Diagnosis Of Parkinson's Disease Research Articles

Understanding Parkinson disease in Spain: Genetic and clinical insights.

Parkinson disease (PD) is a complex and heterogeneous neurodegenerative disorder with a broad spectrum of clinical manifestations, determined by a complex interplay of environmental and genetic factors. This study aimed to investigate genetic variants associated with PD and assess their impact on the disease phenotype through genotype-phenotype correlations. We employed a targeted resequencing panel to analyze 27 genes linked to PD in a cohort of 1185 PD patients from southern Spain. Variants were categorized based on the American College of Medical Genetics and Genomics pathogenicity criteria. Demographic and clinical data were also collected. Among the patients analyzed, 13.5% carried potential disease-causing pathogenic or likely pathogenic variants in 12 different genes, indicating significant genetic heterogeneity. The most frequently affected genes were LRRK2, PRKN, and GBA1 (accounting for 72.1% of positive cases). Sex-specific differences were observed, with a higher proportion of female patients carrying LRRK2 variants. Differences in age at onset and clinical features were also observed among the different mutated genes. Notably, variants in genes associated with atypical parkinsonism presented distinct clinical presentations, highlighting the importance of genetic factors in the differential diagnosis. Our study provides valuable information on the genetic landscape of PD and its clinical manifestations. The observed genotype-phenotype correlations, along with sex-specific differences, emphasize the complexity of PD pathogenesis, underlining the importance of personalized approaches to PD diagnosis and treatment. Further investigations into genetic interactions and population-specific effects are warranted to enhance our understanding of PD etiology and improve patient care.

Chronic Musculoskeletal Pain and Risk of Incident Parkinson's Disease: A 13-Year Longitudinal Study.

Chronic musculoskeletal pain often co-occurs with Parkinson's disease (PD); however, whether individuals with chronic pain have a higher risk of developing PD is unclear. To investigate the associations between chronic pain and incident risk of three neurodegenerative parkinsonism categories including PD, multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). This study included 355,890 participants (mean [standard deviation] age, 56.51 [8.07] years, 48.40% male) who did not have parkinsonism at baseline from a population-based cohort. Musculoskeletal pain in the hip, neck/shoulder, back, knee, or "all over the body" was assessed. Chronic pain was defined if pain lasted ≥3 months. Participants were categorized into four groups: no chronic pain, having one or two, three or four sites, and pain "all over the body." The diagnosis of PD, MSA, and PSP used self-reports, hospital records, and death registries. Multivariable-adjusted Cox regression was performed for the analyses. Over a median follow-up of 13.0 years, 2044 participants developed PD, 77 participants developed MSA, and 126 participants developed PSP. In multivariable analyses, there was a dose-response relationship between number of chronic pain sites and incident risk of PD (hazard ratio, 1.15; 95% confidence interval, 1.07-1.23). Participants with one or two pain sites and three or four pain sites had an 11% and 49% increased risk of developing PD, respectively. There were no associations between chronic pain and MSA or PSP. Chronic musculoskeletal pain was independently associated with PD, suggesting that chronic pain could be used to identify individuals at risk of developing PD. © 2024 International Parkinson and Movement Disorder Society.

Brain single-cell transcriptomics highlights comorbidity-related cell type-specific changes of Parkinson’s disease with major depressive disorder after paraquat exposure

