Combined diagnosis for Parkinson's disease via gait and eye movement disorders.

BACKGROUND AND OBJECTIVES: With the discovery of the potential role of gait and eye movement disorders in Parkinson's disease (PD) recognition, we intend to investigate the combined diagnostic value of gait and eye movement disorders for PD. METHODS: We enrolled some Chinese PD patients and healthy controls and separated them into the training and validation sets based on enrollment time. Performance in five oculomotor paradigms and in one gait paradigm was examined using an infrared eye tracking device and a wearable gait analysis device. We developed and validated a combined model for PD diagnosis via multivariate stepwise logistic regression analysis. Furthermore, subgroup comparisons and multi-model comparison were performed to assess its applicability and advantages. RESULTS: A total of 145 PD patients and 80 healthy controls in China were recruited. The pro-saccade velocity, the trunk-sway max, and the turn mean angular velocity were finally screened out for the model development. Incorporating age factor, the ternary model demonstrated more satisfactory performance on ROC (AUC of 0.953 in the training set and AUC of 0.972 in the validation set), calibration curve, and decision curve. A nomogram was drawn to visualize the model. The combined model outperforms individual models with a broad application and the unique diagnostic value for early detection of PD patients, especially TD-PD patients. CONCLUSION: We demonstrated the presence of gait and eye movement disorders, as well as the feasibility, applicability, and superiority of employing them together to diagnose PD.

Comprehensive analysis of clinical and biological features in Parkinson's disease associated with the LRRK2 G2019S mutation: Data from the PPMI study.

The Parkinson's Progression Marker Initiative (PPMI) aims to identify biomarkers for Parkinson's disease (PD) risk, onset, and progression. This study focuses on the G2019S missense mutation in the LRRK2 gene, which is associated with hereditary and sporadic PD. Utilizing data from the PPMI database, we conducted an analysis of baseline clinical characteristics, as well as serum and cerebrospinal fluid levels in two groups: patients with PD with the G2019S mutation (PD + G2019S) and patients with PD without the mutation (PD-G2019S). Multiple linear regression and longitudinal analysis were performed, controlling for confounding factors. Compared to the PD-G2019S group, the PD + G2019S group showed more obvious initial motor dysfunction-higher baseline Movement Disorder Society-Sponsored Revision of the Unified Parkinson Disease Rating Scale (MDS-UPDRS) scores (false discovery rate [FDR]-adjusted p < 0.001), but progressed more slowly. Mechanism of Coordinated Access and activities of daily living (ADL) scores were lower at baseline (FDR-adjusted p < 0.001), whereas Scales for Outcomes of Parkinson's Disease (SCOPA)-Thermoregulatory (FDR-adjusted p = 0.015) scores were higher, emphasizing the increase of non-motor symptoms associated with LRRK2-G2019S mutation. During the follow-up period, the motor and non-motor symptoms changed dynamically with time, and there were longitudinal differences in the scores of MDS-UPDRS (FDR-adjusted PI = 0.013, PII = 0.008, PIV < 0.001), Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease (FDR-adjusted p = 0.027), SCOPA-Thermoregulatory (FDR-adjusted p = 0.021), and ADL (FDR-adjusted p = 0.027) scale scores. PD associated with the LRRK2 G2019S mutation demonstrated more severe symptoms at baseline but slower progression. Motor complications and thermoregulatory disorders were more pronounced.

Adversarially Trained Persistent Homology Based Graph Convolutional Network for Disease Identification Using Brain Connectivity.

Brain disease propagation is associated with characteristic alterations in the structural and functional connectivity networks of the brain. To identify disease-specific network representations, graph convolutional networks (GCNs) have been used because of their powerful graph embedding ability to characterize the non-Euclidean structure of brain networks. However, existing GCNs generally focus on learning the discriminative region of interest (ROI) features, often ignoring important topological information that enables the integration of connectome patterns of brain activity. In addition, most methods fail to consider the vulnerability of GCNs to perturbations in network properties of the brain, which considerably degrades the reliability of diagnosis results. In this study, we propose an adversarially trained persistent homology-based graph convolutional network (ATPGCN) to capture disease-specific brain connectome patterns and classify brain diseases. First, the brain functional/structural connectivity is constructed using different neuroimaging modalities. Then, we develop a novel strategy that concatenates the persistent homology features from a brain algebraic topology analysis with readout features of the global pooling layer of a GCN model to collaboratively learn the individual-level representation. Finally, we simulate the adversarial perturbations by targeting the risk ROIs from clinical prior, and incorporate them into a training loop to evaluate the robustness of the model. The experimental results on three independent datasets demonstrate that ATPGCN outperforms existing classification methods in disease identification and is robust to minor perturbations in network architecture. Our code is available at https://github.com/CYB08/ATPGCN.

