A roadmap to precision medicine through post-genomic electronic medical records

Abstract

The promise of integrating Electronic Medical Records (EMR) and genetic data for precision medicine has largely fallen short due to its omission of environmental context over time. Post-genomic data can bridge this gap by capturing the real-time dynamic relationship between underlying genetics and the environment. This perspective highlights the pivotal role of integrating EMR and post-genomics for personalized health, reflecting on lessons from past efforts, and outlining a roadmap of challenges and opportunities that must be addressed to realize the potential of precision medicine.

Fig. 1. Depiction of the cycle of post-genomic research to clinical translation.

This circular flow diagram represents the sequential stages of post-genomic research leading to clinical translation. Starting with patient enrollment, the cycle progresses through clinical visits, biosample collection, electronic medical record (EMR) integration, and -omics data generation. These steps culminate in biomarker discovery, ultimately enabling clinical translation. The circular structure highlights the iterative and interconnected nature of these processes. Created in BioRender. Su, J. (2024) https://BioRender.com/s06p486.

Fig. 2. Comparison of health trajectories over time with (left) and without (right) -omics biomarker panels across patient scenarios, based on three distinct use cases.

This illustrates how the integration of electronic medical records (EMR) and -omics data within healthcare systems can lead to improved health outcomes. Solid red lines represent health trajectories with -omics monitoring, showing improved outcomes due to timely interventions, while dashed red lines reflect trajectories without -omics monitoring, highlighting delayed interventions. EMR data is depicted as red squares (diagnoses) and red circles (medications), while -omics biomarker panels are represented as green circles (genetic risk screening), blue circles (health management), and purple circles (event risk monitoring). Created in BioRender. Su, J. (2024) https://BioRender.com/s06p486.

Fig. 3. Chronological evolution of electronic medical records (EMR) and ‘omics technologies from 1960 to the present.

This timeline maps key developments in EMR, indicated in red, alongside seminal advances in genomics, marked in blue, and post-genomic fields, highlighted in yellow. Underscoring the integration of EMR with genomics, represented in purple, by 2006, and the subsequent integration with post-genomic data, in brown, by 2013. Created in BioRender. Su, J. (2024) https://BioRender.com/s06p486.