1
|
Semnani-Azad Z, Toledo E, Babio N, Ruiz-Canela M, Wittenbecher C, Razquin C, Wang F, Dennis C, Deik A, Clish CB, Corella D, Fitó M, Estruch R, Arós F, Ros E, García-Gavilan J, Liang L, Salas-Salvadó J, Martínez-González MA, Hu FB, Guasch-Ferré M. Plasma metabolite predictors of metabolic syndrome incidence and reversion. Metabolism 2024; 151:155742. [PMID: 38007148 PMCID: PMC10872312 DOI: 10.1016/j.metabol.2023.155742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 11/19/2023] [Accepted: 11/19/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND Metabolic Syndrome (MetS) is a progressive pathophysiological state defined by a cluster of cardiometabolic traits. However, little is known about metabolites that may be predictors of MetS incidence or reversion. Our objective was to identify plasma metabolites associated with MetS incidence or MetS reversion. METHODS The study included 1468 participants without cardiovascular disease (CVD) but at high CVD risk at enrollment from two case-cohort studies nested within the PREvención con DIeta MEDiterránea (PREDIMED) study with baseline metabolomics data. MetS was defined in accordance with the harmonized International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute criteria, which include meeting 3 or more thresholds for waist circumference, triglyceride, HDL cholesterol, blood pressure, and fasting blood glucose. MetS incidence was defined by not having MetS at baseline but meeting the MetS criteria at a follow-up visit. MetS reversion was defined by MetS at baseline but not meeting MetS criteria at a follow-up visit. Plasma metabolome was profiled by LC-MS. Multivariable-adjusted Cox regression models and elastic net regularized regressions were used to assess the association of 385 annotated metabolites with MetS incidence and MetS reversion after adjusting for potential risk factors. RESULTS Of the 603 participants without baseline MetS, 298 developed MetS over the median 4.8-year follow-up. Of the 865 participants with baseline MetS, 285 experienced MetS reversion. A total of 103 and 88 individual metabolites were associated with MetS incidence and MetS reversion, respectively, after adjusting for confounders and false discovery rate correction. A metabolomic signature comprised of 77 metabolites was robustly associated with MetS incidence (HR: 1.56 (95 % CI: 1.33-1.83)), and a metabolomic signature of 83 metabolites associated with MetS reversion (HR: 1.44 (95 % CI: 1.25-1.67)), both p < 0.001. The MetS incidence and reversion signatures included several lipids (mainly glycerolipids and glycerophospholipids) and branched-chain amino acids. CONCLUSION We identified unique metabolomic signatures, primarily comprised of lipids (including glycolipids and glycerophospholipids) and branched-chain amino acids robustly associated with MetS incidence; and several amino acids and glycerophospholipids associated with MetS reversion. These signatures provide novel insights on potential distinct mechanisms underlying the conditions leading to the incidence or reversion of MetS.
Collapse
Affiliation(s)
- Zhila Semnani-Azad
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Estefanía Toledo
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Nancy Babio
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere i Virgili, Hospital Universitari Sant Joan de Reus, Reus, Spain.
| | - Miguel Ruiz-Canela
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Clemens Wittenbecher
- Division of Food and Nutrition Sciences, Department of Biology, Chalmers University of Technology, Gothenburg, Sweden.
| | - Cristina Razquin
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Fenglei Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Courtney Dennis
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Amy Deik
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Clary B Clish
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Dolores Corella
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Preventive Medicine and Public Health, University of Valencia, Valencia, Spain.
| | - Montserrat Fitó
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; IMIM Hospital del Mar Medical Research Institute, Grup de Risc Cardiovascular i Nutrició, Barcelona, Spain.
| | - Ramon Estruch
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain.
| | - Fernando Arós
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, Vitoria-Gasteiz, Spain; University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain.
| | - Emilio Ros
- Lipid Clinic, Department of Endocrinology and Nutrition, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain.
| | - Jesús García-Gavilan
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain.
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Jordi Salas-Salvadó
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Reus, Spain; Institut d'Investigació Sanitària Pere i Virgili, Hospital Universitari Sant Joan de Reus, Reus, Spain.
| | - Miguel A Martínez-González
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Preventive Medicine and Public Health, University of Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Public Health and Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), University of Copenhagen, Copenhagen, Denmark.
| |
Collapse
|
2
|
Semnani-Azad Z, Wang WZN, Cole DEC, Johnston LW, Wong BYL, Fu L, Retnakaran R, Harris SB, Hanley AJ. Urinary Vitamin D Binding Protein: A Marker of Kidney Tubular Dysfunction in Patients at Risk for Type 2 Diabetes. J Endocr Soc 2024; 8:bvae014. [PMID: 38352963 PMCID: PMC10862653 DOI: 10.1210/jendso/bvae014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Indexed: 02/16/2024] Open
Abstract
Context Recent studies have reported elevated urinary vitamin D binding protein (uVDBP) concentrations in patients with diabetic kidney disease, although the utility of uVDBP to predict deterioration of kidney function over time has not been examined. Objective Our objective was to assess the association of uVDBP with longitudinal changes in kidney function. Methods Adults at-risk for type 2 diabetes from the Prospective Metabolism and Islet Cell Evaluation (PROMISE) study had 3 assessments over 6 years (n = 727). Urinary albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) were used as measures of kidney function. Measurements of uVDBP were performed with enzyme-linked immunosorbent assay and normalized to urine creatinine (uVDBP:cr). Generalized estimating equations (GEEs) evaluated longitudinal associations of uVDBP and uVDBP:cr with measures of kidney function, adjusting for covariates. Results Renal uVDBP loss increased with ACR severity at baseline. Individuals with normoalbuminuria, microalbuminuria, and macroalbuminuria had median log uVDBP:cr concentrations of 1.62 μg/mmol, 2.63 μg/mmol, and 2.48 μg/mmol, respectively, and ACR positively correlated with uVDBP concentrations (r = 0.37; P < .001). There was no significant association between uVDBP and eGFR at baseline. Adjusted longitudinal GEE models indicated that each SD increase both in baseline and longitudinal uVDBP:cr was significantly associated with higher ACR over 6 years (β = 30.67 and β = 32.91, respectively). Conversely, neither baseline nor longitudinal uVDBP:cr measures showed a significant association with changes in eGFR over time. These results suggest that loss of uVDBP:cr over time may be a useful marker for predicting renal tubular damage in individuals at risk for diabetes.
Collapse
Affiliation(s)
- Zhila Semnani-Azad
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Nutritional Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Windy Z N Wang
- Department of Nutritional Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - David E C Cole
- Department of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Pediatrics (Genetics), University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Centre, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Luke W Johnston
- Department of Public Health, Aarhus University, Aarhus 8000, Denmark
| | - Betty Y L Wong
- Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Centre, Toronto, ON M4N 3M5, Canada
| | - Lei Fu
- Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Centre, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Ravi Retnakaran
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, ON M5S 1A8, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
| | - Stewart B Harris
- Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5C1, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, ON M5S 1A8, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5S 1A8, Canada
| |
Collapse
|
3
|
Semnani-Azad Z, Gaillard R, Hughes AE, Boyle KE, Tobias DK, Perng W. Precision stratification of prognostic risk factors associated with outcomes in gestational diabetes mellitus: a systematic review. Commun Med (Lond) 2024; 4:9. [PMID: 38216688 PMCID: PMC10786838 DOI: 10.1038/s43856-023-00427-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 12/12/2023] [Indexed: 01/14/2024] Open
Abstract
BACKGROUND The objective of this systematic review is to identify prognostic factors among women and their offspring affected by gestational diabetes mellitus (GDM), focusing on endpoints of cardiovascular disease (CVD) and type 2 diabetes (T2D) for women, and cardiometabolic profile for offspring. METHODS This review included studies published in English language from January 1st, 1990, through September 30th, 2021, that focused on the above outcomes of interest with respect to sociodemographic factors, lifestyle and behavioral characteristics, traditional clinical traits, and 'omics biomarkers in the mothers and offspring during the perinatal/postpartum periods and across the lifecourse. Studies that did not report associations of prognostic factors with outcomes of interest among GDM-exposed women or children were excluded. RESULTS Here, we identified 109 publications comprising 98 observational studies and 11 randomized-controlled trials. Findings indicate that GDM severity, maternal obesity, race/ethnicity, and unhealthy diet and physical activity levels predict T2D and CVD in women, and greater cardiometabolic risk in offspring. However, using the Diabetes Canada 2018 Clinical Practice Guidelines for studies, the level of evidence was low due to potential for confounding, reverse causation, and selection biases. CONCLUSIONS GDM pregnancies with greater severity, as well as those accompanied by maternal obesity, unhealthy diet, and low physical activity, as well as cases that occur among women who identify as racial/ethnic minorities are associated with worse cardiometabolic prognosis in mothers and offspring. However, given the low quality of evidence, prospective studies with detailed covariate data collection and high fidelity of follow-up are warranted.
