Cytosolic nucleic acid sensing and mitochondrial transcriptomic changes as early triggers of metabolic disease in db/db mice.

Animal models of diabetes, such as db/db mice, are a useful tool for deciphering the genetic background of molecular changes at the initial stages of disease development. Our goal was to find early transcriptomic changes in three tissues involved in metabolism regulation in db/db mice: adipose tissue, muscle tissue and liver tissue. Nine animals (three per time point) were studied. Tissues were collected at 8, 12 and 16 weeks of age. Transcriptome-wide analysis was performed using mRNA-seq. Libraries were sequenced on NextSeq (Illumina). Differential expression (DE) analysis was performed with edgeR. The analysis of the gene expression profile shared by all three tissues revealed eight upregulated genes (Irf7, Sp100, Neb, Stat2, Oas2, Rtp4, H2-T24 and Oasl2) as early as between 8 and 12 weeks of age. The most pronounced differences were found in liver tissue: nine DE genes between 8 and 12 weeks of age (Irf7, Ly6a, Ly6g6d, H2-Dma, Pld4, Ly86, Fcer1g, Ly6e and Idi1) and five between 12 and 16 weeks of age (Irf7, Plac8, Ifi44, Xaf1 and Ly6a) (adj. p-value < 0.05). The mitochondrial transcriptomic profile also changed with time: we found two downregulated genes in mice between 8 and 12 weeks old (Ckmt2 and Cox6a2) and five DE genes between 12 and 16 weeks of age (Mavs, Tomm40L, Mtfp1, Ckmt2 and Cox6a2). The KEGG pathway analysis showed significant enrichment in pathways related to the autoimmune response and cytosolic DNA sensing. Our results suggest an important involvement of the immunological response, mainly cytosolic nucleic acid sensing, and mitochondrial signalling in the early stages of diabetes and obesity.

Variants influencing age at diagnosis of HNF1A-MODY.

BACKGROUND: HNF1A-MODY is a monogenic form of diabetes caused by variants in the HNF1A gene. Different HNF1A variants are associated with differences in age of disease onset, but other factors are postulated to influence this trait. Here, we searched for genetic variants influencing age of HNF1A-MODY onset. METHODS: Blood samples from 843 HNF1A-MODY patients from Czech Republic, France, Poland, Slovakia, the UK and the US were collected. A validation set consisted of 121 patients from the US. We conducted a genome-wide association study in 843 HNF1A-MODY patients. Samples were genotyped using Illumina Human Core arrays. The core analysis was performed using the GENESIS package in R statistical software. Kinship coefficients were estimated with the KING and PC-Relate algorithms. In the linear mixed model, we accounted for year of birth, sex, and location of the HNF1A causative variant. RESULTS: A suggestive association with age of disease onset was observed for rs2305198 (p = 2.09E-07) and rs7079157 (p = 3.96E-06) in the HK1 gene, rs2637248 in the LRMDA gene (p = 2.44E-05), and intergenic variant rs2825115 (p = 2.04E-05). Variant rs2637248 reached nominal significance (p = 0.019), while rs7079157 (p = 0.058) and rs2825115 (p = 0.068) showed suggestive association with age at diabetes onset in the validation set. CONCLUSIONS: rs2637248 in the LRMDA gene is associated with age at diabetes onset in HNF1A-MODY patients.

Mitochondrial genome variations, mitochondrial-nuclear compatibility, and their association with metabolic diseases.

Two genomes regulate the energy metabolism of eukaryotic cells: the nuclear genome, which codes for most cellular proteins, and the mitochondrial genome, which, together with the nuclear genome, coregulates cellular bioenergetics. Therefore, mitochondrial genome variations can affect, directly or indirectly, all energy-dependent cellular processes and shape the metabolic state of the organism. This review provides a current and up-to-date overview on how codependent these two genomes are, how they appear to have coevolved, and how variations within the mitochondrial genome might be associated with the manifestation of metabolic diseases. This review summarizes and structures results obtained from epidemiological studies that identified links between mitochondrial haplogroups and individual risks for developing obesity and diabetes. This is complemented by findings on the compatibility of mitochondrial and nuclear genomes and cellular bioenergetic fitness, which have been acquired from well-controlled studies in conplastic animal models. These elucidate, more mechanistically, how single-nucleotide variants can influence cellular metabolism and physiology. Overall, it seems that certain mitochondrial genome variations negatively affect mitochondrial-nuclear compatibility and are statistically linked with the onset of metabolic diseases, whereas, for others, greater uncertainty exists, and additional research into this exciting field is required.

