Diagnostic criteria for depression in Parkinson's disease: a study of symptom patterns using latent class analysis

Depressive Symptoms and the Subsequent Risk of Parkinson's Disease: A Nationwide Cohort Study

OBJECTIVE

Only a few studies have focused on depressive symptoms and Parkinson's disease (PD) risk. As a time lag exists from the onset of depressive symptoms to the diagnosis of depression, elucidating the association between depressive symptoms and PD development might be helpful for the early prediction of PD. We investigate the association between depressive symptoms and subsequent PD risk using nationwide population-based cohort database.

DESIGN AND SETTING

Cohort study using the Korean National Health Insurance Service data between 2007 and 2017, with longitudinal follow-up until 2019.

PARTICIPANTS

A total of 98,296 elderly people responded to a self-reported questionnaire from the National Health Screening Program on depressive symptoms.

MEASUREMENTS

The association between depressive symptoms such as 1) decreased activity or motivation, 2) worthlessness, and 3) hopelessness and PD risk was analyzed.

RESULTS

During median 5.06-year follow-up, 839 PD cases occurred: 230 in individuals with depressive symptoms and 609 in those without symptoms. Results showed an increased risk of PD development in those with depressive symptoms (HR = 1.47, 95% CI, 1.26-1.71), with dose-response association between the number of depressive symptoms and PD risk. Even in those already diagnosed with depression, combined depressive symptoms were linked to a higher risk compared to those without symptoms (with symptoms, HR = 2.71, 95% CI, 2.00-3.68; without symptoms, HR = 1.84, 95% CI, 1.43-2.36).

CONCLUSION

Individuals with depressive symptoms were at an increased risk of developing PD, and there was a dose-response association between the number of depressive symptoms and PD risk.

Investigation of non-invasive focused ultrasound efficacy on depressive-like behavior in hemiparkinsonian rats

Depression is a common non-motor symptom in Parkinson's disease (PD) that includes anhedonia and impacts quality of life but is not effectively treated with conventional antidepressants clinically. Vagus nerve stimulation improves treatment-resistant depression in the general population, but research about its antidepressant efficacy in PD is limited. Here, we administered peripheral non-invasive focused ultrasound to hemiparkinsonian ('PD') and non-parkinsonian (sham) rats to mimic vagus nerve stimulation and assessed its antidepressant-like efficacy. Following 6-hydroxydopamine (6-OHDA) lesion, akinesia-like immobility was assessed in the limb-use asymmetry test, and despair- and anhedonic-like behaviors were evaluated in the forced swim test and sucrose preference test, respectively. After, tyrosine hydroxylase immuno-staining was employed to visualize and quantify dopaminergic degeneration in the substantia nigra pars compacta, ventral tegmental area, and striatum. We found that PD rats exhibited akinesia-like immobility and > 90% reduction in tyrosine hydroxylase immuno-staining ipsilateral to the lesioned side. PD rats also demonstrated anhedonic-like behavior in the sucrose preference test compared to sham rats. No 6-OHDA lesion effect on immobility in the forced swim test limited conclusions about the efficacy of ultrasound on despair-like behavior. However, ultrasound improved anhedonic-like behavior in PD rats and this efficacy was sustained through the end of the 1-week recovery period. The greatest number of animals demonstrating increased sucrose preference was in the PD group receiving ultrasound. Our findings here are the first to posit that peripheral non-invasive focused ultrasound to the celiac plexus may improve anhedonia in PD with further investigation needed to reveal its potential for clinical applicability.

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.

Abnormal cortical atrophy and functional connectivity are associated with depression in Parkinson’s disease

Objective

This study aimed to investigate the association of altered cortical thickness and functional connectivity (FC) with depression in Parkinson’s disease (PD).

Materials and methods

A total of 26 non-depressed PD patients (PD-ND), 30 PD patients with minor depression (PD-MnD), 32 PD patients with major depression (PD-MDD), and 30 healthy controls (HC) were enrolled. Differences in cortical thickness among the four groups were assessed, and the results were used to analyze FC differences in regions of cortical atrophy. Binary logistic regression and receiver operating characteristic (ROC) curve analyses were also performed to identify clinical features and neuroimaging biomarkers that might help in the prediction of PD-MDD.

Results

Patients with PD-MDD showed decreased cortical thickness compared to patients with PD-ND in the left superior temporal and right rostral middle frontal gyri (RMFG), as well as weak FC between the left superior temporal gyrus and right cerebellum posterior lobe and between right RMFG and right inferior frontal gyrus and insula. The combination of cortical thickness, FC, and basic clinical features showed strong potential for predicting PD-MDD based on the area under the ROC curve (0.927, 95% CI 0.854–0.999, p < 0.001).

Conclusion

Patients with PD-MDD show extensive cortical atrophy and FC alterations, suggesting that cortical thickness and FC may be neuroimaging-based diagnostic biomarkers for PD-MDD.

