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Neirinck J, Buysse M, De Vriendt C, Hofmans M, Bonroy C. The role of immunophenotyping in common variable immunodeficiency: a narrative review. Crit Rev Clin Lab Sci 2024:1-20. [PMID: 39364936 DOI: 10.1080/10408363.2024.2404842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Revised: 08/06/2024] [Accepted: 09/12/2024] [Indexed: 10/05/2024]
Abstract
Common variable immunodeficiency (CVID) is a heterogeneous primary immunodeficiency (PID) characterized by an impaired immunoglobulin production, in association with an increased susceptibility to infections and a diversity of clinical manifestations. This narrative review summarizes immunophenotypic abnormalities in CVID patients and their relevance for diagnosis and disease classification. A comprehensive search across four databases - PubMED, Web of Science, EMBASE and Google Scholar - yielded 170 relevant studies published between 1988 and April 31, 2023. Over the past decades, the role of immunophenotyping in CVID diagnosis has become evident by identifying "hallmark" immunophenotypic aberrancies in patient subsets, with some now integrated in the consensus diagnostic criteria. Furthermore, the role of immunophenotyping in subclassifying CVID in relation to clinical presentation and prognosis has been extensively studied. Certain immunophenotypic patterns consistently correlate with clinical manifestations and/or subsets of CVID, particularly those associated with noninfectious complications (i.e. low switched memory B cells, shifts in follicular helper T cell subsets, low naïve CD4+ T cells, low regulatory T cells, and expansion of CD21low B cells, often associated with autoimmunity and/or splenomegaly). Also, efforts to associate subset levels of innate immune cells, such as Natural Killer (NK) cells, invariant (i)NKT cells, innate lymphoid cells (ILCs), and dendritic cells (DCs) to CVID complications are evident albeit in a lesser degree. However, inconsistencies regarding the role of flow cytometry in classification and prognosis persist, reflecting the disease complexity, but probably also cohort variations and methodological differences between published studies. This underscores the need for collaborative efforts to integrate emerging concepts, such as standardized flow cytometry and computational tools, for a more precise CVID classification approach. Additionally, recent studies suggest a potential value of (epi)genetic-based molecular assays to this effort.
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Affiliation(s)
- Jana Neirinck
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Malicorne Buysse
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Ciel De Vriendt
- Department of Haematology, University Hospital Ghent, Ghent, Belgium
| | - Mattias Hofmans
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Carolien Bonroy
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
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Neirinck J, Emmaneel A, Buysse M, Philippé J, Van Gassen S, Saeys Y, Bossuyt X, De Buyser S, van der Burg M, Pérez-Andrés M, Orfao A, van Dongen JJM, Lambrecht BN, Kerre T, Hofmans M, Haerynck F, Bonroy C. The Euroflow PID Orientation Tube in the diagnostic workup of primary immunodeficiency: Daily practice performance in a tertiary university hospital. Front Immunol 2022; 13:937738. [PMID: 36177024 PMCID: PMC9513319 DOI: 10.3389/fimmu.2022.937738] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 08/16/2022] [Indexed: 11/23/2022] Open
Abstract
