Detection of Cognitive Impairment From eSAGE Metadata Using Machine Learning.

OBJECTIVE: Using the metadata collected in the digital version of the Self-Administered Gerocognitive Examination (eSAGE), we aim to improve the prediction of mild cognitive impairment (MCI) and dementia (DM) by applying machine learning methods. PATIENTS AND METHODS: A total of 66 patients had a diagnosis of normal cognition (NC), MCI, or DM, and eSAGE scores and metadata were used. eSAGE scores and metadata were obtained. Each eSAGE question was scored and behavioral features (metadata) such as the time spent on each test page, drawing speed, and average stroke length were extracted for each patient. Logistic regression (LR) and gradient boosting models were trained using these features to detect cognitive impairment (CI). Performance was evaluated using 10-fold cross-validation, with accuracy, precision, recall, F1 score, and receiver operating characteristic area under the curve (AUC) score as evaluation metrics. RESULTS: LR with feature selection achieved an AUC of 89.51%, a recall of 87.56%, and an F1 of 85.07% using both behavioral and scoring. LR using scores and metadata also achieved an AUC of 84.00% in detecting MCI from NC, and an AUC of 98.12% in detecting DM from NC. Average stroke length was particularly useful for prediction and when combined with 4 other scoring features, LR achieved an even better AUC of 92.06% in detecting CI. The study shows that eSAGE scores and metadata are predictive of CI. CONCLUSIONS: eSAGE scores and metadata are predictive of CI. With machine learning methods, the metadata could be combined with scores to enable more accurate detection of CI.

Potential Neuroprotective Effects of Dietary Omega-3 Fatty Acids on Stress in Alzheimer's Disease.

BACKGROUND: A large number of individual potentially modifiable factors are associated with risk for Alzheimer's disease (AD). However, less is known about the interactions between the individual factors. METHODS: In order to begin to examine the relationship between a pair of factors, we performed a pilot study, surveying patients with AD and controls for stress exposure and dietary omega-3 fatty acid intake to explore their relationship for risk of AD. RESULTS: For individuals with the greatest stress exposure, omega-3 fatty acid intake was significantly greater in healthy controls than in AD patients. There was no difference among those with low stress exposure. CONCLUSIONS: These initial results begin to suggest that omega-3 fatty acids may mitigate AD risk in the setting of greater stress exposure. This will need to be examined with larger populations and other pairs of risk factors to better understand these important relationships. Examining how individual risk factors interact will ultimately be important for learning how to optimally decrease the risk of AD.

Explainable machine learning aggregates polygenic risk scores and electronic health records for Alzheimer's disease prediction.

Alzheimer's disease (AD) is the most common late-onset neurodegenerative disorder. Identifying individuals at increased risk of developing AD is important for early intervention. Using data from the Alzheimer Disease Genetics Consortium, we constructed polygenic risk scores (PRSs) for AD and age-at-onset (AAO) of AD for the UK Biobank participants. We then built machine learning (ML) models for predicting development of AD, and explored feature importance among PRSs, conventional risk factors, and ICD-10 codes from electronic health records, a total of > 11,000 features using the UK Biobank dataset. We used eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), which provided superior ML performance as well as aided ML model explanation. For participants age 40 and older, the area under the curve for AD was 0.88. For subjects of age 65 and older (late-onset AD), PRSs were the most important predictors. This is the first observation that PRSs constructed from the AD risk and AAO play more important roles than age in predicting AD. The ML model also identified important predictors from EHR, including urinary tract infection, syncope and collapse, chest pain, disorientation and hypercholesterolemia, for developing AD. Our ML model improved the accuracy of AD risk prediction by efficiently exploring numerous predictors and identified novel feature patterns.

Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer's disease.

