Isaac J Nijman1, Joris M van Montfrans2, Marlous Hoogstraat3, Marianne L Boes2, Lisette van de Corput4, Ellen D Renner5, Patrick van Zon1, Stef van Lieshout1, Martin G Elferink1, Mirjam van der Burg6, Clementien L Vermont7, Bert van der Zwaag1, Esther Janson1, Edwin Cuppen1, Johannes K Ploos van Amstel1, Marielle E van Gijn8. 1. Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands. 2. Department of Pediatric Immunology and Infectious Diseases, University Medical Center Utrecht, Utrecht, The Netherlands. 3. Department of Medical Oncology, University Medical Center Utrecht, Utrecht, The Netherlands. 4. Department of Immunology, University Medical Center Utrecht, Utrecht, The Netherlands. 5. Department of Immunology, University Children's Hospital, Ludwig-Maximilians-Universität, Munich, Germany. 6. Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands. 7. Department of Pediatric Infectious Diseases, Immunology and Stem Cell Transplantation, Leiden University Medical Center, Leiden, The Netherlands. 8. Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: m.e.vangijn@umcutrecht.nl.
Abstract
BACKGROUND: Primary immunodeficiency (PID) disorders are a heterogeneous group of inherited disorders caused by a variety of monogenetic immune defects. Thus far, mutations in more than 170 different genes causing PIDs have been described. A clear genotype-phenotype correlation is often not available, which makes a genetic diagnosis in patients with PIDs complex and laborious. OBJECTIVE: We sought to develop a robust, time-effective, and cost-effective diagnostic method to facilitate a genetic diagnosis in any of 170 known PID-related genes by using next-generation sequencing (NGS). METHODS: We used both targeted array-based and in-solution enrichment combined with a SOLiD sequencing platform and a bioinformatic pipeline developed in house to analyze genetic changes in the DNA of 41 patients with PIDs with known mutations and 26 patients with undiagnosed PIDs. RESULTS: This novel NGS-based method accurately detected point mutations (sensitivity and specificity >99% in covered regions) and exonic deletions (100% sensitivity and specificity). For the 170 genes of interest, the DNA coverage was greater than 20× in 90% to 95%. Nine PID-related genes proved not eligible for evaluation by using this NGS-based method because of inadequate coverage. The NGS method allowed us to make a genetic diagnosis in 4 of 26 patients who lacked a genetic diagnosis despite routine functional and genetic testing. Three of these patients proved to have an atypical presentation of previously described PIDs. CONCLUSION: This novel NGS tool facilitates accurate simultaneous detection of mutations in 161 of 170 known PID-related genes. In addition, these analyses will generate more insight into genotype-phenotype correlations for the different PID disorders.
BACKGROUND:Primary immunodeficiency (PID) disorders are a heterogeneous group of inherited disorders caused by a variety of monogenetic immune defects. Thus far, mutations in more than 170 different genes causing PIDs have been described. A clear genotype-phenotype correlation is often not available, which makes a genetic diagnosis in patients with PIDs complex and laborious. OBJECTIVE: We sought to develop a robust, time-effective, and cost-effective diagnostic method to facilitate a genetic diagnosis in any of 170 known PID-related genes by using next-generation sequencing (NGS). METHODS: We used both targeted array-based and in-solution enrichment combined with a SOLiD sequencing platform and a bioinformatic pipeline developed in house to analyze genetic changes in the DNA of 41 patients with PIDs with known mutations and 26 patients with undiagnosed PIDs. RESULTS: This novel NGS-based method accurately detected point mutations (sensitivity and specificity >99% in covered regions) and exonic deletions (100% sensitivity and specificity). For the 170 genes of interest, the DNA coverage was greater than 20× in 90% to 95%. Nine PID-related genes proved not eligible for evaluation by using this NGS-based method because of inadequate coverage. The NGS method allowed us to make a genetic diagnosis in 4 of 26 patients who lacked a genetic diagnosis despite routine functional and genetic testing. Three of these patients proved to have an atypical presentation of previously described PIDs. CONCLUSION: This novel NGS tool facilitates accurate simultaneous detection of mutations in 161 of 170 known PID-related genes. In addition, these analyses will generate more insight into genotype-phenotype correlations for the different PID disorders.
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