Fibroblast Growth Factor-23 and Cardiac Magnetic Resonance Indices of Myocardial Fibrosis in the Multi-Ethnic Study of Atherosclerosis By MOHAMED FAHER ALMAHMOUD, MD A Thesis submitted to the Graduate Faculty of WAKE FOREST UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES In Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE Clinical Population and Translational Sciences May 2016 Winston-Salem, North Carolina Approved by: David M. Herrington, MD, Mentor/Advisor Beverly M. Snively, PhD Jennifer Hawthorne Jordan, PhD, MS
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Fibroblast Growth Factor-23 and Cardiac Magnetic Resonance Indices of
Myocardial Fibrosis in the Multi-Ethnic Study of Atherosclerosis
By
MOHAMED FAHER ALMAHMOUD, MD
A Thesis submitted to the Graduate Faculty of
WAKE FOREST UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES
In Partial Fulfillment of the Requirements
for the Degree of
MASTER OF SCIENCE
Clinical Population and Translational Sciences
May 2016
Winston-Salem, North Carolina
Approved by:
David M. Herrington, MD, Mentor/Advisor
Beverly M. Snively, PhD
Jennifer Hawthorne Jordan, PhD, MS
i
ACKNOWLEDGMENTS
I am wholeheartedly grateful to Dr. David Herrington for his continued support,
guidance and mentorship during this fellowship and while preparing this thesis. I am very
thankful for every minute he spent teaching me by example what it means to be dedicated
and what it takes to be a successful clinical investigator. I am also grateful to Dr. Waqas
Qureshi who guided me to this excellent program and for being always available for any
questions. I am also grateful and appreciative of the time and support by Dr. Beverly
Snively who taught me basics of statistics. Thank you for reviewing every detail in this
work and for the thorough advices. I am also grateful to Dr. Jennifer Jordan for all her
support and encouragement. Thank you for answering my questions about the technical
basics of cardiac magnetic resonance imaging and T1 mapping. My strongest
appreciation and gratefulness to the CPTS program and the faculty who put every effort
to make sure I receive the best teaching I need to excell in all aspects of research. I would
also like to acknowledge Karen Blinson, Randi Sullivan, and Georgia Saylor for all their
assistance and support. My greatest gratitude goes to my mother Dr. Elham Tajeddin and
to my father Dr. Jamal Almahmoud. Thank you for inspiring me to seek the best
education and for supporting me during my research adventures. Thank you for being my
role models of dedication and hard work. And finally, I am most grateful to my wife, Dr.
Khulood Raslan, for her love and support at every step of my career.
ii
TABLE OF CONTENTS
LIST OF ILLUSTRATIONS AND TABLES……………………………………………V
LIST OF ABBREVIATIONS…………………………………………………………...Vii
ABSTRACT……………………………………………………………………………Viii
CHAPTER ONE: BACKGROUND………………………………………………………1
A. Introduction………………………………………………………………………..1
B. Definition of CKD………………………………………………………………...2
C. Cardiovascular disease in CKD population……………………………………….3
D. The pathophysiology of CVD in CKD……………………………………………4
E. Myocardial fibrosis in CKD………………………………………………………5
F. Fibroblast growth factor-23 in individuals with CKD……………………………9
G. The relationship between FGF-23 and all-cause and cardiovascular mortality….10
H. The role of FGF-23 in the pathogenesis of CVD in individuals with CKD……..10
I. Cardiac Magnetic Resonance indices of myocardial fibrosis……………………10
J. FGF-23 and CMR………………………………………………………………..15
K. Conceptual Model………………………………………………………………..15
L. Knowledge gap…………………………………………………………………..17
M. Aims and Hypotheses……………………………………………………………18
N. Methods………………………………………………………………………….19
O. References………………………………………………………………………..20
iii
CHAPTER TWO: MANUSCRIPT
A. KEYWORDS…………………………………………………………………….25
B. ABSTRACT……………………………………………………………………...26
Background………………………………………………………………………26
Methods…………………………………………………………………………..26
Results……………………………………………………………………………26
Conclusion……………………………………………………………………….27
C. INTRODUCTION……………………………………………………………….28
D. METHODS………………………………………………………………………29
Study population…………………………………………………………………29
Study procedure: CMR imaging…………………………………………………30
Measurement of serum FGF-23 concentrations………………………………….32
T1 mapping after 12 min, post-contrast T1 mapping after 25 min, ejection fraction,
incident HFpEF, incident HFrEF.
Primary Hypothesis: higher levels of FGF-23 are associated with higher levels of ECV
Secondary Hypothesis: FGF-23 levels are associated with both heart failure with
preserved ejection fraction and heart failure with reduced ejection fraction.
19
Methods:
We will address the first aim using a large cohort study of 1183 participants free
of cardiovascular diseae at baseline with FGF-23 measured at exam 1 (between 2000-
2002) and CMR T1 mapping performed at exam 5 (between 2010-2012). A subset of
these participants (n=588) had ECV calculated at exam 5. Participants with myocardial
scar (detected by visual assessment of any size using late gadolinium enhancement
imaging) were excluded. We will use multiple linear regression models to examine the
associations between FGF-23 and CMR indices of myocardial fibrosis (pre-contrast T1
mapping, 12-min and 25-min post-contrast T1 mapping and ECV %). ANOVA procedure
will be used to compare SAS driven least square means of CMR indices of fibrosis
between quartiles of FGF-23.
