The present invention includes a method for identifying an Alzheimer's disease (AD) patient prior to reaching clinical disease classification, comprising: obtaining a dataset associated with a blood, serum, or plasma sample from the patient, wherein the dataset comprises data representing the level of one or more microRNA biomarkers in the blood, serum, or plasma sample; assessing the dataset for a presence or an increase in an amount of miRNA-455-3p; determining the likelihood that the patient will develop AD patient prior to reaching clinical disease classification by detecting the presence or the increase in miRNA-455-3p to produce a score that is indicative of a likelihood of developing AD, wherein a higher score relative to a healthy control indicates that the patient is likely to have the prognosis for transitioning to classified AD, wherein the healthy control is derived from a non-AD patient with no clinical evidence of AD.