The pathway not taken: understanding 'omics data in the perinatal context
The pathway not taken: understanding 'omics data in the perinatal context
复制标题
DOI：
10.1016/j.ajog.2015.03.023
复制
发表时间：
2015-07-01
影响因子：
9.8
通讯作者：
Bianchi, Diana W.
中科院分区：
文献类型：
--
作者：
Edlow, Andrea G.;Slonim, Donna K.;Bianchi, Diana W.
目的：大型数据集的组学分析在围产期研究中发挥着越来越重要的作用，但了解胎儿背景下的基因表达分析仍然是一个挑战。我们比较了广泛使用的系统生物学资源提供的解释（独创性途径分析[IPA]）与基因集富集分析（GSEA）的结果进行比较，其中功能注释专门针对胎儿进行研究设计：使用我们小组先前产生的羊水上清液转录组数据集，我们分析了3种不同的发育扰动：非整倍体（21三体[T21]）、血流动力学（双胞胎输血综合征[TTTS]）和代谢（母亲肥胖）与性别和胎龄匹配的对照受试者。差异表达的探针组通过使用配对t检验和Benjamini-Hochberg校正进行多重检验来鉴定（P <0.05）。用IPA和GSEA/DFLAT进行功能分析。结果：与对照组相比，有414个显着失调的探针集T21胎儿，2226 TTTS受体双胞胎，470肥胖妇女的胎儿。每项分析产出都是独特的，但又是互补的。对于T21，IPA和GSEA/DFLAT都确定了脑、心血管和皮肤系统发育的失调。对于TTTS，两种分析工具都确定了细胞生长/增殖、免疫和炎症信号传导、大脑和心血管发育的失调。对于母亲肥胖，这两种工具都确定了免疫和炎症信号，大脑和肌肉骨骼发育以及细胞死亡的失调。GSEA/DFLAT在肥胖妇女的胎儿中发现了更多的生物学功能失调（1203 vs 151）。对于所有3个数据集，GSEA/DFLAT提供了关于大脑发育的更全面的信息。IPA始终提供关于细胞死亡的更详细注释。IPA产生了许多与癌症相关的失调术语（T21中14个，TTTS中109个，母体肥胖中26个）; GSEA/DFLAT没有。结论：胎儿羊水上清液转录组的解释取决于分析程序，这表明应使用> 1个资源。在IPA中，胎儿的生理细胞增殖产生了许多与癌症有关的“假阳性”注释，这反映了其对成人疾病的偏见。这项研究支持使用基因注释资源与发展的重点，如DFLAT，在围产期医学的组学研究。
OBJECTIVE: 'Omics analysis of large datasets has an increasingly important role in perinatal research, but understanding gene expression analyses in the fetal context remains a challenge. We compared the interpretation provided by a widely used systems biology resource (ingenuity pathway analysis [IPA]) with that from gene set enrichment analysis (GSEA) with functional annotation curated specifically for the fetus (Developmental FunctionaL Annotation at Tufts [DFLAT]).STUDY DESIGN: Using amniotic fluid supernatant transcriptome datasets previously produced by our group, we analyzed 3 different developmental perturbations: aneuploidy (Trisomy 21 [T21]), hemodynamic (twin-twin transfusion syndrome [TTTS]), and metabolic (maternal obesity) vs sex-and gestational age-matched control subjects. Differentially expressed probe sets were identified with the use of paired t-tests with the Benjamini-Hochberg correction for multiple testing (P < .05). Functional analyses were performed with IPA and GSEA/DFLAT. Outputs were compared for biologic relevance to the fetus.RESULTS: Compared with control subjects, there were 414 significantly dysregulated probe sets in T21 fetuses, 2226 in TTTS recipient twins, and 470 in fetuses of obese women. Each analytic output was unique but complementary. For T21, both IPA and GSEA/DFLAT identified dysregulation of brain, cardiovascular, and integumentary system development. For TTTS, both analytic tools identified dysregulation of cell growth/proliferation, immune and inflammatory signaling, brain, and cardiovascular development. For maternal obesity, both tools identified dysregulation of immune and inflammatory signaling, brain and musculoskeletal development, and cell death. GSEA/DFLAT identified substantially more dysregulated biologic functions in fetuses of obese women (1203 vs 151). For all 3 datasets, GSEA/DFLAT provided more comprehensive information about brain development. IPA consistently provided more detailed annotation about cell death. IPA produced many dysregulated terms that pertained to cancer (14 in T21, 109 in TTTS, 26 in maternal obesity); GSEA/DFLAT did not.CONCLUSION: Interpretation of the fetal amniotic fluid supernatant transcriptome depends on the analytic program, which suggests that > 1 resource should be used. Within IPA, physiologic cellular proliferation in the fetus produced many "false positive" annotations that pertained to cancer, which reflects its bias toward adult diseases. This study supports the use of gene annotation resources with a developmental focus, such as DFLAT, for 'omics studies in perinatal medicine.