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Hasbani NR, Westerman KE, Kwak SH, Chen H, Li X, Di Corpo D, Wessel J, Bis JC, Sarnowski C, Wu P, Bielak LF, Guo X, Heard-Costa N, Kinney GL, Mahaney MC, Montasser ME, Palmer ND, Raffield LM, Terry JG, Yanek LR, Bon J, Bowden DW, Brody JA, Duggirala R, Jacobs DR, Kalyani RR, Lange LA, Mitchell BD, Smith JA, Taylor KD, Carson AP, Curran JE, Fornage M, Freedman BI, Gabriel S, Gibbs RA, Gupta N, Kardia SLR, Kral BG, Momin Z, Newman AB, Post WS, Viaud-Martinez KA, Young KA, Becker LC, Bertoni AG, Blangero J, Carr JJ, Pratte K, Psaty BM, Rich SS, Wu JC, Malhotra R, Peyser PA, Morrison AC, Vasan RS, Lin X, Rotter JI, Meigs JB, Manning AK, de Vries PS. Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2023; 16:e004176. [PMID: 38014529 PMCID: PMC10843644 DOI: 10.1161/circgen.123.004176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 09/29/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D. METHODS We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test. RESULTS Using a Bonferroni-corrected significance threshold of P<1.6×10-4, we identified 3 genes (ATP1B1, ARVCF, and LIPG) associated with CAC and 2 genes (ABCG8 and EIF2B2) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both ATP1B1 and ARVCF also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis. CONCLUSIONS These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC.
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Affiliation(s)
- Natalie R Hasbani
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
| | - Kenneth E Westerman
- Department of Medicine, Clinical and Translation Epidemiology Unit (K.E.W., A.K.M.), Massachusetts General Hospital, Boston
- Programs in Metabolism and Medical and Population Genetics (K.E.W., J.B.M., A.K.M.), Broad Institute, Cambridge
- Department of Medicine, Harvard Medical School, Boston, MA (K.E.W., J.B.M., A.K.M.)
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, South Korea (S.H.K.)
| | - Han Chen
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
- School of Biomedical Informatics, Center for Precision Health (H.C.), The University of Texas Health Science Center at Houston
| | - Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health (X. Li, X. Lin), Boston University School of Public Health, MA
| | - Daniel Di Corpo
- Department of Biostatistics (D.D., P.W.), Boston University School of Public Health, MA
| | - Jennifer Wessel
- Department of Epidemiology, Fairbanks School of Public Health, Indianapolis, IN (J.W.)
| | - Joshua C Bis
- Department of Medicine, Cardiovascular Health Research Unit (J.C.B., J.A.B., B.M.P.), University of Washington, Seattle
| | - Chloè Sarnowski
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
| | - Peitao Wu
- Department of Biostatistics (D.D., P.W.), Boston University School of Public Health, MA
| | - Lawrence F Bielak
- Department of Medicine, Harvard Medical School, Boston, MA (K.E.W., J.B.M., A.K.M.)
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-University of California Los Angeles Medical Center, Torrance (X.G., K.D.T.)
| | | | - Gregory L Kinney
- Department of Epidemiology, University of Colorado School of Public Health, Aurora (G.L.K., K.A.Y.)
| | - Michael C Mahaney
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville (M.C.M., J.E.C., J. Blangero)
| | - May E Montasser
- Department of Medicine, Division of Endocrinology Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore (M.E.M., B.D.M.)
| | - Nicholette D Palmer
- Department of Biochemistry (N.D.P., D.W.B.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill (L.M.R.)
| | - James G Terry
- Department of Radiology, Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, TN (J.G.T., J.J.C.)
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (L.R.Y., R.R.K., B.G.K., L.C.B.)
| | - Jessica Bon
- Department of Medicine, Division of Pulmonary Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, PA (J. Bon)
| | - Donald W Bowden
- Department of Biochemistry (N.D.P., D.W.B.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Jennifer A Brody
- Department of Medicine, Cardiovascular Health Research Unit (J.C.B., J.A.B., B.M.P.), University of Washington, Seattle
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, McAllen (R.D.)
| | | | - Rita R Kalyani
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (L.R.Y., R.R.K., B.G.K., L.C.B.)
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, School of Medicine University of Colorado, Aurora (L.A.L.)
| | - Braxton D Mitchell
- Department of Medicine, Division of Endocrinology Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore (M.E.M., B.D.M.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, MD (B.D.M.)
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (L.F.B., J.A.S., S.L.R.K., P.A.P.)
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor (J.A.S.)
| | - Kent D Taylor
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-University of California Los Angeles Medical Center, Torrance (X.G., K.D.T.)
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson (A.P.C.)
