妊娠初期HbA1c値および空腹時血糖値と妊娠糖尿病発症との関連の検討（TWC Study）

第3回日本DOHaD研究会学術集会　抄録集　【ポスター発表

Quantitative Relationship Between Cumulative Risk Alleles Based on Genome-Wide Association Studies and Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis

Many epidemiological studies have assessed the genetic risk of having undiagnosed or of developing type 2 diabetes mellitus (T2DM) using several single nucleotide polymorphisms (SNPs) based on findings of genome-wide association studies (GWAS). However, the quantitative association of cumulative risk alleles (RAs) of such SNPs with T2DM risk has been unclear. The aim of this meta-analysis is to review the strength of the association between cumulative RAs and T2DM risk. Systematic literature searches were conducted for cross-sectional or longitudinal studies that examined odds ratios (ORs) for T2DM in relation to genetic profiles. Logarithm of the estimated OR (log OR) of T2DM for 1 increment in RAs carried (1-ΔRA) in each study was pooled using a random-effects model. There were 46 eligible studies that included 74,880 cases among 249,365 participants. In 32 studies with a cross-sectional design, the pooled OR for T2DM morbidity for 1-ΔRA was 1.16 (95% confidence interval [CI], 1.13–1.19). In 15 studies that had a longitudinal design, the OR for incident T2DM was 1.10 (95% CI, 1.08–1.13). There was large heterogeneity in the magnitude of log OR (P < 0.001 for both cross-sectional studies and longitudinal studies). The top 10 commonly used genes significantly explained the variance in the log OR (P = 0.04 for cross-sectional studies; P = 0.006 for longitudinal studies). The current meta-analysis indicated that carrying 1-ΔRA in T2DM-associated SNPs was associated with a modest risk of prevalent or incident T2DM, although the heterogeneity in the used genes among studies requires us to interpret the results with caution

Unstable bodyweight and incident type 2 diabetes mellitus: A meta-analysis

Aims/IntroductionThe present meta-analysis aimed to clarify the association of unstable bodyweight with the risk of type 2 diabetes mellitus, an association that has been controversial among longitudinal studies.Materials and MethodsAn electronic literature search using EMBASE and MEDLINE was followed up to 31 August 2016. The relative risks (RRs) of type 2 diabetes mellitus in individuals with unstable bodyweight were pooled using the inverse variance method.ResultsEight studies were eligible for the meta-analysis. The median duration of measurements of weight change and follow-up years for ascertaining type 2 diabetes mellitus were 13.5 and 9.4 years, respectively. The pooled RR for the least vs most stable category was 1.33 (95% confidence interval 1.12–1.57). Between-study heterogeneity was statistically significant (P = 0.048). Whether type 2 diabetes mellitus was ascertained by blood testing explained 66.0% of the variance in the logarithm of RR (P = 0.02). In three studies in which blood testing was carried out, type 2 diabetes mellitus risk was not significant (RR 1.06, 95% confidence interval 0.91–1.25). Furthermore, publication bias that inflated type 2 diabetes mellitus risk was statistically detected by Egger\u27s test (P = 0.09).ConclusionsUnstable bodyweight might be modestly associated with the elevated risk of type 2 diabetes mellitus; although serious biases, such as diagnostic suspicion bias and publication bias, made it difficult to assess this association

Association of Helicobacter pylori Infection with Glycemic Control in Patients with Diabetes: A Meta-Analysis

Objective. To assess the association between Helicobacter pylori (HP) infection and glycemic control in patients with diabetes through a meta-analytic approach. Research Design and Methods. Electronic literature searches were conducted for cross-sectional studies that examined the hemoglobin A1c (A1C) level by whether patients with diabetes were or were not carriers of HP. Mean differences in A1C between groups with and without HP infection were pooled with a random-effects model. Results. Thirteen eligible studies were included in this meta-analysis. Overall, the HP carriers did not have significantly higher A1C levels compared with HP noncarriers (mean difference (95% CI), 0.19% (−0.18 to 0.46), P = 0.16). When the analysis was limited to studies targeting patients with type 1 diabetes, there was also no significant difference in A1C (0.69% (−0.31 to 1.68), P = 0.18). Conclusions. There was insufficient evidence that HP infection worsened glycemic control in patients with diabetes

The Relationship between Diabetic Neuropathy and Sleep Apnea Syndrome: A Meta-Analysis