For the second aim we will use participants with baseline FGF-23 measured at
baseline exam 1 (n=6549) to examine the associations of FGF-23 with incident heart
failure, HFrEF and HFpEF. We will use Kaplan-Meier curves and log-rank procedure to
compare cumulative incidence of Heart failure, HFrEF and HFpEF by quartiles of FGF-
23. Cox proportional hazards regression models will be used to compute hazard ratios
using multivariate models.
20
References
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17. Xie J, Cha SK, An SW, Kuro OM, Birnbaumer L, Huang CL. Cardioprotection by Klotho through downregulation of TRPC6 channels in the mouse heart. Nature communications 2012;3:1238. 18. Levey AS, Eckardt KU, Tsukamoto Y, et al. Definition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney international 2005;67:2089-100. 19. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. The New England journal of medicine 2004;351:1296-305. 20. Astor BC, Muntner P, Levin A, Eustace JA, Coresh J. Association of kidney function with anemia: the Third National Health and Nutrition Examination Survey (1988-1994). Archives of internal medicine 2002;162:1401-8. 21. Gansevoort RT, Matsushita K, van der Velde M, et al. Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts. Kidney international 2011;80:93-104. 22. Chronic Kidney Disease Prognosis C, Matsushita K, van der Velde M, et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet 2010;375:2073-81. 23. Longenecker JC, Coresh J, Powe NR, et al. Traditional cardiovascular disease risk factors in dialysis patients compared with the general population: the CHOICE Study. Journal of the American Society of Nephrology : JASN 2002;13:1918-27. 24. Fleischmann EH, Bower JD, Salahudeen AK. Are conventional cardiovascular risk factors predictive of two-year mortality in hemodialysis patients? Clinical nephrology 2001;56:221-30. 25. Sarnak MJ, Levey AS, Schoolwerth AC, et al. Kidney disease as a risk factor for development of cardiovascular disease: a statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention. Hypertension 2003;42:1050-65. 26. Tonelli M, Wiebe N, Culleton B, et al. Chronic kidney disease and mortality risk: a systematic review. J Am Soc Nephrol 2006;17:2034-47. 27. Herzog CA, Ma JZ, Collins AJ. Poor long-term survival after acute myocardial infarction among patients on long-term dialysis. N Engl J Med 1998;339:799-805. 28. Foley RN, Parfrey PS, Sarnak MJ. Epidemiology of cardiovascular disease in chronic renal disease. Journal of the American Society of Nephrology : JASN 1998;9:S16-23. 29. Foley RN, Parfrey PS, Harnett JD, et al. Clinical and echocardiographic disease in patients starting end-stage renal disease therapy. Kidney Int 1995;47:186-92. 30. Tucker B, Fabbian F, Giles M, Thuraisingham RC, Raine AE, Baker LR. Left ventricular hypertrophy and ambulatory blood pressure monitoring in chronic renal failure. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 1997;12:724-8. 31. Levin A, Singer J, Thompson CR, Ross H, Lewis M. Prevalent left ventricular hypertrophy in the predialysis population: identifying opportunities for intervention. American journal of kidney diseases : the official journal of the National Kidney Foundation 1996;27:347-54. 32. Dhingra R, Gaziano JM, Djousse L. Chronic kidney disease and the risk of heart failure in men. Circulation Heart failure 2011;4:138-44. 33. Amann K, Wanner C, Ritz E. Cross-talk between the kidney and the cardiovascular system. J Am Soc Nephrol 2006;17:2112-9.
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67. Bull S, White SK, Piechnik SK, et al. Human non-contrast T1 values and correlation with histology in diffuse fibrosis. Heart 2013;99:932-7. 68. Messroghli DR, Radjenovic A, Kozerke S, Higgins DM, Sivananthan MU, Ridgway JP. Modified Look-Locker inversion recovery (MOLLI) for high-resolution T1 mapping of the heart. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine 2004;52:141-6. 69. Neilan TG, Coelho-Filho OR, Shah RV, et al. Myocardial extracellular volume fraction from T1 measurements in healthy volunteers and mice: relationship to aging and cardiac dimensions. JACC Cardiovascular imaging 2013;6:672-83. 70. Dall'Armellina E, Piechnik SK, Ferreira VM, et al. Cardiovascular magnetic resonance by non contrast T1-mapping allows assessment of severity of injury in acute myocardial infarction. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 2012;14:15. 71. Messroghli DR, Walters K, Plein S, et al. Myocardial T1 mapping: application to patients with acute and chronic myocardial infarction. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine 2007;58:34-40. 72. Ferreira VM, Piechnik SK, Dall'Armellina E, et al. Non-contrast T1-mapping detects acute myocardial edema with high diagnostic accuracy: a comparison to T2-weighted cardiovascular magnetic resonance. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 2012;14:42. 73. Flett AS, Sado DM, Quarta G, et al. Diffuse myocardial fibrosis in severe aortic stenosis: an equilibrium contrast cardiovascular magnetic resonance study. European heart journal cardiovascular Imaging 2012;13:819-26. 74. Flett AS, Hayward MP, Ashworth MT, et al. Equilibrium contrast cardiovascular magnetic resonance for the measurement of diffuse myocardial fibrosis: preliminary validation in humans. Circulation 2010;122:138-44.
25
CHAPTER TWO: MANUSCRIPT
Fibroblast Growth Factor-23 and Cardiac-MRI Indices of
Myocardial Fibrosis in the Multi-Ethnic Study of
Atherosclerosis
Short Title: FGF-23 and CMR indices of myocardial fibrosis in MESA.
