Section Chief’s Welcome
The Section of Genetic Medicine was created over 10 years ago to both build research infrastructure in genetics within the Department of Medicine and to focus translational efforts related to genetics. As a result, the Section of Genetic Medicine is shaping the future of precision medicine with very active and successful research programs focused on the quantitative genetics, systems biology and genomics, and bioinformatics and computational biology. The Section provides extremely valuable collaborations with investigators in the Department of Medicine who are seeking to develop new and more powerful ways to identify genetic risk factors for common, complex disorders with almost immediate clinical application.
About the Section
The Section of Genetic Medicine continues to shape the future of personalized medicine with successful research programs focused on the quantitative genetic and genomic science. The Section provides extremely valuable collaborations with investigators in the Department of Medicine who are seeking to develop new and more powerful ways to identify genetic risk factors for common, complex disorders with almost immediate clinical application.
The Section of Genetic Medicine conducts impactful investigations focused on quantitative genetics, systems biology and genomics, bioinformatics and computational biology. Some recent highlights include:
- Demonstrated that RNA splicing is a primary link between genetic variation and disease ( Li, Gilad, et al, Science , 2016)
- Demonstrated the importance of microbial signals in the development of pre- leukaemic myeloproliferation prompting new lines of investigation that may profoundly affect the prevention and management of haematopoietic malignancies (Meisel, Jabri, Barriero, et al., Nature, 2018)
- Developed a new RNA splicing approach, LeafCutter, to study sample and population variation in alternative splicing that allows for the discovery more sQTLs and improves the interpretation of disease-associated variants (Li, Pritchard, Im, et al., Nature Genetics, 2018)
- Applied the phylogenetic scan test for investigating cross-group differences in microbiome compositions using the Dirichlet-tree multinomial model (Tang, Nicolae, et al., Annals of Applied Statistics, 2018)
- Determined the genetic basis of anthracycline-cardiotoxicity by molecular response quantitative trait loci mapping in induced cardiomyocytes which could potentially lead to accurate predictions of a patient’s response to a particular chemotherapy drug to personalize their cancer treatment (Knowles, Gilad, et al., eLife, 2018)
- Developed a new method to accurately estimate the association between gene expression and DNA methylation in tumor samples (Sun, Lin, Chen, et al., Nucleic Acids Research, 2018)
- Developed methods to leverage GTEx resources and identify target genes to guide drug discovery, treatment, and prevention strategies (Barbeira, Im, Nicolae, et al., Nature Communications, 2018)