Naisyin Wang

Chemopreventive n-3 Polyunsaturated Fatty Acids Reprogram Genetic Signatures during Colon Cancer Initiation and Progression in the Rat

The mechanisms by which n-3 polyunsaturated fatty acids (PUFAs) decrease colon tumor formation have not been fully elucidated. Examination of genes up- or down-regulated at various stages of tumor development via the monitoring of gene expression relationships will help to determine the biological processes ultimately responsible for the protective effects of n-3 PUFA. Therefore, using a 3 × 2 × 2 factorial design, we used Codelink DNA microarrays containing ∼9000 genes to help decipher the global changes in colonocyte gene expression profiles in carcinogen-injected Sprague Dawley rats. Animals were assigned to three dietary treatments differing only in the type of fat (corn oil/n-6 PUFA, fish oil/n-3 PUFA, or olive oil/n-9 monounsaturated fatty acid), two treatments (injection with the carcinogen azoxymethane or with saline), and two time points (12 hours and 10 weeks after first injection). Only the consumption of n-3 PUFA exerted a protective effect at the initiation (DNA adduct formation) and promotional (aberrant crypt foci) stages. Importantly, microarray analysis of colonocyte gene expression profiles discerned fundamental differences among animals treated with n-3 PUFA at both the 12 hours and 10-week time points. Thus, in addition to demonstrating that dietary fat composition alters the molecular portrait of gene expression profiles in the colonic epithelium at both the initiation and promotional stages of tumor development, these findings indicate that the chemopreventive effect of fish oil is due to the direct action of n-3 PUFA and not to a reduction in the content of n-6 PUFA.

Bias Analysis and SIMEX Approach in Generalized Linear Mixed Measurement Error Models

Abstract We consider generalized linear mixed models (GLMMs) for clustered data when one of the predictors is measured with error. When the measurement error is additive and normally distributed and the error-prone predictor is itself normally distributed, we show that the observed data also follow a GLMM but with a different fixed effects structure from the original model, a different and more complex random effects structure, and restrictions on the parameters. This characterization enables us to compute the biases that result in common GLMMs when one ignores measurement error. For instance, in one common situation the biases in parameter estimates become larger as the number of observations within a cluster increases, both for regression coefficients and for variance components. Parameter estimation is described using the SIMEX method, a relatively new functional method that makes no assumptions about the structure of the unobservable predictors. Simulations and an example illustrate the results.

n-3 Polyunsaturated fatty acids modulate carcinogen-directed non-coding microRNA signatures in rat colon

We have hypothesized that dietary modulation of intestinal non-coding RNA [microRNA (miRNA)] expression may contribute to the chemoprotective effects of nutritional bioactives (fish oil and pectin). To fully understand the effects of these agents on the expression of miRNAs, Sprague-Dawley rats were fed diets containing corn oil or fish oil with pectin or cellulose and injected with azoxymethane (AOM, a colon-specific carcinogen) or saline (control). Real-time polymerase chain reaction using miRNA-specific primers and Taq Man probes was carried out to quantify effects on miRNA expression in colonic mucosa. From 368 mature miRNAs assayed, at an early stage of cancer progression (10 week post AOM injection), let-7d, miR-15b, miR-107, miR-191 and miR-324-5p were significantly (P < 0.05) affected by diet x carcinogen interactions. Overall, fish oil fed animals exhibited the smallest number of differentially expressed miRNAs (AOM versus saline treatment). With respect to the tumor stage (34 week post AOM injection), 46 miRNAs were dysregulated in adenocarcinomas compared with normal mucosa from saline-injected animals. Of the 27 miRNAs expressed at higher (P < 0.05) levels in tumors, miR-34a, 132, 223 and 224 were overexpressed at >10-fold. In contrast, the expression levels of miR-192, 194, 215 and 375 were dramatically reduced (< or = 0.32-fold) in adenocarcinomas. These results demonstrate for the first time the utility of the rat AOM model and the novel role of fish oil in protecting the colon from carcinogen-induced miRNA dysregulation.

