Dr Mark Iles
- Position: Associate Professor
- Areas of expertise: Statistics; Epidemiology; Genetics; Melanoma
- Email: M.M.Iles@leeds.ac.uk
- Phone: +44(0)113 206 6607
- Location: LIDA, level 11 Worsley Building
I design and analyse population-based genetic epidemiology studies and research the theoretical statistics and methodology underlying them. I am currently working on a variety of applied medical genetic studies as well as carrying out methodological research related to genetic epidemiology.
After a degree in Mathematics from Bristol University, I studied for a Masters in Biometry at Reading University, where I was first introduced to the field of statistical genetics, including a project modelling the evolution of repeated sequences of DNA supervised by Robert Curnow and John Whittaker. I studied for my PhD with Tim Bishop at the University of Leeds on “Using Population Structure to Locate Low Penetrance Disease Genes”. After this, I worked as a lecturer at the University of Sheffield for several years in Chris Cannings’ group, where I co-organised the MSc in Genetic Epidemiology and supervised a number of Masters students’ projects in addition to continuing my own research. Subsequent to this I worked at the Karolinska Institute in Stockholm in the Department of Medical Epidemiology and Biostatistics during which time I was awarded the International Genetic Epidemiology Society’s James V Neel Young Investigator Award.
I am Programme lead for the Msc in Precision Medicine: Genomics and analytics, recently awarded funding for three years by HDRUK. I co-organise and teach on the RESS3 course for third-year undergraduate medical students. I lead the Introduction to Genetic Epidemiology MSc module. I am the Medical School representative on the Advanced Research Computing Management Committee, and a member of the course management teams for RESS2 and ESREP. Other non-epidemiological research has included a theoretical study into the evolution of recombination rates and how this is affected by population size and degree of selection.
2004-2005: Senior Scientist, Karolinska Institutet, Stockholm
1999-2004: Lecturer, University of Sheffield
1996-2000: PhD, Imperial Cancer Research Fund, University of Leeds Thesis title: Using Population Structure to Locate Low Penetrance Disease Genes Supervisor: Prof Tim Bishop
1995-1996: MSc in Biometry, Department of Applied Statistics, University of Reading Supervisors: Prof Robert Curnow, Prof Richard Sibley, Dr John Whittaker
1992-1995: BSc in Mathematics, University of Bristol
Ernest Mangantig, successful viva March 2017, co-supervisors Mark Iles and Tim Bishop. Thesis title: The effect of patient and tumour genetics on survival from melanoma
Adam Trower, sucessful viva April 2021, supervised by Tim Bishop (main supervisor), Mark Iles and Julia Newton Bishop. Thesis title: Using big data and statistics to understand melanoma skin cancer
Theofanis Tsismentzoglou, started 2017, co-supervised with Eamonn Sheridan.
John Taylor, started 2018, co-supervised with Phil Quirke, Dermot Burke and Eva Morris
Harriett Fuller, started 2018, co-supervised with Michael Zulyniak and Bernadette Mooret
Natalie Chaddock, started 2018, co-supervised with Ann Morgan and Jenny Barrett
Michal Zulcinski, started 2018, co-supervised with Ann Morgan and Jenny Barrett
Statistics, genetics, epidemiology
- Programme manager for MSc Precision Medicine: Genomics and Analytics
- Co-lead of RESS3 module
- Lead fo the Introduction to Genetic Epidemiology module
My current applied research includes the analysis of a large, multi-national genome-wide association study (GWAS) of melanoma, as part of the GenoMEL consortium (for which I am on the Analysis Group), and I am involved in the meta-analysis of several melanoma GWAS as well as fine mapping previously-identified regions and sequencing these genes in several thousand samples. My particular areas of interest regarding melanoma include the use of genetic predictors of related phenotypes (polygenic risk scores for pigemntation, naevus count and telomere length) to improve prediction and understanding of melanoma risk.
I am currently involved in genetic studies of Giant Cell Artiritis, using both germline and gene expression data, and of gestational diabetes, looking at the impact of genetic predictors of metabolites and how this varies by ethnicity. In addition, I have previously worked on cardiovascular disease (as part of the Wellcome Trust Case Control Consortium), breast cancer, bowel cancer, testis cancer and rheumatoid arthritis, amongst others.
I also work on the Born in Bradford cohort, a large multi-ethnic cohort of mothers and children.
My theoretical research interests are in the area of genetic association analysis, with a particular interest in population genetics considerations and the design of population-based genetic studies (GWAS, fine mapping and the analysis of sequence data). I have worked on a variety of statistical genetics-related problems such as the effect of incomplete LD on the apparent mode of inheritance of a disease, estimating the efficacy of tag SNPs, sequential genotyping of nuclear families and extensions to the TDT (as did seemingly every other genetic epidemiologist in the late 90s).
Research groups and institutes
- Leeds Institute of Medical Research at St James's
- Rare Diseases & Genetics
- Pathology and Data Analytics