miRNAs peripheral biomarkers for early diagnosis of AD in Latinamerican population - Orellana, Paulina; Caviedes, Ariel; Gonzalez, Carolina; Salcidua, Stefanny; Henriquez, Fernando; Cabello, Victoria; Lillo, Patricia; Villagra, Roque; Cerda, Mauricio; Zitko, Pedro; Thumala, Daniela; Gonzalez, Christian; et al. (Alzheimer's & dementia, 2023)
Background Timely diagnosis of Alzheimer’s disease (AD) is a critical first step in clinical care treatment. However, the availability of diagnostic tools for these conditions is either unavailable or unaffordable, especially in Latin American and the Caribbean (LAC) countries. In this scenario, microRNAs (miRNA) have recently emerged as promising cost‐effective and noninvasive biomarkers since they can be readily detected in different biofluids such as plasma bound to protein or inside exosomes. Our aim is to identify new blood biomarkers to calculate the risk to develop AD in the early stages using machine learning based on exosomal miRNAs detection and different cognitive domains. Method miRNAs were extracted from plasma circulating exosomes samples of Subjective Cognitive Complaint subjects belonging to the GERO cohort in two different times (T1 = baseline and T2 = 18 months, n = 50). miRNAs were sequencing to identify the expression levels. Dysregulated miRNAs were analyzed and correlated with neuropsychological evaluations to create machine learning algorithms. miRNAs obtained from algorithms were validated in a new population of subjects at both stages (T1 and T2, n = 50), using qRT‐PCR and correlation analysis with neuropsychological tests. Result For algorithm development, we classified subjects into stationary and progressive impairment. Algorithms were trained using the sequenced miRNAs, neuropsychological tests and neuroimaging. As possible predictors of progression of cognitive impairment, the best performing algorithm was Random forest using only miRNAs data. In a new group of subjects, three miRNAs selected by the algorithm and four miRNAs obtained from the literature were validated and the ROC curves were constructed. The combination of these miRNAs (algorithm and literature miRNAs), were the best predictor of the progression of cognitive impairment. Conclusion This study could be used in the initial phases of the diagnostic process of AD because it is minimally invasive, low cost and accessible to a large number of patients in Latin American and the Caribbean (LAC) countries.