Functional connectivity markers of depression in advanced Parkinson's disease

Lin, Hai; Cai, Xiaodong; Zhang, Doudou; Liu, Jiali; Peng, Na; Li, Weiping

doi:10.1016/j.nicl.2019.102130

Cited by 34 publications

(30 citation statements)

References 38 publications

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“…A RSFC study in DPD found the increased ALFF in the DMN compared with the NDPD and HCs. Other previous studies also found that the BGN, DMN, LFPN, and SN were involved DPD (Hu, Song, Li, et al., 2015), which facilitated the advancement of more detailed and integrative neural models of DPD (Lin et al., 2019; Wei et al., 2017).…”

Section: Discussionmentioning

confidence: 79%

“…A previous study on FC markers of depression in advanced PD also found RSFC features located in the subcortical, auditory, SMN, VIN, cognitive control, DMN, and cerebellar networks. These networks were significantly relevant to classification and provided preliminary evidence that can characterize DPD patients compared with NDPD (Lin et al., 2019).…”

Section: Discussionmentioning

confidence: 99%

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Aberrant functional connectivity and activity in Parkinson’s disease and comorbidity with depression based on radiomic analysis

et al. 2021

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Introduction The current diagnosis of Parkinson's disease (PD) comorbidity with depression (DPD) largely depends on clinical evaluation. However, the modality may tend to lack precision in detecting PD with depression. A radiomic approach that combines functional connectivity and activity with clinical scores has the potential to achieve accurate and differential diagnosis between PD and DPD. Methods In this study, we aimed to employ the radiomic approach to extract large‐scale features of functional connectivity and activity for differentiating among DPD, PD with no depression (NDPD), and healthy controls (HC). We extracted 6,557 features of five types from all subjects including clinical characteristics, resting‐state functional connectivity (RSFC), amplitude of low‐frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel‐mirrored homotopic connectivity (VMHC). Lasso, random forest, and support vector machine (SVM) were implemented for feature selection and dimension reduction based on the training sets, and the prediction performance for different methods in the testing sets was compared. Results The results showed that nineteen features were selected for the group of DPD versus HC, 34 features were selected for the group of NDPD versus HC, and 17 features were retained for the group of DPD versus NDPD. In the testing sets, Lasso prediction achieved the accuracies of 0.95, 0.96, and 0.85 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. Random forest achieved the accuracies of 0.90, 0.82, and 0.90 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively, while SVM yielded the accuracies of 1, 0.86 and 0.65 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. Conclusions By identifying aberrant functional connectivity and activity as potential biomarkers, the radiomic approach facilitates a deeper understanding and provides new insights into the pathophysiology of DPD to support the clinical diagnosis with high prediction accuracy.

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Section: Discussionmentioning

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Aberrant functional connectivity and activity in Parkinson’s disease and comorbidity with depression based on radiomic analysis

et al. 2021

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“…Anxiety and depression are prominent non-motor symptoms of Parkinson’s disease (PD) that are clinically debilitating ( Seppi et al, 2019 ) and may predate the onset of motor signs ( Postuma et al, 2015 ). Functional imaging studies in patients with PD and comorbid anxiety ( Dan et al, 2017 ; Wang et al, 2017 ) and depression ( Luo et al, 2014 ; Dan et al, 2017 ; Wang et al, 2018 , 2020 ; Lin et al, 2020 ) point to involvement of prefrontal cortical areas, but the associated circuit mechanisms are poorly understood. Much progress has been made in understanding circuit mechanisms related to motor signs of PD utilizing invasive intracranial recording at both cortical ( Panov et al, 2017 ) and subcortical ( Brittain and Brown, 2014 ) sites in the motor network.…”