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville (M.C.M., J.E.C., J. Blangero)
| | - Myriam Fornage
- Institute of Molecular Medicine (M.F.), The University of Texas Health Science Center at Houston
| | - Barry I Freedman
- Department of Internal Medicine, Section on Nephrology (B.I.F.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Stacey Gabriel
- Genomics Platform (S.G., N.G.), Broad Institute, Cambridge
| | - Richard A Gibbs
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX (R.A.G., Z.M.)
| | - Namrata Gupta
- Genomics Platform (S.G., N.G.), Broad Institute, Cambridge
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (L.F.B., J.A.S., S.L.R.K., P.A.P.)
| | - Brian G Kral
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (L.R.Y., R.R.K., B.G.K., L.C.B.)
| | - Zeineen Momin
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX (R.A.G., Z.M.)
| | - Anne B Newman
- Department of Epidemiology, University of Pittsburgh School of Public Health, PA (A.B.N.)
| | - Wendy S Post
- Division of Cardiology, Johns Hopkins Medicine, Baltimore, MD (W.S.P.)
| | | | - Kendra A Young
- Department of Epidemiology, University of Colorado School of Public Health, Aurora (G.L.K., K.A.Y.)
| | - Lewis C Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (L.R.Y., R.R.K., B.G.K., L.C.B.)
| | - Alain G Bertoni
- Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC (A.G.B.)
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville (M.C.M., J.E.C., J. Blangero)
| | - John J Carr
- Department of Radiology, Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University Medical Center, Nashville, TN (J.G.T., J.J.C.)
| | - Katherine Pratte
- Department of Biostatistics, National Jewish Health, Denver, CO (K.P.)
| | - Bruce M Psaty
- Department of Medicine, Cardiovascular Health Research Unit (J.C.B., J.A.B., B.M.P.), University of Washington, Seattle
- Department of Epidemiology (B.M.P.), University of Washington, Seattle
- Department of Health Systems and Population Health (B.M.P.), University of Washington, Seattle
| | | | - Joseph C Wu
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville (J.C.W.)
- Department of Medicine, Division of Cardiovascular Medicine, Stanford Cardiovascular Institute, Stanford University School of Medicine (J.C.W.), Stanford University, CA
| | - Rajeev Malhotra
- Division of Cardiology (R.M.), Massachusetts General Hospital, Boston
- Department of Radiology Molecular Imaging Program at Stanford (R.M.), Stanford University, CA
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (L.F.B., J.A.S., S.L.R.K., P.A.P.)
| | - Alanna C Morrison
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
| | - Ramachandran S Vasan
- Framingham Heart Study, MA (N.H.-C., R.S.V.)
- Department of Quantitative and Qualitative Health Sciences, University of Texas Health San Antonio School of Public Health (R.S.V.)
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health (X. Li, X. Lin), Boston University School of Public Health, MA
| | | | - James B Meigs
- Division of General Internal Medicine (J.B.M.), Massachusetts General Hospital, Boston
- Programs in Metabolism and Medical and Population Genetics (K.E.W., J.B.M., A.K.M.), Broad Institute, Cambridge
- Department of Medicine, Harvard Medical School, Boston, MA (K.E.W., J.B.M., A.K.M.)
| | - Alisa K Manning
- Department of Medicine, Clinical and Translation Epidemiology Unit (K.E.W., A.K.M.), Massachusetts General Hospital, Boston
- Programs in Metabolism and Medical and Population Genetics (K.E.W., J.B.M., A.K.M.), Broad Institute, Cambridge
- Department of Medicine, Harvard Medical School, Boston, MA (K.E.W., J.B.M., A.K.M.)
| | - Paul S de Vries
- Department of Epidemiology Human Genetics and Environmental Sciences, Human Genetics Center, The University of Texas Health Science Center at Houston School of Public Health (N.R.H., H.C., C.S., A.C.M., P.S.d.V.)
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Lin X, Xiang QY, Li S, Song WL, Wang YJ, Ni YQ, Zhao Y, Li C, Wang Y, Li HH, Liang Z, Zhan JK, Liu YS. BMF-AS1/BMF Promotes Diabetic Vascular Calcification and Aging both In Vitro and In Vivo. Aging Dis 2023; 14:170-183. [PMID: 36818559 PMCID: PMC9937703 DOI: 10.14336/ad.2022.0427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 04/27/2022] [Indexed: 11/18/2022] Open
Abstract
Vascular calcification and aging often increase morbidity and mortality in patients with diabetes mellitus (DM); however, the underlying mechanisms are still unknown. In the present study, we found that Bcl-2 modifying factor (BMF) and BMF antisense RNA 1 (BMF-AS1) were significantly increased in high glucose-induced calcified and senescent vascular smooth muscle cells (VSMCs) as well as artery tissues from diabetic mice. Inhibition of BMF-AS1 and BMF reduced the calcification and senescence of VSMCs, whereas overexpression of BMF-AS1 and BMF generates the opposite results. Mechanistic analysis showed that BMF-AS1 interacted with BMF directly and up-regulated BMF at both mRNA and protein levels, but BMF did not affect the expression of BMF-AS1. Moreover, knocking down BMF-AS1 and BMF suppressed the calcification and senescence of VSMCs, and BMF knockout (BMF-/-) diabetic mice presented less vascular calcification and aging compared with wild type diabetic mice. In addition, higher coronary artery calcification scores (CACs) and increased plasma BMF concentration were found in patients with DM, and there was a positive correlation between CACs and plasma BMF concentration. Thus, BMF-AS1/BMF plays a key role in promoting high glucose-induced vascular calcification and aging both in vitro and in vivo. BMF-AS1 and BMF represent potential therapeutic targets in diabetic vascular calcification and aging.