The altered multiscale dynamics of spontaneous brain activity in depression with Parkinson’s disease

Background

Depression is one typical mood disorder in Parkinson’s disease (DPD). The alterations in the resting-state brain activities are believed to be associated with DPD. These resting-state activities are regulated by neurophysiological components over multiple temporal scales. The multiscale dynamics of these spontaneous fluctuations are thus complex, but not well-characterized.

Objective

To characterize the complexity of the spontaneous blood-oxygen-level-dependent (BOLD) of fMRI in DPD. We hypothesized that (1) compared to non-depression PD (NDPD), the complexity in DPD would be lower; and (2) the diminished complexity would be associated with lower connections/communications between brain regions.

Methods

Twenty-nine participants (10 in DPD and 19 in NDPD) who were naïve to medications completed a resting-sate functional MRI scan. The BOLD complexity within each voxel was calculated by using multiscale entropy (MSE). The complexity of the whole brain and each of the 90 regions parcellated following automated-anatomical-labeling template was then obtained by averaging voxel-wised complexity across all brain regions or within each region. The level of connections of regions with diminished complexity was measured by their own global functional connectivity (FC).

Results

As compared to NDPD patients, the whole-brain complexity and complexity in 18 regions were significantly lower in DPD (F > 16.3, p < 0.0005). Particularly, in eight of the 18 regions, lower complexity was associated with lower global FC (Beta = 0.333 ~ 0.611, p = 0.000 ~ 0.030).

Conclusion

The results from this pilot study suggest that the resting-state BOLD complexity may provide critical knowledge into the pathology of DPD. Future studies are thus warranted to confirm the findings of this study.

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.

Applying latent class analysis to risk stratification of incident diabetes among Chinese adults

OBJECTIVE

To use latent class analysis to identify unobservable subpopulations amongst the heterogeneous population and explore the relationship between subpopulations and incident diabetes among Chinese adults.

METHODS

The retrospective study included 32,312 Chinese adults without diabetes at baseline. Latent class indicators included demographic and clinical variables. The outcome was incident diabetes. The relationship between latent class and outcome was evaluated with Cox proportional hazard regression analysis.

RESULTS

After screening, the two-class latent class model best fits the population. Participants in class 2 are characterized by higher age, body mass index, systolic and diastolic blood pressure, fasting plasma glucose, total cholesterol, triglyceride, low-density lipoprotein cholesterol, serum creatinine, serum urea nitrogen, alanine aminotransferase, and a higher proportion of males, ever/current smokers and drinkers, but lower high-density lipoprotein cholesterol and a lower proportion of family history of diabetes. The risk of diabetes in class 2 was 5.451 times (HR: 6.451, 95%CI: 4.179-9.960, P < 0.00001) and 5.264 times (HR: 6.264, 95%CI: 4.680-8.385, P < 0.00001) higher than that in class 1 during 3-year and 5-year follow-up, respectively.

CONCLUSIONS

We used latent class analysis to identify two distinct subpopulations with differential risk of diabetes during 3-year and 5-year follow-up.

Variation of Minimum Clinically Important Difference by Age, Gender, Baseline Disability, and Change of Direction in Adult Spinal Deformity Population: Is It a Constant Value?

BACKGROUND

The minimum clinically important difference (MCID), an important concept to evaluate the effectiveness of treatments, might not be a single "magical" constant for any given health-related quality of life (HRQoL) scale. Thus, we analyzed the effects of various factors on MCIDs for several HRQoL measures in an adult spinal deformity population.

METHODS

Surgical and nonsurgical patients from a multicenter adult spinal deformity database who had completed pretreatment and 1-year follow-up questionnaires (Core Outcome Measures Index [COMI], Oswestry Disability Index [ODI], Medical Outcomes Study 36-item short-form questionnaire, 22-item Scoliosis Research Society Outcomes questionnaire, and an anchor question of "back health"-related change during the previous year) were evaluated. The MCIDs for each HRQoL measure were calculated using an anchor-based method and latent class analysis for the overall population and subpopulations stratified by age, gender, and baseline scores (ODI and COMI) separately for patients with positive versus negative perceptions of change.

RESULTS

Patients with a baseline ODI score of <20, 20-40, and >40 had an MCID of 2.24, 11.35, and 26.57, respectively. Similarly, patients with a baseline COMI score of <2.75, 2.8-5.4, and >5.4 had an MCID of 0.59, 1.38, and 3.67 respectively. The overall MCID thresholds for deterioration and improvement were 0.27 and 2.62 for COMI, 2.23 and 14.31 for ODI, and 0.01 and 0.71 for 22-item Scoliosis Research Society Outcomes questionnaire, respectively.

CONCLUSIONS

The results from the present study have demonstrated that MCIDs change in accordance with the baseline scores and direction of change but not by age or gender. The MCID, in its current state, should be considered a concept rather than a constant.

Parkinson's Disease With Depression: The Correlations Between Neuroinflammatory Factors and Neurotransmitters in Cerebrospinal Fluid

Background: To explore the changes of neuroinflammatory factors in cerebrospinal fluid (CSF) and their correlation with monoamine neurotransmitters in Parkinson’s disease (PD) with depression (PD-D) patients.

