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Nathan DM, Lachin JM, Bebu I, Burch HB, Buse JB, Cherrington AL, Fortmann SP, Green JB, Kahn SE, Kirkman MS, Krause-Steinrauf H, Larkin ME, Phillips LS, Pop-Busui R, Steffes M, Tiktin M, Tripputi M, Wexler DJ, Younes N. Glycemia Reduction in Type 2 Diabetes - Microvascular and Cardiovascular Outcomes. N Engl J Med 2022; 387:1075-1088. [PMID: 36129997 PMCID: PMC9832916 DOI: 10.1056/nejmoa2200436] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [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: 02/02/2023]
Abstract
BACKGROUND Data are lacking on the comparative effectiveness of commonly used glucose-lowering medications, when added to metformin, with respect to microvascular and cardiovascular disease outcomes in persons with type 2 diabetes. METHODS We assessed the comparative effectiveness of four commonly used glucose-lowering medications, added to metformin, in achieving and maintaining a glycated hemoglobin level of less than 7.0% in participants with type 2 diabetes. The randomly assigned therapies were insulin glargine U-100 (hereafter, glargine), glimepiride, liraglutide, and sitagliptin. Prespecified secondary outcomes with respect to microvascular and cardiovascular disease included hypertension and dyslipidemia, confirmed moderately or severely increased albuminuria or an estimated glomerular filtration rate of less than 60 ml per minute per 1.73 m2 of body-surface area, diabetic peripheral neuropathy assessed with the Michigan Neuropathy Screening Instrument, cardiovascular events (major adverse cardiovascular events [MACE], hospitalization for heart failure, or an aggregate outcome of any cardiovascular event), and death. Hazard ratios are presented with 95% confidence limits that are not adjusted for multiple comparisons. RESULTS During a mean 5.0 years of follow-up in 5047 participants, there were no material differences among the interventions with respect to the development of hypertension or dyslipidemia or with respect to microvascular outcomes; the mean overall rate (i.e., events per 100 participant-years) of moderately increased albuminuria levels was 2.6, of severely increased albuminuria levels 1.1, of renal impairment 2.9, and of diabetic peripheral neuropathy 16.7. The treatment groups did not differ with respect to MACE (overall rate, 1.0), hospitalization for heart failure (0.4), death from cardiovascular causes (0.3), or all deaths (0.6). There were small differences with respect to rates of any cardiovascular disease, with 1.9, 1.9, 1.4, and 2.0 in the glargine, glimepiride, liraglutide, and sitagliptin groups, respectively. When one treatment was compared with the combined results of the other three treatments, the hazard ratios for any cardiovascular disease were 1.1 (95% confidence interval [CI], 0.9 to 1.3) in the glargine group, 1.1 (95% CI, 0.9 to 1.4) in the glimepiride group, 0.7 (95% CI, 0.6 to 0.9) in the liraglutide group, and 1.2 (95% CI, 1.0 to 1.5) in the sitagliptin group. CONCLUSIONS In participants with type 2 diabetes, the incidences of microvascular complications and death were not materially different among the four treatment groups. The findings indicated possible differences among the groups in the incidence of any cardiovascular disease. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others; GRADE ClinicalTrials.gov number, NCT01794143.).
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Affiliation(s)
- David M Nathan
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - John M Lachin
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Ionut Bebu
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Henry B Burch
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - John B Buse
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Andrea L Cherrington
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Stephen P Fortmann
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Jennifer B Green
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Steven E Kahn
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - M Sue Kirkman
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Heidi Krause-Steinrauf
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Mary E Larkin
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Lawrence S Phillips
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Rodica Pop-Busui
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Michael Steffes
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Margaret Tiktin
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Mark Tripputi
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Deborah J Wexler
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
| | - Naji Younes
- From the Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston (D.M.N., M.E.L., D.J.W.); the Biostatistics Center, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Rockville (J.M.L., I.B., H.K.-S., M. Tripputi, N.Y.), and the National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda (H.B.B.) - both in Maryland; the Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill (J.B.B., M.S.K.), and the Department of Medicine, Duke Division of Endocrinology, Metabolism, and Nutrition, Duke University Medical Center, Durham (J.B.G.) - both in North Carolina; the University of Alabama, Birmingham (A.L.C.); Kaiser Permanente Center for Health Research, Portland, OR (S.P.F.); the Division of Metabolism, Endocrinology, and Nutrition, Department of Medicine, Veterans Affairs (VA) Puget Sound Health Care System, University of Washington, Seattle (S.E.K.); the Atlanta VA Medical Center, Decatur, GA (L.S.P.); the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor (R.P.-B.); the Advanced Research and Diagnostic Laboratory, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis (M.S.); and the Louis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland (M. Tiktin)
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Gubitosi-Klug RA, Braffett BH, Hitt S, Arends V, Uschner D, Jones K, Diminick L, Karger AB, Paterson AD, Roshandel D, Marcovina S, Lachin JM, Steffes M, Palmer JP. Residual β cell function in long-term type 1 diabetes associates with reduced incidence of hypoglycemia. J Clin Invest 2021; 131:143011. [PMID: 33529168 PMCID: PMC7843223 DOI: 10.1172/jci143011] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [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: 08/04/2020] [Accepted: 12/09/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUNDWe investigated residual β cell function in Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study participants with an average 35-year duration of type 1 diabetes mellitus (T1DM).METHODSSerum C-peptide was measured during a 4-hour mixed-meal tolerance test. Associations with metabolic outcomes and complications were explored among nonresponders (all C-peptide values after meal <0.003 nmol/L) and 3 categories of responders, classified by peak C-peptide concentration (nmol/L) as high (>0.2), intermediate (>0.03 to ≤0.2), and low (≥ 0.003 to ≤0.03).RESULTSOf the 944 participants, 117 (12.4%) were classified as responders. Residual C-peptide concentrations were associated with higher DCCT baseline concentrations of stimulated C-peptide (P value for trend = 0.0001). Residual C-peptide secretion was not associated with current or mean HbA1c, HLA high-risk haplotypes for T1DM, or the current presence of T1DM autoantibodies. The proportion of subjects with a history of severe hypoglycemia was lower with high (27%) and intermediate (48%) residual C-peptide concentrations than with low (74%) and no (70%) residual C-peptide concentrations (P value for trend = 0.0001). Responders and nonresponders demonstrated similar rates of advanced microvascular complications.CONCLUSIONβ Cell function can persist in long-duration T1DM. With a peak C-peptide concentration of >0.03 nmol/L, we observed clinically meaningful reductions in the prevalence of severe hypoglycemia.TRIAL REGISTRATIONClinicalTrials.gov NCT00360815 and NCT00360893.FUNDINGDivision of Diabetes Endocrinology and Metabolic Diseases of the National Institute of Diabetes and Digestive and Kidney Diseases (DP3-DK104438, U01 DK094176, and U01 DK094157).
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Affiliation(s)
- Rose A. Gubitosi-Klug
- Rainbow Babies and Children’s Hospital, Case Western Reserve University, Cleveland, Ohio, USA
| | - Barbara H. Braffett
- The Biostatistics Center, George Washington University, Rockville, Maryland, USA
| | - Susan Hitt
- University of Missouri, Columbia, Missouri, USA
| | | | - Diane Uschner
- The Biostatistics Center, George Washington University, Rockville, Maryland, USA
| | | | - Lisa Diminick
- The Biostatistics Center, George Washington University, Rockville, Maryland, USA
| | - Amy B. Karger
- University of Minnesota, Minneapolis, Minnesota, USA
| | - Andrew D. Paterson
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
- Divisions of Epidemiology and Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Delnaz Roshandel
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - John M. Lachin
- The Biostatistics Center, George Washington University, Rockville, Maryland, USA
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Geiger S, Suarez-Lopez J, Colangelo L, Jacobs D, Steffes M, Allen N, Krefman A, Lee DH. Persistent Organochlorine Pollutants and Cardiovascular Disease, By Diabetes and Triglycerides. Ann Epidemiol 2020. [DOI: 10.1016/j.annepidem.2020.08.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Genuth SM, Vlachos H, Brooks MM, Bantle JP, Chaitman BR, Green J, Kelsey SF, King SB, McBane R, Sako EY, Schneider DJ, Steffes M, Frye RL. BARI 2D: A Reanalysis Focusing on Cardiovascular Events. Mayo Clin Proc 2019; 94:2249-2262. [PMID: 31590967 PMCID: PMC6832788 DOI: 10.1016/j.mayocp.2019.04.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [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: 09/12/2018] [Revised: 04/09/2019] [Accepted: 04/10/2019] [Indexed: 01/04/2023]
Abstract
OBJECTIVE To reanalyze the Bypass Angioplasty Revascularization Investigation 2 Diabetes trial using a new composite cardiovascular disease (CVD) outcome to determine how best to treat patients with type 2 diabetes mellitus and stable coronary artery disease. PATIENTS AND METHODS From January 1, 2001, to November 30, 2008, 2368 patients with type 2 diabetes mellitus and angiographically proven coronary artery disease were randomly assigned to insulin-sensitizing (IS) or insulin-providing (IP) therapy and simultaneously to coronary revascularization (REV) or no or delayed REV (intensive medical therapy [MED]), with all patients receiving intensive medical treatment. The outcome of this analysis was a composite of 8 CVD events. RESULTS Four-year Kaplan-Meier rates for the composite CVD outcome were 35.8% (95% CI, 33.1%-38.5%) with IS therapy and 41.6% (95% CI, 38.7%-44.5%) with IP therapy (P=.004). Much of this difference was associated with lower in-trial levels of fibrinogen, C-reactive protein, and hemoglobin A1c with IS therapy. Four-year composite CVD rates were 32.7% (95% CI, 30.0%-35.4%) with REV and 44.7% (95% CI, 41.8%-47.6%) with MED (P<.001). A beneficial effect of IS vs IP therapy was present with REV (27.7%; 95% CI, 24.0%-31.4% vs 37.5%; 95% CI, 33.6%-41.4%; P<.001), but not with MED (43.6%; 95% CI, 39.5%-47.7% vs 45.7%; 95% CI, 41.6%-49.8%; P=.37) (homogeneity, P=.05). This interaction between IS therapy and REV was limited to participants preselected for coronary artery bypass grafting (CABG). The lowest composite CVD rates occurred in patients preselected for CABG and assigned to IS therapy and REV (17.3%; 95% CI, 11.8%-22.8%). CONCLUSION In the Bypass Angioplasty Revascularization Investigation 2 Diabetes trial, the IS treatment strategy and the REV treatment strategy each reduces cardiovascular events. The combination of IS drugs and CABG results in the lowest risk of subsequent CVD events. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00006305.
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Affiliation(s)
- Saul M Genuth
- Division of Clinical and Molecular Endocrinology, Department of Medicine, Case Western Reserve University, Cleveland, OH
| | - Helen Vlachos
- Epidemiology Data Center, University of Pittsburgh, PA
| | | | - John P Bantle
- Department of Medicine, University of Minnesota, Minneapolis; Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Bernard R Chaitman
- Division of Cardiology, Department of Medicine, St. Louis University, MO
| | - Jennifer Green
- Division of Endocrinology, Department of Medicine, Duke University Medical Center, Durham, NC
| | | | | | | | - Edward Y Sako
- Department of Cardiothoracic Surgery, University of Texas Health Science Center at San Antonio
| | - David J Schneider
- Department of Medicine, University of Vermont Medical Center, Burlington
| | - Michael Steffes
- Department of Medicine, University of Minnesota, Minneapolis; Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
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Molitch ME, Gao X, Bebu I, de Boer IH, Lachin J, Paterson A, Perkins B, Saenger AK, Steffes M, Zinman B. Early Glomerular Hyperfiltration and Long-Term Kidney Outcomes in Type 1 Diabetes: The DCCT/EDIC Experience. Clin J Am Soc Nephrol 2019; 14:854-861. [PMID: 31123181 PMCID: PMC6556717 DOI: 10.2215/cjn.14831218] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 03/24/2019] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND OBJECTIVES Glomerular hyperfiltration has been considered to be a contributing factor to the development of diabetic kidney disease (DKD). To address this issue, we analyzed GFR follow-up data on participants with type 1 diabetes undergoing 125I-iothalamate clearance on entry into the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications study. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS This was a cohort study of DCCT participants with type 1 diabetes who underwent an 125I-iothalamate clearance (iGFR) at DCCT baseline. Presence of hyperfiltration was defined as iGFR levels ≥140 ml/min per 1.73 m2, with secondary thresholds of 130 or 150 ml/min per 1.73 m2. Cox proportional hazards models assessed the association between the baseline hyperfiltration status and the subsequent risk of reaching an eGFR <60 ml/min per 1.73 m2. RESULTS Of the 446 participants, 106 (24%) had hyperfiltration (iGFR levels ≥140 ml/min per 1.73 m2) at baseline. Over a median follow-up of 28 (interquartile range, 23, 33) years, 53 developed an eGFR <60 ml/min per 1.73 m2. The cumulative incidence of eGFR <60 ml/min per 1.73 m2 at 28 years of follow-up was 11.0% among participants with hyperfiltration at baseline, compared with 12.8% among participants with baseline GFR <140 ml/min per 1.73 m2. Hyperfiltration was not significantly associated with subsequent risk of developing an eGFR <60 ml/min per 1.73 m2 in an unadjusted Cox proportional hazards model (hazard ratio, 0.83; 95% confidence interval, 0.43 to 1.62) nor in an adjusted model (hazard ratio, 0.77; 95% confidence interval, 0.38 to 1.54). Application of alternate thresholds to define hyperfiltration (130 or 150 ml/min per 1.73 m2) showed similar findings. CONCLUSIONS Early hyperfiltration in patients with type 1 diabetes was not associated with a higher long-term risk of decreased GFR. Although glomerular hypertension may be a mechanism of kidney injury in DKD, higher total GFR does not appear to be a risk factor for advanced DKD.
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Affiliation(s)
- Mark E Molitch
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois;
| | - Xiaoyu Gao
- Biostatistics Center, George Washington University, Rockville, Maryland
| | - Ionut Bebu
- Biostatistics Center, George Washington University, Rockville, Maryland
| | - Ian H de Boer
- Division of Nephrology and Kidney Research Institute, University of Washington, Seattle, Washington
| | - John Lachin
- Biostatistics Center, George Washington University, Rockville, Maryland
| | - Andrew Paterson
- Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Bruce Perkins
- Division of Endocrinology and Metabolism, University of Toronto and University Health Network, Toronto, Ontario, Canada
| | - Amy K Saenger
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota; and
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota; and
| | - Bernard Zinman
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
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Molitch M, Gao X, Bebu I, De Boer I, Lachin J, Paterson A, Perkins B, Saenger A, Steffes M, Zinman B. OR14-4 Early Glomerular Hyperfiltration and Long Term Kidney Outcomes in Type 1 Diabetes: The DCCT/EDIC Experience. J Endocr Soc 2019. [PMCID: PMC6555076 DOI: 10.1210/js.2019-or14-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Glomerular hyperfiltration has long been considered to be a major contributing factor to the development of diabetic kidney disease but most studies assessed increased albumin excretion rather than reduced GFR as an outcome. To address whether early glomerular hyperfiltration results in subsequent increased risk of clinically significant loss of GFR, namely Stage 3 CKD (eGFR <60 ml/min/1.73m2), we analyzed 30 year GFR follow-up data in participants undergoing 125I-iothalamate clearance on entry into the DCCT/EDIC Study. METHODS125I-iothalamate clearance was added to the DCCT protocol in 1986 and was assessed at DCCT baseline in 446 participants. This analysis reports long-term eGFR (CKD-EPI equation) follow-up data on these participants. The association of baseline hyperfiltration (primary cutpoint of ≥140 ml/min/1.73m2) with the risk of developing Stage 3 CKD (eGFR < 60 ml/min/1.73m2) was analyzed using Cox proportional hazards models. RESULTS Of the 446 participants, 178 had iothalamate GFR levels ≥ 130 mL/min/1.73m2 and of these, 106 had levels ≥ 140 mL/min/1.73m2 and 55 had levels ≥ 150 mL/min/1.73m2 upon entry into the DCCT. Among these 446 participants, 53 developed an eGFR < 60 mL/min/1.73m2 events over a median follow-up time of 28 years (rate of 4.69 events per 1000 individuals at risk for one year), and 34 developed a sustained (i.e., two consecutive visits) eGFR <60 mL/min/1.73m2 events over a median follow-up time of 28 years (rate of 2.98 sustained events per 1000 individuals at risk for one year) in DCCT/EDIC. The proportion maintaining an eGFR ≥ 60 mL/min/1.73m2 was not decreased and was actually somewhat greater in the hyperfiltration group (95/106 = 89.6% vs. 298/340 = 87.6%) using the cutoff of 140 mL/min/1.73m2. The cumulative incidences of developing an eGFR < 60 mL/min/1.73m2 were again similar in the two hyperfiltration groups (≥140 vs. < 140 mL/min/1.73m2 - 4.1% vs. 5.9% after 20 years and 11% vs. 12.8% after 28 years). Hyperfiltration as assessed by iothalamate GFR ≥140 mL/min/1.73m2 was not associated with subsequent risk of developing an eGFR < 60 mL/min/1.73m2 in an unadjusted Cox PH model (HR= 0.83, 95%CI [0.43, 1.62]) nor in the adjusted model (HR= 0.77, 95%CI [0.38, 1.54]). Similar results were obtained for the developing of a sustained eGFR < 60 mL/min/1.73m2. Hyperfiltration cut-offs of 130 and 150 ml/min/1.73m2 showed similar findings. CONCLUSIONS Early hyperfiltration in patients with type 1 diabetes was not associated with any long-term decrease in kidney function. Though it is known with certainty that long-term improved glycemic control reduces the development of microalbuminuria, macroalbuminuria and Stage 3 CKD, the notion that early hyperfiltration is a marker of poor long term renal outcome is not supported by these findings.