Human middle temporal gyrus (MTG) is a vulnerable brain region in early Alzheimer's disease (AD), but little is known about the molecular mechanisms underlying this regional vulnerability. Here we utilize the 10 × Visium platform to define the spatial transcriptomic profile in both AD and control (CT) MTG. We identify unique marker genes for cortical layers and the white matter, and layer-specific differentially expressed genes (DEGs) in human AD compared to CT. Deconvolution of the Visium spots showcases the significant difference in particular cell types among cortical layers and the white matter. Gene co-expression analyses reveal eight gene modules, four of which have significantly altered co-expression patterns in the presence of AD pathology. The co-expression patterns of hub genes and enriched pathways in the presence of AD pathology indicate an important role of cell-cell-communications among microglia, oligodendrocytes, astrocytes, and neurons, which may contribute to the cellular and regional vulnerability in early AD. Using single-molecule fluorescent in situ hybridization, we validated the cell-type-specific expression of three novel DEGs (e.g., KIF5A, PAQR6, and SLC1A3) and eleven previously reported DEGs associated with AD pathology (i.e., amyloid beta plaques and intraneuronal neurofibrillary tangles or neuropil threads) at the single cell level. Our results may contribute to the understanding of the complex architecture and neuronal and glial response to AD pathology of this vulnerable brain region.

Wolframin is a novel regulator of tau pathology and neurodegeneration.

Selective neuronal vulnerability to protein aggregation is found in many neurodegenerative diseases including Alzheimer's disease (AD). Understanding the molecular origins of this selective vulnerability is, therefore, of fundamental importance. Tau protein aggregates have been found in Wolframin (WFS1)-expressing excitatory neurons in the entorhinal cortex, one of the earliest affected regions in AD. The role of WFS1 in Tauopathies and its levels in tau pathology-associated neurodegeneration, however, is largely unknown. Here we report that WFS1 deficiency is associated with increased tau pathology and neurodegeneration, whereas overexpression of WFS1 reduces those changes. We also find that WFS1 interacts with tau protein and controls the susceptibility to tau pathology. Furthermore, chronic ER stress and autophagy-lysosome pathway (ALP)-associated genes are enriched in WFS1-high excitatory neurons in human AD at early Braak stages. The protein levels of ER stress and autophagy-lysosome pathway (ALP)-associated proteins are changed in tau transgenic mice with WFS1 deficiency, while overexpression of WFS1 reverses those changes. This work demonstrates a possible role for WFS1 in the regulation of tau pathology and neurodegeneration via chronic ER stress and the downstream ALP. Our findings provide insights into mechanisms that underpin selective neuronal vulnerability, and for developing new therapeutics to protect vulnerable neurons in AD.

Discriminating memory disordered patients from controls using diffusion model parameters from recognition memory.

One hundred and five memory disordered (MD) patients and 57 controls were tested on item recognition memory and lexical decision tasks, and diffusion model analyses were conducted on accuracy and response time distributions for correct and error responses. The diffusion model fit the data well for the MD patients and control subjects, the results replicated earlier studies with young and older adults, and individual differences were consistent between the item recognition and lexical decision tasks. In the diffusion model analysis, MD patients had lower drift rates (with mild Alzheimer's [AD] patients lower than mild cognitive impairment [MCI] patients) as well as wider boundaries and longer nondecision times. These data and results were used in a series of studies to examine how well MD patients could be discriminated from controls using machine-learning techniques, linear discriminant analysis, logistic regression, and support vector machines (all of which produced similar results). There was about 83% accuracy in separating MD from controls, and within the MD group, AD patients had about 90% accuracy and MCI patients had about 68% accuracy (controls had about 90% accuracy). These methods might offer an adjunct to traditional clinical diagnosis. Limitations are noted including difficulties in obtaining a matched group of control subjects as well as the possibility of misdiagnosis of MD patients. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Treating the most vulnerable: A discursive review of experimental pain in Alzheimer's disease.

AIM: The purpose of this manuscript is to summarize research on how experimental pain is experienced by adults with Alzheimer's disease (AD) and to translate results into implications for nurses. DESIGN: This discursive review synthesizes the results of three previous research studies exploring experimental pain in adults with AD. METHODS: Using a series of fictional clinical vignettes, the authors discuss how the results from three previous papers using acute experimental pain can potentially be translated into clinical practice. The authors also introduce the reader to the concept of research-related psychophysics using introductory definitions and concepts with the impetus to encourage other nurses to consider this research methodology. RESULTS: Pain characteristics in AD that differ from cognitively intact controls must be explored to properly address pain in this population. Nurses are well positioned to address these issues in order to provide a high quality of care to adults with AD.

Self-Administered Gerocognitive Examination: longitudinal cohort testing for the early detection of dementia conversion.

