Detecting depression in Parkinson disease: A systematic review and meta-analysis

Pattern of Cortical Thickness in Depression Among Early-stage Parkinson's Disease: A Potential Neuroimaging Indicator for Early Recognition

PURPOSE

This study aims to investigate the early change in cortical thickness and surface area in early-stage depressed PD (dPD) patients, and its associations with severity of depression.

METHODS

59 patients with dPD, 27 patients with non-depressed PD (ndPD), and 43 healthy controls (HC) were recruited. The dPD patients were subclassified into mild-depressed PD (mi-dPD, n=24), moderate-depressed PD (mo-dPD, n=21) and severe-depressed PD (se-dPD, n=14) subgroups. Structural MRI and surface-based morphometry analysis were applied to compare differences in cortical thickness and surface area among groups, and their correlations with Beck Depression Inventory (BDI) scores were analyzed.

RESULTS

Compared with ndPD, dPD exhibited cortical thinning in the dorsolateral prefrontal cortex (dlPFC, mainly invoving the left superior frontal and bilateral middle frontal gyri), the right pars opercularis and bilateral lateral occipital gyri. The mean cortical thickness values within these regions negatively correlated with BDI scores. Subgroup analysis revealed that patients with mi-dPD had cortical thinning only in the right middle frontal gyrus, while se-dPD showed cortical thinning more extensively involving the right fusiform gyrus, posterior cingulate gyrus, and pars opercularis. There was no significant change in cortical surface area in either the dPD or its subgroups.

CONCLUSION

Our findings indicated that PD-related depression was associated with decrease of cortical thickness, instead of surface area, of which the patterns correlated with the severity of depression. Cortical thinning in dlPFC, mainly involving the left middle frontal gyrus, may serve as a potential neuroimaging indicator for early recognition of depression in PD patients.

Non-motor Symptoms and Treatments in Parkinson's Disease

SYNOPSIS

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms. The non-motor features may precede the onset of motor symptoms and occur throughout all stages of PD. The non-motor symptoms reflect multisystem involvement of the central and peripheral nervous systems, multiple neurotransmitters, and multiple pathologies. PD management necessitates a comprehensive approach to address non-motor symptoms, including pharmacologic and non-pharmacological interventions and often multiple different disciplines or specialists in the PD care team. This review article discusses symptoms and treatments for the non-motor symptoms of PD including those affecting mood, cognition, behavior, sleep, autonomic function, and sensory systems.

Risk factors associated with severe progression of Parkinson's disease: random forest and logistic regression models

Background and aim

Parkinson's disease (PD) is a neurodegenerative disorder with significant variability in disease progression. Identifying clinical and environmental risk factors associated with severe progression is essential for early diagnosis and personalized treatment. This study evaluates the performance of Random Forest (RF) and Logistic Regression (LR) models in forecasting the major risk factors associated with severe PD progression.

Methods

We performed a retrospective analysis of 378 PD patients (aged 40-75 years) with at 2 years of follow-up. The dataset included patient demographics, clinical features, medication history, comorbidities, and environmental exposures. The data were randomly split into a training group (70%) and a validation group (30%). Both the RF and LR models were trained on the training set, and performance was assessed through accuracy, sensitivity, specificity, and the Area Under the Curve (AUC) derived from ROC analysis.

Results

Both models identified similar risk factors for severe PD progression, including older age, tremor-dominant motor subtype, long-term levodopa use, comorbid depression, and occupational pesticide exposure. The RF model outperformed the LR model, achieving an AUC of 0.85, accuracy of 82%, sensitivity of 79%, and specificity of 85%. In comparison, the LR model had an AUC of 0.78, accuracy of 76%, sensitivity of 74%, and specificity of 79%. ROC analysis showed that while both models could distinguish between slow and rapid disease progression, the RF model had stronger discriminatory power, particularly for identifying high-risk patients.

Conclusion

The RF model provides better predictive accuracy and discriminatory power compared to Logistic Regression in identifying risk factors for severe PD progression. This study highlights the potential of machine learning techniques like Random Forest for early risk stratification and personalized management of PD.

Advances in the study of depression and anxiety in Parkinson's disease: A review

Motor symptoms are central to diagnosing Parkinson's disease (PD), but depression and anxiety significantly impact the prognosis and course of PD. For many PD patients, these mental health issues may be the most crucial determinants of quality of life. This study uses an interdisciplinary approach to provide an in-depth understanding of the pathogenesis, diagnostic methods, and therapeutic strategies for depression and anxiety in PD, incorporating neuroscience, psychiatry, and psychology. It aims to offer theoretical support for developing personalized medicine and precise treatments, as well as insights into future research directions. The objective of this study was to systematically sort out the research progress of PD with depression and anxiety and to provide a basis for clinical optimization of treatment strategies. Extensive searches of relevant domestic and international databases, including PubMed, Web of Science, Embase, Cochrane Library, CNKI, etc., were conducted to screen the high-quality research literature on the treatment of PD depression and anxiety in the last decade and to conduct comprehensive analyses and generalizations. Pharmacological treatments, including 5-hydroxytryptamine reuptake inhibitors, norepinephrine system agents, and dopamine agonists, showed some efficacy but with individual differences and side effects. Psychotherapies such as cognitive-behavioral therapy and group counseling improved patient mood. Neuromodulation techniques like deep brain stimulation also showed promise in refractory cases. The combined application of multiple therapeutic approaches shows good prospects in the treatment of depression and anxiety in PD, but in-depth studies are still needed to determine the optimal treatment plan while focusing on individual patient differences to achieve precise treatment.

Attentional Bias in Older Adults with Non-Clinical Depression: An Eye-Tracking Study

BACKGROUND

Cognitive models of depression assert that attentional biases play an important role in the maintenance of depression. However, few studies have explored attentional bias in depressed older adults, and no consistent conclusions have been reached.

METHODS

In the current study, we investigated attentional bias in older adults with non-clinical depression. Older adults aged over 60 with non-clinical depression and without depression were instructed to perform a free viewing task while their eye movements were tracked.

RESULTS

The results showed that, compared to older adults without depression, non-clinically depressed older adults had longer total fixation durations and a greater number of fixations on sad stimuli. Moreover, non-depressed older adults exhibited a preference for pleasant images, whereas this effect was not observed in older adults with non-clinical depression.

CONCLUSION

This study suggested that non-clinically depressed older adults have attentional bias, which is manifested as increased attention to sad stimuli and decreased attention to pleasant stimuli.The current study has functional and potential functional implications.

Identification of Depression Subtypes in Parkinson's Disease Patients via Structural MRI Whole-Brain Radiomics: An Unsupervised Machine Learning Study

OBJECTIVE

Current clinical evaluation may tend to lack precision in detecting depression in Parkinson's disease (DPD). Radiomics features have gradually shown potential as auxiliary diagnostic tools in identifying and distinguishing different subtypes of Parkinson's disease (PD), and a radiomic approach that combines unsupervised machine learning has the potential to identify DPD.

METHODS

Analyze the clinical and imaging data of 272 Parkinson's disease (PD) patients from the PPMI dataset, along with 45 PD patients from the NACC dataset. Extract radiomic features from T1-weighted MRI images and employ principal component analysis (PCA) for dimensionality reduction. Subsequently, apply four unsupervised clustering methods including Gaussian mixture model (GMM), hierarchical clustering, K-means, and partitioning around medoids (PAM) to classify cases in the PPMI dataset into distinct subtypes. Identify high-risk subtypes of DPD on the basis of the time and number of depression progression, and validate these findings using the NACC dataset. The data from the high-risk subtype were divided into a training subtype and a testing subtype in a 7:3 ratio. Multiple logistic regression analysis was conducted on the training subtype data to develop a traditional logistic regression model for the high-risk subtype, which was subsequently compared with a supervised logistic regression model constructed for the entire PPMI cohort. Finally, the performance of both models was evaluated using receiver operating characteristic (ROC) curves. In addition, a decision tree (DT) model was constructed based on independent risk factors of high-risk subtypes and validated using low-risk subtype data. ROC curves were employed to validate this model across training subtype, testing subtype, and low-risk subtype datasets.

RESULTS

The PAM clustering method demonstrates superior performance compared to the other three clustering methods when the number of clusters is 2. High-risk subtypes of DPD can be effectively distinguished in both the PPMI and NACC datasets. A traditional logistic regression model was developed based on rapid-eye-movement behavior disorder, UPDRS I score, UPDRS II score, and ptau in high-risk subgroups. This model exhibits a diagnostic efficacy (AUC = 0.731) that surpasses that of the traditional regression model constructed using the entire PPMI cohort (AUC = 0.674). The prediction model based on high-risk subtypes had AUC values of 0.853 and 0.81 in the training and testing subtypes, sensitivities of 0.765 and 0.786, and specificities of 0.771 and 0.815, respectively. The AUC, sensitivity, and specificity in the nonhigh-risk subtype were 0.859, 0.654, and 0.852, respectively.

CONCLUSION

By identifying MRI structural radiomics and clinical features as potential biomarkers, the radiomic approach and UCA provide new insights into the pathophysiology of DPD to support the clinical diagnosis with high prediction accuracy.