Mohamed Faher Almahmoud, MD1, Jennifer H Jordan, PhD, MS
1, Bryan Kestenbaum,
MD2, Ronit Katz, PhD
2, Bharath Amble Venkatesh, PhD
3, João A. C. Lima, MD
3,4, Chia-
Ying Liu, PHD5, Erin D. Michos, MD, M.H.S
4, David M Herrington, MD, M.H.S
1
1Department of Internal Medicine, Section on Cardiovascular medicine, Wake Forest School of
Medicine, Winston-Salem, NC, USA
2Kidney Research Institute, Department of Medicine, Division of Nephrology, University of
Washington, Seattle, WA, USA
3Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
4Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
5Radiology and Imaging Sciences, National Institutes of Health (NIH), Bethesda, MD, USA
Correspondence:
Mohamed Faher Almahmoud MD, Department of Internal Medicine, Section on Cardiology
1. Sutton MG, Sharpe N. Left ventricular remodeling after myocardial infarction: pathophysiology and therapy. Circulation 2000;101:2981-8. 2. Liu CY, Liu YC, Wu C, et al. Evaluation of age-related interstitial myocardial fibrosis with cardiac magnetic resonance contrast-enhanced T1 mapping: MESA (Multi-Ethnic Study of Atherosclerosis). Journal of the American College of Cardiology 2013;62:1280-7. 3. Schwartzkopff B, Frenzel H, Dieckerhoff J, et al. Morphometric investigation of human myocardium in arterial hypertension and valvular aortic stenosis. European heart journal 1992;13 Suppl D:17-23. 4. St John Sutton MG, Lie JT, Anderson KR, O'Brien PC, Frye RL. Histopathological specificity of hypertrophic obstructive cardiomyopathy. Myocardial fibre disarray and myocardial fibrosis. British heart journal 1980;44:433-43. 5. Tyralla K, Amann K. Morphology of the heart and arteries in renal failure. Kidney international Supplement 2003:S80-3. 6. Wong TC, Piehler KM, Kang IA, et al. Myocardial extracellular volume fraction quantified by cardiovascular magnetic resonance is increased in diabetes and associated with mortality and incident heart failure admission. European heart journal 2014;35:657-64. 7. Wong TC, Piehler K, Meier CG, et al. Association between extracellular matrix expansion quantified by cardiovascular magnetic resonance and short-term mortality. Circulation 2012;126:1206-16. 8. Gulati A, Jabbour A, Ismail TF, et al. Association of fibrosis with mortality and sudden cardiac death in patients with nonischemic dilated cardiomyopathy. Jama 2013;309:896-908. 9. Kwong RY, Korlakunta H. Diagnostic and prognostic value of cardiac magnetic resonance imaging in assessing myocardial viability. Topics in magnetic resonance imaging : TMRI 2008;19:15-24. 10. Conrad CH, Brooks WW, Hayes JA, Sen S, Robinson KG, Bing OH. Myocardial fibrosis and stiffness with hypertrophy and heart failure in the spontaneously hypertensive rat. Circulation 1995;91:161-70. 11. Faul C, Amaral AP, Oskouei B, et al. FGF23 induces left ventricular hypertrophy. The Journal of clinical investigation 2011;121:4393-408. 12. Xie J, Cha SK, An SW, Kuro OM, Birnbaumer L, Huang CL. Cardioprotection by Klotho through downregulation of TRPC6 channels in the mouse heart. Nature communications 2012;3:1238. 13. Kestenbaum B, Sachs MC, Hoofnagle AN, et al. Fibroblast growth factor-23 and cardiovascular disease in the general population: the Multi-Ethnic Study of Atherosclerosis. Circulation Heart failure 2014;7:409-17. 14. Lutsey PL, Alonso A, Selvin E, et al. Fibroblast growth factor-23 and incident coronary heart disease, heart failure, and cardiovascular mortality: the Atherosclerosis Risk in Communities study. Journal of the American Heart Association 2014;3:e000936. 15. Saeed M, Wagner S, Wendland MF, Derugin N, Finkbeiner WE, Higgins CB. Occlusive and reperfused myocardial infarcts: differentiation with Mn-DPDP--enhanced MR imaging. Radiology 1989;172:59-64. 16. Mewton N, Liu CY, Croisille P, Bluemke D, Lima JA. Assessment of myocardial fibrosis with cardiovascular magnetic resonance. Journal of the American College of Cardiology 2011;57:891-903. 17. White SK, Sado DM, Flett AS, Moon JC. Characterising the myocardial interstitial space: the clinical relevance of non-invasive imaging. Heart 2012;98:773-9. 18. Bull S, White SK, Piechnik SK, et al. Human non-contrast T1 values and correlation with histology in diffuse fibrosis. Heart 2013;99:932-7.
