Depression symptomatology correlates with event-related potentials in Parkinson's disease: An affective priming study

Higher cortical excitability to negative emotions involved in musculoskeletal pain in Parkinson's disease

OBJECTIVE

Changes in brain structure and neurotransmitter systems are involved in pain in Parkinson's disease (PD), and emotional factors are closely related to pain. Our study applied electroencephalography (EEG) to investigate the role of emotion in PD patients with chronic musculoskeletal pain.

METHODS

Forty-two PD patients with chronic musculoskeletal pain and 38 without were enrolled. EEG data were recorded under resting conditions, and while viewing pictures with neutral, positive, and negative content. We compared spectrum power, functional connectivity, and late positive potential (LPP), an event-related potential (ERP), between the groups.

RESULTS

PD patients with pain tended to have higher scores for the Hamilton Rating Scale for Depression (HRSD). In the resting EEG, mean β-band amplitude was significantly higher in patients with pain than in those without. Logistic regression analysis showed that higher HRSD scores and higher mean β-band amplitude were associated with pain. ERP analysis revealed that the amplitudes of LPP difference waves (the absolute difference between positive and negative condition LPP and neutral condition LPP) at the central-parietal region were significantly reduced in patients with pain (P = 0.029). Spearman correlation analysis showed that the amplitudes of late (700-1000 ms) negative versus neutral condition LPP difference waves were negatively correlated with pain intensity, assessed by visual analogue scale, (r = -0.393, P = 0.010) and HRSD scores (r = -0.366, P = 0.017).

CONCLUSION

Dopaminergic and non-dopaminergic systems may be involved in musculoskeletal pain in PD by increasing β-band activity and weakening the connection of the θ-band at the central-parietal region. PD patients with musculoskeletal pain have higher cortical excitability to negative emotions. The changes in pain-related EEG may be used as electrophysiological markers and therapeutic targets in PD patients with chronic pain.

Transcranial direct current stimulation of the prefrontal cortex improves depression-like behaviors in rats with Parkinson's disease

Depression associated with Parkinson's disease (PD) seriously affects patients, and there is a lack of effective treatments. Transcranial direct current stimulation (tDCS) is increasingly used as a new non-invasive neuromodulation technique in the treatment of neuropsychiatric diseases. However, there is a paucity of research on tDCS for PD-related depression. Our study used PD model rats established with unilateral destruction of the medial forebrain bundle (MFB) to observe the modulatory effects of tDCS acting on the mPFC on depression-like behaviors. We found that tDCS acting on the mPFC improved depression-like behaviors in PD model rats by increasing sucrose intake in sucrose preference test (n = 7-10 rats/group) and shortening immobility time in forced swimming test (n = 7-8 rats/group). Meanwhile, tDCS decreased the expression of c-Fos protein (n = 8-11 rats/group) and the excitation of glutamatergic neurons (n = 6-8 rats/group) in the PrL and LHb of PD model rats. Western blots showed that tDCS decreased the overexpression of serine 845 phosphorylation site of AMPA receptor GluR1 (p-GluR1-S845) in the PrL and LHb of PD model rats (n = 8-11 rats/group), and the overexpression of p-GluR1-S831 in the LHb (n = 8-11 rats/group). The results of this study show that tDCS acting on the mPFC helps to improve PD-related depression, which involves the modulation of excitability and AMPA receptor phosphorylation on the PrL and LHb neurons.

A pilot study of machine learning of resting-state EEG and depression in Parkinson's disease

Introduction

Depression is a non-motor symptom of Parkinson's disease (PD). PD-related depression is difficult to diagnose, and the neurophysiological basis is poorly understood. Depression can markedly affect cortical function, which suggests that scalp electroencephalography (EEG) may be able to distinguish depression in PD. We conducted a pilot study of depression and resting-state EEG in PD.