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Affiliation(s)
- Mark Molitch
- NWestern Univ Feinberg Med Sch, Chicago, IL, United States
| | - Xiaoyu Gao
- Biostatistics Center, George Washington University, Rockville, MD, United States
| | - Ionut Bebu
- Biostatistics Center, George Washington University, Rockville, MD, United States
| | - Ian De Boer
- University of Washington, Seattle, WA, United States
| | - John Lachin
- Biostatistics Center, George Washington University, Rockville, MD, United States
| | - Andrew Paterson
- Genetics and Genome Biology, Hosp for Sick Children, Toronto, ON, Canada
| | - Bruce Perkins
- Dept. Of Endocrinology, Sinai Health System, Toronto, ON, Canada
| | - Amy Saenger
- University of Medicine, Chicago, IL, United States
| | - Michael Steffes
- DEPT OF LAB MED & PATH, Univ of Minnesota Med Sch, Minneapolis, MN, United States
| | - Bernard Zinman
- Leadership Sinai Ctr for Diab, Mount Sinai Hosp, University of Toronto, Toronto, ON, Canada
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Chen T, Brewster P, Tuttle KR, Dworkin LD, Henrich W, Greco BA, Steffes M, Tobe S, Jamerson K, Pencina K, Massaro JM, D'Agostino RB, Cutlip DE, Murphy TP, Cooper CJ, Shapiro JI. Prediction of cardiovascular outcomes with machine learning techniques: application to the Cardiovascular Outcomes in Renal Atherosclerotic Lesions (CORAL) study. Int J Nephrol Renovasc Dis 2019; 12:49-58. [PMID: 30962703 PMCID: PMC6433104 DOI: 10.2147/ijnrd.s194727] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [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] [Indexed: 11/29/2022] Open
Abstract
Background Data derived from the Cardiovascular Outcomes in Renal Atherosclerotic Lesions (CORAL) study were analyzed in an effort to employ machine learning methods to predict the composite endpoint described in the original study. Methods We identified 573 CORAL subjects with complete baseline data and the presence or absence of a composite endpoint for the study. These data were subjected to several models including a generalized linear (logistic-linear) model, support vector machine, decision tree, feed-forward neural network, and random forest, in an effort to attempt to predict the composite endpoint. The subjects were arbitrarily divided into training and testing subsets according to an 80%:20% distribution with various seeds. Prediction models were optimized within the CARET package of R. Results The best performance of the different machine learning techniques was that of the random forest method which yielded a receiver operator curve (ROC) area of 68.1%±4.2% (mean ± SD) on the testing subset with ten different seed values used to separate training and testing subsets. The four most important variables in the random forest method were SBP, serum creatinine, glycosylated hemoglobin, and DBP. Each of these variables was also important in at least some of the other methods. The treatment assignment group was not consistently an important determinant in any of the models. Conclusion Prediction of a composite cardiovascular outcome was difficult in the CORAL population, even when employing machine learning methods. Assignment to either the stenting or best medical therapy group did not serve as an important predictor of composite outcome. Clinical Trial Registration ClinicalTrials.gov, NCT00081731
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Affiliation(s)
- Tian Chen
- University of Toledo, Toledo, OH, USA
| | | | | | | | - William Henrich
- University of Texas Health Science Center, San Antonio, TX, USA
| | | | | | | | | | - Karol Pencina
- Harvard Clinical Research Institute, Boston University, Boston, MA, USA
| | - Joseph M Massaro
- Harvard Clinical Research Institute, Boston University, Boston, MA, USA
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Triolo TM, Fouts A, Pyle L, Yu L, Gottlieb PA, Steck AK, Greenbaum CJ, Atkinson M, Baidal D, Battaglia M, Becker D, Bingley P, Bosi E, Buckner J, Clements M, Colman P, DiMeglio L, Gitelman S, Goland R, Gottlieb P, Herold K, Knip M, Krischer J, Lernmark A, Moore W, Moran A, Muir A, Palmer J, Peakman M, Philipson L, Raskin P, Redondo M, Rodriguez H, Russell W, Spain L, Schatz D, Sosenko J, Wentworth J, Wherrett D, Wilson D, Winter W, Ziegler A, Anderson M, Antinozzi P, Benoist C, Blum J, Bourcier K, Chase P, Clare-Salzler M, Clynes R, Eisenbarth G, Fathman C, Grave G, Hering B, Insel R, Kaufman F, Kay T, Leschek E, Mahon J, Marks J, Nanto-Salonen K, Nepom G, Orban T, Parkman R, Pescovitz M, Peyman J, Pugliese A, Roep B, Roncarolo M, Savage P, Simell O, Sherwin R, Siegelman M, Skyler J, Steck A, Thomas J, Trucco M, Wagner J, Krischer JP, Leschek E, Rafkin L, Bourcier K, Cowie C, Foulkes M, Insel R, Krause-Steinrauf H, Lachin JM, Malozowski S, Peyman J, Ridge J, Savage P, Skyler JS, Zafonte SJ, Rafkin L, Sosenko JM, Kenyon NS, Santiago I, Krischer JP, Bundy B, Abbondondolo M, Dixit S, Pasha M, King K, Adcock H, Atterberry L, Fox K, Englert N, Mauras J, Permuy K, Sikes T, Adams T, Berhe B, Guendling L, McLennan L, Paganessi C, Murphy M, Draznin M, Kamboj S, Sheppard V, Lewis L, Coates W, Amado D, Moore G, Babar J, Bedard D, Brenson-Hughes J, Cernich M, Clements R, Duprau S, Goodman L, Hester L, Huerta-Saenz A, Asif I, Karmazin T, Letjen S, Raman D, Morin W, Bestermann E, Morawski J, White A, Brockmyer R, Bays S, Campbell A, Boonstra M, Stapleton N, Stone A, Donoho H, Everett H, Hensley M, Johnson C, Marshall N, Skirvin P, Taylor R, Williams L, Burroughs C, Ray C, Wolverton D, Nickels C, Dothard P, Speiser M, Pellizzari L, Bokor K, Izuora S, Abdelnour P, Cummings S, Cuthbertson D, Paynor M, Leahy M, Riedl S, Shockley R, Saad T, Briones S, Casella C, Herz K, Walsh J, Greening F, Deemer M, Hay S, Hunt N, Sikotra L, Simons D, Karounos R, Oremus L, Dye L, Myers D, Ballard W, Miers R, Eberhard C, Sparks K, Thraikill K, Edwards J, Fowlkes S, Kemp A, Morales L, Holland L, Johnson P, Paul A, Ghatak K, Fiske S, Phelen H, Leyland T, Henderson D, Brenner E, Oppenheimer I, Mamkin C, Moniz C, Clarson M, Lovell A, Peters V, Ford J, Ruelas D, Borut D, Burt M, Jordan S, Castilla P, Flores M, Ruiz L, Hanson J, Green-Blair R, Sheridan K, Garmeson J, Wintergerst G, Pierce A, Omoruyi M, Foster S, Kingery A, Lunsford I, Cervantes T, Parker P, Price J, Urben I, Guillette H, Doughty H, Haydock V, Parker P, Bergman S, Duncum C, Rodda A, Perelman R, Calendo C, Barrera E, Arce-Nunez Y, Geyer S, Martinez M, De la Portilla I, Cardenas L, Garrido M, Villar R, Lorini E, Calandra G, D’Annuzio K, Perri N, Minuto C, Hays B, Rebora R, Callegari O, Ali J, Kramer B, Auble S, Cabrera P, Donohoue R, Fiallo-Scharer M, Hessner P, Wolfgram A, Henderson C, Kansra N, Bettin R, McCuller A, Miller S, Accacha J, Corrigan E, Fiore R, Levine T, Mahoney C, Polychronakos V, Henry M, Gagne H, Starkman M, Fox D, Chin F, Melchionne L, Silverman I, Marshall L, Cerracchio J, Cruz A, Viswanathan J, Heyman K, Wilson S, Chalew S, Valley S, Layburn A, Lala P, Clesi M, Genet G, Uwaifo A, Charron T, Allerton W, Hsiao B, Cefalu L, Melendez-Ramirez R, Richards C, Alleyn E, Gustafson M, Lizanna J, Wahlen S, Aleiwe M, Hansen H, Wahlen C, Karges C, Levy A, Bonaccorso R, Rapaport Y, Tomer D, Chia M, Goldis L, Iazzetti M, Klein C, Levister L, Waldman E, Keaton N, Wallach M, Regelmann Z, Antal M, Aranda C, Reynholds A, Vinik P, Barlow M, Bourcier M, Nevoret J, Couper S, Kinderman A, Beresford N, Thalagne H, Roper J, Gibbons J, Hill S, Balleaut C, Brennan J, Ellis-Gage L, Fear T, Gray L, Law P, Jones C, McNerney L, Pointer N, Price K, Few D, Tomlinson N, Leech D, Wake C, Owens M, Burns J, Leinbach A, Wotherspoon A, Murray K, Short G, Curry S, Kelsey J, Lawson J, Porter S, Stevens E, Thomson S, Winship L, Liu S, Wynn E, Wiltshire J, Krebs P, Cresswell H, Faherty C, Ross L, Denvir J, Drew T, Randell P, Mansell S, Lloyd J, Bell S, Butler Y, Hooton H, Navarra A, Roper G, Babington L, Crate H, Cripps A, Ledlie C, Moulds R, Malloy J, Norton B, Petrova O, Silkstone C, Smith K, Ghai M, Murray V, Viswanathan M, Henegan O, Kawadry J, Olson L, Maddox K, Patterson T, Ahmad B, Flores D, Domek S, Domek K, Copeland M, George J, Less T, Davis M, Short A, Martin J, Dwarakanathan P, O’Donnell B, Boerner L, Larson M, Phillips M, Rendell K, Larson C, Smith K, Zebrowski L, Kuechenmeister M, Miller J, Thevarayapillai M, Daniels H, Speer N, Forghani R, Quintana C, Reh A, Bhangoo P, Desrosiers L, Ireland T, Misla C, Milliot E, Torres S, Wells J, Villar M, Yu D, Berry D, Cook J, Soder A, Powell M, Ng M, Morrison Z, Moore M, Haslam M, Lawson B, Bradley J, Courtney C, Richardson C, Watson E, Keely D, DeCurtis M, Vaccarcello-Cruz Z, Torres K, Muller S, Sandberg H, Hsiang B, Joy D, McCormick A, Powell H, Jones J, Bell S, Hargadon S, Hudson M, Kummer S, Nguyen T, Sauder E, Sutton K, Gensel R, Aguirre-Castaneda V, Benavides, Lopez D, Hemp S, Allen J, Stear E, Davis T, O’Donnell R, Jones A, Roberts J, Dart N, Paramalingam L, Levitt Katz N, Chaudhary K, Murphy S, Willi B, Schwartzman C, Kapadia D, Roberts A, Larson D, McClellan G, Shaibai L, Kelley G, Villa C, Kelley R, Diamond M, Kabbani T, Dajani F, Hoekstra M, Sadler K, Magorno J, Holst V, Chauhan N, Wilson P, Bononi M, Sperl A, Millward M, Eaton L, Dean J, Olshan H, Stavros T, Renna C, Milliard, Brodksy L, Bacon J, Quintos L, Topor S, Bialo B, Bancroft A, Soto W, Lagarde H, Tamura R, Lockemer T, Vanderploeg M, Ibrahim M, Huie V, Sanchez R, Edelen R, Marchiando J, Palmer T, Repas M, Wasson P, Wood K, Auker J, Culbertson T, Kieffer D, Voorhees T, Borgwardt L, DeRaad K, Eckert E, Isaacson H, Kuhn A, Carroll M, Xu P, Schubert G, Francis S, Hagan T, Le M, Penn E, Wickham C, Leyva K, Rivera J, Padilla I, Rodriguez N, Young K, Jospe J, Czyzyk B, Johnson U, Nadgir N, Marlen G, Prakasam C, Rieger N, Glaser E, Heiser B, Harris C, Alies P, Foster H, Slater K, Wheeler D, Donaldson M, Murray D, Hale R, Tragus D, Word J, Lynch L, Pankratz W, Badias F, Rogers R, Newfield S, Holland M, Hashiguchi M, Gottschalk A, Philis-Tsimikas R, Rosal S, Franklin S, Guardado N, Bohannon M, Baker A, Garcia T, Aguinaldo J, Phan V, Barraza D, Cohen J, Pinsker U, Khan J, Wiley L, Jovanovic P, Misra M, Bassi M, Wright D, Cohen K, Huang M, Skiles S, Maxcy C, Pihoker K, Cochrane J, Fosse S, Kearns M, Klingsheim N, Beam C, Wright L, Viles H, Smith S, Heller M, Cunningham A, Daniels L, Zeiden J, Field R, Walker K, Griffin L, Boulware D, Bartholow C, Erickson J, Howard B, Krabbenhoft C, Sandman A, Vanveldhuizen J, Wurlger A, Zimmerman K, Hanisch L, Davis-Keppen A, Bounmananh L, Cotterill J, Kirby M, Harris A, Schmidt C, Kishiyama C, Flores J, Milton W, Martin C, Whysham A, Yerka T, Bream S, Freels J, Hassing J, Webster R, Green P, Carter J, Galloway D, Hoelzer S, Roberts S, Said P, Sullivan H, Freeman D, Allen E, Reiter E, Feinberg C, 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Frank E, Liu J, Perry J, Pyle R, Rigby A, Riley K, Soto A, Gitelman S, Adi S, Anderson M, Berhel A, Breen K, Fraser K, Gerard-Gonzalez A, Jossan P, Lustig R, Moassesfar S, Mugg A, Ng D, Prahalod P, Rangel-Lugo M, Sanda S, Tarkoff J, Torok C, Wesch R, Aslan I, Buchanan J, Cordier J, Hamilton C, Hawkins L, Ho T, Jain A, Ko K, Lee T, Phelps S, Rosenthal S, Sahakitrungruang T, Stehl L, Taylor L, Wertz M, Wong J, Philipson L, Briars R, Devine N, Littlejohn E, Grant T, Gottlieb P, Klingensmith G, Steck A, Alkanani A, Bautista K, Bedoy R, Blau A, Burke B, Cory L, Dang M, Fitzgerald-Miller L, Fouts A, Gage V, Garg S, Gesauldo P, Gutin R, Hayes C, Hoffman M, Ketchum K, Logsden-Sackett N, Maahs D, Messer L, Meyers L, Michels A, Peacock S, Rewers M, Rodriguez P, Sepulbeda F, Sippl R, Steck A, Taki I, Tran BK, Tran T, Wadwa RP, Zeitler P, Barker J, Barry S, Birks L, Bomsburger L, Bookert T, Briggs L, Burdick P, Cabrera R, Chase P, Cobry E, Conley A, Cook G, Daniels J, DiDomenico D, Eckert J, Ehler A, Eisenbarth G, Fain P, Fiallo-Scharer R, Frank N, Goettle H, Haarhues M, Harris S, Horton L, Hutton J, Jeffrrey J, Jenison R, Jones K, Kastelic W, King MA, Lehr D, Lungaro J, Mason K, Maurer H, Nguyen L, Proto A, Realsen J, Schmitt K, Schwartz M, Skovgaard S, Smith J, Vanderwel B, Voelmle M, Wagner R, Wallace A, Walravens P, Weiner L, Westerhoff B, Westfall E, Widmer K, Wright H, Schatz D, Abraham A, Atkinson M, Cintron M, Clare-Salzler M, Ferguson J, Haller M, Hosford J, Mancini D, Rohrs H, Silverstein J, Thomas J, Winter W, Cole G, Cook R, Coy R, Hicks E, Lewis N, Marks J, Pugliese A, Blaschke C, Matheson D, Pugliese A, Sanders-Branca N, Ray Arce LA, Cisneros M, Sabbag S, Moran A, Gibson C, Fife B, Hering B, Kwong C, Leschyshyn J, Nathan B, Pappenfus B, Street A, Boes MA, Peterson Eck S, Finney L, Albright Fischer T, Martin A, Jacqueline Muzamhindo C, Rhodes M, Smith J, Wagner J, Wood B, Becker D, Delallo K, Diaz A, Elnyczky B, Libman I, Pasek B, Riley K, Trucco M, Copemen B, Gwynn D, Toledo F, Rodriguez H, Bollepalli S, Diamond F, Eyth E, Henson D, Lenz A, Shulman D, Raskin P, Adhikari S, Dickson B, Dunnigan E, Lingvay I, Pruneda L, Ramos-Roman M, Raskin P, Rhee C, Richard J, Siegelman M, Sturges D, Sumpter K, White P, Alford M, Arthur J, Aviles-Santa ML, Cordova E, Davis R, Fernandez S, Fordan S, Hardin T, Jacobs A, Kaloyanova P, Lukacova-Zib I, Mirfakhraee S, Mohan A, Noto H, Smith O, Torres N, Wherrett D, Balmer D, Eisel L, Kovalakovska R, Mehan M, Sultan F, Ahenkorah B, Cevallos J, Razack N, Jo Ricci M, Rhode A, Srikandarajah M, Steger R, Russell WE, Black M, Brendle F, Brown A, Moore D, Pittel E, Robertson A, Shannon A, Thomas JW, Herold K, Feldman L, Sherwin R, Tamborlane W, Weinzimer S, Toppari J, Kallio T, Kärkkäinen M, Mäntymäki E, Niininen T, Nurmi B, Rajala P, Romo M, Suomenrinne S, Näntö-Salonen K, Simell O, Simell T, Bosi E, Battaglia M, Bianconi E, Bonfanti R, Grogan P, Laurenzi A, Martinenghi S, Meschi F, Pastore M, Falqui L, Teresa Muscato M, Viscardi M, Bingley P, Castleden H, Farthing N, Loud S, Matthews C, McGhee J, Morgan A, Pollitt J, Elliot-Jones R, Wheaton C, Knip M, Siljander H, Suomalainen H, Colman P, Healy F, Mesfin S, Redl L, Wentworth J, Willis J, Farley M, Harrison L, Perry C, Williams F, Mayo A, Paxton J, Thompson V, Volin L, Fenton C, Carr L, Lemon E, Swank M, Luidens M, Salgam M, Sharma V, Schade D, King C, Carano R, Heiden J, Means N, Holman L, Thomas I, Madrigal D, Muth T, Martin C, Plunkett C, Ramm C, Auchus R, Lane W, Avots E, Buford M, Hale C, Hoyle J, Lane B, Muir A, Shuler S, Raviele N, Ivie E, Jenkins M, Lindsley K, Hansen I, Fadoju D, Felner E, Bode B, Hosey R, Sax J, Jefferies C, Mannering S, Prentis R, She J, Stachura M, Hopkins D, Williams J, Steed L, Asatapova E, Nunez S, Knight S, Dixon P, Ching J, Donner T, Longnecker S, Abel K, Arcara K, Blackman S, Clark L, Cooke D, Plotnick L, Levin P, Bromberger L, Klein K, Sadurska K, Allen C, Michaud D, Snodgrass H, Burghen G, Chatha S, Clark C, 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Madison M, Rincon M, Carlucci R, Shridharani B, Rusk E, Tessman D, Huffman H, Abrams B, Biederman M, Jones V, Leathers W, Brickman P, Petrie D, Zimmerman J, Howard L, Miller R, Alemzadeh D, Mihailescu R, Melgozza-Walker N, Abdulla C, Boucher-Berry D, Ize-Ludlow R, Levy C, Swenson, Brousell N, Crimmins D, Edler T, Weis C, Schultz D, Rogers D, Latham C, Mawhorter C, Switzer W, Spencer P, Konstantnopoulus S, Broder J, Klein L, Knight L, Szadek G, Welnick B, Thompson R, Hoffman A, Revell J, Cherko K, Carter E, Gilson J, Haines G, Arthur B, Bowen W, Zipf P, Graves R, Lozano D, Seiple K, Spicer A, Chang J, Fregosi J, Harbinson C, Paulson S, Stalters P, Wright D, Zlock A, Freeth J, Victory H, Maheshwari A, Maheshwari T, Holmstrom J, Bueno R, Arguello J, Ahern L, Noreika V, Watson S, Hourse P, Breyer C, Kissel Y, Nicholson M, Pfeifer S, Almazan J, Bajaj M, Quinn K, Funk J, McCance E, Moreno R, Veintimilla A, Wells J, Cook S, Trunnel J, Henske S, Desai K, Frizelis F, Khan R, Sjoberg K, Allen P, Manning G, Hendry B, Taylor S, Jones W, Strader M, Bencomo T, Bailey L, Bedolla C, Roldan C, Moudiotis B, Vaidya C, Anning S, Bunce S, Estcourt E, Folland E, Gordon C, Harrill J, Ireland J, Piper L, Scaife K, Sutton S, Wilkins M, Costelloe J, Palmer L, Casas C, Miller M, Burgard C, Erickson J, Hallanger-Johnson P, Clark W, Taylor A, Lafferty S, Gillett C, Nolan M, Pathak L, Sondrol T, Hjelle S, Hafner J, Kotrba R, Hendrickson A, Cemeroglu T, Symington M, Daniel Y, Appiagyei-Dankah D, Postellon M, Racine L, Kleis K, Barnes S, Godwin H, McCullough K, Shaheen G, Buck L, Noel M, Warren S, Weber S, Parker I, Gillespie B, Nelson C, Frost J, Amrhein E, Moreland A, Hayes J, Peggram J, Aisenberg M, Riordan J, Zasa E, Cummings K, Scott T, Pinto A, Mokashi K, McAssey E, Helden P, Hammond L, Dinning S, Rahman S, Ray C, Dimicri S, Guppy H, Nielsen C, Vogel C, Ariza L, Morales Y, Chang R, Gabbay L, Ambrocio L, Manley R, Nemery W, Charlton P, Smith L, Kerr B, Steindel-Kopp M, Alamaguer D, Liljenquist G, Browning T, Coughenour M, Sulk E, Tsalikan M, Tansey J, Cabbage N. Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes. Diabetes Care 2019; 42:192-199. [PMID: 30061316 PMCID: PMC6341285 DOI: 10.2337/dc18-0288] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [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] [Received: 02/07/2018] [Accepted: 06/28/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings. RESEARCH DESIGN AND METHODS Subjects from the TrialNet Pathway to Prevention Study (N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years. RESULTS At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects. CONCLUSIONS Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins.
