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 institute, and a genome browser of UK10K association results.
Nicole is the team leader. Nicole was trained in quantitative population and statistical genetics at the University of Milano, University of Dundee and University College London, where she applied genetic analysis to evolutionary studies of natural populations and human traits. She spent two years in the pharmaceutical industry in the US, applying human genetics to improve drug discovery and pharmacogenomics. She returned to the UK at the Sanger Institute, where she started her group in 2009. In 2013 she became adjunct faculty at the University of Cambridge School of Clinical Medicine, and in 2015 was awarded a personal chair in Human Genetics at the University of Cambridge School of Clinical Medicine in October 2015.
The hematopoietic system provides a good model system to inform interpretation of association studies owing to simple phenotypes at the cellular level; nearly unlimited access to suitable tissue with good ability for in vitro manipulation; suitable model organisms; widespread clinical relevance. We use genetic approaches to identify novel genes and gene variants affecting the development in humans.
We use large-scale explorations of genetic influences on high-dimensional metabolomic profiles to define the in vivo blueprint and connectivity of human metabolism. Exploration of these findings in the context of human disease genetics provides insights into the role of inherited variation in blood metabolic diversity and identify potential new opportunities for drug development and for understanding disease.
Show Previous Key Projects, Collaborations, Tools & Data
We have recently completed the first pass analysis of the UK10K project, a multi-cohort, multi-investigator study funded through a Wellcome Trust strategic award. In the Cohorts arm of the project, we analysed the contribution of low frequency and rare genetic variants to over 50 different cardiometabolic traits using low-read depth whole-genome sequencing. Through this effort we discovered several low frequency variants associated with a host of complex traits.
Programmes, Associate Research Programmes and Facilities
The Health Data Research (HDR) UK Cambridge site is part of the national institute for health data science (HDR UK) and comprises the Wellcome Sanger Institute, EMBL-EBI, the University of Cambridge and its hospitals. HDR UK Cambridge aims to advance understanding of disease prediction, causation, and progression through the integration of molecular data and other intermediate phenotypes with routine clinical data.
The Human Genetics Programme is driving a step-change in our understanding of genetic causes and biological mechanisms of disease susceptibility and progression, focusing on developmental disorders and diseases of the blood and immune system. We integrate population-scale genetics, longitudinal clinical data, and large-scale genetic perturbation studies in cellular model systems. We aim to transform the clinical utility of human genetic variation.
DNA sequence remains at the heart of molecular biology and bioinformatics. The Birney Associate Faculty Research Group at the Sanger Institute focuses on developing sequence algorithms and using genetic variation to explore elements of basic biology within and between species
In collaboration with our colleagues in Cellular Operations and Stem Cell Informatics, our work focuses on supporting and delivering the gene editing requirements of the Institute's faculty and research programmes. Through the adoption and implementation of modern genome editing techniques, we tailor our technical experience to help answer biological questions. We optimise, develop and democratise the delivery of genome editing tools and platforms for the Institute’s research programmes. For our collaborating partners we provide an agile, project focused, cost effective and efficient service as well as develop and provide biological resources, technical support and training for research groups and their staff.
Human Genetics Informatics (HGI) supports the scientific aims of the Human Genetics programme by developing and operating computational analysis workflows, managing shared storage, and providing bioinformatics software tools for the use of researchers across all Human Genetics faculty groups.
As an extension to 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 characterize the role of human variation on the epigenomic landscape.
This Epigenesys-funded project aims to apply system genetic approaches based on Bayesian networks to model regulatory pathways between genetic variants and molecular phenotypes measured in blood cells. Specifically, the project will seek to characterize genetic variants regulating the processes of differentiation, proliferation and fate determination in the human haematopoietic system. Such analyses will be based on novel genomic, transcriptomic and epigenetic datasets generated for all mature blood cell types and their precursors by the EU-funded BLUEPRINT project. Furthermore, through collaboration with Dr Cedric Ghevaert and Dr Ludovic Vallier at the University of Cambridge, we will seek to extend analyses to select blood cells derived from human induced pluripotent stem cells. Dr Louella Vasquez (PhD Physics, WTSI Postdoctoral Fellow) is responsible for the statistical analyses and development of new modeling approaches.
We are extending the previous metabolomics genetics approaches to drug development applications with different aims. The first is looking at other associations to the same metabolite as potential additional loci involved in the disease process. The second is understanding of potential causal pathways involving these metabolites. The third is the development of metabolite measurements as useful biomarkers / alternative end points.
We are part on the newly launched NIHR Blood and Transplant Research Unit in Donor Health and Genomics, where we coordinate theme 1 - 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”.