Gene expression profiles in peripheral lymphocytes by arsenic exposure and skin lesion status in a Bangladeshi population
Gene expression profiles in peripheral lymphocytes by arsenic exposure and skin lesion status in a Bangladeshi population
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DOI：
10.1158/1055-9965.epi-06-0106
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发表时间：
2006-07-01
影响因子：
3.8
通讯作者：
Ahsan, Habibul
中科院分区：
文献类型：
--
作者：
Argos, Maria;Kibriya, Muhammad G.;Ahsan, Habibul
全世界数百万人通过饮用水长期暴露于砷。在这项研究中，砷暴露和砷的皮肤病变状态对全基因组基因表达模式的影响进行了评估，从砷的健康影响纵向研究中选择的个人的外周血淋巴细胞的RNA。使用AffyrneumHG-U133 A基因芯片（Affyrneum，SantaClara，CA）阵列测量类似于22，000个转录物的表达。我们的主要统计分析涉及识别差异表达基因的参与者和砷皮肤病变的基础上的显着性分析的微阵列统计与先验定义的1%的错误发现率，以尽量减少假阳性。为了更好地表征差异表达，除了基因特异性分析之外，我们还进行了基因本体和途径比较。468个基因在这两组之间差异表达，其中312个差异表达的基因通过限制对女性不吸烟者的分析来确定。我们还探讨了可能的差异基因表达的砷暴露水平之间的个人没有明显的砷皮肤病变，但是，没有差异表达的基因可以确定从这个比较。我们的研究结果表明，基于微阵列的基因表达分析是一个强大的方法来表征砷暴露和砷诱导的疾病的分子概况。从这项分析中确定的基因可能提供深入了解砷诱导的疾病的潜在过程，并代表化学预防研究的潜在目标，以减少砷诱导的皮肤癌在这一人群中。
Millions of individuals worldwide are chronically exposed to arsenic through their drinking water. In this study, the effect of arsenic exposure and arsenical skin lesion status on genome-wide gene expression patterns was evaluated using RNA from peripheral blood lymphocytes of individuals selected from the Health Effects of Arsenic Longitudinal Study. Affyrnetrix HG-U133A GeneChip (Affymetrix, Santa Clara, CA) arrays were used to measure the expression of similar to 22,000 transcripts. Our primary statistical analysis involved identifying differentially expressed genes between participants with and without arsenical skin lesions based on the significance analysis of microarrays statistic with an a priori defined 1% false discovery rate to minimize false positives. To better characterize differential expression, we also conducted Gene Ontology and pathway comparisons in addition to the gene-specific analyses. Four-hundred sixty-eight genes were differentially expressed between these two groups, from which 312 differentially expressed genes were identified by restricting the analysis to female never-smokers. We also explored possible differential gene expression by arsenic exposure levels among individuals without manifest arsenical skin lesions; however, no differentially expressed genes could be identified from this comparison. Our findings show that microarray-based gene expression analysis is a powerful method to characterize the molecular profile of arsenic exposure and arsenic-induced diseases. Genes identified from this analysis may provide insights into the underlying processes of arsenic-induced disease and represent potential targets for chemoprevention studies to reduce arsenicinduced skin cancer in this population.