Factors associated with higher caregiver burden among informal caregivers of Parkinson's disease: A systematic review

BACKGROUND

Parkinson's disease is a progressive neurodegenerative disease and the care burden in informal caregivers is huge. Summarizing factors associated with the informal caregivers burden can improve our understanding of providing proactive support to informal caregivers caring for patients with Parkinson's disease (PwP) at risk, and provides evidence for clinical practice.

METHODS

PRISMA guidelines were followed in this systematic review. We searched 9 databases in May 2024 for studies reporting data on factors associated with the care burden of informal caregivers for PwP.

RESULTS

We identified 16456 records of which 28 met inclusion criteria. Informal caregivers from 12 countries were included. There were 38 factors shown to be linked to higher care burden. The evidence indicated that informal caregivers who were depressed, caring for PwP with lower quality of life, caring for PwP with lower ADL scores, or caring for PwP with depression reported high care burden.

CONCLUSION

Targeted interventions addressing those modifiable factors should be developed and investigated to lighten the care burden of informal caregivers for PwP.

Enhancing Cough Motor Learning in Parkinson's Disease Through Variable Practice During Skill Training

BACKGROUND

When re-learning a motor skill, practicing a variety of treatment targets promotes error processing and the exploration of motor control strategies, which initially disrupts accuracy during training (motor performance), but ultimately enhances generalization, retention, and transfer (motor learning). Cough skill training (CST) is feasible and efficacious to improve cough strength; however, previous studies have used the same practice target during training.

OBJECTIVES

Our goal was to examine the impact of CST with variable practice on motor performance, motor learning, and respiratory system adaptations.

METHOD

The study was a prospective three-visit single group design. Twenty individuals with Parkinson's disease (PD) and concomitant dysphagia and dystussia completed two sessions of CST involving three randomized practice targets. Cough, lung volume, and airway clearance outcomes were assessed before and after treatment sessions with long-term retention evaluated after 1 month.

RESULTS

Peak expiratory flow rate improved after CST with variable practice for voluntary single (β = 0.35 L/s) and sequential (β = 0.22 L/s) cough, which were maintained after 1 month without treatment. The ability to expel material from the upper airway demonstrated a small magnitude of improvement (β = -1.87%). During CST, participants altered lung volume based on the treatment target and lung volume decreased during reflex cough after completing CST.

CONCLUSIONS

Individuals with PD demonstrated improvements in several aspects of motor learning after two sessions of CST with variable practice. Increasing lung volume may not be an implicit strategy to upregulate voluntary cough strength in this treatment paradigm. The findings support the need for larger investigations exploring the potential benefits of this CST approach.

The Prevalence of Depressive Symptoms in Patients with Idiopathic Parkinson's Disease: Cross-Sectional Study from Somalia

Introduction

Depression is one of the most common non-motor symptom of Parkinson's disease (PD), with an increasing prevalence in recent years. It causes significant psychological consequences that affect the disease course, overall quality of life, and functioning. The objective of this study was to determine the prevalence of depression in outpatients with Parkinson's disease evaluated in the neurology clinic at tertiary hospital in Mogadishu, Somalia.

Methods

A cross-sectional study was conducted among 50 PD patients without dementia to determine the prevalence of depression at the neurology clinic of the Mogadishu Somalia Türkiye Training and Research Hospital between February and November 2022. All eligible participants were interviewed by a team of doctors using a structured questionnaire that consisted of sociodemographics and clinical characteristics, the Beck Depression Inventory-II (BDI-II) for depression assessment, and the Modified Hoehn and Yahr Scale for PD staging.

Results

Of the 50 PD participants, 60% were male and 58% were older than 60 years. 20% of them had a family history of PD and HTN as comorbid conditions. The prevalence of depression among the participants was 46% (95% CI 31.8-60.7). Of the patients with depression, 22% and 24% had mild and moderate depressive symptoms, respectively. The Mann-Whitney U-test revealed a statistically significant association between depression symptoms and the presence of comorbidity (χ2 = 136.50, p<0.01). The Kruskal-Wallis test revealed a statistically significant association between depression symptoms and a longer duration of PD (χ2 (2) = 18.21, p<0.01) and advanced stages of PD (χ2 (2) = 13.74, p<0.01).

Conclusion

This is the first study conducted on patients with PD in Somalia and found that a significant proportion of these patients experienced depressive symptoms. We also highlighted that factors such the presence of medical comorbidities, high monthly income, advanced PD stage, longer duration of PD, and use of multiple medications for PD were significantly associated with the presence of depressive symptoms.

SEND-PD in Parkinsonian Syndromes: Results of a Monocentric Cross-Sectional Study

Introduction

Neuropsychiatric symptoms in particular impair health-related quality of life (QoL) of patients with Parkinson's disease and atypical Parkinsonian syndromes. For this reason, various scales have been developed for detection of neuropsychiatric symptoms, such as the Scale for evaluation of neuropsychiatric disorders in Parkinson's disease (SEND-PD).

Objective

First, the objective of this study was to explore the interrelation between the SEND-PD and clinical parameters in patients with Parkinson's disease and thus confirm its validity. In addition, the applicability in a well-defined cohort of patients with atypical Parkinsonian syndromes was investigated for the very first time.

Methods

A clinically well-defined cohort of 122 patients with Parkinson's disease (PD), 55 patients with Progressive Supranuclear Palsy (PSP) and 33 patients with Multiple System Atrophy (MSA) were analyzed. First, the SEND-PD was correlated with established disease-specific scores in patients with PD. Next, the results of the SEND-PD were compared between the different Parkinsonian syndromes.

Results

The SEND-PD showed a strong significant correlation with several scores, especially the UPDRS I (Rho = 0.655) and GDS-15 (Rho = 0.645). Depressive burden was significantly higher in MSA patients in comparison to the PD patient cohort (PD, 3.8 ± 3.3; MSA, 5.45 ± 3.87), while PSP patients showed significantly less psychotic (PD 1.6 ± 2.1; PSP 0.6 ± 0.9) and impulse control disorders (PD 0.3 ± 1.0; PSP 0.02 ± 0.1).

Conclusion

The SEND-PD is a useful, brief and highly applicable screening tool for neuropsychiatric symptoms in PD, but not in atypical Parkinsonism, as their unique neuropsychiatric symptom composition is not fully captured.

Risk of Parkinson's disease and depression severity in different populations: A two-sample Mendelian randomization analysis

BACKGROUND

Depression is widely recognized as a common non-motor symptom of Parkinson's disease (PD). Across different studies, the reported prevalence of depression in PD varies widely, ranging from 2.7% to 90%, but it is unclear whether this association is due to genetic or acquired factors. Whether there is a causal relationship remains unknown. The aim of this study was to use a two-sample Mendelian randomization (MR) approach to investigate the causal effect of PD on depression.

METHODS

Analyses were conducted separately for individuals of European and East Asian ancestry using publicly available summary data from genome-wide association studies. Depression was divided into two categories: ever depressed for a whole week and major depressive disorder (MDD). PD data were used as the exposure and were obtained from the International Parkinson's Disease Genomics Consortium and the BioBank Japan PheWeb, while depression data were used as the outcome and were obtained from the ntegrative Epidemiology Unit (IEU) Open GWAS Project(A public GWAS database） and the Psychiatric Genomics Consortium. The influence of PD on depression was assessed using inverse variance weighted (IVW), weighted median, MR-Egger, and weighted mode methods. Heterogeneity and pleiotropy were tested, and the results were validated using FinnGen GWAS data from version R9.

RESULTS

In individuals of European ancestry, there was a causal relationship between PD and ever depressed for a whole week (IVW method, odds ratio [OR] = 0.990; 95% CI, 0.984-0.996; p = .002), but no causal relationship was observed between PD and MDD (IVW method, OR = 0.974; 95% CI, 0.942-1.009; p = .141). In individuals of East Asian ancestry, no causal relationship was observed between PD and ever depressed for a whole week (IVW method, OR = 1.001; 95% CI, 0.829-1.209; p = .990) and between PD and MDD (IVW method, OR = 1.017; 95% CI, 0.982-1.052; p = .342). The results of the three additional analysis methods were similar to those of the IVW method, and there was no heterogeneity according to Cochran's Q-test. There was no evidence of pleiotropy based on MR-Egger intercept test and MR-PRESSO. The FinnGen validation dataset supported these findings. The results are stable and reliable.

CONCLUSION

The observed increase in depression among PD patients could potentially be attributed to modifiable acquired factors. Consequently, there is an urgent need to strengthen the management of PD patients in order to prevent the development of depression in the future.

Subthalamic DBS does not restore deficits in corticospinal suppression during movement preparation in Parkinson's disease

OBJECTIVE

Parkinson's disease (PD) patients exhibit changes in mechanisms underlying movement preparation, particularly the suppression of corticospinal excitability - termed "preparatory suppression" - which is thought to facilitate movement execution in healthy individuals. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) being an attractive treatment for advanced PD, we aimed to study the potential contribution of this nucleus to PD-related changes in such corticospinal dynamics.

METHODS

On two consecutive days, we applied single-pulse transcranial magnetic stimulation to the primary motor cortex of 20 advanced PD patients treated with bilateral STN-DBS (ON vs. OFF), as well as 20 healthy control subjects. Motor-evoked potentials (MEPs) were elicited at rest or during movement preparation in an instructed-delay choice reaction time task including left- or right-hand responses. Preparatory suppression was assessed by expressing MEPs during movement preparation relative to rest.

