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Professor Panos (Panagiotis) Deloukas

Panos (Panagiotis)

Director of the WHRI and Professor of Cardiovascular Genomics

Centre: Clinical Pharmacology and Precision Medicine

Email: p.deloukas@qmul.ac.uk
Telephone: +44(0) 20 7882 2103; +44 207 882 7098 (Jo Odetola - PA to Prof Panos Deloukas)

Profile

ORCID iD: 0000-0001-9251-070X

Panos Deloukas obtained his BSc in Chemistry from the Aristotelian University of Thessaloniki, Greece and MSc in Microbiology from University Paris 7, France. He received his PhD from the Biozentrum University of Basel, Switzerland in 1991. He joined the Sanger Centre in 1994 where he set up a high-throughput pipeline for radiation hybrid mapping, leading an effort to map 30,000 gene markers, GeneMap98. Panos was an active member of the Human Genome Project coordinating the sequencing and analysis of chromosomes 10 and 20. After the completion of the HGP he joined the International HapMap project constructing SNP maps of the human genome. Since 2005 he is studying the molecular basis of common disease and variable response to drugs in humans through large-scale genetic studies. He joined the William Harvey Research Institute at Queen Mary University London in September 2013 working on the genomics of coronary artery disease and lipid levels. Panos is a member of many consortia including CARDIoGRAMplusC4D, Global Lipids Genetics Consortium, GIANT, the UK Biobank Cardiometabolic Consortium, and the Cardiovascular Genomics England Clinical Interpretation Partnership. He has authored over 400 publications (H-index 121) and is listed by Thomson Reuters among the 1% highly cited researchers in Molecular Biology & Genetics since 2012.

Memberships and awards

  • Executive member of the CARDIoGRAMplusC4D consortium
  • Member of the Steering Committee of the GIANT consortium
  • Member of the Steering Committee and Co-chair of the lipids working group of  the UK CardioMetabolic Consortium
  • Member of the Cardiovascular GeCIP and lead of the functional subgroup since 2015

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  • Highly Cited Researchers - top 200 influential scientists  in Molecular Biology & Genetics for the period 2002-2012
  • Highly Cited Researchers 2014, 2015 and 2016 (top 1%  in Molecular Biology & Genetics)

Research

Group members

Dr Stavroula Kanoni (Statistical Geneticist); Dr Andrew Smith (BHF Research Fellow); Dr Stephane Bourgeois (Lab Manager and Analyst); Dr Ioanna Ntalla (Post-doctoral fellow, genetic analyses); Dr Eirini Marouli (Post-doctoral fellow, genetic  analyses); Mrs Kawah Li (Technical Assistant); Ms Olga Giannakopoulou (BHF PhD student)

Summary 

Our group investigates the molecular basis of complex traits in humans focusing on coronary heart disease (CHD) and related cardiometabolic traits. 

CHD and its main complication, myocardial infarction (MI), is the leading cause of death worldwide. Through large scale trans-ethnic genetic studies we have identified thus far 70 loci robustly associated with CHD /MI risk and are currently undertaking further analyses in UK Biobank including gene-gene and gene-environment interactions. In parallel, we are investigating the genetic architecture of CHD risk factors such as lipid levels, blood pressure, haematological traits, and height through QTL analyses in large, well-phenotyped cohorts. To identify the functional variants underlying CHD risk we are integrating genetic findings with gene expression and DNA methylation QTL maps as well as open chromatin maps in relevant cell types.

Though age-standardized death rates from CHD are falling, the ageing of the population and the absence of effective therapeutic interventions/cures indicate that the burden of CHD will continue to increase. Among patients surviving a first MI event, circa 17% will experience a second event within 18 months. However, after five years the risk of an MI event is the same between MI patients and the general population. To identify biomarkers that will allow us to improve the stratification of MI patients for recurrent events we are assessing gene expression and DNA methylation in the blood. We hypothesise that such biomarkers may capture relevant environmental factors which in concert with genetic factors underscore bad prognosis. The ultimate goal is to develop a risk model for recurrent MI and test its clinical utility.

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