2
|
Lane WS, Favaro E, Rathor N, Jang HC, Kjærsgaard MIS, Oviedo A, Rose L, Senior P, Sesti G, Soto Gonzalez A, Franek E. A Randomized Trial Evaluating the Efficacy and Safety of Fast-Acting Insulin Aspart Compared With Insulin Aspart, Both in Combination With Insulin Degludec With or Without Metformin, in Adults With Type 2 Diabetes (ONSET 9). Diabetes Care 2020; 43:1710-1716. [PMID: 32209647 PMCID: PMC7372057 DOI: 10.2337/dc19-2232] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 02/15/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To evaluate the efficacy and safety of fast-acting insulin aspart (faster aspart) compared with insulin aspart (IAsp), both with insulin degludec with or without metformin, in adults with type 2 diabetes not optimally controlled with a basal-bolus regimen. RESEARCH DESIGN AND METHODS This multicenter, double-blind, treat-to-target trial randomized participants to faster aspart (n = 546) or IAsp (n = 545). All available information, regardless of treatment discontinuation or use of ancillary treatment, was used for evaluation of effect. RESULTS Noninferiority for the change from baseline in HbA1c 16 weeks after randomization (primary end point) was confirmed for faster aspart versus IAsp (estimated treatment difference [ETD] -0.04% [95% CI -0.11; 0.03]; -0.39 mmol/mol [-1.15; 0.37]; P < 0.001). Faster aspart was superior to IAsp for change from baseline in 1-h postprandial glucose (PPG) increment using a meal test (ETD -0.40 mmol/L [-0.66; -0.14]; -7.23 mg/dL [-11.92; -2.55]; P = 0.001 for superiority). Change from baseline in self-measured 1-h PPG increment for the mean over all meals favored faster aspart (ETD -0.25 mmol/L [-0.42; -0.09]); -4.58 mg/dL [-7.59; -1.57]; P = 0.003). The overall rate of treatment-emergent severe or blood glucose (BG)-confirmed hypoglycemia was statistically significantly lower for faster aspart versus IAsp (estimated treatment ratio 0.81 [95% CI 0.68; 0.97]). CONCLUSIONS In combination with insulin degludec, faster aspart provided effective overall glycemic control, superior PPG control, and a lower rate of severe or BG-confirmed hypoglycemia versus IAsp in adults with type 2 diabetes not optimally controlled with a basal-bolus regimen.
Collapse
Affiliation(s)
- Wendy S Lane
- Mountain Diabetes and Endocrine Centre, Asheville, NC
| | | | | | - Hak C Jang
- Department of Internal Medicine, Seoul National University College of Medicine and Seoul National University Bundang Hospital, Seongnam, South Korea
| | | | - Alejandra Oviedo
- Santojanni Hospital and CENUDIAB, Ciudad Autonoma de Buenos Aires, Buenos Aires, Argentina
| | - Ludger Rose
- Institute of Diabetes Research, Münster, Germany
| | - Peter Senior
- Division of Endocrinology and Metabolism, University of Alberta, Edmonton, Alberta, Canada
| | - Giorgio Sesti
- Department of Clinical and Molecular Medicine, Sapienza University of Rome, Rome, Italy
| | - Alfonso Soto Gonzalez
- Service of Endocrinology and Nutrition, University Hospital of A Coruña, La Coruña, Spain
| | - Edward Franek
- Mossakowski Clinical Research Center, Polish Academy of Sciences, and Department of Endocrinology and Diabetology, Central Clinical Hospital of the MSWiA, Warsaw, Poland
| |
Collapse
|
4
|
Chen YJ, Chen JT, Tai MC, Liang CM, Chen YY, Kao TW, Fang WH, Chen WL. Examining the associations among intraocular pressure, hepatic steatosis, and anthropometric parameters. Medicine (Baltimore) 2019; 98:e17598. [PMID: 31651867 PMCID: PMC6824641 DOI: 10.1097/md.0000000000017598] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 08/15/2019] [Accepted: 09/19/2019] [Indexed: 01/28/2023] Open
Abstract
Emerging evidences had reported the positive relationship between obesity and intraocular pressure (IOP). The aim of the present study was to investigate the association between hepatic steatosis and IOP in an adult Taiwanese population.Seven thousand seven hundred twelve males and 6325 females who received a health examination at the Tri-Service General Hospital during the period from 2010 to 2016 were included in this study.IOP was measured by noncontact tonometry. Hepatic steatosis was diagnosed by abdominal ultrasound examination. Multivariate regression analyses were used to assess the associations among various anthropometric parameters and IOP.After adjusting for pertinent covariables, hepatic steatosis had a closer association with increased IOP than percentage body fat, body mass index, or waist circumference (β = 0.017, 95% confidence interval [CI] = 0.006, 0.028). This relationship remained significant among males in the study population (β = 0.015, 95% CI = 0.001, 0.029). Furthermore, hepatic steatosis was significantly correlated with increased risk of high IOP (odd ratios = 1.235, 95% CI = 1.041-1.465).Our study highlights that hepatic steatosis is a better index for assessing the relationship with increased IOP than other anthropometric parameters. Underlying pathophysiological mechanisms regulating the association between hepatic steatosis and increasing IOP and even the risk of glaucoma should be examined in further studies.