RESULTS

PD patients exhibited a deficit in preparatory suppression when it was probed on the responding hand side, particularly when this corresponded to their most-affected hand, regardless of their STN-DBS status.

CONCLUSIONS

Advanced PD patients displayed a reduction in preparatory suppression which was not restored by STN-DBS.

SIGNIFICANCE

The current findings confirm that PD patients lack preparatory suppression, as previously reported. Yet, the fact that this deficit was not responsive to STN-DBS calls for future studies on the neural source of this regulatory mechanism during movement preparation.

Early Detection of Depression in Parkinson's Disease: Psychometrics and Diagnostics of the Spanish Version of the Beck Depression Inventory

OBJECTIVE

Depression is one of the most disabling non-motor symptoms in Parkinson's disease (PD) and requires proper diagnosis as it negatively impacts patients' and their relatives quality of life. The present study aimed to examine the psychometric and diagnostic properties of the Beck Depression Inventory-I (BDI-I) in a Spanish PD cohort.

METHOD

Consecutive PD outpatients completed the Spanish version of the BDI-I and other questionnaires assessing anxiety and apathy. Patients' caregivers completed the depression/dysphoria domain of the Neuropsychiatric Inventory (NPI-D). The internal consistency, convergent and divergent validity and the factorial structure of BDI-I were evaluated, and an optimal cut-off was defined by means of the Youden index.

RESULTS

The BDI-I proved to have a good internal consistency and was underpinned by a mono-component structure. Regarding construct validity, the BDI-I was substantially related to anxiety and apathy measures in PD. Furthermore, the BDI-I overall showed good accuracy with adequate sensitivity and specificity. The optimal cut-off point was defined at 10.

CONCLUSIONS

We provided evidence of the psychometric and diagnostic properties of the Spanish version of the BDI-I as a screening tool for depression in Spanish speaking PD patients, suggesting its usefulness in clinical research and practice.

Altered functional-structural coupling may predict Parkinson's patient's depression

We aimed to elucidate the neurobiological basis of depression in Parkinson's disease and identify potential imaging markers for depression in patients with Parkinson's disease. We recruited 43 normal controls (NC), 46 depressed Parkinson's disease patients (DPD) and 56 non-depressed Parkinson's disease (NDPD). All participants underwent routine T2-weighted, T2Flair, and resting-state scans on the same 3.0 T magnetic resonance imaging (MRI) scanner at our hospital. Pre-processing includes calculating surface-based Regional Homogeneity (2DReHo) and cortical thickness. Then we defined the correlation coefficient between 2DReHo and cortical thickness as the functional-structural coupling index. Between-group comparisons were conducted on the Fisher's Z-transformed correlation coefficients. To identify specific regions of decoupling, the 2DReHo for each participant were divided by cortical thickness at each vertex, followed by threshold-free cluster enhancement (TFCE) multiple comparison correction. Binary logistic regression analysis was performed with DPD as the dependent variable, and significantly altered indicators as the independent variables. Receiver operating characteristic curves were constructed to compare the diagnostic performance of individual predictors and combinations using R and MedCalc software. DPD patients exhibited a significantly lower whole-brain functional-structural coupling index than NDPD patients and NC. Abnormal functional-structural coupling was primarily observed in the left inferior parietal lobule and right primary and early visual cortices in DPD patients. Receiver operating characteristic analysis revealed that the combination of cortical functional-structural coupling, surface-based ReHo, and thickness had the best diagnostic performance, achieving a sensitivity of 65% and specificity of 77.7%. This is the first study to explore the relationship between functional and structural changes in DPD patients and evaluate the diagnostic performance of these altered correlations to predict depression in Parkinson's disease patients. We posit that these changes in functional-structural relationships may serve as imaging biomarkers for depression in Parkinson's disease patients, potentially aiding in the classification and diagnosis of Parkinson's disease. Additionally, our findings provide functional and structural imaging evidence for exploring the neurobiological basis of depression in Parkinson's disease.

Depression is associated with the nonmotor symptoms of Parkinson's disease: A comparative analysis

Background and aims

The nonmotor symptoms (NMS) of Parkinson's disease (PD) and their potential role in early diagnosis are recent debates. Herein, we aimed to investigate the association between depression and NMS of PD including sleep disorders, hyposexuality, hyposmia, constipation, and orthostatic hypotension.

Methods

A total of 93 PD patients with depression and 67 PD patients without depression were included in the study, and NMS were compared between the two groups. Furthermore, the possible associations between depression severity measured by Beck Depression Inventory (BDI) and NMS were investigated using linear regression or binary logistic regression models controlled for possible confounders. Eventually, we performed a subgroup analysis in each mild, moderate, and severe depression group.

Results

Orthostatic hypotension, constipation, and hyposexuality showed a significant difference between PD patients with and without depression (p < 0.001, p = 0.029, and p < 0.001, respectively). The BDI score was significantly associated with hyposexuality, Montreal cognitive assessment (MoCA), and Pittsburgh Sleep Quality (p = 0.016, p = 0.010, and p = 0.011, respectively); however, after adjustments for possible confounders, the associations of the BDI score with the MoCA score and hyposexuality remained significant (p = 0.015 and p = 0.019, respectively). Considering subgroup analysis, a similar pattern of significant results was observed particularly in the severe group.

Conclusions

This study suggests a possible association between depression in PD patients and some NMS observed in the course of PD. These findings could be beneficial for early diagnosis of the disease, which eventually could make a considerable difference in the management of PD patients. Additional interventional longitudinal studies are warranted to explore how controlling depression could impact the NMS of patients with PD.

The Interrelationship of Benefit Finding, Demoralization, and Stigma among Patients with Parkinson's Disease and Their Caregivers

Parkinson's disease (PD) is a debilitating neurodegenerative disease with a relentlessly progressive course of illness. This study aimed to assess the dyadic dynamics of benefit finding (BF), demoralization, and stigma on the depression severity of PD patients and their caregivers. This study used a cross-sectional design with purposive sampling. In total, 120 PD patients and 120 caregivers were recruited from the neurological ward or neurological outpatient clinic of a medical center in Taiwan from October 2021 to September 2022. PD patients and their caregivers were enrolled and assessed using the Mini International Neuropsychiatric Interview, the Benefit Finding scale, Demoralization Scale, Stigma Subscale of the Explanatory Model Interview Catalogue, and Taiwanese Depression Questionnaire. Among the 120 patients and 120 caregivers that successfully completed the study, 41.7% (N = 50) and 60% (N = 72) were female, respectively. The most common psychiatric diagnoses of both the PD patients (17.5%) and their caregivers (13.3%) were depressive disorders. Using structural equation modeling, we found that the stigma, BF, and demoralization of PD patients might contribute to their depression severity. Demoralization and stigma of PD patients' caregivers might also contribute to the depression severity of PD patients. Caregivers' BF and demoralization were significantly linked with their depression severity. PD patients' BF degree and their caregivers' BF degree had significant interactive effects. Both patients' and their caregivers' stigma levels had significant interactive effects. Clinicians should be aware of and manage these contributing factors between PD patients and their caregivers in order to prevent them from exacerbating each other's depression.

Perceived control as a predictor of medication adherence in people with Parkinson's: a large-scale cross-sectional study

PURPOSE

Medication adherence is a multi-faceted construct associated with several positive consequences in people with chronic conditions. However, non-adherence currently represents a major issue in Parkinson's, potentially due to low perceptions of control. This study investigated the predictive ability of several aspects of perceived control on adherence in people with Parkinson's, while accounting for previously established predictors such as depression and medication variables.

MATERIALS AND METHODS

An online cross-sectional survey was carried out with 1210 adults with Parkinson's from 15 English-speaking countries. Demographic and clinical questions, as well as measures of depression, aspects of perceived control, and medication adherence were included. Pearson's correlations and a 4-block hierarchical regression analysis were performed to assess the relationship between the variables.

RESULTS

Perceived control explained a slightly higher amount of variance in medication adherence compared to medication variables when entered in the last block. Unexpectedly, depression was not significantly related with adherence. Internal locus of control was an independent negative predictor of adherence, while external dimensions of locus of control emerged as independent positive predictors.

CONCLUSIONS

In people with Parkinson's, perceptions of control may have a larger impact on adherence compared to medication variables. Implications for clinical practice and future research are discussed.Implications for RehabilitationPerceived control and depression are considered important constructs for medication adherence in Parkinson's, which in turn is often problematic for affected individuals.The specific predictive value of different aspects of perceived control on medication adherence in Parkinson's is currently unclear.This large-scale study found that perceptions of control may have a larger impact on adherence compared to medication variables, while depression was unrelated to it.A need for psychologically-informed interventions, person-centred approaches to medication management, and Parkinson-specific measures of adherence are highlighted.

Feasibility and Acceptability of a Videoconferencing CBT Intervention for Anxiety in People with Parkinson's Disease

OBJECTIVES

In people with Parkinson's disease (PwPD), non-motor symptoms such as anxiety are common and have negative impacts on their quality of life. There are currently few interventions that address anxiety in PwPD, and access to diagnosis and treatment is often limited for those living in rural areas. The aim of this study was to evaluate the feasibility and acceptability of a telehealth videoconferencing CBT intervention for anxiety in PwPD.

