Altered Regional Homogeneity in Parkinson's Disease with Depression: A Resting-State fMRI Study

Altered Regional Homogeneity in Parkinson's Disease with Depression: A Resting-State fMRI Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Altered Regional Homogeneity in Parkinson's Disease with Depression: A Resting-State fMRI Study Shihua Liu, Xvdong Zhu, Yan Chen, Chao Zhang, Xiaowei Zhu, Rumeng Zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6957749/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Depression is a prevalent non-motor symptom in Parkinson's disease (PD) with unclear pathogenesis and lacking established biomarkers. This study investigated depression in PD (DPD) using Regional Homogeneity (ReHo) analysis of resting-state functional magnetic resonance imaging (rs-fMRI). We enrolled 23 DPD patients, 24 non-depressed PD (NDPD) patients, and 20 healthy controls (HC). Results demonstrated that DPD patients exhibited increased ReHo in the left inferior temporal gyrus (ITG) and decreased ReHo in the right middle frontal gyrus (MFG), left insula, and left hippocampus compared to NDPD patients. These ReHo alterations significantly correlated with HAMD scores in PD patients. ROC analysis indicated that decreased ReHo in the left insula and left hippocampus demonstrates potential as a neuroimaging biomarker for distinguishing DPD (AUC = 0.8062). Distinct ReHo patterns involving temporal, frontal, and limbic regions may underlie DPD, with left insular and hippocampal changes showing diagnostic biomarker potential. Health sciences/Neurology Health sciences/Neurology/Neurological disorders Health sciences/Neurology/Neurological disorders/Parkinsons disease Depression in Parkinson's disease Resting-state functional MRI Regional homogeneity Neuroimaging Biomarkers Figures Figure 1 Figure 2 Figure 3 Introduction Parkinson's disease (PD) represents the second most common neurodegenerative disorder, characterized clinically by cardinal motor symptoms—bradykinesia, resting tremor, and rigidity—alongside non-motor symptoms (NMS) including sensory disturbances, affective disorders, and sleep disturbances 1 . Crucially, NMS, particularly depression, profoundly impair the quality of life in PD patients. Epidemiological studies indicate that approximately 20%-40% of PD patients exhibit comorbid depressive symptoms, a prevalence significantly higher than that in age-matched healthy populations 2–4 . Nevertheless, only 26% receive targeted treatment, while 20%-60% of cases remain undiagnosed or untreated 3 . Depression in Parkinson's disease (DPD) not only accelerates cognitive decline and motor deterioration but also correlates with increased disability rates and healthcare burdens 4 . However, the pathophysiological mechanisms underlying DPD remain elusive, and clinical diagnosis still relies on subjective scale-based assessments, lacking objective biological markers 5 . This critical gap severely hampers the development of early interventions and precision therapeutic strategies. In recent years, resting-state functional magnetic resonance imaging (rs-fMRI) technology has provided a novel approach for investigating the neural mechanisms underlying DPD 6–8 . Rs-fMRI detects blood-oxygen-level-dependent (BOLD) signals to reflect spontaneous neuronal activity, serving as a method to investigate intrinsic brain function during rest. Unlike task-based fMRI, rs-fMRI requires no specific cognitive tasks, instead recording neural activity while subjects remain awake and calm. This technique has gained increasing traction in PD research 9 . Regional Homogeneity (ReHo), an emerging rs-fMRI analytic approach, quantifies regional voxel-wise synchronization using Kendall’s coefficient of concordance (KCC, or Kendall’s W). This metric evaluates the coherence of spontaneous activity within localized brain areas 10 . ReHo has been extensively applied in neuropsychiatric disorders, including major depressive disorder 11 , schizophrenia 12 , Alzheimer’s disease 13 , epilepsy 14 , and Parkinson’s disease 15,16 . The pathogenesis of DPD remains elusive. Consequently, rs-fMRI-based biomarkers for DPD have become a major research focus in recent years. Previous studies have reported the following findings: widespread weakened connectivity between the temporo-occipital visual cortex and the prefrontal-limbic network in DPD patients 17 ; the degree of reduced functional connectivity within the