The Gut Microbiota Profile According to Glycemic Control in Type 1 Diabetes Patients Treated with Personal Insulin Pumps.

Recently, several studies explored associations between type 1 diabetes (T1DM) and microbiota. The aim of our study was to assess the colonic microbiota structure according to the metabolic control in T1DM patients treated with insulin pumps. We studied 89 T1DM patients (50.6% women) at the median age of 25 (IQR, 22-29) years. Pielou's evenness (p = 0.02), and Shannon's (p = 0.04) and Simpson's diversity indexes (p = 0.01), were higher in patients with glycosylated hemoglobin (HbA1c) ≥ 53 mmol/mol (7%). There were no differences in beta diversity between groups. A linear discriminant analysis effect size (LEfSe) algorithm showed that one family (Ruminococcaceae) was enriched in patients with HbA1c < 53 mmol/mol, whereas one family (Streptococcaceae) and four species (Ruminococcus torques, unclassified species of Lactococcus, Eubacteroim dolichum, and Coprobacillus cateniformis) were enriched in patients with HbA1c ≥ 53 mmol/mol. We found that at class level, the following pathways according to Kyoto Encyclopedia of Genes and Genomes were enriched in patients with HbA1c < 53 mmol/mol: bacterial motility proteins, secretion system, bacterial secretion system, ribosome biogenesis, translation proteins, and lipid biosynthesis, whereas in patients with HbA1c ≥ 53 mmol/mol, the galactose metabolism, oxidative phosphorylation, phosphotransferase system, fructose, and mannose metabolism were enriched. Observed differences in alpha diversity, metabolic pathways, and associations between bacteria and HbA1c in colonic flora need further investigation.

The transcriptome-wide association search for genes and genetic variants which associate with BMI and gestational weight gain in women with type 1 diabetes.

BACKGROUND: Clinical data suggest that BMI and gestational weight gain (GWG) are strongly interconnected phenotypes; however, the genetic basis of the latter is rather unclear. Here we aim to find genes and genetic variants which influence BMI and/or GWG. METHODS: We have genotyped 316 type 1 diabetics using Illumina Infinium Omni Express Exome-8 v1.4 arrays. The GIANT, ARIC and T2D-GENES summary statistics were used for TWAS (performed with PrediXcan) in adipose tissue. Next, the analysis of association of imputed expression with BMI in the general and diabetic cohorts (Analysis 1 and 2) or GWG (Analysis 3 and 4) was performed, followed by variant association analysis (1 Mb around identified loci) with the mentioned phenotypes. RESULTS: In Analysis 1 we have found 175 BMI associated genes and 19 variants (p < 10-4) which influenced GWG, with the strongest association for rs11465293 in CCL24 (p = 3.18E-06). Analysis 2, with diabetes included in the model, led to discovery of 1812 BMI associated loci and 207 variants (p < 10-4) influencing GWG, with the strongest association for rs9690213 in PODXL (p = 9.86E-07). In Analysis 3, among 648 GWG associated loci, 2091 variants were associated with BMI (FDR < 0.05). In Analysis 4, 7 variants in GWG associated loci influenced BMI in the ARIC cohort. CONCLUSIONS: Here, we have shown that loci influencing BMI might have an impact on GWG and GWG associated loci might influence BMI, both in the general and T1DM cohorts. The results suggest that both phenotypes are related to insulin signaling, glucose homeostasis, mitochondrial metabolism, ubiquitinoylation and inflammatory responses.

Next-Generation Sequencing as a Tool to Detect Vaginal Microbiota Disturbances during Pregnancy.

The physiological microbiota of the vagina is responsible for providing a protective barrier, but Some factors can disturb the balance in its composition. At that time, the amounts of the genus Lactobacillus decrease, which may lead to the development of infection and severe complications during pregnancy. The aim of the study was the analysis of the bacterial composition of the vagina in 32 Caucasian women at each trimester of pregnancy using the next-generation sequencing method and primers targeting V3-V4 regions. In the studied group, the dominant species were Lactobacillus iners, Lactobacillus gasseri, and Lactobacillusplantarum. Statistically significant differences in the quantitative composition between trimesters were observed in relation to Lactobacillus jensenii,Streptococcus agalactiae, Lactobacillus iners, Gardnerella spp. Out of the 32 patients, 20 demonstrated fluctuations within the genus Lactobacillus, and 9 of them, at different stages of pregnancy, exhibited the presence of potentially pathogenic microbiota, among others: Streptococcus agalactiae, Gardnerella spp., Atopobium vaginae, and Enterococcus faecalis. The composition of the vaginal microbiota during pregnancy was subject to partial changes over trimesters. Although in one-third of the studied patients, both the qualitative and quantitative composition of microbiota was relatively constant, in the remaining patients, physiological and potentially pathogenic fluctuations were distinguished.