Collapse
Affiliation(s)
- Zhila Semnani-Azad
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Romy Gaillard
- Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Alice E Hughes
- Faculty of Health and Life Sciences, University of Exeter Medical School, Exeter, UK
| | - Kristen E Boyle
- Department of Pediatrics and the Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Deirdre K Tobias
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Wei Perng
- Department of Epidemiology and the Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| |
Collapse
|
4
|
García-Gavilán JF, Babio N, Toledo E, Semnani-Azad Z, Razquin C, Dennis C, Deik A, Corella D, Estruch R, Ros E, Fitó M, Arós F, Fiol M, Lapetra J, Lamuela-Raventos R, Clish C, Ruiz-Canela M, Martínez-González MÁ, Hu F, Salas-Salvadó J, Guasch-Ferré M. Olive oil consumption, plasma metabolites, and risk of type 2 diabetes and cardiovascular disease. Cardiovasc Diabetol 2023; 22:340. [PMID: 38093289 PMCID: PMC10720204 DOI: 10.1186/s12933-023-02066-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 11/14/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Olive oil consumption has been inversely associated with the risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). However, the impact of olive oil consumption on plasma metabolites remains poorly understood. This study aims to identify plasma metabolites related to total and specific types of olive oil consumption, and to assess the prospective associations of the identified multi-metabolite profiles with the risk of T2D and CVD. METHODS The discovery population included 1837 participants at high cardiovascular risk from the PREvención con DIeta MEDiterránea (PREDIMED) trial with available metabolomics data at baseline. Olive oil consumption was determined through food-frequency questionnaires (FFQ) and adjusted for total energy. A total of 1522 participants also had available metabolomics data at year 1 and were used as the internal validation sample. Plasma metabolomics analyses were performed using LC-MS. Cross-sectional associations between 385 known candidate metabolites and olive oil consumption were assessed using elastic net regression analysis. A 10-cross-validation (CV) procedure was used, and Pearson correlation coefficients were assessed between metabolite-weighted models and FFQ-derived olive oil consumption in each pair of training-validation data sets within the discovery sample. We further estimated the prospective associations of the identified plasma multi-metabolite profile with incident T2D and CVD using multivariable Cox regression models. RESULTS We identified a metabolomic signature for the consumption of total olive oil (with 74 metabolites), VOO (with 78 metabolites), and COO (with 17 metabolites), including several lipids, acylcarnitines, and amino acids. 10-CV Pearson correlation coefficients between total olive oil consumption derived from FFQs and the multi-metabolite profile were 0.40 (95% CI 0.37, 0.44) and 0.27 (95% CI 0.22, 0.31) for the discovery and validation sample, respectively. We identified several overlapping and distinct metabolites according to the type of olive oil consumed. The baseline metabolite profiles of total and extra virgin olive oil were inversely associated with CVD incidence (HR per 1SD: 0.79; 95% CI 0.67, 0.92 for total olive oil and 0.70; 0.59, 0.83 for extra virgin olive oil) after adjustment for confounders. However, no significant associations were observed between these metabolite profiles and T2D incidence. CONCLUSIONS This study reveals a panel of plasma metabolites linked to the consumption of total and specific types of olive oil. The metabolite profiles of total olive oil consumption and extra virgin olive oil were associated with a decreased risk of incident CVD in a high cardiovascular-risk Mediterranean population, though no associations were observed with T2D incidence. TRIAL REGISTRATION The PREDIMED trial was registered at ISRCTN ( http://www.isrctn.com/ , ISRCTN35739639).
Collapse
Affiliation(s)
- Jesús F García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Estefanía Toledo
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Zhila Semnani-Azad
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Cristina Razquin
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | | | - Amy Deik
- The Broad Institute of Harvard and MIT, Boston, MA, USA
| | - Dolores Corella
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramón Estruch
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
- Institut de Nutrició I Seguretat Alimentària (INSA-UB), Universitat de Barcelona, Barcelona, Spain
| | - Emilio Ros
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Endocrinology and Nutrition, Lipid Clinic, IDIBAPS, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Montserrat Fitó
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Cardiovascular and Nutrition Research Group, Institut de Recerca Hospital del Mar, Barcelona, Spain
| | - Fernando Arós
- Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba University Hospital, University of the Basque Country UPV/EHU, 01009, Vitoria-Gasteiz, Spain
| | - Miquel Fiol
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Plataforma de Ensayos Clínicos, Instituto de Investigación Sanitaria Illes Balears (IdISBa), Hospital Universitario Son Espases, 07120, Palma, Spain
| | - José Lapetra
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - Rosa Lamuela-Raventos
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Institut de Nutrició I Seguretat Alimentària (INSA-UB), Universitat de Barcelona, Barcelona, Spain
- Polyphenol Research Group, Departament de Nutrició, Ciències de L'Alimentació I Gastronomia, Universitat de Barcelon (UB), Av. de Joan XXII, 27-31, 08028, Barcelona, Spain
| | - Clary Clish
- The Broad Institute of Harvard and MIT, Boston, MA, USA
| | - Miguel Ruiz-Canela
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Miguel Ángel Martínez-González
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Frank Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Øster Farimagsgade 5, 1014, Copenhagen, Denmark.
| |
Collapse
|
5
|
Lai KZH, Semnani-Azad Z, Boucher BA, Retnakaran R, Harris SB, Malik V, Bazinet RP, Hanley AJ. Association of Serum Very-Long-Chain Saturated Fatty Acids With Changes in Insulin Sensitivity and β-Cell Function: The Prospective Metabolism and Islet Cell Evaluation (PROMISE) Cohort. Diabetes 2023; 72:1664-1670. [PMID: 37586083 DOI: 10.2337/db22-1050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 08/03/2023] [Indexed: 08/18/2023]
Abstract
A unique group of circulating very-long-chain saturated fatty acids (VLCSFAs), including arachidic acid (20:0), behenic acid (22:0), and lignoceric acid (24:0), have been associated with a lower risk of type 2 diabetes, although associations with early metabolic risk phenotypes preceding type 2 diabetes have received limited study. We aimed to examine the associations of VLCSFAs with longitudinal changes in insulin sensitivity and β-cell function in a cohort at risk for type 2 diabetes. VLCSFAs in the four main serum pools (phospholipid, triacylglycerol, cholesteryl ester, and nonesterified fatty acid) were extracted from fasting baseline samples (n = 467). Generalized estimating equations were used to determine the associations between VLCSFAs and changes over 9 years in validated indices of insulin sensitivity (HOMA2-%S [insulin sensitivity as percentage of normal population and ISI) and β-cell function (insulinogenic index [IGI], IGI divided by HOMA-insulin resistance [IGI/IR], and insulin secretion sensitivity index 2 [ISSI-2]). Associations of VLCSFAs with outcomes were strongest in the triacylglycerol lipid pool: 20:0 was positively associated with both insulin sensitivity and β-cell function (5.01% increase in HOMA2-%S and 4.01-6.28% increase in IGI/IR and ISSI-2 per SD increase in 20:0); 22:0 was positively associated with insulin sensitivity, with a 6.55% increase in HOMA2-%S and a 5.80% increase in ISI per SD increase in 22:0. Lastly, 24:0 was positively associated with insulin sensitivity and β-cell function (7.94-8.45% increase in HOMA2-%S and ISI, and a 4.61-6.93% increase in IGI/IR and ISSI-2 per SD increase in 24:0). Fewer significant associations were observed in the cholesteryl ester and nonesterified pools. Overall, our results indicate positive longitudinal associations of VLCSFAs with insulin sensitivity and β-cell function, especially within the triacylglycerol pool. ARTICLE HIGHLIGHTS
Collapse
Affiliation(s)
- Kira Zhi Hua Lai
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Zhila Semnani-Azad
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Beatrice A Boucher
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Ravi Retnakaran
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Stewart B Harris
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Vasanti Malik
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Richard P Bazinet
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
| |
Collapse
|
6
|
Tobias DK, Merino J, Ahmad A, Aiken C, Benham JL, Bodhini D, Clark AL, Colclough K, Corcoy R, Cromer SJ, Duan D, Felton JL, Francis EC, Gillard P, Gingras V, Gaillard R, Haider E, Hughes A, Ikle JM, Jacobsen LM, Kahkoska AR, Kettunen JLT, Kreienkamp RJ, Lim LL, Männistö JME, Massey R, Mclennan NM, Miller RG, Morieri ML, Most J, Naylor RN, Ozkan B, Patel KA, Pilla SJ, Prystupa K, Raghavan S, Rooney MR, Schön M, Semnani-Azad Z, Sevilla-Gonzalez M, Svalastoga P, Takele WW, Tam CHT, Thuesen ACB, Tosur M, Wallace AS, Wang CC, Wong JJ, Yamamoto JM, Young K, Amouyal C, Andersen MK, Bonham MP, Chen M, Cheng F, Chikowore T, Chivers SC, Clemmensen C, Dabelea D, Dawed AY, Deutsch AJ, Dickens LT, DiMeglio LA, Dudenhöffer-Pfeifer M, Evans-Molina C, Fernández-Balsells MM, Fitipaldi H, Fitzpatrick SL, Gitelman SE, Goodarzi MO, Grieger JA, Guasch-Ferré M, Habibi N, Hansen T, Huang C, Harris-Kawano A, Ismail HM, Hoag B, Johnson RK, Jones AG, Koivula RW, Leong A, Leung GKW, Libman IM, Liu K, Long SA, Lowe WL, Morton RW, Motala AA, Onengut-Gumuscu S, Pankow JS, Pathirana M, Pazmino S, Perez D, Petrie JR, Powe CE, Quinteros A, Jain R, Ray D, Ried-Larsen M, Saeed Z, Santhakumar V, Kanbour S, Sarkar S, Monaco GSF, Scholtens DM, Selvin E, Sheu WHH, Speake C, Stanislawski MA, Steenackers N, Steck AK, Stefan N, Støy J, Taylor R, Tye SC, Ukke GG, Urazbayeva M, Van der Schueren B, Vatier C, Wentworth JM, Hannah W, White SL, Yu G, Zhang Y, Zhou SJ, Beltrand J, Polak M, Aukrust I, de Franco E, Flanagan SE, Maloney KA, McGovern A, Molnes J, Nakabuye M, Njølstad PR, Pomares-Millan H, Provenzano M, Saint-Martin C, Zhang C, Zhu Y, Auh S, de Souza R, Fawcett AJ, Gruber C, Mekonnen EG, Mixter E, Sherifali D, Eckel RH, Nolan JJ, Philipson LH, Brown RJ, Billings LK, Boyle K, Costacou T, Dennis JM, Florez JC, Gloyn AL, Gomez MF, Gottlieb PA, Greeley SAW, Griffin K, Hattersley AT, Hirsch IB, Hivert MF, Hood KK, Josefson JL, Kwak SH, Laffel LM, Lim SS, Loos RJF, Ma RCW, Mathieu C, Mathioudakis N, Meigs JB, Misra S, Mohan V, Murphy R, Oram R, Owen KR, Ozanne SE, Pearson ER, Perng W, Pollin TI, Pop-Busui R, Pratley RE, Redman LM, Redondo MJ, Reynolds RM, Semple RK, Sherr JL, Sims EK, Sweeting A, Tuomi T, Udler MS, Vesco KK, Vilsbøll T, Wagner R, Rich SS, Franks PW. Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine. Nat Med 2023; 29:2438-2457. [PMID: 37794253 PMCID: PMC10735053 DOI: 10.1038/s41591-023-02502-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 07/14/2023] [Indexed: 10/06/2023]
