Emerging Therapeutic Potential of Fluoxetine on Cognitive Decline in Alzheimer's Disease: Systematic Review.

Fluoxetine, a commonly prescribed medication for depression, has been studied in Alzheimer's disease (AD) patients for its effectiveness on cognitive symptoms. The aim of this systematic review is to investigate the therapeutic potential of fluoxetine in cognitive decline in AD, focusing on its anti-degenerative mechanisms of action and clinical implications. According to PRISMA, we searched MEDLINE, up to 1 April 2024, for animal and human studies examining the efficacy of fluoxetine with regard to the recovery of cognitive function in AD. Methodological quality was evaluated using the ARRIVE tool for animal AD studies and the Cochrane tool for clinical trials. In total, 22 studies were analyzed (19 animal AD studies and 3 clinical studies). Fluoxetine promoted neurogenesis and enhanced synaptic plasticity in preclinical models of AD, through a decrease in Aß pathology and increase in BDNF, by activating diverse pathways (such as the DAF-16-mediated, TGF-beta1, ILK-AKT-GSK3beta, and CREB/p-CREB/BDNF). In addition, fluoxetine has anti-inflammatory properties/antioxidant effects via targeting antioxidant Nrf2/HO-1 and hindering TLR4/NLRP3 inflammasome. Only three clinical studies showed that fluoxetine ameliorated the cognitive performance of people with AD; however, several methodological issues limited the generalizability of these results. Overall, the high-quality preclinical evidence suggests that fluoxetine may have neuroprotective, antioxidant, and anti-inflammatory effects in AD animal models. While more high-quality clinical research is needed to fully understand the mechanisms underlying these effects, fluoxetine is a promising potential treatment for AD patients. If future clinical trials confirm its anti-degenerative and neuroprotective effects, fluoxetine could offer a new therapeutic approach for slowing down the progression of AD.

Non-Motor Disorders in Parkinson Disease and Other Parkinsonian Syndromes.

Parkinsonism is an umbrella term that refers to multisystemic neurodegenerative disorders characterized by a broad spectrum of motor and non-motor symptoms (NMSs) [...].

An Artificial Neural Network Predicts Gender Differences of Motor and Non-Motor Symptoms of Patients with Advanced Parkinson's Disease under Levodopa-Carbidopa Intestinal Gel.

Background and Objectives: Currently, no tool exists to predict clinical outcomes in patients with advanced Parkinson's disease (PD) under levodopa-carbidopa intestinal gel (LCIG) treatment. The aim of this study was to develop a novel deep neural network model to predict the clinical outcomes of patients with advanced PD after two years of LCIG therapy. Materials and Methods: This was a longitudinal, 24-month observational study of 59 patients with advanced PD in a multicenter registry under LCIG treatment from September 2019 to September 2021, including 43 movement disorder centers. The data set includes 649 measurements of patients, which make an irregular time series, and they are turned into regular time series during the preprocessing phase. Motor status was assessed with the Unified Parkinson's Disease Rating Scale (UPDRS) Parts III (off) and IV. The NMS was assessed by the NMS Questionnaire (NMSQ) and the Geriatric Depression Scale (GDS), the quality of life by PDQ-39, and severity by Hoehn and Yahr (HY). Multivariate linear regression, ARIMA, SARIMA, and Long Short-Term Memory-Recurrent NeuralNetwork (LSTM-RNN) models were used. Results: LCIG significantly improved dyskinesia duration and quality of life, with men experiencing a 19% and women a 10% greater improvement, respectively. Multivariate linear regression models showed that UPDRS-III decreased by 1.5 and 4.39 units per one-unit increase in the PDQ-39 and UPDRS-IV indexes, respectively. Although the ARIMA-(2,0,2) model is the best one with AIC criterion 101.8 and validation criteria MAE = 0.25, RMSE = 0.59, and RS = 0.49, it failed to predict PD patients' features over a long period of time. Among all the time series models, the LSTM-RNN model predicts these clinical characteristics with the highest accuracy (MAE = 0.057, RMSE = 0.079, RS = 0.0053, mean square error = 0.0069). Conclusions: The LSTM-RNN model predicts, with the highest accuracy, gender-dependent clinical outcomes in patients with advanced PD after two years of LCIG therapy.

