The work of Professor Peter Visscher, a quantitative geneticist, focuses on better understanding genetic variation for complex traits, including quantitative traits and diseases. He has developed and applied statistical analysis methods to quantify and dissect the contributions of DNA polymorphisms to inter-individual variation, and has shown the pervasiveness of the polygenic and pleiotropic aspect of quantitative traits and disease risk.
is research began in livestock genetics, but now has fundamental applications in medicine and evolutionary biology.
Originally from the Netherlands, Peter Visscher specialised in quantitative genetics at the University of Edinburgh, where he did his Master's degree and then his thesis under the supervision of William Hill FRS. His thesis, devoted to the estimation of genetic parameters in dairy cattle, was followed by post-doctoral studies in Melbourne and then Edinburgh, where he was interested in methods for mapping the loci involved in complex traits.
After initially working at the University of Edinburgh, where he developed mapping methods and related software with applications in human and animal genetics, he worked at the Queensland Institute of Medical Research in 2005, and was then appointed Professor of Quantitative Genetics at the University of Queensland in Brisbane, Australia, in 2011.
He is a Laureate Fellow of the Australia Research Council, a Fellow of the Australian Academy of Science since 2010, was elected a Fellow of the Royal Society in the United Kingdom in 2018 and also elected a Foreign Member of the Royal Netherlands Academy of Arts and Sciences in that year.
His work has had a profound impact on research in his field, as evidenced by his h-index (123) and the number of citations (over 86,000 in total, and more than 62,000 since 2014, according to Google Scholar).
In awarding this distinction to Professor Visscher, the University of Liège and its Faculty of Veterinary Medicine wish to highlight his impact on the understanding of the polygenic architecture of common complex diseases, as well as on the development of statistical methods to analyse them and predict the risks incurred by individuals.