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Wagenknecht LE, Divers J, Register TC, Russell GB, Bowden DW, Xu J, Langefeld CD, Lenchik L, Hruska KA, Carr JJ, Freedman BI. Bone Mineral Density and Progression of Subclinical Atherosclerosis in African-Americans With Type 2 Diabetes. J Clin Endocrinol Metab 2016; 101:4135-4141. [PMID: 27552541 PMCID: PMC5095232 DOI: 10.1210/jc.2016-1934] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [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: 01/12/2023]
Abstract
CONTEXT Relative to European Americans, calcified atherosclerotic plaque (CP) is less prevalent and severe in African-Americans (AAs). OBJECTIVE Predictors of progression of CP in the aorta, carotid, and coronary arteries were examined in AAs over a mean 5.3 ± 1.4-year interval. DESIGN This is the African American-Diabetes Heart Study. SETTING A type 2 diabetes (T2D)-affected cohort was included. PARTICIPANTS A total of 300 unrelated AAs with T2D; 50% female, mean age 55 ± 9 years, baseline hemoglobin A1c 8.1 ± 1.8% was included. MAIN OUTCOME MEASURES Glycemic control, renal parameters, vitamin D, and computed tomography-derived measures of adiposity, vascular CP, and volumetric bone mineral density (vBMD) in lumbar and thoracic vertebrae were obtained at baseline and follow-up. RESULTS CP increased in incidence and quantity/mass in all three vascular beds over the 5-year study (P < .0001). Lower baseline lumbar and thoracic vBMD were associated with progression of abdominal aorta CP (P < .008), but not progression of carotid or coronary artery CP. Lower baseline estimated glomerular filtration rate was associated with progression of carotid artery CP (P = .0004), and higher baseline pericardial adipose volume was associated with progression of coronary artery (P = .001) and aorta (P = .0006) CP independent of body mass index. There was a trend for an inverse relationship between change in thoracic vBMD and change in aortic CP (P = .05). CONCLUSIONS In this longitudinal study, lower baseline thoracic and lumbar vBMD and estimated glomerular filtration rate and higher pericardial adipose volumes were associated with increases in CP in AAs with T2D. Changes in these variables and baseline levels and/or changes in glycemic control, albuminuria, and vitamin D were not significantly associated with progression of CP.
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Affiliation(s)
- Lynne E Wagenknecht
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jasmin Divers
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Thomas C Register
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Gregory B Russell
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Donald W Bowden
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jianzhao Xu
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Carl D Langefeld
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Leon Lenchik
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Keith A Hruska
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - J Jeffrey Carr
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Barry I Freedman
- Division of Public Health Sciences (L.E.W., J.D., G.B.R., C.D.L.), Department of Pathology (T.C.R.), Department of Biochemistry (D.W.B., J.X.), and Department of Radiology (L.L.), Wake Forest School of Medicine, Winston-Salem, North Carolina; Division of Pediatric Nephrology (K.A.H.), Washington University School of Medicine, St. Louis, Missouri; Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, Tennessee; Department of Internal Medicine (B.I.F.), Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
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102
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Hsu FC, Yuan M, Bowden DW, Xu J, Smith SC, Wagenknecht LE, Langefeld CD, Divers J, Register TC, Carr JJ, Williamson JD, Sink KM, Maldjian JA, Freedman BI. Adiposity is inversely associated with hippocampal volume in African Americans and European Americans with diabetes. J Diabetes Complications 2016; 30:1506-1512. [PMID: 27615667 PMCID: PMC5050135 DOI: 10.1016/j.jdiacomp.2016.08.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 08/08/2016] [Accepted: 08/11/2016] [Indexed: 11/29/2022]
Abstract
AIMS To assess associations between body mass index (BMI), waist circumference (WC), and computed tomography-determined volumes of pericardial, visceral, and subcutaneous adipose tissue with magnetic resonance imaging-(MRI) based cerebral structure and cognitive performance in individuals with type 2 diabetes (T2D). METHODS This study was performed in 348 African Americans (AAs) and 256 European Americans (EAs) with T2D. Associations between adiposity measures with cerebral volumes of white matter (WMV), gray matter (GMV), white matter lesions, hippocampal GMV, and hippocampal WMV, cognitive performance and depression were examined using marginal models incorporating generalized estimating equations. All models were adjusted for age, sex, education, smoking, HbA1c, hypertension, statins, cardiovascular disease, MRI scanner (MRI outcomes only), and time between scans; some neuroimaging measures were additionally adjusted for intracranial volume. RESULTS Participants were 59.9% female with mean (SD) age 57.7(9.3)years, diabetes duration 9.6(6.8)years, and HbA1c 7.8(1.9)%. In AAs, inverse associations were detected between hippocampal GMV and both BMI (β [95% CI]-0.18 [-0.30, -0.07], P=0.0018) and WC (-0.23 [-0.35, -0.12], P=0.0001). In the full bi-ethnic sample, inverse associations were detected between hippocampal WMV and WC (P≤0.0001). Positive relationships were observed between BMI (P=0.0007) and WC (P<0.0001) with depression in EAs. CONCLUSIONS In patients with T2D, adiposity is inversely associated with hippocampal gray and white matter volumes.
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Affiliation(s)
- Fang-Chi Hsu
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Mingxia Yuan
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Donald W Bowden
- Centers for Genomics and Personalized Medicine Research & Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jianzhao Xu
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - S Carrie Smith
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Carl D Langefeld
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jasmin Divers
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA; Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Thomas C Register
- Department of Pathology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - J Jeffrey Carr
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeff D Williamson
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Kaycee M Sink
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Joseph A Maldjian
- Department of Radiology, Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Barry I Freedman
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA; Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
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103
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Parrinello CM, Matsushita K, Woodward M, Wagenknecht LE, Coresh J, Selvin E. Risk prediction of major complications in individuals with diabetes: the Atherosclerosis Risk in Communities Study. Diabetes Obes Metab 2016; 18:899-906. [PMID: 27161077 PMCID: PMC4993670 DOI: 10.1111/dom.12686] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Revised: 04/29/2016] [Accepted: 05/03/2016] [Indexed: 12/11/2022]
Abstract
AIMS To develop a prediction equation for 10-year risk of a combined endpoint (incident coronary heart disease, stroke, heart failure, chronic kidney disease, lower extremity hospitalizations) in people with diabetes, using demographic and clinical information, and a panel of traditional and non-traditional biomarkers. METHODS We included in the study 654 participants in the Atherosclerosis Risk in Communities (ARIC) study, a prospective cohort study, with diagnosed diabetes (visit 2; 1990-1992). Models included self-reported variables (Model 1), clinical measurements (Model 2), and glycated haemoglobin (Model 3). Model 4 tested the addition of 12 blood-based biomarkers. We compared models using prediction and discrimination statistics. RESULTS Successive stages of model development improved risk prediction. The C-statistics (95% confidence intervals) of models 1, 2, and 3 were 0.667 (0.64, 0.70), 0.683 (0.65, 0.71), and 0.694 (0.66, 0.72), respectively (p < 0.05 for differences). The addition of three traditional and non-traditional biomarkers [β-2 microglobulin, creatinine-based estimated glomerular filtration rate (eGFR), and cystatin C-based eGFR] to Model 3 significantly improved discrimination (C-statistic = 0.716; p = 0.003) and accuracy of 10-year risk prediction for major complications in people with diabetes (midpoint percentiles of lowest and highest deciles of predicted risk changed from 18-68% to 12-87%). CONCLUSIONS These biomarkers, particularly those of kidney filtration, may help distinguish between people at low versus high risk of long-term major complications.
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Affiliation(s)
- Christina M. Parrinello
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kunihiro Matsushita
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Mark Woodward
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- The George Institute for Global Health, University of Oxford, Oxford, UK
- The George Institute for Global Health, University of Sydney, New South Wales, Australia
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Josef Coresh
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Elizabeth Selvin
- Department of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
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104
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Loehr LR, Meyer ML, Poon AK, Selvin E, Palta P, Tanaka H, Pankow JS, Wright JD, Griswold ME, Wagenknecht LE, Heiss G. Prediabetes and Diabetes Are Associated With Arterial Stiffness in Older Adults: The ARIC Study. Am J Hypertens 2016; 29:1038-45. [PMID: 27068705 DOI: 10.1093/ajh/hpw036] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2015] [Accepted: 03/23/2016] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND To determine whether prediabetes and diabetes in older adults are associated with arterial stiffness measured in central and peripheral arteries and to examine characteristics that modify these associations. METHODS Cohort members attending the 5th exam (2011-2013) of the Atherosclerosis Risk in Communities (ARIC) study had pulse wave velocity (PWV) measures performed at the carotid-femoral (cfPWV), brachial-ankle (baPWV), and femoral-ankle (faPWV) segments. Fasting glucose ≥126mg/dl, glycated hemoglobin (HbA1c) ≥6.5%, or currently taking diabetes medication defined diabetes. Fasting glucose 100-125mg/dl or HbA1c 5.7%-6.4% among those without diabetes defined prediabetes. Cross-sectional associations were modeled using multivariable linear regression. RESULTS Among 4,279 eligible participants with cfPWV measures (mean age 75 years), 22% were African-American, 25.5% had diabetes, and 54.7% had prediabetes. Compared to those with normal glucose, cfPWV was 95.8cm/s higher (stiffer) on average for those with diabetes (for reference: being 1 year older was associated with 14.4cm/s higher cfPWV). Similar findings were seen for diabetes and baPWV, although attenuated. Interestingly, faPWV was 17.6cm/s lower for those with diabetes compared to normal glucose. There was a significant positive association between baPWV and prediabetes. Among those with diabetes, cfPWV was higher for those with albuminuria, reduced kidney function, duration of diabetes ≥10 years, and elevated HbA1c (HbA1c ≥7). CONCLUSION Among older adults, diabetes is associated with higher central arterial stiffness and lower peripheral arterial stiffness, and prediabetes is associated with higher baPWV. Cross-sectionally, the magnitude of the effect of diabetes on central stiffness is equivalent to 6 years of arterial aging.
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Affiliation(s)
- Laura R Loehr
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA;
| | - Michelle L Meyer
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Anna K Poon
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Priya Palta
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | | | - Jacqueline D Wright
- National Institutes of Health, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA
| | | | | | - Gerardo Heiss
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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105
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Yuan M, Hsu FC, Bowden DW, Xu J, Smith SC, Wagenknecht LE, Comeau ME, Divers J, Register TC, Carr JJ, Langefeld CD, Freedman BI. Relationships between measures of adiposity with subclinical atherosclerosis in patients with type 2 diabetes. Obesity (Silver Spring) 2016; 24:1810-8. [PMID: 27356020 PMCID: PMC4963287 DOI: 10.1002/oby.21540] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Revised: 04/06/2016] [Accepted: 04/06/2016] [Indexed: 01/21/2023]
Abstract
OBJECTIVE Assess cross-sectional relationships between body mass index (BMI), waist circumference (WC), pericardial (PAT), visceral (VAT), and subcutaneous adipose tissue (SAT) volumes with calcified plaque (CP) in African Americans (AAs) and European Americans (EAs) with type 2 diabetes. METHODS Computed tomography measured PAT, VAT, SAT, and CP in coronary arteries (CAC), carotid arteries, and aorta. Generalized estimating equations models were fitted to test for associations between adiposity and CP, stratified by ethnicity while accounting for familial correlations. RESULTS AAs (N = 753) vs. EAs (N = 562) had significantly lower PAT and VAT, despite equal or higher BMI. In multivariable models adjusting for age, gender, education, HbA1c, statins, smoking, cardiovascular disease, hypertension, nephropathy, and C-reactive protein, PAT positively associated with presence of CAC in AAs (P < 0.001), not EAs (P = 0.68; ethnicity interaction P < 0.01). Inverse associations were detected between SAT and severity of aorta CP (P < 0.01) in AAs and between BMI, WC, and SAT with severity of aorta CP in all participants. CONCLUSIONS Ethnic- and gender-specific differences in BMI, WC, PAT, SAT, and VAT were present in AAs and EAs with diabetes. Only PAT was positively associated with CAC in AAs; paradoxical inverse associations were seen between several other adiposity measures and subclinical cardiovascular disease.
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Affiliation(s)
- Mingxia Yuan
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Centers for Genomics and Personalized Medicine Research & Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Fang-Chi Hsu
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Donald W. Bowden
- Centers for Genomics and Personalized Medicine Research & Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Jianzhao Xu
- Centers for Genomics and Personalized Medicine Research & Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - S. Carrie Smith
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Mary E. Comeau
- Centers for Genomics and Personalized Medicine Research & Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Jasmin Divers
- Centers for Genomics and Personalized Medicine Research & Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Thomas C. Register
- Department of Pathology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - J. Jeffrey Carr
- Department of Radiology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Carl D. Langefeld
- Centers for Genomics and Personalized Medicine Research & Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Barry I. Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Centers for Genomics and Personalized Medicine Research & Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
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106
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Keaton JM, Hellwege JN, Ng MCY, Palmer ND, Pankow JS, Fornage M, Wilson JG, Correa A, Rasmussen-Torvik LJ, Rotter JI, Chen YDI, Taylor KD, Rich SS, Wagenknecht LE, Freedman BI, Bowden DW. Genome-Wide Interaction with Insulin Secretion Loci Reveals Novel Loci for Type 2 Diabetes in African Americans. PLoS One 2016; 11:e0159977. [PMID: 27448167 PMCID: PMC4957757 DOI: 10.1371/journal.pone.0159977] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [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] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 07/11/2016] [Indexed: 11/18/2022] Open
Abstract
Type 2 diabetes (T2D) is the result of metabolic defects in insulin secretion and insulin sensitivity, yet most T2D loci identified to date influence insulin secretion. We hypothesized that T2D loci, particularly those affecting insulin sensitivity, can be identified through interaction with insulin secretion loci. To test this hypothesis, single nucleotide polymorphisms (SNPs) associated with acute insulin response to glucose (AIRg), a dynamic measure of first-phase insulin secretion, were identified in African Americans from the Insulin Resistance Atherosclerosis Family Study (IRASFS; n = 492 subjects). These SNPs were tested for interaction, individually and jointly as a genetic risk score (GRS), using genome-wide association study (GWAS) data from five cohorts (ARIC, CARDIA, JHS, MESA, WFSM; n = 2,725 cases, 4,167 controls) with T2D as the outcome. In single variant analyses, suggestively significant (Pinteraction<5×10-6) interactions were observed at several loci including LYPLAL1 (rs10746381), CHN2 (rs7796525), and EXOC1 (rs4289500). Notable AIRg GRS interactions were observed with SAMD4A (rs11627203) and UTRN (rs17074194). These data support the hypothesis that additional genetic factors contributing to T2D risk can be identified by interactions with insulin secretion loci.
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Affiliation(s)
- Jacob M. Keaton
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Jacklyn N. Hellwege
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Maggie C. Y. Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Nicholette D. Palmer
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Myriam Fornage
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - James G. Wilson
- University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Adolfo Correa
- University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Yii-Der I. Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Lynne E. Wagenknecht
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Barry I. Freedman
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Internal Medicine - Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Donald W. Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
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107
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Liu CT, Raghavan S, Maruthur N, Kabagambe EK, Hong J, Ng MCY, Hivert MF, Lu Y, An P, Bentley AR, Drolet AM, Gaulton KJ, Guo X, Armstrong LL, Irvin MR, Li M, Lipovich L, Rybin DV, Taylor KD, Agyemang C, Palmer ND, Cade BE, Chen WM, Dauriz M, Delaney JAC, Edwards TL, Evans DS, Evans MK, Lange LA, Leong A, Liu J, Liu Y, Nayak U, Patel SR, Porneala BC, Rasmussen-Torvik LJ, Snijder MB, Stallings SC, Tanaka T, Yanek LR, Zhao W, Becker DM, Bielak LF, Biggs ML, Bottinger EP, Bowden DW, Chen G, Correa A, Couper DJ, Crawford DC, Cushman M, Eicher JD, Fornage M, Franceschini N, Fu YP, Goodarzi MO, Gottesman O, Hara K, Harris TB, Jensen RA, Johnson AD, Jhun MA, Karter AJ, Keller MF, Kho AN, Kizer JR, Krauss RM, Langefeld CD, Li X, Liang J, Liu S, Lowe WL, Mosley TH, North KE, Pacheco JA, Peyser PA, Patrick AL, Rice KM, Selvin E, Sims M, Smith JA, Tajuddin SM, Vaidya D, Wren MP, Yao J, Zhu X, Ziegler JT, Zmuda JM, Zonderman AB, Zwinderman AH, Adeyemo A, Boerwinkle E, Ferrucci L, Hayes MG, Kardia SLR, Miljkovic I, Pankow JS, Rotimi CN, Sale MM, Wagenknecht LE, Arnett DK, Chen YDI, Nalls MA, Province MA, Kao WHL, Siscovick DS, Psaty BM, Wilson JG, Loos RJF, Dupuis J, Rich SS, Florez JC, Rotter JI, Morris AP, Meigs JB. Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin. Am J Hum Genet 2016; 99:56-75. [PMID: 27321945 PMCID: PMC5005440 DOI: 10.1016/j.ajhg.2016.05.006] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 05/02/2016] [Indexed: 12/11/2022] Open
Abstract
Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.
