Submitting Institution
University of SouthamptonUnit of Assessment
Clinical MedicineSummary Impact Type
HealthResearch Subject Area(s)
Biological Sciences: Genetics
Summary of the impact
Research carried out by the University of Southampton into the genetic
causes of diseases, and the gene mapping techniques and applications
derived from this research, has benefited patients worldwide through
improved prediction, diagnosis and treatment for common diseases with a
complex genetic basis. A particularly striking example is age-related
macular degeneration which is a common cause of blindness. Commercially,
the research provides cost-effective strategies for genotyping DNA
samples, and marker-based selection strategies for economically relevant
animal species, such as cattle. The work underpins the development of the
personal genomics industry, which specialises in individual genetic risk
profiling.
Underpinning research
With the race to find the genetic causes of diseases gathering pace,
there is less focus on diseases caused by rare single gene mutations, such
as cystic fibrosis, and more on common diseases with a complex genetic
basis, such as breast cancer and Type 2 diabetes. Research at the
University of Southampton, led by Professors Newton Morton (1988-retired
in 2010) and Andrew Collins (Professor of Genetic Epidemiology and
Bioinformatics, 1989-date), has delivered gene mapping techniques which
enable the identification of specific chromosome sections where the causes
of diseases lie.
Collins and Morton published an early paper on allelic association
mapping which adapted the Malecot model for genetic isolation by distance
to accurately fine-map a Mendelian gene (for cystic fibrosis) as proof of
principle. The model was extended for association mapping in `common'
disease using single nucleotide polymorphisms (SNPs) [3.1].
Morton and Collins were the first to quantify the advantages and
increased power achieved by case-control (contrasting disease cases with
disease-free individuals) versus family-based gene mapping strategies [3.2].
This work facilitated rapid adoption of this simpler, more powerful and
cost-effective format by many research groups, including the Wellcome
Trust Case Control Consortium, which identifies disease genes in
Genome-Wide Association Studies (GWAS: testing many genetic variants in
different individuals to find associations with disease).
Collins and Morton were the first to show cost-effective GWAS can be
achieved using a small panel of marker SNPs (just ~1% of all SNPs) because
of extensive linkage disequilibrium (LD, the population association
between genetic markers in close proximity on a chromosome) [3.1].
Their early findings of extensive LD were in stark contrast to the
(incorrect) assertions of other influential authors and informed the
design and development of the `HapMap' project enabling construction of
genome-wide SNP screening panels.
Collins and Morton developed LD unit (LDU) maps that represent patterns
of LD and, with commercial funding from Applied Biosystems, the LDMAP
software for their construction [3.3]. They demonstrated that LDU
maps increase power for gene mapping and are invaluable for characterising
human population structure. LDU maps are used in research projects by many
different groups internationally including Nelson Freimer (UCLA) [3.4],
Leena Peltonen (Finland) [3.4] and Alec Jeffreys (Leicester).
Collaborative work with the Freimer group revealed the value of isolated
populations for cost-effective gene mapping with reduced genetic
heterogeneity.
Using LDU maps, Morton and Collins identified remarkably numerous and
extensive regions of homozygosity in outbred (and not just isolated)
populations [3.5]. They demonstrated the persistence of unbroken
ancestral haplotypes in regions with low recombination rates. This work
opened a new international research area exploiting homozygosity mapping
in outbred populations to identify novel recessive disease genes.
Collaboration with the University of Sydney (Professors Frank Nicholas,
and Herman Raadsma) underpinned development of SNP panels for marker-based
selection in the bovine genome, enabling commercial applications.
The many applications of case-control based association carried out at
the University of Southampton, exploiting LDU maps for mapping genes
underlying common diseases, include identification of significant
metabolic genes in large birth cohorts [3.4] and genes causing
age-related macular degeneration (AMD) [3.6].
References to the research
3.1 Collins, A., Lonjou, C. and Morton, N.E. (1999)
Genetic epidemiology of single nucleotide polymorphisms. Proc Natl
Acad Sci USA 96(26), 15173-7. (279 citations).
