Chris Foley, Chief Scientist & Managing Director, and Zhana Kuncheva, Director of Health Data Science at bioXcelerate AI, were co-editors for a special issue in Frontiers “Methods in Applied Genetic Epidemiology 2022” – a field that had witnessed considerable growth in recent years.
Foley and Kuncheva, both seasoned industry experts, boast a wealth of accomplishments in their respective fields. Dr. Chris Foley specialized at the University of Cambridge in developing custom machine learning tools. These tools aim to better understand the genetic basis of diseases, particularly cardiovascular disease, and identify potential genetic drug targets. On the other hand, Dr. Zhana Kuncheva has led the implementation of genetic evidence into the target identification and validation pipelines at C4X Discovery and Silence Therapeutics with a focus on neurodegeneration and liver-related disorders.
The advancement of genetic epidemiology can be accredited to significant progress in technology and methodologies. These developments pave the way for the discovery of new therapies and personalized medication. The impact of these discoveries echoes in drug target prioritization and precision medicine, transforming the understanding of human disease biology to disrupt the disease causal pathway.
While great efforts have been put into genetic epidemiology, there’s still more to do. Research on people with diverse ancestral backgrounds can expose genetic differences in disease susceptibility, predict drug responses, and improve polygenic risk scores at a population level. On a broader scale, developing and validating treatments for genetic diseases, particularly in pinpointing targeted drugs, remains a challenge.
This special issue is part of the Frontiers’ ‘Methods in Genetics’ series, which also includes: Methods in Genomic Assay Technology 2022, Methods in Neurogenomics 2022, Methods in Evolutionary and Population Genetics 2022. The aim was to highlight the latest experimental techniques and methods used to investigate fundamental questions in genetic epidemiology research. This covered everything from genetic association studies to the applications of polygenic risk scores. Kuncheva and Foley, alongside their co-editor Dr Qi Guo from Benevolent AI, examined numerous research papers and selected four that most effectively represent the discussed topic.
The research papers aimed to cover genetic association studies. Studies based on Artificial Intelligence Tools, Precision Medicine that incorporates Genetics/Genomics Technology and AI, Rare Variants Gene-Based Methods in Whole Genome/Exome Sequencing Studies, Imputation Methods and their Application for Common and Rare Variants, Causal Inference Methods along with Novel Applications, Variant Function Annotation Strategy, and the Application of Polygenic Risk Scores for Risk Prediction in Diverse Ancestral Populations.
The topics covered in the article reflect the many attributes of genetic epidemiology research, offering a complete view of the latest advancements and future directions. Kuncheva and Foley, as editors, used their experience and knowledge to select a set of articles that contributed greatly to the progress of this field. View the full issue here.