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基于孟德尔随机化分析儿童超重或肥胖与妊娠期糖尿病之间的关联。

Mendelian randomization analysis of the association between childhood overweight or obesity and gestational diabetes mellitus.

机构信息

School of Microelectronics, Tianjin University, Tianjin City, China.

Department of Pediatrics, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai City, China.

出版信息

Diabetes Obes Metab. 2024 Dec;26(12):6016-6022. doi: 10.1111/dom.15975. Epub 2024 Sep 30.

Abstract

OBJECTIVE

To investigate the association between childhood overweight or obesity and gestational diabetes mellitus (GDM).

METHODS

Data were sourced from the Genome-Wide Association Studies database on childhood body mass index (BMI), with 39 620 samples and 8 173 382 single-nucleotide polymorphisms (SNPs), and GDM, with 143 441 samples, including 12 332 GDM cases and 20 149 608 SNPs. Mendelian randomization (MR) was conducted, including inverse variance weighting (IVW), MR-Egger regression, and the weighted median method. Statistical heterogeneity among SNPs was assessed using Cochran's Q test. MR-Egger's intercept, the MR-Pleiotropy RESidual Sum and Outlier (PRESSO) test, and funnel plots were used to evaluate pleiotropy. The leave-one-out method tested the robustness of the IVW results by excluding individual SNPs.

RESULTS

Fifteen SNPs highly related to childhood BMI were identified. IVW analysis indicated that higher childhood BMI is a significant risk factor for GDM (odds ratio 1.50 [95% confidence interval 1.20-1.87]; p < 0.001). The direction of the β value derived from the weighted median method analysis was consistent with that from the IVW analysis. Cochran's Q test showed statistical heterogeneity among SNPs highly related to childhood BMI (p = 0.001), thus prioritizing IVW analysis results. The MR-Egger regression intercept, MR-PRESSO test, and funnel plot analyses demonstrated no horizontal pleiotropy among SNPs highly related to childhood BMI. The leave-one-out analysis indicated that the MR analysis results were largely unchanged after the exclusion of individual SNPs.

CONCLUSION

Elevated childhood BMI is associated with an increased risk of developing GDM, underscoring the need to address childhood obesity as a preventive strategy. Effective interventions to reduce childhood obesity could be crucial in mitigating this risk.

摘要

目的

探讨儿童超重或肥胖与妊娠期糖尿病(GDM)之间的关联。

方法

本研究的数据来源于儿童体重指数(BMI)的全基因组关联研究数据库,共纳入 39620 个样本和 8173382 个单核苷酸多态性(SNP),以及 GDM 病例 143441 例,包括 12332 例 GDM 病例和 20149608 个 SNP。采用逆方差加权(IVW)、MR-Egger 回归和加权中位数法进行孟德尔随机化(MR)分析。采用 Cochran's Q 检验评估 SNP 间的统计学异质性。采用 MR-Egger 截距、MR-Pleiotropy RESidual Sum and Outlier(PRESSO)检验和漏斗图评估偏倚。采用单样本剔除法(leave-one-out)剔除单个 SNP 以检验 IVW 结果的稳健性。

结果

共鉴定出与儿童 BMI 高度相关的 15 个 SNP。IVW 分析表明,较高的儿童 BMI 是 GDM 的显著危险因素(比值比 1.50[95%置信区间 1.20-1.87];p<0.001)。加权中位数法分析得到的β值方向与 IVW 分析一致。Cochran's Q 检验显示,与儿童 BMI 高度相关的 SNP 间存在统计学异质性(p=0.001),因此优先考虑 IVW 分析结果。MR-Egger 回归截距、MR-PRESSO 检验和漏斗图分析表明,与儿童 BMI 高度相关的 SNP 间不存在水平性偏倚。单样本剔除分析表明,剔除单个 SNP 后,MR 分析结果基本保持不变。

结论

儿童 BMI 升高与 GDM 风险增加相关,这强调了将儿童肥胖作为预防策略的重要性。采取有效的干预措施来减少儿童肥胖可能对降低这种风险至关重要。

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