Professor of Human Genetics

Email: ns545@cam.ac.uk
Home page: http://www.sanger.ac.uk/people/directory/soranzo-nicole
Description of research
Our research focuses on the application of large-scale genomic analysis to unravel the spectrum of human genetic variation associated with cardiometabolic diseases, and its interaction with non-genetic and environmental cues. Common, complex conditions such as cardiovascular, inflammatory and immune diseases can be considered as extremes of a broad spectrum of phenotypic variation that is also seen in healthy individuals. Our group is interested in understanding how genetic factors interact with other non-genetic and so-called epigenetic factors to determine such phenotypic variation. To achieve this, we use large-scale genome scans including genome sequencing data, epigenetic profiling and molecular traits such as gene expression and metabolomics. We strongly believe in the value of data sharing. We have generated rich genomic datasets for the scientific community, including an expansive atlas of genetic associations with metabolites, whole-genome sequence and phenotype data for population cohorts in the UK10K project, as well as bioinformatic resources to facilitate the retrieval of information, including a metabolite network, a database of genotype-metabolite associations with our colleagues at the Helmholtz Centre, and a genome browser of UK10K association results.
Genetic and epigenetic determinants of haematopoiesis
We use genetic association scans based on SNP arrays and whole-genome sequencing to identify novel genes and gene variants affecting hematological indices in humans. We are part of the HaemGen consortium, a worldwide effort to discover genetic determinants of blood cell formation and to drive downstream interpretation of sequence variation through a host of integrative analyses and functional approaches. To date, this effort has identified >150 novel loci associated with white and red blood cell and platelet formation (eg, Nat Genet 2009;41:1191, Nature 2011;480:201, Nature 2012;492:369). Further work has validated novel regulators of haematopoiesis in humans and model organisms (Blood 2011;118:4967), and mapped functional consequences of sequence variants in cell systems (e.g. PLoS Genet 2011;7:e1002139).
BLUEPRINT http://www.blueprint-epigenome.eu
As an extension to our genetics projects, we now aim to identify and characterize in greater depth genes implicated in hematopoietic development in the EU FP7-funded BLUEPRINT project, which will generate reference genomes and epigenomes of at least 100 specific blood cell types. Our group coordinates the EpiVar package of the BLUEPRINT project, which is generating genomic (through whole-genome sequencing) and epigenetic characterization of three main immune cell types in 200 individuals, with the aim to characterize the role of human variation on the epigenomic landscape.
NIHR BTRU in Donor Health and Genomics http://donorhealth-btru.nihr.ac.uk/index.html
We are part of the NIHR Blood and Transplant Research Unit in Donor Health and Genomics, where we coordinate a research theme on Determinants of donation-related biomarkers. This theme will address the NIHR BTRU mandate to identify and characterise “genetic, biochemical, lifestyle and other determinants of relevant blood cell traits, and measures of iron homeostasis, including determinants of the trajectories of these factors over time among donors”. The rationale is that such information is needed to understand molecular and health consequences of repeated donation. Through analysis of the INTERVAL Trial data, serial follow-up of donors and mechanistic studies, Theme 1 will help identify people who can give blood more (or less) frequently than is typical, feeding into Themes 2-3 by identifying “genomic and other factors associated with capacity to give blood”, informing “evidence-based strategies to prevent deferral”.
Research focus
Keywords: Cardiometabolic traits, metabolomic genetics, haematopoiesis
Clinical conditions: Coronary artery disease, myocardial infarction
Methodologies: Genetic association analyses, metabolomic phenotyping