Abstract
Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
Collapse
Affiliation(s)
- Deirdre K Tobias
- Division of Preventative Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jordi Merino
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Abrar Ahmad
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Catherine Aiken
- Department of Obstetrics and Gynaecology, The Rosie Hospital, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Jamie L Benham
- Departments of Medicine and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Dhanasekaran Bodhini
- Department of Molecular Genetics, Madras Diabetes Research Foundation, Chennai, India
| | - Amy L Clark
- Division of Pediatric Endocrinology, Department of Pediatrics, Saint Louis University School of Medicine, SSM Health Cardinal Glennon Children's Hospital, St. Louis, MO, USA
| | - Kevin Colclough
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Rosa Corcoy
- CIBER-BBN, ISCIII, Madrid, Spain
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Sara J Cromer
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Daisy Duan
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jamie L Felton
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ellen C Francis
- Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Piscataway, NJ, USA
| | | | - Véronique Gingras
- Department of Nutrition, Université de Montréal, Montreal, Quebec, Quebec, Canada
- Research Center, Sainte-Justine University Hospital Center, Montreal, Quebec, Quebec, Canada
| | - Romy Gaillard
- Department of Pediatrics, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Eram Haider
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Alice Hughes
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Jennifer M Ikle
- Department of Pediatrics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Anna R Kahkoska
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jarno L T Kettunen
- Helsinki University Hospital, Abdominal Centre/Endocrinology, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Raymond J Kreienkamp
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Pediatrics, Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA
| | - Lee-Ling Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Asia Diabetes Foundation, Hong Kong SAR, China
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jonna M E Männistö
- Departments of Pediatrics and Clinical Genetics, Kuopio University Hospital, Kuopio, Finland
- Department of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Robert Massey
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Niamh-Maire Mclennan
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Rachel G Miller
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mario Luca Morieri
- Metabolic Disease Unit, University Hospital of Padova, Padova, Italy
- Department of Medicine, University of Padova, Padova, Italy
| | - Jasper Most
- Department of Orthopedics, Zuyderland Medical Center, Sittard-Geleen, The Netherlands
| | - Rochelle N Naylor
- Departments of Pediatrics and Medicine, University of Chicago, Chicago, IL, USA
| | - Bige Ozkan
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Kashyap Amratlal Patel
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Scott J Pilla
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Katsiaryna Prystupa
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Sridharan Raghavan
- Section of Academic Primary Care, US Department of Veterans Affairs Eastern Colorado Health Care System, Aurora, CO, USA
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Mary R Rooney
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Martin Schön
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Diabetes Research and Metabolic Diseases (IDM), Helmholtz Center Munich, Neuherberg, Germany
- Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Zhila Semnani-Azad
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Magdalena Sevilla-Gonzalez
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Pernille Svalastoga
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Wubet Worku Takele
- Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Claudia Ha-Ting Tam
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Anne Cathrine B Thuesen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mustafa Tosur
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Division of Pediatric Diabetes and Endocrinology, Texas Children's Hospital, Houston, TX, USA
- Children's Nutrition Research Center, USDA/ARS, Houston, TX, USA
| | - Amelia S Wallace
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Caroline C Wang
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jessie J Wong
- Stanford University School of Medicine, Stanford, CA, USA
| | | | - Katherine Young
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Chloé Amouyal
- Department of Diabetology, APHP, Paris, France
- Sorbonne Université, INSERM, NutriOmic team, Paris, France
| | - Mette K Andersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maxine P Bonham
- Department of Nutrition, Dietetics and Food, Monash University, Melbourne, Victoria, Australia
| | - Mingling Chen
- Monash Centre for Health Research and Implementation, Monash University, Clayton, Victoria, Australia
| | - Feifei Cheng
- Health Management Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China
| | - Tinashe Chikowore
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Sian C Chivers
- Department of Women and Children's Health, King's College London, London, UK
| | - Christoffer Clemmensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Dana Dabelea
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Adem Y Dawed
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Aaron J Deutsch
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Laura T Dickens
- Section of Adult and Pediatric Endocrinology, Diabetes and Metabolism, Kovler Diabetes Center, University of Chicago, Chicago, IL, USA
| | - Linda A DiMeglio
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Pediatrics, Riley Hospital for Children, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Carmella Evans-Molina
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
- Richard L. Roudebush VAMC, Indianapolis, IN, USA
| | - María Mercè Fernández-Balsells
- Biomedical Research Institute Girona, IdIBGi, Girona, Spain
- Diabetes, Endocrinology and Nutrition Unit Girona, University Hospital Dr Josep Trueta, Girona, Spain
| | - Hugo Fitipaldi
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
| | - Stephanie L Fitzpatrick
- Institute of Health System Science, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Stephen E Gitelman
- University of California at San Francisco, Department of Pediatrics, Diabetes Center, San Francisco, CA, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jessica A Grieger
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Public Health and Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nahal Habibi
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Chuiguo Huang
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Arianna Harris-Kawano
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Heba M Ismail
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Benjamin Hoag
- Division of Endocrinology and Diabetes, Department of Pediatrics, Sanford Children's Hospital, Sioux Falls, SD, USA
- University of South Dakota School of Medicine, E Clark St, Vermillion, SD, USA
| | - Randi K Johnson
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Angus G Jones
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Robert W Koivula
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Aaron Leong
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Gloria K W Leung
- Department of Nutrition, Dietetics and Food, Monash University, Melbourne, Victoria, Australia
| | | | - Kai Liu
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - S Alice Long
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - William L Lowe
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Robert W Morton
- Department of Pathology & Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Translational Medicine, Medical Science, Novo Nordisk Foundation, Hellerup, Denmark
| | - Ayesha A Motala
- Department of Diabetes and Endocrinology, Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Maleesa Pathirana
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
| | - Sofia Pazmino
- Department of Chronic Diseases and Metabolism, Clinical and Experimental Endocrinologyó, KU Leuven, Leuven, Belgium
| | - Dianna Perez
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - John R Petrie
- School of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Camille E Powe
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Obstetrics, Gynecology, and Reproductive Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Alejandra Quinteros
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Rashmi Jain
- Sanford Children's Specialty Clinic, Sioux Falls, SD, USA
- Department of Pediatrics, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA
| | - Debashree Ray
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Mathias Ried-Larsen
- Centre for Physical Activity Research, Rigshospitalet, Copenhagen, Denmark
- Institute for Sports and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Zeb Saeed
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Vanessa Santhakumar
- Division of Preventative Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sarah Kanbour
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
- AMAN Hospital, Doha, Qatar
| | - Sudipa Sarkar
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Gabriela S F Monaco
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Denise M Scholtens
- Department of Preventive Medicine, Division of Biostatistics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Elizabeth Selvin
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Wayne Huey-Herng Sheu
- Institute of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan, Taiwan
- Divsion of Endocrinology and Metabolism, Taichung Veterans General Hospital, Taichung, Taiwan
- Division of Endocrinology and Metabolism, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Cate Speake
- Center for Interventional Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Maggie A Stanislawski
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Nele Steenackers
- Department of Chronic Diseases and Metabolism, Clinical and Experimental Endocrinologyó, KU Leuven, Leuven, Belgium
| | - Andrea K Steck
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Norbert Stefan
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Diabetes Research and Metabolic Diseases (IDM), Helmholtz Center Munich, Neuherberg, Germany
- University Hospital of Tübingen, Tübingen, Germany
| | - Julie Støy
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | | | - Sok Cin Tye
- Sections on Genetics and Epidemiology, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Marzhan Urazbayeva
- Division of Pediatric Diabetes and Endocrinology, Texas Children's Hospital, Houston, TX, USA