Methods: Neuroinflammatory factors and neurotransmitters in CSF were measured and compared between PD with no depression (PD-ND) and PD-D groups. The relationship between PD-D and neuroinflammatory factors was studied by binary logistic regression equation, and the related factors of PD-D were adjusted. The correlations of the levels of neuroinflammatory factors and neurotransmitters in PD-D group were analyzed.

Results: The levels of tumor necrosis factor (TNF)-α in CSF from PD-D group were significantly higher and there were no significant differences in the levels of interleukin-1β, prostaglandin (PG) E₂, hydrogen peroxide (H₂O₂), and nitric oxide (NO). The 24-item Hamilton Depression Scale (HAMD-24) score was positively correlated with the level of TNF-α in CSF. Binary logistic regression showed that the OR of CSF TNF-α level was 1.035 (95% CI 1.002–1.069). The level of dopamine (DA) in CSF of PD-D group was significantly lower than that in PD-ND group. TNF-α level was negatively correlated with DA level in CSF from PD patients (r = −0.320, P = 0.003).

Conclusions: Neuroinflammatory factors, especially TNF-α, may play an important role in PD-D. It may cause damage to DA neurons and lead to the depletion of DA, which is related to the occurrence and development of PD-D.

Alterations in intrinsic functional networks in Parkinson's disease patients with depression: A resting-state functional magnetic resonance imaging study

Aims

The aim of this research was to investigate the alterations in functional brain networks and to assess the relationship between depressive impairment and topological network changes in Parkinson's disease (PD) patients with depression (DPD).

Methods

Twenty‐two DPD patients, 23 PD patients without depression (NDPD), and 25 matched healthy controls (HCs) were enrolled. All participants were examined by resting‐state functional magnetic resonance imaging scans. Graph theoretical analysis and network‐based statistic methods were used to analyze brain network topological properties and abnormal subnetworks, respectively.

Results

The DPD group showed significantly decreased local efficiency compared with the HC group (P = .008, FDR corrected). In nodal metrics analyses, the degree of the right inferior occipital gyrus (P = .0001, FDR corrected) was positively correlated with the Hamilton Depression Rating Scale scores in the DPD group. Meanwhile, the temporal visual cortex, including the bilateral middle temporal gyri and right inferior temporal gyrus in the HC and NDPD groups and the left posterior cingulate gyrus in the NDPD group, was defined as hub region, but not in the DPD group. Compared with the HC group, the DPD group had extensive weakening of connections between the temporal‐occipital visual cortex and the prefrontal‐limbic network.

Conclusions

These results suggest that PD depression is associated with disruptions in the topological organization of functional brain networks, mainly involved the temporal‐occipital visual cortex and the posterior cingulate gyrus and may advance our current understanding of the pathophysiological mechanisms underlying DPD.

Subtypes of Sleep Disturbance in Parkinson's Disease Based on the Cross-Culturally Validated Korean Version of Parkinson's Disease Sleep Scale-2

BACKGROUND AND PURPOSE

This study aimed to determine the clinimetric properties of the Korean version of Parkinson's Disease Sleep Scale-2 (K-PDSS-2) and whether distinct subtypes of sleep disturbance can be empirically identified in patients with Parkinson's disease (PD) using the cross-culturally validated K-PDSS-2.

METHODS

The internal consistency, test-retest reliability, scale precision, and convergent validity of K-PDSS-2 were assessed in a nationwide, multicenter study of 122 patients with PD. Latent class analysis (LCA) was used to derive subgroups of patients who experienced similar patterns of sleep-related problems and nocturnal disabilities.

RESULTS

The total K-PDSS-2 score was 11.67±9.87 (mean±standard deviation) at baseline and 12.61±11.17 at the retest. Cronbach's α coefficients of the total K-PDSS-2 scores at baseline and follow-up were 0.851 and 0.880, respectively. The intraclass correlation coefficients over the 2-week study period ranged from 0.672 to 0.848. The total K-PDSS-2 score was strongly correlated with health-related quality of life measures and other corresponding nonmotor scales. LCA revealed three distinct subtypes of sleep disturbance in the study patients: "less-troubled sleepers," "PD-related nocturnal difficulties," and "disturbed sleepers."

CONCLUSIONS

K-PDSS-2 showed good clinimetric attributes in accordance with previous studies that employed the original version of the PDSS-2, therefore confirming the cross-cultural usefulness of the scale. This study has further documented the first application of an LCA approach for identifying subtypes of sleep disturbance in patients with PD.

Functional connectivity markers of depression in advanced Parkinson's disease

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Patient-specific 42-ICNs template was created from 156 PD patients’ rs-fMRI data.

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6 FC markers significantly contributed to depression discrimination in PD.

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Classifiers achieved the mean accuracy of 82.4% for depression diagnosis in PD.

Background

Depression is a common comorbid condition in Parkinson's disease and a major contributor to poor quality of life. Despite this, depression in PD is under-diagnosed due to overlapping symptoms and difficulties in the assessment of depression in cognitively impaired old patients.