Introduction Multiparameter flow cytometry (FCM) immunophenotyping is an important tool in the diagnostic screening and classification of primary immunodeficiencies (PIDs). The EuroFlow Consortium recently developed the PID Orientation Tube (PIDOT) as a universal screening tool to identify lymphoid-PID in suspicious patients. Although PIDOT can identify different lymphoid-PIDs with high sensitivity, clinical validation in a broad spectrum of patients with suspicion of PID is missing. In this study, we investigated the diagnostic performance of PIDOT, as part of the EuroFlow diagnostic screening algorithm for lymphoid-PID, in a daily practice at a tertiary reference center for PID. Methods PIDOT was tested in 887 consecutive patients suspicious of PID at the Ghent University Hospital, Belgium. Patients were classified into distinct subgroups of lymphoid-PID vs. non-PID disease controls (non-PID DCs), according to the IUIS and ESID criteria. For the clinical validation of PIDOT, comprehensive characterization of the lymphoid defects was performed, together with the identification of the most discriminative cell subsets to distinguish lymphoid-PID from non-PID DCs. Next, a decision-tree algorithm was designed to guide subsequent FCM analyses. Results The mean number of lymphoid defects detected by PIDOT in blood was 2.87 times higher in lymphoid-PID patients vs. non-PID DCs (p < 0.001), resulting in an overall sensitivity and specificity of 87% and 62% to detect severe combined immunodeficiency (SCID), combined immunodeficiency with associated or syndromic features (CID), immune dysregulation disorder (ID), and common variable immunodeficiency (CVID). The most discriminative populations were total memory and switched memory B cells, total T cells, TCD4+cells, and naive TCD4+cells, together with serum immunoglobulin levels. Based on these findings, a decision-tree algorithm was designed to guide further FCM analyses, which resulted in an overall sensitivity and specificity for all lymphoid-PIDs of 86% and 82%, respectively. Conclusion Altogether, our findings confirm that PIDOT is a powerful tool for the diagnostic screening of lymphoid-PID, particularly to discriminate (S)CID, ID, and CVID patients from other patients suspicious of PID. The combination of PIDOT and serum immunoglobulin levels provides an efficient guide for further immunophenotypic FCM analyses, complementary to functional and genetic assays, for accurate PID diagnostics.
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Affiliation(s)
- Jana Neirinck
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Annelies Emmaneel
- Data Mining and Modelling for Biomedicine Group, Vlaams Instituut voor Biotechnologie (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
| | - Malicorne Buysse
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Jan Philippé
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Sofie Van Gassen
- Data Mining and Modelling for Biomedicine Group, Vlaams Instituut voor Biotechnologie (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
| | - Yvan Saeys
- Data Mining and Modelling for Biomedicine Group, Vlaams Instituut voor Biotechnologie (VIB) Center for Inflammation Research, Ghent, Belgium
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
| | - Xavier Bossuyt
- Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium
- Department of Laboratory Medicine, KU Leuven University Hospitals Leuven, Leuven, Belgium
| | - Stefanie De Buyser
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Mirjam van der Burg
- Laboratory for Pediatric Immunology, Department of Pediatrics, Leiden University Medical Center, Leiden, Netherlands
| | - Martín Pérez-Andrés
- Cancer Research Centre (Instituto de Biología Molecular y Celular del Cáncer (IBMCC), USAL-CSIC; CIBERONC CB16/12/00400), Institute for Biomedical Research of Salamanca (IBSAL), Department of Medicine and Cytometry Service (NUCLEUS Research Support Platform), University of Salamanca (USAL), Salamanca, Spain
- Translational and Clinical Research Program, Centro de Investigación del Cáncer and Instituto de Biología Molecular y Celular del Cáncer, Consejo Superior de Investigaciones Científicas (CSIC)-University of Salamanca (USAL), Department of Medicine, IBSAL and Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), University of Salamanca, Salamanca, Spain
| | - Alberto Orfao
- Cancer Research Centre (Instituto de Biología Molecular y Celular del Cáncer (IBMCC), USAL-CSIC; CIBERONC CB16/12/00400), Institute for Biomedical Research of Salamanca (IBSAL), Department of Medicine and Cytometry Service (NUCLEUS Research Support Platform), University of Salamanca (USAL), Salamanca, Spain
