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使用管道环境的早发性阿尔茨海默病患者的基因相互作用和结构脑变化。

Gene interactions and structural brain change in early-onset Alzheimer's disease subjects using the pipeline environment.

机构信息

Department of Psychiatry, Konkuk University School of Medicine, Chungju, Republic of Korea.

Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA. ; Statistics Online Computational Resource, UMSM, University of Michigan, Ann Arbor, MI, USA.

出版信息

Psychiatry Investig. 2015 Jan;12(1):125-35. doi: 10.4306/pi.2015.12.1.125. Epub 2015 Jan 12.

Abstract

OBJECTIVE

This article investigates subjects aged 55 to 65 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to broaden our understanding of early-onset (EO) cognitive impairment using neuroimaging and genetics biomarkers.

METHODS

Nine of the subjects had EO-AD (Alzheimer's disease) and 27 had EO-MCI (mild cognitive impairment). The 15 most important neuroimaging markers were extracted with the Global Shape Analysis (GSA) Pipeline workflow. The 20 most significant single nucleotide polymorphisms (SNPs) were chosen and were associated with specific neuroimaging biomarkers.

RESULTS

We identified associations between the neuroimaging phenotypes and genotypes for a total of 36 subjects. Our results for all the subjects taken together showed the most significant associations between rs7718456 and L_hippocampus (volume), and between rs7718456 and R_hippocampus (volume). For the 27 MCI subjects, we found the most significant associations between rs6446443 and R_superior_frontal_gyrus (volume), and between rs17029131 and L_Precuneus (volume). For the nine AD subjects, we found the most significant associations between rs16964473 and L_rectus gyrus (surface area), and between rs12972537 and L_rectus_gyrus (surface area).

CONCLUSION

We observed significant correlations between the SNPs and the neuroimaging phenotypes in the 36 EO subjects in terms of neuroimaging genetics. However, larger sample sizes are needed to ensure that the effects will be detectable for a reasonable false-positive error rate using the GSA and Plink Pipeline workflows.

摘要

目的

本文从阿尔茨海默病神经影像学倡议(ADNI)数据库中选取了 55 至 65 岁的受试者,利用神经影像学和遗传学标志物来拓宽我们对早发性(EO)认知障碍的认识。

方法

9 名受试者患有 EO-AD(阿尔茨海默病),27 名受试者患有 EO-MCI(轻度认知障碍)。使用全局形状分析(GSA)管道工作流程提取了 15 个最重要的神经影像学标记物。选择了 20 个最重要的单核苷酸多态性(SNP),并将其与特定的神经影像学生物标志物相关联。

结果

我们总共确定了 36 名受试者的神经影像学表型和基因型之间的关联。我们对所有受试者的综合分析结果显示,rs7718456 与 L_hippocampus(体积)之间,以及 rs7718456 与 R_hippocampus(体积)之间的关联最为显著。对于 27 名 MCI 受试者,我们发现 rs6446443 与 R_superior_frontal_gyrus(体积)之间,以及 rs17029131 与 L_Precuneus(体积)之间的关联最为显著。对于 9 名 AD 受试者,我们发现 rs16964473 与 L_rectus gyrus(表面积)之间,以及 rs12972537 与 L_rectus_gyrus(表面积)之间的关联最为显著。

结论

我们观察到在 36 名 EO 受试者中,SNP 与神经影像学表型之间存在显著的相关性,这与神经影像学遗传学有关。然而,需要更大的样本量来确保使用 GSA 和 Plink Pipeline 工作流程以合理的假阳性错误率检测到这些效应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92a7/4310910/b0b304115b11/pi-12-125-g001.jpg

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