Mild Behavioral Impairment in Parkinson's Disease: An Updated Review on the Clinical, Genetic, Neuroanatomical, and Pathophysiological Aspects.

Neuropsychiatric symptoms (NPS), including depression, anxiety, apathy, visual hallucinations, and impulse control disorders, are very common during the course of Parkinson's disease (PD), occurring even at the prodromal and premotor stages. Mild behavioral impairment (MBI) represents a recently described neurobehavioral syndrome, characterized by the emergence of persistent and impactful NPS in later life, reflecting arisk of dementia. Accumulating evidence suggests that MBI is highly prevalent in non-demented patients with PD, also being associated with an advanced disease stage, more severe motor deficits, as well as global and multiple-domain cognitive impairment. Neuroimaging studies have revealed that MBI in patients with PD may be related todistinct patterns of brain atrophy, altered neuronal connectivity, and distribution of dopamine transporter (DAT) depletion, shedding more light on its pathophysiological background. Genetic studies in PD patients have also shown that specific single-nucleotide polymorphisms (SNPs) may be associated with MBI, paving the way for future research in this field. In this review, we summarize and critically discuss the emerging evidence on the frequency, associated clinical and genetic factors, as well as neuroanatomical and neurophysiological correlates of MBI in PD, aiming to elucidate the underlying pathophysiology and its potential role as an early "marker" of cognitive decline, particularly in this population. In addition, we aim to identify research gaps, and propose novel relative areas of interest that could aid in our better understanding of the relationship of this newly defined diagnostic entity with PD.

First-line disease modifying treatments in pediatric-onset multiple sclerosis in Greece: therapy initiation at more advanced age is the main cause of treatment failure, in a retrospective observational study, with a cohort from a single Multiple Sclerosis Center.

OBJECTIVES: Long-term immunomodulatory therapy of pediatric onset-multiple sclerosis (POMS) is based mainly on published case series and internationally agreed guidelines. Relevant studies in the Greek population are absent from the literature. The purpose of this study is to present data on the efficacy and safety of the 1st line immunomodulatory drugs in the treatment of POMS patients. MATERIALS AND METHODS: The present study included 27 patients meeting the IPMSSG criteria for POMS and who are monitored at the outpatient clinic of the Multiple Sclerosis and Demyelinating Diseases Unit (MSDDU), of the 1st Neurological Department, University Hospital of Aeginition. All patients received 1st line immunomodulatory drugs as initial therapy. Clinical, laboratory, and imaging parameters of the disease were recorded before and after treatment. RESULTS: Post-treatment, a significant reduction of the relapse number (mean ± SD: 2.0 ± 1.0 vs 1.2 ± 1.6, p = 0.002), EDSS progression (mean ± SD: 1.5 ± 0.8 vs 0.9 ± 0.7, p = 0.005) and ARR (mean ± SD: 1.5 ± 0.7 vs 0.4 ± 0.5, p = 0.0001) was observed, while no changes were observed in the EDSS score, (mean ± SD: 1.8 ± 0.6 vs 1.9. 0.6, p = 0.60). Advanced age at treatment initiation increased the risk for drug discontinuation before 24 months of therapy (HR = 0.6, 95% CI (0.35-0.99), p = 0.04). CONCLUSIONS: Most pediatric patients are forced to switch to either more efficacious 1st line or 2nd line drugs. Additionally, our study suggests that older age at the time of the 1st line treatment initiation, contributes to earlier drug discontinuation.

Mobile App Interventions for Parkinson's Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review.