46
19. Jellis CL, Kwon DH. Myocardial T1 mapping: modalities and clinical applications. Cardiovascular diagnosis and therapy 2014;4:126-37. 20. Jerosch-Herold M, Sheridan DC, Kushner JD, et al. Cardiac magnetic resonance imaging of myocardial contrast uptake and blood flow in patients affected with idiopathic or familial dilated cardiomyopathy. Am J Physiol Heart Circ Physiol 2008;295:H1234-H42. 21. Broberg CS, Chugh SS, Conklin C, Sahn DJ, Jerosch-Herold M. Quantification of diffuse myocardial fibrosis and its association with myocardial dysfunction in congenital heart disease. Circulation Cardiovascular imaging 2010;3:727-34. 22. Neilan TG, Coelho-Filho OR, Shah RV, et al. Myocardial extracellular volume fraction from T1 measurements in healthy volunteers and mice: relationship to aging and cardiac dimensions. JACC Cardiovascular imaging 2013;6:672-83. 23. Bild DE, Bluemke DA, Burke GL, et al. Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol 2002;156:871-81. 24. Iles L, Pfluger H, Phrommintikul A, et al. Evaluation of diffuse myocardial fibrosis in heart failure with cardiac magnetic resonance contrast-enhanced T1 mapping. Journal of the American College of Cardiology 2008;52:1574-80. 25. Schelbert EB, Testa SM, Meier CG, et al. Myocardial extravascular extracellular volume fraction measurement by gadolinium cardiovascular magnetic resonance in humans: slow infusion versus bolus. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 2011;13:16. 26. Ugander M, Oki AJ, Hsu LY, et al. Extracellular volume imaging by magnetic resonance imaging provides insights into overt and sub-clinical myocardial pathology. European heart journal 2012;33:1268-78. 27. Messroghli DR, Radjenovic A, Kozerke S, Higgins DM, Sivananthan MU, Ridgway JP. Modified Look-Locker inversion recovery (MOLLI) for high-resolution T1 mapping of the heart. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine 2004;52:141-6. 28. Kellman P, Wilson JR, Xue H, Ugander M, Arai AE. Extracellular volume fraction mapping in the myocardium, part 1: evaluation of an automated method. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 2012;14:63. 29. Lewis MR, Callas PW, Jenny NS, Tracy RP. Longitudinal stability of coagulation, fibrinolysis, and inflammation factors in stored plasma samples. Thrombosis and haemostasis 2001;86:1495-500. 30. Imel EA, Peacock M, Pitukcheewanont P, et al. Sensitivity of fibroblast growth factor 23 measurements in tumor-induced osteomalacia. The Journal of clinical endocrinology and metabolism 2006;91:2055-61. 31. Masoudi FA, Havranek EP, Smith G, et al. Gender, age, and heart failure with preserved left ventricular systolic function. Journal of the American College of Cardiology 2003;41:217-23. 32. From AM, Maleszewski JJ, Rihal CS. Current status of endomyocardial biopsy. Mayo Clinic proceedings 2011;86:1095-102. 33. Dall'Armellina E, Piechnik SK, Ferreira VM, et al. Cardiovascular magnetic resonance by non contrast T1-mapping allows assessment of severity of injury in acute myocardial infarction. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 2012;14:15. 34. Sibley CT, Noureldin RA, Gai N, et al. T1 Mapping in cardiomyopathy at cardiac MR: comparison with endomyocardial biopsy. Radiology 2012;265:724-32.
47
35. Ellims AH, Iles LM, Ling LH, Hare JL, Kaye DM, Taylor AJ. Diffuse myocardial fibrosis in hypertrophic cardiomyopathy can be identified by cardiovascular magnetic resonance, and is associated with left ventricular diastolic dysfunction. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 2012;14:76. 36. Jellis C, Wright J, Kennedy D, et al. Association of imaging markers of myocardial fibrosis with metabolic and functional disturbances in early diabetic cardiomyopathy. Circulation Cardiovascular imaging 2011;4:693-702. 37. Ling LH, Kistler PM, Ellims AH, et al. Diffuse ventricular fibrosis in atrial fibrillation: noninvasive evaluation and relationships with aging and systolic dysfunction. Journal of the American College of Cardiology 2012;60:2402-8. 38. Mongeon FP, Jerosch-Herold M, Coelho-Filho OR, Blankstein R, Falk RH, Kwong RY. Quantification of extracellular matrix expansion by CMR in infiltrative heart disease. JACC Cardiovascular imaging 2012;5:897-907. 39. Rossi MA. Pathologic fibrosis and connective tissue matrix in left ventricular hypertrophy due to chronic arterial hypertension in humans. Journal of hypertension 1998;16:1031-41. 40. Dall'Armellina E, Karia N, Lindsay AC, et al. Dynamic changes of edema and late gadolinium enhancement after acute myocardial infarction and their relationship to functional recovery and salvage index. Circulation Cardiovascular imaging 2011;4:228-36. 41. Brilla CG, Janicki JS, Weber KT. Impaired diastolic function and coronary reserve in genetic hypertension. Role of interstitial fibrosis and medial thickening of intramyocardial coronary arteries. Circulation research 1991;69:107-15. 42. Chan W, Duffy SJ, White DA, et al. Acute left ventricular remodeling following myocardial infarction: coupling of regional healing with remote extracellular matrix expansion. JACC Cardiovascular imaging 2012;5:884-93. 43. Urakawa I, Yamazaki Y, Shimada T, et al. Klotho converts canonical FGF receptor into a specific receptor for FGF23. Nature 2006;444:770-4. 44. Kurosu H, Ogawa Y, Miyoshi M, et al. Regulation of fibroblast growth factor-23 signaling by klotho. The Journal of biological chemistry 2006;281:6120-3. 45. Gutierrez O, Isakova T, Rhee E, et al. Fibroblast growth factor-23 mitigates hyperphosphatemia but accentuates calcitriol deficiency in chronic kidney disease. Journal of the American Society of Nephrology : JASN 2005;16:2205-15. 46. Hu MC, Shi M, Cho HJ, et al. Klotho and phosphate are modulators of pathologic uremic cardiac remodeling. Journal of the American Society of Nephrology : JASN 2015;26:1290-302. 47. Tucker B, Fabbian F, Giles M, Thuraisingham RC, Raine AE, Baker LR. Left ventricular hypertrophy and ambulatory blood pressure monitoring in chronic renal failure. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 1997;12:724-8. 48. Dhingra R, Gaziano JM, Djousse L. Chronic kidney disease and the risk of heart failure in men. Circulation Heart failure 2011;4:138-44. 49. Mall G, Huther W, Schneider J, Lundin P, Ritz E. Diffuse intermyocardiocytic fibrosis in uraemic patients. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 1990;5:39-44. 50. Collins AJ, Foley RN, Chavers B, et al. US Renal Data System 2013 Annual Data Report. American journal of kidney diseases : the official journal of the National Kidney Foundation 2014;63:A7.