medial geniculate network correlates with the severity of depression in DPD patients 7 ; cortical gyrification may serve as a potential neuroimaging marker for depression severity in PD patients 18 ; and reduced volumes of the amygdala and hippocampal subfields are associated with the severity of depressive symptoms 19 . However, Whether ReHo alterations in DPD-associated depression exhibit disease-specific patterns remains debated, with existing evidence largely derived from small samples or studies inadequately controlling for motor symptom confounds; The distinctive ReHo signatures in DPD have not been systematically characterized; The correlation between ReHo abnormalities and depression severity in DPD remains poorly elucidated 17,20 . This study aims to employ rs-fMRI using ReHo analysis, in conjunction with strictly matched cohorts of DPD and non-depressed Parkinson's disease (NDPD) patients, to investigate: 1) Whether there exist characteristic brain regions exhibiting altered ReHo in DPD; 2) Whether ReHo values in these differential brain regions correlate with the severity of depression in PD patients; 3) The diagnostic efficacy of ReHo value changes in specific brain regions for DPD. The study aims to provide imaging evidence for the pathophysiological mechanisms underlying DPD and to develop an objective ReHo-based diagnostic biomarker. Materials and methods Participants This study enrolled 23 patients with DPD recruited between January 2023 and December 2024, selecting 24 gender- and age-matched patients with NDPD and 20 healthy controls (HC). All patients with DPD and NDPD had clinically confirmed primary PD, met the 2015 Movement Disorder Society (MDS) clinical diagnostic criteria for PD 1 . Diagnosis of DPD additionally required fulfillment of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) criteria in the context of established PD and a score of ≥ 14 on the 17-item Hamilton Depression Rating Scale (HAMD-17). All diagnoses were established with the participation of at least two neurologists specializing in movement disorders. Inclusion criteria for PD patients: 1) No antidepressants/anxiolytics within 2 months; 2) Stable anti-parkinsonian medication regimen > 28 days; 3) Right-handedness; 4) Ability to complete assessments independently or with caregiver assistance. Exclusion criteria: 1) Parkinson-plus syndromes (e.g., multiple system atrophy, progressive supranuclear palsy, dementia with Lewy bodies) or secondary parkinsonism (e.g., vascular/drug-induced parkinsonism); 2) Severe psychiatric disorders (e.g., schizophrenia); 3) Major systemic diseases (respiratory/cardiovascular/digestive); 4) Severe cognitive impairment precluding cooperation. HC inclusion criteria: 1) Absence of psychiatric/cognitive disorders; 2) No major systemic diseases; 3) Right-handedness; 4) No structural abnormalities on brain MRI. This study was approved by the Ethics Committee of Suzhou Hospital of Anhui Medical University (Approval No. A2023026). Written informed consent was obtained from all participants. Clinical characteristic measurement Demographic and clinical information was collected for all PD patients and control subjects. Motor severity and disease severity were assessed using the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) and the Hoehn & Yahr (H&Y) stage. The severity of depression in PD patients was quantified using HAMD-17. Patients with HAMD-17 scores ≥ 14 points were defined as the DPD group, while those with scores 12-hour withdrawal from oral antiparkinsonian agents. Scanning was performed on a Philips Ingenia 3T MRI system equipped with a standard head coil. Subjects were positioned supine with head immobilization using foam padding. During acquisition, participants were instructed to maintain rest with eyes closed, avoiding intentional cognitive or motor activities. Structural imaging: High-resolution T1-weighted volumes were acquired via 3D T1W-TFE sequence (Parameters: repetition time (TR) = 6.6 ms, echo time (TE) = 3 ms, flip angle (FA) = 12°, number of slices = 170, slice thickness = 1 mm, slice gap = 1 mm, field of view (FOV) = 240 × 240 mm², matrix size = 512 × 512, and voxel size = 0.5 × 0.5 × 1 mm³). Functional imaging: Resting-state fMRI data were obtained using gradient-echo EPI (8-minute duration; Parameters: TR = 2000 ms, TE = 30 ms, FA = 90°, number of slices = 33, slice thickness = 3.5 mm, slice gap = 0.7 mm, FOV = 224 × 224 mm², matrix size = 128 × 128, and voxel size = 1.75 × 1.75 × 4.2 mm³). Data processing and ReHo index calculation Rs-fMRI data were preprocessed using RESTplus v1.27 ( http://www.restfmri.net/forum/restplus ). The preprocessing pipeline comprised: 1) Initial volume removal: Exclusion of the first 10 time points to achieve longitudinal magnetization equilibrium and mitigate scanner acclimatization effects. 