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

Research updatesMuch research in Caucasian gout

populationsFructose-based food/drinks risk of a

gout attack

EducationNeed for daily

medicationReduce hoha

‘Community buy in’Reduce whakama

90% gout is caused by renal underexcretion

of urate

‘Urate Reabsorption’

BLOOD

Proximal convoluted

tubule

‘Urate Secretion’

LUMEN

BASOLATERAL MEMBRANEAPICAL MEMBRANE

SLC2A9

ABCG2

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.

BLOODLUMEN SLC2A9

Hollis-Moffatt, Xu et al. 2009

SLC2a9

rs16890979-rs5028843-rs11942223-rs12510549

SLC2a9

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.

BLOODLUMEN ABCG2

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)

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

Dealing with population stratification in our sample set

Pritchard et al. (2000)

Hollis-Moffatt, Phipps-Green et al. awaiting publication

ABCG2Test rs2231142 for association in our NZ

Caucasian, Maori and Pacific Island sample sets

Adjusting for population stratification

Polynesian migration

Stratifying our New Zealand Pacific Island sample set

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

ABCG2

Hollis-Moffatt, Phipps-Green et al. awaiting publication

Conclusions – SLC2A9Our 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 – ABCG2Unlike 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