The overall aim of the Biomedical & Translational Group is to understand the interplay of biological – including genetic or epigenetic factors -, life style and environmental determinants that sustain a healthy life or lead to disease onset, and to translate this knowledge into better health promotion, disease prevention practices and improved diagnosis or therapies.
The BTR group gathers several research teams mainly contributing to the Biomedicine, Bioinformatics and Biophysics thematic strands, and cooperating with other thematic lines as new challenges arise. Each research team has been focusing on the dynamics of one or several disorders, on population health determinants and/or on therapy efficacy or adverse reactions, generating and analyzing information at multiple levels on large population datasets. The research teams are established in academic settings (e.g., Deafness group at FCUL), at the Portuguese public health institute (e.g., the Neurogenetics and Mental Health group, the Cardiovascular Disease group and the Cellular and Molecular Immunology group , all at INSA) or in a clinical research environment (the Molecular Pathology group at Hospital de Ponta Delgada).
BTR research teams gather and analyze multilevel data on large datasets of the general population or populations affected with multifactorial diseases, namely brain disorders (ASD, AD, HL and more recently language disabilities) and cardiovascular diseases (CVD) (including FH, ATH, CAD, MI, CHD and stroke).
For specific disease models, the BTR group will strategically focus on: 1) comprehensive data collection and analysis of health and disease determinants for identification of disease biomarkers, broader understanding of disease physiopathology and development of improved therapeutics ; 2) a holistic approach to research in individuals and populations, integrating multiple layers of information from socio-demographic to clinical to genomic; 3) personalized medicine, targeting the identification of factors influencing individual response to therapy, as well as the implementation of a database and biobank for pharmacogenomics.
Graça R, Alves AC, Zimon M, Pepperkok R, Bourbon M (2022) Functional profiling of LDLR variants: Important evidence for variant classification: Functional profiling of LDLR variants. Journal of Clinical Lipidology, 16(4), 516-524. doi: 10.1016/j.jacl.2022.04.005