- Gastroenterology, Baylor College of Medicine, Houston, TX, USA
| | - Bart Van der Schueren
- Department of Chronic Diseases and Metabolism, Clinical and Experimental Endocrinologyó, KU Leuven, Leuven, Belgium
- Department of Endocrinology, University Hospitals Leuven, Leuven, Belgium
| | - Camille Vatier
- Sorbonne University, Inserm U938, Saint-Antoine Research Centre, Institute of Cardiometabolism and Nutrition, Paris, France
- Department of Endocrinology, Diabetology and Reproductive Endocrinology, Assistance Publique-Hôpitaux de Paris, Saint-Antoine University Hospital, National Reference Center for Rare Diseases of Insulin Secretion and Insulin Sensitivity (PRISIS), Paris, France
| | - John M Wentworth
- Royal Melbourne Hospital Department of Diabetes and Endocrinology, Parkville, Victoria, Australia
- Walter and Eliza Hall Institute, Parkville, Victoria, Australia
- University of Melbourne Department of Medicine, Parkville, Victoria, Australia
| | - Wesley Hannah
- Deakin University, Melbourne, Victoria, Australia
- Department of Epidemiology, Madras Diabetes Research Foundation, Chennai, India
| | - Sara L White
- Department of Women and Children's Health, King's College London, London, UK
- Department of Diabetes and Endocrinology, Guy's and St Thomas' Hospitals NHS Foundation Trust, London, UK
| | - Gechang Yu
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yingchai Zhang
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Shao J Zhou
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
- School of Agriculture, Food and Wine, University of Adelaide, Adelaide, South Australia, Australia
| | - Jacques Beltrand
- Institut Cochin, Inserm U 10116, Paris, France
- Pediatric Endocrinology and Diabetes, Hopital Necker Enfants Malades, APHP Centre, Université de Paris, Paris, France
| | - Michel Polak
- Institut Cochin, Inserm U 10116, Paris, France
- Pediatric Endocrinology and Diabetes, Hopital Necker Enfants Malades, APHP Centre, Université de Paris, Paris, France
| | - Ingvild Aukrust
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Elisa de Franco
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Sarah E Flanagan
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Kristin A Maloney
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Andrew McGovern
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Janne Molnes
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Mariam Nakabuye
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Pål Rasmus Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen, Norway
| | - Hugo Pomares-Millan
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Michele Provenzano
- Nephrology, Dialysis and Renal Transplant Unit, IRCCS-Azienda Ospedaliero-Universitaria di Bologna, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Cécile Saint-Martin
- Department of Medical Genetics, AP-HP Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
| | - Cuilin Zhang
- Global Center for Asian Women's Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yeyi Zhu
- Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Sungyoung Auh
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Russell de Souza
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Andrea J Fawcett
- Ann & Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Clinical and Organizational Development, Chicago, IL, USA
| | | | - Eskedar Getie Mekonnen
- College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
- Global Health Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Emily Mixter
- Department of Medicine and Kovler Diabetes Center, University of Chicago, Chicago, IL, USA
| | - Diana Sherifali
- Population Health Research Institute, Hamilton, Ontario, Canada
- School of Nursing, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Robert H Eckel
- Division of Endocrinology, Metabolism, Diabetes, University of Colorado, Aurora, CO, USA
| | - John J Nolan
- Department of Clinical Medicine, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Department of Endocrinology, Wexford General Hospital, Wexford, Ireland
| | - Louis H Philipson
- Department of Medicine and Kovler Diabetes Center, University of Chicago, Chicago, IL, USA
| | - Rebecca J Brown
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Liana K Billings
- Division of Endocrinology, NorthShore University HealthSystem, Skokie, IL, USA
- Department of Medicine, Prtizker School of Medicine, University of Chicago, Chicago, IL, USA
| | - Kristen Boyle
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Tina Costacou
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - John M Dennis
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
| | - Jose C Florez
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anna L Gloyn
- Department of Pediatrics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford School of Medicine, Stanford University, Stanford, CA, USA
| | - Maria F Gomez
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden
- Faculty of Health, Aarhus University, Aarhus, Denmark
| | - Peter A Gottlieb
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Siri Atma W Greeley
- Departments of Pediatrics and Medicine and Kovler Diabetes Center, University of Chicago, Chicago, IL, USA
| | - Kurt Griffin
- Department of Pediatrics, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA
- Sanford Research, Sioux Falls, SD, USA
| | - Andrew T Hattersley
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Irl B Hirsch
- University of Washington School of Medicine, Seattle, WA, USA
| | - Marie-France Hivert
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Department of Medicine, Universite de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Korey K Hood
- Stanford University School of Medicine, Stanford, CA, USA
| | - Jami L Josefson
- Ann & Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Lori M Laffel
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - Siew S Lim
- Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Ruth J F Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ronald C W Ma
- Department of Medicine & Therapeutics, Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, China
| | | | | | - James B Meigs
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Shivani Misra
- Division of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Diabetes & Endocrinology, Imperial College Healthcare NHS Trust, London, UK
| | - Viswanathan Mohan
- Department of Diabetology, Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialities Centre, Chennai, India
| | - Rinki Murphy
- Department of Medicine, Faculty of Medicine and Health Sciences, University of Auckland, Auckland, New Zealand
- Auckland Diabetes Centre, Te Whatu Ora Health New Zealand, Auckland, New Zealand
- Medical Bariatric Service, Te Whatu Ora Counties, Health New Zealand, Auckland, New Zealand
| | - Richard Oram
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Exeter, UK
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | - Katharine R Owen
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Susan E Ozanne
- University of Cambridge, Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, Cambridge, UK
| | - Ewan R Pearson
- Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Wei Perng
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Toni I Pollin
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Epidemiology & Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Rodica Pop-Busui
- Department of Internal Medicine, Division of Metabolism, Endocrinology and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Maria J Redondo
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Division of Pediatric Diabetes and Endocrinology, Texas Children's Hospital, Houston, TX, USA
| | - Rebecca M Reynolds
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Robert K Semple
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | - Emily K Sims
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
- Herman B Wells Center for Pediatric Research, University School of Medicine, Indianapolis, IN, USA
- Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arianne Sweeting
- Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Department of Endocrinology, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
| | - Tiinamaija Tuomi
- Helsinki University Hospital, Abdominal Centre/Endocrinology, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Miriam S Udler
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kimberly K Vesco
- Kaiser Permanente Northwest, Kaiser Permanente Center for Health Research, Portland, OR, USA
| | - Tina Vilsbøll
- Clinial Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Robert Wagner
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Paul W Franks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmö, Sweden.
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK.
- Department of Translational Medicine, Medical Science, Novo Nordisk Foundation, Hellerup, Denmark.
| |
Collapse
|
7
|
Yehia NA, Isai L, Semnani-Azad Z, Lai KZH, Retnakaran R, Harris SB, Beaudry JL, Bazinet RP, Hanley AJ. Association of circulating branched chain fatty acids with insulin sensitivity and beta cell function in the PROMISE cohort. Lipids 2023; 58:171-183. [PMID: 37165723 DOI: 10.1002/lipd.12373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/29/2023] [Accepted: 04/17/2023] [Indexed: 05/12/2023]
Abstract
Branched chain fatty acids (BCFAs) are mainly saturated fatty acids with a methyl branch on the penultimate or antepenultimate carbon atom. While BCFAs are endogenously produced via the catabolism of branched chain amino acids, the primary exogenous source of BCFAs in the human body is via the diet, including dairy products. Recently, BCFAs have been identified as having a potentially protective role in the etiology of cardiometabolic disorders although current literature is limited. We aimed to investigate the longitudinal associations of circulating BCFAs across four serum pools with insulin sensitivity, beta cell function, and glucose concentrations in the PROMISE Cohort. Estimates of insulin sensitivity were assessed using Matsuda's insulin sensitivity index (ISI) and the homeostasis model assessment of insulin sensitivity (HOMA2). Estimates of beta cell function were determined using the insulinogenic index divided by HOMA insulin resistance and the insulin secretion-sensitivity index-2 (ISSI-2). Baseline serum samples were analyzed for BCFAs using gas-chromatography flame ionization detection. Longitudinal associations were determined using generalized estimating equations. In the free fatty acid (FFA) pool, iso15:0 and anteiso15:0 were positively associated with logHOMA2 (iso15:0 logHOMA2-%S: β = 6.86, 95% CI: [1.64, 12.36], p < 0.05, anteiso15:0 logHOMA2-%S: β = 6.36, 95% CI: [0.63, 12.42], p < 0.05) while anteiso14:0 was inversely associated with measures of insulin sensitivity (iso14:0 logHOMA2-%S: β = -2.35, 95% CI: [-4.26, -0.40], p < 0.05, logISI: β = -2.30, 95% CI: [-4.32, -0.23], p < 0.05, anteiso14:0 logHOMA2-%S: β = -4.72, 95% CI: [-7.81, -1.52], p < 0.05, logISI: β = -6.13, 95% CI: [-9.49, -2.66], p < 0.01). Associations in other pools were less consistent. We identified the potential importance of specific BCFAs, specifically iso14:0, anteiso14:0, iso15:0, anteiso15:0, in cardiometabolic phenotypes underlying type 2 diabetes.
