Diet alters age-related remodeling of aortic collagen in mice susceptible to atherosclerosis.

Vascular cells restructure extracellular matrix in response to aging or changes in mechanical loading. Here, we characterized collagen architecture during age-related aortic remodeling in atherosclerosis-prone mice. We hypothesized that changes in collagen fiber orientation reflect an altered balance between passive and active forces acting on the arterial wall. We examined two factors that can alter this balance, endothelial dysfunction and reduced smooth muscle cell (SMC) contractility. Collagen fiber organization was visualized by second-harmonic generation microscopy in aortic adventitia of apolipoprotein E (apoE) knockout (KO) mice at 6 wk and 6 mo of age on a chow diet and at 7.5 mo of age on a Western diet (WD), using image analysis to yield mean fiber orientation. Adventitial collagen fibers became significantly more longitudinally oriented with aging in apoE knockout mice on chow diet. Conversely, fibers became more circumferentially oriented with aging in mice on WD. Total collagen content increased significantly with age in mice fed WD. We compared expression of endothelial nitric oxide synthase and acetylcholine-mediated nitric oxide release but found no evidence of endothelial dysfunction in older mice. Time-averaged volumetric blood flow in all groups showed no significant changes. Wire myography of aortic rings revealed decreases in active stress generation with age that were significantly exacerbated in WD mice. We conclude that the aorta displays a distinct remodeling response to atherogenic stimuli, indicated by altered collagen organization. Collagen reorganization can occur in the absence of altered hemodynamics and may represent an adaptive response to reduced active stress generation by vascular SMCs.NEW & NOTEWORTHY The following major observations were made in this study: 1) aortic adventitial collagen fibers become more longitudinally oriented with aging in apolipoprotein E knockout mice fed a chow diet; 2) conversely, adventitial collagen fibers become more circumferentially oriented with aging in apoE knockout mice fed a high-fat diet; 3) adventitial collagen content increases significantly with age in mice on a high-fat diet; 4) these alterations in collagen organization occur largely in the absence of hemodynamic changes; and 5) circumferential reorientation of collagen is associated with decreased active force generation (contractility) in aged mice on a high-fat diet.

Treatment effect on ordinal functional outcome using piecewise multistate Markov model with unobservable baseline: an application to the modified Rankin scale.

In clinical trials, longitudinally assessed ordinal outcomes are commonly dichotomized and only the final measure is used for primary analysis, partly for ease of clinical interpretation. Dichotomization of the ordinal scale and failure to utilize the repeated measures can reduce statistical power. Additionally, in certain emergent settings, the same measure cannot be assessed at baseline prior to treatment. For such a data set, a piecewise-constant multistate Markov model that incorporates a latent model for the unobserved baseline measure is proposed. These models can be useful in analyzing disease history data and are advantageous in clinical applications where a disease process naturally moves through increasing stages of severity. Two examples are provided using acute stroke clinical trials data. Conclusions drawn in this article are consistent with those from the primary analysis for treatment effect in both of the motivating examples. Use of these models allows for a more refined examination of treatment effect and describes the movement between health states from baseline to follow-up visits which may provide more clinical insight into the treatment effect.

Model Selection and Estimation with Quantal-Response Data in Benchmark Risk Assessment.

This article describes several approaches for estimating the benchmark dose (BMD) in a risk assessment study with quantal dose-response data and when there are competing model classes for the dose-response function. Strategies involving a two-step approach, a model-averaging approach, a focused-inference approach, and a nonparametric approach based on a PAVA-based estimator of the dose-response function are described and compared. Attention is raised to the perils involved in data "double-dipping" and the need to adjust for the model-selection stage in the estimation procedure. Simulation results are presented comparing the performance of five model selectors and eight BMD estimators. An illustration using a real quantal-response data set from a carcinogenecity study is provided.

Comparison of Aortic Collagen Fiber Angle Distribution in Mouse Models of Atherosclerosis Using Second-Harmonic Generation (SHG) Microscopy.