Paraquat (PQ), a commonly used herbicide, is a potent environmental neurotoxin associated with Parkinson’s disease (PD) and major depressive disorder (MDD). While the involvement of various brain cell types in the etiology of each disorder is well recognized, the specific cell subtypes implicated in the comorbidity of PD and MDD, especially under PQ neurotoxicity, remain poorly understood. In this study, we used single-cell RNA sequencing (scRNA-seq) to analyze brain tissues from mice with PQ-induced PD with MDD. By integrating genomic data with scRNA-seq profiles, we identified differences in cellular heterogeneity related to the pathogenesis of PD and MDD under PQ exposure. Our analysis of risk enrichment in genes with cell type-specific expression patterns revealed that astrocytes are predominantly linked to the comorbidity of PQ-induced PD and MDD. Furthermore, we identified a specific astrocyte subtype that plays a major role in the comorbidity-related changes observed in PQ-induced PD and MDD. This subtype appears to interact with and potentially transform into MDD-specific and PD-specific subtypes. Additionally, pathways related to chemical synaptic function and neuro-projection development were involved in all key stages of PD and MDD co-occurrence. We also identified RNF7 and MTCH2 as shared diagnostic hub genes for PD and MDD, which changed significantly in astrocytes following PQ exposure. These genes may serve as potential markers for astrocyte-specific prognostic diagnosis of PQ-induced PD with MDD. In summary, this study provides the first scRNA-seq profile of comorbidity in a PQ-exposed model. It highlights the heterogeneity of astrocytes in comorbidity and elucidates potential mechanisms underlying the co-occurrence of PD and MDD. These findings emphasize the need for further research into the pathogenesis of PD comorbid with MDD and offer novel insights into PQ neurotoxicity.

Diagnostic Potential of NEAT1, hsa-let-7a-5p, and miR-506-3p in Early-stage Parkinson's Disease.

Parkinson's disease (PD) is a multifaceted disease that is influenced by both genetic and environmental parameters. Non-coding RNAs have been shown to be ideal biomarkers for several diseases, including PD. This study was conducted to evaluate the expression levels of NEAT1, hsa-let-7a-5p, and miR-506-3p in individuals with PD to assess their efficacy for early-stage PD diagnosis. Twenty-four patients with PD and 29 healthy individuals participated in this study. The IntaRNA tool was used to predict potential base pairings between NEAT1 and let-7a-5p, and NEAT1 and miR-506-3p. RT-qPCR was employed to measure the relative expression of tyrosine hydroxylase (TH), as well as nuclear enriched abundant transcript 1 (NEAT1), hsa-let-7a-5p, and miR-506-3p levels in both groups. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic value. The PD group exhibited significantly elevated NEAT1 expression levels compared to the healthy control group. While the PD group exhibited an insignificant decreased TH expression level relative to the healthy group. Furthermore, the levels of hsa-let-7a-5p and miR-506-3p expression were seen to be decreased in patients with PD in comparison to the control group. Integration of NEAT1, hsa-let-7a-5p, and miR-506-3p levels significantly enhanced diagnostic capabilities and increased the AUC to 0.9501 (95% confidence interval: 0.8978-1.000, p < .0001). The elevated NEAT1 expression and the decreased expression of hsalet- 7a-5p and miR-506-3p in PD patients indicate that these factors might contribute to the disease's pathogenesis. Combining the ROC curves of NEAT1 and hsa-let-7a-5p with miR-506-3p showed improved sensitivity and specificity, facilitating more accurate PD diagnosis. More importantly, they may contribute as promising non-invasive biomarkers for PD diagnosis.

P1 evoked by facial expression images is enhanced in Parkinson’s disease patients with depressive symptoms

IntroductionDepressive symptoms are most common non-motor symptoms in Parkinson’s disease (PD), which is often overlooked due to absence of rapid and objective diagnostic biomarkers. Electroencephalography (EEG)-based event-related potentials (ERPs) is commonly used to assess emotional processes. The aim of this study was to investigate changes in ERPs in PD patients exhibiting depressive symptoms and to provide a reliable biomarker for assisting in the diagnosis of PD with depressive symptoms.MethodsWe conducted a case–control study involving 30 PD patients with (dPD group) or without depressive symptoms (nPD group) and 13 age matched healthy controls (HC). We recorded EEG of the patients during the emotional picture stimulation task and analyzed the difference in the early ERPs potentials (P1, N170, early posterior negativity) and their correlation with the severity of symptoms in PD patients.ResultsOur results found that P1 amplitude in the occipital region of the dPD group in response to emotional faces was significantly higher than that of nPD and HC group, and it was positively correlated with severity of depressive symptoms in PD patients.ConclusionOur study shows that facial expression-induced enhancement of P1 amplitude can be utilized as a rapid and objective indicator to screen for depressive symptoms in PD.

