K, Alsulami S, Turan-Demirci B, Surendran S, Sendur SN, Lay I, Karabulut E, Ellahi B, Lovegrove JA, Alikasifoglu M, Erbas T, Vimaleswaran KS, Buyuktuncer Z. FTO gene-lifestyle interactions on serum adiponectin concentrations and central obesity in a Turkish population. Int J Food Sci Nutr 2021; 72:375-385. [PMID: 32746650 DOI: 10.1080/09637486.2020.1802580] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 07/07/2020] [Accepted: 07/23/2020] [Indexed: 12/18/2022]
Abstract
The aim of the study was to investigate whether lifestyle factors modify the association between fat mass and obesity-associated (FTO) gene single nucleotide polymorphisms (SNPs) and obesity in a Turkish population. The study included 400 unrelated individuals, aged 24-50 years recruited in a hospital setting. Dietary intake and physical activity were assessed using 24-hour dietary recall and self-report questionnaire, respectively. A genetic risk score (GRS) was developed using FTO SNPs, rs9939609 and rs10163409. Body mass index and fat mass index were significantly associated with FTO SNP rs9939609 (p = 0.001 and p = 0.002, respectively) and GRS (p = 0.002 and p = 0.003, respectively). The interactions between SNP rs9939609 and physical activity on adiponectin concentrations, and SNP rs10163409 and dietary protein intake on increased waist circumference were statistically significant (Pinteraction = 0.027 and Pinteraction = 0.044, respectively). Our study has demonstrated that the association between FTO SNPs and central obesity might be modified by lifestyle factors in this Turkish population.
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Affiliation(s)
- Kubra Isgin-Atici
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Hacettepe University, Ankara, Turkey
| | - Sooad Alsulami
- Department of Food and Nutritional Sciences, University of Reading, Whiteknights, Reading, UK
- Department of Clinical Nutrition, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Busra Turan-Demirci
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Hacettepe University, Ankara, Turkey
| | - Shelini Surendran
- Department of Food and Nutritional Sciences, University of Reading, Whiteknights, Reading, UK
| | - Suleyman Nahit Sendur
- Department of Endocrinology and Metabolism, School of Medicine, Hacettepe University, Ankara, Turkey
| | - Incilay Lay
- Department of Medical Biochemistry, School of Medicine, Hacettepe University, Ankara, Turkey
- Clinical Pathology Laboratory, Hacettepe University Hospitals, Ankara, Turkey
| | - Erdem Karabulut
- Department of Biostatistics, School of Medicine, Hacettepe University, Ankara, Turkey
- Department of Bioinformatics, Hacettepe University, Ankara, Turkey
| | - Basma Ellahi
- Faculty of Health and Social Care, University of Chester, Chester, UK
| | - Julie A Lovegrove
- Department of Food and Nutritional Sciences, University of Reading, Whiteknights, Reading, UK
| | - Mehmet Alikasifoglu
- Department of Medical Genetics, School of Medicine, Hacettepe University Ankara, Turkey
- Genetics Diagnostic Centre, DAMAGEN, Ankara, Turkey
| | - Tomris Erbas
- Department of Endocrinology and Metabolism, School of Medicine, Hacettepe University, Ankara, Turkey
| | | | - Zehra Buyuktuncer
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Hacettepe University, Ankara, Turkey
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17
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Vranceanu M, Pickering C, Filip L, Pralea IE, Sundaram S, Al-Saleh A, Popa DS, Grimaldi KA. A comparison of a ketogenic diet with a LowGI/nutrigenetic diet over 6 months for weight loss and 18-month follow-up. BMC Nutr 2020; 6:53. [PMID: 32983551 PMCID: PMC7513277 DOI: 10.1186/s40795-020-00370-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 08/04/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Obesity and its related metabolic disturbances represent a huge health burden on society. Many different weight loss interventions have been trialled with mixed efficacy, as demonstrated by the large number of individuals who regain weight upon completion of such interventions. There is evidence that the provision of genetic information may enhance long-term weight loss, either by increasing dietary adherence or through underlying biological mechanisms. METHODS The investigators followed 114 overweight and obese subjects from a weight loss clinic in a 2-stage process. 1) A 24-week dietary intervention. The subjects self-selected whether to follow a standardized ketogenic diet (n = 53), or a personalised low-glycemic index (GI) nutrigenetic diet utilising information from 28 single nucleotide polymorphisms (n = 61). 2) After the 24-week diet period, the subjects were monitored for an additional 18 months using standard guidelines for the Keto group vs standard guidelines modified by nutrigenetic advice for the low-Glycaemic Index nutrigenetic diet (lowGI/NG) group. RESULTS After 24 weeks, the keto group lost more weight: - 26.2 ± 3.1 kg vs - 23.5 ± 6.4 kg (p = 0.0061). However, at 18-month follow up, the subjects in the low-GI nutrigenetic diet had lost significantly more weight (- 27.5 ± 8.9 kg) than those in the ketogenic diet who had regained some weight (- 19.4 ± 5.0 kg) (p < 0.0001). Additionally, after the 24-week diet and 18-month follow up the low-GI nutrigenetic diet group had significantly greater (p < 0.0001) improvements in total cholesterol (ketogenic - 35.4 ± 32.2 mg/dl; low-GI nutrigenetic - 52.5 ± 24.3 mg/dl), HDL cholesterol (ketogenic + 4.7 ± 4.5 mg/dl; low-GI nutrigenetic + 11.9 ± 4.1 mg/dl), and fasting glucose (ketogenic - 13.7 ± 8.4 mg/dl; low-GI nutrigenetic - 24.7 ± 7.4 mg/dl). CONCLUSIONS These findings demonstrate that the ketogenic group experienced enhanced weight loss during the 24-week dietary intervention. However, at 18-month follow up, the personalised nutrition group (lowGI/NG) lost significantly more weight and experienced significantly greater improvements in measures of cholesterol and blood glucose. This suggests that personalising nutrition has the potential to enhance long-term weight loss and changes in cardiometabolic parameters. TRIAL REGISTRATION NCT04330209, Registered 01/04/2020, retrospectively registered.
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Affiliation(s)
- Maria Vranceanu
- Department of Toxicology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj Napoca, Romania
| | - Craig Pickering
- Institute of Coaching and Performance, School of Sport and Wellbeing, University of Central Lancashire, Preston, UK
| | - Lorena Filip
- Department of Bromatology and Hygiene, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj Napoca, Romania
| | - Ioana Ecaterina Pralea
- Department of Toxicology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj Napoca, Romania
| | | | | | - Daniela-Saveta Popa
- Department of Toxicology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj Napoca, Romania
| | - Keith A. Grimaldi
- Department of Nutrigenetics and Personalized Nutrition, Eurogenetica, Rome, Italy
- Prenetics DNAfit Research Centre, London, UK
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18
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Quantile-dependent heritability of computed tomography, dual-energy x-ray absorptiometry, anthropometric, and bioelectrical measures of adiposity. Int J Obes (Lond) 2020; 44:2101-2112. [PMID: 32665611 PMCID: PMC7530941 DOI: 10.1038/s41366-020-0636-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 06/07/2020] [Accepted: 07/03/2020] [Indexed: 12/18/2022]
Abstract
Background/Objectives: Quantile-dependent expressivity occurs when a gene’s
phenotypic expression depends upon whether the trait (e.g., BMI) is high or
low relative to its distribution. We have previously shown that the obesity
effects of a genetic risk score (GRSBMI) increased significantly
with increasing quantiles of BMI. However, BMI is an inexact adiposity
measure and GRSBMI explains <3% of the BMI variance. The
purpose of this paper is to test BMI for quantile-dependent expressivity
using a more inclusive genetic measure
(h2, heritability in
the narrow sense), extend the result to other adiposity measures, and
demonstrate its consistency with purported gene-environment
interactions. Subjects/Methods: Quantile-specific offspring-parent regression slopes
(βOP) were obtained from quantile regression for
height (ht) and computed tomography (CT), dual-energy x-ray absorptiometry
(DXA), anthropometric, and bioelectrical impedance (BIA) adiposity measures.
Heritability was estimated by 2βOP/(1+rspouse)
in 6,227 offspring-parent pairs from the Framingham Heart Study, where
rspouse is the spouse correlation. Results: Compared to h2 at the
10th percentile, genetic heritability was significantly
greater at the 90th population percentile for BMI (3.14-fold
greater, P<10−15), waist girth/ht (3.27-fold,
P<10−15), hip girth/ht (3.12-fold,
P=6.3×10−14), waist-to-hip ratio (1.75-fold,
P=0.01), sagittal diameter/ht (3.89-fold,
P=3.7×10−7), DXA total fat/ht2
(3.62-fold, P=0.0002), DXA leg fat/ht2 (3.29-fold,
P=2.0×10−11), DXA arm fat/ht2
(4.02-fold, P=0.001), CT-visceral fat/ht2 (3.03-fold, P=0.002),
and CT-subcutaneous fat/ht2 (3.54-fold, P=0.0004). External
validity was suggested by the phenomenon’s consistency with numerous
published reports. Quantile-dependent expressivity potentially explains
precision medicine markers for weight gain from overfeeding or antipsychotic
medications, and the modifying effects of physical activity, sleep, diet,
polycystic ovary syndrome, socioeconomic status, and depression on gene-BMI
relationships. Conclusion: Genetic heritabilities of anthropometric, CT, and DXA adiposity
measures increase with increasing adiposity. Some gene-environment
interactions may arise from analyzing subjects by characteristics that
distinguish high vs. low adiposity rather than the effects of environmental
stimuli on transcriptional and epigenetic processes.
