National Clinical Research Center for Mental Disorders; Department of Psychiatry, Second Xiangya Hospital, Central South University, Changsha 410011.
Mental Health Center, Xiangya Hospital, Central South University, Changsha 410008.
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2022 Jul 28;47(7):858-864. doi: 10.11817/j.issn.1672-7347.2022.210330.
Autism is a neurodevelopment disorder with unclear etiology. High heterogeneity is one of the main issues in the etiological studies. This study explores the relationship between RELN signaling pathway related genes (, , , , , ) and language development of autism patients based on a cluster analysis model which is established to reduce the heterogeneity.
Autism children were recruited from 5 different medical/autism training institutes from Hunan, Shandong, and Henan provinces, and were divided into 2 parts according to the recruitment time: The first part was the training sample, which was recruited from October 2006 to May 2011, and the second part was the validation sample, which was recruited from July 2011 to May 2012. A two-step cluster analysis was performed to cluster 374 Chinese Han autism patients into different subgroups based on 2 parameters: Onset age of the first word and interval from the first word to the first phase. A Bayes discriminatory equation was established followed the cluster results. Then we used this equation to divide another 310 autism children into prior defined subgroups. After the genotyping data was screened, a single marker case-control association study was conducted.
The cluster analysis clustered 374 samples into 3 subgroups. Onset ages of the first word in the Group A were (11.83±4.37) months and intervals from the first word to the first phase were (24.55±8.67) months; onset ages of the first word in the Group B were (12.17±3.46) months, intervals from the first word to the first phase were (7.07±3.79) months; onset ages of the first word of Group C were (30.94±7.60) months, intervals from the first word to the first phase were (4.73±4.80) months. The established equations based on the cluster analysis were =-14.442+0.525+0.810, =-4.964+0.477+0.264, =-19.843+1.175+0.241. Cross validated analysis showed that the false rate of the equation was 3.8%. A total of 341 single nucleotide polymorphism (SNP) in 6 genes passed the quality control. Before divided subgroups, none of these SNPs reached the significant value (>2.44×10, Bonferroni adjustment). However the result showed that rs1288502 of in Group B was significantly different from the control group (=6.45×10).
Based on the cluster analysis of language development, we could establish a discriminatory equation to reduce heterogeneity of autism sample. The association test indicates that genein RELN signaling pathway is related to a particular type of language development of autism patients.
自闭症是一种病因不明的神经发育障碍。高度异质性是病因研究中的主要问题之一。本研究通过建立聚类分析模型来探索 RELN 信号通路相关基因（、、、、、）与自闭症患者语言发育的关系，以减少异质性。
从湖南、山东和河南的 5 家不同的医学/自闭症培训机构招募自闭症儿童，并根据招募时间分为 2 部分：第一部分为训练样本，招募时间为 2006 年 10 月至 2011 年 5 月；第二部分为验证样本，招募时间为 2011 年 7 月至 2012 年 5 月。根据两个参数：第一个单词的出现年龄和从第一个单词到第一个阶段的间隔，对 374 例汉族自闭症患者进行两阶段聚类分析，将其分为不同的亚组。根据聚类结果建立贝叶斯判别方程。然后，我们使用这个方程将另外 310 名自闭症儿童分为预先定义的亚组。在筛选基因分型数据后，进行了单标记病例对照关联研究。
聚类分析将 374 个样本分为 3 个亚组。A 组的第一个单词出现年龄为（11.83±4.37）个月，从第一个单词到第一个阶段的间隔为（24.55±8.67）个月；B 组的第一个单词出现年龄为（12.17±3.46）个月，从第一个单词到第一个阶段的间隔为（7.07±3.79）个月；C 组的第一个单词出现年龄为（30.94±7.60）个月，从第一个单词到第一个阶段的间隔为（4.73±4.80）个月。基于聚类分析建立的方程为=-14.442+0.525+0.810，=-4.964+0.477+0.264，=-19.843+1.175+0.241。交叉验证分析表明该方程的错误率为 3.8%。在 6 个基因中，共有 341 个单核苷酸多态性（SNP）通过了质量控制。在分组之前，这些 SNP 中没有一个达到显著水平（>2.44×10，Bonferroni 调整）。然而，结果表明，B 组中的 rs1288502 与对照组（=6.45×10）差异显著。
基于语言发育的聚类分析，我们可以建立一个判别方程来减少自闭症样本的异质性。关联测试表明 RELN 信号通路中的基因与自闭症患者特定类型的语言发育有关。