Methods

We recruited 18 PD patients without depression, 18 PD patients with depression, and 12 demographically similar non-PD patients with clinical depression. All patients were on their usual medications. We collected resting-state EEG in all patients and compared cortical brain signal features between patients with and without depression. We used a machine learning algorithm that harnesses the entire power spectrum (linear predictive coding of EEG Algorithm for PD: LEAPD) to distinguish between groups.

Results

We found differences between PD patients with and without depression in the alpha band (8-13 Hz) globally and in the beta (13-30 Hz) and gamma (30-50 Hz) bands in the central electrodes. From two minutes of resting-state EEG, we found that LEAPD-based machine learning could robustly distinguish between PD patients with and without depression with 97 % accuracy and between PD patients with depression and non-PD patients with depression with 100 % accuracy. We verified the robustness of our finding by confirming that the classification accuracy gracefully declines as data are randomly truncated.

Conclusions

Our results suggest that resting-state EEG power spectral analysis has the potential to distinguish depression in PD accurately. We demonstrated the efficacy of the LEAPD algorithm in identifying PD patients with depression from PD patients without depression and controls with depression. Our data provide insight into cortical mechanisms of depression and could lead to novel neurophysiological markers for non-motor symptoms of PD.

Sleep and affective disorders in relation to Parkinson's disease risk among older women from the Women's Health Initiative

OBJECTIVES

To evaluate sleep and affective (mood/anxiety) disorders as clinical predictors of incident Parkinson's disease (PD) among women ≥65 years of age.

METHODS

We performed secondary analyses with available data from the Women's Health Initiative Clinical Trials and Observational Study linked to Medicare claims. Sleep, mood and anxiety disorders at baseline were defined using diagnostic codes. Incident PD was defined using self-reported PD, first PD diagnosis, use of PD medications, and/or deaths attributed to PD. Cox regression was applied to estimate hazard ratios (HR) with 95 % confidence intervals (CI), controlling for socio-demographic/lifestyle/health characteristics. Time-to-event was calculated from baseline (1993-1998) to year of PD event, loss to follow-up, death, or December 31, 2018, whichever came first.

RESULTS

A total of 53,996 study-eligible WHI participants yielded 1756 (3.25 %) PD cases over ~14.39 (±6.18) years of follow-up. The relative risk for PD doubled among women with affective disorders (HR = 2.05, 95 % CI: 1.84, 2.27), mood disorders (HR = 2.18, 95 % CI: 1.97, 2.42) and anxiety disorders (HR = 1.97, 95 % CI: 1.75, 2.22). Sleep disorders alone (without affective) were not significantly associated with PD risk (HR = 0.85, 95 % CI: 0.69, 1.04), whereas affective disorders alone (without sleep) (HR = 1.93, 95 % CI: 1.72, 2.17) or in combination with sleep disorders (HR = 2.18, 95 % CI: 1.85, 2.56) were associated with twice the PD risk relative to no sleep/affective disorders.

LIMITATIONS

Observational design; Selection bias; Information bias; Generalizability.

CONCLUSIONS

Among older women, joint sleep/affective disorders and affective disorders alone are strong clinical predictors of incident PD over 14 years.

Psychotropic medication use and Parkinson's disease risk amongst older women

OBJECTIVE

To examine associations of antidepressant, anxiolytic and hypnotic use amongst older women (≥65 years) with incident Parkinson's Disease (PD), using data from Women's Health Initiative linked to Medicare claims.

METHODS

PD was defined using self-report, first diagnosis, medications and/or death certificates and psychotropic medications were ascertained at baseline and 3-year follow-up. Cox regression models were constructed to calculate adjusted hazard ratios (aHR) with 95% confidence intervals (CI), controlling for socio-demographic, lifestyle and health characteristics, overall and amongst women diagnosed with depression, anxiety and/or sleep disorders (DASD).

