Association between bilirubin and chronic kidney disease in hypertensive patients: The China hypertension registry study

Evaluation of a tumor marker gastrin-releasing peptide precursor in the patients with kidney injuries

Gastrin-releasing peptide precursor (ProGRP) is a bioactive precursor of GRP and might play an important role as an emerging tumor marker in early cancer diagnosis. It might also be abnormal in the nonmalignant disease and renal function abnormalities. The present study was undertaken to investigate the changes of ProGRP levels in patients with kidney injuries, especially with chronic kidney disease (CKD), determine the upper reference intervals and clinical diagnostic value of ProGRP in CKD, and thus help oncologists in interpreting ProGRP levels and making clinical judgments of malignances. 676 individuals were enrolled in this cross-sectional study and divided into five groups: healthy control (n=194), CKD (n=272), nephrotic syndrome (NS) (n=137), antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) (n=41), and urinary tract infection (UTI) (n=32). A total of 27 features including age, gender, and 25 laboratory markers were analyzed. Machine learning algorithms were built for the diagnostic models of CKD. Statistical analysis was performed by R software. It was shown that serum ProGRP level in CKD was significantly higher than that in healthy controls, UTI and NS (P < 0.01). The upper reference limit of ProGRP was 188.42 pg/ml for CKD, 245.40 pg/ml for CKD IV-V, and 97.25 pg/ml for NS. Compared with the healthy control, the level of serum ProGRP in CKD stages II, III, IV-V was significantly increased and elevated progressively with CKD grade (P < 0.01). Random Forest (RF) model works best among 4 building machine learning algorithms. 5 vital indicators, ProGRP, estimated glomerular filtration rate (eGFR), urea, albumin (ALB), and direct bilirubin (DBIL), were selected to establish RF model for diagnosing CKD with an area under the curve (AUC) of 0.96 (95% confidence interval [CI]: 0.94-0.97) and high sensitivity (0.89) and specificity (0.92). This study demonstrates that the level of ProGRP in patients with CKD, nephrotic syndrome or AAV, was significantly higher than that in the healthy population. The machine learning model of ProGRP with DBIL, eGFR, ALB, and urea, could provide good clinical value for CKD evaluation.

Bilirubin bioconversion to urobilin in the gut-liver-kidney axis: A biomarker for insulin resistance in the Cardiovascular-Kidney-Metabolic (CKM) Syndrome

The rising rates of obesity worldwide have increased the incidence of cardiovascular disease (CVD), making it the number one cause of death. Higher plasma bilirubin levels have been shown to prevent metabolic dysfunction and CVD. However, reducing levels leads to deleterious outcomes, possibly due to reduced bilirubin half-life that escalates the production of its catabolized product, urobilinogen, produced by gut bacteria and naturally oxidized to urobilin. Recent findings suggest that the involvement of the microbiome catabolism of bilirubin to urobilin and its absorption via the hepatic portal vein contributes to CVD, suggesting a liver-gut axis involvement. We discuss the studies that demonstrate that urobilin is frequently raised in the urine of persons with CVD and its probable role in acquiring the disease. Urobilin is excreted from the kidneys into the urine and may serve as a biomarker for Cardiovascular-Kidney-Metabolic (CKM) Syndrome. We deliberate on the newly discovered bilirubin reductase (BilR) bacterial enzyme that produces urobilin. We discuss the bacterial species expressing BilR, how they impact CVD, and whether suppressing urobilin production and increasing bilirubin may provide new therapeutic strategies for CKM. Possible therapeutic mechanisms for achieving this goal are discussed.

Profiling Exosomal Metabolomics as a Means for Diagnosis and Researching Early-Stage Hypertensive Nephropathy

Aims/Background Hypertension (HT) is a prevalent medical condition showing an increasing incidence rate in various populations over recent years. Long-term hypertension increases the risk of the occurrence of hypertensive nephropathy (HTN), which is also a health-threatening disorder. Given that very little is known about the pathogenesis of HTN, this study was designed to identify disease biomarkers, which enable early diagnosis of the disease, through the utilization of high-throughput untargeted metabolomics strategies. Methods The participants of this study were patients admitted to The Second Affiliated Hospital of Chengdu Medical College, Nuclear Industry 416 Hospital, who were randomly divided into three groups: Normal group (n = 11), HT group (n = 10), and HTN group (n = 12). Urine exosomes were extracted, purified, and subjected to untargeted metabolomics analysis. Differential metabolites and their significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified. The least absolute shrinkage and selection operator (LASSO) regression analysis was then employed to establish a diagnostic model for early-stage HTN. Finally, logistic regression and receiver operating characteristic (ROC) curve analysis were performed to identify biomarkers related to early HTN. Results Orthogonal partial least squares-discriminant analysis (OPLS-DA) revealed significant differences in the metabolic profiles of the three patient groups. Compared to subjects of the Normal group, the HT and HTN groups exhibited significantly upregulated and downregulated profiles of differential metabolites, respectively. LASSO regression analysis results indicated that 4-hydroxyphenylacetic acid, bilirubin, uracil, and iminodiacetic acid are potential biomarkers for HTN or HT. Conclusion With untargeted metabolomics analysis, we successfully identified differential metabolites in HTN. A further LASSO regression analysis revealed that four key metabolites, namely 4-hydroxyphenylacetic acid, bilirubin, uracil, and iminodiacetic acid, hold promise for the diagnosis of early-stage HTN.

Association between bilirubin and chronic kidney disease in hypertensive patients: The China hypertension registry study

Limited data exists on the association between Direct bilirubin (DBIL) and Indirect bilirubin (IBIL) with the risk of chronic kidney disease (CKD) among patients with hypertension. This study aimed to assess the relationship between DBIL and IBIL with the risk of CKD in a cohort of Chinese adults diagnosed with hypertension. This study included 14 182 Chinese patients with hypertension between the ages of 27 and 96. CKD, the outcome variable, was defined by an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 . The study employed multivariate linear and multivariate logistic regression analysis to evaluate the correlation between DBIL and IBIL with the risk of CKD. The prevalence of CKD in the study population was 9.77%. Multivariate logistic regression analysis showed that the increase in DBIL (OR: 0.66; 95% CI: 0.61, 0.71) and IBIL (OR: 0.75; 95% CI: 0.71, 0.81) were independently and negatively correlated with CKD. Further analyses using a restricted cubic spline (smooth-fitting curve) confirmed the linearly negative association between DBIL and IBIL with the risk of CKD. The subgroup analysis showed that the correlation between IBIL and CKD was stronger among men and populations <65 years of age (p for interaction <.05). DBIL and IBIL were independently and negatively associated with CKD. Furthermore, the correlation between DBIL and IBIL with CKD in the hypertensive population is more significant in those under 65 years of age. These findings may inform future strategies for the management of CKD.