Collapse
Affiliation(s)
- Nagam A Yehia
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Liridona Isai
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Zhila Semnani-Azad
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Kira Zhi Hua Lai
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Ravi Retnakaran
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Stewart B Harris
- Department of Family Medicine, Western University, London, Canada
| | - Jacqueline L Beaudry
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Richard P Bazinet
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Family Medicine, Western University, London, Canada
| |
Collapse
|
8
|
Semnani-Azad Z, Gaillard R, Hughes AE, Boyle KE, Tobias DK, Perng W. Predictors and risk factors of short-term and long-term outcomes among women with gestational diabetes mellitus (GDM) and their offspring: Moving toward precision prognosis? medRxiv 2023:2023.04.14.23288199. [PMID: 37131686 PMCID: PMC10153333 DOI: 10.1101/2023.04.14.23288199] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
As part of the American Diabetes Association Precision Medicine in Diabetes Initiative (PMDI) - a partnership with the European Association for the Study of Diabetes (EASD) - this systematic review is part of a comprehensive evidence evaluation in support of the 2 nd International Consensus Report on Precision Diabetes Medicine. Here, we sought to synthesize evidence from empirical research papers published through September 1 st , 2021 to evaluate and identify prognostic conditions, risk factors, and biomarkers among women and children affected by gestational diabetes mellitus (GDM), focusing on clinical endpoints of cardiovascular disease (CVD) and type 2 diabetes (T2D) among women with a history of GDM; and adiposity and cardiometabolic profile among offspring exposed to GDM in utero. We identified a total of 107 observational studies and 12 randomized controlled trials testing the effect of pharmaceutical and/or lifestyle interventions. Broadly, current literature indicates that greater GDM severity, higher maternal body mass index, belonging to racial/ethnic minority group; and unhealthy lifestyle behaviors would predict a woman's risk of incident T2D and CVD, and an unfavorable cardiometabolic profile among offspring. However, the level of evidence is low (Level 4 according to the Diabetes Canada 2018 Clinical Practice Guidelines for diabetes prognosis) largely because most studies leveraged retrospective data from large registries that are vulnerable to residual confounding and reverse causation bias; and prospective cohort studies that may suffer selection and attrition bias. Moreover, for the offspring outcomes, we identified a relatively small body of literature on prognostic factors indicative of future adiposity and cardiometabolic risk. Future high-quality prospective cohort studies in diverse populations with granular data collection on prognostic factors, clinical and subclinical outcomes, high fidelity of follow-up, and appropriate analytical approaches to deal with structural biases are warranted.
Collapse
|
9
|
Semnani-Azad Z, Perron P, Bouchard L, Hivert MF. Abstract 26: Plasma Metabolomic Profile of Adiposity in Childhood: Gen3G Study. Circulation 2023. [DOI: 10.1161/circ.147.suppl_1.26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Abstract
Objective:
Childhood obesity is associated with long-term adverse outcomes including increased risk of cardiometabolic diseases. The integration of metabolomics in determining metabolites specific to excess adiposity could identify novel markers of adverse adiposity accumulation and insights into the pathogenesis of obesity-related outcomes, but investigations in childhood are limited. Thus, our aim was to identify metabolite networks associated with adiposity in childhood using gold-standard measurements.
Methods:
This study used cross-sectional data from 329 children at mid-childhood (age 5.3 ± 0.3 years) from the Gen3G prospective pre-birth cohort. We quantified 1,038 plasma metabolites including 798 annotated and 240 unannotated molecules. We measured adiposity using the gold-standard dual-energy X-ray absorptiometry (DXA), as well as skinfold, waist circumference and body mass index (BMI). We applied weighted-correlation network analysis to identify networks of highly correlated metabolites. Spearman’s partial correlations were applied to determine the associations of adiposity measures with metabolite networks and individual metabolites, adjusting for age and sex, with false discovery rate correction.
Results:
We identified a network of 23 metabolites (MEmagenta on Figure), primarily comprised of lipids (primary and secondary bile acids metabolism sub-pathways), that showed positive correlations with DXA total and truncal fat (ρ
adjusted
= 0.11 to 0.19), skinfold measures (ρ
adjusted
= 0.09 to 0.26), and BMI and waist circumference (ρ
adjusted
= 0.15 and 0.18, respectively). Within this network, glycol-alpha-muricholate and glycol-beta-muricholate metabolites, bile acid sub-species associated with glucose and lipid metabolism, appeared to be driving the associations. These correlations remained consistent when stratified by sex.
Conclusions:
A unique network of metabolites was associated with adiposity measures at 5 years of age.
Collapse
|
10
|
Yehia NA, Lai KZH, Semnani-Azad Z, Blanco Mejia S, Bazinet RP, Beaudry JL, Hanley AJ. Association of branched chain fatty acids with cardiometabolic disorders in humans: a systematic review. Nutr Rev 2023; 81:180-190. [PMID: 36029228 DOI: 10.1093/nutrit/nuac051] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
CONTEXT Despite advances in treatments for cardiometabolic disorders such as type 2 diabetes mellitus and obesity, the increasing frequency of these conditions is of major clinical and public health concern. Therefore, primary prevention including diet and lifestyle approaches continues to play a key role in risk reduction. Meta-analyses of prospective cohort studies have documented inverse associations of dairy consumption with the incidence of different cardiometabolic disorders. Dairy is the largest dietary contributor of branched chain fatty acids (BCFAs), which have been suggested to not only serve as biomarkers of dairy consumption but may also have bioactive properties contributing to reducing the risk of cardiometabolic outcomes. To date, however, the literature on this topic has not been systematically reviewed. OBJECTIVE The aim here was to report the results of a systematic review of the association of BCFAs with cardiometabolic disorders in humans. DATA SOURCES Search terms were developed and run through the Ovid MEDLINE, Ovid Embase, and the Cochrane Library databases. DATA EXTRACTION Articles were selected on the basis of prespecified inclusion criteria and assessed for risk of bias by independent reviewers. RESULTS Four studies (n = 2 cross sectional; n = 1 randomized feeding trial and n = 1 pre-post study) were identified. Two studies reported significant inverse associations between serum BCFAs and insulin resistance, triglycerides and/or body mass index. One study identified an inverse association between adipose tissue monomethyl BCFAs and skeletal muscle insulin resistance. In contrast, the randomized feeding trial reported no significant differences to stool BCFA concentrations or body mass index in obese participants following assignment to fruit-vegetable or whole-grain diet groups compared with a refined-grain control group. CONCLUSIONS Current evidence suggests beneficial associations of circulating BCFAs with cardiometabolic risk phenotypes, although data in human participants are limited, indicating that additional research is required. PROSPERO REGISTRATION NO CRD42021224975.
Collapse
Affiliation(s)
- Nagam Anna Yehia
- are with the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Kira Zhi Hua Lai
- are with the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Zhila Semnani-Azad
- with the Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sonia Blanco Mejia
- are with the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,is with the Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Risk Factor Modification Centre, St Michael's Hospital, Toronto, Ontario, Canada
| | - Richard P Bazinet
- are with the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Jacqueline L Beaudry
- are with the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Anthony J Hanley
- are with the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,with the Department of Medicine, Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada.,is with the Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
| |
Collapse
|
11
|
Lai KZH, Yehia NA, Semnani-Azad Z, Mejia SB, Boucher BA, Malik V, Bazinet RP, Hanley AJ. Lifestyle Factors Associated with Circulating Very Long-Chain Saturated Fatty Acids in Humans: A Systematic Review of Observational Studies. Adv Nutr 2023; 14:99-114. [PMID: 36811597 PMCID: PMC10102996 DOI: 10.1016/j.advnut.2022.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 09/22/2022] [Accepted: 10/28/2022] [Indexed: 12/23/2022] Open
Abstract
Recent observational studies have documented inverse associations of circulating very long-chain saturated fatty acids (VLCSFAs), namely arachidic acid (20:0), behenic acid (22:0), and lignoceric acid (24:0), with cardiometabolic outcomes. In addition to their endogenous production, it has been suggested that dietary intake or an overall healthier lifestyle may influence VLCSFA concentrations; however, a systematic review of the modifiable lifestyle contributors to circulating VLCSFAs is lacking. Therefore, this review aimed to systematically assess the effects of diet, physical activity, and smoking on circulating VLCSFAs. Following registration on PROSPERO (International Prospective Register of Systematic Reviews) (ID: CRD42021233550), a systematic search of observational studies was conducted in MEDLINE, EMBASE, and The Cochrane databases up to February 2022. A total of 12 studies consisting of mostly cross-sectional analyses were included in this review. The majority of the studies documented the associations of dietary intake with total plasma or red blood cell VLCSFAs, in which a range of macronutrients and food groups were examined. Two cross-sectional analyses showed a consistent positive association between total fat and peanut intake with 22:0 and 24:0 and an inverse association between alcohol intake and 20:0 and 22:0. Furthermore, a moderate positive association between physical activity and 22:0 and 24:0 was observed. Lastly, there were conflicting results on the effects of smoking on VLCSFA. Although most studies had a low risk of bias; the findings of this review are limited by the bi-variate analyses presented in the majority of the included studies, therefore, the impact of confounding is unclear. In conclusion, although the current observational literature examining lifestyle determinants of VLCSFAs is limited, existing evidence suggests that circulating 22:0 and 24:0 may be influenced by higher total and saturated fat consumption and nut intake.
