In the aging population, cognitive performance shows substantial variability, ranging from stable function to rapid decline. This variation is not fully accounted for by known neurodegenerative diseases such as Alzheimer's disease. Approximately 60% of the variance in cognitive trajectory remains unexplained by common pathologies like β-amyloid plaques, neurofibrillary tangles, and Lewy bodies. MicroRNAs (miRNAs), small non-coding RNAs that regulate gene expression, are promising candidates to explain this missing heritability because they influence multiple biological processes relevant to neuronal function and survival. Given their known roles in synaptic plasticity, neurodegenerative pathology aggregation, and memory processes, the researchers hypothesized that miRNAs contribute to individual differences in cognitive trajectories. This study aimed to identify novel biological mechanisms underlying variation in cognitive trajectory through a comprehensive investigation of miRNAs and their downstream effects on mRNAs and proteins in the dorsolateral prefrontal cortex (dlPFC) of four independent longitudinal cohorts of older adults. The study design involved a global miRNA association study of cognitive trajectory in a discovery and replication cohort, followed by a meta-analysis. This was supplemented by integrative analysis with transcriptomic and proteomic data from the dlPFC to further elucidate the downstream effects of identified miRNAs.

The existing literature highlights the incomplete explanation of cognitive decline solely by known neurodegenerative pathologies. Previous studies have demonstrated that a significant portion of cognitive decline remains unexplained after accounting for common pathologies. Furthermore, the importance of microRNAs (miRNAs) in regulating gene expression, synaptic plasticity, and neurodegenerative processes has been established. Studies have shown the involvement of miRNAs in regulating learning, memory, and neuronal survival. In particular, miR-132 has been linked to Alzheimer's disease pathology and cognitive function in prior studies.

This study utilized data from four longitudinal cohorts: the Religious Orders Study (ROS), Rush Memory and Aging Project (MAP), Banner Sun Health Research Institute (Banner), and the Baltimore Longitudinal Study of Aging (BLSA). Individual cognitive trajectories were determined from longitudinal cognitive test scores (17 tests annually in ROS/MAP, MMSE annually in Banner/BLSA). Postmortem brain tissue from the dorsolateral prefrontal cortex (dlPFC) was used to profile microRNAs (using nCounter Human miRNA), transcriptomes (using Illumina HiSeq RNA sequencing), and proteomes (previously published methods for Banner/BLSA). A global microRNA association study was conducted separately in the discovery (n=454) and replication (n=134) cohorts (ROS/MAP), followed by a meta-analysis. Integrative analyses were performed to examine the relationships between significant miRNAs and the transcriptome and proteome. These analyses involved adjusting for confounders such as sex, age, postmortem interval (PMI), RNA integrity number (RIN), and cell-type proportions. Statistical analyses employed linear mixed-effects models for cognitive trajectory estimation, limma for global miRNA association studies, METAL for meta-analysis, and variancePartition for variance decomposition. Predicted targets of miRNAs were validated using luciferase reporter assays.

The meta-analysis of the discovery and replication cohorts identified six miRNAs significantly associated with cognitive trajectory. After adjusting for eight cerebral pathologies (neurofibrillary tangles, β-amyloid, Lewy bodies, macroinfarct, microinfarcts, cerebral atherosclerosis, cerebral amyloid angiopathy, and hippocampal sclerosis), four miRNAs remained significant (miR-132-3p, miR-129-5p, miR-129-3p, and miR-29a-3p). Further analysis using a multiple regression model identified miR-132-3p and miR-29a-3p as the most robust contributors to cognitive trajectory, independent of the eight pathologies. miR-132-3p explained 18.2% of the variance in cognitive trajectory before adjusting for pathologies and 11.8% after adjustment. miR-29a-3p explained 1.6% and 2.0% of the variance before and after adjusting for pathologies, respectively. Integrative analyses showed miR-132-3p was associated with 24 of 47 co-expressed gene modules, while miR-29a-3p was associated with 3 modules. Putative downstream targets for miR-132-3p and miR-29a-3p were identified at both the transcript and protein levels. Luciferase reporter assays validated several of these targets. Notably, the combined effect of miR-132-3p and miR-29a-3p accounted for a substantial 19.8% of the variance in cognitive trajectory.

This study provides the first comprehensive analysis of the association between brain microRNA expression and cognitive trajectories in a large cohort of older adults. The findings demonstrate that miR-132-3p and miR-29a-3p are robust predictors of cognitive trajectory, independent of known cerebral pathologies. These microRNAs exert broad effects on gene expression networks in the brain, affecting multiple biological pathways relevant to cognitive function. The identification of downstream targets provides valuable insights into the potential mechanisms by which these miRNAs influence cognitive aging. This study highlights the importance of considering molecular mechanisms beyond known pathologies to understand individual variation in cognitive aging. Future research could focus on further validation of miRNA targets, exploration of the functional interactions between these miRNAs and their target genes, and development of targeted interventions to enhance cognitive resilience in older adults.

This study identifies miR-132-3p and miR-29a-3p as significant and independent predictors of cognitive trajectory in aging, explaining a substantial portion of the variance not accounted for by established pathologies. The identification of their downstream targets suggests potential therapeutic avenues for enhancing cognitive resilience. Future research should focus on validating these findings in larger, more diverse cohorts and investigating the mechanistic roles of these microRNAs in age-related cognitive decline.

This study is an association study; therefore, causal inferences cannot be definitively drawn. The use of postmortem brain tissue limits the ability to fully capture real-time changes in miRNA expression and their dynamic interactions with target genes. The proteomic data was from a separate cohort than the miRNA profiling, limiting the certainty of target identification at the protein level. The Nanostring platform used may not have captured the full spectrum of miRNAs.