The aetiology of inflammatory bowel diseases (IBD) seems to be strongly connected to changes in the enteral microbiome. The dysbiosis pattern seen in Crohn’s disease (CD) differs among published studies depending on patients’ age, disease phenotype and microbiome research methods. The aims was to investigate microbiome in treatment-naive paediatric patients to get an insight into its structure at the early stage of the disease in comparison to healthy. Stool samples were obtained from controls and newly diagnosed patients prior to any intervention. Microbiota was analysed by 16SrRNAnext-generation-sequencing (NGS). Differences in the within-sample phylotype richness and evenness (alpha diversity) were detected between controls and patients. Statistically significant dissimilarities between samples were present for all used metrics. We also found a significant increase in the abundance of OTUs of the Enterococcus genus and reduction in, among others, Bifidobacterium (B. adolescentis), Roseburia (R.faecis), Faecalibacterium (F. prausnitzii), Gemmiger (G. formicilis), Ruminococcus (R. bromii) and Veillonellaceae (Dialister). Moreover, differences in alpha and beta diversities in respect to calprotectin and PCDAI were observed: patients with calprotectin <100 µg/g and with PCDAI below 10 points vs those with calprotectin >100 µg/g and mild (10–27.7 points), moderate (27.5–40 points) or severe (>40 points) CD disease activity had higher richness and diversity of gut microbiota. The results of our study highlight reduced diversity and dysbiosis at the earliest stage of the disease. Microbial imbalance and low abundance of butyrate-producing bacteria, including Bifidobacterium adolescentis, may suggest benefits of microbial modification therapy.

Introduction Scientific data indicate a possible influence of gut microbiota on the development of type 1 and type 2 diabetes mellitus (T1DM and T2DM, respectively). Sequence analysis of 16S ribosomal RNA identified several hundred bacterial species of the intestinal ecosystem, most of which cannot be cultured. Objectives We aimed to evaluate gut microbiota composition in adult patients with T1DM and T2DM and establish a link between microbiological test results and patients' clinical data. Patients and methods We examined DNA isolated from fecal samples in 3 groups: healthy volunteers (n = 23), patients with T1DM (n = 22), and patients with T2DM (n = 23). Next‑generation sequencing was performed on the MiSeq platform. Results At the phylum level, the Firmicutes bacteria prevailed (>77%) in all groups. At the taxonomic levels L2 (phylum) and L6 (genus), significant differences were demonstrated in bacterial profiles, particularly in the T2DM group. A negative correlation was observed between several genera of bacteria and the percentage of glycated hemoglobin A1c in the T2DM group, while a positive correlation was revealed between bacteria belonging to the genus Bifidobacterium and high‑density lipoprotein cholesterol levels in both T1DM and T2DM groups. Conclusions Our results provide grounds for conducting research in the field of gut microbiota in order to develop individualized therapy for patients with diabetes based on modifying the microbiota composition, as a new method for controlling glycemia. Next‑generation sequencing allows a rapid identification of the DNA of all bacteria present in the sample and their taxonomic classification.

In T1DM-complicated pregnancy, CSII compared to MDI therapy resulted in better first trimester glycaemic control; this difference decreased in subsequent trimesters. CSII therapy was associated with lower insulin requirements, higher GWG and altered risk for infants being LGA and SGA.

The aim of the study was to determine the impact of biological treatment with tumor necrosis factor α antibodies (anti-TNF-α) on the intestinal microbiome of children with severe Crohn’s disease (CD) and to evaluate the differences in the intestinal microbiome between patients treated with biological therapy and healthy children. Microbiota composition was analyzed by 16S next-generation sequencing (NGS) and microbial profiles were compared between studied groups. Fifty-four samples (from 18 patients before and after anti-TNF-α induction therapy and 18 healthy children) were used in the sequencing analysis. Shannon’s diversity index (p = 0.003, adj. p = 0.010) and observed operational taxonomic units (OTUs) (p = 0.007, adj. p = 0.015) were different between controls and patients with prior therapy for CD. Statistically significant dissimilarities between beta diversity metrics, indicating distinct community composition across groups, were observed in patients with CD before and after therapy. We did not observe any differences between controls and patients with CD after therapy. Core microbiome analysis at species level showed that 32 species were present only in patients with CD but not in controls. The results show that biological treatment is associated with changes in the intestinal microbiome of patients with CD: these changes result in an intestinal microbiome pattern similar to that seen in healthy children. Long-term observation is necessary to determine whether treatment can lead to full restoration of a healthy-like microbiome.

PurposeOur insight in the genetics of Hashimoto’s thyroiditis (HT) has become clearer through information provided by genome-wide association studies and candidate gene studies, but remains still not fully understood. Our aim was to assess how many different genetic risk variants contribute to the development of HT.Methods147 HT cases (10.2% men) and 147 controls (13.6% men) were qualified for the analysis. Intrinsic and environmental factors were controlled for. Polymorphisms (SNP) were chosen based on the literature and included markers of the genes PTPN22, CTLA4, TG, TPO among others, and of genomic regions pointed by GWAS studies. SNP were typed on a microarray. Variants in the HLA-DRB1 gene were identified by Sanger sequencing.ResultsMultivariate predisposition to HT was modeled. Based on the investigated group, a model of seven variables was obtained. The variability explained by this model was assessed at only 5.4821% (p = 2 × 10−6), which indicates that many dozens of factors are required simultaneously to explain HT predisposition.ConclusionsWe analyzed genetic regions commonly and most significantly associated with autoimmune thyroid disorders in the literature, on a carefully selected cohort. Our results indicated a lack of possibility to predict the risk of HT development, even with a multivariate model. We therefore conclude that strong associations of single genetic regions with HT should be interpreted with great caution. We believe that a change in the attitude towards genetic association analyses of HT predisposition is necessary. Studies including multiple factors simultaneously are needed to unravel the intricacies of genetic associations with HT.Electronic supplementary materialThe online version of this article (10.1007/s40618-018-0910-4) contains supplementary material, which is available to authorized users.