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Updated: Oct 23, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Genetic Diagnosis in Hereditary Hemochromatosis: Discovering and Understanding the Biological Relevance of Variants
Floor S Baas1,2, Gautam Rishi2, Dorine W Swinkels1
1Translational Metabolic Laboratory (TML 831), Radboudumc, Nijmegen, the Netherlands.
Background:
Hereditary hemochromatosis (HH) is a genetic disease, leading to iron accumulation and possible organ damage. Patients are usually homozygous for p. Cys282Tyr in the homeostatic iron regulator gene but may have mutations in other genes involved in the regulation of iron. Next-generation sequencing is increasingly being utilized for the diagnosis of patients, leading to the discovery of novel genetic variants. The clinical significance of these variants is often unknown.
Content:
Determining the pathogenicity of such variants of unknown significance is important for diagnostics and genetic counseling. Predictions can be made using in silico computational tools and population data, but additional evidence is required for a conclusive pathogenicity classification. Genetic disease models, such as in vitro models using cellular overexpression, induced pluripotent stem cells or organoids, and in vivo models using mice or zebrafish all have their own challenges and opportunities when used to model HH and other iron disorders. Recent developments in gene-editing technologies are transforming the field of genetic disease modeling.
Summary:
In summary, this review addresses methods and developments regarding the discovery and classification of genetic variants, from in silico tools to in vitro and in vivo models, and presents them in the context of HH. It also explores recent gene-editing developments and how they can be applied to the discussed models of genetic disease.
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