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51. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. The New England journal of medicine 2004;351:1296-305. 52. Edwards NC, Moody WE, Yuan M, et al. Diffuse interstitial fibrosis and myocardial dysfunction in early chronic kidney disease. The American journal of cardiology 2015;115:1311-7. 53. Olivetti G, Giordano G, Corradi D, et al. Gender differences and aging: effects on the human heart. Journal of the American College of Cardiology 1995;26:1068-79. 54. Mallat Z, Fornes P, Costagliola R, et al. Age and gender effects on cardiomyocyte apoptosis in the normal human heart. The journals of gerontology Series A, Biological sciences and medical sciences 2001;56:M719-23. 55. Kostkiewicz M, Tracz W, Olszowska M, Podolec P, Drop D. Left ventricular geometry and function in patients with aortic stenosis: gender differences. International journal of cardiology 1999;71:57-61. 56. Gardner JD, Brower GL, Janicki JS. Gender differences in cardiac remodeling secondary to chronic volume overload. Journal of cardiac failure 2002;8:101-7. 57. Moon JC, Messroghli DR, Kellman P, et al. Myocardial T1 mapping and extracellular volume quantification: a Society for Cardiovascular Magnetic Resonance (SCMR) and CMR Working Group of the European Society of Cardiology consensus statement. Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 2013;15:92. 58. Biondi-Zoccai GG, Abate A, Bussani R, et al. Reduced post-infarction myocardial apoptosis in women: a clue to their different clinical course? Heart 2005;91:99-101.
49
CHAPTER THREE: ANCILLARY ANALYSES
Fibroblast Growth Factor-23 associations with Incident Heart
Failure with Reduced versus Preserved Ejection Fraction in
the Multi Ethnic Study of Atherosclerosis
Short Title: FGF-23 and HFrEF or HFpEF in MESA.
Mohamed Faher Almahmoud, MD1, Elsayed Z. Soliman MD
1, Alain G. Bertoni, MD
1,
Bryan Kestenbaum, MD2, Ronit Katz, PhD
2, João A. C. Lima, MD
3, Pamela Ouyang,
MD6, P. Elliot Miller, MD
5, Erin D. Michos, MD, M.H.S
4, David M Herrington, MD,
M.H.S1
1Department of Internal Medicine, Section on Cardiology, Wake Forest School of Medicine,
Winston-Salem, NC, USA
2Kidney Research Institute, Department of Medicine, Division of Nephrology, University of
Washington, Seattle, WA, USA
3Department of Radiology, John Hopkins University School of Medicine, Baltimore, MD, USA
4Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
5Department of Internal Medicine, Division of Hospitalist, John Hopkins University School of
Medicine, Baltimore, MD, USA
6Department of Internal Medicine, Director of women’s cardiovascular health center, John
Hopkins University School of Medicine, Baltimore, MD, USA
Correspondence:
Mohamed Faher Almahmoud MD, Department of Internal Medicine, Section on Cardiology
Low Density Lipoprotein (LDL), High Density Lipoprotein (HDL), diabetes mellitus
status (yes versus no), C-reactive protein (CRP), smoking (Current versus former and
never), urine albumin-creatinine ratio, and eGFRCKD-Epi. P<0.05 was considered
significant for all analyses including interaction terms. All statistical analyses were
performed with SAS software, version 9.3 (SAS Institute, Cary, NC). We tested for the
proportional hazards assumption that the effect of an explanatory variable on the hazard
is constant in time using SAS and we found no evidence of departure from this
assumption.
Results:
Among the 6549 participants (mean age 62±5.5 years), there were 53% women,
39% white, 12% Chinese, 27% black and 22% hispanics. The mean FGF-23 was 40±15
pg/ml. The mean eGFR was 81±18 mL/min/1.73m2.
Compared to participants in the lowest FGF-23 quartile (<31 pg/ml), those in the
highest quartile were older, had higher BMI, systolic blood pressure, lower eGFR, and
more likely to be diabetic (Table 1).
During a mean follow up of 11.1±3 years and a median follow up of 12.1(IQR:
11.6-12.7) years, 227 participants had incident heart failure events. Among these, 125
were classified as HFrEF and 102 were classified as HFpEF. When divided by FGF-23
57
quartiles, Q1 participants had 16 HFrEF and 16 HFpEF events, Q2 participants had 30
HFrEF and 18 HFpEF events, Q3 participants had 37 HFrEF and 24 HFpEF events, and
Q4 had 42 HFrEF and 44 HFpEF events.
We found that higher FGF-23 levels are significantly predictive of future HF
events. In adjusted models, there was an estimated 26% higher risk of HF for every 20
pg/mL increase in FGF-23 (HR 1.26; 95% CI, 1.1-1.5, p value=0.003). Each doubling of
FGF-23 levels was associated with 80% higher risk of incident HF (HR 1.8; 95% CI: 1.3-
2.5, p value <0.001) (Table 2A). We found stronger associations between higher FGF-23
levels and HFpEF events (HR 2.4; 95% CI: 1.4-4, p value <0.001) compared to HFrEF
events (HR 1.5; 95 CI 1-2.3, p value =0.06) for each doubling of FGF-23.
