Gut microbiota in children with type 1 diabetes differs from that in healthy children: a case-control study.

BACKGROUND A recent study using a rat model found significant differences at the time of diabetes onset in the bacterial communities responsible for type 1 diabetes modulation. We hypothesized that type 1 diabetes in humans could also be linked to a specific gut microbiota. Our aim was to quantify and evaluate the difference in the composition of gut microbiota between children with type 1 diabetes and healthy children and to determine the possible relationship of the gut microbiota of children with type 1 diabetes with the glycemic level. METHODS A case-control study was carried out with 16 children with type 1 diabetes and 16 healthy children. The fecal bacteria composition was investigated by polymerase chain reaction-denaturing gradient gel electrophoresis and real-time quantitative polymerase chain reaction. RESULTS The mean similarity index was 47.39% for the healthy children and 37.56% for the children with diabetes, whereas the intergroup similarity index was 26.69%. In the children with diabetes, the bacterial number of Actinobacteria and Firmicutes, and the Firmicutes to Bacteroidetes ratio were all significantly decreased, with the quantity of Bacteroidetes significantly increased with respect to healthy children. At the genus level, we found a significant increase in the number of Clostridium, Bacteroides and Veillonella and a significant decrease in the number of Lactobacillus, Bifidobacterium, Blautia coccoides/Eubacterium rectale group and Prevotella in the children with diabetes. We also found that the number of Bifidobacterium and Lactobacillus, and the Firmicutes to Bacteroidetes ratio correlated negatively and significantly with the plasma glucose level while the quantity of Clostridium correlated positively and significantly with the plasma glucose level in the diabetes group. CONCLUSIONS This is the first study showing that type 1 diabetes is associated with compositional changes in gut microbiota. The significant differences in the number of Bifidobacterium, Lactobacillus and Clostridium and in the Firmicutes to Bacteroidetes ratio observed between the two groups could be related to the glycemic level in the group with diabetes. Moreover, the quantity of bacteria essential to maintain gut integrity was significantly lower in the children with diabetes than the healthy children. These findings could be useful for developing strategies to control the development of type 1 diabetes by modifying the gut microbiota.

Prevalence and Clinical Characteristics of HIV Type 1-Infected Patients Receiving Dialysis in Spain: Results of a Spanish Survey in 2006: GESIDA 48/05 Study

End-stage renal diseases (ESRD) are becoming more frequent in HIV-infected patients. In Europe there is little information about HIV-infected patients on dialysis. A cross-sectional multicenter survey in 328 Spanish dialysis units was conducted in 2006. Information from 14,876 patients in dialysis was obtained (81.6% of the Spanish dialysis population). Eighty-one were HIV infected (0.54%; 95% CI, 0.43-0.67), 60 were on hemodialysis, and 21 were on peritoneal dialysis. The mean (range) age was 45 (28-73) years. Seventy-two percent were men and 33% were former drug users. The mean (range) time of HIV infection was 11 (1-27) years and time on dialysis was 4.6 (0.4-25) years. ESRD was due to glomerulonephritis (36%) and diabetes (15%). HIV-associated nephropathy was not reported. Eighty-five percent were on HAART, 76.5% had a CD4 T cell count above 200 cells, and 73% had undetectable viral load. Thirty-nine percent of patients met criteria for inclusion on the renal transplant (RT) waiting list but only 12% were included. Sixty-one percent had HCV coinfection. HCV-coinfected patients had a longer history of HIV, more previous AIDS events, parenteral transmission as the most common risk factor for acquiring HIV infection, and less access to the RT waiting list (p < 0.05). The prevalence of HIV infection in Spanish dialysis units in 2006 was 0.54% HCV coinfection was very frequent (61%) and the percentage of patients included on the Spanish RT waiting list was low (12%).

IL2RA/CD25 gene polymorphisms: uneven association with multiple sclerosis (MS) and type 1 diabetes (T1D).

BACKGROUND: IL-2 receptor (IL2R) alpha is the specific component of the high affinity IL2R system involved in the immune response and in the control of autoimmunity. METHODS AND RESULTS: Here we perform a replication and fine mapping of the IL2RA gene region analyzing 3 SNPs previously associated with multiple sclerosis (MS) and 5 SNPs associated with type 1 diabetes (T1D) in a collection of 798 MS patients and 927 matched Caucasian controls from the south of Spain. We observed association with MS in 6 of 8 SNPs. The rs1570538, at the 3'- UTR extreme of the gene, previously reported to have a weak association with MS, is replicated here (P = 0.032). The most associated T1D SNP (rs41295061) was not associated with MS in the present study. However, the rs35285258, belonging to another independent group of SNPs associated with T1D, showed the maximal association in this study but different risk allele. We replicated the association of only one (rs2104286) of the two IL2RA SNPs identified in the recently performed genome-wide association study of MS. CONCLUSIONS: These findings confirm and extend the association of this gene with MS and reveal a genetic heterogeneity of the associated polymorphisms and risk alleles between MS and T1D suggesting different immunopathological roles of IL2RA in these two diseases.

Expert study: A bolus calculator improves glycemic control and quality of life of type 1 diabetic patients (T1DM) (preliminary results)

Aims: To evaluate the impact on glycemic control and quality of life of a bolus calculator. Methods: Multicentre randomized prospective crosssectional study. Patients were randomized to control phase (3 months; calculation of prandial insulin according to insulinto-carbohydrate ratio and insulin sensitivity factor using a single strip meter) or intervention phase (3 months; calculation of prandial insulin with a bolus advisor), with a washout period (3 months). Patients wore a continuous glucosensor (7 days) and answered a quality of life questionnaire at the beginning and at the end of each phase. A questionnaire of satisfaction was obtained at the end of both phases. Inclusion criteria: Adults; T1DM> 1 year, HbA1c > 7.5%, basal-bolus therapy with insulin analogs, experience with carbohydrate Results: Data from the first 32 subjects with at least 1 ended phase (27 females, age 38 – 11 years, diabetes duration 16.8 – 7.5 years). Basal characteristics were comparable independently of the starting phase. No differences were found between phases in terms of mean blood glucose, standard deviation (from meter neither from sensor) and satisfaction. Conclusions: The use of a bolus calculator improves glycemic control and quality of life of T1DM subjects.