Prevalence and Clinical Significance of Skin Manifestations in Parkinson Disease Patients

Background: Parkinson's disease (PD) is primarily characterized by motor symptoms, but non-motor symptoms, including skin manifestations, are increasingly recognized. These remain underexplored despite their potential impact on quality of life. Objectives: This study aimed to evaluate the prevalence and clinical features of skin findings in PD patients, with a focus on identifying potential pathogenetic links between dermatological conditions and PD. Methods: A total of 215 PD patients were included. Comprehensive dermatological examinations were performed, and demographic and clinical data were collected. Statistical analysis was conducted using SPSS 23.0, with significance set at P &lt; 0.05. Results: Skin conditions were found in 92.1% of PD patients. Xerosis, seborrheic dermatitis, and hyperhidrosis were the most common findings. Pre-PD xerosis was associated with an earlier stage of PD (P = 0.001). Use of PD medications, such as levodopa/carbidopa/entacapone, was linked to a lower incidence of seborrheic dermatitis (P = 0.040). A significant correlation was also noted between rosacea and cherry angioma (P = 0.01). Conclusion: Dermatological conditions are prevalent in PD and may precede its motor symptoms. Skin assessments could aid early diagnosis and management of PD, highlighting the need for further research on their pathogenetic mechanisms.

Health care utilization at the end of life in Parkinson’s disease: a population-based register study

BackgroundKnowledge of health care utilization at the end of life in Parkinson’s disease (PD) is sparse. This study aims to investigate end of life health care utilization, characterized by emergency room (ER) visits, receipt of specialized palliative care (SPC), and acute hospital deaths in a Swedish population-based PD cohort.MethodsWe conducted a retrospective cohort study on deceased patients (≥ 18 years) with a PD diagnosis during their last year of life (n = 922), based on health care-provider data from Region Stockholm´s data warehouse, for the study period 2015–2021. Univariable and multivariable logistic regression analyses tested associations and adjusted Odds ratios (aORs) were calculated.ResultsDuring the last month of life, approx. half of the cohort had emergency room (ER) visits and risk of frailty (measured by Hospital Frailty Risk Score) significantly predicted these visits (aOR, 3.90 (2.75–5.55)). In total, 120 people (13%) received SPC during their last three months of life, which positively associated with risk for frailty, (aOR, 2.65 (1.43–4.94, p = 0.002). In total, 284 people (31%) died in acute hospital settings. Among community-dwellers, male gender and frailty were strongly associated with acute hospital deaths (aOR, 1.90 (1.15–3.13, p = 0.01) and 3.70 (1.96–6.98, p < 0.0001)).ConclusionsRates of ER visits at end of life and hospital deaths were relatively high in this population-based cohort. Considering a high disease burden, referral to SPC at end of life was relatively low. Sex-specific disparities in health care utilization are apparent. Identifying people with high risk for frailty could assist the planning of optimal end-of-life care for people with PD.

Synthetic assessment of cardiac autonomic modulation and Baevsky stress index in patients with synucleinopathies

