Genome-wide Association Study of Change in Fasting Glucose over time in 13,807 non-diabetic European Ancestry Individuals

Genome-wide Association Study of Change in Fasting Glucose over time in 13,807 non-diabetic European Ancestry Individuals
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DOI:
10.1038/s41598-019-45823-7
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发表时间:
2019-07-01
期刊:
影响因子:
4.6
通讯作者:
Bouatia-Naji, Nabila
Bouatia-Naji, Nabila
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Liu, Ching-Ti;Merino, Jordi;Bouatia-Naji, Nabila

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2型糖尿病(T2 D)影响着全球数百万人的健康。随着时间的推移,与糖尿病的变化相关的遗传决定因素的识别可能会阐明T2 D发展之前的生物学特征。在这里,我们对来自9个队列的多达13,807名欧洲血统的非糖尿病个体的纵向空腹血糖变化进行了全基因组关联研究。空腹血糖随时间的变化定义为通过长达14年的观察获得的多次空腹血糖测量值定义的线的斜率。我们检测了遗传变异与随时间推移的反正态转换空腹血糖变化的相关性,调整了基线时的年龄、性别和遗传变异的主成分。我们没有发现全基因组的显著关联(P < 5 × 10(-8))与空腹血糖随时间的变化。先前与T2 D、空腹血糖或HbA 1c相关的7个位点与空腹血糖随时间的变化名义上相关(P < 0.05)。有限的功率影响明确的解释,但这些数据表明,遗传对空腹血糖随时间变化的影响可能很小。该数据的公开版本提供了基因组资源,可与未来的研究联合收割机相结合,以评估与T2 D和其他代谢风险特征的共同遗传联系。
Type 2 diabetes (T2D) affects the health of millions of people worldwide. The identification of genetic determinants associated with changes in glycemia over time might illuminate biological features that precede the development of T2D. Here we conducted a genome-wide association study of longitudinal fasting glucose changes in up to 13,807 non-diabetic individuals of European descent from nine cohorts. Fasting glucose change over time was defined as the slope of the line defined by multiple fasting glucose measurements obtained over up to 14 years of observation. We tested for associations of genetic variants with inverse-normal transformed fasting glucose change over time adjusting for age at baseline, sex, and principal components of genetic variation. We found no genome-wide significant association (P < 5 x 10(-8)) with fasting glucose change over time. Seven loci previously associated with T2D, fasting glucose or HbA1c were nominally (P < 0.05) associated with fasting glucose change over time. Limited power influences unambiguous interpretation, but these data suggest that genetic effects on fasting glucose change over time are likely to be small. A public version of the data provides a genomic resource to combine with future studies to evaluate shared genetic links with T2D and other metabolic risk traits.