Evidence map›Paper›PMID 41629888›Full record

ArticleBMC pediatrics2026

Impact of phototherapy on gut microbiota composition and function in neonates with hyperbilirubinemia: a metagenomic analysis.

Mengjie Luo, Xiaodong Xiao, Yi Wu

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Article in BMC pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mengjie Luo *Department of Clinical Laboratory Science, Shenzhen Yantian District People's Hospital, 2010 Wutong Road, Yantian District, Shenzhen, 518081, China.
Xiaodong Xiao *Department of Pediatrics, Shenzhen Yantian District People's Hospital, Shenzhen, 518081, China.
Yi WuDepartment of Clinical Laboratory Science, Shenzhen Yantian District People's Hospital, 2010 Wutong Road, Yantian District, Shenzhen, 518081, China. 845007571@qq.com.

Funding

Science and Technology Funding Program of Yantian District Bureau of Science and Technology No. YTWS20210102
6 · The paper itself

Abstract

backgroundPhototherapy serves as the primary treatment for neonatal hyperbilirubinemia (NH). This research aims to investigate the impact of phototherapy on the gut microbiota of NH, and to provide reliable theoretical evidence for the clinical application of phototherapy in such cases.

methodsIn this self-controlled longitudinal study, 26 newborns diagnosed with NH were enrolled. Fecal samples were collected before (pre-treatment) and 48 h after (post-treatment) initiating phototherapy. The gut microbiota was profiled using high-throughput 16 S ribosomal RNA (rRNA) gene sequencing. Gut microbiota composition and diversity were analyzed using standard bioinformatics pipelines. Data were processed with standard bioinformatics tools for taxonomic annotation, diversity analysis, and functional prediction based on the COG, KEGG, and MetaCyc databases. Statistical significance was assessed using the Wilcoxon signed-rank test (P < 0.05).

resultsWhile no significant differences were observed at the species level, analysis at the genus level revealed significant alterations in the gut microbiota. The genera Clostridium and Megamonas were identified as significantly increased post-phototherapy. Linear discriminant analysis effect size (LEfSe) analysis further confirmed distinct microbial signatures between the two groups: pre-treatment samples were enriched with families such as Porphyromonadaceae, Lachnospiraceae, Alcaligenaceae, Ruminococcaceae, Moraxellaceae, and the order Pseudomonadales. In contrast, post-treatment samples were predominantly characterized by the class Erysipelotrichi and its associated taxa (Erysipelotrichales and Erysipelotrichaceae). α-diversity indices (Sobs, Chao, Shannon, Simpson) showed no significant differences between the two groups, whereas β-diversity analysis indicated significant microbial community separation (P < 0.05). Predicted functional profiles (based on 16 S rRNA gene data using PICRUSt2) suggested predominant roles in metabolism, genetic information processing, and biosynthesis. However, no significant differences were observed between the pre- and post-treatment groups.

conclusionsPhototherapy significantly modulated the gut microbial composition of neonates with NH, notably increasing the abundance of Clostridium and Megamonas, and shifting the community towards Erysipelotrichi, while overall microbial functional capacity remained stable. These findings highlight the dynamic yet resilient nature of the neonatal gut microbiota under phototherapy and provide a foundation for microbiome-informed management strategies in neonatal hyperbilirubinemia.

Indexed as

Gastrointestinal MicrobiomeHyperbilirubinemia, NeonatalPhototherapyFecesFemaleHumansInfant, NewbornLongitudinal StudiesMaleMetagenomicsGut microbiomeHigh-throughput sequencingMetagenomicsNeonatal hyperbilirubinemia (NH)Phototherapy

Identifiers

PMID41629888
PMCPMC12955324

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.