Central nervous system diseases (CNSDs) lead to significant disability worldwide. Mobile app interventions have recently shown the potential to facilitate monitoring and medical management of patients with CNSDs. In this direction, the characteristics of the mobile apps used in research studies and their level of clinical effectiveness need to be explored in order to advance the multidisciplinary research required in the field of mobile app interventions for CNSDs. A systematic review of mobile app interventions for three major CNSDs, i.e., Parkinson's disease (PD), multiple sclerosis (MS), and stroke, which impose significant burden on people and health care systems around the globe, is presented. A literature search in the bibliographic databases of PubMed and Scopus was performed. Identified studies were assessed in terms of quality, and synthesized according to target disease, mobile app characteristics, study design and outcomes. Overall, 21 studies were included in the review. A total of 3 studies targeted PD (14%), 4 studies targeted MS (19%), and 14 studies targeted stroke (67%). Most studies presented a weak-to-moderate methodological quality. Study samples were small, with 15 studies (71%) including less than 50 participants, and only 4 studies (19%) reporting a study duration of 6 months or more. The majority of the mobile apps focused on exercise and physical rehabilitation. In total, 16 studies (76%) reported positive outcomes related to physical activity and motor function, cognition, quality of life, and education, whereas 5 studies (24%) clearly reported no difference compared to usual care. Mobile app interventions are promising to improve outcomes concerning patient's physical activity, motor ability, cognition, quality of life and education for patients with PD, MS, and Stroke. However, rigorous studies are required to demonstrate robust evidence of their clinical effectiveness.

Genetics of Multiple System Atrophy and Progressive Supranuclear Palsy: A Systemized Review of the Literature.

Multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) are uncommon multifactorial atypical Parkinsonian syndromes, expressed by various clinical features. MSA and PSP are commonly considered sporadic neurodegenerative disorders; however, our understanding is improving of their genetic framework. The purpose of this study was to critically review the genetics of MSA and PSP and their involvement in the pathogenesis. A systemized literature search of PubMed and MEDLINE was performed up to 1 January 2023. Narrative synthesis of the results was undertaken. In total, 43 studies were analyzed. Although familial MSA cases have been reported, the hereditary nature could not be demonstrated. COQ2 mutations were involved in familial and sporadic MSA, without being reproduced in various clinical populations. In terms of the genetics of the cohort, synuclein alpha (SNCA) polymorphisms were correlated with an elevated likelihood of manifesting MSA in Caucasians, but a causal effect relationship could not be demonstrated. Fifteen MAPT mutations were linked with PSP. Leucine-rich repeat kinase 2 (LRRK2) is an infrequent monogenic mutation of PSP. Dynactin subunit 1 (DCTN1) mutations may imitate the PSP phenotype. GWAS have noted many risk loci of PSP (STX6 and EIF2AK3), suggesting pathogenetic mechanisms related to PSP. Despite the limited evidence, it seems that genetics influence the susceptibility to MSA and PSP. MAPT mutations result in the MSA and PSP pathologies. Further studies are crucial to elucidate the pathogeneses of MSA and PSP, which will support efforts to develop novel drug options.

Cognitive Impairment in Parkinson's Disease: An Updated Overview Focusing on Emerging Pharmaceutical Treatment Approaches.

