背景:表面活性蛋白(SP)的单核苷酸多态性(SNPs)之间的相互作用与急性呼吸衰竭(ARF)及其短期结果相关,儿童出院时肺功能障碍(PDAD)。然而,以前没有使用单个SNP进行遗传关联研究。我们假设SP遗传变异与小儿ARF及其短期并发症有关。
方法:我们使用Floros生物样本库中的可用基因型和临床数据,该样本包括248名年龄≤24个月的ARF儿童;86名患有PDAD。对14个选定的SNP中的每一个进行逻辑回归分析,SP-A1和SP-A2基因型。小于Bonferroni校正阈值的P值被认为是显著的。进行似然比测试以比较两个模型(一个具有人口统计数据,另一个具有遗传变异)。
结果:在Bonferroni校正之前,女性与ARF风险降低相关。黑人种族和SFTPD的rs721917与ARF的风险增加有关。Bonferroni校正后,SFTPA2的1A01A1基因型与ARF风险降低相关.似然比检验表明,基因型信息与人口统计学数据的模型更适合预测ARF风险。SPSNP和SP-A1、SP-A2基因型均不与PDAD相关。
结论:我们的结果表明,参与先天免疫和宿主防御的SPs的SNP和基因型在ARF中起重要作用,在未来,可用作生物标志物。
BACKGROUND: Interactions among single nucleotide polymorphisms (SNPs) of surfactant protein (SP) are associated with acute respiratory failure (ARF) and its short-term outcome, pulmonary dysfunction at discharge (PDAD) in children. However, genetic association studies using individual SNPs have not been conducted before. We hypothesize that SP genetic variants are associated with pediatric ARF and its short-term complications by themselves.
METHODS: We used available genotype and clinical data in the Floros biobank consisting of 248 children aged ≤24 months with ARF; 86 developed PDAD. A logistic regression analysis was performed for each of the 14 selected SNPs, SP-A1 and SP-A2 genotypes. A p-value less than the Bonferroni correction threshold was considered significant. A likelihood ratio test was done to compare two models (one with demographic data and another with genetic variants).
RESULTS: Before Bonferroni correction, female sex is associated with a decreased risk of ARF. Black race and the rs721917 of the SFTPD are associated with increased risk of ARF. After Bonferroni correction, the 1A0 1A1 genotype of SFTPA2 was associated with decreased risk of ARF. The likelihood ratio test showed that the model of the genotype information with demographic data was a better fit to predict ARF risk. None of the SP SNPs and SP-A1, SP-A2 genotypes were associated with PDAD.
CONCLUSIONS: Our results indicate that SNPs and genotypes of SPs involved in innate immunity and host defense play an important role in ARF and, in the future, may be used as biomarkers.