Dr Inga Prokopenko, MSc, PhD, trained in Biology and Chemistry, Kiev, Ukraine, and subsequently in Molecular Genetics and Genetic Epidemiology at the University of Pavia, Italy. She continued studies for her PhD in Pharmacoepidemiology and Pharmacoeconomy at the University of Pavia. After a two-year R&D experience within Psychiatry Translational Medicine & Genetics at GlaxoSmithKline, Verona, Italy, she undertook a postdoctoral training at the Wellcome Trust Centre for Human Genetics, University of Oxford, UK, before being appointed in 2013 as Senior Lecturer in Human Genomics at Imperial College London. Since then she set up her group focusing on the development of approaches for the analysis of high-dimensional multi-omics data. She expanded her major applied research interest in the genetics of type 2 diabetes, glycaemic and early growth traits to dissection of the longitudinal multi-omics effects for improved profiling, prevention and progression tracking of diabetes and its major comorbidities.
Group leader within the the Section of Genomics of Complex Disease.
Rising Star award holder from the European Association for the Study of Diabetes, 2011.
Board Member, European Society of Human Genetics (ESHG), 2014-2019.
Educational Committee member, European Society of Human Genetics (ESHG), since 2017.
Section Editor, Statistical Genetics, European Journal of Human Genetics (EJHG), since 2014.
Steering Committee member, MAGIC (Meta-Analysis of Glucose and Insulin-related traits Consortium)
Highly cited researcher in the category “Molecular Biology & Genetics”, 2014-currently.
Key Research Interests:
Large-scale high-dimensional multi-omics data analysis approaches.
Genomics of human complex diseases and their comorbidities.
Relationships between disease and its endophenotypes.
Pleiotropic effects and mediation.
et al., 2017, An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans, Diabetes, Vol:66, ISSN:0012-1797, Pages:2888-2902
et al., 2017, MARV: a tool for genome-wide multi-phenotype analysis of rare variants, BMC Bioinformatics, Vol:18, ISSN:1471-2105
et al., 2017, SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes, BMC Bioinformatics, Vol:18, ISSN:1471-2105
et al., 2016, The genetic architecture of type 2 diabetes, Nature, Vol:536, ISSN:0028-0836, Pages:41-+
et al., 2016, Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research, European Journal of Human Genetics, Vol:24, ISSN:1018-4813, Pages:521-528
et al., 2015, Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation, PLOS Genetics, Vol:11, ISSN:1553-7390
et al., 2015, The impact of low-frequency and rare variants on lipid levels, Nature Genetics, Vol:47, ISSN:1061-4036, Pages:589-597
et al., 2015, Age- and Sex-Specific Causal Effects of Adiposity on Cardiovascular Risk Factors, Diabetes, Vol:64, ISSN:0012-1797, Pages:1841-1852
et al., 2015, Adiposity as a cause of cardiovascular disease: a Mendelian randomization study, International Journal of Epidemiology, Vol:44, ISSN:0300-5771, Pages:578-586
Marullo L, Moustafa JSE-S, Prokopenko I, 2014, Insights into the Genetic Susceptibility to Type 2 Diabetes from Genome-Wide Association Studies of Glycaemic Traits, Current Diabetes Reports, Vol:14, ISSN:1534-4827
et al., 2014, Pleiotropic genes for metabolic syndrome and inflammation, Molecular Genetics and Metabolism, Vol:112, ISSN:1096-7192, Pages:317-338
et al., 2014, A Central Role for GRB10 in Regulation of Islet Function in Man, Plos Genetics, Vol:10, ISSN:1553-7404