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Interaction between Metabolic Genetic Risk Score and Dietary Fatty Acid Intake on Central Obesity in a Ghanaian Population. Nutrients 2020; 12:nu12071906. [PMID: 32605047 PMCID: PMC7400498 DOI: 10.3390/nu12071906] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/04/2020] [Accepted: 06/24/2020] [Indexed: 02/07/2023] Open
Abstract
Obesity is a multifactorial condition arising from the interaction between genetic and lifestyle factors. We aimed to assess the impact of lifestyle and genetic factors on obesity-related traits in 302 healthy Ghanaian adults. Dietary intake and physical activity were assessed using a 3 day repeated 24 h dietary recall and global physical activity questionnaire, respectively. Twelve single nucleotide polymorphisms (SNPs) were used to construct 4-SNP, 8-SNP and 12-SNP genetic risk scores (GRSs). The 4-SNP GRS showed significant interactions with dietary fat intakes on waist circumference (WC) (Total fat, Pinteraction = 0.01; saturated fatty acids (SFA), Pinteraction = 0.02; polyunsaturated fatty acids (PUFA), Pinteraction = 0.01 and monounsaturated fatty acids (MUFA), Pinteraction = 0.01). Among individuals with higher intakes of total fat (>47 g/d), SFA (>14 g/d), PUFA (>16 g/d) and MUFA (>16 g/d), individuals with ≥3 risk alleles had a significantly higher WC compared to those with <3 risk alleles. This is the first study of its kind in this population, suggesting that a higher consumption of dietary fatty acid may have the potential to increase the genetic susceptibility of becoming centrally obese. These results support the general dietary recommendations to decrease the intakes of total fat and SFA, to reduce the risk of obesity, particularly in individuals with a higher genetic predisposition to central obesity.
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20
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Vimaleswaran KS. A nutrigenetics approach to study the impact of genetic and lifestyle factors on cardiometabolic traits in various ethnic groups: findings from the GeNuIne Collaboration. Proc Nutr Soc 2020; 79:194-204. [PMID: 32000867 DOI: 10.1017/s0029665119001186] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Several studies on gene-diet interactions (nutrigenetics) have been performed in western populations; however, there are only a few studies to date in lower middle-income countries (LMIC). A large-scale collaborative project called gene-nutrient interactions (GeNuIne) Collaboration, the main objective of which is to investigate the effect of GeNuIne on cardiometabolic traits using population-based studies from various ethnic groups, has been initiated at the University of Reading, UK. While South Asians with higher genetic risk score (GRS) showed a higher risk of obesity in response to a high-carbohydrate diet, South East and Western Asian populations with higher GRS showed an increased risk of central obesity in response to a high-protein diet. The paper also provides a summary of other gene-diet interaction analyses that were performed in LMIC as part of this collaborative project and gives an overview of how these nutrigenetic findings can be translated to personalised and public health approaches for the prevention of cardiometabolic diseases such as obesity, type 2 diabetes and CVD.
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Affiliation(s)
- Karani S Vimaleswaran
- Department of Food and Nutritional Sciences, Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, UK
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21
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Crovesy L, Rosado EL. Interaction between genes involved in energy intake regulation and diet in obesity. Nutrition 2019; 67-68:110547. [DOI: 10.1016/j.nut.2019.06.027] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Revised: 06/20/2019] [Accepted: 06/26/2019] [Indexed: 01/01/2023]
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22
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Contu L, Nizari S, Heath CJ, Hawkes CA. Pre- and Post-natal High Fat Feeding Differentially Affects the Structure and Integrity of the Neurovascular Unit of 16-Month Old Male and Female Mice. Front Neurosci 2019; 13:1045. [PMID: 31632236 PMCID: PMC6783577 DOI: 10.3389/fnins.2019.01045] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 09/17/2019] [Indexed: 01/20/2023] Open
Abstract
Compelling experimental and clinical evidence supports a role for maternal obesity in offspring health. Adult children of obese mothers are at greater risk of obesity, diabetes, coronary heart disease and stroke. These offspring may also be at greater risk of age-related neurodegenerative diseases for which mid-life obesity is a risk factor. Rodent diet-induced obesity models have shown that high fat (HF) diet consumption damages the integrity of the blood–brain barrier (BBB) in the adult brain. However, there is currently little information about the effect of chronic HF feeding on the BBB of aged animals. Moreover, the long-term consequences of maternal obesity on the cerebrovasculature of aged offspring are not known. This study determined the impact of pre- and post-natal HF diet on the structure and integrity of cerebral blood vessels in aged male and female mice. Female C57Bl/6 mice were fed either a 10% fat control (C) or 45% HF diet before mating and during gestation and lactation. At weaning, male and female offspring were fed the C or HF diet until sacrifice at 16-months of age. Both dams and offspring fed the HF diet weighed significantly more than mice fed the C diet. Post-natal HF diet exposure increased hippocampal BBB leakiness in female offspring, in association with loss of astrocyte endfoot coverage of arteries. Markers of tight junctions, pericytes or smooth muscle cells were not altered by pre- or post-natal HF diet. Male offspring born to HF-fed mothers showed decreased parenchymal GFAP expression compared to offspring of mothers fed C diet, while microglial and macrophage markers were higher in the same female diet group. In addition, female offspring exposed to the HF diet for their entire lifespan showed more significant changes in vessel structure, BBB permeability and inflammation compared to male animals. These results suggest that the long-term impact of prenatal HF diet on the integrity of cerebral blood vessels differs between male and female offspring depending on the post-natal diet. This may have implications for the prevention and management of age- and obesity-related cerebrovascular diseases that differentially affect men and women.
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Affiliation(s)
- Laura Contu
- School of Life, Health and Chemical Sciences, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, United Kingdom
| | - Shereen Nizari
- School of Life, Health and Chemical Sciences, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, United Kingdom
| | - Christopher J Heath
- School of Life, Health and Chemical Sciences, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, United Kingdom
| | - Cheryl A Hawkes
- School of Life, Health and Chemical Sciences, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, United Kingdom
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23
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Al Ali M, El hajj Chehadeh S, Osman W, Almansoori K, Abdulrahman M, Tay G, Alsafar H. Investigating the association of rs7903146 of TCF7L2 gene, rs5219 of KCNJ11 gene, rs10946398 of CDKAL1 gene, and rs9939609 of FTO gene with type 2 diabetes mellitus in Emirati population. Meta Gene 2019. [DOI: 10.1016/j.mgene.2019.100600] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
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24
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Gene-Environment Interactions on Body Fat Distribution. Int J Mol Sci 2019; 20:ijms20153690. [PMID: 31357654 PMCID: PMC6696304 DOI: 10.3390/ijms20153690] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 07/18/2019] [Accepted: 07/19/2019] [Indexed: 02/08/2023] Open
Abstract
The prevalence of obesity has been increasing markedly in the U.S. and worldwide in the past decades; and notably, the obese populations are signified by not only the overall elevated adiposity but also particularly harmful accumulation of body fat in the central region of the body, namely, abdominal obesity. The profound shift from “traditional” to “obesogenic” environments, principally featured by the abundance of palatable, energy-dense diet, reduced physical activity, and prolonged sedentary time, promotes the obesity epidemics and detrimental body fat distribution. Recent advances in genomics studies shed light on the genetic basis of obesity and body fat distribution. In addition, growing evidence from investigations in large cohorts and clinical trials has lent support to interactions between genetic variations and environmental factors, e.g., diet and lifestyle factors, in relation to obesity and body fat distribution. This review summarizes the recent discoveries from observational studies and randomized clinical trials on the gene–environment interactions on obesity and body fat distribution.
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25
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Jiang Y, Mei H, Lin Q, Wang J, Liu S, Wang G, Jiang F. Interaction effects of FTO rs9939609 polymorphism and lifestyle factors on obesity indices in early adolescence. Obes Res Clin Pract 2019; 13:352-357. [DOI: 10.1016/j.orcp.2019.06.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 05/26/2019] [Accepted: 06/18/2019] [Indexed: 12/19/2022]
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26
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Koochakpour G, Esfandiar Z, Hosseini-Esfahani F, Mirmiran P, Daneshpour MS, Sedaghati-Khayat B, Azizi F. Evaluating the interaction of common FTO genetic variants, added sugar, and trans-fatty acid intakes in altering obesity phenotypes. Nutr Metab Cardiovasc Dis 2019; 29:474-480. [PMID: 30954417 DOI: 10.1016/j.numecd.2019.01.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Revised: 11/21/2018] [Accepted: 01/14/2019] [Indexed: 10/27/2022]
Abstract
BACKGROUND AND AIMS The results of studies on the effect of trans-fatty acids (TFAs) and added sugars on obesity are not consistent. This study aimed to investigate whether the association of changes in general and central obesity with added sugar and TFA intakes is modified by common fat mass and obesity-associated gene (FTO) polymorphisms, in isolation or in a combined-form genetic risk score (GRS). METHODS AND RESULTS Subjects of this cohort study were selected from among adult participants of the Tehran Lipid and Glucose Study (n = 4292, 43.2% male). Dietary data were collected using a valid and reliable food frequency questionnaire. The genotypes of selected polymorphisms (rs1421085, rs1121980, and rs8050136) were determined. Genetic risk score (GRS) was calculated using the dominant weighted method. The mean age of participants was 42.6 ± 14 and 40.4 ± 13 years in men and women, respectively. FTO rs8050136 polymorphisms and TFAs have a significant interaction in changing body mass index (BMI) (P interaction = 0.01). There were no changes in waist circumference (WC) and BMI among FTO risk allele carriers, across quartiles of added sugar intake. GRS and TFA intakes significantly interacted in altering the BMI and WC; thus, a higher intake of TFAs was associated with higher changes of BMI and WC in subjects with high GRS (P trend<0.05) compared to individuals with low GRS. CONCLUSION Our findings suggest that TFA intake can increase the genetic susceptibility of FTO SNPs to BMI or WC change.