2) Slice-timing correction: Temporal realignment for inter-slice acquisition delay compensation. 3) Motion correction: Rigid-body realignment to the first volume, with subjects excluded if exhibiting > 3 mm maximum translation or > 3° rotation. 4) Spatial normalization: Coregistration to T1-weighted structural images, followed by tissue segmentation and nonlinear warping to the Montreal Neurological Institute (MNI) template via deformation fields. 5) Linear detrending: Elimination of signal trends associated with scanner drift artifacts. 6) Nuisance regression: Incorporation of covariates including Friston-24 motion parameters, cerebrospinal fluid (CSF), and white matter signals. 7) Bandpass filtering: Frequency-based noise reduction (0.01–0.08 Hz) to suppress low-frequency drifts and physiological high-frequency noise. ReHo computation was performed as follows: 1) Kendall's Concordance Calculation: The ReHo value for each voxel was derived by computing KCC between its time series and those of its 26 nearest neighboring voxels. For standardization, individual voxel-wise ReHo values were normalized by dividing by the global mean ReHo across the whole brain. 2) Spatial Smoothing: The normalized ReHo maps were smoothed using a Gaussian kernel with a full-width at half-maximum (FWHM) of 4 mm. Statistical Analysis Demographic and clinical data were analyzed using GraphPad Prism v9.0 (GraphPad Software, USA) across DPD, NDPD, and HC groups. Intergroup comparisons were performed as follows: One-way analysis of variance (ANOVA) for continuous variables among three groups; Pearson's chi-square test (χ²) for categorical variables (sex); Continuous variables including age, H &Y stage, UPDRS-III scores, HAMD-17 scores, and levodopa equivalent daily dose (LEDD) were analyzed using independent samples t -test. Neuroimaging analysis: ReHo statistical maps underwent analysis of covariance (ANCOVA) with post-hoc testing in REST 1.8 toolkit. Statistical significance was defined at a voxel-level threshold of P < 0.01 and cluster-level threshold of P < 0.05 (family-wise error corrected). Significant clusters were overlaid onto the standard CH2 template. Automated Anatomical Labeling (AAL) atlas identified anatomical labels of differential brain regions, with Montreal Neurological Institute (MNI) coordinates, cluster size (voxels), and peak t -values recorded. Correlational analysis and statistical validation: Mean ReHo values from significant clusters were extracted for Pearson correlation analysis with HAMD-17 scores in PD patients. Gaussian random field (GRF) theory correction addressed multiple comparisons (voxel P < 0.05, cluster P < 0.05, two-tailed).To evaluate the discriminative power between DPD and NDPD groups, receiver operating characteristic (ROC) curve analysis was employed, with diagnostic accuracy quantified by the area under the curve (AUC). Statistical significance was defined as P < 0.05 (two-tailed). Results Demographic and clinical characteristics No statistically significant differences were observed in gender distribution or age among the DPD, NDPD, and HC groups. The DPD and NDPD groups demonstrated comparable scores on the UPDRS-III, H&Y staging, and LEDD. The DPD group exhibited significantly higher HAMD-17 scores compared to both the NDPD and HC groups (Table 1 ). Table 1 Comparison of Demographic and Clinical Characteristics Across Groups Demographic and clinical data DPD group ( n = 23) NDPD group ( n = 24) HC ( n = 20) F / χ² / t P value Age/year 65.78 ± 9.06 63.67 ± 8.38 62.70 ± 6.57 0.822 a 0.444 Sex,male/female 12/11 12/12 10/10 0.029 b 0.986 UPDRS-III score 35.39 ± 12.04 33.38 ± 10.33 NA 0.704 c 0.485 H &Y stage 2.59 ± 0.96 2.25 ± 0.72 NA 1.354 c 0.183 HAMD-17 scores 28.00 ± 6.69 14.17 ± 3.12 NA 30.83 c <0.001 LEDD, mg/d 532.6 ± 152.9 500.0 ± 153.1 NA 0.730 c 0.469 a one-way ANOVA test , b χ 2 test , c Two independent samples t test ReHo differences in brain regions ANCOVA revealed significant inter-group differences in ReHo primarily localized to the left inferior