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Affiliation(s)
- Xiao Lin
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Department of Radiology, the Second Xiangya Hospital of Central South University, Hunan, China.
| | - Qun-Yan Xiang
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Institute of Aging and Age-related Disease Research, Central South University, Hunan, China.
| | - Shuang Li
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Institute of Aging and Age-related Disease Research, Central South University, Hunan, China.
| | - Wan-Ling Song
- Department of Biochemistry, University of Oxford, Oxford, UK.
| | - Yan-Jiao Wang
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Institute of Aging and Age-related Disease Research, Central South University, Hunan, China.
| | - Yu-Qing Ni
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Institute of Aging and Age-related Disease Research, Central South University, Hunan, China.
| | - Yan Zhao
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Institute of Aging and Age-related Disease Research, Central South University, Hunan, China.
| | - Chen Li
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Institute of Aging and Age-related Disease Research, Central South University, Hunan, China.
| | - Yi Wang
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Institute of Aging and Age-related Disease Research, Central South University, Hunan, China.
| | - Hua-Hua Li
- Department of Geriatrics, Hunan Provincial People's Hospital, the First Affiliated Hospital of Hunan Normal University, Hunan, China.
| | - Zhen Liang
- Department of Geriatrics, Shenzhen People's Hospital (the Second Clinical Medical College, Jinan University; the First Affiliated Hospital, Southern University of Science and Technology), Guangdong, China
| | - Jun-Kun Zhan
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Institute of Aging and Age-related Disease Research, Central South University, Hunan, China.,Correspondence should be addressed to: Dr. You-Shuo Liu (E-mail: ) and Jun-Kun Zhan (E-mail: ). the Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - You-Shuo Liu
- Department of Geriatrics, the Second Xiangya Hospital of Central South University, Hunan, China.,Institute of Aging and Age-related Disease Research, Central South University, Hunan, China.,Correspondence should be addressed to: Dr. You-Shuo Liu (E-mail: ) and Jun-Kun Zhan (E-mail: ). the Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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3
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Lin FY, Goebel BP, Lee BC, Lu Y, Baskaran L, Yoon YE, Maliakal GT, Gianni U, Bax AM, Sengupta PP, Slomka PJ, Dey DS, Rozanski A, Han D, Berman DS, Budoff MJ, Miedema MD, Nasir K, Rumberger J, Whelton SP, Blaha MJ, Shaw LJ. Mortality impact of low CAC density predominantly occurs in early atherosclerosis: explainable ML in the CAC consortium. J Cardiovasc Comput Tomogr 2023; 17:28-33. [PMID: 36376147 DOI: 10.1016/j.jcct.2022.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 09/15/2022] [Accepted: 10/28/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND Machine learning (ML) models of risk prediction with coronary artery calcium (CAC) and CAC characteristics exhibit high performance, but are not inherently interpretable. OBJECTIVES To determine the direction and magnitude of impact of CAC characteristics on 10-year all-cause mortality (ACM) with explainable ML. METHODS We analyzed asymptomatic subjects in the CAC consortium. We trained ML models on 80% and tested on 20% of the data with XGBoost, using clinical characteristics + CAC (ML 1) and additional CAC characteristics of CAC density and number of calcified vessels (ML 2). We applied SHAP, an explainable ML tool, to explore the relationship of CAC and CAC characteristics with 10-year all-cause and CV mortality. RESULTS 2376 deaths occurred among 63,215 patients [68% male, median age 54 (IQR 47-61), CAC 3 (IQR 0-94.3)]. ML2 was similar to ML1 to predict all-cause mortality (Area Under the Curve (AUC) 0.819 vs 0.821, p = 0.23), but superior for CV mortality (0.847 vs 0.845, p = 0.03). Low CAC density increased mortality impact, particularly ≤0.75. Very low CAC density ≤0.75 was present in only 4.3% of the patients with measurable density, and 75% occurred in CAC1-100. The number of diseased vessels did not increase mortality overall when simultaneously accounting for CAC and CAC density. CONCLUSION CAC density contributes to mortality risk primarily when it is very low ≤0.75, which is primarily observed in CAC 1-100. CAC and CAC density are more important for mortality prediction than the number of diseased vessels, and improve prediction of CV but not all-cause mortality. Explainable ML techniques are useful to describe granular relationships in otherwise opaque prediction models.
