Targeted next-generation sequencing in the molecular diagnosis of hereditary hemochromatosis

Abstract Hereditary hemochromatosis (HH) is a genetic disorder of iron metabolism characterized by excessive iron accumulation and considerable phenotypic variability, often making diagnosis challenging. This study aimed to identify pathogenic variants associated with HH using targeted next-generation sequencing (NGS). In addition, we investigated rare and novel genetic variants to improve diagnostic accuracy and support more personalized patient management strategies. A targeted NGS panel encompassing 12 genes involved in HH and iron homeostasis was applied. Variant interpretation followed the American College of Medical Genetics and Genomics (ACMG) guidelines, with all findings confirmed by PCR–Sanger sequencing. Structural analyses were conducted exclusively for variants of uncertain significance (VUS) using AlphaFold3 and visualized in PyMOL. Pathogenic variants were detected, notably the established HJV- p.Gly320Val variant, supporting a diagnosis of juvenile HH. An ultra-rare variant of uncertain significance, ERFE -c.478G > A (p.Ala160Thr), was also identified, with structural modeling indicating potential alterations that could affect protein function. Additionally, the established SLC40A1 -p.Arg178Gln variant was detected in a control sample, validating the robustness of the methodology. Overall, these results highlight the utility of targeted NGS and structural modeling in improving diagnostic accuracy and enabling precision medicine approaches in HH.

Authors

Institutions

Publication Details

Journal
Annals of Hematology
Published
2026-09-12
DOI
https://doi.org/10.1007/s00277-026-07269-6
Primary Topic
Iron Metabolism and Disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Targeted next-generation sequencing in the molecular diagnosis of hereditary hemochromatosis

Styliani Sarrou, Eleni Papchianou, Alexia Matziri, Fani Kalala et al.
Annals of Hematology
Iron Metabolism and Disorders
article

Targeted next-generation sequencing in the molecular diagnosis of hereditary hemochromatosis

Styliani Sarrou, Eleni Papchianou, Alexia Matziri, Fani Kalala, Kalliopi Zachou, Achilleas P. Galanopoulos, Anna Kioumi, Chrysoula Apostolou, George Dalekos, Matthaios Speletas, Vasiliki Galani, Christos Hadjichristodoulou, Dimitrios Fotios Gkousiaris
article en

Abstract

Abstract Hereditary hemochromatosis (HH) is a genetic disorder of iron metabolism characterized by excessive iron accumulation and considerable phenotypic variability, often making diagnosis challenging. This study aimed to identify pathogenic variants associated with HH using targeted next-generation sequencing (NGS). In addition, we investigated rare and novel genetic variants to improve diagnostic accuracy and support more personalized patient management strategies. A targeted NGS panel encompassing 12 genes involved in HH and iron homeostasis was applied. Variant interpretation followed the American College of Medical Genetics and Genomics (ACMG) guidelines, with all findings confirmed by PCR–Sanger sequencing. Structural analyses were conducted exclusively for variants of uncertain significance (VUS) using AlphaFold3 and visualized in PyMOL. Pathogenic variants were detected, notably the established HJV- p.Gly320Val variant, supporting a diagnosis of juvenile HH. An ultra-rare variant of uncertain significance, ERFE -c.478G > A (p.Ala160Thr), was also identified, with structural modeling indicating potential alterations that could affect protein function. Additionally, the established SLC40A1 -p.Arg178Gln variant was detected in a control sample, validating the robustness of the methodology. Overall, these results highlight the utility of targeted NGS and structural modeling in improving diagnostic accuracy and enabling precision medicine approaches in HH.

Annals of Hematology
University of Thessaly (GR), Papageorgiou General Hospital (GR)
Good health and well-being
Openalex Percentile: Top 10%
Iron Metabolism and Disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.