Understanding polygenic models, their development and the potential application of polygenic scores in healthcare
Chantal Babb de Villiers, Mark Kroese, Sowmiya Moorthie
Abstract
The use of genomic information to better understand and prevent common complex diseases has been an ongoing goal of genetic research. Over the past few years, research in this area has proliferated with several proposed methods of generating polygenic scores. This has been driven by the availability of larger data sets, primarily from genome-wide association studies and concomitant developments in statistical methodologies. Here we provide an overview of the methodological aspects of polygenic model construction. In addition, we consider the state of the field and implications for potential applications of polygenic scores for risk estimation within healthcare.
Topics & Concepts
Polygenic risk scoreData scienceGenome-wide association studyComputer scienceField (mathematics)Multifactorial InheritanceHealth careEstimationGenetic associationComputational biologyBiologyData miningGeneticsMathematicsGenotypeEngineeringSingle-nucleotide polymorphismGenePure mathematicsEconomicsSystems engineeringEconomic growthGenetic Associations and EpidemiologyLiver Disease Diagnosis and TreatmentAdvanced Causal Inference Techniques