SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

Modeling Techniques for the High-Resolution Interpretation of Cryo-Electron Microscopy Reconstructions

Essential biological processes are governed by organized, dynamic interactions between multiple biomolecular systems. Complexes are thus formed to enable the biological function and get dissembled as the process is completed. Examples of such processes include the translation of the messenger RNA into protein by the ribosome, the folding of proteins by chaperonins or the entry of viruses in host cells. Understanding these fundamental processes by characterizing the molecular mechanisms that enable then, would allow the (better) design of therapies and drugs. Such molecular mechanisms may be revealed trough the structural elucidation of the biomolecular assemblies at the core of these processes. Various experimental techniques may be applied to investigate the molecular architecture of biomolecular assemblies. High-resolution techniques, such as X-ray crystallography, may solve the atomic structure of the system, but are typically constrained to biomolecules of reduced flexibility and dimensions. In particular, X-ray crystallography requires the sample to form a three dimensional (3D) crystal lattice which is technically di‑cult, if not impossible, to obtain, especially for large, dynamic systems. Often these techniques solve the structure of the different constituent components within the assembly, but encounter difficulties when investigating the entire system. On the other hand, imaging techniques, such as cryo-electron microscopy (cryo-EM), are able to depict large systems in near-native environment, without requiring the formation of crystals. The structures solved by cryo-EM cover a wide range of resolutions, from very low level of detail where only the overall shape of the system is visible, to high-resolution that approach, but not yet reach, atomic level of detail. In this dissertation, several modeling methods are introduced to either integrate cryo-EM datasets with structural data from X-ray crystallography, or to directly interpret the cryo-EM reconstruction. Such computational techniques were developed with the goal of creating an atomic model for the cryo-EM data. The low-resolution reconstructions lack the level of detail to permit a direct atomic interpretation, i.e. one cannot reliably locate the atoms or amino-acid residues within the structure obtained by cryo-EM. Thereby one needs to consider additional information, for example, structural data from other sources such as X-ray crystallography, in order to enable such a high-resolution interpretation. Modeling techniques are thus developed to integrate the structural data from the different biophysical sources, examples including the work described in the manuscript I and II of this dissertation. At intermediate and high-resolution, cryo-EM reconstructions depict consistent 3D folds such as tubular features which in general correspond to alpha-helices. Such features can be annotated and later on used to build the atomic model of the system, see manuscript III as alternative. Three manuscripts are presented as part of the PhD dissertation, each introducing a computational technique that facilitates the interpretation of cryo-EM reconstructions. The first manuscript is an application paper that describes a heuristics to generate the atomic model for the protein envelope of the Rift Valley fever virus. The second manuscript introduces the evolutionary tabu search strategies to enable the integration of multiple component atomic structures with the cryo-EM map of their assembly. Finally, the third manuscript develops further the latter technique and apply it to annotate consistent 3D patterns in intermediate-resolution cryo-EM reconstructions. The first manuscript, titled An assembly model for Rift Valley fever virus, was submitted for publication in the Journal of Molecular Biology. The cryo-EM structure of the Rift Valley fever virus was previously solved at 27Å-resolution by Dr. Freiberg and collaborators. Such reconstruction shows the overall shape of the virus envelope, yet the reduced level of detail prevents the direct atomic interpretation. High-resolution structures are not yet available for the entire virus nor for the two different component glycoproteins that form its envelope. However, homology models may be generated for these glycoproteins based on similar structures that are available at atomic resolutions. The manuscript presents the steps required to identify an atomic model of the entire virus envelope, based on the low-resolution cryo-EM map of the envelope and the homology models of the two glycoproteins. Starting with the results of the exhaustive search to place the two glycoproteins, the model is built iterative by running multiple multi-body refinements to hierarchically generate models for the different regions of the envelope. The generated atomic model is supported by prior knowledge regarding virus biology and contains valuable information about the molecular architecture of the system. It provides the basis for further investigations seeking to reveal different processes in which the virus is involved such as assembly or fusion. The second manuscript was recently published in the of Journal of Structural Biology (doi:10.1016/j.jsb.2009.12.028) under the title Evolutionary tabu search strategies for the simultaneous registration of multiple atomic structures in cryo-EM reconstructions. This manuscript introduces the evolutionary tabu search strategies applied to enable a multi-body registration. This technique is a hybrid approach that combines a genetic algorithm with a tabu search strategy to promote the proper exploration of the high-dimensional search space. Similar to the Rift Valley fever virus, it is common that the structure of a large multi-component assembly is available at low-resolution from cryo-EM, while high-resolution structures are solved for the different components but lack for the entire system. Evolutionary tabu search strategies enable the building of an atomic model for the entire system by considering simultaneously the different components. Such registration indirectly introduces spatial constrains as all components need to be placed within the assembly, enabling the proper docked in the low-resolution map of the entire assembly. Along with the method description, the manuscript covers the validation, presenting the benefit of the technique in both synthetic and experimental test cases. Such approach successfully docked multiple components up to resolutions of 40Å. The third manuscript is entitled Evolutionary Bidirectional Expansion for the Annotation of Alpha Helices in Electron Cryo-Microscopy Reconstructions and was submitted for publication in the Journal of Structural Biology. The modeling approach described in this manuscript applies the evolutionary tabu search strategies in combination with the bidirectional expansion to annotate secondary structure elements in intermediate resolution cryo-EM reconstructions. In particular, secondary structure elements such as alpha helices show consistent patterns in cryo-EM data, and are visible as rod-like patterns of high density. The evolutionary tabu search strategy is applied to identify the placement of the different alpha helices, while the bidirectional expansion characterizes their length and curvature. The manuscript presents the validation of the approach at resolutions ranging between 6 and 14Å, a level of detail where alpha helices are visible. Up to resolution of 12 Å, the method measures sensitivities between 70-100% as estimated in experimental test cases, i.e. 70-100% of the alpha-helices were correctly predicted in an automatic manner in the experimental data. The three manuscripts presented in this PhD dissertation cover different computation methods for the integration and interpretation of cryo-EM reconstructions. The methods were developed in the molecular modeling software Sculptor (http://sculptor.biomachina.org) and are available for the scientific community interested in the multi-resolution modeling of cryo-EM data. The work spans a wide range of resolution covering multi-body refinement and registration at low-resolution along with annotation of consistent patterns at high-resolution. Such methods are essential for the modeling of cryo-EM data, and may be applied in other fields where similar spatial problems are encountered, such as medical imaging.