Cognitive impairment in patients with Parkinson's disease (PD) is one of the commonest and most disabling non-motor manifestations during the course of the disease. The clinical spectrum of PD-related cognitive impairment includes subjective cognitive decline (SCD), mild cognitive impairment (MCI) and PD dementia (PDD). As the disease progresses, cognitive decline creates a significant burden for the family members and/or caregivers of patients with PD, and has a great impact on quality of life. Current pharmacological treatments have demonstrated partial efficacy and failed to halt disease progression, and novel, effective, and safe therapeutic strategies are required. Accumulating preclinical and clinical evidence shows that several agents may provide beneficial effects on patients with PD and cognitive impairment, including ceftriaxone, ambroxol, intranasal insulin, nilotinib, atomoxetine, mevidalen, blarcamesine, prasinezumab, SYN120, ENT-01, NYX-458, GRF6021, fosgonimeton, INT-777, Neuropeptide S, silibinin, osmotin, cordycepin, huperzine A, fibroblast growth factor 21, Poloxamer 188, ginsenoside Rb1, thioredoxin-1, tangeretin, istradefylline and Eugenia uniflora. Potential underlying mechanisms include the inhibition of a-synuclein aggregation, the improvement of mitochondrial function, the regulation of synaptic plasticity, an impact on the gut-brain axis, the modulation of neuroinflammation and the upregulation of neurotrophic factors, as well as cholinergic, dopaminergic, serotoninergic and norepinephrine neurotransmission. In this updated overview, we aim to cover the clinical aspects of the spectrum of PD-related cognitive impairment and discuss recent evidence on emerging treatment approaches that are under investigation at a preclinical and clinical level. Finally, we aim to provide additional insights and propose new ideas for investigation that may be feasible and effective for the spectrum of PD-related cognitive impairment.

Ambiental Factors in Parkinson's Disease Progression: A Systematic Review.

Background and Objectives: So far, there is little evidence of the ambient effect on motor and non-motor symptoms of Parkinson's Disease (PD). This systematic review aimed to determine the association between ambiental factors and the progression of PD. Materials and Methods: A systematic literature search of PubMed, Cochrane, Embase, and Web of Science was conducted up to 21 December 2021 according the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Eight articles were used in the analyses. Long-term exposure to fine particles (particulate matter ≤ 2.5 µm; PM2.5) was positively associated with disease aggravation in two studies. Short-term PM2.5 exposure was positively associated with disease aggravation in three studies. Significant associations were found between PD aggravation and NO2, SO2, CO, nitrate and organic matter (OM) concentrations in two studies. Associations were more pronounced, without reaching statistical significance however, in women, patients over 65 years old and cold temperatures. A 1% increase in temperature was associated with a significant 0.18% increase in Levodopa Equivalent Dose (LED). Ultraviolet light and humidity were not significantly associated with an increase in LED. There was no difference in hallucination severity with changing seasons. There was no evidence for seasonal fluctuation in Unified Parkinson's Disease Rating Scale (UPDRS) scores. Conclusions: There is a link between air pollutants and temperature for PD progression, but this has yet to be proven. More longitudinal studies are warranted to confirm these findings.

Genetic Insights into the Molecular Pathophysiology of Depression in Parkinson's Disease.

Background and Objectives: Parkinson's disease (PD) is a clinically heterogeneous disorder with poorly understood pathological contributing factors. Depression presents one of the most frequent non-motor PD manifestations, and several genetic polymorphisms have been suggested that could affect the depression risk in PD. Therefore, in this review we have collected recent studies addressing the role of genetic factors in the development of depression in PD, aiming to gain insights into its molecular pathobiology and enable the future development of targeted and effective treatment strategies. Materials and Methods: we have searched PubMed and Scopus databases for peer-reviewed research articles published in English (pre-clinical and clinical studies as well as relevant reviews and meta-analyses) investigating the genetic architecture and pathophysiology of PD depression. Results: in particular, polymorphisms in genes related to the serotoninergic pathway (sodium-dependent serotonin transporter gene, SLC6A4, tryptophan hydrolase-2 gene, TPH2), dopamine metabolism and neurotransmission (dopamine receptor D3 gene, DRD3, aldehyde dehydrogenase 2 gene, ALDH2), neurotrophic factors (brain-derived neurotrophic factor gene, BDNF), endocannabinoid system (cannabinoid receptor gene, CNR1), circadian rhythm (thyrotroph embryonic factor gene, TEF), the sodium-dependent neutral amino acid transporter B(0)AT2 gene, SLC6A15), and PARK16 genetic locus were detected as altering susceptibility to depression among PD patients. However, polymorphisms in the dopamine transporter gene (SLC6A3), monoamine oxidase A (MAOA) and B (MAOB) genes, catechol-O-methyltransferase gene (COMT), CRY1, and CRY2 have not been related to PD depression. Conclusions: the specific mechanisms underlying the potential role of genetic diversity in PD depression are still under investigation, however, there is evidence that they may involve neurotransmitter imbalance, mitochondrial impairment, oxidative stress, and neuroinflammation, as well as the dysregulation of neurotrophic factors and their downstream signaling pathways.