Abstract Background The Baevsky Stress Index (BSTRi), calculated from Heart Rate Variability (HRV) data, has been proposed for quantitative assessment of physiological stress, with higher scores indicating higher levels of physical and/or psychological stress [1]. Cardiac autonomic modulation can be synthetically quantified by calculating the parasympathetic (PNSi) and the sympathetic (SNSi) indexes. The values of the BSTRi, SNSi, and PNSi in patients with synucleinopathies of different prognoses have not been reported yet. Purpose To quantify, in patients with Parkinson's disease (PD) and Multisystem Atrophy (MSA), the BSTRi, its correlation with the PNSi and the SNSi indexes, and their potential value for a synthetic assessment of cardiac autonomic modulation and early differential diagnosis between PD and MSA. Methods Holter ECG data of 66 patients with Parkinsonian syndromes were retrospectively analyzed after 10 years of follow-up. Out of them, 34 patients with a certain diagnosis of PD (17) and MSA (17) were selected for this study. HRV was analyzed with the Kubios software (version 4.0), providing automatic calculation of the BSTRi, PNSi, and SNSi [2], as well as of time domain (TD), frequency domain (FD), nonlinear (NL), and time-varying (TV) HRV parameters. HRV was calculated from selected short-term intervals (of 5 minutes), during daily activity (ACT5’), and non-REM sleep (NREM5’), and from 24-hours Holter recordings. Patients’ HRV findings were compared with those of 51 age-matched healthy subjects (HS). Results An example of individual automatic graphic summary is shown in Figure 1. Both short-term and 24-hour BSTRi and SNSi values were significantly (p &amp;lt; 0.05) higher in PD and MSA compared to those of HS, in all investigated conditions. Short-term PNSi was significantly higher in HS than in PD in all conditions, but only during NREM5’ in MSA patients (Table 1). No significant difference was found between the indexes of PD and MSA patients. As in HS (R=92), BSTRi was positively correlated with the SNSi in MSA (average R= 0.83 and 0.89 during ACT5’ and NREM5’, respectively), but less evident in PD (R=0.67). The inverse correlation between PNSi and SNSi (R=0.75 in HS) was lost in both MSA and PD. Conclusions Higher values of BSTRi in PD and MSA compared to HS suggest that patients with synucleinopathies do experience higher levels of psychophysiological stress, which may affect their quality of life negatively. However, since no significant difference was found in this study between BSTRi values of PD and MSA patients, BSTRi seems at present unreliable for early differentiation between the two diseases. Telematic assessment of BSTRi, SNSi, and PNSi could be useful for remote monitoring of PD and MSA patients’ psychophysiological stress, to provide timely intervention and adaptive treatment.Fig.1 Example of graphic summary (ACT5')

Unveiling early signs of Parkinson’s disease via a longitudinal analysis of celebrity speech recordings

Numerous studies proposed methods to detect Parkinson’s disease (PD) via speech analysis. However, existing corpora often lack prodromal recordings, have small sample sizes, and lack longitudinal data. Speech samples from celebrities who publicly disclosed their PD diagnosis provide longitudinal data, allowing the creation of a new corpus, ParkCeleb. We collected videos from 40 subjects with PD and 40 controls and analyzed evolving speech features from 10 years before to 20 years after diagnosis. Our longitudinal analysis, focused on 15 subjects with PD and 15 controls, revealed features like pitch variability, pause duration, speech rate, and syllable duration, indicating PD progression. Early dysarthria patterns were detectable in the prodromal phase, with the best classifiers achieving AUCs of 0.72 and 0.75 for data collected ten and five years before diagnosis, respectively, and 0.93 post-diagnosis. This study highlights the potential for early detection methods, aiding treatment response identification and screening in clinical trials.

Microbial biomarker discovery in Parkinson’s disease through a network-based approach

Associations between the gut microbiota and Parkinson’s disease (PD) have been widely investigated. However, the replicable biomarkers for PD diagnosis across multiple populations remain elusive. Herein, we performed a meta-analysis to investigate the pivotal role of the gut microbiome in PD and its potential diagnostic implications. Six 16S rRNA gene amplicon sequence datasets from five independent studies were integrated, encompassing 550 PD and 456 healthy control samples. The analysis revealed significant alterations in microbial composition and alpha and beta diversity, emphasizing altered gut microbiota in PD. Specific microbial taxa, including Faecalibacterium, Roseburia, and Coprococcus_2, known as butyrate producers, were notably diminished in PD, potentially contributing to intestinal inflammation. Conversely, genera such as Akkermansia and Bilophila exhibited increased relative abundances. A network-based algorithm called NetMoss was utilized to identify potential biomarkers of PD. Afterwards, a classification model incorporating 11 optimized genera demonstrated high performance. Further functional analyses indicated enrichment in pathways related to neurodegeneration and metabolic pathways. These findings illuminate the intricate relationship between the gut microbiota and PD, offering insights into potential therapeutic interventions and personalized diagnostic strategies.