BACKGROUND: Significant cognitive changes as individuals' age are not being identified in a timely manner, delaying diagnosis and treatments. Use of brief, multi-domain, self-administered, objective cognitive assessment tools may remove some barriers in assessing and identifying cognitive changes. We compared longitudinal Self-Administered Gerocognitive Examination (SAGE) test scores to non-self-administered Mini-Mental State Examination (MMSE) scores in 5 different diagnostic subgroups. METHODS: A cohort study evaluating annual rates of change was performed on 665 consecutive patients from Ohio State University Memory Disorders Clinic. Patients with at least two visits 6 months apart evaluated with SAGE and MMSE and classified according to standard clinical criteria as subjective cognitive decline (SCD), mild cognitive impairment (MCI), or Alzheimer's disease (AD) dementia were included. The pattern of change in SAGE scores was compared to MMSE. One way and repeated measures ANOVA and linear regression models were used. RESULTS: Four hundred twenty-four individuals (40 SCD, 94 MCI non-converters to dementia, 70 MCI converters to dementia (49 to AD dementia and 21 to non-AD dementia), 220 AD dementia) met inclusion criteria. SAGE and MMSE scores declined respectively at annual rates of 1.91 points/year (p < 0.0001) and 1.68 points/year (p < 0.0001) for MCI converters to AD dementia, and 1.82 points/year (p < 0.0001) and 2.38 points/year (p < 0.0001) for AD dementia subjects. SAGE and MMSE scores remained stable for SCD and MCI non-converters. Statistically significant decline from baseline scores in SAGE occurred at least 6 months earlier than MMSE for MCI converters to AD dementia (14.4 vs. 20.4 months), MCI converters to non-AD dementia (14.4 vs. 32.9 months), and AD dementia individuals (8.3 vs. 14.4 months). CONCLUSIONS: SAGE detects MCI conversion to dementia at least 6 months sooner than MMSE. Being self-administered, SAGE also addresses a critical need of removing some barriers in performing cognitive assessments. Limitations of our single-site cohort study include potential referral and sampling biases. Repetitively administering SAGE and identifying stability or decline may provide clinicians with an objective cognitive biomarker impacting evaluation and management choices.

The Effect of Donepezil on Problem-solving Ability in Individuals With Amnestic Mild Cognitive Impairment: A Pilot Study.

BACKGROUND: Clinical trials involving individuals with mild cognitive impairment (MCI) have reported mixed results for the effects of cholinesterase inhibitors on cognitive outcomes. Our previous work demonstrated that a visuospatial problem-solving task was sensitive to non-memory impairments in individuals with MCI. OBJECTIVE: To determine whether the same task is also sensitive to the effects of cholinesterase inhibitors in individuals with amnestic MCI (aMCI). METHOD: We gave 22 individuals with aMCI (clinical dementia rating of 0.5) and Mini-Mental State Examination (MMSE) scores of at least 24 the following measures at baseline and at follow-up 1 year later: Hopkins Verbal Learning Test, Boston Naming Test, Rey Complex Figures Test copying task, anagrams task, and visuospatial problem-solving task. The MMSE was also given at the 1-year follow-up. Twelve of the individuals were drug naïve, having never taken cholinesterase inhibitors before, and donepezil was initiated and titrated to 10 mg daily after baseline in an open-label manner. Ten of the individuals had already been taking donepezil, and there was no change in treatment. We compared the two groups for amount of performance change over 1 year. RESULTS: Individuals for whom donepezil was initiated performed significantly better on the visuospatial problem-solving task after 1 year compared with individuals who had already been taking donepezil. No difference was observed for any of the other variables. CONCLUSION: The visuospatial problem-solving task appeared to be more sensitive than memory measures to the effects of cholinesterase inhibitors in individuals with aMCI, perhaps due to the high attentional demand of the task.

Immediate effects of treadmill walking in individuals with Lewy body dementia and Huntington's disease.

