Karrah Peterson, Camille E Powe, Quan Sun, Crystal Azure, Tia Azure, Hailey Davis, Kennedy Gourneau, Shyanna LaRocque, Craig Poitra, Sabra Poitra, Shayden Standish, Tyler J Parisien, Kelsey J Morin, Lyle G Best
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引用次数: 0
Abstract
Background/objectives: Gestational diabetes mellitus (GDM) is a state of hyperglycemia during pregnancy, increasing the risk of birth complications, and subsequent type 2 diabetes mellitus in the mother and offspring. Risk factors such as diet, obesity, and family history have demonstrated strong association with GDM, but no clear pathophysiology has been ascertained.
Methods: An analysis was conducted on 38 women with and 296 without GDM, within a case/control study of pre-eclampsia. The genetic variants examined were selected from among a published polygenic risk score of 10 variants (PRS-10). Genetic models were evaluated for each variant by multivariate logistic regression methods adjusted for age, body mass index, and pre-eclampsia. Since the genotypes for three of the PRS-10 were not available, a risk score comprising the total risk alleles among seven of the variants (PRS-7) was evaluated among those with all genotypes available.
Results: Multivariate logistic regression showed significant, independent, positive associations between body mass index (BMI) and age. The posited PRS-7 showed a trend (OR 1.56, 95% CI 0.92-2.56, p = 0.070), and sensitivity analysis comprising three variants (PRS-3) was significantly associated with GDM (OR 2.43, 95% CI 1.17-5.06, p = 0.017). In univariate analysis, rs1421085 was associated with GDM (OR 0.50, 95% CI 0.26-0.95, p = 0.034), but not after adjustment for covariates, and paradoxically not for the expected risk allele. None of the other six variants showed an individual association with GDM. The previously published meta-analysis of PRS-10 showed a degree of heterogeneity (pQ= 0.03) among the three cohorts analyzed, suggesting that variant effects may differ according to the genetic background, which points to the importance of examining the generalizability of any posited polygenic risk scores.
Conclusions: In conclusion, we provide additional support for and further refine the results of a previously published polygenic risk score for GDM in an ethically unrelated population.
背景/目的：妊娠期糖尿病（Gestational diabetes， GDM）是一种妊娠期高血糖状态，增加了母亲和后代发生出生并发症和随后发生2型糖尿病的风险。饮食、肥胖和家族史等危险因素已证实与GDM密切相关，但尚未明确病理生理机制。方法：在子痫前期病例/对照研究中，对38名患有GDM的女性和296名未患有GDM的女性进行分析。所检查的遗传变异是从已发表的10个多基因风险评分（PRS-10）中选择的。通过调整年龄、体重指数和先兆子痫的多变量logistic回归方法评估每个变异的遗传模型。由于无法获得其中3种PRS-10的基因型，因此在具有所有基因型的人群中评估了包含7种变异（PRS-7）中总风险等位基因的风险评分。结果：多因素logistic回归显示体重指数（BMI）与年龄呈正相关。假设的PRS-7显示出趋势（OR 1.56, 95% CI 0.92-2.56, p = 0.070），包含三个变异的敏感性分析（PRS-3）与GDM显著相关（OR 2.43, 95% CI 1.17-5.06, p = 0.017）。在单因素分析中，rs1421085与GDM相关（OR 0.50, 95% CI 0.26-0.95, p = 0.034），但在协变量调整后与GDM无关，矛盾的是，与预期的风险等位基因无关。其他六种变异均未显示出与GDM的个体关联。先前发表的PRS-10荟萃分析显示，在分析的三个队列中存在一定程度的异质性（pQ= 0.03），这表明变异效应可能因遗传背景而异，这表明了检验任何假设的多基因风险评分的普遍性的重要性。结论：总之，我们为先前发表的GDM多基因风险评分结果提供了额外的支持，并进一步完善了该结果。
期刊介绍：
Journal of Personalized Medicine (JPM; ISSN 2075-4426) is an international, open access journal aimed at bringing all aspects of personalized medicine to one platform. JPM publishes cutting edge, innovative preclinical and translational scientific research and technologies related to personalized medicine (e.g., pharmacogenomics/proteomics, systems biology). JPM recognizes that personalized medicine—the assessment of genetic, environmental and host factors that cause variability of individuals—is a challenging, transdisciplinary topic that requires discussions from a range of experts. For a comprehensive perspective of personalized medicine, JPM aims to integrate expertise from the molecular and translational sciences, therapeutics and diagnostics, as well as discussions of regulatory, social, ethical and policy aspects. We provide a forum to bring together academic and clinical researchers, biotechnology, diagnostic and pharmaceutical companies, health professionals, regulatory and ethical experts, and government and regulatory authorities.
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