Institute of Clinical Pharmacology, Goethe-University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany.
Department of Anaesthesiology, Intensive Care and Pain Medicine, University of Helsinki and Helsinki University Hospital, P.O. Box 440, 00029 HUS Helsinki, Finland.
Int J Mol Sci. 2021 Jan 16;22(2):878. doi: 10.3390/ijms22020878.
The genetic background of pain is becoming increasingly well understood, which opens up possibilities for predicting the individual risk of persistent pain and the use of tailored therapies adapted to the variant pattern of the patient's pain-relevant genes. The individual variant pattern of pain-relevant genes is accessible via next-generation sequencing, although the analysis of all "pain genes" would be expensive. Here, we report on the development of a cost-effective next generation sequencing-based pain-genotyping assay comprising the development of a customized AmpliSeq™ panel and bioinformatics approaches that condensate the genetic information of pain by identifying the most representative genes. The panel includes 29 key genes that have been shown to cover 70% of the biological functions exerted by a list of 540 so-called "pain genes" derived from transgenic mice experiments. These were supplemented by 43 additional genes that had been independently proposed as relevant for persistent pain. The functional genomics covered by the resulting 72 genes is particularly represented by mitogen-activated protein kinase of extracellular signal-regulated kinase and cytokine production and secretion. The present genotyping assay was established in 61 subjects of Caucasian ethnicity and investigates the functional role of the selected genes in the context of the known genetic architecture of pain without seeking functional associations for pain. The assay identified a total of 691 genetic variants, of which many have reports for a clinical relevance for pain or in another context. The assay is applicable for small to large-scale experimental setups at contemporary genotyping costs.
疼痛的遗传背景越来越被深入了解,这为预测个体持续疼痛的风险和使用针对患者疼痛相关基因变异模式的定制疗法开辟了可能性。通过下一代测序可以获得疼痛相关基因的个体变异模式,尽管分析所有“疼痛基因”的成本会很高。在这里,我们报告了一种具有成本效益的下一代测序疼痛基因分型检测方法的开发,该方法包括开发定制的 AmpliSeq™ 面板和生物信息学方法,通过识别最具代表性的基因来浓缩疼痛的遗传信息。该面板包括 29 个关键基因,这些基因已被证明涵盖了 540 个所谓“疼痛基因”中 70%的生物学功能,这些基因是从转基因小鼠实验中衍生出来的。此外,还补充了 43 个被认为与持续性疼痛相关的其他基因。由此产生的 72 个基因所涵盖的功能基因组学特别代表了细胞外信号调节激酶和细胞因子产生和分泌的有丝分裂原激活蛋白激酶。本基因分型检测方法是在 61 名白种人受试者中建立的,调查了所选基因在疼痛已知遗传结构背景下的功能作用,而不是寻找与疼痛相关的功能关联。该检测总共确定了 691 个遗传变异,其中许多与疼痛或其他方面的临床相关性有关。该检测适用于当代基因分型成本下的小型到大型实验设置。