PDF(Pubmed)
Abstract：
OBJECTIVE: Huntington\'s disease (HD) is a progressive neurodegenerative disorder with heterogeneous clinical manifestations. Identifying distinct clinical clusters and their relevant biomarkers could elucidate the underlying disease pathophysiology.
METHODS: Following the Enroll-HD program initiated in 2018.09, we have recruited 104 HD patients (including 21 premanifest) and 31 health controls at Beijing Tiantan Hospital. Principal components analysis and k-means cluster analysis were performed to determine HD clusters. Chi-square test, one-way ANOVA, and covariance were used to identify features among these clusters. Furthermore, plasma cytokines levels and brain structural imaging were used as biomarkers to delineate the clinical features of each cluster.
RESULTS: Three clusters were identified. Cluster 1 demonstrated the most severe motor and nonmotor symptoms except for chorea, the lowest whole brain volume, the plasma levels of IL-2 were higher and significantly associated with cluster 1. Cluster 2 was characterized with the most severe chorea and the largest pallidum volume. Cluster 3 had the most benign motor symptoms but moderate psychiatric problems.
CONCLUSIONS: We have identified three HD clusters via clinical manifestations with distinct biomarkers. Our data shed light on better understanding about the pathophysiology of HD.
METHODS: Following the Enroll-HD program initiated in 2018.09, we have recruited 104 HD patients (including 21 premanifest) and 31 health controls at Beijing Tiantan Hospital. Principal components analysis and k-means cluster analysis were performed to determine HD clusters. Chi-square test, one-way ANOVA, and covariance were used to identify features among these clusters. Furthermore, plasma cytokines levels and brain structural imaging were used as biomarkers to delineate the clinical features of each cluster.
RESULTS: Three clusters were identified. Cluster 1 demonstrated the most severe motor and nonmotor symptoms except for chorea, the lowest whole brain volume, the plasma levels of IL-2 were higher and significantly associated with cluster 1. Cluster 2 was characterized with the most severe chorea and the largest pallidum volume. Cluster 3 had the most benign motor symptoms but moderate psychiatric problems.
CONCLUSIONS: We have identified three HD clusters via clinical manifestations with distinct biomarkers. Our data shed light on better understanding about the pathophysiology of HD.
摘要：
目的：亨廷顿病（HD）是一种临床表现异质性的进行性神经退行性疾病。识别不同的临床簇及其相关的生物标志物可以阐明潜在的疾病病理生理学。
方法：在2018.09启动的Enroll-HD计划之后，我们在北京天坛医院招募了104名HD患者（包括21名显证前）和31名健康对照。进行主成分分析和k均值聚类分析以确定HD簇。卡方检验,单向方差分析,和协方差被用来识别这些聚类之间的特征。此外，血浆细胞因子水平和脑结构成像被用作生物标志物来描绘每个集群的临床特征.
结果：确定了三个簇。除舞蹈病外，第1组表现出最严重的运动和非运动症状，最低的全脑容量，血浆IL-2水平较高,且与第1组显著相关.第2组的特征是最严重的舞蹈病和最大的苍白球体积。第3组的良性运动症状最多，但精神问题中等。
结论：我们已经通过具有不同生物标志物的临床表现确定了三个HD簇。我们的数据揭示了更好地理解HD的病理生理学。
方法：在2018.09启动的Enroll-HD计划之后，我们在北京天坛医院招募了104名HD患者（包括21名显证前）和31名健康对照。进行主成分分析和k均值聚类分析以确定HD簇。卡方检验,单向方差分析,和协方差被用来识别这些聚类之间的特征。此外，血浆细胞因子水平和脑结构成像被用作生物标志物来描绘每个集群的临床特征.
结果：确定了三个簇。除舞蹈病外，第1组表现出最严重的运动和非运动症状，最低的全脑容量，血浆IL-2水平较高,且与第1组显著相关.第2组的特征是最严重的舞蹈病和最大的苍白球体积。第3组的良性运动症状最多，但精神问题中等。
结论：我们已经通过具有不同生物标志物的临床表现确定了三个HD簇。我们的数据揭示了更好地理解HD的病理生理学。
