Bariatric surgery in morbid obesity, either through sleeve gastrectomy (SG) or Roux-Y gastric bypass (RYGB), leads to sustainable weight loss, improvement of metabolic disorders and changes in intestinal microbiota. Yet, the relationship between changes in gut microbiota, weight loss and surgical procedure remains incompletely understood. We determined temporal changes in microbiota composition in 45 obese patients undergoing crash diet followed by SG ( n = 22) or RYGB ( n = 23). Intestinal microbiota composition was determined before intervention (baseline, S1), 2 weeks after crash diet (S2), and 1 week (S3), 3 months (S4) and 6 months (S5) after surgery. Relative to S1, the microbial diversity index declined at S2 and S3 ( p < 0.05), and gradually returned to baseline levels at S5. Rikenellaceae relative abundance increased and Ruminococcaceae and Streptococcaceae abundance decreased at S2 ( p < 0.05). At S3, Bifidobacteriaceae abundance decreased, whereas those of Streptococcaceae and Enterobacteriaceae increased ( p < 0.05). Increased weight loss between S3-S5 was not associated with major changes in microbiota composition. No significant differences appeared between both surgical procedures. In conclusion, undergoing a crash diet and bariatric surgery were associated with an immediate but temporary decline in microbial diversity, with immediate and permanent changes in microbiota composition, independent of surgery type.

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Background: In Behçet's disease (BD), an auto-inflammatory vasculitis, an unbalanced gut microbiota can contribute to pro-inflammatory reactions. In separate studies, distinct pro-and anti-inflammatory bacteria associated with BD have been identified. Methods: To establish disease-associated determinants, we performed gut microbiome profiling in BD patients from the Netherlands (n = 19) and Italy (n = 13), matched healthy controls (HC) from the Netherlands (n = 17) and Italy (n = 15) and oral microbiome profiling in Dutch BD patients (n = 18) and HC (n = 15) by 16S rRNA gene sequencing. In addition, we used fecal IgA-SEQ analysis to identify specific IgA coated bacterial taxa in Dutch BD patients (n = 13) and HC (n = 8). Results: In BD stool samples alpha-diversity was conserved, whereas beta-diversity analysis showed no clustering based on disease, but a significant segregation by country of origin. Yet, a significant decrease of unclassified Barnesiellaceae and Lachnospira genera was associated with BD patients compared to HC. Subdivided by country, the Italian cohort displays a significant decrease of unclassified Barnesiellaceae and Lachnospira genera, in the Dutch cohort this decrease is only a trend. Increased IgA-coating of Bifidobacterium spp., Dorea spp. and Ruminococcus bromii species was found in stool from BD patients. Moreover, oral Dutch BD microbiome displayed increased abundance of Spirochaetaceae and Dethiosulfovibrionaceae families. Conclusions: BD patients show decreased fecal abundance of Barnesiellaceae and Lachnospira and increased oral abundance of Spirochaetaceae and Dethiosulfovibrionaceae. In addition, increased fecal IgA coating of Bifidobacterium, van der Houwen et al. Microbiota in Behçet's Disease Ruminococcus bromii and Dorea may reflect retention of anti-inflammatory species and neutralization of pathosymbionts in BD, respectively. Additional studies are warranted to relate intestinal microbes with the significance of ethnicity, diet, medication and response with distinct pro-and inflammatory pathways in BD patients.

Patients with common variable immunodeficiency (CVID) can develop immune dysregulation complications such as autoimmunity, lymphoproliferation, enteritis, and malignancy, which cause significant morbidity and mortality. We aimed to (i) assess the potential of serum proteomics in stratifying patients with immune dysregulation using two independent cohorts and (ii) identify cytokine and chemokine signaling pathways that underlie immune dysregulation in CVID. A panel of 180 markers was measured in two multicenter CVID cohorts using Olink Protein Extension Assay technology. A classification algorithm was trained to distinguish CVID with immune dysregulation (CVIDid, n = 14) from CVID with infections only (CVIDio, n = 16) in the training cohort, and validated on a second testing cohort (CVIDid n = 23, CVIDio n = 24). Differential expression in both cohorts was used to determine relevant signaling pathways. An elastic net classifier using MILR1, LILRB4, IL10, IL12RB1, and CD83 could discriminate between CVIDid and CVIDio patients with a sensitivity of 0.83, specificity of 0.75, and area under the curve of 0.73 in an independent testing cohort. Activated pathways (fold change > 1.5, FDR-adjusted p < 0.05) in CVIDid included Th1 and Th17-associated signaling, as well as IL10 and other immune regulatory markers (LAG3, TNFRSF9, CD83). Targeted serum proteomics provided an accurate and reproducible tool to discriminate between patients with CVIDid and CVIDio. Cytokine profiles provided insight into activation of Th1 and Th17 pathways and indicate a possible role for chronic inflammation and exhaustion in immune dysregulation. These findings serve as a first step towards the development of biomarkers for immune dysregulation in CVID.