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

Three-dimensional structure of tropism-switching Bordetella bacteriophage.

Bacteriophage BPP-1, which infects Bordetella species, can switch its specificity by mutations to the ligand-binding surface of its major tropism-determinant protein, Mtd. This targeted mutagenesis results from the activity of a phage-encoded diversity-generating retroelement. Purified Mtd binds its receptor with low affinity, yet BPP-1 binding and infection of Bordettella cells are efficient because of high-avidity binding between phage-associated Mtd and its receptor. Here, using an integrative approach of three-dimensional (3D) structural analyses of the entire phage by cryo-electron tomography and single-prticle cryo-electron microscopy, we provide direct localization of Mtd in the phage and the structural basis of the high-avidity binding of the BPP-1 phage. Our structure shows that each BPP-1 particle has a T = 7 icosahedral head and an unusual tail apparatus consisting of a short central tail "hub," six short tail spikes, and six extended tail fibers. Subtomographic averaging of the tail fiber maps revealed a two-lobed globular structure at the distal end of each long tail fiber. Tomographic reconstructions of immuno-gold-labeled BPP-1 directly localized Mtd to these globular structures. Finally, our icosahedral reconstruction of the BPP-1 head at 7A resolution reveals an HK97-like major capsid protein stabilized by a smaller cementing protein. Our structure represents a unique bacteriophage reconstruction with its tail fibers and ligand-binding domains shown in relation to its tail apparatus. The localization of Mtd at the distal ends of the six tail fibers explains the high avidity binding of Mtd molecules to cell surfaces for initiation of infection.