Mitochondrial GWAS and association of nuclear - mitochondrial epistasis with BMI in T1DM patients.

BACKGROUND: BMI is a strong indicator of complications from type I diabetes, especially under intensive treatment. METHODS: We have genotyped 435 type 1 diabetics using Illumina Infinium Omni Express Exome-8 v1.4 arrays and performed mitoGWAS on BMI. We identified additive interactions between mitochondrial and nuclear variants in genes associated with mitochondrial functioning MitoCarta2.0 and confirmed and refined the results on external cohorts: the Framingham Heart Study (FHS) and GTEx data. Linear mixed model analysis was performed using the GENESIS package in R/Bioconductor. RESULTS: We find a borderline significant association between the mitochondrial variant rs28357980, localized to MT-ND2, and BMI (ß = - 0.69, p = 0.056). This BMI association was confirmed on 1889 patients from FHS cohort (ß = - 0.312, p = 0.047). Next, we searched for additive interactions between mitochondrial and nuclear variants. MT-ND2 variants interacted with variants in the genes SIRT3, ATP5B, CYCS, TFB2M and POLRMT. TFB2M is a mitochondrial transcription factor and together with TFAM creates a transcription promoter complex for the mitochondrial polymerase POLRMT. We have found an interaction between rs3021088 in MT-ND2 and rs6701836 in TFB2M leading to BMI decrease (inter_pval = 0.0241), while interaction of rs3021088 in MT-ND2 and rs41542013 in POLRMT led to BMI increase (inter_pval = 0.0004). The influence of these interactions on BMI was confirmed in external cohorts. CONCLUSIONS: Here, we have shown that variants in the mitochondrial genome as well as additive interactions between mitochondrial and nuclear SNPs influence BMI in T1DM and general cohorts.

Changes in the Intestinal Microbiota Are Seen Following Treatment with Infliximab in Children with Crohn's Disease.

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.

Differences in the intestinal microbiome of healthy children and patients with newly diagnosed Crohn's disease.

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.

Effects of Negative Pressure Wound Therapy on Levels of Angiopoetin-2 and Other Selected Circulating Signaling Molecules in Patients with Diabetic Foot Ulcer.

BACKGROUND AND AIMS: Diabetic foot ulcers (DFUs) are linked to amputations and premature deaths. Negative pressure wound therapy (NPWT) has been used for DFUs. The mechanism of NPWT's action may be associated with its influence on circulating molecules. We assessed NPWT's effect on the plasma levels of angiopoietin-2 (Ang2), a key regulator of angiogenesis, and its microvesicular receptors (Tie2) as well as the microvesicles (MVs) themselves in DFU patients. MATERIALS AND METHODS: We included 69 patients with type 2 diabetes mellitus (T2DM) and neuropathic, noninfected DFUs-49 were treated with NPWT and 20 were treated with standard therapy (ST). Assigning patients to the NPWT group was not random but based on DFU characteristics, especially wound area. Ang2 was measured by ELISA in the entire group, while in a subgroup of 19 individuals on NPWT and 10 on ST, flow cytometry was used to measure Tie2+ and the corresponding isotype control (Iso+) and annexin V (AnnV+) as well as total MVs. Measurements were performed at the beginning and after 8 ± 1 days of therapy. RESULTS: Treatment groups were similar for basic characteristics but differed by their median DFU areas (10.3 (4.2-18.9) vs. 1.3 (0.9-3.4) cm2, p = 0.0001). At day 0, no difference was observed in Ang2 levels, total MVs, MV Tie+, and MV AnnV+ between the groups. Ang2 decreased after 8 days in the NPWT group, unlike in the ST group (3.54 (2.40-5.40) vs. 3.32 (2.33-4.61), p = 0.02, and 3.19 ± 1.11 vs. 3.19 ± 1.29 ng/mL, p = 0.98, respectively). No other parameters were identified that may have been influenced by the NPWT treatment. CONCLUSION: NPWT in T2DM patients with neuropathic, noninfected DFU seems to lead to reduction of the Ang2 level. Influencing the level of Ang2 may constitute one of NPWT-related mechanisms to accelerate wound healing.

