Patients with VEXAS diagnosed in a Danish tertiary rheumatology setting have highly elevated inflammatory markers, macrocytic anaemia and negative autoimmune biomarkers

BACKGROUND: Vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) is an autoinflammatory condition with overlapping features of rheumatology and haematology caused by somatic mutations in the UBA1 gene. Patients present with highly variable symptoms and their path towards diagnosis are often complicated and characterised by extensive examinations. It is, therefore, pivotal that clinicians become familiar with the clinical presentation of VEXAS to advance identification of patients with the disease. OBJECTIVES: We aimed to (1) characterise patients diagnosed with VEXAS in a tertiary rheumatology referral centre, (2) identify common rheumatological biomarkers that may distinguish VEXAS from other rheumatic diseases and (3) suggest which clinical findings should motivate genetic testing for VEXAS. METHODS: Patients were identified and diagnosed at the department of Rheumatology, Aarhus University Hospital (AUH), Denmark. Blood samples were examined for VEXAS-associated UBA1 variants by Sanger sequencing at the department of Clinical Immunology, AUH. Clinical and biochemical data were retrieved from the hospital electronic patient chart. RESULTS: Eleven male patients with clinical suspicion of VEXAS underwent sequencing. Five of these carried known VEXAS-associated variants. Median age at diagnosis was 84 (75–87) years. All patients had significantly elevated inflammatory markers with a median C-reactive protein (CRP) of 297 (196–386) mg/L and macrocytic anaemia. None of the patients presented common biomarkers for autoimmunity. CONCLUSION: Danish patients with VEXAS syndrome are men with persistent inflammation, constitutional symptoms and heterogeneous clinical presentations. Shared features for all patients in this study were highly elevated inflammatory markers, macrocytic anaemia and negative autoimmune biomarkers

Endotoxemia Is Associated with Altered Innate and Adaptive Immune Responses in Untreated HIV-1 Infected Individuals

BACKGROUND: Microbial translocation may contribute to the immunopathogenesis in HIV infection. We investigated if microbial translocation and inflammation were associated with innate and adaptive immune responses in adults with HIV. METHODOLOGY/PRINCIPAL FINDINGS: This was an observational cohort study. Sera from HIV-infected and HIV-uninfected individuals were analyzed for microbial translocation (soluble CD14, lipopolysaccharides [LPS], endotoxin core antibody, and anti-α-galactosyl antibodies) and inflammatory markers (high sensitivity C-reactive protein, IL-6, IL-1 receptor antagonist, soluble tumor necrosis factor receptor II, and IL-10) with enzyme-linked immunosorbent assays. Peripheral blood mononuclear cells (PBMC) from HIV-infected persons and healthy controls (primed with single-stranded HIV-1-derived RNA) were stimulated with LPS, and cytokine production was measured. Finally, HIV-infected patients were immunized with Prevnar 7vPnC±CpG 7909 followed by Pneumo Novum PPV-23. Effects of microbial translocation and inflammation on immunization were analyzed in a predictive regression model. We included 96 HIV-infected individuals, 76 on highly active antiretroviral therapy (HAART), 20 HAART-naive, and 50 healthy controls. Microbial translocation and inflammatory markers were higher among HIV-infected persons than controls. Cytokine levels following LPS stimulation were increased in PBMCs from HAART-naive compared to HAART-treated HIV-infected persons. Further, RNA-priming of PBMCs from controls acted synergistically with LPS to augment cytokine responses. Finally, high serum LPS levels predicted poor vaccine responses among HAART-naive, but not among HAART-treated HIV-infected individuals. CONCLUSIONS/SIGNIFICANCE: LPS acts synergistically with HIV RNA to stimulate innate immune responses in vitro and increasing serum LPS levels seem to predict poor antibody responses after vaccination among HAART-naive HIV-infected persons. Thus, our results suggest that microbial translocation may be associated with innate and adaptive immune dysfunction in untreated HIV infection

Polysaccharide responsiveness is not biased by prior pneumococcal-conjugate vaccination

