Effects of HFE C282Y and H63D Polymorphisms and Polygenic Background on Iron Stores in a Large Community Sample of Twins

Whitfield, John B.; Cullen, Lara M.; Jazwinska, Elizabeth C.; Powell, Lawrie W.; Heath, Andrew C.; Zhu, Gu; Duffy, David L.; Martin, Nicholas G.

doi:10.1086/302862

Cited by 154 publications

(133 citation statements)

References 41 publications

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“…This finding is in line with previous reports of large populationbased studies. 14,19,29 Serum ferritin showed the weakest association with the two HFE mutations studied. A significantly higher serum ferritin was observed only for the C282Y homozygotes (men and women) and compound heterozygous men.…”

Section: Discussionmentioning

confidence: 88%

“…Increased levels of serum iron, ferritin and transferrin saturation have been found in subjects homozygous or heterozygous for the C282Y and H63D mutations as well as compound heterozygotes. 8,13,14,16,18 However, it is not clear to what extent the relation between the C282Y or H63D heterozygosity and iron status can be explained by subjects who are compound heterozygotes. Further, a significant additive effect on iron status of the H63D mutation was found, 14 suggesting that individuals heterozygous or homozygous for the common H63D mutation may be at increased risk for hemochromatosis and related disorders.…”

Section: Introductionmentioning

confidence: 99%

“…8,14,19 The mean age of the largest study 8 conducted to date in Caucasians was 56.9 years. Owing to their subtle effect on iron status, the effect of heterozygosity may be pronounced in older people.…”

Section: Introductionmentioning

confidence: 99%

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A population-based study of the effect of the HFE C282Y and H63D mutations on iron metabolism

et al. 2003

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The C282Y and H63D mutations in the HFE gene are important causes of hemochromatosis. In the elderly, these mutations might be associated with increased morbidity because of the lifelong accumulation of iron. In a population-based sample of the elderly, we determined the value of genotyping for HFE mutations to screen for subclinical hemochromatosis. HFE genotype frequencies were determined in a random group of 2095 subjects (55 years and over). In this random group, we selected within the six genotype groups a total of 342 individuals and measured their serum transferrin saturation, iron and ferritin levels. We also estimated the heritability and parameters needed to evaluate screening, including the sensitivity, specificity, positive and negative predictive values (PPV, NPV) of HFE genotypes. Iron parameters were significantly increased in subjects homozygous, heterozygous or compound heterozygous. The effect of the mutations was more pronounced in men than in women. For the H63D mutation, an allele dose effect was observed. The HFE gene explained about 5% of the variability in serum iron indices. The PPV for hemochromatosis for the C282Y homozygous was 100% in men and 67% in women. The NPV of the wild-type allele was 97% for both men and women. The sensitivity of both mutations was 70% for men and 52% for women and the specificity was 62% for men and 64% for women. Our study shows that the HFE C282Y and H63D are determinants of iron parameters in the elderly and will be effective in detecting individuals at high risk of hemochromatosis. However, when screening based on these two mutations, some individuals with subclinical hemochromatosis will be missed.

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Section: Discussionmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

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A population-based study of the effect of the HFE C282Y and H63D mutations on iron metabolism

et al. 2003

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“…This SNP was specifically included in the discovery step in spite of its MAF being o5% because, of all known genetic polymorphisms, it explains the largest fraction of the variance of the body iron storage indicator ferritin. 15,20 (In the KORA cohorts, it explained 0.5% (KORA F3) to 0.8% (KORA F4) of the variance of the age-and sex-adjusted log 10 (ferritin) values).…”