Characterization of collagen fiber angle distribution throughout the blood vessel wall provides insight into the mechanical behavior of healthy and diseased arteries and their capacity to remodel. Atherosclerotic plaque contributes to the overall mechanical behavior, yet little is known experimentally about how collagen fiber orientation is influenced by atherogenesis. We hypothesized that atherosclerotic lesion development, and the factors contributing to lesion development, leads to a shift in collagen fiber angles within the aorta. Second-harmonic generation microscopy was used to visualize the three-dimensional organization of collagen throughout the aortic wall and to examine structural differences in mice maintained on high-fat Western diet versus age-matched chow diet mice in a model of atherosclerosis. Image analysis was performed on thoracic and abdominal sections of the aorta from each mouse to determine fiber orientation, with the circumferential (0°) and blood flow directions (axial ±90°) as the two reference points. All measurements were used in a multiple regression analysis to determine the factors having a significant influence on mean collagen fiber angle. We found that mean absolute angle of collagen fibers is 43° lower in Western diet mice compared with chow diet mice. Mice on a chow diet have a mean collagen fiber angle of ±63°, whereas mice on a Western diet have a more circumferential fiber orientation (~20°). This apparent shift in absolute angle coincides with the development of extensive aortic atherosclerosis, suggesting that atherosclerotic factors contribute to collagen fiber angle orientation.

Asymptotics for a Class of Dynamic Recurrent Event Models.

Asymptotic properties, both consistency and weak convergence, of estimators arising in a general class of dynamic recurrent event models are presented. The class of models take into account the impact of interventions after each event occurrence, the impact of accumulating event occurrences, the induced informative and dependent right-censoring mechanism due to the data-accrual scheme, and the effect of covariate processes on the recurrent event occurrences. The class of models subsumes as special cases many of the recurrent event models that have been considered in biostatistics, reliability, and in the social sciences. The asymptotic properties presented have the potential of being useful in developing goodness-of-fit and model validation procedures, confidence intervals and confidence bands constructions, and hypothesis testing procedures for the finite- and infinite-dimensional parameters of a general class of dynamic recurrent event models, albeit the models without frailties.

Nonparametric estimation with recurrent competing risks data.

Nonparametric estimators of component and system life distributions are developed and presented for situations where recurrent competing risks data from series systems are available. The use of recurrences of components' failures leads to improved efficiencies in statistical inference, thereby leading to resource-efficient experimental or study designs or improved inferences about the distributions governing the event times. Finite and asymptotic properties of the estimators are obtained through simulation studies and analytically. The detrimental impact of parametric model misspecification is also vividly demonstrated, lending credence to the virtue of adopting nonparametric or semiparametric models, especially in biomedical settings. The estimators are illustrated by applying them to a data set pertaining to car repairs for vehicles that were under warranty.

Information-theoretic model-averaged benchmark dose analysis in environmental risk assessment.

An important objective in environmental risk assessment is estimation of minimum exposure levels, called Benchmark Doses (BMDs), that induce a pre-specified Benchmark Response (BMR) in a dose-response experiment. In such settings, representations of the risk are traditionally based on a specified parametric model. It is a well-known concern, however, that existing parametric estimation techniques are sensitive to the form employed for modeling the dose response. If the chosen parametric model is in fact misspecified, this can lead to inaccurate low-dose inferences. Indeed, avoiding the impact of model selection was one early motivating issue behind development of the BMD technology. Here, we apply a frequentist model averaging approach for estimating benchmark doses, based on information-theoretic weights. We explore how the strategy can be used to build one-sided lower confidence limits on the BMD, and we study the confidence limits' small-sample properties via a simulation study. An example from environmental carcinogenicity testing illustrates the calculations. It is seen that application of this information-theoretic, model averaging methodology to benchmark analysis can improve environmental health planning and risk regulation when dealing with low-level exposures to hazardous agents.

The Impact of Model Uncertainty on Benchmark Dose Estimation.

