1
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Yang PK, Jackson SL, Charest BR, Cheng YJ, Sun YV, Raghavan S, Litkowski EM, Legvold BT, Rhee MK, Oram RA, Kuklina EV, Vujkovic M, Reaven PD, Cho K, Leong A, Wilson PWF, Zhou J, Miller DR, Sharp SA, Staimez LR, North KE, Highland HM, Phillips LS. Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP). Diabetes Care 2024:dc231927. [PMID: 38608262 DOI: 10.2337/dc23-1927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 03/11/2024] [Indexed: 04/14/2024]
Abstract
OBJECTIVE To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates. RESEARCH DESIGN AND METHODS Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011-2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%). RESULTS T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥ 90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and they resembled T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001. CONCLUSIONS Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.
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Affiliation(s)
- Peter K Yang
- Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC
| | - Sandra L Jackson
- Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Brian R Charest
- Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA
| | - Yiling J Cheng
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Yan V Sun
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Rollins School of Public Health, Emory University, Atlanta, GA
| | - Sridharan Raghavan
- Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO
- University of Colorado School of Medicine, Denver, CO
| | - Elizabeth M Litkowski
- Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO
- University of Colorado School of Medicine, Denver, CO
| | - Brian T Legvold
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA
| | - Mary K Rhee
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA
| | - Richard A Oram
- College of Medicine and Health, University of Exeter Medical School, Devon, U.K
| | - Elena V Kuklina
- Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Marijana Vujkovic
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Peter D Reaven
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA
- Brigham and Women's Hospital, Boston, MA
| | - Aaron Leong
- Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
- Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA
| | - Peter W F Wilson
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Rollins School of Public Health, Emory University, Atlanta, GA
- College of Medicine and Health, University of Exeter Medical School, Devon, U.K
| | - Jin Zhou
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
- UCLA Department of Medicine, University of California, Los Angeles, CA
| | | | - Seth A Sharp
- Division of Endocrinology and Diabetes, Stanford University, Palo Alto, CA
| | - Lisa R Staimez
- Rollins School of Public Health, Emory University, Atlanta, GA
| | - Kari E North
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC
| | - Heather M Highland
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC
| | - Lawrence S Phillips
- Atlanta Veterans Administration Medical Center, Atlanta, GA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA
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Breeyear JH, Mitchell SL, Nealon CL, Hellwege JN, Charest B, Khakharia A, Halladay CW, Yang J, Garriga GA, Wilson OD, Basnet TB, Hung AM, Reaven PD, Meigs JB, Rhee MK, Sun Y, Lynch MG, Sobrin L, Brantley MA, Sun YV, Wilson PW, Iyengar SK, Peachey NS, Phillips LS, Edwards TL, Giri A. Development of Portable Electronic Health Record Based Algorithms to Identify Individuals with Diabetic Retinopathy. medRxiv 2024:2023.11.10.23298311. [PMID: 38014167 PMCID: PMC10680882 DOI: 10.1101/2023.11.10.23298311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Objectives To develop, validate and implement algorithms to identify diabetic retinopathy (DR) cases and controls from electronic health care records (EHR)s. Methods : We developed and validated EHR-based algorithms to identify DR cases and individuals with type I or II diabetes without DR (controls) in three independent EHR systems: Vanderbilt University Medical Center Synthetic Derivative (VUMC), the VA Northeast Ohio Healthcare System (VANEOHS), and Massachusetts General Brigham (MGB). Cases were required to meet one of three criteria: 1) two or more dates with any DR ICD-9/10 code documented in the EHR, or 2) at least one affirmative health-factor or EPIC code for DR along with an ICD9/10 code for DR on a different day, or 3) at least one ICD-9/10 code for any DR occurring within 24 hours of an ophthalmology exam. Criteria for controls included affirmative evidence for diabetes as well as an ophthalmology exam. Results The algorithms, developed and evaluated in VUMC through manual chart review, resulted in a positive predictive value (PPV) of 0.93 for cases and negative predictive value (NPV) of 0.97 for controls. Implementation of algorithms yielded similar metrics in VANEOHS (PPV=0.94; NPV=0.86) and lower in MGB (PPV=0.84; NPV=0.76). In comparison, use of DR definition as implemented in Phenome-wide association study (PheWAS) in VUMC, yielded similar PPV (0.92) but substantially reduced NPV (0.48). Implementation of the algorithms to the Million Veteran Program identified over 62,000 DR cases with genetic data including 14,549 African Americans and 6,209 Hispanics with DR. Conclusions/Discussion We demonstrate the robustness of the algorithms at three separate health-care centers, with a minimum PPV of 0.84 and substantially improved NPV than existing high-throughput methods. We strongly encourage independent validation and incorporation of features unique to each EHR to enhance algorithm performance for DR cases and controls.
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Shuey MM, Lee KM, Keaton J, Khankari NK, Breeyear JH, Walker VM, Miller DR, Heberer KR, Reaven PD, Clarke SL, Lee J, Lynch JA, Vujkovic M, Edwards TL. A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records. EBioMedicine 2023; 94:104674. [PMID: 37399599 PMCID: PMC10328805 DOI: 10.1016/j.ebiom.2023.104674] [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: 12/16/2022] [Revised: 06/06/2023] [Accepted: 06/07/2023] [Indexed: 07/05/2023] Open
Abstract
BACKGROUND The identification of new uses for existing drug therapies has the potential to identify treatments for comorbid conditions that have the added benefit of glycemic control while also providing a rapid, low-cost approach to drug (re)discovery. METHODS We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR). FINDINGS After filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p = 0.01 and -0.85 mg/dL, p = 0.02, respectively; MR: OR = 0.84, 95% CI = 0.81, 0.87, p = 5.0 x 10-25). INTERPRETATION Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions. FUNDING National Institutes of Health, Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK Medical Research Council, American Heart Association, and Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program.
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Affiliation(s)
- Megan M Shuey
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kyung Min Lee
- VA Informatics and Computer Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Jacob Keaton
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA; Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nikhil K Khankari
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Joseph H Breeyear
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Nashville VA Medical Center, Nashville, TN, USA
| | - Venexia M Walker
- Medical Research Council, Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Bristol Medical School, UK; Population Health Sciences, University of Bristol, Bristol, UK; Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Donald R Miller
- Center for Healthcare Organization and Implementation Research, Bedford VA Healthcare System, Bedford, MA, USA; Center for Population Health, Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, MA, USA
| | - Kent R Heberer
- VA Palo Alto Health Care System, Palo Alto, CA, USA; Departments of Medicine and Endocrinology, Stanford University School of Medicine, Stanford, CA, USA
| | - Peter D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, USA; College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Shoa L Clarke
- Departments of Medicine and Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jennifer Lee
- VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Julie A Lynch
- VA Informatics and Computer Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA; School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA; Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Todd L Edwards
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Nashville VA Medical Center, Nashville, TN, USA.
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4
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Reaven PD, Newell M, Rivas S, Zhou X, Norman GJ, Zhou JJ. Initiation of Continuous Glucose Monitoring Is Linked to Improved Glycemic Control and Fewer Clinical Events in Type 1 and Type 2 Diabetes in the Veterans Health Administration. Diabetes Care 2023; 46:854-863. [PMID: 36807492 PMCID: PMC10260873 DOI: 10.2337/dc22-2189] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 01/23/2023] [Indexed: 02/19/2023]
Abstract
OBJECTIVE To determine the benefit of starting continuous glucose monitoring (CGM) in adult-onset type 1 diabetes (T1D) and type 2 diabetes (T2D) with regard to longer-term glucose control and serious clinical events. RESEARCH DESIGN AND METHODS A retrospective observational cohort study within the Veterans Affairs Health Care System was used to compare glucose control and hypoglycemia- or hyperglycemia-related admission to an emergency room or hospital and all-cause hospitalization between propensity score overlap weighted initiators of CGM and nonusers over 12 months. RESULTS CGM users receiving insulin (n = 5,015 with T1D and n = 15,706 with T2D) and similar numbers of nonusers were identified from 1 January 2015 to 31 December 2020. Declines in HbA1c were significantly greater in CGM users with T1D (-0.26%; 95% CI -0.33, -0.19%) and T2D (-0.35%; 95% CI -0.40, -0.31%) than in nonusers at 12 months. Percentages of patients achieving HbA1c <8 and <9% after 12 months were greater in CGM users. In T1D, CGM initiation was associated with significantly reduced risk of hypoglycemia (hazard ratio [HR] 0.69; 95% CI 0.48, 0.98) and all-cause hospitalization (HR 0.75; 95% CI 0.63, 0.90). In patients with T2D, there was a reduction in risk of hyperglycemia in CGM users (HR 0.87; 95% CI 0.77, 0.99) and all-cause hospitalization (HR 0.89; 95% CI 0.83, 0.97). Several subgroups (based on baseline age, HbA1c, hypoglycemic risk, or follow-up CGM use) had even greater responses. CONCLUSIONS In a large national cohort, initiation of CGM was associated with sustained improvement in HbA1c in patients with later-onset T1D and patients with T2D using insulin. This was accompanied by a clear pattern of reduced risk of admission to an emergency room or hospital for hypoglycemia or hyperglycemia and of all-cause hospitalization.
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Affiliation(s)
| | | | - Salvador Rivas
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
| | - Xinkai Zhou
- Medicine and Biostatistics, University of California Los Angeles, Los Angeles, CA
| | | | - Jin J. Zhou
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
- Medicine and Biostatistics, University of California Los Angeles, Los Angeles, CA
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5
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Verma A, Minnier J, Wan ES, Huffman JE, Gao L, Joseph J, Ho YL, Wu WC, Cho K, Gorman BR, Rajeevan N, Pyarajan S, Garcon H, Meigs JB, Sun YV, Reaven PD, McGeary JE, Suzuki A, Gelernter J, Lynch JA, Petersen JM, Zekavat SM, Natarajan P, Dalal S, Jhala DN, Arjomandi M, Gatsby E, Lynch KE, Bonomo RA, Freiberg M, Pathak GA, Zhou JJ, Donskey CJ, Madduri RK, Wells QS, Huang RDL, Polimanti R, Chang KM, Liao KP, Tsao PS, Wilson PWF, Hung AM, O’Donnell CJ, Gaziano JM, Hauger RL, Iyengar SK, Luoh SW. A MUC5B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality. Am J Respir Crit Care Med 2022; 206:1220-1229. [PMID: 35771531 PMCID: PMC9746845 DOI: 10.1164/rccm.202109-2166oc] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Rationale: A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. Objectives: To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). Methods: The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post-COVID-19 pneumonia were performed in MVP subjects. Measurements and Main Results: The rs35705950-T allele was associated with fewer COVID-19 hospitalizations in transancestry meta-analyses within the MVP (Ncases = 4,325; Ncontrols = 507,640; OR = 0.89 [0.82-0.97]; P = 6.86 × 10-3) and joint meta-analyses with the HGI (Ncases = 13,320; Ncontrols = 1,508,841; OR, 0.90 [0.86-0.95]; P = 8.99 × 10-5). The rs35705950-T allele was not associated with reduced COVID-19 positivity in transancestry meta-analysis within the MVP (Ncases = 19,168/Ncontrols = 492,854; OR, 0.98 [0.95-1.01]; P = 0.06) but was nominally significant (P < 0.05) in the joint meta-analysis with the HGI (Ncases = 44,820; Ncontrols = 1,775,827; OR, 0.97 [0.95-1.00]; P = 0.03). Associations were not observed with severe outcomes or mortality. Among individuals of European ancestry in the MVP, rs35705950-T was associated with fewer post-COVID-19 pneumonia events (OR, 0.82 [0.72-0.93]; P = 0.001). Conclusions: The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.
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Affiliation(s)
- Anurag Verma
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Department of Medicine, Perelman School of Medicine, and
| | - Jessica Minnier
- OHSU-PSU School of Public Health and,Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon;,VA Portland Health Care System, Portland, Oregon
| | - Emily S. Wan
- Department of Medicine, Pulmonary, Critical Care, Sleep, and Allergy Section,,Channing Division of Network Medicine and
| | | | - Lina Gao
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon;,VA Portland Health Care System, Portland, Oregon
| | - Jacob Joseph
- Department of Medicine,,Medicine, Cardiovascular, Brigham & Women’s Hospital, Boston, Massachusetts
| | | | - Wen-Chih Wu
- Department of Medicine, Cardiology, Providence VA Healthcare System, Providence, Rhode Island;,Alpert Medical School & School of Public Health, Brown University, Providence, Rhode Island
| | - Kelly Cho
- MAVERIC,,Medicine, Aging, Brigham & Women’s Hospital and
| | | | - Nallakkandi Rajeevan
- Yale Center for Medical Informatics,,Clinical Epidemiology Research Center (CERC)
| | - Saiju Pyarajan
- MAVERIC,,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | | | | | - Yan V. Sun
- Epidemiology, School of Public Health and,Atlanta VA Healthcare System, Decatur, Georgia
| | - Peter D. Reaven
- Department of Medicine, Phoenix VA Healthcare System, Phoenix, Arizona;,College of Medicine, University of Arizona, Phoenix, Arizona
| | - John E. McGeary
- Department of Psychiatry and Human Behavior, Providence VA Medical Center, Providence, Rhode Island;,Department of Psychiatry and Human Behavior, Brown University Medical School, Providence, Rhode Island
| | - Ayako Suzuki
- Department of Medicine, Gastroenterology, Durham VA Medical Center, Durham, North Carolina;,Department of Medicine, Gastroenterology, Duke University, Durham, North Carolina
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, and,VA Connecticut Healthcare System, West Haven, Connecticut
| | - Julie A. Lynch
- VA Informatics & Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah;,Department of Medicine and
| | - Jeffrey M. Petersen
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Seyedeh Maryam Zekavat
- Computational Biology & Bioinformatics, Yale University School of Medicine, New Haven, Connecticut;,Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Pradeep Natarajan
- Department of Medicine, Harvard Medical School, Boston, Massachusetts;,Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts;,Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Sharvari Dalal
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Darshana N. Jhala
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Mehrdad Arjomandi
- Medicine, Pulmonary and Critical Care, San Francisco VA Healthcare System, University of California, San Francisco, San Francisco, California
| | - Elise Gatsby
- VA Informatics & Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah
| | - Kristine E. Lynch
- VA Informatics & Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah;,Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
| | | | | | - Gita A. Pathak
- Division of Human Genetics, Department of Psychiatry, and,VA Connecticut Healthcare System, West Haven, Connecticut
| | - Jin J. Zhou
- Department of Medicine, University of California, Los Angeles, Los Angeles, California;,Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona
| | | | - Ravi K. Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, Illinois
| | - Quinn S. Wells
- Department of Medicine,,Department of Biomedical Informatics, and,Department of Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, and,VA Connecticut Healthcare System, West Haven, Connecticut
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | | | - Philip S. Tsao
- Precision Medicine, VA Palo Alto Health Care System, Palo Alto, California
| | - Peter W. F. Wilson
- Emory University, Atlanta, Georgia;,Atlanta VA Healthcare System, Decatur, Georgia
| | - Adriana M. Hung
- Department of Veteran’s Affairs, Tennessee Valley Healthcare System, Vanderbilt University Medical Center, Division of Nephrology & Hypertension, Nashville, Tennessee
| | | | | | - Richard L. Hauger
- Center of Excellence for Stress & Mental Health, VA San Diego Healthcare System, San Diego, California; and,Center for Behavioral Genetics of Aging, University of California, San Diego, La Jolla, California
| | - Sudha K. Iyengar
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio;,Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio
| | - Shiuh-Wen Luoh
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon;,VA Portland Health Care System, Portland, Oregon
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Griffiths DR, Matthew Law L, Young C, Fuentes A, Truran S, Karamanova N, Bell LC, Turner G, Emerson H, Mastroeni D, Gonzales RJ, Reaven PD, Chad Quarles C, Migrino RQ, Lifshitz J. Chronic Cognitive and Cerebrovascular Function after Mild Traumatic Brain Injury in Rats. J Neurotrauma 2022; 39:1429-1441. [PMID: 35593008 PMCID: PMC10870816 DOI: 10.1089/neu.2022.0015] [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] [Indexed: 11/12/2022] Open
Abstract
Severe traumatic brain injury (TBI) results in cognitive dysfunction in part due to vascular perturbations. In contrast, the long-term vasculo-cognitive pathophysiology of mild TBI (mTBI) remains unknown. We evaluated mTBI effects on chronic cognitive and cerebrovascular function and assessed their interrelationships. Sprague-Dawley rats received midline fluid percussion injury (n = 20) or sham (n = 21). Cognitive function was assessed (3- and 6-month novel object recognition [NOR], novel object location [NOL], and temporal order object recognition [TOR]). Six-month cerebral blood flow (CBF) and cerebral blood volume (CBV) using contrast magnetic resonance imaging (MRI) and ex vivo circle of Willis artery endothelial and smooth muscle-dependent function were measured. mTBI rats showed significantly impaired NOR, with similar trends (non-significant) in NOL/TOR. Regional CBF and CBV were similar in sham and mTBI. NOR correlated with CBF in lateral hippocampus, medial hippocampus, and primary somatosensory barrel cortex, whereas it inversely correlated with arterial smooth muscle-dependent dilation. Six-month baseline endothelial and smooth muscle-dependent arterial function were similar among mTBI and sham, but post-angiotensin 2 stimulation, mTBI showed no change in smooth muscle-dependent dilation from baseline response, unlike the reduction in sham. mTBI led to chronic cognitive dysfunction and altered angiotensin 2-stimulated smooth muscle-dependent vasoreactivity. The findings of persistent pathophysiological consequences of mTBI in this animal model add to the broader understanding of chronic pathophysiological sequelae in human mild TBI.