The utility of MODY Probability Calculator in probands of families with early-onset autosomal dominant diabetes from Poland.

BACKGROUND: Maturity-onset diabetes of the young (MODY) accounts for 1-2% of all diabetes cases. Unfortunately, circa 90% of MODY cases are misdiagnosed as type 1 or type 2 diabetes. A proper genetic diagnosis based on automatic sequencing is crucial for the use of a tailored treatment. However, this method is still expensive and, thus, patients' selection for testing should be performed precisely. In 2012, an easy-to-use tool was developed in Exeter, UK, to support genetic testing for MODY in the British population. The aim of the study was to assess the utility of MODY Probability Calculator in probands from Polish families with early-onset autosomal dominant diabetes. METHODS: We have performed a retrospective analysis of 155 probands who were qualified for genetic testing between 2006 and 2018. Probands were recruited for MODY testing based on the following criteria: 1) early age of diagnosis (≤35 years); 2) a positive, multigenerational family history of diabetes. Automatic sequencing, Sanger and, in case of initial negative results, new generation sequencing (NGS) of a set of 28 genes, were performed. MODY Probability was calculated on the website www.diabetesgenes.org. RESULTS: The group of probands consisted of 64 GCK-, 37 HNF1A-, and three HNF4A-MODY patients and 51 NGS-negative subjects. The median positive predictive value (PPV) was 75.5% (95% CI: 75.5-75.5%), 49.4% (95% CI: 24.4-75.5%), 45.5% (95% CI: 21.0-75.5%) and 49.4% (95% CI: 32.9-75.5%) for GCK-, HNF1A-, HNF4A-MODY and NGS-negative, respectively. The discriminative accuracy, as expressed by AUC, of PPV between MODY and NGS negative groups was 0.62 (95% CI: 0.52-0.71) with the corresponding sensitivity of 71.2% and specificity of 51.0%. CONCLUSIONS: In this highly pre-selected group of probands that were qualified for genetic testing based on clinical features, the use of MODY Probability Calculator would not substantially improve the patients' selection process for genetic testing. Further efforts to improve this tool are desirable.

Characteristics of gut microbiota in adult patients with type 1 and type 2 diabetes based on next­generation sequencing of the 16S rRNA gene fragment.

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). Next­generation 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 high­density 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. Next­generation sequencing allows a rapid identification of the DNA of all bacteria present in the sample and their taxonomic classification.

Continuous subcutaneous insulin infusion vs multiple daily injections in pregnant women with type 1 diabetes mellitus: a systematic review and meta-analysis of randomised controlled trials and observational studies.

BACKGROUND: Randomised controlled trials (RCTs) have shown an advantage of continuous subcutaneous insulin infusion (CSII) over multiple daily injections (MDI) in the general type 1 diabetes mellitus (T1DM) population. RCT data on T1DM management in pregnancy remain limited. OBJECTIVE: We performed a systematic review of both RCTs and non-RCTs evaluating CSII vs MDI in T1DM-complicated pregnancy. STUDY DESIGN: Electronic databases were searched for studies comparing CSII with MDI in T1DM-complicated pregnancy. METHODS: A meta-analysis provided point estimates with 95% confidence intervals (CI). Continuous outcomes were reported as weighted mean differences (WMD) or standardised mean differences (SMD), and dichotomous data as relative risk (RR). RESULTS: The search identified 47 studies, including 43 non-RCTs, reporting on 7824 pregnancies. The meta-analysis showed a lower HbA1c level with CSII vs MDI in the first trimester (WMD: -0.45%; 95%CI: -0.62, -0.27). This difference decreased in subsequent trimesters. Compared to MDI, therapy with CSII resulted in higher gestational weight gain (GWG) (WMD: 1.02 kg; 95%CI: 0.41, 1.62), and lower daily insulin dose requirements in the first (SMD: -0.46; 95%CI: -0.68, -0.24) and subsequent trimesters. Moreover, infants from the CSII group were more likely to be large for gestational age (LGA) (RR: 1.16; 95%CI: 1.07, 1.24) and less likely to be small for gestational age (SGA) (RR: 0.66; 95%CI: 0.45; 0.97). CONCLUSIONS: 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.