temporal gyrus (ITG), right middle frontal gyrus (MFG), left insula and left hippocampus (Table 2 ). Post-hoc tests demonstrated that compared with the HC group:The DPD group exhibited significantly increased ReHo in the left ITG, but decreased ReHo in the right MFG, left insula and left hippocampus; the NDPD group showed elevated ReHo in the right precuneus and left ITG, with reduced ReHo in the right MFG, left insula. Furthermore, relative to the NDPD group, the DPD group displayed increased ReHo in the left ITG and decreased ReHo in the right MFG, left insula and left hippocampus (Table 3 ; Fig. 1A, Fig. 1B). Table 2 Brain regions with significant differences in ReHo among the three groups Brain regions(ALL) Cluster size Peak MNI coordinates F value X Y Z Temporal_Inf_L 250 -39 -9 -36 10.0801 Frontal_Mid_R 429 39 54 12 10.4113 Insula_L/Hippocampus_L 262 -39 -12 -3 10.5336 AAL the automated anatomical labeling Table 3 Brain regions with significant differences in ReHo between groups Comparison results and regions(AAL) Cluster size Peak MNI coordinates t value X Y Z DPD>HC Temporal_Inf_L 250 -42 -9 -33 5.7282 DPDHC Precuneus_R 167 -18 -63 36 4.1622 Temporal_Inf_L 186 18 -33 39 3.8351 NDPDNDPD Temporal_Inf_L 148 -39 -18 -45 3.3718 DPD< NDPD Frontal_Mid_R 396 39 54 12 -4.1428 Insula_L/Hippocampus_L 135 -27 -27 -12 -3.2201 AAL the automated anatomical labeling Correlation Analysis Between Altered ReHo Values and HAMD Scores Correlation analysis was performed between the ReHo values of brain regions showing significant differences between the DPD and NDPD groups and their HAMD scores. The results revealed a significant positive correlation between ReHo values in Cluster 1 (Temporal_Inf_L) and HAMD scores (r = 0.4347, P = 0.0023). Conversely, significant negative correlations were observed between ReHo values in Cluster 2 (Frontal_Mid_R) and HAMD scores ( r = -0.5262, P = 0.0001), as well as between ReHo values in Cluster 3 (Insula_L/Hippocampus_L) and HAMD scores (r = -0.4049, P = 0.0048) (Fig. 2). Diagnostic Performance of ReHo Values in Discriminating DPD ROC curve analysis was employed to evaluate the ability of altered ReHo values in the identified differential brain regions to distinguish DPD. The results demonstrated that the AUC for Cluster 1 (Temporal_Inf_L) was 0.7301. The AUC for Cluster 2 (Frontal_Mid_R) was 0.7971. The AUC for Cluster 3 (Insula_L/Hippocampus_L) was 0.8062 (95% CI: 0.683–0.930, P < 0.001). Discussion This study employed rs-fMRI with ReHo analysis to investigate the characteristics of brain functional activity in patients with DPD. The results demonstrated significant ReHo alterations in DPD patients within brain regions including the left ITG, right MFG, left insula, and left hippocampus. These alterations were significantly correlated with the severity of depressive symptoms in DPD. Furthermore, ReHo changes in the left insula and left hippocampus exhibited high discriminative power for diagnosing DPD (AUC = 0.8062), suggesting their potential as neuroimaging biomarkers for DPD. 1. Neural Mechanisms of ReHo Alterations in DPD Patients 1.1 Increased ReHo in the Left ITG and Impaired Emotion Regulation This study revealed a significant increase in ReHo values within the left ITG in DPD patients compared to NDPD. The left ITG, belonging to the higher-order association cortex, is implicated in emotion processing, semantic memory, and social cognition. Hyperactivation within temporal lobe cortices, potentially reflecting aberrantly enhanced processing of negative emotions, is frequently observed in patients with major depressive disorder 21,22 . In PD patients, degeneration of the dopaminergic neurotransmitter system may disrupt functional connectivity within limbic circuits (e.g., the amygdala-temporal lobe circuit), contributing to impaired emotion regulation 23 . Existing research has linked metabolic abnormalities in this region to negative emotional biases in depression 24–26 . The elevated ReHo observed here suggests a heightened processing bias toward negative emotional stimuli in DPD patients. This finding aligns with previous reports of hyperactivation in the posterior default mode network (DMN) in individuals with depressive disorders 8 . Our results support the view that increased ReHo in the left inferior temporal gyrus of DPD patients may represent aberrant neural compensation for depressive symptomatology, analogous to the pattern of temporal lobe hyperactivation observed in primary depression 27 . 