Exploration of the gene expression correlates of chronic unexplained fatigue using factor analysis
Exploration of the gene expression correlates of chronic unexplained fatigue using factor analysis
复制标题
DOI：
10.2217/14622416.7.3.441
复制
发表时间：
2006-04-01
期刊：
影响因子：
2.1
通讯作者：
Lloyd, A
中科院分区：
文献类型：
--
作者：
Fostel, J;Boneva, R;Lloyd, A
目的：通过对基因芯片数据、病理学检查结果和自我报告症状的分析，确定慢性疲劳综合征（CFS）及其相关疾病的生物标志物。方法：为了从经验上得出疾病的症状域，在用独立数据集进行验证之前，对自我报告问卷（多维疲劳量表、疾病控制和预防中心（CDC）症状量表和Zung抑郁量表）的响应进行因子分析。然后寻找在每个因素维度上区分受试者的基因表达模式。结果：一个四因素的解决方案，具有“疲劳”和“情绪障碍”的因素。这些因素的得分与简表（SF）-36的残疾指标相关。总共有57个基因，区分科目沿着每个因素的维度进行了鉴定，虽然分离是显着的，只有受试者超过极端（第15和第85）的严重程度。实验室参数与这些基因表达的聚类显示与pH、电解质、葡萄糖、尿素、肌酐和肝酶（天冬氨酸氨基转移酶[AST]和丙氨酸氨基转移酶[AST]）的血清测量值以及红细胞压积和白色细胞计数相关。结论：CFS是一种复杂的综合征，不能简单地与个体实验室检查或个体基因表达水平的变化相关。基因表达与个体症状领域之间没有明确的联系，但对这些多方面数据集的分析可能是阐明CFS发病机制的重要手段。
Objective: To identify biomarkers of chronic fatigue syndrome (CFS) and related disorders through analysis of microarray data, pathology test results and self-report symptom profiles. Method: To empirically derive the symptom domains of the illnesses, factor analysis was performed on responses to self-report questionnaires (multidimensional fatigue inventory, Centers for Disease Control and Prevention (CDC) symptom inventory and Zung depression scale) before validation with independent datasets. Gene expression patterns that distinguished subjects across each factor dimension were then sought. Results: A four-factor solution was favored, featuring 'fatigue' and 'mood disturbance' factors. Scores on these factors correlated with measures of disability on the Short Form (SF)-36. A total of 57 genes that distinguished subjects along each factor dimension were identified, although the separation was significant only for subjects beyond the extreme (15th and 85th) percentiles of severity. Clustering of laboratory parameters with expression of these genes revealed associations with serum measurements of pH, electrolytes, glucose, urea, creatinine, and liver enzymes (aspartate amino transferase [AST] and alanine amino transferase [AST]); as well as hematocrit and white cell count. Conclusion: CFS is a complex syndrome that cannot simply be associated with changes in individual laboratory tests or expression levels of individual genes. No clear association with gene expression and individual symptom domains was found. However, analysis of such multifacetted datasets is likely to be an important means to elucidate the pathogenesis of CFS.