3.2 Morton, N.E. and Collins, A. (1998) Tests and
estimates of allelic association in complex inheritance. Proc Natl
Acad Sci USA 95, 11389-11393. (248 citations in GS).
3.3 Maniatis, N., Collins, A., Ku, X-F., McCarthy, L.C.,
Hewett, D.R., Tapper, W., Ennis, S., Ke, X., Morton, N.E. (2002)
The first linkage disequilibrium (LD) maps: delineation of hot and cold
blocks by diplotype analysis. Proc Natl Acad Sci USA, 99(4),
2228-2233. (164 citations).
3.4 Sabatti C, Service SK, Hartikainen A-L, Pouta A, Ripatti S,
Brodsky J, Jones CG, Varilo T, Kaakinen M, Sovia U, Ruokonen A, Laitinen
J, Jakkula E, Coin L, Hoggart C, Elliot P, Collins A, Turunen H,
Gabriel S, McCarthy MI, Daly MJ, Järvelin M-R, Freimer NB, Peltonen L
(2008). Genomewide association analysis of metabolic phenotypes in a birth
cohort from a founder population. Nature Genetics, 41:35-46. (314
citations).
3.5 Gibson, J., Morton, N.E., Collins, A. (2006)
Extended tracts of homozygosity in outbred human populations. Human
Molecular Genetics 15 (5), 789-95. (114 citations).
3.6 Ennis S, Jomary C, Mullins R, Cree A, Chen X, MacLeod A, Jones
S, Collins A, Stone E, Lotery A (2008). Association between the
SERPING1 gene and age-related macular degeneration: a two-stage
case-control study. Lancet, 372:1828-34. (102 citations).
Grants
1998-2003. Collins A. Medical Research Council, Career
Establishment Grant+supplement: Integration of maps to support disease
gene mapping. £456,568.
2001-2005. Morton NE and Collins A. Medical Research
Council. Linkage disequilibrium in the human genome. £157,259.
2004-2005. Collins A. Applied Biosystems, Foster City,
California. Linkage disequilibrium maps. £59,466. [Commercial funding
for development of LDU maps used in their SNPbrowser™ software.]
2004-2006. Collins A and Morton NE. BBSRC. Linkage
disequilibrium maps for human populations. £274,260.
2004-2008. Morton NE and Collins A. NIH. Development and
application of methods to map disease genes by allelic association.
~£300,000.
2006-2009. Lotery A, Collins A, Ennis S. Macular Vision Research
Foundation. Linkage disequilibrium mapping of genes associated with
age-related macular degeneration. ~£150,000
2011-2013. Eccles D, Collins A, Tapper W. Breast Cancer Campaign.
Does inherited genetic variation influence breast cancer biology and
prognosis?. £128,222.
Details of the impact
The research by Collins and Morton (CAM) has substantial impact in
translational medicine, contributing new ways to predict disease and
diagnose and treat patients. The work enables creation of new,
cost-effective, technologies, commercial exploitation of livestock genomes
and development of the personal genomics industry.
These methods provide a basis for >450 genome-wide association studies
undertaken worldwide since 2008 which have identified many novel disease
variants and opened new avenues of research highlighting unanticipated
disease pathways and mechanisms. The research has identified disease genes
underlying cancer, metabolic traits, ophthalmic traits and others,
enabling risk prediction and therapeutic interventions.
Age-related macular degeneration (AMD), the most common cause of
blindness in developed countries, is an excellent example. The mapping by
GWAS (Genome-Wide Association Studies) of a key gene, Complement Factor H
(CFH) paved the way for identification of related genes. Application of
CAM's gene mapping methods, in collaboration with Southampton Professor of
Ophthalmology, Andrew Lotery, identified the SERPING1 gene and established
a virtually complete understanding of the genetic causes of AMD by 2010 [5.1].