The Role of Acidic Fibroblast Growth Factor and Fibroblast Growth Factor Receptor 4 in High Grade Serous Carcinoma

Background: High grade serous carcinoma whether ovarian, tubal or primary peritoneal, continues to be the most lethal gynecologic malignancy in the USA. Although combination chemotherapy and aggressive surgical resection has improved survival in the past decade the majority of patients still succumb to chemo-resistant disease recurrence. It has recently been reported that amplification of 5q31-5q35.3 is associated with poor prognosis in patients with high grade serous ovarian carcinoma. Although the amplicon contains over 50 genes, it is notable for the presence of several members of the fibroblast growth factor signaling axis. In particular acidic fibroblast growth factor (FGF1) has been demonstrated to be one of the driving genes in mediating the observed prognostic effect of the amplicon in ovarian cancer patients. This study seeks to further validate the prognostic value of fibroblast growth receptor 4 (FGFR4), another candidate gene of the FGF/FGFR axis located in the same amplicon. The emphasis will be delineating the role the FGF1/FGFR4 signaling axis plays in high grade serous ovarian carcinoma; and test the feasibility of targeting the FGF1/FGFR4 axis therapeutically. Materials and Methods: Spearman and Pearson correlation studies on data generated from array CGH and transcriptome profiling analyses on 51 microdissected tumor samples were used to identify genes located on chromosome 5q31-35.3 that showed significant correlation between DNA and mRNA copy numbers. Significant correlation between FGF1 and FGFR4 DNA copy numbers was further validated by qPCR analysis on DNA isolated from 51 microdissected tumor samples. Immunolocalization and quantification of FGFR4 expression were performed on paraffin embedded tissue samples from 183 cases of high-grade serous ovarian carcinoma. The expression was then correlated with clinical data to assess impact on survival. The expression of FGF1 and FGFR4 in vitro was quantified by real-time PCR and western blotting in six high-grade serous ovarian carcinoma cell lines and compared to those in human ovarian surface epithelial cells to identify overexpression. The effect of FGF1 on these cell lines after serum starvation was quantified for in vitro cellular proliferation, migration/invasion, chemoresistance and survival utilizing a combination of commercially available colorimetric, fluorometric and electrical impedance assays. FGFR4 expression was then transiently silenced via siRNA transfection and the effects on response to FGF1, cellular proliferation, and migration were quantified. To identify relevant cellular pathways involved, responsive cell lines were transduced with different transcription response elements using the Cignal-Lenti reporter system and treated with FGF1 with and without transient FGFR4 knock down. This was followed by western blot confirmation for the relevant phosphoproteins. Anti-FGF1 antibodies and FGFR trap proteins were used to attempt inhibition of FGF mediated phenotypic changes and relevant signaling in vitro. Orthotopic intraperitoneal tumors were established in nude mice using serous cell lines that have been previously transfected with luciferase expressing constructs. The mice were then treated with FGFR trap protein. Tumor progression was then followed via bioluminescent imaging. The FGFR4 gene from 52 clinical samples was sequenced to screen for mutations. Results: FGFR4 DNA and mRNA copy numbers were significantly correlated and FGFR4 DNA copy number was significantly correlated with that of FGF1. Survival of patients with high FGFR4 expressing tumors was significantly shorter that those with low expression(median survival 28 vs 55 month p< 0.001) In a multivariate cox regression model FGFR expression significantly increased risk of death (HR 2.1, p<0.001). FGFR4 expression was significantly higher in all cell lines tested compared to HOSE, OVCA432 cell line in particular had very high expression suggesting amplification. FGF1 was also particularly overexpressed in OVCA432. FGF1 significantly increased cell survival after serum deprivation in all cell lines. Transient knock down of FGFR4 caused significant reduction in cell migration and proliferation in vitro and significantly decreased the proliferative effects of FGF1 in vitro. FGFR1, FGFR4 traps and anti-FGF1 antibodies did not show activity in vitro. OVCA432 transfected with the cignal lenti reporter system revealed significant activation of MAPK, NFkB and WNT pathways, western blotting confirmed the results. Reverse phase protein array (RPPA) analysis also showed activation of MAPK, AKT, WNT pathways and down regulation of E Cadherin. FGFR trap protein significantly reduced tumor growth in vivo in an orthotopic mouse model. Conclusions: Overexpression and amplification of several members of the FGF signaling axis present on the amplicon 5q31-35.3 is a negative prognostic indicator in high grade serous ovarian carcinoma and may drive poor survival associated with that amplicon. Activation of The FGF signaling pathway leads to downstream activation of MAPK, AKT, WNT and NFkB pathways leading to a more aggressive cancer phenotype with increased tumor growth, evasion of apoptosis and increased migration and invasion. Inhibition of FGF pathway in vivo via FGFR trap protein leads to significantly decreased tumor growth in an orthotopic mouse model.