When comparing quartiles of FGF-23, there was a graded significant increase of
the risk of incident HF, incident HFrEF and incident HFpEF. Participants in the highest
FGF-23 quartile had higher risk of HF (HR 2.6; 95%CI; 1.5-4.7), HFrEF (HR 2.3; 95%
CI 1-5), and HFpEF (HR 2.9; 95% CI: 1.2-7.1) compared to participants in the lowest
quartile (reference) (Table 2B, Figure 1). We presented Kaplan-Meier curves with 95%
Hall-Wellner Bands and log-rank test for each outcome in Figure 2, Figure 3A and Figure
3B.
Compared to women, men had -statistically but not clinically significant- higher
FGF-23 concentration (mean FGF-23=40.6 in men compared to 39.6 in women). Because
of the observed difference we repeated the analysis with gender specific FGF-23 quartiles
with minimal cutpoints changes. However, the results were similar.
58
As we found differences between men and women in myocardial response to
higher levels of FGF-23 (in the previous chapter), we repeated the analysis after
stratification by gender. Men had 134 incident HF events with an estimated 60% higher
risk with doubling FGF-23 levels (HR 1.6; 95%CI: 1, 2.5, p value=0.05). In men, we
found significant associations between FGF-23 and each HF types in unadjusted models;
however these associations became non-significant in fully adjusted models. Women had
93 total heart failure events with stronger associations between FGF-23 levels and
incident HF (HR 2.7; 95% CI: 1.5-4.7, p value <0.001) compared to men(supplemental
Table 1). This association was especially stronger for HFpEF (HR 5.2; 95% CI: 2.4-11.7,
p value<0.001).
In sensitivity analyses we performed the analyses without adjusting for LV mass
(Supplemental Table 2A), and again after adjusting for LVH detected by
electrocardiogram (LVH-ECG) instead of LV mass (Supplemental Table 2B) and found
similar results. In additional sensitivity analyses, we adjusted for 24-hour urine phospate
excretion, serum calcium level, serum 1-25 hydroxy vitamin D level, and serum
Parathyroid hormone level and had similar findings.
Discussion:
In a middle-aged multi-ethnic population free of cardiovascular diseae at baseline
(MESA), we demonstrated that higher levels of FGF-23 were associated with higher
incidence of both HFrEF and HFpEF. We also confirmed a previous study done with the
same population but with smaller number of events (n=183) due to less follow up time,
which demonstrated an estimated 19% greater risk of incident HF with each 20 pg/mL
59
increase in FGF-23 (HR 1.19; 95% CI, 1.03-1.37).19
We found similar results. In our
linear model there was an estimated 80% higher risk of incident heart failure with
doubling of FGF-23 levels (Table 2A), and an estimated 26% higher risk for every 20
pg/mL increase in FGF-23 (HR 1.26;95% CI, 1.1-1.5, p value=0.003).
When comparing quartiles we found a graded increase in the risk of all types of
HF. Participants in the highest quartile had at least double the risk of developing HFrEF
and almost 3 times the risk of HFpEF.
We believe the findings of a strong association between FGF-23 with HF can be
explained by the previous observations that found a strong association between FGF-23
with higher LV mass.18,19
However, the reasons why we found stronger associations
between FGF-23 and HFpEF are uncertain. Several previous reports demonstrated that
higher LV mass is associated with greater risk of HF events.24-26
In a study by Velagaleti
et al, eccentric LVH was associated with higher risk of HFrEF, while concentric LVH
was associated with higher risk of HFpEF.24
Furthermore, Seliger et al, demonstrated that
LVH was associated with higher risk of both types of HF especially HFrEF. Although we
adjusted for LV mass in our fully adjusted model, other pathological mechanisms such as
myocardial fibrosis (as we demonstrated in the previous chapter) should be recognize as
another potential step that lead to the development of both HF types.
When comparing risk of heart failure by gender, we found high association
between FGF-23 levels and risk of incident HF in both men and women. The risk for
incident HF was stronger in women than in men. In women, the higher risk of HF was
especially because of strong association with HFpEF. However, our results were limited
60
with wide confidence intervals in these strata because of small number of events. Further
studies are needed to make more accurate conclusions.
To our knowledge this is the first study comparing the associations of FGF-23
with HFrEF and HFpEF. Previous studies examined the association between FGF-23
with ejection fraction as a continuous variable. For example, Kestenbaum et al, found no
significant relationship between FGF-23 and ejection fraction.19
In previous community
based studies, FGF-23 was associated with reduced ejection fraction.21,27
However, these
studies were in participants with chronic kidney disease,21
and in a population undergoing
elective coronary angiography.27
Both of these populations have sicker patients with
more cardiovascular risk factors.
Based on our findings we believe that higher levels of baseline FGF-23 are more
predictive of future HFpEF events. This is important because a significant proportion of
patients with chronic kidney disease suffer from HF especially HFpEF. For example,
50% of ESRD patients have heart failure and up to 85% have abnormal left ventricular
structure and function.28
Since patients with CKD have increasing FGF-23 levels even at
early stages,29,30
it is important to estimate the risk and understand the underlying
mechanism in order to develop new preventive and therapeutic techniques.
Furthermore, our findings of gender differences in the risk of incidence HF with
higher levels of FGF-23 confirm our previous observations of different gender-related
myocardial reaction to higher FGF-23 levels.
61
Limitations:
We only included participants with known EF at the time of HF diagnosis, thus it is
unknown whether the relationship would change had we known the EF of these
participants. Also we are limited by a small number of events to compare both types of
HF so we used definite and probable events which could lead to misclassification error.
However, even with close number of events the association was stronger for HFpEF. We
adjusted for left ventricular mass in our fully adjusted models. This adjustment led to
significant reduction in sample size and loss of power with wider confidence intervals.