BACKGROUND: Treadmill training may improve gait disorders associated with neurodegenerative diseases. In Parkinson's disease (PD), treadmill training alters gait patterns after one session, and long-term training improves gait parameters, fall risk, and quality of life. RESEARCH QUESTION: What is the feasibility and safety of using this intervention for people with Lewy body dementia (LBD) or Huntington's disease (HD)? METHODS: In this observational study, 10 individuals with HD, 8 individuals with LBD, and 10 control individuals walked for 20 min on a treadmill using a speed dependent protocol starting at a slow comfortable speed and increasing incrementally toward their normal overground speed. Feasibility was determined by compliance to protocol and safety by no incidents of abnormal vital signs or expressions of distress. Changes in gait measures, Timed Up and Go (TUG) scores and quantitative motor function measures (Q-Motor; precision grasp force variability, finger and foot tapping frequency) before and after treadmill walking were analyzed using linear models. RESULTS: Treadmill training is feasible and safe in LBD and HD; although, participants could not initiate treadmill walking at their comfortable overground speeds, and only 3 participants with HD were able to achieve their overground walking speed within the 20-minute session. No changes in gait measures, TUG times, and Q-Motor measures were found among LBD and HD participants after treadmill walking, although control participants demonstrated significant increases in several gait measures, and foot tap frequency (estimated difference = 0.290; p = 0.026). SIGNIFICANCE: Longer and more frequent treadmill sessions may be needed to see gait and motor function effects in LBD and HD. Motor and cognitive impairments associated with these diseases may make them less amenable to the effects of treadmill training.

Fluid and Tissue Biomarkers of Lewy Body Dementia: Report of an LBDA Symposium.

The Lewy Body Dementia Association (LBDA) held a virtual event, the LBDA Biofluid/Tissue Biomarker Symposium, on January 25, 2021, to present advances in biomarkers for Lewy body dementia (LBD), which includes dementia with Lewy bodies (DLBs) and Parkinson's disease dementia (PDD). The meeting featured eight internationally known scientists from Europe and the United States and attracted over 200 scientists and physicians from academic centers, the National Institutes of Health, and the pharmaceutical industry. Methods for confirming and quantifying the presence of Lewy body and Alzheimer's pathology and novel biomarkers were discussed.

Race-Related Differences Between and Within Sex to Experimental Thermal Pain in Middle and Older Adulthood: An Exploratory Pilot Analysis.

This brief report details a pilot analysis conducted to explore racial differences in pain sensitivity and unpleasantness between cognitively healthy Black and White adults, stratified by sex. A total of 24 cognitively healthy adults (12 Black and 12 White) from two completed studies were matched by age and sex, and divided into two groups based on race. Stratified analyses by sex demonstrated that Black females reported experiencing pain intensity ratings of all three intensity sensations at lower temperatures than White females. These findings will inform future research studies to determine if these results hold true in a fully-powered sample and should include mixed methodologies, incorporating neuroimaging data to further assess this phenomenon. Improving pain assessment and management across racial/ethnic groups will help healthcare providers such as nurses and physicians to ensure optimal quality of life for all.

Mindfulness in Motion and Dietary Approaches to Stop Hypertension (DASH) in Hypertensive African Americans.

OBJECTIVES: Hypertension increases the risk of developing Alzheimer's disease or related dementias. This pilot study's purpose was to examine the feasibility and acceptability of a novel intervention, Mindfulness in Motion (MIM) and Dietary Approaches to Stop Hypertension DASH (MIM DASH), to improve diet, mindfulness, stress, and systolic blood pressure (BP) in older African Americans with mild cognitive impairment (MCI) and hypertension. DESIGN: Cluster randomized controlled trial. SETTING: Intergenerational community center in a large metropolitan area. PARTICIPANTS: African Americans with MCI and hypertension. Participants were divided into six groups randomized 1:1:1 to the MIM DASH group, attention only (non-hypertensive education) group, or true control group. The MIM DASH and attention only interventions were delivered in 8-weekly 2 hour group sessions. MIM included mindful movements from chair/standing, breathing exercises, and guided meditation. The DASH component used a critical thinking approach of problem solving, goal setting, reflection, and self-efficacy. The true control group received a DASH pamphlet at the end. MEASUREMENTS: Feasibility was tracked through enrollment and attendance records; acceptability was assessed through interviews. Blood pressure was measured using the Omron HEM-907XL Monitor. Dietary intake was measured by DASH-Q. Mindfulness was measured by the Cognitive and Affective Mindfulness Scale. Stress was measured by the Perceived Stress Scale. MCI was determined using the Self-Administered Gerocognitive Examination. Data were collected at baseline and 3-months. RESULTS: Median session attendance was six for the MIM DASH group and six for the attention only group. There were no changes in diet, mindfulness, or stress. There was a clinically significant reduction in systolic BP in the MIM DASH group (-7.2 mmHg) relative to the attention only group (-.7), and no change between the MIM DASH and true control groups. CONCLUSION: Results indicate that the MIM DASH intervention was feasible and culturally acceptable in African Americans with hypertension and MCI.

