Federico Murgia
Bioinformatician and DPhil student
Federico is a bioinformatician with longstanding experience in bioinformatics, genetics and genetic epidemiology.
He joined the Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU) in 2018, where he's involved in discovery and in-depth exploration of genomic predictors for vascular disease and its risk factors, working on a wealth of projects related CTSU's vascular mega-trials, biobanks and large studies.
He is also currently undertaking a part-time DPhil in Population Health under the supervision of Professor Jemma Hopewell with the aims to investigate the impact of rare genetic variation on statin response in the Heart Protection Study.
Federico has extensive experience in the processing of large-scale human genetic datasets, the analysis of exome/whole sequencing data, GWAS and downstream analysis to assign the SNPs to functional genomic features, development of automated pipelines and data visualisation.
After a degree in biological sciences and a postgraduate research degree in Bioinformatics applied to personalised medicine, Federico worked for several years as a biostatistician and bioinformatician for public and private organisations. He focused his research activity on the application of genetic and genomic methods to study complex traits in both general and genetically isolated populations.
Recent publications
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Independent relevance of adiposity measures to coronary heart disease risk among 0.5 million adults in UK Biobank.
Journal article
Trichia E. et al, (2023), Int J Epidemiol, 52, 1836 - 1844
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Determining the Relationship Between Blood Pressure, Kidney Function, and Chronic Kidney Disease: Insights From Genetic Epidemiology.
Journal article
Staplin N. et al, (2022), Hypertension, 79, 2671 - 2681
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Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.
Journal article
Aragam KG. et al, (2022), Nat Genet, 54, 1803 - 1815
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Are polygenic risk scores for systolic blood pressure and LDL-cholesterol associated with treatment effectiveness, and clinical outcomes among those on treatment?
Journal article
Tapela NM. et al, (2022), Eur J Prev Cardiol, 29, 925 - 937
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Assessment of the causal relevance of ECG parameters for risk of atrial fibrillation: A mendelian randomisation study.
Journal article
Gajendragadkar PR. et al, (2021), PLoS Med, 18