MRC Human Genetics Unit
Medical Research Council Human Genetics Unit

Jim Wilson Research Group (Affiliate)

Quantitative traits in health and disease

Research in a Nutshell 

Professor J.Wilson
Professor Jim Wilson - Personal Chair of Human Genetics

Research in my group spans the interface of population and disease genetics, with a focus on the genetic architecture of complex traits and the identification of genetic variants influencing quantitative risk factors for common diseases such as heart disease and diabetes. I am particularly interested in high kinship isolate populations which have increased utility for rare variant discovery, but we also make use of the UK Biobank and Generation Scotland resources. I am principal investigator of the the ORCADES and VIKING studies, platform resources for health research to which we continue to recruit participants from the Northern Isles of Scotland.

My major research interest is in homozygosity and the potential role of recessive genetic variants in determining disease risk – I steer an international consortium (ROHgen) of >200 cohort studies and >1.4 M research participants, which seeks to understand the effect of inbreeding on complex traits in humans. After developing the methods to measure homozygosity and describing the global distribution, we demonstrated an effect of genome-wide homozygosity on height and cognition. More recently we showed for the first time that parental relatedness has a profound effect on fertility of the individual, and smaller effects on risk-taking traits. Moreover, we could show using sibling comparisons that this effect was causally genetic and not confounded, and that this effect is likely due to rare variants in the genome.

Together with Albert Tenesa, I have recently set up a new international study, Coronagenes, to understand the genetic factors influencing the severity and symptoms of COVID-19 coronavirus infection. Other research themes in my group include the genetics of lifespan, retinal vessel traits, dietary genetics, homozygous knockouts from sequence data, the genetics of proteomics, the contribution of the Y chromosome to complex trait variation and genetic architecture more generally in terms of heritability, pleiotropy, etc. I also run a study of Multiple Sclerosis in Orkney and Shetland, focussing both on genetics and the role of vitamin D.

A final strand of activity is in population genetics, particularly focussed on the genetic history of the British Isles, where I was the first to discover genetic evidence for Norse Viking ancestry. I recently described the fine-scale genetic structure of Britain and Ireland, focussing on Scotland. An important SW to NE divide in Scottish genetics was apparent, as well as a number of isolated populations with their own distinct gene pools – the Northern Isles, the Hebrides, the Isle of Man and County Donegal. Detailed analysis in Shetland has shown that 10% of all genetic variants found there are either unique to the islands or at least tenfold enriched there, compared to Edinburgh.

Our recent collaborations with clinical geneticists in NHS Grampian have started to reveal the consequences of these unique gene pools for the people of the Northern Isles, as certain actionable variants are at much higher frequency than elsewhere. After our initial study of a Long QT Syndrome variant in Shetland, we are now moving on to a broader survey of recessive Mendelian variants in Orkney and Shetland. We are at the forefront of applying genomic medicine in Scotland through the approved return of actionable genetic findings in our VIKING II study, as an exemplar for larger-scale studies.

 

Research Programme

J.Wilson group

People

 
Professor Jim Wilson Group Leader
Dr Peter Joshi Chancellor’s Fellow
Dr Nicola Pirastu Chancellor’s Fellow

Dr Xia Shen

Chancellor's Fellow
Dr Shona Kerr Project Manager
David Buchanan Data Manager
Rachel Edwards Administrator
Dr Paul Timmers data analyst
Erin Macdonald-Dunlop PhD Student
Linda Repetto PhD Student
David Clark PhD Student
Katherine Kentistou PhD Student
Ciara McDonnell PhD student
Marisa Muckian PhD student
Arianna Landini PhD student
Sebastian May-Wilson PhD student

Affiliates

 
Dr Rob Young Academic Track Lecturer (Zhejiang)
Dr Lucija Klaric UKRI Fellow

Alumni

 
Dr Ruth McQuillan PhD student
Dr Chris Franklin PhD student
Dr Mirna Kirin PhD student
Dr Emily Weiss PhD student
Dr Kate Schraut PhD student
Dr Katie Barnes PhD student
Dr Ross Fraser postdoc

Contact

Jim.Wilson@ed.ac.uk

Collaborations

  • IGMM, University of Edinburgh: Prof Malcolm Dunlop, Prof David Porteous, Prof Colin Semple, Prof Wendy Bickmore, Dr Andrew Wood, Prof Stuart Ralston
  • University of Edinburgh: Prof Harry Campbell, Prof Ian Deary, Prof Igor Rudan, Prof Nik Morton, Prof Brian Walker, Prof Sarah Wild
  • University of Tartu, Estonia: Dr Tonu Esko, Dr Krista Fischer
  • University of Trieste, Italy: Dr Ilaria Gandin, Prof Paolo Gasparini
  • Wellcome Trust Sanger Institute: Hinxton, UK: Prof Ele Zeggini
  • University of Split, Croatia: Dr Ozren Polasek
  • University of Zagreb, Croatia: Prof Gordan Lauc
  • University of Helsinki, Finland: Prof Markus Perola, Hannele Mattson
  • University of Uppsala, Sweden: Prof Ulf Gyllensten, Dr Asa Johansson
  • Mount Sinai School of Medicine, New York City, USA: Dr Claudia Schurmann
  • Icelandic Heart Association, Reykjavik, Iceland: Dr Albert Smith
  • European Academy, Bolzano, Italy: Prof Peter Pramstaller, Dr Andrew Hicks, Dr Cristian Pattaro, Dr Christian Fuchsberger

Partners and Funders

  • Medical Research Council
  • Chief Scientist Office of Scottish Government
  • Shetland and Orkney Multiple Sclerosis Research Project

Scientific Themes

genetic architecture, rare variants, GWAS, isolated populations, cohort studies, inbreeding depression, runs of homozygosity, Multiple Sclerosis, vitamin D, bodyfat, retinal vessels, Y chromosome, mtDNA, multi-omics, lifespan, food preferences

Technology Expertise

The Wilson group is a dry group with expertise in population and quantitative genetics, including genome-wide association, mixed models, polygenic risk scores, quantitative traits, whole genome sequence analysis, pipelining, running cohort studies