A minimally invasive biomarker for sensitive and accurate diagnosis of Parkinson’s disease

Seeding activities of disease-associated α-synuclein aggregates (αSynD), a hallmark of Parkinson’s disease (PD), are detectable by seed amplification assay (αSyn-SAA) and being developed as a diagnostic biomarker for PD. Sensitive and accurate αSyn-SAA for blood or saliva would greatly facilitate PD diagnosis. This prospective diagnostic study conducted αSyn-SAA analyses on serum and saliva samples collected from patients clinically diagnosed with PD or healthy controls (HC). 124 subjects (82 PD, 42 HC) donated blood and had extensive clinical assessments, of whom 74 subjects (48 PD, 26 HC) also donated saliva at the same visits. An additional 57 subjects (35 PD, 22 HC) donated saliva and had more limited clinical assessments. The mean ages were 69.21, 66.55, 69.58, and 64.71 years for PD serum donors, HC serum donors, PD saliva donors, and HC saliva donors, respectively. αSynD seeding activities in either sample type alone or both sample types together were evaluated for PD diagnosis. Serum αSyn-SAA data from 124 subjects showed 80.49% sensitivity, 90.48% specificity, and 0.9006 accuracy (AUC of ROC); saliva αSyn-SAA data from 131 subjects attained 74.70% sensitivity, 97.92% specificity, and 0.8966 accuracy. Remarkably, the combined serum and saliva αSyn-SAA from 74 subjects with both sample types achieved better diagnostic performance: 95.83% sensitivity, 96.15% specificity, and 0.98 accuracy. In addition, serum αSynD seeding activities correlated inversely with Montreal Cognitive Assessment in males and positively with Hamilton Depression Rating Scale in females and in the < 70 age group, whereas saliva αSynD seeding activities correlated inversely with age at diagnosis in males and in the < 70 age group. Our data indicate that serum and saliva αSyn-SAA together can achieve high diagnostic accuracy for PD comparable to that of CSF αSyn-SAA, suggesting their potential utility for highly sensitive, accurate, and minimally invasive diagnosis of PD in routine clinical practice and clinical studies.

Hearing Loss, Incident Parkinson Disease, and Treatment With Hearing Aids

The risk of developing Parkinson disease (PD) after objective hearing loss is unknown. PD studies using self-reported hearing loss are insensitive, and objective data are lacking. To examine the association of hearing loss with incident PD in US veterans and its effect modification by well-established prodromal conditions and hearing aids. This cohort study analyzed electronic health record data from the US Department of Veterans Affairs for veterans who had an audiogram from January 1, 1999, to December 30, 2022. Individuals with data missing or a preexisting PD diagnosis were excluded. Audiogram-confirmed hearing loss. Cumulative incidence of PD was calculated with adjustment for competing risk of death. Among 7 296 051 veterans with an audiogram, 3 596 365 were included. They were mostly male (n = 3 452 898 [96%]) and had a mean (SD) age of 67 (10.3) years. A total of 750 010 individuals (20.8%) had normal hearing at the time of audiometry examination; among those with hearing loss, 1 080 651 (30.0%), 1 039 785 (28.9%), 568 296 (15.8%), and 157 623 (4.3%) individuals had mild (20-<35 dB), moderate (35-<50 dB), moderate to severe (50-<65 dB), and severe to profound (65-120 dB) hearing loss, respectively. Age, gender, and smoking history were balanced between all exposed and unexposed groups with further adjustment for race, ethnicity, and frailty. At 10 years after the baseline audiogram, the numbers of additional cases of PD were 6.1 (95% CI, 4.5-7.79, 15.8 (95% CI, 12.8-18.8), 16.2 (95% CI, 11.9-20.6), and 12.1 (95% CI, 4.5-19.6) among veterans with mild, moderate, moderate to severe, and severe to profound hearing loss, respectively, compared with those with normal hearing. When combined with established prodromal conditions, hearing loss was associated with 5.7 (95% CI, 2.2-9.2) additional cases of PD at 10 years compared with either condition alone. With prompt hearing aid dispensation, incident cases of PD decreased by 21.6 cases (95% CI, 19.5-23.6) at 10 years. Hearing loss appears to be an independent risk factor for later development of PD. Hearing aids attenuate this risk, and therefore widespread screening for hearing loss and appropriate use of hearing aids may reduce the incidence of PD. Additional studies are needed to examine the mechanisms underlying the association between hearing loss and PD.

