MRC Human Genetics Unit
Medical Research Council Human Genetics Unit

Quantitative Trait Loci Research Group

Quantitative Traits in Health and Disease

Section: Biomedical Genomics

QTL PI's
left to right: Professor C.Haley, Dr Veronique Vitart, Dr Caroline Hayward, Professor Jim Wilson

Research in a Nutshell 

  • Dissection of genetic architecture of complex traits using kinship-structured and isolate populations with very rich phenotypes, particularly in terms of “omics”
  • Coordination of and contribution to genetic analyses in international consortia including CHARGE, SPIROMETA, CKDGen, GUGC, ROHgen, Ygen and LifeGen

The QTL (Quantitative Trait Locus) programme leverages the special population structures in our Scottish and Croatian cohorts to deliver biological understanding of the causes of variation in complex traits. A substantial part of the genetic component of disease remains hidden in rare variants that cannot be easily detected in traditional genome-wide association studies (GWAS), which have identified many common variants contributing to complex disease. Rare variants tend to have stronger effects, therefore are critical to risk stratification in precision medicine and more amenable to functional follow-up studies. Moreover, otherwise rare variants can increase in frequency by drift in isolated populations, facilitating their detection. The QTL group leads collaborative research integrating biochemical measures with “omics” data to elucidate uric acid metabolism, kidney function and control of body fat distribution. Discovering the genes affecting these and other traits pinpoints important biological pathways and molecular mechanisms. The QTL group makes the data and samples it generates available in line with the MRC’s policy on data sharing in human population cohorts. The kinship-based structure of our cohorts allows identification of both the contribution of genetic variation associated with the pedigree and the role of family environments and specific environmental variables, understanding of which will be crucial for future predictive medicine.

Research Programme

 

QTL group

People

 

Professor Chris Haley

Co-Principal Investigator
Professor Caroline Hayward

Co-Principal Investigator

Dr Veronique Vitart

Co-Principal Investigator

Professor Jim Wilson

Co-Principal Investigator

Susan Campbell Technical Support
Shona Kerr Project Manager
Jonathan Marten PhD Student
Thibaud Boutin Data Analyst
Reka Nagy Data Analyst
Lucija Klaric PhD Student

Contact

shona.kerr@igmm.ed.ac.uk

Key Publications

Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants

Genome Med.  2017; 9: 23 (link to paper on PubMedCentral)

Directional dominance on stature and cognition in diverse human populations

Nature. 2015; 523:459  (link to paper on PubMedCentral)

Homozygous loss-of-function variants in European cosmopolitan and isolate populations. Hum Mol Genet.2015. 24:5464-74 (link to paper on PubMedCentral)

Genome-wide association analyses identify 18 new loci associated with serum urate concentrations.  Nat Genet. 2013. 45:145 (link to paper on PubMedCentral)

Loci Associated with N-Glycosylation of Human Immunoglobulin G Show Pleiotropy with Autoimmune Diseases and Haematological Cancers. PLoS Genet. 2013. 9(1): ):e1003225 (link to paper on PubMedCentral)

Data and Sample Access

The CROATIA, ORCADES, VIKING and GS:SFHS study data have been the subject of many internal (within the University of Edinburgh) and external collaborations, which are encouraged.  Written informed consent was obtained from all participants and is broad and enduring. Summary data from specific projects have been deposited in the University of Edinburgh DataShare repository. 

University of Edinburgh DataShare Repository

All exome sequence data generated to date on the cohorts described here, along with whole genome sequence data for ORCADES, have been deposited in the European Genome-phenome Archive (EGA, https://www.ebi.ac.uk/ega/homeunder the management of the QTL data access committee.

The procedure for those who wish to work with any of the datasets is to email:

The data and sample sharing process is facilitated by a full-time project manager and agreed proposals are conducted in collaboration with appropriate members of the QTL team.

Collaborations

  • IGMM, University of Edinburgh: Professor Malcolm Dunlop, Dr Toby Hurd, Professor Andrew Jackson, Professor David Porteous, Dr Philip Riches, Professor Colin Semple, Professor Martin Taylor, Dr Pippa Thomson, Professor Wendy Bickmore, Dr Andrew Wood
  • University of Edinburgh, Professor Harry Campbell, Professor Ian Deary, Professor Andrew McIntosh, Professor Igor Rudan, Professor Nik Morton, Professor Brian Walker, Professor Sarah Wild
  • University of Glasgow, Professor Sandosh Padmanabhan and Professor Christian Delles (Institute of Cardiovascular and Medical Sciences); Professor Ruth Jarrett (Institute of Infection, Immunity and Inflammation)
  • University of Dundee, Dundee, UK, Prof Colin Palmer, Professor Blair Smith (School of Medicine).

  • University of Aberdeen, Aberdeen UK Dr Lynne Hocking (Institute of Medical Sciences)
  • University of Split, Croatia, Dr Ozren Polasek and Dr Ivana Kolcic  (Public Health Sciences)
  • University of Zagreb, Croatia, Professor Gordan Lauc (Faculty of Pharmacy and Biochemistry)
  • Institute for Anthropological Research, Zagreb, Croatia, Dr Branca Janicijevic, Dr Nina Smolej-Narancic
  • University of Zurich, Switzerland, Professor Olivier Devuyst, Professor Murielle Bochud
  • University of Leicester, Leicester, UK, Professor Martin Tobin (Department of Health Sciences)
  • University of Lausanne, Switzerland, Dr Zoltan Kutalik (Swiss Institute of Bioinformatics)
  • University of Otago, New Zealand, Prof Tony Merriman (School of Medical Sciences)
  • University of Tartu, Estonia, Dr Tonu Esko, Dr Krista Fischer (Estonian Genome Centre)
  • University of Trieste, Italy, Dr Ilaria Gandin, Professor Paolo Gasparini (Burlo Garofolo Hospital)
  • Wellcome Trust Sanger Institute, Hinxton, UK, Professor Ele Zeggini
  • University of Helsinki, Helsinki, Finland, Prof Markus Perola, Hannele Mattson (Finnish Institute of Molecular Medicine)
  • University of Uppsala, Uppsala, Sweden, Prof Ulf Gyllensten, Dr Asa Johansson (Science for Life Laboratory)
  • 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

  • MRC
  • CROATIA Cohorts
  • Generation Scotland
  • The Viking Health Study

Scientific Themes

Genetic risk factors, quantitative traits, isolate populations, disease mechanisms, DNA sequence analysis, deep phenotyping, linkage, omics, genetic architecture, homozygosity, Y chromosome

Technology Expertise

GWAS, genomics, imputation, statistical genetics, population genetics, electronic health record linkage, populations cohort recruitment and biobanking