Physical Exercise and Biomolecular Analysis to Reduce Uremic Toxins in Chronic Kidney Disease: An Exploratory Study

This study is a randomized, triple-blind clinical trial with a 10-year follow-up. Sampling is non-probabilistic by accessibility or convenience. Recruitment: Recruitment will be widely promoted via mass media (social media, TV) to invite individuals with chronic kidney disease. Additionally, the investigators will receive referrals from partner physicians and public-private partnerships. Participants will be recruited from dialysis clinics, outpatient clinics, and hospitals in Brasília, DF, respecting privacy and confidentiality. The investigators aim to recruit a minimum of 1,600 adult patients (both sexes), aged 18+, divided into those with CKD in conservative treatment (stages 2, 3, 4, 5, n\~400), renal replacement therapy (hemodialysis and peritoneal dialysis, n\~800), and kidney transplant patients (n\~400). Participants will receive all pertinent information about the study and potential risks and benefits. Those who agree will sign an informed consent form. Following consent, each patient will undergo a comprehensive history assessment, including exercise, medical, and nutritional histories, along with an analysis of their medical records. Monthly evaluations will cover all procedures and interventions outlined for their allocated group. Patient Randomization: Participants will be stratified by CKD stage (conservative treatment, hemodialysis, peritoneal dialysis, and post-transplant) and further randomized by pre-training variables (biological sex, body weight, BMI, and body composition), using an online application. Patients will then be allocated to one of four groups: control (CTL; n\~100), strength training (ST; n\~100), aerobic training (AT; n\~100), and combined training (CT; n\~100). Assessments: Body Composition: BMI, DEXA, 7-Skinfold (Jackson and Pollock protocol); Cardiopulmonary Capacity: Anaerobic threshold, Fitcheck, respiratory muscle strength, spirometry; Muscle Strength: 1RM, handgrip, isokinetic force and power, E-lastic portable dynamometer; Autonomic Nervous System: Cardiovascular regulation during deep breathing, Valsalva maneuver with handgrip exercise, post-exercise ischemia, cold-water hand immersion, perceived exertion, respiratory rate, heart rate, arterial oxygen saturation, HRV, BPV, spontaneous baroreflex sensitivity, EEG, cognitive assessment; Nutritional Assessment: 24-hour dietary recall, food frequency questionnaire; Psychological Assessment: Quality of life (KDQOL-SF36), sleep quality, Beck Depression Inventory; Biochemical and biomolecular Assessments: Biological sample collection (urine, feces, saliva, blood) for measurements of creatinine, cystatin-C, leptin, GDF-15, TGF-β, insulin, albumin, SIRT-1, C-reactive protein, irisin, intact FGF23, C-terminal FGF23, ADMA, soluble α-Klotho, glycated hemoglobin (HbA1c), total cholesterol, LDL-c, HDL-c, triglycerides, myeloperoxidase, lipoperoxidation assay, paraoxonase-1, total antioxidant capacity, nitric oxide, lactate, creatine kinase, uremic toxins (KIM-1, NGAL, indoxyl sulfate, p-cresyl sulfate, TMAO, TNF-α, IL-6, ADMA, exercise-related proteins, BDNF, DNA and RNA isolation (salting out method), telomere length and telomerase activity, microRNA expression analysis, HPLC quantification, and identification of compounds by MALDI TOF/TOF mass spectrometry); Ancestry Analysis: Ancestry genome-wide association stratification; Training Protocols: Physical training protocols will include strength, aerobic, and combined training; Statistical Analysis: Sample size is calculated for 99% power (1-β = 0.99) with an alpha of 5% (α = 0.05) and effect size of 0.1, resulting in 400 patients. Descriptive analysis will be presented in tables and charts. Normality and homogeneity of data will be tested by Shapiro-Wilk and Levene's tests. For normally distributed data, group comparisons will be conducted by two-way ANOVA with Tukey's post-hoc test for significant differences. Non-normally distributed data will be analyzed by Kruskal-Wallis with Dunn's post-test, with results expressed as medians and interquartile ranges. Significance will be set at p \< 0.05, with effect size calculated by Cohen's d. Associations between variables will be evaluated by Spearman's correlation. To minimize type II error, the investigators will calculate variations before and after training as Δ = post-training - pre-training. Principal Component Analysis (PCA) and individual variability analysis will use delta results to identify key variables affecting estimated glomerular filtration rate. This analysis will use the Past software (v4.09). Typical error and smallest worthwhile change (SWC) will be calculated per Swinton et al. (2018). Effect size will follow Hopkins' scale: \<0.2 (trivial), 0.2-0.6 (small), 0.6-1.2 (moderate), 1.2-2.0 (large), 2.0-4.0 (very large), \>4.0 (extremely large). Additionally, K-means cluster analysis, an unsupervised machine learning method, will identify patterns based on numerical distance between variables. Statistical analyses will use Microsoft Excel® 2010, GraphPad Prism 6.0, R and RStudio (v4.1.3), and SPSS (v.21.0).