Disease trajectories in older adults with non-AD pathologic change and comparison with Alzheimer's disease pathophysiology: A longitudinal study.

Based on the 'AT(N)' system, individuals with normal amyloid biomarkers but abnormal tauopathy or neurodegeneration biomarkers are classified as non-Alzheimer's disease (AD) pathologic change. This study aimed to assess the long-term clinical and cognitive trajectories of individuals with non-AD pathologic change among older adults without dementia, comparing them to those with normal AD biomarkers and AD pathophysiology. Analyzing Alzheimer's Disease Neuroimaging Initiative data, we evaluated clinical outcomes and conversion risk longitudinally using mixed effects models and multivariate Cox proportional hazard models. We found that compared to individuals with A-T-N-, those with abnormal tauopathy or neurodegeneration biomarkers (A-T + N-, A-T-N + , and A-T + N + ) had a faster rate of cognitive decline and disease progression. Individuals with A-T + N + had a faster rate of decline than those with A-T + N-. Additionally, in individuals with the same baseline tauopathy and neurodegeneration biomarker status, the presence of baseline amyloid could accelerate cognitive decline and clinical progression. These findings provide a foundation for future studies on non-AD pathologic change and its comparison with AD pathophysiology.

Exploring the links among peripheral immunity, biomarkers, cognition, and neuroimaging in Alzheimer's disease.

INTRODUCTION: We analyzed relationships among peripheral immunity markers, cognition, Alzheimer's disease (AD)-related biomarkers, and neuroimaging to understand peripheral immunity involvement in AD. METHODS: Peripheral immunity markers were assessed in AD, non-AD neurodegenerative disorders, and controls, examining their connections with cognition, AD-related biomarkers, and neuroimaging using multiple regression models. RESULTS: The study included 1579 participants. Higher levels of white blood cell, neutrophil, monocyte, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and lower lymphocyte-to-monocyte ratio (LMR) were associated with cognitive decline and more severe anxiety and depression. The impact of lower LMR, lymphocyte count, and higher NLR on cognitive decline is mediated through cerebrospinal fluid amyloid beta (Aß) levels. Additionally, increased PLR, NLR, and SII were associated with brain atrophy and hippocampal Aß deposition (amyloid positron emission tomography). DISCUSSION: Peripheral immunity markers offer a non-invasive and cost-effective means of studying AD-related pathophysiological changes, providing valuable insights into its pathogenesis and treatment. Highlights: Peripheral immunity markers linked to cognitive decline and anxiety/depression.Low LMR, LYM, and high NLR linked to reduced CSF Aß, impacting cognition.High PLR, NLR, SII associated with brain atrophy and hippocampal Aß deposition.

Associations Between TREML2 Gene Variants and Alzheimer's Disease: Biomarkers, Neuroimage, and Cognition.

BACKGROUND: Recent genetic research identified a protective factor against late-onset Alzheimer's disease (AD) in Caucasians, a variant called rs3747742-C in the TREML2 gene. However, the roles of other TREML2 variants in AD have not been fully explored. OBJECTIVE: We conducted a focused analysis of 16 TREML2 variants, examining their connection to AD by studying their correlation with cerebrospinal fluid (CSF) proteins, neuroimage, and cognition in the Alzheimer's Disease Neuroimaging Initiative database (ADNI). METHODS: A multiple linear regression model was utilized to estimate potential associations between TREML2 genotypes and various endophenotypes in the entire ADNI sample at baseline, with age, gender, years of education, and APOE ɛ4 status included as covariates. To examine changes in clinical outcomes over time, linear mixed-effects models were employed. RESULTS: We found that the SNP rs17328707-A was associated with higher ADNI-VS scores, smaller ventricles, and larger middle temporal volume at baseline. The SNP rs6915083-G was linked to lower CSF t-tau and p-tau levels, and higher CSF Aß levels. The SNP rs9394766-G was associated with a smaller hippocampus and larger ventricles at baseline. In longitudinal cohorts, the rs6915083-G SNP was associated with changes in ADNI-MEM and ADNI-EF scores, as well as the rate of hippocampal and middle temporal atrophy. CONCLUSION: Our findings reveal that TREML2 gene variants have different effects on AD. Two variants are protective, while one may be a risk factor. This enhances our understanding of AD genetics and could guide future research and personalized treatments.

