Department of Medicine, Channing Division of Network of Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA.
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
Exp Mol Med. 2018 Jul 4;50(7):1-7. doi: 10.1038/s12276-018-0110-5.
It is well known that depression is associated with asthma symptoms. We assessed the combined effects of genetic factors and depression on asthma symptom severity using Bayesian network (BN) analysis. The common 100 top-ranked single-nucleotide polymorphisms (SNPs) were obtained from two genome-wide association studies of symptom severity in two childhood asthmatics trials (CAMP (Childhood Asthma Management Program) and CARE (Childhood Asthma Research and Education)). Using SNPs plus five discretized variables (depression, anxiety, age, sex, and race), we performed BN analysis in 529 CAMP subjects. We identified two nodes (depression and rs4672619 mapping to ERBB4 (Erb-B2 receptor tyrosine kinase 4)) that were within the Markov neighborhood of the symptom node in the network and then evaluated the interactive effects of depressive status and rs4672619 genotypes on asthma symptom severity. In childhood asthmatics with homozygous reference alleles, severe depression was related to less severe symptoms. However, in childhood asthmatics with heterozygous alleles and homozygous variant alleles, depression and symptom severity showed a positive correlation (interaction permutation P value = 0.019). We then tried to evaluate whether the interactive effects that we found were sustained in another independent cohort of elderly asthmatics. Contrary to the findings from childhood asthmatics, elderly asthmatics with homozygous reference alleles showed a positive correlation between depression and symptom severity, and elderly asthmatics with heterozygous alleles and homozygous variant alleles showed a negative correlation (interaction permutation P value = 0.003). In conclusion, we have identified a novel SNP, rs4672619, that shows interactive effects with depression on asthma symptom severity in childhood and elderly asthmatics in opposite directions.
众所周知，抑郁与哮喘症状有关。我们使用贝叶斯网络（BN）分析评估了遗传因素和抑郁对哮喘症状严重程度的综合影响。从两项儿童哮喘严重程度的全基因组关联研究（CAMP（儿童哮喘管理计划）和 CARE（儿童哮喘研究和教育））中获得了常见的前 100 个排名最高的单核苷酸多态性（SNP）。使用 SNPs 加上五个离散变量（抑郁、焦虑、年龄、性别和种族），我们对 529 名 CAMP 受试者进行了 BN 分析。我们确定了两个节点（抑郁和映射到 ERBB4（Erb-B2 受体酪氨酸激酶 4）的 rs4672619），它们位于网络中症状节点的 Markov 邻域内，然后评估了抑郁状态和 rs4672619 基因型对哮喘症状严重程度的交互作用。在纯合参考等位基因的儿童哮喘患者中，严重抑郁与症状较轻相关。然而，在杂合子和纯合子变异等位基因的儿童哮喘患者中，抑郁和症状严重程度呈正相关（交互置换 P 值=0.019）。然后，我们试图评估我们发现的交互作用是否在另一组独立的老年哮喘患者中持续存在。与儿童哮喘患者的发现相反，携带纯合参考等位基因的老年哮喘患者中，抑郁与症状严重程度呈正相关，而携带杂合子和纯合子变异等位基因的老年哮喘患者中，抑郁与症状严重程度呈负相关（交互置换 P 值=0.003）。总之，我们已经确定了一个新的 SNP，rs4672619，它在儿童和老年哮喘患者中与抑郁对哮喘症状严重程度的交互作用呈相反方向。
