支持 Janus 激酶 2 在前列腺癌中起因果作用的遗传证据：一项孟德尔随机化研究。

Genetic evidence supporting a causal role of Janus kinase 2 in prostate cancer: a Mendelian randomization study.

机构信息

Department of Urology, The Second Hospital of Shanxi Medical University, Shanxi Medical University, Taiyuan, China.

Shanxi Provincial Key Laboratory of Rheumatism Immune Microecology, Taiyuan, PR China.

出版信息

Aging Male. 2023 Dec;26(1):2257300. doi: 10.1080/13685538.2023.2257300.

DOI:10.1080/13685538.2023.2257300

PMID:37706641

Abstract

BACKGROUND

Janus kinase-2 (JAK2) inhibitors are now being tried in basic research and clinical practice in prostate cancer (PCa). However, the causal relationship between JAK2 and PCa has not been uniformly described. Here, we examined the cause-effect relation between JAK2 and PCa.

METHODS

Two-sample Mendelian randomization (MR) analysis of genetic variation data of JAK2, PCa from IEU OpenGWAS Project was performed by inverse variance weighted, MR-Egger, and weighted median. Cochran's heterogeneity test and MR-Egger multiplicity analysis were performed to normalize the MR analysis results to reduce the effect of bias on the results.

RESULTS

Five instrumental variables were identified for further MR analysis. Specifically, combining the inverse variance-weighted (OR: 1.0009, 95% CI: 1.0001-1.0015, = 0.02) and weighted median (OR: 1.0009, 95% CI: 1.0000-1.0017, = 0.03). Sensitivity analysis showed that there was no heterogeneity ( = 0.448) and horizontal multiplicity ( = 0.770) among the instrumental variables.

CONCLUSIONS

We found JAK2 was associated with the development of PCa and was a risk factor for PCa, which might be instructive for the use of JAK2 inhibitors in PCa patients.

摘要

背景

Janus 激酶-2（JAK2）抑制剂目前正在前列腺癌（PCa）的基础研究和临床实践中进行尝试。然而，JAK2 与 PCa 之间的因果关系尚未得到统一描述。在这里，我们研究了 JAK2 与 PCa 之间的因果关系。

方法

通过逆方差加权、MR-Egger 和加权中位数对来自 IEU OpenGWAS 项目的 JAK2 和 PCa 的遗传变异数据进行两样本孟德尔随机化（MR）分析。进行 Cochran's 异质性检验和 MR-Egger 多重性分析，以归一化 MR 分析结果，减少偏倚对结果的影响。

结果

确定了五个工具变量用于进一步的 MR 分析。具体来说，结合逆方差加权（OR：1.0009，95%CI：1.0001-1.0015， = 0.02）和加权中位数（OR：1.0009，95%CI：1.0000-1.0017， = 0.03）。敏感性分析表明，工具变量之间没有异质性（ = 0.448）和水平多重性（ = 0.770）。