Laboratory of Pharmacogenomics, Department of Molecular Neuropharmacology, Maj Institute of Pharmacology, Polish Academy of Sciences, Krakow, Poland.
Intelliseq sp. z o.o., Krakow, Poland.
J Neurochem. 2023 Aug;166(3):623-632. doi: 10.1111/jnc.15902. Epub 2023 Jun 26.
Prediction of post-stroke depressive symptoms (DSs) is challenging in patients without a history of depression. Gene expression profiling in blood cells may facilitate the search for biomarkers. The use of an ex vivo stimulus to the blood helps to reveal differences in gene profiles by reducing variation in gene expression. We conducted a proof-of-concept study to determine the usefulness of gene expression profiling in lipopolysaccharide (LPS)-stimulated blood for predicting post-stroke DS. Out of 262 enrolled patients with ischemic stroke, we included 96 patients without a pre-stroke history of depression and not taking any anti-depressive medication before or during the first 3 months after stroke. We assessed DS at 3 months after stroke using the Patient Health Questionnaire-9. We used RNA sequencing to determine the gene expression profile in LPS-stimulated blood samples taken on day 3 after stroke. We constructed a risk prediction model using a principal component analysis combined with logistic regression. We diagnosed post-stroke DS in 17.7% of patients. Expression of 510 genes differed between patients with and without DS. A model containing 6 genes (PKM, PRRC2C, NUP188, CHMP3, H2AC8, NOP10) displayed very good discriminatory properties (area under the curve: 0.95) with the sensitivity of 0.94 and specificity of 0.85. Our results suggest the potential utility of gene expression profiling in whole blood stimulated with LPS for predicting post-stroke DS. This method could be useful for searching biomarkers of post-stroke depression.
预测无抑郁病史的脑卒中后抑郁症状(DS)具有挑战性。血细胞的基因表达谱分析可能有助于寻找生物标志物。使用体外刺激血液有助于通过减少基因表达的差异来揭示基因谱的差异。我们进行了一项概念验证研究,以确定脂多糖(LPS)刺激的血液中的基因表达谱在预测脑卒中后 DS 中的有用性。在 262 名缺血性脑卒中患者中,我们纳入了 96 名无脑卒中前抑郁史且在脑卒中后 3 个月内未服用任何抗抑郁药物的患者。我们使用患者健康问卷-9 在脑卒中后 3 个月评估 DS。我们使用 RNA 测序来确定脑卒中后第 3 天采集的 LPS 刺激的血液样本中的基因表达谱。我们使用主成分分析结合逻辑回归构建了风险预测模型。我们在 17.7%的患者中诊断出脑卒中后 DS。脑卒中后 DS 患者与无 DS 患者的基因表达谱存在差异。包含 6 个基因(PKM、PRRC2C、NUP188、CHMP3、H2AC8、NOP10)的模型显示出非常好的判别性能(曲线下面积:0.95),敏感性为 0.94,特异性为 0.85。我们的结果表明,LPS 刺激全血中的基因表达谱在预测脑卒中后 DS 方面具有潜在的应用价值。这种方法可能有助于寻找脑卒中后抑郁的生物标志物。