METHODS

A pre- and post-test feasibility study (N = 10) was conducted and evaluated utilizing the RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance).

RESULTS

Lack of access to the internet and videoconferencing technology were identified as barriers to participation. Physical health issues also impacted recruitment and retention. Non-completers were significantly older and less likely to have a carer involved in the intervention. Clinician adoption of the intervention was low while participant acceptability of videoconferencing technology varied and required carer support.

CONCLUSIONS

Providing access to technology and support to overcome technological issues, as well as telehealth training for clinicians, are recommended in future studies to improve recruitment, retention, and implementation.

CLINICAL IMPLICATIONS

Identification of barriers and facilitators provides future studies with the knowledge to tailorize their program to better suit PwPD.

A general clinical overview of the non-motor symptoms in Parkinson's disease: Neuropsychiatric symptoms

The heterogeneity of non-motor features observed in people with Parkinson's disease (PD) is often dominated by one or more symptoms belonging to the neuropsychiatric spectrum, such as cognitive impairment, psychosis, depression, anxiety, and apathy. Due to their high prevalence in people with PD (PwP) and their occurrence in every stage of the disease, from the prodromal to the advanced stage, it is not surprising that PD can be conceptualised as a complex neuropsychiatric disorder. Despite progress in understanding the pathophysiological mechanisms underlying the neuropsychiatric signs and symptoms in PD, and better identification and diagnosis of these symptoms, effective treatments are still a major unmet need. The impact of these symptoms on the quality of life of PwP and caregivers, as well as their contribution to the overall non-motor symptom burden can be greater than that of motor symptoms and require a personalised, holistic approach. In this chapter, we provide a general clinical overview of the major neuropsychiatric symptoms of PD.

Knowledge, attitude, and practice of healthcare professionals toward cognitive dysfunction in Parkinson's disease and cognitive rehabilitation

BACKGROUND

To investigate the knowledge, attitude, and practice (KAP) of healthcare professionals regarding cognitive dysfunction and cognitive rehabilitation in Parkinson's disease (PD).

METHODS

This multicenter, cross-sectional survey enrolled physicians and nurses in 10 hospitals between October 2022 and November 2022. A self-administered questionnaire was developed to collect the demographic information of the participants and their knowledge, attitude, and practice toward cognitive dysfunction in PD and cognitive rehabilitation.

RESULTS

This study enrolled 224 physicians and 229 nurses. The knowledge, attitude, and practice scores were 12.57 ± 3.76 (total score: 22), 29.10 ± 3.71 (total score: 32), and 21.07 ± 8.03 (total score: 28) among physicians, and 9.97 ± 4.70 (total score: 22), 25.27 ± 8.96 (total score: 32), and 25.27 ± 8.96 (total score: 28) among nurses. Among physicians, the knowledge scores (OR = 4.23, 95%CI: 2.36-7.58, P < 0.001) and attitude scores (OR = 3.00, 95%CI: 1.67-5.37, P < 0.001) were independently associated with good practice. Among nurses, the knowledge scores (OR = 4.31, 95%CI: 2.31-8.05, P < 0.001), attitude scores (OR = 5.18, 95%CI: 2.82-9.53, P < 0.001), working department (Ref: rehabilitation; neurology: OR = 2.26, 95%CI: 1.01-5.08, P = 0.048; public health service/chronic disease follow-up center: OR = 2.98, 95%CI: 1.12-7.92, P = 0.028) were independently associated with good practice.

CONCLUSIONS

Physicians and nurses have insufficient knowledge, favorable attitudes, and active practice regarding cognitive dysfunction and cognitive rehabilitation in PD. This study identified gaps in KAP and suggested education activities to improve the KAP toward cognitive dysfunction in PD.

Exploring the interplay between metabolomics and genetics in Parkinson's disease: Insights from ongoing research and future avenues

Parkinson's disease (PD) is a widespread neurodegenerative disorder, whose complex aetiology remains under construction. While rare variants have been associated with the monogenic PD form, most PD cases are influenced by multiple genetic and environmental aspects. Nonetheless, the pathophysiological pathways and molecular networks involved in monogenic/idiopathic PD overlap, and genetic variants are decisive in elucidating the convergent underlying mechanisms of PD. In this scenario, metabolomics has furnished a dynamic and systematic picture of the synergy between the genetic background and environmental influences that impact PD, making it a valuable tool for investigating PD-related metabolic dysfunctions. In this review, we performed a brief overview of metabolomics current research in PD, focusing on significant metabolic alterations observed in idiopathic PD from different biofluids and strata and exploring how they relate to genetic factors associated with monogenic PD. Dysregulated amino acid metabolism, lipid metabolism, and oxidative stress are the critical metabolic pathways implicated in both genetic and idiopathic PD. By merging metabolomics and genetics data, it is possible to distinguish metabolic signatures of specific genetic backgrounds and to pinpoint subgroups of PD patients who could derive personalized therapeutic benefits. This approach holds great promise for advancing PD research and developing innovative, cost-effective treatments.

Association of physical activity with the risk of Parkinson's disease in depressive disorder: A nationwide longitudinal cohort study

Regular physical activity (PA) has been suggested as effective disease preventable strategies for Parkinson's disease (PD). Depression often precedes PD but whether PA also would reduce the risk of PD in patients with depression has not been known. The aim of study is to examine the association of regular PA with risk of PD among patients with depressive disorder. A total of 1,342,282 patients with depressive disorder were identified from a nationwide health screening cohort from 2010 to 2016. The exposure was changes in pattern of regular PA between pre-and post-diagnosis of depressive disorder, categorized as four groups; 1) no PA, 2) increased PA, 3) decreased PA, and 4) maintaining PA. The outcome was risk of incident PD, calculated using multivariate adjusted Cox proportional hazards regressions according to the PA categorization. Total of 8901 PD cases (0.66%) were developed during 5.3 years of follow-up period. Maintaining PA group was associated with the lowest risk of PD (adjusted hazard ratio [aHR] 0.89, 95% CI 0.83-0.97) among all other PA groups with depressive disorder (with no PA group as reference). Otherwise, decreased PA group significantly increased the risk of PD (aHR 1.10, 95% CI 1.03-1.16). Those who maintained PA before and after diagnosis of depressive disorder were associated with lower risk of incident PD.

Identification and Experimental Validation of Parkinson's Disease with Major Depressive Disorder Common Genes

Parkinson's disease (PD) is the second most common neurodegenerative disease that affects about 10 million people worldwide. Non-motor and motor symptoms usually accompany PD. Major depressive disorder (MDD) is one of the non-motor manifestations of PD it remains unrecognized and undertreated effectively. MDD in PD has complicated pathophysiologies and remains unclear. The study aimed to explore the candidate genes and molecular mechanisms of PD with MDD. PD (GSE6613) and MDD (GSE98793) gene expression profiles were downloaded from Gene Expression Omnibus (GEO). Above all, the data of the two datasets were standardized separately, and differentially expressed genes (DEGs) were obtained by using the Limma package of R. Take the intersection of the two differential genes and remove the genes with inconsistent expression trends. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were investigated to explore the function of the common DEGs. Additionally, the construction of the protein-protein interaction (PPI) network was to search the hub genes, and then the least absolute shrinkage and selection operator (LASSO) regression was used to further identify the key genes. GSE99039 for PD and GSE201332 for MDD were performed to validate the hub genes by the violin plot and receiver operating characteristic (ROC) curve. Last but not least, immune cell dysregulation in PD was investigated by immune cell infiltration. As a result, a total of 45 common genes with the same trend. Functional analysis revealed that they were enriched in neutrophil degranulation, secretory granule membrane, and leukocyte activation. LASSO was performed on 8 candidate hub genes after CytoHubba filtered 14 node genes. Finally, AQP9, SPI1, and RPH3A were validated by GSE99039 and GSE201332. Additionally, the three genes were also detected by the qPCR in vivo model and all increased compared to the control. The co-occurrence of PD and MDD can be attributed to AQP9, SPI1, and RPH3A genes. Neutrophils and monocyte infiltration play important roles in the development of PD and MDD. Novel insights may be gained from the findings for the study of mechanisms.

Towards a better Comprehension and Management of Pain and Psychological Distress in Parkinson's: The Role of Catastrophizing

OBJECTIVES

Pain is very prevalent in Parkinson's and challenging to manage. As many people with Parkinson's (PwP) with pain suffer from anxious and depressive symptoms, we examined the role of catastrophizing in mediating the relationship between pain and psychological distress for this population.

METHODS

169 international PwP completed an online survey with socio-demographic and medical data. Participants completed psychometric tests to assess their pain (King's Parkinson's Disease Pain Questionnaire, McGill Pain Questionnaire and Brief Pain Inventory), psychological distress (Beck Depression Inventory and Parkinson Anxiety Scale), pain coping strategies (Coping Strategies Questionnaire) and pain catastrophizing (Pain Catastrophizing Scale).

RESULTS

Depending on the tool used, 82.8% to 95.2% of participants reported pain. 23.5 % and 67.5% of participants showed respectively significant levels of depressive and anxiety symptoms. Psychological distress was significantly correlated with the quality of pain (both sensory and affective dimensions). Statistical models highlighted the mediating role of catastrophizing in the relationship between psychological distress and pain in Parkinson's.