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Affiliation(s)
- G Koochakpour
- Maragheh University of Medical Sciences, Maragheh, Iran
| | - Z Esfandiar
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - F Hosseini-Esfahani
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - P Mirmiran
- Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Faculty of Nutrition Sciences and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - M S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - B Sedaghati-Khayat
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - F Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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27
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Dietary patterns modify the association between fat mass and obesity-associated genetic variants and changes in obesity phenotypes. Br J Nutr 2019; 121:1247-1254. [PMID: 30929646 DOI: 10.1017/s0007114519000643] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The present study investigated whether dietary patterns could interact with fat mass and obesity-associated (FTO) polymorphisms in relation to changes in BMI and waist circumference (WC) over 3⋅6 years of follow-up. Subjects were selected from participants of the Tehran Lipid and Glucose Study (n 4292, 43⋅2 % male). Dietary data were collected using a valid and reliable FFQ. Dietary patterns were determined using factor analysis. The genotypes of polymorphisms (rs1421085, rs1121980, rs17817449, rs8050136, rs9939973 and rs3751812) were determined. Genetic risk score (GRS) was calculated using the weighted method. Mean ages of men and women were 42·6 (sd 14) and 40⋅4 (sd 13) years, respectively. The healthy (e.g. vegetables and fruits) and the Western dietary patterns (WDP; e.g. soft drinks and fast foods) were extracted. In carriers of the risk alleles rs1121980, rs1421085, rs8050136, rs1781799 and rs3751812, BMI was approximately 2-fold higher in individuals in the higher quartile of WDP score, compared with the first quartile (P < 0⋅05). WC increased with increasing WDP score in carriers of the risk alleles rs1121980 and rs3751812, but not in individuals who did not carry any risk alleles. BMI and WC increased to a greater extent in the high GRS group while increasing quartiles of the WDP score, compared with the low GRS group (BMI change; Q1: 1⋅04 (se 0⋅34) v. Q4: 2⋅26 (se 0⋅36)) (WC change; Q1: 0⋅47 (se 0⋅32) v. Q4: 0⋅95 (se 0⋅34)) (P interaction < 0⋅05). These results suggest that adults with higher genetic predisposition to obesity are more susceptible to the harmful effects of adherence to the WDP, which emphasised the need to reduce the consumption of unhealthy foods for the prevention of obesity.
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28
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Barroso I, McCarthy MI. The Genetic Basis of Metabolic Disease. Cell 2019; 177:146-161. [PMID: 30901536 PMCID: PMC6432945 DOI: 10.1016/j.cell.2019.02.024] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 02/11/2019] [Accepted: 02/14/2019] [Indexed: 02/06/2023]
Abstract
Recent developments in genetics and genomics are providing a detailed and systematic characterization of the genetic underpinnings of common metabolic diseases and traits, highlighting the inherent complexity within systems for homeostatic control and the many ways in which that control can fail. The genetic architecture underlying these common metabolic phenotypes is complex, with each trait influenced by hundreds of loci spanning a range of allele frequencies and effect sizes. Here, we review the growing appreciation of this complexity and how this has fostered the implementation of genome-scale approaches that deliver robust mechanistic inference and unveil new strategies for translational exploitation.
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Affiliation(s)
- Inês Barroso
- Wellcome Sanger Institute, Hinxton, Cambridge CB10 1SA, UK.
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Churchill Hospital, Old Road, Headington, Oxford OX3 7LJ, UK; Oxford NIHR Biomedical Research Centre, Churchill Hospital, Old Road, Headington, Oxford OX3 7LJ, UK
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29
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Galmés S, Cifre M, Palou A, Oliver P, Serra F. A Genetic Score of Predisposition to Low-Grade Inflammation Associated with Obesity May Contribute to Discern Population at Risk for Metabolic Syndrome. Nutrients 2019; 11:E298. [PMID: 30704070 PMCID: PMC6412420 DOI: 10.3390/nu11020298] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Revised: 01/16/2019] [Accepted: 01/24/2019] [Indexed: 12/26/2022] Open
Abstract
Omega-3 rich diets have been shown to improve inflammatory status. However, in an ex vivo system of human blood cells, the efficacy of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) modulating lipid metabolism and cytokine response is attenuated in overweight subjects and shows high inter-individual variability. This suggests that obesity may be exerting a synergistic effect with genetic background disturbing the anti-inflammatory potential of omega-3 long-chain polyunsaturated fatty acids (PUFA). In the present work, a genetic score aiming to explore the risk associated to low grade inflammation and obesity (LGI-Ob) has been elaborated and assessed as a tool to contribute to discern population at risk for metabolic syndrome. Pro-inflammatory gene expression and cytokine production as a response to omega-3 were associated with LGI-Ob score; and lower anti-inflammatory effect of PUFA was observed in subjects with a high genetic score. Furthermore, overweight/obese individuals showed positive correlation of both plasma C-Reactive Protein and triglyceride/HDLc-index with LGI-Ob; and high LGI-Ob score was associated with greater hypertension (p = 0.047), Type 2 diabetes (p = 0.026), and metabolic risk (p = 0.021). The study shows that genetic variation can influence inflammation and omega-3 response, and that the LGI-Ob score could be a useful tool to classify subjects at inflammatory risk and more prone to suffer metabolic syndrome and associated metabolic disturbances.
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Affiliation(s)
- Sebastià Galmés
- NUO Group, Laboratory of Molecular Biology, Nutrition and Biotechnology, Universitat de les Illes Balears, 07122 Palma, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), 28029 Madrid, Spain.
- Institut d'Investigació Sanitària Illes Balears (IdISBa), 07120 Palma, Spain.
| | - Margalida Cifre
- NUO Group, Laboratory of Molecular Biology, Nutrition and Biotechnology, Universitat de les Illes Balears, 07122 Palma, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), 28029 Madrid, Spain.
| | - Andreu Palou
- NUO Group, Laboratory of Molecular Biology, Nutrition and Biotechnology, Universitat de les Illes Balears, 07122 Palma, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), 28029 Madrid, Spain.
- Institut d'Investigació Sanitària Illes Balears (IdISBa), 07120 Palma, Spain.
| | - Paula Oliver
- NUO Group, Laboratory of Molecular Biology, Nutrition and Biotechnology, Universitat de les Illes Balears, 07122 Palma, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), 28029 Madrid, Spain.
- Institut d'Investigació Sanitària Illes Balears (IdISBa), 07120 Palma, Spain.
| | - Francisca Serra
- NUO Group, Laboratory of Molecular Biology, Nutrition and Biotechnology, Universitat de les Illes Balears, 07122 Palma, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), 28029 Madrid, Spain.
- Institut d'Investigació Sanitària Illes Balears (IdISBa), 07120 Palma, Spain.
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30
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Reddon H, Patel Y, Turcotte M, Pigeyre M, Meyre D. Revisiting the evolutionary origins of obesity: lazy versus peppy-thrifty genotype hypothesis. Obes Rev 2018; 19:1525-1543. [PMID: 30261552 DOI: 10.1111/obr.12742] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 06/26/2018] [Accepted: 07/01/2018] [Indexed: 12/31/2022]
Abstract
The recent global obesity epidemic is attributed to major societal and environmental changes, such as excessive energy intake and sedentary lifestyle. However, exposure to 'obesogenic' environments does not necessarily result in obesity at the individual level, as 40-75% of body mass index variation in population is attributed to genetic differences. The thrifty genotype theory posits that genetic variants promoting efficient food sequestering and optimal deposition of fat during periods of food abundance were evolutionarily advantageous for the early hunter-gatherer and were positively selected. However, the thrifty genotype is likely too simplistic and fails to provide a justification for the complex distribution of obesity predisposing gene variants and for the broad range of body mass index observed in diverse ethnic groups. This review proposes that gene pleiotropy may better account for the variability in the distribution of obesity susceptibility alleles across modern populations. We outline the lazy-thrifty versus peppy-thrifty genotype hypothesis and detail the body of evidence in the literature in support of this novel concept. Future population genetics and mathematical modelling studies that account for pleiotropy may further improve our understanding of the evolutionary origins of the current obesity epidemic.
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Affiliation(s)
- H Reddon
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - Y Patel
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - M Turcotte
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - M Pigeyre
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
| | - D Meyre
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
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31
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Goodarzi MO. Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications. Lancet Diabetes Endocrinol 2018; 6:223-236. [PMID: 28919064 DOI: 10.1016/s2213-8587(17)30200-0] [Citation(s) in RCA: 252] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 05/24/2017] [Accepted: 05/24/2017] [Indexed: 01/01/2023]
Abstract
Genome-wide association studies (GWAS) for BMI, waist-to-hip ratio, and other adiposity traits have identified more than 300 single-nucleotide polymorphisms (SNPs). Although there is reason to hope that these discoveries will eventually lead to new preventive and therapeutic agents for obesity, this will take time because such developments require detailed mechanistic understanding of how an SNP influences phenotype (and this information is largely unavailable). Fortunately, absence of functional information has not prevented GWAS findings from providing insights into the biology of obesity. Genes near loci regulating total body mass are enriched for expression in the CNS, whereas genes for fat distribution are enriched in adipose tissue itself. Gene by environment and lifestyle interaction analyses have revealed that our increasingly obesogenic environment might be amplifying genetic risk for obesity, yet those at highest risk could mitigate this risk by increasing physical activity and possibly by avoiding specific dietary components. GWAS findings have also been used in mendelian randomisation analyses probing the causal association between obesity and its many putative complications. In supporting a causal association of obesity with diabetes, coronary heart disease, specific cancers, and other conditions, these analyses have clinical relevance in identifying which outcomes could be preventable through weight loss interventions.
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Affiliation(s)
- Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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32
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Abadi A, Alyass A, Robiou du Pont S, Bolker B, Singh P, Mohan V, Diaz R, Engert JC, Yusuf S, Gerstein HC, Anand SS, Meyre D. Penetrance of Polygenic Obesity Susceptibility Loci across the Body Mass Index Distribution. Am J Hum Genet 2017; 101:925-938. [PMID: 29220676 PMCID: PMC5812888 DOI: 10.1016/j.ajhg.2017.10.007] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2017] [Accepted: 10/12/2017] [Indexed: 12/17/2022] Open
Abstract
A growing number of single-nucleotide polymorphisms (SNPs) have been associated with body mass index (BMI) and obesity, but whether the effects of these obesity-susceptibility loci are uniform across the BMI distribution remains unclear. We studied the effects of 37 BMI-associated SNPs in 75,230 adults of European ancestry across BMI percentiles by using conditional quantile regression (CQR) and meta-regression (MR) models. The effects of nine SNPs (24%)-rs1421085 (FTO; p = 8.69 × 10-15), rs6235 (PCSK1; p = 7.11 × 10-6), rs7903146 (TCF7L2; p = 9.60 × 10-6), rs11873305 (MC4R; p = 5.08 × 10-5), rs12617233 (FANCL; p = 5.30 × 10-5), rs11672660 (GIPR; p = 1.64 × 10-4), rs997295 (MAP2K5; p = 3.25 × 10-4), rs6499653 (FTO; p = 6.23 × 10-4), and rs3824755 (NT5C2; p = 7.90 × 10-4)-increased significantly across the sample BMI distribution. We showed that such increases stemmed from unadjusted gene interactions that enhanced the effects of SNPs in persons with a high BMI. When 125 height-associated SNPs were analyzed for comparison, only one (<1%), rs6219 (IGF1, p = 1.80 × 10-4), showed effects that varied significantly across height percentiles. Cumulative gene scores of these SNPs (GS-BMI and GS-height) showed that only GS-BMI had effects that increased significantly across the sample distribution (BMI: p = 7.03 × 10-37; height: p = 0.499). Overall, these findings underscore the importance of gene-gene and gene-environment interactions in shaping the genetic architecture of BMI and advance a method for detecting such interactions by using only the sample outcome distribution.