- Translational and Clinical Research Program, Centro de Investigación del Cáncer and Instituto de Biología Molecular y Celular del Cáncer, Consejo Superior de Investigaciones Científicas (CSIC)-University of Salamanca (USAL), Department of Medicine, IBSAL and Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), University of Salamanca, Salamanca, Spain
| | | | - Bart N. Lambrecht
- Laboratory of Mucosal Immunology, VIB-UGhent Center for Inflammation Research, Ghent University, Ghent, Belgium
- Department of Internal Medicine and Pediatrics, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
- Department of Pulmonary Medicine, University Hospital Ghent, Ghent, Belgium
| | - Tessa Kerre
- Department of Hematology, Ghent University Hospital, Ghent, Belgium
| | - Mattias Hofmans
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Filomeen Haerynck
- Department of Pediatric Pulmonology and Immunology and Primary Immunodeficiency (PID) Research Lab, Ghent University Hospital, Ghent, Belgium
| | - Carolien Bonroy
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
- Department of Laboratory Medicine, Ghent University Hospital, Ghent, Belgium
- *Correspondence: Carolien Bonroy,
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Emmaneel A, Bogaert DJ, Van Gassen S, Tavernier SJ, Dullaers M, Haerynck F, Saeys Y. A Computational Pipeline for the Diagnosis of CVID Patients. Front Immunol 2019; 10:2009. [PMID: 31543876 PMCID: PMC6730493 DOI: 10.3389/fimmu.2019.02009] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 08/08/2019] [Indexed: 12/22/2022] Open
Abstract
Common variable immunodeficiency (CVID) is one of the most frequently diagnosed primary antibody deficiencies (PADs), a group of disorders characterized by a decrease in one or more immunoglobulin (sub)classes and/or impaired antibody responses caused by inborn defects in B cells in the absence of other major immune defects. CVID patients suffer from recurrent infections and disease-related, non-infectious, complications such as autoimmune manifestations, lymphoproliferation, and malignancies. A timely diagnosis is essential for optimal follow-up and treatment. However, CVID is by definition a diagnosis of exclusion, thereby covering a heterogeneous patient population and making it difficult to establish a definite diagnosis. To aid the diagnosis of CVID patients, and distinguish them from other PADs, we developed an automated machine learning pipeline which performs automated diagnosis based on flow cytometric immunophenotyping. Using this pipeline, we analyzed the immunophenotypic profile in a pediatric and adult cohort of 28 patients with CVID, 23 patients with idiopathic primary hypogammaglobulinemia, 21 patients with IgG subclass deficiency, six patients with isolated IgA deficiency, one patient with isolated IgM deficiency, and 100 unrelated healthy controls. Flow cytometry analysis is traditionally done by manual identification of the cell populations of interest. Yet, this approach has severe limitations including subjectivity of the manual gating and bias toward known populations. To overcome these limitations, we here propose an automated computational flow cytometry pipeline that successfully distinguishes CVID phenotypes from other PADs and healthy controls. Compared to the traditional, manual analysis, our pipeline is fully automated, performing automated quality control and data pre-processing, automated population identification (gating) and deriving features from these populations to build a machine learning classifier to distinguish CVID from other PADs and healthy controls. This results in a more reproducible flow cytometry analysis, and improves the diagnosis compared to manual analysis: our pipelines achieve on average a balanced accuracy score of 0.93 (±0.07), whereas using the manually extracted populations, an averaged balanced accuracy score of 0.72 (±0.23) is achieved.