Collapse
Affiliation(s)
- Kira Zhi Hua Lai
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Nagam A Yehia
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Zhila Semnani-Azad
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sonia Blanco Mejia
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Risk Factor Modification Centre, St Michael's Hospital, Toronto, Ontario, Canada
| | - Beatrice A Boucher
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Vasanti Malik
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Richard P Bazinet
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada; Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada.
| |
Collapse
|
12
|
Kaspy MS, Semnani-Azad Z, Malik VS, Jenkins DJA, Hanley AJ. Metabolomic profile of combined healthy lifestyle behaviours in humans: A systematic review. Proteomics 2022; 22:e2100388. [PMID: 35816426 DOI: 10.1002/pmic.202100388] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 06/28/2022] [Accepted: 07/08/2022] [Indexed: 11/10/2022]
Abstract
A combination of healthy lifestyle behaviours (i.e. regular physical activity, nutritious diet, no smoking, moderate alcohol, and healthy body mass) has been consistently associated with beneficial health outcomes including reduced risk of cardiometabolic diseases. Metabolomic profiles, characterized by distinct sets of biomarkers, have been described for healthy lifestyle behaviours individually and in combination. However, recent literature calls for systematic evaluation of these heterogenous data to identify potential clinical biomarkers relating to a combined healthy lifestyle. The objective was to systematically review existing literature on the metabolomic profile of combined healthy lifestyle behaviours. MEDLINE, EMBASE and Cochrane databases were searched through March 2022. Studies in humans outlining the metabolomic profile of a combination of two or more healthy lifestyle behaviours were included. Collectively, the metabolomic profile following regular adherence to combined healthy lifestyle behaviours points to a positive association with beneficial fatty acids and phosphocreatine, and inverse associations with triglycerides, trimethylamine N-oxide, and acylcarnitines. The findings suggest that a unique metabolomic profile is associated with combined healthy lifestyle behaviours. Additional research is warranted to further describe this metabolomic profile using targeted and untargeted metabolomic approaches along with uniform definitions of combined healthy lifestyle variables across populations. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Matthew S Kaspy
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Zhila Semnani-Azad
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Vasanti S Malik
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - David J A Jenkins
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, Ontario, Canada.,Division of Endocrinology & Metabolism, Department of Medicine, St. Michael's Hospital, Toronto, Ontario, Canada.,Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Division of Endocrinology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
| |
Collapse
|
13
|
Nolan JJ, Kahkoska AR, Semnani-Azad Z, Hivert MF, Ji L, Mohan V, Eckel RH, Philipson LH, Rich SS, Gruber C, Franks PW. ADA/EASD Precision Medicine in Diabetes Initiative: An International Perspective and Future Vision for Precision Medicine in Diabetes. Diabetes Care 2022; 45:261-266. [PMID: 35050364 PMCID: PMC8914425 DOI: 10.2337/dc21-2216] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 11/08/2021] [Indexed: 02/03/2023]
Affiliation(s)
- John J. Nolan
- Department of Clinical Medicine, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Anna R. Kahkoska
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC
| | - Zhila Semnani-Azad
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, and Diabetes Unit, Massachusetts General Hospital, Boston, MA
| | - Linong Ji
- Peking University Diabetes Center, Peking University People’s Hospital, Beijing, China
| | - Viswanathan Mohan
- Dr. Mohan’s Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India
| | - Robert H. Eckel
- University of Colorado Anschutz College of Medicine, Aurora, CO
| | - Louis H. Philipson
- Departments of Medicine and Pediatrics, The University of Chicago, Chicago, IL
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA
| | | | - Paul W. Franks
- Lund University Diabetes Center, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Harvard T.H. Chan School of Public Health, Boston, MA
- Novo Nordisk Foundation, Copenhagen, Denmark
| |
Collapse
|
14
|
Lai KZH, Semnani-Azad Z, Retnakaran R, Harris SB, Hanley AJ. Changes in adiposity mediate the associations of diet quality with insulin sensitivity and beta-cell function. Nutr Metab Cardiovasc Dis 2021; 31:3054-3063. [PMID: 34518089 DOI: 10.1016/j.numecd.2021.07.025] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 07/20/2021] [Accepted: 07/22/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS To examine the mediating role of adiposity on the associations of diet quality with longitudinal changes in insulin sensitivity and beta-cell function. METHODS AND RESULTS Adults at-risk for type 2 diabetes (T2D) in the PROMISE cohort had 4 assessments over 9 years (n = 442). Alternate Healthy Eating Index (AHEI) scores were used to assess diet quality. Generalized Estimating Equations (GEE) evaluated the associations between the AHEI and longitudinal changes in insulin sensitivity (HOMA2-%S and ISI) and beta-cell function (IGI/HOMA-IR and ISSI-2). The proportion of the mediating effect of waist circumference changes was estimated using the difference method. In the primary longitudinal analysis, AHEI was positively associated with insulin sensitivity and beta-cell function over time (% difference per standard deviation increase of AHEI for HOMA2-%S (β = 11.0, 95%CI 5.43-17.0), ISI (β = 10.4, 95%CI 4.35-16.8), IGI/HOMA-IR (β = 7.12, 95%CI 0.98-13.6) and ISSI-2 (β = 4.38, 95%CI 1.05-7.80), all p < 0.05). There was no significant association between AHEI and dysglycemia incidence (OR = 0.95, 95%CI 0.77-1.17). Adjustments for longitudinal changes in waist circumference substantially attenuated all associations of AHEI with insulin sensitivity and beta-cell function. Mediation analysis indicated that waist circumference mediated 73%, 70%, 83% and 81% of the association between AHEI and HOMA2-%S, ISI, IGI/HOMA-IR, and ISSI-2, respectively (all p < 0.01). CONCLUSION In a Canadian population at-risk for T2D, AHEI score was positively associated with changes in insulin sensitivity and beta-cell function. These associations were substantially mediated by waist circumference, suggesting that changes in adiposity may represent an important pathway linking diet quality with risk phenotypes for T2D.
Collapse
Affiliation(s)
- Kira Zhi Hua Lai
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada.
| | - Zhila Semnani-Azad
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada.
| | - Ravi Retnakaran
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Canada; Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada; Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada.
| | - Stewart B Harris
- Department of Family Medicine, Western University, London, Canada.
| | - Anthony J Hanley
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada; Division of Endocrinology and Metabolism, University of Toronto, Toronto, Canada; Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada.
| |
Collapse
|
15
|
Semnani-Azad Z, Blanco Mejia S, Connelly PW, Bazinet RP, Retnakaran R, Jenkins DJA, Harris SB, Hanley AJ. The association of soluble CD163, a novel biomarker of macrophage activation, with type 2 diabetes mellitus and its underlying physiological disorders: A systematic review. Obes Rev 2021; 22:e13257. [PMID: 33913230 DOI: 10.1111/obr.13257] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 03/27/2021] [Indexed: 12/29/2022]
Abstract
This systematic review investigates the association of sCD163, a novel biomarker of macrophage activation, with type 2 diabetes mellitus (T2DM), insulin resistance, and beta-cell dysfunction. Sixteen studies (seven cross-sectional, two case-control, one nested case-control, three prospective cohort, and three experimental) were identified. Most studies demonstrated that elevated sCD163 concentrations were associated with increased insulin resistance. Cross-sectional, case-control, and nested case-control studies showed higher sCD163 in subjects with T2DM compared with healthy individuals. An 18-year follow-up prospective cohort study showed that elevated baseline sCD163 was a strong predictor of T2DM incidence. Prospective cohort studies demonstrated that baseline measures and longitudinal changes in sCD163 were positively associated with insulin resistance; however, associations with beta-cell function were inconsistent. Two experimental studies evaluated the relationship of sCD163 with T2DM and HOMA-IR after weight-reducing interventions. After very low-calorie diet treatments, sCD163 concentration declined significantly in patients with T2DM but was not associated with insulin resistance. Bariatric surgery did not significantly impact sCD163 levels. In a double-blind randomized controlled trial, resveratrol supplementation significantly reduced circulating sCD163 in T2DM patients. Current studies demonstrate the potential utility of sCD163 as an early biomarker of T2DM risk and highlight a potential mechanism linking obesity with T2DM onset.