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Affiliation(s)
- Fay Y Lin
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA; Department of Population Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Benjamin P Goebel
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA
| | - Benjamin C Lee
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA
| | - Yao Lu
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Lohendran Baskaran
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA; Department of Cardiology, National Heart Centre Singapore, Singapore
| | - Yeonyee E Yoon
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA; Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Sungnam, South Korea
| | - Gabriel Thomas Maliakal
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA; Department of Computer Science, Michigan State University, East Lansing, MI, USA
| | - Umberto Gianni
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA
| | - A Maxim Bax
- Department of Radiology, New York-Presbyterian Hospital and Weill Cornell Medicine, New York, NY, USA
| | - Partho P Sengupta
- Division of Cardiology, Rutgers Robert Wood Medical School and University Hospital, New Brunswick, NJ, USA
| | - Piotr J Slomka
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Damini S Dey
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alan Rozanski
- Department of Cardiology, Mount Sinai St. Luke's Hospital, New York, NY, USA
| | - Donghee Han
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel S Berman
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Matthew J Budoff
- Department of Medicine, Lundquist Institute at Harbor UCLA Medical Center, Torrance, CA, USA
| | - Michael D Miedema
- Cardiovascular Prevention, Minneapolis Heart Institute Foundation, Minneapolis Heart Institute, Minneapolis, MN, USA
| | - Khurram Nasir
- Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist Hospital, Houston, TX, USA
| | - John Rumberger
- Princeton Longevity Center, Princeton Forrestal Village, Princeton, NJ, USA
| | - Seamus P Whelton
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Michael J Blaha
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, USA
| | - Leslee J Shaw
- Department of Population Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Zhao Y, Malik S, Criqui MH, Allison MA, Budoff MJ, Sandfort V, Wong ND. Coronary calcium density in relation to coronary heart disease and cardiovascular disease in adults with diabetes or metabolic syndrome: the Multi-ethnic Study of Atherosclerosis (MESA). BMC Cardiovasc Disord 2022; 22:536. [PMID: 36494811 PMCID: PMC9733236 DOI: 10.1186/s12872-022-02956-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 11/14/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Coronary artery calcium (CAC) density is inversely associated with coronary heart disease (CHD) and cardiovascular disease (CVD) risk. We examined this relation in those with diabetes mellitus (DM) or metabolic syndrome (MetS). METHODS We studied 3,818 participants with non-zero CAC scores from the Multiethnic Study of Atherosclerosis and classified them as DM, MetS (without DM) or neither DM/MetS. Risk factor-adjusted CAC density was calculated and examined in relation to incident CHD and CVD events over a median follow-up of 15 years among these three disease groups. RESULTS Adjusted CAC density was 2.54, 2.61 and 2.69 among those with DM, MetS or neither DM/MetS. Hazard ratios (HRs) for CHD per 1 SD increase of CAC density was 0.91 (95% CI: 0.72-1.16), 0.70 (95% CI: 0.56-0.87) and 0.79 (95% CI: 0.66-0.95) for those with DM, MetS or neither DM/MetS groups and were 0.77 (95% CI: 0.64-0.94), 0.83 (95% CI: 0.70-0.99) and 0.82 (95% CI: 0.71-0.95) for CVD, respectively. Adjustment for CAC density increased the HRs of CAC volume for CHD/CVD events. Compared to prediction models with or without single CAC measures, c-statistics of models with CAC volume and density were the highest ranging 0.67-0.72. CONCLUSION CAC density is lower among patients with DM or MetS than those with neither DM/MetS and is inversely associated with future CHD/CVD risk among them. Including CAC density in risk assessment among those with MetS may improve prediction of CHD and CVD.
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Affiliation(s)
- Yanglu Zhao
- grid.19006.3e0000 0000 9632 6718Department of Epidemiology, University of California Los Angeles, Los Angeles, USA ,grid.266093.80000 0001 0668 7243Heart Disease Prevention Program, University of California Irvine, Irvine, USA
| | - Shaista Malik
- grid.266093.80000 0001 0668 7243Heart Disease Prevention Program, University of California Irvine, Irvine, USA
| | - Michael H. Criqui
- grid.266100.30000 0001 2107 4242Division of Preventive Medicine, University of California San Diego, San Diego, USA
| | - Matthew A. Allison
- grid.266100.30000 0001 2107 4242Division of Preventive Medicine, University of California San Diego, San Diego, USA
| | - Matthew J. Budoff
- grid.239844.00000 0001 0157 6501Lindquist Institute, Harbor-UCLA Medical Center, Los Angeles, USA
| | - Veit Sandfort
- grid.94365.3d0000 0001 2297 5165Radiology & Imaging Sciences, National Institutes of Health, Bethesda, USA
| | - Nathan D. Wong
- grid.19006.3e0000 0000 9632 6718Department of Epidemiology, University of California Los Angeles, Los Angeles, USA ,grid.266093.80000 0001 0668 7243Heart Disease Prevention Program, University of California Irvine, Irvine, USA
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5
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Akbari J, Shirvani H, Shamsoddini A, Bazgir B, Samadi M. Investigation of expression of myocardial miR-126, miR-29a and miR-222 as a potential marker in STZ- induced diabetic rats following interval and continuous exercise training. J Diabetes Metab Disord 2022; 21:189-195. [PMID: 35673452 PMCID: PMC9167327 DOI: 10.1007/s40200-021-00957-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 12/07/2021] [Indexed: 01/13/2023]
Abstract
Purpose Cardiac miRNAs are the recently discovered key modulators of gene expression in the heart which have been shown to contribute to both transcriptional and post-transcriptional regulation in diabetic cardiomyopathy. The aim of this study was to evaluate the protective effects of interval and continuous aerobic training on diabetic hearts by examining the expression of myocardial miR-126, miR-222 and miR-29a genes. Methods Thirty male wistar rats (200 ± 20 g) were randomly divided into six groups of healthy control (HC), diabetes control (DC), continuous training (CT), interval training (IT), continuous training with diabetes (CTD), and interval training with diabetes (ITD). Nicotinamide and Streptozotocin (STZ) were injected to induce type 2 diabetes. CT was performed with a speed of 10 to 22 m/min and 20 to 30 min and IT was performed with 10 to 39 m/min and total time of 15 min, five sessions per week for 6 weeks. Muscle expression of miR-126, miR-29a and miR-222 was determined by the RT-PCR method. Results The results show that gene expression of miR-126 was higher in IT (p < 0.01) compare to other groups. Also expression of miR-126 was higher in the CT compare to DC (p < 0.05) group. Gene expression of miR-222 was higher in aerobic groups than other groups (p < 0.01). Also expression of miR-222 was higher in ITD compare to the DC and CTD (p < 0.01) groups. Expression of miR-29a gene was higher in the aerobic groups compare to other groups. Also miR-29a was higher in the IT compare to CT (p < 0.01) group. Conclusion Diabetes decreased the expression of genes associated with the development of cardiac function. It seems that IT played a more effective role in cardiac protection than CT through higher miR-126, miR-222 and miR-29a gene expression.
