234 resultados para TYPE I DIABETES
Resumo:
AIMS/HYPOTHESIS: Parental type 2 diabetes mellitus increases the risk of diabetic nephropathy in offspring with type 1 diabetes mellitus. Several single nucleotide polymorphisms (SNPs) that predispose to type 2 diabetes mellitus have recently been identified. It is, however, not known whether such SNPs also confer susceptibility to diabetic nephropathy in patients with type 1 diabetes mellitus. METHODS: We genotyped nine SNPs associated with type 2 diabetes mellitus in genome-wide association studies in the Finnish population, and tested for their association with diabetic nephropathy as well as with severe retinopathy and cardiovascular disease in 2,963 patients with type 1 diabetes mellitus. Replication of significant SNPs was sought in 2,980 patients from three other cohorts. RESULTS: In the discovery cohort, rs10811661 near gene CDKN2A/B was associated with diabetic nephropathy. The association remained after robust Bonferroni correction for the total number of tests performed in this study (OR 1.33 [95% CI 1.14, 1.56], p?=?0.00045, p (36tests)?=?0.016). In the meta-analysis, the combined result for diabetic nephropathy was significant, with a fixed effects p value of 0.011 (OR 1.15 [95% CI 1.02, 1.29]). The association was particularly strong when patients with end-stage renal disease were compared with controls (OR 1.35 [95% CI 1.13, 1.60], p?=?0.00038). The same SNP was also associated with severe retinopathy (OR 1.37 [95% CI 1.10, 1.69] p?=?0.0040), but the association did not remain after Bonferroni correction (p (36tests)?=?0.14). None of the other selected SNPs was associated with nephropathy, severe retinopathy or cardiovascular disease. CONCLUSIONS/INTERPRETATION: A SNP predisposing to type 2 diabetes mellitus, rs10811661 near CDKN2A/B, is associated with diabetic nephropathy in patients with type 1 diabetes mellitus.
Resumo:
Aim
To assess the association of POMC haplotype-tagged single nucleotide polymorphisms (htSNPs) with the development of type 1 diabetes (T1D) in a Caucasian population.
Methods
All exons, intron 1, and approximately 6-kb upstream and 3-kb downstream of the POMC gene were bidirectionally resequenced to identify DNA polymorphisms in 30 individuals. Allele frequencies were determined (60 chromosomes) and efficient htSNPs were selected using the htSNP2 programme. Genotyping was performed in 390 cases, 339 controls and 245 T1D parent-offspring trios, using Taqman, Sequenom and direct-sequencing technologies.
Results
Thirteen polymorphisms (two novel) with a minor allele frequency greater than 1% were identified. Six POMC htSNPs (rs3754863 G>A, ss161151662 A>G, rs3754860 C>T, rs1009388 G>C, rs3769671 A>C, rs1042571 G>A) were identified. Allele and haplotype frequencies were similar between case and control groups (P>0.60 by permutation test), and assessment of allele transmission distortion from informative parents to affected offspring also failed to find any association. Stratification of these analyses for age-at-onset and HLA-DR risk group (DR3/DR4) revealed no significant associations. A haplotype block of 9.86-kb from rs3754863 to rs1042571 was identified, encompassing the POMC gene. Comparison of haplotype frequencies identified the GGCGAG haplotype as protective against T1D in 12.9% of cases vs. 18.3% of controls: ?2=8.18, Pc=0.03 by permutation test.
Conclusion
The POMC SNP haplotype GGCGAG may have a protective effect against T1D in the UK population. However, this finding needs to be replicated, and the cellular and molecular processes influenced by this POMC haplotype determined to fully appreciate its impact.
Resumo:
Objectives: To investigate seasonal variation in month of diagnosis in children with type 1 diabetes registered in EURODIAB centres during 1989-2008.
Methods: 23 population-based registers recorded date of diagnosis in new cases of clinically diagnosed type 1 diabetes in children aged under 15 years. Completeness of ascertainment was assessed through capture-recapture methodology and was high in most centres. A general test for seasonal variation (11df) and Edward's test for sinusoidal (sine wave) variation (2df) were employed. Time series methods were also used to investigate if meteorological data were predictive of monthly counts after taking account of seasonality and long term trends.
Results: Significant seasonal variation was apparent in all but two small centres, with an excess of cases apparent in the winter quarter. Significant sinusoidal pattern was also evident in all but two small centres with peaks in December (14 centres), January (5 centres) or February (2 centres). Relative amplitude varied from ±11% to ±39% (median ±18%). There was no relationship across the centres between relative amplitude and incidence level. However there was evidence of significant deviation from the sinusoidal pattern in the majority of centres. Pooling results over centres, there was significant seasonal variation in each age-group at diagnosis, but with significantly less variation in those aged under 5 years. Boys showed marginally greater seasonal variation than girls. There were no differences in seasonal pattern between four sub-periods of the 20 year period. In most centres monthly counts of cases were not associated with deviations from normal monthly average temperature or sunshine hours; short term meteorological variations do not explain numbers of cases diagnosed.
