This study employs a two-sample bidirectional Mendelian randomization (MR) approach to systematically evaluate the causal relationship between gut microbiota and oral cavity cancer (OCC).Objective: To address the challenge in establishing the causal relationship between gut microbiota and OCC, we applied a systematic MR analysis.Methods: Utilizing GWAS data from the MiBioGen consortium (18,340 individuals) and UK Biobank (n = 264,137), we selected instrumental variables and employed MR-Egger, weighted median, IVW, and weighted mode analyses. Heterogeneity and pleiotropy were assessed using Cochran’s Q test and MR-Egger intercept test.Results: Our findings indicate, at the order level, Bacteroidales (OR = 0.9990, 95% CI = 0.9980–1.0000, P = 0.046), Burkholderiales (OR = 1.0009, 95% CI = 1.0001–1.0018, P = 0.033), and Victivallales (OR = 0.9979, 95% CI = 0.9962–0.9995, P = 0.037) exhibit causality on OCC in the Weighted median, IVW, and MR-Egger analyses, respectively. At the family level, Alcaligenaceae (OR = 1.0012, 95% CI = 1.0004–1.0019, P = 0.002) and Clostridiaceae1 (OR = 0.9970, 95% CI = 0.9948–0.9992, P = 0.027) show causality on OCC in IVW and MR-Egger analyses. At the genus level, Clostridiumsensustricto1 (IVW, OR = 0.9987, 95% CI = 0.9980–0.9995, P = 0.001; MR-Egger, OR = 0.9978, 95% CI = 0.9962–0.9995, P = 0.035), Desulfovibrio (IVW, OR = 1.0008, 95% CI = 1.0001–1.0015, P = 0.016), Eggerthella (IVW, OR = 0.9995, 95% CI = 0.9990–1.0000, P = 0.048), Eubacterium fissicatena group (IVW, OR = 1.0005, 95% CI = 1.0000–1.0009, P = 0.032), and Holdemanella (IVW, OR = 0.9994, 95% CI = 0.9989–0.9999, P = 0.018) are implicated in causing OCC in related analyses.Conclusion: Our study identifies Burkholderiales order, Alcaligenaceae family, Desulfovibrio genus, and Eubacterium fissicatena group as causally increasing OCC risk. In contrast, Bacteroidales order, Victivallales order, Clostridiaceae1 family, Clostridiumsensustricto1 genus, Eggerthella genus, and Holdemanella genus are causally associated with a decreased OCC risk. However, further investigations are essential to delineate an optimal gut microbiota composition and unravel the underlying mechanisms of specific bacterial taxa in OCC pathophysiology.

Multiple methods have been proposed for evaluating the symmetry of facial contour by utilizing the median sagittal plane of the skull as a reference and measuring the maxillofacial region. To replace the manual mark point analysis method, we used the anterior cerebral falx plane in MRI images as an indicator of the craniofacial midline. The MRI examination data of 30 individuals were analyzed with a MeVisLab workstation. Two independent examiners performed 15 anthropometric measurements (4 angular, 11 linear) and compared the MRI-based anterior cerebral falx plane with the manual mark point analysis of the craniofacial midline estimation. All measurements were repeated after 3 weeks. Statistical analyses included the repeatability and reproducibility of the 2 methods based on intra-observer and inter-observer correlation coefficients (ICCs), respectively. Precision was estimated by intergroup comparison of the coefficient of variation. The anterior falx plane derived from the MRI data resulted in an intra-observer ICC of 0.869 ± 0.065 (range 0.733–0.936) and inter-observer ICC of 0.876 ± 0.0417 (0.798–0.932) for all measurements, showing significant correlations with the ICC values obtained by the mark point method (p < 0.05). The coefficient of variation showed that the precisions of the 2 methods were statistically comparable. We conclude that, for MRI-based craniofacial midline estimation, measurements made using the anterior cerebral falx plane are as precise, repeatable, and reproducible as those using the manual mark point analysis method. It has a high potential for application in radiation-free 3-dimensional craniofacial analysis.

Anatomical network analysis (AnNA) is a systems biological framework based on network theory that enables anatomical structural analysis by incorporating modularity to model structural complexity. The human brain and facial structures exhibit close structural and functional relationships, suggestive of a co-evolved anatomical network. The present study aimed to analyze the human head as a modular entity that comprises the central nervous system, including the brain, spinal cord, and craniofacial skeleton. An AnNA model was built using 39 anatomical nodes from the brain, spinal cord, and craniofacial skeleton. The linkages were identified using peripheral nerve supply and direct contact between structures. The Spinglass algorithm in the igraph software was applied to construct a network and identify the modules of the central nervous system-craniofacial skeleton anatomical network. Two modules were identified. These comprised an anterior module, which included the forebrain, anterior cranial base, and upper-middle face, and a posterior module, which included the midbrain, hindbrain, mandible, and posterior cranium. These findings may reflect the genetic and signaling networks that drive the mosaic central nervous system and craniofacial development and offer important systems biology perspectives for developmental disorders of craniofacial structures.

Genitourinary infections (GUIs) during pregnancy are a significant clinical concern linked to maternal morbidity. While Streptococcus is a common gut commensal and a known urogenital pathobiont, whether gut-resident Streptococcus plays a causal role in the etiology of pregnancy-related infections remains unclear due to confounding in observational studies. To investigate the potential causal effect of gut Streptococcus abundance on the risk of maternal genitourinary infection during pregnancy using Mendelian randomization (MR). We performed a two-sample MR analysis using publicly available genome-wide association study (GWAS) summary statistics. Genetic instruments for gut Streptococcus abundance were obtained from the MiBioGen consortium (N=18,340). Outcome data for maternal genitourinary infection (ICD-10 O23.x) were sourced from the FinnGen consortium (N=111,731). The inverse-variance weighted (IVW) method was used as the primary analysis, supplemented by sensitivity analyses (MR-Egger, weighted median, MR-PRESSO). We further assessed potential mediation via systemic inflammation (C-reactive protein, interleukin-6) and associations with eleven major adverse pregnancy outcomes (APOs). Genetically predicted higher gut Streptococcus abundance was associated with a reduced risk of maternal genitourinary infection (IVW odds ratio [OR] = 0.63, 95% confidence interval [CI]: 0.43–0.93, p = 0.020). Sensitivity analyses supported this protective association, with no evidence of horizontal pleiotropy (MR-Egger intercept p = 0.942) or significant heterogeneity. No causal effects were observed on systemic inflammatory markers (CRP, IL-6, all p > 0.05) or on major APOs, including postpartum haemorrhage, placental abruption, etc. This MR study provides genetic evidence supporting a causal, protective role of gut Streptococcus against the risk of clinically diagnosed genitourinary infection during pregnancy. This effect appears specific and is not mediated through the systemic inflammatory pathways examined, suggesting a localized mechanism within the genitourinary tract.