HFE (hemochromatosis)

Dorak, MT

doi:10.4267/2042/44377

Cited by 3 publications

(5 citation statements)

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“…HFE encompasses 9,609 bp of DNA on chromosome 6p within the extended HLA class I region. Histone genes are present on both sides of HFE [39]. Exon 1 corresponds to the signal peptide and exons 2–4 to the α1, α2, and α3 domains, respectively.…”

Section: Hfe Gene Structurementioning

confidence: 99%

“…The cytoplasmic tail is encoded by the 5’ portion of exon 6 that includes a native stop codon. Thus, the full-length transcript represents 6 exons [39].…”

Section: Hfe Gene Structurementioning

confidence: 99%

“…HFE expression is subjected to alternative splicing [44–47], like other MHC class I proteins [48,49]. Nine HFE splicing variants have been reported [39]. The predominant HFE full-length transcript is ~4.2 kb [47,50].…”

Section: Hfe Gene Structurementioning

confidence: 99%

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HFE gene: Structure, function, mutations, and associated iron abnormalities

Barton

Edwards

Acton

2015

Gene

111

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The hemochromatosis gene HFE was discovered in 1996, more than a century after clinical and pathologic manifestations of hemochromatosis were reported. Linked to the major histocompatibility complex (MHC) on chromosome 6p, HFE encodes the MHC class I-like protein HFE that binds beta-2 microglobulin. HFE influences iron absorption by modulating the expression of hepcidin, the main controller of iron metabolism. Common HFE mutations account for ~90% of hemochromatosis phenotypes in whites of western European descent. We review HFE mapping and cloning, structure, promoters and controllers, and coding region mutations, HFE protein structure, cell and tissue expression and function, mouse Hfe knockouts and knockins, and HFE mutations in other mammals with iron overload. We describe the pertinence of HFE and HFE to mechanisms of iron homeostasis, the origin and fixation of HFE polymorphisms in European and other populations, and the genetic and biochemical basis of HFE hemochromatosis and iron overload.

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Section: Hfe Gene Structurementioning

confidence: 99%

“…The cytoplasmic tail is encoded by the 5’ portion of exon 6 that includes a native stop codon. Thus, the full-length transcript represents 6 exons [39].…”

Section: Hfe Gene Structurementioning

confidence: 99%

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HFE gene: Structure, function, mutations, and associated iron abnormalities

Barton

Edwards

Acton

2015

Gene

111

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“…HFE has seven exons of 12 kb [39]. HFE includes 9.6 kb of DNA on chromosome 6p in the extended region of HLA class I. Histone genes on both sides of HFE are present [50]. Exon 1 corresponds to the peptide of the signal and exons 2-4, respectively, to the domains α1, α2, and α3.…”

Section: Structure and Function Of Hfe Gene Humanmentioning

confidence: 99%

Serum Hepcidin Hormone Level and Its Genes Polymorphism

Faraj¹,

Al-Abedy²

2021

Genetic Variation

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This chapter sheds light on hepcidin, historical view of hepcidin, and the time of its discovery in the first section. Then this chapter gives information about the genetic aspect and the importance of gene knowledge of hepcidin in explaining many disorders in human beings, supported by illustration figures. The regulation of iron in the human body as an essential function of hepcidin is discussed in this chapter. Examples of the genes of hepcidin (HAMP and HFE) are highlighted in detail as they are essential in regulating iron as well as discussing the genetic mutations that occur in these genes and their medical and clinical impacts for many diseases such as thalassemia. Finally, the inherited disorders related to hepcidin that lead to genetic diseases are discussed.