CONCLUSION

These findings offer new perspectives toward understanding the underlying mechanisms of pain in Parkinson's and for effective therapeutic intervention goals to facilitate adaptation to pain symptoms in Parkinson's.

Acupuncture Improves Sleep Disorders and Depression among Patients with Parkinson's Disease: A Meta-Analysis

Parkinson's disease (PD) is associated with a range of non-motor symptoms that lack effective treatments. Acupuncture is a popular alternative therapy for PD patients that has been shown to improve motor symptoms. However, the efficacy of acupuncture in treating non-motor symptoms has remained controversial. The goal of our study was to systematically assess the existing evidence for acupuncture's efficacy in treating PD non-motor symptoms of sleep disorders, depression, anxiety, and fatigue. We conducted a meta-analysis of clinical trials by searching Pubmed, Embase, CINAHL, and Web of Science as electronic databases to evaluate acupuncture treatment for PD non-motor symptoms. Thirteen clinical trials met our inclusion criteria, and their methodological quality was assessed using the modified Jadad scale, indicating a moderate overall quality. Our results showed that acupuncture improved PD-related sleep disorders and depression but had no effect on anxiety and fatigue. Our meta-analysis suggests that acupuncture can be used as a complementary treatment for sleep disturbances and depression in PD patients and may exhibit a dual therapeutic effect on motor and non-motor symptoms. However, further well-designed clinical trials with larger sample sizes are needed to confirm these findings. Overall, our study highlights the potential of acupuncture as a viable complementary therapy for the treatment of PD non-motor symptoms of sleep disorders and depression, which can improve the quality of life of PD patients.

Depressive Symptoms and Their Impact on Quality of Life in Parkinson's Disease: An Exploratory Network Analysis Approach

The clinical presentation of Parkinson's disease (PD) is often dominated by depressive symptoms, which can significantly impact the patients' quality of life (QoL). However, it is not clear how these depressive symptoms are interconnected, or if some symptoms are more influential in affecting QoL. In the Cohort of Patients with Parkinson's Disease in Spain (COPPADIS) study, 686 patients with PD were analyzed using network analyses. The patients completed the Beck Depression Inventory II (BDI-II) and provided their overall QoL (EUROHIS-QOL) at the beginning of the study. The study used centrality measures such as Expected Influence and Bridge Expected Influence to identify depressive symptoms that had the greatest impact on overall QoL. The results of exploratory network analyses indicate that the BDI-II items related to loss of energy, past failure, and tiredness or fatigue have the greatest impact on overall QoL as measured by the EUROHIS-QOL 8-item index. The loss of energy and tiredness or fatigue BDI-II items are also strongly associated with a number of different EUROHIS-QOL items, according to Bridge Expected Influences. For individuals suffering from PD, network analysis can aid in identifying significant non-motor symptoms that impact their QoL, thus paving the way for potential improvements.

Association Between Depression and Physical Conditions Requiring Hospitalization

Importance

Depression is associated with an increased risk of physical illness, but the most common causes of hospitalization among people with depression are unclear.

Objective

To examine the association of depression with an array of physical conditions requiring hospital treatment.

Design, Setting, and Participants

In this outcomewide prospective multicohort study, primary analysis was based on data from the UK Biobank, a population-based study in the United Kingdom. Analyses were repeated in an independent data set of 2 cohorts in Finland, a population-based study and an occupational cohort. Data analysis was conducted between April and September 2022.

Exposures

Self-reported depression, recurrent severe major depression, recurrent moderate major depression, and a single major depressive episode.

Main Outcomes and Measures

A total of 77 common health conditions ascertained from linkage data to national hospital and mortality registries.

Results

The analytical sample of UK Biobank participants consisted of 130 652 individuals (71 565 women [54.8%]; 59 087 men [45.2%]; mean [SD] age at baseline, 63.3 [7.8] years). The pooled data from the Finnish replication cohorts included 109 781 participants (82 921 women [78.6%]; 26 860 men [21.4%]; mean [SD] age, 42 [10.8] years). In the main analysis, severe/moderately severe depression was associated with the incidence of 29 nonoverlapping conditions requiring hospital treatment during a 5-year follow-up. Twenty-five of these associations remained after adjustment for confounders and multiple testing (adjusted hazard ratio [HR] range, 1.52-23.03) and were confirmed in the analysis of the Finnish cohorts. These included sleep disorders (HR, 5.97; 95% CI, 3.27-10.89), diabetes (HR, 5.15; 95% CI, 2.52-10.50), ischemic heart disease (HR, 1.76; 95% CI, 1.36-2.29), chronic obstructive bronchitis (HR, 4.11; 95% CI, 2.56-6.60), bacterial infections (HR, 2.52; 95% CI, 1.99-3.19), back pain (HR, 3.99; 95% CI, 2.96-5.38), and osteoarthritis (HR, 1.80; 95% CI, 1.46-2.20). The highest cumulative incidence was observed for endocrine and related internal organ diseases (245 per 1000 persons with depression; risk difference relative to unaffected individuals: 9.8%), musculoskeletal diseases (91 per 1000 persons; risk difference, 3.7%), and diseases of the circulatory system and blood (86 per 1000 persons; risk difference, 3.9%). The cumulative incidence was lower for hospital-treated mental, behavioral, and neurological disorders (20 in 1000 persons; risk difference, 1.7%). Depression was also associated with disease progression in people with prevalent heart disease or diabetes, and for 12 conditions, there was evidence of a bidirectional relationship.

Conclusions and Relevance

In this study, the most common causes of hospitalization in people with depression were endocrine, musculoskeletal, and vascular diseases, not psychiatric disorders. These findings suggest that depression should be considered as a target for the prevention of physical and mental disease.

Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease

The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson's disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1-6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.

Neurobiology of depression in Parkinson's disease: Insights into epidemiology, molecular mechanisms and treatment strategies

Parkinson's disease (PD) is characterized mainly by motor dysfunctions due to the progressive loss of dopaminergic neurons. However, PD patients experience a multitude of debilitating non-motor symptoms, including depression, which may have deleteriously detrimental effects on life. Depression is multifactorial and exhibits a bimodal progression in PD, but its underlying molecular mechanisms are poorly understood. Studies demonstrating the pathophysiology of depression in PD and the specific treatment strategies for depression-like symptoms in PD patients are largely lacking, often underrated, under-recognized and, consequently, inadequately/under-treated. Nevertheless, reports suggest that the incidence of depression is approximately 20-30% of PD patients and may precede the onset of motor symptoms. Diagnosing depression in PD becomes difficult due to the clinical overlap in symptomatology between the two diseases, and the nigrostriatal dysfunction alone is insufficient to explain depressive symptoms in PD. Therefore, the current study provides an overview of the molecular mechanisms underlying the development of depression in PD and new insights into developing current antidepressant strategies to treat depression in PD. This review will identify and understand the molecular pathological mechanisms of depression in PD that will fundamentally help tailoring therapeutic interventions for depressive symptoms in PD.

Depression in Major Neurodegenerative Diseases and Strokes: A Critical Review of Similarities and Differences among Neurological Disorders

Depression and anxiety are highly prevalent in most neurological disorders and can have a major impact on the patient's disability and quality of life. However, mostly due to the heterogeneity of symptoms and the complexity of the underlying comorbidities, depression can be difficult to diagnose, resulting in limited recognition and in undertreatment. The early detection and treatment of depression simultaneously with the neurological disorder is key to avoiding deterioration and further disability. Although the neurologist should be able to identify and treat depression initially, a neuropsychiatry team should be available for severe cases and those who are unresponsive to treatment. Neurologists should be also aware that in neurodegenerative diseases, such as Alzheimer's or Parkinson's, different depression symptoms could develop at different stages of the disease. The treatment options for depression in neurological diseases include drugs, cognitive-behavioral therapy, and somatic interventions, among others, but often, the evidence-based efficacy is limited and the results are highly variable. Here, we review recent research on the diagnosis and treatment of depression in the context of Alzheimer's disease, Parkinson's disease, and strokes, with the aim of identifying common approaches and solutions for its initial management by the neurologist.

Awareness of Dysphagia-Related Complications and Risks and the Importance of Early Intervention in Patients with Parkinson's Disease: A Qualitative Study

OBJECTIVE

To investigate the awareness of dysphagia-related complications and risks and the importance of early intervention in patients with Parkinson's disease (PD).

METHODS

Using the phenomenological approach of the qualitative study, 18 patients with PD in a Grade A tertiary hospital in Nantong were selected, and semistructured personal in-depth interviews were conducted. The interview content was analyzed using Colaizzi's seven-step method, and the topics and subtopics were further refined.

RESULTS

Awareness of dysphagia-related complications and risks and the importance of early intervention in patients with PD can be summarized into three topics: lack of knowledge about PD and dysphagia, changes in emotional cognition, and low need for early intervention for dysphagia.

CONCLUSIONS

Patients with PD have a low awareness of dysphagia, do not follow any preventative measures, and have difficulty in recognizing the disease symptoms; hence, there is a vital need for early intervention. Medical staff need to create awareness among patients and their families, provide health education through multiple channels, popularize the knowledge of PD complications such as dysphagia, improve patient compliance with respect to medication, regular consultation, and medical treatment, guide the transformation of negative emotions in patients to positive emotions, and help patients with PD to actively prevent dysphagia and other complications and improve their quality of life.