Objectives

This study is to explore functional connectivity markers of depression in PD patients using resting-state fMRI and help diagnose whether patients have depression or not.

Methods

We reviewed 156 advanced PD patients (duration > 5 years; 59 depressed ones) and 45 healthy control subjects who underwent a resting-state fMRI scanning. Functional connectivity analysis was employed to characterize intrinsic connectivity networks using group independent component analysis and extract connectivity features. Features were put into an all-relevant feature selection procedure within cross-validation loops, to identify features with significant discriminative power for classification. Random forest classifiers were built for depression diagnosis, on the basis of identified features.

Results

42 intrinsic connectivity networks were identified and arranged into subcortical, auditory, somatomotor, visual, cognitive control, default-mode and cerebellar networks. Six features were significantly relevant to classification. They were connectivity within posterior cingulate cortex, within insula, between posterior cingulate cortex and insula/hippocampus+amygdala, between insula and precuneus, and between superior parietal lobule and medial prefrontal cortex. The mean accuracy achieved with classifiers to discriminate depressed patients from the non-depressed was 82.4%.

Conclusions

Our findings provide preliminary evidence that resting-state functional connectivity can characterize depressed PD patients and help distinguish them from non-depressed ones.

Discerning depressive symptoms in patients with obstructive sleep apnea: the effect of continuous positive airway pressure therapy on Hamilton Depression Rating Scale symptoms

The assessment of depression in obstructive sleep apnea (OSA) is confounded by the overlap in symptoms between the disorders. However, previous analysis by our group has suggested that while some depressive symptoms tend to overlap with OSA (such as insomnia, lethargy, impaired concentration, psychomotor retardation) other, nonoverlapping symptoms appear more specific to depression (such as negative affect, anhedonia, and depressive cognitions). We sought to determine the value of such categorization of depressive symptoms in identifying clinical depression within OSA patient populations by examining the response of these two categories of depression symptoms to treatment of OSA by continuous positive airway pressure (CPAP). Three hundred fifty-seven unselected, CPAP-naïve OSA patients were treated with CPAP and followed over 12 weeks. Depressive symptoms were elicited before, during and at the end of this period using the Hamilton Rating Scale for Depression (HAM-D). Data were analyzed using latent growth curve modeling. At baseline, individuals reported proportionally more severe overlapping than nonoverlapping depressive symptoms. Both overlapping and nonoverlapping symptoms significantly decreased over time, but with a greater reduction in the severity of overlapping than nonoverlapping depressive symptoms. Moreover, greater CPAP use was associated with a faster rate of improvement in overlapping symptoms, but not in nonoverlapping symptoms. These findings suggest that nonoverlapping depressive symptoms may be useful discriminators of clinical depression amongst patients with untreated, symptomatic OSA.

Suicide in Parkinson's disease

Persons with Parkinson's disease (PwP) have many known risk factors for suicide and suicidal ideation (SI). Despite this, there is limited understanding of suicidality in this population. We conducted a systematic review to synthesise the available literature on suicidality in PwP and highlight areas for potential intervention and further research. We identified 116 articles discussing SI, suicidal behaviours, suicide attempts and/or fatal suicide in PwP. These articles describe prevalence, suicide methods, risk factors for suicide and SI and treatment of suicidality. In this review, we summarise the current literature and provide suggestions for how clinicians can identify and treat PwP who are at risk for suicide, for example, through aggressive treatment of depression and improved screening for access to lethal means.

Anxiety and Levodopa Equivalent Daily Dose Are Potential Predictors of Sleep Quality in Patients With Parkinson Disease in Taiwan

Background and Purpose: Non-motor symptoms of Parkinson disease (PD) have a strong negative impact on the health-related quality of life (QoL) of patients with PD. Sleep disturbance is an important non-motor symptom because of its high prevalence. However, previous studies investigating the determinants of sleep quality in patients with PD have revealed inconsistent results. Our study evaluated the correlations between sleep quality in patients with PD and disease-related variables, medications used depression, anxiety, and QoL and identified the determinants of sleep disturbance in people with PD in Taiwan.

Methods: A total of 134 patients with PD were recruited from the outpatient clinic. We examined the correlations between the Parkinson disease sleep scale-2 (PDSS-2) scores and different variables, namely the Unified Parkinson Disease Rating Scale, Parkinson disease questionnaire, Beck Depression Inventory, and Beck Anxiety Inventory (BAI). Logistic regression analysis was used to assess the potential predictive variables for sleep quality in patients with PD.

Results: Among our participants, 47.8% were classified as poor sleepers (PDSS-2 = 15–60). Correlation analysis demonstrated that poor sleepers exhibited longer disease durations, higher levodopa equivalent daily doses (LEDDs), higher PD severity, more depression and anxiety symptoms, poorer QoL, more frequent unemployed status, higher hypnotics use, higher dependency for activities of daily living, more motor impairments, and more therapy-related complications. Logistic regression revealed that the LEDD was a significant predictive factor of sleep quality.

