Abstract:
PURPOSE:Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers. MATERIALS AND METHODS:We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD) in the Atherosclerosis Risk in Communities (ARIC) cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration. RESULTS:The addition of a GRS to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC. RESULTS are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor single nucleotide polymorphisms (SNPs) are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider. CONCLUSION:The proposed method facilitates the standardized incorporation of a GRS in risk assessment.
journal_name
Front Genetjournal_title
Frontiers in geneticsauthors
Goldstein BA,Knowles JW,Salfati E,Ioannidis JP,Assimes TLdoi
10.3389/fgene.2014.00254subject
Has Abstractpub_date
2014-08-01 00:00:00pages
254issn
1664-8021journal_volume
5pub_type
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