Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology, Center of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
Bioinformatics. 2009 Dec 1;25(23):3121-7. doi: 10.1093/bioinformatics/btp559. Epub 2009 Sep 28.
Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal models and human subjects. We asked whether these heterogeneous models can be integrated to provide consistent and robust biological insights into the biology of insulin resistance.
We perform integrative analysis of the 16 DGAP data sets that span multiple tissues, conditions, array types, laboratories, species, genetic backgrounds and study designs. For each data set, we identify differentially expressed genes compared with control. Then, for the combined data, we rank genes according to the frequency with which they were found to be statistically significant across data sets. This analysis reveals RetSat as a widely shared component of mechanisms involved in insulin resistance and sensitivity and adds to the growing importance of the retinol pathway in diabetes, adipogenesis and insulin resistance. Top candidates obtained from our analysis have been confirmed in recent laboratory studies.
2 型糖尿病是一种涉及环境和遗传因素的慢性代谢性疾病。为了了解 2 型糖尿病和胰岛素抵抗的遗传学，启动了糖尿病基因组解剖计划（DGAP），以对各种相关动物模型和人类受试者的基因表达进行分析。我们想知道这些异质模型是否可以整合，以提供对胰岛素抵抗生物学的一致和稳健的生物学见解。
我们对跨越多个组织、条件、阵列类型、实验室、物种、遗传背景和研究设计的 16 个 DGAP 数据集进行了综合分析。对于每个数据集，我们都确定了与对照相比差异表达的基因。然后，对于组合数据，我们根据它们在数据集中被发现具有统计学意义的频率对基因进行排序。该分析揭示了 RetSat 是涉及胰岛素抵抗和敏感性的机制的广泛共享成分，并增加了视黄醇途径在糖尿病、脂肪生成和胰岛素抵抗中的重要性。我们分析得到的顶级候选物已在最近的实验室研究中得到证实。