Collapse
Affiliation(s)
- Zhila Semnani-Azad
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Sonia Blanco Mejia
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Toronto, Ontario, Canada.,Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Philip W Connelly
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Ontario, Canada.,Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Richard P Bazinet
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Ravi Retnakaran
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - David J A Jenkins
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Center, St. Michael's Hospital, Toronto, Ontario, Canada.,Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, Ontario, Canada.,Department of Medicine, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.,Division of Endocrinology and Metabolism, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Stewart B Harris
- Department of Family Medicine, Western University, London, Ontario, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada.,Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
16
|
Semnani-Azad Z, Connelly PW, Bazinet RP, Retnakaran R, Jenkins DJA, Harris SB, Zinman B, Hanley AJ. Adipose Tissue Insulin Resistance Is Longitudinally Associated With Adipose Tissue Dysfunction, Circulating Lipids, and Dysglycemia: The PROMISE Cohort. Diabetes Care 2021; 44:1682-1691. [PMID: 34001534 DOI: 10.2337/dc20-1918] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 04/01/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To determine the association of adipose tissue insulin resistance with longitudinal changes in biomarkers of adipose tissue function, circulating lipids, and dysglycemia. RESEARCH DESIGN AND METHODS Adults at risk for type 2 diabetes in the Prospective Metabolism and Islet Cell Evaluation (PROMISE) cohort had up to four assessments over 9 years (n = 468). Adipose tissue insulin resistance was determined using a novel validated index, Adipo-IR, calculated as the product of fasting insulin and nonesterified fatty acids measured at baseline. Fasting serum was used to measure biomarkers of adipose tissue function (adiponectin and soluble CD163 [sCD163]), circulating lipids (total cholesterol, HDL, LDL, triglyceride [TG]), and systemic inflammation (interleukin-6 [IL-6] and tumor necrosis factor-α [TNF-α]). Incident dysglycemia was defined as the onset of impaired fasting glucose, impaired glucose tolerance, or type 2 diabetes at follow-up. Generalized estimating equation (GEE) models were used to assess the relationship of Adipo-IR with longitudinal outcomes. RESULTS GEE analyses showed that elevated Adipo-IR was longitudinally associated with adipose tissue dysfunction (adiponectin -4.20% [95% CI -6.40 to -1.95]; sCD163 4.36% [1.73-7.06], HDL -3.87% [-5.15 to -2.57], TG 9.26% [5.01-13.69]). Adipo-IR was associated with increased risk of incident dysglycemia (odds ratio 1.59 [95% CI 1.09-2.31] per SD increase). Associations remained significant after adjustment for waist circumference and surrogate indices for insulin resistance. There were no significant longitudinal associations of Adipo-IR with IL-6, TNF-α, total cholesterol, or LDL. CONCLUSIONS Our findings demonstrate that adipose tissue insulin resistance is prospectively associated with adipose tissue function, HDL, TG, and incident dysglycemia.
Collapse
Affiliation(s)
- Zhila Semnani-Azad
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Philip W Connelly
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Ontario, Canada.,Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Richard P Bazinet
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Ravi Retnakaran
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada.,Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada.,Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - David J A Jenkins
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital, Toronto, Ontario, Canada.,Department of Medicine, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.,Division of Endocrinology and Metabolism, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Stewart B Harris
- Department of Family Medicine, Western University, London, Ontario, Canada
| | - Bernard Zinman
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada.,Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada.,Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada .,Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada.,Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
17
|
Semnani-Azad Z, Khan T, Kabisch S, Kahleova H, Kendall C, Lau D, Wharton S, Leiter L, Lean M, Harris L, Rahelic D, Salas-Salvado J, Sharma A, Sievenpiper J. Effect of Intermittent Fasting Strategies on Cardiometabolic Risk Factors: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials. Curr Dev Nutr 2021. [DOI: 10.1093/cdn/nzab053_084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Objectives
Intermittent fasting (IF) is a popular trending diet, yet there is limited evidence-based support considering its clinical impact on cardiometabolic outcomes. In an effort to inform the European Association for the Study of Diabetes (EASD) clinical practice guidelines for nutrition therapy, we conducted a network meta-analysis of randomized controlled trials (RCTs) comparing IF strategies and continuous energy restriction (CER) on cardiometabolic outcomes using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach.
Methods
MEDLINE, EMBASE, and Cochrane databases were searched through Nov 2020. We included RCTs assessing the effect of IF strategies (alternate-day fasting (ADF), whole-day periodic fasting (WDF), time-restricted feeding (TRF)), CER, and ad libitum diet. Outcomes included body weight, fasting glucose and LDL-cholesterol. Two independent researchers extracted data and assessed risk of bias. A network meta-analysis was performed and data were expressed as mean differences (MD) with 95% confidence intervals (CI). The certainty of the evidence was assessed using GRADE.
Results
We identified 19 RCTs (n = 590) including adults of varying health backgrounds. ADF and CER both showed a benefit for body weight reduction compared to ad libitum diet (18 trials, n = 520; MD −3.95 kg [95% CI −6.09, −1.81] and MD −2.85 kg [95% CI −4.99, −0.71], respectively). For fasting glucose (17 trials, n = 590), TRF showed a benefit compared to ad libitum diet (MD −0.39 mmol/L [95% CI −0.59, −0.20]), to CER (MD −0.25 mmol/L [95% CI, −0.45 to −0.06]) and to WDF (MD −0.20 mmol/L [95% CI, −0.45, −0.05]). Furthermore, ADF showed a benefit in reducing LDL-cholesterol (17 trials, n = 590) compared to ad libitum diet (MD −0.21 mmol/L [95% CI −0.40, −0.1]), and to CER (MD −0.15 mmol/L [95% CI −0.31, −0.01]). The certainty of the evidence ranged from high to moderate due to variable downgrades for imprecision.
Conclusions
Current evidence provides a good indication that IF strategies have similar benefits to CER for weight loss but may have additional benefits for fasting glucose and LDL-cholesterol. Long-term high quality RCTs are needed to clarify the effect of different IF strategies on cardiometabolic outcomes.
Funding Sources
Diabetes and Nutrition Study Group of the EASD, Canadian Institutes of Health Research (CIHR), Diabetes Canada.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Jordi Salas-Salvado
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana
| | | | | |
Collapse
|
18
|
Semnani-Azad Z, Khan TA, Blanco Mejia S, de Souza RJ, Leiter LA, Kendall CWC, Hanley AJ, Sievenpiper JL. Association of Major Food Sources of Fructose-Containing Sugars With Incident Metabolic Syndrome: A Systematic Review and Meta-analysis. JAMA Netw Open 2020; 3:e209993. [PMID: 32644139 PMCID: PMC7348689 DOI: 10.1001/jamanetworkopen.2020.9993] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
IMPORTANCE Sugar-sweetened beverages (SSBs) are associated with increased risk of metabolic syndrome (MetS). However, the role of other important food sources of fructose-containing sugars in the development of MetS remains unclear. OBJECTIVE To examine the association of major food sources of fructose-containing sugars with incident MetS. DATA SOURCES MEDLINE, Embase, and Cochrane Library were searched from database inception to March 24, 2020, in addition to manual searches of reference lists from included studies using the following search terms: sugar-sweetened beverages, fruit drink, yogurt, metabolic syndrome, and prospective study. STUDY SELECTION Inclusion criteria included prospective cohort studies of 1 year or longer that investigated the association of important food sources of fructose-containing sugars with incident MetS in participants free of MetS at the start of the study. DATA EXTRACTION AND SYNTHESIS Study quality was assessed using the Newcastle-Ottawa Scale. Extreme quantile risk estimates for each food source with MetS incidence were pooled using a random-effects meta-analysis. Interstudy heterogeneity was assessed (Cochran Q statistic) and quantified (I2 statistic). Dose-response analyses were performed using a 1-stage linear mixed-effects model. The certainty of the evidence was assessed using GRADE (Grading of Recommendations, Assessment, Development, and Evaluation). Results were reported according to the Meta-analysis of Observational Studies in Epidemiology (MOOSE) and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. MAIN OUTCOMES AND MEASURES Pooled risk ratio (RR) of incident MetS (pairwise and dose response). RESULTS Thirteen prospective cohort studies (49 591 participants [median age, 51 years; range, 6-90 years]; 14 205 with MetS) that assessed 8 fructose-containing foods and MetS were included. An adverse linear dose-response association for SSBs (RR for 355 mL/d, 1.14; 95% CI, 1.05-1.23) and an L-shaped protective dose-response association for yogurt (RR for 85 g/d, 0.66; 95% CI, 0.58-0.76) and fruit (RR for 80 g/d, 0.82; 95% CI, 0.78-0.86) was found. Fruit juices (mixed and 100%) had a U-shaped dose-response association with protection at moderate doses (mixed fruit juice: RR for 125 mL/d, 0.58; 95% CI, 0.42-0.79; 100% fruit juice: RR for 125 mL/d, 0.77; 95% CI, 0.61-0.97). Honey, ice cream, and confectionary had no association with MetS incidence. The certainty of the evidence was moderate for SSBs, yogurt, fruit, mixed fruit juice, and 100% fruit juice and very low for all other food sources. CONCLUSIONS AND RELEVANCE The findings of this meta-analysis suggest that the adverse association of SSBs with MetS does not extend to other food sources of fructose-containing sugars, with a protective association for yogurt and fruit throughout the dose range and for 100% fruit juice and mixed fruit juices at moderate doses. Therefore, current policies and guidelines on the need to limit sources of free sugars may need to be reexamined.
