Insulin resistance is prevalent in chronic kidney disease and may accelerate the progression of chronic kidney disease. This study aimed to investigate whether insulin resistance is associated with the development of incident chronic kidney disease in a population with normal renal function. Methods: A total of 3,331 participants from a community-based cohort with normal renal function were prospectively analyzed. We determined the relationship of insulin resistance indices with the incident chronic kidney disease using the Cox proportional hazard model and Kaplan-Meier survival analysis. Results: During a mean follow-up of 11.03 ± 4.22 years, incident chronic kidney disease occurred in 414 participants (12.4%). The high homeostasis model assessment-insulin resistance level group had an increased risk of incident chronic kidney disease (hazard ratio [HR], 1.40; 95% confidence interval [CI], 1.13–1.74; p = 0.002) compared to the normal group after adjustment for age, sex, history of hypertension, body mass index, total cholesterol, alcohol drinking status, smoking status, and baseline estimated glomerular filtration rate. The risk of incident chronic kidney disease also increased with the lower quantitative insulin sensitivity check index level (HR, 0.62; 95% CI, 0.41–0.92; p = 0.02) and higher leptin-adiponectin ratio level (HR, 1.23; 95% CI, 1.06–1.42; p = 0.006). Conclusion: Higher insulin resistance indices are associated with the incidence of chronic kidney disease. Our data suggest that increased insulin resistance may be involved in the development of incident chronic kidney disease in a population with normal renal function.

Fabry disease (FD) is an X-linked lysosomal disorder caused by α-galactosidase A enzyme activity deficiency. Although glycosphingolipid analogs have been identified in the plasma or urine of patients with FD, there is a limited understanding of altered metabolomics profiles beyond the globotriaosylceramide accumulation in FD. Methods: Metabolomics study was performed for monitoring of biomarker and altered metabolism related with disease progression in serum and urine from male α-galactosidase A knockout mice and age-matched wild-type mice at 20 and 40 weeks. Profiling analysis for metabolites, including organic acids, amino acids, fatty acids, kynurenine pathway metabolites, and nucleosides in the serum and urine was performed using gas chromatography-tandem mass spectrometry and liquid chromatography-tandem mass spectrometry combined with star symbol patterns and partial least squares discriminant analysis (PLS-DA). Results: A total of 27 and 23 metabolites from the serum and urine of FD mice were distinguished from those of wild-type mice, respectively, based on p-value (<0.05) and variable importance in projection scores (>1.0) of PLS-DA. In the serum, metabolites of the glutathione, glutathione disulfide, citrulline, and kynurenine pathways that are related to oxidative stress, nitric oxide biosynthesis, and inflammation were increased, whereas those involved in pyruvate and tyrosine metabolism and the tricarboxylic acid cycle were altered in the 20- and 40-week-old urine of FD model mice. Conclusion: Altered metabolic signatures associated with disease progression by oxidative stress, inflammation, nitric oxide biosynthesis, and immune regulation in the early and late stages of FD.

Background/Aims: Obesity has known to be a modifiable risk factor associated with worse outcomes in chronic kidney disease (CKD), but few studies have examined the impact of obesity on CKD incidence in the general population. The purpose of this study was to investigate the role of body mass index (BMI) and waist-to-hip ratio (WHR) as predictors of incident CKD and to evaluate the impact of weight reduction on CKD prevention. Methods: A total of 2,711 participants from a community-based cohort with normal renal function were prospectively analyzed. Among participants with obesity, we analyzed the change in WHR to evaluate the association of obesity reduction with CKD development. Results: During a mean follow-up of 11.03 ± 4.22 years, incident CKD occurred in 190 (7.0%) participants. In the fully adjusted multivariable Cox proportional hazard models, the risk of incident CKD increased with higher BMI (hazard ratio, 1.06; 95% confidence interval, 1.00–1.11; p = 0.033) and higher WHR (hazard ratio, 1.33; 95% confidence interval, 1.07–1.66; p = 0.009). In the Kaplan–Meier analysis, cumulative adverse renal events were significantly more common in the maintained obesity group than in the reduced obesity group (p = 0.001). Conclusions Both higher BMI and WHR were associated with development of CKD, but the magnitude of the effect of WHR was higher than that of BMI. Moreover, reducing obesity would be beneficial for renal prognosis.

Artificial intelligence (AI) is revolutionizing healthcare by providing tools for disease prediction, diagnosis, and patient management. This review focuses on two key AI methodologies in healthcare: predictive modeling and causal inference. Predictive models excel in identifying patterns to forecast outcomes but are limited in explaining the underlying causes. In contrast, causal inference focuses on understanding cause-and-effect relationships, which makes effective medical interventions possible. Although randomized controlled trials (RCTs) are the gold standard for causal inference, they face limitations including cost and ethical concerns. As alternatives, emulated RCTs and advanced machine learning techniques have emerged for estimating causal effects, bridging the gap between prediction and causality. Additionally, Shapley values and Local Interpretable Model-Agnostic Explanations improve the interpretability of complex AI models, making them more actionable in clinical settings. Integrating prediction and causal inference holds great promise for advancing personalized medicine, enhancing patient outcomes, and optimizing healthcare delivery. However, careful application of AI tools is crucial to avoid misinterpretation and maximize their potential.