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Affiliation(s)
- Ching-Ti Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA.
| | - Sridharan Raghavan
- Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA; Department of Veterans Affairs Medical Center, Eastern Colorado Health Care System, Denver, CO 80220, USA; Division of General Internal Medicine, Department of Medicine, University of Colorado School of Medicine, Denver, CO 80220, USA
| | - Nisa Maruthur
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD 21287, USA; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Edmond Kato Kabagambe
- Division of Epidemiology, Department of Medicine, School of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Jaeyoung Hong
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Center for Diabetes Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA 02215, USA; Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Universite de Sherbrooke, Sherbrooke, QC J1G 0A2, Canada
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ping An
- Division of Statistical Genomics, Department of Genetics, School of Medicine, Washington University, St Louis, MO 63108, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Anne M Drolet
- Center for Molecular Medicine and Genetics, School of Medicine, Wayne State University, Detroit, MI 48201, USA
| | - Kyle J Gaulton
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Loren L Armstrong
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama - Birmingham, Birmingham, AL 35294, USA
| | - Man Li
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Leonard Lipovich
- Center for Molecular Medicine and Genetics, School of Medicine, Wayne State University, Detroit, MI 48201, USA; Department of Neurology, School of Medicine, Wayne State University, Detroit, MI 48201, USA
| | - Denis V Rybin
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Charles Agyemang
- Department of Public Health, Academic Medical Center Amsterdam, Meibergdreef 15, 1105 AZ Amsterdam, the Netherlands
| | - Nicholette D Palmer
- Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Marco Dauriz
- Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, University of Verona, 37126 Verona, Italy
| | - Joseph A C Delaney
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine, School of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA 94107, USA
| | - Michele K Evans
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Leslie A Lange
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27607, USA
| | - Aaron Leong
- Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Jingmin Liu
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Yongmei Liu
- Center for Human Genetics, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Uma Nayak
- Center for Public Health Genomics, Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Sanjay R Patel
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Bianca C Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Marieke B Snijder
- Department of Public Health, Academic Medical Center Amsterdam, Meibergdreef 15, 1105 AZ Amsterdam, the Netherlands
| | - Sarah C Stallings
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute of Aging at Harbor Hospital, Baltimore, MD 21225, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Diane M Becker
- GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA; Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Mary L Biggs
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; Cardiovascular Health Research Unit, Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Center for Diabetes Research, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - David J Couper
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Dana C Crawford
- Department of Epidemiology and Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Mary Cushman
- Department of Medicine and Pathology, University of Vermont, College of Medicine, Burlington, VT 05405, USA
| | - John D Eicher
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA; Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Framingham, MA 01702, USA
| | - Myriam Fornage
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Yi-Ping Fu
- Cardiovascular Epidemiology and Human Genomics Branch, National Heart, Lung, and Blood Institute, NIH, Framingham, MA 01702, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes & Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Omri Gottesman
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kazuo Hara
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan; Department of Diabetes, Endocrinology, and Metabolism, Tokyo Medical University, Tokyo 163-0023, Japan
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, NIH, Bethesda, MD 20892, USA
| | - Richard A Jensen
- Cardiovascular Health Research Unit, Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Andrew D Johnson
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, NIH, Framingham, MA 01702, USA
| | - Min A Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Andrew J Karter
- Division of Research, Kaiser Permanente, Northern California Region, Oakland, CA 94612, USA
| | - Margaux F Keller
- Department of Genetics and Pharmacogenomics, Merck Research Laboratories, 33 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Abel N Kho
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Jorge R Kizer
- Department of Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY 10461, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Ronald M Krauss
- Children's Hospital Oakland Research Institute, Oakland, CA 94609, USA
| | - Carl D Langefeld
- Center for Public Health Genomics, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Xiaohui Li
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jingling Liang
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Simin Liu
- Department of Epidemiology, Brown University, Providence, RI 02912, USA; Department of Medicine, Brown University, Providence, RI 02903, USA
| | - William L Lowe
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Thomas H Mosley
- Division of Geriatrics/Gerontology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Jennifer A Pacheco
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Alan L Patrick
- Tobago Health Studies Office, Scarborough, Tobago, Trinidad and Tobago
| | - Kenneth M Rice
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Elizabeth Selvin
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD 21287, USA; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Mario Sims
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Salman M Tajuddin
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Dhananjay Vaidya
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA; GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Mary P Wren
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Julie T Ziegler
- Center for Public Health Genomics, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA; Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Joseph M Zmuda
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Alan B Zonderman
- Behavioral Epidemiology Section, Laboratory of Epidemiology & Population Science, Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD 21224, US
| | - Aeilko H Zwinderman
- Department of Public Health, Academic Medical Center Amsterdam, Meibergdreef 15, 1105 AZ Amsterdam, the Netherlands
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Eric Boerwinkle
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute of Aging at Harbor Hospital, Baltimore, MD 21225, USA
| | - M Geoffrey Hayes
- Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Iva Miljkovic
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Michele M Sale
- Center for Public Health Genomics, Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Donna K Arnett
- University of Kentucky College of Public Health, Lexington, KY 40563, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Michael A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD 20892, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, School of Medicine, Washington University, St Louis, MO 63108, USA
| | - W H Linda Kao
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - David S Siscovick
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Cardiovascular Health Research Unit, Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, USA; The New York Academy of Medicine, New York, NY 10029, USA
| | - Bruce M Psaty
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Cardiovascular Health Research Unit, Department of Medicine, School of Medicine, University of Washington, Seattle, WA 98195, USA; Department of Health Services, University of Washington, Seattle, WA 98195, USA; Group Health Research Institute, Group Health Cooperative, Seattle, WA 98101, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Josée Dupuis
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA; National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Jose C Florez
- Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114, USA; Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA; Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Andrew P Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK; Institute of Translational Medicine, Department of Biostatistics, University of Liverpool, Liverpool L69 3BX, UK
| | - James B Meigs
- Division of General Internal Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
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Palmer ND, Wagenknecht LE, Langefeld CD, Wang N, Buchanan TA, Xiang AH, Allayee H, Bergman RN, Raffel LJ, Chen YDI, Haritunians T, Fingerlin T, Goodarzi MO, Taylor KD, Rotter JI, Watanabe RM, Bowden DW. Improved Performance of Dynamic Measures of Insulin Response Over Surrogate Indices to Identify Genetic Contributors of Type 2 Diabetes: The GUARDIAN Consortium. Diabetes 2016; 65:2072-80. [PMID: 27207554 PMCID: PMC4915581 DOI: 10.2337/db15-1543] [Citation(s) in RCA: 3] [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] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Accepted: 04/09/2016] [Indexed: 01/24/2023]
Abstract
Type 2 diabetes (T2D) is a heterogeneous disorder with contributions from peripheral insulin resistance and β-cell dysfunction. For minimization of phenotypic heterogeneity, quantitative intermediate phenotypes characterizing basal glucose homeostasis (insulin resistance and HOMA of insulin resistance [HOMAIR] and of β-cell function [HOMAB]) have shown promise in relatively large samples. We investigated the utility of dynamic measures of glucose homeostasis (insulin sensitivity [SI] and acute insulin response [AIRg]) evaluating T2D-susceptibility variants (n = 57) in Hispanic Americans from the GUARDIAN Consortium (n = 2,560). Basal and dynamic measures were genetically correlated (HOMAB-AIRg: ρG = 0.28-0.73; HOMAIR-SI: ρG = -0.73 to -0.83) with increased heritability for the dynamic measure AIRg Significant association of variants with dynamic measures (P < 8.77 × 10(-4)) was observed. A pattern of superior performance of AIRg was observed for well-established loci including MTNR1B (P = 9.46 × 10(-12)), KCNQ1 (P = 1.35 × 10(-4)), and TCF7L2 (P = 5.10 × 10(-4)) with study-wise statistical significance. Notably, significant association of MTNR1B with AIRg (P < 1.38 × 10(-9)) was observed in a population one-fourteenth the size of the initial discovery cohort. These observations suggest that basal and dynamic measures provide different views and levels of sensitivity to discrete elements of glucose homeostasis. Although more costly to obtain, dynamic measures yield significant results that could be considered physiologically "closer" to causal pathways and provide insight into the discrete mechanisms of action.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Carl D Langefeld
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Nan Wang
- Department of Preventative Medicine, Keck School of Medicine of USC, Los Angeles, CA Department of Physiology and Biophysics, Keck School of Medicine of USC, Los Angeles, CA
| | - Thomas A Buchanan
- Department of Physiology and Biophysics, Keck School of Medicine of USC, Los Angeles, CA Department of Medicine, Keck School of Medicine of USC, Los Angeles, CA
| | - Anny H Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA
| | - Hooman Allayee
- Department of Preventative Medicine, Keck School of Medicine of USC, Los Angeles, CA
| | - Richard N Bergman
- Department of Physiology and Biophysics, Keck School of Medicine of USC, Los Angeles, CA
| | - Leslie J Raffel
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA
| | - Talin Haritunians
- F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Tasha Fingerlin
- Department of Epidemiology, University of Colorado Denver, Aurora, CO Department of Biostatistics and Informatics, University of Colorado Denver, Aurora, CO
| | - Mark O Goodarzi
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Kent D Taylor
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA
| | - Richard M Watanabe
- Department of Preventative Medicine, Keck School of Medicine of USC, Los Angeles, CA Department of Physiology and Biophysics, Keck School of Medicine of USC, Los Angeles, CA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
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Gottesman RF, Schneider ALC, Zhou Y, Chen X, Green E, Gupta N, Knopman DS, Mintz A, Rahmim A, Sharrett AR, Wagenknecht LE, Wong DF, Mosley TH. The ARIC-PET amyloid imaging study: Brain amyloid differences by age, race, sex, and APOE. Neurology 2016; 87:473-80. [PMID: 27371485 DOI: 10.1212/wnl.0000000000002914] [Citation(s) in RCA: 114] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Accepted: 03/11/2016] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To evaluate differences in amyloid deposition in a community-based cohort without dementia by age, sex, race, education, and APOE ε4 allele status. METHODS Recruited from the longitudinal Atherosclerosis Risk in Communities study, 329 participants without dementia, ages 67-88 years, were imaged using florbetapir PET at 3 US community sites (Washington County, Maryland; Forsyth County, North Carolina; and Jackson, Mississippi). Standardized uptake value ratios (SUVRs) were calculated; global cortical SUVR >1.2 was evaluated as the primary outcome. Age, race, sex, education level, and number of APOE ε4 alleles were evaluated in multivariable models including vascular risk factors, brain white matter hyperintensity and total intracranial volume, and cognitive status. RESULTS A total of 141 of the participants (43%) were black. In multivariable models, odds of elevated SUVR was increased in participants with increasing age (odds ratio [OR] 1.63, 95% confidence interval [CI] 1.01-2.65 per 10 years of age) and black race (OR 2.08, 95% CI 1.23-3.51) but did not differ by educational level. Each ε4 allele was associated with increased odds of elevated SUVR (OR 2.65, 95% CI 1.61-4.39). CONCLUSIONS In this community-based cohort without dementia, florbetapir uptake is associated with older age and APOE genotype. Black race was associated with higher SUVR, after adjusting for demographics, vascular risk factors, cognitive status, white matter hyperintensity volume, and APOE genotype, with effect sizes nearing those seen for APOE ε4. Replication of these findings is needed in other cohorts, and reasons for and consequences of these observed differences by race warrant further study.
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Affiliation(s)
- Rebecca F Gottesman
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC.
| | - Andrea L C Schneider
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Yun Zhou
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Xueqi Chen
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Edward Green
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Naresh Gupta
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - David S Knopman
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Akiva Mintz
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Arman Rahmim
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - A Richey Sharrett
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Lynne E Wagenknecht
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Dean F Wong
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Thomas H Mosley
- From the Department of Neurology (R.F.G., A.L.C.S.), Department of Radiology, Section of High-Resolution Brain PET Imaging (Y.Z., X.C., A.R., D.F.W.), and Departments of Psychiatry (D.F.W.) and Neuroscience (D.F.W.), Johns Hopkins University School of Medicine; Departments of Epidemiology (R.F.G., A.L.C.S., A.R.S.) and Environmental Health Sciences (D.F.W.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Departments of Radiology (E.G.) and Medicine (T.H.M.), University of Mississippi Medical Center, Jackson; Hagerstown Imaging (N.G.), MD; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and Department of Radiology (A.M.) and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, NC
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Hughes TM, Wagenknecht LE, Coker L, Heiss G, Wong DF, Zhou Y, Mosley TH, Gottesman RF. IC‐P‐125: Arterial Stiffness and β‐Amyloid Deposition in The ARIC‐PET Study. Alzheimers Dement 2016. [DOI: 10.1016/j.jalz.2016.06.155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
| | | | | | - Gerardo Heiss
- School of Public Health, University of North Carolina at Chapel HillChapel HillNC USA
| | - Dean F. Wong
- Johns Hopkins University School of MedicineBaltimoreMD USA
| | - Yun Zhou
- Johns Hopkins UniversityBaltimoreMD USA
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111
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Palmer ND, Divers J, Lu L, Register TC, Carr JJ, Hicks PJ, Smith SC, Xu J, Judd SE, Irvin MR, Gutierrez OM, Bowden DW, Wagenknecht LE, Langefeld CD, Freedman BI. Admixture mapping of serum vitamin D and parathyroid hormone concentrations in the African American-Diabetes Heart Study. Bone 2016; 87:71-7. [PMID: 27032714 PMCID: PMC4862915 DOI: 10.1016/j.bone.2016.01.028] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2015] [Revised: 11/17/2015] [Accepted: 01/19/2016] [Indexed: 10/22/2022]
Abstract
Vitamin D and intact parathyroid hormone (iPTH) concentrations differ between individuals of African and European descent and may play a role in observed racial differences in bone mineral density (BMD). These findings suggest that mapping by admixture linkage disequilibrium (MALD) may be informative for identifying genetic variants contributing to these ethnic disparities. Admixture mapping was performed for serum 25-hydroxyvitamin D, 1,25-dihydroxyvitamin D, vitamin D-binding protein (VDBP), bioavailable vitamin D, and iPTH concentrations and computed tomography measured thoracic and lumbar vertebral volumetric BMD in 552 unrelated African Americans with type 2 diabetes from the African American-Diabetes Heart Study. Genotyping was performed using a custom Illumina ancestry informative marker (AIM) panel. For each AIM, the probability of inheriting 0, 1, or 2 copies of a European-derived allele was determined. Non-parametric linkage analysis was performed by testing for association between each AIM using these probabilities among phenotypes, accounting for global ancestry, age, and gender. Fine-mapping of MALD peaks was facilitated by genome-wide association study (GWAS) data. VDBP levels were significantly linked in proximity to the protein coding locus (rs7689609, LOD=11.05). Two loci exhibited significant linkage signals for 1,25-dihydroxyvitamin D on 13q21.2 (rs1622710, LOD=3.20) and 12q13.2 (rs11171526, LOD=3.10). iPTH was significantly linked on 9q31.3 (rs7854368, LOD=3.14). Fine-mapping with GWAS data revealed significant known (rs7041 with VDBP, P=1.38×10(-82)) and novel (rs12741813 and rs10863774 with VDBP, P<6.43×10(-5)) loci with plausible biological roles. Admixture mapping in combination with fine-mapping has focused efforts to identify loci contributing to ethnic differences in vitamin D-related traits.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Center for Diabetes Research, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Center for Public Health Genomics, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - Jasmin Divers
- Center for Public Health Genomics, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Department of Biostatistical Sciences, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - Lingyi Lu
- Center for Public Health Genomics, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Department of Biostatistical Sciences, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - Thomas C Register
- Department of Pathology, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - J Jeffrey Carr
- Department of Radiology, Vanderbilt University School of Medicine, 2525 West End Ave, Suite 300-B, Nashville, TN 37203, USA.
| | - Pamela J Hicks
- Department of Biochemistry, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - S Carrie Smith
- Department of Biochemistry, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - Jianzhao Xu
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - Suzanne E Judd
- Department of Biostatistics, University of Alabama at Birmingham, 1665 University Boulevard, Birmingham, AL 35294, USA.
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, 1665 University Boulevard, Birmingham, AL 35294, USA.
| | - Orlando M Gutierrez
- Department of Epidemiology, University of Alabama at Birmingham, 1665 University Boulevard, Birmingham, AL 35294, USA; Department of Medicine, University of Alabama at Birmingham, 1665 University Boulevard, Birmingham, AL, 35294, USA.
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Center for Diabetes Research, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - Carl D Langefeld
- Center for Public Health Genomics, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Department of Biostatistical Sciences, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
| | - Barry I Freedman
- Center for Diabetes Research, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Center for Public Health Genomics, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA; Department of Internal Medicine-Section on Nephrology, Wake Forest School of Medicine, 1 Medical Center Blvd, Winston-Salem, NC 27157, USA.
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112
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Lee CC, Watkins SM, Lorenzo C, Wagenknecht LE, Il'yasova D, Chen YDI, Haffner SM, Hanley AJ. Branched-Chain Amino Acids and Insulin Metabolism: The Insulin Resistance Atherosclerosis Study (IRAS). Diabetes Care 2016; 39:582-8. [PMID: 26895884 PMCID: PMC4806771 DOI: 10.2337/dc15-2284] [Citation(s) in RCA: 107] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2015] [Accepted: 01/30/2016] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Recent studies using untargeted metabolomics approaches have suggested that plasma branched-chain amino acids (BCAAs) are associated with incident diabetes. However, little is known about the role of plasma BCAAs in metabolic abnormalities underlying diabetes and whether these relationships are consistent across ethnic populations at high risk for diabetes. We investigated the associations of BCAAs with insulin sensitivity (SI), acute insulin response (AIR), and metabolic clearance of insulin (MCRI) in a multiethnic cohort. RESEARCH DESIGN AND METHODS In 685 participants without diabetes of the Insulin Resistance Atherosclerosis Study (IRAS) (290 Caucasians, 165 African Americans, and 230 Hispanics), we measured plasma BCAAs (sum of valine, leucine, and isoleucine) by mass spectrometry and SI, AIR, and MCRI by frequently sampled intravenous glucose tolerance tests. RESULTS Elevated plasma BCAAs were inversely associated with SI and MCRI and positively associated with fasting insulin in regression models adjusted for potential confounders (β = -0.0012 [95% CI -0.0018, -0.00059], P < 0.001 for SI; β = -0.0013 [95% CI -0.0018, -0.00082], P < 0.001 for MCRI; and β = 0.0015 [95% CI 0.0008, 0.0023], P < 0.001 for fasting insulin). The association of BCAA with SI was significantly modified by ethnicity, with the association only being significant in Caucasians and Hispanics. Elevated plasma BCAAs were associated with incident diabetes in Caucasians and Hispanics (multivariable-adjusted odds ratio per 1-SD increase in plasma BCAAs: 1.67 [95% CI 1.21, 2.29], P = 0.002) but not in African Americans. Plasma BCAAs were not associated with SI-adjusted AIR. CONCLUSIONS Plasma BCAAs are associated with incident diabetes and underlying metabolic abnormalities, although the associations were generally stronger in Caucasians and Hispanics.
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Affiliation(s)
- C Christine Lee
- Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Steve M Watkins
- Lipomics Technologies, Inc., a division of Metabolon, Inc., West Sacramento, CA
| | - Carlos Lorenzo
- Division of Clinical Epidemiology, University of Texas Health Science Center, San Antonio, TX
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Dora Il'yasova
- School of Public Health, Georgia State University, Atlanta, GA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Torrance, CA
| | | | - Anthony J Hanley
- Department of Nutritional Sciences, University of Toronto, Toronto, ON, Canada Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, ON, Canada
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Freedman BI, Divers J, Russell GB, Palmer ND, Bowden DW, Carr JJ, Wagenknecht LE, Hightower RC, Xu J, Smith SC, Langefeld CD, Hruska KA, Register TC. Plasma FGF23 and Calcified Atherosclerotic Plaque in African Americans with Type 2 Diabetes Mellitus. Am J Nephrol 2015; 42:391-401. [PMID: 26693712 DOI: 10.1159/000443241] [Citation(s) in RCA: 23] [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] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Accepted: 12/06/2015] [Indexed: 12/16/2022]
Abstract
BACKGROUND Fibroblast growth factor 23 (FGF23) is a phosphaturic hormone implicated in disorders of serum phosphorus concentration and vitamin D. The role of FGF23 in vascular calcification remains controversial. METHODS Relationships between FGF23 and coronary artery calcified atherosclerotic plaque (CAC), aortoiliac calcified plaque (CP), carotid artery CP, volumetric bone mineral density (vBMD), albuminuria, and estimated glomerular filtration rate (eGFR) were determined in 545 African Americans with type 2 diabetes (T2D) and preserved kidney function in African American-Diabetes Heart Study participants. Generalized linear models were fitted to test associations between FGF23 and cardiovascular, bone, and renal phenotypes, and change in measurements over time, adjusting for age, gender, African ancestry proportion, body mass index, diabetes duration, hemoglobin A1c, blood pressure, renin-angiotensin-system inhibitors, statins, calcium supplements, serum calcium, and serum phosphate. RESULTS The sample was 56.7% female with a mean (SD) age of 55.6 (9.6) years, diabetes duration of 10.3 (8.2) years, eGFR 90.9 (22.1) ml/min/1.73 m2, urine albumin:creatinine ratio (UACR) 151 (588) (median 13) mg/g, plasma FGF23 161 (157) RU/ml, and CAC 637 (1,179) mg. In fully adjusted models, FGF23 was negatively associated with eGFR (p < 0.0001) and positively associated with UACR (p < 0.0001) and CAC (p = 0.0006), but not with carotid CP or aortic CP. Baseline FGF23 concentration did not associate with changes in vBMD or CAC after a mean of 5.1 years follow-up. CONCLUSIONS Plasma FGF23 concentrations were independently associated with subclinical coronary artery disease, albuminuria, and kidney function in the understudied African American population with T2D. Findings support relationships between FGF23 and vascular calcification, but not between FGF23 and bone mineral density, in African Americans lacking advanced nephropathy.