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Affiliation(s)
- Arkan Abadi
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Akram Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Sebastien Robiou du Pont
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Ben Bolker
- Department of Mathematics and Statistics, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Pardeep Singh
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation, Gopalapuram, Chennai 600086, India
| | - Rafael Diaz
- Estudios Clínicos Latino America, Paraguay 160, S2000CVD Rosario, Santa Fe, Argentina
| | | | - Salim Yusuf
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton General Hospital, Hamilton, ON L8S 4L8, Canada; Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Hertzel C Gerstein
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton General Hospital, Hamilton, ON L8S 4L8, Canada; Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Sonia S Anand
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton General Hospital, Hamilton, ON L8S 4L8, Canada; Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada.
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Gene-nutrient interactions and susceptibility to human obesity. GENES AND NUTRITION 2017; 12:29. [PMID: 29093760 PMCID: PMC5663124 DOI: 10.1186/s12263-017-0581-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 07/04/2017] [Indexed: 12/28/2022]
Abstract
A large number of genome-wide association studies, transferability studies, and candidate gene studies performed in diverse populations around the world have identified gene variants that are associated with common human obesity. The mounting evidence suggests that these obesity gene variants interact with multiple environmental factors and increase susceptibility to this complex metabolic disease. The objective of this review article is to provide concise and updated information on energy balance, heritability of body weight, origins of gene variants, and gene-nutrient interactions in relation to human obesity. It is proposed that knowledge of these related topics will provide valuable insight for future preventative lifestyle intervention using targeted nutritional and medicinal therapies.
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Dietary Fatty Acid Composition Modulates Obesity and Interacts with Obesity-Related Genes. Lipids 2017; 52:803-822. [DOI: 10.1007/s11745-017-4291-9] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Accepted: 08/18/2017] [Indexed: 12/22/2022]
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Albuquerque D, Nóbrega C, Manco L, Padez C. The contribution of genetics and environment to obesity. Br Med Bull 2017; 123:159-173. [PMID: 28910990 DOI: 10.1093/bmb/ldx022] [Citation(s) in RCA: 130] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Accepted: 06/23/2017] [Indexed: 12/26/2022]
Abstract
BACKGROUND Obesity is a global health problem mainly attributed to lifestyle changes such as diet, low physical activity or socioeconomics factors. However, several evidences consistently showed that genetics contributes significantly to the weight-gain susceptibility. SOURCES OF DATA A systematic literature search of most relevant original, review and meta-analysis, restricted to English was conducted in PubMed, Web of Science and Google scholar up to May 2017 concerning the contribution of genetics and environmental factors to obesity. AREAS OF AGREEMENT Several evidences suggest that obesogenic environments contribute to the development of an obese phenotype. However, not every individual from the same population, despite sharing the same obesogenic environment, develop obesity. AREAS OF CONTROVERSY After more than 10 years of investigation on the genetics of obesity, the variants found associated with obesity represent only 3% of the estimated BMI-heritability, which is around 47-80%. Moreover, genetic factors per se were unable to explain the rapid spread of obesity prevalence. GROWING POINTS The integration of multi-omics data enables scientists having a better picture and to elucidate unknown pathways contributing to obesity. AREAS TIMELY FOR DEVELOPING RESEARCH New studies based on case-control or gene candidate approach will be important to identify new variants associated with obesity susceptibility and consequently unveiling its genetic architecture. This will lead to an improvement of our understanding about underlying mechanisms involved in development and origin of the actual obesity epidemic. The integration of several omics will also provide insights about the interplay between genes and environments contributing to the obese phenotype.
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Affiliation(s)
- David Albuquerque
- Research Center for Anthropology and Health (CIAS), Department of Life Sciences, University of Coimbra, Coimbra, Portugal.,Fundación Investigación Hospital General Universitario de Valencia, Genomics group, Valencia, Spain
| | - Clévio Nóbrega
- Department of Biomedical Sciences and Medicine (DCBM), University of Algarve, Faro, Portugal.,Centre for Biomedical Research (CBMR), University of Algarve, Faro, Portugal.,Algarve Biomedical Center (ABC), University of Algarve, Faro, Portugal
| | - Licínio Manco
- Research Center for Anthropology and Health (CIAS), Department of Life Sciences, University of Coimbra, Coimbra, Portugal.,Faculty of Sciences and Technology, Department of Life Sciences, University of Coimbra, Coimbra, Portugal
| | - Cristina Padez
- Research Center for Anthropology and Health (CIAS), Department of Life Sciences, University of Coimbra, Coimbra, Portugal.,Faculty of Sciences and Technology, Department of Life Sciences, University of Coimbra, Coimbra, Portugal
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36
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The importance of gene-environment interactions in human obesity. Clin Sci (Lond) 2017; 130:1571-97. [PMID: 27503943 DOI: 10.1042/cs20160221] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Accepted: 05/23/2016] [Indexed: 12/16/2022]
Abstract
The worldwide obesity epidemic has been mainly attributed to lifestyle changes. However, who becomes obese in an obesity-prone environment is largely determined by genetic factors. In the last 20 years, important progress has been made in the elucidation of the genetic architecture of obesity. In parallel with successful gene identifications, the number of gene-environment interaction (GEI) studies has grown rapidly. This paper reviews the growing body of evidence supporting gene-environment interactions in the field of obesity. Heritability, monogenic and polygenic obesity studies provide converging evidence that obesity-predisposing genes interact with a variety of environmental, lifestyle and treatment exposures. However, some skepticism remains regarding the validity of these studies based on several issues, which include statistical modelling, confounding, low replication rate, underpowered analyses, biological assumptions and measurement precision. What follows in this review includes (1) an introduction to the study of GEI, (2) the evidence of GEI in the field of obesity, (3) an outline of the biological mechanisms that may explain these interaction effects, (4) methodological challenges associated with GEI studies and potential solutions, and (5) future directions of GEI research. Thus far, this growing body of evidence has provided a deeper understanding of GEI influencing obesity and may have tremendous applications in the emerging field of personalized medicine and individualized lifestyle recommendations.
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Muñoz AM, Velásquez CM, Agudelo GM, Uscátegui RM, Estrada A, Patiño FA, Parra BE, Parra MV, Bedoya G. Examining for an association between candidate gene polymorphisms in the metabolic syndrome components on excess weight and adiposity measures in youth: a cross-sectional study. GENES AND NUTRITION 2017; 12:19. [PMID: 28690685 PMCID: PMC5496328 DOI: 10.1186/s12263-017-0567-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Accepted: 04/28/2017] [Indexed: 01/14/2023]
Abstract
Background A polymorphism in a gene may exert its effects on multiple phenotypes. The aim of this study is to explore the association of 10 metabolic syndrome candidate genes with excess weight and adiposity and evaluate the effect of perinatal and socioeconomic factors on these associations. Methods The anthropometry, socioeconomic and perinatal conditions and 10 polymorphisms were evaluated in 1081 young people between 10 and 18 years old. Genotypic associations were calculated using logistic and linear models adjusted by age, gender, and pubertal maturation, and a genetic risk score (GRS) was calculated by summing the number of effect alleles. Results We found that AGT-rs699 and the IRS2-rs1805097 variants were significantly associated with excess weight, OR = 1.25 (CI 95% 1.01–1.54; p = 0.034); OR = 0.77 (CI 95% 0.62–0.96; p = 0.022), respectively. AGT-rs699 and FTO-rs17817449 variants were significantly and directly associated with body mass index (BMI) (p = 0.036 and p = 0.031), while IRS2-rs1805097 and UCP3-rs1800849 were significantly and negatively associated with BMI and waist circumference, correspondingly. Each additional effect allele in GRS was associated with an increase of 0.020 log(BMI) (p = 0.004). No effects from the socioeconomic and perinatal factors evaluated on the association of the candidate genes with the phenotypes were detected. Conclusions Our observation suggests that AGT-rs699 and FTO-rs17817449 variants may contribute to the risk development of excess weight and an increase in the BMI, while IRS2-rs1805097 showed a protector effect; in addition, UCP3- rs1800849 showed a decreasing waist circumference. Socioeconomic and perinatal factors had no effect on the associations of the candidate gene. Electronic supplementary material The online version of this article (doi:10.1186/s12263-017-0567-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Angélica María Muñoz
- Research Group on Food and Human Nutrition, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellin, Colombia
| | - Claudia María Velásquez
- Research Group on Food and Human Nutrition, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellin, Colombia.,Sede de Investigación Universitaria (SIU), Universidad de Antioquia (UdeA), Calle 62 No. 52-59, Laboratorio 413, Medellin, Colombia
| | - Gloria María Agudelo
- Research Group on Food and Human Nutrition, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellin, Colombia.,Vidarium Research Group, Nutrition, Health and Wellness Research Center, Nutresa Business Group (Grupo Empresarial Nutresa), Calle 8 Sur No. 50-67, Medellin, Colombia
| | | | - Alejandro Estrada
- Research Group on Demography and Health, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellin, Colombia
| | - Fredy Alonso Patiño
- Research Group of Sciences Applied to Physical Activity and Sports, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellin, Colombia
| | - Beatriz Elena Parra
- Research Group on Food and Human Nutrition, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellin, Colombia
| | - María Victoria Parra
- Molecular Genetics Group, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellin, Colombia
| | - Gabriel Bedoya
- Molecular Genetics Group, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellin, Colombia
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Effect of dietary consumption as a modifier on the association between FTO gene variants and excess body weight in children from an admixed population in Brazil: the Social Changes, Asthma and Allergy in Latin America (SCAALA) cohort study. Br J Nutr 2017; 117:1503-1510. [PMID: 28659218 DOI: 10.1017/s0007114517001386] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Previous studies have shown associations of variants of the FTO gene with body weight, but none of these have involved Latin American populations with a high level of miscegenation, as is seen in the north-eastern Brazilian population. This study evaluated the association between SNP in the FTO gene and excess weight in Salvador, Bahia, Brazil. In addition, the effect of diet as a modifier on this association was also investigated. This cross-sectional study included 1191 participants aged 4-11 years, who were genotyped for 400 variants of the FTO gene. Direct anthropometric measures were made and dietary data were obtained by 24-h food recall. Multivariate logistic regression analyses were used to assess the associations of interest. Overall, 11·2 % of the individuals included in the study were overweight/obese. Interactions were identified between the percentage energy intake from proteins and obesity risk linked to the rs62048379 SNP (P interaction=0·01) and also between fat intake (PUFA:SFA ratio) and obesity risk linked to the rs62048379 SNP (P interaction=0·01). The T allele for the variant rs62048379 was positively associated with overweight/obesity in individuals whose percentage energy intake from protein was above the median (OR 2·00; 95 % CI 1·05, 3·82). The rs62048379 SNP was also associated with overweight/obesity in individuals whose PUFA:SFA ratio was below the median (OR 1·63; 95 % CI 1·05, 2·55). The association between FTO gene variants and excess body weight can be modulated by dietary characteristics, particularly by fatty acid distribution and dietary protein intake in children.