Angiotensin-(1-7) relieves behavioral defects and α-synuclein expression through NEAT1/miR-153-3p axis in Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, whose characteristic pathology involves progressive deficiency of dopaminergic neurons and generation of Lewy bodies (LBs). Aggregated and misfolded α-synuclein (α-syn) is the major constituent of LBs. As the newly discovered pathway of renin-angiotensin system (RAS), Angiotensin-(1-7) (Ang-(1-7)) and receptor Mas have attracted increasing attentions for their correlation with PD, but underlying mechanisms remain not fully clear. Based on above, this study established PD models of mice and primary dopaminergic neurons with AAV-hα-syn(A53T), then discussed the effects of Ang-(1-7)/Mas on α-syn level and neuronal apoptosis for these models combined with downstream long non-coding RNA (lncRNA) and microRNA (miRNA). Results showed that Ang-(1-7) alleviated behavioral impairments, rescued dopaminergic neurons loss and lowered α-syn expression in substantia nigra of hα-syn(A53T) overexpressed PD mice. We also discovered that Ang-(1-7) decreased level of α-syn and apoptosis in the hα-syn(A53T) overexpressed dopaminergic neurons through lncRNA NEAT1/miR-153-3p axis. Moreover, miR-153-3p level in peripheral blood is found negatively correlated with that of α-syn. In conclusion, our work not only showed neuroprotective effect and underlying mechanisms for Ang-(1-7) on α-syn in vivo and vitro, but also brought new hope on miR-153-3p and NEAT1 for diagnosis and treatment in PD.

Parkinson’s families project: a UK-wide study of early onset and familial Parkinson’s disease

The Parkinson’s Families Project is a UK-wide study aimed at identifying genetic variation associated with familial and early-onset Parkinson’s disease (PD). We recruited individuals with a clinical diagnosis of PD and age at motor symptom onset ≤45 years and/or a family history of PD in up to third-degree relatives. Where possible, we also recruited affected and unaffected relatives. We analysed DNA samples with a combination of single nucleotide polymorphism (SNP) array genotyping, multiplex ligation-dependent probe amplification (MLPA), and whole-genome sequencing (WGS). We investigated the association between identified pathogenic mutations and demographic and clinical factors such as age at motor symptom onset, family history, motor symptoms (MDS-UPDRS) and cognitive performance (MoCA). We performed baseline genetic analysis in 718 families, of which 205 had sporadic early-onset PD (sEOPD), 113 had familial early-onset PD (fEOPD), and 400 had late-onset familial PD (fLOPD). 69 (9.6%) of these families carried pathogenic variants in known monogenic PD-related genes. The rate of a molecular diagnosis increased to 28.1% in PD with motor onset ≤35 years. We identified pathogenic variants in LRRK2 in 4.2% of families, and biallelic pathogenic variants in PRKN in 3.6% of families. We also identified two families with SNCA duplications and three families with a pathogenic repeat expansion in ATXN2, as well as single families with pathogenic variants in VCP, PINK1, PNPLA6, PLA2G6, SPG7, GCH1, and RAB32. An additional 73 (10.2%) families were carriers of at least one pathogenic or risk GBA1 variant. Most early-onset and familial PD cases do not have a known genetic cause, indicating that there are likely to be further monogenic causes for PD.

