Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany.
Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Transl Psychiatry. 2020 Nov 22;10(1):403. doi: 10.1038/s41398-020-01074-z.
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.
阿尔茨海默病(AD)是最常见的神经退行性疾病,也是老年人中最常见的痴呆症形式。AD 的易感性在很大程度上取决于遗传因素,迄今为止,这些遗传因素主要是通过病例对照设计来确定的。阐明与 AD 相关的其他表型特征(理想情况下是与潜在疾病过程相关的特征)的遗传结构,有望深入了解 AD 的遗传基础,并开发更好的临床预测模型。为此,我们在 931 名欧洲医学信息框架阿尔茨海默病多模态生物标志物发现(EMIF-AD MBD)样本参与者中生成了全基因组单核苷酸多态性(SNP)基因分型数据,以寻找 AD 生物标志物变异性的新遗传决定因素。具体来说,我们对 16 个特征进行了全基因组关联研究(GWAS)分析,包括 14 种从脑脊液(CSF)中五种不同的淀粉样蛋白-β(Aβ)和 tau 蛋白测量中得出的测量值。除了证实载脂蛋白 E(APOE)对诊断结果和与 Aβ42 相关的表型的既定影响外,我们还在锌指同源框 3(ZFHX3)中检测到 CSF-Aβ38 和 CSF-Aβ40 水平的新潜在信号,并证实了先前描述的性别特异性 GMNC 中 SNPs 与 CSF-tau 之间的关联。利用独立的病例对照 AD GWAS 的结果构建多基因风险评分(PRS)表明,AD 风险变异仅解释了 CSF 生物标志物变异性的一小部分。总之,我们的研究代表了在 EMIF-AD MBD 数据集中对 CSF-Aβ 和 -tau 相关特征进行 GWAS 分析的详细首次报告。在后续工作中,我们将利用在此处生成的基因组学数据在该独特数据集中确定的其他与 AD 相关的临床结果的 GWAS 中进行分析。