RT journal article
T1 A microRNA Signature for the Diagnosis of Statins Intolerance
A1 Mangas Rojas, Alipio
A1 Perez-Serra, Alexandra
A1 Bonet Martínez, Fernando
A1 Muñiz, Ovidio
A1 Fuentes, Francisco
A1 Gonzalez-Estrada, Aurora
A1 Campuzano, Oscar
A1 Rodriguez Roca, Juan Sebastian
A1 Alonso Villa, Elena
A1 Toro Cebada, Rocío
A2 Medicina
K1 circulating microRNAs
K1 statin intolerance
K1 biomarkers
K1 atherosclerotic cardiovascular diseases
K1 statins-adverse myalgia symptoms
AB 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 (n = 10); (ii) SI (n = 10). Ten miRNAs were identified as being overexpressed in plasma and validated in the plasma of NSI (n = 45) and SI (n = 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.
PB MDPI
SN 1422-0067
YR 2022
FD 2022-08
LK http://hdl.handle.net/10498/28005
UL http://hdl.handle.net/10498/28005
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 22-sep-2026