Polysaccharide responsiveness is tested by measuring antibody responses to polysaccharide vaccines to diagnose for humoral immunodeficiency. A common assumption is that this responsiveness is biased by any previous exposure to the polysaccharides in the form of protein-coupled polysaccharide vaccines, such as those used in many childhood vaccination programmes. To examine this assumption, we investigated the effect of protein-coupled polysaccharide vaccination on subsequent polysaccharide responsiveness. HIV-infected adults (n = 47) were vaccinated twice with protein-coupled polysaccharides and six months later with pure polysaccharides. We measured immunoglobulin G responses against three polysaccharides present in only the polysaccharide vaccine (non-memory polysaccharides) and seven recurring polysaccharides (memory polysaccharides). Responsiveness was evaluated according to the consensus guidelines published by the American immunology societies. Impaired responsiveness to non-memory polysaccharides was more frequent than to memory polysaccharides (51% versus 28%, P = 0.015), but the individual polysaccharides did not differ in triggering sufficient responses (74% versus 77%, P = 0.53). Closer analysis revealed important shortcomings of the current evaluation guidelines. The interpreted responses number and their specificities influenced the likelihood of impaired responsiveness in a complex manor. This influence was propelled by the dichotomous approaches inherent to the American guidelines. We therefore define a novel more robust polysaccharide responsiveness measure, the Z-score, which condenses multiple, uniformly weighted responses into one continuous variable. Using the Z-score, responsiveness to non-memory polysaccharides and memory-polysaccharides were found to correlate (R(2) = 0.59, P<0.0001). We found that polysaccharide responsiveness was not biased by prior protein-coupled polysaccharide vaccination in HIV-infected adults. Studies in additional populations are warranted

Correlation of Z-scores to memory polysaccharides and non-memory polysaccharides.

<p>Z-scores of responses to non-memory polysaccharides after polysaccharide vaccination were compared to Z-scores of responses to memory polysaccharides (<b>A</b>): after polysaccharide vaccination and (<b>B</b>): after protein-coupled polysaccharide vaccination. The Z-scores of participants with impaired polysaccharide responsiveness to non-memory polysaccharides according to consensus guidelines are presented as black symbols whereas the Z-scores of participants with intact responsiveness are presented as white symbols.</p

Flow diagram illustrating patient inclusion.

<p>Flow diagram illustrating patient inclusion.</p

Polysaccharide responsiveness depending on the number of tested responses and their specificities.

<p><b>A:</b> Participantś polysaccharide responsiveness was evaluated according to consensus guidelines from a variable number of responses (one to nine). All combinations of response specificities were evaluated yielding a total of 1022 responsiveness evaluations per participant. Responsiveness was evaluated according to the consensus guidelines. The populations mean frequencies of impaired responsiveness are presented with SDs ordered according to the number of included responses. The particular frequencies for the three non-memory polysaccharides and seven memory polysaccharides are indicated (blue symbol and red symbol, respectively). <b>B:</b> The percentage attaining a sufficient response to the individual polysaccharides according to consensus guidelines. Blue bars represent responses to non-memory polysaccharides and red bars represent responses to memory polysaccharides.</p

Alternative measures of polysaccharide responsiveness.

<p><b>A:</b> Participantś polysaccharide responsiveness was evaluated using means of responses. A variable number of responses were included (one to nine). All combinations of response specificities were evaluated. The populations mean frequencies of impaired responsiveness for a given number of responses were determined from geometric means (black), concentration-corrected geometric means (white), means of standard normal deviates (yellow), means of standard normal deviates transformed to standard normal deviates (green). See <b>Methods</b> for impaired responsiveness definition. Error bars indicate SDs. <b>B</b>: Populations geometric mean IgG concentrations to polysaccharides after polysaccharide vaccination (with 95% confidence intervals). IgG concentrations to non-memory polysaccharides are presented as blue bars and IgG concentrations to memory polysaccharides are presented as red bars. <b>C</b>: Means of polysaccharide responsiveness based on standard normal deviates obtained from the simulation. Error bars indicate SDs. The arbitrary limit defining impaired responsiveness (–0.79) are illustrated for comparison.</p

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