Parkinson's Disease: Cognitive Impairment

Oxidative and Excitatory Neurotoxic Stresses in CRISPR/Cas9-Induced Kynurenine Aminotransferase Knockout Mice: A Novel Model for Despair-Based Depression and Post-Traumatic Stress Disorder

BACKGROUNDS

Memory and emotion are especially vulnerable to psychiatric disorders such as post-traumatic stress disorder (PTSD), which is linked to disruptions in serotonin (5-HT) metabolism. Over 90% of the 5-HT precursor tryptophan (Trp) is metabolized via the Trp-kynurenine (KYN) metabolic pathway, which generates a variety of bioactive molecules. Dysregulation of KYN metabolism, particularly low levels of kynurenic acid (KYNA), appears to be linked to neuropsychiatric disorders. The majority of KYNA is produced by the aadat (kat2) gene-encoded mitochondrial kynurenine aminotransferase (KAT) isotype 2. Little is known about the consequences of deleting the KYN enzyme gene.

METHODS

In CRISPR/Cas9-induced aadat knockout (kat2-/-) mice, we examined the effects on emotion, memory, motor function, Trp and its metabolite levels, enzyme activities in the plasma and urine of 8-week-old males compared to wild-type mice.

RESULTS

Transgenic mice showed more depressive-like behaviors in the forced swim test, but not in the tail suspension, anxiety, or memory tests. They also had fewer center field and corner entries, shorter walking distances, and fewer jumping counts in the open field test. Plasma metabolite levels are generally consistent with those of urine: antioxidant KYNs, 5-hydroxyindoleacetic acid, and indole-3-acetic acid levels were lower; enzyme activities in KATs, kynureninase, and monoamine oxidase/aldehyde dehydrogenase were lower, but kynurenine 3-monooxygenase was higher; and oxidative stress and excitotoxicity indices were higher. Transgenic mice displayed depression-like behavior in a learned helplessness model, emotional indifference, and motor deficits, coupled with a decrease in KYNA, a shift of Trp metabolism toward the KYN-3-hydroxykynurenine pathway, and a partial decrease in the gut microbial Trp-indole pathway metabolite.

CONCLUSIONS

This is the first evidence that deleting the aadat gene induces depression-like behaviors uniquely linked to experiences of despair, which appear to be associated with excitatory neurotoxic and oxidative stresses. This may lead to the development of a double-hit preclinical model in despair-based depression, a better understanding of these complex conditions, and more effective therapeutic strategies by elucidating the relationship between Trp metabolism and PTSD pathogenesis.

A mini review of polysaccharides from Zanthoxylum bungeanum maxim: Their extraction, purification, structural characteristics, bioactivity and potential applications

Zanthoxylum bungeanum Maxim (Z. bungeanum), commonly known as Sichuan pepper or Chinese prickly ash, is a deciduous shrub in the Rutaceae family, with a lengthy history of use as a food ingredient and traditional medicine in China. Z. bungeanum polysaccharides (ZBPs) represent one of the crucial bioactive components of Z. bungeanum, garnering global attention due to their potential medicinal value, culinary significance, and promising application prospects. The principal methods for extracting ZBPs are hot water extraction, ultrasound-assisted extraction, enzyme-assisted extraction and microbial fermentation extraction. However, the structural characteristics of ZBPs remain ambiguous, necessitating further exploration and elucidation of the structure-activity relationship using the advanced analytical techniques. In addition, ZBPs demonstrate diverse bioactivities, including antioxidant activity, neuroprotective effect, antibacterial activity, and the anti-fatigue effect, positioning them as promising candidates for various therapeutic and health-promoting applications. This review provides a comprehensive overview of the extraction, purification, structural characteristics, bioactivities, and potential applications of ZBPs, emphasizing the significant promise of ZBPs as valuable natural compounds with a range of bioactivities, supporting their further exploitation and application in various fields of industries and therapeutics.

Missed Insights for Earlier Management of Parkinson's Disease and the Value of Dopamine Transporter (DAT) Scans

Background/Objectives: This retrospective study focused on the role of Dopamine Transporter (DAT) scans in diagnosing Parkinson's Disease (PD) in older adults with cognitive impairment (CI). Methods: We retrospectively analyzed brain imaging of 6483 individuals aged 60 and above with CI. Among these, 297 underwent a DAT scan, with 189 testing positive and 89 starting dopamine therapy. In contrast, 173 patients exhibited PD-associated structural changes on CT or MRI without receiving DAT scans or treatment. Results: Of these patients, 50 (29%) experienced falls. This points towards a potential missed diagnosis of PD, which can respond to therapy in the early stages. Conclusions: Our results suggest that providers may overlook subtle signs of parkinsonism in patients with CI, resulting in symptoms worsening and treatment delay. Since CI is often first brought to the attention of PCPs, our findings call for an increased effort to inform PCPs of the role of DAT scans in aiding the diagnosis of dopamine deficiency states. By understanding PD-related structural changes seen on brain imaging and using a DAT scan to confirm dopamine deficiency, treatment for PD or related states might be started earlier or a timely referral made to a specialist, reducing patient disability and improving their quality of life.