We study the popular benchmark dose (BMD) approach for estimation of low exposure levels in toxicological risk assessment, focusing on dose-response experiments with quantal data. In such settings, representations of the risk are traditionally based on a specified, parametric, dose-response model. It is a well-known concern, however, that uncertainty can exist in specification and selection of the model. If the chosen parametric form is in fact misspecified, this can lead to inaccurate, and possibly unsafe, lowdose inferences. We study the effects of model selection and possible misspecification on the BMD, on its corresponding lower confidence limit (BMDL), and on the associated extra risks achieved at these values, via large-scale Monte Carlo simulation. It is seen that an uncomfortably high percentage of instances can occur where the true extra risk at the BMDL under a misspecified or incorrectly selected model can surpass the target BMR, exposing potential dangers of traditional strategies for model selection when calculating BMDs and BMDLs.

Semiparametric Estimation with Recurrent Event Data under Informative Monitoring.

Consider a study where the times of occurrences of a recurrent event for n units are monitored. For the ith unit, T(i1), T(i2), …, denote the successive event interoccurrence times and this unit is monitored over a random period [0, τ(i)] with τ(i) independent of the T(ij)s. Over this monitoring period, [Formula: see text] is the random number of event occurrences. The T(ij)s are independent and identically distributed (IID) from an unknown continuous distribution function F and the τ(i)s are IID from a distribution function G. A generalized Koziol-Green (GKG) structure wherein 1-G = (1-F)(ß) for some ß > 0 is assumed. Under this model, Nelson-Aalen and product-limit type estimators of Λ = -log(1-F) and F are obtained, as well as an estimator of ß. Asymptotic and small-sample properties of these estimators are obtained and the estimator of F is compared to the fully nonparametric estimator in Peña et al. (2001) in terms of their finite-sample and asymptotic efficiency. The performance of the estimators of F are also examined when the GKG structure does not hold through a simulation study.

POWER-ENHANCED MULTIPLE DECISION FUNCTIONS CONTROLLING FAMILY-WISE ERROR AND FALSE DISCOVERY RATES.

Improved procedures, in terms of smaller missed discovery rates (MDR), for performing multiple hypotheses testing with weak and strong control of the family-wise error rate (FWER) or the false discovery rate (FDR) are developed and studied. The improvement over existing procedures such as the Sidák procedure for FWER control and the Benjamini-Hochberg (BH) procedure for FDR control is achieved by exploiting possible differences in the powers of the individual tests. Results signal the need to take into account the powers of the individual tests and to have multiple hypotheses decision functions which are not limited to simply using the individual p-values, as is the case, for example, with the Sidák, Bonferroni, or BH procedures. They also enhance understanding of the role of the powers of individual tests, or more precisely the receiver operating characteristic (ROC) functions of decision processes, in the search for better multiple hypotheses testing procedures. A decision-theoretic framework is utilized, and through auxiliary randomizers the procedures could be used with discrete or mixed-type data or with rank-based nonparametric tests. This is in contrast to existing p-value based procedures whose theoretical validity is contingent on each of these p-value statistics being stochastically equal to or greater than a standard uniform variable under the null hypothesis. Proposed procedures are relevant in the analysis of high-dimensional "large M, small n" data sets arising in the natural, physical, medical, economic and social sciences, whose generation and creation is accelerated by advances in high-throughput technology, notably, but not limited to, microarray technology.

Randomised P-values and nonparametric procedures in multiple testing.

The validity of many multiple hypothesis testing procedures for false discovery rate (FDR) control relies on the assumption that P-value statistics are uniformly distributed under the null hypotheses. However, this assumption fails if the test statistics have discrete distributions or if the distributional model for the observables is misspecified. A stochastic process framework is introduced that, with the aid of a uniform variate, admits P-value statistics to satisfy the uniformity condition even when test statistics have discrete distributions. This allows nonparametric tests to be used to generate P-value statistics satisfying the uniformity condition. The resulting multiple testing procedures are therefore endowed with robustness properties. Simulation studies suggest that nonparametric randomised test P-values allow for these FDR methods to perform better when the model for the observables is nonparametric or misspecified.

The mRNA binding proteins HuR and tristetraprolin regulate cyclooxygenase 2 expression during colon carcinogenesis.