Abnormal eye movements in Parkinson's disease: From experimental study to clinical application.

Parkinson's disease (PD) is a neurodegenerative disease that integrates a series of motor symptoms and non-motor symptoms, making early recognition challenging. The exploration of biomarkers is urgently required. Abnormal eye movements in PD have been reported to appear in a variety of ways since eye tracking technology was developed, such as decreased saccade amplitude, extended saccade latency, and unique saccade patterns. Non-invasive, objective and simple eye tracking has the potential to provide effective biomarkers for the PD diagnosis, progression and cognitive impairment, as well as ideas for research into the occurrence and treatment strategy of motor symptoms. In this review, we introduced the fundamental eye movement patterns and typical eye movement paradigms (such as fixation, pro-saccade, anti-saccade, smooth tracking, and visual search), summarized the symptoms of various ocular motor abnormalities in PD, and discussed the research implications of oculomotor investigation to the pathogenesis of PD and related motor symptoms, as well as the clinical implications as biomarkers and its inspiration on treatment.

Clinical characteristics in early Parkinson's disease with excessive daytime sleepiness: A cross-sectional and longitudinal study.

We aimed to explore excessive daytime sleepiness (EDS) and correlates of clinical characteristics by using cross-sectional and longitudinal analyses from the Parkinson's Progression Markers Initiative database. Four hundred twenty-three patients with Parkinson's disease (PD; EDS: non-EDS = 357:66) and 195 healthy controls (HCs; EDS: nEDS = 171:24) were enrolled in our study at baseline. Multiple linear and linear mixed-effects models were used to research the relationships between EDS/daytime sleepiness severity and clinical characteristics. Relationships between the change rates of clinical characteristics and daytime sleepiness severity were further investigated through multiple linear regression models. Mediating effect analysis was used to determine whether autonomic dysfunction was the mediator between cognition assessments and daytime sleepiness severity. Patients with PD with EDS and greater daytime sleepiness severity presented faster cognitive decline, high possibility for rapid eye movement sleep behavior disorder, autonomic dysfunction, depression, and anxiety from cross-sectional and longitudinal analyses. Furthermore, HC individuals with EDS showed a higher striatal binding ratio of the right putamen, right striatum, and mean striatum. Autonomic dysfunction may act as a mediator between PD and cognitive decline. In early PD, EDS and daytime sleepiness severity were related to several clinical variables, suggesting that EDS might play an essential role in regulating PD progression.

CD33 polymorphisms and Parkinson's disease Parkinson's disease in northern Chinese Han population: A case-control study.

OBJECTIVE: Parkinson's disease (PD) represents the multisystem illness involving immunological and neuroinflammatory dysfunction. The present work focused on evaluating link of CD33 single nucleotide polymorphisms (SNPs) with PD vulnerability of the northern Chinese Han people, considering CD33's role as a critical immunoregulatory receptor in neuroinflammatory responses. METHODS: The present case-control study included 475 PD cases together with 475 normal controls. A further division of PD patients into two categories was made: 74 patients with early-onset PD (EOPD; onset age ≤ 50 years) and 401 patients with late-onset PD (LOPD; onset age > 50 years). DNA extraction was conducted, followed by genotyping for 2SNPs of CD33 polymorphisms with polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). RESULTS: Alleles (G vs. A, P = 0.028) and AA genotypes (P = 0.042) of rs12985029 were significantly different between the groups. Distinctions were observed between the two groups in the recessive, co-dominant, and additive models (nominal P = 0.030, nominal P = 0.045, and P = 0.032). AA genotype frequency among male PD was higher compared to corresponding male controls (P = 0.034), and in the male group allele A was a factor causing the disease (P = 0.026). The rs12985029 genotypes and allele frequency were different in EOPD compared with LOPD (P = 0.002, P = 0.002, respectively), and in LOPD group relative to healthy control group (P = 0.020 and P = 0.004, separately). Regarding the rs3826656 polymorphism, the frequency of GA genotype was higher in the control group than in the case group (nominal P = 0.036). Overdominance and co-dominant models were different between these groups (P = 0.026, nominal P = 0.030). Subgroup analysis revealed genotype frequency differences between rs3826656 LOPD group and control group (P = 0.018). Furthermore, relationship between rs3826656 and rs12985029 (D' = 0.162, r2 = 0.021) did not reach a complete level of linkage disequilibrium (LD) of northern Chinese Han people. CONCLUSION: This study establishes an association between CD33 rs12985029 and rs3826656 polymorphisms and PD risk among the selected northern Chinese Han people. The GA genotype, rs3826656, may act as a protective factor against PD, while the A allele, rs12985029,could be genetic risk factor related to PD. Future research should include larger sample sizes and other human populations to further investigate how CD33 polymorphisms contribute to PD.

