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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