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Affiliation(s)
- Taylor M. Triolo
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Alexandra Fouts
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Laura Pyle
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Liping Yu
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Peter A. Gottlieb
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Andrea K. Steck
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO
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Redondo MJ, Geyer S, Steck AK, Sharp S, Wentworth JM, Weedon MN, Antinozzi P, Sosenko J, Atkinson M, Pugliese A, Oram RA, Antinozzi P, Atkinson M, Battaglia M, Becker D, Bingley P, Bosi E, Buckner J, Colman P, Gottlieb P, Herold K, Insel R, Kay T, Knip M, Marks J, Moran A, Palmer J, Peakman M, Philipson L, Pugliese A, Raskin P, Rodriguez H, Roep B, Russell W, Schatz D, Wherrett D, Wilson D, Winter W, Ziegler A, Benoist C, Blum J, Chase P, Clare-Salzler M, Clynes R, Eisenbarth G, Fathman C, Grave G, Hering B, Kaufman F, Leschek E, Mahon J, Nanto-Salonen K, Nepom G, Orban T, Parkman R, Pescovitz M, Peyman J, Roncarolo M, Simell O, Sherwin R, Siegelman M, Steck A, Thomas J, Trucco M, Wagner J, Greenbaum ,CJ, Bourcier K, Insel R, Krischer JP, Leschek E, Rafkin L, Spain L, Cowie C, Foulkes M, Krause-Steinrauf H, Lachin JM, Malozowski S, Peyman J, Ridge J, Savage P, Skyler JS, Zafonte SJ, Kenyon NS, Santiago I, Sosenko JM, Bundy B, Abbondondolo M, Adams T, Amado D, Asif I, Boonstra M, Bundy B, Burroughs C, Cuthbertson D, Deemer M, Eberhard C, Fiske S, Ford J, Garmeson J, Guillette H, Browning G, Coughenour T, Sulk M, Tsalikan E, Tansey M, Cabbage J, Dixit N, Pasha S, King M, Adcock K, Geyer S, Atterberry H, Fox L, Englert K, Mauras N, Permuy J, Sikes K, Berhe T, Guendling B, McLennan L, Paganessi L, Hays B, Murphy C, Draznin M, Kamboj M, Sheppard S, Lewis V, Coates L, Moore W, Babar G, Bedard J, Brenson-Hughes D, Henderson C, Cernich J, Clements M, Duprau R, Goodman S, Hester L, Huerta-Saenz L, Karmazin A, Letjen T, Raman S, Morin D, Henry M, Bestermann W, Morawski E, White J, Brockmyer A, Bays R, Campbell S, Stapleton A, Stone N, Donoho A, Everett H, Heyman K, Hensley H, Johnson M, Marshall C, Skirvin N, Taylor P, Williams R, Ray L, Wolverton C, Nickels D, Dothard C, Hsiao B, Speiser P, Pellizzari M, Bokor L, Izuora K, Abdelnour S, Cummings P, Paynor S, Leahy M, Riedl M, Shockley S, Karges C, Saad R, Briones T, Casella S, Herz C, Walsh K, Greening J, Hay F, Hunt S, Sikotra N, Simons L, Keaton N, Karounos D, Oremus R, Dye L, Myers L, Ballard D, Miers W, Sparks R, Thraikill K, Edwards K, Fowlkes J, Kinderman A, Kemp S, Morales A, Holland L, Johnson L, Paul P, Ghatak A, Phelen K, Leyland H, Henderson T, Brenner D, Law P, Oppenheimer E, Mamkin I, Moniz C, Clarson C, Lovell M, Peters A, Ruelas V, Borut D, Burt D, Jordan M, Leinbach A, Castilla S, Flores P, Ruiz M, Hanson L, Green-Blair J, Sheridan R, Wintergerst K, Pierce G, Omoruyi A, Foster M, Linton C, Kingery S, Lunsford A, Cervantes I, Parker T, Price P, Urben J, Doughty I, Haydock H, Parker V, Bergman P, Liu S, Duncum S, Rodda C, Thomas A, Ferry R, McCommon D, Cockroft J, Perelman A, Calendo R, Barrera C, Arce-Nunez E, Lloyd J, Martinez Y, De la Portilla M, Cardenas I, Garrido L, Villar M, Lorini R, Calandra E, D’Annuzio G, Perri K, Minuto N, Malloy J, Rebora C, Callegari R, Ali O, Kramer J, Auble B, Cabrera S, Donohoue P, Fiallo-Scharer R, Hessner M, Wolfgram P, Maddox K, Kansra A, Bettin N, McCuller R, Miller A, Accacha S, Corrigan J, Fiore E, Levine R, Mahoney T, Polychronakos C, Martin J, Gagne V, Starkman H, Fox M, Chin D, Melchionne F, Silverman L, Marshall I, Cerracchio L, Cruz J, Viswanathan A, Miller J, Wilson J, Chalew S, Valley S, Layburn S, Lala A, Clesi P, Genet M, Uwaifo G, Charron A, Allerton T, Milliot E, Cefalu W, Melendez-Ramirez L, Richards R, Alleyn C, Gustafson E, Lizanna M, Wahlen J, Aleiwe S, Hansen M, Wahlen H, Moore M, Levy C, Bonaccorso A, Rapaport R, Tomer Y, Chia D, Goldis M, Iazzetti L, Klein M, Levister C, Waldman L, Muller S, Wallach E, Regelmann M, Antal Z, Aranda M, Reynholds C, Leech N, Wake D, Owens C, Burns M, Wotherspoon J, Nguyen T, Murray A, Short K, Curry G, Kelsey S, Lawson J, Porter J, Stevens S, Thomson E, Winship S, Wynn L, O’Donnell R, Wiltshire E, Krebs J, Cresswell P, Faherty H, Ross C, Vinik A, Barlow P, Bourcier M, Nevoret M, Couper J, Oduah V, Beresford S, Thalagne N, Roper H, Gibbons J, Hill J, Balleaut S, Brennan C, Ellis-Gage J, Fear L, Gray T, Pilger J, Jones L, McNerney C, Pointer L, Price N, Few K, Tomlinson D, Denvir L, Drew J, Randell T, Mansell P, Roberts A, Bell S, Butler S, Hooton Y, Navarra H, Roper A, Babington G, Crate L, Cripps H, Ledlie A, Moulds C, Sadler K, Norton R, Petrova B, Silkstone O, Smith C, Ghai K, Murray M, Viswanathan V, Henegan M, Kawadry O, Olson J, Stavros T, Patterson L, Ahmad T, Flores B, Domek D, Domek S, Copeland K, George M, Less J, Davis T, Short M, Tamura R, Dwarakanathan A, O’Donnell P, Boerner B, Larson L, Phillips M, Rendell M, Larson K, Smith C, Zebrowski K, Kuechenmeister L, Wood K, Thevarayapillai M, Daniels M, Speer H, Forghani N, Quintana R, Reh C, Bhangoo A, Desrosiers P, Ireland L, Misla T, Xu P, Torres C, Wells S, Villar J, Yu M, Berry D, Cook D, Soder J, Powell A, Ng M, Morrison M, Young K, Haslam Z, Lawson M, Bradley B, Courtney J, Richardson C, Watson C, Keely E, DeCurtis D, Vaccarcello-Cruz M, Torres Z, Alies P, Sandberg K, Hsiang H, Joy B, McCormick D, Powell A, Jones H, Bell J, Hargadon S, Hudson S, Kummer M, Badias F, Sauder S, Sutton E, Gensel K, Aguirre-Castaneda R, Benavides Lopez V, Hemp D, Allen S, Stear J, Davis E, Jones T, Baker A, Roberts A, Dart J, Paramalingam N, Levitt Katz L, Chaudhary N, Murphy K, Willi S, Schwartzman B, Kapadia C, Larson D, Bassi M, McClellan D, Shaibai G, Kelley L, Villa G, Kelley C, Diamond R, Kabbani M, Dajani T, Hoekstra F, Magorno M, Beam C, Holst J, Chauhan V, Wilson N, Bononi P, Sperl M, Millward A, Eaton M, Dean L, Olshan J, Renna H, Boulware D, Milliard C, Snyder D, Beaman S, Burch K, Chester J, Ahmann A, Wollam B, DeFrang D, Fitch R, Jahnke K, Bounmananh L, Hanavan K, Klopfenstein B, Nicol L, Bergstrom R, Noland T, Brodksy J, Bacon L, Quintos J, Topor L, Bialo S, Bream S, Bancroft B, Soto A, Lagarde W, Lockemer H, Vanderploeg T, Ibrahim M, Huie M, Sanchez V, Edelen R, Marchiando R, Freeman D, Palmer J, Repas T, Wasson M, Auker P, Culbertson J, Kieffer T, Voorhees D, Borgwardt T, DeRaad L, Eckert K, Gough J, Isaacson E, Kuhn H, Carroll A, Schubert M, Francis G, Hagan S, Le T, Penn M, Wickham E, Leyva C, Ginem J, Rivera K, Padilla J, Rodriguez I, Jospe N, Czyzyk J, Johnson B, Nadgir U, Marlen N, Prakasam G, Rieger C, Granger M, Glaser N, Heiser E, Harris B, Foster C, Slater H, Wheeler K, Donaldson D, Murray M, Hale D, Tragus R, Holloway M, Word D, Lynch J, Pankratz L, Rogers W, Newfield R, Holland S, Hashiguchi M, Gottschalk M, Philis-Tsimikas A, Rosal R, Kieffer M, Franklin S, Guardado S, Bohannon N, Garcia M, Aguinaldo T, Phan J, Barraza V, Cohen D, Pinsker J, Khan U, Lane P, Wiley J, Jovanovic L, Misra P, Wright M, Cohen D, Huang K, Skiles M, Maxcy S, Pihoker C, Cochrane K, Nallamshetty L, Fosse J, Kearns S, Klingsheim M, Wright N, Viles L, Smith H, Heller S, Cunningham M, Daniels A, Zeiden L, Parrimon Y, Field J, Walker R, Griffin K, Bartholow L, Erickson C, Howard J, Krabbenhoft B, Sandman C, Vanveldhuizen A, Wurlger J, Paulus K, Zimmerman A, Hanisch K, Davis-Keppen L, Cotterill A, Kirby J, Harris M, Schmidt A, Kishiyama C, Flores C, Milton J, Ramiro J, Martin W, Whysham C, Yerka A, Freels T, Hassing J, Webster J, Green R, Carter P, Galloway J, Hoelzer D, Ritzie AQL, Roberts S, Said S, Sullivan P, Allen H, Reiter E, Feinberg E, Johnson C, Newhook L, Hagerty D, White N, Sharma A, Levandoski L, Kyllo J, Johnson M, Benoit C, Iyer P, Diamond F, Hosono H, Jackman S, Barette L, Jones P, Shor A, Sills I, Bzdick S, Bulger J, Weinstock R, Douek I, Andrews R, Modgill G, Gyorffy G, Robin L, Vaidya N, Song X, Crouch S, O’Brien K, Thompson C, Thorne N, Blumer J, Kalic J, Klepek L, Paulett J, Rosolowski B, Horner J, Terry A, Watkins M, Casey J, Carpenter K, Burns C, Horton J, Pritchard C, Soetaert D, Wynne A, Kaiserman K, Halvorson M, Weinberger J, Chin C, Molina O, Patel C, Senguttuvan R, Wheeler M, Furet O, Steuhm C, Jelley D, Goudeau S, Chalmers L, Wootten M, Greer D, Panagiotopoulos C, Metzger D, Nguyen D, Horowitz M, Christiansen M, Glades E, Morimoto C, Macarewich M, Norman R, Harding P, Patin K, Vargas C, Barbanica A, Yu A, Vaidyanathan P, Osborne W, Mehra R, Kaster S, Neace S, Horner J, McDonough S, Reeves G, Cordrey C, Marrs L, Miller T, Dowshen S, Doyle D, Walker S, Catte D, Dean H, Drury-Brown M, McGee PF, Hackman B, Lee M, Malkani S, Cullen K, Johnson K, Hampton P, McCarrell M, Curtis C, Paul E, Zambrano Y, Hess KO, Phoebus D, Quinlan S, Raiden E, Batts E, Buddy C, Kirpatrick K, Ramey M, Shultz A, Webb C, Romesco M, Fradkin J, Blumberg E, Beck G, Brillon D, Gubitosi-Klug R, Laffel L, Veatch R, Wallace D, Braun J, Lernmark A, Lo B, Mitchell H, Naji A, Nerup J, Orchard T, Steffes M, Tsiatis A, Zinman B, Loechelt B, Baden L, Green M, Weinberg A, Marcovina S, Palmer JP, Weinberg A, Yu L, Babu S, Winter W, Eisenbarth GS, Bingley P, Clynes R, DiMeglio L, Eisenbarth G, Hays B, Marks J, Matheson D, Rodriguez H, Wilson D, Redondo MJ, Gomez D, Zheng X, Pena S, Pietropaolo M, Batts E, Brown T, Buckner J, Dove A, Hammond M, Hefty D, Klein J, Kuhns K, Letlau M, Lord S, McCulloch-Olson M, Miller L, Nepom G, Odegard J, Ramey M, Sachter E, St. Marie M, Stickney K, VanBuecken D, Vellek B, Webber C, Allen L, Bollyk J, Hilderman N, Ismail H, Lamola S, Sanda S, Vendettuoli H, Tridgell D, Monzavi R, Bock M, Fisher L, Halvorson M, Jeandron D, Kim M, Wood J, Geffner M, Kaufman F, Parkman R, Salazar C, Goland R, Clynes R, Cook S, Freeby M, Gallagher MP, Gandica R, Greenberg E, Kurland A, Pollak S, Wolk A, Chan M, Koplimae L, Levine E, Smith K, Trast J, DiMeglio L, Blum J, Evans-Molina C, Hufferd R, Jagielo B, Kruse C, Patrick V, Rigby M, Spall M, Swinney K, Terrell J, Christner L, Ford L, Lynch S, Menendez M, Merrill P, Pescovitz M, Rodriguez H, Alleyn C, Baidal D, Fay S, Gaglia J, Resnick B, Szubowicz S, Weir G, Benjamin R, Conboy D, deManbey A, Jackson R, Jalahej H, Orban T, Ricker A, Wolfsdorf J, Zhang HH, Wilson D, Aye T, Baker B, Barahona K, Buckingham B, Esrey K, Esrey T, Fathman G, Snyder R, Aneja B, Chatav M, Espinoza O, Frank E, Liu J, Perry J, Pyle R, Rigby A, Riley K, Soto A, Gitelman S, Adi S, Anderson M, Berhel A, Breen K, Fraser K, Gerard-Gonzalez A, Jossan P, Lustig R, Moassesfar S, Mugg A, Ng D, Prahalod P, Rangel-Lugo M, Sanda S, Tarkoff J, Torok C, Wesch R, Aslan I, Buchanan J, Cordier J, Hamilton C, Hawkins L, Ho T, Jain A, Ko K, Lee T, Phelps S, Rosenthal S, Sahakitrungruang T, Stehl L, Taylor L, Wertz M, Wong J, Philipson L, Briars R, Devine N, Littlejohn E, Grant T, Gottlieb P, Klingensmith G, Steck A, Alkanani A, Bautista K, Bedoy R, Blau A, Burke B, Cory L, Dang M, Fitzgerald-Miller L, Fouts A, Gage V, Garg S, Gesauldo P, Gutin R, Hayes C, Hoffman M, Ketchum K, Logsden-Sackett N, Maahs D, Messer L, Meyers L, Michels A, Peacock S, Rewers M, Rodriguez P, Sepulbeda F, Sippl R, Steck A, Taki I, Tran BK, Tran T, Wadwa RP, Zeitler P, Barker J, Barry S, Birks L, Bomsburger L, Bookert T, Briggs L, Burdick P, Cabrera R, Chase P, Cobry E, Conley A, Cook G, Daniels J, DiDomenico D, Eckert J, Ehler A, Eisenbarth G, Fain P, Fiallo-Scharer R, Frank N, Goettle H, Haarhues M, Harris S, Horton L, Hutton J, Jeffrrey J, Jenison R, Jones K, Kastelic W, King MA, Lehr D, Lungaro J, Mason K, Maurer H, Nguyen L, Proto A, Realsen J, Schmitt K, Schwartz M, Skovgaard S, Smith J, Vanderwel B, Voelmle M, Wagner R, Wallace A, Walravens P, Weiner L, Westerhoff B, Westfall E, Widmer K, Wright H, Schatz D, Abraham A, Atkinson M, Cintron M, Clare-Salzler M, Ferguson J, Haller M, Hosford J, Mancini D, Rohrs H, Silverstein J, Thomas J, Winter W, Cole G, Cook R, Coy R, Hicks E, Lewis N, Marks J, Pugliese A, Blaschke C, Matheson D, Sanders-Branca N, Sosenko J, Arazo L, Arce R, Cisneros M, Sabbag S, Moran A, Gibson C, Fife B, Hering B, Kwong C, Leschyshyn J, Nathan B, Pappenfus B, Street A, Boes MA, Eck SP, Finney L, Fischer TA, Martin A, Muzamhindo CJ, Rhodes M, Smith J, Wagner J, Wood B, Becker D, Delallo K, Diaz A, Elnyczky B, Libman I, Pasek B, Riley K, Trucco M, Copemen B, Gwynn D, Toledo F, Rodriguez H, Bollepalli S, Diamond F, Eyth E, Henson D, Lenz A, Shulman D, Raskin P, Adhikari S, Dickson B, Dunnigan E, Lingvay I, Pruneda L, Ramos-Roman M, Raskin P, Rhee C, Richard J, Siegelman M, Sturges D, Sumpter K, White P, Alford M, Arthur J, Aviles-Santa ML, Cordova E, Davis R, Fernandez S, Fordan S, Hardin T, Jacobs A, Kaloyanova P, Lukacova-Zib I, Mirfakhraee S, Mohan A, Noto H, Smith O, Torres N, Wherrett D, Balmer D, Eisel L, Kovalakovska R, Mehan M, Sultan F, Ahenkorah B, Cevallos J, Razack N, Ricci MJ, Rhode A, Srikandarajah M, Steger R, Russell WE, Black M, Brendle F, Brown A, Moore D, Pittel E, Robertson A, Shannon A, Thomas JW, Herold K, Feldman L, Sherwin R, Tamborlane W, Weinzimer S, Toppari J, Kallio T, Kärkkäinen M, Mäntymäki E, Niininen T, Nurmi B, Rajala P, Romo M, Suomenrinne S, Näntö-Salonen K, Simell O, Simell T, Bosi E, Battaglia M, Bianconi E, Bonfanti R, Grogan P, Laurenzi A, Martinenghi S, Meschi F, Pastore M, Falqui L, Muscato MT, Viscardi M, Castleden H, Farthing N, Loud S, Matthews C, McGhee J, Morgan A, Pollitt J, Elliot-Jones R, Wheaton C, Knip M, Siljander H, Suomalainen H, Colman P, Healy F, Mesfin S, Redl L, Wentworth J, Willis J, Farley M, Harrison L, Perry C, Williams F, Mayo A, Paxton J, Thompson V, Volin L, Fenton C, Carr L, Lemon E, Swank M, Luidens M, Salgam M, Sharma V, Schade D, King C, Carano R, Heiden J, Means N, Holman L, Thomas I, Madrigal D, Muth T, Martin C, Plunkett C, Ramm C, Auchus R, Lane W, Avots E, Buford M, Hale C, Hoyle J, Lane B, Muir A, Shuler S, Raviele N, Ivie E, Jenkins M, Lindsley K, Hansen I, Fadoju D, Felner E, Bode B, Hosey R, Sax J, Jefferies C, Mannering S, Prentis R, She J, Stachura M, Hopkins D, Williams J, Steed L, Asatapova E, Nunez S, Knight S, Dixon P, Ching J, Donner T, Longnecker S, Abel K, Arcara K, Blackman S, Clark L, Cooke D, Plotnick L, Levin P, Bromberger L, Klein K, Sadurska K, Allen C, Michaud D, Snodgrass H, Burghen G, Chatha S, Clark C, Silverberg J, Wittmer C, Gardner J, LeBoeuf C, Bell P, McGlore O, Tennet H, Alba N, Carroll M, Baert L, Beaton H, Cordell E, Haynes A, Reed C, Lichter K, McCarthy P, McCarthy S, Monchamp T, Roach J, Manies S, Gunville F, Marosok L, Nelson T, Ackerman K, Rudolph J, Stewart M, McCormick K, May S, Falls T, Barrett T, Dale K, Makusha L, McTernana C, Penny-Thomas K, Sullivan K, Narendran P, Robbie J, Smith D, Christensen R, Koehler B, Royal C, Arthur T, Houser H, Renaldi J, Watsen S, Wu P, Lyons L, House B, Yu J, Holt H, Nation M, Vickers C, Watling R, Heptulla R, Trast J, Agarwal C, Newell D, Katikaneni R, Gardner C, Del Rio A, Logan A, Collier H, Rishton C, Whalley G, Ali A, Ramtoola S, Quattrin T, Mastrandea L, House A, Ecker M, Huang C, Gougeon C, Ho J, Pacuad D, Dunger D, May J, O’Brien C, Acerini C, Salgin B, Thankamony A, Williams R, Buse J, Fuller G, Duclos M, Tricome J, Brown H, Pittard D, Bowlby D, Blue A, Headley T, Bendre S, Lewis K, Sutphin K, Soloranzo C, Puskaric J, Madison H, Rincon M, Carlucci M, Shridharani R, Rusk B, Tessman E, Huffman D, Abrams H, Biederman B, Jones M, Leathers V, Brickman W, Petrie P, Zimmerman D, Howard J, Miller L, Alemzadeh R, Mihailescu D, Melgozza-Walker R, Abdulla N, Boucher-Berry C, Ize-Ludlow D, Levy R, Swenson Brousell C, Scott R, Heenan H, Lunt H, Kendall D, Willis J, Darlow B, Crimmins N, Edler D, Weis T, Schultz C, Rogers D, Latham D, Mawhorter C, Switzer C, Spencer W, Konstantnopoulus P, Broder S, Klein J, Bachrach B, Gardner M, Eichelberger D, Knight L, Szadek L, Welnick G, Thompson B, Hoffman R, Revell A, Cherko J, Carter K, Gilson E, Haines J, Arthur G, Bowen B, Zipf W, Graves P, Lozano R, Seiple D, Spicer K, Chang A, Fregosi J, Harbinson J, Paulson C, Stalters S, Wright P, Zlock D, Freeth A, Victory J, Maheshwari H, Maheshwari A, Holmstrom T, Bueno J, Arguello R, Ahern J, Noreika L, Watson V, Hourse S, Breyer P, Kissel C, Nicholson Y, Pfeifer M, Almazan S, Bajaj J, Quinn M, Funk K, McCance J, Moreno E, Veintimilla R, Wells A, Cook J, Trunnel S, Transue D, Surhigh J, Bezzaire D, Moltz K, Zacharski E, Henske J, Desai S, Frizelis K, Khan F, Sjoberg R, Allen K, Manning P, Hendry G, Taylor B, Jones S, Couch R, Danchak R, Lieberman D, Strader W, Bencomo M, Bailey T, Bedolla L, Roldan C, Moudiotis C, Vaidya B, Anning C, Bunce S, Estcourt S, Folland E, Gordon E, Harrill C, Ireland J, Piper J, Scaife L, Sutton K, Wilkins S, Costelloe M, Palmer J, Casas L, Miller C, Burgard M, Erickson C, Hallanger-Johnson J, Clark P, Taylor W, Galgani J, Banerjee S, Banda C, McEowen D, Kinman R, Lafferty A, Gillett S, Nolan C, Pathak M, Sondrol L, Hjelle T, Hafner S, Kotrba J, Hendrickson R, Cemeroglu A, Symington T, Daniel M, Appiagyei-Dankah Y, Postellon D, Racine M, Kleis L, Barnes K, Godwin S, McCullough H, Shaheen K, Buck G, Noel L, Warren M, Weber S, Parker S, Gillespie I, Nelson B, Frost C, Amrhein J, Moreland E, Hayes A, Peggram J, Aisenberg J, Riordan M, Zasa J, Cummings E, Scott K, Pinto T, Mokashi A, McAssey K, Helden E, Hammond P, Dinning L, Rahman S, Ray S, Dimicri C, Guppy S, Nielsen H, Vogel C, Ariza C, Morales L, Chang Y, Gabbay R, Ambrocio L, Manley L, Nemery R, Charlton W, Smith P, Kerr L, Steindel-Kopp B, Alamaguer M, Tabisola-Nuesca E, Pendersen A, Larson N, Cooper-Olviver H, Chan D, Fitz-Patrick D, Carreira T, Park Y, Ruhaak R, Liljenquist D. A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk. Diabetes Care 2018; 41:1887-1894. [PMID: 30002199 PMCID: PMC6105323 DOI: 10.2337/dc18-0087] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [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: 01/11/2018] [Accepted: 06/06/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals. RESEARCH DESIGN AND METHODS We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables. RESULTS Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002). CONCLUSIONS The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.
