Paediatrics (RCH) - Research Publications
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ItemHFE p.C282Y homozygosity predisposes to rapid serum ferritin rise after menopause: A genotype-stratified cohort study of hemochromatosis in Australian women(WILEY, 2017-04)BACKGROUND AND AIM: Women who are homozygous for the p.C282Y mutation in the HFE gene are at much lower risk of iron overload-related disease than p.C282Y homozygous men, presumably because of the iron-depleting effects of menstruation and pregnancy. We used data from a population cohort study to model the impact of menstruation cessation at menopause on serum ferritin (SF) levels in female p.C282Y homozygotes, with p.C282Y/p.H63D simple or compound heterozygotes and those with neither p.C282Y nor p.H63D mutations (HFE wild types) as comparison groups. METHODS: A sample of the Melbourne Collaborative Cohort Study was selected for the "HealthIron" study (n = 1438) including all HFE p.C282Y homozygotes plus a random sample stratified by HFE-genotype (p.C282Y and p.H63D). The relationship between the natural logarithm of SF and time since menopause was examined using linear mixed models incorporating spline smoothing. RESULTS: For p.C282Y homozygotes, SF increased by a factor of 3.6 (95% CI (1.8, 7.0), P < 0.001) during the first 10 years postmenopause, after which SF continued to increase but at less than half the previous rate. In contrast, SF profiles for other HFE genotype groups increase more gradually and did not show a distinction between premenopausal and postmenopausal SF levels. Only p.C282Y homozygotes had predicted SF exceeding 200 μg/L postmenopause, but the projected SF did not increase the risk of iron overload-related disease. CONCLUSIONS: These data provide the first documented evidence that physiological blood loss is a major factor in determining the marked gender difference in expression of p.C282Y homozygosity.
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ItemNo Preview AvailableNatural history of HFE simple heterozygosity for C282Y and H63D: A prospective 12-year study(WILEY, 2015-04)BACKGROUND AND AIM: The risk of hemochromatosis-related morbidity for HFE simple heterozygosity for either the C282Y or H63D substitutions in the HFE protein was assessed using a prospective community-based cohort study. METHODS: HFE genotypes were measured for 31,192 persons of northern European descent, aged between 40 and 69 years when recruited to the Melbourne Collaborative Cohort Study, and subjects were followed for an average of 12 years. For a random sample of 1438 participants stratified according to HFE genotype, two sets of biochemical iron indices performed 12 years apart and, at follow-up only, the presence/absence of six disease features associated with hereditary hemochromatosis were obtained. Summary data for 257 (139 female) C282Y simple heterozygotes and 123 (74 female) H63D simple heterozygotes were compared with 330 (181 female) controls with neither HFE mutation. RESULTS: At baseline, mean transferrin saturation (TS) (95% confidence interval) and prevalence of TS > 55% were 35.14% (33.25, 37.04) and 3/112 (3%), 33.03% (29.9, 36.15) and 0/39 (0%), and 29.67% (27.93, 31.4) and 3/135 (2%) for C282Y, H63D and wild-type male participants, respectively. At follow-up, mean TS levels remained similar to baseline levels for both men and women irrespective of simple heterozygosity for either mutation. No HFE C282Y or H63D simple heterozygotes had documented iron overload (based on hepatic iron measures or serum ferritin greater than 1000 mg/L at baseline with documented therapeutic venesection). CONCLUSION: No documented iron overload was observed for HFE simple heterozygotes for either C282Y or H63D, and morbidity for both HFE simple heterozygote groups was similar to that of HFE wild-type participants.
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ItemSNP selection for genes of iron metabolism in a study of genetic modifiers of hemochromatosis(BMC, 2008-03-20)BACKGROUND: We report our experience of selecting tag SNPs in 35 genes involved in iron metabolism in a cohort study seeking to discover genetic modifiers of hereditary hemochromatosis. METHODS: We combined our own and publicly available resequencing data with HapMap to maximise our coverage to select 384 SNPs in candidate genes suitable for typing on the Illumina platform. RESULTS: Validation/design scores above 0.6 were not strongly correlated with SNP performance as estimated by Gentrain score. We contrasted results from two tag SNP selection algorithms, LDselect and Tagger. Varying r2 from 0.5 to 1.0 produced a near linear correlation with the number of tag SNPs required. We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the > or = 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing. Resequencing can reveal adjacent SNPs (within 60 bp) which may affect assay performance. We report the number of SNPs present within the region of six of our larger candidate genes, for different versions of stock genotyping assays. CONCLUSION: A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data. Tag SNP software must be fast and flexible to data changes, since tag SNP selection involves iteration as investigators seek to satisfy the competing demands of coverage within and between populations, and typability on the technology platform chosen.