Evaluation of Nocturnal Symptoms in Chinese Parkinson's Disease Patients Based on the PDSS-2 Scale: A Multicenter Cross-Sectional Study.

BACKGROUND: Nocturnal symptoms have a significant effect on the quality of life in Parkinson's disease (PD) patients. OBJECTIVE: This study aimed to investigate the prevalence and associated factors of nocturnal symptoms in Chinese PD patients. METHODS: This multicenter cross-sectional study included 1,500 patients with primary PD from 18 centers in China was carried out between February 2019 and February 2020. Questionnaires including Parkinson's disease sleep scale 2 (PDSS-2), Parkinson's disease questionnaire 8 (PDQ-8), Beck depression inventory (BDI), and generalized anxiety disorder scale 7 (GAD-7) were used to assess nocturnal symptoms, quality of life, depression, and anxiety. RESULTS: Among 1,500 Chinese PD patients, 576 (38.4%) reported nocturnal symptoms. Of them, 59.2% were older than 65 years. The PDQ-8 total score was higher in patients with nocturnal symptoms (p < 0.01). Moderate and severe depression was reported more often in patients with nocturnal symptoms (p < 0.01), and the occurrence and severity of anxiety were higher as well (p < 0.01). Longer disease duration and higher Hoehn-Yahr (HY) stage were independently associated with nocturnal symptoms (p < 0.01). Education level, depression, disease course, HY stage, and nocturnal symptoms were related to the quality of life in Chinese PD patients (p < 0.01). CONCLUSION: Our study found that 38.4% of Chinese PD patients have nocturnal symptoms, even in early and mid-stage PD. Nocturnal symptoms were associated with worse quality of life and higher incidences of depression and anxiety. Nocturnal symptoms should be included in the assessment and care plan, especially in patients with longer disease courses and higher HY stages.

Repetitive transcranial magnetic stimulation alleviates glial activation through suppressing HMGB1/TLR4 pathway in a rat model of Parkinson's disease.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) has been demonstrated to be effective in Parkinson's disease (PD), but whether rTMS treatment has a relieving effect on neuroinflammation remains to be investigated. In this article, we explored the effects of rTMS on forelimb use asymmetry and neuroinflammation-related mechanisms in a 6-hydroxydopamine (6-OHDA)-induced PD rat model. METHODS AND RESULTS: Rats in the 6-OHDA+rTMS group received 10 Hz rTMS daily for 4 weeks. Behavioral tests (the cylinder test) were performed at the 3rd and 7th weeks after the operation. Astrocyte and microglia activation and protein levels of tyrosine hydroxylase(TH), high-mobility group box 1(HMGB1) and toll-like receptors 4(TLR4) were investigated by immunohistochemistry and Western blot analyses, respectively. After 4 weeks of treatment, forelimb use asymmetry was ameliorated in the 6-OHDA+rTMS group. Consistent with the behavioral tests, rTMS increased TH in the substantia nigra (SN) and the striatum of PD rats. High glial activation and HMGB1/TLR4 expression in the SN and the striatum were observed in the 6-OHDA group, while rTMS alleviated these changes. CONCLUSIONS: This study showed that rTMS might be a promising method for alleviating neuroinflammation in PD rat models, and the effects might be mediated through the downregulation of the HMGB1/TLR4 pathway.

Disease trajectories in elders with suspected non-Alzheimer's pathophysiology and its comparison with Alzheimer's disease pathophysiology: a longitudinal study.