Neurocognitive functioning of patients with early-stage Parkinson's disease

Parkinson's disease (PD) is a neurological disorder commonly associated with motor deficits. However, cognitive impairment is also common in patients with PD. Cognitive concerns in PD may affect multiple domains of neurocognition and vary across different stages of the disease. Extant research has focused mainly on cognitive deficits in middle to late stages of PD, whereas few studies have examined the unique cognitive profiles of patients with early-stage PD. This study addressed this gap in the published literature and examined neurocognitive functioning and functional capacity of patients with de novo PD, focusing on the unique pattern of cognitive deficits specific to the early stage of the disease. Results indicated that the pattern of cognitive deficits in patients with PD (n = 55; mean age = 72.93) was significantly different from healthy controls (n = 59; mean age = 71.88). Specifically, tasks related to executive functioning, attention, and verbal memory demonstrated the most pronounced deficits in patients with early-stage PD. Clinical implications of these findings are discussed.

Machine learning for predicting cognitive decline within five years in Parkinson's disease: Comparing cognitive assessment scales with DAT SPECT and clinical biomarkers

OBJECTIVE

Parkinson's disease (PD) is an age-related neurodegenerative condition characterized mostly by motor symptoms. Although a wide range of non-motor symptoms (NMS) are frequently experienced by PD patients. One of the important and common NMS is cognitive impairment, which is measured using different cognitive scales. Monitoring cognitive impairment and its decline in PD is essential for patient care and management. In this study, our goal is to identify the most effective cognitive scale in predicting cognitive decline over a 5-year timeframe initializing clinical biomarkers and DAT SPECT.

METHODS

Machine Learning has previously shown superior performance in image and clinical data classification and detection. In this study, we propose to use machine learning with different types of data, such as DAT SPECT and clinical biomarkers, to predict PD-CD based on various cognitive scales. We collected 330 DAT SPECT images and their clinical data in baseline, years 2,3,4, and 5 from Parkinson's Progression Markers Initiative (PPMI). We then designed a 3D Autoencoder to extract deep radiomic features (DF) from DAT SPECT images, and we then concatenated it with 17 clinical features (CF) to predict cognitive decline based on Montreal Cognitive Assessment (MoCA) and The Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS-I).

RESULTS

The utilization of MoCA as a cognitive decline scale yielded better performance in various years compared to MDS-UPDRS-I. In year 4, the application of the deep radiomic feature resulted in the highest achievement, with a cross-validation AUC of 89.28, utilizing the gradient boosting classifier. For the MDS-UPDRS-I scale, the highest achievement was obtained by utilizing the deep radiomic feature, resulting in a cross-validation AUC of 81.34 with the random forest classifier.

CONCLUSIONS

The study findings indicate that the MoCA scale may be a more effective predictor of cognitive decline within 5 years compared to MDS-UPDRS-I. Furthermore, deep radiomic features had better performance compared to sole clinical biomarkers or clinical and deep radiomic combined. These results suggest that using the MoCA score and deep radiomic features extracted from DAT SPECT could be a promising approach for identifying individuals at risk for cognitive decline in four years. Future research is needed to validate these findings and explore their utility in clinical practice.

Connectome-based predictive modelling estimates individual cognitive status in Parkinson's disease

INTRODUCTION

The progressive nature of Parkinson's disease (PD) affords emphasis on accurate early-stage individual-level assessment of risk and intervention appropriateness. In PD, cognitive impairment (CI) may follow or precede motor symptoms but are generally underdetected. In addition to impeding daily functioning and quality of life, CIs increase the risk for later conversion to dementia, providing a pressing need to develop novel tools to detect and interpret them. Connectome-based predictive modelling (CPM) is an emerging machine-learning approach to individual prediction that holds translational promise due to its noninvasiveness and simple implementation. The aim of this study was to investigate CPM's potential to predict and understand CIs in PD.

METHODS

Resting-state functional connectivity from 58 patients with PD of varying cognitive status was used to train a CPM-model to predict a global cognitive composite (GCC) score. The model was validated using cross-validation, permutation testing, and internal stability analyses. The combined predictive strength of two brain connectivity networks, positive and negative, directly and inversely correlated with GCC, respectively, was assessed.