Frequency of Impulsive-Compulsive Behavior and Associated Psychological Factors in Parkinson's Disease: Lack of Control or Too Much of It?

Background and Objectives: Impulse Control Disorders (ICDs) including pathological gambling, hypersexuality, compulsive eating, compulsive buying, and other related behaviors are well-known distinct non-motor symptoms in Parkinson's Disease (PD). Some large-scale studies present a prevalence of at least 10%, however, there are other reports providing much higher rates. The majority of the conducted studies investigating ICDs focus mainly on pharmacological factors, however, from a psychological perspective, there is yet enough room for investigation. In order to address the above issues, we designed a two-part study. Materials and Methods: First, we aimed to identify the incidence of ICD and related behaviors in a cohort of 892 Greek PD patients. Second, we administered a comprehensive battery of psychometric tools to assess psychological factors such as personality dimensions, quality of life, defenses, coherence, and resilience as well as to screen general cognitive capacity in PD patients with ICD manifestations. Results: With regard to the first part, we identified ICD manifestations in 12.4% of the patients. Preliminary findings from the second part indicate elevated activity, rather than impulsivity, as well as interrelations between several variables, including measures of activity, coping mechanisms, and quality of life. Conclusions: We present a working hypothesis for the contribution of high activity channeled to specific behavioral patterns through specific coping mechanisms, concerning the emergence of ICDs and related behaviors in PD, and further stress the importance of compulsivity rather than impulsivity in this process.

Pharmacological and Non-Pharmacological Treatments for Depression in Parkinson's Disease: An Updated Review.

Depression represents one of the most common non-motor disorders in Parkinson's disease (PD) and it has been related to worse life quality, higher levels of disability, and cognitive impairment, thereby majorly affecting not only the patients but also their caregivers. Available pharmacological therapeutic options for depression in PD mainly include selective serotonin reuptake inhibitors, serotonin and norepinephrine reuptake inhibitors, and tricyclic antidepressants; meanwhile, agents acting on dopaminergic pathways used for motor symptoms, such as levodopa, dopaminergic agonists, and monoamine oxidase B (MAO-B) inhibitors, may also provide beneficial antidepressant effects. Recently, there is a growing interest in non-pharmacological interventions, including cognitive behavioral therapy; physical exercise, including dance and mind-body exercises, such as yoga, tai chi, and qigong; acupuncture; therapeutic massage; music therapy; active therapy; repetitive transcranial magnetic stimulation (rTMS); and electroconvulsive therapy (ECT) for refractory cases. However, the optimal treatment approach for PD depression is uncertain, its management may be challenging, and definite guidelines are also lacking. It is still unclear which of these interventions is the most appropriate and for which PD stage under which circumstances. Herein, we aim to provide an updated comprehensive review of both pharmacological and non-pharmacological treatments for depression in PD, focusing on recent clinical trials, systematic reviews, and meta-analyses. Finally, we discuss the pharmacological agents that are currently under investigation at a clinical level, as well as future approaches based on the pathophysiological mechanisms underlying the onset of depression in PD.

Double Trouble: Association of Malignant Melanoma with Sporadic and Genetic Forms of Parkinson's Disease and Asymptomatic Carriers of Related Genes: A Brief Report.