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Raatz SK, Conrad Z, Johnson LK, Picklo MJ, Jahns L. Relationship of the Reported Intakes of Fat and Fatty Acids to Body Weight in US Adults. Nutrients 2017; 9:nu9050438. [PMID: 28452961 PMCID: PMC5452168 DOI: 10.3390/nu9050438] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Revised: 04/10/2017] [Accepted: 04/19/2017] [Indexed: 01/09/2023] Open
Abstract
Dietary fat composition may modulate energy expenditure and body weight. Little is known about the relationship between fatty acid intake and body weight at a population level. The purposes of this study were to compare intakes of energy, macronutrients, and individual fatty acids across BMI categories (1) for the US adult population and, (2) by sociodemographic groups. Reported dietary intake data from the National Health and Nutrition Examination Survey (NHANES) and What We Eat in America (WWEIA) surveys in the years 2005-2012 were analyzed. Overall, we found that the reported intake of carbohydrate, protein, total fat, total saturated fat (as well as long-chain saturated fatty acids 14:0-18:0), and monounsaturated fatty acids (MUFAs) were positively associated with BMI; while lauric acid (a medium-chain saturated fatty acid, 12:0) and total polyunsaturated fatty acids (PUFAs) (as well as all individual PUFAs) were not associated with BMI. Non-Hispanic black individuals demonstrated a negative association between BMI and energy intake and a positive association between total PUFAs, linoleic acid (LA), α-linolenic acid (ALA) and BMI. Individuals with less than a high school education showed a negative association between BMI and DHA. Mexican-Americans reported intakes with no association between BMI and energy, any macronutrient, or individual fatty acids. These findings support those of experimental studies demonstrating fatty acid-dependent associations between dietary fatty acid composition and body weight. Notably, we observed divergent results for some sociodemographic groups which warrant further investigation.
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Affiliation(s)
- Susan K Raatz
- Grand Forks Human Nutrition Research Center, USDA-ARS, Grand Forks, ND 58203, USA.
- Food Science and Nutrition, University of Minnesota, Saint Paul, MN 55108, USA.
| | - Zach Conrad
- Grand Forks Human Nutrition Research Center, USDA-ARS, Grand Forks, ND 58203, USA.
| | - LuAnn K Johnson
- Grand Forks Human Nutrition Research Center, USDA-ARS, Grand Forks, ND 58203, USA.
| | - Matthew J Picklo
- Grand Forks Human Nutrition Research Center, USDA-ARS, Grand Forks, ND 58203, USA.
| | - Lisa Jahns
- Grand Forks Human Nutrition Research Center, USDA-ARS, Grand Forks, ND 58203, USA.
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Corella D, Coltell O, Mattingley G, Sorlí JV, Ordovas JM. Utilizing nutritional genomics to tailor diets for the prevention of cardiovascular disease: a guide for upcoming studies and implementations. Expert Rev Mol Diagn 2017; 17:495-513. [PMID: 28337931 DOI: 10.1080/14737159.2017.1311208] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Personalized diets based on an individual's genome to optimize the success of dietary intervention and reduce genetic cardiovascular disease (CVD) risk, is one of the challenges most frequently discussed in the scientific community. Areas covered: The authors gathered literature-based evidence on nutritional genomics and CVD phenotypes, our own results and research experience to provide a critical overview of the current situation of using nutritional genomics to tailor diets for CVD prevention and to propose guidelines for future studies and implementations. Expert commentary: Hundreds of studies on gene-diet interactions determining CVD intermediate (plasma lipids, hypertension, etc.) and final phenotypes (stroke, etc.) have furnished top-level scientific evidence for claiming that the genetic effect in cardiovascular risk is not deterministic, but can be modified by diet. However, despite the many results obtained, there are still gaps in practically applying a personalized diet design to specific genotypes. Hence, a better systemization and methodological improvement of new studies is required to obtain top-level evidence that will allow their application in the future precision nutrition/medicine. The authors propose several recommendations for tackling new approaches and applications.
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Affiliation(s)
- Dolores Corella
- a Department of Preventive Medicine and Public Health, School of Medicine , University of Valencia , Valencia , Spain.,b CIBER Fisiopatología de la Obesidad y Nutrición , Instituto de Salud Carlos III , Madrid , Spain
| | - Oscar Coltell
- b CIBER Fisiopatología de la Obesidad y Nutrición , Instituto de Salud Carlos III , Madrid , Spain.,c Department of Computer Languages and Systems, School of Technology and Experimental Sciences , Universitat Jaume I , Castellón , Spain
| | - George Mattingley
- a Department of Preventive Medicine and Public Health, School of Medicine , University of Valencia , Valencia , Spain
| | - José V Sorlí
- a Department of Preventive Medicine and Public Health, School of Medicine , University of Valencia , Valencia , Spain.,b CIBER Fisiopatología de la Obesidad y Nutrición , Instituto de Salud Carlos III , Madrid , Spain
| | - Jose M Ordovas
- d Nutrition and Genomics Laboratory , JM-USDA Human Nutrition Research Center on Aging at Tufts University , Boston , MA , USA
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Graff M, Scott RA, Justice AE, Young KL, Feitosa MF, Barata L, Winkler TW, Chu AY, Mahajan A, Hadley D, Xue L, Workalemahu T, Heard-Costa NL, den Hoed M, Ahluwalia TS, Qi Q, Ngwa JS, Renström F, Quaye L, Eicher JD, Hayes JE, Cornelis M, Kutalik Z, Lim E, Luan J, Huffman JE, Zhang W, Zhao W, Griffin PJ, Haller T, Ahmad S, Marques-Vidal PM, Bien S, Yengo L, Teumer A, Smith AV, Kumari M, Harder MN, Justesen JM, Kleber ME, Hollensted M, Lohman K, Rivera NV, Whitfield JB, Zhao JH, Stringham HM, Lyytikäinen LP, Huppertz C, Willemsen G, Peyrot WJ, Wu Y, Kristiansson K, Demirkan A, Fornage M, Hassinen M, Bielak LF, Cadby G, Tanaka T, Mägi R, van der Most PJ, Jackson AU, Bragg-Gresham JL, Vitart V, Marten J, Navarro P, Bellis C, Pasko D, Johansson Å, Snitker S, Cheng YC, Eriksson J, Lim U, Aadahl M, Adair LS, Amin N, Balkau B, Auvinen J, Beilby J, Bergman RN, Bergmann S, Bertoni AG, Blangero J, Bonnefond A, Bonnycastle LL, Borja JB, Brage S, Busonero F, Buyske S, Campbell H, Chines PS, Collins FS, Corre T, Smith GD, Delgado GE, Dueker N, Dörr M, Ebeling T, Eiriksdottir G, Esko T, Faul JD, Fu M, Færch K, Gieger C, Gläser S, Gong J, Gordon-Larsen P, Grallert H, Grammer TB, Grarup N, van Grootheest G, Harald K, Hastie ND, Havulinna AS, Hernandez D, Hindorff L, Hocking LJ, Holmens OL, Holzapfel C, Hottenga JJ, Huang J, Huang T, Hui J, Huth C, Hutri-Kähönen N, James AL, Jansson JO, Jhun MA, Juonala M, Kinnunen L, Koistinen HA, Kolcic I, Komulainen P, Kuusisto J, Kvaløy K, Kähönen M, Lakka TA, Launer LJ, Lehne B, Lindgren CM, Lorentzon M, Luben R, Marre M, Milaneschi Y, Monda KL, Montgomery GW, De Moor MHM, Mulas A, Müller-Nurasyid M, Musk AW, Männikkö R, Männistö S, Narisu N, Nauck M, Nettleton JA, Nolte IM, Oldehinkel AJ, Olden M, Ong KK, Padmanabhan S, Paternoster L, Perez J, Perola M, Peters A, Peters U, Peyser PA, Prokopenko I, Puolijoki H, Raitakari OT, Rankinen T, Rasmussen-Torvik LJ, Rawal R, Ridker PM, Rose LM, Rudan I, Sarti C, Sarzynski MA, Savonen K, Scott WR, Sanna S, Shuldiner AR, Sidney S, Silbernagel G, Smith BH, Smith JA, Snieder H, Stančáková A, Sternfeld B, Swift AJ, Tammelin T, Tan ST, Thorand B, Thuillier D, Vandenput L, Vestergaard H, van Vliet-Ostaptchouk JV, Vohl MC, Völker U, Waeber G, Walker M, Wild S, Wong A, Wright AF, Zillikens MC, Zubair N, Haiman CA, Lemarchand L, Gyllensten U, Ohlsson C, Hofman A, Rivadeneira F, Uitterlinden AG, Pérusse L, Wilson JF, Hayward C, Polasek O, Cucca F, Hveem K, Hartman CA, Tönjes A, Bandinelli S, Palmer LJ, Kardia SLR, Rauramaa R, Sørensen TIA, Tuomilehto J, Salomaa V, Penninx BWJH, de Geus EJC, Boomsma DI, Lehtimäki T, Mangino M, Laakso M, Bouchard C, Martin NG, Kuh D, Liu Y, Linneberg A, März W, Strauch K, Kivimäki M, Harris TB, Gudnason V, Völzke H, Qi L, Järvelin MR, Chambers JC, Kooner JS, Froguel P, Kooperberg C, Vollenweider P, Hallmans G, Hansen T, Pedersen O, Metspalu A, Wareham NJ, Langenberg C, Weir DR, Porteous DJ, Boerwinkle E, Chasman DI, Abecasis GR, Barroso I, McCarthy MI, Frayling TM, O’Connell JR, van Duijn CM, Boehnke M, Heid IM, Mohlke KL, Strachan DP, Fox CS, Liu CT, Hirschhorn JN, Klein RJ, Johnson AD, Borecki IB, Franks PW, North KE, Cupples LA, Loos RJF, Kilpeläinen TO. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults. PLoS Genet 2017; 13:e1006528. [PMID: 28448500 PMCID: PMC5407576 DOI: 10.1371/journal.pgen.1006528] [Citation(s) in RCA: 119] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 12/07/2016] [Indexed: 11/23/2022] Open
Abstract
Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
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Affiliation(s)
- Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Robert A. Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Anne E. Justice
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kristin L. Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Mary F. Feitosa
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Llilda Barata
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Audrey Y. Chu
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - David Hadley
- Division of Population Health Sciences and Education, St. George's, University of London, London, United Kingdom
| | - Luting Xue
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Tsegaselassie Workalemahu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Nancy L. Heard-Costa
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | - Marcel den Hoed
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Tarunveer S. Ahluwalia
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Julius S. Ngwa
- Howard University, Department of Internal Medicine, Washington DC, United States of America
| | - Frida Renström
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Department of Biobank Research, Umeå University, Umeå, Sweden
| | - Lydia Quaye
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - John D. Eicher
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - James E. Hayes
- Cell and Developmental Biology Graduate Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, New York, United States of America
- Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Marilyn Cornelis
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Zoltan Kutalik
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Elise Lim
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Jian’an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Jennifer E. Huffman
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Paula J. Griffin
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Shafqat Ahmad
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
| | - Pedro M. Marques-Vidal
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Stephanie Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Loic Yengo
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Albert Vernon Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Meena Kumari
- ISER, University of Essex, Colchester, Essex, United Kingdom
| | - Marie Neergaard Harder
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Johanne Marie Justesen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marcus E. Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Nutrition, Friedrich Schiller University Jena, Jena, Germany
| | - Mette Hollensted
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kurt Lohman
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Natalia V. Rivera
- Karolinska Institutet, Respiratory Unit, Department of Medicine Solna, Stockholm, Sweden
| | - John B. Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Heather M. Stringham
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland
| | - Charlotte Huppertz
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
- Department of Public and Occupational Health, VU University Medical Center, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
| | - Wouter J. Peyrot
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Kati Kristiansson
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Ayse Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Maija Hassinen
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Gemma Cadby