Corticospinal Suppression Underlying Intact Movement Preparation Fades in Parkinson's Disease

BACKGROUND

In Parkinson's disease (PD), neurophysiological abnormalities within the primary motor cortex (M1) have been shown to contribute to bradykinesia, but exact modalities are still uncertain. We propose that such motor slowness could involve alterations in mechanisms underlying movement preparation, especially the suppression of corticospinal excitability-called "preparatory suppression"-which is considered to propel movement execution by increasing motor neural gain in healthy individuals.

METHODS

On two consecutive days, 29 PD patients (on and off medication) and 29 matched healthy controls (HCs) underwent transcranial magnetic stimulation over M1, eliciting motor-evoked potentials (MEPs) in targeted hand muscles, while they were either at rest or preparing a left- or right-hand response in an instructed-delay choice reaction time task. Preparatory suppression was assessed by expressing MEP amplitudes during movement preparation relative to rest.

RESULTS

Contrary to HCs, PD patients showed a lack of preparatory suppression when the side of the responding hand was analyzed, especially when the latter was the most affected one. This deficit, which did not depend on dopamine medication, increased with disease duration and also tended to correlate with motor impairment, as measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale, Part III (both total and bradykinesia scores).

CONCLUSIONS

Our novel findings indicate that preparatory suppression fades in PD, in parallel with worsening motor symptoms, including bradykinesia. Such results suggest that an alteration in this marker of intact movement preparation could indeed cause motor slowness and support its use in future studies on the relation between M1 alterations and motor impairment in PD. © 2022 International Parkinson and Movement Disorder Society.

Inflammatory markers and depression in Parkinson's disease: a systematic review

BACKGROUND

Parkinson's disease (PD) patients experience non-motor symptoms (NMS), which may appear before motor manifestations. The most common NMS is depression, affecting about 30-40% of PD patients. Both PD and depression are associated with an increased inflammatory burden, with studies showing elevation of diverse inflammatory markers in patients with both conditions.

METHODS

A systematic review was conducted in PubMed and PsycINFO databases to investigate what inflammatory markers are associated with PD depression (PDD). Only studies in English that measured inflammatory markers and analyzed against depression scores in PD patients were included.

RESULTS

A total of 1132 articles were retrieved, and 14 entries were found to be eligible. Twelve were cross-sectional studies, one was a cohort, and one was a non-randomized controlled trial. IL-17A was the only marker strongly associated with PDD, while studies assessing sIL-2R and serum amyloid A found a moderate correlation. C-reactive protein, IL-10, tumor necrosis factor-α, monocyte chemoattractant protein-1, and IL-6 yielded conflicting results. Their possible roles in PDD are discussed. PDD was also related to longer disease duration and other NMS, such as anxiety, fatigue, dementia, REM sleep behavior disorder, and autonomic dysfunction.

CONCLUSION

We suggest that these markers may be used for distinguishing isolated depression from that related to neurodegeneration, especially in individuals that concurrently present with other known prodromal symptoms of PD and other α-synucleinopathies. However, future prospective studies are warranted to confirm this hypothesis.

The pathobiological basis of depression in Parkinson disease: challenges and outlooks

Depression, with an estimated prevalence of about 40% is a most common neuropsychiatric disorder in Parkinson disease (PD), with a negative impact on quality of life, cognitive impairment and functional disability, yet the underlying neurobiology is poorly understood. Depression in PD (DPD), one of its most common non-motor symptoms, can precede the onset of motor symptoms but can occur at any stage of the disease. Although its diagnosis is based on standard criteria, due to overlap with other symptoms related to PD or to side effects of treatment, depression is frequently underdiagnosed and undertreated. DPD has been related to a variety of pathogenic mechanisms associated with the underlying neurodegenerative process, in particular dysfunction of neurotransmitter systems (dopaminergic, serotonergic and noradrenergic), as well as to disturbances of cortico-limbic, striato-thalamic-prefrontal, mediotemporal-limbic networks, with disruption in the topological organization of functional mood-related, motor and other essential brain network connections due to alterations in the blood-oxygen-level-dependent (BOLD) fluctuations in multiple brain areas. Other hypothetic mechanisms involve neuroinflammation, neuroimmune dysregulation, stress hormones, neurotrophic, toxic or metabolic factors. The pathophysiology and pathogenesis of DPD are multifactorial and complex, and its interactions with genetic factors, age-related changes, cognitive disposition and other co-morbidities awaits further elucidation.

Predictors of health-related quality of life in Parkinson's disease: the impact of overlap between health-related quality of life and clinical measures

PURPOSE

This study aimed to determine predictors of health-related quality of life (HRQoL) in Parkinson's disease (PD) and to explore their predictive value before and after controlling overlapping items between HRQoL and clinical variables.

METHODS

One hundred and eight PD patients underwent motor, anxiety, depression, apathy, fatigue, and neurocognition assessment. HRQoL was assessed by the Parkinson's Disease Questionnaire-39 (PDQ-39). In order to determine predictors of HRQoL in PD, stepwise multiple regression analyses were performed in two ways: before and after removing the emotional well-being dimension from PDQ-39 to control the overlap between depression and anxiety, and HRQoL.

RESULTS

HRQoL total index was predicted by anxiety, fatigue, motor symptoms, and depression, explaining 26.9%, 7.2%, 2.8%, and 1.9% of the variance. However, after removing overlapping items, HRQoL total index was predicted by fatigue (16.5%), anxiety (6.1%), motor symptoms (3.9%), and neurocognition (2.5%), but not depression. Regarding HRQoL dimensions, mobility and activities of daily living were predicted by fatigue (19.7% and 5%) and UPDRS-III (4% and 10.2%); emotional well-being by fatigue (7.9%); social support by anxiety (12.2%) and UPDRS-III (8.6%); communication by neurocognition (5.3%) and UPDRS-III (3.4%); cognition by anxiety (10.6%) and bodily discomfort by anxiety (23%) and fatigue (4.1%).

CONCLUSION

These findings showed the importance of identifying and controlling overlapping items of HRQoL and clinical measures to perform an accurate interpretation. HRQoL dimensions showed different predictors before and after controlling the overlap. Based on these results fatigue, anxiety, motor symptoms, and neurocognition, but not depression are the main predictors of HRQoL in PD patients.

High frequency of Depressive Disorders and Suicidal Phenomena in Late-Stage Parkinson´s Disease - A Cross-Sectional Study

BACKGROUND

Depressive disorders (DD) are widely recognized as one of the most frequent neuropsychiatric disorders in Parkinson´s disease. Patients with late-stage Parkinson´s disease (LSPD) continue to be a neglected population, and little is known about DD frequency in LSPD.

OBJECTIVES

To determine the frequency of DD in LSPD patients through a clinical diagnostic interview (CDI) and according to diagnostic DSM- 5 criteria. Secondary objectives were to determine the predictive ability of depressive scales to detect DD, to identify potential predictors of DD in LSPD and, to evaluate suicidal phenomena in LSPD.

METHODS

A cross-sectional study including LSPD patients (≥7 years from symptom onset and Hoehn and Yahr scale score >3 or a Schwab and England scale score <50% in the ON condition) was conducted. Patients were subjected to psychiatric, neurological, and neuropsychological evaluations. Six depression scales were applied.

RESULTS

92 LSPD patients were included. 59.78% of LSPD patients had a current diagnosis of DD according to CDI, 38.04% patients had a diagnosis of major depressive disorder, and 21.72% non-major depressive disorder. Suicidal ideation was present in 36.96% of patients. All applied scales were able to detect depressive disorders.

CONCLUSIONS

More than half of LSPD patients met DD diagnostic criteria and over one-third were diagnosed with major depressive disorder. Overall, the LSPD population seem to have a unique clinical phenotype regarding the frequency and features of DD, whose early identification and treatment could improve the quality of life of patients and caregivers.

Effect of acupuncture for non-motor symptoms in patients with Parkinson's disease: A systematic review and meta-analysis

Background

Although non-motor symptoms of Parkinson's disease (PD) are serious, effective treatments are still lacking. Acupuncture may have clinical benefits for non-motor symptoms of PD patients, but high-quality evidence supporting this possibility is still limited. Hence, we conducted this meta-analysis to evaluate the effect of acupuncture treatment on non-motor symptoms in patients with PD.

Methods

Randomized controlled trials (RCTs) of acupuncture treatment for PD were retrieved from the following electronic databases: Medline (OVID), Embase (OVID), Cochrane Library, Web of Science, China National Knowledge Infrastructure, Chinese BioMedical Literature Database, Chonqing VIP (CQVIP), and Wangfang database. Studies evaluating non-motor symptoms of PD were retrieved. Methodological quality was assessed using the Cochrane Handbook for Systematic Reviews of Interventions.

