Kogan Vladimir, Millstein Joshua, London Stephanie J, Ober Carole, White Steven R, Naureckas Edward T, Gauderman W James, Jackson Daniel J, Barraza-Villarreal Albino, Romieu Isabelle, Raby Benjamin A, Breton Carrie V
Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA.
Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA,
Hum Hered. 2018;83(3):130-152. doi: 10.1159/000489765. Epub 2019 Jan 22.
There is evidence to suggest that asthma pathogenesis is affected by both genetic and epigenetic variation independently, and there is some evidence to suggest that genetic-epigenetic interactions affect risk of asthma. However, little research has been done to identify such interactions on a genome-wide scale. The aim of this studies was to identify genes with genetic-epigenetic interactions associated with asthma.
Using asthma case-control data, we applied a novel nonparametric gene-centric approach to test for interactions between multiple SNPs and CpG sites simultaneously in the vicinities of 18,178 genes across the genome.
Twelve genes, PF4, ATF3, TPRA1, HOPX, SCARNA18, STC1, OR10K1, UPK1B, LOC101928523, LHX6, CHMP4B, and LANCL1, exhibited statistically significant SNP-CpG interactions (false discovery rate = 0.05). Of these, three have previously been implicated in asthma risk (PF4, ATF3, and TPRA1). Follow-up analysis revealed statistically significant pairwise SNP-CpG interactions for several of these genes, including SCARNA18, LHX6, and LOC101928523 (p = 1.33E-04, 8.21E-04, 1.11E-03, respectively).
Joint effects of genetic and epigenetic variation may play an important role in asthma pathogenesis. Statistical methods that simultaneously account for multiple variations across chromosomal regions may be needed to detect these types of effects on a genome-wide scale.
有证据表明哮喘发病机制分别受到遗传变异和表观遗传变异的影响,并且有一些证据表明遗传-表观遗传相互作用会影响哮喘风险。然而,在全基因组范围内识别此类相互作用的研究较少。本研究的目的是识别与哮喘相关的具有遗传-表观遗传相互作用的基因。
利用哮喘病例对照数据,我们应用了一种新颖的以基因为中心的非参数方法,以同时测试全基因组18178个基因附近多个单核苷酸多态性(SNP)与CpG位点之间的相互作用。
12个基因,即PF4、ATF3、TPRA1、HOPX、SCARNA18、STC1、OR10K1、UPK1B、LOC101928523、LHX6、CHMP4B和LANCL1,表现出具有统计学意义的SNP-CpG相互作用(错误发现率=0.05)。其中,三个基因先前已被认为与哮喘风险有关(PF4、ATF3和TPRA1)。后续分析揭示了其中几个基因具有统计学意义的成对SNP-CpG相互作用,包括SCARNA18、LHX6和LOC101928523(p值分别为1.33E-04、8.21E-04、1.11E-03)。
遗传变异和表观遗传变异的联合效应可能在哮喘发病机制中起重要作用。可能需要同时考虑染色体区域多个变异的统计方法,以便在全基因组范围内检测这类效应。