A Multi-Dimensional Approach to Evaluating Family Preservation Programs

The current study evaluates the effectiveness of family preservation programs funded by the Mississippi Department of Human Services. This venture encompassed scrutiny and assessment of improvements in child functioning, positive changes in parental functioning and family functioning and the decrease in foster care placement. Further, this evaluation assessed client and staff satisfaction. It also included an assessment of the perceived impact this program had on the community. Results indicate that the family preservation programs were effective in improving the self-esteem of participants, family cohesion, and adaptability. There were no significant changes in child placement, teen births, or abuse rates. Client and staff satisfaction were high on all quality dimensions. The majority of the sample of community members felt that the family preservation programs were effective in the community.

Back pain in migrant farmworker families and farmworker high school students from Starr County, Texas

Back symptoms are a major global public health problem with the lifetime prevalence ranging between 50-80%. Research suggests that work-related factors contribute to the occurrence of back pain in various industries. Despite the hazardous nature, strenuous tasks, and awkward postures associated with farm work, little is known about back injury and symptoms in farmworker adults and children. Research in the United States is particularly limited. This is a concern given the large proportion of migrant farmworkers in the United States without adequate access to healthcare as well as a substantial number of youth working in agriculture. The present study describes back symptoms and identifies work-related factors associated with back pain in migrant farmworker families and farmworker high school students from Starr County, TX. Two separate datasets were used from two cohort studies "Injury and Illness Surveillance in Migrant Farmworkers (MANOS)" (study A: n=267 families) and "South Texas Adolescent Rural Research Study (STARRS)" (study B: n=345). Descriptive and inferential statistics including multivariable logistic regression were used to identify work-related factors associated with back pain in each study. In migrant farmworker families, the prevalence of chronic back pain during the last migration season ranged from 9.5% among youngest children to 33.3% among mothers. Chronic back pain was significantly associated with increasing age; fairly bad/very bad quality of sleep while migrating; fewer than eight hours of sleep at home in Starr County, TX; depressive symptoms while migrating; self-provided water for washing hands/drinking; weeding at work; and exposure to pesticide drift/direct spray. Among farmworker adolescents, the prevalence of severe back symptoms was 15.7%. Severe back symptoms were significantly associated with being female; history of a prior accident/back injury; feeling tense, stressed, or anxious sometimes/often; lifting/carrying heavy objects not at work; current tobacco use; increasing lifetime number of migrant farmworker years; working with/around knives; and working on corn crops. Overall, results support that associations between work-related exposures and chronic back pain and severe back symptoms remain after controlling for the effect of non-work exposures in farmworker populations. ^

Evaluation of the city of Houston HIV/STD prevention program in Houston Independent School District (HISD) high schools

This cross-sectional study was undertaken to evaluate the impact in terms of HIV/STD knowledge and sexual behavior that the City of Houston HIV/STD prevention program in HISD high schools has had on students who have participated in it by comparing them with their peers who have not, based on self reports. The study further evaluated the program cost-effectiveness for averting future HIV infections by computing Cost-Utility Ratios based on reported sexual behavior. ^ Mixed results were obtained, indicating a statistically significant difference in knowledge with the intervention group having scored higher (p-value 0.001) but not for any of the behaviors assessed. The knowledge score outcome's overall p-value after adjusting for each stratifying variable (age, grade, gender and ethnicity) was statistically significant. The Odds Ratio of intervention group participants aged 15 years or more scoring 70% or higher was 1.86 times; that of intervention group female participants was 2.29 times; and that of intervention group Black/African American participants was 2.47 times relative to their comparison group counterparts. The knowledge score results remained statistically significant in the logistic regression model, which controlled for age, grade level, gender and ethnicity. The Odds Ratio in this case was 1.74. ^ Three scenarios based on the difference in the risk of HIV infection between the intervention and comparison group were used for computation of Cost-Utility Ratios: Base, worst and best-case scenario. The best-case scenario yielded cost-effective results for male participants and cost-saving results for female participants when using ethnicity-adjusted HIV prevalence. The scenario remained cost-effective for female participants when using the unadjusted HIV prevalence. ^ The challenge to the program is to devise approaches that can enhance benefits for male participants. If it is a threshold problem implying that male participants require more intensive programs for behavioral change, then programs should first be piloted among boys before being implemented across the board. If it is a reflection of gender differences, then we might have to go back to the drawing board and engage boys in focus group discussions that will help formulate more effective programs. Gender-blind approaches currently in vogue do not seem to be working. ^