Background: According to the new 'AT(N)' system, those with a normal amyloid biomarker but with abnormal tauopathy or biomarkers of neurodegeneration or neuronal injury, have been labeled suspected non-Alzheimer's pathophysiology (SNAP). We aimed to estimate the long-term clinical and cognitive trajectories of SNAP individuals in non-demented elders and its comparison with individual in the Alzheimer's disease (AD) pathophysiology using 'AT(N)' system. Methods: We included individuals with available baseline cerebrospinal fluid (CSF) Aß (A), CSF phosphorylated tau examination (T) and 18F-uorodeoxyglucose PET or volumetric magnetic resonance imaging (N) from the Alzheimer's Disease Neuroimaging Initiative database. Longitudinal change in clinical outcomes are assessed using linear mixed effects models. Conversion risk from cognitively normal (CN) to cognitively impairment, and conversion from mild cognitive impairment (MCI) to dementia are assessed using multivariate Cox proportional hazard models. Results: Totally, 366 SNAP individuals were included (114 A-T-N-, 154 A-T + N-, 54 A-T-N + and 44 A-T + N+) of whom 178 were CN and 188 were MCI. Compared with A-T-N-, CN elders with A-T + N-, A-T-N + and A-T + N + had a faster rate of ADNI-MEM score decline. Moreover, CN older individuals with A-T + N + also had a faster rate of decline in ADNI-MEM score than those with A-T + N- individuals. MCI patients with A-T + N + had a faster rate of ADNI-MEM and ADNI-EF decline and hippocampal volume loss compared with A-T-N- and A-T + N- profiles. CN older individuals with A-T + N + had an increased risk of conversion to cognitive impairment (CDR-GS ≥ 0.5) compared with A-T + N- and A-T-N-. In MCI patients, A-T + N + also had an increased risk of conversion to dementia compared with A-T + N- and A-T-N-. Compared with A-T + N-, CN elders and MCI patients with A + T + N- and A + T + N + had a faster rate of ADNI-MEM score, ADNI-EF score decline, and hippocampal volume loss. CN individuals with A + T + N + had a faster rate of ADNI-EF score decline compare with A-T + N + individuals. Moreover, MCI patients with A + T + N + also had a faster rate of decline in ADNI-MEM score, ADNI-EF score and hippocampal volume loss than those with A-T + N + individuals. Conclusions: The findings from clinical, imaging and biomarker studies on SNAP, and its comparison with AD pathophysiology offered an important foundation for future studies.

Effects of soluble TREM2 on motor progression in Parkinson's disease.

OBJECTIVES: To determine whether sTREM2 is changed during the pathogenesis of PD and reflect motor decline in PD individuals. METHODS: The cerebrospinal fluid (CSF) from PD and healthy individuals were obtained to measure the expression of sTREM2 and further to evaluate the motor function at baseline and after four years of follow-up using the Parkinson's Progression Markers Initiative (PPMI) database. The relationship between motor disease progression at baseline and longitudinal CSF sTREM2 was evaluated by linear mixed-effects (LME) and multiple linear regression (MLR) models. The change rates of the motor symptoms and sTREM2 level in CSF were further rigorously analyzed using the LME model. Cox proportional-hazards regression models were used to evaluate the predictive values of sTREM2 in CSF for motor progression. The regulatory role of CSF α-syn and Tau between sTREM2 and motor assessments was evaluated by Mediating effect analysis. RESULTS: We found no significant difference in CSF sTREM2 levels between the PD and HC groups (p = 0.155). However, late-onset PD patients had higher CSF sTREM2 levels than early-onset PD patients (p = 0.044). The basal levels of sTREM2 could predict motor progression over the four years of follow-up. The change rate of CSF sTREM2 was correlated with the progressive deterioration of motor function in PD individuals. Our observations also showed that CSF Tau was a significant mediator of the association between CSF sTREM2 and total UPDRS scores and UPDRS III and tremor at baseline with 26.5% and 33.5%, and 28.7% mediation, respectively. CONCLUSION: Our results indicated that CSF sTREM2 was associated with the prognosis of PD motor symptoms. Besides, CSF Tau could effectively mediate the association of sTREM2 with motor progression.

Associations of striatal dopamine transporter binding with motor and non-motor symptoms in early Parkinson's disease.