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Affiliation(s)
- Daniel R. Griffiths
- Phoenix VA Health Care System, Phoenix, Arizona, USA
- University of Arizona College of Medicine – Phoenix, Phoenix, Arizona, USA
- Barrow Neurological Institute at Phoenix Children’s Hospital, Phoenix, Arizona, USA
| | - L. Matthew Law
- Phoenix VA Health Care System, Phoenix, Arizona, USA
- University of Arizona College of Medicine – Phoenix, Phoenix, Arizona, USA
- Barrow Neurological Institute at Phoenix Children’s Hospital, Phoenix, Arizona, USA
| | - Conor Young
- University of Arizona College of Medicine – Phoenix, Phoenix, Arizona, USA
| | | | - Seth Truran
- Phoenix VA Health Care System, Phoenix, Arizona, USA
| | | | - Laura C. Bell
- Barrow Neurological Institute, Phoenix, Arizona, USA
| | | | | | | | - Rayna J. Gonzales
- University of Arizona College of Medicine – Phoenix, Phoenix, Arizona, USA
| | - Peter D. Reaven
- Phoenix VA Health Care System, Phoenix, Arizona, USA
- University of Arizona College of Medicine – Phoenix, Phoenix, Arizona, USA
| | | | - Raymond Q. Migrino
- Phoenix VA Health Care System, Phoenix, Arizona, USA
- University of Arizona College of Medicine – Phoenix, Phoenix, Arizona, USA
| | - Jonathan Lifshitz
- Phoenix VA Health Care System, Phoenix, Arizona, USA
- University of Arizona College of Medicine – Phoenix, Phoenix, Arizona, USA
- Barrow Neurological Institute at Phoenix Children’s Hospital, Phoenix, Arizona, USA
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7
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Koska J, Furtado J, Hu Y, Sinari S, Budoff MJ, Billheimer D, Nedelkov D, McClelland RL, Reaven PD. Plasma proteoforms of apolipoproteins C-I and C-II are associated with plasma lipids in the Multi-Ethnic Study of Atherosclerosis. J Lipid Res 2022; 63:100263. [PMID: 35952903 PMCID: PMC9494236 DOI: 10.1016/j.jlr.2022.100263] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/23/2022] [Accepted: 07/09/2022] [Indexed: 11/23/2022] Open
Abstract
Apolipoproteins (apo) C-I and C-II are key regulators of triglyceride and HDL metabolism. Both exist as full-size native and truncated (apoC-I'; apoC-II') posttranslational proteoforms. However, the determinants and the role of these proteoforms in lipid metabolism are unknown. Here, we measured apoC-I and apoC-II proteoforms by mass spectrometry immunoassay in baseline and 10-year follow-up plasma samples from the Multi-Ethnic Study of Atherosclerosis. We found that baseline total apoC-I (mean = 9.2 mg/dl) was lower in African Americans (AA), Chinese Americans (CA), and Hispanics (by 1.8; 1.0; 1.0 mg/dl vs. whites), higher in women (by 1.2 mg/dl), and positively associated with plasma triglycerides and HDL. Furthermore, we observed that the truncated-to-native apoC-I ratio (apoC-I'/C-I) was lower in CA, negatively associated with triglycerides, and positively associated with HDL. We determined that total apoC-II (8.8 mg/dl) was lower in AA (by 0.8 mg/dl) and higher in CA and Hispanics (by 0.5 and 0.4 mg/dl), positively associated with triglycerides, and negatively associated with HDL. In addition, apoC-II'/C-II was higher in AA and women, negatively associated with triglycerides, and positively associated with HDL. We showed that the change in triglycerides was positively associated with changes in total apoC-I and apoC-II and negatively associated with changes in apoC-I'/C-I and apoC-II'/C-II, whereas the change in HDL was positively associated with changes in total apoC-I and apoC-II'/C-II and negatively associated with change in total apoC-II. This study documents racial/ethnic variation in apoC-I and apoC-II plasma levels and highlights apolipoprotein posttranslational modification as a potential regulator of plasma lipids.
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Affiliation(s)
- Juraj Koska
- Phoenix VA Health Care System, Phoenix, AZ, USA.
| | - Jeremy Furtado
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Shripad Sinari
- Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
| | | | - Dean Billheimer
- Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
| | | | | | - Peter D Reaven
- College of Health Solutions, Arizona State University, Phoenix, AZ, USA
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8
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Tcheandjieu C, Zhu X, Hilliard AT, Clarke SL, Napolioni V, Ma S, Lee KM, Fang H, Chen F, Lu Y, Tsao NL, Raghavan S, Koyama S, Gorman BR, Vujkovic M, Klarin D, Levin MG, Sinnott-Armstrong N, Wojcik GL, Plomondon ME, Maddox TM, Waldo SW, Bick AG, Pyarajan S, Huang J, Song R, Ho YL, Buyske S, Kooperberg C, Haessler J, Loos RJF, Do R, Verbanck M, Chaudhary K, North KE, Avery CL, Graff M, Haiman CA, Le Marchand L, Wilkens LR, Bis JC, Leonard H, Shen B, Lange LA, Giri A, Dikilitas O, Kullo IJ, Stanaway IB, Jarvik GP, Gordon AS, Hebbring S, Namjou B, Kaufman KM, Ito K, Ishigaki K, Kamatani Y, Verma SS, Ritchie MD, Kember RL, Baras A, Lotta LA, Kathiresan S, Hauser ER, Miller DR, Lee JS, Saleheen D, Reaven PD, Cho K, Gaziano JM, Natarajan P, Huffman JE, Voight BF, Rader DJ, Chang KM, Lynch JA, Damrauer SM, Wilson PWF, Tang H, Sun YV, Tsao PS, O'Donnell CJ, Assimes TL. Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. Nat Med 2022; 28:1679-1692. [PMID: 35915156 PMCID: PMC9419655 DOI: 10.1038/s41591-022-01891-3] [Citation(s) in RCA: 87] [Impact Index Per Article: 43.5] [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: 02/25/2021] [Accepted: 06/08/2022] [Indexed: 02/03/2023]
Abstract
We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.
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Affiliation(s)
- Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto, CA, USA.
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA.
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
| | - Xiang Zhu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
- Department of Statistics, The Pennsylvania State University, University Park, PA, USA
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
| | | | - Shoa L Clarke
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Shining Ma
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Kyung Min Lee
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Huaying Fang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Fei Chen
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Yingchang Lu
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Noah L Tsao
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sridharan Raghavan
- Medicine Service, VA Eastern Colorado Health Care System, Aurora, CO, USA
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Bryan R Gorman
- VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Derek Klarin
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Vascular Surgery and Endovascular Therapy, University of Florida School of Medicine, Gainesville, FL, USA
- Stanford University School of Medicine, Stanford, CA, USA
| | - Michael G Levin
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nasa Sinnott-Armstrong
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Genevieve L Wojcik
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Mary E Plomondon
- Department of Medicine, Rocky Mountain Regional VA Medical Center, Aurora, CO, USA
- CART Program, VHA Office of Quality and Patient Safety, Washington, DC, USA
| | - Thomas M Maddox
- Healthcare Innovation Lab, JC HealthCare/Washington University School of Medicine, St Louis, MO, USA
- Division of Cardiology, Washington University School of Medicine, St Louis, MO, USA
| | - Stephen W Waldo
- Department of Medicine, Rocky Mountain Regional VA Medical Center, Aurora, CO, USA
- CART Program, VHA Office of Quality and Patient Safety, Washington, DC, USA
- Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Alexander G Bick
- Department of Biomedical Informatics, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jie Huang
- VA Boston Healthcare System, Boston, MA, USA
- Department of Global Health, Peking University School of Public Health, Beijing, China
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | | | - Yuk-Lam Ho
- VA Boston Healthcare System, Boston, MA, USA
| | - Steven Buyske
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ron Do
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marie Verbanck
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- EA 7537 BioSTM, Université de Paris, Paris, France
| | - Kumardeep Chaudhary
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Christy L Avery
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Loïc Le Marchand
- Cancer Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Lynne R Wilkens
- Cancer Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Joshua C Bis
- Department of Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Hampton Leonard
- Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Data Tecnica Int'l, LLC, Glen Echo, MD, USA
| | - Botong Shen
- Health Disparities Research Section, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Leslie A Lange
- Department of Medicine, Division of Biomedical Informatics and Personalized Medicine, Aurora, CO, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ayush Giri
- Department of Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Obstetrics and Gynecology, Division of Quantitative Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ozan Dikilitas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ian B Stanaway
- Department of Medicine, Division of Nephrology, University of Washington, Seattle, WA, USA
| | - Gail P Jarvik
- Department of Medicine, Medical Genetics, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Adam S Gordon
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Scott Hebbring
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Bahram Namjou
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Kenneth M Kaufman
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences - The University of Tokyo, Tokyo, Japan
| | - Shefali S Verma
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rachel L Kember
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
| | | | - Sekar Kathiresan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Cardiology Division, Massachusetts General Hospital, Boston, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - Elizabeth R Hauser
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Donald R Miller
- Center for Healthcare Organization and Implementation Research, Bedford VA Healthcare System, Bedford, MA, USA
- Center for Population Health, Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, MA, USA
| | - Jennifer S Lee
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Danish Saleheen
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Division of Cardiology, Columbia University, New York, NY, USA
| | - Peter D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, USA
- College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Michael Gaziano
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Cardiology Division, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | | | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel J Rader
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Julie A Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- College of Nursing and Health Sciences, University of Massachusetts, Boston, MA, USA
| | - Scott M Damrauer
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Peter W F Wilson
- Atlanta VA Medical Center, Atlanta, GA, USA
- Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Yan V Sun
- Atlanta VA Health Care System, Atlanta, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Themistocles L Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, USA.
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
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9
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Verma A, Huffman JE, Gao L, Minnier J, Wu WC, Cho K, Ho YL, Gorman BR, Pyarajan S, Rajeevan N, Garcon H, Joseph J, McGeary JE, Suzuki A, Reaven PD, Wan ES, Lynch JA, Petersen JM, Meigs JB, Freiberg MS, Gatsby E, Lynch KE, Zekavat SM, Natarajan P, Dalal S, Jhala DN, Arjomandi M, Bonomo RA, Thompson TK, Pathak GA, Zhou JJ, Donskey CJ, Madduri RK, Wells QS, Gelernter J, Huang RDL, Polimanti R, Chang KM, Liao KP, Tsao PS, Sun YV, Wilson PWF, O’Donnell CJ, Hung AM, Gaziano JM, Hauger RL, Iyengar SK, Luoh SW. Association of Kidney Comorbidities and Acute Kidney Failure With Unfavorable Outcomes After COVID-19 in Individuals With the Sickle Cell Trait. JAMA Intern Med 2022; 182:796-804. [PMID: 35759254 PMCID: PMC9237798 DOI: 10.1001/jamainternmed.2022.2141] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Importance Sickle cell trait (SCT), defined as the presence of 1 hemoglobin beta sickle allele (rs334-T) and 1 normal beta allele, is prevalent in millions of people in the US, particularly in individuals of African and Hispanic ancestry. However, the association of SCT with COVID-19 is unclear. Objective To assess the association of SCT with the prepandemic health conditions in participants of the Million Veteran Program (MVP) and to assess the severity and sequelae of COVID-19. Design, Setting, and Participants COVID-19 clinical data include 2729 persons with SCT, of whom 353 had COVID-19, and 129 848 SCT-negative individuals, of whom 13 488 had COVID-19. Associations between SCT and COVID-19 outcomes were examined using firth regression. Analyses were performed by ancestry and adjusted for sex, age, age squared, and ancestral principal components to account for population stratification. Data for the study were collected between March 2020 and February 2021. Exposures The hemoglobin beta S (HbS) allele (rs334-T). Main Outcomes and Measures This study evaluated 4 COVID-19 outcomes derived from the World Health Organization severity scale and phenotypes derived from International Classification of Diseases codes in the electronic health records. Results Of the 132 577 MVP participants with COVID-19 data, mean (SD) age at the index date was 64.8 (13.1) years. Sickle cell trait was present in 7.8% of individuals of African ancestry and associated with a history of chronic kidney disease, diabetic kidney disease, hypertensive kidney disease, pulmonary embolism, and cerebrovascular disease. Among the 4 clinical outcomes of COVID-19, SCT was associated with an increased COVID-19 mortality in individuals of African ancestry (n = 3749; odds ratio, 1.77; 95% CI, 1.13 to 2.77; P = .01). In the 60 days following COVID-19, SCT was associated with an increased incidence of acute kidney failure. A counterfactual mediation framework estimated that on average, 20.7% (95% CI, -3.8% to 56.0%) of the total effect of SCT on COVID-19 fatalities was due to acute kidney failure. Conclusions and Relevance In this genetic association study, SCT was associated with preexisting kidney comorbidities, increased COVID-19 mortality, and kidney morbidity.
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Affiliation(s)
- Anurag Verma
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Perelman School of Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
| | | | - Lina Gao
- Knight Cancer Institute, Biostatistics Shared Resource, Oregon Health & Science University, Portland
- VA Portland Health Care System, Portland, Oregon
| | - Jessica Minnier
- VA Portland Health Care System, Portland, Oregon
- OHSU-PSU School of Public Health, Oregon Health & Science University, Portland
- Knight Cancer Institute, Biostatistics Shared Resource, Oregon Health & Science University, Portland
| | - Wen-Chih Wu
- Department of Medicine, Cardiology, Providence VA Healthcare System, Providence, Rhode Island
- Alpert Medical School & School of Public Health, Brown University, Providence, Rhode Island
| | - Kelly Cho
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts
- Medicine, Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Yuk-Lam Ho
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts
| | | | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Nallakkandi Rajeevan
- Yale Center for Medical Informatics, Yale School of Medicine, New Haven, Connecticut
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven
| | - Helene Garcon
- MAVERIC, VA Boston Healthcare System, Boston, Massachusetts
| | - Jacob Joseph
- Department of Medicine, VA Boston Healthcare System, Boston, Massachusetts
- Brigham & Women’s Hospital, Boston, Massachusetts
| | - John E. McGeary
- Department of Psychiatry and Human Behavior, Providence VA Medical Center, Providence, Rhode Island
- Brown University Medical School, Providence, Rhode Island
| | - Ayako Suzuki
- Department of Medicine, Gastroenterology, Durham VA Medical Center, Durham, North Carolina
- Department of Medicine, Gastroenterology, Duke University, Durham, North Carolina
| | - Peter D. Reaven
- Department of Medicine, Phoenix VA Healthcare System, Phoenix, Arizona
- University of Arizona, Phoenix
| | - Emily S. Wan
- Department of Medicine, Pulmonary, Critical Care, Sleep, and Allergy Section, VA Boston Healthcare System, Boston, Massachusetts
- Channing Division of Network Medicine, Brigham & Women’s Hospital, Boston, Massachusetts
| | - Julie A. Lynch
- VA Informatics & Computing Infrastructure, VA Salt Lake City Utah & University of Utah, School of Medicine, Salt Lake City
| | - Jeffrey M. Petersen
- Pathology and Laboratory Medicine, Corporal Michael Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - James B. Meigs
- Medicine, General Internal Medicine, Massachusetts General Hospital, Boston
| | | | - Elise Gatsby
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah
| | - Kristine E. Lynch
- VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah
- Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City
| | - Seyedeh Maryam Zekavat
- Computational Biology & Bioinformatics, Yale School of Medicine, New Haven, Connecticut
- Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
- Cardiovascular Research Center, Massachusetts General Hospital, Boston
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Clinical Data Science Research Group, ORD, Portland VA Medical Center, Portland, Oregon
| | - Sharvari Dalal
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Pathology and Laboratory Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - Darshana N. Jhala
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Pathology and Laboratory Medicine, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - Mehrdad Arjomandi
- Medicine, Pulmonary and Critical Care, San Francisco VA Healthcare System, San Francisco, California
- University of California San Francisco
| | - Robert A. Bonomo
- Cleveland VA Medical Center, Cleveland, Ohio
- Medicine, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | | | - Gita A. Pathak
- Department of Psychiatry, Division of Human Genetics, Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare System, West Haven
| | - Jin J. Zhou
- Medicine, University of California, Los Angeles
- Epidemiology and Biostatistics, University of Arizona, Phoenix
| | - Curtis J. Donskey
- Infectious Disease Section, Louis Stokes Cleveland VA, Cleveland, Ohio
- Case Western Reserve University, Cleveland, Ohio
| | - Ravi K. Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, Illinois
| | - Quinn S. Wells
- Departments of Medicine, Biomedical Informatics, and Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Joel Gelernter
- VA Connecticut Healthcare System, West Haven
- Psychiatry, Human Genetics, Yale University School of Medicine, West Haven, Connecticut
| | | | - Renato Polimanti
- Departments of Medicine, Biomedical Informatics, and Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
- Psychiatry, Human Genetics, Yale University School of Medicine, West Haven, Connecticut
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Katherine P. Liao
- Medicine, Rheumatology, VA Boston Healthcare System, Boston, Massachusetts
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Medicine & Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Philip S. Tsao
- Precision Medicine, VA Palo Alto Health Care System, Palo Alto, California
| | - Yan V. Sun
- Epidemiology, Emory University School of Public Health, Atlanta, Georgia
- Atlanta VA Health Care System, Decatur, Georgia
| | - Peter W. F. Wilson
- Atlanta VA Health Care System, Decatur, Georgia
- Emory University School of Medicine, Atlanta, Georgia
| | | | - Adriana M. Hung
- Vanderbilt University Medical Center, Nashville, Tennessee
- Nashville VA Medical Center, Nashville, Tennessee
| | - J. Michael Gaziano
- VA Boston Health Care System, Boston, Massachusetts
- Medicine, Harvard Medical School, Boston, Massachusetts
| | - Richard L. Hauger
- Center of Excellence for Stress & Mental Health, VA San Diego Healthcare System, San Diego, California
- Center for Behavioral Genetics of Aging, University of California, San Diego, La Jolla
| | - Sudha K. Iyengar
- Departments of Population and Quantitative Health Sciences, Ophthalmology and Visual Sciences and Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio
- Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio
| | - Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, Oregon
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland
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10
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Koska J, Gerstein HC, Beisswenger PJ, Reaven PD. Response to Comment on Koska et al. Advanced Glycation End Products Predict Loss of Renal Function and High-Risk Chronic Kidney Disease in Type 2 Diabetes. Diabetes Care 2022;44:684-691. Diabetes Care 2022; 45:e111-e112. [PMID: 35653599 PMCID: PMC9210513 DOI: 10.2337/dci22-0013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Juraj Koska
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
| | | | | | - Peter D Reaven
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ.,The University of Arizona College of Medicine-Phoenix, Phoenix, AZ
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11
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Vujkovic M, Ramdas S, Lorenz KM, Guo X, Darlay R, Cordell HJ, He J, Gindin Y, Chung C, Myers RP, Schneider CV, Park J, Lee KM, Serper M, Carr RM, Kaplan DE, Haas ME, MacLean MT, Witschey WR, Zhu X, Tcheandjieu C, Kember RL, Kranzler HR, Verma A, Giri A, Klarin DM, Sun YV, Huang J, Huffman JE, Creasy KT, Hand NJ, Liu CT, Long MT, Yao J, Budoff M, Tan J, Li X, Lin HJ, Chen YDI, Taylor KD, Chang RK, Krauss RM, Vilarinho S, Brancale J, Nielsen JB, Locke AE, Jones MB, Verweij N, Baras A, Reddy KR, Neuschwander-Tetri BA, Schwimmer JB, Sanyal AJ, Chalasani N, Ryan KA, Mitchell BD, Gill D, Wells AD, Manduchi E, Saiman Y, Mahmud N, Miller DR, Reaven PD, Phillips LS, Muralidhar S, DuVall SL, Lee JS, Assimes TL, Pyarajan S, Cho K, Edwards TL, Damrauer SM, Wilson PW, Gaziano JM, O'Donnell CJ, Khera AV, Grant SFA, Brown CD, Tsao PS, Saleheen D, Lotta LA, Bastarache L, Anstee QM, Daly AK, Meigs JB, Rotter JI, Lynch JA, Rader DJ, Voight BF, Chang KM. A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation. Nat Genet 2022; 54:761-771. [PMID: 35654975 PMCID: PMC10024253 DOI: 10.1038/s41588-022-01078-z] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [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: 12/18/2020] [Accepted: 04/18/2022] [Indexed: 02/05/2023]
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic elevation of alanine aminotransferase (cALT) levels without other liver diseases, we performed a multiancestry genome-wide association study (GWAS) in the Million Veteran Program (MVP) including 90,408 cALT cases and 128,187 controls. Seventy-seven loci exceeded genome-wide significance, including 25 without prior NAFLD or alanine aminotransferase associations, with one additional locus identified in European American-only and two in African American-only analyses (P < 5 × 10-8). External replication in histology-defined NAFLD cohorts (7,397 cases and 56,785 controls) or radiologic imaging cohorts (n = 44,289) replicated 17 single-nucleotide polymorphisms (SNPs) (P < 6.5 × 10-4), of which 9 were new (TRIB1, PPARG, MTTP, SERPINA1, FTO, IL1RN, COBLL1, APOH and IFI30). Pleiotropy analysis showed that 61 of 77 multiancestry and all 17 replicated SNPs were jointly associated with metabolic and/or inflammatory traits, revealing a complex model of genetic architecture. Our approach integrating cALT, histology and imaging reveals new insights into genetic liability to NAFLD.
