The neonatal intensive care unit (NICU) experience is known to be one of the most crucial factors that drive preterm infants’ neurodevelopmental and health outcome. It is hypothesized that stressful early life experience of very preterm neonate is imprinting gut microbiome by the regulation of the so-called brain-gut axis, and, consequently, certain microbiome markers are predictive of later infant neurodevelopment. To investigate, a preterm infant study was conducted; infant fecal samples were collected during the infants’ first month of postnatal age, resulting in functional compositional microbiome data, and neurobehavioral outcomes were measured when infants reached 36–38 weeks of postmenstrual age. To identify potential microbiome markers and estimate how the trajectories of gut microbiome compositions during early postnatal stage impact later neurobehavioral outcomes of the preterm infants, we innovate a sparse log-contrast regression with functional compositional predictors. The functional simplex structure is strictly preserved, and the functional compositional predictors are allowed to have sparse, smoothly varying and accumulating effects on the outcome through time. Through a pragmatic basis expansion step, the problem boils down to a linearly constrained sparse group regression, for which we develop an efficient algorithm and obtain theoretical performance guarantees. Our approach yields insightful results in the preterm infant study. The identified microbiome markers and the estimated time dynamics of their impact on the neurobehavioral outcome shed lights on the linkage between stress accumulation in early postnatal stage and neurodevelpomental process of infants.

中文翻译：

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具有功能成分预测因子的对数对比回归：将早产儿的肠道微生物组轨迹与神经行为结果联系起来

众所周知，新生儿重症监护病房 (NICU) 的经历是推动早产儿神经发育和健康结果的最关键因素之一。据推测，极早产儿的压力早期生活经历正在通过所谓的脑-肠轴的调节影响肠道微生物组，因此，某些微生物组标记可预测婴儿后期的神经发育。为了调查，进行了一项早产儿研究；在婴儿出生后的第一个月收集婴儿粪便样本，产生功能性微生物组数据，并在婴儿达到 36-38 周后测量神经行为结果。为了识别潜在的微生物组标记并估计产后早期肠道微生物组组成的轨迹如何影响早产儿的后期神经行为结果，我们创新了具有功能组成预测因子的稀疏对数对比回归。函数单纯形结构被严格保留，并且允许函数组成预测变量随着时间的推移对结果具有稀疏、平滑变化和累积的影响。通过实用的基础扩展步骤，问题归结为线性约束稀疏组回归，为此我们开发了一种有效的算法并获得了理论性能保证。我们的方法在早产儿研究中产生了有见地的结果。