Alzheimer's disease is a devastating neurodegenerative disorder affecting a significant portion of the world's rapidly growing aging population. In spite of its prevalence, the etiology of the disease is still poorly understood, and effective therapy is all but unavailable. Over the past decade, noncoding RNA, including microRNA (miRNA), has emerged as a major class of regulatory molecules involved in virtually all physiological and disease states. The specificity provided by miRNA sequence complementarity, together with the ability of these molecules to regulate complex networks of genes, has made them exciting novel targets for therapeutic agents. In this chapter, we review recent progress on understanding the role of noncoding RNA in Alzheimer's disease (AD). The majority of available work has focused on miRNA, and we review the many studies implicating specific miRNAs in the development of the disease. More recently, several studies have tied other RNA classes to the disorder, including long noncoding RNA, circular RNA, and Y RNAs, and we review this fascinating field as well. Finally, we explore the potential promise of these findings for future therapeutic applications.

Alzheimer's disease (AD) involves changes in both lipid and RNA metabolism, but it remained unknown if these differences associate with AD's cognition and/or post-mortem neuropathology indices. Here, we report RNA-sequencing evidence of inter-related associations between lipid processing, cognition level, and AD neuropathology. In two unrelated cohorts, we identified pathway-enriched facilitation of lipid processing and alternative splicing genes, including the neuronal-enriched NOVA1 and hnRNPA1. Specifically, this association emerged in temporal lobe tissue samples from donors where postmortem evidence demonstrated AD neuropathology, but who presented normal cognition proximate to death. The observed changes further associated with modified ATP synthesis and mitochondrial transcripts, indicating metabolic relevance; accordingly, mass-spectrometry-derived lipidomic profiles distinguished between individuals with and without cognitive impairment prior to death. In spite of the limited group sizes, tissues from persons with both cognitive impairment and AD pathology showed elevation in several drug-targeted genes of other brain, vascular and autoimmune disorders, accompanied by pathology-related increases in distinct lipid processing transcripts, and in the RNA metabolism genes hnRNPH2, TARDBP, CLP1 and EWSR1. To further detect 3′-polyadenylation variants, we employed multiple cDNA primer pairs. This identified variants that showed limited differences in scope and length between the tested cohorts, yet enabled superior clustering of demented and non-demented AD brains versus controls compared to total mRNA expression values. Our findings indicate inter-related cognition-associated differences in AD's lipid processing, alternative splicing and 3′-polyadenylation, calling for pursuing the underlying psychological and therapeutics implications.

Tremor is a core feature of Parkinson's disease and the most easily recognized parkinsonian sign. Nonetheless, its pathophysiology remains poorly understood. Here, we show that multispectral spiking activity in the posterior-dorso-lateral oscillatory (motor) region of the subthalamic nucleus distinguishes resting tremor from the other Parkinsonian motor signs and strongly correlates with its severity. We evaluated microelectrode-spiking activity from the subthalamic dorsolateral oscillatory region of 70 Parkinson’s disease patients who underwent deep brain stimulation surgery (114 subthalamic nuclei, 166 electrode trajectories). We then investigated the relationship between patients’ clinical Unified Parkinson’s Disease Rating Scale score and their peak theta (4-7Hz) and beta (13-30Hz) powers. We found a positive correlation between resting tremor and theta activity (r = 0.41, p < 0.01) and a non-significant negative correlation with beta activity (r=-0.2, p = 0.5). Hypothesizing that the two neuronal frequencies mask each other’s relationship with resting tremor, we created a non-linear model of their proportional spectral powers and investigated its relationship with resting tremor. As hypothesized, patients' proportional scores correlated better than either theta or beta alone (r = 0.54, p < 0.001). However, theta and beta oscillations were frequently temporally correlated (38/70 patients manifested significant positive temporal correlations and 1/70 exhibited significant negative correlation between the two frequency bands). When comparing theta and beta temporal relationship (rθβ) to patients' resting tremor scores, we found a significant negative correlation between the two (r=-0.38, p < 0.01). Patients manifesting a positive correlation between the two bands (i.e., theta and beta were likely to appear simultaneously) were found to have lower resting tremor scores than those with near zero correlation values (i.e., theta and beta were likely to appear separately). We therefore created a new model incorporating patients' proportional theta-beta power and rθβ scores to obtain an improved neural correlate of resting tremor (r = 0.62, p < 0.001). We then used the Akaike and Bayesian information criteria for model selection and found the multispectral model, incorporating theta-beta proportional power and their correlation, to be the best fitting model, with 0.96 and 0.89 probabilities respectively. Here we found that as theta increases, beta decreases and the two appear separately – resting tremor is worsened. Our results therefore show that theta and beta convey information about resting tremor in opposite ways. Furthermore, the finding that theta and beta coactivity is negatively correlated with resting tremor suggests that theta-beta non-linear scale may be a valuable biomarker for Parkinson's resting tremor in future adaptive deep brain stimulation techniques.