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Affiliation(s)
- Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Shweta Ramdas
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kim M Lorenz
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Rebecca Darlay
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Heather J Cordell
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Jing He
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Robert P Myers
- Gilead Sciences, Inc., Foster City, CA, USA
- The Liver Company, Palo Alto, CA, USA
| | - Carolin V Schneider
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joseph Park
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kyung Min Lee
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Marina Serper
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rotonya M Carr
- Division of Gastroenterology, University of Washington, Seattle, WA, USA
| | - David E Kaplan
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mary E Haas
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matthew T MacLean
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Walter R Witschey
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Xiang Zhu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Statistics, The Pennsylvania State University, University Park, PA, USA
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Rachel L Kember
- Mental Illness Research Education and Clinical Center, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Henry R Kranzler
- Mental Illness Research Education and Clinical Center, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Anurag Verma
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ayush Giri
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Derek M Klarin
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Division of Vascular Surgery, Stanford University School of Medicine, Palo Alto, CA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yan V Sun
- Atlanta VA Medical Center, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Jie Huang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | | | - Kate Townsend Creasy
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nicholas J Hand
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Michelle T Long
- Department of Medicine, Section of Gastroenterology, Boston University School of Medicine, Boston, MA, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Matthew Budoff
- Department of Cardiology, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Xiaohui Li
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Henry J Lin
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ruey-Kang Chang
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ronald M Krauss
- Departments of Pediatrics and Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Silvia Vilarinho
- Section of Digestive Diseases, Department of Internal Medicine, and Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Joseph Brancale
- Section of Digestive Diseases, Department of Internal Medicine, and Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | | | | | | | | | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - K Rajender Reddy
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Jeffrey B Schwimmer
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Arun J Sanyal
- Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Naga Chalasani
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kathleen A Ryan
- Program for Personalized and Genomic Medicine, Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Braxton D Mitchell
- Program for Personalized and Genomic Medicine, Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Andrew D Wells
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pathology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Elisabetta Manduchi
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yedidya Saiman
- Department of Medicine, Section of Hepatology, Lewis Katz School of Medicine at Temple University, Temple University Hospital, Philadelphia, PA, USA
| | - Nadim Mahmud
- Department of Medicine, Division of Gastroenterology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Donald R Miller
- Center for Healthcare Organization and Implementation Research, Bedford VA Healthcare System, Bedford, MA, USA
- Center for Population Health, Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, MA, USA
| | - Peter D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, USA
- College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Lawrence S Phillips
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Endocrinology, Emory University School of Medicine, Atlanta, GA, USA
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC, USA
| | - Scott L DuVall
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Jennifer S Lee
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Themistocles L Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Todd L Edwards
- Nashville VA Medical Center, Nashville, TN, USA
- Division of Epidemiology, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Scott M Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Peter W Wilson
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA
| | - J Michael Gaziano
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Amit V Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Struan F A Grant
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Christopher D Brown
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Danish Saleheen
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
| | | | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Quentin M Anstee
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- Newcastle NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Ann K Daly
- Newcastle NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - James B Meigs
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Julie A Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
- College of Nursing and Health Sciences, University of Massachusetts, Lowell, MA, USA
| | - Daniel J Rader
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
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12
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Khankari NK, Keaton JM, Walker VM, Lee KM, Shuey MM, Clarke SL, Heberer KR, Miller DR, Reaven PD, Lynch JA, Vujkovic M, Edwards TL. Using Mendelian randomisation to identify opportunities for type 2 diabetes prevention by repurposing medications used for lipid management. EBioMedicine 2022; 80:104038. [PMID: 35500537 PMCID: PMC9062817 DOI: 10.1016/j.ebiom.2022.104038] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 03/14/2022] [Accepted: 04/14/2022] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Maintaining a healthy lifestyle to reduce type 2 diabetes (T2D) risk is challenging and additional strategies for T2D prevention are needed. We evaluated several lipid control medications as potential therapeutic options for T2D prevention using tissue-specific predicted gene expression summary statistics in a two-sample Mendelian randomisation (MR) design. METHODS Large-scale European genome-wide summary statistics for lipids and T2D were leveraged in our multi-stage analysis to estimate changes in either lipid levels or T2D risk driven by tissue-specific predicted gene expression. We incorporated tissue-specific predicted gene expression summary statistics to proxy therapeutic effects of three lipid control medications [i.e., statins, icosapent ethyl (IPE), and proprotein convertase subtilisin/kexin type-9 inhibitors (PCSK-9i)] on T2D susceptibility using two-sample Mendelian randomisation (MR). FINDINGS IPE, as proxied via increased FADS1 expression, was predicted to lower triglycerides and was associated with a 53% reduced risk of T2D. Statins and PCSK-9i, as proxied by reduced HMGCR and PCSK9 expression, respectively, were predicted to lower LDL-C levels but were not associated with T2D susceptibility. INTERPRETATION Triglyceride lowering via IPE may reduce the risk of developing T2D in populations of European ancestry. However, experimental validation using animal models is needed to substantiate our results and to motivate randomized control trials (RCTs) for IPE as putative treatment for T2D prevention. FUNDING Only summary statistics were used in this analysis. Funding information is detailed under Acknowledgments.
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Affiliation(s)
- Nikhil K Khankari
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, 2525 West End Ave, Suite 700, Nashville, TN 37203, USA.
| | - Jacob M Keaton
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA; Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Venexia M Walker
- Medical Research Council, Integrative Epidemiology Unit, University of Bristol, Bristol, UK; Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK; Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kyung Min Lee
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Megan M Shuey
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, 2525 West End Ave, Suite 700, Nashville, TN 37203, USA
| | - Shoa L Clarke
- Departments of Medicine and Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Kent R Heberer
- VA Palo Alto Health Care System, Palo Alto, CA, USA; Departments of Medicine and Endocrinology, Stanford University School of Medicine, Stanford, CA, USA
| | - Donald R Miller
- Center for Healthcare Organization and Implementation Research, Bedford VA Healthcare System, Bedford, MA, USA; Center for Population Health, Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, MA, USA
| | - Peter D Reaven
- Phoenix VA Health Care Center, Phoenix, AZ, USA; College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA; College of Nursing and Health Sciences, University of Massachusetts, Lowell, MA, USA
| | - Marijana Vujkovic
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Todd L Edwards
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, 2525 West End Ave, Suite 700, Nashville, TN 37203, USA; Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Nashville VA Medical Center, Nashville, TN, USA.
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13
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Nuyujukian DS, Newell MS, Zhou JJ, Koska J, Reaven PD. Baseline blood pressure modifies the role of blood pressure variability in mortality: Results from the ACCORD trial. Diabetes Obes Metab 2022; 24:951-955. [PMID: 35014154 PMCID: PMC8986598 DOI: 10.1111/dom.14649] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [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: 11/15/2021] [Revised: 12/22/2021] [Accepted: 01/06/2022] [Indexed: 11/30/2022]
Affiliation(s)
- Daniel S Nuyujukian
- Research Service, Phoenix VA Health Care System, Phoenix, Arizona, USA
- Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA
| | - Michelle S Newell
- Research Service, Phoenix VA Health Care System, Phoenix, Arizona, USA
| | - Jin J Zhou
- Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA
- Medicine, University of California, Los Angeles, California, USA
| | - Juraj Koska
- Research Service, Phoenix VA Health Care System, Phoenix, Arizona, USA
| | - Peter D Reaven
- Research Service, Phoenix VA Health Care System, Phoenix, Arizona, USA
- College of Medicine-Phoenix, University of Arizona, Phoenix, Arizona, USA
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14
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Koska J, Gerstein HC, Beisswenger PJ, Reaven PD. Advanced Glycation End Products Predict Loss of Renal Function and High-Risk Chronic Kidney Disease in Type 2 Diabetes. Diabetes Care 2022; 45:684-691. [PMID: 35051276 PMCID: PMC8918197 DOI: 10.2337/dc21-2196] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [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: 10/21/2021] [Accepted: 12/18/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To evaluate the association of a multicomponent advanced glycation end product (AGE) panel with decline in kidney function and its utility in predicting renal function loss (RFL) when added to routine clinical measures in type 2 diabetes. RESEARCH DESIGN AND METHODS Carboxymethyl and carboxyethyl lysine and methylglyoxal, 3-deoxyglucosone, and glyoxal hydroimidazolones were measured in baseline serum and plasma samples, respectively, from Action to Control Cardiovascular Risk in Diabetes (ACCORD) (n = 1,150) and Veterans Affairs Diabetes Trial (VADT) (n = 447) participants. A composite AGE score was calculated from individual AGE z scores. The primary outcome was a sustained 30% decline in estimated glomerular filtration rate (eGFR) (30% RFL in both cohorts). Secondary outcomes (in ACCORD) were 40% RFL, macroalbuminuria, and high-risk chronic kidney disease (hrCKD). RESULTS After adjustment for baseline and follow-up HbA1c and other risk factors in ACCORD, the AGE score was associated with reduction in eGFR (β-estimate -0.66 mL/min ⋅ 1.73 m2 per year; P = 0.001), 30% RFL (hazard ratio 1.42 [95% CI 1.13-1.78]; P = 0.003), 40% RFL (1.40 [1.13-1.74]; P = 0.003), macroalbuminuria (1.53 [1.13-2.06]; P = 0.006), and hrCKD (1.88 [1.37-2.57]; P < 0.0001). AGE score improved net reclassification (NRI) and relative integrated discrimination (IDI) for 30% RFL (NRI 23%; P = 0.02) (relative IDI 7%; P = 0.009). In VADT, the AGE score calculated by the ACCORD-derived coefficients was associated with 30% RFL (1.37 [1.03-1.82); P = 0.03) and improved NRI (24%; P = 0.03) but not IDI (P = 0.18). CONCLUSIONS These data provide further support for a causal role of AGEs in diabetic nephropathy independently of glycemic control and suggest utility of the composite AGE panel in predicting long-term decline in renal function.
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Affiliation(s)
- Juraj Koska
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
| | | | | | - Peter D Reaven
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ.,University of Arizona College of Medicine-Phoenix, Phoenix, AZ
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15
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Nuyujukian DS, Zhou JJ, Koska J, Reaven PD. Refining determinants of associations of visit-to-visit blood pressure variability with cardiovascular risk: results from the Action to Control Cardiovascular Risk in Diabetes Trial. J Hypertens 2021; 39:2173-2182. [PMID: 34232160 PMCID: PMC8500916 DOI: 10.1097/hjh.0000000000002931] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [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] [Indexed: 11/27/2022]
Abstract
OBJECTIVES As there is uncertainty about the extent to which baseline blood pressure level or cardiovascular risk modifies the relationship between blood pressure variability (BPv) and cardiovascular disease, we comprehensively examined the role of BPv in cardiovascular disease risk in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Trial. METHODS Using data from ACCORD, we examined the relationship of BPv with development of the primary CVD outcome, major coronary heart disease (CHD), and total stroke using time-dependent Cox proportional hazards models. RESULTS BPv was associated with the primary CVD outcome and major CHD but not stroke. The positive association with the primary CVD outcome and major CHD was more pronounced in low and high strata of baseline SBP (<120 and >140 mmHg) and DBP (<70 and >80 mmHg). The effect of BPv on CVD and CHD was more pronounced in those with both prior CVD history and low blood pressure. Dips, not elevations, in blood pressure appeared to drive these associations. The relationships were generally not attenuated by adjustment for mean blood pressure, medication adherence, or baseline comorbidities. A sensitivity analysis using CVD events from the long-term posttrial follow-up (ACCORDION) was consistent with the results from ACCORD. CONCLUSION In ACCORD, the effect of BPv on adverse cardiovascular (but not cerebrovascular) outcomes is modified by baseline blood pressure and prior CVD. Recognizing these more nuanced relationships may help improve risk stratification and blood pressure management decisions as well as provide insight into potential underlying mechanisms.
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Affiliation(s)
| | - Jin J Zhou
- Phoenix VA Healthcare System, Phoenix
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson
| | | | - Peter D Reaven
- Phoenix VA Healthcare System, Phoenix
- College of Medicine-Phoenix, University of Arizona, Phoenix, Arizona, USA
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16
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Azad N, Agrawal L, Bahn G, Emanuele NV, Reaven PD, Hayward R, Reda D. Eye Outcomes in Veteran Affairs Diabetes Trial (VADT) After 17 Years. Diabetes Care 2021; 44:dc202882. [PMID: 34187839 PMCID: PMC8929183 DOI: 10.2337/dc20-2882] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [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: 11/25/2020] [Accepted: 05/03/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The objective of this study was to assess the long-term role of intensive glycemic control (INT) compared with standard glycemic control in accumulated eye procedures in patients with advanced diabetes. RESEARCH DESIGN AND METHODS We compared the effect of treatment assignment on the accumulated number of eye procedures during the intervention period of the Veteran Affairs Diabetes Trial (VADT) (2000-2008) (median follow-up 5.6 years), the interim VADT follow-up study (2000-2013), and the full 17 years of VADT follow-up (2000-2017). We further analyzed data using various cardiovascular markers in two models. Model I included total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, systolic and diastolic blood pressure, and BMI. Model II included these covariates plus age and diabetic retinopathy (DR) severity score at baseline of the original trial. RESULTS The final analysis of the data showed a mild but nonsignificant increase in number of procedures and in retinal or retinal plus cataract surgery during the three periods of the study. CONCLUSIONS We found no significant benefit of INT during the original trial period in eye-related procedures, such as various procedures for DR, or during the 17 years of follow-up in cataract surgery. However, after adjusting data for some known vascular markers, the increase in the number of eye procedures with INT becomes more prevalent. This finding indicates that INT might not have a protective role in events requiring surgery in individuals with advanced diabetes.