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Affiliation(s)
- Maria J. Redondo
- Texas Children’s Hospital, Baylor College of Medicine, Houston, TX
| | | | - Andrea K. Steck
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Seth Sharp
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, U.K
| | - John M. Wentworth
- Walter and Eliza Hall Institute of Medical Research and Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Michael N. Weedon
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, U.K
| | | | | | | | | | - Richard A. Oram
- Institute of Biomedical and Clinical Science, University of Exeter, Exeter, U.K
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Tang WW, McGee P, Lachin JM, Li DY, Hoogwerf B, Hazen SL, Nathan D, Zinman B, Crofford O, Genuth S, Brown‐Friday J, Crandall J, Engel H, Engel S, Martinez H, Phillips M, Reid M, Shamoon H, Sheindlin J, Gubitosi‐Klug R, Mayer L, Pendegast S, Zegarra H, Miller D, Singerman L, Smith‐Brewer S, Novak M, Quin J, Genuth S, Palmert M, Brown E, McConnell J, Pugsley P, Crawford P, Dahms W, Gregory N, Lackaye M, Kiss S, Chan R, Orlin A, Rubin M, Brillon D, Reppucci V, Lee T, Heinemann M, Chang S, Levy B, Jovanovic L, Richardson M, Bosco B, Dwoskin A, Hanna R, Barron S, Campbell R, Bhan A, Kruger D, Jones J, Edwards P, Bhan A, Carey J, Angus E, Thomas A, Galprin A, McLellan M, Whitehouse F, Bergenstal R, Johnson M, Gunyou K, Thomas L, Laechelt J, Hollander P, Spencer M, Kendall D, Cuddihy R, Callahan P, List S, Gott J, Rude N, Olson B, Franz M, Castle G, Birk R, Nelson J, Freking D, Gill L, Mestrezat W, Etzwiler D, Morgan K, Aiello L, Golden E, Arrigg P, Asuquo V, Beaser R, Bestourous L, Cavallerano J, Cavicchi R, Ganda O, Hamdy O, Kirby R, Murtha T, Schlossman D, Shah S, Sharuk G, Silva P, Silver P, Stockman M, Sun J, Weimann E, Wolpert H, Aiello L, Jacobson A, Rand L, Rosenzwieg J, Nathan D, Larkin M, Christofi M, Folino K, Godine J, Lou P, Stevens C, Anderson E, Bode H, Brink S, Cornish C, Cros D, Delahanty L, eManbey ., Haggan C, Lynch J, McKitrick C, Norman D, Moore D, Ong M, Taylor C, Zimbler D, Crowell S, Fritz S, Hansen K, Gauthier‐Kelly C, Service F, Ziegler G, Barkmeier A, Schmidt L, French B, Woodwick R, Rizza R, Schwenk W, Haymond M, Pach J, Mortenson J, Zimmerman B, Lucas A, Colligan R, Luttrell L, Lopes‐Virella M, Caulder S, Pittman C, Patel N, Lee K, Nutaitis M, Fernandes J, Hermayer K, Kwon S, Blevins A, Parker J, Colwell J, Lee D, Soule J, Lindsey P, Bracey M, Farr A, Elsing S, Thompson T, Selby J, Lyons T, Yacoub‐Wasef S, Szpiech M, Wood D, Mayfield R, Molitch M, Adelman D, Colson S, Jampol L, Lyon A, Gill M, Strugula Z, Kaminski L, Mirza R, Simjanoski E, Ryan D, Johnson C, Wallia A, Ajroud‐Driss S, Astelford P, Leloudes N, Degillio A, Schaefer B, Mudaliar S, Lorenzi G, Goldbaum M, Jones K, Prince M, Swenson M, Grant I, Reed R, Lyon R, Kolterman O, Giotta M, Clark T, Friedenberg G, Sivitz W, Vittetoe B, Kramer J, Bayless M, Zeitler R, Schrott H, Olson N, Snetselaar L, Hoffman R, MacIndoe J, Weingeist T, Fountain C, Miller R, Johnsonbaugh S, Patronas M, Carney M, Mendley S, Salemi P, Liss R, Hebdon M, Counts D, Donner T, Gordon J, Hemady R, Kowarski A, Ostrowski D, Steidl S, Jones B, Herman W, Martin C, Pop‐Busui R, Greene D, Stevens M, Burkhart N, Sandford T, Floyd J, Bantle J, Flaherty N, Terry J, Koozekanani D, Montezuma S, Wimmergren N, Rogness B, Mech M, Strand T, Olson J, McKenzie L, Kwong C, Goetz F, Warhol R, Hainsworth D, Goldstein D, Hitt S, Giangiacomo J, Schade D, Canady J, Burge M, Das A, Avery R, Ketai L, Chapin J, Schluter M, Rich J, Johannes C, Hornbeck D, Schutta M, Bourne P, Brucker A, Braunstein S, Schwartz S, Maschak‐Carey B, Baker L, Orchard T, Cimino L, Songer T, Doft B, Olson S, Becker D, Rubinstein D, Bergren R, Fruit J, Hyre R, Palmer C, Silvers N, Lobes L, Rath PP, Conrad P, Yalamanchi S, Wesche J, Bratkowksi M, Arslanian S, Rinkoff J, Warnicki J, Curtin D, Steinberg D, Vagstad G, Harris R, Steranchak L, Arch J, Kelly K, Ostrosaka P, Guiliani M, Good M, Williams T, Olsen K, Campbell A, Shipe C, Conwit R, Finegold D, Zaucha M, Drash A, Morrison A, Malone J, Bernal M, Pavan P, Grove N, Tanaka E, McMillan D, Vaccaro‐Kish J, Babbione L, Solc H, DeClue T, Dagogo‐Jack S, Wigley C, Ricks H, Kitabchi A, Chaum E, Murphy M, Moser S, Meyer D, Iannacone A, Yoser S, Bryer‐Ash M, Schussler S, Lambeth H, Raskin P, Strowig S, Basco M, Cercone S, Zinman B, Barnie A, Devenyi R, Mandelcorn M, Brent M, Rogers S, Gordon A, Bakshi N, Perkins B, Tuason L, Perdikaris F, Ehrlich R, Daneman D, Perlman K, Ferguson S, Palmer J, Fahlstrom R, de Boer I, Kinyoun J, Van Ottingham L, Catton S, Ginsberg J, McDonald C, Harth J, Driscoll M, Sheidow T, Mahon J, Canny C, Nicolle D, Colby P, Dupre J, Hramiak I, Rodger N, Jenner M, Smith T, Brown W, May M, Lipps Hagan J, Agarwal A, Adkins T, Lorenz R, Feman S, Survant L, White N, Levandoski L, Grand G, Thomas M, Joseph D, Blinder K, Shah G, Burgess D, Boniuk I, Santiago J, Tamborlane W, Gatcomb P, Stoessel K, Ramos P, Fong K, Ossorio P, Ahern J, Gubitosi‐Klug R, Meadema‐Mayer L, Beck C, Farrell K, Genuth S, Quin J, Gaston P, Palmert M, Trail R, Dahms W, Lachin J, Backlund J, Bebu I, Braffett B, Diminick L, Gao X, Hsu W, Klumpp K, Pan H, Trapani V, Cleary P, McGee P, Sun W, Villavicencio S, Anderson K, Dews L, Younes N, Rutledge B, Chan K, Rosenberg D, Petty B, Determan A, Kenny D, Williams C, Cowie C, Siebert C, Steffes M, Arends V, Bucksa J, Nowicki M, Chavers B, O'Leary D, Polak J, Harrington A, Funk L, Crow R, Gloeb B, Thomas S, O'Donnell C, Soliman E, Zhang Z, Li Y, Campbell C, Keasler L, Hensley S, Hu J, Barr M, Taylor T, Prineas R, Feldman E, Albers J, Low P, Sommer C, Nickander K, Speigelberg T, Pfiefer M, Schumer M, Moran M, Farquhar J, Ryan C, Sandstrom D, Williams T, Geckle M, Cupelli E, Thoma F, Burzuk B, Woodfill T, Danis R, Blodi B, Lawrence D, Wabers H, Gangaputra S, Neill S, Burger M, Dingledine J, Gama V, Sussman R, Davis M, Hubbard L, Budoff M, Darabian S, Rezaeian P, Wong N, Fox M, Oudiz R, Kim L, Detrano R, Cruickshanks K, Dalton D, Bainbridge K, Lima J, Bluemke D, Turkbey E, der Geest ., Liu C, Malayeri A, Jain A, Miao C, Chahal H, Jarboe R, Nathan D, Monnier V, Sell D, Strauch C, Hazen S, Pratt A, Tang W, Brunzell J, Purnell J, Natarajan R, Miao F, Zhang L, Chen Z, Paterson A, Boright A, Bull S, Sun L, Scherer S, Lopes‐Virella M, Lyons T, Jenkins A, Klein R, Virella G, Jaffa A, Carter R, Stoner J, Garvey W, Lackland D, Brabham M, McGee D, Zheng D, Mayfield R, Maynard J, Wessells H, Sarma A, Jacobson A, Dunn R, Holt S, Hotaling J, Kim C, Clemens Q, Brown J, McVary K. Oxidative Stress and Cardiovascular Risk in Type 1 Diabetes Mellitus: Insights From the DCCT/EDIC Study. J Am Heart Assoc 2018. [PMCID: PMC6015340 DOI: 10.1161/jaha.117.008368] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background
Hyperglycemia leading to increased oxidative stress is implicated in the increased risk for the development of macrovascular and microvascular complications in patients with type 1 diabetes mellitus.
Methods and Results
A random subcohort of 349 participants was selected from the
DCCT
/
EDIC
(Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications) cohort. This included 320 controls and 29 cardiovascular disease cases that were augmented with 98 additional known cases to yield a case cohort of 447 participants (320 controls, 127 cases). Biosamples from
DCCT
baseline, year 1, and closeout of
DCCT
, and 1 to 2 years post‐
DCCT
(
EDIC
years 1 and 2) were measured for markers of oxidative stress, including plasma myeloperoxidase, paraoxonase activity, urinary F
2α
isoprostanes, and its metabolite, 2,3 dinor‐8
iso
prostaglandin F
2α
. Following adjustment for glycated hemoblobin and weighting the observations inversely proportional to the sampling selection probabilities, higher paraoxonase activity, reflective of antioxidant activity, and 2,3 dinor‐8
iso
prostaglandin F
2α
, an oxidative marker, were significantly associated with lower risk of cardiovascular disease (−4.5% risk for 10% higher paraoxonase,
P
<0.003; −5.3% risk for 10% higher 2,3 dinor‐8
iso
prostaglandin F
2α
,
P
=0.0092). In contrast, the oxidative markers myeloperoxidase and F
2α
isoprostanes were not significantly associated with cardiovascular disease after adjustment for glycated hemoblobin. There were no significant differences between
DCCT
intensive and conventional treatment groups in the change in all biomarkers across time segments.
Conclusions
Heightened antioxidant activity (rather than diminished oxidative stress markers) is associated with lower cardiovascular disease risk in type 1 diabetes mellitus, but these biomarkers did not change over time with intensification of glycemic control.
Clinical Trial Registration
URL
:
https://www.clinicaltrials.gov
. Unique identifiers:
NCT
00360815 and
NCT
00360893.
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Affiliation(s)
- W.H. Wilson Tang
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH
| | - Paula McGee
- The Biostatistics Center, George Washington University, Rockville, MD
| | - John M. Lachin
- The Biostatistics Center, George Washington University, Rockville, MD
| | - Daniel Y. Li
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
| | | | - Stanley L. Hazen
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH
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11
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Schultheiss UT, Daya N, Grams ME, Seufert J, Steffes M, Coresh J, Selvin E, Köttgen A. Thyroid function, reduced kidney function and incident chronic kidney disease in a community-based population: the Atherosclerosis Risk in Communities study. Nephrol Dial Transplant 2017; 32:1874-1881. [PMID: 27540046 PMCID: PMC5837276 DOI: 10.1093/ndt/gfw301] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [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: 01/04/2016] [Accepted: 07/12/2016] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Reduced kidney function is a common public health problem that increases risk for a wide variety of adverse outcomes, making the identification of potentially modifiable factors associated with the development of incident chronic kidney disease (CKD) important. Alterations in the hypothalamic-pituitary-thyroid axis have been linked to reduced kidney function, but the association of thyroid function with the development of incident CKD is largely uncharacterized. METHODS Concentrations of thyroid stimulating hormone (TSH), free thyroxine (FT4), triiodothyronine (T3) and thyroid peroxidase antibody (TPOAb) were quantified in 12 785 black and white participants of the ongoing community-based prospective Atherosclerosis Risk in Communities study. Thyroid markers and clinical categories of thyroid dysfunction (euthyroidism, combined subclinical and overt hypothyroidism, combined subclinical and overt hyperthyroidism) were also evaluated for their association with reduced kidney function (estimated glomerular filtration rate <60 mL/min/1.73 m2) at study baseline and with incident CKD over a median follow-up time of 19.6 years. RESULTS Higher TSH and FT4 as well as lower T3 concentrations were strongly and independently associated with reduced kidney function at study baseline. The clinical entities hypothyroidism and hyperthyroidism were also associated with higher odds of baseline reduced kidney function, but this was not significant. However, none of the markers of thyroid function nor different clinical categories of thyroid dysfunction (hypothyroidism, hyperthyroidism or TPOAb positivity) were associated with incident CKD in adjusted analyses. CONCLUSIONS Elevated TSH, FT4 and reduced T3 concentrations were associated with reduced kidney function cross-sectionally. The lack of association with the development of incident CKD suggests that altered thyroid function in the general population is not causally related to CKD development, but screening for thyroidal status may be especially relevant in persons with reduced kidney function.
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Affiliation(s)
- Ulla T Schultheiss
- Renal Division, Department of Medicine IV, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Division of Genetic Epidemiology, Institute of Medical Biometry and Statistics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Natalie Daya
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Morgan E Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Nephrology, Johns Hopkins University, Baltimore, MD, USA
| | - Jochen Seufert
- Division of Endocrinology and Diabetology, Department of Medicine II, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Anna Köttgen
- Renal Division, Department of Medicine IV, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Division of Genetic Epidemiology, Institute of Medical Biometry and Statistics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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12
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Cao J, Li D, Steffes M, Bellin MD. HbA 1c measurements across- different platforms: exercising caution when making decisions regarding diagnosis. Diabet Med 2016; 33:1601-1602. [PMID: 27150388 DOI: 10.1111/dme.13149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- J Cao
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - D Li
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - M Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - M D Bellin
- Division of Pediatric Endocrinology, Department of Pediatrics and Surgery, University of Minnesota, Minneapolis, MN, USA
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13
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Kim C, Karvonen-Gutierrez C, Kong S, Arends V, Steffes M, McConnell DS, Randolph JF, Harlow SD. Antimüllerian hormone among women with and without type 1 diabetes: the Epidemiology of Diabetes Interventions and Complications Study and the Michigan Bone Health and Metabolism Study. Fertil Steril 2016; 106:1446-1452. [PMID: 27475411 PMCID: PMC5159208 DOI: 10.1016/j.fertnstert.2016.07.009] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Revised: 07/07/2016] [Accepted: 07/08/2016] [Indexed: 12/18/2022]
Abstract
OBJECTIVE To compare concentrations of antimüllerian hormone (AMH) in women with and without type 1 diabetes. DESIGN Cross-sectional analysis of longitudinal studies, adjusting for repeated measures. SETTING Not applicable. PATIENT(S) Women aged 30-45 years who had not undergone oophorectomy, hysterectomy, or natural menopause at the time of AMH measurement were included (n = 376 in the Michigan Bone Health and Metabolism Study and n = 321 in the Epidemiology of Interventions and Complications Study). Linear mixed regression was used to evaluate whether AMH concentrations differed by diabetes status, adjusting for repeated measurements of AMH within individual women, body mass index, smoking status, and oral contraceptive use. INTERVENTION(S) None. MAIN OUTCOME MEASURE(S) Concentrations of AMH. RESULT(S) In unadjusted comparisons, women with and without diabetes had similar median AMH values before 35 years of age, although women with type 1 diabetes had a lower proportion of women with elevated AMH concentrations (≥5.0 ng/dL). After adjustment for covariates and multiple observations per woman, log AMH concentrations were significantly lower among women with type 1 diabetes compared with women without diabetes (β-coefficient -1.27, 95% confidence interval [-2.18, -0.36] in fully adjusted models) before 35 years of age. CONCLUSION(S) Before 35 years of age, women with type 1 diabetes have lower AMH levels than women without diabetes. Further investigation is needed to determine the etiologies of this difference and how it may contribute to reproductive disorders among women with type 1 diabetes.
