An R-package for the Estimation and Testing of Multiple Covariates and Biomarker Interactions for Survival Data Based on Local Partial Likelihood

When we study the variables that a ffect survival time, we usually estimate their eff ects by the Cox regression model. In biomedical research, e ffects of the covariates are often modi ed by a biomarker variable. This leads to covariates-biomarker interactions. Here biomarker is an objective measurement of the patient characteristics at baseline. Liu et al. (2015) has built up a local partial likelihood bootstrap model to estimate and test this interaction e ffect of covariates and biomarker, but the R code developed by Liu et al. (2015) can only handle one variable and one interaction term and can not t the model with adjustment to nuisance variables. In this project, we expand the model to allow adjustment to nuisance variables, expand the R code to take any chosen interaction terms, and we set up many parameters for users to customize their research. We also build up an R package called "lplb" to integrate the complex computations into a simple interface. We conduct numerical simulation to show that the new method has excellent fi nite sample properties under both the null and alternative hypothesis. We also applied the method to analyze data from a prostate cancer clinical trial with acid phosphatase (AP) biomarker.

Bullying Involvement and Adolescent Substance Use: A Study of Multilevel Risk and Protective Factors

Bullying, frequent drunkenness, and frequent cannabis use are significant health-risk behaviours among youth. While many studies have demonstrated that bullying involvement may initiate a developmental pathway to both types of frequent substance use, there is a limited understanding of the connection between these behaviours. The presence of risk and protective factors within youths’ relationships and within their neighbourhoods may alter the associations between bullying involvement and both types of frequent substance use. A systemic approach is needed to assess the complex, social environments in which youth are embedded. The current thesis consists of two studies that examined the associations between bullying and both types of frequent substance use within the context of youths’ social environments. In Study 1, multilevel modeling was used to examine the associations between bullying and frequent substance use within the context of individual and neighbourhood risk factors. Our results indicated that the risk factors associated with both frequent drunkenness and frequent cannabis use exist at both levels, with neighbourhoods altering the association of individual risk factors. Moreover, bullying was a unique risk factor associated with both types of frequent substance use, whereas indirect associations were observed for victimization. Study 2 used a similar methodology to examine the association between bullying and both types of frequent substance use within the context of individual and neighbourhood protective factors. Once again, our results indicated that the protective factors associated with both types of frequent substance use exist at multiple levels, and that neighbourhoods altered the association of individual protective factors. Additionally, positive relationship characteristics interacted with the link between bullying and both types of frequent substance use. Together, these findings clarify the nature of the bullying-substance use link and emphasize the need to study adolescent development in context.

The differential impact of oxytocin receptor (OXTR) genotypes on the risk of autism spectrum disorder (ASD) and resulting social communication deficits

Background: Autism spectrum disorder (ASD) is multifactorial and is likely the result of complex interactions between multiple environmental and genetic factors. Recently, it has been suggested that each symptom cluster of the disorder, such as poor social communication, may be mediated by different genetic influences. Genes in the oxytocin pathway, which mediates social behaviours in humans, have been studied with single nucleotide polymorphisms (SNPs) in the oxytocin receptor gene (OXTR) being implicated in ASD. This thesis examines the presence of different oxytocin receptor genotypes, and their associations with ASD and resulting social communication deficits. Methods: The relationship between four OXTR variants and ASD was evaluated in 607 ASD simplex (SPX) families. Cases were compared to their unaffected siblings using a conditional logistic approach. Odds ratios and associated 95 percent confidence intervals were obtained. A second sample of 235 individuals with a diagnosis of ASD was examined to evaluate whether these four OXTR variants were associated with social communication scores on the Autism Diagnostic Interview – Revised (ADI-R). Parameter estimates and associated 95 percent confidence intervals were generated using a linear regression approach. Multiple testing issues were addressed using false discovery adjustments. Results: The rs53576 AG genotype was significantly associated with a lower risk of ASD (OR = 0.707, 95% CI: 0.512-0.975). A single genotype (AG) provided by the rs2254298 marker was found to be significantly associated with higher social communication scores (Parameter estimate = 1.833, SE = 0.762, p = 0.0171). This association was also seen in a Caucasian only and mothers as the respondent samples. No association was significant following false discovery rate adjustments. Conclusion: The findings from these studies provide limited support for the role of OXTR SNPs in ASD, especially in social communication skills. The clinical significance of these associations remains unknown, however, it is likely that these associations do not play a role in the severity of symptoms associated with ASD. Rather, they may be important in the appearance of social deficits due to the rs2254298 markers association with enlarged amygdalas.

Subfornical organ neurons integrate cardiovascular and metabolic signals

The subfornical organ (SFO) is a critical circumventricular organ involved in the control of cardiovascular and metabolic homeostasis. Despite the abundant literature clearly demonstrating the ability of SFO neurons to sense and respond to a plethora of circulating signals that influence various physiological systems, investigation of how simultaneously sensed signals interact and are integrated in the SFO is lacking. In this study, we use patch clamp techniques to investigate how the traditionally classified ‘cardiovascular’ hormone angiotensin II (ANG), ‘metabolic’ hormone cholecystokinin (CCK) and ‘metabolic’ signal glucose interact and are integrated in the SFO. Sequential bath-application of CCK (10nM) and ANG (10nM) onto dissociated SFO neurons revealed that: 63% of responsive SFO neurons depolarized to both CCK & ANG; 25% depolarized to ANG only; and 12% hyperpolarized to CCK only. We next investigated the effects of glucose by incubating and recording neurons in either hypo-, normo- or hyperglycemic conditions for a minimum of 24 hours and comparing the proportions of responses to ANG (n=55) or CCK (n=83) application in each condition. A hyperglycemic environment was associated with a larger proportion of depolarizing responses to ANG (X2, p<0.05), and a smaller proportion of depolarizing responses along with a larger proportion of hyperpolarizing responses to CCK (X2, p<0.01). These data demonstrate that SFO neurons excited by CCK are also excited by ANG, suggesting that CCK may influence fluid intake or blood pressure via the SFO, complementary to the well-understood actions of ANG at this site. Additionally, the demonstration that glucose environment affects the responsiveness of neurons to both these hormones highlights the ability of SFO neurons to integrate multiple metabolic and cardiovascular signals to affect transmission of information from the circulation to the brain, which has important implications for this structure’s critical role regulation of autonomic function.