Intestinal Candida albicans overgrowth in IgA deficiency.

BACKGROUND: Secretory IgA interacts with commensal bacteria, but its impact on human mycobiota ecology has not been widely explored. In particular, whether human IgA-deficiency is associated with gut fungal dysbiosis remains unknown. OBJECTIVES: Our goal was to study the impact of IgA on gut mycobiota ecology. METHODS: The Fungi-Flow method was used to characterize fecal, systemic, and maternal IgA, IgM, and IgG responses against 14 representative fungal strains (yeast/spores or hyphae forms) in healthy donors (HDs) (n = 34, 31, and 20, respectively) and to also compare gut mycobiota opsonization by secretory antibodies in HDs (n = 28) and patients with selective IgA deficiency (SIgAd) (n = 12). Stool mycobiota composition was determined by internal transcribed spacer gene sequencing in HDs (n = 23) and patients with SIgAd (n = 17). Circulating CD4+ T-cell cytokine secretion profiles were determined by intracellular staining. The impact of secretory IgA, purified from breast milk (n = 9), on Candidaalbicans growth and intestinal Caco-2 cell invasion was tested in vitro. RESULTS: Homeostatic IgA binds commensal fungi with a body fluid-selective pattern of recognition. In patients with SIgAd, fungal gut ecology is preserved by compensatory IgM binding to commensal fungi. Gut Calbicans overgrowth nevertheless occurs in this condition but only in clinically symptomatic patients with decreased TH17/TH22 T-cell responses. Indeed, secretory IgA can reduce in vitro budding and invasion of intestinal cells by Calbicans and therefore exert control on this pathobiont. CONCLUSION: IgA has a selective impact on Calbicans ecology to preserve fungal-host mutualism.

Distinct cytokine profiles associated with COVID-19 severity and mortality.

BACKGROUND: Markedly elevated levels of proinflammatory cytokines and defective type-I interferon responses were reported in patients with coronavirus disease 2019 (COVID-19). OBJECTIVE: We sought to determine whether particular cytokine profiles are associated with COVID-19 severity and mortality. METHODS: Cytokine concentrations and severe acute respiratory syndrome coronavirus 2 antigen were measured at hospital admission in serum of symptomatic patients with COVID-19 (N = 115), classified at hospitalization into 3 respiratory severity groups: no need for mechanical ventilatory support (No-MVS), intermediate severity requiring mechanical ventilatory support (MVS), and critical severity requiring extracorporeal membrane oxygenation (ECMO). Principal-component analysis was used to characterize cytokine profiles associated with severity and mortality. The results were thereafter confirmed in an independent validation cohort (N = 86). RESULTS: At time of hospitalization, ECMO patients presented a dominant proinflammatory response with elevated levels of TNF-α, IL-6, IL-8, and IL-10. In contrast, an elevated type-I interferon response involving IFN-α and IFN-ß was characteristic of No-MVS patients, whereas MVS patients exhibited both profiles. Mortality at 1 month was associated with higher levels of proinflammatory cytokines in ECMO patients, higher levels of type-I interferons in No-MVS patients, and their combination in MVS patients, resulting in a combined mortality prediction accuracy of 88.5% (risk ratio, 24.3; P < .0001). Severe acute respiratory syndrome coronavirus 2 antigen levels correlated with type-I interferon levels and were associated with mortality, but not with proinflammatory response or severity. CONCLUSIONS: Distinct cytokine profiles are observed in association with COVID-19 severity and are differentially predictive of mortality according to oxygen support modalities. These results warrant personalized treatment of COVID-19 patients based on cytokine profiling.

Monitoring Disease Activity in Systemic Lupus Erythematosus With Single-Molecule Array Digital Enzyme-Linked Immunosorbent Assay Quantification of Serum Interferon-α.

OBJECTIVE: No simple or standardized assay is available to quantify interferon-α (IFNα) in routine clinical practice. Single-molecule array (Simoa) digital enzyme-linked immunosorbent assay (ELISA) technology enables direct IFNα quantification at attomolar (femtogram per milliliter [fg/ml]) concentrations. This study was undertaken to assess IFNα digital ELISA diagnostic performances to monitor systemic lupus erythematosus (SLE) activity. METHODS: IFNα concentrations in serum samples from 150 consecutive SLE patients in a cross-sectional study were determined with digital ELISA and a functional biologic activity assay (bioassay). According to their Safety of Estrogens in Lupus Erythematosus National Assessment version of the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) flare composite scores, patients were divided into groups with inactive SLE (SLEDAI score of <4 or clinical SLEDAI score of 0) or active SLE (SLEDAI score of ≥4 or clinical SLEDAI score of >0), and into groups with no flare or mild/moderate flare or severe flare. RESULTS: Based on serum samples from healthy blood donors, the abnormal serum IFNα level threshold value was 136 fg/ml. Next, using receiver operating characteristic curves for an SLE patient series that was widely heterogeneous in terms of disease activity and organ involvement, the threshold IFNα value associated with active disease was determined to be 266 fg/ml. The digital ELISA-assessed serum IFNα level was a better biomarker of disease activity than the Farr assay because its specificity, likelihood ratio for positive results, and positive predictive value better discerned active SLE or flare from inactive disease. The digital ELISA was more sensitive than the bioassay for detecting low-abnormal serum IFNα concentrations and identifying patients with low disease activity. CONCLUSION: Direct serum IFNα determination with a highly sensitive assay might improve monitoring of clinical SLE activity and selection of the best candidates for anti-IFNα treatment.

Assessment of an ultra-sensitive IFNγ immunoassay prototype for latent tuberculosis diagnosis.

Worldwide there are about 1.7 billion individuals with latent tuberculosis infection (LTBI) and only 5% to 15% will develop active tuberculosis (TB). It is recommended to treat only those most at risk of developing active TB to avoid problems of drug resistance. LTBI diagnosis involves reviewing the individual's medical history, physical examination, and biological tests. Interferon gamma release assays (IGRA) can yield "undeterminate" or "uncertain" results, which makes clinical management decisions difficult. We assessed an ultra-sensitive immunoassay prototype based on single molecule array (SiMoA) technology to evaluate its overall performance, and in particular, its performance for indeterminate and uncertain positive or negative samples, as classified by the results from the current ELISA technique used for IFNγ quantification. We analyzed samples from hospitalized or consulting patients and healthcare workers from three hospitals in Paris, previously classified as negative (n = 30), positive (n = 35), uncertain negative (n = 25), uncertain positive (n = 31), or indeterminate (n = 30). We observed that with the SiMoA assay 83.3% of the indeterminate samples became interpretable and could be classified as negative, whereas 74% of uncertain positive samples were classified as positive. Most uncertain negative samples (72%) were reclassified as uncertain positive (68%) or positive (4%). The results suggest that the ultra-sensitive SiMoA IFNγ assay could represent a useful tool for the identification of true positive and negative samples among those giving indeterminate or uncertain results with the TB IGRA assay currently used.