Advances in high-throughput technologies and the generation of multiomics, such as genomic, epigenomic, transcriptomic, and metabolomic data, are paving the way for the biological risk stratification and prediction of oral diseases. When integrated with electronic health records, survey, census, and/or epidemiologic data, multiomics are anticipated to facilitate data-driven precision oral health, or the delivery of the right oral health intervention to the right individuals/populations at the right time. Meanwhile, multiomics may be modified by a multitude of social exposures, cumulatively along the life course and at various time points from conception onward, also referred to as the socio-exposome. For example, adverse exposures, such as precarious social and living conditions and related psychosocial stress among others, have been linked to specific genes being switched “on and off” through epigenetic mechanisms. These in turn are associated with various health conditions in different age groups and populations. This article argues that considering the impact of the socio-exposome in the biological profiling for precision oral health applications is necessary to ensure that definitions of biological risk do not override social ones. To facilitate the uptake of the socio-exposome in multiomics oral health studies and subsequent interventions, 3 pertinent facets are discussed. First, a summary of the epigenetic landscape of oral health is presented. Next, findings from the nondental literature are drawn on to elaborate the pathways and mechanisms that link the socio-exposome with gene expression—or the biological embedding of social experiences through epigenetics. Then, methodological considerations for implementing social epigenomics into oral health research are highlighted, with emphasis on the implications for study design and interpretation. The article concludes by shedding light on some of the current and prospective opportunities for social epigenomics research applied to the study of life course oral epidemiology.

高通量技术的进步和多组学的产生，例如基因组、表观基因组、转录组和代谢组学数据，正在为口腔疾病的生物学风险分层和预测铺平道路。当与电子健康记录、调查、人口普查和/或流行病学数据相结合时，多组学有望促进数据驱动的精准口腔健康，或在正确的时间向正确的个人/人群提供正确的口腔健康干预。同时，多组学可以通过大量的社会暴露来修改，沿着生命历程和从受孕开始的不同时间点累积，也称为社会暴露. 例如，不利的暴露，如不稳定的社会和生活条件以及相关的社会心理压力等，与通过表观遗传机制“开启和关闭”的特定基因有关。这些反过来又与不同年龄组和人群的各种健康状况有关。本文认为，有必要考虑社会暴露在精确口腔健康应用的生物分析中的影响，以确保生物风险的定义不会凌驾于社会风险之上。为了促进在多组学口腔健康研究和随后的干预中吸收社会暴露，讨论了 3 个相关方面。首先，总结了口腔健康的表观遗传景观。下一个，来自非牙科文献的发现被用来阐述将社会暴露与基因表达联系起来的途径和机制——或通过表观遗传学将社会经验的生物学嵌入。然后，强调了将社会表观基因组学应用于口腔健康研究的方法论考虑，重点是对研究设计和解释的影响。文章最后阐明了应用于生命历程口腔流行病学研究的社会表观基因组学研究的一些当前和未来机会。强调对研究设计和解释的影响。文章最后阐明了应用于生命历程口腔流行病学研究的社会表观基因组学研究的一些当前和未来机会。强调对研究设计和解释的影响。文章最后阐明了应用于生命历程口腔流行病学研究的社会表观基因组学研究的一些当前和未来机会。