Genetics of inborn errors of immunity: Diagnostic strategies and new approaches to CNV detection

Background Genetic diagnosis of inborn errors of immunity (IEI) is complex due to the large number of genes involved and their molecular features. Missense variants have been reported as the most common cause of IEI. However, the frequency of copy number variants (CNVs) may be underestimated since t...

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Published in:European journal of clinical investigation 2024-06, Vol.54 (6), p.e14191-n/a
Main Authors: Pérez, Elisabet Matas, Torbay, Andrea González, López, Mario Solis, Cámara, Ricardo Cuesta Martín, Jiménez, Carmen Rodríguez, Álvarez, Mari Ángeles Mori, Blanco, Julián Nevado, Gianelli, Carla, Hijón, Carmen Cámara, Granados, Eduardo López, Pena, Rebeca Rodríguez, Pozo Mate, Ángela, García‐Morato, María Bravo
Format: Article
Language:English
Subjects:
Algorithms
Child
CNVs
Copy number
deletions
Diagnosis
DNA Copy Number Variations - genetics
Errors
Family studies
Female
genetic diagnosis
Genetic screening
Genetics
High-Throughput Nucleotide Sequencing
Humans
inborn errors of immunity (IEI)
Male
Mutation, Missense - genetics
Next-generation sequencing
Nucleotides
Polymorphism, Single Nucleotide
primary immune deficiency diseases (PIDDs)
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Summary:Background Genetic diagnosis of inborn errors of immunity (IEI) is complex due to the large number of genes involved and their molecular features. Missense variants have been reported as the most common cause of IEI. However, the frequency of copy number variants (CNVs) may be underestimated since their detection requires specific quantitative techniques. At this point, the use of Next Generation Sequencing (NGS) is acquiring relevance. Methods In this article, we present our experience in the genetic diagnosis of IEI based on three diagnostic algorithms that allowed the detection of single nucleotide variants (SNVs) and CNVs. Following this approximation, 703 index cases were evaluated between 2014 and 2021. Sanger sequencing, MLPA, CGH array, breakpoint spanning PCR or a customized NGS‐based multigene‐targeted panel were performed. Results A genetic diagnosis was reached in 142 of the 703 index cases (20%), 19 of them presented deletions as causal variants. Deletions were also detected in 5 affected relatives and 16 healthy carriers during the family studies. Additionally, we compile, characterize and present all the CNVs detected by our diagnostic algorithms, representing the largest cohort of deletions related to IEI to date. Furthermore, three bioinformatic tools (LACONv, XHMM, VarSeq™) based on NGS data were evaluated. VarSeq™ was the most sensitive and specific bioinformatic tool; detecting 21/23 (91%) deletions located in captured regions. Conclusion Based on our results, we propose a strategy to guide the molecular diagnosis that can be followed by expert and non‐expert centres in the field of IEI. The diagnosis of IEI is complex due to the clinical overlap, the presence of pseudogenes and the difficult detection of CNVs that requires quantitative techniques. In our centre, 703 patients with an IEI suspicion were evaluated: 142 were diagnosed, of whom 19 had a causative CNV. We characterized these CNVs and compared the sensitivity and specificity of MLPA, CHG array and NGS for the detection of CNVS. Finally, we propose a genetic algorithm for the evaluation of IEI suspicions.
ISSN:0014-2972
1365-2362
DOI:10.1111/eci.14191