Collapse
Affiliation(s)
- Zhila Semnani-Azad
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Tauseef A. Khan
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Risk Factor Modification Centre, St Michael’s Hospital, Toronto, Ontario, Canada
| | - Sonia Blanco Mejia
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Risk Factor Modification Centre, St Michael’s Hospital, Toronto, Ontario, Canada
| | - Russell J. de Souza
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Risk Factor Modification Centre, St Michael’s Hospital, Toronto, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton, Ontario, Canada
| | - Lawrence A. Leiter
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Risk Factor Modification Centre, St Michael’s Hospital, Toronto, Ontario, Canada
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael’s Hospital, Toronto, Ontario, Canada
| | - Cyril W. C. Kendall
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Risk Factor Modification Centre, St Michael’s Hospital, Toronto, Ontario, Canada
- Division of Nutrition and Dietetics, College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Anthony J. Hanley
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - John L. Sievenpiper
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Risk Factor Modification Centre, St Michael’s Hospital, Toronto, Ontario, Canada
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael’s Hospital, Toronto, Ontario, Canada
| |
Collapse
|
19
|
Semnani-Azad Z, Connelly PW, Johnston LW, Retnakaran R, Harris SB, Zinman B, Hanley AJ. The Macrophage Activation Marker Soluble CD163 is Longitudinally Associated With Insulin Sensitivity and β-cell Function. J Clin Endocrinol Metab 2020; 105:5611046. [PMID: 31677389 PMCID: PMC7112970 DOI: 10.1210/clinem/dgz166] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 10/30/2019] [Indexed: 02/01/2023]
Abstract
CONTEXT Chronic inflammation arising from adipose tissue macrophage (ATM) activation may be central in type 2 diabetes etiology. Our objective was to assess the longitudinal associations of soluble CD163 (sCD163), a novel biomarker of ATM activation, with insulin sensitivity, β-cell function, and dysglycemia in high-risk subjects. METHODS Adults at risk for type 2 diabetes in the Prospective Metabolism and Islet Cell Evaluation (PROMISE) study had 3 assessments over 6 years (n = 408). Levels of sCD163 were measured using fasting serum. Insulin sensitivity was assessed by HOMA2-%S and the Matsuda index (ISI). β-cell function was determined by insulinogenic index (IGI) over HOMA-IR and insulin secretion-sensitivity index-2 (ISSI-2). Incident dysglycemia was defined as the onset of impaired fasting glucose, impaired glucose tolerance, or type 2 diabetes. Generalized estimating equations (GEE) evaluated longitudinal associations of sCD163 with insulin sensitivity, β-cell function, and incident dysglycemia adjusting for demographic and lifestyle covariates. Areas under receiver-operating-characteristic curve (AROC) tested whether sCD163 improved dysglycemia prediction in a clinical model. RESULTS Longitudinal analyses showed significant inverse associations between sCD163 and insulin sensitivity (% difference per standard deviation increase of sCD163 for HOMA2-%S (β = -7.01; 95% CI, -12.26 to -1.44) and ISI (β = -7.60; 95% CI, -11.09 to -3.97) and β-cell function (ISSI-2 (β = -4.67; 95 %CI, -8.59 to -0.58) and IGI/HOMA-IR (β = -8.75; 95% CI, -15.42 to -1.56)). Increased sCD163 was associated with greater risk for incident dysglycemia (odds ratio = 1.04; 95% CI, 1.02-1.06; P < 0.001). Adding sCD163 data to a model with clinical variables improved prediction of incident dysglycemia (AROC=0.6731 vs 0.638; P < 0.05). CONCLUSIONS sCD163 was longitudinally associated with core disorders that precede the onset of type 2 diabetes.
Collapse
MESH Headings
- Adipose Tissue/cytology
- Adipose Tissue/immunology
- Adult
- Antigens, CD/blood
- Antigens, CD/metabolism
- Antigens, Differentiation, Myelomonocytic/blood
- Antigens, Differentiation, Myelomonocytic/metabolism
- Biomarkers/blood
- Biomarkers/metabolism
- Blood Glucose/analysis
- Blood Glucose/metabolism
- Diabetes Mellitus, Type 2/blood
- Diabetes Mellitus, Type 2/diagnosis
- Diabetes Mellitus, Type 2/immunology
- Diabetes Mellitus, Type 2/physiopathology
- Female
- Glucose Tolerance Test
- Humans
- Insulin Resistance/immunology
- Islets of Langerhans/physiopathology
- Longitudinal Studies
- Macrophage Activation
- Macrophages/immunology
- Macrophages/metabolism
- Male
- Middle Aged
- Prospective Studies
- Receptors, Cell Surface/blood
- Receptors, Cell Surface/metabolism
Collapse
Affiliation(s)
- Zhila Semnani-Azad
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Philip W Connelly
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Canada
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
| | - Luke W Johnston
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Ravi Retnakaran
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada
| | - Stewart B Harris
- Department of Family Medicine, Western University, London, Canada
| | - Bernard Zinman
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Canada
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada
- Correspondence and Reprint Requests: Anthony J. Hanley, PhD. Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Medical Sciences Building, 1 King’s College Circle, Toronto, ON, Canada M5S 1A8. Tel: 416-978-3616, E-mail: , ORCID ID: 0000-0002-6364-2444
| |
Collapse
|
20
|
Semnani-Azad Z, Johnston LW, Lee C, Retnakaran R, Connelly PW, Harris SB, Zinman B, Hanley AJ. Determinants of longitudinal change in insulin clearance: the Prospective Metabolism and Islet Cell Evaluation cohort. BMJ Open Diabetes Res Care 2019; 7:e000825. [PMID: 31803485 PMCID: PMC6887510 DOI: 10.1136/bmjdrc-2019-000825] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 10/03/2019] [Accepted: 10/28/2019] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVE To evaluate multiple determinants of the longitudinal change in insulin clearance (IC) in subjects at high risk for type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS Adults (n=492) at risk for T2D in the Prospective Metabolism and Islet Cell Evaluation cohort, a longitudinal observational cohort, had four visits over 9 years. Values from oral glucose tolerance tests collected at each assessment were used to calculate the ratios of both fasting C peptide-to-insulin (ICFASTING) and areas under the curve of C peptide-to-insulin (ICAUC). Generalized estimating equations (GEE) evaluated multiple determinants of longitudinal changes in IC. RESULTS IC declined by 20% over the 9-year follow-up period (p<0.05). Primary GEE results indicated that non-European ethnicity, as well as increases in baseline measures of waist circumference, white cell count, and alanine aminotransferase, was associated with declines in ICFASTING and ICAUC over time (all p<0.05). There were no significant associations of IC with sex, age, physical activity, smoking, or family history of T2D. Both baseline and longitudinal IC were associated with incident dysglycemia. CONCLUSIONS Our findings suggest that non-European ethnicity and components of the metabolic syndrome, including central obesity, non-alcoholic fatty liver disease, and subclinical inflammation, may be related to longitudinal declines in IC.
Collapse
Affiliation(s)
- Zhila Semnani-Azad
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Luke W Johnston
- Department of Public Health, Aarhus Universitet, Aarhus, Denmark
| | - Christine Lee
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Ravi Retnakaran
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Philip W Connelly
- Keenan Research Centre for Biomedical Science, St Michael’s Hospital, Toronto, Ontario, Canada
| | - Stewart B Harris
- Centre for Studies in Family Medicine, Western University, London, Ontario, Canada
| | - Bernard Zinman
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Anthony J Hanley
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
- Division of Endocrinology and Metabolism, University of Toronto, Toronto, Ontario, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
| |
Collapse
|
21
|
Semnani-Azad Z, Scourboutakos MJ, L’Abbé MR. Kids’ meals from Canadian chain restaurants are exceedingly high in calories, fats, and sodium: a cross-sectional study. BMC Nutr 2016. [DOI: 10.1186/s40795-016-0056-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
|
22
|
Abstract
Objective To analyze the added sugars in kids' meals from Canadian chain restaurants in relation to the World Health Organization's proposed sugar recommendation (less than 5% of total daily calories should come from added sugars) and current recommendation (less than 10% of total daily calories should come from added sugars). Methods Total sugar levels were retrieved from the websites of 10 fast-food and 7 sit-down restaurants in 2010. The added sugar levels in 3178 kids' meals from Canadian chain restaurants were calculated in 2014 (in Toronto, Canada) by subtracting all naturally occurring sugars from the total sugar level. Results The average amount of added sugars in restaurant kids' meals (25 ± 0.36 g) exceeded the WHO's proposed daily recommendation for sugar intake. There was a wide range of added sugar levels in kids' meals ranging from 0 g to 114 g. 50% of meals exceeded the WHO's proposed daily sugar recommendation, and 19% exceeded the WHO's current daily sugar recommendation. Conclusion There is a wide range of sugar levels in kids' meals from restaurants, and many contain more than a day's worth of sugar. The amount of added sugars in kids’ meals (25 ± 0.36 g) was equivalent to the WHO’s proposed daily sugar recommendation. There was a wide range of added sugar levels in kids’ meals ranging from 0 g to 114 g. 50% of meals exceeded the WHO’s proposed daily sugar recommendation. 19% exceeded the WHO’s current daily sugar recommendation.
Collapse
Affiliation(s)
- Mary J Scourboutakos
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Zhila Semnani-Azad
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Mary R L'Abbé
- Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
23
|
|