1.2 Decreased ReHo in the Right MFG and Impairments in Emotion and Cognitive Control This study demonstrated a significant decrease in ReHo values within the right MFG in DPD patients. As a key component of the dorsolateral prefrontal cortex (DLPFC), the MFG plays a crucial role in emotion regulation and cognitive control 28 . The observed reduction in its functional activity (as indicated by lower ReHo) may reflect an impairment in top-down emotion regulation in DPD patients. This finding aligns with the clinical characteristics of diminished executive control function commonly observed in individuals with depression 29,30 . Depressive symptoms in PD patients are frequently accompanied by "executive dysfunction" and "negative cognitive bias", manifesting as difficulties in suppressing negative thoughts and modulating emotional responses 31 . Our results suggest that the decreased ReHo in the right MFG may reflect functional impairment within the prefrontal-striatal circuit in DPD patients, leading to a diminished capacity to regulate emotional information. This discovery is consistent with previous studies on PD-related depression 32–34 , supporting the view that dysfunction within the prefrontal-limbic system represents one of the core neural mechanisms underlying DPD 7 . 1.3 Reduced ReHo in the Left Insula and Left Hippocampus Related to Emotion-Somatic Integration Impairment Another key finding of this study is the significantly reduced Regional Homogeneity (ReHo) values in the left insula and left hippocampus of patients with depression in Parkinson's disease (DPD). The insula, a critical hub of the Salience Network (SN), is responsible for integrating interoceptive signals (such as emotion, pain, and autonomic responses) and directing attentional resource allocation 7 . In patients with major depressive disorder (MDD), insular dysfunction is closely associated with emotional blunting and somatic symptoms 35 . Altered insular function in PD patients may involve dual dysregulation of the dopaminergic and serotonergic (5-HT) systems. Animal models demonstrate that PD-related substantia nigra degeneration can impact synaptic plasticity within the insula, while reductions in 5-HT neurotransmission may further exacerbate impairments in emotional perception 36 . Our findings support the hypothesis that reduced ReHo in the left insula of DPD patients may reflect impaired emotion-somatic integration function, potentially leading to the exacerbation of depressive symptoms such as anhedonia and fatigue. Notably, the reduced ReHo value in the left hippocampal region likely carries dual pathological significance. On the one hand, as a core structure of the limbic system, hippocampal hypofunction may directly contribute to the formation of depression-related affective disturbances 19 . On the other hand, considering the inherent neurodegenerative nature of PD, abnormalities in this region may simultaneously reflect the superimposed effects of damage to both dopaminergic and non-dopaminergic systems during disease progression 37 . 2. Correlation Between Altered ReHo in Differential Brain Regions and Depression Severity in PD Patients Another significant finding of this study is the significant correlation between ReHo values in these differential brain regions and HAMD scores in PD patients. A significant positive correlation was observed between ReHo values in the left ITG and HAMD scores in PD patients. This suggests that hyper-synchronization in this region may directly contribute to the neuropathological processes underlying depressive symptoms, consistent with previous research findings 38 . Conversely, ReHo values in the right MFG, left insula, and left hippocampus showed significant negative correlations with HAMD scores. This finding further supports the critical role of prefrontal-limbic neural circuitry imbalance in the development and progression of DPD 39 .This distinct pattern of bidirectional neural activity alterations may constitute a characteristic neural signature of DPD. 3. Clinical Significance of Left Insula and Left Hippocampus ReHo as Potential Biomarkers for DPD Currently, the diagnosis of DPD primarily relies on clinical interviews and rating scales (e.g., HAMD), lacking objective biological markers. Through ROC analysis, this study demonstrated that alterations in ReHo within the left insula