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Affiliation(s)
- Catherine Kim
- Department of Medicine, University of Michigan, Ann Arbor, Michigan.
| | | | | | - Valerie Arends
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota
| | | | - John F Randolph
- Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, Michigan
| | - Siobán D Harlow
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan
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14
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Murphy TP, Cooper CJ, Pencina KM, D'Agostino R, Massaro J, Cutlip DE, Jamerson K, Matsumoto AH, Henrich W, Shapiro JI, Tuttle KR, Cohen DJ, Steffes M, Gao Q, Metzger DC, Abernethy WB, Textor SC, Briguglio J, Hirsch AT, Tobe S, Dworkin LD. Relationship of Albuminuria and Renal Artery Stent Outcomes: Results From the CORAL Randomized Clinical Trial (Cardiovascular Outcomes With Renal Artery Lesions). Hypertension 2016; 68:1145-1152. [PMID: 27647847 DOI: 10.1161/hypertensionaha.116.07744] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [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: 06/08/2016] [Accepted: 08/15/2016] [Indexed: 11/16/2022]
Abstract
Randomized clinical trials have not shown an additional clinical benefit of renal artery stent placement over optimal medical therapy alone. However, studies of renal artery stent placement have not examined the relationship of albuminuria and treatment group outcomes. The CORAL study (Cardiovascular Outcomes in Renal Atherosclerotic Lesions) is a prospective clinical trial of 947 participants with atherosclerotic renal artery stenosis randomized to optimal medical therapy with or without renal artery stent which showed no treatment differences (3(5.8% and 35.1% event rate at mean 43-month follow-up). In a post hoc analysis, the study population was stratified by the median baseline urine albumin/creatinine ratio (n=826) and analyzed for the 5-year incidence of the primary end point (myocardial infarction, hospitalization for congestive heart failure, stroke, renal replacement therapy, progressive renal insufficiency, or cardiovascular disease- or kidney disease-related death), for each component of the primary end point, and overall survival. When baseline urine albumin/creatinine ratio was ≤ median (22.5 mg/g, n=413), renal artery stenting was associated with significantly better event-free survival from the primary composite end point (73% versus 59% at 5 years; P=0.02), cardiovascular disease-related death (93% versus 85%; P≤ 0.01), progressive renal insufficiency (91% versus 77%; P=0.03), and overall survival (89% versus 76%; P≤0.01), but not when baseline urine albumin/creatinine ratio was greater than median (n=413). These data suggest that low albuminuria may indicate a potentially large subgroup of those with renal artery stenosis that could experience improved event-free and overall-survival after renal artery stent placement plus optimal medical therapy compared with optimal medical therapy alone. Further research is needed to confirm these preliminary observations. CLINICAL TRIAL REGISTRATION URL: https://www.clinicaltrials.gov. Unique identifier: NCT00081731.
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Affiliation(s)
- Timothy P Murphy
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada.
| | - Christopher J Cooper
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Karol M Pencina
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Ralph D'Agostino
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Joseph Massaro
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Donald E Cutlip
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Kenneth Jamerson
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Alan H Matsumoto
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - William Henrich
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Joseph I Shapiro
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Katherine R Tuttle
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - David J Cohen
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Michael Steffes
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Qi Gao
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - D Christopher Metzger
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - William B Abernethy
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Stephen C Textor
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - John Briguglio
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Alan T Hirsch
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Sheldon Tobe
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
| | - Lance D Dworkin
- From the Departments of Diagnostic Imaging (T.P.M.) and Medicine (L.D.D.), Rhode Island Hospital, Providence; Alpert Medical School of Brown University, Providence, RI (T.P.M., L.D.D.); Department of Medicine, University of Toledo, OH (C.J.C.); Departments of Statistics (K.M.P., R.B.D, J.M.M.), Medicine (D.E.C.), and Biostatistics (Q.G.), Harvard Clinical Research Institute, Boston, MA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA (D.E.C.); Department of Mathematics and Statistics, Boston University, MA (R.B.D.); Department of Medicine, University of Michigan, Ann Arbor (K.J.); Department of Radiology, University of Virginia, Charlottesville (A.H.M.); Department of Medicine, University of Texas Health Science Center, San Antonio (W.H.); Department of Medicine, Marshall University, Huntington, WV (J.I.S.); Department of Medicine, Providence Health Care and University of Washington School of Medicine, Spokane (K.R.T.); Department of Medicine, St. Luke's Hospital, Kansas City, MO (D.J.C.); Departments of Pathology (M.S.) and Medicine (A.H.), The University of Minnesota Medical School, Minneapolis; Department of Medicine, Wellmont-Holston Valley Medical Center, Kingsport, TN (D.C.M.); Department of Medicine, Asheville Cardiology Associates, NC (W.B.A.); Department of Medicine, Mayo Clinic, Rochester, MN (S.C.T.); Department of Radiology, Lancaster General Hospital, PA (J.B.); and Department of Medicine, Sunnybrook Research Institute (S.T.), Toronto, Ontario, Canada
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Tuttle KR, Dworkin LD, Henrich W, Greco BA, Steffes M, Tobe S, Shapiro JI, Jamerson K, Lyass A, Pencina K, Massaro JM, D’Agostino RB, Cutlip DE, Murphy TP, Cooper CJ. Effects of Stenting for Atherosclerotic Renal Artery Stenosis on eGFR and Predictors of Clinical Events in the CORAL Trial. Clin J Am Soc Nephrol 2016; 11:1180-1188. [PMID: 27225988 PMCID: PMC4934844 DOI: 10.2215/cjn.10491015] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [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: 10/01/2015] [Accepted: 04/05/2016] [Indexed: 01/09/2023]
Abstract
BACKGROUND AND OBJECTIVES Atherosclerotic renal artery stenosis may cause kidney function loss, but effects of stenting on eGFR and clinical events associated with CKD are uncertain. Our study objectives were to determine effects of stenting on eGFR and predictors of clinical events. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Participants (n=931) in the Cardiovascular Outcomes in Renal Artery Stenosis Trial (from May of 2005 to September of 2012) had >60% atherosclerotic renal artery stenosis and systolic hypertension on two or more antihypertensive drugs and/or stage ≥3 CKD. The intervention was stenting versus no stenting on a background of risk factor management: renin-angiotensin system inhibition, statin, antiplatelet therapy, and smoking cessation education. The effect of stenting on eGFR by the serum creatinine-cystatin C Chronic Kidney Disease Epidemiology Collaboration equation was the prespecified analysis of kidney function. Predictors of eGFR and CKD outcomes (≥30% eGFR loss, ESRD, and death) and cardiovascular disease outcomes (stroke, myocardial infarction, heart failure, and death) controlling for eGFR and albuminuria were also determined. RESULTS eGFR was 59±24 ml/min per 1.73 m(2) (mean±SD) at baseline. Over 3 years, eGFR change, assessed by generalized estimating equations, was -1.5±7.0 ml/min per 1.73 m(2) per year in the stent group versus -2.3±6.3 ml/min per 1.73 m(2) per year in the medical therapy only group (P=0.18). eGFR predictors (multiple variable generalized estimating equations) were age, albuminuria, systolic BP, and diabetes (inverse associations) as well as men, total cholesterol, and HDL cholesterol (positive associations). CKD outcomes events occurred in 19% (175 of 931), and predictors (Cox proportional hazards models) included albuminuria (positive association), systolic BP (positive association), and HDL cholesterol (inverse association). Cardiovascular disease outcomes events occurred in 22% (207 of 931), and predictors included age, albuminuria, total cholesterol, prior cardiovascular disease, and bilateral atherosclerotic renal artery stenosis (positive associations). CONCLUSIONS Stenting did not influence eGFR in participants with atherosclerotic renal artery stenosis receiving renin-angiotensin system inhibition-based therapy. Predictors of clinical events were traditional risk factors for CKD and cardiovascular disease.
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Affiliation(s)
| | - Lance D. Dworkin
- Brown University, Providence, Rhode Island
- Rhode Island Hospital, Providence, Rhode Island
| | - William Henrich
- University of Texas Health Science Center, San Antonio, Texas
| | | | | | | | | | | | - Asya Lyass
- Harvard Clinical Research Institute, Boston University, Boston, Massachusetts
| | - Karol Pencina
- Harvard Clinical Research Institute, Boston University, Boston, Massachusetts
| | - Joseph M. Massaro
- Harvard Clinical Research Institute, Boston University, Boston, Massachusetts
| | - Ralph B. D’Agostino
- Harvard Clinical Research Institute, Boston University, Boston, Massachusetts
| | - Donald E. Cutlip
- Beth Israel Deaconess Medical Center, Boston, Massachusetts; and
| | - Timothy P. Murphy
- Brown University, Providence, Rhode Island
- Rhode Island Hospital, Providence, Rhode Island
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Kim C, Bebu I, Braffett B, Cleary PA, Arends V, Steffes M, Wessells H, Orchard T, Sarma AV. Testosterone and cardiac mass and function in men with type 1 diabetes in the Epidemiology of Diabetes Interventions and Complications Study (EDIC). Clin Endocrinol (Oxf) 2016; 84:693-9. [PMID: 26641212 PMCID: PMC4824167 DOI: 10.1111/cen.12990] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [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: 09/15/2015] [Revised: 10/29/2015] [Accepted: 11/26/2015] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Low testosterone concentrations have been reported to be associated with increased risk of congestive heart failure, but the mechanisms are unclear. Our objective was to examine the relationship between endogenous testosterone and measures of cardiac mass and function among men with type 1 diabetes. DESIGN Secondary analysis of a prospective observational study. PARTICIPANTS Men (n = 508) in the Epidemiology of Diabetes Interventions and Complications (EDIC) study, the observational follow-up of the Diabetes Control and Complications Trial (DCCT). MEASUREMENTS Testosterone assessed by liquid chromatography mass spectrometry at EDIC year 10 and cardiac magnetic resonance imaging (CMR) measures at EDIC years 14/15. Linear regression models were used to assess the relationship between testosterone, sex hormone binding globulin (SHBG) and left ventricular (LV) mass, volume, ejection fraction and cardiac index before and after adjustment for age, randomization arm, alcohol and cigarette use, macroalbuminuria, haemoglobin A1c, insulin dose, body mass index, lipids, blood pressure, use of antihypertensive medications and microvascular complications. RESULTS In fully adjusted models, total testosterone concentrations were significantly associated with LV mass (P = 0·014), end-diastolic volume (P = 0·002), end-systolic volume (P = 0·012) and stroke volume (P = 0·022), but not measures of LV function after adjustment for cardiac risk factors. Bioavailable testosterone was associated with LV mass, but not volume or function, while SHBG was associated with volume, but not mass or function. CONCLUSIONS Among men with type 1 diabetes, higher total testosterone was associated with higher LV mass and volume, but not with function. The clinical significance of this association remains to be established.
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Affiliation(s)
- Catherine Kim
- Departments of Medicine, Obstetrics & Gynecology, and Epidemiology, University of Michigan, Ann Arbor, MI
| | - Ionut Bebu
- The Biostatistics Center, George Washington University, Rockville, MD
| | - Barbara Braffett
- The Biostatistics Center, George Washington University, Rockville, MD
| | | | - Valerie Arends
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Hunter Wessells
- Department of Urology, University of Washington, Seattle, WA
| | - Trevor Orchard
- Department of Epidemiology, University of Pittsburgh, PA
| | - Aruna V. Sarma
- Department of Urology, University of Michigan, Ann Arbor, MI
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Kim C, Dunn RL, Braffett B, Cleary PA, Arends V, Steffes M, Lanham MSM, Randolph JF, Wessells H, Wellons MF, Sarma AV. Ovarian reserve in women with Type 1 diabetes in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study. Diabet Med 2016; 33:691-2. [PMID: 26798983 PMCID: PMC4837044 DOI: 10.1111/dme.13072] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [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] [Accepted: 01/15/2016] [Indexed: 10/22/2022]
Abstract
Markers of ovarian reserve such as anti-Müllerian hormone (AMH) are used in the management of fertility and prediction of menopause. Although women with type 1 diabetes have a high prevalence of reproductive disorders, no studies have examined whether markers of ovarian reserve are associated with randomization to intensive insulin therapy and subsequent markers of glycemic control. Using data from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study, we found that the strongest predictor of AMH was chronologic age, and that diabetes-specific variables such as randomization to intensive therapy, insulin dose, and glycemic control were not associated with AMH concentrations.
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Affiliation(s)
- C Kim
- Departments of Medicine, Obstetrics & Gynecology, and Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - R L Dunn
- Department of Urology, University of Michigan, Ann Arbor, MI, USA
| | - B Braffett
- The Biostatistics Center, George Washington University, Rockville, MD, USA
| | - P A Cleary
- The Biostatistics Center, George Washington University, Rockville, MD, USA
| | - V Arends
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - M Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - M S M Lanham
- Department of Obstetrics & Gynecology, University of Michigan, Ann Arbor, MI, USA
| | - J F Randolph
- Department of Obstetrics & Gynecology, University of Michigan, Ann Arbor, MI, USA
| | - H Wessells
- Department of Urology, University of Washington, Seattle, WA, USA
| | - M F Wellons
- Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - A V Sarma
- Department of Urology, University of Michigan, Ann Arbor, MI, USA
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Murphy T, Dworkin L, Tobe S, Abernethy W, Cooper C, Cutlip D, D’Agostino R, Gao Q, Henrich W, Jamerson K, Massaro J, Metzger D, Pencina K, Shapiro J, Steffes M, Tuttle K, Matsumoto A, Textor S, Briguglio J, Hirsch A. Relationship of albuminuria and renal artery stent outcomes in the CORAL study. J Vasc Interv Radiol 2016. [DOI: 10.1016/j.jvir.2015.12.189] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Selvin E, Rawlings A, Lutsey P, Maruthur N, Pankow JS, Steffes M, Coresh J. Association of 1,5-Anhydroglucitol With Cardiovascular Disease and Mortality. Diabetes 2016; 65:201-8. [PMID: 26395741 PMCID: PMC4686946 DOI: 10.2337/db15-0607] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [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: 05/07/2015] [Accepted: 09/16/2015] [Indexed: 12/16/2022]
Abstract
In diabetes, low concentrations of the biomarker 1,5-anhydroglucitol (1,5-AG) reflect hyperglycemic excursions over the prior 1-2 weeks. To the extent that hyperglycemic excursions are important in atherogenesis, 1,5-AG may provide independent information regarding cardiovascular risk. Nonetheless, few studies have evaluated associations of 1,5-AG with long-term cardiovascular outcomes in a population-based setting. We measured 1,5-AG in 11,106 participants in the Atherosclerosis Risk in Communities (ARIC) study without cardiovascular disease at baseline (1990-1992) and examined prospective associations with coronary heart disease (n = 1,159 events), ischemic stroke (n = 637), heart failure (n = 1,553), and death (n = 3,120) over 20 years of follow-up. Cox proportional hazards models were adjusted for demographic and cardiovascular risk factors. Compared with persons with 1,5-AG ≥6 μg/mL and no history of diabetes, persons with diabetes and 1,5-AG <6.0 μg/mL had an increased risk of coronary heart disease (HR 3.85, 95% CI 3.11-4.78), stroke (HR 3.48, 95% CI 2.66-4.55), heart failure (HR 3.50, 95% CI 2.93-4.17), and death (HR 2.44, 95% CI 2.11-2.83). There was a threshold effect, with little evidence for associations at "nondiabetic" concentrations of 1,5-AG (e.g., >10 μg/mL). Associations remained but were attenuated with additional adjustment for fasting glucose or HbA1c. These data add to the growing evidence for the prognostic value of 1,5-AG for long-term complications in the setting of diabetes.
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Affiliation(s)
- Elizabeth Selvin
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD
| | - Andreea Rawlings
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Pamela Lutsey
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - Nisa Maruthur
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD
| | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Josef Coresh
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD
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Selvin E, Rawlings AM, Lutsey PL, Maruthur N, Pankow JS, Steffes M, Coresh J. Fructosamine and Glycated Albumin and the Risk of Cardiovascular Outcomes and Death. Circulation 2015; 132:269-77. [PMID: 26022911 DOI: 10.1161/circulationaha.115.015415] [Citation(s) in RCA: 94] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2015] [Accepted: 05/15/2015] [Indexed: 11/16/2022]
Abstract
BACKGROUND Hemoglobin A1c (HbA1c) is the standard measure to monitor glucose control in diabetes mellitus and is a marker of future cardiovascular risk. Fructosamine and glycated albumin are markers of short-term glycemic control, but their associations with cardiovascular outcomes are uncharacterized. METHODS AND RESULTS We measured glycated albumin and fructosamine in 11 104 participants with and without diabetes in the community-based Atherosclerosis Risk in Communities (ARIC) Study in 1990 to 1992 (baseline). We evaluated associations of fructosamine and glycated albumin with risk of coronary heart disease, ischemic stroke, heart failure, and mortality. We compared associations with those observed for HbA1c. During two decades of follow-up there were 1096 new cases of coronary heart disease, 605 of ischemic stroke, 1432 of heart failure, and 2860 deaths. Elevated baseline concentrations of fructosamine and glycated albumin were significantly associated with each of the outcomes even after adjustment for traditional cardiovascular risk factors, with especially strong associations in persons with diabetes mellitus. Associations were of similar magnitude to those observed for HbA1c and-as has been previously observed for HbA1c-the associations tended to be J-shaped, with an elevation of risk at the lowest levels of each biomarker. CONCLUSIONS The acceptance of new measures of hyperglycemia is partly dependent on establishing their association with long-term outcomes. We found that fructosamine and glycated albumin were associated with vascular outcomes and mortality and that these associations were similar to those observed for HbA1c.
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Affiliation(s)
- Elizabeth Selvin
- From Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (E.S., A.M.R., J.C.); Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD (E.S., N.M., J.C.); Division of Epidemiology & Community Health (P.L.L., J.S.P.) and Department of Laboratory Medicine and Pathology (M.S.), University of Minnesota, Minneapolis.
| | - Andreea M Rawlings
- From Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (E.S., A.M.R., J.C.); Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD (E.S., N.M., J.C.); Division of Epidemiology & Community Health (P.L.L., J.S.P.) and Department of Laboratory Medicine and Pathology (M.S.), University of Minnesota, Minneapolis
| | - Pamela L Lutsey
- From Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (E.S., A.M.R., J.C.); Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD (E.S., N.M., J.C.); Division of Epidemiology & Community Health (P.L.L., J.S.P.) and Department of Laboratory Medicine and Pathology (M.S.), University of Minnesota, Minneapolis
| | - Nisa Maruthur
- From Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (E.S., A.M.R., J.C.); Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD (E.S., N.M., J.C.); Division of Epidemiology & Community Health (P.L.L., J.S.P.) and Department of Laboratory Medicine and Pathology (M.S.), University of Minnesota, Minneapolis
| | - James S Pankow
- From Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (E.S., A.M.R., J.C.); Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD (E.S., N.M., J.C.); Division of Epidemiology & Community Health (P.L.L., J.S.P.) and Department of Laboratory Medicine and Pathology (M.S.), University of Minnesota, Minneapolis
| | - Michael Steffes
- From Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (E.S., A.M.R., J.C.); Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD (E.S., N.M., J.C.); Division of Epidemiology & Community Health (P.L.L., J.S.P.) and Department of Laboratory Medicine and Pathology (M.S.), University of Minnesota, Minneapolis
| | - Josef Coresh
- From Department of Epidemiology and the Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (E.S., A.M.R., J.C.); Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD (E.S., N.M., J.C.); Division of Epidemiology & Community Health (P.L.L., J.S.P.) and Department of Laboratory Medicine and Pathology (M.S.), University of Minnesota, Minneapolis
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Slinin Y, Peters KW, Ishani A, Yaffe K, Fink HA, Stone KL, Steffes M, Ensrud KE. Cystatin C and cognitive impairment 10 years later in older women. J Gerontol A Biol Sci Med Sci 2014; 70:771-8. [PMID: 25362662 DOI: 10.1093/gerona/glu189] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [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: 06/11/2014] [Accepted: 09/08/2014] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Results of prospective studies examining the association between cystatin C and incident cognitive impairment have been inconsistent. We tested the hypothesis that there is a U-shaped association in older women between cystatin C and risk of incident cognitive impairment 10 years later. METHODS We conducted a longitudinal analysis of a prospective cohort of 1,332 community-dwelling elderly women without dementia at baseline who had baseline cystatin C and serum creatinine measurements and completed an extended cognitive battery of neuropsychological tests with determination of cognitive status 10 years later. Incident cognitive impairment was defined as either new onset of adjudicated diagnosis of mild cognitive impairment or dementia. RESULTS Incident mild cognitive impairment or dementia was identified among 140 (26.0%) women in quartile 1 (Q1), 122 (22.6%) in Q2, 121 (22.5%) in Q3, and 156 (28.9%) in Q4 of cystatin C. In the fully adjusted model, compared to women in Q2-Q3 of cystatin C, adjusted odds ratios (95% CI) for incident cognitive impairment were 1.31 (0.98-1.75) for Q1, and 1.25 (0.94-1.66) for Q4 Compared to women in Q2-Q3 of estimated glomerular filtration rate (eGFRCysC), adjusted odds ratios (95% CI) for incident cognitive impairment after 10 years of follow-up were 1.18 (0.88-1.58) for Q4 (eGFRCysC 76.1-109.4mL/min/1.73 m(2)) and 1.26 (0.94-1.67) for Q1 (eGFRCysC 21.8-55.5mL/min/1.73 m(2)). CONCLUSIONS These results support a U-shaped association between cystatin C concentration and risk of cognitive impairment or dementia 10 years later, but the association is not independent of potential confounding factors.
