A full pedigree based method for the statistical assessment of genetic anticipation

Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^

Rationale for reading fluconazole MICs at 24 hours rather than 48 hours when testing Candida spp. by the CLSI M27-A2 standard method.

We investigated if CLSI M27-A2 Candida species breakpoints for fluconazole MIC are valid when read at 24 h. Analysis of a data set showed good correlation between 48- and 24-h MICs, as well as similar outcomes and pharmacodynamic efficacy parameters, except for isolates in the susceptible dose-dependent category, such as Candida glabrata.

Nonlinear tests for genetic studies of complex disease

Linkage and association studies are major analytical tools to search for susceptibility genes for complex diseases. With the availability of large collection of single nucleotide polymorphisms (SNPs) and the rapid progresses for high throughput genotyping technologies, together with the ambitious goals of the International HapMap Project, genetic markers covering the whole genome will be available for genome-wide linkage and association studies. In order not to inflate the type I error rate in performing genome-wide linkage and association studies, multiple adjustment for the significant level for each independent linkage and/or association test is required, and this has led to the suggestion of genome-wide significant cut-off as low as 5 × 10 −7. Almost no linkage and/or association study can meet such a stringent threshold by the standard statistical methods. Developing new statistics with high power is urgently needed to tackle this problem. This dissertation proposes and explores a class of novel test statistics that can be used in both population-based and family-based genetic data by employing a completely new strategy, which uses nonlinear transformation of the sample means to construct test statistics for linkage and association studies. Extensive simulation studies are used to illustrate the properties of the nonlinear test statistics. Power calculations are performed using both analytical and empirical methods. Finally, real data sets are analyzed with the nonlinear test statistics. Results show that the nonlinear test statistics have correct type I error rates, and most of the studied nonlinear test statistics have higher power than the standard chi-square test. This dissertation introduces a new idea to design novel test statistics with high power and might open new ways to mapping susceptibility genes for complex diseases. ^

Teaching safety at a summer camp: Evaluation of a children's fire safety curriculum in an urban community setting

Objectives: The purpose of this study was to evaluate the effectiveness of the Danger Rangers Fire Safety Curriculum in increasing the fire safety knowledge of low-income, minority children in pre-kindergarten to third grade in Austin, TX during a summer day camp in 2007.^ Methods: Data was collected from child participants via teacher and researcher administered tests at pretest, posttest (immediately after the completion of the fire safety module), and at a 3 week follow-up to asses retention. In addition, a self-administered questionnaire was collected from parents pre- and post-intervention to assess home-related fire/burn risk factors. Paired t-tests were conducted using STATA 12.0 to evaluate pretest, posttest, and retention test mean scores as well as mean fire safety rules listed by grade group. McNemar's test was used to determine if there was a difference in fire-related risk factors as reported by the parents of the participants before and after the intervention. Only those who had paired data for the tests/surveys being compared were included in the analysis.^ Results: The first/second grade group and the third grade group scored significantly higher on fire safety knowledge on the posttest compared to the pretest (p<0.0001 for both groups). However, there was no significant change in knowledge scores for the pre-kindergarten to kindergarten group (p=0.14). Among the first/second grade group, knowledge levels did not significantly decline between the posttest and retention test (p=0.25). However, the third grade group had significantly lower fire safety knowledge scores on the retention test compared to the posttest (p<0.001). A similar increase was seen in the amount of fire safety rules listed after the intervention (p<0.0001 between pre and posttest for both the first/second grade and third grade groups), with no decline from the posttest to the retention test (p=0.50) for the first/second grade group, but a significant decline in the third grade group (p=0.001). McNemar's chi-square test showed a significant increase in the percentage of participants' parents reporting smoke detector testing on a regular basis and having a fire escape plan for their family after the intervention (p=0.01 and p<0.0001, respectively). However, there was no significant change in the frequency of reports of the child playing in the kitchen while the parent cooks or the house/apartment having a working smoke detector.^ Conclusion: We found that general fire safety knowledge improved and the number of specific fire safety rules increased among the first to third grade children who participated in the Danger Rangers fire safety program. However, it did not significantly increase general fire safety knowledge among the pre-k/k group. This study also showed that a program targeted towards children has the potential to influence familial risk factors by proxy. The Danger Rangers Fire Safety Curriculum should be further evaluated by conducting a randomized controlled trial, using valid measures that assess fire safety attitudes, beliefs, behaviors, as well as fire/burn related outcomes.^