Collapse
Affiliation(s)
- Ying-Jen Chen
- Department of Ophthalmology, Tri-Service General Hospital
| | | | - Ming-Cheng Tai
- Department of Ophthalmology, Tri-Service General Hospital
| | | | - Yuan-Yuei Chen
- Department of Internal Medicine, Tri-Service General Hospital Songshan Branch
- Division of Family Medicine
| | - Tung-Wei Kao
- Division of Family Medicine
- Division of Geriatric Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical Center, Taipei, Taiwan, Republic of China
| | | | - Wei-Liang Chen
- Division of Family Medicine
- Division of Geriatric Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical Center, Taipei, Taiwan, Republic of China
| |
Collapse
|
5
|
Laville V, Kang JH, Cousins CC, Iglesias AI, Nagy R, Cooke Bailey JN, Igo RP, Song YE, Chasman DI, Christen WG, Kraft P, Rosner BA, Hu F, Wilson JF, Gharahkhani P, Hewitt AW, Mackey DA, Hysi PG, Hammond CJ, vanDuijn CM, Haines JL, Vitart V, Fingert JH, Hauser MA, Aschard H, Wiggs JL, Khawaja AP, MacGregor S, Pasquale LR. Genetic Correlations Between Diabetes and Glaucoma: An Analysis of Continuous and Dichotomous Phenotypes. Am J Ophthalmol 2019; 206:245-255. [PMID: 31121135 PMCID: PMC6864262 DOI: 10.1016/j.ajo.2019.05.015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2018] [Revised: 05/03/2019] [Accepted: 05/09/2019] [Indexed: 01/05/2023]
Abstract
PURPOSE A genetic correlation is the proportion of phenotypic variance between traits that is shared on a genetic basis. Here we explore genetic correlations between diabetes- and glaucoma-related traits. DESIGN Cross-sectional study. METHODS We assembled genome-wide association study summary statistics from European-derived participants regarding diabetes-related traits like fasting blood sugar (FBS) and type 2 diabetes (T2D) and glaucoma-related traits (intraocular pressure [IOP], central corneal thickness [CCT], corneal hysteresis [CH], corneal resistance factor [CRF], cup-to-disc ratio [CDR], and primary open-angle glaucoma [POAG]). We included data from the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database, the UK Biobank, and the International Glaucoma Genetics Consortium. We calculated genetic correlation (rg) between traits using linkage disequilibrium score regression. We also calculated genetic correlations between IOP, CCT, and select diabetes-related traits based on individual level phenotype data in 2 Northern European population-based samples using pedigree information and Sequential Oligogenic Linkage Analysis Routines. RESULTS Overall, there was little rg between diabetes- and glaucoma-related traits. Specifically, we found a nonsignificant negative correlation between T2D and POAG (rg = -0.14; P = .16). Using Sequential Oligogenic Linkage Analysis Routines, the genetic correlations between measured IOP, CCT, FBS, fasting insulin, and hemoglobin A1c were null. In contrast, genetic correlations between IOP and POAG (rg ≥ 0.45; P ≤ 3.0 × 10-4) and between CDR and POAG were high (rg = 0.57; P = 2.8 × 10-10). However, genetic correlations between corneal properties (CCT, CRF, and CH) and POAG were low (rg range -0.18 to 0.11) and nonsignificant (P ≥ .07). CONCLUSION These analyses suggest that there is limited genetic correlation between diabetes- and glaucoma-related traits.