Conclusion: Poor sleepers constituted approximately half of our patients with PD. The participants experienced more favorable sleep if they were currently working. Increased PD duration, severity, depression or anxiety symptoms, and doses of dopaminergic therapy were significantly associated with poor sleep quality. Continued working, attempts to treat comorbid anxiety or depression, and avoidance of overdosage of dopaminergic treatments may improve sleep quality in patients with PD.

Committed vs. uncommitted meat eaters: Understanding willingness to change protein consumption

There is a growing trend of consumers in developed countries substituting alternative protein sources for meat and purchasing meat products with specific production-system related credence attributes. This study of Australian meat consumers identifies consumer segments with varying levels of willingness to make the following changes to their protein consumption: reduce meat consumption, follow a meat-free diet most of the time, avoid meat consumption altogether, and follow a strict plant-based diet (i.e., stop eating all animal-products). Segments are characterised, and predictors of segment membership are determined. Discrete Factor analysis, based on a nationally-representative sample of 287 Australian meat consumers surveyed in 2016, identified four unique segments. Findings show that 46% of consumers are not willing to make any changes to their meat/protein consumption ('Committed Meat Eaters'), 22% are willing to reduce meat consumption ('Willing Meat Reducers'), 15% are willing to stop meat consumption/consume plant-based protein foods only ('Prospective Veg*ns'), and 17% are undecided about future change ('Undecided Meat Eaters'). The key factor differentiating Committed Meat Eaters from other segments is the perception that food choices are inadequate in meat-free diets. Committed Meat Eaters are also less likely to believe livestock farming contributes to climate change, and to report a recent reduction in the consumption of at least one type of meat than are Willing Meat Reducers and Prospective Veg*ns. These findings are expected to be of interest to individuals and organisations who may play a role in meeting current and future consumer demand for meat and alternative protein products.

An Investigation on the Clinical Features and Neurochemical Changes in Parkinson's Disease With Depression

Objective: To investigate the clinical features and neurochemical changes in Parkinson's disease with depression (PD-D). Methods: A total of 478 PD patients were divided into PD-D and PD patients without depression (PD-ND) groups according to the 24-item Hamilton Depression Rating Scale (HAMD) score. Demographic variables, motor and non-motor symptoms and activities of daily living were evaluated. The independent influencing factors of PD-D were investigated via binary logistic regression analysis. The levels of neurotransmitters in cerebrospinal fluid (CSF) were measured and their correlations with HAMD score were analyzed. Results: The proportion of PD-D was 59.0%, of which 76.95, 20.92, and 2.13% had mild, moderate, and severe depression, respectively. Anxiety/somatization was the most prevalent sub-factor of HAMD in PD-D. The scores of UPDRS III, postural instability/gait difficulty (PIGD) type and the scores of 14-item Hamilton Anxiety Scale (HAMA) and 14-item Chalder Fatigue Scale (FS) were independently associated with PD-D. The levels of dopamine (DA) and 5-hydroxytryptamine (5-HT) were all significantly reduced in PD-D group compared with those in PD-ND group. HAMD scores were negatively correlated with the DA levels in CSF. Conclusions: PD patients have a high proportion of depression, mainly of mild and moderate levels. The profile of depression in PD population is subtly different from that of the general population. Motor symptoms, PIGD type, anxiety and fatigue are the significant influencing factors of PD-D. Compared to 5-HT, DA may play a more important role in PD-D.

Clinical Presentation of Anxiety in Parkinson's Disease: A Scoping Review

Up to 40% of all individuals with Parkinson's disease (PD) are estimated to experience anxiety that interferes with daily functioning. This article describes research regarding the presentation of anxiety in PD and the influence anxiety has on participation in this population. A scoping review identified 1,635 articles, of which 49 met the inclusion criteria. This review identified that anxiety in PD is often associated with a range of clinical correlates related to demographic and clinical characteristics (age, gender, disease stage, duration, progression), motor symptoms (tremor, bradykinesia, dystonia, freezing of gait, symptom severity), treatment-related complications (on/off fluctuations, on with dyskinesia, unpredictable off), and non-motor symptoms (sleep abnormalities, fatigue, cognitive impairment, depression). These findings can be used to increase clinicians' awareness toward the specific clinical correlates linked to anxiety in PD so that mental health concerns can be detected and addressed more readily in practice.

Diagnostic Validity and Factor Analysis of Montgomery-Asberg Depression Rating Scale in Parkinson Disease Population

BACKGROUND

The Montgomery-Asberg Depression Rating Scale (MADRS) is commonly used to assess major depression in Parkinson disease (PD), but studies on its utility are few. This study examines the validity and factor structure of MADRS in population with PD.

METHODS

In 104 patients with idiopathic PD, major depression was diagnosed by Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision; DSM-IV-TR) criteria, and all patients were rated by MADRS.