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Affiliation(s)
- Annelies Emmaneel
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.,Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
| | - Delfien J Bogaert
- Primary Immunodeficiency Research Lab, Center for Primary Immunodeficiency Ghent, Jeffrey Modell Diagnosis and Research Center, Ghent University Hospital, Ghent, Belgium.,Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Sofie Van Gassen
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.,Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
| | - Simon J Tavernier
- Primary Immunodeficiency Research Lab, Center for Primary Immunodeficiency Ghent, Jeffrey Modell Diagnosis and Research Center, Ghent University Hospital, Ghent, Belgium.,Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium.,Unit of Molecular Signal Transduction in Inflammation, VIB Center for Inflammation Research, Ghent, Belgium
| | | | - Filomeen Haerynck
- Primary Immunodeficiency Research Lab, Center for Primary Immunodeficiency Ghent, Jeffrey Modell Diagnosis and Research Center, Ghent University Hospital, Ghent, Belgium.,Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
| | - Yvan Saeys
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.,Data Mining and Modeling for Biomedicine, VIB Center for Inflammation Research, Ghent, Belgium
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Huberty J, Eckert R, Dueck A, Kosiorek H, Larkey L, Gowin K, Mesa R. Online yoga in myeloproliferative neoplasm patients: results of a randomized pilot trial to inform future research. BMC COMPLEMENTARY AND ALTERNATIVE MEDICINE 2019; 19:121. [PMID: 31174535 PMCID: PMC6556039 DOI: 10.1186/s12906-019-2530-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 05/29/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND Myeloproliferative neoplasm (MPN) patients suffer from significant symptoms, inflammation and reduced quality of life. Yoga improves these outcomes in other cancers, but this hasn't been demonstrated in MPNs. The purpose of this study was to: (1) explore the limited efficacy (does the program show promise of success) of a 12-week online yoga intervention among MPN patients on symptom burden and quality of life and (2) determine feasibility (practicality: to what extent a measure can be carried out) of remotely collecting inflammatory biomarkers. METHODS Patients were recruited nationally and randomized to online yoga (60 min/week of yoga) or wait-list control (asked to maintain normal activity). Weekly yoga minutes were collected with Clicky (online web analytics tool) and self-report. Those in online yoga completed a blood draw at baseline and week 12 to assess inflammation (interleukin-6, tumor necrosis factor-alpha [TNF-α]). All participants completed questionnaires assessing depression, anxiety, fatigue, pain, sleep disturbance, sexual function, total symptom burden, global health, and quality of life at baseline, week seven, 12, and 16. Change from baseline at each time point was computed by group and effect sizes were calculated. Pre-post intervention change in inflammation for the yoga group was compared by t-test. RESULTS Sixty-two MPN patients enrolled and 48 completed the intervention (online yoga = 27; control group = 21). Yoga participation averaged 40.8 min/week via Clicky and 56.1 min/week via self-report. Small/moderate effect sizes were generated from the yoga intervention for sleep disturbance (d = - 0.26 to - 0.61), pain intensity (d = - 0.34 to - 0.51), anxiety (d = - 0.27 to - 0.37), and depression (d = - 0.53 to - 0.78). A total of 92.6 and 70.4% of online yoga participants completed the blood draw at baseline and week 12, respectively, and there was a decrease in TNF-α from baseline to week 12 (- 1.3 ± 1.5 pg/ml). CONCLUSIONS Online yoga demonstrated small effects on sleep, pain, and anxiety as well as a moderate effect on depression. Remote blood draw procedures are feasible and the effect size of the intervention on TNF-α was large. Future fully powered randomized controlled trials are needed to test for efficacy. TRIAL REGISTRATION This trial was retrospectively registered with clinicaltrials.gov (ID: NCT03503838 ) on 4/19/2018.