Collapse
Affiliation(s)
- Vincent Laville
- Department of Computational Biology, Institut Pasteur, Paris, France
| | - Jae H Kang
- Channing Division of Network Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Clara C Cousins
- Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, Massachusetts, USA
| | - Adriana I Iglesias
- Departments of Ophthalmology and Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Réka Nagy
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Jessica N Cooke Bailey
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA; Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Robert P Igo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Yeunjoo E Song
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA; Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - William G Christen
- Division of Preventive Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, Massachusetts, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, Massachusetts, USA
| | - Bernard A Rosner
- Channing Division of Network Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, USA; Department of Biostatistics, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, Massachusetts, USA
| | - Frank Hu
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, Massachusetts, USA; Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, Massachusetts, USA
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom; Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Puya Gharahkhani
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Alex W Hewitt
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia; School of Medicine, Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - David A Mackey
- Lions Eye Institute, Centre for Ophthalmology and Visual Science, University of Western Australia, Perth, Western Australia, Australia
| | - Pirro G Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London, United Kingdom
| | - Christopher J Hammond
- Department of Twin Research and Genetic Epidemiology, King's College London, United Kingdom
| | - Cornelia M vanDuijn
- Departments of Ophthalmology and Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Jonathan L Haines
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA; Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - John H Fingert
- Department of Ophthalmology and Visual Science, University of Iowa, Iowa City, Iowa, USA
| | - Michael A Hauser
- Departments of Ophthalmology and Medicine, Duke University, Durham, North Carolina, USA
| | - Hugues Aschard
- Department of Computational Biology, Institut Pasteur, Paris, France; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Harvard Medical School, Boston, Massachusetts, USA
| | - Janey L Wiggs
- Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, Massachusetts, USA
| | - Anthony P Khawaja
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Louis R Pasquale
- Channing Division of Network Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts, USA; Department of Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
| |
Collapse
|
6
|
Yi YH, Cho YH, Kim YJ, Lee SY, Lee JG, Kong EH, Cho BM, Tak YJ, Hwang HR, Lee SH, Park EJ. Metabolic syndrome as a risk factor for high intraocular pressure: the Korea National Health and Nutrition Examination Survey 2008-2010. Diabetes Metab Syndr Obes 2019; 12:131-137. [PMID: 30666141 PMCID: PMC6336017 DOI: 10.2147/dmso.s185604] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND High intraocular pressure (IOP) is well established as the most significant risk factor for both the development and progression of primary open-angle glaucoma. Elevated IOP is more frequently seen in the presence of metabolic disturbances that are associated with the components of metabolic syndrome (MetS). The aim of this study was to investigate the association between ocular hypertension and MetS. PATIENTS AND METHODS We examined the relationship between ocular hypertension and MetS in 17,160 Korean adults without glaucoma aged >19 years (7,368 men and 9,792 women) who participated in the 2008-2010 Korea National Health and Nutrition Examination Survey. Multivariate logistic regression analysis was used to assess the relationship between MetS and ocular hypertension, after adjusting for age, body mass index, smoking, alcohol consumption, and regular exercise. RESULTS The prevalence of MetS was 35.1% among males and 30.1% among females. The prevalence of ocular hypertension was 1.3% among males with MetS and 0.7% among females with MetS. Participants with MetS had a significantly higher IOP than those without MetS (P≤0.001), and each component of MetS had a different effect on the IOP. Hypertension was the strongest predictor of an elevated IOP. In multivariate regression analysis, ocular hypertension was significantly associated with MetS (P=0.027 for men; P=0.015 for women). CONCLUSION There is a statistically significant relationship between MetS and ocular hypertension.
Collapse
Affiliation(s)
- Yu Hyeon Yi
- Department of Family Medicine, Pusan National University School of Medicine, Yangsan 626-780, Korea
- Department of Family Medicine, Biomedical Research Institute, Pusan National University Hospital, Busan 626-770, Korea
| | - Young Hye Cho
- Department of Family Medicine, Research Institute of Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 626-780, Korea,
| | - Yun Jin Kim
- Department of Family Medicine, Pusan National University School of Medicine, Yangsan 626-780, Korea
- Department of Family Medicine, Biomedical Research Institute, Pusan National University Hospital, Busan 626-770, Korea
| | - Sang Yeoup Lee
- Department of Family Medicine, Research Institute of Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 626-780, Korea,
| | - Jeong Gyu Lee
- Department of Family Medicine, Pusan National University School of Medicine, Yangsan 626-780, Korea
- Department of Family Medicine, Biomedical Research Institute, Pusan National University Hospital, Busan 626-770, Korea
| | - Eun Hee Kong
- Department of Family Medicine, College of Medicine, Kosin University, Busan, Korea
| | - Byung Mann Cho
- Department of Preventive Medicine, Pusan National University School of Medicine, Yangsan 626-780, Korea
| | - Young Jin Tak
- Department of Family Medicine, Pusan National University School of Medicine, Yangsan 626-780, Korea
- Department of Family Medicine, Biomedical Research Institute, Pusan National University Hospital, Busan 626-770, Korea
| | - Hye Rim Hwang
- Department of Family Medicine, Pusan National University School of Medicine, Yangsan 626-780, Korea
- Department of Family Medicine, Biomedical Research Institute, Pusan National University Hospital, Busan 626-770, Korea
| | - Seung Hun Lee
- Department of Family Medicine, Pusan National University School of Medicine, Yangsan 626-780, Korea
- Department of Family Medicine, Biomedical Research Institute, Pusan National University Hospital, Busan 626-770, Korea
| | - Eun Ju Park
- Department of Family Medicine, Research Institute of Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 626-780, Korea,
| |
Collapse
|