Introduction: Previous epidemiological evidence has established the co-occurrence of malignant melanoma (MM) and Parkinson's disease (PD). Shared molecular mechanisms have been proposed to be implicated in this relationship. The aim of the present study was to assess the prevalence of MM in patients with sporadic and genetic types of PD, as well as in asymptomatic carriers of PD-related genes. Methods: Data regarding past medical history and concomitant disease of 1416 patients with PD (including 20 participants with prodromal disease who phenoconverted to PD), 275 healthy controls (HCs) and 670 asymptomatic carriers of PD-related genes were obtained from the database of the Parkinson's Progression Markers Initiative (PPMI). Focus was placed on information about a medical record of MM. We also retrieved data regarding the genetic status of selected PPMI participants with a positive MM history. Results: In total, 46 patients with PD reported a positive MM history. Concerning the genetic forms of PD, nine of these PD patients (2.47%) carried a Leucine Rich Repeat Kinase 2 (LRRK2) gene mutation (mainly the G2019S), while eight (4.49%) harbored a Glucocerebrosidase (GBA) gene mutation (mainly the N370S). No alpha-synuclein (SNCA) gene mutation was identified in patients with an MM history. The remaining 29 PD patients (3.5%) were genetically undetermined. In total, 18 asymptomatic carriers of PD-related genes had a positive medical history for MM: among them, 10 carried an LRRK2 gene mutation (2.69%) and 10 a GBA gene mutation (3.51%) (2 were dual carriers). MM history was identified for seven HCs (2.5%). Conclusions: We replicated the previously reported association between genetically undetermined PD (GU-PD) and MM. A correlation of LRRK2 mutations with the development of MM could not be verified in either symptomatic PD patients or asymptomatic carriers, implicating distinct pathogenetic mechanisms as compared to GU-PD. Importantly, despite the limited literature evidence on Gaucher disease, this study highlights for the first time the relatively high prevalence of MM among asymptomatic and symptomatic PD GBA mutation carriers, with potential clinical implications.

A Novel Machine Learning Algorithm Predicts Dementia With Lewy Bodies Versus Parkinson's Disease Dementia Based on Clinical and Neuropsychological Scores.

OBJECTIVE: Our aim was to develop a machine learning algorithm based only on non-invasively clinic collectable predictors, for the accurate diagnosis of these disorders. METHODS: This is an ongoing prospective cohort study (ClinicalTrials.gov identifier NCT number NCT04448340) of 78 PDD and 62 DLB subjects whose diagnostic follow-up is available for at least 3 years after the baseline assessment. We used predictors such as clinico-demographic characteristics, 6 neuropsychological tests (mini mental, PD Cognitive Rating Scale, Brief Visuospatial Memory test, Symbol digit written, Wechsler adult intelligence scale, trail making A and B). We investigated logistic regression, K-Nearest Neighbors (K-NNs) Support Vector Machine (SVM), Naïve Bayes classifier, and Ensemble Model for their ability to predict successfully PDD or DLB diagnosis. RESULTS: The K-NN classification model had an accuracy 91.2% of overall cases based on 15 best clinical and cognitive scores achieving 96.42% sensitivity and 81% specificity on discriminating between DLB and PDD. The binomial logistic regression classification model achieved an accuracy of 87.5% based on 15 best features, showing 93.93% sensitivity and 87% specificity. The SVM classification model had an accuracy 84.6% of overall cases based on 15 best features achieving 90.62% sensitivity and 78.58% specificity. A model created on Naïve Bayes classification had 82.05% accuracy, 93.10% sensitivity and 74.41% specificity. Finally, an Ensemble model, synthesized by the individual ones, achieved 89.74% accuracy, 93.75% sensitivity and 85.73% specificity. CONCLUSION: Machine learning method predicted with high accuracy, sensitivity and specificity PDD or DLB diagnosis based on non-invasively and easily in-the-clinic and neuropsychological tests.

Psychosocial and Trauma-Related Stress and Risk of Dementia: A Meta-Analytic Systematic Review of Longitudinal Studies.

