Validation and improvement of our Machine Learning approach to analyze interactions in your genotyping/imputation data for better Familial Hypercholesterolemia diagnostics
Principal Investigator:
Dr Marco Schmidt
Approved Research ID:
36226
Approval date:
December 23rd 2019
Lay summary
biotx.ai has developed a novel genome analysis tool specifically designed for the identification of gene-gene-interactions. This may allow more insights from genetically complex diseases. We applied our method before to find genes causing Familial Hypercholesterolemia (FH). FH is a genetic disorder that leads to high blood cholesterol levels, eventually to heart attacks in young age and, from there, to a reduced life expectancy. FH is caused by not a single gene, but by several genes in a complex interaction. Our rationale with the UK Biobank data is to confirm our previous findings in a broader population. Finally, our aim is to provide a highly accurate genetic diagnostic that predicts FH patients so that existing therapy of cholesterol-lowering drugs can start earlier. Heart attacks in young age should be avoided so that patients' life expectancy can be expanded.