Alpha-synuclein mRNA isoform formation and translation affected by polymorphism in the human SNCA 3'UTR.

BACKGROUND: Multiple variants in SNCA, encoding alpha-synuclein, a main component of Lewy bodies, are implicated in Parkinson's disease. METHODS: We searched for cis-acting SNCA variants using allelic mRNA ratios in human brain tissues. In a SNCA 3'UTR (2,520 bp) luciferase reporter gene assay, translation in SH-SY5Y cells in the presence of the rs17016074 G/A alleles was measured. To assess clinical impact, we queried neurocognitive genome-wide association studies. RESULTS: Allelic ratios deviated up to twofold, measured at a marker SNP in the middle of a long 3' untranslated region (3'UTR), but not at a marker at its start, suggesting regulation of 3'UTR processing. 3'UTR SNP rs17016074 G/A, minor allele frequency (MAF) <1% in Caucasians, 13% in Africans, strongly associates with large allelic mRNA expression imbalance (AEI), resulting in reduced expression of long 3'UTR isoforms. A second 3'UTR SNP (rs356165) associates with moderate AEI and enhances SNCA mRNA expression. The rs17016074 A allele reduces overall 3'UTR expression in luciferase reporter gene assays but supports more efficient translation, resolving previous contradictory results. We failed to detect significant genome-wide associations for rs17016074, possibly a result of low MAF in Caucasians or its absence from most genotyping panels. In the "Genome Wide Association Study of Yoruba in Nigeria," rs356165 was associated with reduced memory performance. CONCLUSIONS: Here, we identify two cis-acting regulatory variants affecting SNCA mRNA expression, measured by allelic ratios in the 3'UTR. The rs17016074 minor A allele is associated with higher expression of luciferase protein activity. Resolving the genetic influence of SNCA polymorphisms requires study of the interactions between multiple regulatory variants with distinct frequencies among populations.

Deep Brain Stimulation of Frontal Lobe Networks to Treat Alzheimer's Disease.

The study objective was to evaluate the safety and efficacy of deep brain stimulation (DBS) at the ventral capsule/ventral striatum (VC/VS) region to specifically modulate frontal lobe behavioral and cognitive networks as a novel treatment approach for Alzheimer's disease (AD) patients. This is a non-randomized phase I prospective open label interventional trial of three subjects with matched comparison groups. AD participants given DBS for at least 18 months at the VC/VS target were compared on the Clinical Dementia Rating-Sum of Boxes (CDR-SB), our primary outcome clinical measure, to matched groups without DBS from the AD Neuroimaging Initiative (ADNI) cohort. Serial 2-Deoxy-2-[18F]fluoro-D-glucose (FDG) positron emission tomography (PET) images of AD participants were also compared longitudinally over time. Three AD DBS participants were matched to subjects from the ADNI cohort. All participants tolerated DBS well without significant adverse events. All three AD DBS participants had less performance decline and two of them meaningfully less decline over time on our primary outcome measure, CDR-SB, relative to matched comparison groups from the ADNI using score trajectory slopes. Minimal changes or increased metabolism on FDG-PET were seen in frontal cortical regions after chronic DBS at the VC/VS target. The first use of DBS in AD at a frontal lobe behavior regulation target (VC/VS) was well-tolerated and revealed less performance decline in CDR-SB. Frontal network modulation to improve executive and behavioral deficits should be furthered studied in AD.

Computational integration of nanoscale physical biomarkers and cognitive assessments for Alzheimer's disease diagnosis and prognosis.

