Complex Disease and Quantitative Genetics
The core aim of our research activities is to increase our understanding of the genetic basis of common complex diseases and develop new and innovative strategies for their prevention, prognosis and treatment. Research activities of this group encompass the identification of novel susceptibility genes, assessing how our genetic make-up and environment shape gene regulation through epigenetic mechanisms, developing statistical and analytical strategies for dealing with the ever increasing complexities of genomic data and assimilating this knowledge into the development and evaluation of new treatments in the clinic and improvements in the quality of advice we can give to patients.
Group members work on a diverse range of common diseases including cancer, mitochondrial disorders, Crohn's disease and ulcerative colitis, kidney disease, cardiovascular disease, obesity and type 2 diabetes. Our research utilises the world class laboratory facilities within the IHG and applies a spectrum of molecular genetics techniques coupled with advanced bioinformatic and biostatistical capability. The group adopts
many approaches ranging from conventional genetics (family-based and population-based studies) through to transcriptomic and epigenomic applications.
Key researchers:
Professor John Burn - Aspects of Clinical Genetics: Heart Malformation, Cancer Prevention and Neurodegeneration
Professor Heather Cordell - Development of statistical methodology for detection and characterisation of genetic factors in complex disease
Dr Mike Jackson - Genome Instability and the Genetics of Neuroblastoma
Professor Tim Goodship - Genetics of Atypical Haemolytic Uraemic
Professor Bernard Keavney - Finding genes that cause heart and circulatory disease
Dr. John Mansfield – Crohn’s disease and ulcerative colitis
Professor Simon Pearce - Autoimmune endocrine disease and subclinical hyperthyroidism
Dr Caroline Relton - Epigenetic variation in common complex disease
Dr Mauro Santibanez-Koref - Using allelic expression differences to ascertain cis-acting functional polymorphisms
Dr Ian Wilson - Development of Statistical Methods for Population Genomic Data