RESULTS

The model significantly predicted individual GCC scores, r = 0.63, pperm < .05. Separately, the positive and negative networks were similar in performance, rs ≥ .58, ps < .05, but varied in anatomical distribution.

CONCLUSIONS

This study identified a connectome predictive of cognitive scores in PD, with features overlapping with established and emerging evidence on aberrant connectivity in PD-related CIs. Overall, CPM appears promising for clinical translation in this population, but longitudinal studies with out-of-sample validation are needed.

Supplementation of probiotic Bifidobacterium breve Bif11 reverses neurobehavioural deficits, inflammatory changes and oxidative stress in Parkinson's disease model

Human gut microbiota are thought to affect different physiological processes in the body, including brain functions. Gut dysbiosis has been linked to the progression of Parkinson's disease (PD) and thus, restoring the healthy gut microbiota with supplementation of putative probiotic strains can confer some benefits in PD. In the current study, we explored the neuroprotective potential of Bifidobacterium breve Bif11 supplementation in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine hydrochloride (MPTP) treated female Sprague Dawley rats. This study investigated the behavioural, molecular and biochemical parameters in the MPTP rat model. A pharmacological intervention of Bif11 at doses of 1 × 1010 CFU and 2 × 1010 CFU for 21 days was found to attenuate the cognitive and motor changes in the MPTP rat model. Furthermore, it also increased the tyrosine hydroxylase levels, reduced pro-inflammatory markers and decreased oxidative and nitrosative stress in the mid brain of MPTP-lesioned rats. Bif11 supplementation even restored the levels of short-chain fatty acids and decreased intestinal epithelial permeability in MPTP-induced PD model rats. In summary, these findings demonstrate that B. breve Bif11 has the potential to ameliorate symptoms of PD. However, this therapy needs to be further investigated with in-depth mechanistic insights in the future for the treatment of PD.

The assessment of executive functions to test the integrity of the nigrostriatal network: A pilot study

Background

Parkinson’s disease (PD) is a chronic neurodegenerative disorder characterized by motor and non-motor symptoms. The latter mainly include affective, sleep, and cognitive deficits. Non-demented PD patients often demonstrate impairments in several executive domains following neuropsychological evaluation. The current pilot study aims at assessing the discriminatory power of the Frontal Assessment Battery-15 (FAB15) in differentiating (i) non-demented PD patients and healthy controls and (ii) PD patients with more and less pronounced motor symptoms.

Methods

Thirty-nine non-demented early-stage PD patients in the “on” dopamine state (26 females, mean age = 64.51 years, SD = 6.47, mean disease duration = 5.49 years, SD = 2.28) and 39 healthy participants (24 females, mean age = 62.60 years, SD = 5.51) were included in the study. All participants completed the FAB15. Motor symptoms of PD patients were quantified via the Unified Parkinson’s Disease Rating Scale-Part III (UPDRS-Part III) and Hoehn and Yahr staging scale (H&amp;Y).

Results

The FAB15 score, adjusted according to normative data for sex, age, and education, proved to be sufficiently able to discriminate PD patients from healthy controls (AUC = 0.69 [95% CI 0.60–0.75], SE = 0.06, p = 0.04, optimal cutoff = 11.29). Conversely, the battery lacked sufficient discriminative capability to differentiate PD patients based on the severity of motor symptoms.

Conclusion

The FAB15 may be a valid tool for distinguishing PD patients from healthy controls. However, it might be less sensitive in identifying clinical phenotypes characterized by visuospatial impairments resulting from posteroparietal and/or temporal dysfunctions. In line with previous evidence, the battery demonstrated to be not expendable in the clinical practice for monitoring the severity of PD-related motor symptoms.

Spontaneous Object Exploration in a Recessive Gene Knockout Model of Parkinson's Disease: Development and Progression of Object Recognition Memory Deficits in Male Pink1-/- Rats

Cognitive impairments appear at or before motor signs in about one third of patients with Parkinson's disease (PD) and have a cumulative prevalence of roughly 80% overall. These deficits exact an unrelenting toll on patients' quality and activities of daily life due in part to a lack of available treatments to ameliorate them. This study used three well-validated novel object recognition-based paradigms to explore the suitability of rats with knockout of the PTEN-induced putative kinase1 gene (Pink1) for investigating factors that induce cognitive decline in PD and for testing new ways to mitigate them. Longitudinal testing of rats from 3-9 months of age revealed significant impairments in male Pink1-/- rats compared to wild type controls in Novel Object Recognition, Novel Object Location and Object-in-Place tasks. Task-specific differences in the progression of object discrimination/memory deficits across age were also seen. Finally, testing using an elevated plus maze, a tapered balance beam and a grip strength gauge showed that in all cases recognition memory deficits preceded potentially confounding impacts of gene knockout on affect or motor function. Taken together, these findings suggest that knockout of the Pink1 gene negatively impacts the brain circuits and/or neurochemical systems that support performance in object recognition tasks. Further investigations using Pink1-/- rats and object recognition memory tasks should provide new insights into the neural underpinnings of the visual recognition memory and visuospatial information processing deficits that are often seen in PD patients and accelerate the pace of discovery of better ways to treat them.