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Affiliation(s)
- Yelena Slinin
- Department of Medicine, University of Minnesota, Minneapolis. Department of Medicine, Minneapolis VA Health Care System, Minnesota.
| | | | - Areef Ishani
- Department of Medicine, University of Minnesota, Minneapolis. Department of Medicine, Minneapolis VA Health Care System, Minnesota
| | - Kristine Yaffe
- Department of Psychiatry, Neurology, and Epidemiology & Biostatistics, University of California, San Francisco
| | - Howard A Fink
- Department of Medicine, University of Minnesota, Minneapolis. Department of Medicine, Minneapolis VA Health Care System, Minnesota. Division of Epidemiology & Community Health and
| | - Katie L Stone
- California Pacific Medical Center Research Institute, San Francisco
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Kristine E Ensrud
- Department of Medicine, University of Minnesota, Minneapolis. Department of Medicine, Minneapolis VA Health Care System, Minnesota. Division of Epidemiology & Community Health and
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McGee P, Steffes M, Nowicki M, Bayless M, Gubitosi-Klug R, Cleary P, Lachin J, Palmer J. Insulin secretion measured by stimulated C-peptide in long-established Type 1 diabetes in the Diabetes Control and Complications Trial (DCCT)/ Epidemiology of Diabetes Interventions and Complications (EDIC) cohort: a pilot study. Diabet Med 2014; 31:1264-8. [PMID: 24836354 PMCID: PMC4167980 DOI: 10.1111/dme.12504] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [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] [Received: 09/18/2013] [Revised: 03/07/2014] [Accepted: 05/13/2014] [Indexed: 01/12/2023]
Abstract
AIMS To evaluate whether clinically relevant concentrations of stimulated C-peptide in response to a mixed-meal tolerance test can be detected after almost 30 years of diabetes in people included in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications cohort. METHODS Mixed-meal tolerance tests were performed in a sample of 58 people. C-peptide levels were measured using a chemiluminescent immunoassay. This sample size assured a high probability of detecting C-peptide response if the true prevalence was at least 5%, a level that would justify the subsequent assessment of C-peptide in the entire cohort. RESULTS Of the 58 participants, 17% showed a definite response, defined as one or more post-stimulus concentrations of C-peptide > 0.03 nmol/l, and measurable concentrations were found in all participants. CONCLUSIONS These results show that a stimulated C-peptide response can be measured in some people with long-term Type 1 diabetes. Further investigation of all participants in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications study will help relate long-term residual C-peptide response to glycaemia over time and provide insight into the relevance of this response in terms of insulin dose, severe hypoglycaemia, retinopathy, nephropathy and macrovascular disease. Establishing the clinical relevance of long-term C-peptide responses is important in understanding the impact that therapy to preserve or improve β-cell function may have in patients with long-term Type 1 diabetes.
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Affiliation(s)
- P McGee
- The George Washington University Biostatistics Center, Rockville, MD, USA
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Abstract
BACKGROUND 1,5-Anhydroglucitol (1,5-AG) is inversely related to hyperglycemia and may be a useful indicator of short-term (1-2 weeks) hyperglycemia and glycemic excursions, but its prognostic value is unclear. We sought to evaluate the associations of 1,5-AG with risk of diabetes and microvascular disease. METHODS We measured 1,5-AG in blood samples from over 10 000 participants in the ARIC (Atherosclerosis Risk in Communities) Study (baseline, 1990-1992) and characterized the independent associations with prevalent retinopathy and with incident chronic kidney disease and incident diabetes during approximately 20 years of follow-up. RESULTS We found that 1,5-AG was associated with prevalent retinopathy, driven primarily by the strong association in persons with diagnosed diabetes: adjusted odds ratio (OR) 11.26 (95% CI, 6.17-20.53) for <6 μg/mL compared to 1,5-AG ≥10 μg/mL. This result remained significant after further adjustment for hemoglobin A(1c) (Hb A(1c)) (OR, 4.85; 95% CI, 2.42-9.74). In persons with diagnosed diabetes, low 1,5-AG (<6 μg/mL vs ≥10 μg/mL) was also associated with a >2-fold increased risk of incident chronic kidney disease [adjusted hazard ratio (HR), 2.83; 95% CI, 2.15-3.74] and remained significant after adjustment for Hb A(1c) (HR, 1.43; 95% CI, 1.02-2.00). Nondiabetic participants with high 1,5-AG (≥10 μg/mL) had the lowest prevalence of retinopathy and lowest risk of kidney disease. In persons without diagnosed diabetes at baseline, 1,5-AG <10 μg/mL was also associated with incident diabetes (adjusted HR, 2.29; 95% CI, 2.03-2.58). CONCLUSIONS 1,5-AG was associated with long-term risk of important microvascular outcomes, particularly in persons with diagnosed diabetes and even after adjustment for Hb A(1c). Our results suggest 1,5-AG may capture risk information associated with hyperglycemic excursions.
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Affiliation(s)
- Elizabeth Selvin
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD;
| | - Andreea M Rawlings
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Morgan Grams
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, MD
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MD
| | - Josef Coresh
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD
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Rao M, Steffes M, Bostom A, Ix JH. Effect of niacin on FGF23 concentration in chronic kidney disease. Am J Nephrol 2014; 39:484-90. [PMID: 24854458 DOI: 10.1159/000362424] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Accepted: 03/21/2014] [Indexed: 12/22/2022]
Abstract
BACKGROUND Elevated serum phosphorus and FGF23 are independent cardiovascular risk factors in patients with chronic kidney disease. In a randomized controlled trial of patients with dyslipidemia assigned to either extended release niacin (ERN) alone, ERN combined with the selective prostaglandin D2 receptor subtype 1 inhibitor laropiprant (ERN-L) or placebo, niacin lowered serum phosphorus; however, it is not known if it lowers FGF23 concentrations. METHODS This is an ancillary study to a multicenter, randomized, double-blind, placebo-controlled trial among patients with dyslipidemia and an estimated glomerular filtration rate (eGFR) of 30-74 ml/min/1.73 m(2). Participants were randomized to ERN-L (n = 162), ERN (n = 97), or placebo (n = 68) in a 3:2:1 ratio for 24 weeks. The primary outcome was a change in serum FGF23 concentrations, and secondary outcomes were changes in other mineral metabolism parameters. RESULTS Both the ERN and ERN-L groups showed significant declines in serum phosphorus, calcium and calcium·phosphorus product at 24 weeks compared to placebo. A significant decline from baseline (10.9%, p < 0.01) in the serum FGF23 concentration was observed in the ERN group compared to placebo, but not in the ERN-L group compared to placebo (p = 0.36 and 0.97 for ERN-L and placebo, respectively), despite equivalent declines in serum phosphorus. Similarly, the most marked declines in PTH occurred in the ERN-only group versus placebo; no change in PTH was observed in the ERN-L group. CONCLUSIONS In this ancillary study of hyperlipidemic patients with an eGFR of 30-74 ml/min/1.73 m(2), ERN alone but not in combination with laropiprant lowered FGF23 and PTH concentrations. If confirmed, niacin may provide a novel strategy to decrease phosphorus, FGF23, and PTH concentrations in patients with chronic kidney disease.
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Affiliation(s)
- Madhumathi Rao
- Division of Nephrology, Tufts Medical Center, Boston, Mass., USA
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Selvin E, Rawlings AM, Grams M, Klein R, Sharrett AR, Steffes M, Coresh J. Fructosamine and glycated albumin for risk stratification and prediction of incident diabetes and microvascular complications: a prospective cohort analysis of the Atherosclerosis Risk in Communities (ARIC) study. Lancet Diabetes Endocrinol 2014; 2:279-288. [PMID: 24703046 PMCID: PMC4212648 DOI: 10.1016/s2213-8587(13)70199-2] [Citation(s) in RCA: 175] [Impact Index Per Article: 17.5] [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: 12/13/2022]
Abstract
BACKGROUND HbA1c is the standard measure by which to monitor long-term (2-3 months) glucose control in people with diabetes and is now used for diagnosis of diabetes. Fructosamine and glycated albumin are markers of short-term (2-4 weeks) glycaemic control that might add complementary prognostic information to HbA1c. Our aim was to clarify the performance of fructosamine and glycated albumin measurements for identifying people at risk of incident diabetes or diabetic complications. METHODS We measured glycated albumin and fructosamine in blood samples from 11 348 adults without diabetes and 958 adults diagnosed with diabetes mellitus (both type 1 and 2) who attended the second examination of the Atherosclerosis Risk in Communities (ARIC) study in 1990-92 (baseline). We assessed the associations of fructosamine and glycated albumin with risk of incident diabetes, retinopathy, and risk of incident chronic kidney disease (CKD), during two decades of follow-up. We compared these associations with those of HbA1c with incident diabetes, retinopathy, and CKD. For analyses of associations with incident diabetes and CKD, adjusted hazard ratios (HRs) and their corresponding 95% CIs were estimated using Cox proportional hazards models. Model discrimination was assessed using Harrell's C statistic. FINDINGS The HRs for incident diabetes were 4·96 (4·36-5·64) for fructosamine above the 95th percentile and 6·17 (5·45-6·99) for glycated albumin above the 95th percentile. Associations were attenuated but persisted after adjustment for HbA1c. Fructosamine and glycated albumin were strongly associated with retinopathy (p<0·0001 for trend). The multivariable-adjusted HRs for CKD for people with fructosamine and glycated albumin above the 95th percentile were 1·50 (95% CI 1·22-1·85) and 1·48 (1·20-1·83), respectively, when compared with people with no diabetes and fructosamine or glycated albumin below the 75th percentile. Prediction of incident CKD by fructosamine (C statistic 0·717) and glycated albumin (0·717) were nearly as strong as by HbA1c (0·726), but HbA1c outperformed fructosamine and glycated albumin for prediction of incident diabetes with C statistics of 0·760, 0·706, and 0·703, respectively. INTERPRETATION Fructosamine and glycated albumin were strongly associated with incident diabetes and its microvascular complications, with prognostic value comparable to HbA1c. FUNDING National Heart, Lung, and Blood Institute.
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Affiliation(s)
- Elizabeth Selvin
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA.
| | - Andreea M Rawlings
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Morgan Grams
- Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A Richey Sharrett
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MD, USA
| | - Josef Coresh
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
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Cooper CJ, Murphy TP, Cutlip DE, Jamerson K, Henrich W, Reid DM, Cohen DJ, Matsumoto AH, Steffes M, Jaff MR, Prince MR, Lewis EF, Tuttle KR, Shapiro JI, Rundback JH, Massaro JM, D'Agostino RB, Dworkin LD. Stenting and medical therapy for atherosclerotic renal-artery stenosis. N Engl J Med 2014; 370:13-22. [PMID: 24245566 PMCID: PMC4815927 DOI: 10.1056/nejmoa1310753] [Citation(s) in RCA: 569] [Impact Index Per Article: 56.9] [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: 12/21/2022]
Abstract
BACKGROUND Atherosclerotic renal-artery stenosis is a common problem in the elderly. Despite two randomized trials that did not show a benefit of renal-artery stenting with respect to kidney function, the usefulness of stenting for the prevention of major adverse renal and cardiovascular events is uncertain. METHODS We randomly assigned 947 participants who had atherosclerotic renal-artery stenosis and either systolic hypertension while taking two or more antihypertensive drugs or chronic kidney disease to medical therapy plus renal-artery stenting or medical therapy alone. Participants were followed for the occurrence of adverse cardiovascular and renal events (a composite end point of death from cardiovascular or renal causes, myocardial infarction, stroke, hospitalization for congestive heart failure, progressive renal insufficiency, or the need for renal-replacement therapy). RESULTS Over a median follow-up period of 43 months (interquartile range, 31 to 55), the rate of the primary composite end point did not differ significantly between participants who underwent stenting in addition to receiving medical therapy and those who received medical therapy alone (35.1% and 35.8%, respectively; hazard ratio with stenting, 0.94; 95% confidence interval [CI], 0.76 to 1.17; P=0.58). There were also no significant differences between the treatment groups in the rates of the individual components of the primary end point or in all-cause mortality. During follow-up, there was a consistent modest difference in systolic blood pressure favoring the stent group (-2.3 mm Hg; 95% CI, -4.4 to -0.2; P=0.03). CONCLUSIONS Renal-artery stenting did not confer a significant benefit with respect to the prevention of clinical events when added to comprehensive, multifactorial medical therapy in people with atherosclerotic renal-artery stenosis and hypertension or chronic kidney disease. (Funded by the National Heart, Lung and Blood Institute and others; ClinicalTrials.gov number, NCT00081731.).
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Affiliation(s)
- Christopher J Cooper
- From the University of Toledo, Toledo, OH (C.J.C.); Rhode Island Hospital (T.P.M., L.D.D.) and Alpert Medical School of Brown University (T.P.M., L.D.D.) - both in Providence; Harvard Clinical Research Institute (D.E.C., J.M.M., R.B.D.), Beth Israel Deaconess Medical Center (D.E.C.), Massachusetts General Hospital (M.R.J.), Brigham and Women's Hospital (E.F.L.), and Boston University School of Public Health (R.B.D.) - all in Boston; University of Michigan, Ann Arbor (K.J.); University of Texas Health Science Center, San Antonio (W.H.); National Heart, Lung and Blood Institute, Bethesda, MD (D.M.R.); Saint Luke's Mid America Heart Institute, University of Missouri-Kansas City School of Medicine, Kansas City (D.J.C.); University of Virginia, Charlottesville (A.H.M.); University of Minnesota, Minneapolis (M.S.); Weill Cornell Medical Center, New York (M.R.P.); Providence Sacred Heart Medical Center and University of Washington School of Medicine, Spokane (K.R.T.); Marshall University, Huntington, WV (J.I.S.); and Holy Name Medical Center, Teaneck NJ (J.H.R.)
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August P, Hardison RM, Hage FG, Marroquin OC, McGill JB, Rosenberg Y, Steffes M, Wall BM, Molitch M. Change in albuminuria and eGFR following insulin sensitization therapy versus insulin provision therapy in the BARI 2D study. Clin J Am Soc Nephrol 2013; 9:64-71. [PMID: 24178969 DOI: 10.2215/cjn.12281211] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND AND OBJECTIVES In the Bypass Angioplasty Revascularization Investigation 2 Diabetes randomized trial, glycemic control with insulin-sensitization therapy was compared with insulin-provision therapy in patients with type 2 diabetes and coronary artery disease. This study examined differences in albumin excretion and renal function in the insulin-sensitization group versus the insulin-provision group over 5 years. DESIGN, SETTING, PARTICIPANTS & MEASUREMENTS In total, 1799 patients with measurements of creatinine and urine albumin/creatinine ratio at baseline and at least two follow-up visits were included. Management of BP, lipids, and lifestyle counseling was uniform. Progression of albuminuria was defined as doubling of baseline albumin/creatinine ratio to at least 100 mg/g or worsening of albumin/creatinine ratio status on two or more visits. Worsening renal function was defined as >25% decline in estimated GFR and annualized decline of >3 ml/min per 1.73 m(2) per year. RESULTS By 6 months and thereafter, the mean glycated hemoglobin levels were lower in the insulin-sensitization group compared with the insulin-provision group (P<0.002 for each time point; absolute difference=0.4%). Albumin/creatinine ratio increased over time in the insulin-sensitization group (P value for trend<0.001) and was stable in the insulin-provision group. Risk for progression of albumin/creatinine ratio was higher in the insulin-sensitization group compared with the insulin-provision group (odds ratio, 1.59; 95% confidence interval, 1.25 to 2.02; P=0.02). Over 5 years, albumin/creatinine ratio increased from 11.5 (interquartile range=5.0-46.7) to 15.7 mg/g (interquartile range=6.2-55.4) in the insulin-sensitization group (P<0.001) and from 12.1 (interquartile range=5.3-41.3) to 12.4 mg/g (interquartile range=5.8-50.6) in the insulin-provision group (P=0.21). Estimated GFR declined from 75.0±20.6 to 66.3±22.6 ml/min per 1.73 m(2) in the insulin-sensitization group (P<0.001) and from 76.1±29.5 to 66.8±22.1 ml/min per 1.73 m(2) in the insulin-provision group (P<0.001). CONCLUSION Over 5 years, despite lower glycated hemoglobin levels, the insulin-sensitization treatment group had greater progression of albumin/creatinine ratio compared with the insulin-provision treatment group. Decline in estimated GFR was similar.
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Affiliation(s)
- Phyllis August
- Due to the number of contributing authors, the affiliations are provided in the Supplemental Material
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Musani SK, Vasan RS, Bidulescu A, Liu J, Xanthakis V, Sims M, Gawalapu RK, Samdarshi TE, Steffes M, Taylor HA, Fox ER. Aldosterone, C-reactive protein, and plasma B-type natriuretic peptide are associated with the development of metabolic syndrome and longitudinal changes in metabolic syndrome components: findings from the Jackson Heart Study. Diabetes Care 2013; 36:3084-92. [PMID: 23757435 PMCID: PMC3781556 DOI: 10.2337/dc12-2562] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.7] [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] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Several pathomechanisms are implicated in the pathogenesis of metabolic syndrome (MetS), most of which have not been investigated in African Americans (AAs). We examined the contribution of a selected panel of biomarkers to the development of MetS in Jackson Heart Study (JHS) participants in this investigation. RESEARCH DESIGN AND METHODS We evaluated 3,019 JHS participants (mean age, 54 years; 64% women) with measurements for seven biomarkers representing inflammation (high-sensitivity C-reactive protein [CRP]), adiposity (leptin), natriuretic pathway (B-natriuretic peptide [BNP]), adrenal pathway (cortisol and aldosterone), and endothelial function (endothelin and homocysteine). We related the biomarker panel to the development of MetS on follow-up and to longitudinal changes in MetS components. RESULTS There were 278 (22.9%) of 1,215 participants without MetS at baseline who had development of new-onset MetS at follow-up. The incidence of MetS was significantly associated with serum aldosterone (P=0.004), CRP (P=0.03), and BNP (P for trend=0.005). The multivariable-adjusted odds ratios (95% CI) per SD increment of log biomarker were as follows: 1.25 (1.07-1.45) for aldosterone, 1.20 (1.02-1.43) for CRP, and 1.54 (1.07-2.23) and 1.91 (1.31-2.80) for low and high BNP quartiles, respectively. Aldosterone was positively associated with change in all MetS risk components, except low HDL cholesterol and waist circumference. CRP concentration was significantly and directly associated with change in systolic blood pressure (SBP) and waist circumference but inversely associated with HDL cholesterol. For BNP, we observed a U-shape relation with SBP and triglycerides. CONCLUSIONS Our analysis confirms that, in AAs, higher circulating aldosterone and CRP concentrations predict incident MetS. The nonlinear U-shape relation of BNP with MetS and its components has not been reported before and thus warrants replication.
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Bansal N, Vittinghoff E, Peralta CA, Shlipak MG, Grubbs V, Jacobs DR, Siscovick D, Steffes M, Carr JJ, Bibbins-Domingo K. Estimated kidney function based on serum cystatin C and risk of subsequent coronary artery calcium in young and middle-aged adults with preserved kidney function: results from the CARDIA study. Am J Epidemiol 2013; 178:410-7. [PMID: 23813702 DOI: 10.1093/aje/kws581] [Citation(s) in RCA: 8] [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] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Whether kidney dysfunction is associated with coronary artery calcium (CAC) in young and middle-aged adults who have a cystatin C-derived estimated glomerular filtration rate (eGFRcys) greater than 60 mL/min/1.73 m(2) is unknown. In the Coronary Artery Risk Development in Young Adults (CARDIA) cohort (recruited in 1985 and 1986 in Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and Oakland, California), we examined 1) the association of eGFRcys at years 10 and 15 and detectable CAC over the subsequent 5 years and 2) the association of change in eGFRcys and subsequent CAC, comparing those with stable eGFRcys to those whose eGFRcys increased (>3% annually over 5 years), declined moderately (3%-5%), or declined rapidly (>5%). Generalized estimating equation Poisson models were used, with adjustment for age, sex, race, educational level, income, family history of coronary artery disease, diabetes, body mass index, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and tobacco use. Among 3,070 participants (mean age 35.6 (standard deviation, 4.1) years and mean eGFRcys 106.7 (standard deviation, 18.5) mL/min/1.73 m(2)), 529 had detectable CAC. Baseline eGFRcys was not associated with CAC. Moderate eGFRcys decline was associated with a 33% greater relative risk of subsequent CAC (95% confidence interval: 5, 68; P = 0.02), whereas rapid decline was associated with a 51% higher relative risk (95% confidence interval: 10, 208; P = 0.01) in adjusted models. In conclusion, among young and middle-aged adults with eGFRcys greater than 60 mL/min/1.73 m(2), annual decline in eGFRcys is an independent risk factor for subsequent CAC.