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Affiliation(s)
- Barry I Freedman
- Department of Internal Medicine, Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, N.C., USA
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Papandonatos GD, Pan Q, Pajewski NM, Delahanty LM, Peter I, Erar B, Ahmad S, Harden M, Chen L, Fontanillas P, Wagenknecht LE, Kahn SE, Wing RR, Jablonski KA, Huggins GS, Knowler WC, Florez JC, McCaffery JM, Franks PW. Genetic Predisposition to Weight Loss and Regain With Lifestyle Intervention: Analyses From the Diabetes Prevention Program and the Look AHEAD Randomized Controlled Trials. Diabetes 2015; 64:4312-21. [PMID: 26253612 PMCID: PMC4657576 DOI: 10.2337/db15-0441] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [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: 03/31/2015] [Accepted: 08/04/2015] [Indexed: 12/22/2022]
Abstract
Clinically relevant weight loss is achievable through lifestyle modification, but unintentional weight regain is common. We investigated whether recently discovered genetic variants affect weight loss and/or weight regain during behavioral intervention. Participants at high-risk of type 2 diabetes (Diabetes Prevention Program [DPP]; N = 917/907 intervention/comparison) or with type 2 diabetes (Look AHEAD [Action for Health in Diabetes]; N = 2,014/1,892 intervention/comparison) were from two parallel arm (lifestyle vs. comparison) randomized controlled trials. The associations of 91 established obesity-predisposing loci with weight loss across 4 years and with weight regain across years 2-4 after a minimum of 3% weight loss were tested. Each copy of the minor G allele of MTIF3 rs1885988 was consistently associated with greater weight loss following lifestyle intervention over 4 years across the DPP and Look AHEAD. No such effect was observed across comparison arms, leading to a nominally significant single nucleotide polymorphism×treatment interaction (P = 4.3 × 10(-3)). However, this effect was not significant at a study-wise significance level (Bonferroni threshold P < 5.8 × 10(-4)). Most obesity-predisposing gene variants were not associated with weight loss or regain within the DPP and Look AHEAD trials, directly or via interactions with lifestyle.
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Affiliation(s)
| | - Qing Pan
- The Biostatistics Center, George Washington University, Rockville, MD
| | - Nicholas M Pajewski
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Linda M Delahanty
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Bahar Erar
- Center for Statistical Sciences, Brown University, Providence, RI
| | - Shafqat Ahmad
- Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University, Skåne University Hospital Malmö, Malmö, Sweden
| | | | - Ling Chen
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Pierre Fontanillas
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | | | - Lynne E Wagenknecht
- Look AHEAD Coordinating Center, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Steven E Kahn
- Division of Metabolism, Endocrinology & Nutrition, Department of Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, WA
| | - Rena R Wing
- Weight Control and Diabetes Research Center, The Miriam Hospital and The Warren Alpert Medical School of Brown University, Providence, RI
| | | | - Gordon S Huggins
- Center for Translational Genomics, Molecular Cardiology Research Institute, Tufts Medical Center, Boston, MA
| | - William C Knowler
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Jose C Florez
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Jeanne M McCaffery
- Weight Control and Diabetes Research Center, The Miriam Hospital and The Warren Alpert Medical School of Brown University, Providence, RI
| | - Paul W Franks
- Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, Lund University, Skåne University Hospital Malmö, Malmö, Sweden Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
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Gao C, Wang N, Guo X, Ziegler JT, Taylor KD, Xiang AH, Hai Y, Kridel SJ, Nadler JL, Kandeel F, Raffel LJ, Chen YDI, Norris JM, Rotter JI, Watanabe RM, Wagenknecht LE, Bowden DW, Speliotes EK, Goodarzi MO, Langefeld CD, Palmer ND. A Comprehensive Analysis of Common and Rare Variants to Identify Adiposity Loci in Hispanic Americans: The IRAS Family Study (IRASFS). PLoS One 2015; 10:e0134649. [PMID: 26599207 PMCID: PMC4658008 DOI: 10.1371/journal.pone.0134649] [Citation(s) in RCA: 18] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Accepted: 07/10/2015] [Indexed: 11/18/2022] Open
Abstract
Obesity is growing epidemic affecting 35% of adults in the United States. Previous genome-wide association studies (GWAS) have identified numerous loci associated with obesity. However, the majority of studies have been completed in Caucasians focusing on total body measures of adiposity. Here we report the results from genome-wide and exome chip association studies focusing on total body measures of adiposity including body mass index (BMI), percent body fat (PBF) and measures of fat deposition including waist circumference (WAIST), waist-hip ratio (WHR), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) in Hispanic Americans (nmax = 1263) from the Insulin Resistance Atherosclerosis Family Study (IRASFS). Five SNPs from two novel loci attained genome-wide significance (P<5.00x10-8) in IRASFS. A missense SNP in the isocitrate dehydrogenase 1 gene (IDH1) was associated with WAIST (rs34218846, MAF = 6.8%, PDOM = 1.62x10-8). This protein is postulated to play an important role in fat and cholesterol biosynthesis as demonstrated in cell and knock-out animal models. Four correlated intronic SNPs in the Zinc finger, GRF-type containing 1 gene (ZGRF1; SNP rs1471880, MAF = 48.1%, PDOM = 1.00x10-8) were strongly associated with WHR. The exact biological function of ZGRF1 and the connection with adiposity remains unclear. SNPs with p-values less than 5.00x10-6 from IRASFS were selected for replication. Meta-analysis was computed across seven independent Hispanic-American cohorts (nmax = 4156) and the strongest signal was rs1471880 (PDOM = 8.38x10-6) in ZGRF1 with WAIST. In conclusion, a genome-wide and exome chip association study was conducted that identified two novel loci (IDH1 and ZGRF1) associated with adiposity. While replication efforts were inconclusive, when taken together with the known biology, IDH1 and ZGRF1 warrant further evaluation.
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Affiliation(s)
- Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Nan Wang
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, California, United States of America
- Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, California, United States of America
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Julie T. Ziegler
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Anny H. Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, United States of America
| | - Yang Hai
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Steven J. Kridel
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Jerry L. Nadler
- Department of Internal Medicine, Strelitz Diabetes Center, Eastern Virginia Medical School, Norfolk, Virginia, United States of America
| | - Fouad Kandeel
- Department of Diabetes and Metabolic Diseases Research, Beckman Research Institute of City of Hope, Duarte, California, United States of America
| | - Leslie J. Raffel
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Yii-Der I. Chen
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Jill M. Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado, United States of America
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Richard M. Watanabe
- Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, California, United States of America
- Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, California, United States of America
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Donald W. Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Elizabeth K. Speliotes
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Mark O. Goodarzi
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
- Division of Endocrinology, Diabetes, and Metabolism, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Carl D. Langefeld
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Nicholette D. Palmer
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- * E-mail:
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Dearborn JL, Schneider ALC, Sharrett AR, Mosley TH, Bezerra DC, Knopman DS, Selvin E, Jack CR, Coker LH, Alonso A, Wagenknecht LE, Windham BG, Gottesman RF. Obesity, Insulin Resistance, and Incident Small Vessel Disease on Magnetic Resonance Imaging: Atherosclerosis Risk in Communities Study. Stroke 2015; 46:3131-6. [PMID: 26451022 DOI: 10.1161/strokeaha.115.010060] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2015] [Accepted: 08/26/2015] [Indexed: 12/29/2022]
Abstract
BACKGROUND AND PURPOSE The term metabolic syndrome describes the clustering of risk factors found in many individuals with obesity. Because of their pathophysiology, we hypothesized that 2 features of metabolic syndrome, central obesity and insulin resistance (IR), would be associated with cerebrovascular changes on magnetic resonance imaging, and specifically with incident lacunar disease and not white matter hyperintensity (WMH) progression. METHODS Risk factors were defined at study baseline in 934 participants in the Atherosclerosis Risk in Communities (ARIC) study, who completed 2 brain magnetic resonance imagings≈10 years apart. WMH progression and incident lacunes between the 2 magnetic resonance imagings were determined. An IR score for each participant was created using principal component analysis of 11 risk factors, including (among others): insulin, homeostatic model assessment-IR, body mass index, and waist circumference. Metabolic syndrome (presence/absence), using standard clinical definitions, and IR score at the first magnetic resonance imaging, were independent variables, evaluated in multivariate logistic regression to determine odds of WMH progression (Q5 versus Q1-Q4) and incident lacunes. RESULTS Metabolic syndrome (adjusted odds ratio, 1.98; 95% confidence interval, 1.28-3.05) and IR score (adjusted odds ratio per 1-SD increase, 1.33; 95% confidence interval, 1.05-1.68) were associated with incident lacunes but not with WMH progression. Insulin, homeostatic model assessment-IR, and body mass index were not associated with incident lacunes or WMH progression in separate models. CONCLUSIONS The IR score and central obesity are associated with incident lacunar disease but not WMH progression in individuals. Central obesity and IR may be important risk factors to target to prevent lacunar disease.
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Affiliation(s)
- Jennifer L Dearborn
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Andrea L C Schneider
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - A Richey Sharrett
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Thomas H Mosley
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Daniel C Bezerra
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - David S Knopman
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Elizabeth Selvin
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Clifford R Jack
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Laura H Coker
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Alvaro Alonso
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Lynne E Wagenknecht
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Beverly G Windham
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.)
| | - Rebecca F Gottesman
- From the Department of Neurology, Yale University School of Medicine, New Haven, CT (J.L.D.); Department of Epidemiology, Bloomberg School of Public Health (A.L.C.S., A.R.S., E.S.), Department of Neurology, School of Medicine (A.L.C.S., R.F.G.), and Welch Center for Prevention, Epidemiology and Clinical Research (E.S., R.F.G.), Johns Hopkins University, Baltimore, MD; Division of Geriatrics, Department of Medicine, The University of Mississippi School of Medicine, Jackson (T.H.M., B.G.W.); Department of Neurology, Pro Cardiaco Hospital, Rio de Janeiro, Brazil (D.C.B.); Departments of Neurology (D.S.K.) and Radiology (C.R.J.), Mayo Clinic, Rochester, MN; Division of Public Health Sciences, The Wake Forest University School of Medicine, Winston-Salem, NC (L.H.C., L.E.W.); and Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (A.A.).
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Freedman BI, Divers J, Russell GB, Palmer ND, Wagenknecht LE, Smith SC, Xu J, Carr JJ, Bowden DW, Register TC. Vitamin D Associations With Renal, Bone, and Cardiovascular Phenotypes: African American-Diabetes Heart Study. J Clin Endocrinol Metab 2015; 100. [PMID: 26196951 PMCID: PMC4596046 DOI: 10.1210/jc.2015-2167] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
CONTEXT Vitamin D binding protein (DBP) is an important determinant of bioavailable vitamin D (BAVD) and may provide clues to racial variation in osteoporosis and atherosclerosis. OBJECTIVE The objective was to assess relationships between DBP, BAVD, 25-hydroxyvitamin D (25OHD), and 1,25 di-hydroxyvitamin D (1,25OH2D) with kidney, bone, adipose, and atherosclerosis phenotypes in African Americans with type 2 diabetes. DESIGN Cross-sectional (N = 545) and longitudinal (N = 288; mean 5.1 ± 0.9-year follow-up) relationships between vitamin D concentrations with renal phenotypes, vertebral bone mineral density, aorto-iliac, coronary artery, and carotid artery calcified plaque (CP), and adipose tissue volumes were studied. SETTING African American-Diabetes Heart Study. PATIENTS Participants were 56.7% female with mean ± standard deviation (sd) age 55.6 ± 9.6 years, diabetes duration 10.3 ± 8.2 years, and eGFR 90.9 ± 22.1 ml/min/1.73 m(2). INTERVENTIONS None. MAIN OUTCOMES AND MEASURES Associations tested between vitamin D and the previously mentioned phenotypes adjusting for age, sex, African ancestry proportion, diabetes duration, statins, smoking, changes in estimated glomerular filtration rate, body mass index, hemoglobin A1c, and blood pressure. RESULTS 1,25OH2D was inversely associated with change in coronary artery CP (parameter estimate [β] -0.005, standard error [SE] 0.002; P = .037), with a trend for change in carotid artery CP (β -0.007, SE 0.004; P = .074). Further adjustment for renin-aldosterone-system blockade revealed inverse association between 1,25OH2D and change in albuminuria (β -0.004, SE 0.002; P = .037). DBP, BAVD, and 25OHD did not associate significantly with changes in albuminuria, CP, or bone mineral density. BAVD was inversely associated with visceral, subcutaneous, intermuscular, and pericardial adipose volumes. CONCLUSIONS In contrast to BAVD and 25OHD, only 1,25OH2D levels were significantly and inversely associated with changes in subclinical atherosclerosis and albuminuria in African Americans, suggesting potential beneficial effects.
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Affiliation(s)
- Barry I Freedman
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
| | - Jasmin Divers
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
| | - Gregory B Russell
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
| | - Nicholette D Palmer
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
| | - Lynne E Wagenknecht
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
| | - S Carrie Smith
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
| | - Jianzhao Xu
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
| | - J Jeffrey Carr
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
| | - Donald W Bowden
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
| | - Thomas C Register
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Center for Genomics and Personalized Medicine Research (B.I.F., J.D., G.B.R., N.D.P., J.X., D.W.B.), Center for Diabetes Research (B.I.F. J.D., G.B.R., N.D.P., L.E.W., J.X.), Center for Public Health Genomics (B.I.F. J.D., G.B.R., N.D.P., D.W.B.), Division of Public Health Sciences-Department of Biostatistical Sciences (J.D., G.B.R., L.E.W.), Department of Biochemistry (N.D.P., S.C.S., J.X.), and Department of Pathology (T.C.R.), Wake Forest School of Medicine, Winston-Salem, NC 27157; and Department of Radiology (J.J.C.), Vanderbilt University School of Medicine, Nashville, TN 37240
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Sharma PR, Mackey AJ, Dejene EA, Ramadan JW, Langefeld CD, Palmer ND, Taylor KD, Wagenknecht LE, Watanabe RM, Rich SS, Nunemaker CS. An Islet-Targeted Genome-Wide Association Scan Identifies Novel Genes Implicated in Cytokine-Mediated Islet Stress in Type 2 Diabetes. Endocrinology 2015; 156:3147-56. [PMID: 26018251 PMCID: PMC4541617 DOI: 10.1210/en.2015-1203] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Genome-wide association studies in human type 2 diabetes (T2D) have renewed interest in the pancreatic islet as a contributor to T2D risk. Chronic low-grade inflammation resulting from obesity is a risk factor for T2D and a possible trigger of β-cell failure. In this study, microarray data were collected from mouse islets after overnight treatment with cytokines at concentrations consistent with the chronic low-grade inflammation in T2D. Genes with a cytokine-induced change of >2-fold were then examined for associations between single nucleotide polymorphisms and the acute insulin response to glucose (AIRg) using data from the Genetics Underlying Diabetes in Hispanics (GUARDIAN) Consortium. Significant evidence of association was found between AIRg and single nucleotide polymorphisms in Arap3 (5q31.3), F13a1 (6p25.3), Klhl6 (3q27.1), Nid1 (1q42.3), Pamr1 (11p13), Ripk2 (8q21.3), and Steap4 (7q21.12). To assess the potential relevance to islet function, mouse islets were exposed to conditions modeling low-grade inflammation, mitochondrial stress, endoplasmic reticulum (ER) stress, glucotoxicity, and lipotoxicity. RT-PCR revealed that one or more forms of stress significantly altered expression levels of all genes except Arap3. Thapsigargin-induced ER stress up-regulated both Pamr1 and Klhl6. Three genes confirmed microarray predictions of significant cytokine sensitivity: F13a1 was down-regulated 3.3-fold by cytokines, Ripk2 was up-regulated 1.5- to 3-fold by all stressors, and Steap4 was profoundly cytokine sensitive (167-fold up-regulation). Three genes were thus closely associated with low-grade inflammation in murine islets and also with a marker for islet function (AIRg) in a diabetes-prone human population. This islet-targeted genome-wide association scan identified several previously unrecognized candidate genes related to islet dysfunction during the development of T2D.
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Affiliation(s)
- Poonam R Sharma
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - Aaron J Mackey
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - Eden A Dejene
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - James W Ramadan
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - Carl D Langefeld
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - Nicholette D Palmer
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - Kent D Taylor
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - Lynne E Wagenknecht
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - Richard M Watanabe
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - Stephen S Rich
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
| | - Craig S Nunemaker
- Department of Medicine (P.R.S., E.A.D., J.W.R., C.S.N.), Center for Public Health Genomics (A.J.M., S.S.R.), and Department of Chemistry (E.A.D.), University of Virginia, Charlottesville, Virginia 22904; Department of Biochemistry (N.D.P.), Center for Genomics and Personalized Medicine Research (N.D.P.), Center for Diabetes Research (N.D.P.), Center for Public Health Genomics (C.D.L., N.D.P., L.E.W.), Department of Biostatistical Sciences (C.D.L.), and Division of Public Health Sciences (L.E.W.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; Department of Physiology and Biophysics (R.M.W.), Department of Preventive Medicine, and USC Diabetes and Obesity Research Institute (R.M.W.), Keck School of Medicine of University of Southern California, Los Angeles, California 90033; and Institute for Translational Genomics and Population Sciences (K.D.T.) and Department of Pediatrics (K.D.T.), Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502
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119
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Palmer ND, Goodarzi MO, Langefeld CD, Wang N, Guo X, Taylor KD, Fingerlin TE, Norris JM, Buchanan TA, Xiang AH, Haritunians T, Ziegler JT, Williams AH, Stefanovski D, Cui J, Mackay AW, Henkin LF, Bergman RN, Gao X, Gauderman J, Varma R, Hanis CL, Cox NJ, Highland HM, Below JE, Williams AL, Burtt NP, Aguilar-Salinas CA, Huerta-Chagoya A, Gonzalez-Villalpando C, Orozco L, Haiman CA, Tsai MY, Johnson WC, Yao J, Rasmussen-Torvik L, Pankow J, Snively B, Jackson RD, Liu S, Nadler JL, Kandeel F, Chen YDI, Bowden DW, Rich SS, Raffel LJ, Rotter JI, Watanabe RM, Wagenknecht LE. Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium. Diabetes 2015; 64:1853-66. [PMID: 25524916 PMCID: PMC4407862 DOI: 10.2337/db14-0732] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2014] [Accepted: 12/06/2014] [Indexed: 12/31/2022]
Abstract
Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10(-8)) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Carl D Langefeld
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Nan Wang
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA Diabetes & Obesity Research Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Tasha E Fingerlin
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO
| | - Thomas A Buchanan
- Diabetes & Obesity Research Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Physiology and Biophysics, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Anny H Xiang
- Research and Evaluation Branch, Kaiser Permanente of Southern California, Pasadena, CA
| | - Talin Haritunians
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Julie T Ziegler
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Adrienne H Williams
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Darko Stefanovski
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jinrui Cui
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Adrienne W Mackay
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Leora F Henkin
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | | | - Xiaoyi Gao
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Ophthalmology and Visual Science, University of Illinois at Chicago, Chicago, IL
| | - James Gauderman
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Ophthalmology and Visual Science, University of Illinois at Chicago, Chicago, IL
| | - Rohit Varma
- Department of Ophthalmology and Visual Science, University of Illinois at Chicago, Chicago, IL
| | - Craig L Hanis
- Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, TX
| | - Nancy J Cox
- Department of Human Genetics, University of Chicago, Chicago, IL
| | - Heather M Highland
- Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, TX
| | - Jennifer E Below
- Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, TX
| | - Amy L Williams
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA Howard Hughes Medical Institute, Chicago, IL Biological Sciences Department, Columbia University, New York, NY
| | - Noel P Burtt
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Carlos A Aguilar-Salinas
- Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Alicia Huerta-Chagoya
- Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico Universidad Nacional Autónoma de México, Mexico City, Mexico
| | | | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN
| | - W Craig Johnson
- Collaborative Health Studies Coordinating Center, Department of Biostatistics, University of Washington, Seattle, WA
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Laura Rasmussen-Torvik
- Division of Epidemiology, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Evanston, IL
| | - James Pankow
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN
| | - Beverly Snively
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | | | - Simin Liu
- Department of Epidemiology, Brown University, Providence, RI
| | - Jerry L Nadler
- Department of Medicine, Eastern Virginia Medical School, Norfolk, VA
| | - Fouad Kandeel
- Department of Diabetes, Endocrinology & Metabolism, City of Hope, Duarte, CA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC Section on Endocrinology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA
| | - Leslie J Raffel
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Richard M Watanabe
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA Diabetes & Obesity Research Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Physiology and Biophysics, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Lynne E Wagenknecht
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
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Pownall HJ, Bray GA, Wagenknecht LE, Walkup MP, Heshka S, Hubbard VS, Hill J, Kahn SE, Nathan DM, Schwartz AV, Johnson KC. Changes in body composition over 8 years in a randomized trial of a lifestyle intervention: the look AHEAD study. Obesity (Silver Spring) 2015; 23:565-72. [PMID: 25707379 PMCID: PMC4707962 DOI: 10.1002/oby.21005] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2014] [Accepted: 11/17/2014] [Indexed: 12/25/2022]
Abstract
OBJECTIVE To determine the effects of an intensive lifestyle intervention versus a comparison group on body composition in obese or overweight persons with type 2 diabetes at baseline and at 1, 4, and 8 years. METHODS Body composition was measured by dual-energy X-ray absorptiometry in a subset of 1019 Look AHEAD study volunteers randomized to intervention or comparison groups. The intervention was designed to achieve and maintain ≥7% weight loss through increased physical activity and reduced caloric intake. The comparison group received social support and diabetes education. RESULTS At 1 year, the intervention group lost fat (5.6 ± 0.2 kg) and lean mass (2.3 ± 0.1 kg) but regained fat (∼100%) and lost lean mass between years 1 and 8. Between baseline and year 8, weight loss was greater in intervention versus comparison groups (4.0 ± 0.4 vs. 2.3 ± 0.4 kg); comparison group weight loss was mostly lean mass (2.1 ± 0.17 kg). Fat mass in the intervention group was lower than that of the comparison group at all post-baseline time points. CONCLUSIONS Reduced fat mass may place the intervention group at a lower risk of obesity-linked sequelae, a hypothesis that can be tested by future studies of this cohort.