The impact of an individual's genetic makeup is now quantified as risk to
develop AMD, and at least five commercial genetic testing kits now predict
patient risk [5.2], with clinical trials of genetic therapy
underway [5.3]. About 20% of the population is at risk of AMD and
genetic models have 83% predictive value [5.2].
The work enables commercial development of cost-effective strategies for
genotyping DNA samples in association studies, including GWAS. Powerful
GWAS with very large sample sizes are therefore economically feasible and
identify genetic factors underlying different diseases, improving disease
prediction and identifying potential routes to therapy. The power of CAM's
work was recognised by Life Technologies, a US company which funded the
development of LDU maps for incorporation in their SNPbrowser™ software [5.4].
With subsequent LDU map updates the browser reached its full commercial
potential from 2008, continuing to the present day. The software enables
effective genotyping strategies in cases and controls for the
identification of disease genes.
The methodologies developed by CAM are applicable in commercially
significant animal genomes. Collaboration with the University of Sydney
enabled development of cost-effective commercial genotyping of DNAs from
dairy cattle, focusing on the identification of superior cattle strains to
increase milk yields [5.5]. A direct result of this research let
to the development of LDU maps for cattle which enabled the construction
of non-redundant `reduced' SNP panels which have practical application in
genetic marker-based selection. Beneficiaries of commercial livestock
genotyping are primarily cattle breeders — an important market in
Australia alone, which is the world's second largest beef exporter. As a
result of this work several companies focus on genetic profiling of
livestock. One example is the Neogen Corporation which has a new GeneSeek®
Genomic Profiler™ to maximise the genetic potential of stock animals to
increase profitability [5.6]. Neogen reported $6.6 million net
income for the third quarter of the 2013 financial year.
The personal genomics industry, which has developed since 2008, has
become possible through disease gene identification in GWAS for which
CAM's research was pivotal [5.7]. Personal genomics is concerned
with the analysis of individual genomes and particularly the
characterisation of genomic variation known to be implicated in disease.
One example is the 23andme service and offers genetic risk
profiles for more than 40 diseases, with the aim of detecting risk
profiles early, motivating lifestyle changes and focussing medical
screening. Users of these new commercial services include insurance
companies and individuals interested in their own risk profiles.
An additional impact of the research is through contribution to
pharmacogenomics, which deals with the influence of genetic variation on
drug response in patients. Profiling is important to avoid dangerous
adverse drug responses and wasteful prescription of medicines unsuitable
for a specific patient. Collated information available on the genetic
basis of drug response has become available via the PharmGKB database [5.8].
This provides data on around 170 drug-gene relationships that are valuable
in clinical practice. The case of AMD, described above, is an example in
which a patient's genetic profile strongly determines disease risk and
provides invaluable information for tailoring screening and treatment
regimens. The database identifies AMD genetic variants mapped by
association studies/GWAS as targets for the drug Ranibizumab (Lucentis)
which has been approved to treat `wet' AMD. The ultimate beneficiaries of
the research, the patients can, therefore, be treated more effectively
using this Southampton-led approach to personalised/stratified medicine.
In summary, these methods enable the mapping of genes involved in human
diseases with significant impact on disease prediction and the development
of personalised medicine. The work also underpins genetic profiling in
cattle and other genomes of commercial importance. The continuing
development of disease and trait genomics will have far-reaching impact in
the coming years.
Sources to corroborate the impact
5.1 Genes identified using methodologies developed by Collins and
Morton for case-control based GWAS, include the SERPING1 gene. It is one
of six AMD genes which account for 45% of the risk of developing
age-related macular degeneration (87% population attributable risk). Ref.:
Gibson J, Cree A, Collins A, Lotery A, Ennis S, 2010,
"Determination of a gene and environment risk model for age-related
macular degeneration". Br J Ophthalmol, 94(10):1382-1387).
Metabolic trait related genes identified (reference 3.4) include
high-density lipoprotein with NR1H3, low-density lipoprotein with AR and
FADS1-FADS2, glucose with MTNR1B, and insulin with PANK1.