Stress has deleterious effects on brain health and yet, the prognostic value of psychosocial stress regarding the most common types of dementias, including Alzheimer disease, is still unclear. The primary aim of this systematic review was to explore the association between psychosocial stress and late onset dementia. We classified 24articles from Medline, PsycINFO, CINAHL, and Web of Science, as pertaining toxic categories of psychosocial and trauma-related stress (low socio-economic status [SES] related inequalities, marital status, posttraumatic stress disorder, work stress, "vital exhaustion" [VE], and, combined stressors). Using the Quality of Prognosis Studies in Systematic Reviews tool, we judged the quality of evidence to be low. This systematic review provided some non-robust, yet suggestive evidence that the above psychosocial types of stress are associated with increased risk of dementia in later life. Future robust, longitudinal studies with repeated validated measures of psychosocial stress and dementiaare required to strengthen or refute these findings.

MicroRNA as Candidate Biomarkers in Atypical Parkinsonian Syndromes: Systematic Literature Review.

Background and Objectives: Multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) are rare atypical parkinsonian syndromes, characterized by motor and cognitive symptoms. Their clinical diagnosis is challenging because there are no established biomarkers. Dysregulation of microRNAs (miRNAs/miRs) has been reported to serve an important role in neurodegenerative diseases. However, the miRNA profiles of MSA and PSP patients are rarely reported. The aim of this study was to critically review the role of miRNAs as diagnostic biomarkers to differentiate these atypical parkinsonian disorders and their role in disease pathogenesis. Materials and Methods: A systematic literature search of PubMed was conducted up to February 2022 according the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: A total of 15 studies were analyzed. Three studies have shown that miR-9-3p, miR-19a, miR-19b, and miR-24 are potential biomarkers for MSA. In two studies, miR-132 was downregulated, whereas miR-147a and miR-518e were upregulated in the brain tissue of PSP patients. Conclusions: The potential of miRNA is still uncertain as a potential differential diagnostic marker to identify these disorders. Pre-analytical and analytical factors of included studies were important limitations to justify the introduction of miRNAs into clinical practice.

Biomarkers in Alzheimer Disease and Other Dementias: What's Next into Pathophysiology to Support Clinical Practice and Drug Development.

Neurodegenerative diseases are a heterogeneous group of disorders characterized by gradual progressive neuronal loss in the central nervous system [...].

Migraine, Tension-Type Headache and Parkinson's Disease: A Systematic Review and Meta-Analysis.

Background and Objectives: The relationship between migraine and tension-type headache (TTH) with Parkinson's disease (PD) is controversial, while a common pathophysiological link remains obscure. The aim of this systematic review is to investigate the association between PD, migraine and TTH. Materials and Methods: Following PRISMA, we searched MEDLINE, WebofScience, Scopus, CINAHL, Cochrane Library and ClinicalTrials.gov up to 1 July 2022 for observational studies examining the prevalence and/or associations of PD with migraine and TTH. We pooled proportions, standardized mean differences (SMD) and odds ratios (OR) with random effects models. The risk of bias was assessed with the Newcastle-Ottawa scale (PROSPERO CRD42021273238). Results: Out of 1031 screened studies, 12 were finally included in our review (median quality score 6/9). The prevalence of any headache among PD patients was estimated at 49.1% (760 PD patients; 95% CI 24.8-73.6), migraine prevalence at 17.2% (1242 PD patients; 95% CI 9.9-25.9), while 61.5% (316 PD patients; 95% CI 52.6-70.1) of PD patients with migraine reported headache improvement after PD onset. Overall, migraine was not associated with PD (302,165 individuals; ORpooled = 1.11; 95% CI 0.72-1.72).However, cohort studies demonstrated a positive association of PD among lifetime migraineurs (143,583 individuals; ORpooled = 1.54, 95% CI 1.28-1.84), while studies on 12-month migraine prevalence yielded an inverse association (5195 individuals; ORpooled = 0.64, 95% CI 0.43-0.97). Similar findings were reported by 3 studies with data on the TTH-PD relationship (high prevalence, positive association when examined prospectively and an inverse relationship on 12-month prevalence). These data were not quantitatively synthesized due to methodological differences among the studies. Finally, PD patients suffering from any headache had a lower motor unified Parkinson's disease rating scale (UPDRS) score (503 PD patients; SMD -0.39; 95% CI -0.57 to -0.21) compared to PD patients not reporting headache. There is an unclear association of headaches in genetic PD cohorts. Conclusions: Observational data suggest that migraine and TTH could be linked to PD, but the current literature is conflicting.