and left hippocampus possess moderate to high discriminatory power for identifying DPD (AUC > 0.8), suggesting their potential utility as adjunctive diagnostic tools. The abnormal ReHo pattern identified provides a potential neuroimaging biomarker for the early detection of DPD. This finding holds significant clinical value: 1) Improved Diagnostic Accuracy: Depressive symptoms in some PD patients may be obscured by motor manifestations (e.g., hypomimia, bradykinesia), potentially leading to misdiagnosis. Objective measurement of left insula and left hippocampus ReHo could aid in distinguishing DPD from NDPD. 2) Guiding Personalized Treatment: If future research confirms that functional alterations in the insula and hippocampus correlate with the efficacy of specific antidepressants (e.g., SSRIs), ReHo analysis could potentially be used to predict treatment response. In recent years, neuromodulation techniques, such as transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS), have shown promise for treatment-resistant depression 40–42 . This study's finding of key functional abnormalities in the insula and left hippocampus in DPD suggests that targeted neuromodulation of the left insula, hippocampus, or their connected networks may alleviate DPD symptoms. However, this study has several limitations. First, the cross-sectional design precludes the determination of a causal relationship between the observed ReHo alterations and depressive symptoms. Second, limitations include a relatively small sample size, a single-center setting, and reliance on a single neuroimaging metric (ReHo). Future studies employing larger, multi-center cohorts, longitudinal follow-up, and multimodal neuroimaging techniques are warranted to further elucidate the temporal dynamics of these neural activity characteristics during disease progression and their association with the evolution of clinical symptoms. Conclusion This study employed rs-fMRI using the ReHo method and revealed characteristic ReHo alterations in patients with DPD. Functional changes in the left ITG, right MFG, left insula, and left hippocampus may underlie the neural mechanisms of DPD. The neural mechanisms underlying DPD may involve the synergistic impairment of networks responsible for emotional processing, cognitive control, and emotion-somatic integration. Altered ReHo in the left insula and left hippocampus shows promise as a neuroimaging biomarker to aid the clinical diagnosis of DPD and inform treatment decisions. Declarations Data availability The data generated and analyzed during this study are available from the corresponding author upon reasonable request. Funding This study was funded by the Translational Medicine Project of the Science and Technology Department of Anhui Province (Project Number: 202204295107020063). Author contributions Shihua Liu, Xvdong Zhu, Ping Zhong, Yan Chen, Chao Zhang and Xiaowei Zhu participated in study implementation and manuscript drafting/critical revision. Shihua Liu, Xvdong Zhu, Chao Zhang, Rumeng Zhang, Bin Li and Lei Chen contributed to clinical data collection. Shihua Liu, Chao Zhang, and Ping Zhong were involved in study conceptualization and coordination. Bin Li and Shihua Liu performed the image analysis. Shihua Liu, Xvdong Zhu and Xiaowei Zhu performed statistical analysis and participated in critical appraisal of the manuscript. Conflict of interest The authors declare no conflicts of interest. Unsectioned Paragraphs Postuma, R.B. , et al. 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Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYBACPmYGBmYGgwMMDOwNbBChAwS0sMG18BwgVgsDSAtImUQCsVrYeYw/FxTcSeyf+fjZo5ttDHJ8NxIYPxfgdRiPmfQMg2eJM26nmRvntjEYS95IYJaeQUALM4/B4cSG2wlm0kAtiRtuJAAF8Wsx/gzSMv/m8W8gLfXEaDGQBmnZcIMHbEuCAWEtbGUgLcYbz+SUSeeckzCceeZhszQ+Lfz8hzd/5vlzWHbe8ePbpHPKbOT5jicf/IxPCzqQAGLGBhI0jIJRMApGwSjABgBS3kX1abeogwAAAABJRU5ErkJggg==","orcid":"","institution":"Suzhou Hospital of Anhui Medical University","correspondingAuthor":true,"prefix":"","firstName":"Shihua","middleName":"","lastName":"Liu","suffix":""},{"id":492787477,"identity":"215bf9dc-cb17-4d07-868c-e2292fa2a756","order_by":1,"name":"Xvdong Zhu","email":"","orcid":"","institution":"Suzhou Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xvdong","middleName":"","lastName":"Zhu","suffix":""},{"id":492787479,"identity":"495cc5b8-5eca-420a-a42e-71f09fba992f","order_by":2,"name":"Yan