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Genome-wide epistasis analysis for Alzheimer’s disease and implications for genetic risk prediction

机译:基因组的阿尔茨海默病疾病及其遗传风险预测的影响分析

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摘要

Single-nucleotide polymorphisms (SNPs) identified by genome-wide association studies only explain part of the heritability of Alzheimer’s disease (AD). Epistasis has been considered as one of the main causes of “missing heritability” in AD. We performed genome-wide epistasis screening (N?=?10,389) for the clinical diagnosis of AD using three popularly adopted methods. Subsequent analyses were performed to eliminate spurious associations caused by possible confounding factors. Then, candidate genetic interactions were examined for their co-expression in the brains of AD patients and analyzed for their association with intermediate AD phenotypes. Moreover, a new approach was developed to compile the epistasis risk factors into an epistasis risk score (ERS) based on multifactor dimensional reduction. Two independent datasets were used to evaluate the feasibility of ERSs in AD risk prediction. We identified 2 candidate genetic interactions with PFDR? 0.05 (RAMP3-SEMA3A and NSMCE1-DGKE/C17orf67) and another 5 genetic interactions with PFDR? 0.1. Co-expression between the identified interactions supported the existence of possible biological interactions underlying the observed statistical significance. Further association of candidate interactions with intermediate phenotypes helps explain the mechanisms of neuropathological alterations involved in AD. Importantly, we found that ERSs can identify high-risk individuals showing earlier onset of AD. Combined risk scores of SNPs and SNP-SNP interactions showed slightly but steadily increased AUC in predicting the clinical status of AD. In summary, we performed a genome-wide epistasis analysis to identify novel genetic interactions potentially implicated in AD. We found that ERS can serve as an indicator of the genetic risk of AD.
机译:通过基因组 - 宽协会研究鉴定的单核苷酸多态性(SNP)仅解释了阿尔茨海默病(AD)的遗传性的一部分。 Epostasis被认为是广告中“遗失遗传性”的主要原因之一。我们使用三种普遍采用的方法进行了针对广告临床诊断的基因组 - 范围的外观筛选(N?= 10,389)。进行后续分析以消除由可能的混淆因素引起的杂散关联。然后,检查候选遗传相互作用在AD患者的大脑中进行共同表达,并分析它们与中间广告表型的关系。此外,开发了一种新方法,以基于多因素尺寸减少来编制简化危险因素的超越风险评分(ERS)。使用两个独立数据集来评估AD风险预测中的ERS的可行性。我们确定了与PFDR的候选遗传相互作用?& 0.05(ramp3-sema3a和nsmce1-dgke / c17orf67)和与pfdr的另外5个遗传相互作用?<& 0.1。所识别的相互作用之间的共同表达支持了所观察到的统计学意义的可能生物相互作用。进一步与中间表型的候选相互作用的关系有助于解释广告中涉及的神经病理改变的机制。重要的是,我们发现ERSS可以识别出现早期广告发作的高风险个体。 SNP和SNP-SNP相互作用的组合风险评分略微略高,但稳定地增加了AC的AD临床状态。总之,我们进行了基因组的外观分析,以识别可能涉及AD的新型遗传相互作用。我们发现,ERS可以作为广告遗传风险的指标。

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