Aims. High prevalence of sleep apnea syndrome (SAS) has been reported in patients with diabetes. However, whether diabetic neuropathy (DN) contributes to this high prevalence is controversial. Our aim of this study is to compare the prevalence of SAS between patients with and without DN. Methods. Systematic literature searches were conducted for cross-sectional studies that reported the number of patients with DN and SAS using MEDLINE (from 1966 to Nov 5, 2012) and EMBASE (from 1974 to Nov 5, 2012). Odds ratios (ORs) of SAS related to DN were pooled with the Mantel-Haenszel method. Results. Data were obtained from 5 eligible studies (including 6 data sets, 880 participants, and 429 cases). Overall, the pooled OR of SAS in patients with DN compared with that in non-DN patients was significant (OR (95% CI), −1.95 (1.03–3.70)). The pooled OR of SAS was 1.90 (0.97–3.71) in patients with type 2 diabetes. Excluding data on patients with type 1 diabetes, a higher OR was observed in younger patients (mean age <60 years) than in those ≥60 years among whom the OR remained significant (3.82; 95% CI, 2.24–6.51 and 1.17; 95% CI, 0.81–1.68). Conclusions. Current meta-analysis suggested the association of some elements of neuropathy with SAS in type 2 diabetes. Further investigations are needed to clarify whether the association is also true for patients with type 1 diabetes

Quantitative Relationship Between Cumulative Risk Alleles Based on Genome-Wide Association Studies and Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis

Many epidemiological studies have assessed the genetic risk of having undiagnosed or of developing type 2 diabetes mellitus (T2DM) using several single nucleotide polymorphisms (SNPs) based on findings of genome-wide association studies (GWAS). However, the quantitative association of cumulative risk alleles (RAs) of such SNPs with T2DM risk has been unclear. The aim of this meta-analysis is to review the strength of the association between cumulative RAs and T2DM risk. Systematic literature searches were conducted for cross-sectional or longitudinal studies that examined odds ratios (ORs) for T2DM in relation to genetic profiles. Logarithm of the estimated OR (log OR) of T2DM for 1 increment in RAs carried (1-ΔRA) in each study was pooled using a random-effects model. There were 46 eligible studies that included 74,880 cases among 249,365 participants. In 32 studies with a cross-sectional design, the pooled OR for T2DM morbidity for 1-ΔRA was 1.16 (95% confidence interval [CI], 1.13–1.19). In 15 studies that had a longitudinal design, the OR for incident T2DM was 1.10 (95% CI, 1.08–1.13). There was large heterogeneity in the magnitude of log OR (P < 0.001 for both cross-sectional studies and longitudinal studies). The top 10 commonly used genes significantly explained the variance in the log OR (P = 0.04 for cross-sectional studies; P = 0.006 for longitudinal studies). The current meta-analysis indicated that carrying 1-ΔRA in T2DM-associated SNPs was associated with a modest risk of prevalent or incident T2DM, although the heterogeneity in the used genes among studies requires us to interpret the results with caution

Alcohol Consumption and Risk of Atrial Fibrillation A Meta-Analysis

ObjectivesThe purpose of this meta-analysis is to summarize the estimated risk of atrial fibrillation (AF) related to alcohol consumption.BackgroundResults from observational studies examining the relationship between alcohol consumption and AF are inconsistent.MethodsA systematic electronic search of Medline (January 1966 to December 2009) and Embase (January 1974 to December 2009) databases was conducted for studies using key words related to alcohol and AF. Studies were included if data on effect measures for AF associated with habitual alcohol intake were reported or could be calculated. The effect measures for AF for the highest versus lowest alcohol intake in individual studies were pooled with a variance-based method. Linear and spline regression analyses were conducted to quantify the relationship between alcohol intake and AF risk.ResultsFourteen eligible studies were included in this meta-analysis. The pooled estimate of AF for the highest versus the lowest alcohol intake was 1.51 (95% confidence interval: 1.31 to 1.74). A linear regression model showed that the pooled estimate for an increment of 10 g per day alcohol intake was 1.08 (95% confidence interval: 1.05 to 1.10; R2 = 0.43, p < 0.001). A spline regression model also indicated that the AF risk increased with increasing levels of alcohol consumption.ConclusionsResults of this meta-analysis suggest that not consuming alcohol is most favorable in terms of AF risk reduction