With the increasing prevalence of Alzheimer's disease (AD), significant efforts have been directed toward developing novel diagnostics and biomarkers that can enhance AD detection and management. AD affects the cognition, behavior, function, and physiology of patients through mechanisms that are still being elucidated. Current AD diagnosis is contingent on evaluating which symptoms and signs a patient does or does not display. Concerns have been raised that AD diagnosis may be affected by how those measurements are analyzed. Unbiased means of diagnosing AD using computational algorithms that integrate multidisciplinary inputs, ranging from nanoscale biomarkers to cognitive assessments, and integrating both biochemical and physical changes may provide solutions to these limitations due to lack of understanding for the dynamic progress of the disease coupled with multiple symptoms in multiscale. We show that nanoscale physical properties of protein aggregates from the cerebral spinal fluid and blood of patients are altered during AD pathogenesis and that these properties can be used as a new class of "physical biomarkers." Using a computational algorithm, developed to integrate these biomarkers and cognitive assessments, we demonstrate an approach to impartially diagnose AD and predict its progression. Real-time diagnostic updates of progression could be made on the basis of the changes in the physical biomarkers and the cognitive assessment scores of patients over time. Additionally, the Nyquist-Shannon sampling theorem was used to determine the minimum number of necessary patient checkups to effectively predict disease progression. This integrated computational approach can generate patient-specific, personalized signatures for AD diagnosis and prognosis.

Digitally translated Self-Administered Gerocognitive Examination (eSAGE): relationship with its validated paper version, neuropsychological evaluations, and clinical assessments.

BACKGROUND: The original paper Self-Administered Gerocognitive Examination (SAGE) is a valid and reliable cognitive assessment tool used to identify individuals with mild cognitive impairment (MCI) or early dementia. We evaluated identical test questions in a digital format (eSAGE) made for tablet use with the goals of calibrating it against SAGE and establishing its association with other neuropsychological tests and clinical assessments of cognitive impairment. METHODS: Subjects aged 50 and over who had taken SAGE were recruited from community and clinic settings. Subjects were randomly selected to participate in a clinical evaluation including neuropsychological evaluations. SAGE and eSAGE were administered using a crossover design. Subjects were identified as dementia, MCI, or normal based on standard clinical criteria. Associations were investigated using Spearman correlations, linear regression, and sensitivity and specificity measures. RESULTS: Of the 426 subjects screened, 66 completed the evaluation. eSAGE score correlation to a battery of neuropsychological tests was 0.73 (p < 0.0001) with no significant difference between the paper and digital format. Spearman correlation of SAGE versus eSAGE was 0.88 (p < 0.0001), and they are related by the formula: eSAGE score = -1.05 + 0.99 × SAGE score. Since the slope is very close to 1 (p = 0.86) there is strong evidence that the scaling is identical between eSAGE and SAGE, with no scale bias. Overall, eSAGE scores are lower by an average of 1.21 and the decrease is statistically significant (p < 0.0001). For those subjects familiar with smartphones or tablets (one measure of digital proficiency), eSAGE scores are lower by an average of 0.83 points (p = 0.029). With a score 16 and higher being classified as normal, eSAGE had 90% specificity and 71% sensitivity in detecting those with cognitive impairment from normal subjects. CONCLUSIONS: Tablet-based eSAGE shows a strong association with the validated paper SAGE and a neuropsychological battery. It shows no scale bias compared to SAGE. Both have the advantage of self-administration, brevity, four interchangeable forms, and high sensitivity and specificity in detecting cognitive impairment from normal subjects. Their potential widespread availability will be a major factor in overcoming the many obstacles in identifying early cognitive changes. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02544074 . Registered on 18 March 2015.

Gene expression profiling of brain samples from patients with Lewy body dementia.

Dementia with Lewy Bodies (DLB) is the second most common neurodegenerative disorder in the elderly. The development and progression of DLB remain unclear. In this study we used next generation sequencing to assess RNA expression profiles and cellular processes associated with DLB in the anterior cingulate cortex, a brain region affected by DLB pathology. The expression measurements were made in autopsy brain tissues from 8 DLB subjects and 10 age-matched controls using AmpliSeq technology with ion torrent sequencing. The analysis of RNA expression profiles revealed 490 differentially expressed genes, among which 367 genes were down-regulated and 123 were up-regulated. Functional enrichment analysis of genes differentially expressed in DLB indicated downregulation of genes associated with myelination, neurogenesis, and regulation of nervous system development. miRNA binding sites enriched in these mRNAs yielded a list of candidate miRNAs participating in DLB pathophysiology. Our study provides a comprehensive picture of gene expression landscape in DLB, identifying key cellular processes associated with DLB pathology.