Addressing the inequalities in global genetic studies for the advancement of Genetic Epidemiology

Abstract

The human reference genome assembly has been available for two decades, and advancements in sequencing technology have enabled rapid whole-genome sequencing in single institutes. WGS (whole-genome sequencing) data analysis applications will enable large-scale data analysis on multi-clouds, integrate datasets with a population scale, and ensure the reproducibility of publications through modern workflow engines and scalability. In human genetics, expert-knowledge-driven approaches from medical and biological professionals and data-driven approaches from computer science applied to epidemiology, such as AI (artificial intelligence), are required for domain-specific downstream data interpretations. For reliable diagnostic, prognostic, and therapeutic tools, as well as generalized outcomes, genomic studies should involve a wide range of majority and minority populations. The field of genomics in medicine is entering a new era, and to increase the application of gene therapy in the treatment of emerging infections and disorders, there needs to be a united worldwide effort.