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Evaluation of in silico predictors on short nucleotide variants in HBA1, HBA2 and HBB associated with haemoglobinopathies

View ORCID ProfileStella Tamana, View ORCID ProfileMaria Xenophontos, View ORCID ProfileAnna Minaidou, View ORCID ProfileCoralea Stephanou, View ORCID ProfileCornells L. Harteveld, Celeste Bento, Joanne Traeger-Synodinos, View ORCID ProfileIrene Fylaktou, Norafiza Mohd Yasin, Faidatul Syazlin Abdul Hamid, Ezalia Esa, Hashim Halim-Fikri, Bin Alwi Zilfalil, Andrea C. Kakouri, ClinGen Hemoglobinopathy VCEP, Marina Kleanthous, View ORCID ProfilePetros Kountouris
doi: https://doi.org/10.1101/2022.04.07.484934
Stella Tamana
1Molecular Genetics Thalassaemia Department, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
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Maria Xenophontos
1Molecular Genetics Thalassaemia Department, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
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Anna Minaidou
1Molecular Genetics Thalassaemia Department, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
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Coralea Stephanou
1Molecular Genetics Thalassaemia Department, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
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Cornells L. Harteveld
2Leiden University Medical Center, Leiden, Netherlands
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Celeste Bento
3Centro Hospitalare Universitário de Coimbra, Coimbra, Portugal
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Joanne Traeger-Synodinos
4Laboratory of Medical Genetics, National and Kapodistrian University of Athens, Athens, Greece
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Irene Fylaktou
5Division of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, National and Kapodistrian University of Athens, Athens, Greece
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  • ORCID record for Irene Fylaktou
Norafiza Mohd Yasin
6Haematology Unit, Cancer Research Centre (CaRC), Institute for Medical Research (IMR), National Health of Institutes (NIH), Ministry of Health Malaysia (MOH), Selangor, Malaysia
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Faidatul Syazlin Abdul Hamid
6Haematology Unit, Cancer Research Centre (CaRC), Institute for Medical Research (IMR), National Health of Institutes (NIH), Ministry of Health Malaysia (MOH), Selangor, Malaysia
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Ezalia Esa
6Haematology Unit, Cancer Research Centre (CaRC), Institute for Medical Research (IMR), National Health of Institutes (NIH), Ministry of Health Malaysia (MOH), Selangor, Malaysia
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Hashim Halim-Fikri
7Malaysian Node of the Human Variome Project (MyHVP), School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia
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Bin Alwi Zilfalil
8Human Genome Centre, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia
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Andrea C. Kakouri
1Molecular Genetics Thalassaemia Department, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
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Marina Kleanthous
1Molecular Genetics Thalassaemia Department, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
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Petros Kountouris
1Molecular Genetics Thalassaemia Department, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
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  • ORCID record for Petros Kountouris
  • For correspondence: petrosk@cing.ac.cy
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Abstract

Introduction Haemoglobinopathies are the commonest monogenic diseases worldwide and are caused by variants in the globin gene clusters. With over 2400 variants detected to date, their interpretation using the ACMG/AMP guidelines is challenging, with computational evidence able to provide valuable input about their functional annotation. While many in silico predictors have already been developed, their performance varies for different genes and diseases.

Materials and Methods We evaluate 31 in silico predictors using a dataset of 1627 variants in HBA1, HBA2, and HBB. Through varying the decision threshold for each tool, we analyse their performance (a) as binary classifiers of pathogenicity, and (b) using different nonoverlapping pathogenic and benign thresholds for their optimal use in the ACMG/AMP framework.

Results CADD, Eigen-PC, and REVEL are the overall top performers, with the former reaching moderate strength level for pathogenic prediction. Eigen-PC and REVEL achieve the highest accuracies for missense variants, while CADD is also a reliable predictor of nonmissense variants. Moreover, SpliceAl is the top performing splicing predictor, reaching strong level of evidence, while GERP++ and phyloP are the most accurate conservation tools.

Discussion This study provides evidence about the optimal use of computational evidence in globin gene clusters under the ACMG/AMP framework.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵‡ Joint first authorship

  • ↵§ Joint last authorship

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 09, 2022.
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Evaluation of in silico predictors on short nucleotide variants in HBA1, HBA2 and HBB associated with haemoglobinopathies
Stella Tamana, Maria Xenophontos, Anna Minaidou, Coralea Stephanou, Cornells L. Harteveld, Celeste Bento, Joanne Traeger-Synodinos, Irene Fylaktou, Norafiza Mohd Yasin, Faidatul Syazlin Abdul Hamid, Ezalia Esa, Hashim Halim-Fikri, Bin Alwi Zilfalil, Andrea C. Kakouri, ClinGen Hemoglobinopathy VCEP, Marina Kleanthous, Petros Kountouris
bioRxiv 2022.04.07.484934; doi: https://doi.org/10.1101/2022.04.07.484934
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Evaluation of in silico predictors on short nucleotide variants in HBA1, HBA2 and HBB associated with haemoglobinopathies
Stella Tamana, Maria Xenophontos, Anna Minaidou, Coralea Stephanou, Cornells L. Harteveld, Celeste Bento, Joanne Traeger-Synodinos, Irene Fylaktou, Norafiza Mohd Yasin, Faidatul Syazlin Abdul Hamid, Ezalia Esa, Hashim Halim-Fikri, Bin Alwi Zilfalil, Andrea C. Kakouri, ClinGen Hemoglobinopathy VCEP, Marina Kleanthous, Petros Kountouris
bioRxiv 2022.04.07.484934; doi: https://doi.org/10.1101/2022.04.07.484934

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