How Telemedicine Can Improve the Quality of Care for Patients with Alzheimer's Disease and Related Dementias? A Narrative Review.

Background and Objectives: Dementia affects more than 55 million patients worldwide, with a significant societal, economic, and psychological impact. However, many patients with Alzheimer's disease (AD) and other related dementias have limited access to effective and individualized treatment. Care provision for dementia is often unequal, fragmented, and inefficient. The COVID-19 pandemic accelerated telemedicine use, which holds promising potential for addressing this important gap. In this narrative review, we aim to analyze and discuss how telemedicine can improve the quality of healthcare for AD and related dementias in a structured manner, based on the seven dimensions of healthcare quality defined by the World Health Organization (WHO), 2018: effectiveness, safety, people-centeredness, timeliness, equitability, integrated care, and efficiency. Materials and Methods: MEDLINE and Scopus databases were searched for peer-reviewed articles investigating the role of telemedicine in the quality of care for patients with dementia. A narrative synthesis was based on the seven WHO dimensions. Results: Most studies indicate that telemedicine is a valuable tool for AD and related dementias: it can improve effectiveness (better access to specialized care, accurate diagnosis, evidence-based treatment, avoidance of preventable hospitalizations), timeliness (reduction of waiting times and unnecessary transportation), patient-centeredness (personalized care for needs and values), safety (appropriate treatment, reduction of infection risk),integrated care (interdisciplinary approach through several dementia-related services), efficiency (mainly cost-effectiveness) and equitability (overcoming geographical barriers, cultural diversities). However, digital illiteracy, legal and organizational issues, as well as limited awareness, are significant potential barriers. Conclusions: Telemedicine may significantly improve all aspects of the quality of care for patients with dementia. However, future longitudinal studies with control groups including participants of a wide educational level spectrum will aid in our deeper understanding of the real impact of telemedicine in quality care for this population.

Silent Pauses and Speech Indices as Biomarkers for Primary Progressive Aphasia.

Background and Objectives: Recent studies highlight the importance of investigating biomarkers for diagnosing and classifying patients with primary progressive aphasia (PPA). Even though there is ongoing research on pathophysiological indices in this field, the use of behavioral variables, and especially speech-derived factors, has drawn little attention in the relevant literature. The present study aims to investigate the possible utility of speech-derived indices, particularly silent pauses, as biomarkers for primary progressive aphasia (PPA). Materials and Methods: We recruited 22 PPA patients and 17 healthy controls, from whom we obtained speech samples based on two elicitation tasks, i.e., cookie theft picture description (CTP) and the patients' personal narration of the disease onset and course. Results: Four main indices were derived from these speech samples: speech rate, articulation rate, pause frequency, and pause duration. In order to investigate whether these indices could be used to discriminate between the four groups of participants (healthy individuals and the three patient subgroups corresponding to the three variants of PPA), we conducted three sets of analyses: a series of ANOVAs, two principal component analyses (PCAs), and two hierarchical cluster analyses (HCAs). The ANOVAs revealed significant differences between the four subgroups for all four variables, with the CTP results being more robust. The subsequent PCAs and HCAs were in accordance with the initial statistical comparisons, revealing that the speech-derived indices for CTP provided a clearer classification and were especially useful for distinguishing the non-fluent variant from healthy participants as well as from the two other PPA taxonomic categories. Conclusions: In sum, we argue that speech-derived indices, and especially silent pauses, could be used as complementary biomarkers to efficiently discriminate between PPA and healthy speakers, as well as between the three variants of the disease.