Simple Summary Breast cancer is the most common cancer in females worldwide. To date, many gene-environment interaction (GxE) studies have been conducted to better understand how genetic factors... Show moreSimple Summary Breast cancer is the most common cancer in females worldwide. To date, many gene-environment interaction (GxE) studies have been conducted to better understand how genetic factors combine with environmental factors to influence risk. However, previous studies have not found or found only a few interactions by using SNPs which were discovered from genome-wide association studies and have been conducted, for the most part, within European populations. In this study, we focused on estrogen-related lifestyle factors that have been identified for breast cancer, including several well-established reproductive factors that are mediated by hormonal mechanisms. We aimed to examine whether there are any gene and environmental factor interactions related to estrogen exposure or metabolism using a candidate approach in Korean women. We found two interactions in this study, although they were not replicated in the independent large consortium data. These findings suggest specificity in Koreans for breast cancer risk.In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 x 10(-3)). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 x 10(-4)). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk. Show less
Curriculum-Based Measurement (CBM) is a progress-monitoring system designed to be used by educators to screen performance, to monitor growth, and to evaluate the effectiveness of interventions on... Show moreCurriculum-Based Measurement (CBM) is a progress-monitoring system designed to be used by educators to screen performance, to monitor growth, and to evaluate the effectiveness of interventions on the growth of students with learning difficulties. Implementation of CBM for monitoring growth and evaluating instruction involves frequent measurement of student performance. Scores from the measures are placed on graphs that depict growth over time and provide information to educators about how effective instruction has been. The research focuses on CBM at the secondary-school level in reading and foreign-language learning. Chapter 3 focuses on the development of CBM measures in foreign-language learning. The technical adequacy from scores on two CBM measures are examined: maze selection and word translation. In Chapters 4 and 5, our attention turns to reading, specifically, to using CBM to monitor growth in reading for secondary-school students. In Chapter 4, alternate-form reliability, sensitivity, and validity of the scores as indicators of reading performance level and growth are examined. Both linear and nonlinear growth trajectories are considered. In Chapter 5, the stability of slopes generated from CBM maze scores, and factors related to the stability, are examined. The factors examined include duration, data collection schedule, and variation in maze scores. Show less
