通过整合全基因组关联研究中微弱关联的单核苷酸多态性预测晚期年龄相关性黄斑变性
Predicting late-stage age-related macular degeneration by integrating marginally weak SNPs in GWA studies.
作者信息
Zhou Xueping, Zhang Jipeng, Ding Ying, Huang Heng, Li Yanming, Chen Wei
机构信息
Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, United States.
Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States.
出版信息
Front Genet. 2023 Mar 30;14:1075824. doi: 10.3389/fgene.2023.1075824. eCollection 2023.
Age-related macular degeneration (AMD) is a progressive neurodegenerative disease and the leading cause of blindness in developed countries. Current genome-wide association studies (GWAS) for late-stage age-related macular degeneration are mainly single-marker-based approaches, which investigate one Single-Nucleotide Polymorphism (SNP) at a time and postpone the integration of inter-marker Linkage-disequilibrium (LD) information in the downstream fine mappings. Recent studies showed that directly incorporating inter-marker connection/correlation into variants detection can help discover novel marginally weak single-nucleotide polymorphisms, which are often missed in conventional genome-wide association studies, and can also help improve disease prediction accuracy. Single-marker analysis is performed first to detect marginally strong single-nucleotide polymorphisms. Then the whole-genome linkage-disequilibrium spectrum is explored and used to search for high-linkage-disequilibrium connected single-nucleotide polymorphism clusters for each strong single-nucleotide polymorphism detected. Marginally weak single-nucleotide polymorphisms are selected a joint linear discriminant model with the detected single-nucleotide polymorphism clusters. Prediction is made based on the selected strong and weak single-nucleotide polymorphisms. Several previously identified late-stage age-related macular degeneration susceptibility genes, for example, , , , , , are confirmed. Novel genes , , , and are discovered as marginally weak signals. Overall prediction accuracy of 76.8% and 73.2% was achieved with and without the inclusion of the identified marginally weak signals, respectively. Marginally weak single-nucleotide polymorphisms, detected from integrating inter-marker linkage-disequilibrium information, may have strong predictive effects on age-related macular degeneration. Detecting and integrating such marginally weak signals can help with a better understanding of the underlying disease-development mechanisms for age-related macular degeneration and more accurate prognostics.
年龄相关性黄斑变性(AMD)是一种进行性神经退行性疾病,也是发达国家失明的主要原因。目前针对晚期年龄相关性黄斑变性的全基因组关联研究(GWAS)主要是基于单标记的方法,该方法一次研究一个单核苷酸多态性(SNP),并在下游精细定位中推迟标记间连锁不平衡(LD)信息的整合。最近的研究表明,将标记间的连接/相关性直接纳入变异检测可以帮助发现新的微弱单核苷酸多态性,这些多态性在传统的全基因组关联研究中常常被遗漏,并且还可以帮助提高疾病预测准确性。首先进行单标记分析以检测强单核苷酸多态性。然后探索全基因组连锁不平衡谱,并用于为每个检测到的强单核苷酸多态性搜索高连锁不平衡连接的单核苷酸多态性簇。通过与检测到的单核苷酸多态性簇的联合线性判别模型选择微弱单核苷酸多态性。基于选定的强和弱单核苷酸多态性进行预测。几个先前确定的晚期年龄相关性黄斑变性易感基因,例如,,,,,得到了证实。发现新基因,,和作为微弱信号。分别在纳入和不纳入已识别的微弱信号的情况下,总体预测准确率分别达到76.8%和73.2%。从整合标记间连锁不平衡信息中检测到的微弱单核苷酸多态性可能对年龄相关性黄斑变性具有很强的预测作用。检测和整合这些微弱信号有助于更好地理解年龄相关性黄斑变性的潜在疾病发展机制和更准确的预后。