Analysis of chronic kidney disease epidemiology in Kazakhstan using nationwide data for 2014-2020 and forecasting future trends of prevalence and mortality for 2030.

According to the Global Burden of Disease (GBD) study, chronic kidney disease (CKD) was prevalent in 697.5 million individuals worldwide in 2017. By 2040, it is anticipated that CKD will rank as the fifth most common cause of death. This study aims to examine the epidemiology of CKD in Kazakhstan and to project future trends in CKD prevalence and mortality by 2030. The retrospective analysis was performed on a database acquired from the Unified National Electronic Health System for 703,122 patients with CKD between 2014 and 2020. During the observation period, 444,404 women and 258,718 men were registered with CKD, 459,900 (66%) were Kazakhs and 47% were older than 50. The incidence rate notably decreased: 6365 people per million population (PMP) in 2014 and 4040 people PMP in 2020. The prevalence changed from 10,346 to 38,287 people PMP, and the mortality rate increased dramatically from 279 PMP to 916 PMP. Kazakhstan's central regions, Turkestan and Kyzylorda were identified as the most burdensome ones. The ARIMA model projected 1,504,694 expected prevalent cases in 2030. The predicted mortality climbed from 17,068 cases in 2020 to 37,305 deaths in 2030. By 2030, the prevalence and mortality of CKD will significantly increase, according to the predicted model. A thorough action plan with effective risk factor management, enhanced screening among risk populations, and prompt treatment are required to lessen the burden of disease in Kazakhstan.

Urinary Protein Profiling for Potential Biomarkers of Chronic Kidney Disease: A Pilot Study.

Proteinuria is a risk factor for chronic kidney disease (CKD) progression and associated complications. However, there is insufficient information on individual protein components in urine and the severity of CKD. We aimed to investigate urinary proteomics and its association with proteinuria and kidney function in early-stage CKD and in healthy individuals. A 24 h urine sample of 42 individuals (21-CKD and 21-healthy individuals) was used for mass spectrometry-based proteomics analysis. An exponentially modified protein abundance index (emPAI) was calculated for each protein. Data were analyzed by Mascot software using the SwissProt database and bioinformatics tools. Overall, 298 unique proteins were identified in the cohort; of them, 250 proteins belong to the control group with median (IQR) emPAI 39.1 (19−53) and 142 proteins belong to the CKD group with median (IQR) emPAI 67.8 (49−117). The level of 24 h proteinuria positively correlated with emPAI (r = 0.390, p = 0.011). The emPAI of some urinary proteomics had close positive (ALBU, ZA2G, IGKC) and negative (OSTP, CD59, UROM, KNG1, RNAS1, CD44, AMBP) correlations (r < 0.419, p < 0.001) with 24 h proteinuria levels. Additionally, a few proteins (VTDB, AACT, A1AG2, VTNC, and CD44) significantly correlated with kidney function. In this proteomics study, several urinary proteins correlated with proteinuria and kidney function. Pathway analysis identified subpathways potentially related to early proteinuric CKD, allowing the design of prospective studies that explore their response to therapy and their relationship to long-term outcomes.

Development and validation of hybrid Brillouin-Raman spectroscopy for non-contact assessment of mechano-chemical properties of urine proteins as biomarkers of kidney diseases.

BACKGROUND: Proteinuria is a major marker of chronic kidney disease (CKD) progression and the predictor of cardiovascular mortality. The rapid development of renal failure is expected in those patients who have higher level of proteinuria however, some patients may have slow decline of renal function despite lower level of urinary protein excretion. The different mechanical (visco-elastic) and chemical properties, as well as the proteome profiles of urinary proteins might explain their tubular toxicity mechanism. Brillouin light scattering (BLS) and surface enhanced Raman scattering (SERS) spectroscopies are non-contact, laser optical-based techniques providing visco-elastic and chemical property information of probed human biofluids. We proposed to study and compare these properties of urinary proteins using BLS and SERS spectroscopies in nephrotic patient and validate hybrid BLS-SERS spectroscopy in diagnostic of urinary proteins as well as their profiling. The project ultimately aims for the development of an optical spectroscopic sensor for rapid, non-contact monitoring of urine samples from patients in clinical settings. METHODS: BLS and SERS spectroscopies will be used for non-contact assessment of urinary proteins in proteinuric patients and healthy subjects and will be cross-validated by Liquid Chromatography-Mass Spectrometry (LC-MS). Participants will be followed-up during the 1 year and all adverse events such as exacerbation of proteinuria, progression of CKD, complications of nephrotic syndrome, disease relapse rate and inefficacy of treatment regimen will be registered referencing incident dates. Associations between urinary protein profiles (obtained from BLS and SERS as well as LC-MS) and adverse outcomes will be evaluated to identify most unfavored protein profiles. DISCUSSION: This prospective study is focused on the development of non-contact hybrid BLS - SERS sensing tool and its clinical deployment for diagnosis and prognosis of proteinuria. We will identify the most important types of urine proteins based on their visco-elasticity, amino-acid profile and molecular weight responsible for the most severe cases of proteinuria and progressive renal function decline. We will aim for the developed hybrid BLS - SERS sensor, as a new diagnostic & prognostic tool, to be transferred to other biomedical applications. TRIAL REGISTRATION: The trial has been approved by ClinicalTrials.gov (Trial registration ID NCT04311684). The date of registration was March 17, 2020.