New Genetic Maps From KAUST Improve Personalized Medicine For Saudi And Japanese Populations

A collaborative study by King Abdullah University of Science and Technology (KAUST), Tufts University, and the Japan Institute for Health Security (JIHS) has developed pangenome graphs for Saudi and Japanese populations. This research aims to enhance precision medicine and clinical genetics for these groups, which are often underrepresented in existing pangenome databases.

Professor Malak Abedalthagafi from Tufts Medical Center highlighted the significance of this work. "Up to 12% of patients with genetic disorders go undiagnosed due to reliance on reference genomes that do not reflect their population’s genetic background. By constructing population-specific pangenome graphs, we improve variant calling and help close this diagnostic gap," she stated. Her involvement in the Saudi genome project underscores her dedication to improving genomic representation.

KAUST Professor Robert Hoehndorf, involved in the study, elaborated on the creation of JaSaPaGe (Japanese Saudi PanGenome). This initiative uses samples from distinct populations to explore differences between reference genomes and actual population genetics, providing new health insights. "Japan and Saudi Arabia are pretty much at the opposite ends of Asia and have been separated for a long time. It gave us a chance to study the effects of population-specific pangenome graphs on variant calling when populations do not match," he explained.

Yosuke Kawai from JIHS emphasized the clinical advantages this research offers both populations. "The joint development of a population-specific pangenome graph for the Japanese and Saudi Arabian populations addresses a critical gap in global genomic representation. By integrating diverse data from both countries, we have created a powerful resource that not only improves variant detection accuracy but also holds great potential for advancing precision medicine tailored to each population’s unique genetic landscape," he remarked.

This study's findings promise significant advancements in precision medicine by tailoring healthcare solutions to specific genetic backgrounds. The collaboration between these institutions highlights the importance of including diverse genetic data in global databases, potentially leading to more accurate diagnoses and treatments for underrepresented groups.

With inputs from SPA