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Affiliation(s)
- Henry J Pownall
- Department of Cardiology, Division of Atherosclerosis, Houston Methodist Research Institute and Baylor College of Medicine, Houston, Texas, USA
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121
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Palmer ND, Stevens RD, Antinozzi PA, Anderson A, Bergman RN, Wagenknecht LE, Newgard CB, Bowden DW. Metabolomic profile associated with insulin resistance and conversion to diabetes in the Insulin Resistance Atherosclerosis Study. J Clin Endocrinol Metab 2015; 100:E463-8. [PMID: 25423564 PMCID: PMC4333040 DOI: 10.1210/jc.2014-2357] [Citation(s) in RCA: 174] [Impact Index Per Article: 19.3] [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: 12/12/2022]
Abstract
CONTEXT Metabolomic profiling of amino acids and acylcarnitines has revealed consistent patterns associated with metabolic disease. OBJECTIVE This study used metabolomic profiling to identify analytes associated with insulin sensitivity (SI) and conversion to type 2 diabetes (T2D). DESIGN A multiethnic cohort from the Insulin Resistance Atherosclerosis Study. SETTING Community-based. PATIENTS A total of 196 subjects (European American, Hispanic, and African American) were selected to represent extremes of the SI distribution and conversion to T2D between baseline and followup exams. MAIN OUTCOME Mass spectrometry-based profiling of 69 metabolites. Subjects participated in a frequently sampled i.v. glucose tolerance test to measure SI and acute insulin response. T2D status was determined by a 2-hour oral glucose tolerance test. RESULTS Logistic regression analysis from 72 high and 75 low SI subjects revealed significantly decreased glycine and increased valine, leucine, phenylalanine, and combined glutamine and glutamate (P = .0079-7.7 × 10(-6)) in insulin-resistant subjects. Ethnic-stratified results were strongest in European Americans. Comparing amino acid profiles between subjects that converted to T2D (76 converters; 70 nonconverters) yielded a similar pattern of associations: decreased glycine and increased valine, leucine, and combined glutamine and glutamate (P = .016-.00010). Importantly, β-cell function as a covariate revealed a similar pattern of association. CONCLUSIONS A distinct pattern of differences in amino acids were observed when comparing subjects with high and low levels of SI. This pattern was associated with conversion to T2D, remaining significant when accounting for β-cell function, emphasizing a link between this metabolic profile and insulin resistance. These results demonstrate a consistent metabolic signature associated with insulin resistance and conversion to T2D, providing potential insight into underlying mechanisms of disease pathogenesis.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry (N.D.P., P.A.A., D.W.B.), Center for Genomics and Personalized Medicine Research (N.D.P., P.A.A., D.W.B.), and Center for Diabetes Research (N.D.P., P.A.A., D.W.B.), Wake Forest School of Medicine, Winston Salem, North Carolina 27157; Sarah W. Stedman Nutrition and Metabolism Center (R.D.S., C.B.N.), Duke University School of Medicine, Durham, North Carolina 27710; Department of Biostatistical Sciences (A.A.) and Department of Epidemiology & Prevention (L.E.W.), Wake Forest School of Medicine, Winston Salem, North Carolina 27157; and Department of Physiology and Biophysics (R.N.B.), Keck School of Medicine, University of Southern California, Los Angeles, California 90033
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122
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Wessel J, Chu AY, Willems SM, Wang S, Yaghootkar H, Brody JA, Dauriz M, Hivert MF, Raghavan S, Lipovich L, Hidalgo B, Fox K, Huffman JE, An P, Lu Y, Rasmussen-Torvik LJ, Grarup N, Ehm MG, Li L, Baldridge AS, Stančáková A, Abrol R, Besse C, Boland A, Bork-Jensen J, Fornage M, Freitag DF, Garcia ME, Guo X, Hara K, Isaacs A, Jakobsdottir J, Lange LA, Layton JC, Li M, Hua Zhao J, Meidtner K, Morrison AC, Nalls MA, Peters MJ, Sabater-Lleal M, Schurmann C, Silveira A, Smith AV, Southam L, Stoiber MH, Strawbridge RJ, Taylor KD, Varga TV, Allin KH, Amin N, Aponte JL, Aung T, Barbieri C, Bihlmeyer NA, Boehnke M, Bombieri C, Bowden DW, Burns SM, Chen Y, Chen YD, Cheng CY, Correa A, Czajkowski J, Dehghan A, Ehret GB, Eiriksdottir G, Escher SA, Farmaki AE, Frånberg M, Gambaro G, Giulianini F, Goddard WA, Goel A, Gottesman O, Grove ML, Gustafsson S, Hai Y, Hallmans G, Heo J, Hoffmann P, Ikram MK, Jensen RA, Jørgensen ME, Jørgensen T, Karaleftheri M, Khor CC, Kirkpatrick A, Kraja AT, Kuusisto J, Lange EM, Lee IT, Lee WJ, Leong A, Liao J, Liu C, Liu Y, Lindgren CM, Linneberg A, Malerba G, Mamakou V, Marouli E, Maruthur NM, Matchan A, McKean-Cowdin R, McLeod O, Metcalf GA, Mohlke KL, Muzny DM, Ntalla I, Palmer ND, Pasko D, Peter A, Rayner NW, Renström F, Rice K, Sala CF, Sennblad B, Serafetinidis I, Smith JA, Soranzo N, Speliotes EK, Stahl EA, Stirrups K, Tentolouris N, Thanopoulou A, Torres M, Traglia M, Tsafantakis E, Javad S, Yanek LR, Zengini E, Becker DM, Bis JC, Brown JB, Adrienne Cupples L, Hansen T, Ingelsson E, Karter AJ, Lorenzo C, Mathias RA, Norris JM, Peloso GM, Sheu WHH, Toniolo D, Vaidya D, Varma R, Wagenknecht LE, Boeing H, Bottinger EP, Dedoussis G, Deloukas P, Ferrannini E, Franco OH, Franks PW, Gibbs RA, Gudnason V, Hamsten A, Harris TB, Hattersley AT, Hayward C, Hofman A, Jansson JH, Langenberg C, Launer LJ, Levy D, Oostra BA, O'Donnell CJ, O'Rahilly S, Padmanabhan S, Pankow JS, Polasek O, Province MA, Rich SS, Ridker PM, Rudan I, Schulze MB, Smith BH, Uitterlinden AG, Walker M, Watkins H, Wong TY, Zeggini E, Laakso M, Borecki IB, Chasman DI, Pedersen O, Psaty BM, Shyong Tai E, van Duijn CM, Wareham NJ, Waterworth DM, Boerwinkle E, Linda Kao WH, Florez JC, Loos RJ, Wilson JG, Frayling TM, Siscovick DS, Dupuis J, Rotter JI, Meigs JB, Scott RA, Goodarzi MO. Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility. Nat Commun 2015; 6:5897. [PMID: 25631608 PMCID: PMC4311266 DOI: 10.1038/ncomms6897] [Citation(s) in RCA: 153] [Impact Index Per Article: 17.0] [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] [Subscribe] [Scholar Register] [Received: 06/05/2014] [Accepted: 11/12/2014] [Indexed: 12/30/2022] Open
Abstract
Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
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Affiliation(s)
- Jennifer Wessel
- Department of Epidemiology, Fairbanks School of Public Health, Indianapolis, Indiana 46202, USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana 46202, USA
| | - Audrey Y Chu
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02215, USA
- National Heart, Lung, and Blood Institute (NHLBI) Framingham Heart Study, Framingham, Massachusetts 01702, USA
| | - Sara M Willems
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0SL, UK
| | - Shuai Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118, USA
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98101, USA
- Department of Medicine, University of Washington, Seattle, Washington 98195, USA
| | - Marco Dauriz
- Massachusetts General Hospital, General Medicine Division, Boston, Massachusetts 02114, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Verona Medical School and Hospital Trust of Verona, Verona 37126, Italy
| | - Marie-France Hivert
- Harvard Pilgrim Health Care Institute, Department of Population Medicine, Harvard Medical School, Boston, Massachusetts 02215, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada J1K 2R1
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Sridharan Raghavan
- Massachusetts General Hospital, General Medicine Division, Boston, Massachusetts 02114, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Leonard Lipovich
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan 48201, USA
- Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan 48202, USA
| | - Bertha Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama 35233, USA
| | - Keolu Fox
- Department of Medicine, University of Washington, Seattle, Washington 98195, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Jennifer E Huffman
- National Heart, Lung, and Blood Institute (NHLBI) Framingham Heart Study, Framingham, Massachusetts 01702, USA
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh, Scotland EH4 2XU, UK
| | - Ping An
- Division of Statistical Genomics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen DK-2200, Denmark
| | - Margaret G Ehm
- Quantitative Sciences, PCPS, GlaxoSmithKline, North Carolina 27709, USA
| | - Li Li
- Quantitative Sciences, PCPS, GlaxoSmithKline, North Carolina 27709, USA
| | - Abigail S Baldridge
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois 60611, USA
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio FI-70211, Finland
| | - Ravinder Abrol
- Department of Medicine and Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA
- Materials and Process Simulation Center, California Institute of Technology, Pasadena, California 91125, USA
| | - Céline Besse
- CEA, Institut de Génomique, Centre National de Génotypage, 2 Rue Gaston Crémieux, EVRY Cedex 91057, France
| | - Anne Boland
- CEA, Institut de Génomique, Centre National de Génotypage, 2 Rue Gaston Crémieux, EVRY Cedex 91057, France
| | - Jette Bork-Jensen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen DK-2200, Denmark
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center, Houston, Texas 77030, USA
| | - Daniel F Freitag
- The Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
- Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge CB1 8RN, UK
| | - Melissa E Garcia
- Intramural Research Program, National Institute on Aging, Bethesda, Maryland 21224, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502, USA
| | - Kazuo Hara
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
| | | | - Leslie A Lange
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Jill C Layton
- Indiana University, Fairbanks School of Public Health, Indianapolis, Indiana 46202, USA
| | - Man Li
- Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland 21205, USA
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0SL, UK
| | - Karina Meidtner
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal DE-14558, Germany
| | - Alanna C Morrison
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas 77225, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland 20892, USA
| | - Marjolein J Peters
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
- The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam 2300 RC, The Netherlands
| | - Maria Sabater-Lleal
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm SE-171 77, Sweden
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Angela Silveira
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm SE-171 77, Sweden
| | - Albert V Smith
- Icelandic Heart Association, Holtasmari 1, Kopavogur IS-201, Iceland
- University of Iceland, Reykjavik IS-101, Iceland
| | - Lorraine Southam
- The Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
- Wellcome Trust Centre for Human Genetics, Oxford OX3 7BN, UK
| | - Marcus H Stoiber
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Rona J Strawbridge
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm SE-171 77, Sweden
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502, USA
| | - Tibor V Varga
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital, Malmö SE-205 02, Sweden
| | - Kristine H Allin
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen DK-2200, Denmark
| | - Najaf Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
| | - Jennifer L Aponte
- Quantitative Sciences, PCPS, GlaxoSmithKline, North Carolina 27709, USA
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
| | - Caterina Barbieri
- Division of Genetics and Cell Biology, San Raffaele Research Institute, Milano 20132, Italy
| | - Nathan A Bihlmeyer
- Predoctoral Training Program in Human Genetics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Maryland 21205, USA
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Cristina Bombieri
- Section of Biology and Genetics, Department of Life and Reproduction Sciences, University of Verona, Verona 37100, Italy
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157, USA
| | - Sean M Burns
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Yuning Chen
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118, USA
| | - Yii-DerI Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502, USA
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Office of Clinical Sciences, Duke-NUS Graduate Medical School, National University of Singapore, Singapore 169857, Singapore
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi 39216, USA
| | - Jacek Czajkowski
- Division of Statistical Genomics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
| | - Georg B Ehret
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21205, USA
- Division of Cardiology, Geneva University Hospital Geneva 1211, Switzerland
| | | | - Stefan A Escher
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital, Malmö SE-205 02, Sweden
| | - Aliki-Eleni Farmaki
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens 17671, Greece
| | - Mattias Frånberg
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm SE-171 77, Sweden
- Department of Numerical Analysis and Computer Science, SciLifeLab, Stockholm University, Stockholm SE-106 91, Sweden
| | - Giovanni Gambaro
- Division of Nephrology, Department of Internal Medicine and Medical Specialties, Columbus-Gemelli University Hospital, Catholic University, Rome 00168, Italy
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02215, USA
| | - William A Goddard
- Materials and Process Simulation Center, California Institute of Technology, Pasadena, California 91125, USA
| | - Anuj Goel
- Department of Cardiovascular Medicine, The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Omri Gottesman
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Megan L Grove
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas 77225, USA
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala SE-751 85, Sweden
| | - Yang Hai
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502, USA
| | - Göran Hallmans
- Department of Biobank Research, Umeå University, Umeå SE-901 87, Sweden
| | - Jiyoung Heo
- Department of Biomedical Technology, Sangmyung University, Chungnam 330-720, Korea
| | - Per Hoffmann
- Institute of Human Genetics, Department of Genomics, Life & Brain Center, University of Bonn, Bonn DE-53127, Germany
- Human Genomics Research Group, Division of Medical Genetics, University Hospital Basel Department of Biomedicine 4031, Basel, Switzerland
- Institute of Neuroscience and Medicine (INM-1) Genomic Imaging Research Center Juelich, Juelich DE-52425, Germany
| | - Mohammad K Ikram
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
- Office of Clinical Sciences, Duke-NUS Graduate Medical School, National University of Singapore, Singapore 169857, Singapore
- Memory Aging & Cognition Centre (MACC), National University Health System, Singapore 117599, Singapore
| | - Richard A Jensen
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98101, USA
- Department of Medicine, University of Washington, Seattle, Washington 98195, USA
| | | | - Torben Jørgensen
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup DK-2600, Denmark
- Faculty of Medicine, University of Aalborg, Aalborg DK-9220, Denmark
| | | | - Chiea C Khor
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Division of Human Genetics, Genome Institute of Singapore, Singapore 138672, Singapore
| | - Andrea Kirkpatrick
- Materials and Process Simulation Center, California Institute of Technology, Pasadena, California 91125, USA
| | - Aldi T Kraja
- Division of Statistical Genomics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio FI-70211, Finland
| | - Ethan M Lange
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - I T Lee
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung 407, Taiwan
- School of Medicine, National Yang-Ming University, Taipei 112, Taiwan
| | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung 407, Taiwan
| | - Aaron Leong
- Massachusetts General Hospital, General Medicine Division, Boston, Massachusetts 02114, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Jiemin Liao
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
| | - Chunyu Liu
- National Heart, Lung, and Blood Institute (NHLBI) Framingham Heart Study, Framingham, Massachusetts 01702, USA
| | - Yongmei Liu
- Department of Epidemiology & Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, North Carolina 27106, USA
| | - Cecilia M Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Allan Linneberg
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup DK-2600, Denmark
- Department of Clinical Experimental Research, Copenhagen University Hospital Glostrup, Glostrup DK-2600, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen DK-2200, Denmark
| | - Giovanni Malerba
- Section of Biology and Genetics, Department of Life and Reproduction Sciences, University of Verona, Verona 37100, Italy
| | - Vasiliki Mamakou
- National and Kapodistrian University of Athens, Faculty of Medicine, Athens 115 27, Greece
- Dromokaiteio Psychiatric Hospital, Athens 124 61, Greece
| | - Eirini Marouli
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens 17671, Greece
| | - Nisa M Maruthur
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland 21205, USA
| | - Angela Matchan
- The Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
| | - Roberta McKean-Cowdin
- Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles 90033, USA
| | - Olga McLeod
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm SE-171 77, Sweden
| | - Ginger A Metcalf
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Donna M Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Ioanna Ntalla
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens 17671, Greece
- University of Leicester, Leicester LE1 7RH, UK
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina 27106, USA
| | - Dorota Pasko
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK
| | - Andreas Peter
- Department of Internal Medicine, Division of Endocrinology, Metabolism, Pathobiochemistry and Clinical Chemistry and Institute of Diabetes Research and Metabolic Diseases, University of Tübingen, Tübingen DE-72076, Germany
- German Center for Diabetes Research (DZD), Neuherberg DE-85764, Germany
| | - Nigel W Rayner
- The Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
- Wellcome Trust Centre for Human Genetics, Oxford OX3 7BN, UK
- The Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LE, UK
| | - Frida Renström
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital, Malmö SE-205 02, Sweden
| | - Ken Rice
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98101, USA
- Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
| | - Cinzia F Sala
- Division of Genetics and Cell Biology, San Raffaele Research Institute, Milano 20132, Italy
| | - Bengt Sennblad
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm SE-171 77, Sweden
- Science for Life Laboratory, Karolinska Institutet, Stockholm SE-171 77, Sweden
| | | | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Nicole Soranzo
- The Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
- Department of Hematology, Long Road, Cambridge CB2 0XY, UK
| | - Elizabeth K Speliotes
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Eli A Stahl
- Division of Psychiatric Genomics, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Kathleen Stirrups
- The Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 4NS, UK
| | - Nikos Tentolouris
- First Department of Propaedeutic and Internal Medicine, Athens University Medical School, Laiko General Hospital, Athens 11527, Greece
| | - Anastasia Thanopoulou
- Diabetes Centre, 2nd Department of Internal Medicine, National University of Athens, Hippokration General Hospital, Athens 11527, Greece
| | - Mina Torres
- Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles 90033, USA
| | - Michela Traglia
- Division of Genetics and Cell Biology, San Raffaele Research Institute, Milano 20132, Italy
| | | | - Sundas Javad
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0SL, UK
| | - Lisa R Yanek
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Eleni Zengini
- Dromokaiteio Psychiatric Hospital, Athens 124 61, Greece
- University of Sheffield, Sheffield S10 2TN, UK
| | - Diane M Becker
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98101, USA
- Department of Medicine, University of Washington, Seattle, Washington 98195, USA
| | - James B Brown
- Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
- Department of Statistics, University of California at Berkeley, Berkeley, California 94720, USA
| | - L Adrienne Cupples
- National Heart, Lung, and Blood Institute (NHLBI) Framingham Heart Study, Framingham, Massachusetts 01702, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118, USA
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen DK-2200, Denmark
- Faculty of Health Science, University of Copenhagen, Copenhagen 1165, Denmark
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala SE-751 85, Sweden
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Andrew J Karter
- Division of Research, Kaiser Permanente, Northern California Region, Oakland, California 94612, USA
| | - Carlos Lorenzo
- Department of Medicine, University of Texas Health Science Center, San Antonio, Texas 77030, USA
| | - Rasika A Mathias
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado 80204, USA
| | - Gina M Peloso
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Wayne H.-H. Sheu
- Division of Endocrine and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung 407, Taiwan
- School of Medicine, National Yang-Ming University, Taipei 112, Taiwan
- College of Medicine, National Defense Medical Center, Taipei 114, Taiwan
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffaele Research Institute, Milano 20132, Italy
| | - Dhananjay Vaidya
- The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
| | - Rohit Varma
- Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles 90033, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina 27106, USA
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam Rehbrücke, Nuthetal DE-14558, Germany
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens 17671, Greece
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 4NS, UK
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah 22254, Saudi Arabia
| | | | - Oscar H Franco
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
| | - Paul W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital, Malmö SE-205 02, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA
- Department of Public Health & Clinical Medicine, Umeå University, Umeå SE-901 87, Sweden
| | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Holtasmari 1, Kopavogur IS-201, Iceland
- University of Iceland, Reykjavik IS-101, Iceland
| | - Anders Hamsten
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm SE-171 77, Sweden
