Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Eastman Institute for Oral Health, University of Rochester Medical Center, Rochester, NY 14642, USA.
Genes (Basel). 2023 Mar 3;14(3):641. doi: 10.3390/genes14030641.
Early childhood caries (ECC) is a disease that globally affects pre-school children. It is important to identify both protective and risk factors associated with this disease. This paper examined a set of saliva samples of Thai mother-child dyads and aimed to analyze how the maternal factors and oral microbiome of the dyads influence the development of ECC. However, heterogeneous latent subpopulations may exist that have different characteristics in terms of caries development. Therefore, we introduce a novel method to cluster the correlated outcomes of dependent observations while selecting influential independent variables to unearth latent groupings within this dataset and reveal their association in each group. This paper describes the discovery of three heterogeneous clusters in the dataset, each with its own unique mother-child outcome trend, as well as identifying several microbial factors that contribute to ECC. Significantly, the three identified clusters represent three typical clinical conditions in which mother-child dyads have typical (cluster 1), high-low (cluster 2), and low-high caries experiences (cluster 3) compared to the overall trend of mother-child caries status. Intriguingly, the variables identified as the driving attributes of each cluster, including specific taxa, have the potential to be used in the future as caries preventive measures.
婴幼儿龋（ECC）是一种全球性影响学龄前儿童的疾病。识别与这种疾病相关的保护因素和风险因素很重要。本文研究了一组泰国母婴对的唾液样本，旨在分析母婴因素和口腔微生物组如何影响 ECC 的发展。然而，可能存在具有不同龋病发展特征的异质潜在亚群。因此，我们引入了一种新的方法，即在选择有影响力的自变量的同时，对相关的依存观测结果进行聚类，以揭示数据集中的潜在分组，并揭示每个组中的关联。本文描述了在数据集发现了三个异质聚类，每个聚类都有其独特的母婴结果趋势，并确定了几个对 ECC 有贡献的微生物因素。重要的是，三个确定的聚类代表了母婴对具有典型（聚类 1）、高低（聚类 2）和低高龋经验（聚类 3）的三种典型临床情况，与母婴龋状态的总体趋势相比。有趣的是，被确定为每个聚类驱动属性的变量，包括特定的分类单元，将来有可能被用作预防龋齿的措施。
