LOG-CONTRAST REGRESSION WITH FUNCTIONAL COMPOSITIONAL PREDICTORS: LINKING PRETERM INFANT'S GUT MICROBIOME TRAJECTORIES TO NEUROBEHAVIORAL OUTCOME.

LOG-CONTRAST REGRESSION WITH FUNCTIONAL COMPOSITIONAL PREDICTORS: LINKING PRETERM INFANT'S GUT MICROBIOME TRAJECTORIES TO NEUROBEHAVIORAL OUTCOME.
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与功能组成预测指标的对比对比回归:将早产儿的肠道微生物组轨迹与神经行为结果联系起来。

DOI:
10.1214/20-aoas1357
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发表时间:
2020-09
期刊:
The annals of applied statistics
影响因子:
--
通讯作者:
Chen K
Chen K
中科院分区:
其他
文献类型:
--
作者:
Sun Z;Xu W;Cong X;Li G;Chen K

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众所周知,新生儿重症监护病房 (NICU) 的经历是影响早产儿神经发育和健康结果的最关键因素之一。据推测,早产儿早期生活的压力经历通过所谓的脑肠轴的调节对肠道微生物组产生了影响,因此,某些微生物组标记物可以预测婴儿后期的神经发育。为了进行调查,进行了一项早产儿研究;在婴儿出生后第一个月内收集婴儿粪便样本,产生功能性组成微生物组数据,并在婴儿达到月经后年龄 36-38 周时测量神经行为结果。为了识别潜在的微生物组标记并估计出生后早期肠道微生物组组成的轨迹如何影响早产儿后期的神经行为结果,我们创新了具有功能组成预测因子的稀疏对数对比回归。严格保留函数单纯形结构,并且允许函数组合预测变量随着时间的推移对结果产生稀疏、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富有洞察力的结果。已确定的微生物组标记及其对神经行为结果影响的估计时间动态揭示了产后早期压力积累与婴儿神经发育过程之间的联系。
The neonatal intensive care unit (NICU) experience is known to be one of the most crucial factors that drive preterm infant’s 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 post-menstrual 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.
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