Dopamine transporter (DAT) imaging is an in vivo tool to assess presynaptic dopaminergic function in the clinical practices of Parkinson's disease (PD). Current clinical practices focused on qualitatively visual interpretation of DAT imaging, whereas quantitative analyses are potentially more helpful when monitoring the progression of PD. Previous cross-sectional studies indicated certain motor and non-motor features were associated with striatal DAT binding, whereas limited data were reported in terms of the longitudinal correlation between clinical features of PD with striatal DAT binding. The purpose of our study is to clarify current and longitudinal correlations between striatal DAT binding and clinical measures. A total of 352 untreated PD individuals and 167 healthy controls with complete baseline clinical measures and neuroimaging data were identified from the Parkinson's Progression and Markers Initiative (PPMI) database. Patients with PD underwent DAT imaging at the screening visit and following months 12, 24, and 48. Multiple linear regression models and linear mixed-effect models were respectively conducted to investigate the cross-sectional and longitudinal correlation between clinical characteristics and DAT binding. Associations between changes in clinical characteristics and changes in DAT binding were further evaluated and the Spearman rank correlation coefficients were reported. In the cross-sectional analysis, baseline striatal DAT binding was significantly associated with the Hoehn and Yahr scale, the Movement Disorder Society-Sponsored Revision of the Unified Parkinson Disease Rating Scale (MDS-UPDRS) scores, the rigidity scores, and the axial scores in PD individuals (false discovery rate [FDR]-adjusted p = 0.0017 for all above). Patients who developed freezing of gait had lower striatal DAT binding (FDR-adjusted p = 0.0161). Healthy controls who had higher tremor scores and suffered more severe olfactory dysfunction had lower striatal DAT binding (FDR-adjusted p = 0.0257 for all above). Longitudinal analysis indicated that baseline severity of rapid-eye-movement sleep behavior disorder was significantly associated with longitudinal striatal DAT binding in patients with PD (FDR-adjusted p = 0.0120). Furthermore, changes in MDS-UPDRS scores and the State-Trait Anxiety Inventory (STAI) scores demonstrated significant correlations with changes in striatal DAT binding over 4 years (p = 0.005 and p = 0.032, respectively). Our findings clarified quantitative associations between certain motor and non-motor features with current and future striatal dopamine binding, suggesting the feasibility of using DAT images as a progression predictive marker for PD. Further studies are needed to investigate correlations between different regional dopamine binding with specific clinical features.

Association of AQP4 single nucleotide polymorphisms (rs335929 and rs2075575) with Parkinson's disease: A case-control study.

OBJECTIVE: The glymphatic system plays an important role in brain waste removal and is functionally and structurally dependent on astrocyte aquaporin-4 (AQP4). Genetic variation in the AQP4 gene has therefore been hypothesized to be associated with genetic susceptibility to neurodegenerative diseases. This study aimed to investigate whether two specific single nucleotide polymorphisms (SNP) in the AQP4 gene, rs335929, and rs2075575, are associated with the risk and clinical features of PD. METHODS: A total of 950 participants, including 475 patients with sporadic PD and 475 independent healthy controls, were included in this case-control study. Two SNPs (rs335929 and rs2075575) of the AQP4 gene were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Sanger sequencing was used to determine whether the genotyping results were accurate. A chi-square (χ2) test was used to compare the frequencies of alleles and genotypes between patients and controls. Logistic regression was used to calculate dominance ratios (OR) and 95% confidence intervals (CI). RESULTS: The difference between rs2075575 in the dominant model (GG vs GA + AA: P = 0.019) and the overdominant model (GG + AA vs GA: P = 0.013) was statistically significant. Subgroup analysis showed that the frequency of the rs2075575 A allele was significantly higher in female PD patients than in matched female controls (P = 0.017). rs2075575 A allele was significantly more frequent in LOPD patients than in matched elderly controls (P = 0.033). rs335929 polymorphism was not significantly correlated with PD susceptibility in either the overall or subgroup analysis. Haplotype analysis between the two SNPs did not show an association with PD susceptibility. In addition, we found that the rs2075575 G allele was significantly associated with Rapid Eye Movement Behaviour Disorder (RBD) (P = 0.044), and the rs335929 A allele with memory impairment (P = 0.028) in PD. CONCLUSION: The AQP4 gene rs2075575 polymorphism may be associated with PD susceptibility, but not the rs335929 polymorphism. rs2075575 is associated with RBD and rs335929 is associated with memory cognition. Regulation of the glymphatic system by interfering with the genetics of AQP4 and thus influencing the pathology of PD may be a direction worth investigating. Studies in larger sample sizes and across ethnicities are essential for further understanding the potential association between AQP genes and PD pathogenesis.