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Affiliation(s)
- Nasrin Azad
- Endocrinology Section, Edward Hines, Jr. VA Hospital, Hines, IL
- Cooperative Studies Program Coordinating Center, Hines, IL
| | - Lily Agrawal
- Endocrinology Section, Edward Hines, Jr. VA Hospital, Hines, IL
- Cooperative Studies Program Coordinating Center, Hines, IL
| | - Gideon Bahn
- Cooperative Studies Program Coordinating Center, Hines, IL
| | - Nicholas V Emanuele
- Endocrinology Section, Edward Hines, Jr. VA Hospital, Hines, IL
- Cooperative Studies Program Coordinating Center, Hines, IL
| | - Peter D Reaven
- Endocrinology Section, Carl T. Hayden VA Medical Center, Phoenix, AZ
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17
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Koska J, Migrino RQ, Chan KC, Cooper-Cox K, Reaven PD. The Effect of Exenatide Once Weekly on Carotid Atherosclerosis in Individuals With Type 2 Diabetes: An 18-Month Randomized Placebo-Controlled Study. Diabetes Care 2021; 44:1385-1392. [PMID: 33495294 PMCID: PMC8247511 DOI: 10.2337/dc20-2014] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [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: 08/13/2020] [Accepted: 11/23/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Glucagon-like peptide 1 receptor agonists (GLP-1RAs) improved multiple proatherogenic risk factors and reduced cardiovascular events in recent clinical trials, suggesting that they may slow progression of atherosclerosis. We tested whether exenatide once weekly reduces carotid plaque progression in individuals with type 2 diabetes. RESEARCH DESIGN AND METHODS In a double-blind, pragmatic trial, 163 participants were randomized (2:1) to exenatide (n = 109) or placebo (n = 54). Changes in carotid plaque volume and composition were measured at 9 and 18 months by multicontrast 3 Tesla MRI. Fasting and post-high-fat meal plasma glucose and lipids, and endothelial function responses, were measured at 3, 9, and 18 months. RESULTS Exenatide reduced hemoglobin A1c (HbA1c) (estimated difference vs. placebo 0.55%, P = 0.0007) and fasting and postmeal plasma glucose (19 mg/dL, P = 0.0002, and 25 mg/dL, P < 0.0001, respectively). Mean (SD) change in plaque volume in the exenatide group (0.3% [2%]) was not different from that in the placebo group (-2.2% [8%]) (P = 0.4). The change in plaque volume in the exenatide group was associated with changes in HbA1c (r = 0.38, P = 0.0004), body weight, and overall plasma glucose (r = 0.29, P = 0.007 both). There were no differences in changes in plaque composition, body weight, blood pressure, fasting and postmeal plasma triglycerides, and endothelial function between the groups. CONCLUSIONS Exenatide once weekly for up to 18 months improved fasting and postprandial glycemic control but did not modify change in carotid plaque volume or composition. This study raises the possibility that short-term antiatherosclerotic effects may not play a central role in the cardiovascular benefits of GLP-1RAs.
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Affiliation(s)
- Juraj Koska
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
| | | | - Keith C Chan
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
| | | | - Peter D Reaven
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
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18
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Nuyujukian DS, Koska J, Bahn G, Reaven PD, Zhou JJ. Blood Pressure Variability and Risk of Heart Failure in ACCORD and the VADT. Diabetes Care 2020; 43:1471-1478. [PMID: 32327422 PMCID: PMC7305004 DOI: 10.2337/dc19-2540] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [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: 12/18/2019] [Accepted: 03/31/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Although blood pressure variability is increasingly appreciated as a risk factor for cardiovascular disease, its relationship with heart failure (HF) is less clear. We examined the relationship between blood pressure variability and risk of HF in two cohorts of type 2 diabetes participating in trials of glucose and/or other risk factor management. RESEARCH DESIGN AND METHODS Data were drawn from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial and the Veterans Affairs Diabetes Trial (VADT). Coefficient of variation (CV) and average real variability (ARV) were calculated for systolic (SBP) and diastolic blood pressure (DBP) along with maximum and cumulative mean SBP and DBP during both trials. RESULTS In ACCORD, CV and ARV of SBP and DBP were associated with increased risk of HF, even after adjusting for other risk factors and mean blood pressure (e.g., CV-SBP: hazard ratio [HR] 1.15, P = 0.01; CV-DBP: HR 1.18, P = 0.003). In the VADT, DBP variability was associated with increased risk of HF (ARV-DBP: HR 1.16, P = 0.001; CV-DBP: HR 1.09, P = 0.04). Further, in ACCORD, those with progressively lower baseline blood pressure demonstrated a stepwise increase in risk of HF with higher CV-SBP, ARV-SBP, and CV-DBP. Effects of blood pressure variability were related to dips, not elevations, in blood pressure. CONCLUSIONS Blood pressure variability is associated with HF risk in individuals with type 2 diabetes, possibly a consequence of periods of ischemia during diastole. These results may have implications for optimizing blood pressure treatment strategies in those with type 2 diabetes.
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Affiliation(s)
- Daniel S Nuyujukian
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ .,Carl T. Hayden Veterans Affairs Medical Center, Phoenix, AZ
| | - Juraj Koska
- Carl T. Hayden Veterans Affairs Medical Center, Phoenix, AZ
| | - Gideon Bahn
- Hines Veterans Affairs Cooperative Studies Program Coordinating Center, Edward Hines, Jr. Veterans Affairs Hospital, Hines, IL
| | - Peter D Reaven
- Carl T. Hayden Veterans Affairs Medical Center, Phoenix, AZ
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19
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Vujkovic M, Keaton JM, Lynch JA, Miller DR, Zhou J, Tcheandjieu C, Huffman JE, Assimes TL, Lorenz K, Zhu X, Hilliard AT, Judy RL, Huang J, Lee KM, Klarin D, Pyarajan S, Danesh J, Melander O, Rasheed A, Mallick NH, Hameed S, Qureshi IH, Afzal MN, Malik U, Jalal A, Abbas S, Sheng X, Gao L, Kaestner KH, Susztak K, Sun YV, DuVall SL, Cho K, Lee JS, Gaziano JM, Phillips LS, Meigs JB, Reaven PD, Wilson PW, Edwards TL, Rader DJ, Damrauer SM, O'Donnell CJ, Tsao PS, Chang KM, Voight BF, Saleheen D. Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis. Nat Genet 2020; 52:680-691. [PMID: 32541925 PMCID: PMC7343592 DOI: 10.1038/s41588-020-0637-y] [Citation(s) in RCA: 351] [Impact Index Per Article: 87.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2019] [Accepted: 04/29/2020] [Indexed: 12/19/2022]
Abstract
We investigated type 2 diabetes (T2D) genetic susceptibility via multi-ethnic meta-analysis of 228,499 cases and 1,178,783 controls in the Million Veteran Program, DIAMANTE, Biobank Japan, and other studies. We report 568 associations, including 286 autosomal, 7 X chromosomal, and 25 identified in ancestry-specific analyses that were previously unreported. Transcriptome-wide association analysis detected 3,568 T2D-associations with genetically predicted gene expression in 687 novel genes; of these, 54 are known to interact with FDA-approved drugs. A polygenic risk score was strongly associated with increased risk of T2D-related retinopathy and modestly associated with chronic kidney disease (CKD), peripheral artery disease (PAD), and neuropathy. We investigated the genetic etiology of T2D-related vascular outcomes in MVP and observed statistical SNP-T2D interactions at 13 variants, including coronary heart disease, CKD, PAD, and neuropathy. These findings may help to identify potential therapeutic targets for T2D and genomic pathways that link T2D to vascular outcomes.
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Affiliation(s)
- Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.,Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jacob M Keaton
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System, Nashville, TN, USA.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.,Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Julie A Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA.,College of Nursing and Health Sciences, University of Massachusetts, Lowell, MA, USA
| | - Donald R Miller
- Edith Nourse Rogers Memorial VA Hospital, Bedford, MA, USA.,Center for Population Health, University of Massachusetts, Lowell, MA, USA
| | - Jin Zhou
- Phoenix VA Health Care System, Phoenix, AZ, USA.,Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
| | - Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto, CA, USA.,Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.,Department of Pediatric Cardiology, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Themistocles L Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, USA.,Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Kimberly Lorenz
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.,Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Xiang Zhu
- VA Palo Alto Health Care System, Palo Alto, CA, USA.,Department of Statistics, Stanford University, Stanford, CA, USA
| | - Austin T Hilliard
- VA Palo Alto Health Care System, Palo Alto, CA, USA.,Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Renae L Judy
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.,Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jie Huang
- VA Boston Healthcare System, Boston, MA, USA.,Department of Global Health, Peking University School of Public Health, Beijing, China
| | - Kyung M Lee
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Derek Klarin
- VA Boston Healthcare System, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Division of Vascular Surgery and Endovascular Therapy, University of Florida School of Medicine, Gainesville, FL, USA
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, MA, USA.,Department of Medicine, Brigham Women's Hospital, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - John Danesh
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Olle Melander
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Asif Rasheed
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan
| | | | - Shahid Hameed
- Punjab Institute of Cardiology, Lahore, Punjab, Pakistan
| | - Irshad H Qureshi
- Department of Medicine, King Edward Medical University, Lahore, Punjab, Pakistan.,Mayo Hospital, Lahore, Punjab, Pakistan
| | - Muhammad Naeem Afzal
- Department of Medicine, King Edward Medical University, Lahore, Punjab, Pakistan.,Mayo Hospital, Lahore, Punjab, Pakistan
| | - Uzma Malik
- Department of Medicine, King Edward Medical University, Lahore, Punjab, Pakistan.,Mayo Hospital, Lahore, Punjab, Pakistan
| | - Anjum Jalal
- Department of Cardiology, Faisalabad Institute of Cardiology, Faisalabad, Punjab, Pakistan
| | - Shahid Abbas
- Department of Cardiology, Faisalabad Institute of Cardiology, Faisalabad, Punjab, Pakistan
| | - Xin Sheng
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Long Gao
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Klaus H Kaestner
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Katalin Susztak
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yan V Sun
- Atlanta VA Medical Center, Decatur, GA, USA.,Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Scott L DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA.,Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA.,Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - Jennifer S Lee
- VA Palo Alto Health Care System, Palo Alto, CA, USA.,Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - J Michael Gaziano
- VA Boston Healthcare System, Boston, MA, USA.,Department of Medicine, Brigham Women's Hospital, Boston, MA, USA
| | - Lawrence S Phillips
- Atlanta VA Medical Center, Decatur, GA, USA.,Division of Endocrinology, Emory University School of Medicine, Atlanta, GA, USA
| | - James B Meigs
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Peter D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, USA.,College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Peter W Wilson
- Atlanta VA Medical Center, Decatur, GA, USA.,Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA
| | - Todd L Edwards
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Nashville VA Medical Center, Nashville, TN, USA
| | - Daniel J Rader
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Scott M Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.,Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Boston, MA, USA.,Department of Medicine, Brigham Women's Hospital, Boston, MA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA.,Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | | | | | | | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.,Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,South Texas Veterans Health Care System, San Antonio, TX, USA
| | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA. .,Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. .,Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Danish Saleheen
- Center for Non-Communicable Diseases, Karachi, Sindh, Pakistan. .,Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA. .,Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA.
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20
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Sheng CS, Tian J, Miao Y, Cheng Y, Yang Y, Reaven PD, Bloomgarden ZT, Ning G. Prognostic Significance of Long-term HbA 1c Variability for All-Cause Mortality in the ACCORD Trial. Diabetes Care 2020; 43:1185-1190. [PMID: 32229597 DOI: 10.2337/dc19-2589] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [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: 12/25/2019] [Accepted: 03/02/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The association between high glycemic variability and all-cause mortality has been widely investigated in epidemiological studies but rarely validated in glucose-lowering clinical trials. We aimed to identify the prognostic significance of visit-to-visit HbA1c variability in treated patients in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial population. RESEARCH DESIGN AND METHODS We studied the risk of all-cause mortality in relation to long-term visit-to-visit HbA1c variability, expressed as coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV), from the 8th month to the transition from intensive to standard glycemic therapy. Multivariable Cox proportional hazards models were used to estimate adjusted hazard ratio (HR) and 95% CI. RESULTS Compared with the standard therapy group (n = 4,728), the intensive therapy group (n = 4,755) had significantly lower mean HbA1c (6.6% [49 mmol/mol] vs. 7.7% [61 mmol/mol], P < 0.0001) and lower CV, VIM, and ARV (P < 0.0001). In multivariate adjusted analysis, all three HbA1c variability indices were significantly associated with total mortality in all patients as well as in the standard- and intensive-therapy groups analyzed separately. The hazard ratios for a 1-SD increase in HbA1c variability indices for all-cause mortality were 1.19 and 1.23 in intensive and standard therapy, respectively. Cross-tabulation analysis showed the third tertile of HbA1c mean and VIM had significantly higher all-cause mortality (HR 2.05; 95% CI 1.17-3.61; P < 0.01) only in the intensive-therapy group. CONCLUSIONS Long-term visit-to-visit HbA1c variability was a strong predictor of all-cause mortality. HbA1c VIM combined with HbA1c mean conferred an increased risk for all-cause mortality in the intensive-therapy group.
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Affiliation(s)
- Chang-Sheng Sheng
- State Key Laboratory of Medical Genomics, Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Center for Epidemiological Studies and Clinical Trials and Center for Vascular Evaluation, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jingyan Tian
- State Key Laboratory of Medical Genomics, Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China .,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrinology and Metabolism, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Ya Miao
- State Key Laboratory of Medical Genomics, Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrinology and Metabolism, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yi Cheng
- State Key Laboratory of Medical Genomics, Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Center for Epidemiological Studies and Clinical Trials and Center for Vascular Evaluation, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yulin Yang
- State Key Laboratory of Medical Genomics, Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrinology and Metabolism, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Peter D Reaven
- Carl T. Hayden Veterans Affairs Medical Center, Phoenix, AZ
| | - Zachary T Bloomgarden
- Division of Endocrinology, Diabetes and Bone Disease, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Guang Ning
- State Key Laboratory of Medical Genomics, Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China .,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrinology and Metabolism, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
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21
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Li M, Marquez RC, Vinales KL, Reaven PD, Behari G, Dildeep A, Harman SM. Considerations for Thyroid Fine Needle Aspiration (FNA) Biopsies During the COVID-19 Pandemic. ACTA ACUST UNITED AC 2020. [DOI: 10.1089/ct.2020;32.156-158] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Ming Li
- Division of Endocrinology, Diabetes and Metabolism; Phoenix VA Healthcare System, Phoenix, Arizona, U.S.A
- University of Arizona College of Medicine-Phoenix, Phoenix, Arizona, U.S.A
| | - Ricardo C. Marquez
- Division of Endocrinology, Diabetes and Metabolism; Phoenix VA Healthcare System, Phoenix, Arizona, U.S.A
- University of Arizona College of Medicine-Phoenix, Phoenix, Arizona, U.S.A
| | - Karyne L. Vinales
- Division of Endocrinology, Diabetes and Metabolism; Phoenix VA Healthcare System, Phoenix, Arizona, U.S.A
- University of Arizona College of Medicine-Phoenix, Phoenix, Arizona, U.S.A
| | - Peter D. Reaven
- Division of Endocrinology, Diabetes and Metabolism; Phoenix VA Healthcare System, Phoenix, Arizona, U.S.A
- University of Arizona College of Medicine-Phoenix, Phoenix, Arizona, U.S.A
| | - Gauri Behari
- Division of Endocrinology, Diabetes and Metabolism; Phoenix VA Healthcare System, Phoenix, Arizona, U.S.A
- University of Arizona College of Medicine-Phoenix, Phoenix, Arizona, U.S.A
| | - Ambujakshan Dildeep
- Division of Ear, Nose and Throat, Surgery Service, Phoenix VA Healthcare System, Phoenix, Arizona, U.S.A
| | - Sherman M. Harman
- Division of Endocrinology, Diabetes and Metabolism; Phoenix VA Healthcare System, Phoenix, Arizona, U.S.A
- University of Arizona College of Medicine-Phoenix, Phoenix, Arizona, U.S.A
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22
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Koska J, Osredkar T, D'Souza K, Sands M, Sinha S, Zhang W, Meyer C, Reaven PD. Effects of saxagliptin on adipose tissue inflammation and vascular function in overweight and obese people: a placebo-controlled study. Diabet Med 2019; 36:1399-1407. [PMID: 30580454 DOI: 10.1111/dme.13889] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/19/2018] [Indexed: 12/15/2022]
Abstract
AIMS To test the effect of the dipeptidyl peptidase-4 inhibitor saxagliptin on adipose tissue inflammation and microvascular function, and whole-body postprandial endothelial function. METHODS A randomized, double-blind, placebo-controlled, parallel study was conducted between June 2013 and November 2016 in 44 overweight or obese people without diabetes (saxagliptin, n=28; placebo, n=16). Subcutaneous abdominal adipose tissue biopsies, a 4-h fat-enriched meal test and peripheral arterial tonometry for measurement of endothelial function were performed at baseline and after 6 weeks of treatment with saxagliptin (5 mg/day) or matching placebo. RESULTS Forty participants were analysed (saxagliptin, n=26; placebo, n=14). Secretion of interleukin-8 from adipose tissue explants was reduced after saxagliptin (median fold-change from baseline: 0.8 saxagliptin vs 3.3 placebo; P=0.02). Adipose tissue expression of thioredoxin-inhibitory protein (TxNIP) was lower after saxagliptin (0.75 vs 1.0; P=0.02), while there were no significant differences in adipose tissue secretion of interleukin-1b, interleukin-6 or macrophage chemoattractant protein 1 (MCP-1), adipose tissue macrophage content, adipose tissue mRNA levels of mcp1, cd36, cd68, il6, il8, txnip and adpq, and activation of adipose tissue inflammatory pathways [extracellular signal-regulated kinase, c-Jun N-terminal kinase (JNK) and nuclear factor-κB (NF- κB)] or insulin-induced vasodilation of adipose tissue arterioles. Postprandial plasma glucose was slightly lower (by an estimated 0.3 mmol/l; P=0.01), while postprandial insulin, triglyceride levels and endothelial function were unchanged after saxagliptin. CONCLUSIONS The effect of saxagliptin on adipose tissue inflammation was relatively modest, with many inflammatory markers unchanged. We also found no evidence that saxagliptin therapy improved adipose tissue arteriole vasodilation or postprandial endothelial function.
