Pain Clinic, Department of Perioperative Medicine, Intensive Care and Pain Medicine, Helsinki University Hospital and SleepWell Research Programme, University of Helsinki, 00014 Helsinki, Finland.
Metabolomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, 00014 Helsinki, Finland.
Int J Mol Sci. 2022 May 3;23(9):5085. doi: 10.3390/ijms23095085.
Recent scientific evidence suggests that chronic pain phenotypes are reflected in metabolomic changes. However, problems associated with chronic pain, such as sleep disorders or obesity, may complicate the metabolome pattern. Such a complex phenotype was investigated to identify common metabolomics markers at the interface of persistent pain, sleep, and obesity in 71 men and 122 women undergoing tertiary pain care. They were examined for patterns in d = 97 metabolomic markers that segregated patients with a relatively benign pain phenotype (low and little bothersome pain) from those with more severe clinical symptoms (high pain intensity, more bothersome pain, and co-occurring problems such as sleep disturbance). Two independent lines of data analysis were pursued. First, a data-driven supervised machine learning-based approach was used to identify the most informative metabolic markers for complex phenotype assignment. This pointed primarily at adenosine monophosphate (AMP), asparagine, deoxycytidine, glucuronic acid, and propionylcarnitine, and secondarily at cysteine and nicotinamide adenine dinucleotide (NAD) as informative for assigning patients to clinical pain phenotypes. After this, a hypothesis-driven analysis of metabolic pathways was performed, including sleep and obesity. In both the first and second line of analysis, three metabolic markers (NAD, AMP, and cysteine) were found to be relevant, including metabolic pathway analysis in obesity, associated with changes in amino acid metabolism, and sleep problems, associated with downregulated methionine metabolism. Taken together, present findings provide evidence that metabolomic changes associated with co-occurring problems may play a role in the development of severe pain. Co-occurring problems may influence each other at the metabolomic level. Because the methionine and glutathione metabolic pathways are physiologically linked, sleep problems appear to be associated with the first metabolic pathway, whereas obesity may be associated with the second.
最近的科学证据表明，慢性疼痛表型反映在代谢组学变化中。然而，与慢性疼痛相关的问题，如睡眠障碍或肥胖，可能会使代谢组模式复杂化。为了在接受三级疼痛治疗的 71 名男性和 122 名女性中确定持续疼痛、睡眠和肥胖之间的共同代谢组学标志物，研究了这种复杂的表型。对 d = 97 个代谢组学标志物的模式进行了检查，这些标志物将具有相对良性疼痛表型（低且令人烦恼少的疼痛）的患者与具有更严重临床症状（高疼痛强度、更令人烦恼的疼痛以及睡眠障碍等并发问题）的患者分开。进行了两种独立的数据分析。首先，使用基于数据驱动的监督机器学习方法来识别最能为复杂表型分配提供信息的代谢标志物。这主要指向单磷酸腺苷（AMP）、天冬酰胺、脱氧胞苷、葡萄糖醛酸和丙酰肉碱，其次是半胱氨酸和烟酰胺腺嘌呤二核苷酸（NAD），这些标志物为将患者分配到临床疼痛表型提供信息。在此之后，对代谢途径进行了假设驱动的分析，包括睡眠和肥胖。在第一和第二分析线中，发现了三个代谢标志物（NAD、AMP 和半胱氨酸）与肥胖相关，包括与氨基酸代谢变化相关的代谢途径分析，以及与下调蛋氨酸代谢相关的睡眠问题。总的来说，目前的研究结果提供了证据，表明与并发问题相关的代谢组变化可能在严重疼痛的发展中起作用。并发问题可能在代谢组学水平上相互影响。由于蛋氨酸和谷胱甘肽代谢途径在生理上是相互关联的，因此睡眠问题似乎与第一个代谢途径有关，而肥胖可能与第二个代谢途径有关。
