Abstract
To 1) investigate the morphological brain-tissue changes in patients with dialysis- and non-dialysis-dependent chronic kidney disease (CKD); 2) analyze the effects of CKD on whole-brain cortical thickness, cortical volume, surface area, and surface curvature; and 3) analyze the correlation of these changes with clinical and biochemical indices. This study included normal controls (NCs, n = 34) and patients with CKD who were divided into dialysis (dialysis-dependent chronic kidney disease [DD-CKD], n = 26) and non-dialysis (non-dialysis patients who underwent cranial magnetic resonance imaging scans [NDD-CKD], n = 26) groups. Cortical thickness, volume, surface area, and surface curvature in each group were calculated using FreeSurfer software. Brain morphological indicators with statistical differences were correlated with clinical and biochemical indicators. Patients with CKD exhibited a significant and widespread decrease in cortical thickness and volume compared with NCs. Among the brain regions associated with higher neural activity, patients with CKD exhibited more significant morphological changes in the paracentral gyrus, transverse temporal gyrus, and lateral occipital cortex than in other brain regions. Cortical thickness and volume in patients with CKD correlated with blood pressure, lipid, hemoglobin, creatinine, and urea nitrogen levels. The extent of brain atrophy was further increased in the DD-CKD group compared with that in the NDD-CKD group. Patients with CKD potentially exhibit a certain degree of structural brain-tissue imaging changes, with morphological changes more pronounced in patients with DD-CKD, suggesting that blood urea nitrogen and dialysis may be influential factors in brain morphological changes in patients with CKD.
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Agarwal R, Sinha AD, Cramer AE et al (2021) Chlorthalidone for hypertension in advanced chronic kidney disease. N Engl J Med 385:2507–2519. https://doi.org/10.1056/NEJMoa2110730
Ammothumkandy A, Ravina K, Wolseley V et al (2022) Altered adult neurogenesis and gliogenesis in patients with mesial temporal lobe epilepsy. Nat Neurosci 25:493–503. https://doi.org/10.1038/s41593-022-01044-2
Chen X, Kong J, Pan J et al (2021) Kidney damage causally affects the brain cortical structure: A Mendelian randomization study. EBioMedicine 72:103592. https://doi.org/10.1016/j.ebiom.2021.103592
Dale AM, Fischl B, Sereno MI (1999) Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 9(2):179–194. https://doi.org/10.1006/nimg.1998.0395
Desikan RS, Ségonne F, Fischl B et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31(3):968–980. https://doi.org/10.1016/j.neuroimage.2006.01.021
Drew DA, Weiner DE, Sarnak MJ (2019) Cognitive impairment in CKD: Pathophysiology, management, and prevention. Am J Kidney Dis 74:782–790. https://doi.org/10.1053/j.ajkd.2019.05.017
Dusek P, Lescinskij A, Ruzicka F et al (2021) Associations of brain atrophy and cerebral iron accumulation at MRI with clinical severity in Wilson disease. Radiology 299:662–672. https://doi.org/10.1148/radiol.2021202846
Fischl B (2012) FreeSurfer. Neuroimage 62(2):774–781. https://doi.org/10.1016/j.neuroimage.2012.01.021
Fischl B, Dale AM (2000) Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A 97(20):11050–11055. https://doi.org/10.1073/pnas.200033797
Fischl B, Salat DH, Busa E et al (2002) Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33(3):341–55. https://doi.org/10.1016/s0896-6273(02)00569-x
Giarrocco F, Averbeck BB (2021) Organization of parietoprefrontal and temporoprefrontal networks in the macaque. J Neurophysiol 126:1289–1309. https://doi.org/10.1152/jn.00092.2021
Giovagnoli AR, Tallarita GM, Parente A et al (2020) The understanding of mental states and the cognitive phenotype of frontal lobe epilepsy. Epilepsia 61:747–757. https://doi.org/10.1111/epi.16457
Grundy SM, Stone NJ, Bailey AL et al (2019) 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 139:e1082–e1143. https://doi.org/10.1161/CIR.0000000000000625
