Table 3.
Direction | Knowledge gaps | Suggested studies |
---|---|---|
Genetic mapping of AF | Total number of genetic variants | •GWAS: Larger, non-European ancestry groups, more specific AF phenotypes •Whole-exome and -genome sequencing |
Biology of AF | • Expand eQTL studies • Network analyses • In vivo and in vitro experiments • Gene–gene interaction • Epigenetics • Transcriptomics • Proteomics • Metabolomics |
|
Heterogeneity of AF | • Discover new AF clinical risk factors • Validate AF risk models • Genetic classification of AF phenotypes • Investigate gene–environment interaction • PheWAS • Mendelian randomization studies of AF risk factors |
|
AF prediction | Polygenic risk scores | • Improve genetic risk scores for AF, AF subtypes, and AF-related phenotypes |
Therapeutic development | Treatment response | • Improve genetic risk scores for AF treatment • Increase cohorts with both genetics and treatment response data • Investigate the underlying biological mechanisms of genetic variants to identify new drug targets |
Patient specific management | Individual concerns | • Focus on individualized risk assessment • How to relate to AF genetics and the ethical concept and resulting patient behavior |
Societal concerns | • Cost-effective consequences |