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Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue

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Decoding Kidney Pathophysiology: Omics-Driven Approaches in Precision Medicine.

Charlotte Delrue¹, Marijn M Speeckaert^1,2

¹Department of Nephrology, Ghent University Hospital, 9000 Ghent, Belgium.

Journal of Personalized Medicine

|December 27, 2024

Summary

This summary is machine-generated.

Precision medicine uses multi-omics to understand chronic kidney disease (CKD) heterogeneity. This approach aims to improve diagnosis, identify biomarkers, and personalize treatments for better patient outcomes.

Keywords:

kidney disease biomarkers multi-omics precision medicine

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Area of Science:

Nephrology
Genomics
Proteomics
Metabolomics
Epigenomics

Background:

Chronic kidney disease (CKD) is a global health issue with complex biology and progressive nature.
Current diagnostic and therapeutic methods often lack efficacy due to disease heterogeneity.
Precision medicine offers a personalized approach to kidney disease research and treatment.

Purpose of the Study:

To explore the role of precision medicine in understanding and treating chronic kidney disease.
To highlight the application of multi-omics technologies in identifying CKD subtypes and therapeutic targets.
To discuss the potential of personalized treatment strategies for improving patient outcomes.

Main Methods:

Integration of multi-omics data, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics.
Application of pharmacogenomics for predicting treatment responses.
Utilizing single-cell and spatial transcriptomics to analyze biological heterogeneity.

Main Results:

Multi-omics integration enhances understanding of CKD by revealing molecular pathways involved in progression and treatment resistance.
Identification of discrete disease subtypes, molecular biomarkers, and potential therapeutic targets.
Insights into biological heterogeneity and personalized treatment responses.

Conclusions:

Precision medicine, through multi-omics, offers a promising avenue for advancing CKD diagnosis, risk assessment, and personalized care.
Overcoming challenges like data integration, cost, and ethical considerations is crucial for realizing its full potential.
Development of standardized protocols, data-sharing frameworks, and advanced computational tools will drive innovation in nephrology.