XEMLPD: an explainable ensemble machine learning approach for Parkinson disease diagnosis with optimized features

XEMLPD: an explainable ensemble machine learning approach for Parkinson disease diagnosis with optimized features

AIMP2 accumulation in brain leads to cognitive deficits and blood secretion in Parkinson’s disease

BackgroundPropagation of neuronal α-synuclein aggregate pathology to the cortex and hippocampus correlates with cognitive impairment in Parkinson’s disease (PD) dementia and dementia with Lewy body disease. Previously, we showed accumulation of the parkin substrate aminoacyl-tRNA synthetase interacting multifunctional protein-2 (AIMP2) in the temporal lobe of postmortem brains of patients with advanced PD. However, the potential pathological role of AIMP2 accumulation in the cognitive dysfunction of patients with PD remains unknown.MethodsWe performed immunofluorescence imaging to examine cellular distribution and accumulation of AIMP2 in brains of conditional AIMP2 transgenic mice and postmortem PD patients. The pathological role of AIMP2 was investigated in the AIMP2 transgenic mice by assessing Nissl-stained neuron counting in the hippocampal area and Barnes maze to determine cognitive functions. Potential secretion and cellular uptake of AIMP2 was monitored by dot blot analysis and immunofluorescence. The utility of AIMP2 as a new PD biomarker was evaluated by dot blot and ELISA measurement of plasma AIMP2 collected from PD patients and healthy control followed by ROC curve analysis.ResultsWe demonstrated that AIMP2 is toxic to the dentate gyrus neurons of the hippocampus and that conditional AIMP2 transgenic mice develop progressive cognitive impairment. Moreover, we found that neuronal AIMP2 expression levels correlated with the brain endothelial expression of AIMP2 in both AIMP2 transgenic mice and in the postmortem brains of patients with PD. AIMP2, when accumulated, was released from the neuronal cell line SH-SY5Y cells. Secreted AIMP2 was taken up by human umbilical vein endothelial cells. Consistent with the fact that AIMP2 can be released into the extracellular space, we showed that AIMP2 transgenic mice have higher levels of plasma AIMP2. Finally, ELISA-based assessment of AIMP2 in plasma samples from patients with PD and controls, and subsequent ROC curve analysis proved that high plasma AIMP2 expression could serve as a reliable molecular biomarker for PD diagnosis.ConclusionsThe pathological role in the hippocampus and the cell-to-cell transmissibility of AIMP2 provide new therapeutic avenues for PD treatment, and plasma AIMP2 combined with α-synuclein may improve the accuracy of PD diagnosis in the early stages.

Sex Differences in Neuropsychiatric Symptoms in Alpha-Synucleinopathies: A Systematic Review and Meta-Analysis.

Alpha-synucleinopathies, such as Parkinson's disease (PD), Parkinson's disease dementia (PDD), and dementia with Lewy bodies (DLB), demonstrate sex differences with regard to prevalence, age of onset, and motor manifestations. Neuropsychiatric symptoms (NPS) are common early and late manifestations of these disorders. We aimed to describe sex differences in NPS across alpha-synucleinopathies. We searched Web of Science Core collection databases to identify observational studies published between January 1, 2000, and June 1, 2022, reporting the prevalence or severity of NPS among individuals with a diagnosis of PD, PDD, or DLB. Prevalence and severity were pooled for each NPS according to sex using random-effects models. Two-hundred-and-forty studies, representing 796,026 participants (45% females), were included in the meta-analysis. Female sex was associated with a higher prevalence of anxiety (OR = 1.60 [95% CI: 1.40, 1.82]), depression (OR = 1.56 [1.45, 1.67]), fatigue (OR = 1.21 [1.02, 1.43]), and psychotic symptoms (OR = 1.26 [1.14, 1.40]) and more severe anxiety (g = 1.35 [95% CI: 0.58, 2.13]), depression (g = 1.57 [1.05, 2.08]), and fatigue (g = 0.86 [0.41, 1.32]), while male sex was associated with a higher prevalence of apathy (OR = 0.77 [0.63, 0.93]), impulse control disorders (OR = 0.67 [0.55, 0.82]), REM sleep behavior disorder (OR = 0.54 [0.42, 0.70]), hypersomnolence (OR = 0.67 [0.56, 0.80]), and suicide (OR = 0.30 [0.20, 0.44]). NPS have different prevalences and severities in alpha-synucleinopathies according to sex. These findings support consideration of sex in the elaboration of clinical tools.

