OBJECTIVES: Systemic auto-inflammatory disorders (SAIDs) are a heterogeneous group of monogenic diseases sharing a primary dysfunction of the innate immune system. More than 50% of patients with SAID does not show any mutation at gene(s) tested because of lack of precise clinical classification criteria and/or incomplete gene screening. To improve the molecular diagnosis and genotype interpretation of SAIDs, we undertook the development of a next-generation sequencing (NGS)-based protocol designed to simultaneous screening of 10 genes. METHODS: Fifty patients with SAID, already genotyped for the respective causative gene(s), were massively sequenced for the coding portions of MEFV, MVK, TNFRSF1A, NLRP3, NLRP12, NOD2, PSTPIP1, IL1RN, LPIN2 and PSMB8. Three different bioinformatic pipelines (Ion Reporter, CLC Bio Genomics Workbench, GATK-based in-house workflow) were compared. RESULTS: Once resulting variants were compared with the expected mutation list, no workflow turned out to be able to detect all the 79 variants known in the 50 DNAs. Additional variants were also detected, validated by Sanger sequencing and compared to assess true and false positive detection rates of the three workflows. Finally, the overall clinical picture of 34 patients was re-evaluated in the light of the new mutations found. CONCLUSIONS: The present gene panel has resulted suitable for molecular diagnosis of SAIDs. Moreover, genotype-phenotype correlation has confirmed that the interpretation of NGS data in patients with an undefined inflammatory phenotype is remarkably difficult, thus supporting the need of evidence-based and validated clinical criteria to be used concurrently with the genetic analysis for the final diagnosis and classification of patients with SAIDs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Next-generation sequencing and its initial applications for molecular diagnosis of systemic auto-inflammatory diseases

Tommasini A;
2016-01-01

Abstract

OBJECTIVES: Systemic auto-inflammatory disorders (SAIDs) are a heterogeneous group of monogenic diseases sharing a primary dysfunction of the innate immune system. More than 50% of patients with SAID does not show any mutation at gene(s) tested because of lack of precise clinical classification criteria and/or incomplete gene screening. To improve the molecular diagnosis and genotype interpretation of SAIDs, we undertook the development of a next-generation sequencing (NGS)-based protocol designed to simultaneous screening of 10 genes. METHODS: Fifty patients with SAID, already genotyped for the respective causative gene(s), were massively sequenced for the coding portions of MEFV, MVK, TNFRSF1A, NLRP3, NLRP12, NOD2, PSTPIP1, IL1RN, LPIN2 and PSMB8. Three different bioinformatic pipelines (Ion Reporter, CLC Bio Genomics Workbench, GATK-based in-house workflow) were compared. RESULTS: Once resulting variants were compared with the expected mutation list, no workflow turned out to be able to detect all the 79 variants known in the 50 DNAs. Additional variants were also detected, validated by Sanger sequencing and compared to assess true and false positive detection rates of the three workflows. Finally, the overall clinical picture of 34 patients was re-evaluated in the light of the new mutations found. CONCLUSIONS: The present gene panel has resulted suitable for molecular diagnosis of SAIDs. Moreover, genotype-phenotype correlation has confirmed that the interpretation of NGS data in patients with an undefined inflammatory phenotype is remarkably difficult, thus supporting the need of evidence-based and validated clinical criteria to be used concurrently with the genetic analysis for the final diagnosis and classification of patients with SAIDs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2954299
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