Pediatric Research ( IF 3.6 ) Pub Date : 2024-03-20 , DOI: 10.1038/s41390-024-03129-z Hannah E. Laue , Julia A. Bauer , Wimal Pathmasiri , Susan C. J. Sumner , Susan McRitchie , Thomas J. Palys , Anne G. Hoen , Juliette C. Madan , Margaret R. Karagas
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Background
Gut-derived metabolites, products of microbial and host co-metabolism, may inform mechanisms underlying children’s neurodevelopment. We investigated whether infant fecal metabolites were related to toddler social behavior.
Methods
Stool samples collected from 6-week-olds (n = 86) and 1-year-olds (n = 209) in the New Hampshire Birth Cohort Study (NHBCS) were analyzed using nuclear magnetic resonance spectroscopy metabolomics. Autism-related behavior in 3-year-olds was assessed by caregivers using the Social Responsiveness Scale (SRS-2). To assess the association between metabolites and SRS-2 scores, we used a traditional single-metabolite approach, quantitative metabolite set enrichment (QEA), and self-organizing maps (SOMs).
Results
Using a single-metabolite approach and QEA, no individual fecal metabolite or metabolite set at either age was associated with SRS-2 scores. Using the SOM method, fecal metabolites of six-week-olds organized into four profiles, which were unrelated to SRS-2 scores. In 1-year-olds, one of twelve fecal metabolite profiles was associated with fewer autism-related behaviors, with SRS-2 scores 3.4 (95%CI: −7, 0.2) points lower than the referent group. This profile had higher concentrations of lactate and lower concentrations of short chain fatty acids than the reference.
Conclusions
We uncovered metabolic profiles in infant stool associated with subsequent social behavior, highlighting one potential mechanism by which gut bacteria may influence neurobehavior.
Impact
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Differences in host and microbial metabolism may explain variability in neurobehavioral phenotypes, but prior studies do not have consistent results.
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We applied three statistical techniques to explore fecal metabolite differences related to social behavior, including self-organizing maps (SOMs), a novel machine learning algorithm.
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A 1-year-old fecal metabolite pattern characterized by high lactate and low short-chain fatty acid concentrations, identified using SOMs, was associated with social behavior less indicative of autism spectrum disorder.
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Our findings suggest that social behavior may be related to metabolite profiles and that future studies may uncover novel findings by applying the SOM algorithm.
中文翻译：
婴儿粪便代谢物浓度模式和幼儿社会行为发展
背景
肠道衍生的代谢物、微生物和宿主共同代谢的产物，可能为儿童神经发育的机制提供信息。我们调查了婴儿粪便代谢物是否与幼儿社会行为有关。
方法
使用核磁共振波谱代谢组学分析了新罕布什尔州出生队列研究 (NHBCS) 中从 6 周龄儿童 ( n = 86) 和 1 岁儿童 ( n = 209) 收集的粪便样本。护理人员使用社会反应量表 (SRS-2) 评估 3 岁儿童的自闭症相关行为。为了评估代谢物和 SRS-2 评分之间的关联，我们使用了传统的单一代谢物方法、定量代谢物集富集 (QEA) 和自组织图 (SOM)。
结果
使用单一代谢物方法和 QEA，没有任何个体粪便代谢物或任一年龄的代谢物组与 SRS-2 评分相关。使用 SOM 方法，六周龄婴儿的粪便代谢物分为四个谱，与 SRS-2 评分无关。在 1 岁儿童中，12 种粪便代谢物谱中的一种与较少的自闭症相关行为相关，SRS-2 评分比参照组低 3.4 (95% CI: -7, 0.2) 分。与参考相比，该谱具有较高浓度的乳酸和较低浓度的短链脂肪酸。
结论
我们发现了婴儿粪便中与随后的社会行为相关的代谢特征，强调了肠道细菌可能影响神经行为的一种潜在机制。
影响
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宿主和微生物代谢的差异可能解释神经行为表型的变异性，但先前的研究并没有得出一致的结果。
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我们应用了三种统计技术来探索与社会行为相关的粪便代谢物差异，包括自组织图（SOM），一种新颖的机器学习算法。
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使用 SOM 识别出一种以高乳酸浓度和低短链脂肪酸浓度为特征的 1 岁粪便代谢模式，与不太表明自闭症谱系障碍的社会行为相关。
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我们的研究结果表明，社会行为可能与代谢物谱有关，未来的研究可能会通过应用 SOM 算法发现新的发现。
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