| Title: | Validation and improvement of our Machine Learning approach to analyze interactions in your genotyping/imputation data for better Familial Hypercholesterolemia diagnostics |
| Lead Institution: | biotx.ai GmbH |
| Principal investigator: | Dr Marco Schmidt |
Application 36226
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About
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.2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 9392 | Exploring disease-causing traits for drug repurposing in critically ill COVID-19 patients: A causal inference approach | Hannes A. Baukmann (+9) | 2023 | iScience |
| 9218 | Targeting Longevity Gene SLC13A5: A Novel Approach to Prevent Age-Related Bone Fragility and Osteoporosis | Grit Zahn (+6) | 2023 | Metabolites |
Enabling scientific discoveries that improve human health