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Affiliation(s)
- J Koska
- Phoenix VA Health Care System, Phoenix, AZ, USA
| | - T Osredkar
- Phoenix VA Health Care System, Phoenix, AZ, USA
| | - K D'Souza
- Phoenix VA Health Care System, Phoenix, AZ, USA
| | - M Sands
- Phoenix VA Health Care System, Phoenix, AZ, USA
| | - S Sinha
- Phoenix VA Health Care System, Phoenix, AZ, USA
| | - W Zhang
- Phoenix VA Health Care System, Phoenix, AZ, USA
| | - C Meyer
- Phoenix VA Health Care System, Phoenix, AZ, USA
| | - P D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, USA
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23
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Agrawal L, Azad N, Bahn GD, Reaven PD, Hayward RA, Reda DJ, Emanuele NV. Intensive Glycemic Control Improves Long-term Renal Outcomes in Type 2 Diabetes in the Veterans Affairs Diabetes Trial (VADT). Diabetes Care 2019; 42:e181-e182. [PMID: 31548245 PMCID: PMC6804611 DOI: 10.2337/dc19-0891] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 08/23/2019] [Indexed: 02/03/2023]
Affiliation(s)
- Lily Agrawal
- Endocrinology Section, Medical Service, Edward Hines Jr. VA Hospital, Hines, IL
| | - Nasrin Azad
- Endocrinology Section, Medical Service, Edward Hines Jr. VA Hospital, Hines, IL
| | | | | | - Rodney A Hayward
- Department of Internal Medicine, VA Ann Arbor Healthcare System, Ann Arbor, MI
| | - Domenic J Reda
- Cooperative Studies Program Coordinating Center, Edward Hines Jr. VA Hospital, Hines, IL
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Reaven PD, Emanuele NV, Wiitala WL, Bahn GD, Reda DJ, McCarren M, Duckworth WC, Hayward RA. Intensive Glucose Control in Patients with Type 2 Diabetes - 15-Year Follow-up. N Engl J Med 2019; 380:2215-2224. [PMID: 31167051 PMCID: PMC6706253 DOI: 10.1056/nejmoa1806802] [Citation(s) in RCA: 143] [Impact Index Per Article: 28.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND We previously reported that a median of 5.6 years of intensive as compared with standard glucose lowering in 1791 military veterans with type 2 diabetes resulted in a risk of major cardiovascular events that was significantly lower (by 17%) after a total of 10 years of combined intervention and observational follow-up. We now report the full 15-year follow-up. METHODS We observationally followed enrolled participants (complete cohort) after the conclusion of the original clinical trial by using central databases to identify cardiovascular events, hospitalizations, and deaths. Participants were asked whether they would be willing to provide additional data by means of surveys and chart reviews (survey cohort). The prespecified primary outcome was a composite of major cardiovascular events, including nonfatal myocardial infarction, nonfatal stroke, new or worsening congestive heart failure, amputation for ischemic gangrene, and death from cardiovascular causes. Death from any cause was a prespecified secondary outcome. RESULTS There were 1655 participants in the complete cohort and 1391 in the survey cohort. During the trial (which originally enrolled 1791 participants), the separation of the glycated hemoglobin curves between the intensive-therapy group (892 participants) and the standard-therapy group (899 participants) averaged 1.5 percentage points, and this difference declined to 0.2 to 0.3 percentage points by 3 years after the trial ended. Over a period of 15 years of follow-up (active treatment plus post-trial observation), the risks of major cardiovascular events or death were not lower in the intensive-therapy group than in the standard-therapy group (hazard ratio for primary outcome, 0.91; 95% confidence interval [CI], 0.78 to 1.06; P = 0.23; hazard ratio for death, 1.02; 95% CI, 0.88 to 1.18). The risk of major cardiovascular disease outcomes was reduced, however, during an extended interval of separation of the glycated hemoglobin curves (hazard ratio, 0.83; 95% CI, 0.70 to 0.99), but this benefit did not continue after equalization of the glycated hemoglobin levels (hazard ratio, 1.26; 95% CI, 0.90 to 1.75). CONCLUSIONS Participants with type 2 diabetes who had been randomly assigned to intensive glucose control for 5.6 years had a lower risk of cardiovascular events than those who received standard therapy only during the prolonged period in which the glycated hemoglobin curves were separated. There was no evidence of a legacy effect or a mortality benefit with intensive glucose control. (Funded by the VA Cooperative Studies Program; VADT ClinicalTrials.gov number, NCT00032487.).
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Affiliation(s)
- Peter D Reaven
- From the Phoenix Veterans Affairs (VA) Health Care System, Phoenix (P.D.R., W.C.D.); the Hines VA Cooperative Studies Program Coordinating Center and Hines VA Hospital (N.V.E., G.D.B., D.J.R.) and the VA Pharmacy Benefits Management Services (M.M.), Hines, IL; and the VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI (W.L.W., R.A.H.)
| | - Nicholas V Emanuele
- From the Phoenix Veterans Affairs (VA) Health Care System, Phoenix (P.D.R., W.C.D.); the Hines VA Cooperative Studies Program Coordinating Center and Hines VA Hospital (N.V.E., G.D.B., D.J.R.) and the VA Pharmacy Benefits Management Services (M.M.), Hines, IL; and the VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI (W.L.W., R.A.H.)
| | - Wyndy L Wiitala
- From the Phoenix Veterans Affairs (VA) Health Care System, Phoenix (P.D.R., W.C.D.); the Hines VA Cooperative Studies Program Coordinating Center and Hines VA Hospital (N.V.E., G.D.B., D.J.R.) and the VA Pharmacy Benefits Management Services (M.M.), Hines, IL; and the VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI (W.L.W., R.A.H.)
| | - Gideon D Bahn
- From the Phoenix Veterans Affairs (VA) Health Care System, Phoenix (P.D.R., W.C.D.); the Hines VA Cooperative Studies Program Coordinating Center and Hines VA Hospital (N.V.E., G.D.B., D.J.R.) and the VA Pharmacy Benefits Management Services (M.M.), Hines, IL; and the VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI (W.L.W., R.A.H.)
| | - Domenic J Reda
- From the Phoenix Veterans Affairs (VA) Health Care System, Phoenix (P.D.R., W.C.D.); the Hines VA Cooperative Studies Program Coordinating Center and Hines VA Hospital (N.V.E., G.D.B., D.J.R.) and the VA Pharmacy Benefits Management Services (M.M.), Hines, IL; and the VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI (W.L.W., R.A.H.)
| | - Madeline McCarren
- From the Phoenix Veterans Affairs (VA) Health Care System, Phoenix (P.D.R., W.C.D.); the Hines VA Cooperative Studies Program Coordinating Center and Hines VA Hospital (N.V.E., G.D.B., D.J.R.) and the VA Pharmacy Benefits Management Services (M.M.), Hines, IL; and the VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI (W.L.W., R.A.H.)
| | - William C Duckworth
- From the Phoenix Veterans Affairs (VA) Health Care System, Phoenix (P.D.R., W.C.D.); the Hines VA Cooperative Studies Program Coordinating Center and Hines VA Hospital (N.V.E., G.D.B., D.J.R.) and the VA Pharmacy Benefits Management Services (M.M.), Hines, IL; and the VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI (W.L.W., R.A.H.)
| | - Rodney A Hayward
- From the Phoenix Veterans Affairs (VA) Health Care System, Phoenix (P.D.R., W.C.D.); the Hines VA Cooperative Studies Program Coordinating Center and Hines VA Hospital (N.V.E., G.D.B., D.J.R.) and the VA Pharmacy Benefits Management Services (M.M.), Hines, IL; and the VA Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI (W.L.W., R.A.H.)
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Davis SN, Duckworth W, Emanuele N, Hayward RA, Wiitala WL, Thottapurathu L, Reda DJ, Reaven PD. Effects of Severe Hypoglycemia on Cardiovascular Outcomes and Death in the Veterans Affairs Diabetes Trial. Diabetes Care 2019; 42:157-163. [PMID: 30455335 PMCID: PMC6463547 DOI: 10.2337/dc18-1144] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 10/15/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To determine the risk factors for severe hypoglycemia and the association between severe hypoglycemia and serious cardiovascular adverse events and cardiovascular and all-cause mortality in the Veterans Affairs Diabetes Trial (VADT). RESEARCH DESIGN AND METHODS This post hoc analysis of data from the VADT included 1,791 military veterans (age 60.5 ± 9.0 years) with suboptimally controlled type 2 diabetes (HbA1c 9.4 ± 2.0%) of 11.5 ± 7.5 years disease duration with or without known cardiovascular disease and additional cardiovascular risk factors. Participants were randomized to intensive (HbA1c <7.0%) versus standard (HbA1c <8.5%) glucose control. RESULTS The rate of severe hypoglycemia in the intensive treatment group was 10.3 per 100 patient-years compared with 3.7 per 100 patient-years in the standard treatment group (P < 0.001). In multivariable analysis, insulin use at baseline (P = 0.02), proteinuria (P = 0.009), and autonomic neuropathy (P = 0.01) were independent risk factors for severe hypoglycemia, and higher BMI was protective (P = 0.017). Severe hypoglycemia within the past 3 months was associated with an increased risk of serious cardiovascular events (P = 0.032), cardiovascular mortality (P = 0.012), and total mortality (P = 0.024). However, there was a relatively greater increased risk for total mortality in the standard group compared with the intensive group (P = 0.019). The association between severe hypoglycemia and cardiovascular events increased significantly as overall cardiovascular risk increased (P = 0.012). CONCLUSIONS Severe hypoglycemic episodes within the previous 3 months were associated with increased risk for major cardiovascular events and cardiovascular and all-cause mortality regardless of glycemic treatment group assignment. Standard therapy further increased the risk for all-cause mortality after severe hypoglycemia.
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Affiliation(s)
- Stephen N Davis
- Department of Medicine, University of Maryland, Baltimore, MD
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D'Souza KM, Oh C, Zhang W, Reaven PD. TXNIP as a Mediator of Palmitic Acid‐Induced Programmed Cell‐Death in Cardiomyocytes. FASEB J 2018. [DOI: 10.1096/fasebj.2018.32.1_supplement.719.14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Koska J, Saremi A, Howell S, Bahn G, De Courten B, Ginsberg H, Beisswenger PJ, Reaven PD. Advanced Glycation End Products, Oxidation Products, and Incident Cardiovascular Events in Patients With Type 2 Diabetes. Diabetes Care 2018; 41:570-576. [PMID: 29208654 PMCID: PMC5829965 DOI: 10.2337/dc17-1740] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Accepted: 11/05/2017] [Indexed: 02/06/2023]
Abstract
OBJECTIVE The goal of this study was to determine whether plasma levels of advanced glycation end products (AGE) and oxidation products (OP) predict the incidence of cardiovascular disease (CVD) in type 2 diabetes. RESEARCH DESIGN AND METHODS Five specific AGE (methylglyoxal hydroimidazolone, carboxymethyl lysine, carboxyethyl lysine, 3-deoxyglucosone hydroimidazolone, and glyoxal hydroimidazolone) and two OP (2-aminoadipic acid and methionine sulfoxide [MetSO]) were measured at baseline in two intensive glucose-lowering studies: 1) a subcohort of the Veterans Affairs Diabetes Trial (VADT) (n = 445) and 2) a nested case-control subgroup from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study (n = 271). RESULTS Increased levels of several AGE and OP were associated with older age, decreased kidney function, previous CVD, and longer diabetes duration, but not with hemoglobin A1c. In the VADT, increased risk of incident CVD events (n = 107) was associated with lower MetSO after adjusting for age, race/ethnicity, sex, prior CVD event, kidney function, treatment assignment, and diabetes duration (hazard ratio [HR] 0.53; 95% CI 0.28-0.99; P = 0.047). Individuals with both low MetSO and high 3-deoxyglucosone hydroimidazolone concentrations were at highest risk for CVD (HR 1.70; P = 0.01). In the ACCORD study, those with incident CVD events (n = 136) had lower MetSO (by 14%; P = 0.007) and higher glyoxal hydroimidazolone and carboxymethyl lysine (by 18% and 15%, respectively; P = 0.04 for both); however, only the difference in MetSO remained significant after adjustment for prior CVD event (P = 0.002). CONCLUSIONS Lower levels of MetSO and higher levels of select AGE are associated with increased incident CVD and may help account for the limited benefit of intensive glucose lowering in type 2 diabetes.
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Affiliation(s)
| | | | | | - Gideon Bahn
- Hines VA Cooperative Studies Program Coordinating Center, Edward Hines Jr. VA Hospital, Hines, IL
| | - Barbora De Courten
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria, Australia
| | - Henry Ginsberg
- Department of Medicine, Columbia University, New York, NY
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Agrawal L, Azad N, Bahn GD, Ge L, Reaven PD, Hayward RA, Reda DJ, Emanuele NV. Long-term follow-up of intensive glycaemic control on renal outcomes in the Veterans Affairs Diabetes Trial (VADT). Diabetologia 2018; 61:295-299. [PMID: 29101421 PMCID: PMC5747983 DOI: 10.1007/s00125-017-4473-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [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: 06/16/2017] [Accepted: 09/08/2017] [Indexed: 01/21/2023]
Abstract
AIMS/HYPOTHESIS We conducted an analysis of data collected during the Veterans Affairs Diabetes Trial (VADT) and the follow-up study (VADT-F) to determine whether intensive (INT) compared with standard (STD) glycaemic control during the VADT resulted in better long-term kidney outcomes. METHODS VADT randomly assigned 1791 veterans from 20 Veterans Affairs (VA) medical centres who had type 2 diabetes mellitus and a mean HbA1c of 9.4 ± 2% (79.2 mmol/mol) at baseline to receive either INT or STD glucose control for a median of 5.6 years (randomisation December 2000 to May 2003; intervention ending in May 2008). After the trial, participants received routine care through their own physicians within the VA. This is an interim analysis of the VADT-F (June 2008 to December 2013). We collected data using VA and National databases and report renal outcomes based on serum creatinine, eGFR and urine albumin to creatinine ratio (ACR) in 1033 people who provided informed consent to participate in the VADT-F. RESULTS By the end of the VADT-F, significantly more people who received INT treatment during the VADT maintained an eGFR >60 ml min-1 1.73 m-2 (OR 1.34 [95% CI 1.05, 1.71], p = 0.02). This benefit was most evident in those who were classified as at moderate risk (INT vs STD, RR 1.3, p = 0.03) or high risk (RR 2.3, p = 0.04) of chronic kidney disease on the Kidney Disease Improving Global Outcomes (KDIGO-CKD) at the beginning of VADT. At the end of VADT-F, significantly more people from the INT group improved to a low KDIGO risk category (RR 6.1, p = 0.002). During the VADT-F there were no significant differences between INT and STD for average HbA1c, blood pressure or lipid levels. CONCLUSIONS/INTERPRETATION After just over 11 years of follow-up, there was a 34% greater odds of maintaining an eGFR of >60 ml min-1 1.73 m-2 and of improving the KDIGO category in individuals with type 2 diabetes who had received INT for a median of 5.6 years. VADT clinical trials.gov number: NCT 00032487.