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Affiliation(s)
- Javad Akbari
- Exercise Physiology Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Hossein Shirvani
- Exercise Physiology Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Alireza Shamsoddini
- Exercise Physiology Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Behzad Bazgir
- Exercise Physiology Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Mohammad Samadi
- Exercise Physiology Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
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6
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Lin Y, Zhong X, Xiong Z, Zhang S, Liu M, Fan Y, Huang Y, Sun X, Zhou H, Xu X, Guo Y, Li Y, Yang D, Ye X, Zhuang X, Liao X. Intensity of Glycemic Exposure in Early Adulthood and Target Organ Damage in Middle Age: The CARDIA Study. Front Physiol 2021; 12:614532. [PMID: 34248653 PMCID: PMC8260980 DOI: 10.3389/fphys.2021.614532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 03/19/2021] [Indexed: 11/29/2022] Open
Abstract
AIM To determine whether long-term intensity of glycemic exposure (IGE) during young adulthood is associated with multiple target organs function at midlife independent of single fasting glucose (FG) measurement. METHODS We included 2,859 participants, aged 18-30 years at Y0, in the Coronary Artery Risk Development in Young Adults (CARDIA) Study. IGE was calculated as the sum of (average FG of two consecutive examinations × years between the examinations) over 25 years. Target organs function was indicated by cardiac structure, left ventricular (LV) systolic function, LV diastolic function, coronary artery calcium (CAC), and urine albumin-to-creatinine ratio (UACR) at Y25. We evaluated the associations between IGE with target organs function using linear regression models and estimated the associations between IGE with numbers of organs involved (0, 1, or ≥ 2 organs) using multinomial logistic regression models. RESULTS A 1-SD increment of IGE was significantly associated with worse target organs function after multivariable adjustment: left ventricular mass (β [SE], 5.468 [1.175]); global longitudinal strain (β [SE], 0.161 [0.071]); E/e' ratio (β[SE], 0.192 [0.071]); CAC score (β [SE], 27.948 [6.116]); and log UACR (β [SE], 0.076 [0.010]). Besides, IGE was independently associated with having ≥ 2 organs involved in both overall population (OR [95% CI], 1.48 [1.23, 1.41], P < 0.001) and subgroups stratified by diabetes at Y25. CONCLUSION Higher intensity of glycemic exposure during young adulthood was independently associated with subclinical alterations of target organs function at midlife. Our findings highlight the importance of early screening and management of IGE in youth.
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Affiliation(s)
- Yifen Lin
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Xiangbin Zhong
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Zhenyu Xiong
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Shaozhao Zhang
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Menghui Liu
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Yongqiang Fan
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Yiquan Huang
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Xiuting Sun
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Huimin Zhou
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Xingfeng Xu
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Yue Guo
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Yuqi Li
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Daya Yang
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Xiaomin Ye
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Xiaodong Zhuang
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
| | - Xinxue Liao
- Department of Cardiology, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-sen University, Guangzhou, China
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7
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Rajbhandari J, Fernandez CJ, Agarwal M, Yeap BXY, Pappachan JM. Diabetic heart disease: A clinical update. World J Diabetes 2021; 12:383-406. [PMID: 33889286 PMCID: PMC8040078 DOI: 10.4239/wjd.v12.i4.383] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 02/27/2021] [Accepted: 03/13/2021] [Indexed: 02/06/2023] Open
Abstract
Diabetes mellitus (DM) significantly increases the risk of heart disease, and DM-related healthcare expenditure is predominantly for the management of cardiovascular complications. Diabetic heart disease is a conglomeration of coronary artery disease (CAD), cardiac autonomic neuropathy (CAN), and diabetic cardiomyopathy (DCM). The Framingham study clearly showed a 2 to 4-fold excess risk of CAD in patients with DM. Pathogenic mechanisms, clinical presentation, and management options for DM-associated CAD are somewhat different from CAD among nondiabetics. Higher prevalence at a lower age and more aggressive disease in DM-associated CAD make diabetic individuals more vulnerable to premature death. Although common among diabetic individuals, CAN and DCM are often under-recognised and undiagnosed cardiac complications. Structural and functional alterations in the myocardial innervation related to uncontrolled diabetes result in damage to cardiac autonomic nerves, causing CAN. Similarly, damage to the cardiomyocytes from complex pathophysiological processes of uncontrolled DM results in DCM, a form of cardiomyopathy diagnosed in the absence of other causes for structural heart disease. Though optimal management of DM from early stages of the disease can reduce the risk of diabetic heart disease, it is often impractical in the real world due to many reasons. Therefore, it is imperative for every clinician involved in diabetes care to have a good understanding of the pathophysiology, clinical picture, diagnostic methods, and management of diabetes-related cardiac illness, to reduce morbidity and mortality among patients. This clinical review is to empower the global scientific fraternity with up-to-date knowledge on diabetic heart disease.
