Robust Hierarchical Finite Mixture Modeling of Collagen Fibril Diameters

描述(申请人提供)：细胞外基质组装是一个多步骤的过程，每一步都需要特定的调控相互作用。明确基质组装的步骤及其调控机制将有助于我们更好地了解肌腱的发育、生长、修复和与衰老或损伤相关的病理变化，以及损伤或手术干预后的修复/再生。研究了肌腱细胞外基质组装的机制，部分是通过研究肌腱原纤维直径分布分解成具有不同特征和功能作用的亚群。因此，将纤维直径作为正常亚群的有限混合物进行统计建模，可以深入了解胶原纤维形成的调控机制。这个应用程序的总体目标是开发稳健的单目标函数估计方法和相应的软件，用于拟合具有多个水平的随机效果和条件分布的分层随机效果模型，这些随机效果和条件分布被建模为正态分量的有限混合。这一方法将为对正在进行的肌腱细胞外基质受控组装研究(NIH/NIAMSD R01AR44745)和类似的胶原纤维形成研究产生的胶原纤维直径数据进行新颖而有效的统计分析提供一个框架。虽然将要开发的统计方法是为了满足对胶原纤维直径分布进行稳健和有效分析的需要，但所提出的模型和估计方法是非常通用的，将有助于对最一般的聚集生物数据的分析。拟议的研究将(1)扩展统计方法和软件，以生成新的模型，并为具有由正态成分的有限混合表示的条件分布的多水平聚集数据开发相应的最大似然和稳健估计方法；(2)通过模拟研究所提出的模型的统计特性；(3)比较用于将条件胶原纤维直径分布建模为正态成分的有限混合的离群值估计方法的最大似然和稳健估计的性能；(4)使用所提出的分层随机效应模型和稳健估计方法来分析从肌腱胶原纤维形成研究中获得的大量数据，这些方法被发现是对纤维直径数据最优的。对胶原纤维发育的研究对于我们理解与衰老或损伤相关的生长、修复和病理变化，以及创伤或手术干预后的修复/再生具有重要意义。通过将原纤维直径分布分解为具有不同特征和功能作用的亚群，可以研究原纤维发育的机理。这个项目的重点是开发新的统计方法来分析这种分解。

DESCRIPTION (provided by applicant): Extracellular matrix assembly is a multi-step process, with each step requiring specific regulatory interactions. Definition of the steps in matrix assembly and the mechanisms regulating them will enhance our understanding of tendon development, growth, repair and pathological changes associated with aging or injury and repair/regeneration after wounding or surgical intervention. The mechanisms involved in tendon extracellular matrix assembly are investigated, in part, by studying decomposition of the fibril diameter distributions into subpopulations with different characteristics and functional roles. Therefore, statistical modeling of fibril diameters as finite mixtures of normal subpopulations provides insight into the mechanisms regulating collagen fibrillogenesis. The overall goal of this application is to develop robust one-objective-function estimation methods and corresponding software for fitting a hierarchical random effects model with multiple levels of random effects and conditional distributions modeled as finite mixtures of normal components. This methodology will provide a framework for novel and efficient statistical analysis of the collagen fibril diameters data generated by the ongoing study Regulated Assembly of Tendon Extracellular Matrix (NIH/NIAMSD R01AR44745) and similar studies of collagen fibrillogenesis. While statistical methodology that will be developed is geared toward the needs of robust and efficient analyses of collagen fibril diameter distributions, the proposed models and estimation methods are very general, and will be useful for analyses of most general clustered biological data. The proposed studies will (1) extend statistical methodology and software to generate novel models and develop corresponding maximum likelihood and robust estimation methods for multilevel clustered data with conditional distributions represented by finite mixtures of normal components; (2) investigate the statistical properties of the proposed models using simulations; (3) compare the performance of the maximum likelihood and robust with respect to outliers estimation methods for modeling conditional collagen fibril diameter distributions as finite mixtures of normal components; (4) analyze extensive data from the study of tendon collagen fibrillogenesis using the proposed hierarchical random effects model and robust estimating approaches that are found optimal for fibril diameters data. The studies of collagen fibril development are important for our understanding of growth, repair and pathological changes associated with aging or injury and repair/regeneration after wounding or surgical intervention. The mechanisms of fibril development may be studied by decomposing the fibril diameter distributions into subpopulations with different characteristics and functional roles. This project focuses on developing novel statistical methods for analyses of such decompositions.