Sagar Bhayana, Philip Andreas Schytz, Emma Tina Bisgaard Olesen, Keng Soh, Vivek Das
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Single-Cell Advances in Investigating and Understanding Chronic Kidney Disease and Diabetic Kidney Disease.
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. Leveraging advancements in single-cell omics technologies and artificial intelligence, we can explore the intricate cellular mechanisms underlying CKD and diabetic kidney disease pathogenesis. By dissecting the cellular heterogeneity and identifying rare cell populations using single-cell approaches, it will be possible to uncover 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.
期刊介绍:
The American Journal of Pathology, official journal of the American Society for Investigative Pathology, published by Elsevier, Inc., seeks high-quality original research reports, reviews, and commentaries related to the molecular and cellular basis of disease. The editors will consider basic, translational, and clinical investigations that directly address mechanisms of pathogenesis or provide a foundation for future mechanistic inquiries. Examples of such foundational investigations include data mining, identification of biomarkers, molecular pathology, and discovery research. Foundational studies that incorporate deep learning and artificial intelligence are also welcome. High priority is given to studies of human disease and relevant experimental models using molecular, cellular, and organismal approaches.