Bio-inspired feature selection for early diagnosis of Parkinson's disease through optimization of deep 3D nested learning.

Parkinson's disease (PD) is one of the most common neurodegenerative disorders that affect the quality of human life of millions of people throughout the world. The probability of getting affected by this disease increases with age, and it is common among the elderly population. Early detection can help in initiating medications at an earlier stage. It can significantly slow down the progression of this disease, assisting the patient to maintain a good quality of life for a more extended period. Magnetic resonance imaging (MRI)-based brain imaging is an area of active research that is used to diagnose PD disease early and to understand the key biomarkers. The prior research investigations using MRI data mainly focus on volume, structural, and morphological changes in the basal ganglia (BG) region for diagnosing PD. Recently, researchers have emphasized the significance of studying other areas of the human brain for a more comprehensive understanding of PD and also to analyze changes happening in brain tissue. Thus, to perform accurate diagnosis and treatment planning for early identification of PD, this work focuses on learning the onset of PD from images taken from whole-brain MRI using a novel 3D-convolutional neural network (3D-CNN) deep learning architecture. The conventional 3D-Resent deep learning model, after various hyper-parameter tuning and architectural changes, has achieved an accuracy of 90%. In this work, a novel 3D-CNN architecture was developed, and after several ablation studies, the model yielded results with an improved accuracy of 93.4%. Combining features from the 3D-CNN and 3D ResNet models using Canonical Correlation Analysis (CCA) resulted in 95% accuracy. For further enhancements of the model performance, feature fusion with optimization was employed, utilizing various optimization techniques. Whale optimization based on a biologically inspired approach was selected on the basis of a convergence diagram. The performance of this approach is compared to other methods and has given an accuracy of 97%. This work represents a critical advancement in improving PD diagnosis techniques and emphasizing the importance of deep nested 3D learning and bio-inspired feature selection.

Exploring the hub Genes and Potential Mechanisms of Complement system-related Genes in Parkinson Disease: Based on Transcriptome Sequencing and Mendelian Randomization.

An accurate diagnosis of Parkinson's disease (PD) remains challenging and the exact cause of the disease is unclean. The aims are to identify hub genes associated with the complement system in PD and to explore their underlying molecular mechanisms. Initially, differentially expressed genes (DEGs) and key module genes related to PD were mined through differential expression analysis and WGCNA. Then, differentially expressed CSRGs (DE-CSRGs) were obtained by intersecting the DEGs, key module genes and CSRGs. Subsequently, MR analysis was executed to identify genes causally associated with PD. Based on genes with significant MR results, the expression level and diagnostic performance verification were achieved to yield hub genes. Functional enrichment and immune infiltration analyses were accomplished to insight into the pathogenesis of PD. qRT-PCR was employed to evaluate the expression levels of hub genes. After MR analysis and related verification, CD93, CTSS, PRKCD and TLR2 were finally identified as hub genes. Enrichment analysis indicated that the main enriched pathways for hub genes. Immune infiltration analysis found that the hub genes showed significant correlation with a variety of immune cells (such as myeloid-derived suppressor cell and macrophage). In the qRT-PCR results, the expression levels of CTSS, PRKCD and TLR2 were consistent with those we obtained from public databases. Hence, we mined four hub genes associated with complement system in PD which provided novel perspectives for the diagnosis and treatment of PD.

A rare patient with Parkinson's disease presenting with isolated progressive micrographia.

Although handwriting impairment is a frequent sign of Parkinson's disease (PD), its significance in the evaluation processes of these patients may be overlooked among physicians. Therefore, we would like to report an illustrative patient who presented with isolated micrographia initially; but received the diagnosis of PD in the follow-up.