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Affiliation(s)
- Nisha Bansal
- Division of Nephrology, University of California, San Francisco, 521 Parnassus Avenue, Box 0532, San Francisco, CA 94143, USA.
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Ensrud KE, Parimi N, Fink HA, Ishani A, Taylor BC, Steffes M, Cauley JA, Lewis CE, Orwoll ES. Estimated GFR and risk of hip fracture in older men: comparison of associations using cystatin C and creatinine. Am J Kidney Dis 2013; 63:31-9. [PMID: 23890927 DOI: 10.1053/j.ajkd.2013.05.022] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [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: 11/14/2012] [Accepted: 05/29/2013] [Indexed: 01/02/2023]
Abstract
BACKGROUND Higher serum cystatin C level is associated with an increased risk of hip fracture in postmenopausal white women, but there is a paucity of data for men. Whether estimated glomerular filtration rate (eGFR) based on cystatin C (eGFRcys) is superior in predicting hip fracture risk to eGFR based on creatinine (eGFRcr) or the combination (eGFR(cr-cys)) also is uncertain. STUDY DESIGN Nested case-cohort. SETTING & PARTICIPANTS Participants enrolled in the Osteoporotic Fractures in Men (MrOS) Study (5,994 men aged ≥ 65 years from 6 US centers) including a random subcohort of 1,602 men and 168 men with incident hip fractures (51 of whom were in the subcohort). PREDICTOR eGFR(cys), eGFR(cr), and eGFR(cr-cys) computed using the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equations and expressed in categories of <60, 60-74, and ≥ 75 mL/min/1.73 m(2) (referent group). OUTCOME Incident hip fracture ascertained by participant contacts every 4 months and confirmed with radiographic reports. RESULTS Median eGFR(cys) was 72.9 (IQR, 60.5-85.7) mL/min/1.73 m(2). In unadjusted models, all measures of eGFR were associated with increased hip fracture risk. However, after adjustment for age, race, site, and body mass index, the association of lower eGFR(cys) (but not lower eGFR(cr) or lower eGFR(cr-cys)) with higher hip fracture risk remained: for <60 versus ≥ 75 mL/min/1.73 m(2), HRs were 1.96 [95% CI, 1.25-3.09], 0.84 [95% CI, 0.52-1.37], and 1.08 [95% CI, 0.66-1.77] for eGFR(cys), eGFR(cr), and eGFR(cr-cys), respectively. Similarly, after adjustment for age, race, site, and body mass index, eGFR < 60 mL/min/1.73 m(2) defined by eGFR(cys), but not eGFR(cr) or eGFR(cr-cys), was associated with higher hip fracture risk. The association between eGFR(cys) and hip fracture was not explained by levels of calciotropic hormones or inflammatory markers, but the relationship was attenuated and no longer reached significance (for <60 vs ≥ 75 mL/min/1.73 m(2): HR, 1.43; 95% CI, 0.88-2.34) after consideration of additional clinical risk factors and bone mineral density. LIMITATIONS Findings not generalizable to other populations; residual confounding may exist. CONCLUSIONS Older community-dwelling men with lower eGFR(cys) have an increased risk of hip fracture that is explained in large part by greater burden of risk factors among men with lower eGFR(cys). In contrast, lower eGFR(cr) or lower eGFR(cr-cys) was not associated with a higher age-adjusted hip fracture risk.
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Affiliation(s)
- Kristine E Ensrud
- Department of Medicine, University of Minnesota, Minneapolis, MN; Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN; Center for Chronic Disease Outcomes Research, VA Health Care System, Minneapolis, MN.
| | - Neeta Parimi
- California Pacific Medical Center Research Institute, San Francisco, CA
| | - Howard A Fink
- Department of Medicine, University of Minnesota, Minneapolis, MN; Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN; Center for Chronic Disease Outcomes Research, VA Health Care System, Minneapolis, MN
| | - Areef Ishani
- Department of Medicine, University of Minnesota, Minneapolis, MN; Department of Nephrology, VA Health Care System, Minneapolis, MN
| | - Brent C Taylor
- Department of Medicine, University of Minnesota, Minneapolis, MN; Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN; Center for Chronic Disease Outcomes Research, VA Health Care System, Minneapolis, MN
| | - Michael Steffes
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Jane A Cauley
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA
| | - Cora E Lewis
- Division of Preventative Medicine, University of Alabama, Birmingham, AL
| | - Eric S Orwoll
- Bone & Mineral Unit, Oregon Health & Science University, Portland, OR
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Ensrud KE, Parimi N, Cauley JA, Ishani A, Slinin Y, Hillier TA, Taylor BC, Steffes M, Cummings SR. Cystatin C and risk of hip fractures in older women. J Bone Miner Res 2013; 28:1275-82. [PMID: 23300153 PMCID: PMC3646079 DOI: 10.1002/jbmr.1858] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2012] [Revised: 12/05/2012] [Accepted: 12/17/2012] [Indexed: 01/23/2023]
Abstract
To test the hypothesis that older women with higher cystatin C are at increased risk of hip fracture independent of traditional risk factors including hip bone mineral density (BMD), we performed a case-cohort analysis nested in a cohort of 4709 white women attending a Year 10 (1997-1998) examination of the Study of Osteoporotic Fractures that included a random sample of 1170 women and the first 300 women with incident hip fracture occurring after Year 10 examination. Serum cystatin C and creatinine were measured in Year 10 sera. In a model adjusted for age, clinical site, body mass index, and total hip BMD, higher cystatin C was associated with an increased risk of hip fracture (p for linear trend 0.008) with women in quartile 4 having a 1.9-fold higher risk (hazard ratio [HR] 1.91; 95% confidence interval [CI], 1.24-2.95) compared with those in quartile 1 (referent group). Further adjustment for additional risk factors only slightly attenuated the association; the risk for hip fracture was 1.7-fold higher (HR 1.74; 95% CI, 1.11-2.72) in women in quartile 4 compared with those in quartile 1. In contrast, neither serum creatinine nor creatinine-based estimated glomerular filtration rate (eGFRCr ) were associated with risk of hip fracture. Older women with higher cystatin C, but not higher serum creatinine or lower eGFRCr , have an increased risk of hip fracture independent of traditional risk factors. These findings suggest that cystatin C may be a promising biomarker for identification of older adults at high risk of hip fracture.
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Affiliation(s)
- Kristine E Ensrud
- Department of Medicine, University of Minnesota, Minneapolis, MN, USA.
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Padala S, Tighiouart H, Inker LA, Contreras G, Beck GJ, Lewis J, Steffes M, Rodby RA, Schmid CH, Levey AS. Accuracy of a GFR estimating equation over time in people with a wide range of kidney function. Am J Kidney Dis 2012; 60:217-24. [PMID: 22495467 DOI: 10.1053/j.ajkd.2012.01.024] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2011] [Accepted: 01/31/2012] [Indexed: 01/13/2023]
Abstract
BACKGROUND Change in glomerular filtration rate (GFR) is important for clinical decision making. GFR estimates from serum creatinine level provide an unbiased but imprecise estimate of GFR at single time points. However, the accuracy of estimated GFR over time is not well known. STUDY DESIGN Longitudinal study of diagnostic test accuracy. SETTINGS & PARTICIPANTS 4 clinical trials with longitudinal measurements of GFR and serum creatinine on the same day, including individuals with and without kidney disease with a wide range of kidney function, diverse racial backgrounds, and varied clinical characteristics. INDEX TEST GFR estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. REFERENCE TEST GFR measured using urinary clearance of (125)I-iothalamate. RESULTS Data included 19,735 GFR measurements in 3,531 participants during a mean follow-up of 2.6 years. Mean values at baseline for measured and estimated GFR and error (measured GFR - estimated GFR) were 73.1 (95% CI, 71.6 to 74.5), 72.7 (95% CI, 71.5 to 74.0), and 0.14 (95% CI, -0.35 to 0.63) mL/min/1.73 m(2), respectively. Mean rates of change in measured and estimated GFR and error were -2.3 (95% CI, -2.4 to -2.1), -2.2 (95% CI, -2.4 to -2.1), and -0.09 (95% CI, -0.24 to 0.05) mL/min/1.73 m(2) per year (P < 0.001, P < 0.001, and P = 0.2, respectively). Variability (ie, standard deviation) among participants in rate of change in measured GFR, estimated GFR, and error was 4.3, 3.4, and 3.3 mL/min/1.73 m(2) per year, respectively. Only 15% of participants had a rate of change in error >3 mL/min/1.73 m(2) per year, and only 2% had a rate of change in error >5% per year. LIMITATIONS Participants' characteristics were not available over time. CONCLUSION The accuracy of GFR estimates did not change over time. Clinicians should interpret changes in estimated GFR over time as reflecting changes in measured GFR rather than changes in errors in the GFR estimates in most individuals.
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Beck R, Steffes M, Xing D, Ruedy K, Mauras N, Wilson DM, Kollman C. The interrelationships of glycemic control measures: HbA1c, glycated albumin, fructosamine, 1,5-anhydroglucitrol, and continuous glucose monitoring. Pediatr Diabetes 2011; 12:690-5. [PMID: 21496193 PMCID: PMC3193556 DOI: 10.1111/j.1399-5448.2011.00764.x] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVES To describe the interrelationships of glycemic control measures: hemoglobin A1c (HbA1c), glycated albumin, fructosamine, 1,5-anhydroglucitrol (1,5-AG), and continuous glucose monitoring (CGM) in children and adolescents with type 1 diabetes. METHODS In total, 26 subjects of age 4-17 had HbA1c measurement followed within 14 d by three laboratory measures of glycemia and the collection of CGM glucose data (N = 21). RESULTS Glycated albumin and fructosamine levels had a higher correlation with each other than with HbA1c. The correlation of 1,5-AG with HbA1c was lower (absolute r value = 0.25). All four measures had a similar degree of correlation with CGM-measured mean glucose (absolute r value = 0.50-0.56) and with hyperglycemic area under the curve (AUC) at 180 mg/dL (0.50-0.60). CONCLUSION Each of the four measures (i.e., HbA1c, glycated albumin, fructosamine, and 1,5-AG) had a similar correlation with mean glucose and hyperglycemic AUC-180. 1,5-AG did not correlate with hyperglycemic AUC-180 better than did HbA1c.
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Affiliation(s)
- Roy Beck
- Jaeb Center for Health Research, Tampa, FL 33647, USA.
| | | | - Dongyuan Xing
- Jaeb Center for Health Research, Tampa, FL, US, 33647
| | - Katrina Ruedy
- Jaeb Center for Health Research, Tampa, FL, US, 33647
| | - Nelly Mauras
- Nemours Children’s Clinic, Jacksonville, FL 32256
| | | | - Craig Kollman
- Jaeb Center for Health Research, Tampa, FL, US, 33647, and the Diabetes Research in Children Network (DirecNet) Study Group*
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Cresci S, Wu J, Province MA, Spertus JA, Steffes M, McGill JB, Alderman EL, Brooks MM, Kelsey SF, Frye RL, Bach RG. Peroxisome proliferator-activated receptor pathway gene polymorphism associated with extent of coronary artery disease in patients with type 2 diabetes in the bypass angioplasty revascularization investigation 2 diabetes trial. Circulation 2011; 124:1426-34. [PMID: 21911782 DOI: 10.1161/circulationaha.111.029173] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND Coronary artery disease (CAD) is the major cause of death in patients with type 2 diabetes mellitus. Although demographic and clinical factors associated with extent of CAD in patients with diabetes mellitus have been described, genetic factors have not. We hypothesized that genetic variation in peroxisome proliferator-activated receptor (PPAR) pathway genes, important in diabetes mellitus and atherosclerosis, would be associated with extent of CAD in patients with diabetes mellitus. METHODS AND RESULTS We genotyped 1043 patients (702 white, 175 blacks) from the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) genetic cohort for 3351 variants in 223 PPAR pathway genes using a custom targeted-genotyping array. Angiographic end points were determined by a core laboratory. In whites, a single variant (rs1503298) in TLL1 was significantly (P=5.5 × 10(-6)) associated with extent of CAD, defined as number of lesions with percent diameter stenosis ≥20%, after stringent Bonferroni correction for all 3351 single nucleotide polymorphisms. This association was validated in the diabetic subgroups of 2 independent cohorts, the Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients' Health Status (TRIUMPH) post-myocardial infarction registry and the prospective Family Heart Study (FHS) of individuals at risk for CAD. TLL1rs1503298 was also significantly associated with extent of severe CAD (≥70% diameter stenosis; P=3.7 × 10(-2)) and myocardial jeopardy index (P=8.7 × 10(-4)). In general linear regression modeling, TLL1rs1503298 explained more variance of extent of CAD than the previously determined clinical factors. CONCLUSIONS We identified a variant in a single PPAR pathway gene, TLL1, that is associated with the extent of CAD independently of clinical predictors, specifically in patients with type 2 diabetes mellitus and CAD. Clinical Trial Registration- URL: http://www.clinicaltrials.gov. Unique identifier: NCT00006305.
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Affiliation(s)
- Sharon Cresci
- Cardiovascular Division, Washington University School of Medicine, 660 S Euclid Ave, Campus Box 8086, St. Louis, MO 63110-1093, USA.
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Yu H, Zhang D, Haller S, Kanjwal K, Colyer W, Brewster P, Steffes M, Shapiro JI, Cooper CJ. Determinants of renal function in patients with renal artery stenosis. Vasc Med 2011; 16:331-8. [PMID: 21908683 DOI: 10.1177/1358863x11419998] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Renal artery stenosis (RAS) is an important cause of renal failure; however, the factors associated with loss of kidney function in patients with RAS are poorly described, as are the predictors of an improvement in kidney function after stenting. One hundred patients at seven centers undergoing renal stenting were randomly assigned to an embolic protection device or double-blind use of a platelet glycoprotein IIb/IIIa inhibitor. The glomerular filtration rate (GFR) was measured using the creatinine-derived modified Modification of Diet in Renal Disease (MDRD) equation, cystatin C, and iohexol clearance. In univariate and multivariate models, baseline MDRD and cystatin C GFR were associated with congestive heart failure (CHF) (p = 0.01), lesion length (p = 0.01), and percent stenosis (-0.27, p = 0.01). In multivariate models, MDRD-estimated GFR 1 month after stenting was associated with bilateral stenosis (p < 0.05) and lesion length (p < 0.05), whereas with cystatin C the multivariate model included angiotensin receptor blocker (ARB) (p < 0.05) and minimal luminal diameter (MLD) (p < 0.05). The improvement in GFR from baseline to 1 month, measured as percent change, was related to baseline MDRD (p = 0.009) and cystatin C (p = 0.03) GFR. For MDRD GFR combined treatment with abciximab and Angioguard(®) embolic protection (p = 0.02) remained significant in multivariate analysis as did CHF, which was also significant with cystatin C (p = 0.05). In conclusion, CHF and lesion characteristics (MLD, percent stenosis and lesion length) are determinants of renal function in patients with RAS. In contrast, the acute improvement in renal function after revascularization is most strongly influenced by baseline GFR, and to a lesser degree CHF and combined procedural treatment with abciximab and embolic protection but not lesion characteristics. Clinical Trial Registration - URL:http://www.clinicaltrials.gov. Unique identifier: NCT00234585.
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Kanjwal MK, Zhang D, Adlakha S, Yu H, Brewster PS, Hoetzl K, Haller S, Steffes M, Shapiro J, Colyer WR, Cooper CJ. LACTATE DEHYDROGENASE (LDH) AND RESPONSE TO RENAL ARTERY STENTING. J Am Coll Cardiol 2011. [DOI: 10.1016/s0735-1097(11)61452-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Wilson DM, Xing D, Beck RW, Block J, Bode B, Fox LA, Hirsch I, Kollman C, Laffel L, Ruedy KJ, Steffes M, Tamborlane WV. Hemoglobin A1c and mean glucose in patients with type 1 diabetes: analysis of data from the Juvenile Diabetes Research Foundation continuous glucose monitoring randomized trial. Diabetes Care 2011; 34:540-4. [PMID: 21266647 PMCID: PMC3041177 DOI: 10.2337/dc10-1054] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To determine the relationship between mean sensor glucose concentrations and hemoglobin A(1c) (HbA(1c)) values measured in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications laboratory at the University of Minnesota in a cohort of subjects with type 1 diabetes from the Juvenile Diabetes Research Foundation continuous glucose monitoring randomized trial. RESEARCH DESIGN AND METHODS Near-continuous glucose sensor data (≥ 4 days/week) were collected for 3 months before a central laboratory-measured HbA(1c) was performed for 252 subjects aged 8-74 years, the majority of whom had stable HbA(1c) values (77% within ± 0.4% of the patient mean). RESULTS The slope (95% CI) for mean sensor glucose concentration (area under the curve) versus a centrally measured HbA(1c) was 24.4 mg/dL (22.0-26.7) for each 1% change in HbA(1c), with an intercept of -16.2 mg/dL (-32.9 to 0.6). Although the slope did not vary with age or sex, there was substantial individual variability, with mean sensor glucose concentrations ranging from 128 to 187 mg/dL for an HbA(1c) of 6.9-7.1%. The root mean square of the errors between the actual mean sensor glucose concentration versus the value calculated using the regression equation was 14.3 mg/dL, whereas the median absolute difference was 10.1 mg/dL. CONCLUSIONS There is substantial individual variability between the measured versus calculated mean glucose concentrations. Consequently, estimated average glucose concentrations calculated from measured HbA(1c) values should be used with caution.
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Hu S, Akhlaghi F, Chitnis S, Chiu R, Go S, Rout P, Steffes M, Abbott JD, Dworkin L, Bostom A. Comparison of Plasma Clearance of Iodixanol During Versus After Angiography. Am J Kidney Dis 2010; 56:1219-20. [DOI: 10.1053/j.ajkd.2010.08.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2010] [Accepted: 08/11/2010] [Indexed: 11/11/2022]
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Kanjwal K, Cooper CJ, Virmani R, Haller S, Shapiro JI, Burket MW, Steffes M, Brewster P, Zhang H, Colyer WR. Predictors of embolization during protected renal artery angioplasty and stenting: Role of antiplatelet therapy. Catheter Cardiovasc Interv 2010; 76:16-23. [PMID: 20209644 DOI: 10.1002/ccd.22469] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVE The objective of this study was to identify the predictors of distal embolization (DE) during protected renal artery angioplasty and stenting. BACKGROUND DE may contribute to worsening renal function after renal artery stenting. The factors associated with DE, rates of platelet-rich emboli, and treatments that may prevent DE during renal stenting have not been evaluated. METHODS The current study evaluated patients randomized to receive an embolic protection device (EPD) in the RESIST trial. Forty-two patients were identified for inclusion in this study. These patients were further randomized to abciximab (N = 22) or placebo (N = 20). Modification in Diet in Renal Disease glomerular filtration rate (GFR) was used as the primary measure of renal function. Creatinine was measured by a modified Jaffe reaction using the IDMS-traceable assay. The primary endpoint was capture of platelet rich emboli in the angioguard basket. RESULTS DE occurred in 15/42 (35%) of the patients and platelet rich DE in 10 (24%) of the patients who received an EPD. Of the angiographic characteristics only lesion length was significantly higher in patients with DE (16 +/- 7 mm vs. 10 +/- 5 mm, P = 0.04). Preprocedural abciximab reduced DE from 42 to 8% (P = 0.02). The rate of platelet rich emboli was 50% with neither abciximab nor a thienopyridine, 36% with thienopyridine only, 15% abciximab only, and 0% in patients who received both a thienopyridine and abciximab. Only Abciximab use was associated with improved renal function at 1-month, thienopyridine was not. Angiographic characteristics including percent stenosis, minimal luminal diameter (MLD), reference diameter, change in MLD, contrast volume, and procedure time were not predictors of DE during renal stenting. CONCLUSION Capture of DE and specifically platelet DE are common during protected renal stenting using a filter-type EPD. Abciximab use, and potentially combined thienopyridine and abciximab use, decreased the rate of platelet rich DE; however, only abciximab improved renal function at 1-month.
