Professor David Evans found the notion that one might be able to use mathematics and statistics to answer fundamental questions about the causes of common diseases like osteoporosis completely fascinating. 

“I’ve always been interested in how things work, and the area of statistical genetics provided the perfect forum for that passion. First you need to understand how the mathematics underlying the method works. Then you apply the maths to the biology, and this in turn provides clues on how the disease arises,” says Evans.

Professor Evans completed his undergraduate degree and PhD at The University of Queensland and the Queensland Institute of Medical Research (QIMR). He came into statistical genetics quite by accident. The difficulty he had experienced previously was that he enjoyed learning about biology, but didn’t like working in wet labs. Up until that time, Evans says he had no idea that the face of medical research was undergoing a revolution, and that there were amazing new areas of medical science opening up in the area of statistics and genetics, and these areas were available to those with an aptitude for maths and computing. Evans was astounded at the cutting edge research that could be performed without ever having to step into a wet lab again.

Completing his post-doctoral fellowship at the Wellcome Trust Centre for Human Genetics (WTCHG) at the University of Oxford from 2003 until July 2007, Professor Evans says that working at one of the world’s premier scientific institutions was an amazing experience. Evans worked on the International HapMap Project (a map of the human genome that facilitates the genetic mapping of diseases) and then the Wellcome Trust Case Control Consortium (WTCCC); one of the first large scale genetic studies to look across the genome for disease genes.

“It was amazing to be involved in the Wellcome Trust Case Control Study, as it was one of the first to conclusively show that it was possible to identify individual genes that affected risk of common diseases like diabetes and heart disease using statistical genetics approaches,” he says.

“I was also lucky enough to work on a number of projects relating to the development of statistical genetics methodologies, meaning that I could contribute to the identification of disease genes by providing methods that other researchers could use in their own studies.”

In 2007, Evans moved to the University of Bristol to take up a Senior Lecturer and then Reader position. His main task in Bristol was to lead genetic studies within the Avon Longitudinal Study of Parents and Children (ALSPAC) - a local population based cohort of 10,000 mothers and children that has since become one of the world’s leading cohorts for genetics research. Since this time, ALSPAC has contributed to over forty large scale genetic studies spanning a diverse range of medically relevant traits and diseases, including osteoporosis and eczema, and has helped identify hundreds of genes that predispose to disease in the process. Evans remains heavily involved in this research and is hoping to find PhD students who are interested in pursuing closer links between Australia and the UK.

His research focuses on dissecting the genetic aetiology of complex traits and diseases by genome-wide association and next generation sequencing approaches, with a particular interest in osteoporosis, ankylosing spondylitis and eczema, but Evans also performs genetic studies across a wide variety of other complex traits and diseases and is active in the development and refinement of statistical genetics methodologies.

“It’s wonderful to discover things that nobody else has before. It’s also exciting to think that some of your discoveries may make a difference to peoples’ lives,” says Evans.

Research projects

Genetic mapping of common complex diseases and traits

  • Osteoporosis
  • Ankylosing spondylitis
  • Atopic dermatitis (eczema)
  • Craniofacial size and shape
  • Genetics, genomics and cytokines in septic shock patients
  • Genetics of antibody response

Statistical genetics

  • Genetic architecture of complex traits and diseases
  • Epistasis and genetic non-additivity

Statistical methodology

  • Causal modelling and mendelian randomization
  • Structural equation modelling


  • Methylation and its relationship to complex traits and diseases


  • Using genetic variants to understand causal relationships between environmental exposures and disease