A microRNA signature that correlates with cognition and is a target against cognitive decline

While some individuals age without pathological memory impairments, others develop age‐associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study, we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3‐microRNA signature that reflects key processes linked to neural homeostasis and inform about cognitive status. We furthermore provide evidence that expression changes in this signature represent multiple mechanisms deregulated in the aging and diseased brain and are a suitable target for RNA therapeutics. SYNOPSIS Alzheimer’s disease (AD) is usually diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. This study aimed to identify a minimally invasive biomarker that can help to identify individuals at risk for cognitive decline before clinical manifestation. Circulating microRNAs are linked to cognitive function in young and healthy humans. A circulating 3‐microRNA signature is identified using a longitudinal mouse model of age‐associated memory decline. The expression of the 3‐microRNA signature is increased in patients with mild cognitive impairment (MCI) and is associated with future conversion from MCI to AD. Targeting all 3‐ microRNAs using anti‐miRs ameliorates cognitive decline in AD mice. Graphical Abstract Alzheimer’s disease (AD) is usually diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. This study aimed to identify a minimally invasive biomarker that can help to identify individuals at risk for cognitive decline before clinical manifestation.