A population-based approach to analyzing pulses in time series of hormone data.
A population-based approach to analyzing pulses in time series of hormone data.
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DOI：
10.1002/sim.7292
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发表时间：
2017-07-20
影响因子：
2
通讯作者：
Polotsky AJ
中科院分区：
文献类型：
--
作者：
Horton KW;Carlson NE;Grunwald GK;Mulvahill MJ;Polotsky AJ
生殖生理学的研究涉及快速采样协议，导致激素浓度的时间序列。这些时间序列的特征模式是荷尔蒙释放的脉冲。存在用于量化脉冲释放特征的各种统计模型。目前，这些模型分别适用于每一个人，所得估计数取平均数，以得出事后人口水平估计数。当信噪比较小或观测时间较短时（例如，6小时），这种两阶段估计方法可能会失败。这项工作将单一主题建模框架扩展到类似于复杂的药物代谢数据的人群框架。目标是利用受试者之间的信息来更清楚地识别脉搏位置并改善其他模型参数的估计。这种建模扩展已被证明是困难的，因为脉冲数和位置是未知的。在这里，我们表明，同时建模一组科目是计算上可行的贝叶斯框架，使用出生-死亡马尔可夫链蒙特卡罗（BDMCMC）估计算法。通过模拟，我们表明，这种基于人口的方法降低了假阳性和阴性脉冲检测率，并导致人口水平的频率，脉冲大小和激素消除参数的估计偏差较小。然后，我们将该方法应用于健康女性的生殖研究，其中研究中的21名受试者中约有1/3使用单一受试者拟合方法没有适当的拟合。使用群体模型产生了所有模型参数的更精确、生物学上合理的估计值。
Studies of reproductive physiology involve rapid sampling protocols that result in time series of hormone concentrations. The signature pattern in these times series is pulses of hormone release. Various statistical models for quantifying the pulsatile release features exist. Currently these models are fitted separately to each individual and the resulting estimates averaged to arrive at post-hoc population level estimates. When the signal-to-noise ratio is small or the time of observation short (e.g., 6 hours) this two-stage estimation approach can fail. This work extends the single subject modelling framework to a population framework similar to what exists for complex pharamacokinetics data. The goal is to leverage information across subjects to more clearly identify pulse locations and improve estimation of other model parameters. This modelling extension has proven difficult because the pulse number and locations are unknown. Here we show that simultaneously modelling a group of subjects is computationally feasible in a Bayesian framework using a birth-death Markov chain Monte Carlo (BDMCMC) estimation algorithm. Via simulation we show that this population based approach reduces the false positive and negative pulse detection rates and results in less biased estimates of population level parameters of frequency, pulse size and hormone elimination. We then apply the approach to a reproductive study in healthy women where approximately 1/3 of the 21 subjects in the study did not have appropriate fits using the single subject fitting approach. Using the population model produced more precise, biologically plausible estimates of all model parameters.
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影响因子：
1.9
作者：
Carlson, Nichole E.;Johnson, Timothy D.;Brown, Morton B.
通讯作者：
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影响因子：
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作者：
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作者：
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DOI：
10.1152/ajpregu.00310.2010
发表时间：
2010-09-01
影响因子：
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作者：
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作者：
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