The immunophenotypic fingerprint of patients with primary antibody deficiencies is partially present in their asymptomatic first-degree relatives

The Euroflow PID Orientation Tube in the diagnostic workup of primary immunodeficiency: Daily practice performance in a tertiary university hospital

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.

A Computational Pipeline for the Diagnosis of CVID Patients

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.

Online yoga in myeloproliferative neoplasm patients: results of a randomized pilot trial to inform future research

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.

Defects in memory B-cell and plasma cell subsets expressing different immunoglobulin-subclasses in patients with CVID and immunoglobulin subclass deficiencies

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.

Early-onset primary antibody deficiency resembling common variable immunodeficiency challenges the diagnosis of Wiedeman-Steiner and Roifman syndromes

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.