BACKGROUND & AIMS: During tumorigenesis, loss of rapid messenger RNA (mRNA) decay allows for overexpression of cancer-associated genes. The RNA-binding proteins Hu antigen R (HuR) and tristetraprolin (TTP) bind AU-rich elements in the 3' untranslated region of many cancer-associated mRNAs and target them for stabilization or rapid decay, respectively. We examined the functions of HuR and TTP during colon tumorigenesis and their ability to regulate cyclooxygenase (COX-2), a mediator of prostaglandin synthesis that increases in the colon tumor microenvironment. METHODS: We evaluated expression of HuR and TTP during colorectal tumorigenesis and in colon cancer cells and associated them with COX-2 expression. HuR and TTP-inducible cells were created to investigate HuR- and TTP-mediated regulation of COX-2. RESULTS: In normal colon tissues, low levels of nuclear HuR and higher levels of TTP were observed. By contrast, increased HuR expression and cytoplasmic localization were observed in 76% of adenomas and 94% of adenocarcinomas, and TTP expression was lost in >75% of adenomas and adenocarcinomas. Similar results were obtained for HuR and TTP mRNA levels in normal and staged tumor samples. In both adenomas and adenocarcinomas, COX-2 overexpression was associated with increased HuR and decreased TTP (P < .0001); similar associations were observed in colon cancer cells. HuR overexpression in cells up-regulated COX-2 expression, whereas overexpression of TTP inhibited it; limited TTP expression antagonized HuR-mediated COX-2 overexpression. CONCLUSIONS: Increased expression of the mRNA stability factor HuR and loss of the decay factor TTP occurs during early stages of colorectal tumorigenesis. These changes promote COX-2 overexpression and could contribute to colon tumorigenesis.

Estimation and Efficiency with Recurrent Event Data under Informative Monitoring.

This article deals with studies that monitor occurrences of a recurrent event for n subjects or experimental units. It is assumed that the i(th) unit is monitored over a random period [0,tau(i)]. The successive inter-event times T(i1), T(i2), ..., are assumed independent of tau(i). The random number of event occurrences over the monitoring period is K(i) = max{k in {0, 1, 2, ...} : T(i1) + T(i2) + ... + T(ik) 0, a generalized Koziol-Green (cf., Koziol and Green (1976); Chen, Hollander, and Langberg (1982)) model. Asymptotic properties of estimators of theta, beta, and F are presented. Efficiencies of estimators of theta and F are ascertained relative to estimators which ignores the informative monitoring aspect. These comparisons reveal the gain in efficiency when the informative structure of the model is exploited. Concrete demonstrations were performed for F exponential and a two-parameter Weibull.

Recurrent events and the exploding Cox model.

Counting process models have played an important role in survival and event history analysis for more than 30 years. Nevertheless, almost all models that are being used have a very simple structure. Analyzing recurrent events invites the application of more complex models with dynamic covariates. We discuss how to define valid models in such a setting. One has to check carefully that a suggested model is well defined as a stochastic process. We give conditions for this to hold. Some detailed discussion is presented in relation to a Cox type model, where the exponential structure combined with feedback lead to an exploding model. In general, counting process models with dynamic covariates can be formulated to avoid explosions. In particular, models with a linear feedback structure do not explode, making them useful tools in general modeling of recurrent events.

Transforming Growth Factor Beta3 is Required for Cardiovascular Development.