Kelly DM, Ademi Z, Doehner W et al (2021) Chronic kidney disease and cerebrovascular disease: Consensus and guidance from a KDIGO Controversies Conference. Stroke 52:e328–e346. https://doi.org/10.1161/STROKEAHA.120.029680
Liu P, Quinn RR, Lam NN et al (2021) Accounting for age in the definition of chronic kidney disease. JAMA Intern Med 181:1359–1366. https://doi.org/10.1001/jamainternmed.2021.4813
Madre M, Canales-Rodríguez EJ, Fuentes-Claramonte P et al (2020) Structural abnormality in schizophrenia versus bipolar disorder: A whole brain cortical thickness, surface area, volume and gyrification analyses. Neuroimage Clin 25:102131. https://doi.org/10.1016/j.nicl.2019.102131
Miglinas M, Cesniene U, Janusaite MM et al (2020) Cerebrovascular disease and cognition in chronic kidney disease patients. Front Cardiovasc Med 7:96. https://doi.org/10.3389/fcvm.2020.00096
Murphy M, Ding A, Berk J et al (2021) Kidney disease among people who are incarcerated. Clin J Am Soc Nephrol 16:1766–1772. https://doi.org/10.2215/CJN.01910221
Narasimhan S, González HFJ, Johnson GW et al (2022) Functional connectivity between mesial temporal and default mode structures may help lateralize surgical temporal lobe. J Neurosurg 1–11. https://doi.org/10.3171/2022.1.JNS212031
Peng X, Lin P, Zhang T, Wang J (2013) Extreme learning machine-based classification of ADHD using brain structural MRI data. PLoS ONE 8(11):e79476. https://doi.org/10.1371/journal.pone.0079476
Querfeld U, Mak RH, Pries AR (2020) Microvascular disease in chronic kidney disease: the base of the iceberg in cardiovascular comorbidity. Clin Sci (Lond) 134:1333–1356. https://doi.org/10.1042/CS20200279
Sanchez-Meza F, Torre A, Castillo-Martinez L et al (2021) Evaluation of cerebral dysfunction in patients with chronic kidney disease using neuropsychometric and neurophysiological tests. Ren Fail 43:577–584. https://doi.org/10.1080/0886022X.2021.1901740
Schaer M, Cuadra MB, Tamarit L et al (2008) A surface-based approach to quantify local cortical gyrification. IEEE Trans Med Imaging 27(2):161–170. https://doi.org/10.1109/TMI.2007.903576
Towle VL, Pham T, McCaffrey M et al (2021) Toward the development of a color visual prosthesis. J Neural Eng 18:023001. https://doi.org/10.1088/1741-2552/abd520
Tsuruya K, Yoshida H, Kuroki Y et al (2015) Brain atrophy in peritoneal dialysis and CKD stages 3–5: a cross-sectional and longitudinal study. Am J Kidney Dis 65(2):312–321. https://doi.org/10.1053/j.ajkd.2014.07.011
Vinti V, Dell’Isola GB, Tascini G et al (2021) Temporal lobe epilepsy and psychiatric comorbidity. Front Neurol 12:775781. https://doi.org/10.3389/fneur.2021.775781
Yang QZC (2021) Timing of dialysis initiation and end-stage kidney disease incidence. JAMA Intern Med 181:724–725. https://doi.org/10.1001/jamainternmed.2020.8809
Zhang WR, Parikh CR (2019) Biomarkers of acute and chronic kidney disease. Annu Rev Physiol 81:309–333. https://doi.org/10.1146/annurev-physiol-020518-114605
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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Huan Yu, Chaoyang Zhang, Yan Cai, Ning Wu, Xiuqin Jia, Jiaojiao Wu, Feng Shi, Rui Hua, and Qi Yang. The first draft of the manuscript was written by Huan Yu and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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This study was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments was approved by the Ethics Committee of Liangxiang Hospital of Capital Medical University (date of approval: May 8, 2021; approval number: 2016126).
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Yu, H., Zhang, C., Cai, Y. et al. Morphological brain alterations in dialysis- and non-dialysis-dependent patients with chronic kidney disease. Metab Brain Dis 38, 1311–1321 (2023). https://doi.org/10.1007/s11011-022-01150-x
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DOI: https://doi.org/10.1007/s11011-022-01150-x