RESULTS

The MADRS showed good concurrent validity with DSM-IV-TR criteria. The diagnostic cutoff was established as 16/17 (sensitivity 97.43, specificity 100%, positive predictive value 100%, and negative predictive value 98.48%). Factor analysis identified 3 factors, accounting for 76% of total variance: "sadness-anhedonia" comprising apparent sadness, reported sadness, concentration difficulties, lassitude, inability to feel, pessimistic thoughts, and suicidal ideas; "anxiety" with reduced sleep and inner tension; and "vegetative symptoms" with reduced appetite.

CONCLUSION

The MADRS has diagnostic utility in major depression in PD. The 3-factor structure of MADRS may help to understand the different dimensions of major depression and identify distinct symptom subgroups in this population.

Four Distinct Health Profiles in Older Patients With Cancer: Latent Class Analysis of the Prospective ELCAPA Cohort

BACKGROUND

Several studies have evaluated the independent prognostic value of impairments in single geriatric-assessment (GA) components in elderly cancer patients. None identified homogeneous subgroups. Our aims were to identify such subgroups based on combinations of GA components and to assess their associations with treatment decisions, admission, and death.

METHODS

We prospectively included 1,021 patients aged ≥70 years who had solid or hematologic malignancies and who underwent a GA in one of two French teaching hospitals. Two geriatricians independently selected candidate GA parameters for latent class analysis, which was then performed on the 821 cases without missing data. Age, gender, tumor site, metastatic status, and inpatient versus outpatient status were used as active covariates and predictors of class membership. Outcomes were cancer treatment decisions, overall 1-year mortality, and 6-month unscheduled admissions. Sensitivity analyses were performed on the overall population of 1,021 patients and on 375 newly enrolled patients.

RESULTS

We identified four classes: relatively healthy (LC1, 28%), malnourished (LC2, 36%), cognitive and mood impaired (LC3, 15%), and globally impaired (LC4, 21%). Tumor site, metastatic status, age, and in/outpatient status independently predicted class membership (p < .001). In adjusted pairwise comparisons, compared to LC1, the three other LCs were associated with higher risks of palliative treatment, death, and unscheduled admission (p ≤ .05). LC4 was associated with 1-year mortality and palliative treatment compared to LC2 and LC3 (p ≤ .05).

CONCLUSION

We identified four health profiles that may help physicians select cancer treatments and geriatric interventions. Researchers may find these profiles useful for stratifying patients in clinical trials.

Altered brain network centrality in depressed Parkinson's disease patients

BACKGROUND

Depression is a relatively common and serious nonmotor symptom of Parkinson's disease (PD), which reduces the quality of patients' life. Although disturbances in some related brain networks have been reported, the pathophysiology of depression in PD is still unclear. Here, we aim to investigate whole-brain functional connectivity patterns in depressed PD patients.

METHODS

We recruited 17 PD patients diagnosed with major depressive disorder, 17 PD patients without depression, and 17 healthy control subjects. Resting-state functional MRI and eigenvector centrality mapping were used to identify functional connectivity alterations among these groups.

RESULTS

Results showed that depressed PD patients had decreased functional connectivity in the left dorsolateral prefrontal cortex and right superior temporal gyrus and increased functional connectivity in the right posterior cingulate cortex, compared to nondepressed patients. In addition, there was a significant negative correlation between functional connectivity and depression scores in the posterior cingulate cortex.

CONCLUSIONS

This study suggests that functional connectivity changes in certain nodes of brain networks might contribute to depression in patients with PD.

Prevalence, clinical features and treatment of depression in Parkinson’s disease: An update

Parkinson’s disease (PD) is one of the most prevalent neurodegenerative diseases which typically affects individuals over 65 years. Although the symptomatology is predominantly motor, neuropsychiatric manifestations, e.g., depression, apathy, anxiety, and cognitive impairment occur in the course of the illness and can have a great impact on the quality of life in these patients. Parkinson’s disease is commonly comorbid with depression with prevalence rates of depression, generally higher than those reported in general population. Depression in PD is frequently underestimated and consequently undertreated, which have significant effects on the quality of life in these patients. The neurobiology of depression in PD is complex and involves alterations in dopaminergic, serotonergic, noradrenergic and possibly other neurotransmitter systems which are affected in the course of the disease. The tricyclic antidepressants and the selective serotonin reuptake inhibitors are the two classes of antidepressant drugs used for depressive symptoms in PD. Several published studies suggested that both classes are of comparable efficacy. Other serotonergic antidepressants, e.g., nefazodone and trazodone have also been of benefit. Meanwhile, there are limited data available on other drugs but these suggest a benefit from the serotonin and noradrenaline reuptake inhibitors such as mirtazapine, venlafaxine, atomoxetine and duloxetine. Some of the drugs used in symptomatic treatment of PD, e.g., the irreversible selective inhibitors of the enzyme monoamine oxidase-B, rasagiline and selegiline as well as the dopamine receptor agonist pramipexole are likely to have direct antidepressant activity independent of their motor improving action. This would make these drugs an attractive option in depressed subjects with PD. The aim of this review is to provide an updated data on the prevalence, clinical features of depression in subjects with PD. The effects of antiparkinsonian and antidepressant drugs on depressive symptoms in these patients are also discussed.

