Archna Bajaj1, Dawei Xie2, Esteban Cedillo-Couvert3, Jeanne Charleston4, Jing Chen5, Rajat Deo6, Harold I Feldman7, Alan S Go8, Jiang He9, Edward Horwitz10, Radhakrishna Kallem6, Mahboob Rahman11, Matthew R Weir12, Amanda H Anderson13, Daniel J Rader14. 1. Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. Electronic address: bajaja@pennmedicine.upenn.edu. 2. Department of Biostatistics and Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. 3. Division of Nephrology, Department of Medicine, University of Illinois College of Medicine at Chicago, Chicago, IL. 4. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD. 5. Division of Nephrology and Hypertension, Department of Medicine, Tulane University School of Medicine, New Orleans, LA. 6. Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. 7. Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Department of Biostatistics and Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. 8. Division of Research, Kaiser Permanente Northern California, Oakland, CA. 9. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA. 10. Division of Nephrology, MetroHealth Medical Center, Case Western Reserve University, Cleveland, OH. 11. Division of Nephrology and Hypertension, Case Western Reserve University, University Hospitals Case Medical Center, Cleveland, OH. 12. Division of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD. 13. Department of Biostatistics and Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA. 14. Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Department of Genetics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; The Penn Cardiovascular Institute, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA; Institute for Translational Medicine and Therapeutics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA.
Abstract
RATIONALE & OBJECTIVE: A large residual risk for atherosclerotic cardiovascular disease (ASCVD) remains in the setting of chronic kidney disease (CKD) despite treatment with statins. We sought to evaluate the associations of lipid and apolipoprotein levels with risk for ASCVD in individuals with CKD. STUDY DESIGN: Prospective cohort study. SETTINGS & PARTICIPANTS: Adults aged 21 to 74 years with non-dialysis-dependent CKD at baseline enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study in 7 clinical study centers in the United States. PREDICTOR: Baseline total cholesterol, non-high-density lipoprotein cholesterol (non-HDL-C), very low-density lipoprotein cholesterol (VLDL-C), triglycerides, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (Apo-B), HDL-C, and apolipoprotein AI (Apo-AI) values stratified into tertiles. OUTCOME: A composite ASCVD event of myocardial infarction or ischemic stroke. ANALYTIC APPROACH: Multivariable Cox proportional hazards regression to estimate the risk for ASCVD for each tertile of lipoprotein predictor. RESULTS: Among 3,811 CRIC participants (mean age, 57.7 years; 41.8% white), there were 451 ASCVD events during a median follow-up of 7.9 years. There was increased ASCVD risk among participants with VLDL-C levels in the highest tertile (HR, 1.28; 95% CI, 1.01-1.64), Apo-B levels in the middle tertile (HR, 1.30; 95% CI, 1.03-1.64), HDL-C levels in the middle and lowest tertiles (HRs of 1.40 [95% CI, 1.08-1.83] and 1.77 [95% CI, 1.35-2.33], respectively), and Apo-AI levels in the middle and lowest tertiles (HRs of 1.77 [95% CI, 1.02-1.74] and 1.77 [95% CI, 1.36-2.32], respectively). LDL-C level was not significantly associated with the ASCVD outcome in this population (HR, 1.00 [95% CI, 0.77-1.30] for the highest tertile). LIMITATIONS: Associations based on observational data do not permit inferences about causal associations. CONCLUSIONS: Higher VLDL-C and Apo-B levels, as well as lower HDL-C and Apo-AI levels, are associated with increased risk for ASCVD. These findings support future investigations into pharmacologic targeting of lipoproteins beyond LDL-C, such as triglyceride-rich lipoproteins, to reduce residual risk for ASCVD among individuals with CKD.
RATIONALE & OBJECTIVE: A large residual risk for atherosclerotic cardiovascular disease (ASCVD) remains in the setting of chronic kidney disease (CKD) despite treatment with statins. We sought to evaluate the associations of lipid and apolipoprotein levels with risk for ASCVD in individuals with CKD. STUDY DESIGN: Prospective cohort study. SETTINGS & PARTICIPANTS: Adults aged 21 to 74 years with non-dialysis-dependent CKD at baseline enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study in 7 clinical study centers in the United States. PREDICTOR: Baseline total cholesterol, non-high-density lipoprotein cholesterol (non-HDL-C), very low-density lipoprotein cholesterol (VLDL-C), triglycerides, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (Apo-B), HDL-C, and apolipoprotein AI (Apo-AI) values stratified into tertiles. OUTCOME: A composite ASCVD event of myocardial infarction or ischemic stroke. ANALYTIC APPROACH: Multivariable Cox proportional hazards regression to estimate the risk for ASCVD for each tertile of lipoprotein predictor. RESULTS: Among 3,811 CRIC participants (mean age, 57.7 years; 41.8% white), there were 451 ASCVD events during a median follow-up of 7.9 years. There was increased ASCVD risk among participants with VLDL-C levels in the highest tertile (HR, 1.28; 95% CI, 1.01-1.64), Apo-B levels in the middle tertile (HR, 1.30; 95% CI, 1.03-1.64), HDL-C levels in the middle and lowest tertiles (HRs of 1.40 [95% CI, 1.08-1.83] and 1.77 [95% CI, 1.35-2.33], respectively), and Apo-AI levels in the middle and lowest tertiles (HRs of 1.77 [95% CI, 1.02-1.74] and 1.77 [95% CI, 1.36-2.32], respectively). LDL-C level was not significantly associated with the ASCVD outcome in this population (HR, 1.00 [95% CI, 0.77-1.30] for the highest tertile). LIMITATIONS: Associations based on observational data do not permit inferences about causal associations. CONCLUSIONS: Higher VLDL-C and Apo-B levels, as well as lower HDL-C and Apo-AI levels, are associated with increased risk for ASCVD. These findings support future investigations into pharmacologic targeting of lipoproteins beyond LDL-C, such as triglyceride-rich lipoproteins, to reduce residual risk for ASCVD among individuals with CKD.
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