OBJECTIVE Despite extensive evidence for genetic susceptibility to diabetic nephropathy, the identification of susceptibility genes and their variants has had limited success. To search for genes that contribute to diabetic nephropathy, a genome-wide association scan was implemented on the Genetics of Kidneys in Diabetes collection. RESEARCH DESIGN AND METHODS We genotyped ∼360,000 single nucleotide polymorphisms (SNPs) in 820 case subjects (284 with proteinuria and 536 with end-stage renal disease) and 885 control subjects with type 1 diabetes. Confirmation of implicated SNPs was sought in 1,304 participants of the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, a long-term, prospective investigation of the development of diabetes-associated complications. RESULTS A total of 13 SNPs located in four genomic loci were associated with diabetic nephropathy with P < 1 × 10−5. The strongest association was at the FRMD3 (4.1 protein ezrin, radixin, moesin [FERM] domain containing 3) locus (odds ratio [OR] = 1.45, P = 5.0 × 10−7). A strong association was also identified at the CARS (cysteinyl-tRNA synthetase) locus (OR = 1.36, P = 3.1 × 10−6). Associations between both loci and time to onset of diabetic nephropathy were supported in the DCCT/EDIC study (hazard ratio [HR] = 1.33, P = 0.02, and HR = 1.32, P = 0.01, respectively). We demonstratedexpression of both FRMD3 and CARS in human kidney. CONCLUSIONS We identified genetic associations for susceptibility to diabetic nephropathy at two novel candidate loci near the FRMD3 and CARS genes. Their identification implicates previously unsuspected pathways in the pathogenesis of this important late complication of type 1 diabetes.
22 October 2016 in European Journal of Clinical Microbiology & Infectious Diseases
Blood is considered to be a sterile microenvironment, in which bacteria appear only periodically. Previously used methods allowed only for the detection of either viable bacteria with low sensitivity or selected species of bacteria. The Next-Generation Sequencing method (NGS) enables the identification of all bacteria in the sample with their taxonomic classification. We used NGS for the analysis of blood samples from healthy volunteers (n = 23) and patients with sepsis (n = 62) to check whether any bacterial DNA exists in the blood of healthy people and to identify bacterial taxonomic profile in the blood of septic patients. The presence of bacterial DNA was found both in septic and healthy subjects; however, bacterial diversity was significantly different (P = 0.002) between the studied groups. Among healthy volunteers, a significant predominance of anaerobic bacteria (76.2 %), of which most were bacteria of the order Bifidobacteriales (73.0 %), was observed. In sepsis, the majority of detected taxa belonged to aerobic or microaerophilic microorganisms (75.1 %). The most striking difference was seen in the case of Actinobacteria phyla, the abundance of which was decreased in sepsis (P < 0.001) and Proteobacteria phyla which was decreased in the healthy volunteers (P < 0.001). Our research shows that bacterial DNA can be detected in the blood of healthy people and that its taxonomic composition is different from the one seen in septic patients. Detection of bacterial DNA in the blood of healthy people may suggest that bacteria continuously translocate into the blood, but not always cause sepsis; this observation can be called DNAemia.
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 theEnterococcusgenus 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 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, includingBifidobacterium adolescentis, may suggest benefits of microbial modification therapy.
1 April 2008 in Journal of the American Society of Nephrology
Progressive renal function decline begins in one third of patients with microalbuminuria and type 1 diabetes. This study examined whether this decline is associated with elevated excretion of inflammatory markers in urine. Five inflammatory markers (IL-6, IL-8, monocyte chemoattractant protein-1, interferon-gamma-inducible protein (IP-10), and macrophage inflammatory protein-1δ) were measured in urine samples from the First Joslin Study of the Natural History of Microalbuminuria in Type 1 Diabetes, a cohort recruited in 1991. Samples were obtained from 43 participants with microalbuminuria and stable renal function (nondecliners), from 28 with microalbuminuria and early progressive renal function decline (decliners), and from 74 with normoalbuminuria and stable renal function (reference). Urinary concentrations of all five inflammatory markers were significantly higher in decliners than in nondecliners, who were similar to the reference group. Multivariate analysis revealed that those with more than two markers elevated were more than five times as likely to have early progressive decline of renal function. In contrast, serum concentrations of C-reactive protein, IL-8, and macrophage inflammatory protein-1δ did not differ between decliners and nondecliners. These results support the hypothesis that inflammatory processes in the kidney contribute to the progression of nephropathy in patients with type 1 diabetes.
15 April 2018 in Polish Archives of Internal Medicine
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.