Aim
The BALDER project (2021-2023) aimed to develop a novel statistical software package that can help researchers identify new biomarkers and drug targets using already existing genomic data from Type 2 Diabetes Mellitus patients.
Approach
The team developed a mathematical approach called Multi-Trait Bayesian Linear Regression and implemented it into a software package. This package allows users to input genes of interest and apply various filters tailored to their needs. It assists users in interpreting existing data, revealing new connections, and identifying potential biomarkers and drug targets.
In the BALDER project, the team has taken advantage of the vast amount of genetic data from Type 2 Diabetes Mellitus patients that is already out there. These data have been used as a case study to demonstrate the usefulness of the software package. However, researchers can use the software for basically any disease of interest.
On this page, you can watch a video recorded at the beginning of the project. You can also read an article on the project's output and find lists of project participants and articles published by the BALDER team.
THE BALDER TEAM
Academic team members
- Peter Sørensen, Senior Scientist, Aarhus University
- Mads Fuglsang Kjølby, Assoc. Professor, Aarhus University
- Palle Duun Rohde, Assoc. Professor, Aalborg University
- Emily Somohardjo
- Astrid Johannesson Hjelholt
- Tahereh Gholipourshahraki
- Zhonghao Bai
- Merina Shrestha
Industrial team member
- Joanna Howson, Novo Nordisk Reseearch Center
- Sile Hu, Novo Nordisk Reseearch Center
ARTICLES FROM THE BALDER PROJECT
- Rohde PD, et al. 2021. Multi-Trait Genomic Risk Stratification for Type 2 Diabetes. Front Med (Lausanne). 8:711208. doi: https://doi.org/10.3389/fmed.2021.711208
- Rohde PD, et al. 2023. Expanded Utility of the R Package qgg with Applications Within Genomic Medicine. Bioinformatics. 39(11). doi: https://doi.org/10.1093/bioinformatics/btad656
- Bai Z, et al. 2024. Evaluation of Bayesian Linear Regression Derived Gene Set Test Methods. BMC Genomics. 25(1):1236. doi: https://doi.org/10.1186/s12864-024-11026-2
- Gholipourshahraki T, et al. 2024. Evaluation of Bayesian Linear Regression Models for Gene Set Prioritization in Complex Diseases. PLoS Genet. 20(11):e1011463. doi: https://doi.org/10.1371/journal.pgen.1011463
- Shrestha M, et al. 2025. Enhanced Genetic Fine Mapping Accuracy with Bayesian Linear Regression Models in diverse genetic architechtures. PLoS Genet. 21(7):e1011783. doi: https://doi.org/10.1371/journal.pgen.1011783
- Kunkel D, et al. 2025. Improving Polygenic Prediction From Summary Data by Learning Patterns of Effect Sharing Across Multiple Phenotypes. PLoS Genet. 21(1)e1011519. doi: https://doi.org/10.1371/journal.pgen.1011519
- Hjelholt AJ, et al. 2025. Leveraging Genetic Correlations to Prioritize Drug Groups for Repurposing in Type 2 Diabetes. Pharmacogenomics J. 25(6):33. doi: https://doi.org/10.1038/s41397-025-00392-z
PREPRINTS
Preprints are manuscripts made publicly available before peer review. They are included to support rapid dissemination of research findings and are clearly identified as preprints.
- Fourie Sørensen I, Sørensen P. 2025. Privacy-Preserving Multivariate Bayesian Regression Models for Overcoming Data Sharing Barriers in Health and Genomics. medRxiv. doi: https://doi.org/10.1101/2025.07.30.25332448
- Sørensen P, Rohde PD. 2025. A Versatile Data Repository for GWAS Summary Statistics-Based Downstream Genomic Analysis of Human Complex Traits. medRxiv. doi: https://doi.org/10.1101/2025.10.01.25337099
ABOUT ODIN
ODIN brings researchers from academia and industry together to co-create need-driven research projects that can lead to new treatments, diagnostics, tools, and technologies. We fund the strongest project ideas through competitive funding calls. Companies cannot receive ODIN funding, but participation is free of charge and gives access to academic expertise, new collaborations, and opportunities to explore early-stage research challenges.
ODIN is supported by the Novo Nordisk Foundation and the Lundbeck Foundation.
CONTACT ODIN
You are welcome to contact us if you have questions or comments. Reach out to odin@au.dk.
Although the platform spans five Danish universities, we're based in Aarhus. Our office is located at Aarhus University, Ny Munkegade 116, Bldg 1535-117.