However, we found similar results when adjusting for LVH detected by ECG (available
for majority of participants). Nevertheless, left ventricular hypertrophy could be a
mediator and a pathologic mechanism by which higher levels of FGF-23 lead to heart
failure.18
Finally, because of the complexity of FGF-23 physiology, residual confounding
cannot be excluded. For example, we did not adjust for 24-hour urine phosphate
excretion, serum calcium level, vitamin D level, or parathyroid hormone. However, in
sensitivity analyses, adjusting for these covariates didn’t change our results.
Conclusion:
In the Multi-Ethnic Study of Atherosclerosis, higher levels of FGF-23 were associated
with increased risk of incident HFrEF and HFpEF. We observed stronger association
with HFpEF. When comparing the risk of HF by gender, women had stronger risk for
HF, especially HFpEF.
62
Table 1. Baseline Characteristics by Fibroblast Growth Factor-23 1quartile
Values are mean ±SD. SBP: Systolic blood pressure. Smoking: current and former versus never. HTN: Hypertension. GFR: glomerular filtration rate. LV mass: left ventricular mass.
FGF-23 Quartiles
Characteristic overall <31 31-38 38-46 >46 P value
LV mass (g) 120±29 116±28 120±29 121±30 124±31 <0.001
63
Table 2A. Associations of FGF-23 and incident heart failure, HFrEF and HFpEF
Incident
heart
failure
events
Hazard ratio
(95% CI)
P
value
Incident
HFrEF
events
Hazard ratio
(95% CI)
P
value
Incident
HFpEF
events
Hazard ratio
(95% CI)
P value
Model 1 227 2.1
(1.6-2.7)
<0.001 125 1.8
(1.3-2.5)
0.001 102 2.6
(1.8-3.7)
<0.001
Model 2 226 1.7
(1.3-2.2)
<0.001 124 1.5
(1-2)
0.04 102 2
(1.4-2.9)
<0.001
Model 3 138 1.8
(1.3-2.5)
<0.001 84 1.5
(1-2.3)
0.06 54 2.4
(1.4-4)
0.001
Cox proportional models were used to calculate the hazards ratios of each unit increase in log2 FGF-23 for the development of incident
heart failure, HFrEF and HFpEF. Log2 FGF-23 is interpreted as doubling of FGF-23. For example, for each doubling of FGF-23 there is an increase of 2.4 of the risk of HFpEF. Model 1; unadjusted, Model 2; adjusted for age, gender, race/ethnicity, education, study
site and BMI, Model 3 adjusted for model 2 and systolic blood pressure, antihypertensive medications, LV mass, heart rate, low
density lipoprotein, high density lipoprotein, diabetes mellitus, smoking, C-reactive protein, urine albumin-creatinine ratio and eGFRCKD-EPI. P value <0.05 is considered significant.
Table 2B. Association of FGF-23 and incident heart failure, HFrEF and HFpEF
(Hazards ratios per FGF-23 quartiles)
Fibroblast Growth Factor-23 Quartiles
Q1 Q2 Q3 Q4
Incident heart failure
Model 1 1.0(ref) 1.5(0.96-2.4) 1.9(1.2-2.9) 2.7(1.8-4.1)
Model 2 1.0(ref) 1.3(0.9-2.1) 1.5(1-2.4) 1.9(1.3-2.9)
Model 3 1.0(ref) 1.8(1-3.3) 2.1(1.2-3.8) 2.6(1.5-4.7)
Incident HFrEF
Model 1 1.0(ref) 1.9(1-3.4) 2.2(1.2-4) 2.7(1.5-4.8)
Model 2 1.0(ref) 1.7(0.9-3.1) 1.9(1-3.4) 2(1.2-3.6)
Model 3 1.0(ref) 2(0.9-4.4) 2.8(1.3-5.9) 2.3(1-5)
Incident HFpEF
Model 1 1.0(ref) 1.1(0.6-2.2) 1.5(0.8-2.8) 2.8(1.6-5)
Model 2 1.0(ref) 1(0.5-2) 1.1(0.6-2.2) 1.8(1-3.3)
Model 3 1.0 (ref) 1.6(0.6-4.1) 1.3 (0.5-3.3) 2.9 (1.2-7.1)
Cox proportional model was used to calculate the hazards ratios. Values presented are hazards ratios and (95% confidence intervals)
for each quartile of FGF-23 compared to reference group(Q1). Model 1; unadjusted, Model 2; adjusted for age, gender, race/ethnicity, education, study site and BMI, Model 3 adjusted for model 2 and systolic blood pressure, antihypertensive medications, LV mass,
heart rate, low density lipoprotein, high density lipoprotein, diabetes mellitus, smoking, C-reactive protein, urine albumin-creatinine
ratio and eGFRCKD-EPI. P value <0.05 is considered significant.
64
Figure 1. Hazard ratios of the associations of FGF-23 quartiles with incident heart failure, HFrEF
and HFpEF
Figure 2. Higher FGF-23 levels are associated with increased risk of incident heart failure.
Participants were stratified into quartiles of FGF-23. (Kaplan-Meier curve with 95% Hall-Wellner
Brands and log-rank test). Notice the Y axis start from 90% survival, X axis is the time to heart
failure event (days).
0
0.5
1
1.5
2
2.5
3
3.5
q1 q2 q3 q4
Haz
arad
rat
io p
er
FGF-
23
qu
arti
les
Incident Heart Failure
0
0.5
1
1.5
2
2.5
3
3.5
q1 q2 q3 q4
Incident HFrEF
0
0.5
1
1.5
2
2.5
3
3.5
q1 q2 q3 q4
Incident HFpEF
65
Figure 3A. Higher FGF-23 levels are associated with increased risk of incident HFrEF.
