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BACKGROUND: While early life exposures such as mode of birth, breastfeeding, and antibiotic use are established regulators of microbiome composition in early childhood, recent research suggests that the social environment may also exert influence. Two recent studies in adults demonstrated associations between socioeconomic factors and microbiome composition. This study expands on this prior work by examining the association between family socioeconomic status (SES) and host genetics with microbiome composition in infants and children. METHODS: Family SES was used to predict a latent variable representing six genera abundances generated from whole-genome shotgun sequencing. A polygenic score derived from a microbiome genome-wide association study was included to control for potential genetic associations. Associations between family SES and microbiome diversity were assessed. RESULTS: Anaerostipes, Bacteroides, Eubacterium, Faecalibacterium, and Lachnospiraceae spp. significantly loaded onto a latent factor, which was significantly predicted by SES (p < 0.05) but not the polygenic score (p > 0.05). Our results indicate that SES did not predict alpha diversity but did predict beta diversity (p < 0.001). CONCLUSIONS: Our results demonstrate that modifiable environmental factors influence gut microbiome composition at an early age. These results are important as our understanding of gut microbiome influences on health continue to expand.
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AIM: To explore differential DNA methylation (DNAm) in Aicardi syndrome (AIC), a severe neurodevelopmental disorder with largely unknown etiology. PATIENTS & METHODS: We characterized DNAm in AIC female patients and parents using the Illumina 450 K array. Differential DNAm was assessed using the local outlier factor algorithm, and results were validated via qPCR in a larger set of AIC female patients, parents and unrelated young female controls. Functional epigenetic modules analysis was used to detect pathways integrating both genome-wide DNAm and RNA-seq data. RESULTS & CONCLUSION: We detected differential methylation patterns in AIC patients in several neurodevelopmental and/or neuroimmunological networks. These networks may be part of the underlying pathogenic mechanisms involved in the disease.