| | - Tamara B Harris
- Intramural Research Program, National Institute on Aging, Bethesda, Maryland 21224, USA
| | - Andrew T Hattersley
- Genetics of Diabetes, University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh, Scotland EH4 2XU, UK
| | - Albert Hofman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
| | - Jan-Håkan Jansson
- Department of Public Health & Clinical Medicine, Umeå University, Umeå SE-901 87, Sweden
- Research Unit, Skellefteå SE-931 87, Sweden
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0SL, UK
| | - Lenore J Launer
- Intramural Research Program, National Institute on Aging, Bethesda, Maryland 21224, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
- Framingham Heart Study, Framingham, Massachusetts 01702, USA
| | - Ben A Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
| | - Christopher J O'Donnell
- National Heart, Lung, and Blood Institute (NHLBI) Framingham Heart Study, Framingham, Massachusetts 01702, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
- Cardiology Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Stephen O'Rahilly
- University of Cambridge Metabolic Research Laboratories, MRC Metabolic Diseases Unit and NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 1TN, UK
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow G12 8TA, UK
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Split 21000, Croatia
| | - Michael A Province
- Division of Statistical Genomics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia 22908, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02215, USA
- Division of Cardiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Igor Rudan
- Centre for Population Health Sciences, Medical School, University of Edinburgh, Edinburgh, Scotland EH8 9YL, UK
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal DE-14558, Germany
- German Center for Diabetes Research (DZD), Neuherberg DE-85764, Germany
| | - Blair H Smith
- Medical Research Institute, University of Dundee, Dundee DD1 9SY, UK
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
| | - Mark Walker
- Institute of Cellular Medicine, Newcastle University, Newcastle-upon-Tyne NE1 7RU, UK
| | - Hugh Watkins
- Department of Cardiovascular Medicine, The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Tien Y Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
- Department of Ophthalmology, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Office of Clinical Sciences, Duke-NUS Graduate Medical School, National University of Singapore, Singapore 169857, Singapore
| | | | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio FI-70211, Finland
| | - Ingrid B Borecki
- Division of Statistical Genomics and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02215, USA
- Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen DK-2200, Denmark
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98101, USA
- Department of Medicine, University of Washington, Seattle, Washington 98195, USA
- Department of Epidemiology, University of Washington, Seattle, Washington 98195, USA
- Department of Health Services, University of Washington, Seattle, Washington 98195, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, Washington 98195, USA
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 119228, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Cornelia M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3000 CE, The Netherlands
- Center for Medical Systems Biology, Leiden 2300, The Netherlands
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0SL, UK
| | - Dawn M Waterworth
- Genetics, PCPS, GlaxoSmithKline, Philadelphia, Pennsylvania 19104, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas 77225, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - W H Linda Kao
- Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland 21205, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland 21205, USA
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland 21205, USA
| | - Jose C Florez
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi 38677, USA
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK
| | - David S Siscovick
- New York Academy of Medicine, New York, New York 10029, USA
- Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, Washington 98195, USA
| | - Josée Dupuis
- National Heart, Lung, and Blood Institute (NHLBI) Framingham Heart Study, Framingham, Massachusetts 01702, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90502, USA
| | - James B Meigs
- Massachusetts General Hospital, General Medicine Division, Boston, Massachusetts 02114, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0SL, UK
| | - Mark O Goodarzi
- Department of Medicine and Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA
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Freedman BI, Langefeld CD, Lu L, Palmer ND, Smith SC, Bagwell BM, Hicks PJ, Xu J, Wagenknecht LE, Raffield LM, Register TC, Carr JJ, Bowden DW, Divers J. APOL1 associations with nephropathy, atherosclerosis, and all-cause mortality in African Americans with type 2 diabetes. Kidney Int 2015; 87:176-81. [PMID: 25054777 PMCID: PMC4281283 DOI: 10.1038/ki.2014.255] [Citation(s) in RCA: 66] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2014] [Revised: 05/30/2014] [Accepted: 06/05/2014] [Indexed: 12/30/2022]
Abstract
Albuminuria and reduced estimated glomerular filtration rate (eGFR) associate with two apolipoprotein L1 gene (APOL1) variants in nondiabetic African Americans (AAs). Whether APOL1 associates with subclinical atherosclerosis and survival remains unclear. To determine this, 717 African American-Diabetes Heart Study participants underwent computed tomography to determine coronary artery-, carotid artery-, and aorta-calcified atherosclerotic plaque mass scores in addition to the urine albumin:creatinine ratio (UACR), eGFR, and C-reactive protein (CRP). Associations between mass scores and APOL1 were assessed adjusting for age, gender, African ancestry, body mass index (BMI), hemoglobin A1c, smoking, hypertension, use of statins and angiotensin-converting enzyme inhibitors, albuminuria, and eGFR. Participants were 58.9% female with mean age 56.5 years, eGFR 89.5 ml/min per 1.73 m(2), UACR 169.6 mg/g, and coronary artery-, carotid artery-, and aorta-calcified plaque mass scores of 610, 171, and 5378, respectively. In fully adjusted models, APOL1 risk variants were significantly associated with lower levels of carotid artery-calcified plaque (β=-0.42, s.e. 0.18; dominant model) and marginally lower coronary artery plaque (β=-0.36, s.e. 0.21; dominant model), but not with aorta-calcified plaque, CRP, UACR, or eGFR. By the end of a mean follow-up of 5.0 years, 89 participants had died. APOL1 nephropathy risk variants were significantly associated with improved survival (hazard ratio 0.67 for one copy; 0.44 for two copies). Thus, APOL1 nephropathy variants associate with lower levels of subclinical atherosclerosis and reduced risk of death in AAs with type 2 diabetes mellitus.
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Affiliation(s)
- Barry I. Freedman
- Department of Internal Medicine–Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Carl D. Langefeld
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Division of Public Health Sciences-Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Lingyi Lu
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Division of Public Health Sciences-Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Nicholette D. Palmer
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Division of Public Health Sciences-Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - S. Carrie Smith
- Department of Internal Medicine–Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Benjamin M. Bagwell
- Department of Internal Medicine–Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Pamela J. Hicks
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jianzhao Xu
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences-Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Laura M. Raffield
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Thomas C. Register
- Department of Pathology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - J. Jeffrey Carr
- Department of Radiology; Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Donald W. Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jasmin Divers
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Division of Public Health Sciences-Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
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Hellwege JN, Palmer ND, Brown WM, Ziegler JT, An SS, Guo X, Chen YDI, Taylor K, Hawkins GA, Ng MCY, Speliotes EK, Lorenzo C, Norris JM, Rotter JI, Wagenknecht LE, Langefeld CD, Bowden DW. Erratum to: Empirical characteristics of family-based linkage to a complex trait: the ADIPOQ region and adiponectin levels. Hum Genet 2014. [DOI: 10.1007/s00439-014-1518-1] [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: 11/24/2022]
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Rawlings AM, Sharrett AR, Schneider ALC, Coresh J, Albert M, Couper D, Griswold M, Gottesman RF, Wagenknecht LE, Windham BG, Selvin E. Diabetes in midlife and cognitive change over 20 years: a cohort study. Ann Intern Med 2014; 161:785-93. [PMID: 25437406 PMCID: PMC4432464 DOI: 10.7326/m14-0737] [Citation(s) in RCA: 259] [Impact Index Per Article: 25.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Type 2 diabetes is associated with dementia risk, but evidence is limited for possible associations of diabetes and prediabetes with cognitive decline. OBJECTIVE To determine whether diabetes in midlife is associated with 20-year cognitive decline and to characterize long-term cognitive decline across clinical categories of hemoglobin A1c (HbA1c) levels. DESIGN Prospective cohort study. SETTING The community-based ARIC (Atherosclerosis Risk in Communities) study. PARTICIPANTS 13,351 black and white adults aged 48 to 67 years at baseline (1990 to 1992). MEASUREMENTS Diabetes was defined by self-reported physician diagnosis or medication use or HbA1c level of 6.5% or greater. Undiagnosed diabetes, prediabetes, and glucose control in persons with diagnosed diabetes were defined by clinical categories of HbA1c level. Delayed word recall, digit symbol substitution, and word fluency tests were used to assess cognitive performance and were summarized with a global Z score. RESULTS Diabetes in midlife was associated with a 19% greater cognitive decline over 20 years (adjusted global Z-score difference, -0.15 [;95% CI, -0.22 to -0.08];) compared with no diabetes. Cognitive decline was significantly greater among persons with prediabetes (HbA1c level of 5.7% to 6.4%) than among those with an HbA1c level less than 5.7%. Participants with poorly controlled diabetes (HbA1c level ≥ 7.0%) had greater decline than those whose diabetes was controlled (adjusted global Z-score difference, -0.16; P = 0.071). Longer-duration diabetes was also associated with greater late-life cognitive decline (P for trend < 0.001). Rates of decline did not differ significantly between white and black persons (P for interaction = 0.44). LIMITATION Single HbA1c measurement at baseline, 1 test per cognitive domain, and potential geographic confounding of race comparisons. CONCLUSION Diabetes prevention and glucose control in midlife may protect against late-life cognitive decline. PRIMARY FUNDING SOURCE National Institutes of Health.
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Santaren ID, Watkins SM, Liese AD, Wagenknecht LE, Rewers MJ, Haffner SM, Lorenzo C, Hanley AJ. Serum pentadecanoic acid (15:0), a short-term marker of dairy food intake, is inversely associated with incident type 2 diabetes and its underlying disorders. Am J Clin Nutr 2014; 100:1532-40. [PMID: 25411288 PMCID: PMC4232018 DOI: 10.3945/ajcn.114.092544] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Growing evidence suggests that dairy consumption is associated with lower type 2 diabetes risk. However, observational studies have reported inconsistent results, and few have examined dairy's association with the underlying disorders of insulin resistance and β-cell dysfunction. OBJECTIVE We investigated the association of the dairy fatty acid biomarkers pentadecanoic acid (15:0) and trans-palmitoleic acid (trans 16:1n-7) with type 2 diabetes traits by evaluating 1) prospective associations with incident diabetes after 5 y of follow-up and 2) cross-sectional associations with directly measured insulin resistance and β-cell dysfunction. DESIGN The study analyzed 659 adults without diabetes at baseline from the triethnic multicenter Insulin Resistance Atherosclerosis Study (IRAS). Diabetes status was assessed by using oral-glucose-tolerance tests. Frequently sampled intravenous-glucose-tolerance tests measured insulin sensitivity (SI) and β-cell function [disposition index (DI)]. Serum fatty acids were quantified by using gas chromatography. Logistic and linear regression models were adjusted for demographic, lifestyle, and dietary variables. RESULTS Serum 15:0 was a significant biomarker for total dairy intake in the IRAS cohort. It was associated with a decreased incident diabetes risk (OR: 0.73, P = 0.02) and was positively associated with log SI (β: 0.84, P = 0.03) and log DI (β: 2.21, P = 0.02) in fully adjusted models. trans 16:1n-7 was a marker of total partially hydrogenated dietary fat intake and was not associated with outcomes in fully adjusted models. CONCLUSIONS Serum 15:0, a marker of short-term intake of this fatty acid, was inversely associated with diabetes risk in this multiethnic cohort. This study may contribute to future recommendations regarding the benefits of dairy products on type 2 diabetes risk.
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Affiliation(s)
- Ingrid D Santaren
- From the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada (IDS and AJH); Lipomics, a Division of Metabolon Inc., West Sacramento, CA (SMW); the Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC (ADL); the Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC (LEW); Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO (MJR); the Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, TX (SMH and CL); the Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada (AJH); and Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada (AJH)
| | - Steven M Watkins
- From the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada (IDS and AJH); Lipomics, a Division of Metabolon Inc., West Sacramento, CA (SMW); the Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC (ADL); the Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC (LEW); Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO (MJR); the Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, TX (SMH and CL); the Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada (AJH); and Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada (AJH)
| | - Angela D Liese
- From the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada (IDS and AJH); Lipomics, a Division of Metabolon Inc., West Sacramento, CA (SMW); the Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC (ADL); the Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC (LEW); Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO (MJR); the Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, TX (SMH and CL); the Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada (AJH); and Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada (AJH)
| | - Lynne E Wagenknecht
- From the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada (IDS and AJH); Lipomics, a Division of Metabolon Inc., West Sacramento, CA (SMW); the Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC (ADL); the Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC (LEW); Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO (MJR); the Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, TX (SMH and CL); the Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada (AJH); and Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada (AJH)
| | - Marian J Rewers
- From the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada (IDS and AJH); Lipomics, a Division of Metabolon Inc., West Sacramento, CA (SMW); the Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC (ADL); the Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC (LEW); Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO (MJR); the Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, TX (SMH and CL); the Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada (AJH); and Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada (AJH)
| | - Steven M Haffner
- From the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada (IDS and AJH); Lipomics, a Division of Metabolon Inc., West Sacramento, CA (SMW); the Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC (ADL); the Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC (LEW); Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO (MJR); the Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, TX (SMH and CL); the Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada (AJH); and Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada (AJH)
| | - Carlos Lorenzo
- From the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada (IDS and AJH); Lipomics, a Division of Metabolon Inc., West Sacramento, CA (SMW); the Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC (ADL); the Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC (LEW); Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO (MJR); the Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, TX (SMH and CL); the Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada (AJH); and Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada (AJH)
| | - Anthony J Hanley
- From the Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada (IDS and AJH); Lipomics, a Division of Metabolon Inc., West Sacramento, CA (SMW); the Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC (ADL); the Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC (LEW); Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO (MJR); the Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, TX (SMH and CL); the Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, Canada (AJH); and Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Canada (AJH)
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Lee CTC, Liese AD, Lorenzo C, Wagenknecht LE, Haffner SM, Rewers MJ, Hanley AJ. Egg consumption and insulin metabolism in the Insulin Resistance Atherosclerosis Study (IRAS). Public Health Nutr 2014; 17:1595-602. [PMID: 23777633 PMCID: PMC10282309 DOI: 10.1017/s1368980013001572] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2012] [Revised: 05/07/2013] [Accepted: 05/09/2013] [Indexed: 11/07/2022]
Abstract
OBJECTIVE To examine the association between egg consumption and measures of insulin sensitivity (SI), acute insulin response (AIR) and metabolic clearance rate of insulin (MCRI). DESIGN Cross-sectional analysis. SETTINGS Egg consumption, categorized as <1/week, 1 to <3/week, 3 to <5/week and ≥5/week, was measured using a validated FFQ. SI, AIR and MCRI were determined from frequently sampled intravenous glucose tolerance tests. SUBJECTS Non-diabetic participants (n 949) in the Insulin Resistance Atherosclerosis Study (IRAS). RESULTS Egg consumption was inversely associated with SI and MCRI, and positively associated with fasting insulin in regression models adjusted for demographic, socio-economic, lifestyle and dietary factors (β = -0·22, 95 % CI -0·38, -0·045, P = 0·05 for SI; β = -0·20, 95 % CI -0·34, -0·055, P = 0·005 for MCRI; β = 0·35, 95 % CI 0·15, 0·54, P = 0·002 for fasting insulin; all P values for linear trend). These associations remained significant after additionally adjusting for energy intake or dietary saturated fat, although dietary cholesterol and BMI attenuated these associations to non-significance. Egg consumption was not associated with AIR. CONCLUSIONS Dietary cholesterol and BMI appear to mediate the inverse association of egg consumption with insulin sensitivity and clearance. Alternatively, egg consumption may be clustered with other dietary behaviours which increase BMI, hence negatively impacting on insulin sensitivity and clearance.
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Affiliation(s)
- Chee-Tin Christine Lee
- Department of Nutritional Sciences, University of Toronto, FitzGerald Building, 150 College Street Room 341, Toronto, ON M5S 3E2, Canada
| | - Angela D Liese
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA
| | - Carlos Lorenzo
- Division of Clinical Epidemiology, University of Texas Health Science Centre, San Antonio, TX, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Steven M Haffner
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Marian J Rewers
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Anthony J Hanley
- Department of Nutritional Sciences, University of Toronto, FitzGerald Building, 150 College Street Room 341, Toronto, ON M5S 3E2, Canada
- Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, ON, Canada
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Howard G, Wagenknecht LE, Kernan WN, Cushman M, Thacker EL, Judd SE, Howard VJ, Kissela BM. Racial differences in the association of insulin resistance with stroke risk: the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. Stroke 2014; 45:2257-62. [PMID: 24968932 DOI: 10.1161/strokeaha.114.005306] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND AND PURPOSE Insulin resistance is associated with increased stroke risk, but the effect has not been adequately examined separately in white and black populations. METHODS The association of baseline insulin resistance with risk of cerebral infarction (CI) and intracerebral hemorrhage (ICH) was assessed in 12 366 white and 6782 black participants from the REasons for Geographic And Racial Differences in Stroke (REGARDS) cohort, recruited between 2003 and 2007 and followed for an average of 5.7 years. Insulin resistance was measured with the homeostasis model assessment-insulin resistance. RESULTS There were 364 incident CI and 41 incident ICH events. The risk for CI increased with the log of insulin resistance in whites (hazards ratio [HR]ln(IR)=1.17; 95% confidence interval [CI], 1.00-1.38) but was largely attenuated by adjustment for stroke risk factors (HRln(IR)=1.05; 95% CI, 0.88-1.26). There was no association in blacks (HRln(IR)=1.01; 95% CI, 0.81-1.25). After adjustment for demographic factors and risk factors, there was a significant difference by race in the association of insulin resistance with risk of ICH (P=0.07), with a decrease in the risk of ICH in whites (HRln(IR)=0.61; 95% CI, 0.35-1.04) but a nonsignificant increase in blacks (HRln(IR)=1.20; 95% CI, 0.60-2.39). CONCLUSIONS These data support the growing evidence that insulin resistance may play a more important role in stroke risk among white than black individuals and suggest a potentially discordant relationship of insulin resistance on CI and ICH among whites.