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Western Australia, Australia
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Peter J. van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anne U. Jackson
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Jennifer L. Bragg-Gresham
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jonathan Marten
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Claire Bellis
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research of Singapore, Singapore
- Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Dorota Pasko
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Søren Snitker
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Yu-Ching Cheng
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Veterans Affairs Maryland Health Care System, University of Maryland, Baltimore, Maryland, United States of America
| | - Joel Eriksson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Unhee Lim
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Mette Aadahl
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Linda S. Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Beverley Balkau
- INSERM U-1018, CESP, Renal and Cardiovascular Epidemiology, UVSQ-UPS, Villejuif, France
| | - Juha Auvinen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - John Beilby
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Pathology and Laboratory Medicine, The University of Western Australia, Crawley, Western Australia, Australia
| | - Richard N. Bergman
- Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Sven Bergmann
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - Alain G. Bertoni
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - John Blangero
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Amélie Bonnefond
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
| | - Lori L. Bonnycastle
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Judith B. Borja
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines
- Department of Nutrition and Dietetics, University of San Carlos, Cebu City, Philippines
| | - Søren Brage
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Fabio Busonero
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
| | - Steve Buyske
- Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America
- Department of Statistics and Biostatistics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
| | - Peter S. Chines
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Francis S. Collins
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Tanguy Corre
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
| | - George Davey Smith
- MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Graciela E. Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Nicole Dueker
- University of Maryland School of Medicine, Department of Epidemiology & Public Health, Baltimore, Maryland, United States of America
| | - Marcus Dörr
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Tapani Ebeling
- Department of Medicine, Oulu University Hospital, Oulu, Finland
- Institute of Clinical Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
| | | | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Division of Endocrinology, Boston Children's Hospital, Boston, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Mao Fu
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | | | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Sven Gläser
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Jian Gong
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Penny Gordon-Larsen
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Tanja B. Grammer
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gerard van Grootheest
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Kennet Harald
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Nicholas D. Hastie
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Aki S. Havulinna
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Dena Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Lucia Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Lynne J. Hocking
- Musculoskeletal Research Programme, Division of Applied Medicine, University of Aberdeen, Foresterhill, Aberdeen, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Christina Holzapfel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Nutritional Medicine, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- NCA Institute, VU University & VU Medical Center, Amsterdam, The Netherlands
| | - Jie Huang
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Tao Huang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Jennie Hui
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia
| | - Cornelia Huth
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Nina Hutri-Kähönen
- Department of Pediatrics, Tampere University Hospital, Tampere, Finland
- Department of Pediatrics, University of Tampere School of Medicine, Tampere, Finland
| | - Alan L. James
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
| | - John-Olov Jansson
- Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Min A. Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Markus Juonala
- Department of Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | - Leena Kinnunen
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Heikki A. Koistinen
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Department of Medicine and Abdominal Center: Endocrinology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Ivana Kolcic
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | | | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kirsti Kvaløy
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Department of Clinical Physiology, University of Tampere School of Medicine, Tampere, Finland
| | - Timo A. Lakka
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio Campus, Finland
| | - Lenore J. Launer
- Neuroepidemiology Section, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Cecilia M. Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- The Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Mattias Lorentzon
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Geriatric Medicine, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Robert Luben
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Michel Marre
- INSERM U-1138, Équipe 2: Pathophysiology and Therapeutics of Vascular and Renal diseases Related to Diabetes, Centre de Recherche des Cordeliers, Paris, France
- Department of Endocrinology, Diabetology, Nutrition, and Metabolic Diseases, Bichat Claude Bernard Hospital, Paris, France
| | - Yuri Milaneschi
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Keri L. Monda
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Center for Observational Research, Amgen Inc., Thousand Oaks, California, United States of America
| | - Grant W. Montgomery
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Marleen H. M. De Moor
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
- Section of Clinical Child and Family Studies, Department of Educational and Family Studies, Vrije Universiteit, Amsterdam, The Netherlands
| | - Antonella Mulas
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
- Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Department of Medicine I, Ludwig-Maximilians-Universität, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - A. W. Musk
- Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia
- School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
| | - Reija Männikkö
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Satu Männistö
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Narisu Narisu
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Jennifer A. Nettleton
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Ilja M. Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Albertine J. Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Matthias Olden
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Ken K. Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Sandosh Padmanabhan
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Institute of Cardiovascular and Medical Sciences, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Jeremiah Perez
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Markus Perola
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- University of Tartu, Estonian Genome Centre, Tartu, Estonia
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Inga Prokopenko
- Genomics of Common Disease, Imperial College London, London, United Kingdom
| | | | - Olli T. Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Rajesh Rawal
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lynda M. Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
| | - Cinzia Sarti
- Social Services and Health Care Department, City of Helsinki, Helsinki, Finland
| | - Mark A. Sarzynski
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Kai Savonen
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - William R. Scott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Serena Sanna
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
| | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Veterans Affairs Maryland Health Care System, University of Maryland, Baltimore, Maryland, United States of America
| | - Steve Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Günther Silbernagel
- Division of Angiology, Department of Internal Medicine, Medical University Graz, Austria
| | - Blair H. Smith
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Alena Stančáková
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Barbara Sternfeld
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Amy J. Swift
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America
| | - Tuija Tammelin
- LIKES Research Center for Sport and Health Sciences, Jyväskylä, Finland
| | - Sian-Tsung Tan
- National Heart and Lung Institute, Imperial College London, United Kingdom
| | - Barbara Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Dorothée Thuillier
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
| | - Liesbeth Vandenput
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Vestergaard
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Jana V. van Vliet-Ostaptchouk
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Marie-Claude Vohl
- Institute of Nutrition and Functional Foods, Quebec, Canada
- School of Nutrition, Laval University, Quebec, Canada
| | - Uwe Völker
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Germany
| | - Gérard Waeber
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Mark Walker
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Sarah Wild
- Centre for Population Health Sciences, Usher Institute for Population Health Sciences and Informatics, Teviot Place, Edinburgh, Scotland
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Alan F. Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | | | - Niha Zubair
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Christopher A. Haiman
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Loic Lemarchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands
| | - André G. Uitterlinden
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Louis Pérusse
- Institute of Nutrition and Functional Foods, Quebec, Canada
- Department of Kinesiology, Laval University, Quebec, Canada
| | - James F. Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Ozren Polasek
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy
- Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy
| | - Kristian Hveem
- HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway
| | - Catharina A. Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anke Tönjes
- University of Leipzig, Medical Department, Leipzig, Germany
| | | | - Lyle J. Palmer
- School of Public Health, University of Adelaide, Adelaide, South Australia, Australia
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Thorkild I. A. Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
- Department of Clinical Epidemiology, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, Denmark
| | - Jaakko Tuomilehto
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
- Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Veikko Salomaa
- National Institute for Health and Welfare, Department of Health, Helsinki, Finland
| | - Brenda W. J. H. Penninx
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- NCA Institute, VU University & VU Medical Center, Amsterdam, The Netherlands
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
- National Institute for Health Research Biomedical Research Centre at Guy's and St. Thomas' Foundation Trust, London, United Kingdom