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Affiliation(s)
- Lily Agrawal
- Medical Service, Endocrinology Section, Edward Hines Jr. VA Hospital, 5000 S. 5th Avenue, Building 1, (Mail code 111), Hines, IL, 60141, USA.
| | - Nasrin Azad
- Medical Service, Endocrinology Section, Edward Hines Jr. VA Hospital, 5000 S. 5th Avenue, Building 1, (Mail code 111), Hines, IL, 60141, USA
| | - Gideon D Bahn
- Cooperative Studies Program Coordinating Center, Hines, IL, USA
| | - Ling Ge
- Cooperative Studies Program Coordinating Center, Hines, IL, USA
| | | | | | - Domenic J Reda
- Cooperative Studies Program Coordinating Center, Hines, IL, USA
| | - Nicholas V Emanuele
- Medical Service, Endocrinology Section, Edward Hines Jr. VA Hospital, 5000 S. 5th Avenue, Building 1, (Mail code 111), Hines, IL, 60141, USA
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Koska J, Lopez L, D'Souza K, Osredkar T, Deer J, Kurtz J, Salbe AD, Harman SM, Reaven PD. Effect of liraglutide on dietary lipid-induced insulin resistance in humans. Diabetes Obes Metab 2018; 20:69-76. [PMID: 28605158 DOI: 10.1111/dom.13037] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Revised: 06/01/2017] [Accepted: 06/09/2017] [Indexed: 12/11/2022]
Abstract
AIMS To test whether liraglutide suppresses postprandial elevations in lipids and thus protects against high saturated fatty acid (SFA) diet-induced insulin resistance. METHODS In a randomized placebo-controlled crossover study, 32 participants with normal or mildly impaired glucose tolerance received liraglutide and placebo for 3 weeks each. Insulin suppression tests (IST) were conducted at baseline and after a 24-hour SFA-enriched diet after each treatment. Plasma glucose, insulin, triglycerides and non-esterified fatty acids (NEFA) were measured over the initial 8 hours (breakfast and lunch) on the SFA diet. A subset of participants underwent ex vivo measurements of insulin-mediated vasodilation of adipose tissue arterioles and glucose metabolism regulatory proteins in skeletal muscle. RESULTS Liraglutide reduced plasma glucose, triglycerides and NEFA concentrations during the SFA diet (by 50%, 25% and 9%, respectively), and the SFA diet increased plasma glucose during the IST (by 36%; all P < .01 vs placebo). The SFA diet-induced impairment of vasodilation on placebo (-9.4% vs baseline; P < .01) was ameliorated by liraglutide (-4.8%; P = .1 vs baseline). In skeletal muscle, liraglutide abolished the SFA-induced increase in thioredoxin-interacting protein (TxNIP) expression (75% decrease; P < .01 vs placebo) and increased 5'AMP-activated protein kinase (AMPK) phosphorylation (50% vs -3%; P = .04 vs placebo). CONCLUSIONS Liraglutide blunted the SFA-enriched diet-induced peripheral insulin resistance. This effect may be related to improved microvascular function and modulation of TxNIP and AMPK pathways in skeletal muscle.
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Affiliation(s)
- Juraj Koska
- Phoenix VA Health Care System, Phoenix, Arizona
| | | | | | | | - James Deer
- Phoenix VA Health Care System, Phoenix, Arizona
| | - Julie Kurtz
- Phoenix VA Health Care System, Phoenix, Arizona
| | | | - Sherman M Harman
- Phoenix VA Health Care System, Phoenix, Arizona
- Kronos Longevity Research Institute, Phoenix, Arizona
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Lopez LF, Reaven PD, Harman SM. Review: The relationship of hemoglobin A1c to postoperative surgical risk with an emphasis on joint replacement surgery. J Diabetes Complications 2017; 31:1710-1718. [PMID: 29029935 DOI: 10.1016/j.jdiacomp.2017.08.016] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 08/06/2017] [Accepted: 08/31/2017] [Indexed: 12/12/2022]
Abstract
Patients with diabetes mellitus are known to have a high risk of postoperative complications, including infections, impaired wound healing, cardiovascular events, venous thromboembolism, and mortality. Because hyperglycemia has been thought to mediate this risk, there is a clinical propensity for improving glycemic control, as assessed by hemoglobin A1c (HbA1c) level, prior to proceeding with elective surgery, particularly joint replacement surgery. However, it is not established whether chronic poor glycemic control, indicated by elevated HbA1c levels, predicts increased risk of postoperative complications. The benefit of improving glycemic control must be weighed against risks of delaying necessary elective surgery, such as joint replacement surgery, which risks may include negative impact on long-term glycemic control. Thus, we review the current evidence to determine the relationship between HbA1c and postoperative surgical risk, especially on joint replacement surgery.
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Affiliation(s)
- Lizette F Lopez
- Endocrinology Division, Phoenix VA Health Care System, 650 E. Indian School Road, Phoenix, AZ 85012, USA.
| | - Peter D Reaven
- Endocrinology Division, Phoenix VA Health Care System, 650 E. Indian School Road, Phoenix, AZ 85012, USA; University of Arizona College of Medicine-Phoenix, 550 E. Van Buren St., Phoenix, AZ 85004, USA.
| | - Sherman M Harman
- Endocrinology Division, Phoenix VA Health Care System, 650 E. Indian School Road, Phoenix, AZ 85012, USA; University of Arizona College of Medicine-Phoenix, 550 E. Van Buren St., Phoenix, AZ 85004, USA.
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Saremi A, Howell S, Schwenke DC, Bahn G, Beisswenger PJ, Reaven PD. Advanced Glycation End Products, Oxidation Products, and the Extent of Atherosclerosis During the VA Diabetes Trial and Follow-up Study. Diabetes Care 2017; 40:591-598. [PMID: 28148544 PMCID: PMC5360279 DOI: 10.2337/dc16-1875] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 12/27/2016] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To determine whether plasma levels of advanced glycation end products and oxidation products play a role in the development of atherosclerosis in patients with type 2 diabetes (T2D) over nearly 10 years of the VA Diabetes Trial and Follow-up Study. RESEARCH DESIGN AND METHODS Baseline plasma levels of methylglyoxal hydroimidazolone, Nε-carboxymethyl lysine, Nε-carboxyethyl lysine (CEL), 3-deoxyglucosone hydroimidazolone and glyoxal hydroimidazolone (G-H1), 2-aminoadipic acid (2-AAA), and methionine sulfoxide were measured in a total of 411 participants, who underwent ultrasound assessment of carotid intima-media thickness (CIMT), and computed tomography scanning of coronary artery calcification (CAC) and abdominal aortic artery calcification (AAC) after an average of 10 years of follow-up. RESULTS In risk factor-adjusted multivariable regression models, G-H1 was associated with the extent of CIMT and CAC. In addition, 2-AAA was strongly associated with the extent of CAC, and CEL was strongly associated with the extent of AAC. The combination of specific advanced glycation end products and oxidation products (G-H1 and 2-AAA) was strongly associated with all measures of subclinical atherosclerosis. CONCLUSIONS Specific advanced glycation end products and metabolic oxidation products are associated with the severity of subclinical atherosclerosis over the long term and may play an important role in the "negative metabolic memory" of macrovascular complications in people with long-standing T2D.
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Affiliation(s)
| | | | | | - Gideon Bahn
- Cooperative Studies Program Coordinating Center, Hines, IL
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Espinoza SE, Wang CP, Tripathy D, Clement SC, Schwenke DC, Banerji MA, Bray GA, Buchanan TA, Henry RR, Kitabchi AE, Mudaliar S, Stentz FB, Reaven PD, DeFronzo RA, Musi N. Pioglitazone is equally effective for diabetes prevention in older versus younger adults with impaired glucose tolerance. Age (Dordr) 2016; 38:485-493. [PMID: 27585671 PMCID: PMC5266219 DOI: 10.1007/s11357-016-9946-6] [Citation(s) in RCA: 8] [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] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Accepted: 08/19/2016] [Indexed: 06/06/2023]
Abstract
To determine the efficacy of pioglitazone to prevent type 2 diabetes in older compared to younger adults with pre-diabetes. Six hundred two participants with impaired glucose tolerance (IGT) were randomized in double blind fashion to placebo or pioglitazone for diabetes prevention in the ACT NOW study (NEJM 364:1104-1115, 2011). Cox proportional hazard regression was used to compare time to development of diabetes over a mean of 2 years between older (≥61 years) and younger participants. We compared effects of pioglitazone versus placebo on metabolic profiles, inflammatory markers, adipokines, β cell function (disposition index), insulin sensitivity (Matsuda index), and body composition by ANOVA. Diabetes incidence was reduced by 85 % in older and 69 % in younger subjects (p = 0.41). β cell function (disposition index) increased by 35.0 % in the older and 26.7 % in younger subjects (p = 0.83). Insulin sensitivity (Matsuda index) increased by 3.07 (5.2-fold) in older and by 2.54 (3.8-fold) in younger participants (p = 0.58). Pioglitazone more effectively increased adiponectin in older versus younger subjects (22.9 ± 3.2 μg/mL [2.7-fold] vs. 12.7 ± 1.4 μg/mL [2.2-fold], respectively; p = 0.04). Younger subjects tended to have a greater increase in whole body fat mass compared to older subjects (3.6 vs. 3.1 kg; p = 0.061). Younger and older subjects had similar decreases in bone mineral density (0.018 ± 0.0071 vs. 0.0138 ± 0.021 g/cm2). Younger and older pre-diabetic adults taking pioglitazone had similar reductions in conversion to diabetes and older adults had similar or greater improvements in metabolic risk factors, demonstrating that pioglitazone is useful in preventing diabetes in older adults.
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Affiliation(s)
- Sara E Espinoza
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78223, USA.
- Geriatrics Research, Education and Clinical Center, South Texas Veterans Health Care System, 7400 Merton Minter Blvd., San Antonio, TX, 78229, USA.
| | - Chen-Pin Wang
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78223, USA
- Geriatrics Research, Education and Clinical Center, South Texas Veterans Health Care System, 7400 Merton Minter Blvd., San Antonio, TX, 78229, USA
| | - Devjit Tripathy
- Texas Diabetes Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA
- South Texas Veterans Health Care System, 7400 Merton Minter Blvd., San Antonio, TX, 78229, USA
| | - Stephen C Clement
- Department of Medicine Division of Endocrinology and Metabolism, Georgetown University, 3700 O St NW, Washington, DC, 20057, USA
| | | | - Mary Ann Banerji
- Department of Medicine Division of Endocrinology, State University of New York Downstate Medical Center, 450 Clarkson Ave, Brooklyn, NY, 11203, USA
| | - George A Bray
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Thomas A Buchanan
- Department of Medicine Division of Endocrinology and Diabetes, University of Southern California, Los Angeles, CA, USA
| | - Robert R Henry
- Department of Medicine Division of Endocrinology and Metabolism, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Abbas E Kitabchi
- Department of Medicine Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, 920 Court Ave, Memphis, TN, 38163, USA
| | - Sunder Mudaliar
- Department of Medicine Division of Endocrinology and Metabolism, University of California San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA
| | - Frankie B Stentz
- Department of Medicine Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, 920 Court Ave, Memphis, TN, 38163, USA
| | - Peter D Reaven
- Phoenix Veterans Affairs Health Care System, 650 E Indian School Rd, Phoenix, AZ, 85012, USA
| | - Ralph A DeFronzo
- Texas Diabetes Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA
- South Texas Veterans Health Care System, 7400 Merton Minter Blvd., San Antonio, TX, 78229, USA
| | - Nicolas Musi
- Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX, 78223, USA.
- Geriatrics Research, Education and Clinical Center, South Texas Veterans Health Care System, 7400 Merton Minter Blvd., San Antonio, TX, 78229, USA.
- Texas Diabetes Institute, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 78229, USA.
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Trenchevska O, Koska J, Sinari S, Yassine H, Reaven PD, Billheimer DD, Nelson RW, Nedelkov D. Association of Cystatin C Proteoforms with Estimated Glomerular Filtration Rate. Clin Mass Spectrom 2016; 1:27-31. [PMID: 36778895 PMCID: PMC9913891 DOI: 10.1016/j.clinms.2016.11.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Background Cystatin C (CysC), a marker for chronic kidney disease, exists as three sequence proteoforms, in addition to the wild-type sequence: one contains hydroxyproline at position 3 (3Pro-OH), the two others have truncated sequences (des-S and des-SSP). Here, we examine correlations between each of these CysC proteoforms and estimated glomerular filtration rate (eGFR), a diagnostic criterion for chronic kidney disease (CKD). Methods CysC proteoform concentrations were determined from the plasma of 297 diabetes patients at a baseline time point and nine-months later, using a mass spectrometric immunoassay, and were correlated with eGFR calculations. Results In all samples, 3Pro-OH was the most abundant CysC proteoform, followed by the wild-type proteoform. Least abundant were the truncated CysC proteoforms, des-S and des-SSP, although they demonstrated stronger negative correlation with eGFR than the 3Pro-OH and wild-type proteoforms. The des-SSP truncated proteoform exhibited negative predictive value for eGFR. Conclusions The truncated CysC proteoforms show potential for clinical and prognostic utility in CKD staging. This could be useful in populations where current methods do not provide satisfactory solutions.
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Affiliation(s)
| | - Juraj Koska
- Department of Medicine, Phoenix Veteran Affairs Medical Center, Phoenix, AZ, USA
| | - Shripad Sinari
- Biostatics Consulting Lab, University of Arizona, Tucson, AZ, USA
| | - Hussein Yassine
- Department of Medicine, University of Southern California, Los Angeles, USA
| | - Peter D. Reaven
- Department of Medicine, Phoenix Veteran Affairs Medical Center, Phoenix, AZ, USA
| | | | | | - Dobrin Nedelkov
- The Biodesign Institute, Arizona State University, Tempe, AZ, USA,Corresponding author: , PO Box 876601, Tempe AZ 85287-6601, USA, Tel. 480-727-2280
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Koska J, Ozias MK, Deer J, Kurtz J, Salbe AD, Harman SM, Reaven PD. A human model of dietary saturated fatty acid induced insulin resistance. Metabolism 2016; 65:1621-1628. [PMID: 27733250 DOI: 10.1016/j.metabol.2016.07.015] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Revised: 07/25/2016] [Accepted: 07/30/2016] [Indexed: 01/22/2023]
Abstract
BACKGROUND Increased consumption of high-fat diets is associated with the development of insulin resistance and type 2 diabetes. Current models to study the mechanisms of high-fat diet-induced IR in humans are limited by their long duration or low efficacy. In the present study we developed and characterized an acute dietary model of saturated fatty acid-enriched diet induced insulin resistance. METHODS High caloric diets enriched with saturated fatty acids (SFA) or carbohydrates (CARB) were evaluated in subjects with normal and impaired glucose tolerance (NGT or IGT). Both diets were compared to a standard eucaloric American Heart Association (AHA) control diet in a series of crossover studies. Whole body insulin resistance was estimated as steady state plasma glucose (SSPG) concentrations during the last 30min of a 3-h insulin suppression test. RESULTS SSPG was increased after a 24-h SFA diet (by 83±74% vs. control, n=38) in the entire cohort, which was comprised of participants with NGT (92±82%, n=22) or IGT (65±55%, n=16) (all p<0.001). SSPG was also increased after a single SFA breakfast (55±32%, p=0.008, n=7). The increase in SSPG was less pronounced after an overnight fast following a daylong SFA diet (24±31%, p=0.04, n=10), and further attenuated 24h after returning to the control diet (19±35%, p=0.09, n=11). SSPG was not increased after a 24-h CARB diet (26±50%, p=0.11, n=12). CONCLUSIONS A short-term SFA-enriched diet induced whole body insulin resistance in both NGT and IGT subjects. Insulin resistance persisted overnight after the last SFA meal and was attenuated by one day of a healthy diet. This model offers opportunities for identifying early mechanisms and potential treatments of dietary saturated fat induced insulin resistance.
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Affiliation(s)
| | | | - James Deer
- Phoenix VA Health Care System, Phoenix, AZ
| | | | | | - S Mitchell Harman
- Phoenix VA Health Care System, Phoenix, AZ; Kronos Longevity Research Institute, Phoenix, AZ
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Hu X, Reaven PD, Saremi A, Liu N, Abbasi MA, Liu H, Migrino RQ. Machine learning to predict rapid progression of carotid atherosclerosis in patients with impaired glucose tolerance. EURASIP J Bioinform Syst Biol 2016; 2016:14. [PMID: 27642290 PMCID: PMC5011483 DOI: 10.1186/s13637-016-0049-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2016] [Accepted: 08/25/2016] [Indexed: 12/31/2022]
Abstract
Objectives Prediabetes is a major epidemic and is associated with adverse cardio-cerebrovascular outcomes. Early identification of patients who will develop rapid progression of atherosclerosis could be beneficial for improved risk stratification. In this paper, we investigate important factors impacting the prediction, using several machine learning methods, of rapid progression of carotid intima-media thickness in impaired glucose tolerance (IGT) participants. Methods In the Actos Now for Prevention of Diabetes (ACT NOW) study, 382 participants with IGT underwent carotid intima-media thickness (CIMT) ultrasound evaluation at baseline and at 15–18 months, and were divided into rapid progressors (RP, n = 39, 58 ± 17.5 μM change) and non-rapid progressors (NRP, n = 343, 5.8 ± 20 μM change, p < 0.001 versus RP). To deal with complex multi-modal data consisting of demographic, clinical, and laboratory variables, we propose a general data-driven framework to investigate the ACT NOW dataset. In particular, we first employed a Fisher Score-based feature selection method to identify the most effective variables and then proposed a probabilistic Bayes-based learning method for the prediction. Comparison of the methods and factors was conducted using area under the receiver operating characteristic curve (AUC) analyses and Brier score. Results The experimental results show that the proposed learning methods performed well in identifying or predicting RP. Among the methods, the performance of Naïve Bayes was the best (AUC 0.797, Brier score 0.085) compared to multilayer perceptron (0.729, 0.086) and random forest (0.642, 0.10). The results also show that feature selection has a significant positive impact on the data prediction performance. Conclusions By dealing with multi-modal data, the proposed learning methods show effectiveness in predicting prediabetics at risk for rapid atherosclerosis progression. The proposed framework demonstrated utility in outcome prediction in a typical multidimensional clinical dataset with a relatively small number of subjects, extending the potential utility of machine learning approaches beyond extremely large-scale datasets.
