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儿童肥胖与成人新型糖尿病亚型:一项孟德尔随机化和全基因组遗传相关性研究。

Childhood adiposity and novel subtypes of diabetes in adults: a Mendelian randomisation and genome-wide genetic correlation study.

作者信息

Wei Yuxia, Zhan Yiqiang, Carlsson Sofia

机构信息

Karolinska Institutet, Stockholm, Sweden.

Karolinska Institutet, Stockholm, Sweden; Sun Yat-sen University, Guangzhou, China.

出版信息

Lancet Glob Health. 2023 Mar;11 Suppl 1:S1. doi: 10.1016/S2214-109X(23)00086-4.

Abstract

BACKGROUND

Five novel subtypes of adult-onset diabetes were identified in 2018. We aimed to investigate whether childhood adiposity increases the risks of these subtypes using a Mendelian randomisation design, and to explore genetic overlaps between body size (self-reported perceived body size [ie, thinner, about average, or plumper] in childhood, and BMI measured in adulthood) and these subtypes.

METHODS

The Mendelian randomisation and genetic correlation analyses were based on summary statistics from European genome-wide association studies of childhood body size (n=453 169), adult BMI (n=359 983), latent autoimmune diabetes in adults (n=8581), severe insulin-deficient diabetes (n=3937), severe insulin-resistant diabetes (n=3874), mild obesity-related diabetes (n=4118), and mild age-related diabetes (n=5605). We identified 267 independent genetic variants as instrumental variables for childhood body size in the Mendelian randomisation analysis of latent autoimmune diabetes in adults and 258 independent genetic variants as instrumental variables for other diabetes subtypes. The inverse variance-weighted method was used as the primary estimator in the Mendelian randomisation analysis, supplemented by other Mendelian randomisation estimators. We calculated overall genetic correlations (rg) between childhood or adult adiposity and different subtypes using linkage disequilibrium score regression.

FINDINGS

A large childhood body size was associated with increased risk of latent autoimmune diabetes in adults (odds ratio [OR] 1·62, 95% CI 1·95-2·52), severe insulin-deficient diabetes (OR 2·45, 1·35-4·46), severe insulin-resistant diabetes (OR 3·08, 1·73-5·50), and mild obesity-related diabetes (OR 7·70, 4·32-13·7), but not mild age-related diabetes in the main Mendelian randomisation analysis. Other Mendelian randomisation estimators gave similar results and did not support the existence of horizontal pleiotropy. There was genetic overlap between childhood body size and mild obesity-related diabetes (rg 0·282; p=0·0003), and between adult BMI and all diabetes subtypes.

INTERPRETATION

This study provides genetic evidence that higher childhood adiposity is a risk factor for all subtypes of adult-onset diabetes, except mild age-related diabetes. It is therefore important to prevent and intervene in childhood overweight or obesity. There is shared genetic contribution to childhood obesity and mild obesity-related diabetes.

FUNDING

The study was supported by the China Scholarship Council, the Swedish Research Council (grant number 2018-03035), Research Council for Health, Working Life and Welfare (grant number 2018-00337), and Novo Nordisk Foundation (grant number NNF19OC0057274).

摘要

背景

2018年确定了五种成人发病型糖尿病的新亚型。我们旨在使用孟德尔随机化设计研究儿童肥胖是否会增加这些亚型的风险,并探讨体型(儿童时期自我报告的感知体型[即较瘦、中等或较胖]以及成年时测量的体重指数)与这些亚型之间的遗传重叠。

方法

孟德尔随机化和遗传相关性分析基于欧洲全基因组关联研究的汇总统计数据,这些研究涉及儿童体型(n = 453169)、成人BMI(n = 359983)、成人潜伏性自身免疫性糖尿病(n = 8581)、严重胰岛素缺乏性糖尿病(n = 3937)、严重胰岛素抵抗性糖尿病(n = 3874)、轻度肥胖相关性糖尿病(n = 4118)和轻度年龄相关性糖尿病(n = 5605)。在成人潜伏性自身免疫性糖尿病的孟德尔随机化分析中,我们确定了267个独立的遗传变异作为儿童体型的工具变量,以及258个独立的遗传变异作为其他糖尿病亚型的工具变量。逆方差加权法用作孟德尔随机化分析中的主要估计方法,并辅以其他孟德尔随机化估计方法。我们使用连锁不平衡评分回归计算儿童或成人肥胖与不同亚型之间的总体遗传相关性(rg)。

结果

在主要的孟德尔随机化分析中,儿童体型较大与成人潜伏性自身免疫性糖尿病风险增加相关(比值比[OR]为1.62,95%置信区间为1.95 - 2.52)、严重胰岛素缺乏性糖尿病(OR为2.45,1.35 - 4.46)、严重胰岛素抵抗性糖尿病(OR为3.08,1.73 - 5.50)和轻度肥胖相关性糖尿病(OR为7.70,4.32 - 13.7),但与轻度年龄相关性糖尿病无关。其他孟德尔随机化估计方法给出了类似的结果,不支持水平多效性的存在。儿童体型与轻度肥胖相关性糖尿病之间存在遗传重叠(rg为0.282;p = 0.0003),成人BMI与所有糖尿病亚型之间也存在遗传重叠。

解读

本研究提供了遗传证据,表明儿童期较高的肥胖是成人发病型糖尿病所有亚型的危险因素,但轻度年龄相关性糖尿病除外。因此,预防和干预儿童超重或肥胖很重要。儿童肥胖和轻度肥胖相关性糖尿病存在共同的遗传贡献。

资助

该研究得到了中国国家留学基金管理委员会、瑞典研究理事会(资助编号2018 - 03035)、卫生、工作生活和福利研究理事会(资助编号2018 - 00337)以及诺和诺德基金会(资助编号NNF19OC0057274)的支持。

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