5.2 The mapping of many of the genes underlying AMD has enabled
the development of commercial kits for genetic prediction such as
RetnaGene http://www.sequenomcmm.com/AMD
(Sequenom). Ref.: Hageman GS et al., Clinical validation of a genetic
model to estimate the risk of developing choroidal neovascular age-related
macular degeneration. Hum Genomics. 2011; 5(5). The Macula risk
model has 83% predictive value and stratifies individuals into five
categories with increased risk of AMD, representing 20% of the population:
http://www.revoptom.com/continuing_education/tabviewtest/lessonid/107647/
5.3 An example of a clinical trial program (2010) for AMD is
Oxford Biomedica, a gene therapy company in the U.K., which has received
FDA authorization to launch a clinical trial of its RetinoStat® gene
therapy for the treatment of wet age-related macular degeneration:
http://www.blindness.org/index.php?option=com_content&view=article&id=2360:clinical-trial-for-wet-amd-gene-therapy-to-begin-in-december-2010&catid=64:macular-degeneration&Itemid=120
5.4 The SNPbrowser™ software now owned by Life Technologies,
version 4.0 was published on March 25 2012: http://www.mybiosoftware.com/population-genetics/5641.
It is a freely available tool enabling knowledge-guided selection of over
six million TaqMan® or SNPlex™ System SNP Genotyping Assays, including 650
million genotypes generated for over three million SNPs validated by the
International HapMap Project or Applied Biosystems in five major
populations. It includes visualization of SNPs integrated with the
physical genome maps and haplotype block information. The tool features
the linkage disequilibrium unit (LDU) maps developed by Collins and Morton
to enable selection and purchase of cost-effective SNP panels.
5.5 Collins established a strong collaboration with the University
of Sydney Cooperative Research Centre (CRC) for Innovative Dairy Products.
The CRC is a seven-year, $80 million, research consortium set up by the
dairy industry and the Commonwealth Government, and involves a number of
Australia's leading research institutes and dairy companies:
http://www.ausbiotech.org/directory/details.asp?companyid=%7B295B6313-9CFA-4912-9CEC-82642C6BABC7%7D&returntourl=%2Fdirectory%2Fsearch.asp%3Fpg%3D15.
The collaboration established the first LDU maps for cattle and the first
comprehensive understanding of the LD structure of cattle genomes. Ref.:
Extent of genome-wide linkage disequilibrium in Australian
Holstein-Friesian cattle based on a high-density SNP panel. MS Khatkar, FW
Nicholas, AR Collins et al., BMC genomics, 2008, 9 (1),
187.
5.6 The LDU maps of cattle, and the development of reduced panels
of marker SNPs, enable genetic-marker based selection for traits of
importance. Companies which now exploit marker-based selection include:
the Canadian Dairy Network which established commercial genetic testing in
2012: http://www.ciaq.com/news/news-items/2012/alliance-gives-dairy-producers-access-to-new-genetic-testing-services.html
and Neogen which has a comprehensive cattle genomic test:
http://www.neogen.com/Corporate/PR2013/2013-05-06.html
5.7 Our development of association mapping methods for the
identification of genes underlying disease has enabled the development of
personal genomics companies such as 23andMe
(https://www.23andme.com/) whose
personal genome test kit was named "Invention of the Year" in 2008:
"TIME's Best Inventions of 2008". Time magazine. 2008-10-29. The company
is aiming to achieve a one million customer base in 2013.
5.8 The Pharmacogenomics Knowledge Base (PharmGKB) http://www.pharmgkb.org/ provides data on ~170 drug-gene
relationships that are valuable in clinical practice. Web service for
pharmacogenetic study published Gong L, Owen RP, Gor W, Altman RB, Klein
TE. (2008). PharmGKB: an integrated resource of pharmacogenomic data and
knowledge. Curr Protoc Bioinformatics. Chapter 14:Unit14.7