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Affiliation(s)
- Xia Hu
- Arizona State University, Tempe, AZ USA ; Texas A&M University, College Station, TX USA
| | - Peter D Reaven
- Arizona State University, Tempe, AZ USA ; Phoenix Veterans Affairs Health Care System, Phoenix, AZ USA ; University of Arizona College of Medicine-Phoenix, Phoenix, AZ USA
| | - Aramesh Saremi
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ USA
| | - Ninghao Liu
- Texas A&M University, College Station, TX USA
| | | | - Huan Liu
- Arizona State University, Tempe, AZ USA
| | - Raymond Q Migrino
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ USA ; University of Arizona College of Medicine-Phoenix, Phoenix, AZ USA
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Azad N, Bahn GD, Emanuele NV, Agrawal L, Ge L, Reda D, Klein R, Reaven PD, Hayward R. Association of Blood Glucose Control and Lipids With Diabetic Retinopathy in the Veterans Affairs Diabetes Trial (VADT). Diabetes Care 2016; 39:816-22. [PMID: 27006510 DOI: 10.2337/dc15-1897] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [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: 08/31/2015] [Accepted: 01/21/2016] [Indexed: 02/03/2023]
Abstract
OBJECTIVE This study examined whether lipids modify the relationship between intensive glucose control (INT) and diabetic retinopathy (DR). RESEARCH DESIGN AND METHODS The incidence and progression of DR were assessed in 858 of 1,791 participants with 7-field stereoscopic fundus photographs at baseline and 5 years later. RESULTS Odds of DR progression were lower by ∼40% in those with baseline total cholesterol (TC) ≥200 mg/dL (P = 0.007), LDL-C ≥120 mg/dL (P < 0.02), or HDL-C ≥40 mg/dL (P < 0.007) in the INT arm versus standard glycemic treatment. Odds of DR progression were reduced by ∼40% in those who had TC ≤140 mg/dL (P ≤ 0.024), triglycerides (TG) ≤120 mg/dL (P = 0.004), or HDL-C ≥45 mg/dL (P = 0.01) at the fifth year. Odds of DR progression were lower by ∼40-50% with reductions of TC by ≥40 mg/dL (P < 0.0001), of LDL-C of ≥40 mg/dL (P < 0.004), and of TG by ≥60 mg/dL (P = 0.004) at the fifth year. Odds of DR progression increased by 80% with increases in TC of ≥20 mg/dL (P < 0.0001) and by 180% with increases in LDL-C by ≥60 mg/dL (P < 0.004). After adjusting for covariants, those with higher TC at baseline and lower TC during and at the fifth year and higher HDL-C throughout study had significantly decreased odds of DR progression in INT. CONCLUSIONS INT was associated with decreased odds of progression but not with onset of retinopathy in those with worse lipid levels at baseline and more improved lipid levels during the study. Higher HDL-C was consistently associated with better response to INT throughout the study.
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Affiliation(s)
- Nasrin Azad
- Endocrinology Section, Edward Hines, Jr. VA Hospital, Hines, IL
| | - Gideon D Bahn
- Cooperative Studies Program Coordinating Center, Hines, IL
| | | | - Lily Agrawal
- Endocrinology Section, Edward Hines, Jr. VA Hospital, Hines, IL
| | - Ling Ge
- Cooperative Studies Program Coordinating Center, Hines, IL
| | - Dominic Reda
- Cooperative Studies Program Coordinating Center, Hines, IL
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin, Madison, WI
| | - Peter D Reaven
- Endocrinology Section, Carl T. Hayden VA Medical Center, Phoenix, AZ
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Tripathy D, Schwenke DC, Banerji M, Bray GA, Buchanan TA, Clement SC, Henry RR, Kitabchi AE, Mudaliar S, Ratner RE, Stentz FB, Musi N, Reaven PD, DeFronzo RA. Diabetes Incidence and Glucose Tolerance after Termination of Pioglitazone Therapy: Results from ACT NOW. J Clin Endocrinol Metab 2016; 101:2056-62. [PMID: 26982008 PMCID: PMC6287507 DOI: 10.1210/jc.2015-4202] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
CONTEXT Thiazolidinediones have proven efficacy in preventing diabetes in high-risk individuals. However, the effect of thiazolidinediones on glucose tolerance after cessation of therapy is unclear. OBJECTIVE To examine the effect of pioglitazone (PIO) on incidence of diabetes after discontinuing therapy in ACT NOW. Design, Settings and Patients: Two-hundred ninety-three subjects (placebo [PLAC], n = 138; PIO, n = 152) completed a median followup of 11.7 mo after study medication was stopped. RESULTS Diabetes developed in 138 (12.3%) of PLAC vs 17 of 152 PIO patients (11.2%; P = not significant, PIO vs PLAC). However, the cumulative incidence of diabetes from start of study medication to end of washout period remained significantly lower in PIO vs PLAC (10.7 vs 22.3%; P < .005). After therapy was discontinued, 23.0% (35/152) of PIO-treated patients remained normal-glucose tolerant (NGT) vs 13.8% (19/138) of PLAC-treated patients (P = .04). Insulin secretion/insulin resistance index (I0-120/G0-120 × Matsuda index) was markedly lower in subjects with impaired glucose tolerance (IGT) who converted to diabetes during followup vs those who remained IGT or NGT. The decline in-cell function (insulin secretion/insulin resistance index) was similar in subjects with IGT who developed diabetes, irrespective of whether they were treated with PIO or PLAC. CONCLUSIONS 1) The protective effect of PIO on incidence of diabetes attenuates after discontinuation of therapy, 2) cumulative incidence of diabetes in individuals exposed to PIO remained significantly (56%) lower than PLAC and a greater number of PIO-treated individuals maintained NGT after median followup of 11.4 mo, and 3) low insulin secretion/insulin resistance index is a strong predictor of future diabetes following PIO discontinuation.
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Affiliation(s)
- Devjit Tripathy
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Dawn C Schwenke
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - MaryAnn Banerji
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - George A Bray
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Thomas A Buchanan
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Stephen C Clement
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Robert R Henry
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Abbas E Kitabchi
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Sunder Mudaliar
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Robert E Ratner
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Frankie B Stentz
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Nicolas Musi
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Peter D Reaven
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
| | - Ralph A DeFronzo
- Texas Diabetes Institute and University of Texas Health Science Center (D.T., N.M., R.A.D.), South Texas Veterans Health Care System, San Antonio, Texas 78229; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing & Health Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85281; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center (G.A.B.), Louisiana State University, Baton Rouge, Louisiana 70803; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; VA San Diego Healthcare System and University of California, San Diego (R.R.H., S.M.), San Diego, California 92093; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee-Memphis, Memphis, Tennessee; and Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782
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Yassine HN, Trenchevska O, Dong Z, Bashawri Y, Koska J, Reaven PD, Nelson RW, Nedelkov D. The association of plasma cystatin C proteoforms with diabetic chronic kidney disease. Proteome Sci 2016; 14:7. [PMID: 27019641 PMCID: PMC4807542 DOI: 10.1186/s12953-016-0096-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 03/18/2016] [Indexed: 01/20/2023] Open
Abstract
Background Cystatin C (CysC) is an endogenous cysteine protease inhibitor that can be used to assess the progression of kidney function. Recent studies demonstrate that CysC is a more specific indicator of glomerular filtration rate (GFR) than creatinine. CysC in plasma exists in multiple proteoforms. The goal of this study was to clarify the association of native CysC, CysC missing N-terminal Serine (CysC des-S), and CysC without three N-terminal residues (CysC des-SSP) with diabetic chronic kidney disease (CKD). Results Using mass spectrometric immunoassay, the plasma concentrations of native CysC and the two CysC truncation proteoforms were examined in 111 individuals from three groups: 33 non-diabetic controls, 34 participants with type 2 diabetes (DM) and without CKD and 44 participants with diabetic CKD. Native CysC concentrations were 1.4 fold greater in CKD compared to DM group (p = 0.02) and 1.5 fold greater in CKD compared to the control group (p = 0.001). CysC des-S concentrations were 1.55 fold greater in CKD compared to the DM group (p = 0.002) and 1.9 fold greater in CKD compared to the control group (p = 0.0002). CysC des-SSP concentrations were 1.8 fold greater in CKD compared to the DM group (p = 0.008) and 1.52 fold greater in CKD compared to the control group (p = 0.002). In addition, the concentrations of CysC proteoforms were greater in the setting of albuminuria. The truncated CysC proteoform concentrations were associated with estimated GFR independent of native CysC concentrations. Conclusion Our findings demonstrate a greater amount of CysC proteoforms in diabetic CKD. We therefore suggest assessing the role of cystatin C proteoforms in the progression of CKD. Electronic supplementary material The online version of this article (doi:10.1186/s12953-016-0096-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Olgica Trenchevska
- Molecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, P.O. Box 876601, Tempe, AZ 85287-6601 USA
| | - Zhiwei Dong
- University of Southern California, Los Angeles, CA USA
| | - Yara Bashawri
- University of Southern California, Los Angeles, CA USA
| | - Juraj Koska
- Phoenix VA Health Care System, Phoenix, AZ USA
| | | | - Randall W Nelson
- Molecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, P.O. Box 876601, Tempe, AZ 85287-6601 USA
| | - Dobrin Nedelkov
- Molecular Biomarkers Laboratory, Biodesign Institute, Arizona State University, P.O. Box 876601, Tempe, AZ 85287-6601 USA
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Azizkhanian I, Trenchevska O, Bashawri Y, Hu J, Koska J, Reaven PD, Nelson RW, Nedelkov D, Yassine HN. Posttranslational modifications of apolipoprotein A-II proteoforms in type 2 diabetes. J Clin Lipidol 2016; 10:808-815. [PMID: 27578111 DOI: 10.1016/j.jacl.2016.03.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [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: 11/03/2015] [Revised: 02/25/2016] [Accepted: 03/01/2016] [Indexed: 01/04/2023]
Abstract
BACKGROUND Apolipoprotein A-II (apoA-II) is the second most abundant protein in high-density lipoprotein particles. However, it exists in plasma in multiple forms. The effect of diabetes on apoA-II proteoforms is not known. OBJECTIVE Our objective was to characterize plasma apoA-II proteoforms in participants with and without type 2 diabetes. METHODS Using a novel mass spectrometric immunoassay, the relative abundance of apoA-II proteoforms was examined in plasma of 30 participants with type 2 diabetes and 25 participants without diabetes. RESULTS Six apoA-II proteoforms (monomer, truncated TQ monomer, truncated Q monomer, dimer, truncated Q dimer, and truncated 2Qs dimer) and their oxidized proteoforms were identified. The ratios of oxidized monomer and all oxidized proteoforms to the native apoA-II were significantly greater in the diabetic group (P = .004 and P = .005, respectively) compared with the nondiabetic group. CONCLUSION The relative abundance of oxidized apoA-II is significantly increased in type 2 diabetes.
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Affiliation(s)
- Ida Azizkhanian
- Department of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Yara Bashawri
- Department of Medicine, University of Southern California, Los Angeles, CA, USA; King Fahad Medical City, Riyadh, Saudi Arabia
| | - Jiaqi Hu
- Department of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Juraj Koska
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ, USA
| | - Peter D Reaven
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ, USA
| | | | | | - Hussein N Yassine
- Department of Medicine, University of Southern California, Los Angeles, CA, USA.
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Koska J, Yassine H, Trenchevska O, Sinari S, Schwenke DC, Yen FT, Billheimer D, Nelson RW, Nedelkov D, Reaven PD. Disialylated apolipoprotein C-III proteoform is associated with improved lipids in prediabetes and type 2 diabetes. J Lipid Res 2016; 57:894-905. [PMID: 26945091 DOI: 10.1194/jlr.p064816] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [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: 10/28/2015] [Indexed: 11/20/2022] Open
Abstract
The apoC-III proteoform containing two sialic acid residues (apoC-III2) has different in vitro effects on lipid metabolism compared with asialylated (apoC-III0) or the most abundant monosialylated (apoC-III1) proteoforms. Cross-sectional and longitudinal associations between plasma apoC-III proteoforms (by mass spectrometric immunoassay) and plasma lipids were tested in two randomized clinical trials: ACT NOW, a study of pioglitazone in subjects with impaired glucose tolerance (n = 531), and RACED (n = 296), a study of intensive glycemic control and atherosclerosis in type 2 diabetes patients. At baseline, higher relative apoC-III2 and apoC-III2/apoC-III1 ratios were associated with lower triglycerides and total cholesterol in both cohorts, and with lower small dense LDL in the RACED. Longitudinally, changes in apoC-III2/apoC-III1 were inversely associated with changes in triglycerides in both cohorts, and with total and small dense LDL in the RACED. apoC-III2/apoC-III1 was also higher in patients treated with PPAR-γ agonists and was associated with reduced cardiovascular events in the RACED control group. Ex vivo studies of apoC-III complexes with higher apoC-III2/apoC-III1 showed attenuated inhibition of VLDL uptake by HepG2 cells and LPL-mediated lipolysis, providing possible functional explanations for the inverse association between a higher apoC-III2/apoC-III1 and hypertriglyceridemia, proatherogenic plasma lipid profiles, and cardiovascular risk.
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Affiliation(s)
- Juraj Koska
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
| | | | | | | | | | - Frances T Yen
- Université de Lorraine, URAFPA, INSERM, Vandoeuvre-lès-Nancy, France
| | | | | | | | - Peter D Reaven
- Phoenix Veterans Affairs Health Care System, Phoenix, AZ
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Saremi A, Bahn GD, Reaven PD. A Link Between Hypoglycemia and Progression of Atherosclerosis in the Veterans Affairs Diabetes Trial (VADT). Diabetes Care 2016; 39:448-54. [PMID: 26786575 PMCID: PMC5317238 DOI: 10.2337/dc15-2107] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [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: 09/25/2015] [Accepted: 11/30/2015] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To determine whether a link exists between serious hypoglycemia and progression of atherosclerosis in a substudy of the Veterans Affairs Diabetes Trial (VADT) and to examine whether glycemic control during the VADT modified the association between serious hypoglycemia and coronary artery calcium (CAC) progression. RESEARCH DESIGN AND METHODS Serious hypoglycemia was defined as severe episodes with loss of consciousness or requiring assistance or documented glucose <50 mg/dL. Progression of CAC was determined in 197 participants with baseline and follow-up computed tomography scans. RESULTS During an average follow-up of 4.5 years between scans, 97 participants reported severe hypoglycemia (n = 23) or glucose <50 mg/dL (n = 74). Serious hypoglycemia occurred more frequently in the intensive therapy group than in the standard treatment group (74% vs. 21%, P < 0.01). Serious hypoglycemia was not associated with progression of CAC in the entire cohort, but the interaction between serious hypoglycemia and treatment was significant (P < 0.01). Participants with serious hypoglycemia in the standard therapy group, but not in the intensive therapy group, had ∼50% greater progression of CAC than those without serious hypoglycemia (median 11.15 vs. 5.4 mm(3), P = 0.02). Adjustment for all baseline differences, including CAC, or time-varying risk factors during the trial, did not change the results. Examining the effect of serious hypoglycemia by on-trial HbA1c levels (cutoff 7.5%) yielded similar results. In addition, a dose-response relationship was found between serious hypoglycemia and CAC progression in the standard therapy group only. CONCLUSIONS Despite a higher frequency of serious hypoglycemia in the intensive therapy group, serious hypoglycemia was associated with progression of CAC in only the standard therapy group.
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Affiliation(s)
| | - Gideon D Bahn
- Cooperative Studies Program Coordinating Center, Hines, IL
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Florez H, Reaven PD, Bahn G, Moritz T, Warren S, Marks J, Reda D, Duckworth W, Abraira C, Hayward R, Emanuele N. Rosiglitazone treatment and cardiovascular disease in the Veterans Affairs Diabetes Trial. Diabetes Obes Metab 2015; 17:949-55. [PMID: 25964070 PMCID: PMC4676911 DOI: 10.1111/dom.12487] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Revised: 03/31/2015] [Accepted: 05/02/2015] [Indexed: 01/17/2023]
Abstract
AIMS To evaluate the relationship between patterns of rosiglitazone use and cardiovascular (CV) outcomes in the Veterans Affairs Diabetes Trial (VADT). METHODS Time-dependent survival analyses, case-control and 1 : 1 propensity matching approaches were used to examine the relationship between patterns of rosiglitazone use and CV outcomes in the VADT, a randomized controlled study that assessed the effect of intensive glycaemic control on CV outcomes in 1791 patients with type 2 diabetes (T2D) whose mean age was 60.4 ± 9 years. Participants were recruited between 1 December 2000 and 31 May 2003, and were followed for 5-7.5 years (median 5.6) with a final visit by 31 May 2008. Rosiglitazone (4 mg and 8 mg daily) was initiated per protocol in both the intensive-therapy and standard-therapy groups. Main outcomes included a composite CV outcome, CV death and myocardial infarction (MI). RESULTS Both daily doses of rosiglitazone were associated with lower risk for the primary composite CV outcome [4 mg: hazard ratio (HR) 0.63, 95% confidence interval (CI) 0.49-0.81 and 8 mg: HR 0.60, 95% CI 0.49-0.75] after adjusting for demographic and clinical covariates. A reduction in CV death was also observed (HR 0.25, p < 0.001, for both 4 and 8 mg/day rosiglitazone); however, the effect on MI was less evident for 8 mg/day and not significant for 4 mg/day. CONCLUSIONS In older patients with T2D the use of rosiglitazone was associated with decreased risk of the primary CV composite outcome and CV death. Rosiglitazone use did not lead to a higher risk of MI.