Chen","email":"","orcid":"","institution":"Suzhou Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Chen","suffix":""},{"id":492787481,"identity":"ac25aca7-1dc0-4f21-87a6-440341dfc7b4","order_by":3,"name":"Chao Zhang","email":"","orcid":"","institution":"Suzhou Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Zhang","suffix":""},{"id":492787483,"identity":"21eac7f3-8dee-43f6-aae5-4f0f81224e76","order_by":4,"name":"Xiaowei Zhu","email":"","orcid":"","institution":"Suzhou Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaowei","middleName":"","lastName":"Zhu","suffix":""},{"id":492787485,"identity":"3b64d895-54ef-4079-a027-c46bd1bffdfd","order_by":5,"name":"Rumeng Zhang","email":"","orcid":"","institution":"Suzhou Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Rumeng","middleName":"","lastName":"Zhang","suffix":""},{"id":492787487,"identity":"75a764d2-2b60-417f-ac06-dcaacbb5e81c","order_by":6,"name":"Lei Chen","email":"","orcid":"","institution":"Suzhou Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Chen","suffix":""},{"id":492787490,"identity":"e63ffeab-b25b-40d8-a566-01440cf9c4a2","order_by":7,"name":"Bin Li","email":"","orcid":"","institution":"Suzhou Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Li","suffix":""},{"id":492787493,"identity":"fb7c7b38-fc5d-4113-b938-8d480d224900","order_by":8,"name":"Ping Zhong","email":"","orcid":"","institution":"Suzhou Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Zhong","suffix":""}],"badges":[],"createdAt":"2025-06-23 14:23:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6957749/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6957749/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88035088,"identity":"52b69710-0759-4209-bcea-5a139c85e7a9","added_by":"auto","created_at":"2025-07-31 16:11:08","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1613610,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6957749/v1/194d9b6829ecde0420f8bae0.jpeg"},{"id":88035107,"identity":"76d54e40-ac32-4efe-865c-51ffd40c81ab","added_by":"auto","created_at":"2025-07-31 16:11:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1654861,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6957749/v1/3d3a4469c04f7b96078417c1.png"},{"id":88035106,"identity":"fc68923b-283c-4c49-8e61-ff19eadb3b6f","added_by":"auto","created_at":"2025-07-31 16:11:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":199666,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6957749/v1/d6e12af95f56d849cc5363fd.png"},{"id":90932722,"identity":"1a62bd13-6ad5-4b44-9aec-befbafe9b59c","added_by":"auto","created_at":"2025-09-09 16:31:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4567479,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6957749/v1/92a4006b-35b4-44c8-8700-9edaa7956804.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Altered Regional Homogeneity in Parkinson's Disease with Depression: A Resting-State fMRI Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eParkinson's disease (PD) represents the second most common neurodegenerative disorder, characterized clinically by cardinal motor symptoms\u0026mdash;bradykinesia, resting tremor, and rigidity\u0026mdash;alongside non-motor symptoms (NMS) including sensory disturbances, affective disorders, and sleep disturbances \u003csup\u003e1\u003c/sup\u003e. Crucially, NMS, particularly depression, profoundly impair the quality of life in PD patients. Epidemiological studies indicate that approximately 20%-40% of PD patients exhibit comorbid depressive symptoms, a prevalence significantly higher than that in age-matched healthy populations \u003csup\u003e2\u0026ndash;4\u003c/sup\u003e. Nevertheless, only 26% receive targeted treatment, while 20%-60% of cases remain undiagnosed or untreated\u003csup\u003e3\u003c/sup\u003e. Depression in Parkinson's disease (DPD) not only accelerates cognitive decline and motor deterioration but also correlates with increased disability rates and healthcare burdens\u003csup\u003e4\u003c/sup\u003e. However, the pathophysiological mechanisms underlying DPD remain elusive, and clinical diagnosis still relies on subjective scale-based assessments, lacking objective biological markers \u003csup\u003e5\u003c/sup\u003e. This critical gap severely hampers the development of early interventions and precision therapeutic strategies.