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초록
The maternal–neonatal microbiome axis has emerged as a critical biological framework linking maternal health, early-life microbial colonization, neonatal immune and metabolic programming, and disease susceptibility. Maternal microbial reservoirs in the gut, vagina, oral cavity, skin, and breast milk contribute to the assembly of the neonatal microbiome through vertical and environmental transmission. Maternal conditions such as gestational diabetes mellitus, systemic lupus erythematosus, obesity, fetal growth restriction, and antibiotic exposure may alter microbial composition and function, thereby influencing neonatal microbial programming and subsequent health trajectories. In preterm infants, delayed microbial maturation and dysbiosis are frequently observed and are associated with neonatal morbidities. Recent domestic cohort studies further suggest that distinct neonatal phenotypes, including prematurity, intrauterine growth status, cardiovascular instability, respiratory disease, and antibiotic exposure, are accompanied by characteristic microbial signatures and altered ecological network structures. Beyond compositional profiling, microbiome research is rapidly expanding toward multiomics integration, including metagenomics, metabolomics, transcriptomics, and host clinical data. These approaches are increasingly complemented by artificial intelligence-based analysis to characterize microbial maturation trajectories, identify disease-associated biomarkers, and improve predictive modeling. In particular, non-invasive technologies such as electronic nose-based microbial volatile organic compound monitoring represent promising tools for neonatal microbiome surveillance in the neonatal intensive care unit. This review summarizes current evidence on the maternal–neonatal microbiome continuum, highlights cohort-based insights into neonatal microbiome development and disease-associated dysbiosis, and discusses how artificial intelligence-driven multiomics approaches may advance microbiome-based precision diagnostics and precision medicine in neonatology.
키워드
- 제목
- 산모–신생아 마이크로바이옴 축: 차세대 마이크로바이옴 연구를 위한 다중오믹스와 인공지능의 통합
- 제목 (타언어)
- Maternal–Neonatal Microbiome Axis: Integrating Multiomics and Artificial Intelligence for Next-Generation Microbiome Research
- 저자
- 황제균; 박현경
- 발행일
- 2026-06
- 유형
- Y
- 저널명
- Perinatology
- 권
- 37
- 호
- 2
- 페이지
- 27 ~ 38