Chronic Kidney Disease (CKD) is a progressive condition characterized by the gradual loss of renal function over time, affecting millions worldwide and representing a significant public health challenge. CKD is associated with increased morbidity and mortality, primarily due to cardiovascular complications, and its prevalence continues to rise due to factors such as diabetes, hypertension, and aging populations. Despite advances in understanding its etiology, early detection remains a challenge, and current diagnostic methods often identify the disease at advanced stages, limiting therapeutic options and impacting patient outcomes. Early diagnosis of CKD is crucial for implementing interventions that can slow disease progression, prevent complications, and improve quality of life. Consequently, there is a growing emphasis on personalized management strategies tailored to the unique molecular and clinical profiles of patients. Personalized approaches enable targeted therapies, optimize treatment efficacy, and reduce adverse effects, ultimately transforming CKD care from a one-size-fits-all model to precision medicine. Multi-omics approaches have emerged as powerful tools in modern medicine, offering comprehensive insights into the molecular landscape of diseases like CKD. By integrating data from various biological layers, such as genomics, transcriptomics, proteomics, epigenomics, and metabolomics, researchers can achieve a holistic understanding of disease mechanisms, identify novel biomarkers, and uncover therapeutic targets. This systems biology perspective enables the characterization of individual variability, facilitating the development of personalized treatment strategies. In conclusion, multi-omics has the potential to revolutionize early diagnosis, refine patient stratification, and guide the design of targeted pharmacological interventions, paving the way for a new paradigm in disease management.
Li et al. (Sat,) studied this question.