Urinary proteomics for kidney dysfunction: insights and trends

Omics Studies in CKD: Diagnostic Opportunities and Therapeutic Potential

Omics technologies have significantly advanced the prediction and therapeutic approaches for chronic kidney disease (CKD) by providing comprehensive molecular insights. This is a review of the current state and future prospects of integrating biomarkers into the clinical practice for CKD, aiming to improve patient outcomes by targeted therapeutic interventions. In fact, the integration of genomic, transcriptomic, proteomic, and metabolomic data has enhanced our understanding of CKD pathogenesis and identified novel biomarkers for an early diagnosis and targeted treatment. Advanced computational methods and artificial intelligence (AI) have further refined multi-omics data analysis, leading to more accurate prediction models for disease progression and therapeutic responses. These developments highlight the potential to improve CKD patient care with a precise and individualized treatment plan .

Association of four metalloids in the serum and urine of individuals with major depressive disorders: a case-control study

Background

Major depressive disorder (MDD) pathogenesis may involve metalloids in a significant way. The aim of our study was to identify potential links between MDD and metalloid elements [boron (B), germanium (Ge), arsenic (As), antimony (Sb)].

Methods

A total of 72 MDD cases and 75 healthy controls (HCs) were recruited from Zhumadian Second People's Hospital in Henan Province, China. The levels of four metallic elements (B, Ge, As, and Sb) in the serum and urine were measured using inductively coupled plasma mass spectrometry (ICP-MS).

Results

In comparison to the HCs, the B, As, and Sb levels were considerably lower in the MDD group (p < 0.05) in the serum; the MDD group had significantly higher (p < 0.05) and significantly lower (p < 0.001) B and Sb levels in the urine. After adjusting for potential confounders, serum B (OR = 0.120; 95% CI, 0.048, 0.300; p < 0.001) and Sb (OR = 0.133; 95% CI, 0.055, 0.322; p < 0.001) showed a negative correlation with MDD. Urine B had a negative correlation (OR = 0.393; 95% CI, 0.193, 0.801; p = 0.01) with MDD, while urine Sb had a positive correlation (OR = 3.335; 95% CI, 1.654, 6.726; p = 0.001) with MDD.

Conclusion

Our current research offers insightful hints for future investigation into the function of metalloids in connection to MDD processes.

Prognostic Biomarkers Based on Proteomic Technology in COPD: A Recent Review

Chronic obstructive pulmonary disease (COPD) is a common heterogeneous respiratory disease which is characterized by persistent and incompletely reversible airflow limitation. Due to the heterogeneity and phenotypic complexity of COPD, traditional diagnostic methods provide limited information and pose a great challenge to clinical management. In recent years, with the development of omics technologies, proteomics, metabolomics, transcriptomics, etc., have been widely used in the study of COPD, providing great help to discover new biomarkers and elucidate the complex mechanisms of COPD. In this review, we summarize the prognostic biomarkers of COPD based on proteomic studies in recent years and evaluate their association with COPD prognosis. Finally, we present the prospects and challenges of COPD prognostic-related studies. This review is expected to provide cutting-edge evidence in prognostic evaluation of clinical patients with COPD and to inform future proteomic studies on prognostic biomarkers of COPD.

Urinary extracellular vesicles: does cargo reflect tissue?

PURPOSE OF REVIEW

To review recent developments in urinary extracellular vesicles (uEVs) to study kidney physiology and disease.

RECENT FINDINGS

Proteomic analysis in rats showed significant correlations between kidney and uEV protein abundances. Consistent with uEV biogenesis, these correlations were stronger for membrane-associated proteins than for e.g. soluble kinases or E3 ubiquitin ligases. When challenged with a high potassium diet, the physiologically predicted protein changes occurred both in kidney and uEVs, suggesting that analysis of uEVs might be utilized as a proxy or even replacement for tissue analysis. Although kidney-uEV correlations are more difficult to obtain in humans, analysis of uEV cargo from patients with inherited tubulopathies or with primary aldosteronism were also consistent with the predicted changes at the tissue level. The kidney appears to be the main source of uEVs, with a recent study showing that nephron mass determines uEV excretion rate. Therefore, a measure of nephron mass should be included for between-subject comparisons.

SUMMARY

The overall good correlation between kidney and uEV protein abundances renders uEVs an attractive noninvasive source of biomarkers for studying kidney physiology or disease. However, differences in per-protein kidney-uEV correlations and per-person uEV excretion rates should be considered in uEV biomarker studies.

Using human urinary extracellular vesicles to study physiological and pathophysiological states and regulation of the sodium chloride cotransporter

The thiazide-sensitive sodium chloride cotransporter (NCC), expressed in the renal distal convoluted tubule, plays a major role in Na+, Cl- and K+ homeostasis and blood pressure as exemplified by the symptoms of patients with non-functional NCC and Gitelman syndrome. NCC activity is modulated by a variety of hormones, but is also influenced by the extracellular K+ concentration. The putative "renal-K+ switch" mechanism is a relatively cohesive model that links dietary K+ intake to NCC activity, and may offer new targets for blood pressure control. However, a remaining hurdle for full acceptance of this model is the lack of human data to confirm molecular findings from animal models. Extracellular vesicles (EVs) have attracted attention from the scientific community due to their potential roles in intercellular communication, disease pathogenesis, drug delivery and as possible reservoirs of biomarkers. Urinary EVs (uEVs) are an excellent sample source for the study of physiology and pathology of renal, urothelial and prostate tissues, but the diverse origins of uEVs and their dynamic molecular composition present both methodological and data interpretation challenges. This review provides a brief overview of the state-of-the-art, challenges and knowledge gaps in current uEV-based analyses, with a focus on the application of uEVs to study the "renal-K+ switch" and NCC regulation. We also provide recommendations regarding biospecimen handling, processing and reporting requirements to improve experimental reproducibility and interoperability towards the realisation of the potential of uEV-derived biomarkers in hypertension and clinical practice.