Abstract

Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data. Furthermore, we highlight the current challenges to put quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data with genomics data for future applications in precision medicine.

Highlights

  • Precision medicine aims to stratify patient populations so as to provide targeted and efficient treatments and reduce adverse treatment effects for human health (König et al, 2017)

  • Genome-wide association studies (GWAS) has not been able to bridge the gap between genotype and phenotype because most of the identified associations only explain a small fraction of heritability and do not provide causality between genetic variants and traits

  • Quantitative proteomics is emerging as a powerful technology for precision medicine

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Summary

Towards Building a Quantitative Proteomics Toolbox in Precision

Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. It opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data.

INTRODUCTION
ANALYSIS OF QUANTITATIVE PROTEOMICS DATA
Statistical and Enrichment Analyses
Network Inference
INTEGRATION WITH GENOMIC DATA
CLINICAL APPLICATIONS
Polygenic Risk Scores
CONCLUSION
AUTHOR CONTRIBUTIONS

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