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Affiliation(s)
- Jake Rajbhandari
- College of Medical and Dental Sciences, University of Birmingham Medical School, Birmingham B15 2TH, United Kingdom
| | | | - Mayuri Agarwal
- Department of Endocrinology and Metabolism, Pilgrim Hospital, Boston PE21 9QS, United Kingdom
| | - Beverly Xin Yi Yeap
- Department of Medicine, The University of Manchester Medical School, Manchester M13 9PL, United Kingdom
| | - Joseph M Pappachan
- Department of Endocrinology and Metabolism, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, United Kingdom
- Faculty of Science, Manchester Metropolitan University, Manchester M15 6BH, United Kingdom
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PL, United Kingdom
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8
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Chen Y, Zhao X, Wu H. Transcriptional Programming in Arteriosclerotic Disease: A Multifaceted Function of the Runx2 (Runt-Related Transcription Factor 2). Arterioscler Thromb Vasc Biol 2021; 41:20-34. [PMID: 33115268 PMCID: PMC7770073 DOI: 10.1161/atvbaha.120.313791] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Despite successful therapeutic strategies in the prevention and treatment of arteriosclerosis, the cardiovascular complications remain a major clinical and societal issue worldwide. Increased vascular calcification promotes arterial stiffness and accelerates cardiovascular morbidity and mortality. Upregulation of the Runx2 (Runt-related transcription factor 2), an essential osteogenic transcription factor for bone formation, in the cardiovascular system has emerged as an important regulator for adverse cellular events that drive cardiovascular pathology. This review discusses the regulatory mechanisms that are critical for Runx2 expression and function and highlights the dynamic and complex cross talks of a wide variety of posttranslational modifications, including phosphorylation, acetylation, ubiquitination, and O-linked β-N-acetylglucosamine modification, in regulating Runx2 stability, cellular localization, and osteogenic transcriptional activity. How the activation of an array of signaling cascades by circulating and local microenvironmental factors upregulates Runx2 in vascular cells and promotes Runx2-mediated osteogenic transdifferentiation of vascular smooth muscle cells and expression of inflammatory cytokines that accelerate macrophage infiltration and vascular osteoclast formation is summarized. Furthermore, the increasing appreciation of a new role of Runx2 upregulation in promoting vascular smooth muscle cell phenotypic switch, and Runx2 modulated by O-linked β-N-acetylglucosamine modification and Runx2-dependent repression of smooth muscle cell-specific gene expression are discussed. Further exploring the regulation of this key osteogenic transcription factor and its new perspectives in the vasculature will provide novel insights into the transcriptional regulation of vascular smooth muscle cell phenotype switch, reprograming, and vascular inflammation that promote the pathogenesis of arteriosclerosis.
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Affiliation(s)
- Yabing Chen
- Department of Pathology, University of Alabama at Birmingham
- Research Department, Birmingham Veterans Affairs Medical Center, Birmingham, Alabama 35294
| | - Xinyang Zhao
- Department of Biochemistry, University of Alabama at Birmingham
| | - Hui Wu
- Department of Integrative Biomedical & Diagnostic Sciences, Oregon Health and Science University School of Dentistry, Portland, Oregon 97239
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9
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Nashawi M, Sheikh O, Mir M, Te T, Chilton R. The systemic implication of novel non-statin therapies in cardiovascular diabetology: PCSK9 as a case model. Cardiovasc Endocrinol Metab 2020; 9:143-152. [PMID: 33225229 PMCID: PMC7673769 DOI: 10.1097/xce.0000000000000204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 03/23/2020] [Indexed: 12/17/2022]
Abstract
PCSK9, like other novel non-statin drugs were primarily developed to help patients achieve low-density lipoprotein cholesterol targets, especially in patients with dyslipidemia not achieving lipid goals with statins due to poor tolerance or inadequate response. PCSK9 inhibitors, in addition to modulating lipid metabolism, improve mortality outcomes in cardiovascular disease. These benefits are markedly pronounced in patients with type 2 diabetes mellitus. However, these benefits do not come without associated risk. Multiple trials, studies, and case reports have attempted to explain observed outcomes with PCSK9 expression and administration of PCSK9 inhibitors from multiple perspectives, such as their effects on insulin sensitivity and glucose tolerance, changes in renal physiology, thyroid physiology, vascular tone, intestinal regulation of lipids, and improved cardiovascular function. These agents represent an opportunity for physicians to exercise prudence by using appropriate clinical judgement when managing comorbidities in the hyperglycemic patient, a concept that extends to other novel non-statin drugs.