Transforming growth factor beta3 (TGFB3) gene mutations in patients of arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD1) and Loeys-Dietz syndrome-5 (LDS5)/Rienhoff syndrome are associated with cardiomyopathy, cardiac arrhythmia, cardiac fibrosis, cleft palate, aortic aneurysms, and valvular heart disease. Although the developing heart of embryos express Tgfb3, its overarching role remains unclear in cardiovascular development and disease. We used histological, immunohistochemical, and molecular analyses of Tgfb3-/- fetuses and compared them to wildtype littermate controls. The cardiovascular phenotypes were diverse with approximately two thirds of the Tgfb3-/- fetuses having one or more cardiovascular malformations, including abnormal ventricular myocardium (particularly of the right ventricle), outflow tract septal and alignment defects, abnormal aortic and pulmonary trunk walls, and thickening of semilunar and/or atrioventricular valves. Ventricular septal defects (VSD) including the perimembranous VSDs were observed in Tgfb3-/- fetuses with myocardial defects often accompanied by the muscular type VSD. In vitro studies using TGFß3-deficient fibroblasts in 3-D collagen lattice formation assays indicated that TGFß3 was required for collagen matrix reorganization. Biochemical studies indicated the 'paradoxically' increased activation of canonical (SMAD-dependent) and noncanonical (MAP kinase-dependent) pathways. TGFß3 is required for cardiovascular development to maintain a balance of canonical and noncanonical TGFß signaling pathways.

Loss of Function of Phosphodiesterase 11A4 Shows that Recent and Remote Long-Term Memories Can Be Uncoupled.

Systems consolidation is a process by which memories initially require the hippocampus for recent long-term memory (LTM) but then become increasingly independent of the hippocampus and more dependent on the cortex for remote LTM. Here, we study the role of phosphodiesterase 11A4 (PDE11A4) in systems consolidation. PDE11A4, which degrades cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP), is preferentially expressed in neurons of CA1, the subiculum, and the adjacently connected amygdalohippocampal region. In male and female mice, deletion of PDE11A enhances remote LTM for social odor recognition and social transmission of food preference (STFP) despite eliminating or silencing recent LTM for those same social events. Measurement of a surrogate marker of neuronal activation (i.e., Arc mRNA) suggests the recent LTM deficits observed in Pde11 knockout mice correspond with decreased activation of ventral CA1 relative to wild-type littermates. In contrast, the enhanced remote LTM observed in Pde11a knockout mice corresponds with increased activation and altered functional connectivity of anterior cingulate cortex, frontal association cortex, parasubiculum, and the superficial layer of medial entorhinal cortex. The apparent increased neural activation observed in prefrontal cortex of Pde11a knockout mice during remote LTM retrieval may be related to an upregulation of the N-methyl-D-aspartate receptor subunits NR1 and NR2A. Viral restoration of PDE11A4 to vCA1 alone is sufficient to rescue both the LTM phenotypes and upregulation of NR1 exhibited by Pde11a knockout mice. Together, our findings suggest remote LTM can be decoupled from recent LTM, which may have relevance for cognitive deficits associated with aging, temporal lobe epilepsy, or transient global amnesia.

Both diet and Helicobacter pylori infection contribute to atherosclerosis in pre- and postmenopausal cynomolgus monkeys.

A number of viruses and bacterial species have been implicated as contributors to atherosclerosis, potentially providing novel pathways for prevention. Epidemiological studies examining the association between Helicobacter pylori and cardiovascular disease have yielded variable results and no studies have been conducted in nonhuman primates. In this investigation, we examined the relationship between H. pylori infection and atherosclerosis development in socially housed, pre- and postmenopausal cynomolgus macaques consuming human-like diets. Ninety-four premenopausal cynomolgus monkeys (Macaca fascicularis) were fed for 36 months an atherogenic diet deriving its protein from either casein lactalbumin(CL) or high isoflavone soy (SOY). Animals were then ovariectomized and fed either the same or the alternate diet for an additional 36 months. Iliac artery biopsies were obtained at the time of ovariectomy and iliac and coronary artery sections were examined at the end of the study. Evidence of H. pylori infection was found in 64% of the monkeys and 46% of animals had live H. pylori within coronary atheromas as determined by mRNA-specific in situ hybridization. There was a significant linear relationship between the densities of gastric and atheroma organisms. Helicobactor pylori infection correlated with increased intimal plaque area and thickness at both the premenopausal and postmenopausal time points and regardless of diet (p< 0.01), although animals consuming the SOY diet throughout had the least amount of atherosclerosis. Additionally, plasma lipid profiles, intimal collagen accumulation, ICAM-1, and plaque macrophage densities were adversely affected by H. pylori infection among animals consuming the CL diet, while the SOY diet had the opposite effect. Plaque measurements were more highly associated with the densities of cagA-positive H. pylori within coronary atheromas than with the densities of gastric organisms, whereas plasma lipid changes were associated with H. pylori infection, but not cagA status. This study provides strong evidence that live H. pylori infects atheromas, exacerbates atherosclerotic plaque development, and alters plasma lipid profiles independently of diet or hormonal status. Finally, socially subordinate animals relative to their dominant counterparts had a greater prevalence of H. pylori, suggesting a stress effect. The results indicate that early H. pylori eradication could prevent or delay development of cardiovascular disease.

