Rachana Shah1, Gregory J Matthews2, Rhia Y Shah3, Catherine McLaughlin4, Jing Chen5, Melanie Wolman6, Stephen R Master7, Boyang Chai6, Dawei Xie6, Daniel J Rader3, Dominic S Raj8, Nehal N Mehta9, Matthew Budoff10, Michael J Fischer11, Alan S Go12, Raymond R Townsend13, Jiang He5, John W Kusek14, Harold I Feldman15, Andrea S Foulkes2, Muredach P Reilly16. 1. Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA. Electronic address: shahr@email.chop.edu. 2. School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA. 3. Cardiovascular Institute, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. 4. Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom. 5. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA. 6. Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. 7. Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. 8. The George Washington University, Washington, DC. 9. National Heart, Lung and Blood Institute, Bethesda, MD. 10. Los Angeles Biomedical Research Institute, Torrance, CA. 11. Medicine, Jesse Brown VA Medical Center and University of Hospital and Health Sciences System, Chicago; Center of Innovation for Complex Chronic Healthcare, Edward Hines Jr VA Hospital, Hines, IL. 12. Division of Research, Kaiser Permanente of Northern California, Oakland, CA. 13. Renal Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia PA. 14. National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD. 15. Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Renal Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia PA. 16. Cardiovascular Institute, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. Electronic address: muredach@mail.med.upenn.edu.
Abstract
BACKGROUND: Cardiometabolic disease is a major cause of morbidity and mortality in persons with chronic kidney disease (CKD). Fractalkine (CX3CL1) is a potential mediator of both atherosclerosis and metabolic disease. Studies of the relationship of CX3CL1 with risk of cardiovascular disease (CVD) events and metabolic traits are lacking, particularly in the high-risk setting of CKD. STUDY DESIGN: Cross-sectional and longitudinal observational analysis. SETTING & PARTICIPANTS: Adults with CKD from 7 US sites participating in the Chronic Renal Insufficiency Cohort (CRIC) Study. PREDICTOR: Quartiles of plasma CX3CL1 levels at baseline. OUTCOMES: Baseline estimated glomerular filtration rate from a creatinine and cystatin C-based equation, prevalent and incident CVD, diabetes, metabolic syndrome and its criteria, homeostatic model assessment of insulin resistance, hemoglobin A1c level, myocardial infarction, all-cause mortality, and the composite outcome of myocardial infarction/all-cause mortality. RESULTS: Among 3,687 participants, baseline CX3CL1 levels were associated positively with several CVD risk factors and metabolic traits, lower estimated glomerular filtration rate, and higher levels of inflammatory cytokines, as well as prevalent CVD (OR, 1.09; 95% CI, 1.01-1.19; P=0.03). Higher CX3CL1 level also was associated with prevalent diabetes (OR, 1.26; 95% CI, 1.16-1.38; P<0.001) in adjusted models. During a mean follow-up of 6 years, there were 352 deaths, 176 myocardial infarctions, and 484 composite outcomes. In fully adjusted models, 1-SD higher CX3CL1 level increased the hazard for all-cause mortality (1.11; 95% CI, 1.00-1.22; P=0.02) and the composite outcome (1.09; 95% CI, 1.00-1.19; P=0.04). LIMITATIONS: Study design did not allow evaluation of changes over time, correlation with progression of phenotypes, or determination of causality of effect. CONCLUSIONS: Circulating CX3CL1 level may contribute to both atherosclerotic CVD and diabetes in a CKD cohort. Further studies are required to establish mechanisms through which CX3CL1 affects the pathogenesis of atherosclerosis and diabetes.
BACKGROUND:Cardiometabolic disease is a major cause of morbidity and mortality in persons with chronic kidney disease (CKD). Fractalkine (CX3CL1) is a potential mediator of both atherosclerosis and metabolic disease. Studies of the relationship of CX3CL1 with risk of cardiovascular disease (CVD) events and metabolic traits are lacking, particularly in the high-risk setting of CKD. STUDY DESIGN: Cross-sectional and longitudinal observational analysis. SETTING & PARTICIPANTS: Adults with CKD from 7 US sites participating in the Chronic Renal Insufficiency Cohort (CRIC) Study. PREDICTOR: Quartiles of plasma CX3CL1 levels at baseline. OUTCOMES: Baseline estimated glomerular filtration rate from a creatinine and cystatin C-based equation, prevalent and incident CVD, diabetes, metabolic syndrome and its criteria, homeostatic model assessment of insulin resistance, hemoglobin A1c level, myocardial infarction, all-cause mortality, and the composite outcome of myocardial infarction/all-cause mortality. RESULTS: Among 3,687 participants, baseline CX3CL1 levels were associated positively with several CVD risk factors and metabolic traits, lower estimated glomerular filtration rate, and higher levels of inflammatory cytokines, as well as prevalent CVD (OR, 1.09; 95% CI, 1.01-1.19; P=0.03). Higher CX3CL1 level also was associated with prevalent diabetes (OR, 1.26; 95% CI, 1.16-1.38; P<0.001) in adjusted models. During a mean follow-up of 6 years, there were 352 deaths, 176 myocardial infarctions, and 484 composite outcomes. In fully adjusted models, 1-SD higher CX3CL1 level increased the hazard for all-cause mortality (1.11; 95% CI, 1.00-1.22; P=0.02) and the composite outcome (1.09; 95% CI, 1.00-1.19; P=0.04). LIMITATIONS: Study design did not allow evaluation of changes over time, correlation with progression of phenotypes, or determination of causality of effect. CONCLUSIONS: Circulating CX3CL1 level may contribute to both atherosclerotic CVD and diabetes in a CKD cohort. Further studies are required to establish mechanisms through which CX3CL1 affects the pathogenesis of atherosclerosis and diabetes.
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