Section: Resultsmentioning

confidence: 99%

Dilution of candidates: the case of iron-related genes in restless legs syndrome

et al. 2012

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Restless legs syndrome (RLS) is a common multifactorial disease. Some genetic risk factors have been identified. RLS susceptibility also has been related to iron. We therefore asked whether known iron-related genes are candidates for association with RLS and, vice versa, whether known RLS-associated loci influence iron parameters in serum. RLS/control samples (n ¼ 954/1814 in the discovery step, 735/736 in replication 1, and 736/735 in replication 2) were tested for association with SNPs located within 4 Mb intervals surrounding each gene from a list of 111 iron-related genes using a discovery threshold of P ¼ 5 Â 10 À4 . Two population cohorts (KORA F3 and F4 with together n ¼ 3447) were tested for association of six known RLS loci with iron, ferritin, transferrin, transferrin-saturation, and soluble transferrin receptor. Results were negative. None of the candidate SNPs at the iron-related gene loci was confirmed significantly. An intronic SNP, rs2576036, of KATNAL2 at 18q21.1 was significant in the first (P ¼ 0.00085) but not in the second replication step (joint nominal P-value ¼ 0.044). Especially, rs1800652 (C282Y) in the HFE gene did not associate with RLS. Moreover, SNPs at the known RLS loci did not significantly affect serum iron parameters in the KORA cohorts. In conclusion, the correlation between RLS and iron parameters in serum may be weaker than assumed. Moreover, in a general power analysis, we show that genetic effects are diluted if they are transmitted via an intermediate trait to an end-phenotype. Sample size formulas are provided for small effect sizes. Keywords: restless legs syndrome; iron parameters; MEIS1 haplotype; power calculation; linear regression; logistic regression INTRODUCTIONRestless legs syndrome (RLS) 1 is a sensory-motor disorder characterized by an urge to move and unpleasant sensations in the lower limbs at rest. In Caucasians, RLS is present in up to 10% of the population. 2,3 Pregnancy, uremia, celiac disease, and iron deficiency are considered to be risk factors. 4 RLS also has a considerable heritability and is associated with multiple genetic risk factors. Genome-wide association studies 5-10 identified variants in six loci encompassing the genes MEIS1, BTBD9, MAP2K5/SKOR1, PTPRD, and TOX3/non-coding RNA.Aiming for the identification of further genetic risk factors of RLS, we addressed the apparent relation of RLS susceptibility to iron metabolism and iron availability 11 that has been explained by cerebral iron being crucial in the etiology of RLS. 12 We therefore tested the SNPs at the loci of a candidate set of genes known to be involved in iron metabolism for association with RLS. Vice versa, we asked whether RLS genes are involved in iron metabolism because the RLSassociated SNP rs3923809 at the BTBD9 locus has previously been reported to be associated with the serum level of ferritin in a study on RLS subjects and their relatives. 6

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“…20 (3) Linkage analysis of a recessive phenotype may unravel a variant of low penetrance in the heterozygote state (for example, the C282Y mutation of the hemochromatosis gene HFE). 21,22 The genetic architecture of traits and diseases thus governs the method and the expenditure to be used for their analyses. General assumptions on the architecture of multifactorial diseases have been made before.…”

Section: Discussionmentioning

confidence: 99%

A remark on rare variants

Oexle

2010

J Hum Genet

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The genetic architecture of a disease determines the epidemiological methods for its examination. Recently, Bodmer and Bonilla suggested that moderately strong, moderately rare variants contribute substantially to the genetic population attributable risk (PAR) of common diseases. In the first part of this communication, I provide a concise reconstruction of their deliberation. Variants contributing to human disease can be identified by linkage or by association tests. Risch and Merikangas analyzed the power of these tests by comparing the affected sib-pair linkage test (ASP) and the transmission disequilibrium association test (TDT). In the second part of this paper, I give an accessible reconstruction of this comparison and derive simple approximations in the low allele frequency range, directly showing that the linkage test is much more sensitive to a decrease of frequency or effect size. In the third part, I analyze a disease model whose genetic architecture is proportional to Kimura's infinite sites model. The relation between a variant's selection coefficient and its effect size in disease generation is assumed to be simple, and the number of contributing genetic variants is determined by the sum of their approximative PAR contributions. An association test (TDT) is finally applied to this disease model. For different ranges of effect size and allele frequency, I derive the minimal sample size necessary to detect at least one contributing variant. It turns out that, although the majority of contributing variants is not accessible with realistic sample sizes, a minimum of sample size may be given for moderately strong variants in the 1% frequency range.

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Effects of HFE C282Y and H63D Polymorphisms and Polygenic Background on Iron Stores in a Large Community Sample of Twins

Cited by 154 publications

References 41 publications

A population-based study of the effect of the HFE C282Y and H63D mutations on iron metabolism

A population-based study of the effect of the HFE C282Y and H63D mutations on iron metabolism

Dilution of candidates: the case of iron-related genes in restless legs syndrome

A remark on rare variants

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