The associations of cerebrospinal fluid biomarkers with cognition, and rapid eye movement sleep behavior disorder in early Parkinson's disease.

Background: In Parkinson's disease (PD), levels of cerebrospinal fluid (CSF) biomarkers and progression of non-motor symptoms are associated, but the specifics are not yet clear. Objective: The aim of this study was to investigate the associations of non-motor symptoms with CSF biomarkers in PD. Materials and methods: We assessed 487 individuals from the Parkinson's Progression Markers Initiative (PPMI), consisting of 155 healthy controls (HCs) and 332 individuals with PD. Patients with PD were grouped according to non-motor symptoms and compared CSF α-synuclein (α-syn), amyloid-beta 1-42 (Aß1-42), and total tau (t-tau) levels. Multiple linear regressions were used in baseline analysis and linear mixed-effects models in longitudinal analysis. Analyses of mediating effects between cognition and CSF biomarkers were also performed. Results: At baseline, PD patients with cognitive impairment (PDCI) exhibited significantly lower CSF α-syn (ß = -0.1244; P = 0.0469), Aß (ß = -0.1302; P = 0.0447), and t-tau (ß = -0.1260; P = 0.0131) levels than PD patients without cognitive impairment (PDCU). Moreover, a faster decline of α-syn (ß = -0.2152; P = 0.0374) and Aß (ß = -0.3114; P = 0.0023) and a faster rise of t-tau (ß = -0.1534; P = 0.0274) have been found in longitudinal analysis. The Aß positive group showed an earlier decline in cognitive performance (ß = -0.5341; P = 0.0180) compared with the negative Aß group in both analyses. In addition, we found that PD patients with probable rapid eye movement sleep behavior disorder (pRBD) showed decreased CSF α-syn (ß = -0.1343; P = 0.0033) levels. Finally, mediation analysis demonstrated that olfactory function partially mediated the relationship between cognition and CSF biomarkers levels. Conclusion: Our study shows that CSF biomarkers are associated with cognition at baseline and longitudinally. Cognitive impairment is more severe in patients with a heavier Aß burden. CSF α-syn decreased in PD patients with pRBD. This study suggests that early recognition of the increased risk of non-motor symptoms is important for disease surveillance and may be associated with the pathological progression of CSF markers.

Multi-predictor modeling for predicting early Parkinson's disease and non-motor symptoms progression.

Background: Identifying individuals with high-risk Parkinson's disease (PD) at earlier stages is an urgent priority to delay disease onset and progression. In the present study, we aimed to develop and validate clinical risk models using non-motor predictors to distinguish between early PD and healthy individuals. In addition, we constructed prognostic models for predicting the progression of non-motor symptoms [cognitive impairment, Rapid-eye-movement sleep Behavior Disorder (RBD), and depression] in de novo PD patients at 5 years of follow-up. Methods: We retrieved the data from the Parkinson's Progression Markers Initiative (PPMI) database. After a backward variable selection approach to identify predictors, logistic regression analyses were applied for diagnosis model construction, and cox proportional-hazards models were used to predict non-motor symptom progression. The predictive models were internally validated by correcting measures of predictive performance for "optimism" or overfitting with the bootstrap resampling approach. Results: For constructing diagnostic models, the final model reached a high accuracy with an area under the curve (AUC) of 0.93 (95% CI: 0.91-0.96), which included eight variables (age, gender, family history, University of Pennsylvania Smell Inventory Test score, Montreal Cognitive Assessment score, RBD Screening Questionnaire score, levels of cerebrospinal fluid α-synuclein, and SNCA rs356181 polymorphism). For the construction of prognostic models, our results showed that the AUC of the three prognostic models improved slightly with increasing follow-up time. The overall AUCs fluctuated around 0.70. The model validation established good discrimination and calibration for predicting PD onset and progression of non-motor symptoms. Conclusion: The findings of our study facilitate predicting the individual risk at an early stage based on the predictors derived from these models. These predictive models provide relatively reliable information to prevent PD onset and progression. However, future validation analysis is still needed to clarify these findings and provide more insight into the predictive models over more extended periods of disease progression in more diverse samples.

Neurofilament light as a biomarker for motor decline in Parkinson's disease.