Efficient Semiparametric Marginal Estimation for Longitudinal/Clustered Data

We consider marginal generalized semiparametric partially linear models for clustered data. Lin and Carroll derived the semiparametric efficient score function for this problem in the multivariate Gaussian case, but they were unable to construct a semiparametric efficient estimator that actually achieved the semiparametric information bound. Here we propose such an estimator and generalize the work to marginal generalized partially linear models. We investigate asymptotic relative efficiencies of the estimators that ignore the within-cluster correlation structure either in nonparametric curve estimation or throughout. We evaluate the finite-sample performance of these estimators through simulations and illustrate it using a longitudinal CD4 cell count dataset. Both theoretical and numerical results indicate that properly taking into account the within-subject correlation among the responses can substantially improve efficiency.

Ozone Exposure and Population Density in Harris County, Texas

Abstract We address the following question: What is the pattern of human exposure to ozone in Harris County (Houston) since 1980? While there has been considerable research on characterizing ozone measured at fixed monitoring stations, little is known about ozone away from the monitoring stations, and whether areas of higher ozone correspond to areas of high population density. To address this question, we build a spatial-temporal model for hourly ozone levels that predicts ozone at any location in Harris County at any time between 1980 and 1993. Along with building the model, we develop a fast model-fitting method that can cope with the massive amounts of available data and takes into account the substantial number of missing observations. Having built the model, we combine it with census tract information, focusing on young children. We conclude that the highest ozone levels occur at locations with relatively small populations of young children. Using various measures of exposure, we estimate that expos...

Regulatory activity of polyunsaturated fatty acids in T-cell signaling.

n-3 Polyunsaturated fatty acids (PUFA) are considered to be authentic immunosuppressors and appear to exert beneficial effects with respect to certain immune-mediated diseases. In addition to promoting T-helper 1 (Th1) cell to T-helper 2 (Th2) cell effector T-cell differentiation, n-3 PUFA may also exert anti-inflammatory actions by inducing apoptosis in Th1 cells. With respect to mechanisms of action, effects range from the modulation of membrane receptors to gene transcription via perturbation of a number of second messenger cascades. In this review, the putative targets of anti-inflammatory n-3 PUFA, activated during early and late events of T-cell activation will be discussed. Studies have demonstrated that these fatty acids alter plasma membrane micro-organization (lipid rafts) at the immunological synapse, the site where T-cells and antigen-presenting cells (APC) form a physical contact for antigen initiated T-cell signaling. In addition, the production of diacylglycerol and the activation of different isoforms of protein kinase C (PKC), mitogen-activated protein kinase (MAPK), calcium signaling, and nuclear translocation/activation of transcriptional factors, can be modulated by n-3 PUFA. Advantages and limitations of diverse methodologies to study the membrane lipid raft hypothesis, as well as apparent contradictions regarding the effect of n-3 PUFA on lipid rafts will be critically presented.

Apigenin and naringenin suppress colon carcinogenesis through the aberrant crypt stage in azoxymethane-treated rats

Epidemiological evidence suggests that a diet abundant in fruits and vegetables may protect against colon cancer. Bioactive compounds, including flavonoids and limonoids, have been shown to possess antiproliferative and antitumorigenic effects in various cancer models. This experiment investigated the effects of four citrus flavonoids and one limonoid mixture at the promotion stage of chemically induced colon cancer in rats. Male Sprague–Dawley rats (n = 10 rats/group) were randomly allocated to one of six diets formulated to contain 0.1% apigenin, 0.02% naringenin, 0.1% hesperidin, 0.01% nobiletin, 0.035% limonin glucoside/obacunone glucoside mixture or a control diet (0% flavonoid/limonoid). Rats received experimental diets for 10 weeks and were injected with azoxymethane (15 mg/kg) at weeks 3 and 4. Excised colons were evaluated for aberrant crypt foci (ACF) formation, colonocyte proliferation (proliferating cell nuclear antigen assay), apoptosis (terminal deoxynucleotidyl transferase dUTP nick end labeling assay) and expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) (immunoblotting). When compared with the control diet, apigenin lowered the number of high multiplicity ACF (HMACF >4 aberrant crypts/focus) by 57% (P < 0.05), while naringenin lowered both the number of HMACF by 51% (P < 0.05) and the proliferative index by 32% (P < 0.05). Both apigenin and naringenin increased apoptosis of luminal surface colonocytes (78% and 97%, respectively; P < 0.05) when compared with the control diet. Hesperidin, nobiletin and the limonin glucoside/obacunone glucoside mixture did not affect these variables. The colonic mucosal protein levels of iNOS or COX-2 were not different among the six diet groups. The ability of dietary apigenin and naringenin to reduce HMACF, lower proliferation (naringenin only) and increase apoptosis may contribute toward colon cancer prevention. However, these effects were not due to mitigation of iNOS and COX-2 protein levels at the ACF stage of colon cancer.