RESULTS

A total of 53,996 WHI participants (1,756 PD cases)-including 27,631 women diagnosed with DASD (1,137 PD cases)-were followed up for ~14 years. Use of hypnotics was not significantly associated with PD risk (aHR = 0.98, 95% CI: 0.82, 1.16), whereas PD risk was increased amongst users of antidepressants (aHR = 1.75, 95% CI: 1.56, 1.96) and anxiolytics (aHR = 1.48, 95% CI: 1.25, 1.73). Compared to non-users of psychotropic medications, those who used 1 type had ~50% higher PD risk, whereas those who used ≥2 types had ~150% higher PD risk. Women who experienced transitions in psychotropic medication use ('use to non-use' or 'non-use to use') between baseline and 3-year follow-up had higher PD risk than those who did not. We obtained similar results with propensity scoring and amongst DASD-diagnosed women.

INTERPRETATION

The use of antidepressants, anxiolytics or multiple psychotropic medication types and transitions in psychotropic medication use was associated with increased PD risk, whereas the use of hypnotics was not associated with PD risk amongst older women.

Theta and gamma connectivity is linked with affective and cognitive symptoms in Parkinson's disease

BACKGROUND

The progression of Parkinson's disease (PD) can often exacerbate symptoms of depression, anxiety, and/or cognitive impairment. In this study, we explore the possibility that multiple brain network responses are associated with symptoms of depression, anxiety and cognitive impairment in PD. This association is likely to provide insights into a single multivariate relationship, where common affective symptoms occurring in PD cohorts are related with alterations to electrophysiological response.

METHODS

70 PD patients and 21 healthy age-matched controls (HC) participated in a high-density electroencephalography (EEG) study. Functional connectivity differences between PD and HC groups of oscillatory activity at rest and during completion of an emotion-cognition task were examined to identify key brain oscillatory activities. A canonical correlation analysis (CCA) was applied to identify a putative multivariate relationship between connectivity patterns and affective symptoms in PD groups.

RESULTS

A CCA analysis identified a single mode of co-variation linking theta and gamma connectivity with affective symptoms in PD groups. Increases in frontotemporal gamma, frontal and parietal theta connectivity were related with increased anxiety and cognitive impairment. Decreases in temporal region theta and frontoparietal gamma connectivity were associated with higher depression ratings and PD patient age.

LIMITATIONS

This study only reports on optimal dosage of dopaminergic treatment ('on' state) in PD and did not investigate at "off" medication".

CONCLUSIONS

Theta and gamma connectivity during rest and task-states are linked to affective and cognitive symptoms within fronto-temporo-parietal networks, suggesting a potential assessment avenue for understanding brain-behaviour associations in PD with electrophysiological task paradigms.

Source activity during emotion processing and its relationship to cognitive impairment in Parkinson's disease

BACKGROUND

Neural mechanisms contributing to an underlying cognitive impairment in Parkinson's disease (PD) are poorly understood. An effective method to probe cognitive processing deficits in PD is the examination of brain activity during emotional processes, particularly in explicit language emotion recognition contexts.

METHODS

The present study utilised cortical source imaging of event related potentials (ERP) from electroencephalography (EEG) to evaluate valence judgements on negative and neutral target words in an automatic affective priming paradigm. Fifty non-demented PD patients, unmedicated for depression or anxiety, completed affective priming tasks during EEG monitoring. Cognitive impairment was measured using the validated Parkinson's Disease-Cognitive Rating Scale (PD-CRS).

RESULTS

Results reveal that compared to healthy age-matched controls, PD patients demonstrate a reduced N400 activation during affective priming tasks in bilateral regions of the middle frontal gyrus (MFG), inferior parietal lobule (IPL) and, notably, have a late wave ERP component (LPP) in left MFG, present between 600 and 800 ms, following family-wise error correction (p_FWE < 0.05). LPP in PD patients were significantly associated with PD-CRS scores.

LIMITATIONS

Although affective priming paradigms are an effective means for various domains of cognition, it is not a focused cognitive behavioural test for cognitive dysfunction. Our study is thus limited to a surrogate measure of cognitive dysfunction via examination of emotional word processing cues.

CONCLUSIONS

These findings suggest that source imaging methods with ERP paradigms in PD are effective in identifying delayed cognitive processes in PD.