Results

A total of 27 RCTs were included, among which 8 outcomes related to non-motor symptoms were evaluated. The results showed that acupuncture combined with medication had benefits for PD-related insomnia relative to medication alone or sham acupuncture [standardized mean difference (SMD) = 0.517; 95% confidence interval (CI) = 0.242-0.793; p = 0.000], and acupuncture treatment had benefits at 8 weeks (SMD = 0.519; 95% CI = 0.181-0.857; p = 0.003). Regarding depression, acupuncture treatment was more effective (SMD = -0.353; 95% CI = -0.669 to -0.037; p = 0.029) within 2 months (SMD = -0.671; 95% CI = -1.332 to -0.011; p = 0.046). Regarding cognition, quality of life, and Unified Parkinson's Disease Rating Scale (UPDRS) I and II scores, acupuncture treatment was effective [SMD = 0.878, 95% CI = 0.046-1.711, p = 0.039; SMD = -0.690, 95% CI = -1.226 to -0.155, p = 0.011; weighted mean difference (WMD) = -1.536, 95% CI = -2.201 to -0.871, p = 0.000; WMD = -2.071, 95% CI = -3.792 to -0.351, p = 0.018; respectively]. A significant difference was not found in terms of PD-related constipation. Only one study evaluated PD-related fatigue.

Conclusion

The results of the analysis suggested that acupuncture treatment could ameliorate the symptoms of depression, quality of life, cognition, total mentation, behavior and mood, and activities of daily living in PD patients. Nevertheless, more prospective, well-designed RCTs with larger sample sizes are required to confirm our findings.

Morbidity and Associated Factors of Depressive Disorder in Patients With Parkinson's Disease

Parkinson's disease (PD) is a progressive, neurodegenerative disorder and is commonly comorbid with depression. The aim of this cross-sectional study was to assess morbidity and associated factors of depression in patients with PD. In total, 181 patients with PD were enrolled and assessed using the Mini-International Neuropsychiatric Interview. Of the sample, 51% had at least one psychiatric diagnosis. The most prevalent psychiatric disorder was depressive disorder (27.6%), followed by rapid eye movement sleep behavior disorder (9.9%), insomnia disorder (8.8%), and adjustment disorder (2.8%). Severity of anxiety, suicide risk, and anxiolytics/hypnotics use were factors associated with depressive disorder in PD patients. Furthermore, severity of anxiety was significantly linked with suicide risk. We suggest that use of a standardized structured interview for early detection of depression in PD patients is crucial. Anxiety, anxiolytics/hypnotics use, depression, and suicide risks are interrelated and warrant clinical concerns regarding PD patients.

Harmonic ratio is the most responsive trunk-acceleration derived gait index to rehabilitation in people with Parkinson's disease at moderate disease stages

BACKGROUND

Harmonic ratios (HRs), recurrence quantification analysis in the antero-posterior direction (RQA_detAP), and stride length coefficient of variation (CV) have recently been shown to characterize gait abnormalities and fall risk in people with Parkinson's disease (pwPD) at moderate disease stages.

RESEARCH QUESTION

This study aimed to i) assess the internal and external responsiveness to rehabilitation of HR, RQA_detAP, and CV, ii) identify the baseline predictors of normalization of the gait stability indexes, and iii) investigate the correlations between the gait indexes modifications (∆) and clinical and kinematic ∆s in pwPD at Hoehn and Yahr disease staging classification 3.

METHODS

The trunk acceleration patterns of 21 pwPD and 21 age- and speed-matched healthy subjects (HSmatched) were acquired during gait using an inertial measurement unit at baseline (T0). pwPD were also assessed after a 4-week rehabilitation period (T1). Each participant's HR in the antero-posterior (HR_AP), medio-lateral (HR_ML), and vertical directions, RQA_detAP, CV, spatio-temporal, and kinematic variables were calculated.

RESULTS

At T1, HR_AP and HR_ML improved to normative values and showed high internal and external responsiveness. Lower HRs and higher pelvic rotation values at baseline were predictors of ∆HRs. A minimal clinically important difference (MCID) ≥ 21.5 % is required to normalize HR_AP with 95 % probability. MCID ≥ 36.9 % is required to normalize HR_ML with 92 % probability. ∆HR_AP correlated with ∆HR_ML and both correlated with ∆stride length and ∆pelvic rotation, regardless of ∆gait speed. RQAdetAP and step length CV were not responsive to rehabilitation.

SIGNIFICANCE

When using inertial measurement units, HR_AP and HR_ML can be considered as responsive outcome measures for assessing the effectiveness of rehabilitation on trunk smoothness during walking in pwPD at moderate disease stages.

Depression in Parkinson's Disease: A Narrative Review

Parkinson's disease (PD) is a progressive neurodegenerative age-related disorder that affects the central nervous system (CNS) and is characterized by uncontrollable movements such as shaking, stiffness, and loss of balance and coordination. Depression is a common non-motor manifestation of PD, but unfortunately, depression remains unrecognized and often undertreated. The underlying pathophysiology of depression in PD is complicated, and many studies have been conducted to know the exact cause, but the question remains unanswered.

In this article, we discuss various pathophysiologies by which depression occurs in PD. The most widely accepted theories are neuroinflammation and monoamine oxidase theory. This article also explored the pharmacological treatment of depression in PD; this involves standard antidepressant therapy such as tricyclic antidepressants (TCA), serotonin-norepinephrine reuptake inhibitors (SNRI), selective serotonin reuptake inhibitors (SSRI), and monoamine oxidase inhibitors (MAO); non-pharmacological treatments such as electroconvulsive therapy (ECT), cognitive-behavioral therapy (CBT) have also been discussed. However, physicians hesitate to prescribe antidepressants to patients with PD due to concerns about harmful drug-drug interactions between antidepressants and antiparkinsonian drugs. Despite the complicated link between PD and depression, the co-administration of antidepressants and antiparkinsonian drugs is safe and beneficial when appropriately managed. However, early recognition and initiation of treatment of depression in PD reduces the longitudinal course and improves the cross-sectional picture. This review article also explored the clinical and diagnostic findings and impact on the quality of life of depression in PD.

Research on depression in Parkinson disease: A bibliometric and visual analysis of studies published during 2012-2021

BACKGROUND

The diagnosis and treatment rate of Parkinson disease (PD) with depression has a low diagnostic rate, and there is no consensus on the choice of treatment mode. This study evaluates the global research trends of scientific outputs related to depression in PD from multiple perspectives, using a bibliometric analysis and visualization tool to scientifically analyze the knowledge from the literature.

METHODS

Literature related to depression in PD published from 2012 to 2021 was included and selected from the Web of Science Core Collection database in October 2021. CiteSpace software was used to visualize and analyze co-occurrence analyses for countries, institutions, authors, and keywords.

RESULTS

A total of 4533 articles from the Web of Science database were included. The United States made the largest contribution with the majority of publications (1215; 29.40%). Toronto University was the most productive institution. PD, depression, quality of life, dementia, nonmotor symptom, prevalence, anxiety, Alzheimer disease, symptom, and disorder would be significantly correlated with depression in PD. The current hot spots in this field focus on the following: risk factors for depression in PD, assessment scale of depression in PD, and rehabilitation of depression in PD.

CONCLUSIONS

This analysis not only reveals the current research trends and hotspots but also provides some instructive suggestions on the development of depression in PD.

(R)-ketamine as prophylactic and therapeutic drug for neurological disorders: beyond depression

Neurological disorders are the leading cause of disability and the second leading cause of death worldwide. The increasing social and economic burdens of neurological disorders are driven by global population growth and aging. Depression is a common psychiatric symptom in numerous neurological disorders. It is also a risk factor for Alzheimer's disease (AD) and other dementias, Parkinson's disease (PD), and stroke. The rapid-acting and sustained antidepressant actions of (R,S)-ketamine for severe depression was accidentally discovered. Interestingly, (R)-ketamine has greater potency and longer-lasting antidepressant-like effects than (S)-ketamine in rodents. Importantly, its side effects in rodents and humans are lower than those of (R,S)-ketamine and (S)-ketamine. Furthermore, (R)-ketamine could elicit beneficial actions in various rodent models of neurological disorders, including PD, multiple sclerosis (MS), and stroke. In this article, we review the potential of (R)-ketamine as a prophylactic or therapeutic drug for neurological disorders including AD and other dementias, PD, MS, and stroke.

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.

Prevalence and clinical aspects of depression in Parkinson's disease: a systematic review and meta‑analysis of 129 studies

Depression is one of the most important non-motor symptoms in Parkinson's disease (PD), but its prevalence and related clinical characteristics are unclear. To this end, we performed a systematic review and meta-analysis based on 129 studies, including 38304 participants from 28 countries. Overall, the prevalence of depression in PD was 38%. When compared with patients without depression, those with depression had a younger age of onset, a lower education level, longer disease duration, higher UPDRS-III, higher H&Y staging scale, and lower MMSE, SE-ADL scores. We observed that depression was associated with female patients, patients carrying the GBA1 mutation, freezing of gait (FOG), apathy, anxiety and fatigue. Our results suggest that depression is an independent, frequent non-motor symptom in PD, appearing in the early stage and persisting throughout the disease duration. In addition, several clinical characteristics and motor and non-motor symptoms appeared to be associated with depression and negatively impacted on quality of life.

Identifying Depression in Parkinson's Disease by Using Combined Diffusion Tensor Imaging and Support Vector Machine

Objective

To investigate white matter microstructural alterations in Parkinson's disease (PD) patients with depression using the whole-brain diffusion tensor imaging (DTI) method and to explore the DTI–based machine learning model in identifying depressed PD (dPD).

Methods

The DTI data were collected from 37 patients with dPD and 35 patients with non-depressed PD (ndPD), and 25 healthy control (HC) subjects were collected as the reference. An atlas-based analysis method was used to compare fractional anisotropy (FA) and mean diffusivity (MD) among the three groups. A support vector machine (SVM) was trained to examine the probability of discriminating between dPD and ndPD.

