BackgroundGrowing evidence supports that alterations in the gut microbiota play an essential role in the etiology of anxiety, depression, and other psychiatric disorders. However, the potential effect of oral microbiota on mental health has received little attention.MethodsUsing the latest genome-wide association study (GWAS) summary data of the oral microbiome, polygenic risk scores (PRSs) of 285 salivary microbiomes and 309 tongue dorsum microbiomes were conducted. Logistic and linear regression models were applied to evaluate the relationship between salivary-tongue dorsum microbiome interactions with anxiety and depression. Two-sample Mendelian randomization (MR) was utilized to compute the causal effects between the oral microbiome, anxiety, and depression.ResultsWe observed significant salivary-tongue dorsum microbiome interactions related to anxiety and depression traits. Significantly, one common interaction was observed to be associated with both anxiety score and depression score, Centipeda periodontii SGB 224 × Granulicatella uSGB 3289 (P depressionscore = 1.41 × 10−8, P anxietyscore = 5.10 × 10−8). Furthermore, we detected causal effects between the oral microbiome and anxiety and depression. Importantly, we identified one salivary microbiome associated with both anxiety and depression in both the UKB database and the Finngen public database, Eggerthia (P IVW − majordepression − UKB = 2.99 × 10−6, P IVW − Self − reportedanxiety/panicattacks − UKB = 3.06 × 10−59, P IVW − depression − Finngen = 3.16 × 10,-16 P IVW − anxiety − Finngen = 1.14 × 10−115).ConclusionThis study systematically explored the relationship between the oral microbiome and anxiety and depression, which could help improve our understanding of disease pathogenesis and propose new diagnostic targets and early intervention strategies.

Background Longevity is one of the most complex phenotypes, and its genetic basis remains unclear. This study aimed to explore the genetic correlation and potential causal association between gut microbiota and longevity. Results Linkage disequilibrium score (LDSC) regression analysis and a bi-directional two-sample Mendelian Randomization (MR) analysis were performed to analyze gut microbiota and longevity-related traits. LDSC analysis detected four candidate genetic correlations, including Veillonella (genetic correlation = 0.5578, P = 4.67 × 10− 2) and Roseburia (genetic correlation = 0.4491, P = 2.67 × 10− 2) for longevity, Collinsella (genetic correlation = 0.3144, P = 4.07 × 10− 2) for parental lifespan and Sporobacter (genetic correlation = 0.2092, P = 3.53 × 10− 2) for healthspan. Further MR analysis observed suggestive causation between Collinsella and parental longevity (father’s age at death) (weighted median: b = 1.79 × 10− 3, P = 3.52 × 10− 2). Reverse MR analysis also detected several causal effects of longevity-related traits on gut microbiota, such as longevity and Sporobacter (IVW: b = 7.02 × 10− 1, P = 4.21 × 10− 25). Statistical insignificance of the heterogeneity test and pleiotropy test supported the validity of the MR study. Conclusion Our study found evidence that gut microbiota is causally associated with longevity, or vice versa, providing novel clues for understanding the roles of gut microbiota in aging development.

Multiple previous studies explored the associations between early life factors and the age at onset of the depression. However, they only focused on the influence of environmental or genetic factors, without considering the interactions between them. Based on previous genome-wide association study (GWAS) data, we first calculated polygenic risk score (PRS) for depression. Regression analyses were conducted to assess the interacting effects of depression PRS and 5 early life factors, including felt hated by family member (N = 40,112), physically abused by family (N = 40,464), felt loved (N = 35633), and sexually molested (N = 41,595) in childhood and maternal smoking during pregnancy (N = 38,309), on the age at onset of the depression. Genome-wide environment interaction studies (GWEIS) were then performed to identify the genes interacting with early life factors for the age at onset of the depression. In regression analyses, we observed significant interacting effects of felt loved as a child and depression PRS on the age at onset of depression in total sample (β = 0.708, P = 5.03 × 10−3) and males (β = 1.421, P = 7.64 × 10−4). GWEIS identified a novel candidate loci interacting with felt loved as a child at GSAP (rs2068031, P = 4.24 × 10–8) and detected several genes with suggestive significance association, such as CMYA5 (rs7343, P = 2.03 × 10–6) and KIRREL3 (rs535603, P = 4.84 × 10–6) in males. Our results indicate emotional care in childhood may affect the age at onset of depression, especially in males, and GSAP plays an important role in their interaction.