Research Unit, Biomedical Research and Innovation Institute of Cadiz (INiBICA), Puerta del Mar University Hospital, 11009 Cádiz, Spain.
Medicine Department, School of Medicine, University of Cadiz, 11002 Cádiz, Spain.
Int J Mol Sci. 2022 Jul 24;23(15):8146. doi: 10.3390/ijms23158146.
Atherosclerotic cardiovascular diseases (ASCVD) are the leading cause of morbidity and mortality in Western societies. Statins are the first-choice therapy for dislipidemias and are considered the cornerstone of ASCVD. Statin-associated muscle symptoms are the main reason for dropout of this treatment. There is an urgent need to identify new biomarkers with discriminative precision for diagnosing intolerance to statins (SI) in patients. MicroRNAs (miRNAs) have emerged as evolutionarily conserved molecules that serve as reliable biomarkers and regulators of multiple cellular events in cardiovascular diseases. In the current study, we evaluated plasma miRNAs as potential biomarkers to discriminate between the SI vs. non-statin intolerant (NSI) population. It is a multicenter, prospective, case-control study. A total of 179 differentially expressed circulating miRNAs were screened in two cardiovascular risk patient cohorts (high and very high risk): (i) NSI ( = 10); (ii) SI ( = 10). Ten miRNAs were identified as being overexpressed in plasma and validated in the plasma of NSI ( = 45) and SI ( = 39). Let-7c-5p, let-7d-5p, let-7f-5p, miR-376a-3p and miR-376c-3p were overexpressed in the plasma of SI patients. The receiver operating characteristic curve analysis supported the discriminative potential of the diagnosis. We propose a three-miRNA predictive fingerprint (let-7f, miR-376a-3p and miR-376c-3p) and several clinical variables (non-HDLc and years of dyslipidemia) for SI discrimination; this model achieves sensitivity, specificity and area under the receiver operating characteristic curve (AUC) of 83.67%, 88.57 and 89.10, respectively. In clinical practice, this set of miRNAs combined with clinical variables may discriminate between SI vs. NSI subjects. This multiparametric model may arise as a potential diagnostic biomarker with clinical value.
动脉粥样硬化性心血管疾病（ASCVD）是西方社会发病率和死亡率的主要原因。他汀类药物是治疗血脂异常的首选药物，被认为是 ASCVD 的基石。他汀类药物相关肌肉症状是导致这种治疗方法停药的主要原因。因此，迫切需要识别新的生物标志物，以具有鉴别精度来诊断患者对他汀类药物不耐受（SI）。微小 RNA（miRNA）作为进化上保守的分子，已成为心血管疾病中多种细胞事件的可靠生物标志物和调节剂。在目前的研究中，我们评估了血浆 miRNA 作为潜在的生物标志物，以区分 SI 与非他汀类不耐受（NSI）人群。这是一项多中心、前瞻性、病例对照研究。在两个心血管风险患者队列（高风险和极高风险）中筛选了 179 种差异表达的循环 miRNA：（i）NSI（n=10）；（ii）SI（n=10）。在 NSI（n=45）和 SI（n=39）患者的血浆中验证了 10 种过表达的 miRNA。Let-7c-5p、Let-7d-5p、Let-7f-5p、miR-376a-3p 和 miR-376c-3p 在 SI 患者的血浆中过表达。受试者工作特征曲线分析支持了该诊断的鉴别潜力。我们提出了一个三 miRNA 预测指纹（Let-7f、miR-376a-3p 和 miR-376c-3p）和几个临床变量（非高密度脂蛋白胆固醇和血脂异常年数）用于 SI 鉴别；该模型的灵敏度、特异性和受试者工作特征曲线下面积（AUC）分别为 83.67%、88.57%和 89.10%。在临床实践中，这套 miRNA 与临床变量相结合可用于区分 SI 与 NSI 患者。这种多参数模型可能成为具有临床价值的潜在诊断生物标志物。