Conclusions: Seasonality with a winter excess is apparent in all age-groups and both sexes, but girls and the under 5s show less marked variation. The seasonal pattern changed little in the 20 year period.
Resumo:
Background and aims: In 1989 a number of registers in Europe began recording new cases of type 1 diabetes diagnosed in children aged under 15 years using a common protocol. Trends in incidence rate during the 20 year period 1989-2008 are described.
Materials and methods: All registers operate in geographically defined regions and are based on a clinical diagnosis. When possible, completeness of registration in each register is assessed using capture-recapture methodology by identifying primary and secondary sources of ascertainment. The completeness estimate is obtained by identifying the numbers of cases identified by the primary source only, by the secondary source only and by both the primary and the secondary sources.
Results: Other registers have joined the Group since 1989, and 21 registers in 15 countries continue to submit registration data. In the first five years (1989-93) incidence rates varied from 3.2 per 100,000 in the Former Yugoslav Republic of Macedonia to 25.8 per 100,000 in the Stockholm area of Sweden. In the last five years (2004-2008) these same two registers again had the lowest and highest incidence, but rates had increased to 5.8 per 100,000 and 36.6 per 100,000, respectively. During the 20 year period all but two of the 21 registers showed statistically significant rates of increase (median rate of increase 4% per annum), and similar figures were obtained when this median rate of increase was estimated for the first half of the period (1989-98) and for the second half (1999-2008) . However, rates of increase differed significantly between the first half and the second half of the period for eight of the 17 registers with adequate coverage of both periods; four registers showing significantly higher rates of increase in the first half and four significantly higher rates in the second half.
Conclusion: The childhood type 1 diabetes incidence rate continues to rise across Europe by approximately 4% per annum, but the increase within a register is not necessarily uniform with periods of less rapid and more rapid increase in incidence occurring in some registers. This pattern of change suggests that important risk exposures differ over time in different European countries. Further time trend analysis and comparison of the patterns in defined regions are warranted.
Resumo:
Background and aims: In 1989 a number of registers in Europe began recording new cases of type 1 diabetes diagnosed in children aged under 15 years using a common protocol. Trends in incidence rate during the 20 year period 1989-2008 are described.
Materials and methods: All registers operate in geographically defined regions and are based on a clinical diagnosis. When possible, completeness of registration in each register is assessed using capture-recapture methodology by identifying primary and secondary sources of ascertainment. The completeness estimate is obtained by identifying the numbers of cases identified by the primary source only, by the secondary source only and by both the primary and the secondary sources.
Results: Other registers have joined the Group since 1989, and 21 registers in 15 countries continue to submit registration data. In the first five years (1989-93) incidence rates varied from 3.2 per 100,000 in the Former Yugoslav Republic of Macedonia to 25.8 per 100,000 in the Stockholm area of Sweden. In the last five years (2004-2008) these same two registers again had the lowest and highest incidence, but rates had increased to 5.8 per 100,000 and 36.6 per 100,000, respectively. During the 20 year period all but two of the 21 registers showed statistically significant rates of increase (median rate of increase 4% per annum), and similar figures were obtained when this median rate of increase was estimated for the first half of the period (1989-98) and for the second half (1999-2008) . However, rates of increase differed significantly between the first half and the second half of the period for eight of the 17 registers with adequate coverage of both periods; four registers showing significantly higher rates of increase in the first half and four significantly higher rates in the second half.
Conclusion: The childhood type 1 diabetes incidence rate continues to rise across Europe by approximately 4% per annum, but the increase within a register is not necessarily uniform with periods of less rapid and more rapid increase in incidence occurring in some registers. This pattern of change suggests that important risk exposures differ over time in different European countries. Further time trend analysis and comparison of the patterns in defined regions are warranted.
Resumo:
Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ~2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P?=?1.2×10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P?=?2.0×10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-ß1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P?=?2.1×10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.
Resumo:
Diabetic nephropathy (DN) affects about 30% of patients with type 1 diabetes (T1D) and contributes to serious morbidity and mortality. So far only the 3q21-q25 region has repeatedly been indicated as a susceptibility region for DN. The aim of this study was to search for new DN susceptibility loci in Finnish, Danish and French T1D families.
Resumo:
To investigate the association between polymorphisms of the aldose reductase gene and diabetic nephropathy in both Type 1 and Type 2 diabetes mellitus, and to carry out a meta-analysis of published results.
Resumo:
Linkage and association has been reported between CTLA4 DNA markers and susceptibility to type 1 diabetes in some populations, but not others. We performed case-control and family-based association studies to assess if the CTLA4 A49G and intron 1 C/T polymorphisms were associated with development of early onset type 1 diabetes in the Northern Ireland population. The distribution of A49G and C/T alleles in cases (n = 144) was similar to those observed in controls (n = 307). In contrast, significant distortions in allele transmissions from informative parents to probands were observed for both the A49G (P = 0.02) and C/T (P = 0.01) polymorphisms employing 297 nuclear families. Our results suggest that the CTLA4 gene may play a minor role in the overall genetic predisposition to type 1 diabetes in this UK population.