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Affiliation(s)
- Jennifer Huberty
- Exercise Science and Health Promotion, Arizona State University, 500 North 3rd Street Phoenix, Tempe, AZ 85004 USA
| | - Ryan Eckert
- Mays Cancer Center, University of Texas San Antonio MD Anderson, 7979 Wurzbach Road, San Antonio, TX 78229 USA
| | - Amylou Dueck
- Division of Biostatistics, Mayo Clinic, 13400 East Shea Boulevard, Scottsdale, AZ 85259 USA
| | - Heidi Kosiorek
- Division of Biostatistics, Mayo Clinic, 13400 East Shea Boulevard, Scottsdale, AZ 85259 USA
| | - Linda Larkey
- College of Nursing and Health Innovation, Arizona State University, 550 North 3rd Street, Phoenix, AZ 85004 USA
| | - Krisstina Gowin
- University of Arizona, 1501 North Campbell Avenue, Tucson, AZ 85724 USA
| | - Ruben Mesa
- Mays Cancer Center, University of Texas San Antonio MD Anderson, 7979 Wurzbach Road, San Antonio, TX 78229 USA
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Defects in memory B-cell and plasma cell subsets expressing different immunoglobulin-subclasses in patients with CVID and immunoglobulin subclass deficiencies. J Allergy Clin Immunol 2019; 144:809-824. [PMID: 30826363 DOI: 10.1016/j.jaci.2019.02.017] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 01/29/2019] [Accepted: 02/01/2019] [Indexed: 12/15/2022]
Abstract
BACKGROUND Predominantly antibody deficiencies (PADs) are the most prevalent primary immunodeficiencies, but their B-cell defects and underlying genetic alterations remain largely unknown. OBJECTIVE We investigated patients with PADs for the distribution of 41 blood B-cell and plasma cell (PC) subsets, including subsets defined by expression of distinct immunoglobulin heavy chain subclasses. METHODS Blood samples from 139 patients with PADs, 61 patients with common variable immunodeficiency (CVID), 68 patients with selective IgA deficiency (IgAdef), 10 patients with IgG subclass deficiency with IgA deficiency, and 223 age-matched control subjects were studied by using flow cytometry with EuroFlow immunoglobulin isotype staining. Patients were classified according to their B-cell and PC immune profile, and the obtained patient clusters were correlated with clinical manifestations of PADs. RESULTS Decreased counts of blood PCs, memory B cells (MBCs), or both expressing distinct IgA and IgG subclasses were identified in all patients with PADs. In patients with IgAdef, B-cell defects were mainly restricted to surface membrane (sm)IgA+ PCs and MBCs, with 2 clear subgroups showing strongly decreased numbers of smIgA+ PCs with mild versus severe smIgA+ MBC defects and higher frequencies of nonrespiratory tract infections, autoimmunity, and affected family members. Patients with IgG subclass deficiency with IgA deficiency and those with CVID showed defects in both smIgA+ and smIgG+ MBCs and PCs. Reduced numbers of switched PCs were systematically found in patients with CVID (absent in 98%), with 6 different defective MBC (and clinical) profiles: (1) profound decrease in MBC numbers; (2) defective CD27+ MBCs with almost normal IgG3+ MBCs; (3) absence of switched MBCs; and (4) presence of both unswitched and switched MBCs without and; (5) with IgG2+ MBCs; and (6) with IgA1+ MBCs. CONCLUSION Distinct PAD defective B-cell patterns were identified that are associated with unique clinical profiles.
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A novel IKAROS haploinsufficiency kindred with unexpectedly late and variable B-cell maturation defects. J Allergy Clin Immunol 2017; 141:432-435.e7. [PMID: 28927821 PMCID: PMC6588539 DOI: 10.1016/j.jaci.2017.08.019] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2017] [Revised: 08/01/2017] [Accepted: 08/17/2017] [Indexed: 11/20/2022]
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Bogaert DJ, Dullaers M, Kuehn HS, Leroy BP, Niemela JE, De Wilde H, De Schryver S, De Bruyne M, Coppieters F, Lambrecht BN, De Baets F, Rosenzweig SD, De Baere E, Haerynck F. Early-onset primary antibody deficiency resembling common variable immunodeficiency challenges the diagnosis of Wiedeman-Steiner and Roifman syndromes. Sci Rep 2017. [PMID: 28623346 PMCID: PMC5473876 DOI: 10.1038/s41598-017-02434-4] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Syndromic primary immunodeficiencies are rare genetic disorders that affect both the immune system and other organ systems. More often, the immune defect is not the major clinical problem and is sometimes only recognized after a diagnosis has been made based on extra-immunological abnormalities. Here, we report two sibling pairs with syndromic primary immunodeficiencies that exceptionally presented with a phenotype resembling early-onset common variable immunodeficiency, while extra-immunological characteristics were not apparent at that time. Additional features not typically associated with common variable immunodeficiency were diagnosed only later, including skeletal and organ anomalies and mild facial dysmorphism. Whole exome sequencing revealed KMT2A-associated Wiedemann-Steiner syndrome in one sibling pair and their mother. In the other sibling pair, targeted testing of the known disease gene for Roifman syndrome (RNU4ATAC) provided a definite diagnosis. With this study, we underline the importance of an early-stage and thorough genetic assessment in paediatric patients with a common variable immunodeficiency phenotype, to establish a conclusive diagnosis and guide patient management. In addition, this study extends the mutational and immunophenotypical spectrum of Wiedemann-Steiner and Roifman syndromes and highlights potential directions for future pathophysiological research.
