Single-Cell Advances in Investigating and Understanding Chronic Kidney Disease and Diabetic Kidney Disease
Sagar Bhayana, Philip Andreas Schytz, Emma T. B. Olesen, Keng Soh, Vivek Das
Abstract
Chronic kidney disease (CKD) and its subset diabetic kidney disease are progressive conditions that affect >850 million people worldwide. Diabetes, hypertension, and glomerulonephritis are the most common causes of CKD, which is associated with significant patient morbidity and an increased risk of cardiovascular events, such as heart failure, ultimately leading to premature death. Despite newly approved drugs, increasing evidence shows that patients respond to treatment differently given the complexity of disease heterogeneity and complicated pathophysiology. This review article presents an integrative approach to understanding and addressing CKD through the lens of precision medicine and therapeutics. Advancements in single-cell omics technologies and artificial intelligence can be leveraged to explore the intricate cellular mechanisms underlying CKD and diabetic kidney disease pathogenesis. Dissecting the cellular heterogeneity and identifying rare cell populations using single-cell approaches will facilitate uncovering novel therapeutic targets and biomarkers for personalized treatment strategies. Finally, we discuss the potential of artificial intelligence-driven analyses in predicting disease progression and treatment response, thereby paving the way for tailored interventions.