Participants were stratified into quartiles of FGF-23. (Kaplan-Meier curve with 95% Hall-Wellner
Bands and log-rank test).
Figure 3B. Higher FGF-23 levels are associated with increased risk of incident HFpEF.
Participants were stratified into quartiles of FGF-23. (Kaplan-Meier curve with 95% Hall-Wellner
Bands and log-rank test).
66
SUPPLEMENTAL MATERIAL
Supplemental Table 1. Associations of FGF-23 and incident heart failure, HFrEF and HFpEF
stratified by gender
Incident
heart
failure
events
Hazard
ratio (95%
CI)
P value Incident
HFrEF
events
Hazard
ratio (95%
CI)
P value Incident
HFpEF
events
Hazard
ratio (95%
CI)
P value
Men
Model 1 134 1.9
(1.4-2.7)
<0.001 86 1.8
(1.1-2.7)
0.01 48 2.3
(1.3-4)
0.004
Model 2 133 1.6
(1.1-2.2)
0.008 85 1.5
(1-2.3)
0.054 48 1.8
(1-3.2)
0.056
Model 3 86 1.6
(1-2.5)
0.05 59 1.6
(0.9-2.7)
0.1 27 1.7
(0.7-3.9)
0.2
Women
Model 1 93 2.3
(1.6-3.2)
<0.001 39 1.7
(0.9-3)
0.09 54 2.8
(1.8-4.4)
<0.001
Model 2 93 1.8
(1.2-2.6)
<0.001 39 1.3
(0.7-2.5)
0.4 54 2.2
(1.3-3.7)
0.003
Model 3 52 2.7
(1.5-4.7)
<0.001 25 1.7
(0.7-4.2)
0.24 27 5.2
(2.4-11.7)
<0.001
Cox proportional models were used to calculate the hazards ratios of each unit increase in log2 FGF-23 for the development of incident
heart failure, HFrEF and HFpEF. Log2 FGF-23 is interpreted as doubling of FGF-23. For example, for each doubling of FGF-23 there
is an increase of 5.2 of the risk of HFpEF in women. Model 1; unadjusted, Model 2; adjusted for age, race/ethnicity, education, study site and BMI, Model 3 adjusted for model 2 and systolic blood pressure, antihypertensive medications, LV mass, heart rate, low
density lipoprotein, high density lipoprotein, diabetes mellitus, smoking, C-reactive protein, urine albumin-creatinine ratio and
eGFRCKD-EPI. P value <0.05 is considered significant.
Supplemental Table 2A. Associations of FGF-23 and incident heart failure, HFrEF and HFpEF
overall and stratified by gender without adjustment for LV mass
Model 3 Incident
heart
failure
events
Hazard
ratio (95%
CI)
P value Incident
HFrEF
events
Hazard
ratio (95%
CI)
P value Incident
HFpEF
events
Hazard
ratio (95%
CI)
P value
Overall 217 1.6
(1.2-2.1)
<0.001 121 1.3
(0.9-1.9)
0.13 96 2.1
(1.4-3.1)
<0.001
Men 129 1.5
(1-2.1)
0.03 82 1.5
(0.8-2.3)
0.11 47 1.5
(0.8-2.8)
0.17
Women 88 1.9
(1.3-3)
0.003 39 1.2
(0.6-2.2)
0.7 49 2.9
(1.6-5.3)
<0.001
Cox proportional models were used to calculate the hazards ratios of each unit increase in log2 FGF-23 for the development of incident
heart failure, HFrEF and HFpEF. Log2 FGF-23 is interpreted as doubling of FGF-23. For example, for each doubling of FGF-23 there
is an increase of 2.9 of the risk of HFpEF in women. Model 3 adjusted for age, race/ethnicity, education, study site, BMI, systolic
blood pressure, antihypertensive medications, heart rate, low density lipoprotein, high density lipoprotein, diabetes mellitus, smoking,
C-reactive protein, urine albumin-creatinine ratio and eGFRCKD-EPI. P value <0.05 is considered significant.
67
Supplemental Table 2B. Associations of FGF-23 and incident heart failure, HFrEF and HFpEF
overall and stratified by gender with adjustment for LVH-ECG
Model 3 Incident
heart
failure
events
Hazard
ratio (95%
CI)
P value Incident
HFrEF
events
Hazard
ratio (95%
CI)
P value Incident
HFpEF
events
Hazard
ratio (95%
CI)
P value
Overall 217 1.6
(1.2-2.1)
<0.001 121 1.3
(0.9-1.8)
0.17 96 2.1
(1.4-3.1)
<0.001
Men 129 1.5
(1-2.1)
0.045 82 1.4
(0.9-2.2)
0.13 47 1.5
(0.8-2.8)
0.19
Women 88 1.9
(1.3-3)
0.003 39 1.1
(0.6-2.2)
0.7 49 2.9
(1.6-5.2)
<0.001
Cox proportional models were used to calculate the hazards ratios of each unit increase in log2 FGF-23 for the development of incident heart failure, HFrEF and HFpEF. Log2 FGF-23 is interpreted as doubling of FGF-23. For example, for each doubling of FGF-23 there
is an increase of 2.9 of the risk of HFpEF in women. Model 3 adjusted for age, race/ethnicity, education, study site, BMI, systolic
density lipoprotein, high density lipoprotein, diabetes mellitus, smoking, C-reactive protein, urine albumin-creatinine ratio and
eGFRCKD-EPI. P value <0.05 is considered significant.
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