The role of self-efficacy in a low fat high fiber intervention to reduce breast cancer risk among African American women

Purpose. To determine if self-efficacy (SE) changes predicted total fat (TF) and total fiber (TFB) intake and the relationship between SE changes and the two dietary outcomes. ^ Design. This is a secondary analysis, utilizing baseline and first follow up (FFU) data from the NULIFE, a randomized trial. ^ Setting. Nutrition classes were taught in the Texas Medical Center in Houston, Texas. ^ Participants. 79 pre-menopausal, 25--45 year old African American women with an 85% response rate at FFU. ^ Method. Dietary intake was assessed with the Arizona Food Frequency Questionnaire and SE with the Self Efficacy for Dietary Change Questionnaire. Analysis was done using Stata version 9. Linear and logistic regression was used with adjustment for confounders. ^ Results. Linear regression analyses showed that SE changes for eating fruits and vegetables predicted total fiber intake in the control group for both the univariate (P = 0.001) and multivariate (P = 0.01) models while SE for eating fruits and vegetables at first follow-up predicted total fiber intake in the intervention for both models (P = 0.000). Logistic regression analyses of low fat SE changes and 30% or less for total fat intake, showed an adjusted OR of 0.22 (95% CI = 0.03, 1.48; P = 0.12) in the intervention group. The logistic regression analyses of SE changes in fruits and vegetables and 10g or more for total fiber intake, showed an adjusted OR of 6.25 (95% CI = 0.53, 72.78; P = 0.14) in the control group. ^ Conclusion. SE for eating fruits and vegetables at first follow-up predicted intervention groups' TFB intake and intervention women that increased their SE for eating a low fat diet were more likely to achieve the study goal of 30% or less calories from TF. SE changes for eating fruits and vegetables predicted the control's TFB intake and control women that increased their SE for eating fruits and vegetables were more likely to achieve the study goal of 10 g or more from TFB. Limitations are use of self-report measures, small sample size, and possible control group contamination.^

Locus of control as a predictor of students dropping out of high school

Education is related to health. In cross-sectional data, education level has been associated with physical functioning. Also, lower levels of education have been associated with health behaviors including smoking, alcohol use, and greater body weight. In school, students may benefit from greater exposed to health-related messages, while students who have dropped out may be more susceptible to influences regarding negative health behaviors such as smoking. ^ Improved school retention might improve long-term health outcomes. However, there is limited evidence regarding modifiable factors that predict likelihood of dropping out. Two likely psychosocial measures are locus of control and parent-child academic conversations. In the current study, data from two waves of a population-based longitudinal survey, the National Education Longitudinal Survey, were utilized to evaluate whether these two psychosocial measures could predict likelihood of dropping out, for students (n = 16,749) in tenth grade at 1990, with dropout status determined at 1992, while controlling for recognized sociodemographic predictors including parental income, parental education level, race/ethnicity, and sex. Locus of control was measured with the Pearlin Mastery Scale, and parent-child academic conversations were measured by three questions concerning course selection at school, school activities and events, and things the student studied in class. ^ In a logistic regression model, with the sociodemographic control measures entered in a first step before entry of the psychosocial measures in a second step, this study determined that lower levels of locus of control were associated with greater likelihood of dropping out after two years (odds ratio (OR) = 1.11, 95% confidence interval (CI) 108 to 1.15, p < .001), and two of the three parent-child academic discussion items were associated with greater likelihood of dropping out after two years (OR = 1.69, CI 1.48-1.93, p < .001; OR = 1.22, CI 1.05-1.41, p = .01; OR = 1.01, CI .88-1.15, p = .94). ^ It is possible that interventions aimed at improving locus of control, and aimed at building parent-child academic conversations, could lower the likelihood of students dropping out, and this in turn could yield improved heath behaviors and health status in the child's future. ^

