Host Genotype Links to Salivary and Gut Microbiota by Periodontal Status

Limited evidence describing how host genetic variants affect the composition of the microbiota is currently available. The aim of this study was to assess the associations between a set of candidate host genetic variants and microbial composition in both saliva and gut in the TwinsUK registry. A total of 1,746 participants were included in this study and provided stool samples. A subset of 1,018 participants also provided self-reported periodontal data, and 396 of those participants provided a saliva sample. Host DNA was extracted from whole-blood samples and processed for Infinium Global screening array, focusing on 37 selected single-nucleotide polymorphisms (SNPs) previously associated with periodontitis. The gut and salivary microbiota of participants were profiled using 16S ribosomal RNA amplicon sequencing. Associations between genotype on the selected SNPs and microbial outcomes, including α diversity, β diversity, and amplicon sequence variants (ASVs), were investigated in a multivariate mixed model. Self-reported periodontal status was also compared with microbial outcomes. Downstream analyses in gut microbiota and salivary microbiota were carried out separately. IL10 rs6667202 and VDR 2228570 SNPs were associated with salivary α diversity, and SNPs in IL10, HSA21, UHRF2, and Fc-γR genes were associated with dissimilarity matrix generated from salivary β diversity. The SNP that was associated with the greatest number of salivary ASVs was VDR 2228570 followed by IL10 rs6667202, and that of gut ASVs was NPY rs2521364. There were 77 salivary ASVs and 39 gut ASVs differentially abundant in self-reported periodontal disease versus periodontal health. The dissimilarity between saliva and gut microbiota within individuals appeared significantly greater in self-reported periodontal cases compared to periodontal health. IL10 and VDR gene variants may affect salivary microbiota composition. Periodontal status may drive variations in the salivary microbiota and possibly, to a lesser extent, in the gut microbiota

sj-docx-1-jdr-10.1177_00220345221125402 – Supplemental material for Host Genotype Links to Salivary and Gut Microbiota by Periodontal Status

Supplemental material, sj-docx-1-jdr-10.1177_00220345221125402 for Host Genotype Links to Salivary and Gut Microbiota by Periodontal Status by Y. Kurushima, P.M. Wells, R.C.E. Bowyer, N. Zoheir, S. Doran, J.P. Richardson, D.D. Sprockett, D.A. Relman, C.J. Steves and L. Nibali in Journal of Dental Research</p

Delexicalized Word Embeddings for Cross-lingual Dependency Parsing

International audienceThis paper presents a new approach to the problem of cross-lingual dependency parsing, aiming at leveraging training data from different source languages to learn a parser in a target language. Specifically , this approach first constructs word vector representations that exploit structural (i.e., dependency-based) contexts but only considering the morpho-syntactic information associated with each word and its contexts. These delexicalized word em-beddings, which can be trained on any set of languages and capture features shared across languages, are then used in combination with standard language-specific features to train a lexicalized parser in the target language. We evaluate our approach through experiments on a set of eight different languages that are part the Universal Dependencies Project. Our main results show that using such delexicalized embeddings, either trained in a monolin-gual or multilingual fashion, achieves significant improvements over monolingual baselines