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Affiliation(s)
- Khalil Kanjwal
- Department of Medicine, Division of Cardiology, The University of Toledo, 3000 Arlington Ave., Toledo, OH 43614, USA
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Molitch ME, Steffes M, Sun W, Rutledge B, Cleary P, de Boer IH, Zinman B, Lachin J. Development and progression of renal insufficiency with and without albuminuria in adults with type 1 diabetes in the diabetes control and complications trial and the epidemiology of diabetes interventions and complications study. Diabetes Care 2010; 33:1536-43. [PMID: 20413518 PMCID: PMC2890355 DOI: 10.2337/dc09-1098] [Citation(s) in RCA: 200] [Impact Index Per Article: 14.3] [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] [Indexed: 02/03/2023]
Abstract
OBJECTIVE This multicenter study examined the impact of albumin excretion rate (AER) on the course of estimated glomerular filtration rate (eGFR) and the incidence of sustained eGFR <60 ml/min/1.73 m(2) in type 1 diabetes up to year 14 of the Epidemiology of Diabetes Interventions and Complications (EDIC) study (mean duration of 19 years in the Diabetes Control and Complications Trial [DCCT]/EDIC). RESEARCH DESIGN AND METHODS Urinary albumin measurements from 4-h urine collections were obtained from participants annually during the DCCT and every other year during the EDIC study, and serum creatinine was measured annually in both the DCCT and EDIC study. GFR was estimated from serum creatinine using the abbreviated Modification of Diet in Renal Disease equation. RESULTS A total of 89 of 1,439 subjects developed an eGFR <60 ml/min/1.73 m(2) (stage 3 chronic kidney disease on two or more successive occasions (sustained) during the DCCT/EDIC study (cumulative incidence 11.4%). Of these, 20 (24%) had AER <30 mg/24 h at all prior evaluations, 14 (16%) had developed microalbuminuria (AER 30-300 mg/24 h) before they reached stage 3 chronic kidney disease, and 54 (61%) had macroalbuminuria (AER >300 mg/24 h) before they reached stage 3 chronic kidney disease. Macroalbuminuria is associated with a markedly increased rate of fall in eGFR (5.7%/year vs. 1.2%/year with AER <30 mg/24 h, P < 0.0001) and risk of eGFR <60 ml/min/1.73 m(2) (adjusted hazard ratio 15.3, P < 0.0001), whereas microalbuminuria had weaker and less consistent effects on eGFR. CONCLUSIONS Macroalbuminuria was a strong predictor of eGFR loss and risk of developing sustained eGFR <60 ml/min/1.73 m(2). However, screening with AER alone would have missed 24% of cases of sustained impaired eGFR.
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Kim KY, Kim DS, Lee SK, Lee IK, Kang JH, Chang YS, Jacobs DR, Steffes M, Lee DH. Association of low-dose exposure to persistent organic pollutants with global DNA hypomethylation in healthy Koreans. Environ Health Perspect 2010; 118:370-4. [PMID: 20064773 PMCID: PMC2854765 DOI: 10.1289/ehp.0901131] [Citation(s) in RCA: 159] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2009] [Accepted: 11/06/2009] [Indexed: 05/17/2023]
Abstract
BACKGROUND Global DNA methylation levels have been reported to be inversely associated with blood levels of persistent organic pollutants (POPs), xenobiotics that accumulate in adipose tissue. Whether these associations extend to a population with much lower concentrations of POPs is not known. OBJECTIVES This study was performed to examine whether low-dose exposure to POPs was associated with global DNA hypomethylation in Koreans. METHODS The amount of global DNA hypomethylation was estimated by the percent 5-methyl-cytosine (%5-mC) in Alu and LINE-1 assays in 86 apparently healthy Koreans. Among various POPs, organochlorine (OC) pesticides, polychlorinated biphenyls (PCBs), and polybrominated diphenylethers (PBDEs) were measured. RESULTS Most OC pesticides were inversely and significantly associated with %5-mC in the Alu assay, with correlation coefficients in the range 0.2 to 0.3 after adjusting for age, sex, body mass index, smoking, and alcohol. The strongest OC pesticide associations with %5-mC in the Alu assay were observed with oxychlordane, trans-nonachlor, and p,p -dichlorodiphenyldichloroethylene. The correlation coefficient of age with %5-mC in the Alu assay was 0.24, similar to correlations of OC pesticides with %5-mC in the Alu assay. Most PCBs and PBDEs showed nonsignificant inverse trends with %5-mC in the Alu assay, but for some PCBs the U-shaped association was significant. On the other hand, POPs were not associated with %5-mC in the LINE-1 assay. CONCLUSIONS We found that low-dose exposure to POPs, in particular OC pesticides, was associated with global DNA hypomethylation in apparently healthy Koreans.
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Affiliation(s)
| | | | | | - In-Kyu Lee
- Department of Endocrinology, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Jung-Ho Kang
- School of Environmental Science and Engineering, POSTECH, Pohang, Korea
| | - Yoon-Seok Chang
- School of Environmental Science and Engineering, POSTECH, Pohang, Korea
| | - David R. Jacobs
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
- Division of Epidemiology, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | | | - Duk-Hee Lee
- Department of Preventative Medicine
- Address correspondence to D-H Lee, Department of Preventive Medicine, School of Medicine, Kyungpook National University, 101 Dongin-dong, Jung-gu, Daegu, 700-422 South Korea. Telephone: 82 53 420 4866. Fax: 82 53 425 2447. E-mail:
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Canales MT, Paudel ML, Taylor BC, Ishani A, Mehra R, Steffes M, Stone KL, Redline S, Ensrud KE. Sleep-disordered breathing and urinary albumin excretion in older men. Sleep Breath 2010; 15:137-44. [PMID: 20186573 DOI: 10.1007/s11325-010-0339-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2009] [Revised: 01/31/2010] [Accepted: 02/01/2010] [Indexed: 10/19/2022]
Abstract
PURPOSE Sleep-disordered breathing (SDB) may be deleterious to the cardiovascular system and other organs, including the kidney. Although older men are at increased risk for both kidney disease and SDB, it is unknown whether SDB is associated with higher urinary albumin excretion in this population. METHODS We examined 507 community-dwelling men age ≥ 67 years (mean 76.0 ± 5.3) enrolled in the MrOS Sleep study who underwent overnight polysomnography and gave a spot urine sample. SDB severity was categorized using the respiratory disturbance index and percent total sleep time <90% oxygen saturation (%time O2<90). Urinary albumin excretion was expressed using the albumin-to-creatinine ratio (ACR). RESULTS There was a graded association between respiratory disturbance index and ACR (age- and race-adjusted mean ACR = 9.35 mg/gCr for respiratory disturbance index ≥ 30 versus 6.72 mg/gCr for respiratory disturbance index < 5, p = 0.007). This association was attenuated after further adjustment for body mass index (BMI), hypertension and diabetes and no longer reached significance (p = 0.129). However, even after adjustment for age, race, BMI, hypertension, and diabetes, greater %time O2<90 was associated with higher ACR (10.35 mg/gCr for ≥10%time O2<90 versus 7.45 mg/gCr for <1%time O2<90, p = 0.046). CONCLUSION SDB, measured by elevated respiratory disturbance index or nocturnal hypoxemia, was associated with higher ACR. The relationship between respiratory disturbance index and ACR was partially explained by higher BMI and greater prevalence of hypertension and diabetes among men with SDB. However, greater nocturnal hypoxemia was independently associated with higher ACR, suggesting that the hypoxia component of SDB may mediate any detrimental effect of SDB on the kidney.
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Affiliation(s)
- Muna T Canales
- Department of Medicine, Malcolm-Randall Veterans Affairs Medical Center, Gainesville, FL, USA.
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Abstract
AIMS/HYPOTHESIS We examined the cross-sectional and longitudinal relationships between C-reactive protein (CRP), a marker of low-grade inflammation, and insulin resistance and whether the association was independent of obesity and oxidative stress. METHODS CRP and insulin resistance (homeostasis model assessment of insulin resistance [HOMA-IR]) data were obtained in a population-based, prospective observational study, Coronary Artery Risk Development in Young Adults (CARDIA), during 1992-2006. RESULTS CRP showed a significant positive association with insulin resistance, both cross-sectionally and longitudinally (5 year follow-up). The estimated increment in HOMA-IR was 0.34 log(e)(pmol/l x [mmol/l]/156.25) (p value for trend <0.0001) in the highest vs lowest CRP quartiles in cross-sectional analysis, whereas the corresponding estimate was 0.12 (p trend <0.0001) in the highest vs lowest CRP quartiles longitudinally over 5 years. The gradient of HOMA-IR across CRP was attenuated but remained statistically significant after controlling for body fat measurements (0.06 in the highest vs lowest CRP in both cross-sectional [p value for trend = 0.001] and longitudinal analyses [p value for trend = 0.01]), and was little changed by further adjustment for oxidative stress markers (F(2)-isoprostanes and oxidised LDL). There were consistent increments in the levels of HOMA-IR with increasing concentrations of CRP over time. In contrast, higher HOMA-IR did not predict future increases in CRP. Findings were similar using fibrinogen as the predictor variable. CONCLUSIONS/INTERPRETATION Although a substantial portion of this association was explained by obesity, CRP was independently related to concurrent and future insulin resistance.
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Affiliation(s)
- K Park
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, 1300 South 2nd Street, Suite 300, Minneapolis, MN 55454, USA
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Tsalikian E, Tamborlane W, Xing D, Becker DM, Mauras N, Fiallo-Scharer R, Buckingham B, Weinzimer S, Steffes M, Singh R, Beck R, Ruedy K, Kollman C. Blunted counterregulatory hormone responses to hypoglycemia in young children and adolescents with well-controlled type 1 diabetes. Diabetes Care 2009; 32:1954-9. [PMID: 19675205 PMCID: PMC2768200 DOI: 10.2337/dc08-2298] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.3] [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] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Hypoglycemia in young children with type 1 diabetes is an acute complication of intensive insulin therapy and is commonly observed in the absence of signs or symptoms. The effect of intensive treatment and patient age on sympathoadrenal responses has not been established in youth with type 1 diabetes because of difficulties in testing procedures. RESEARCH DESIGN AND METHODS We developed a standardized inpatient continuous subcutaneous insulin infusion protocol to produce a progressive fall in plasma glucose concentrations in insulin pump-treated patients. Plasma glucose and counterregulatory hormone concentrations were measured in 14 young children (3 to <8 years, A1C 7.7 +/- 0.6%) vs. 14 adolescents (12 to <18 years, A1C 7.6 +/- 0.8%). RESULTS Plasma glucose decreased to similar nadir concentrations in the two groups. Four young children and four adolescents never had an epinephrine response. In the four young children and five adolescents who had a modest epinephrine response, this only occurred when plasma glucose fell to <60 mg/dl. In evaluating symptom scores, 29% of parents of young children felt that their child looked hypoglycemic, even at the lowest plasma glucose concentrations. Adolescents were better able to detect symptoms of hypoglycemia. In comparison with our data, epinephrine response to hypoglycemia in 14 nondiabetic adolescents studied at the Children's Hospital of Pittsburgh was higher. CONCLUSIONS These data suggest that even young children and adolescents with type 1 diabetes are prone to develop hypoglycemia-associated autonomic failure regardless of duration. Whether these abnormalities can be reversed using continuous glucose monitoring and closed-loop insulin delivery systems awaits further study.
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Williams AJK, Somerville M, Rokni S, Bonifacio E, Yu L, Eisenbarth G, Akolkar B, Steffes M, Bingley PJ. Azide and Tween-20 reduce binding to autoantibody epitopes of islet antigen-2; implications for assay performance and reproducibility. J Immunol Methods 2009; 351:75-9. [PMID: 19837075 DOI: 10.1016/j.jim.2009.10.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2009] [Revised: 10/05/2009] [Accepted: 10/08/2009] [Indexed: 11/25/2022]
Abstract
Autoantibodies to islet antigen 2 (IA-2A) are important markers for predicting diabetes in children and young adults. Harmonization of IA-2A assay measurement is essential if results from different laboratories are to be compared. We investigated whether sodium azide, a bacteriostatic agent added to some assays, could affect IA-2A binding and thereby contribute to differences in IA-2A measurement between laboratories. Addition of 0.1% azide to assay buffer was found to reduce median IA-2A binding of 18 selected sera from IA-2A positive patients with type 1 diabetes and their relatives by 41% (range, 78 to -33%, p<0.001). The effect on binding was epitope specific; median IA-2A binding by 14 sera with antibodies to the protein tyrosine phosphatase region of IA-2 was reduced by 48% (range, 11 to 78%, p<0.001), while binding by 4 sera with antibodies specific to only the juxtamembrane region of IA-2 showed no change (median increase 16% (range 6 to 33%, p=0.125). When the Tween-20 concentration was reduced from 1% to 0.15% the median reduction in IA-2A binding with azide by the 18 sera was only 10% (range, -12 to 41%, p<0.001). Tween-20 also exerted an independent effect, since median IA-2A binding increased by 23% (range 3% to 86%, p<0.001) when Tween-20 concentration was reduced from 1% to 0.15% in the absence of azide. We conclude that common assay reagents such as azide and Tween-20 can strongly influence IA-2A binding in an epitope-related manner, and their use may explain some of the differences between laboratories in IA-2A measurement.
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Kanjwal K, Haller S, Steffes M, Virmani R, Shapiro JI, Burket MW, Cooper CJ, Colyer WR. Complete versus partial distal embolic protection during renal artery stenting. Catheter Cardiovasc Interv 2009; 73:725-30. [DOI: 10.1002/ccd.21932] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Bash LD, Selvin E, Steffes M, Coresh J, Astor BC. Poor glycemic control in diabetes and the risk of incident chronic kidney disease even in the absence of albuminuria and retinopathy: Atherosclerosis Risk in Communities (ARIC) Study. ACTA ACUST UNITED AC 2009; 168:2440-7. [PMID: 19064828 DOI: 10.1001/archinte.168.22.2440] [Citation(s) in RCA: 123] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Diabetic nephropathy is the leading cause of kidney failure in the United States. The extent to which an elevated glycated hemoglobin (HbA(1c)) concentration is associated with increased risk of chronic kidney disease (CKD) in the absence of albuminuria and retinopathy, the hallmarks of diabetic nephropathy, is uncertain. METHODS Glycated hemoglobin concentration was measured in 1871 adults with diabetes mellitus followed up for 11 years in the Atherosclerosis Risk in Communities (ARIC) Study. Incident CKD was defined as an estimated glomerular filtration rate less than 60 mL/min/1.73 m(2) after 6 years of follow-up or a kidney disease-related hospitalization. We categorized HbA(1c) concentrations into 4 clinically relevant categories. Albuminuria and retinopathy were measured midway through follow-up. RESULTS Higher HbA(1c) concentrations were strongly associated with risk of CKD in models adjusted for demographic data, baseline glomerular filtration rate, and cardiovascular risk factors. Compared with HbA(1c) concentrations less than 6%, HbA(1c) concentrations of 6% to 7%, 7% to 8%, and greater than 8% were associated with adjusted relative hazard ratios (95% confidence intervals) of 1.4 (0.97-1.91), 2.5 (1.70-3.66), and 3.7 (2.76-4.90), respectively. Risk of CKD was higher in individuals with albuminuria and retinopathy, and the association between HbA(1c) concentration and incident CKD was observed even in participants without either abnormality: adjusted relative hazards, 1.46 (95% confidence intervals, 0.80-2.65), 1.17 (0.43-3.19), and 3.51 (1.67-7.40), respectively; P(trend) = .004. CONCLUSIONS We observed a positive association between HbA(1c) concentration and incident CKD that was strong, graded, independent of traditional risk factors, and present even in the absence of albuminuria and retinopathy. Hyperglycemia is an important indicator of risk of both diabetic nephropathy with albuminuria or retinopathy and of less specific forms of CKD.
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Affiliation(s)
- Lori D Bash
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
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Pambianco G, Lombardero M, Bittner V, Forker A, Kennedy F, Krishnaswami A, Mooradian AD, Pop-Busui R, Rana JS, Rodriguez A, Steffes M, Orchard TJ. Control of lipids at baseline in the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial. Prev Cardiol 2009; 12:9-18. [PMID: 19301686 PMCID: PMC2717619 DOI: 10.1111/j.1751-7141.2008.00014.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
In order to examine lipids, a major treatment parameter in those with diabetes and heart disease, the authors analyzed baseline data from the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial. The study consisted of 2368 participants with type 2 diabetes and coronary artery disease from 49 sites in 6 countries (2295 provided lipid measurements). Fifty-nine percent of participants had a low-density lipoprotein (LDL) cholesterol level < 100 mg/dL. Levels of total, LDL, and non-high-density lipoprotein (HDL) cholesterol and triglycerides differed by age group (younger than 55, 55-64, and 65 years and older); they were lowest in those aged 65 years. Women had higher total, LDL, and non-HDL cholesterol values. Education was associated with lower total, LDL, and non-HDL cholesterol levels. LDL cholesterol and triglyceride values were lower in the United States and Canada. Adjustment for age, sex, education level, randomization year, and medication did not eliminate these differences. Geographic variation was seen and was not fully accounted for by demographic or treatment characteristics (all P values < .05).
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Affiliation(s)
- Georgia Pambianco
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
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Ishani A, Paudel M, Taylor BC, Barrett-Connor E, Jamal S, Canales M, Steffes M, Fink HA, Orwoll E, Cummings SR, Ensrud KE. Renal function and rate of hip bone loss in older men: the Osteoporotic Fractures in Men Study. Osteoporos Int 2008; 19:1549-56. [PMID: 18392664 DOI: 10.1007/s00198-008-0608-0] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.7] [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: 10/25/2007] [Accepted: 01/15/2008] [Indexed: 10/22/2022]
Abstract
UNLABELLED Older men with reduced renal function are at increased risk of hip bone loss. Given the robustness of this association across different measures and a growing body of literature, our findings indicate that clinicians should take into account renal function when evaluating older men for osteoporosis risk and bone loss. Future randomized controlled trials should test whether interventions in this high risk population are effective in preventing bone loss and decreasing fracture incidence. INTRODUCTION Studies examining whether kidney impairment, not requiring dialysis, is associated with osteoporosis have reported conflicting results. METHODS We tested the hypothesis that reduced renal function in older men as manifested by higher concentrations of cystatin C or lower levels of estimated glomerular filtration rate (eGFR) is associated with higher rates of bone loss. We measured serum cystatin C, serum creatinine and total hip bone mineral density (BMD) at baseline in a cohort of 404 older men enrolled in the Osteoporotic Fractures in Men (MrOS) Study and followed them prospectively for an average of 4.4 years for changes in BMD. Associations between renal function and change in hip BMD were examined using linear regression. RESULTS In multivariable analysis, the mean rate of decline in total hip BMD showed an increase in magnitude with higher cystatin C concentration (mean annualized percent change -0.29, -0.34, -0.37 and -0.65% for quartiles 1 to 4; p for trend=0.004). Similarly, adjusted rates of hip bone loss were higher among men with lower eGFR as defined by the modification of diet in renal disease formula (mean annualized percent change -0.58, -0.39, -0.37, and -0.31 for quartiles 1 to 4; p for trend=0.02), but not among men with lower eGFR as defined by the Cockcroft-Gault formula (mean annualized percent change -0.47, -0.44, -0.31 and -0.43 for quartiles 1 to 4; p for trend=0.48). CONCLUSIONS Older men with reduced renal function are at increased risk of hip bone loss. Our findings suggest that health care providers should consider renal function when evaluating older men for risk factors for bone loss and osteoporosis.
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Affiliation(s)
- A Ishani
- Center for Chronic Disease Outcomes Research, Veterans Affairs Medical Center, Minneapolis, MN, USA.
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Abstract
OBJECTIVE Recent epidemiological studies have shown that background exposure to persistent organic pollutants (POPs)--xenobiotics accumulated in adipose tissue--is strongly associated with type 2 diabetes. Hyperglycemia is the cause of long-term complications of diabetes as well as diabetes itself, and POPs are well-known neurotoxicants. This study was performed to explore whether POPs are associated with peripheral neuropathy, a common long-term complication of diabetes, in people with glucose abnormalities. RESEARCH DESIGN AND METHODS We studied cross-sectional associations of peripheral neuropathy with 25 POPs, each of which were detectable in at least 60% of study subjects, in 246 subjects aged >or=40 years with diabetes or impaired fasting glucose (IFG) using National Health and Nutrition Examination Survey 1999-2002 datasets. RESULTS Among five subclasses of POPs, organochlorine pesticides showed a strong dose-response relation with prevalence of peripheral neuropathy; adjusted ORs were 1.0, 3.6, and 7.3 (P for trend <0.01), respectively, across three categories of serum concentrations of organochlorine pesticides. Furthermore, when we restricted the analyses to 187 participants with A1C <7%, the adjusted ORs were still 1.0, 3.9, and 6.7 (P for trend <0.01). Organochlorine pesticides were also strongly associated with the prevalence of A1C >or=7%; adjusted ORs were 1.0, 2.5, and 5.0 (P for trend <0.01). Specific POPs belonging to organochlorine pesticides showed similar positive associations. CONCLUSIONS This study suggests that background exposure to organochlorine pesticides may be associated with higher risk of peripheral neuropathic complications among those with glucose abnormalities, even beyond the influence of diabetes itself.
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Affiliation(s)
- Duk-Hee Lee
- Department of Preventive Medicine and Health Promotion Research Center, School of Medicine, Kyungpook National University, Daegu, Korea.
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