Dragana Vuckovic

I am currently a Lecturer in Computational Epidemiology and Biostatistics at Faculty of Medicine at Imperial College. I am passionate about analytical, data-driven approaches to solve problems in healthcare.

My background is in Mathematics, for which I gained a BSc (University of Torino, Italy) and an MSc (University of Trieste, Italy) with a thesis on partial differential equations. After completing my formal education, I sought for opportunities to work on applied computational projects and opted for a PhD in Statistical Genomics (University of Trieste, Italy). Ever since, genetics, and healthcare in a broader sense, have become a passion.

During my PhD I worked on a variety of aspects of congenital and age-related hearing loss, including epidemiological studies to dissect relevant covariates and genetic association studies to identify the genes involved, such as genome-wide association studies (GWAS) and sequencing data analysis. After completing my PhD I relocated to the Sidra Hospital in Qatar to work on understanding how a consanguineous population can increase discovery power for genetic associations.

In 2017, I was appointed as lead analyst for the NIHR Blood & Transplant Research Unit (NIHR BTRU) in Population Health and Genomics, and specifically the Genetics Theme, working jointly with the Sanger Institute and the University of Cambridge. In this role, I expanded my technical knowledge working with extremely large datasets (more than half a million participants and thousands of variables) and gained experience in research management, by leading an international consortium (Blood Cell Consortium) and by supervising younger researchers. Leveraging this experience and project, I have developed a new research proposal focusing on fundamental aspects of the application of polygenic scores to health outcomes, for instances considering the interplay of polygenic and somatic variation with environmental exposures in the ageing process. Furthermore, I am interested in exploring innovative methods, e.g. machine-learning algorithms, to represent complex interactions between different OMICS datasets.

Selected Publications

Journal Articles

• Chen M-H, Raffield LM, Mousas A, et al., 2020, Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations, Cell, Vol:182, ISSN:0092-8674, Pages:1198-1213.E14
• Vuckovic D, Bao EL, Akbari P, et al., 2020, The polygenic and monogenic basis of blood traits and diseases, Cell, Vol:182, ISSN:0092-8674, Pages:1214-1231.e11
• Nagtegaal AP, Broer L, Zilhao NR, et al., 2019, Genome-wide association meta-analysis identifies five novel loci for age-related hearing impairment., Sci Rep, Vol:9

Affiliations

• Epidemiology and Biostatistics

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