Morphodensitometric analysis of protein kinase C βII expression in rat colon: modulation by diet and relation to in situ cell proliferation and apoptosis

We have recently demonstrated that overexpression of PKC beta(II) renders transgenic mice more susceptible to carcinogen-induced colonic hyperproliferation and aberrant crypt foci formation. In order to further investigate the ability of PKC beta(II) to modulate colonocyte cytokinetics, we determined the localization of PKC beta(II) with respect to cell proliferation and apoptosis along the entire colonic crypt axis following carcinogen and diet manipulation. Rats were provided diets containing either corn oil [containing n-6 polyunsaturated fatty acids (PUFA)] or fish oil (containing n-3 PUFA), cellulose (non-fermentable fiber) or pectin (fermentable fiber) and injected with azoxymethane (AOM) or saline. After 16 weeks, an intermediate time point when no macroscopic tumors are detected, colonic sections were utilized for immunohistochemical image analysis and immunoblotting. Cell proliferation was measured by incorporation of bromodeoxyuridine into DNA and apoptosis by terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end-labeling. In the distal colon, PKC beta(II) staining was localized to the upper portion of the crypt. In comparison, proximal crypts had more (P < 0.05) staining in the lower tertile. AOM enhanced (P < 0.05) PKC beta(II) expression in all regions of the distal colonic crypt (upper, middle and lower tertiles). There was also an interaction (P < 0.05) between dietary fat and fiber on PKC beta(II) expression (corn/pectin > fish/cellulose, fish/pectin > corn/cellulose) in all regions of the distal colonic crypt. With respect to colonic cell kinetics, proliferation paralleled the increase in PKC beta(II) expression in carcinogen-treated animals. In contrast, apoptosis at the lumenal surface was inversely proportional to PKC beta(II) expression in the upper tertile. These results suggest that an elevation in PKC beta(II) expression along the crypt axis in the distal colon is linked to enhancement of cell proliferation and suppression of apoptosis, predictive intermediate biomarkers of tumor development. Therefore, select dietary factors may confer protection against colon carcinogenesis in part by blocking carcinogen-induced PKC beta(II) expression.

Generalized Functional Linear Models with Semiparametric Single-Index Interactions

We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two-step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are predetermined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical dataset where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.

Nearest-Neighbor Variance Estimation (NNVE): Robust Covariance Estimation via Nearest-Neighbor Cleaning

Robust covariance estimation commonly proceeds by downweighting outliers. In this article we measure the “outlyingness” of a data point by the standardized distance between the point and its Kth nearest neighbor. The appropriate weights for robust estimation are found by a model-based mixture modeling approach that follows from considering the data cloud as a realization of a high-dimensional point process. To correct a potential bias when there are no outliers, we introduce a boundary correction procedure that artificially adds in extra outlying points; the resulting methodology is called nearest-neighbor variance estimation (NNVE). The strength of NNVE is its robustness against a large proportion of noise points and against deviation from normality of the signal. A consistency result for the method is established. Under some reasonable assumptions, it is shown that the covariance estimate is bounded and that each point has only bounded influence on the final estimates. NNVE outperformed the popular minimum volume ellipsoid (MVE) estimator in simulation studies, with a big improvement when the proportion of outliers was very large (> 50%). In our simulation study, when the proportion of outliers was ≥ 50%, the mean squared error of the NNVE estimator of variance was at least 100 times smaller than that of the MVE estimator. The proposed estimator also outperformed MVE in cases where the underlying data distribution was not normal. Good performance of NNVE in several real examples is demonstrated. A potential drawback of NNVE is that data points condensed in moderate-sized clusters would be classified as signal. Even though we do not support approaches discarding moderate-sized clusters as outliers without checking, this feature of NNVE could be problematic, particularly when only the main data cloud is of interest. A simple diagnostic tool built on existing model-based clustering procedure is proposed. This procedure allows us to check whether there is more than one separate data cloud in the data after cleaning. It also supplies the central locations of the separated moderate-sized clusters, which allows further investigation. Finally, because NNVE reduces the problem of finding the robustness weights to a one-dimensional problem, it may be useful in high-dimensional problems, such as those encountered in data mining.