Patients' expectations of deep brain stimulation, and subjective perceived outcome related to clinical measures in Parkinson's disease: a mixed-method approach

OBJECTIVE

To study patients' expectations of subthalamic deep brain stimulation (STN-DBS) and their subjective perceived outcome, by using qualitative and quantitative methods in Parkinson's disease (PD).

METHODS

PD patients were prospectively examined before and 3 months after surgery. Semistructured interviews regarding preoperative expectations and postsurgical subjective perceived outcome were conducted. These were analysed using content analysis. For statistical analyses, patients were classified according to their subjective perceived outcome, resulting in three different subjective outcome groups (negative, mixed, positive outcome). The groups were used for multiple comparisons between and within each group regarding motor impairment, quality of life (QoL), neuropsychiatric status and cognitive functioning, using standard instruments. A logistic regression analysis was conducted to find predictors of subjective negative outcome. Receiver operating characteristic curves were used to analyse cut-off scores for predictive tests.

RESULTS

Of the 30 PD patients participating, 8 had a subjective negative outcome, 8 a mixed and 14 a positive outcome. All groups significantly improved in motor functioning. Patients with subjective negative outcome were characterised by preoperative unrealistic expectations, no postsurgical improvement in QoL, and significantly higher presurgical and postsurgical apathy and depression scores. Higher preoperative apathy and depression scores were significant predictors of negative subjective outcome. Cut-off scores for apathy and depression were identified.

CONCLUSIONS

The mixed-method approach proved useful in examining a patient's subjective perception of STN-DBS outcome. Our results show that significant motor improvement does not necessarily lead to a positive subjective outcome. Moreover, PD patients should be screened carefully before surgery regarding apathy and depression. (DRKS-ID: DRKS00003221).

A latent class analysis of psychological disturbance in Parkinson's disease

OBJECTIVE

Psychological symptoms are common in Parkinson's disease (PD). Psychological symptoms do not respond to psychotropic medications as well in patients with PD as in patients with psychiatric illnesses who do not have PD. Evidence that PD patients can be classified into distinct psychological symptom subgroups is conflicting. This study sought to examine potential psychological heterogeneity in PD with a broader range of instruments than has been used in previous studies.

METHODS

A comprehensive battery of psychological measures assessing dysphoria, apathy, anhedonia, anxiety, and negative affect was administered to 95 PD patients without global cognitive impairment. Latent class analysis was used to identify subgroups of patients based on continuous variables derived from the psychological battery. Multinomial regression was used to examine predictors of classification.

RESULTS

The latent class analysis identified three subgroups with incremental levels of psychopathology across most symptom domains. One exception was a greater level of affective flattening in the "psychologically healthy" group compared with the "moderate symptoms" group. Greater motor dysfunction and less education were associated with greater severity of psychological symptoms.

CONCLUSIONS

These results support high psychological co-morbidity in PD, which complicates the treatment of individual symptoms. In addition, emotional blunting and anhedonia may be less indicative of widespread psychological distress than anxiety, dysphoria, and cognitive aspects of apathy. Clinicians should be aware that PD patients with greater motor dysfunction and less education are at greater risk not only for depression but also for a variety of other psychological symptoms that may not be routinely assessed.

Depressive symptoms in Parkinson's disease and in non-neurological medical illnesses

BACKGROUND

Patients with neurological and non-neurological medical illnesses very often complain of depressive symptoms that are associated with cognitive and functional impairments. We compared the profile of depressive symptoms in Parkinson's disease (PD) patients with that of control subjects (CS) suffering from non-neurological medical illnesses.

METHODS

One-hundred PD patients and 100 CS were submitted to a structured clinical interview for identification of major depressive disorder (MDD) and minor depressive disorder (MIND), according to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision (DSM-IV-TR), criteria. The Hamilton Depression Rating Scale (HDRS) and the Beck Depression Inventory (BDI) were also administered to measure depression severity.

RESULTS

When considering the whole groups, there were no differences in depressive symptom frequency between PD and CS apart from worthlessness/guilt, and changes in appetite reduced rates in PD. Further, total scores and psychic and somatic subscores of HDRS and BDI did not differ between PD and CS. After we separated PD and CS in those with MDD, MIND, and no depression (NODEP), comparing total scores and psychic/somatic subscores of HDRS and BDI, we found increased total depression severity in NODEP PD and reduced severity of the psychic symptoms of depression in MDD PD, with no differences in MIND. However, the severity of individual symptom frequency of depression was not different between PD and CS in MDD, MIND, and NODEP groups.

CONCLUSION

Although MDD and MIND phenomenology in PD may be very similar to that of CS with non-neurological medical illnesses, neurological symptoms of PD may worsen (or confound) depression severity in patients with no formal/structured DSM-IV-TR, diagnosis of depressive mood disorders. Thus, a thorough assessment of depression in PD should take into consideration the different impacts of neurological manifestations on MDD, MIND, and NODEP.