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Affiliation(s)
- George Howard
- From the Department of Biostatistics (G.H., S.E.J.) and Department of Epidemiology (V.J.H.), UAB School of Public Health; Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC (L.E.W.); Department of Medicine, Yale University School of Medicine, New Haven, CT (W.N.K.); Department of Medicine, University of Vermont College of Medicine, Burlington (M.C.); Department of Health Science, Brigham Young University, Provo, UT (E.L.T.); and Department of Neurology, School of Medicine, University of Cincinnati, OH (B.M.K.).
| | - Lynne E Wagenknecht
- From the Department of Biostatistics (G.H., S.E.J.) and Department of Epidemiology (V.J.H.), UAB School of Public Health; Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC (L.E.W.); Department of Medicine, Yale University School of Medicine, New Haven, CT (W.N.K.); Department of Medicine, University of Vermont College of Medicine, Burlington (M.C.); Department of Health Science, Brigham Young University, Provo, UT (E.L.T.); and Department of Neurology, School of Medicine, University of Cincinnati, OH (B.M.K.)
| | - Walter N Kernan
- From the Department of Biostatistics (G.H., S.E.J.) and Department of Epidemiology (V.J.H.), UAB School of Public Health; Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC (L.E.W.); Department of Medicine, Yale University School of Medicine, New Haven, CT (W.N.K.); Department of Medicine, University of Vermont College of Medicine, Burlington (M.C.); Department of Health Science, Brigham Young University, Provo, UT (E.L.T.); and Department of Neurology, School of Medicine, University of Cincinnati, OH (B.M.K.)
| | - Mary Cushman
- From the Department of Biostatistics (G.H., S.E.J.) and Department of Epidemiology (V.J.H.), UAB School of Public Health; Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC (L.E.W.); Department of Medicine, Yale University School of Medicine, New Haven, CT (W.N.K.); Department of Medicine, University of Vermont College of Medicine, Burlington (M.C.); Department of Health Science, Brigham Young University, Provo, UT (E.L.T.); and Department of Neurology, School of Medicine, University of Cincinnati, OH (B.M.K.)
| | - Evan L Thacker
- From the Department of Biostatistics (G.H., S.E.J.) and Department of Epidemiology (V.J.H.), UAB School of Public Health; Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC (L.E.W.); Department of Medicine, Yale University School of Medicine, New Haven, CT (W.N.K.); Department of Medicine, University of Vermont College of Medicine, Burlington (M.C.); Department of Health Science, Brigham Young University, Provo, UT (E.L.T.); and Department of Neurology, School of Medicine, University of Cincinnati, OH (B.M.K.)
| | - Suzanne E Judd
- From the Department of Biostatistics (G.H., S.E.J.) and Department of Epidemiology (V.J.H.), UAB School of Public Health; Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC (L.E.W.); Department of Medicine, Yale University School of Medicine, New Haven, CT (W.N.K.); Department of Medicine, University of Vermont College of Medicine, Burlington (M.C.); Department of Health Science, Brigham Young University, Provo, UT (E.L.T.); and Department of Neurology, School of Medicine, University of Cincinnati, OH (B.M.K.)
| | - Virginia J Howard
- From the Department of Biostatistics (G.H., S.E.J.) and Department of Epidemiology (V.J.H.), UAB School of Public Health; Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC (L.E.W.); Department of Medicine, Yale University School of Medicine, New Haven, CT (W.N.K.); Department of Medicine, University of Vermont College of Medicine, Burlington (M.C.); Department of Health Science, Brigham Young University, Provo, UT (E.L.T.); and Department of Neurology, School of Medicine, University of Cincinnati, OH (B.M.K.)
| | - Brett M Kissela
- From the Department of Biostatistics (G.H., S.E.J.) and Department of Epidemiology (V.J.H.), UAB School of Public Health; Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC (L.E.W.); Department of Medicine, Yale University School of Medicine, New Haven, CT (W.N.K.); Department of Medicine, University of Vermont College of Medicine, Burlington (M.C.); Department of Health Science, Brigham Young University, Provo, UT (E.L.T.); and Department of Neurology, School of Medicine, University of Cincinnati, OH (B.M.K.)
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129
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Effoe VS, Rodriguez CJ, Wagenknecht LE, Evans GW, Chang PP, Mirabelli MC, Bertoni AG. Carotid intima-media thickness is associated with incident heart failure among middle-aged whites and blacks: the Atherosclerosis Risk in Communities study. J Am Heart Assoc 2014; 3:e000797. [PMID: 24815496 PMCID: PMC4309069 DOI: 10.1161/jaha.114.000797] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Increased carotid intima‐media thickness (IMT) is associated with subclinical left ventricular myocardial dysfunction, suggesting a possible role of carotid IMT in heart failure (HF) risk determination. Methods and Results Mean far wall carotid IMT, measured by B‐mode ultrasound, was available for 13 590 Atherosclerosis Risk in Communities study participants aged 45 to 64 years and free of HF at baseline. HF was defined using ICD‐9 428 and ICD‐10 I‐50 codes from hospitalization records and death certificates. The association between carotid IMT and incident HF was assessed using Cox proportional hazards analysis with models adjusted for demographic variables, major CVD risk factors, and interim CHD. There were 2008 incident HF cases over a median follow‐up of 20.6 years (8.1 cases per 1000 person‐years). Mean IMT was higher in those with HF than in those without (0.81 mm±0.23 versus 0.71 mm±0.17, P<0.001). Unadjusted rate of HF for the fourth compared with the first quartile of IMT was 15.4 versus 3.9 per 1000 person‐years; P<0.001. In multivariable analysis, after adjustment, each standard deviation increase in IMT was associated with incident HF (HR 1.20 [95% CI: 1.16 to 1.25]). After adjustment, the top quartile of IMT was associated with HF (HR 1.60 [95% CI: 1.37 to 1.87]). Results were similar across race and gender groups. Conclusions Increasing carotid IMT is associated with incident HF in middle‐aged whites and blacks, beyond risks explained by major CVD risk factors and CHD. This suggests that carotid IMT may be associated with HF through mechanisms different from myocardial ischemia or infarction.
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Affiliation(s)
- Valery S Effoe
- Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC
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130
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Gottesman RF, Rawlings AM, Sharrett AR, Albert M, Alonso A, Bandeen-Roche K, Coker LH, Coresh J, Couper DJ, Griswold ME, Heiss G, Knopman DS, Patel MD, Penman AD, Power MC, Selnes OA, Schneider ALC, Wagenknecht LE, Windham BG, Wruck LM, Mosley TH. Impact of differential attrition on the association of education with cognitive change over 20 years of follow-up: the ARIC neurocognitive study. Am J Epidemiol 2014; 179:956-66. [PMID: 24627572 DOI: 10.1093/aje/kwu020] [Citation(s) in RCA: 83] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Studies of long-term cognitive change should account for the potential effects of education on the outcome, since some studies have demonstrated an association of education with dementia risk. Evaluating cognitive change is more ideal than evaluating cognitive performance at a single time point, because it should be less susceptible to confounding. In this analysis of 14,020 persons from a US cohort study, the Atherosclerosis Risk in Communities (ARIC) Study, we measured change in performance on 3 cognitive tests over a 20-year period, from ages 48-67 years (1990-1992) through ages 70-89 years (2011-2013). Generalized estimating equations were used to evaluate the association between education and cognitive change in unweighted adjusted models, in models incorporating inverse probability of attrition weighting, and in models using cognitive scores imputed from the Telephone Interview for Cognitive Status for participants not examined in person. Education did not have a strong relationship with change in cognitive test performance, although the rate of decline was somewhat slower among persons with lower levels of education. Methods used to account for selective dropout only marginally changed these observed associations. Future studies of risk factors for cognitive impairment should focus on cognitive change, when possible, to allow for reduction of confounding by social or cultural factors.
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131
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Hellwege JN, Palmer ND, Raffield LM, Ng MCY, Hawkins GA, Long J, Lorenzo C, Norris JM, Ida Chen YD, Speliotes EK, Rotter JI, Langefeld CD, Wagenknecht LE, Bowden DW. Genome-wide family-based linkage analysis of exome chip variants and cardiometabolic risk. Genet Epidemiol 2014; 38:345-52. [PMID: 24719370 DOI: 10.1002/gepi.21801] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2013] [Revised: 02/14/2014] [Accepted: 02/28/2014] [Indexed: 01/31/2023]
Abstract
Linkage analysis of complex traits has had limited success in identifying trait-influencing loci. Recently, coding variants have been implicated as the basis for some biomedical associations. We tested whether coding variants are the basis for linkage peaks of complex traits in 42 African-American (n = 596) and 90 Hispanic (n = 1,414) families in the Insulin Resistance Atherosclerosis Family Study (IRASFS) using Illumina HumanExome Beadchips. A total of 92,157 variants in African Americans (34%) and 81,559 (31%) in Hispanics were polymorphic and tested using two-point linkage and association analyses with 37 cardiometabolic phenotypes. In African Americans 77 LOD scores greater than 3 were observed. The highest LOD score was 4.91 with the APOE SNP rs7412 (MAF = 0.13) with plasma apolipoprotein B (ApoB). This SNP was associated with ApoB (P-value = 4 × 10(-19)) and accounted for 16.2% of the variance in African Americans. In Hispanic families, 104 LOD scores were greater than 3. The strongest evidence of linkage (LOD = 4.29) was with rs5882 (MAF = 0.46) in CETP with HDL. CETP variants were strongly associated with HDL (0.00049 < P-value <4.6 × 10(-12)), accounting for up to 4.5% of the variance. These loci have previously been shown to have effects on the biomedical traits evaluated here. Thus, evidence of strong linkage in this genome wide survey of primarily coding variants was uncommon. Loci with strong evidence of linkage was characterized by large contributions to the variance, and, in these cases, are common variants. Less compelling evidence of linkage and association was observed with additional loci that may require larger family sets to confirm.
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Affiliation(s)
- Jacklyn N Hellwege
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America; Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America; Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
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132
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Goodarzi MO, Langefeld CD, Xiang AH, Chen YDI, Guo X, Hanley AJG, Raffel LJ, Kandeel F, Buchanan TA, Norris JM, Fingerlin TE, Lorenzo C, Rewers MJ, Haffner SM, Bowden DW, Rich SS, Bergman RN, Rotter JI, Watanabe RM, Wagenknecht LE. Insulin sensitivity and insulin clearance are heritable and have strong genetic correlation in Mexican Americans. Obesity (Silver Spring) 2014; 22:1157-64. [PMID: 24124113 PMCID: PMC3968231 DOI: 10.1002/oby.20639] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2013] [Revised: 08/29/2013] [Accepted: 10/02/2013] [Indexed: 11/08/2022]
Abstract
OBJECTIVE The GUARDIAN (Genetics UndeRlying DIAbetes in HispaNics) consortium is described, along with heritability estimates and genetic and environmental correlations of insulin sensitivity and metabolic clearance rate of insulin (MCRI). METHODS GUARDIAN is comprised of seven cohorts, consisting of 4,336 Mexican-American individuals in 1,346 pedigrees. Insulin sensitivity (SI ), MCRI, and acute insulin response (AIRg) were measured by frequently sampled intravenous glucose tolerance test in four cohorts. Insulin sensitivity (M, M/I) and MCRI were measured by hyperinsulinemic-euglycemic clamp in three cohorts. Heritability and genetic and environmental correlations were estimated within the family cohorts (totaling 3,925 individuals) using variance components. RESULTS Across studies, age, and gender-adjusted heritability of insulin sensitivity (SI , M, M/I) ranged from 0.23 to 0.48 and of MCRI from 0.35 to 0.73. The ranges for the genetic correlations were 0.91 to 0.93 between SI and MCRI; and -0.57 to -0.59 for AIRg and MCRI (all P < 0.0001). The ranges for the environmental correlations were 0.54 to 0.74 for SI and MCRI (all P < 0.0001); and -0.16 to -0.36 for AIRg and MCRI (P < 0.0001-0.06). CONCLUSIONS These data support a strong familial basis for insulin sensitivity and MCRI in Mexican Americans. The strong genetic correlations between MCRI and SI suggest common genetic determinants.
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Affiliation(s)
- Mark O. Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California
- the Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Carl D. Langefeld
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Anny H. Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California Medical Group, Pasadena, California
| | - Yii-Der I. Chen
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Anthony J. G. Hanley
- Departments of Nutritional Sciences and Medicine and Dalla Lana School of Public Health, University of Toronto, Ontario, Canada
| | - Leslie J. Raffel
- the Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Fouad Kandeel
- Department of Diabetes, Endocrinology and Metabolism, City of Hope, Duarte, California
| | - Thomas A. Buchanan
- Department of Medicine, University of Southern California Keck School of Medicine, Los Angeles, California
- Department of Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, California
| | - Jill M. Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado
| | - Tasha E. Fingerlin
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado
| | - Carlos Lorenzo
- Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, Texas
| | - Marian J. Rewers
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado
| | | | - Donald W. Bowden
- Department of Biochemistry, Centers for Diabetes Research and Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia
| | - Richard N. Bergman
- Diabetes and Obesity Research Institute, Burns and Allen Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Richard M. Watanabe
- Department of Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, California
- Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, California
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
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Chang PP, Chambless LE, Shahar E, Bertoni AG, Russell SD, Ni H, He M, Mosley TH, Wagenknecht LE, Samdarshi TE, Wruck LM, Rosamond WD. Incidence and survival of hospitalized acute decompensated heart failure in four US communities (from the Atherosclerosis Risk in Communities Study). Am J Cardiol 2014; 113:504-10. [PMID: 24342763 DOI: 10.1016/j.amjcard.2013.10.032] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2013] [Revised: 10/05/2013] [Accepted: 10/05/2013] [Indexed: 11/19/2022]
Abstract
Most population-based estimates of incident hospitalized heart failure (HF) have not differentiated acute decompensated heart failure (ADHF) from chronic stable HF nor included racially diverse populations. The Atherosclerosis Risk in Communities Study conducted surveillance of hospitalized HF events (age ≥55 years) in 4 US communities. We estimated hospitalized ADHF incidence and survival by race and gender. Potential 2005 to 2009 HF hospitalizations were identified by International Classification of Diseases, Ninth Revision, Clinical Modification, codes; 6,168 records were reviewed to validate ADHF cases. Population estimates were derived from US Census data; 50% of eligible hospitalizations were classified as ADHF, of which 63.6% were incident ADHF and 36.4% were recurrent ADHF. The average incidence of hospitalized ADHF was 11.6 per 1,000 persons, aged ≥55 years, per year, and recurrent hospitalized ADHF was 6.6 per 1,000 persons/yr. Age-adjusted annual ADHF incidence was highest for black men (15.7 per 1,000), followed by black women (13.3 per 1,000), white men (12.3 per 1,000), and white women (9.9 per 1,000). Of incident ADHF events with heart function assessment (89%), 53% had reduced the ejection fraction (heart failure with reduced ejection fraction [HFrEF]) and 47% had preserved ejection fraction (heart failure with preserved ejection fraction [HFpEF]). Black men had the highest proportion of acute HFrEF events (70%); white women had the highest proportion of acute HFpEF (59%). Age-adjusted 28-day and 1-year case fatality after an incident ADHF was 10.4% and 29.5%, respectively. Survival did not differ by race or gender. In conclusion, ADHF hospitalization and HF type varied by both race and gender, but case fatality rates did not. Further studies are needed to explain why black men are at higher risk of hospitalized ADHF and HFrEF.
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Affiliation(s)
- Patricia P Chang
- Department of Medicine, University of North Carolina, Chapel Hill, North Carolina.
| | - Lloyd E Chambless
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
| | - Eyal Shahar
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona
| | - Alain G Bertoni
- Department of Public Health Sciences, Wake Forest University, Winston-Salem, North Carolina
| | - Stuart D Russell
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Hanyu Ni
- Centers for Disease Control and Prevention, National Center for Health Statistics, Hyattsville, Maryland
| | - Max He
- Duke Clinical Research Institute, Durham, North Carolina
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Lynne E Wagenknecht
- Department of Public Health Sciences, Wake Forest University, Winston-Salem, North Carolina
| | - Tandaw E Samdarshi
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Lisa M Wruck
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
| | - Wayne D Rosamond
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina
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Register TC, Hruska KA, Divers J, Bowden DW, Palmer ND, Carr JJ, Wagenknecht LE, Hightower RC, Xu J, Smith SC, Dietzen DJ, Langefeld CD, Freedman BI. Sclerostin is positively associated with bone mineral density in men and women and negatively associated with carotid calcified atherosclerotic plaque in men from the African American-Diabetes Heart Study. J Clin Endocrinol Metab 2014; 99:315-21. [PMID: 24178795 PMCID: PMC3879670 DOI: 10.1210/jc.2013-3168] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [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: 11/19/2022]
Abstract
CONTEXT Bone mineral density (BMD) and calcified atherosclerotic plaque (CP) demonstrate inverse relationships. Sclerostin, an endogenous regulator of the Wnt pathway and bone formation, has been associated with impaired osteoblast activation and may play a role in vascular calcification. OBJECTIVE Our objective was to assess the relationships between sclerostin, BMD, and CP. DESIGN Generalized linear models were fitted to test for associations between sclerostin, volumetric BMD (vBMD), and CP. PARTICIPANTS A targeted population of 450 unrelated African Americans (AAs) with type 2 diabetes (T2D) was 56% female with mean/SD/median age of 55.4/9.5/55.0 years and a diabetes duration of 10.3/8.2/8.0 years. MAIN OUTCOME MEASURES Plasma sclerostin, computed tomography-derived thoracic and lumbar vertebrae trabecular vBMD, coronary artery, carotid artery, and aortoiliac CP were measured. RESULTS Plasma sclerostin was 1119/401/1040 pg/mL, thoracic vBMD was 206.3/52.4/204.8 mg/cm3, lumbar vBMD was 180.7/47.0/179.0 mg/cm3, coronary artery CP score was 284/648/13, carotid artery CP score was 46/132/0, and aortoiliac CP score was 1613/2910/282. Sclerostin levels were higher in men than women (P<.0001). Before and after adjusting for age, sex, body mass index, blood pressure, smoking, hemoglobin A1c, and low-density lipoprotein-cholesterol, plasma sclerostin levels were positively associated with thoracic and lumbar vertebrae vBMD (P<.0001). Sex-stratified analyses verified significant relationships in both men and women (both P<.001). Sclerostin was not associated with CP except for an inverse relationship with carotid CP in men (fully adjusted model, P=.03). CONCLUSIONS In this cross-sectional study of AA men and women with T2D, circulating sclerostin was positively associated with vBMD in the spine in both sexes and inversely associated with carotid artery CP in men. Sclerostin may play a role in skeletal mineral metabolism in AA but fails to explain inverse relationships between BMD and CP.
