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利用英国生物银行的数据,从遗传学角度深入研究多部位慢性疼痛与常见疾病和生物标志物的关联。

Genetic insights into associations of multisite chronic pain with common diseases and biomarkers using data from the UK Biobank.

机构信息

Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR of China.

Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanism of Cardiologic Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR of China.

出版信息

Br J Anaesth. 2024 Feb;132(2):372-382. doi: 10.1016/j.bja.2023.11.007. Epub 2023 Dec 15.

Abstract

BACKGROUND

Chronic pain is a common, complex, and challenging condition, for which specialised healthcare is required. We investigated the relationship between multisite chronic pain (MCP) and different disease traits identify safe biomarker interventions that can prevent MCP.

METHODS

Univariable and multivariable Mendelian randomisation (MR) analysis were conducted to investigate associations between MCP and 36 common diseases in the UK Biobank. Subsequently, we estimated the potential effect of expression of 4774 proteins on MCP utilising existing plasma protein quantitative trait locus data. For the significant biomarkers, we performed phenome-wide MR (Phe-MR) with 1658 outcomes to predict potential safety profiles linked to biomarker intervention.

RESULTS

Multisite chronic pain had a substantial impact on psychiatric and neurodevelopmental traits (major depression and attention deficit hyperactivity disorder), cardiovascular diseases (myocardial infarction, coronary artery disease, and heart failure), respiratory outcomes (asthma, chronic obstructive pulmonary disease, and sleep apnoea), arthropathies, type 2 diabetes mellitus, and cholelithiasis. Higher genetically predicted levels of S100A6, DOCK9, ferritin, and ferritin light chain were associated with a risk of MCP, whereas PTN9 and NEUG were linked to decreased MCP risk. Phe-MR results suggested that genetic inhibition of DOCK9 increased the risk of 21 types of disease, whereas the other biomarker interventions were relatively safe.

CONCLUSIONS

We established that MCP has an effect on health conditions covering various physiological systems and identified six novel biomarkers for intervention. In particular, S100A6, PTN9, NEUG, and ferritin light chain represent promising targets for MCP prevention, as no significant side-effects were predicted in our study.

摘要

背景

慢性疼痛是一种常见、复杂且具有挑战性的病症,需要专业的医疗保健。我们研究了多部位慢性疼痛(MCP)与不同疾病特征之间的关系,以确定可以预防 MCP 的安全生物标志物干预措施。

方法

在英国生物库中,我们进行了单变量和多变量孟德尔随机化(MR)分析,以研究 MCP 与 36 种常见疾病之间的关联。随后,我们利用现有的血浆蛋白数量性状基因座数据来估计 4774 种蛋白质表达对 MCP 的潜在影响。对于显著的生物标志物,我们利用 1658 种结果进行了表型全基因组关联研究(Phe-MR),以预测与生物标志物干预相关的潜在安全特征。

结果

多部位慢性疼痛对精神和神经发育特征(重度抑郁症和注意缺陷多动障碍)、心血管疾病(心肌梗死、冠心病和心力衰竭)、呼吸结局(哮喘、慢性阻塞性肺疾病和睡眠呼吸暂停)、关节病、2 型糖尿病和胆石症有很大影响。遗传预测水平较高的 S100A6、DOCK9、铁蛋白和铁蛋白轻链与 MCP 风险增加相关,而 PTN9 和 NEUG 则与 MCP 风险降低相关。Phe-MR 结果表明,DOCK9 的遗传抑制增加了 21 种疾病的风险,而其他生物标志物干预措施相对安全。

结论

我们发现 MCP 对涉及多种生理系统的健康状况有影响,并确定了 6 种新的干预生物标志物。特别是,S100A6、PTN9、NEUG 和铁蛋白轻链代表了预防 MCP 的有希望的靶点,因为在我们的研究中没有预测到明显的副作用。

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