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Allan Linneberg
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
- Department of Clinical Experimental Research, Rigshospitalet, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Synlab Academy, Synlab Services LLC, Mannheim, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Tamara B. Harris
- Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Lu Qi
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - John C. Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Jaspal S. Kooner
- Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom
- National Heart and Lung Institute, Imperial College London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Philippe Froguel
- University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France
- Hammersmith Hospital, London, United Kingdom
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Peter Vollenweider
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Göran Hallmans
- Department of Biobank Research, Umeå University, Umeå, Sweden
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - David J. Porteous
- Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Eric Boerwinkle
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | | | | | | | - Gonçalo R. Abecasis
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Inês Barroso
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- NIHR Cambridge Biomedical Research Centre, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, United Kingdom
- The University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, United Kingdom
| | - Mark I. McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Oxford, United Kingdom
| | - Timothy M. Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Jeffrey R. O’Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands
- Center of Medical Systems Biology, Leiden, The Netherlands
| | - Michael Boehnke
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Iris M. Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - David P. Strachan
- Population Health Research Institute, St. George's University of London, London, United Kingdom
| | - Caroline S. Fox
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Joel N. Hirschhorn
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
- Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts, United States of America
| | - Robert J. Klein
- Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Andrew D. Johnson
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Ingrid B. Borecki
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Paul W. Franks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden
- Department of Public Health & Clinical Medicine, Umeå University, Umeå, Sweden
| | - Kari E. North
- Carolina Center for Genome Sciences, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - L. Adrienne Cupples
- National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Ruth J. F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Genetics of Obesity and Related Metabolic Traits Program, Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
- The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Tuomas O. Kilpeläinen
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
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Abstract
AbstractBody mass and fat intake are multifactorial traits that have genetic and environmental components. The gene with the greatest effect on body mass is FTO (fat mass and obesity-associated), but several studies have shown that the effect of FTO (and of other genes) on body mass can be modified by the intake of nutrients. The so-called gene–environment interactions may also be important for the effectiveness of weight-loss strategies. Food choices, and thus fat intake, depend to some extent on individual preferences. The most important biological component of food preference is taste, and the role of fat sensitivity in fat intake has recently been pointed out. Relatively few studies have analysed the genetic components of fat intake or fatty acid sensitivity in terms of their relation to obesity. It has been proposed that decreased oral fatty acid sensitivity leads to increased fat intake and thus increased body mass. One of the genes that affect fatty acid sensitivity is CD36 (cluster of differentiation 36). However, little is known so far about the genetic component of fat sensing. We performed a literature review to identify the state of knowledge regarding the genetics of fat intake and its relation to body-mass determination, and to identify the priorities for further investigations.
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Heffernan SM, Stebbings GK, Kilduff LP, Erskine RM, Day SH, Morse CI, McPhee JS, Cook CJ, Vance B, Ribbans WJ, Raleigh SM, Roberts C, Bennett MA, Wang G, Collins M, Pitsiladis YP, Williams AG. Fat mass and obesity associated (FTO) gene influences skeletal muscle phenotypes in non-resistance trained males and elite rugby playing position. BMC Genet 2017; 18:4. [PMID: 28103813 PMCID: PMC5248469 DOI: 10.1186/s12863-017-0470-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 01/10/2017] [Indexed: 11/25/2022] Open
Abstract
Background FTO gene variants have been associated with obesity phenotypes in sedentary and obese populations, but rarely with skeletal muscle and elite athlete phenotypes. Methods In 1089 participants, comprising 530 elite rugby athletes and 559 non-athletes, DNA was collected and genotyped for the FTO rs9939609 variant using real-time PCR. In a subgroup of non-resistance trained individuals (NT; n = 120), we also assessed structural and functional skeletal muscle phenotypes using dual energy x-ray absorptiometry, ultrasound and isokinetic dynamometry. In a subgroup of rugby athletes (n = 77), we assessed muscle power during a countermovement jump. Results In NT, TT genotype and T allele carriers had greater total body (4.8% and 4.1%) and total appendicular lean mass (LM; 3.0% and 2.1%) compared to AA genotype, with greater arm LM (0.8%) in T allele carriers and leg LM (2.1%) for TT, compared to AA genotype. Furthermore, the T allele was more common (94%) in selected elite rugby union athletes (back three and centre players) who are most reliant on LM rather than total body mass for success, compared to other rugby athletes (82%; P = 0.01, OR = 3.34) and controls (84%; P = 0.03, OR = 2.88). Accordingly, these athletes had greater peak power relative to body mass than other rugby athletes (14%; P = 2 x 10-6). Conclusion Collectively, these results suggest that the T allele is associated with increased LM and elite athletic success. This has implications for athletic populations, as well as conditions characterised by low LM such as sarcopenia and cachexia.
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Affiliation(s)
- S M Heffernan
- MMU Sports Genomics Laboratory, Manchester Metropolitan University, Crewe Green Road, Crewe, CW1 5DU, UK.
| | - G K Stebbings
- MMU Sports Genomics Laboratory, Manchester Metropolitan University, Crewe Green Road, Crewe, CW1 5DU, UK
| | - L P Kilduff
- A-STEM, College of Engineering, Swansea University, Swansea, UK
| | - R M Erskine
- Research Institute for Sport & Exercise Sciences, Liverpool John Moores University, Liverpool, UK.,Institute of Sport, Exercise and Health, University College London, London, UK
| | - S H Day
- MMU Sports Genomics Laboratory, Manchester Metropolitan University, Crewe Green Road, Crewe, CW1 5DU, UK
| | - C I Morse
- MMU Sports Genomics Laboratory, Manchester Metropolitan University, Crewe Green Road, Crewe, CW1 5DU, UK
| | - J S McPhee
- School of Healthcare Science, Manchester Metropolitan University, Manchester, UK
| | - C J Cook
- A-STEM, College of Engineering, Swansea University, Swansea, UK.,School of Sport, Health and Exercise Sciences, Bangor University, Bangor, UK
| | - B Vance
- Institute of Cardiovascular & Medical Sciences University of Glasgow, Glasgow, UK
| | - W J Ribbans
- Centre for Physical Activity and Chronic Disease, Institute of Health and Wellbeing, University of Northampton, Northampton, UK
| | - S M Raleigh
- Centre for Physical Activity and Chronic Disease, Institute of Health and Wellbeing, University of Northampton, Northampton, UK
| | - C Roberts
- Medical and Scientific Department, South African Rugby Union, Cape Town, South Africa.,Discipline of Sports Science, Faculty of Health Sciences, University of Kwazulu-Natal, Durban, South Africa
| | - M A Bennett
- A-STEM, College of Engineering, Swansea University, Swansea, UK
| | - G Wang
- FIMS Reference Collaborating Centre of Sports Medicine for Anti-Doping Research, University of Brighton, Brighton, UK
| | - M Collins
- Division of Exercise Science and Sports Medicine, Department of Human Biology, University of Cape Town (UCT), Cape Town, South Africa
| | - Y P Pitsiladis
- FIMS Reference Collaborating Centre of Sports Medicine for Anti-Doping Research, University of Brighton, Brighton, UK
| | - A G Williams
- MMU Sports Genomics Laboratory, Manchester Metropolitan University, Crewe Green Road, Crewe, CW1 5DU, UK.,Institute of Sport, Exercise and Health, University College London, London, UK
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Riscuta G. Nutrigenomics at the Interface of Aging, Lifespan, and Cancer Prevention. J Nutr 2016; 146:1931-1939. [PMID: 27558581 PMCID: PMC5037878 DOI: 10.3945/jn.116.235119] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Accepted: 07/14/2016] [Indexed: 01/21/2023] Open
Abstract
The percentage of elderly people with associated age-related health deterioration, including cancer, has been increasing for decades. Among age-related diseases, the incidence of cancer has grown substantially, in part because of the overlap of some molecular pathways between cancer and aging. Studies with model organisms suggest that aging and age-related conditions are manipulable processes that can be modified by both genetic and environmental factors, including dietary habits. Variations in genetic backgrounds likely lead to differential responses to dietary changes and account for some of the inconsistencies found in the literature. The intricacies of the aging process, coupled with the interrelational role of bioactive food components on gene expression, make this review a complex undertaking. Nevertheless, intriguing evidence suggests that dietary habits can manipulate the aging process and/or its consequences and potentially may have unprecedented health benefits. The present review focuses on 4 cellular events: telomerase activity, bioenergetics, DNA repair, and oxidative stress. These processes are linked to both aging and cancer risk, and their alteration in animal models by selected food components is evident.
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Affiliation(s)
- Gabriela Riscuta
- Nutritional Science Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD
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45
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Nicoletti CF, Kimura BM, de Oliveira BAP, de Pinhel MAS, Salgado W, Marchini JS, Nonino CB. Role of UCP2 polymorphisms on dietary intake of obese patients who underwent bariatric surgery. Clin Obes 2016; 6:354-8. [PMID: 27256164 DOI: 10.1111/cob.12148] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Revised: 04/05/2016] [Accepted: 04/12/2016] [Indexed: 12/26/2022]
Abstract
Uncoupling protein 2 ( UCP2 ) plays an important role in body weight and energy metabolism and may be related to the control of food consumption. This study aimed to investigate the contribution of UCP2 gene variants on the dietary intake on a population after bariatric surgery. This study enrolled 150 obese patients (body mass index ≥ 35kg m(-2) ) who submitted to Roux-en-Y gastric bypass. Weight (kg), BMI (kg m(-2) ), energy (kcal d(-1) ) and macronutrients intake (g d(-1) ) of preoperative and 1-year postoperative period were collected from medical records. Ala55Val and -866G>A polymorphisms in the UCP2 gene were genotyped through allelic discrimination method in real-time polymerase chain reaction using the TaqMan pre-designed SNP Genotyping Assays kits. Hardy-Weinberg equilibrium, t-test and regression models were performed in statistical analysis (P<0.05).We found an allelic frequency of 0.44 for allele Val and 0.41 for allele A. In the postoperative period, patients with at least one rare allele for polymorphisms and with at least one rare allele for both polymorphisms together (haplotype) present a greater energy and carbohydrate intake, even after adjusting for gender, age and weight. Genetic variants in UCP2 gene were associated with the dietary consumption after Roux-En-Y gastric bypass.