Several studies have reported that depression is prevalent in patients with diabetes or chronic kidney disease. However, the relationship between weight changes and the risk of depression has not been elucidated in patients with diabetic kidney disease (DKD). Methods: From the Korean National Health Insurance Service database, we selected 67,866 patients with DKD and body weight data from two consecutive health examinations with a 2-year interval between 2009 and 2012. Weight change over 2 years was categorized into five groups: ≥–10%, <–10% to ≥–5%, <–5% to <5%, ≥5% to <10%, and ≥10%. The occurrence of depression was monitored via the codes of International Statistical Classification of Diseases, 10th revision through the end of 2018. Results: During the 5.24-year follow-up, 17,023 patients with DKD developed depression. Weight change and the risk of depression had a U-shaped relationship: patients with ≥–10% weight change (hazard ratio [HR], 1.12) and those with ≥10% weight change (HR, 1.11) showed higher HRs for depression than those with <–5% to <5% weight change, even after adjusting for several confounding factors. In the subgroup analyses, the risk of depression tended to increase as weight gain or weight loss increased in all subgroups. Conclusion: Both weight loss and weight gain increased the risk of depression in patients with DKD.

Although multiple factors influence the risk of major adverse cardiovascular events (MACE), the effects of socioeconomic status on MACE in the presence and absence of renal dysfunction (RD) have not been comprehensively explored in Korea. Methods: We examined the effects of socioeconomic status on MACE in individuals with and without RD. The data of 44,473 Koreans from 2008 to 2017 were obtained from the Health Care Big Data Platform of the Ministry of Health and Welfare in Korea. Their socioeconomic status was assessed using a socioeconomic score (SES) based on marital status, education, household income, and occupation. The incidence of myocardial infarction (MI), stroke, and death was compared according to SES level (0–4). Multiple linear regression analysis was used to evaluate the hazard ratios and 95% confidence intervals for outcomes based on participant SES. Results: MI risk was only affected by education level. The participants’ income, education, and SES affected their stroke risk, whereas death was associated with all four socioeconomic factors. The incidence of stroke and death increased as SES worsened (from 0 to 4). SES was positively related to risk of stroke and death in participants without RD. SES did not affect MI, stroke, or death in participants with RD. Conclusion: A low socioeconomic status is associated with risk of stroke and death, especially in individuals without RD.

Urine chloride has recently been suggested as a biomarker of renal tubule function in patients with nondialysis chronic kidney disease (CKD), as low urinary chloride concentration is associated with an increased risk of CKD progression. We investigate the association between urinary chloride excretion and the progression of coronary artery calcification (CAC). Methods: A total of 1,065 patients with nondialysis CKD were divided into tertiles by spot urine chloride-to-creatinine ratios. The 1st, 2nd, and 3rd tertiles were defined as low, moderate, and high urinary chloride excretion, respectively. The study outcome was CAC progression, which was defined as an increase in coronary artery calcium score of more than 200 Agatston units during the 4-year follow-up period. Results: Compared to moderate urinary chloride excretion, high urinary chloride excretion was associated with decreased risk of CAC progression (adjusted odds ratio, 0.379; 95% confidence interval, 0.190–0.757), whereas low urinary chloride excretion was not associated with risk of CAC progression. Restricted cubic spine depicted an inverted J-shaped curve, with a significant reduction in the risk of CAC progression in subjects with high spot urine chloride-to-creatinine ratios. Conclusion: High urinary chloride excretion is associated with decreased risk of CAC progression in patients with nondialysis CKD.

Background/Aims: The neutrophil-to-lymphocyte ratio (NLR) has a prognostic value in cardiovascular disease, infection, inflammatory disease, and several malignancies. Therefore, the NLR has a possible predictive value in patients with chronic kidney disease (CKD), but this predictive value has not been validated. Here, we aimed to investigate the possibility of NLR as a predictor of CKD progression. Methods: This retrospective observational study included 141 patients with non-dialysis CKD. The participants were divided into terciles (T1, T2, and T3) according to NLR. The primary outcome was defined as a composite kidney event, which included a decline in the estimated glomerular filtration rate (eGFR) of at least 50% or initiation of renal replacement therapy during the follow-up period. Results: The mean follow-up duration was 5.45 ± 2.11 years. The mean NLRs were 1.35 ± 0.05 in T1 (n = 47), 2.16 ± 0.04 in T2 (n = 47), and 4.29 ± 0.73 in T3 (n = 47). The group with the highest NLR (T3) had higher baseline CKD and serum creatinine and lower eGFR levels than the group with the lowest NLR (T1). The cumulative incidence rate of composite kidney events was significantly higher in T3 compared with T1 (p < 0.001, log-rank test). Cox regression analysis revealed that high NLR was associated with the risk of composite kidney events (adjusted hazard ratio, 3.33; 95% confidence interval, 1.43–7.76). Conclusions A higher NLR reflects the more advanced stage of CKD and suggests a role for NLR as a biomarker for predicting CKD progression.

Osteoprotegerin is an important regulator of bone metabolism and vascular calcification. The association between serum osteoprotegerin level and chronic kidney disease (CKD) progression has not been elucidated. We investigated the prognostic value of serum osteoprotegerin levels in nondialysis CKD patients. Methods: We analyzed 2,082 patients enrolled in the Korean Cohort Study for Outcomes in Patients with CKD between 2011 and 2016. Patients were divided into quartiles by their serum osteoprotegerin levels. The primary outcome was the occurrence of ≥1 of the following: dialysis initiation, kidney transplantation, a two-fold increase in serum creatinine level from baseline, or a 50% decrease in the estimated glomerular filtration rate (eGFR). Cox proportional hazard regression models were used to investigate the prognostic value of the serum osteoprotegerin level to CKD progression. Results: The median follow-up period was 48.9 months, and 641 patients (30.8%) experienced the primary outcome. The hazard ratio of serum osteoprotegerin for renal progression in the full extended Cox proportional hazard model was 1.064 (95% confidence interval, 1.041–1.088). Subgroup analyses by age, presence of diabetes, and eGFR showed significant results consistent with the overall analysis results. Conclusion: Serum osteoprotegerin level is independently associated with renal prognosis and could have prognostic importance in CKD progression.