Yang Tao, Wan GuangYu, Zhou Xiong
Department of Radiology, Xianning Central Hospital, No. 228 Jingui Road, Xianning, China.
BMC Med Imaging. 2025 Jul 17;25(1):287. doi: 10.1186/s12880-025-01782-2.
As a neurodegenerative disease, Alzheimer's disease (AD) has many symptoms, such as memory impairment, cognitive decline, and personality change. Image genetics is the correlation analysis between imageology and genetics, and image genetics research can effectively detect the biomarkers of AD. This paper proposed an orthogonal multi-task sparse canonical correlation analysis (MTOSCCA) algorithm. Based on the multi-task canonical correlation analysis, this algorithm added orthogonal constraints to the weight vectors U and V, which can effectively prevent the influence of redundant features on the results. In this paper, the MTOSCCA algorithm was applied to structural magnetic resonance imaging, single nucleotide polymorphism, and gene expression data integration. The results showed that the proposed algorithm has better correlation performance, and the obtained markers have diagnostic significance for AD and mild cognitive impairment (MCI).
作为一种神经退行性疾病，阿尔茨海默病（AD）有许多症状，如记忆障碍、认知衰退和性格改变。影像遗传学是影像学与遗传学之间的相关性分析，影像遗传学研究可以有效地检测出AD的生物标志物。本文提出了一种正交多任务稀疏典型相关分析（MTOSCCA）算法。该算法在多任务典型相关分析的基础上，对权重向量U和V添加了正交约束，能够有效防止冗余特征对结果的影响。本文将MTOSCCA算法应用于结构磁共振成像、单核苷酸多态性和基因表达数据整合。结果表明，所提算法具有更好的相关性性能，所获得的标志物对AD和轻度认知障碍（MCI）具有诊断意义。
