PT  - JOURNAL ARTICLE
AU  - Adam Kowalczyk
TI  - Predictive and Aetiological Potential of Polygenic Strata with Extreme and Moderate Disease Risks Predictions: <em>Case Study of Coeliac Disease GWAS</em>
AID  - 10.1101/687889
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 687889
4099  - http://biorxiv.org/content/early/2019/07/02/687889.short
4100  - http://biorxiv.org/content/early/2019/07/02/687889.full
AB  - We show by using example of coeliac disease (CD) that a genomic risk assessment could significantly improve efficiency of disease diagnosing. It can detect novel highly deleterious rare variants (penetrance 100%, frequency ∼1:6,700) as well as common protective variants (penetrance 0.03%, frequency ∼1:3). However, the major translational gains with potential for multi-billion-dollar cost savings in Australia or USA alone, could be in assessing patients in cohorts with moderately elevated CD risk (3% −10%) exhibiting clinical symptoms or with family history of CD. The gains result from judicious re-direction of expensive confirmatory testing towards ∼30% of the cohort with the highest likelihood of the condition (∼90% of cohort CD cases), while avoiding costs, inconvenience and risk of side-complications for the remaining majority of ∼70%.We build our estimates using concrete results of CD Genome Wide Association Studies (GWAS) already in the public domain1–4. The largest of five Genomic Risk Score (GRS) models1 considered here deploys 228 directly genotyped Simple Nucleotide Polymorphisms (SNPs), while the simplest2 uses only 6 SNPs. Thus, a DNA profile supporting all these models can be easily accommodated on any commodity, Direct-to-Consumer5 (DTC), saliva-based genotyping platform. Once generated, such a generic profile of over 600,000 SNPs could assist medical practitioners in diagnosing this as well as thousands of other diseases on demand, virtually genotyping cost free.