Department of Anesthesiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Department of Anesthesiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
J Clin Anesth. 2020 Jun;62:109738. doi: 10.1016/j.jclinane.2020.109738. Epub 2020 Feb 12.
To employ systems biology-based machine learning to identify biologic processes over-represented with genetic variants (gene enrichment) implicated in post-surgical pain.
Informed systems biology based integrative computational analyses.
Pediatric research and teaching institution.
Pubmed search (01/01/2001-10/31/2017) was performed to identify "training" genes associated with postoperative pain in humans. Candidate genes were identified and prioritized using Toppgene suite, based on functional enrichment using several gene ontology annotations, and curated gene sets associated with mouse phenotype-knockout studies.
Computationally top-ranked candidate genes and literature-curated genes were included in pathway enrichment analyses. Hierarchical clustering was used to visualize select functional enrichment results between the two phenotypes.
Literature review identified 38 training genes associated with postoperative pain and 31 with CPSP. We identified 2610 prioritized novel candidate genes likely associated with acute and chronic postsurgical pain, the top 10th percentile jointly enriched (p 0.05; Benjamini-Hochberg correction) several pathways, topmost being cAMP response element-binding protein and ion channel pathways. Heat maps demonstrated enrichment of inflammatory/drug metabolism processes in acute postoperative pain and immune mechanisms in CPSP.
High interindividual variability in pain responses immediately after surgery and risk for CPSP suggests genetic susceptibility. Lack of large homogenous sample sizes have led to underpowered genetic association studies. Systems biology can be leveraged to integrate genetic-level data with biologic processes to generate prioritized candidate gene lists and understand novel biological pathways involved in acute postoperative pain and CPSP. Such data would be key to informing future polygenic studies with targeted genome wide profiling. This study demonstrates the utility of functional annotation - based prioritization and enrichment approaches and identifies novel genes and unique/shared biological processes involved in acute and chronic postoperative pain. Results provide framework for future targeted genetic profiling of CPSP risk, to enable preventive and therapeutic approaches.
运用基于系统生物学的机器学习方法，识别与术后疼痛相关的遗传变异（基因富集）所涉及的生物学过程。
基于信息的系统生物学综合计算分析。
儿科研究和教学机构。
通过 PubMed 搜索（2001 年 1 月 1 日至 2017 年 10 月 31 日），确定与人类术后疼痛相关的“训练”基因。使用 Toppgene 套件，根据几个基因本体注释的功能富集，以及与小鼠表型敲除研究相关的已审定基因集，确定候选基因并对其进行优先级排序。
将计算上排名最高的候选基因和文献中审定的基因纳入途径富集分析。采用层次聚类方法，可视化两种表型之间的特定功能富集结果。
文献综述确定了 38 个与术后疼痛相关的训练基因和 31 个与 CPSP 相关的基因。我们确定了 2610 个可能与急性和慢性术后疼痛相关的新型候选基因，排名前 10%的基因共同富集（p<0.05；Benjamini-Hochberg 校正）了几个途径，最重要的是 cAMP 反应元件结合蛋白和离子通道途径。热图显示，急性术后疼痛中炎症/药物代谢过程和 CPSP 中的免疫机制富集。
术后即刻疼痛反应和 CPSP 风险的个体间高度变异性提示存在遗传易感性。缺乏大型同质样本量导致遗传关联研究的效能不足。系统生物学可用于整合遗传水平数据与生物学过程，生成优先候选基因列表，并了解急性术后疼痛和 CPSP 中涉及的新生物学途径。此类数据将是未来进行靶向全基因组分析的多基因研究的关键。本研究证明了基于功能注释的优先级排序和富集方法的实用性，并确定了与急性和慢性术后疼痛相关的新基因和独特/共享的生物学过程。研究结果为未来 CPSP 风险的靶向基因分析提供了框架，以实现预防和治疗方法。