A personalized BEST: characterization of latent clinical classes of nonischemic heart failure that predict outcomes and response to bucindolol

Background

Heart failure patients with reduced ejection fraction (HFREF) are heterogenous, and our ability to identify patients likely to respond to therapy is limited. We present a method of identifying disease subtypes using high-dimensional clinical phenotyping and latent class analysis that may be useful in personalizing prognosis and treatment in HFREF.

Methods

A total of 1121 patients with nonischemic HFREF from the β-blocker Evaluation of Survival Trial were categorized according to 27 clinical features. Latent class analysis was used to generate two latent class models, LCM A and B, to identify HFREF subtypes. LCM A consisted of features associated with HF pathogenesis, whereas LCM B consisted of markers of HF progression and severity. The Seattle Heart Failure Model (SHFM) Score was also calculated for all patients. Mortality, improvement in left ventricular ejection fraction (LVEF) defined as an increase in LVEF ≥5% and a final LVEF of 35% after 12 months, and effect of bucindolol on both outcomes were compared across HFREF subtypes. Performance of models that included a combination of LCM subtypes and SHFM scores towards predicting mortality and LVEF response was estimated and subsequently validated using leave-one-out cross-validation and data from the Multicenter Oral Carvedilol Heart Failure Assessment Trial.

Results

A total of 6 subtypes were identified using LCM A and 5 subtypes using LCM B. Several subtypes resembled familiar clinical phenotypes. Prognosis, improvement in LVEF, and the effect of bucindolol treatment differed significantly between subtypes. Prediction improved with addition of both latent class models to SHFM for both 1-year mortality and LVEF response outcomes.

Conclusions

The combination of high-dimensional phenotyping and latent class analysis identifies subtypes of HFREF with implications for prognosis and response to specific therapies that may provide insight into mechanisms of disease. These subtypes may facilitate development of personalized treatment plans.

Psychiatric syndromes in Parkinson's disease

PURPOSE OF REVIEW

To examine progress about relevant behavioural and psychiatric disorders in Parkinson's disease, such as depression, apathy, psychosis, and impulse control disorder.

RECENT FINDINGS

Several recent studies have characterized the phenomenology of depression in Parkinson's disease, and randomized controlled trials have demonstrated the efficacy of tricyclics, selective serotonin reuptake inhibitors and psychotherapy for depression in Parkinson's disease. Apathy is a valid behavioural syndrome in Parkinson's disease and is associated with depression and cognitive deficits. Psychosis is highly prevalent in the late stages of the disease, but there are few effective therapeutic modalities for this psychiatric condition. Impulse control disorders are also relatively frequent in Parkinson's disease, and are associated with comorbid psychiatric disorders.

SUMMARY

Standardized criteria should be used to diagnose depression and apathy in Parkinson's disease. Psychotherapy and pharmacotherapy are useful treatment modalities for affective disorders in Parkinson's disease. Clozapine is still the most effective, albeit rarely used, treatment for psychosis in Parkinson's disease. Impulse control disorders are relatively frequent in Parkinson's disease and all patients should be screened for this complex disorder.

Components of depression in Parkinson disease

Depression is a clinically heterogeneous disorder common in Parkinson disease (PD). The goal of this study was to characterize PD depression in terms of components, including negative affect, apathy, and anhedonia. Ninety-five, nondemented individuals with idiopathic PD underwent a diagnostic interview and psychological battery. Twenty-seven patients (28%) met Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition [DSM-IV]) criteria for a current depressive episode. The best-fitting confirmatory factor analysis model had 3 factors (negative affect, apathy, and anhedonia). Apathy loaded most strongly onto a second-order factor representing global psychological disturbance. All factors are uniquely associated with depression status. Negative affect exhibited the strongest relationship. Psychological disturbance in PD is heterogeneous and can produce symptoms of apathy, anhedonia, and negative affect. Apathy appears to be the core neuropsychiatric feature of PD, whereas negative affect (eg, dysphoria) seems to be most pathognomonic of depression. Future studies should examine the specific neural correlates and treatment response patterns unique to these 3 components.

Psychosis, apathy, depression and anxiety in Parkinson's disease

Psychiatric symptoms are important non-motor features in PD, which occur at high frequency and have significant impact on health related quality of life. This review concentrates on the prevalence, pathophysiology, diagnosis and treatment of depression, anxiety, apathy and psychosis. The pathophysiology of these disorders is complex, reflecting the widespread brainstem and cortical pathology in PD, with involvement of several neurotransmitters, including dopaminergic, serotonergic, noradrenergic and cholinergic systems. The diagnosis of psychiatric conditions, in particular affective disorders, is challenging because of the overlap of somatic features of psychiatric disorders and underlying movement disorder. The pathogenesis is likely to differ considerably from non-PD patients, and treatments used in general psychiatry services may not be as effective in PD and will require clearer clarification in well-designed clinical studies. Management strategies include adjustment of dopaminergic medication, use of psychotropic treatments and behavioural and psychological approaches. However, the future challenge will be to develop treatments developed specifically for the pathogenesis of these disorders in PD.