American ginseng suppresses inflammation and DNA damage associated with mouse colitis.

Ulcerative colitis (UC) is a dynamic, idiopathic, chronic inflammatory condition associated with a high colon cancer risk. American ginseng has antioxidant properties and targets many of the players in inflammation. The aim of this study was to test whether American ginseng extract prevents and treats colitis. Colitis in mice was induced by the presence of 1% dextran sulfate sodium (DSS) in the drinking water or by 1% oxazolone rectally. American ginseng extract was mixed in the chow at levels consistent with that currently consumed by humans as a supplement (75 p.p.m., equivalent to 58 mg daily). To test prevention of colitis, American ginseng extract was given prior to colitis induction. To test treatment of colitis, American ginseng extract was given after the onset of colitis. In vitro studies were performed to examine mechanisms. Results indicate that American ginseng extract not only prevents but it also treats colitis. Inducible nitric oxide synthase and cyclooxygenase-2 (markers of inflammation) and p53 (induced by inflammatory stress) are also downregulated by American ginseng. Mucosal and DNA damage associated with colitis is at least in part a result of an oxidative burst from overactive leukocytes. We therefore tested the hypothesis that American ginseng extract can inhibit leukocyte activation and subsequent epithelial cell DNA damage in vitro and in vivo. Results are consistent with this hypothesis. The use of American ginseng extract represents a novel therapeutic approach for the prevention and treatment of UC.

Axonal G3BP1 stress granule protein limits axonal mRNA translation and nerve regeneration.

Critical functions of intra-axonally synthesized proteins are thought to depend on regulated recruitment of mRNA from storage depots in axons. Here we show that axotomy of mammalian neurons induces translation of stored axonal mRNAs via regulation of the stress granule protein G3BP1, to support regeneration of peripheral nerves. G3BP1 aggregates within peripheral nerve axons in stress granule-like structures that decrease during regeneration, with a commensurate increase in phosphorylated G3BP1. Colocalization of G3BP1 with axonal mRNAs is also correlated with the growth state of the neuron. Disrupting G3BP functions by overexpressing a dominant-negative protein activates intra-axonal mRNA translation, increases axon growth in cultured neurons, disassembles axonal stress granule-like structures, and accelerates rat nerve regeneration in vivo.

Semiparametric Inference for a General Class of Models for Recurrent Events.

Procedures for estimating the parameters of the general class of semiparametric models for recurrent events proposed by Peña and Hollander (2004) are developed. This class of models incorporates an effective age function encoding the effect of changes after each event occurrence such as the impact of an intervention, it models the impact of accumulating event occurrences on the unit, it admits a link function in which the effect of possibly time-dependent covariates are incorporated, and it allows the incorporation of unobservable frailty components which induce dependencies among the inter-event times for each unit. The estimation procedures are semiparametric in that a baseline hazard function is nonparametrically specified. The sampling distribution properties of the estimators are examined through a simulation study, and the consequences of mis-specifying the model are analyzed. The results indicate that the flexibility of this general class of models provides a safeguard for analyzing recurrent event data, even data possibly arising from a frailtyless mechanism. The estimation procedures are applied to real data sets arising in the biomedical and public health settings, as well as from reliability and engineering situations. In particular, the procedures are applied to a data set pertaining to times to recurrence of bladder cancer and the results of the analysis are compared to those obtained using three methods of analyzing recurrent event data.