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“…Iron overload is a serious condition caused by hereditary hemochromatosis or secondary to chronic blood transfusions received for the management of hematologic diseases such as sickle cell disease or beta‐thalassemia, or as part of cancer treatment 1,2 . Iron overload can cause hepatic fibrosis and cirrhosis, hepatocellular carcinoma, cardiac problems, and other organ dysfunctions if untreated 1,3 . Liver iron stores increase proportionally with total body iron, so assessing hepatic iron content (HIC) is an effective way of monitoring iron overload for treatment management 4 .…”

Section: Introductionmentioning

confidence: 99%

Simulation of a virtual liver iron overload model and R₂* estimation using multispectral fat–water models for GRE and UTE acquisitions at 1.5 T and 3 T

et al. 2023

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R2*‐MRI has emerged as a noninvasive alternative to liver biopsy for assessment of hepatic iron content (HIC). Multispectral fat–water R2* modeling techniques such as the nonlinear least squares (NLSQ) fitting and autoregressive moving average (ARMA) models have been proposed for the accurate assessment of iron overload by also considering fat, which can otherwise confound R2*‐based HIC measurements in conditions of coexisting iron overload and steatosis. However, the R2* estimation by these multispectral models has not been systematically investigated for various acquisition methods in iron overload only conditions and across the full clinically relevant range of HICs (0–40 mg Fe/g dry liver weight). The purpose of this study is to evaluate the R2* accuracy and precision of multispectral models for various multiecho gradient echo (GRE) and ultrashort echo time (UTE) imaging acquisitions by constructing virtual iron overload models based on true histology and synthesizing MRI signals via Monte Carlo simulations at 1.5 T and 3 T, and comparing their results with monoexponential model and published in vivo R2*–HIC calibrations. The signals were synthesized with TE1 = 1.0 ms for GRE and TE1 = 0.1 ms for UTE acquisition for varying echo spacing, ΔTE (0.1, 0.5, 1, 2 ms), and maximum echo time, TEmax (2, 4, 6, 10 ms). An iron‐doped phantom study is also conducted to validate the simulation results in experimental GRE (TE1 = 1.2 ms, ΔTE = 0.72 ms, TEmax = 6.24 ms) and UTE (TE1 = 0.1 ms, ΔTE = 0.5 ms, TEmax = 6.1 ms) acquisitions. For GRE acquisitions, the multispectral ARMA and NLSQ models produced higher slopes (0.032–0.035) compared with the monoexponential model and published in vivo R2*–HIC calibrations (0.025–0.028). However, for UTE acquisition for shorter echo spacing (≤0.5 ms) and longer maximum echo time, TEmax (≥6 ms), the multispectral and monoexponential signal models produced similar R2*–HIC slopes (1.5 T, 0.028–0.032; 3 T, 0.014–0.016) and precision values (coefficient of variation < 25%) across the full clinical spectrum of HICs at both 1.5 T and 3 T. The phantom analysis also showed that all signal models demonstrated a significant improvement in R2* estimation for UTE acquisition compared with GRE, confirming our simulation findings. Future work should investigate the performance of multispectral fat–water models by simulating liver models in coexisting conditions of iron overload and steatosis for accurate R2* and fat quantification.

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HFE (hemochromatosis)

Abstract: This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 France Licence.

Cited by 3 publications

References 0 publications

HFE gene: Structure, function, mutations, and associated iron abnormalities

HFE gene: Structure, function, mutations, and associated iron abnormalities

Serum Hepcidin Hormone Level and Its Genes Polymorphism

Simulation of a virtual liver iron overload model and R₂* estimation using multispectral fat–water models for GRE and UTE acquisitions at 1.5 T and 3 T

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HFE (hemochromatosis)

Abstract: This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 France Licence.

Cited by 3 publications

References 0 publications

HFE gene: Structure, function, mutations, and associated iron abnormalities

HFE gene: Structure, function, mutations, and associated iron abnormalities

Serum Hepcidin Hormone Level and Its Genes Polymorphism

Simulation of a virtual liver iron overload model and R2* estimation using multispectral fat–water models for GRE and UTE acquisitions at 1.5 T and 3 T

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Simulation of a virtual liver iron overload model and R₂* estimation using multispectral fat–water models for GRE and UTE acquisitions at 1.5 T and 3 T