Prevalence of depressive symptoms in urban middle and high school Hispanic and African American students

This cross-sectional study examined the prevalence of depressive symptoms in urban Hispanic and African American middle and high school students (N=1,292) using data collected from a multi-component, multi-wave violence and substance use intervention program targeted at a large urban school district in Texas. Chi-square analysis was used to examine differences in race/ethnicity, gender, grade level and whether or not a student had been held back/repeated a grade in school. Univariate and multivariate logistic regression were used to analyze the association between depressive symptoms and demographic variables. Being female and being held back/repeating a grade was significantly associated with depressive symptoms in both univariate and multivariate analyses. Overall 16% of the students reported depressive symptoms; Hispanic youth had a higher prevalence of depressive symptoms (16.8%) than the African American youth (14.8%). Minority females and those who had been held back/repeated a grade reported a prevalence of 19.4% and 21.2%, respectively. Further research is needed to understand why Hispanic youth continue to report a higher prevalence of depressive symptoms than other minorities. Additionally research is required to further explore the association between academic performance and depressive symptoms in urban minorities, specifically the effect of being held back/repeating a grade.^

High-risk drug use and sexual behaviors among out-of-treatment drug users: An aging and life course perspective

High-risk injection drug use and the sexual behaviors that accompany it have large social and financial costs. Tailored treatments have been shown to successfully reduce high-risk behaviors. However, little is known about how age and age at first drug use are related to high-risk injection or sex behaviors. The current study draws on life course theory and hypothesizes that age will have a strong relationship with high-risk behaviors of out-of-treatment drug users. Data from the NIDA Cooperative Agreement was used to analyze the relationship between (1) age, and (2) age at first drug use with seven high-risk injection and sexual behavior variables. Negative binomial regression models revealed that high-risk sexual behavior decreases between 15.8 and 20.9% with each decade of age, while high-risk injection behavior increases between 32 and 67% with each decade of age after the addition of demographic controls. Both high-risk injection and high-risk sex behaviors are significantly reduced with a delayed age at first drug use. Previous research promotes interventions to reduce the high-risk sexual behaviors of older drug users. The current study suggests a refocusing of public health efforts on the high-risk injection habits of older drug users.^

An ordinal logistic regression model with misclassification of the outcome variable and categorical covariate

Ordinal outcomes are frequently employed in diagnosis and clinical trials. Clinical trials of Alzheimer's disease (AD) treatments are a case in point using the status of mild, moderate or severe disease as outcome measures. As in many other outcome oriented studies, the disease status may be misclassified. This study estimates the extent of misclassification in an ordinal outcome such as disease status. Also, this study estimates the extent of misclassification of a predictor variable such as genotype status. An ordinal logistic regression model is commonly used to model the relationship between disease status, the effect of treatment, and other predictive factors. A simulation study was done. First, data based on a set of hypothetical parameters and hypothetical rates of misclassification was created. Next, the maximum likelihood method was employed to generate likelihood equations accounting for misclassification. The Nelder-Mead Simplex method was used to solve for the misclassification and model parameters. Finally, this method was applied to an AD dataset to detect the amount of misclassification present. The estimates of the ordinal regression model parameters were close to the hypothetical parameters. β1 was hypothesized at 0.50 and the mean estimate was 0.488, β2 was hypothesized at 0.04 and the mean of the estimates was 0.04. Although the estimates for the rates of misclassification of X1 were not as close as β1 and β2, they validate this method. X 1 0-1 misclassification was hypothesized as 2.98% and the mean of the simulated estimates was 1.54% and, in the best case, the misclassification of k from high to medium was hypothesized at 4.87% and had a sample mean of 3.62%. In the AD dataset, the estimate for the odds ratio of X 1 of having both copies of the APOE 4 allele changed from an estimate of 1.377 to an estimate 1.418, demonstrating that the estimates of the odds ratio changed when the analysis includes adjustment for misclassification. ^

