Anne M Murray1,2,3, Yelena Slinin4, David E Tupper5,6, Sarah L Pederson7, Cynthia Davey8, David T Gilbertson9, Paul Drawz10, Ryan Mello11, Allyson Hart11, Kirsten L Johansen9,11, Scott Reule10,12, Rebecca Rossom13, David S Knopman14. 1. The Berman Center for Outcomes and Clinical Research, Hennepin Healthcare Research Institute, Minneapolis, Minnesota, USA. 2. Division of Geriatrics, Department of Medicine, Hennepin Healthcare, Minneapolis, Minnesota, USA. 3. Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA. 4. Kaiser Permanente Fremont Medical Center, Fremont, California, USA. 5. Department of Psychology and Neuropsychology, Hennepin Healthcare Minneapolis, Minneapolis, Minnesota, USA. 6. Department of Neurology, University of Minnesota, Minneapolis, Minnesota, USA. 7. Allina Health, Minneapolis, Minnesota, USA. 8. Biostatistical Design and Analysis Center, Clinical and Translational Science Institute, University of Minnesota, Minneapolis, Minnesota, USA. 9. Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, Minnesota, USA. 10. Division of Nephrology and Hypertension, Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA. 11. Division of Nephrology, Department of Medicine, Hennepin Healthcare, Minneapolis, Minnesota, USA. 12. Nephrology Division, Department of Medicine, Minneapolis Veterans Affairs Health Care System, Minneapolis, Minnesota, USA. 13. HealthPartners Institute, Bloomington, Minnesota, USA. 14. Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA.
Abstract
INTRODUCTION: The associations of kidney-metabolic biomarkers with cognitive impairment (CI) beyond the estimated glomerular filtration rate (eGFR, in mL/min/1.73 m2) and albuminuria levels are not well understood. In exploratory analysis, our objective was to determine the extent that three kidney-metabolic factors, previously proposed as mechanisms of CI and commonly abnormal in chronic kidney disease (CKD), were associated with prevalent CI in CKD participants, adjusted for kidney function measures. METHODS: The study cohort included community-dwelling individuals aged ≥45 years with CKD (eGFR <60), not requiring dialysis, recruited from four health systems. We examined the serum biomarkers bicarbonate (CO2), TNFαR1, and cholesterol as primary exposures. A structured neuropsychological battery conducted by trained staff measured global and domain-specific cognitive performance. Logistic regression analyses estimated the cross-sectional associations between kidney-metabolic measures and global and cognitive domain-specific moderate/severe (Mod/Sev) CI, adjusted for the eGFR, urinary albumin-creatinine ratio (UACR, mg/g), demographics, comorbid conditions, and other kidney-metabolic biomarkers commonly abnormal in CKD. RESULTS: Among 436 CKD participants with mean age 70 years, 16% were Black, the mean eGFR was 34, and the median [IQR] UACR was 49 [0.0, 378] mg/g. In adjusted models, increased TNFαR1 was associated with global Mod/Sev CI (odds ratio [95% confidence interval] = 1.40 [1.02, 1.93]; p = 0.04); low bicarbonate (CO2 <20 mEq/L) with Mod/Sev memory impairment (3.04 [1.09, 8.47]; p = 0.03), and each 10-mg/dL lower cholesterol was associated with Mod/Sev executive function/processing speed impairment (1.12 [1.02, 1.23]; p = 0.02). However, after adjustment for multiple comparisons, these associations were no longer significant nor were any other kidney-metabolic factors significant for any CI classification. CONCLUSION: In exploratory analyses in a CKD population, three kidney-metabolic factors were associated with CI, but after adjustment for multiple comparisons, were no longer significant. Future studies in larger CKD populations are needed to assess these potential risk factors for CI.
INTRODUCTION: The associations of kidney-metabolic biomarkers with cognitive impairment (CI) beyond the estimated glomerular filtration rate (eGFR, in mL/min/1.73 m2) and albuminuria levels are not well understood. In exploratory analysis, our objective was to determine the extent that three kidney-metabolic factors, previously proposed as mechanisms of CI and commonly abnormal in chronic kidney disease (CKD), were associated with prevalent CI in CKD participants, adjusted for kidney function measures. METHODS: The study cohort included community-dwelling individuals aged ≥45 years with CKD (eGFR <60), not requiring dialysis, recruited from four health systems. We examined the serum biomarkers bicarbonate (CO2), TNFαR1, and cholesterol as primary exposures. A structured neuropsychological battery conducted by trained staff measured global and domain-specific cognitive performance. Logistic regression analyses estimated the cross-sectional associations between kidney-metabolic measures and global and cognitive domain-specific moderate/severe (Mod/Sev) CI, adjusted for the eGFR, urinary albumin-creatinine ratio (UACR, mg/g), demographics, comorbid conditions, and other kidney-metabolic biomarkers commonly abnormal in CKD. RESULTS: Among 436 CKD participants with mean age 70 years, 16% were Black, the mean eGFR was 34, and the median [IQR] UACR was 49 [0.0, 378] mg/g. In adjusted models, increased TNFαR1 was associated with global Mod/Sev CI (odds ratio [95% confidence interval] = 1.40 [1.02, 1.93]; p = 0.04); low bicarbonate (CO2 <20 mEq/L) with Mod/Sev memory impairment (3.04 [1.09, 8.47]; p = 0.03), and each 10-mg/dL lower cholesterol was associated with Mod/Sev executive function/processing speed impairment (1.12 [1.02, 1.23]; p = 0.02). However, after adjustment for multiple comparisons, these associations were no longer significant nor were any other kidney-metabolic factors significant for any CI classification. CONCLUSION: In exploratory analyses in a CKD population, three kidney-metabolic factors were associated with CI, but after adjustment for multiple comparisons, were no longer significant. Future studies in larger CKD populations are needed to assess these potential risk factors for CI.
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