Results

As compared with ndPD, dPD group exhibited significantly decreased FA in the bilateral corticospinal tract, right cingulum (cingulate gyrus), left cingulum hippocampus, bilateral inferior longitudinal fasciculus, and bilateral superior longitudinal fasciculus, and increased MD in the right cingulum (cingulate gyrus) and left superior longitudinal fasciculus-temporal part. For discriminating between dPD and ndPD, the SVM model with DTI features exhibited an accuracy of 0.70 in the training set [area under the receiver operating characteristic curve (ROC) was 0.78] and an accuracy of 0.73 in the test set (area under the ROC was 0.71).

Conclusion

Depression in PD is associated with white matter microstructural alterations. The SVM machine learning model based on DTI parameters could be valuable for the individualized diagnosis of dPD.

Comparative efficacy and acceptability of drug treatments for Parkinson's disease with depression: A systematic review with network meta-analysis

Depressive symptom is the prevailing non-motor symptom of Parkinson's disease (PD). Drug treatments for depressed PD (dPD) can mitigate the symptoms of patients. However, the results are discordant and need further analysis. This systematic review with network meta-analysis aims to evaluate the drug treatments for dPD. We included double-blind, randomized controlled trials to compare antidepressants with placebo or other antidepressants in dPD. We performed traditional pairwise analysis and network meta-analysis concerning the efficacy, acceptability, depression score, and adverse effect. The surface under the cumulative ranking curve was to assess the ranking probabilities of the enrolled agents. We enrolled 62 studies, including 12,353 subjects, to analyze these estimates. For the traditional pairwise meta-analysis, dopamine agonist (DOP; OR = 2.20 [95% CI, 1.46 to 3.33]) and selective serotonin reuptake inhibitor (SSRI; OR = 2.30 [95% CI, 1.15 to 4.60]) were observed to improve the efficacy compared with placebo. For network meta-analysis, DOP was observed to improve the efficacy compared with placebo (OR = -0.84 [95% CI, -1.20 to -0.48]). Both direct and indirect evidence showed that several treatments, e.g., DOP, monoamine-oxidase inhibitor, serotonin-norepinephrine reuptake inhibitors, SSRI, and tricyclic antidepressants, significantly improved depressive symptoms. DOP and SSRI had good efficacy and improved symptoms considerably in dPD, but the adverse effect of these agents was needed to follow closely.

Depression in Patients with Parkinson's Disease: Current Understanding of its Neurobiology and Implications for Treatment

Depression is one of the most frequent and burdensome non-motor symptoms in Parkinson’s disease (PD), across all stages. Even when its severity is mild, PD depression has a great impact on quality of life for these patients and their caregivers. Accordingly, accurate diagnosis, supported by validated scales, identification of risk factors, and recognition of motor and non-motor symptoms comorbid to depression are critical to understanding the neurobiology of depression, which in turn determines the effectiveness of dopaminergic drugs, antidepressants and non-pharmacological interventions. Recent advances using in vivo functional and structural imaging demonstrate that PD depression is underpinned by dysfunction of limbic networks and monoaminergic systems, depending on the stage of PD and its associated symptoms, including apathy, anxiety, rapid eye movement sleep behavior disorder (RBD), cognitive impairment and dementia. In particular, the evolution of serotonergic, noradrenergic, and dopaminergic dysfunction and abnormalities of limbic circuits across time, involving the anterior cingulate and orbitofrontal cortices, amygdala, thalamus and ventral striatum, help to delineate the variable expression of depression in patients with prodromal, early and advanced PD. Evidence is accumulating to support the use of dual serotonin and noradrenaline reuptake inhibitors (desipramine, nortriptyline, venlafaxine) in patients with PD and moderate to severe depression, while selective serotonin reuptake inhibitors, repetitive transcranial magnetic stimulation and cognitive behavioral therapy may also be considered. In all patients, recent findings advocate that optimization of dopamine replacement therapy and evaluation of deep brain stimulation of the subthalamic nucleus to improve motor symptoms represents an important first step, in addition to physical activity. Overall, this review indicates that increasing understanding of neurobiological changes help to implement a roadmap of tailored interventions for patients with PD and depression, depending on the stage and comorbid symptoms underlying PD subtypes and their prognosis.

Machine Learning Approach to Support the Detection of Parkinson's Disease in IMU-Based Gait Analysis

The aim of this study was to determine which supervised machine learning (ML) algorithm can most accurately classify people with Parkinson’s disease (pwPD) from speed-matched healthy subjects (HS) based on a selected minimum set of IMU-derived gait features. Twenty-two gait features were extrapolated from the trunk acceleration patterns of 81 pwPD and 80 HS, including spatiotemporal, pelvic kinematics, and acceleration-derived gait stability indexes. After a three-level feature selection procedure, seven gait features were considered for implementing five ML algorithms: support vector machine (SVM), artificial neural network, decision trees (DT), random forest (RF), and K-nearest neighbors. Accuracy, precision, recall, and F1 score were calculated. SVM, DT, and RF showed the best classification performances, with prediction accuracy higher than 80% on the test set. The conceptual model of approaching ML that we proposed could reduce the risk of overrepresenting multicollinear gait features in the model, reducing the risk of overfitting in the test performances while fostering the explainability of the results.

Evaluating the effects of dance on motor outcomes, non-motor outcomes, and quality of life in people living with Parkinson's: a feasibility study

BACKGROUND

Community-based dance programs for people living with Parkinson's have grown in popularity over the past two decades. Studies investigating these programs have demonstrated multidimensional benefits in motor, non-motor, and quality of life related outcomes, yet there is a need to focus on the feasibility of larger trials. The primary objective of this study was to assess the feasibility and acceptability of conducting a trial investigating dance and Parkinson's in Northern Ireland. The secondary objectives were to conduct preliminary analyses of the classes' effects and to assess the appropriateness of outcome measures for a randomized controlled trial.

METHODS

Participants were recruited through the community, Parkinson's UK, and university contacts to participate in a 12-week dance intervention inspired by the Dance for PD® model. Pre- and post-intervention, participants completed the following outcomes: MDS-UPDRS III, TUG, DT-TUG, Sensory Organization Test, MoCA, Trail Making Tests A&B, Digit Symbol Substitution Test, Digit Span, PDQ-39, FOG-Q, PHQ-9, FES-I, and an exit questionnaire (post-test only). Data were analyzed using paired samples t tests or Wilcoxon signed ranked test.

RESULTS

Ten people living with Parkinson's participated. Running a larger trial was deemed infeasible in this setting due to recruitment issues; conversely, the dance intervention was accepted by participants with all but one completing the study. Functional mobility (TUG), symptoms of depression (PHQ-9), and bodily discomfort showed improvement. All other outcomes did not. The exit questionnaire revealed that the social aspect of classes was important, and improvements in mood or mental state were cited most frequently as perceived benefits. Outcome measures were feasible, with some changes suggested for future trials.

CONCLUSIONS

This study highlighted the infeasibility of running a larger trial using this design in this setting despite demonstrating the acceptability of implementing a dance program in Northern Ireland for people living with Parkinson's. The results support existing evidence demonstrating that dance may improve functional mobility and symptoms of depression in people living with Parkinson's, though the study design and small sample size prevent the generalizability of results. The findings also support the idea that dancing has the potential to support several aspects of physical, emotional, mental, and social health.

Incidence of neurological and psychiatric comorbidity over time: a population-based cohort study in Ontario, Canada

INTRODUCTION

Comprehensive, population-based investigations of the extent and temporality of associations between common neurological and psychiatric disorders are scarce.

METHODS

This retrospective cohort study used linked health administrative data for Ontarians aged 40-85 years on 1 April 2002, to estimate the adjusted rate of incident dementia, Parkinson's disease (PD), stroke or mood/anxiety disorder (over 14 years) according to the presence and time since diagnosis of a prior disorder. Sex differences in the cumulative incidence of a later disorder were also examined.

RESULTS

The cohort included 5,283,546 Ontarians (mean age 56.2 ± 12.1 years, 52% female). The rate of dementia was significantly higher for those with prior PD (adjusted hazard ratio [adjHR] 4.05, 95% confidence interval [CI] 3.99-4.11); stroke (adjHR 2.49, CI 2.47-2.52) and psychiatric disorder (adjHR 1.79, CI 1.78-1.80). The rate of PD was significantly higher for those with prior dementia (adjHR 2.23, CI 2.17-2.30) and psychiatric disorder (adjHR 1.77, CI 1.74-1.81). The rate of stroke was significantly higher among those with prior dementia (adjHR 1.56, CI 1.53-1.58). Prior dementia (adjHR 2.36, CI 2.33-2.39), PD (adjHR 1.80, CI 1.75-1.85) and stroke (adjHR 1.47, CI 1.45-1.49) were associated with a higher rate of an incident psychiatric disorder. Generally, associations were strongest in the 6 months following a prior diagnosis and demonstrated a J-shape relationship over time. Significant sex differences were evident in the absolute risks for several disorders.

CONCLUSIONS

The observed nature of bidirectional associations between these neurological and psychiatric disorders indicates opportunities for earlier diagnosis and interventions to improve patient care.