Sleep quality and quantity and associated factors among high school students from south Texas

Background. Insufficient and poor quality sleep among adolescents affects not only the cognitive functioning, but overall health of the individual. Existing research suggests that adolescents from varying ethnic groups exhibit differing sleep patterns. However, little research focuses on sleep patterns and associated factors (i.e. tobacco use, mental health indicators) among Hispanic youth. ^ Methods. The study population (n=2,536) included students in grades 9-12 who attended one of the three public high schools along the Texas-Mexico border in 2003. This was a cross sectional study using secondary data collected via a web-based, confidential, self-administered survey. Separate logistic regression models were estimated to identify factors associated with reduced (<9 hours/night) and poor quality sleep on average during weeknights. ^ Results. Of participants, 49.5% reported reduced sleep while 12.8% reported poor quality sleep. Factors significantly (p<0.05) associated with poor quality sleep were: often feeling stressed or anxious (OR=5.49), being born in Mexico (OR=0.65), using a computer/playing video games 15+ hours per week (OR=2.29), working (OR=1.37), being a current smoker (OR=2.16), and being a current alcohol user (OR=1.64). Factors significantly associated with reduced quantity of sleep were: often feeling stressed or anxious (OR=2.74), often having headaches/stomachaches (OR=1.77), being a current marijuana user (OR=1.70), being a current methamphetamine user (OR=4.92), and being a current alcohol user (OR=1.27). ^ Discussion. Previous research suggests that there are several factors that can influence sleep quality and quantity in adolescents. This paper discusses these factors (i.e. work, smoking, alcohol, etc.) found to be associated with poor sleep quality and reduced sleep quantity in the Hispanic adolescent population. A reduced quantity of sleep (81.20% of the participants) and a poor quality of sleep (12.80% of the participants) were also found in high school students from South Texas. ^

Secondary data analysis of lead screening compliance in high-risk children

Introduction. Despite the ban of lead-containing gasoline and paint, childhood lead poisoning remains a public health issue. Furthermore, a Medicaid-eligible child is 8 times more likely to have an elevated blood lead level (EBLL) than a non-Medicaid child, which is the primary reason for the early detection lead screening mandate for ages 12 and 24 months among the Medicaid population. Based on field observations, there was evidence that suggested a screening compliance issue. Objective. The purpose of this study was to analyze blood lead screening compliance in previously lead poisoned Medicaid children and test for an association between timely lead screening and timely childhood immunizations. The mean months between follow-up tests were also examined for a significant difference between the non-compliant and compliant lead screened children. Methods. Access to the surveillance data of all childhood lead poisoned cases in Bexar County was granted by the San Antonio Metropolitan Health District. A database was constructed and analyzed using descriptive statistics, logistic regression methods and non-parametric tests. Lead screening at 12 months of age was analyzed separately from lead screening at 24 months. The small portion of the population who were also related were included in one analysis and removed from a second analysis to check for significance. Gender, ethnicity, age of home, and having a sibling with an EBLL were ruled out as confounders for the association tests but ethnicity and age of home were adjusted in the nonparametric tests. Results. There was a strong significant association between lead screening compliance at 12 months and childhood immunization compliance, with or without including related children (p<0.00). However, there was no significant association between the two variables at the age of 24 months. Furthermore, there was no significant difference between the median of the mean months of follow-up blood tests among the non-compliant and compliant lead screened population for at the 12 month screening group but there was a significant difference at the 24 month screening group (p<0.01). Discussion. Descriptive statistics showed that 61% and 56% of the previously lead poisoned Medicaid population did not receive their 12 and 24 month mandated lead screening on time, respectively. This suggests that their elevated blood lead level may have been diagnosed earlier in their childhood. Furthermore, a child who is compliant with their lead screening at 12 months of age is 2.36 times more likely to also receive their childhood immunizations on time compared to a child who was not compliant with their 12 month screening. Even though there was no statistical significant association found for the 24 month group, the public health significance of a screening compliance issue is no less important. The Texas Medicaid program needs to enforce lead screening compliance because it is evident that there has been no monitoring system in place. Further recommendations include a need for an increased focus on parental education and the importance of taking their children for wellness exams on time.^