Section: Introductionmentioning

confidence: 99%

Prefrontal Physiomarkers of Anxiety and Depression in Parkinson’s Disease

et al. 2021

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Objective: Anxiety and depression are prominent non-motor symptoms of Parkinson’s disease (PD), but their pathophysiology remains unclear. We sought to understand their neurophysiological correlates from chronic invasive recordings of the prefrontal cortex (PFC).Methods: We studied four patients undergoing deep brain stimulation (DBS) for their motor signs, who had comorbid mild to moderate anxiety and/or depressive symptoms. In addition to their basal ganglia leads, we placed a permanent prefrontal subdural 4-contact lead. These electrodes were attached to an investigational pulse generator with the capability to sense and store field potential signals, as well as deliver therapeutic neurostimulation. At regular intervals over 3–5 months, participants paired brief invasive neural recordings with self-ratings of symptoms related to depression and anxiety.Results: Mean age was 61 ± 7 years, mean disease duration was 11 ± 8 years and a mean Unified Parkinson’s Disease Rating Scale, with part III (UPDRS-III) off medication score of 37 ± 13. Mean Beck Depression Inventory (BDI) score was 14 ± 5 and Beck Anxiety Index was 16.5 ± 5. Prefrontal cortex spectral power in the beta band correlated with patient self-ratings of symptoms of depression and anxiety, with r-values between 0.31 and 0.48. Mood scores showed negative correlation with beta spectral power in lateral locations, and positive correlation with beta spectral power in a mesial recording location, consistent with the dichotomous organization of reward networks in PFC.Interpretation: These findings suggest a physiological basis for anxiety and depression in PD, which may be useful in the development of neurostimulation paradigms for these non-motor disease features.

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“…Thus, rodent studies using systematic activity mapping after acute and chronic stress have been useful to understand functional consequences of stress-related pathology. For example, functional magnetic resonance imaging (fMRI) studies in CRS mice identified dendritic remodeling of the PFC, HPC, and amygdala with altered functional connectivity across regions of the default mode network 39 , in which activity changes are linked to symptom emergence in MDD 40 , PTSD 41 , Parkinson's disease 42 , and substance abuse disorders 43 . Immediate early gene (IEG) markers, such as c-Fos, similarly yield high spatiotemporal resolution for characterizing functional alterations induced by chronic stress.…”

Section: Introductionmentioning

confidence: 99%

Chronic Stress-induced Behaviors Correlate with Exacerbated Acute Stress-induced Cingulate Cortex and Ventral Hippocampus Activation

et al. 2020

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Altered activity of corticolimbic brain regions is a hallmark of stress-related illnesses, including mood disorders, neurodegenerative diseases, and substance abuse disorders. Acute stress adaptively recruits brain region-specific functions for coping, while sustained activation under chronic stress may overwhelm feedback mechanisms and lead to pathological cellular and behavioral responses. The neural mechanisms underlying dysregulated stress response and how they contribute to behavioral deficits are poorly characterized. Here, we tested whether prior exposure to chronic restraint stress (CRS) or unpredictable chronic mild stress (UCMS) in mice could alter neuronal response to acute stress and whether these changes are associated with chronic stress-induced behavioral deficits. More specifically, we assessed neuronal activation indexed by c-Fos+ cell counts in 24 stress-and mood-related brain regions, and determined if changes in acute stress-induced neuronal activation were linked to chronic stress-induced behavioral impairments. Results indicated that CRS and UCMS led to convergent physiological and anxiety-like deficits, whereas cognition was impaired only in UCMS mice. CRS and UCMS exposure exacerbated neuronal activation in response to an acute stressor in anterior cingulate cortex (ACC) area 24b and ventral hippocampal (vHPC) CA1, CA3, and subiculum. In dysregulated brain regions, levels of neuronal activation were positively correlated with principal components capturing variance across widespread behavioral alterations relevant to stress-related disorders. Our data supports an association between a dysregulated stress response, altered corticolimbic excitation/inhibition balance, and the expression of maladaptive behaviors.

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Functional connectivity markers of depression in advanced Parkinson's disease

Abstract: HighlightsPatient-specific 42-ICNs template was created from 156 PD patients’ rs-fMRI data.6 FC markers significantly contributed to depression discrimination in PD.Classifiers achieved the mean accuracy of 82.4% for depression diagnosis in PD.

Cited by 34 publications

References 38 publications

Aberrant functional connectivity and activity in Parkinson’s disease and comorbidity with depression based on radiomic analysis

Aberrant functional connectivity and activity in Parkinson’s disease and comorbidity with depression based on radiomic analysis

Prefrontal Physiomarkers of Anxiety and Depression in Parkinson’s Disease

Chronic Stress-induced Behaviors Correlate with Exacerbated Acute Stress-induced Cingulate Cortex and Ventral Hippocampus Activation

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