| Title: | Influences of rare non-protein-coding genetic variants across the phenome |
| Lead Institution: | Sinai Health System. |
| Principal investigator: |
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About
A major goal of human genetics research is to learn which genetic variants (variants for short; colloquially "mutations") increase the risk of which diseases. This problem is typically approached by measuring the genomes of large numbers of people, and finding variants that have higher frequencies in disease cases than in controls without the disease, after accounting for factors like age, sex and ancestry. However, most genetic studies have focused on the small percent of variants that are present in at least ~1% of the population. Why? First, because it is easier to measure a limited number of variants than to measure a whole genome. Second, because you need to recruit fewer people to find robust statistical evidence that a common variant increases the risk of a disease, compared to a rare variant. Recognizing that overlooking almost all of the variants in the genome is a substantial research gap, the UK Biobank, one of the world's largest biomedical databases, is conducting whole-genome sequencing on all of its 500,000 British participants, with the results expected to be released in late 2023. This dataset will be by far the largest whole-genome sequencing dataset in the world. We propose to harness this world-leading dataset to find rare variants that are linked to each of the several thousand health outcomes measured by the UK Biobank. We will develop statistical methods to group together nearby variants in smart ways, to increase our chances of finding robust links with disease. We will also look for variants that affect multiple health outcomes at once, in the hope that these variants may shed light on shared genetic pathways across diseases and point to opportunities to use new drugs for multiple diseases, or to use existing drugs for a different disease than usual ("drug repurposing"). We will make all these results available to the biomedical research community.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 21269 | The genetic architecture of fibromyalgia across 2.5 million individuals | Isabel Kerrebijn (+52) | 2026 | Nature Medicine |
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