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Affiliation(s)
- Thomas C Register
- Departments of Pathology (T.C.R.), Public Health Sciences (J.D., L.E.W., C.D.L.), Radiology (T.C.R., J.J.C., R.C.H.), and Internal Medicine/Nephrology (B.I.F.) and Center for Genomics and Personalized Medicine Research (D.W.B., N.D.P., J.X., S.C.S.), Wake Forest School of Medicine, Winston-Salem, North Carolina 27157; and Department of Pediatric Nephrology (K.A.H., D.J.D.), Washington University School of Medicine, St Louis, Missouri 63110
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Dearborn JL, Knopman D, Sharrett AR, Schneider ALC, Jack CR, Coker LH, Alonso A, Selvin E, Mosley TH, Wagenknecht LE, Windham BG, Gottesman RF. The metabolic syndrome and cognitive decline in the Atherosclerosis Risk in Communities study (ARIC). Dement Geriatr Cogn Disord 2014; 38:337-46. [PMID: 25171458 PMCID: PMC4201882 DOI: 10.1159/000362265] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [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] [Accepted: 03/17/2014] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Midlife metabolic syndrome (MetS) may impact cognitive health as a construct independently of hypertension, hyperlipidemia and other components. METHODS 10,866 participants aged 45-64 years at baseline were assessed for MetS and completed cognitive testing at two later time points (3 and 9 years from the baseline visit). RESULTS MetS is associated with increased odds of low cognitive performance in the domains of executive function and word fluency, but not with 6-year cognitive decline. Individual MetS components explained this association (hypertension, diabetes, low HDL, elevated triglycerides and increased waist circumference). CONCLUSIONS A focus on the individual risk factors as opposed to MetS during midlife is important to reduce the incidence of cognitive impairment in later life.
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Affiliation(s)
- Jennifer L. Dearborn
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
| | | | - A. Richey Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore MD
| | - Andrea L. C. Schneider
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore MD
| | | | - Laura H. Coker
- Department of Neurology, The Wake Forest School of Medicine, Winston-Salem NC
| | - Alvaro Alonso
- Division of Epidemiology and Community Health, School of Public Health, the University of Minnesota, Minneapolis MN
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore MD
| | - Thomas H. Mosley
- Department of Medicine, Division of Geriatrics, the University of Mississippi School of Medicine, Jackson MS
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem NC
| | - Beverly G. Windham
- Department of Medicine, Division of Geriatrics, the University of Mississippi School of Medicine, Jackson MS
| | - Rebecca F Gottesman
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD
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An SS, Palmer ND, Hanley AJG, Ziegler JT, Brown WM, Freedman BI, Register TC, Rotter JI, Guo X, Chen YDI, Wagenknecht LE, Langefeld CD, Bowden DW. Genetic analysis of adiponectin variation and its association with type 2 diabetes in African Americans. Obesity (Silver Spring) 2013; 21:E721-9. [PMID: 23512866 PMCID: PMC3690163 DOI: 10.1002/oby.20419] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2012] [Accepted: 02/04/2013] [Indexed: 01/02/2023]
Abstract
OBJECTIVE Adiponectin is an adipocytokine that has been implicated in a variety of metabolic disorders, including T2D and cardiovascular disease. Studies evaluating genetic variants in ADIPOQ have been contradictory when testing association with T2D in different ethnic groups. DESIGN AND METHODS In this study, 18 SNPs in ADIPOQ were tested for association with plasma adiponectin levels and diabetes status. SNPs were examined in two independent African-American cohorts (nmax = 1,116) from the Insulin Resistance Atherosclerosis Family Study (IRASFS) and the African American-Diabetes Heart Study (AA-DHS). RESULTS Five polymorphisms were nominally associated with plasma adiponectin levels in the meta-analysis (P = 0.035-1.02 × 10(-6) ) including a low frequency arginine to cysteine mutation (R55C) which reduced plasma adiponectin levels to <15% of the mean. Variants were then tested for association with T2D in a meta-analysis of these and the Wake Forest T2D case-control study (n = 3,233 T2D, 2645 non-T2D). Association with T2D was not observed (P ≥ 0.08), suggesting limited influence of ADIPOQ variants on T2D risk. CONCLUSIONS Despite identification of variants associated with adiponectin levels, a detailed genetic analysis of ADIPOQ revealed no association with T2D risk. This puts into question the role of adiponectin in T2D pathogenesis: whether low adiponectin levels are truly causal for or rather a consequence.
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Affiliation(s)
- S. Sandy An
- Department of Biochemistry, Wake Forest School of Medicine,
Winston-Salem, NC
- Center for Genomics and Personalized Medicine Research, Wake Forest
School of Medicine, Winston-Salem, NC
- Center for Diabetes Research, Wake Forest School of Medicine,
Winston-Salem, NC
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of Medicine,
Winston-Salem, NC
- Center for Genomics and Personalized Medicine Research, Wake Forest
School of Medicine, Winston-Salem, NC
- Center for Diabetes Research, Wake Forest School of Medicine,
Winston-Salem, NC
| | - Anthony J. G. Hanley
- Nutritional Sciences, Medicine, and Dalla Lana School of Public
Health, University of Toronto, Toronto, Canada
| | - Julie T. Ziegler
- Department of Biostatistical Sciences, Wake Forest School of
Medicine, Winston-Salem, NC
| | - W. Mark Brown
- Department of Biostatistical Sciences, Wake Forest School of
Medicine, Winston-Salem, NC
| | - Barry I. Freedman
- Department of Internal Medicine, Wake Forest School of Medicine,
Winston-Salem, NC
| | - Thomas C. Register
- Department of Pathology, Wake Forest School of Medicine,
Winston-Salem, NC
| | - Jerome I. Rotter
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles,
CA
| | - Xiuqing Guo
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles,
CA
| | - Y.-D. Ida Chen
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles,
CA
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine,
Winston-Salem, NC
| | - Carl D. Langefeld
- Department of Biostatistical Sciences, Wake Forest School of
Medicine, Winston-Salem, NC
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest School of Medicine,
Winston-Salem, NC
- Center for Genomics and Personalized Medicine Research, Wake Forest
School of Medicine, Winston-Salem, NC
- Center for Diabetes Research, Wake Forest School of Medicine,
Winston-Salem, NC
- Department of Internal Medicine, Wake Forest School of Medicine,
Winston-Salem, NC
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Samaropoulos XF, Hairston KG, Anderson A, Haffner SM, Lorenzo C, Montez M, Norris JM, Scherzinger AL, Ida Chen YD, Wagenknecht LE. A metabolically healthy obese phenotype in hispanic participants in the IRAS family study. Obesity (Silver Spring) 2013; 21:2303-9. [PMID: 23418072 PMCID: PMC3661693 DOI: 10.1002/oby.20326] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [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: 02/06/2012] [Accepted: 12/09/2012] [Indexed: 01/23/2023]
Abstract
OBJECTIVE Some obese individuals appear to be protected from developing type 2 diabetes mellitus and cardiovascular disease (CVD). This has led to characterizing body size phenotypes based on cardiometabolic risk factors specifically as obese or overweight, and as metabolically healthy (MH) or metabolically abnormal (MA) based upon blood pressure, lipids, glucose homeostasis, and inflammatory parameters. The aim of this study was to measure the prevalence of and describe fat distribution across these phenotypes in a minority population. DESIGN AND METHODS Hispanic participants (N = 1054) in the IRAS Family Study were categorized into different body size phenotypes. Computed tomography (CT) abdominal scans were evaluated for measures of nonalcoholic fatty liver disease (NAFLD) and abdominal fat distribution. Statistical models adjusting for familial relationships were estimated. RESULTS Seventy percent (70%) of the Hispanic cohort was overweight (32%) or obese (38%). Forty-one percent (n = 138) of overweight participants and 19% (n = 74) of obese participants met criteria for MH. Adjusted analyses showed the MH phenotype was associated with lower visceral adipose tissue (VAT) and higher liver density (indicating lower fat content) in obese participants (p = 0.0005 and p = 0.0002, respectively), and lower VAT but not liver density in overweight participants (p = 0.008 and p = 0.162, respectively) compared to their MA counterparts. Odds of NAFLD were reduced in MH obese (OR = 0.34, p = 0.0007) compared to MA obese. VAT did not differ between MH obese or overweight and normal weight groups. CONCLUSIONS These findings suggest that lower levels of visceral and liver fat, despite overall increased total body fat, may be a defining feature of MH obesity in Hispanic Americans.
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Affiliation(s)
- Xanthia F. Samaropoulos
- Department of Medicine, Section of Endocrinology and Metabolism, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Kristen G. Hairston
- Department of Medicine, Section of Endocrinology and Metabolism, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Andrea Anderson
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Steven M. Haffner
- Department of Medicine, University of Texas at San Antonio Health Sciences Center, San Antonio, Texas, USA
| | - Carlos Lorenzo
- Department of Medicine, University of Texas at San Antonio Health Sciences Center, San Antonio, Texas, USA
| | - Maria Montez
- Department of Medicine, University of Texas at San Antonio Health Sciences Center, San Antonio, Texas, USA
| | - Jill M. Norris
- Department of Preventive Medicine and Biometrics, University of Colorado at Denver Health Sciences Center, Denver, Colorado, USA
| | - Ann L. Scherzinger
- Department of Radiology, University of Colorado, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Yii-Der Ida Chen
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
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Festa A, Haffner SM, Wagenknecht LE, Lorenzo C, Hanley AJG. Longitudinal decline of β-cell function: comparison of a direct method vs a fasting surrogate measure: the Insulin Resistance Atherosclerosis Study. J Clin Endocrinol Metab 2013; 98:4152-9. [PMID: 23884776 PMCID: PMC3790620 DOI: 10.1210/jc.2013-1937] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [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: 12/31/2022]
Abstract
CONTEXT β-Cell function (BCF) declines over the course of type 2 diabetes, but little is known about BCF changes across glucose tolerance status (GTS) categories, and comparisons of direct vs surrogate measures. OBJECTIVE To assess longitudinal changes in BCF across GTS. DESIGN The Insulin Resistance Atherosclerosis Study is a multicenter, observational, epidemiologic study. SETTING Four clinical centers in the US that could identify subjects likely to have impaired fasting glucose (IFG) or impaired glucose tolerance (IGT). PATIENTS We compared longitudinal changes in BCF in 1052 subjects over 5 years. Subjects were categorized according to baseline GTS: normal glucose tolerance (NGT: n = 547), impaired fasting glucose or impaired glucose tolerance (IFG/IGT: n = 341), and newly diagnosed type 2 diabetes (n = 164). INTERVENTIONS None. MAIN OUTCOME MEASURES BCF was assessed from a frequently sampled iv glucose tolerance test (AIR, acute insulin response), and the homeostasis model assessment of BCF (HOMA B). RESULTS NGT and IFG/IGT subjects increased their insulin secretion over time, whereas those with type 2 diabetes experienced either decline or little change in BCF. After adjustment for demographic variables and change in insulin resistance, change in HOMA B underestimated the magnitude of changes in BCF, as assessed by change in AIR. Relative to NGT, the 5-year change in insulin secretion in IFG/IGT and type 2 diabetes was 31% and 70% lower (by HOMA B) and 50% and 80% lower (by AIR). CONCLUSIONS The decline in BCF over time in IFG/IGT and type 2 diabetes may be more pronounced than previously estimated; HOMA B may underestimate this decline significantly.
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Affiliation(s)
- A Festa
- PhD, University of Toronto, 150 College Street, Room 341, Toronto, ON, M5S 3E2.
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McCaffery JM, Papandonatos GD, Huggins GS, Peter I, Erar B, Kahn SE, Knowler WC, Lipkin EW, Kitabchi AE, Wagenknecht LE, Wing RR. Human cardiovascular disease IBC chip-wide association with weight loss and weight regain in the look AHEAD trial. Hum Hered 2013; 75:160-74. [PMID: 24081232 DOI: 10.1159/000353181] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND/AIMS The present study identified genetic predictors of weight change during behavioral weight loss treatment. METHODS Participants were 3,899 overweight/obese individuals with type 2 diabetes from Look AHEAD, a randomized controlled trial to determine the effects of intensive lifestyle intervention (ILI), including weight loss and physical activity, relative to diabetes support and education, on cardiovascular outcomes. Analyses focused on associations of single nucleotide polymorphisms (SNPs) on the Illumina CARe iSelect (IBC) chip (minor allele frequency >5%; n = 31,959) with weight change at year 1 and year 4, and weight regain at year 4, among individuals who lost ≥ 3% at year 1. RESULTS Two novel regions of significant chip-wide association with year-1 weight loss in ILI were identified (p < 2.96E-06). ABCB11 rs484066 was associated with 1.16 kg higher weight per minor allele at year 1, whereas TNFRSF11A, or RANK, rs17069904 was associated with 1.70 kg lower weight per allele at year 1. CONCLUSIONS This study, the largest to date on genetic predictors of weight loss and regain, indicates that SNPs within ABCB11, related to bile salt transfer, and TNFRSF11A, implicated in adipose tissue physiology, predict the magnitude of weight loss during behavioral intervention. These results provide new insights into potential biological mechanisms and may ultimately inform weight loss treatment.
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Affiliation(s)
- Jeanne M McCaffery
- Weight Control and Diabetes Research Center, Department of Psychiatry and Human Behavior, The Miriam Hospital and Brown Medical School, Providence, R.I., USA
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Palmer ND, Musani SK, Yerges-Armstrong LM, Feitosa MF, Bielak LF, Hernaez R, Kahali B, Carr JJ, Harris TB, Jhun MA, Kardia SLR, Langefeld CD, Mosley TH, Norris JM, Smith AV, Taylor HA, Wagenknecht LE, Liu J, Borecki IB, Peyser PA, Speliotes EK. Characterization of European ancestry nonalcoholic fatty liver disease-associated variants in individuals of African and Hispanic descent. Hepatology 2013; 58:966-75. [PMID: 23564467 PMCID: PMC3782998 DOI: 10.1002/hep.26440] [Citation(s) in RCA: 109] [Impact Index Per Article: 9.9] [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: 11/21/2012] [Accepted: 04/03/2013] [Indexed: 12/15/2022]
Abstract
UNLABELLED Nonalcoholic fatty liver disease (NAFLD) is an obesity-related condition affecting over 50% of individuals in some populations and is expected to become the number one cause of liver disease worldwide by 2020. Common, robustly associated genetic variants in/near five genes were identified for hepatic steatosis, a quantifiable component of NAFLD, in European ancestry individuals. Here we tested whether these variants were associated with hepatic steatosis in African- and/or Hispanic-Americans and fine-mapped the observed association signals. We measured hepatic steatosis using computed tomography in five African American (n = 3,124) and one Hispanic American (n = 849) cohorts. All analyses controlled for variation in age, age(2) , gender, alcoholic drinks, and population substructure. Heritability of hepatic steatosis was estimated in three cohorts. Variants in/near PNPLA3, NCAN, LYPLAL1, GCKR, and PPP1R3B were tested for association with hepatic steatosis using a regression framework in each cohort and meta-analyzed. Fine-mapping across African American cohorts was conducted using meta-analysis. African- and Hispanic-American cohorts were 33.9/37.5% male, with average age of 58.6/42.6 years and body mass index of 31.8/28.9 kg/m(2) , respectively. Hepatic steatosis was 0.20-0.34 heritable in African- and Hispanic-American families (P < 0.02 in each cohort). Variants in or near PNPLA3, NCAN, GCKR, PPP1R3B in African Americans and PNPLA3 and PPP1R3B in Hispanic Americans were significantly associated with hepatic steatosis; however, allele frequency and effect size varied across ancestries. Fine-mapping in African Americans highlighted missense variants at PNPLA3 and GCKR and redefined the association region at LYPLAL1. CONCLUSION Multiple genetic variants are associated with hepatic steatosis across ancestries. This explains a substantial proportion of the genetic predisposition in African- and Hispanic-Americans. Missense variants in PNPLA3 and GCKR are likely functional across multiple ancestries.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC
| | | | | | - Mary F Feitosa
- Department of Genetics, Washington University, St. Louis, MO
| | | | - Ruben Hernaez
- Department of Medicine, The Johns Hopkins School of Medicine, Baltimore, MD
| | - Bratati Kahali
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI
| | - J Jeffrey Carr
- Department of Radiologic Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Tamara B Harris
- National Institute on Aging, National Institutes of Health, Bethesda, MD
| | - Min A Jhun
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Sharon LR Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Carl D Langefeld
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi, Jackson, MS
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, Denver, CO
| | | | - Herman A Taylor
- Department of Medicine, University of Mississippi, Jackson, MS
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Jiankang Liu
- Jackson Heart Study, University of Mississippi, Jackson, MS
| | | | | | - Elizabeth K Speliotes
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI
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Huggins GS, Papandonatos GD, Erar B, Belalcazar LM, Brautbar A, Ballantyne C, Kitabchi AE, Wagenknecht LE, Knowler WC, Pownall HJ, Wing RR, Peter I, McCaffery JM. Do genetic modifiers of high-density lipoprotein cholesterol and triglyceride levels also modify their response to a lifestyle intervention in the setting of obesity and type-2 diabetes mellitus?: The Action for Health in Diabetes (Look AHEAD) study. ACTA ACUST UNITED AC 2013; 6:391-9. [PMID: 23861364 DOI: 10.1161/circgenetics.113.000042] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
BACKGROUND High-density lipoprotein cholesterol (HDL-C) and triglycerides are cardiovascular risk factors susceptible to lifestyle behavior modification and genetics. We hypothesized that genetic variants identified by genome-wide association studies as associated with HDL-C or triglyceride levels modify 1-year treatment response to an intensive lifestyle intervention, relative to a usual care of diabetes mellitus support and education. METHODS AND RESULTS We evaluated 82 single-nucleotide polymorphisms, which represent 31 loci demonstrated by genome-wide association studies to be associated with HDL-C and triglycerides, in 3561 participants who consented for genetic studies and met eligibility criteria. Variants associated with higher baseline HDL-C levels, cholesterol ester transfer protein (CETP) rs3764261 and hepatic lipase (LIPC) rs8034802, were found to be associated with HDL-C increases with intensive lifestyle intervention (P=0.0038 and 0.013, respectively) and had nominally significant treatment interactions (P=0.047 and 0.046, respectively). The fatty acid desaturase-2 rs1535 variant, associated with low baseline HDL-C (P=0.017), was associated with HDL-C increases with intensive lifestyle intervention (0.0037) and had a nominal treatment interaction (P=0.035). Apolipoprotein B (rs693) and LIPC (rs8034802) single-nucleotide polymorphisms showed nominally significant associations with HDL-C and triglyceride changes with intensive lifestyle intervention and a treatment interaction (P<0.05). Phosphatidylglycerophosphate synthase-1 single-nucleotide polymorphisms (rs4082919) showed the most significant triglyceride treatment interaction in the full cohort (P=0.0009). CONCLUSIONS This is the first study to identify genetic variants modifying lipid responses to a randomized lifestyle behavior intervention in overweight or obese individuals with diabetes mellitus. The effects of genetic factors on lipid changes may differ from the effects on baseline lipids and are modifiable by behavioral intervention.
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Affiliation(s)
- Gordon S Huggins
- Molecular Cardiology Research Institute, Tufts Medical Center, Boston, MA 02111, USA.
