Abstract

Initial expectations for genome-wide association studies were high, as such studies promised to rapidly transform personalized medicine with individualized disease risk predictions, prevention strategies and treatments. Early findings, however, revealed a more complex genetic architecture than was anticipated for most common diseases - complexity that seemed to limit the immediate utility of these findings. As a result, the practice of utilizing the DNA of an individual to predict disease has been judged to provide little to no useful information. Nevertheless, recent efforts have begun to demonstrate the utility of polygenic risk profiling to identify groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to disease. In this context, we review the evidence supporting the personal and clinical utility of polygenic risk profiling.

Keywords

Genetic architecturePersonalized medicineDiseaseBiologyProfiling (computer programming)Polygenic risk scoreGenome-wide association studyMultifactorial InheritancePersonal genomicsProbabilistic logicPrecision medicineGenetic associationComputational biologyBioinformaticsGeneticsGenomicsGenomeQuantitative trait locusComputer scienceArtificial intelligenceMedicineSingle-nucleotide polymorphismGeneGenotypePathology

MeSH Terms

Genetic Predisposition to DiseaseGenetic TestingGenome-Wide Association StudyHumansMultifactorial InheritancePrecision MedicineRisk Factors

Affiliated Institutions

Related Publications

Publication Info

Year
2018
Type
review
Volume
19
Issue
9
Pages
581-590
Citations
1580
Access
Closed

External Links

Download PDF (Free) View on DOI.org PubMed Semantic Scholar

Social Impact

Altmetric
PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

1580
OpenAlex
46
Influential

Cite This

Ali Torkamani, Nathan E. Wineinger, Eric J. Topol (2018). The personal and clinical utility of polygenic risk scores. Nature Reviews Genetics , 19 (9) , 581-590. https://doi.org/10.1038/s41576-018-0018-x

Identifiers

DOI
10.1038/s41576-018-0018-x
PMID
29789686

Data Quality

Data completeness: 86%