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Affiliation(s)
- Mouhamed Nashawi
- Division of Medicine-Cardiology, UT Health San Antonio, San Antonio, Texas, USA
| | - Omar Sheikh
- Division of Medicine-Cardiology, UT Health San Antonio, San Antonio, Texas, USA
| | - Mahnoor Mir
- Division of Medicine-Cardiology, UT Health San Antonio, San Antonio, Texas, USA
| | - Tri Te
- Division of Medicine-Cardiology, UT Health San Antonio, San Antonio, Texas, USA
| | - Robert Chilton
- Division of Medicine-Cardiology, UT Health San Antonio, San Antonio, Texas, USA
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10
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Mukai H, Dai L, Chen Z, Lindholm B, Ripsweden J, Brismar TB, Heimbürger O, Barany P, Qureshi AR, Söderberg M, Bäck M, Stenvinkel P. Inverse J-shaped relation between coronary arterial calcium density and mortality in advanced chronic kidney disease. Nephrol Dial Transplant 2020; 35:1202-1211. [PMID: 30534995 DOI: 10.1093/ndt/gfy352] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 09/28/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND The coronary artery calcium (CAC) score from cardiac computed tomography (CT) is a composite of CAC volume and CAC density. In the general population, CAC volume is positively and CAC density inversely associated with cardiovascular disease (CVD) events, implying that decreased CAC density reflects atherosclerotic plaque instability. We analysed associations of CAC indices with mortality risk in patients with end-stage renal disease [chronic kidney disease Stage 5 (CKD5)]. METHODS In 296 CKD5 patients undergoing cardiac CT (median age 55 years, 67% male, 19% diabetes, 133 dialysed), the Framingham risk score (FRS), presence of CVD and protein-energy wasting (PEW; subjective global assessment) and high-sensitivity C-reactive protein (hsCRP) and interleukin-6 (IL-6) were determined at baseline. During follow-up for a median of 35 months, 51 patients died and 75 patients underwent renal transplantation. All-cause mortality risk was analysed with competing-risk regression models. Vascular calcification was analysed in biopsies of the arteria epigastrica inferior in 111 patients. RESULTS Patients in the middle tertile of CAC density had the highest CAC score, CAC volume, age, CVD, PEW, FRS, hsCRP and IL-6. In competing risk analysis, the middle {subhazard ratio [sHR] 10.7 [95% confidence interval (CI) 2.0-57.3]} and high [sHR 8.9 (95% CI 1.5-51.8)] tertiles of CAC density associated with increased mortality, independent of CAC volume. The high tertile of CAC volume, independent of CAC density, associated with increased mortality [sHR 8.9 (95% CI 1.5-51.8)]. Arterial media calcification was prominent and associated with CAC volume and CAC density. CONCLUSIONS In CKD5, mortality increased linearly with higher CAC score and CAC volume whereas for CAC density an inverse J-shaped pattern was observed, with the crude mortality rate being highest for the middle tertile of CAC density. CAC volume and CAC density were associated with the extent of arterial media calcification.
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Affiliation(s)
- Hideyuki Mukai
- Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | - Lu Dai
- Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | - Zhimin Chen
- Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | - Bengt Lindholm
- Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | - Jonaz Ripsweden
- Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | - Torkel B Brismar
- Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | - Olof Heimbürger
- Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | - Peter Barany
- Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | - Abdul Rashid Qureshi
- Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
| | - Magnus Söderberg
- Department of Pathology, Drug Safety and Metabolism, AstraZeneca, Mölndal, Sweden
| | - Magnus Bäck
- Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden
| | - Peter Stenvinkel
- Division of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Campus Flemingsberg, Stockholm, Sweden
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11
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Taxiarchi P, Martin GP, Curzen N, Kinnaird T, Ludman P, Johnson T, Kwok CS, Rashid M, Kontopantelis E, Mamas MA. Rotational atherectomy and same day discharge: Safety and growth from a national perspective. Catheter Cardiovasc Interv 2020; 98:678-688. [PMID: 32845064 DOI: 10.1002/ccd.29228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 08/02/2020] [Indexed: 11/12/2022]
Abstract
OBJECTIVES We explore whether same day discharge (SDD) is a feasible and safe practice following rotational atherectomy (ROTA) treatment during elective percutaneous coronary intervention (PCI), and examine which baseline characteristics are independently associated with SDD. BACKGROUND SDD following elective ROTA PCI is not recommended as per the recent SCAI consensus. However, reports show it is practiced and no previous study has evaluated its safety and feasibility. METHODS Our dataset included 4,591 patients undergoing elective ROTA PCI in England & Wales within an 8-years period. Independent associations with SDD were quantified via a multiple logistic regression model and the BCIS 30-day mortality risk model was used to evaluate the safety of SDD. RESULTS The majority of elective ROTA PCI cases remain at the hospital for overnight (ON) observation, although SDD rates increased substantially from 6.7% in 2007 to 35.5% in 2014. The use of glycoprotein IIb/IIIa antagonists, Q wave AMI, left main PCI and valvular heart disease were independently associated with ON, while patients operated underwent transradial PCI were more likely to be SDD (OR = 1.77, 95% CI [1.45-2.15]). Over the study period, observed mortality rates were not significantly higher than those expected from the BCIS risk model. CONCLUSIONS Our findings did not show superiority of the ON strategy over SDD for higher risk cases undergoing elective ROTA PCI, in terms of 30-day mortality. This is the first study to examine the safety of SDD after elective ROTA PCI and more should follow.