Objectives: The aim of this study was to determine whether neurofifilament light (NfL) could reflect motor decline and compare the predictive values of cerebrospinal fluid (CSF) and serum NfL in individuals with PD. Methods: CSF/serum samples were collected from patients with PD and healthy controls (HCs) with motor assessments at baseline and after three years of follow-up from the Parkinson's Progression Markers Initiative (PPMI). Multiple linear regression models and linear mixed-effects models were used to investigate the associations of motor assessments with baseline and longitudinal CSF/serum NfL. Associations between the change rates of motor assessments and CSF/serum NfL were further investigated via multiple linear regression models. Mediating effect analysis was used to research whether CSF alpha-synuclein (α-syn) acts as the mediator between NfL and motor assessments. Results: We found patients with PD had higher baseline CSF/serum NfL levels than HCs. Both baseline CSF/serum NfLs and their change rates predicted measurable motor decline in PD assessed by different motor scores. Baseline serum NfL and its rate of change were strongly associated with CSF NfL levels in patients with PD (P < 0.001). Besides, there were also significant differences in CSF/serum NfL levels and predicted values of motor decline between men and women with PD. Mediating effect analysis showed CSF α-syn mediated the effect of CSF NfL on total Unified Parkinson's Disease Rating Scale (UPDRS) scores and UPDRSIII with 30.6 and 20.2% mediation, respectively. Conclusion: Our results indicated that NfL, especially serum NfL concentration, could serve as an easily accessible biomarker to monitor the severity and progression of motor decline in individuals with PD, especially in men with PD. Besides, CSF α-syn acts as a mediator between NfL and motor progression.

Update to the Treatment of Parkinson's Disease Based on the Gut-Brain Axis Mechanism.

Gastrointestinal (GI) symptoms represented by constipation were significant non-motor symptoms of Parkinson's disease (PD) and were considered early manifestations and aggravating factors of the disease. This paper reviewed the research progress of the mechanism of the gut-brain axis (GBA) in PD and discussed the roles of α-synuclein, gut microbiota, immune inflammation, neuroendocrine, mitochondrial autophagy, and environmental toxins in the mechanism of the GBA in PD. Treatment of PD based on the GBA theory has also been discussed, including (1) dietary therapy, such as probiotics, vitamin therapy, Mediterranean diet, and low-calorie diet, (2) exercise therapy, (3) drug therapy, including antibiotics; GI peptides; GI motility agents, and (4) fecal flora transplantation can improve the flora. (5) Vagotomy and appendectomy were associated but not recommended.

Associations of Sleep Disorders With Depressive Symptoms in Early and Prodromal Parkinson's Disease.

Background: Non-motor symptoms, including sleep disorders and depression, are common in Parkinson's disease (PD). The purpose of our study is to explore the effect of sleep disorders, including the probable rapid eye movement (REM) sleep behavior disorder (pRBD) and the daytime sleepiness, on depressive symptoms in patients with early and prodromal PD. Methods: A total of 683 participants who obtained from the Parkinson Progression Markers Initiative (PPMI) were included, consisting of 423 individuals with early PD, 64 individuals with prodromal PD, and 196 healthy controls (HCs), who were followed up to 5 years from baseline. Multiple linear regression models and linear mixed-effects models were conducted to explore the relationship between sleep disorders and depression at baseline and longitudinally, respectively. Multiple linear regression models were used to further investigate the association between the change rates of daytime sleepiness score and depression-related score. Mediation analyses were also performed. Results: At baseline analysis, individuals with early and prodromal PD, who had higher RBD screening questionnaire (RBDSQ) score, or who were considered as pRBD, or who manifested specific behaviors of RBD (things falling down when sleep or disturbance of sleep), showed significantly the higher score of depression-related questionnaires. Our 5-year follow-up study showed that sleep disorders, including pRBD and daytime sleepiness, were associated with the increased depressive-related score in individuals with early and prodromal PD. Interestingly, we also found that the increased possibilities of daytime sleepiness were associated with depressive-related score. Finally, mediation analysis demonstrated that the relationship between RBD and depressive symptoms was partially mediated by autonomic symptoms, such as postural hypertension, salivation, dysphagia, and constipation. Conclusion: Our study shows that sleep disorders, including pRBD and daytime sleepiness, are associated with depression at baseline and longitudinally, which is partially mediated by the autonomic dysfunction in early and prodromal PD, with an implication that sleep management is of great value for disease surveillance.