| Title: | Polygenic risk score transportability across populations and complex traits: characterizing clinical applications of risk profiles within the context of the Genotyping Of ALL (GOALL) project |
| Lead Institution: | Erasmus MC |
| Principal investigator: | Dr Fernando Rivadeneira |
Application 67864
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About
Our research aim is to use the UK Biobank resource to: a) identify novel environmental and genetic factors affecting monogenic and common disorders; b) explore pleiotropic relationships across traits that can help characterize and/or expand current (molecular) disease definitions; c) construct, calibrate and optimize polygenic risk scores that can aid clinicians in improving healthcare of patients affected with monogenic conditions and complex chronic diseases, by stratifying risk and/or re-evaluate treatment indications. Novel genetic insights into the molecular mechanisms will provide support to clinical decision-making; in particular for disease screening, diagnosis, prognosis, and treatment. All efforts are expected to be finished in the next 36 months.5 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 8965 | Defining type 2 diabetes polygenic risk scores through colocalization and network-based clustering of metabolic trait genetic associations | Samuel Ghatan (+10) | 2024 | Genome Medicine |
| 13278 | Evaluating the relationship between glycemic control and bone fragility within the UK Biobank: observational and one-sample Mendelian randomization analyses | Samuel Ghatan (+8) | 2024 | JBMR Plus |
| 11764 | Lifestyle factors and metabolomic aging biomarkers: Meta-analysis of cross-sectional and longitudinal associations in three prospective cohorts | L.M. Kuiper (+14) | 2024 | Mechanisms of Ageing and Development |
| 15871 | Mapping variants in thyroid hormone transporter MCT8 to disease severity by genomic, phenotypic, functional, structural and deep learning integration | Stefan Groeneweg (+121) | 2025 | Nature Communications |
| 18038 | ProtFI, an efficient frailty-trained proteomics-based biomarker of aging, robustly predicts age-related decline | Swier Garst (+9) | 2026 | Cell Reports Methods |
Enabling scientific discoveries that improve human health