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Affiliation(s)
- Paraskevi Taxiarchi
- Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Center, Manchester, UK
| | - Glen P Martin
- Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Center, Manchester, UK
| | - Nick Curzen
- Coronary Research Group, University Hospital Southampton and Faculty of Medicine, University of Southampton, Southampton, UK
| | - Tim Kinnaird
- Department of Cardiology, University Hospital of Wales, Cardiff, UK
| | - Peter Ludman
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
| | | | - Chun Shing Kwok
- Keele Cardiovascular Research Group, Keele University, Keele, UK
| | - Muhammad Rashid
- Keele Cardiovascular Research Group, Keele University, Keele, UK
| | - Evangelos Kontopantelis
- Division of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, UK
| | - Mamas A Mamas
- Keele Cardiovascular Research Group, Keele University, Keele, UK.,Division of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, UK.,Thomas Jefferson University, Philadelphia, Pennsylvania
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12
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Chen Y, Zhao X, Wu H. Arterial Stiffness: A Focus on Vascular Calcification and Its Link to Bone Mineralization. Arterioscler Thromb Vasc Biol 2020; 40:1078-1093. [PMID: 32237904 DOI: 10.1161/atvbaha.120.313131] [Citation(s) in RCA: 98] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
This review focuses on the association between vascular calcification and arterial stiffness, highlighting the important genetic factors, systemic and local microenvironmental signals, and underlying signaling pathways and molecular regulators of vascular calcification. Elevated oxidative stress appears to be a common procalcification factor that induces osteogenic differentiation and calcification of vascular cells in a variety of disease conditions such as atherosclerosis, diabetes mellitus, and chronic kidney disease. Thus, the role of oxidative stress and oxidative stress-regulated signals in vascular smooth muscle cells and their contributions to vascular calcification are highlighted. In relation to diabetes mellitus, the regulation of both hyperglycemia and increased protein glycosylation, by AGEs (advanced glycation end products) and O-linked β-N-acetylglucosamine modification, and its role in enhancing intracellular pathophysiological signaling that promotes osteogenic differentiation and calcification of vascular smooth muscle cells are discussed. In the context of chronic kidney disease, this review details the role of calcium and phosphate homeostasis, parathyroid hormone, and specific calcification inhibitors in regulating vascular calcification. In addition, the impact of the systemic and microenvironmental factors on respective intrinsic signaling pathways that promote osteogenic differentiation and calcification of vascular smooth muscle cells and osteoblasts are compared and contrasted, aiming to dissect the commonalities and distinctions that underlie the paradoxical vascular-bone mineralization disorders in aging and diseases.
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Affiliation(s)
- Yabing Chen
- From the Departments of Pathology (Y.C.), The University of Alabama at Birmingham.,Birmingham Veterans Affairs Medical Center, Research Department, AL (Y.C.)
| | - Xinyang Zhao
- Biochemistry (X.Z.), The University of Alabama at Birmingham
| | - Hui Wu
- Pediatric Dentistry (H.W.), The University of Alabama at Birmingham
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13
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Huo Y, Terry JG, Wang J, Nair S, Lasko TA, Freedman BI, Carr JJ, Landman BA. Fully automatic liver attenuation estimation combing CNN segmentation and morphological operations. Med Phys 2019; 46:3508-3519. [PMID: 31228267 DOI: 10.1002/mp.13675] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 06/13/2019] [Accepted: 06/15/2019] [Indexed: 12/20/2022] Open
Abstract
PURPOSE Manually tracing regions of interest (ROIs) within the liver is the de facto standard method for measuring liver attenuation on computed tomography (CT) in diagnosing nonalcoholic fatty liver disease (NAFLD). However, manual tracing is resource intensive. To address these limitations and to expand the availability of a quantitative CT measure of hepatic steatosis, we propose the automatic liver attenuation ROI-based measurement (ALARM) method for automated liver attenuation estimation. METHODS The ALARM method consists of two major stages: (a) deep convolutional neural network (DCNN)-based liver segmentation and (b) automated ROI extraction. First, liver segmentation was achieved using our previously developed SS-Net. Then, a single central ROI (center-ROI) and three circles ROI (periphery-ROI) were computed based on liver segmentation and morphological operations. The ALARM method is available as an open source Docker container (https://github.com/MASILab/ALARM). RESULTS Two hundred and forty-six subjects with 738 abdomen CT scans from the African American-Diabetes Heart Study (AA-DHS) were used for external validation (testing), independent from the training and validation cohort (100 clinically acquired CT abdominal scans). From the correlation analyses, the proposed ALARM method achieved Pearson correlations = 0.94 with manual estimation on liver attenuation estimations. When evaluating the ALARM method for detection of nonalcoholic fatty liver disease (NAFLD) using the traditional cut point of < 40 HU, the center-ROI achieved substantial agreements (Kappa = 0.79) with manual estimation, while the periphery-ROI method achieved "excellent" agreement (Kappa = 0.88) with manual estimation. The automated ALARM method had reduced variability compared to manual measurements as indicated by a smaller standard deviation. CONCLUSIONS We propose a fully automated liver attenuation estimation method termed ALARM by combining DCNN and morphological operations, which achieved "excellent" agreement with manual estimation for fatty liver detection. The entire pipeline is implemented as a Docker container which enables users to achieve liver attenuation estimation in five minutes per CT exam.
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Affiliation(s)
- Yuankai Huo
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, 37235, USA
| | - James G Terry
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37235, USA
| | - Jiachen Wang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, 37235, USA
| | - Sangeeta Nair
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37235, USA
| | - Thomas A Lasko
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37235, USA
| | - Barry I Freedman
- Department of Internal Medicine-Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - J Jeffery Carr
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37235, USA.,Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37235, USA.,Department of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, 37235, USA
| | - Bennett A Landman
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, 37235, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, 37235, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA.,Institute of Imaging Science, Vanderbilt University, Nashville, TN, 37235, USA
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