Analysis of single nucleotide polymorphisms implicate mTOR signalling in the development of new-onset diabetes after transplantation

Introduction
Despite excellent first year outcomes in kidney transplantation, there remain significant long-term complications related to new-onset diabetes after transplantation (NODAT). The purpose of this study was to validate the findings of previous investigations of candidate gene variants in patients undergoing a protocolised, contemporary immunosuppression regimen, using detailed serial biochemical testing to identify NODAT development.

Methods
One hundred twelve live and deceased donor renal transplant recipients were prospectively followed-up for NODAT onset, biochemical testing at days 7, 90, and 365 after transplantation. Sixty-eight patients were included after exclusion for non-white ethnicity and pre-transplant diabetes. Literature review to identify candidate gene variants was undertaken as described previously.

Results
Over 25% of patients developed NODAT. In an adjusted model for age, sex, BMI, and BMI change over 12 months, five out of the studied 37 single nucleotide polymorphisms (SNPs) were significantly associated with NODAT: rs16936667:PRDM14 OR 10.57;95% CI 1.8–63.0;p = 0.01, rs1801282:PPARG OR 8.5; 95% CI 1.4–52.7; p = 0.02, rs8192678:PPARGC1A OR 0.26; 95% CI 0.08–0.91; p = 0.03, rs2144908:HNF4A OR 7.0; 95% CI 1.1–45.0;p = 0.04 and rs2340721:ATF6 OR 0.21; 95%CI 0.04–1.0; p = 0.05.

Conclusion
This study represents a replication study of candidate SNPs associated with developing NODAT and implicates mTOR as the central regulator via altered insulin sensitivity, pancreatic β cell, and mitochondrial survival and dysfunction as evidenced by the five SNPs.

General significance
1) Highlights the importance of careful biochemical phenotyping with oral glucose tolerance tests to diagnose NODAT in reducing time to diagnosis and missed cases.
2)This alters potential genotype:phenotype association.
3)The replication study generates the hypothesis that mTOR signalling pathway may be involved in NODAT development.

Seasonal variation in month of diagnosis in children with type 1 diabetes registered in 23 European centers during 1989-2008: little short-term influence of sunshine hours or average temperature

BACKGROUND: The month of diagnosis in childhood type 1 diabetes shows seasonal variation.

OBJECTIVE: We describe the pattern and investigate if year-to-year irregularities are associated with meteorological factors using data from 50 000 children diagnosed under the age of 15 yr in 23 population-based European registries during 1989-2008.

METHODS: Tests for seasonal variation in monthly counts aggregated over the 20 yr period were performed. Time series regression was used to investigate if sunshine hour and average temperature data were predictive of the 240 monthly diagnosis counts after taking account of seasonality and long term trends.

RESULTS: Significant sinusoidal pattern was evident in all but two small centers with peaks in November to February and relative amplitudes ranging from ±11 to ±38% (median ±17%). However, most centers showed significant departures from a sinusoidal pattern. Pooling results over centers, there was significant seasonal variation in each age-group at diagnosis, with least seasonal variation in those under 5 yr. Boys showed greater seasonal variation than girls, particularly those aged 10-14 yr. There were no differences in seasonal pattern between four 5-yr sub-periods. Departures from the sinusoidal trend in monthly diagnoses in the period were significantly associated with deviations from the norm in average temperature (0.8% reduction in diagnoses per 1 °C excess) but not with sunshine hours.

CONCLUSIONS: Seasonality was consistently apparent throughout the period in all age-groups and both sexes, but girls and the under 5 s showed less marked variation. Neither sunshine hour nor average temperature data contributed in any substantial way to explaining departures from the sinusoidal pattern.

A cross-sectional study demonstrating increased serum amyloid A-related inflammation in high density lipoproteins from subjects with type 1 diabetes mellitus and how this association was augmented by poor glycaemic control

Inflammatory atherosclerosis is increased in subjects with type 1 diabetes mellitus (T1DM). Normally high-density lipoproteins(HDL) protect against atherosclerosis; however, in the presence of serum amyloid-A- (SAA-) related inflammation this propertymay be reduced. Fasting blood was obtained from fifty subjects with T1DM, together with fifty age, gender and BMI matchedcontrol subjects. HDL was subfractionated into HDL2 and HDL3 by rapid ultracentrifugation. Serum-hsCRP and serum-, HDL2-,and HDL3-SAA were measured by ELISAs. Compared to control subjects, SAA was increased in T1DM subjects, nonsignificantly inserum (P = 0.088), and significantly in HDL2 (P  = 0.003) and HDL3 (P  = 0.005). When the T1DM group were separated accordingto mean HbA1c (8.34%), serum-SAA and HDL3-SAA levels were higher in the T1DM subjects with HbA1c ≥ 8.34%, compared towhen HbA1c was <8.34% (P  < 0.05). Furthermore, regression analysis illustrated, that for every 1%-unit increase in HbA1c, SAAincreased by 20% and 23% in HDL2 and HDL3, respectively, independent of BMI. HsCRP did not differ between groups (P  > 0.05).This cross-sectional study demonstrated increased SAA-related inflammation in subjects with T1DM that was augmented by poorglycaemic control. We suggest that SAA is a useful inflammatory biomarker in T1DM, which may contribute to their increasedatherosclerosis risk.