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      The Utility of Next-Generation Sequencing for Primary Immunodeficiency Disorders: Experience from a Clinical Diagnostic Laboratory

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          Abstract

          Introduction

          Primary immune deficiency disorders (PIDs) are a group of diseases with profound defects in immune cells. The traditional diagnostics have evolved from clinical evaluation, flow cytometry, western blotting, and Sanger sequencing to focusing on small groups of genes. However, this is not sufficient to confirm the suspicion of certain PIDs. Our innovative approach to diagnostics outlines the algorithm for PIDs and the clinical utility of immunophenotyping with a custom-designed multigene panel.

          Materials and Methods

          We have designed a diagnostic algorithm based on flow cytometry studies to classify the patients; then the selected multigene panel was sequenced. In silico analysis for mutations was carried out using SIFT, Polyphen-2, and MutationTaster.

          Results and Discussion

          The causative mutation was identified in 46% of PIDs. Based on these results, this new algorithm including immune phenotyping and NGS for PIDs was suggested for the clinical use.

          Conclusions

          This study provides a thorough validation of diagnostic algorithm and indicates that still the traditional methods can be used to collect significant information related to design of most current diagnostics. The benefits of such testing are for diagnosis and prevention including the prenatal and preimplantation diagnosis, prognosis, treatment, and research.

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          Most cited references8

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          Flow cytometry-based diagnosis of primary immunodeficiency diseases

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            Targeted NGS: A Cost-Effective Approach to Molecular Diagnosis of PIDs

            Background: Primary immunodeficiencies (PIDs) are a diverse group of disorders caused by multiple genetic defects. Obtaining a molecular diagnosis for PID patients using a phenotype-based approach is often complex, expensive, and not always successful. Next-generation sequencing (NGS) methods offer an unbiased genotype-based approach, which can facilitate molecular diagnostics. Objective: To develop an efficient NGS method to identify variants in PID-related genes. Methods: We performed HaloPlex custom target enrichment and NGS using the Ion Torrent PGM to screen 173 genes in 11 healthy controls, 13 PID patients previously evaluated with either an identified mutation or SNP, and 120 patients with undiagnosed PIDs. Sensitivity and specificity were determined by comparing NGS and Sanger sequencing results for 33 patients. Run metrics and coverage analyses were done to identify systematic deficiencies. Results: A molecular diagnosis was identified for 18 of 120 patients who previously lacked a genetic diagnosis, including 9 who had atypical presentations and extensive previous genetic and functional studies. Our NGS method detected variants with 98.1% sensitivity and >99.9% specificity. Uniformity was variable (72–89%), and we were not able to reliably sequence 45 regions (45/2455 or 1.8% of total regions) due to low (<20) average read depth or <90% region coverage; thus, we optimized probe hybridization conditions to improve read-depth and coverage for future analyses, and established criteria to help identify true positives. Conclusion: While NGS methods are not as sensitive as Sanger sequencing for individual genes, targeted NGS is a cost-effective, first-line genetic test for the evaluation of patients with PIDs. This approach decreases time to diagnosis, increases diagnostic rate, and provides insight into the genotype–phenotype correlation of PIDs in a cost-effective way.
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              Clinical efficacy of a next-generation sequencing gene panel for primary immunodeficiency diagnostics

              Primary immunodeficiencies (PIDs) are rare monogenic inborn errors of immunity that result in impairment of functions of the human immune system. PIDs have a broad phenotype with increased morbidity and mortality, and treatment choices are often complex. With increased accessibility of next-generation sequencing (NGS), the rate of discovery of genetic causes for PID has increased exponentially. Identification of an underlying monogenic diagnosis provides important clinical benefits for patients with the potential to alter treatments, facilitate genetic counselling, and pre-implantation diagnostics. We investigated a NGS PID panel of 242 genes within clinical care across a range of PID phenotypes. We also evaluated Phenomizer to predict causal genes from human phenotype ontology (HPO) terms. Twenty-seven participants were recruited, and a total of 15 reportable variants were identified in 48% (13/27) of the participants. The panel results had implications for treatment in 37% (10/27) of participants. Phenomizer identified the genes harbouring variants from HPO terms in 33% (9/27) of participants. This study shows the clinical efficacy that genetic testing has in the care of PID. However, it also highlights some of the disadvantages of gene panels in the rapidly moving field of PID genomics and current challenges in HPO term assignment for PID.
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                Author and article information

                Contributors
                Journal
                Biomed Res Int
                Biomed Res Int
                BMRI
                BioMed Research International
                Hindawi
                2314-6133
                2314-6141
                2018
                16 May 2018
                : 2018
                : 9647253
                Affiliations
                1Medical Genetics Department, Balcali Clinics and Hospital, Faculty of Medicine, Cukurova University, Adana, Turkey
                2Cukurova University Adana Genetic Diseases Diagnosis and Treatment Center (AGENTEM), Adana, Turkey
                3Division of Pediatric Allergy & Immunology, Faculty of Medicine, Cukurova University, Adana, Turkey
                Author notes

                Academic Editor: Marija Mostarica-Stojković

                Author information
                http://orcid.org/0000-0002-2053-9076
                Article
                10.1155/2018/9647253
                5977064
                29888287
                243e22f5-30cf-4bde-825e-fd12a4ea6310
                Copyright © 2018 Atil Bisgin et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 December 2017
                : 6 March 2018
                : 1 April 2018
                Funding
                Funded by: Cukurova University
                Award ID: TAY-2016-4020
                Categories
                Research Article

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