Department of Pediatrics, Pennsylvania State Health Children's Hospital, Hershey, Pennsylvania, USA.
Pediatr Allergy Immunol. 2022 Jun;33(6):e13817. doi: 10.1111/pai.13817.
The pathophysiology of atopic dermatitis (AD) is multifactorial, impacted by individual medical, demographic, environmental, and immunologic factors. This study used multi-omic analyses to assess how host and microbial factors could contribute to infant AD development.
This longitudinal cohort study included 129 term infants, identified as AD (n = 37) or non-AD (n = 92) using the Infant Feeding Practices-II survey and review of medical records. Standardized surveys were used to assess medical and demographic traits (gestational age, sex, race, maternal AD, and atopy family history), and environmental exposures (delivery method, maternal tobacco use, pets, breastfeeding duration, and timing of solid food introduction). Saliva was collected at 6 months for multi-omic assessment of cytokines, microRNAs, mRNAs, and the microbiome. The contribution of each factor to AD status was assessed with logistic regression.
Medical, demographic, and environmental factors did not differ between AD and non-AD infants. Five "omic" factors (IL-8/IL-6, miR-375-3p, miR-21-5p, bacterial diversity, and Proteobacteria) differed between groups (p < .05). The severity of AD was positively associated with levels of miR-375-3p (R = .17, p = .049) and Proteobacteria (R = .22, p = .011), and negatively associated with levels of miR-21-5p (R = .20, p = .022). Multi-omic features accounted for 17% of variance between groups, significantly improving an AD risk model employing medical, demographic, and environmental factors (X = 32.47, p = .006).
Interactions between the microbiome and host signaling may predispose certain infants to AD by promoting a pro-inflammatory environment.
特应性皮炎（AD）的病理生理学是多因素的，受个体医疗、人口统计学、环境和免疫因素的影响。本研究使用多组学分析来评估宿主和微生物因素如何导致婴儿 AD 的发展。
这项纵向队列研究包括 129 名足月婴儿，根据婴儿喂养实践 II 调查和医疗记录回顾，将其确定为 AD（n=37）或非 AD（n=92）。使用标准化调查评估医疗和人口统计学特征（胎龄、性别、种族、母亲 AD 和特应性家族史）以及环境暴露（分娩方式、母亲吸烟、宠物、母乳喂养持续时间和固体食物引入时间）。在 6 个月时采集唾液进行细胞因子、microRNA、mRNA 和微生物组的多组学评估。使用逻辑回归评估每个因素对 AD 状态的贡献。
AD 和非 AD 婴儿的医疗、人口统计学和环境因素无差异。两组间有 5 个“组学”因素（IL-8/IL-6、miR-375-3p、miR-21-5p、细菌多样性和变形菌门）存在差异（p<0.05）。AD 的严重程度与 miR-375-3p 的水平呈正相关（R=0.17，p=0.049），与 Proteobacteria 的水平呈负相关（R=0.22，p=0.011），与 miR-21-5p 的水平呈负相关（R=0.20，p=0.022）。多组学特征占组间变异的 17%，显著改善了使用医疗、人口统计学和环境因素的 AD 风险模型（X 2=32.47，p=0.006）。
微生物组与宿主信号之间的相互作用可能通过促进促炎环境使某些婴儿易患 AD。
