The Path towards Precision Health: Prospects and Challenges

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Background

The science of genomics is strongly and rapidly impacting not only our understanding of life and of concepts of health and disease, but also increasingly the care of patients and the delivery of health services. The identification of the differences between and within populations in relation to susceptibility to disease and in the response to treatment has inspired the concept of “Precision Medicine,” which has been hailed as the future of medicine for well over a decade and is now progressively gaining ground against conventional approaches to health based on simplistic universal notions of an “average patient.” Its promise includes a move toward a practice of medicine that is more “Predictive, Preventive, and Personalized” while maintaining the medical community's standards of being “Effective, Efficient, and Evidence-based.” Fueled by concomitant “Omics” and “Big Data” revolutions, the “Precision Paradigm” has promised to revolutionize all aspects of medicine, including targeted drug development, individualized prescriptions, new methods of testing drugs, evaluating public health programs, and improving the accuracy of diagnoses and personalized prevention.

The Precision Paradigm owes much of its tenets and utility to genomics advancements. Historically intriguing questions (e.g., “Why do we fall sick?”) are now being thoroughly investigated thanks to these bundles of tools, thus inaugurating whole novel paradigms and concepts in biomedical sciences. It has recently become apparent that even in conditions classically attributed to a single input, such as Mendelian diseases, a number of genetic or environmental inputs might be involved. It is therefore imperative to revisit paradigms and dictums, such as monogenic disease (one gene/one disease) scenarios typically explained within a Mendelian framework. Genomic interactions, as well as human-microbial host-parasite genomic and transcriptomic interactions, are increasingly shown to be potent modifiers of phenotypic outcomes in infectious and non-infectious disease, thus adding a layer of complexity to the already complex milieu of interactions that form the current working paradigms of systems biology. There is no place where such challenge is put into test more than the African continent. Africa is mankind's ancestral home and the store of its greatest wealth of genetic diversity. It has equally rich social and cultural legacies that may impinge on the understanding and practice of precision medicine.

An appraisal of the above, as well as of the implementation of stratified and personalized/precision interventions at the community and individual levels, will make the core of this Research Topic.

Recent advances in genomics offer new and powerful tools and techniques, which allow us to dissect and analyze the genetic structure of individuals, families, and populations at unprecedented levels of detail and with nearly global coverage of the variation they contain. They open new avenues to interpret this variation in the context of biology, history, and the environment, furthering our understanding and their relation to the health and wellbeing of individuals and populations worldwide.

Potential sub-topics include, but are not limited to:
• Stratified and individualized approaches in finite and structured populations, incorporating predictive and preventive genomics, applications and caveats, Precision Medicine, and Public Health with emphasis on the hurdles and challenges posed when adopting such approaches in populations of high effective size like African populations.
• Multi-omic contributions to refining disease phenotypes and gene-phenotype correlation (including epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics)
• Pharmacogenomics and genetics for Precision Health: Precision approaches in drug development and testing
• Fundamental tools, platforms, and workflows for Precision in Health
• Population Cohorts and Biobanks
• The Ethics of identification and return of actionable variants in personalized and population genomics

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