Transcript Hollis-Moffatt

Genetics of gout in
Aotearoa
Hyperuricaemia and Gout in
Aotearoa
Klemp et al. 1997
Dalbeth et al. 2007
To help ensure the ‘success’ of
this project
‘Community buy in’
Reduce whakama
90% gout is caused by renal
underexcretion
of urate
Education
Need for daily
medication
Reduce hoha
Research updates
Much research in Caucasian gout
populations
Fructose-based food/drinks  risk of a gout
attack
‘Urate
Secretion’
LUMEN
Proximal
convoluted
tubule
SLC2A9
‘Urate
Reabsorption’
BLOOD
ABCG2
APICAL MEMBRANE
BASOLATERAL MEMBRANE
SLC2a9
•
Solute carrier family 2 member 9 was the first confirmed gene
demonstrated to regulate serum urate levels.
•
also known as glucose transporter 9 (GLUT9), located on human
chromosome 4.
•
a high capacity, low affinity urate transporter that functions to transport
urate across renal tubular cells in both directions.
LUMEN
SLC2A9
BLOOD
SLC2a9
Hollis-Moffatt,
Xu et al. 2009
SLC2a9
 rs16890979-rs5028843-rs11942223-rs12510549
ABCG2
 serum urate influencing gene, ATP-binding cassette subfamily G member 2,
located on human chromosome 4.
 first identified as a multi-drug resistance protein, subsequently found to be
associated with serum urate and gout susceptibility (2008)
 Woodward et al. (2009) demonstrated that
 ABCG2 is a unidirectional urate transporter in the proximal renal tubule
 the rs2231142 lysine allele encodes a transporter with 53% less activity
than the glutamine allele at position 141.
LUMEN
ABCG2
BLOOD
Population stratification
 Defined as the difference in allele frequencies between cases and
controls due to systematic differences in ancestry rather than
association of disease genes
 Population variations arise from a unique set of genetic and social
history influenced by ancestral patterns of migration, mating,
reproductive expansions, bottlenecks and stochastic variation
 Nearly all populations are hindered by genetic admixture at some
level
 For population stratification to exist there needs to be:
 Differences in the disease prevalence between different
populations
 Allele frequencies must vary between the two ancestral
populations

Dealing with population
stratification in our sample set
 Identifying population admixture using STRUCTURE
 a clustering-model program that uses unlinked genomic data to infer
population stratification, assigning individuals to certain populations based
on probabilities.
 The model assumes there are K sub-populations in the sample set and
each sub-population is charaterised by a set of allele frequencies at each
locus.
 Individuals are assigned to various sub-populations on the basis of their
genotypes at the unlinked markers, while concurrently estimating the allele
frequencies in each sub-population.
 We used 16 bi-allelic markers as genomic controls to account for differing
levels of non-Māori and non–Pacific Island ancestry between the cases
and controls in the analyses.
 Assumptions:
 Genomic markers are not linked (or accounted for using a linkage model)
this has been added into the STRUCTURE software
 Hardy-Weinberg equilibrium exists for each sub-population
Pritchard et al. (2000)
Dealing with population
stratification in our sample set
 Correcting for population stratification using STRAT
 After estimating an individuals’ ancestry using STRUCTURE
it is then necessary to test for association by using STRAT.
 Assumptions:
 Unrelated cases and controls
 More than one sub-population
 Null hypothesis – no genetic association within sub-populations
 Used after STRUCTURE so that any association between
alleles and disease within sub-populations cannot be due to
population stratification
Pritchard et al. (2000)
ABCG2
 Test rs2231142 for association in our NZ Caucasian,
Maori and Pacific Island sample sets
 Adjusting for population stratification
Hollis-Moffatt, Phipps-Green et al. awaiting publication
Polynesian migration
Stratifying our New Zealand
Pacific Island sample set
ABCG2
 Stratifying Maori and Pacific Island sample sets
according to Western and Eastern Polynesia
 Emphasises that rs2231142 is associated with gout in
Western but not Eastern Polynesia
Hollis-Moffatt, Phipps-Green et al. awaiting publication
Conclusions – SLC2A9
 Our data confirm a role for SLC2A9 in gout
susceptibility in a NZ Caucasian sample set, with the
effect on risk (OR>2.0).
 We also demonstrate association of SLC2A9 with gout
in samples of Māori and Pacific Island ancestry and a
consistent pattern of haplotypic association.
Conclusions – ABCG2
 Unlike SLC2A9 where the Caucasian-associated
variants are considerably stronger risk factors for gout
in both Māori and Pacific Island people than in
Caucasian, the ABCG2 Q141K variant has a stronger
effect only in Pacific Island people.
 The reason for this could be genetic difference between
Western and Eastern Polynesian populations.
Acknowledgments
Ngati Porou Whanau - Ngati Porou Hauora - Kaiawhina, Nurses, GPs
Te Whare Wananga o Otago - Te Huka Matauraka
National Heart Foundation - Health Research Council
Ngai Tahu Research Consultation Committee
Ngati Porou Advisory Committee – NZ Rheumatology Network
Middlemore Hospital – Mornington Health Centre