Non-HLA SNPs in prediction of clustering of autoimmune diseases.

The results of multivariate models 3 and 4 with research questions: Do the 33 non-linked, non-HLA SNPs (single nucleotide polymorphisms) help to predict clustering of autoimmune diseases in children with multiple autoimmune diseases (Model 3), or in children from autoimmune families (Model 4). For Model 3, the statistics are: AIC for the confounding factors alone 382, AIC of this model 365, joint P value 6.6×10−5. For Model 4, the statistics are: AIC for the confounding factors alone 716, AIC of this model 710, joint P value 0.0059. The joint P values concern the effects of the non-HLA SNPs. HR = Hazard ratio for the minor allele, CI = Confidence interval. Only children with information available on all variables were included in the analyses.

本研究针对多变量模型3与模型4的分析结果对应以下研究问题：33个非连锁、非HLA（Human Leukocyte Antigen, HLA）的单核苷酸多态性（single nucleotide polymorphisms, SNPs）是否可用于预测合并多种自身免疫病的患儿的自身免疫病聚类特征（模型3），或是预测来自自身免疫病家族的患儿的相关特征（模型4）。针对模型3，相关统计指标如下：仅纳入混杂因素的模型的赤池信息准则（Akaike Information Criterion, AIC）为382，本次所构建模型的赤池信息准则为365，非HLA SNPs效应的联合P值为6.6×10^−5。针对模型4，相关统计指标如下：仅纳入混杂因素的模型的赤池信息准则为716，本次所构建模型的赤池信息准则为710，非HLA SNPs效应的联合P值为0.0059。上述联合P值均指代非HLA SNPs的效应。其中HR指次要等位基因的风险比（Hazard Ratio, HR），CI指置信区间（Confidence Interval, CI）。本分析仅纳入所有变量信息均完整的患儿。