Precision medicine’s next era combines clinical data with pangenome sequencing

Precision medicine is an innovative healthcare approach used to tailor disease prevention and therapy strategies by accounting for differences in patients’ genes, environments, and lifestyles. Although this approach to medicine dates to the time of Hippocrates, the advent of new diagnostic tools and the deeper understanding of the molecular basis of disease – particularly genomics – makes possible medical interventions that are predicted based on an individual patient’s response or risk of disease.

Genomics is one of the fundamental pillars for precision medicine. For example, sequencing a patient’s DNA can provide information about which drugs may be most effective in treating a particular patient versus those that either may be ineffective or potentially harmful. This practice is known as “pharmacogenomics.” Other techniques and tools leveraged in the delivery of precision medicine may include various molecular or cellular analyses such as proteomics, imaging analysis, nanoparticle-based theranostics[i] , and others.

Given the diversity of the human genome, understanding a patient’s fundamental biology is necessary to make appropriate health decisions. Human genome sequencing programs carried out in several countries have attempted to deliver databases that can be used in precision medicine research. However, there are at least two major gaps in such databases that must be addressed.

The first gap is the lack of clinical data that can be linked quickly and directly to genomic data. This linkage is essential for genome-wide association studies (GWAS) where patients with a particular disease are sequenced to look for shared mutations in the genome. Having databases available that can be searched for specific diseases and patient cohorts based on clinical data, and then accessing genomic sequencing data for these specific patients, would help accelerate GWAS. In addition, it would also enable AI-based tools to automate many tasks of those studies and provide a basis for personalizing innovative digital healthcare tools for specific patient cohorts. Today, the few clinical databases available lack genomic data and are heavily biased towards people living in affluent societies in Europe and North America[ii].

The second gap is the lack of genomic sequencing data from diverse populations as references for biomarker analysis. Recent research efforts seek to address this gap, most notably the publication of a draft human pangenome[iii] reference. This work has demonstrated significant advantages in using a diverse data set of genomic information compared to the standard GRCh38-based workflows. This is an important moment in human genomics and represents a paradigm shift from a single reference sequence to cohorts of genetically diverse data. The recent publication of a paper by the Chinese Pangenome Consortium[iv] demonstrated a remarkable increase in the discovery of novel and missing sequences when individuals are included from underrepresented minority ethnic groups.

At Syndesis Health, we have a mission to improve global health equity and patient health outcomes. To achieve these goals, we are building a unified repository of de-identified clinical data from populations across Latin America, Africa, the Middle East, and Asia. This clinical data will be accessible through our Syntium platform and, in the future, combined with pangenomic information to provide researchers with a unique resource to help address the current gaps in the advancement of precision medicine. In collaboration with our global Network of hospital partners, Syndesis Health offers a unique platform to healthcare and life sciences organizations for accelerating the development of drugs and therapeutics to benefit global populations.

George Zarkadakis, PhD is Chief Innovation Officer at Syndesis Health. He is the author of 11 books, and has published multiple articles on healthcare, AI and innovation in the Harvard Business Review, The Washington Post and many other periodicals..

References

[i] Xie, J., Lee, S. and Chen, X. (2010). Nanoparticle-based theranostic agents. Advanced Drug Delivery Reviews, 62(11), pp.1064–1079. doi: https://doi.org/10.1016/j.addr.2010.07.009.

[ii] Johnson, C.E. and Whiteside, Y.O. (2021). Real-World Evidence for Equality. Health Equity, [online] 5(1), pp.724–726. doi: https://doi.org/10.1016/j.addr.2010.07.009.

[iii] Liao, W.-W., Asri, M., Ebler, J., Doerr, D., Haukness, M., Hickey, G., Lu, S., Lucas, J.K., Monlong, J., Abel, H.J., Buonaiuto, S., Chang, X.H., Cheng, H., Chu, J., Colonna, V., Eizenga, J.M., Feng, X., Fischer, C., Fulton, R.S. and Garg, S. (2023). A draft human pangenome reference. Nature, [online] 617(7960), pp.312–324. doi: https://doi.org/10.1038/s41586-023-05896-x.

[iv] Gao, Y., Yang, X., Chen, H., Tan, X., Yang, Z., Deng, L., Wang, B., Kong, S., Li, S., Cui, Y., Lei, C., Wang, Y., Pan, Y., Ma, S., Sun, H., Zhao, X., Shi, Y., Yang, Z., Wu, D. and Wu, S. (2023). A pangenome reference of 36 Chinese populations. Nature, [online] 617(312 – 324), pp.1–10. doi: https://doi.org/10.1038/s41586-023-06173-7.

Precision medicine’s next era combines clinical data with pangenome sequencing

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