The Role of the NRF2 Pathway in Maintaining and Improving Cognitive Function

Nuclear factor (erythroid-derived 2)-like 2 (NRF2) is a redox-sensitive transcription factor that binds to the antioxidant response element consensus sequence, decreasing reactive oxygen species and regulating the transcription of a wide array of genes, including antioxidant and detoxifying enzymes, regulating genes involved in mitochondrial function and biogenesis. Moreover, NRF2 has been shown to directly regulate the expression of anti-inflammatory mediators reducing the expression of pro-inflammatory cytokines. In recent years, attention has turned to the role NRF2 plays in the brain in different diseases such Alzheimer’s disease, Parkinson’s disease, Huntington’s disease and others. This review focused on the evidence, derived in vitro, in vivo and from clinical trials, supporting a role for NRF2 activation in maintaining and improving cognitive function and how its activation can be used to elicit neuroprotection and lead to cognitive enhancement. The review also brings a critical discussion concerning the possible prophylactic and/or therapeutic use of NRF2 activators in treating cognitive impairment-related conditions.

Protocol for randomized controlled trial to evaluate the safety and feasibility of a novel helmet to deliver transcranial light emitting diodes photobiomodulation therapy to patients with Parkinson’s disease

Introduction

Parkinson’s disease (PD) is the second most common, progressive, and debilitating neurodegenerative disease associated with aging and the most common movement disorder. Photobiomodulation (PBM), the use of non-thermal light for therapeutic purposes using laser or light emitting diodes (LED) is an emerging non-invasive treatment for a diverse range of neurological conditions. The main objectives of this clinical trial are to investigate the feasibility, safety, tolerability, and efficacy of a novel transcranial LED helmet device (the “PDNeuro”) in the alleviation of symptoms of PD.

Methods and analysis

This is a 24-week, two-arm, triple-blinded randomized placebo-controlled clinical trial of a novel transcranial “PDNeuro” LED Helmet, comparing an active helmet to a sham helmet device. In a survey, 40 PD participants with Hoehn and Yahr Stage I–III during ON periods will be enrolled and randomly assigned into two groups. Both groups will be monitored weekly for the safety and tolerability of the “PDNeuro” LED Helmet. Clinical signs and symptoms assessed will include mobility, fine motor skills and cognition, with data collected at baseline, 12 weeks, and 24 weeks. Assessment tools include the TUG, UPDRS, and MoCA all validated for use in PD patients. Patient’s adherence to the device usage and participant drop out will be monitored weekly. At 12 weeks both placebo and treatment groups will crossover and placebo participants offered the treatment. The main indicator for clinical efficacy of the “PDneuro” Helmet is evidence of sustained improvements in motor and non-motor symptoms obtained from participant self-reported changes, carer reporting of changes and objective reassessment by the investigators. The outcomes will assist in a future larger randomized trial design.

Clinical Trial Registration

[https://www.anzctr.org.au], identifier [12621001722886].

A Mobile Application for Smart Computer-Aided Self-Administered Testing of Cognition, Speech, and Motor Impairment

We present a model for digital neural impairment screening and self-assessment, which can evaluate cognitive and motor deficits for patients with symptoms of central nervous system (CNS) disorders, such as mild cognitive impairment (MCI), Parkinson's disease (PD), Huntington's disease (HD), or dementia. The data was collected with an Android mobile application that can track cognitive, hand tremor, energy expenditure, and speech features of subjects. We extracted 238 features as the model inputs using 16 tasks, 12 of them were based on a self-administered cognitive testing (SAGE) methodology and others used finger tapping and voice features acquired from the sensors of a smart mobile device (smartphone or tablet). Fifteen subjects were involved in the investigation: 7 patients with neurological disorders (1 with Parkinson's disease, 3 with Huntington's disease, 1 with early dementia, 1 with cerebral palsy, 1 post-stroke) and 8 healthy subjects. The finger tapping, SAGE, energy expenditure, and speech analysis features were used for neural impairment evaluations. The best results were achieved using a fusion of 13 classifiers for combined finger tapping and SAGE features (96.12% accuracy), and using bidirectional long short-term memory (BiLSTM) (94.29% accuracy) for speech analysis features.