Developing new statisical methods to detect variants involved in complex disease

我们获得的结果可能为NPC的遗传决定因素提供新的见解，并可能为NPC和其他感染相关疾病的风险基因提供见解。我们从这项研究中学到的东西也可以应用于其他复杂疾病的遗传研究，包括精神疾病，包括精神分裂症，躁郁症和自闭症。 DNA修复在保护免受环境致癌作用中起着关键作用，并且DNA修复基因的遗传变异已被报道与几种人类恶性肿瘤相关。为了评估DNA修复基因变异是否与鼻咽癌（NPC）风险相关，我们在中国广东省的广东人群中进行了一项基于通路的候选基因关联研究。研究分两个阶段进行。在发现阶段，我们对755例鼻咽癌患者和755名社区健康对照进行了配对病例对照研究，共检测了676个SNPs（由包括姚博士在内的专家组筛选），涵盖88个DNA修复基因。发现RAD 51 L1、BRCA 2和TP 53 BP 1三个基因与鼻咽癌的发生发展密切相关。在验证阶段，我们跟踪了第一阶段揭示的信号，发现只有RAD 51 L1基因中的两个遗传变异显著相关。验证的样本量为1，558例病例和1，297例对照。此外，我们还进行了基因-环境互作分析。这是我们第一次有信心地证明吸烟和食用咸鱼与DNA修复基因变异有显著的相互作用。 在这项研究中，我们利用最先进的，高通量的基因分型方法以及复杂的遗传分析方法，考虑到基因-基因相互作用和基因-环境相互作用，除了单SNP分析。例如，我们进行了创新的基于途径的分析，如CART。CART方法在危险因素和TP 53 BP 1、RAD 51、BRCA 2和MNAT 1基因变异中鉴定出一个具有较高鼻咽癌风险的亚组。我们自己的方法证实了这种相互作用。这一发现表明，吸烟和四个基因的变异可能共同导致NPC发展的风险增加。 我们成功地确定了有助于识别NPC发展风险的遗传标记。我们未来的工作将专注于在一个单独的人群中验证这一发现，并通过结合I期和II期分析中使用的临床样本来识别有效预测NPC结果的遗传标记。遗传和临床信息的结合可能比单独使用更具预测性，可能有利于使用适当的方法治疗NPC。 在NPC研究的初步结果的鼓舞下，我们现在将使用我们开发和验证的分析技术来分析来自三个大型公开数据库的数据，这些数据库包含被诊断患有自闭症谱系障碍（ASD）的人及其家庭的人口统计学，环境和遗传构成信息。我们希望在这项研究中改进我们的数据分析统计工具。此外，基于我们早期研究的成功，我们希望这种方法能为遗传变异在ASD和其他精神疾病中的作用提供新的线索。

The results we obtained may provide new insights into the genetic determinants of NPC, and may possibly provide insights on genes contributing to risk for NPC and other diseases related to infections. What we learn from this study can also be applied to genetic research for other complex diseases including psychiatric disorders including schizophrenia, bipolar and autism. DNA repair plays a critical role in protecting against environmental carcinogenesis, and genetic variants of DNA repair genes have been reported to be associated with several human malignancies. To assess whether or not DNA repair gene variants are associated with nasopharyngeal carcinoma (NPC) risk, we conducted a pathway based candidate gene association study among the Cantonese population within Guangdong Province, China. The study was conducted in two stages. In the discover stage, we investigated 676 SNPs (selected by an expert panel including Dr. Yao) which cover 88 DNA repair genes in a matched case-controls study in which 755 patients who were diagnosed of NPC and 755 community based health controls were included. We discovered that three genes, RAD51L1, BRCA2 and TP53BP1 were significantly involved in development of NPC. In the validation stage, we followed up the signals revealed in stage 1 and found that only two genetic variants in the RAD51L1 gene were significantly associated. The sample size of the validation was 1,558 cases and 1,297 controls. Furthermore, we conducted gene-environment interaction analysis. For the first time, we documented that the exposure of cigarette smoking and salted fish consumption had significant interactions with the DNA repair gene variations with confidence. In this study, we utilize state-of-the-art, high-throughput genotyping methods as well as sophisticated methods of genetic analysis that take into account gene-gene interaction and gene-environment interactions in addition to single-SNP analyses. For example, we conducted innovative pathway based analysis such as CART. The CART method identified a subgroup with higher risk of NPC among the risk factors and the genetic variants of Tp53BP1, RAD51, BRCA2 and MNAT1. This interaction was confirmed by our own method. This finding indicated that smoking and variants in four genes may contribute jointly to the increased risk of NPC development. We successfully identified genetic markers that help identify those at risk for NPC development. Our future work will focus on validating this finding in a separate population and identifying genetic markers that effectively predict NPC outcome by combing the clinical samples used in stage I and stage II analysis. The combination of genetic and clinical information may be more predictive than either alone, potentially benefiting the treatment of NPC using appropriate methods. Encouraged by the preliminary results from our NPC studies, we will now use the analytic techniques we have developed and validated to analyze data from three large, publicly available databases containing information on the demographic, environmental, and genetic makeup of people diagnosed with Autism Spectrum Disorders (ASDs) and their families. We expect to improve our statistical tools for data analysis during this study. Based on the success of our earlier studies, moreover, we expect this approach to shed new light on genetic variations role in ASDs and other psychiatric disorders.