I lead a research group within the Division of Developmental Biology & Medicine at the University of Manchester. Currently I manage a two PDRA, two Research Assistants and a Marie Curie Fellow.

My research focus is to define the molecular links between growth, metabolism, genome, and epigenome over the full developmental age range from early embryo through placental development and childhood growth. The quantitative definition of these interactions gives insight into basic biology and provides an important background to define related clinical issues. I use the computational analysis of multi-omic data to facilitate this research aim and my research group is purely computational.

Apr 2021 - present

Lecturer in Child Health and Growth, Division of Developmental Biology and Medicine, University of Manchester.

Aug 2015 – Mar 2021

Research Fellow in Human Development, Manchester Academic Health Sciences Centre, University of Manchester.

May 2007 - July2015                                                                                            

Senior Research Associate, Manchester Academic Health Sciences Centre, University of Manchester, Visiting Scientist AstraZeneca.

Jan 2004 - April 2007                                                                                         

Senior Research Bio-scientist, Pathways Capability, AstraZeneca, Alderley Park 

Jan 2000 - Dec 2003

Research Associate, Dept. Medicine, University of Manchester

From the perspective of basic science, my ambition is to understand the fundamental relationship between growth and metabolism in the early placenta. This relationship is fluid and can fluctuate in the interaction networks that co-ordinate development but can be defined mathematically. The advent of single cell ‘omic technology has facilitated this area of study as we can now model precisely the shifts that occur in the transcriptome and epigenome during development. This means that we can assess developmental trajectories at a cellular level and measure the rate of change involved in relation to the underlying ‘omic data using techniques such as RNA Velocity. These approaches can now be combined with metabolic phenotype to measure and identify the integrated shifts in metabolism that accompany changes in growth trajectories. Currently I have a range of funding supporting this area of research using early human embryology and first trimester placenta where generate quantitative assessment of these links related to the developmental origin of health and disease.

I also work with non-standard animal models to understand the links between growth, metabolism, and the environment. With Prof. Holly Shiels in Manchester I have led work to investigate the use of Zebrafish as a model of human growth transitions (standard animal model with a non-standard application). I also lead work with shark-based models of growth where the ageing and developmental properties of our species of interest (including the Greenland Shark – longest lifespan in the animal kingdom) can be used to investigate links between the environment, development and metabolism that are difficult to assess in other animal models.

From the perspective of translational science, I work with a range of clinical specialties focussed on pediatrics, obstetrics and embryology. I have expertise in growth hormone action and its use therapeutically for short stature related conditions. I am active in research linking fetal and childhood growth involving interactions with both obstetricians and pediatricians. I also collaborate with experts in assisted reproductive therapy mapping growth trajectories in the early embryo. My personal interest in translational science is using causal multi-omic modelling as a basis to identify specific and sensitive ‘omic biomarkers for clinical use. This aspect of my research involves interaction with pharmaceutical companies with clinical trials and, more recently, SME’s to develop our research into assays with clinical utility.

In order to investigate the significance of my findings surrounding age-related gene expression changes in children I have developed approaches using network biology that allow the analysis of gene expression data in the context of models of all known human protein:protein interactions (the “Interactome”). I have also pioneered the use of multiple “–omic” datasets (metabolomic, genetic, transcriptomic) to increase confidence in observed functional associations by taking an integrated approach to data analysis. Such approaches carry great potential in understanding the effect of disease mechanism on development as well as the efficacy and safety of drugs.

BSc (hons), MSc, PhD.