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Affiliation(s)
- C F Nicoletti
- Department of Internal Medicine, Faculty of Medicine of Ribeirao Preto, University of São Paulo, RibeirãoPreto, Brazil
| | - B M Kimura
- Department of Internal Medicine, Faculty of Medicine of Ribeirao Preto, University of São Paulo, RibeirãoPreto, Brazil
| | - B A P de Oliveira
- Department of Internal Medicine, Faculty of Medicine of Ribeirao Preto, University of São Paulo, RibeirãoPreto, Brazil
| | - M A S de Pinhel
- Department of Internal Medicine, Faculty of Medicine of Ribeirao Preto, University of São Paulo, RibeirãoPreto, Brazil
| | - W Salgado
- Department of Surgery and Anatomy, Faculty of Medicine of Ribeirao Preto, University of São Paulo, RibeirãoPreto, Brazil
| | - J S Marchini
- Department of Internal Medicine, Faculty of Medicine of Ribeirao Preto, University of São Paulo, RibeirãoPreto, Brazil
| | - C B Nonino
- Department of Internal Medicine, Faculty of Medicine of Ribeirao Preto, University of São Paulo, RibeirãoPreto, Brazil.
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Multiple novel gene-by-environment interactions modify the effect of FTO variants on body mass index. Nat Commun 2016; 7:12724. [PMID: 27596730 PMCID: PMC5025863 DOI: 10.1038/ncomms12724] [Citation(s) in RCA: 97] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2015] [Accepted: 07/28/2016] [Indexed: 01/14/2023] Open
Abstract
Genetic studies have shown that obesity risk is heritable and that, of the many common variants now associated with body mass index, those in an intron of the fat mass and obesity-associated (FTO) gene have the largest effect. The size of the UK Biobank, and its joint measurement of genetic, anthropometric and lifestyle variables, offers an unprecedented opportunity to assess gene-by-environment interactions in a way that accounts for the dependence between different factors. We jointly examine the evidence for interactions between FTO (rs1421085) and various lifestyle and environmental factors. We report interactions between the FTO variant and each of: frequency of alcohol consumption (P=3.0 × 10−4); deviations from mean sleep duration (P=8.0 × 10−4); overall diet (P=5.0 × 10−6), including added salt (P=1.2 × 10−3); and physical activity (P=3.1 × 10−4). Common variants in the fat mass and obesity associated (FTO) gene are linked to body mass index (BMI). Using the latest UK Biobank data, this study shows novel gene x environment interactions between FTO and lifestyle factors, including frequency of alcohol consumption, sleep, and added dietary salt.
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Vimaleswaran KS, Bodhini D, Lakshmipriya N, Ramya K, Anjana RM, Sudha V, Lovegrove JA, Kinra S, Mohan V, Radha V. Interaction between FTO gene variants and lifestyle factors on metabolic traits in an Asian Indian population. Nutr Metab (Lond) 2016; 13:39. [PMID: 27274759 PMCID: PMC4891824 DOI: 10.1186/s12986-016-0098-6] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Accepted: 05/11/2016] [Indexed: 11/27/2022] Open
Abstract
Background Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D). Methods The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model. Results There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10−5) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction = 0.0008), where individuals with AA genotype who are in the 3rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10−5). Conclusions This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population. Electronic supplementary material The online version of this article (doi:10.1186/s12986-016-0098-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Karani S Vimaleswaran
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Reading, UK
| | - Dhanasekaran Bodhini
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
| | - N Lakshmipriya
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai, India
| | - K Ramya
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
| | - R Mohan Anjana
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India ; Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai, India ; Dr. Mohan's Diabetes Specialties Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, Chennai, India
| | - Vasudevan Sudha
- Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai, India
| | - Julie A Lovegrove
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Reading, UK
| | - Sanjay Kinra
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Viswanathan Mohan
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India ; Department of Foods, Nutrition and Dietetics Research, Madras Diabetes Research Foundation, Chennai, India ; Dr. Mohan's Diabetes Specialties Centre, WHO Collaborating Centre for Non-communicable Diseases Prevention and Control, Chennai, India
| | - Venkatesan Radha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
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48
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Increased Aβ pathology in aged Tg2576 mice born to mothers fed a high fat diet. Sci Rep 2016; 6:21981. [PMID: 26911528 PMCID: PMC4766411 DOI: 10.1038/srep21981] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Accepted: 02/03/2016] [Indexed: 01/24/2023] Open
Abstract
Maternal obesity is associated with increased risk of developing diabetes, obesity and premature death in adult offspring. Mid-life diabetes, hypertension and hypercholesterolaemia are risk factors for the development of sporadic Alzheimer’s disease (AD). A key pathogenic feature of AD is the accumulation of β-amyloid (Aβ) in the brain. The purpose of this study was to investigate the effect of high fat diet feeding during early life on Aβ pathology in the Tg2576 mouse model of AD. Female mice were fed a standard (C) or high fat (HF) diet before mating and during gestation and lactation. At weaning, male offspring were fed a C diet. Significantly higher levels of guanidine-soluble Aβ and plaque loads were observed in the hippocampi of 11-month old Tg2576 mice born to mothers fed a HF diet. Changes in the extracellular matrix led to increased retention of Aβ within the parenchyma. These data support a role for maternal and gestational health on the health of the aged brain and pathologies associated with AD and may provide a novel target for both the prevention and treatment of AD.
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Ferri E, Galimberti A, Casiraghi M, Airoldi C, Ciaramelli C, Palmioli A, Mezzasalma V, Bruni I, Labra M. Towards a Universal Approach Based on Omics Technologies for the Quality Control of Food. BIOMED RESEARCH INTERNATIONAL 2015; 2015:365794. [PMID: 26783518 PMCID: PMC4691458 DOI: 10.1155/2015/365794] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 11/19/2015] [Indexed: 12/03/2022]
Abstract
In the last decades, food science has greatly developed, turning from the consideration of food as mere source of energy to a growing awareness on its importance for health and particularly in reducing the risk of diseases. Such vision led to an increasing attention towards the origin and quality of raw materials as well as their derived food products. The continuous advance in molecular biology allowed setting up efficient and universal omics tools to unequivocally identify the origin of food items and their traceability. In this review, we considered the application of a genomics approach known as DNA barcoding in characterizing the composition of foodstuffs and its traceability along the food supply chain. Moreover, metabolomics analytical strategies based on Nuclear Magnetic Resonance (NMR) and Mass Spectroscopy (MS) were discussed as they also work well in evaluating food quality. The combination of both approaches allows us to define a sort of molecular labelling of food that is easily understandable by the operators involved in the food sector: producers, distributors, and consumers. Current technologies based on digital information systems such as web platforms and smartphone apps can facilitate the adoption of such molecular labelling.
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Affiliation(s)
- Emanuele Ferri
- FEM2 Ambiente s.r.l., P.za della Scienza 2, 20126 Milan, Italy
| | - Andrea Galimberti
- ZooPlantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, P.za della Scienza 2, 20126 Milan, Italy
| | - Maurizio Casiraghi
- ZooPlantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, P.za della Scienza 2, 20126 Milan, Italy
| | - Cristina Airoldi
- BioNMR Lab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, P.za della Scienza 2, 20126 Milan, Italy
| | - Carlotta Ciaramelli
- BioNMR Lab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, P.za della Scienza 2, 20126 Milan, Italy
| | - Alessandro Palmioli
- FEM2 Ambiente s.r.l., P.za della Scienza 2, 20126 Milan, Italy
- BioNMR Lab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, P.za della Scienza 2, 20126 Milan, Italy
| | - Valerio Mezzasalma
- ZooPlantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, P.za della Scienza 2, 20126 Milan, Italy
| | - Ilaria Bruni
- ZooPlantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, P.za della Scienza 2, 20126 Milan, Italy
| | - Massimo Labra
- ZooPlantLab, Department of Biotechnology and Biosciences, University of Milano-Bicocca, P.za della Scienza 2, 20126 Milan, Italy
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Fat mass- and obesity-associated genotype, dietary intakes and anthropometric measures in European adults: the Food4Me study. Br J Nutr 2015; 115:440-8. [PMID: 26620191 DOI: 10.1017/s0007114515004675] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The interplay between the fat mass- and obesity-associated (FTO) gene variants and diet has been implicated in the development of obesity. The aim of the present analysis was to investigate associations between FTO genotype, dietary intakes and anthropometrics among European adults. Participants in the Food4Me randomised controlled trial were genotyped for FTO genotype (rs9939609) and their dietary intakes, and diet quality scores (Healthy Eating Index and PREDIMED-based Mediterranean diet score) were estimated from FFQ. Relationships between FTO genotype, diet and anthropometrics (weight, waist circumference (WC) and BMI) were evaluated at baseline. European adults with the FTO risk genotype had greater WC (AA v. TT: +1·4 cm; P=0·003) and BMI (+0·9 kg/m2; P=0·001) than individuals with no risk alleles. Subjects with the lowest fried food consumption and two copies of the FTO risk variant had on average 1·4 kg/m2 greater BMI (Ptrend=0·028) and 3·1 cm greater WC (Ptrend=0·045) compared with individuals with no copies of the risk allele and with the lowest fried food consumption. However, there was no evidence of interactions between FTO genotype and dietary intakes on BMI and WC, and thus further research is required to confirm or refute these findings.
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