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Affiliation(s)
- H Florez
- Miami VA Healthcare System, GRECC, University of Miami, Miami, FL, USA
| | - P D Reaven
- Phoenix VA Health Care Center, Department of Medicine, Phoenix, AZ, USA
| | - G Bahn
- Hines VA Cooperative Studies Program, Coordinating Center, Hines VA Hospital, Hines, IL, USA
| | - T Moritz
- Hines VA Cooperative Studies Program, Coordinating Center, Hines VA Hospital, Hines, IL, USA
| | - S Warren
- VA Cooperative Studies Program, Clinical Research Pharmacy Coordinating Center, University of New Mexico, Albuquerque, NM, USA
| | - J Marks
- Miami VA Healthcare System, GRECC, University of Miami, Miami, FL, USA
| | - D Reda
- Hines VA Cooperative Studies Program, Coordinating Center, Hines VA Hospital, Hines, IL, USA
| | - W Duckworth
- Phoenix VA Health Care Center, Department of Medicine, Phoenix, AZ, USA
| | - C Abraira
- Miami VA Healthcare System, GRECC, University of Miami, Miami, FL, USA
| | - R Hayward
- VA Center for Practice Management & Outcomes Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - N Emanuele
- Hines VA Cooperative Studies Program, Coordinating Center, Hines VA Hospital, Hines, IL, USA
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Koska J, Sands M, Burciu C, D'Souza KM, Raravikar K, Liu J, Truran S, Franco DA, Schwartz EA, Schwenke DC, D'Alessio D, Migrino RQ, Reaven PD. Exenatide Protects Against Glucose- and Lipid-Induced Endothelial Dysfunction: Evidence for Direct Vasodilation Effect of GLP-1 Receptor Agonists in Humans. Diabetes 2015; 64:2624-35. [PMID: 25720388 PMCID: PMC4477348 DOI: 10.2337/db14-0976] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2014] [Accepted: 02/17/2015] [Indexed: 01/24/2023]
Abstract
GLP-1 receptor (GLP-1R) agonists may improve endothelial function (EF) via metabolic improvement and direct vascular action. The current study determined the effect of GLP-1R agonist exenatide on postprandial EF in type 2 diabetes and the mechanisms underlying GLP-1R agonist-mediated vasodilation. Two crossover studies were conducted: 36 participants with type 2 diabetes received subcutaneous exenatide or placebo for 11 days and EF, and glucose and lipid responses to breakfast and lunch were determined; and 32 participants with impaired glucose tolerance (IGT) or diet-controlled type 2 diabetes had EF measured before and after intravenous exenatide, with or without the GLP-1R antagonist exendin-9. Mechanisms of GLP-1R agonist action were studied ex vivo on human subcutaneous adipose tissue arterioles and endothelial cells. Subcutaneous exenatide increased postprandial EF independent of reductions in plasma glucose and triglycerides. Intravenous exenatide increased fasting EF, and exendin-9 abolished this effect. Exenatide elicited eNOS activation and NO production in endothelial cells, and induced dose-dependent vasorelaxation and reduced high-glucose or lipid-induced endothelial dysfunction in arterioles ex vivo. These effects were reduced with AMPK inhibition. In conclusion, exenatide augmented postprandial EF in subjects with diabetes and prevented high-glucose and lipid-induced endothelial dysfunction in human arterioles. These effects were largely direct, via GLP-1R and AMPK activation.
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Affiliation(s)
- Juraj Koska
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
| | - Michelle Sands
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
| | - Camelia Burciu
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
| | - Karen M D'Souza
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
| | | | - James Liu
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
| | - Seth Truran
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
| | - Daniel A Franco
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
| | - Eric A Schwartz
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
| | - Dawn C Schwenke
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
| | - David D'Alessio
- Division of Endocrinology, Diabetes and Metabolism, Duke University, Durham, NC
| | | | - Peter D Reaven
- Department of Medicine, Phoenix VA Health Care System, Phoenix, AZ
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Hayward RA, Reaven PD, Wiitala WL, Bahn GD, Reda DJ, Ge L, McCarren M, Duckworth WC, Emanuele NV. Follow-up of glycemic control and cardiovascular outcomes in type 2 diabetes. N Engl J Med 2015; 372:2197-206. [PMID: 26039600 DOI: 10.1056/nejmoa1414266] [Citation(s) in RCA: 410] [Impact Index Per Article: 45.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND The Veterans Affairs Diabetes Trial previously showed that intensive glucose lowering, as compared with standard therapy, did not significantly reduce the rate of major cardiovascular events among 1791 military veterans (median follow-up, 5.6 years). We report the extended follow-up of the study participants. METHODS After the conclusion of the clinical trial, we followed participants, using central databases to identify procedures, hospitalizations, and deaths (complete cohort, with follow-up data for 92.4% of participants). Most participants agreed to additional data collection by means of annual surveys and periodic chart reviews (survey cohort, with 77.7% follow-up). The primary outcome was the time to the first major cardiovascular event (heart attack, stroke, new or worsening congestive heart failure, amputation for ischemic gangrene, or cardiovascular-related death). Secondary outcomes were cardiovascular mortality and all-cause mortality. RESULTS The difference in glycated hemoglobin levels between the intensive-therapy group and the standard-therapy group averaged 1.5 percentage points during the trial (median level, 6.9% vs. 8.4%) and declined to 0.2 to 0.3 percentage points by 3 years after the trial ended. Over a median follow-up of 9.8 years, the intensive-therapy group had a significantly lower risk of the primary outcome than did the standard-therapy group (hazard ratio, 0.83; 95% confidence interval [CI], 0.70 to 0.99; P=0.04), with an absolute reduction in risk of 8.6 major cardiovascular events per 1000 person-years, but did not have reduced cardiovascular mortality (hazard ratio, 0.88; 95% CI, 0.64 to 1.20; P=0.42). No reduction in total mortality was evident (hazard ratio in the intensive-therapy group, 1.05; 95% CI, 0.89 to 1.25; P=0.54; median follow-up, 11.8 years). CONCLUSIONS After nearly 10 years of follow-up, patients with type 2 diabetes who had been randomly assigned to intensive glucose control for 5.6 years had 8.6 fewer major cardiovascular events per 1000 person-years than those assigned to standard therapy, but no improvement was seen in the rate of overall survival. (Funded by the VA Cooperative Studies Program and others; VADT ClinicalTrials.gov number, NCT00032487.).
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Affiliation(s)
- Rodney A Hayward
- From the Veterans Affairs (VA) Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI (R.A.H., W.L.W.); Phoenix VA Health Care System, Phoenix, AZ (P.D.R., W.C.D.); and the Hines VA Cooperative Studies Program Coordinating Center and Edward Hines, Jr., VA Hospital (G.D.B., D.J.R., L.G., N.V.E.), and VA Pharmacy Benefits Management Services (M.M.) - all in Hines, IL
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Yassine HN, Ramrakhiani A, Parekh A, Walker R, Goran M, Trenchevska O, Nedelkov D, Nelson R, Koska J, Reaven PD, Yen FT. Abstract 30: Apolipoprotein CIII Sialylation is a Critical Determinant of Liver Triglyceride Metabolism. Arterioscler Thromb Vasc Biol 2015. [DOI: 10.1161/atvb.35.suppl_1.30] [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: 11/16/2022]
Abstract
Apolipoprotein (apo) CIII inhibits lipoprotein lipase (LPL) activity and remnant particle uptake in the liver by the lipolysis stimulated receptor (LSR); and therefore modulates liver and systemic lipid metabolism. Although post-translational modifications of apo CIII lead to asialylated, mono- or di-sialylated variants, the biological relevance of these sialylations is not known. Our objectives were to determine the association of apo C-III sialylation with plasma triglycerides and liver fat content in vivo, and to evaluate the effect of apo CIII sialylation on lipid uptake in liver cells or LPL activity in vitro. In 209 obese non-diabetic adolescent Hispanic participants, apo CIII variants in plasma were measured using mass spectrometric immunoassay. Increased plasma apo C-III sialylation (di- to mono-sialylated apo CIII ratio) was associated with lower triglyceride levels (r=-0.43, p<0.001) and liver fat (by MRI, r=-0.27, p<0.001) independent of total apo CIII concentrations. Higher plasma concentrations of the mono-, but not the di-sialylated variant, were associated with higher triglycerides concentrations (r=0.53, p<0.001). In HepG2 liver cells, immunoprecipitated apo CIII from VLDL of participants in the upper quartile of plasma apo CIII sialylation less effectively inhibited LSR-mediated VLDL uptake compared to apo CIII from those in the lower quartile of apo CIII sialylation (28% difference, p=0.02). This difference in inhibition was abolished by removal of sialic acid with neuraminidase. Apo CIII isolated from VLDL of participants with different level of apo CIII sialylation showed similar capacity to inhibit fatty acid release by LPL of control VLDL. VLDL particles with higher apo CIII sialylation also demonstrated a two-fold increase in ApoE. We conclude that a greater apo CIII sialylation together with particle enrichment in apo E allow for more efficient VLDL liver uptake and less liver fat accumulation. The measurement of plasma apo CIII sialylation may be a useful index of triglyceride metabolism and risk of fatty liver.
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Affiliation(s)
| | | | | | - Ryan Walker
- Preventive Medicine, Univ of Southern California, Los Angeles, CA
| | - Michael Goran
- Preventive Medicine, Univ of Southern California, Los Angeles, CA
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Tripathy D, Cobb JE, Gall W, Adam KP, George T, Schwenke DC, Banerji M, Bray GA, Buchanan TA, Clement SC, Henry RR, Kitabchi AE, Mudaliar S, Ratner RE, Stentz FB, Reaven PD, Musi N, Ferrannini E, DeFronzo RA. A novel insulin resistance index to monitor changes in insulin sensitivity and glucose tolerance: the ACT NOW study. J Clin Endocrinol Metab 2015; 100:1855-62. [PMID: 25603459 PMCID: PMC4422894 DOI: 10.1210/jc.2014-3824] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
OBJECTIVE The objective was to test the clinical utility of Quantose M(Q) to monitor changes in insulin sensitivity after pioglitazone therapy in prediabetic subjects. Quantose M(Q) is derived from fasting measurements of insulin, α-hydroxybutyrate, linoleoyl-glycerophosphocholine, and oleate, three nonglucose metabolites shown to correlate with insulin-stimulated glucose disposal. RESEARCH DESIGN AND METHODS Participants were 428 of the total of 602 ACT NOW impaired glucose tolerance (IGT) subjects randomized to pioglitazone (45 mg/d) or placebo and followed for 2.4 years. At baseline and study end, fasting plasma metabolites required for determination of Quantose, glycated hemoglobin, and oral glucose tolerance test with frequent plasma insulin and glucose measurements to calculate the Matsuda index of insulin sensitivity were obtained. RESULTS Pioglitazone treatment lowered IGT conversion to diabetes (hazard ratio = 0.25; 95% confidence interval = 0.13-0.50; P < .0001). Although glycated hemoglobin did not track with insulin sensitivity, Quantose M(Q) increased in pioglitazone-treated subjects (by 1.45 [3.45] mg·min(-1)·kgwbm(-1)) (median [interquartile range]) (P < .001 vs placebo), as did the Matsuda index (by 3.05 [4.77] units; P < .0001). Quantose M(Q) correlated with the Matsuda index at baseline and change in the Matsuda index from baseline (rho, 0.85 and 0.79, respectively; P < .0001) and was progressively higher across closeout glucose tolerance status (diabetes, IGT, normal glucose tolerance). In logistic models including only anthropometric and fasting measurements, Quantose M(Q) outperformed both Matsuda and fasting insulin in predicting incident diabetes. CONCLUSIONS In IGT subjects, Quantose M(Q) parallels changes in insulin sensitivity and glucose tolerance with pioglitazone therapy. Due to its strong correlation with improved insulin sensitivity and its ease of use, Quantose M(Q) may serve as a useful clinical test to identify and monitor therapy in insulin-resistant patients.
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Affiliation(s)
- Devjit Tripathy
- Texas Diabetes Institute (D.T., N.M., R.A.D.), University of Texas Health Science Center, San Antonio, Texas 78207; South Texas Veterans Health Care System (D.T., N.M., R.A.D.), Audie L. Murphy Division, San Antonio, Texas 78228; Metabolon, Inc (J.E.C., W.G., K.-P.A., T.G.), Durham, North Carolina 27713; Phoenix VA Health Care System (D.C.S., P.D.R.), Phoenix, Arizona 85012; College of Nursing and Health Care Innovation (D.C.S.), Arizona State University, Phoenix, Arizona 85004; SUNY Health Science Center at Brooklyn (M.A.B.), Brooklyn, New York 11203; Pennington Biomedical Research Center/Louisiana State University (G.A.B.), Baton Rouge, Louisiana 70808; University of Southern California Keck School of Medicine (T.A.B.), Los Angeles, California 90033; VA San Diego Healthcare System and University of California at San Diego (R.R.H., S.M.), San Diego, California 92161; Division of Endocrinology, Diabetes and Metabolism (A.E.K., F.B.S.), University of Tennessee, Memphis, Tennessee 38163; Inova Fairfax Hospital (S.C.C.), Falls Church, Virginia 22042; Medstar Research Institute (R.E.R.), Hyattsville, Maryland 20782; and Department of Clinical and Experimental Medicine (E.F.), CNR Institute of Clinical Physiology, 56126 Pisa, Italy
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Chokrungvaranon N, Deer J, Reaven PD. Intensive Glycemic Control and Cardiovascular Disease: Are There Patients Who May Benefit? Postgrad Med 2015; 123:114-23. [DOI: 10.3810/pgm.2011.11.2501] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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Saremi A, Schwenke DC, Bahn G, Ge L, Emanuele N, Reaven PD. The effect of intensive glucose lowering therapy among major racial/ethnic groups in the Veterans Affairs Diabetes Trial. Metabolism 2015; 64:218-25. [PMID: 25456099 PMCID: PMC4982373 DOI: 10.1016/j.metabol.2014.10.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [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: 07/18/2014] [Revised: 10/10/2014] [Accepted: 10/11/2014] [Indexed: 12/19/2022]
Abstract
OBJECTIVE To examine the effect of intensive glycemic control on cardiovascular disease events (CVD) among the major race/ethnic groups in a post-hoc analysis of the VADT. MATERIALS AND METHODS Participants included 1111 non-Hispanic Whites, 307 Hispanics and 306 non-Hispanic Blacks randomized to intensive or standard glucose treatment in VADT. Multivariable Cox proportional hazards models were constructed to assess the effect of intensive glucose treatment on CVD events among race/ethnic groups. RESULTS Mean age was 60.4 years and median follow-up was 5.6 years. By design, modifiable risk factors were managed equally well in both treatment arms and only differed modestly between race/ethnic groups. HbA(1c) decreased significantly from baseline with intensive glucose treatment in each race/ethnic group, with a trend for a greater response in Hispanics (P=0.02 for overall comparison between groups). Intensive glucose treatment was associated with reduced risk of CVD events for Hispanics but not for others (hazard ratios ranged from 0.54 to 0.75 for Hispanics whereas they were consistently close to 1 for others). Sensitivity analyses with different definitions of race/ethnicity or limited to individuals free of previous known CVD yielded similar results. CONCLUSIONS The results of these analyses support the hypothesis that race/ethnicity is worthy of consideration when tailoring intensive treatment for individuals with long-standing type 2 diabetes. However, additional studies are needed to confirm the findings of this post-hoc analysis.
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Affiliation(s)
| | | | - Gideon Bahn
- Cooperative Studies Program Coordinating Center, Hines, Illinois
| | - Ling Ge
- Cooperative Studies Program Coordinating Center, Hines, Illinois
| | - Nicholas Emanuele
- Medical and Research Services, Hines Veterans Affairs Hospital, Hines, Illinois
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Yassine HN, Trenchevska O, He H, Borges CR, Nedelkov D, Mack W, Kono N, Koska J, Reaven PD, Nelson RW. Serum amyloid a truncations in type 2 diabetes mellitus. PLoS One 2015; 10:e0115320. [PMID: 25607823 PMCID: PMC4301920 DOI: 10.1371/journal.pone.0115320] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2014] [Accepted: 11/21/2014] [Indexed: 12/16/2022] Open
Abstract
Serum Amyloid A (SAA) is an acute phase protein complex consisting of several abundant isoforms. The N- terminus of SAA is critical to its function in amyloid formation. SAA is frequently truncated, either missing an arginine or an arginine-serine dipeptide, resulting in isoforms that may influence the capacity to form amyloid. However, the relative abundance of truncated SAA in diabetes and chronic kidney disease is not known.
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Affiliation(s)
- Hussein N Yassine
- University of Southern California, Los Angeles, CA, United States of America
| | | | - Huijuan He
- University of Southern California, Los Angeles, CA, United States of America
| | - Chad R Borges
- Arizona State University, Tempe, AZ, United States of America
| | - Dobrin Nedelkov
- Arizona State University, Tempe, AZ, United States of America
| | - Wendy Mack
- University of Southern California, Los Angeles, CA, United States of America
| | - Naoko Kono
- University of Southern California, Los Angeles, CA, United States of America
| | - Juraj Koska
- Phoenix VA Health Care System, Phoenix, AZ, United States of America
| | - Peter D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, United States of America
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