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Affiliation(s)
- Delfien J Bogaert
- Clinical Immunology Research Lab, Department of Pulmonary Medicine, Centre for Primary Immunodeficiency, Jeffrey Modell Diagnosis and Research Centre, Ghent University Hospital, Ghent, Belgium.,Department of Paediatric Immunology and Pulmonology, Centre for Primary Immunodeficiency, Jeffrey Modell Diagnosis and Research Centre, Ghent University Hospital, Ghent, Belgium.,Center for Medical Genetics, Ghent University and Ghent University Hospital, Ghent, Belgium.,Laboratory of Immunoregulation, VIB Inflammation Research Centre, Ghent, Belgium
| | - Melissa Dullaers
- Clinical Immunology Research Lab, Department of Pulmonary Medicine, Centre for Primary Immunodeficiency, Jeffrey Modell Diagnosis and Research Centre, Ghent University Hospital, Ghent, Belgium.,Laboratory of Immunoregulation, VIB Inflammation Research Centre, Ghent, Belgium.,Department of Internal Medicine, Ghent University, Ghent, Belgium
| | - Hye Sun Kuehn
- Immunology Service, Department of Laboratory Medicine, NIH Clinical Centre, National Institutes of Health, Bethesda, MD, USA
| | - Bart P Leroy
- Center for Medical Genetics, Ghent University and Ghent University Hospital, Ghent, Belgium.,Department of Ophthalmology, Ghent University Hospital, Ghent, Belgium.,Division of Ophthalmology, The Children's Hospital of Philadelphia, Philadelphia, USA
| | - Julie E Niemela
- Immunology Service, Department of Laboratory Medicine, NIH Clinical Centre, National Institutes of Health, Bethesda, MD, USA
| | - Hans De Wilde
- Department of Paediatric Cardiology, Ghent University Hospital, Ghent, Belgium
| | - Sarah De Schryver
- Department of Paediatric Allergy and Immunology, Montreal Children's Hospital, Montreal, QC, Canada
| | - Marieke De Bruyne
- Center for Medical Genetics, Ghent University and Ghent University Hospital, Ghent, Belgium
| | - Frauke Coppieters
- Center for Medical Genetics, Ghent University and Ghent University Hospital, Ghent, Belgium
| | - Bart N Lambrecht
- Laboratory of Immunoregulation, VIB Inflammation Research Centre, Ghent, Belgium.,Department of Internal Medicine, Ghent University, Ghent, Belgium.,Department of Pulmonology, Ghent University Hospital, Ghent, Belgium
| | - Frans De Baets
- Department of Paediatric Immunology and Pulmonology, Centre for Primary Immunodeficiency, Jeffrey Modell Diagnosis and Research Centre, Ghent University Hospital, Ghent, Belgium
| | - Sergio D Rosenzweig
- Immunology Service, Department of Laboratory Medicine, NIH Clinical Centre, National Institutes of Health, Bethesda, MD, USA
| | - Elfride De Baere
- Center for Medical Genetics, Ghent University and Ghent University Hospital, Ghent, Belgium
| | - Filomeen Haerynck
- Clinical Immunology Research Lab, Department of Pulmonary Medicine, Centre for Primary Immunodeficiency, Jeffrey Modell Diagnosis and Research Centre, Ghent University Hospital, Ghent, Belgium. .,Department of Paediatric Immunology and Pulmonology, Centre for Primary Immunodeficiency, Jeffrey Modell Diagnosis and Research Centre, Ghent University Hospital, Ghent, Belgium.
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