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. ^

Nitrogen dioxide exposures among a selected group of residents of substandard housing in Houston, Texas

Nitrogen dioxide (NO$\sb2)$ levels in sixteen substandard houses located in Houston, Texas were examined. The classification of the houses as substandard was based on an assessment of structural integrity which would affect air exchange rates. In these homes, unvented gas space heaters were operated as the primary source of heat.^ The Ogawa passive sampling device was used to measure NO$\sb2$ concentrations over 24 to 48-hour periods during generally cold weather. A sampler was placed in the kitchen and bedroom of each house. The female head of household was asked to wear a monitor during area monitoring to assess her personal exposure. Outdoor levels of NO$\sb2$ were also measured.^ Mean (standard deviation) levels of kitchen, bedroom and personal exposures were 280 (125) ppb, 256 (155) ppb and 164 (102) ppb, respectively. Additional short-term ($<$24 hours) samples were measured in three houses. The mean level of NO$\sb2$ measured outdoors was 51 ppb over the course of the study.^ The measurements obtained with the Ogawa sampler were compared to those levels obtained using a reference method (chemiluminescence). Outdoor levels measured with the diffusion samplers were 48% higher.^ These results suggest that wintertime NO$\sb2$ levels within substandard houses using gas appliances for heating and cooking are extremely elevated. Further work is needed to investigate the prevalence of possible health effects associated with these exposures. ^