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Wing RR, Bolin P, Brancati FL, Bray GA, Clark JM, Coday M, Crow RS, Curtis JM, Egan CM, Espeland MA, Evans M, Foreyt JP, Ghazarian S, Gregg EW, Harrison B, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Kitabchi AE, Knowler WC, Lewis CE, Maschak-Carey BJ, Montez MG, Murillo A, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Regensteiner JG, Rickman AD, Ryan DH, Safford M, Wadden TA, Wagenknecht LE, West DS, Williamson DF, Yanovski SZ. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med 2013; 369:145-54. [PMID: 23796131 PMCID: PMC3791615 DOI: 10.1056/nejmoa1212914] [Citation(s) in RCA: 1758] [Impact Index Per Article: 159.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
BACKGROUND Weight loss is recommended for overweight or obese patients with type 2 diabetes on the basis of short-term studies, but long-term effects on cardiovascular disease remain unknown. We examined whether an intensive lifestyle intervention for weight loss would decrease cardiovascular morbidity and mortality among such patients. METHODS In 16 study centers in the United States, we randomly assigned 5145 overweight or obese patients with type 2 diabetes to participate in an intensive lifestyle intervention that promoted weight loss through decreased caloric intake and increased physical activity (intervention group) or to receive diabetes support and education (control group). The primary outcome was a composite of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for angina during a maximum follow-up of 13.5 years. RESULTS The trial was stopped early on the basis of a futility analysis when the median follow-up was 9.6 years. Weight loss was greater in the intervention group than in the control group throughout the study (8.6% vs. 0.7% at 1 year; 6.0% vs. 3.5% at study end). The intensive lifestyle intervention also produced greater reductions in glycated hemoglobin and greater initial improvements in fitness and all cardiovascular risk factors, except for low-density-lipoprotein cholesterol levels. The primary outcome occurred in 403 patients in the intervention group and in 418 in the control group (1.83 and 1.92 events per 100 person-years, respectively; hazard ratio in the intervention group, 0.95; 95% confidence interval, 0.83 to 1.09; P=0.51). CONCLUSIONS An intensive lifestyle intervention focusing on weight loss did not reduce the rate of cardiovascular events in overweight or obese adults with type 2 diabetes. (Funded by the National Institutes of Health and others; Look AHEAD ClinicalTrials.gov number, NCT00017953.).
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Wing RR, Bolin P, Brancati FL, Bray GA, Clark JM, Coday M, Crow RS, Curtis JM, Egan CM, Espeland MA, Evans M, Foreyt JP, Ghazarian S, Gregg EW, Harrison B, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Kitabchi AE, Knowler WC, Lewis CE, Maschak-Carey BJ, Montez MG, Murillo A, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Regensteiner JG, Rickman AD, Ryan DH, Safford M, Wadden TA, Wagenknecht LE, West DS, Williamson DF, Yanovski SZ. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med 2013. [PMID: 23796131 DOI: 10.1056/nejm] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Weight loss is recommended for overweight or obese patients with type 2 diabetes on the basis of short-term studies, but long-term effects on cardiovascular disease remain unknown. We examined whether an intensive lifestyle intervention for weight loss would decrease cardiovascular morbidity and mortality among such patients. METHODS In 16 study centers in the United States, we randomly assigned 5145 overweight or obese patients with type 2 diabetes to participate in an intensive lifestyle intervention that promoted weight loss through decreased caloric intake and increased physical activity (intervention group) or to receive diabetes support and education (control group). The primary outcome was a composite of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for angina during a maximum follow-up of 13.5 years. RESULTS The trial was stopped early on the basis of a futility analysis when the median follow-up was 9.6 years. Weight loss was greater in the intervention group than in the control group throughout the study (8.6% vs. 0.7% at 1 year; 6.0% vs. 3.5% at study end). The intensive lifestyle intervention also produced greater reductions in glycated hemoglobin and greater initial improvements in fitness and all cardiovascular risk factors, except for low-density-lipoprotein cholesterol levels. The primary outcome occurred in 403 patients in the intervention group and in 418 in the control group (1.83 and 1.92 events per 100 person-years, respectively; hazard ratio in the intervention group, 0.95; 95% confidence interval, 0.83 to 1.09; P=0.51). CONCLUSIONS An intensive lifestyle intervention focusing on weight loss did not reduce the rate of cardiovascular events in overweight or obese adults with type 2 diabetes. (Funded by the National Institutes of Health and others; Look AHEAD ClinicalTrials.gov number, NCT00017953.).
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Lee CC, Lorenzo C, Haffner SM, Wagenknecht LE, Goodarzi MO, Stefanovski D, Norris JM, Rewers MJ, Hanley AJ. Components of metabolic syndrome and 5-year change in insulin clearance - the Insulin Resistance Atherosclerosis Study. Diabetes Obes Metab 2013; 15:441-7. [PMID: 23216702 PMCID: PMC3810428 DOI: 10.1111/dom.12049] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [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: 09/28/2012] [Revised: 11/09/2012] [Accepted: 12/03/2012] [Indexed: 11/30/2022]
Abstract
AIMS Cross-sectional evidence indicates that abdominal adiposity, hypertension, dyslipidaemia and glycaemia are associated with reduced metabolic clearance rate of insulin (MCRI). Little is known about the progression of MCRI and whether components of metabolic syndrome are associated with the change in MCRI. In this study, we examined the association between components of metabolic syndrome and the 5-year change of MCRI. METHODS At baseline and 5-year follow-up, we measured fasting plasma triglycerides (TG), high-density lipoprotein (HDL) cholesterol, blood pressure (BP), waist circumference (WC) and fasting blood glucose (FBG) in 784 non-diabetic participants in the Insulin Resistance Atherosclerosis Study. MCRI, insulin sensitivity (SI ) and acute insulin response (AIR) were determined from frequently sampled intravenous glucose tolerance tests. RESULTS We observed a 29% decline of MCRI at follow-up. TG, systolic BP and WC at baseline were inversely associated with a decline of MCRI regression models adjusted for age, sex, ethnicity, smoking, alcohol consumption, energy expenditure, family history of diabetes, BMI, SI and AIR [β = -0.057 (95% confidence interval, CI: -0.11, -0.0084) for TG, β = -0.0019 (95% CI: -0.0035, -0.00023) for systolic BP and β = -0.0084 (95% CI: -0.013, -0.0039) for WC; all p < 0.05]. Higher HDL cholesterol at baseline was associated with an increase in MCRI [multivariable-adjusted β = 0.0029 (95% CI: 0.0010, 0.0048), p = 0.002]. FBG at baseline was not associated with MCRI at follow-up [multivariable-adjusted β = 0.0014 (95% CI: -0.0026, 0.0029)]. CONCLUSIONS MCRI declined progressively over 5 years in a non-diabetic cohort. Components of metabolic syndrome at baseline were associated with a significant change in MCRI.
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Affiliation(s)
- C. Christine Lee
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Carlos Lorenzo
- Division of Clinical Epidemiology, University of Texas Health Science Centre, San Antonio, TX, USA
| | - Steven M. Haffner
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Darko Stefanovski
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jill M. Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado, Aurora, CO, USA
| | - Marian J. Rewers
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, USA
| | - Anthony J. Hanley
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine and Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Leadership Sinai Centre for Diabetes, Mount Sinai Hospital, Toronto, Ontario, Canada
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Register TC, Divers J, Bowden DW, Carr JJ, Lenchik L, Wagenknecht LE, Hightower RC, Xu J, Smith SC, Hruska KA, Langefeld CD, Freedman BI. Relationships between serum adiponectin and bone density, adiposity and calcified atherosclerotic plaque in the African American-Diabetes Heart Study. J Clin Endocrinol Metab 2013; 98:1916-22. [PMID: 23543659 PMCID: PMC3644610 DOI: 10.1210/jc.2012-4126] [Citation(s) in RCA: 22] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
CONTEXT Adiposity, bone mineral density (BMD), and calcified atherosclerotic plaque (CP) exhibit complex interrelationships that are not well understood. Adipokines vary in relation to changes in body composition and may play roles in regulation of BMD and risk of cardiovascular disease. OBJECTIVE Our objective was to examine the relationship between serum adiponectin and quantitative computed tomography-derived measures of volumetric BMD (vBMD) in thoracic and lumbar vertebrae, adipose tissue volumes, and CP in coronary, carotid, and infrarenal aortoiliac arteries. Generalized linear models were fitted to test for associations between adiponectin and measured phenotypes. PARTICIPANTS A total of 479 unrelated African Americans with type 2 diabetes, 57% female with a mean ± SD (median) age of 55.6 ± 9.5 (55.0) years and diabetes duration of 10.3 ± 8.2 (8.0) years. RESULTS Serum adiponectin was 8.26 ± 7.41 (6.10) μg/mL, coronary artery CP mass score was 280 ± 634 (14), carotid artery CP was 47 ± 133 (0), and aortoiliac CP was 1616 ± 2864 (319). Women had significantly higher body mass index and serum adiponectin and lower coronary and carotid artery calcium than males (all P < .05). Before and after adjusting for age, sex, body mass index, mean arterial pressure, smoking status, hemoglobin A1c, thiazolidinedione use, and low-density lipoprotein-cholesterol, adiponectin was inversely associated with thoracic and lumbar vertebral vBMD [parameter estimates (PEs) of -0.06 and -0.021, respectively; both P < .0005], visceral adipose tissue (PE -0.02; P < 0.0001), and C-reactive protein (PE -0.07; P < .0001) and positively associated with intermuscular adipose tissue (PE 0.01; P = .03). After covariate adjustment, significant associations were not observed between adiponectin and CP in any vascular bed (P > .1). CONCLUSION Serum adiponectin levels were inversely associated with cross-sectional measures of thoracic and lumbar vertebral vBMD, inflammation, and visceral adiposity in African Americans but not with vascular CP after adjustment for covariates. The data support a regulatory/signaling role for adiponectin in the modulation of bone density.
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Affiliation(s)
- Thomas C Register
- Department of Pathology, Wake Forest School of Medicine, Winston-Salem, North Carolina 27157, USA.
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Lorenzo C, Hartnett S, Hanley AJ, Rewers MJ, Wagenknecht LE, Karter AJ, Haffner SM. Impaired fasting glucose and impaired glucose tolerance have distinct lipoprotein and apolipoprotein changes: the insulin resistance atherosclerosis study. J Clin Endocrinol Metab 2013; 98:1622-30. [PMID: 23450048 PMCID: PMC3615208 DOI: 10.1210/jc.2012-3185] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [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: 11/19/2022]
Abstract
CONTEXT Cardiovascular risk is increased in individuals with impaired glucose tolerance (IGT) and impaired fasting glucose (IFG); however, those with IGT appear to be at greater risk. Lipoprotein abnormalities occur also in the prediabetic state. OBJECTIVE The authors examined lipoprotein composition in IGT and IFG. DESIGN AND SETTING Cross-sectional analysis of a large epidemiological study was done. PARTICIPANTS The Insulin Resistance Atherosclerosis Study had a total of 1107 participants. MAIN MEASURES Lipoproteins and apolipoproteins were measured by conventional methods and lipoprotein composition by nuclear magnetic resonance spectroscopy. RESULTS Compared with normal glucose tolerance, apolipoprotein B (105.2 vs 99.8 mg/dL, P < .05) was high in isolated IFG, triglyceride (1.48 vs 1.16 mmol/L, P < .001) was high in isolated IGT, and high-density lipoprotein cholesterol was low in combined IFG/IGT (1.12 vs 1.26 mmol/L, P < .001). Nuclear magnetic resonance spectroscopy revealed additional changes: increased total low-density lipoprotein (LDL) particles (1190 vs 1096 nmol/L, P < .01) in isolated IFG; increased large very-low-density lipoprotein (3.61 vs 2.47 nmol/L, P < .01) and small LDL subclass particles (665 vs 541 nmol/L, P < .05) and decreased large LDL subclass particles (447 vs 513 nmol/L, P < .01) in isolated IGT; and decreased large high-density lipoprotein subclass particles in combined IFG/IGT (4.24 vs 5.39 μmol/L, P < .001). CONCLUSIONS Isolated IFG is characterized by increased apolipoprotein B and total LDL particles, whereas isolated IGT is associated with increased triglycerides, large very-low-density lipoprotein subclass particles, and structural remodeling of LDL particles. These results may help to explain differences in cardiovascular disease risk in the prediabetic state.
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Affiliation(s)
- Carlos Lorenzo
- Division of Clinical Epidemiology, Department of Medicine, University of Texas Health Science Center, San Antonio, TX 78229, USA.
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147
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Lee CC, Haffner SM, Wagenknecht LE, Lorenzo C, Norris JM, Bergman RN, Stefanovski D, Anderson AM, Rotter JI, Goodarzi MO, Hanley AJ. Insulin clearance and the incidence of type 2 diabetes in Hispanics and African Americans: the IRAS Family Study. Diabetes Care 2013; 36:901-7. [PMID: 23223351 PMCID: PMC3609510 DOI: 10.2337/dc12-1316] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.2] [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 We aimed to identify factors that are independently associated with the metabolic clearance rate of insulin (MCRI) and to examine the association of MCRI with incident type 2 diabetes in nondiabetic Hispanics and African Americans. RESEARCH DESIGN AND METHODS We investigated 1,116 participants in the Insulin Resistance Atherosclerosis Study (IRAS) Family Study with baseline examinations from 2000 to 2002 and follow-up examinations from 2005 to 2006. Insulin sensitivity (S(I)), acute insulin response (AIR), and MCRI were determined at baseline from frequently sampled intravenous glucose tolerance tests. MCRI was calculated as the ratio of the insulin dose over the incremental area under the curve of insulin. Incident diabetes was defined as fasting glucose ≥126 mg/dL or antidiabetic medication use by self-report. RESULTS We observed that S(I) and HDL cholesterol were independent positive correlates of MCRI, whereas fasting insulin, fasting glucose, subcutaneous adipose tissue, visceral adipose tissue, and AIR were independent negative correlates (all P < 0.05) at baseline. After 5 years of follow-up, 71 (6.4%) participants developed type 2 diabetes. Lower MCRI was associated with a higher risk of incident diabetes after adjusting for demographics, lifestyle factors, HDL cholesterol, indexes of obesity and adiposity, and insulin secretion (odds ratio 2.01 [95% CI 1.30-3.10], P = 0.0064, per one-SD decrease in loge-transformed MCRI). CONCLUSIONS Our data showed that lower MCRI predicts the incidence of type 2 diabetes.
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Affiliation(s)
- C Christine Lee
- Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
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148
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Divers J, Wagenknecht LE, Bowden DW, Carr JJ, Hightower RC, Smith SC, Xu J, Langefeld CD, Freedman BI. Albuminuria associates with calcified atherosclerotic plaque in African Americans with diabetes. Diabetes Care 2013; 36:e34-5. [PMID: 23431097 PMCID: PMC3579330 DOI: 10.2337/dc12-1589] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Jasmin Divers
- From the Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina; the
| | - Lynne E. Wagenknecht
- From the Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina; the
| | - Donald W. Bowden
- Section on Endocrinology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina; the
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina; the
- Centers for Diabetes Research and Human Genomics and Personalized Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina; the
| | - J. Jeffrey Carr
- From the Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina; the
- Division of Radiologic Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina; and the
| | - R. Caresse Hightower
- Division of Radiologic Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina; and the
| | - S. Carrie Smith
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina; the
- Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jianzhao Xu
- Centers for Diabetes Research and Human Genomics and Personalized Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina; the
| | - Carl D. Langefeld
- From the Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina; the
| | - Barry I. Freedman
- Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
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Unick JL, Beavers D, Bond DS, Clark JM, Jakicic JM, Kitabchi AE, Knowler WC, Wadden TA, Wagenknecht LE, Wing RR. The long-term effectiveness of a lifestyle intervention in severely obese individuals. Am J Med 2013; 126:236-42, 242.e1-2. [PMID: 23410564 PMCID: PMC3574274 DOI: 10.1016/j.amjmed.2012.10.010] [Citation(s) in RCA: 73] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2012] [Revised: 08/22/2012] [Accepted: 10/01/2012] [Indexed: 11/19/2022]
Abstract
OBJECTIVE Severe obesity (body mass index [BMI] ≥40 kg/m(2)) is a serious public health concern. Although bariatric surgery is an efficacious treatment approach, it is limited in reach; thus, nonsurgical treatment alternatives are needed. We examined the 4-year effects of an intensive lifestyle intervention on body weight and cardiovascular disease risk factors among severely obese, compared with overweight (25 ≤BMI <30), class I (30 ≤BMI <35), and class II obese (35 ≤BMI <40) participants. METHODS There were 5145 individuals with type 2 diabetes (45-76 years, BMI ≥25 kg/m(2)) randomized to an intensive lifestyle intervention or diabetes support and education. The lifestyle intervention group received a behavioral weight loss program that included group and individual meetings, a ≥10% weight loss goal, calorie restriction, and increased physical activity. Diabetes support and education received a less intense educational intervention. Four-year changes in body weight and cardiovascular disease risk factors were assessed. RESULTS Across BMI categories, 4-year changes in body weight were significantly greater in lifestyle participants compared with diabetes support and education (Ps <.05). At year 4, severely obese lifestyle participants lost 4.9%±8.5%, which was similar to class I (4.8%±7.2%) and class II obese participants (4.4%±7.6%), and significantly greater than overweight participants (3.4%±7.0%; P <.05). Four-year changes in low-density-lipoprotein cholesterol, triglycerides, diastolic blood pressure, HbA(1c), and blood glucose were similar across BMI categories in lifestyle participants; however, the severely obese had less favorable improvements in high-density-lipoprotein cholesterol (3.1±0.4 mg/dL) and systolic blood pressure (-1.4±0.7 mm Hg) compared with the less obese (Ps <.05). CONCLUSION Lifestyle interventions can result in important long-term weight losses and improvements in cardiovascular disease risk factors among a significant proportion of severely obese individuals.
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Affiliation(s)
- Jessica L Unick
- Weight Control and Diabetes Research Center, The Miriam Hospital and Warren Alpert Medical School at Brown University, Providence, RI 02903, USA.
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150
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Lorenzo C, Hanley AJG, Wagenknecht LE, Rewers MJ, Stefanovski D, Goodarzi MO, Haffner SM. Relationship of insulin sensitivity, insulin secretion, and adiposity with insulin clearance in a multiethnic population: the insulin Resistance Atherosclerosis study. Diabetes Care 2013; 36:101-3. [PMID: 22933441 PMCID: PMC3526225 DOI: 10.2337/dc12-0101] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [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 We aimed to examine insulin clearance, a compensatory mechanism to changes in insulin sensitivity, across sex, race/ethnicity populations, and varying states of glucose tolerance. RESEARCH DESIGN AND METHODS We measured insulin sensitivity index (S(I)), acute insulin response (AIR), and metabolic clearance rate of insulin (MCRI) by the frequently sampled intravenous glucose tolerance test in 1,295 participants in the Insulin Resistance Atherosclerosis Study. RESULTS MCRI was positively related to S(I) and negatively to AIR and adiposity across sex, race/ethnicity populations, and varying states of glucose tolerance, adiposity, and family history of diabetes. Differences in MCRI by race/ethnicity (lower in African Americans and Hispanics compared with non-Hispanic whites) and glucose tolerance were largely explained by differences in adiposity, S(I), and AIR. CONCLUSIONS Insulin sensitivity, insulin secretion, and adiposity are correlates of insulin clearance and appear to explain differences in insulin clearance by race/ethnicity and glucose tolerance status.
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Affiliation(s)
- Carlos Lorenzo
- Department of Medicine, University of Texas Health Science Center, San Antonio, TX, USA.
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