\u003c/p\u003e\u003cp\u003eIn recent years, resting-state functional magnetic resonance imaging (rs-fMRI) technology has provided a novel approach for investigating the neural mechanisms underlying DPD \u003csup\u003e6\u0026ndash;8\u003c/sup\u003e. Rs-fMRI detects blood-oxygen-level-dependent (BOLD) signals to reflect spontaneous neuronal activity, serving as a method to investigate intrinsic brain function during rest. Unlike task-based fMRI, rs-fMRI requires no specific cognitive tasks, instead recording neural activity while subjects remain awake and calm. This technique has gained increasing traction in PD research \u003csup\u003e9\u003c/sup\u003e. Regional Homogeneity (ReHo), an emerging rs-fMRI analytic approach, quantifies regional voxel-wise synchronization using Kendall\u0026rsquo;s coefficient of concordance (KCC, or Kendall\u0026rsquo;s W). This metric evaluates the coherence of spontaneous activity within localized brain areas\u003csup\u003e10\u003c/sup\u003e. ReHo has been extensively applied in neuropsychiatric disorders, including major depressive disorder\u003csup\u003e11\u003c/sup\u003e, schizophrenia\u003csup\u003e12\u003c/sup\u003e, Alzheimer\u0026rsquo;s disease\u003csup\u003e13\u003c/sup\u003e, epilepsy\u003csup\u003e14\u003c/sup\u003e, and Parkinson\u0026rsquo;s disease\u003csup\u003e15,16\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe pathogenesis of DPD remains elusive. Consequently, rs-fMRI-based biomarkers for DPD have become a major research focus in recent years. Previous studies have reported the following findings: widespread weakened connectivity between the temporo-occipital visual cortex and the prefrontal-limbic network in DPD patients\u003csup\u003e17\u003c/sup\u003e; the degree of reduced functional connectivity within the medial geniculate network correlates with the severity of depression in DPD patients\u003csup\u003e7\u003c/sup\u003e; cortical gyrification may serve as a potential neuroimaging marker for depression severity in PD patients\u003csup\u003e18\u003c/sup\u003e; and reduced volumes of the amygdala and hippocampal subfields are associated with the severity of depressive symptoms\u003csup\u003e19\u003c/sup\u003e. However, Whether ReHo alterations in DPD-associated depression exhibit disease-specific patterns remains debated, with existing evidence largely derived from small samples or studies inadequately controlling for motor symptom confounds; The distinctive ReHo signatures in DPD have not been systematically characterized; The correlation between ReHo abnormalities and depression severity in DPD remains poorly elucidated\u003csup\u003e17,20\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study aims to employ rs-fMRI using ReHo analysis, in conjunction with strictly matched cohorts of DPD and non-depressed Parkinson's disease (NDPD) patients, to investigate: 1) Whether there exist characteristic brain regions exhibiting altered ReHo in DPD; 2) Whether ReHo values in these differential brain regions correlate with the severity of depression in PD patients; 3) The diagnostic efficacy of ReHo value changes in specific brain regions for DPD. The study aims to provide imaging evidence for the pathophysiological mechanisms underlying DPD and to develop an objective ReHo-based diagnostic biomarker.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eThis study enrolled 23 patients with DPD recruited between January 2023 and December 2024, selecting 24 gender- and age-matched patients with NDPD and 20 healthy controls (HC). All patients with DPD and NDPD had clinically confirmed primary PD, met the 2015 Movement Disorder Society (MDS) clinical diagnostic criteria for PD \u003csup\u003e1\u003c/sup\u003e. Diagnosis of DPD additionally required fulfillment of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) criteria in the context of established PD and a score of \u0026ge;\u0026thinsp;14 on the 17-item Hamilton Depression Rating Scale (HAMD-17). All diagnoses were established with the participation of at least two neurologists specializing in movement disorders.\u003c/p\u003e\u003cp\u003eInclusion criteria for PD patients: 1) No antidepressants/anxiolytics within 2 months; 2) Stable anti-parkinsonian medication regimen\u0026thinsp;\u0026gt;\u0026thinsp;28 days; 3) Right-handedness; 4) Ability to complete assessments independently or with caregiver assistance. Exclusion criteria: 1) Parkinson-plus syndromes (e.g., multiple system atrophy, progressive supranuclear palsy, dementia with Lewy bodies) or secondary parkinsonism (e.g., vascular/drug-induced parkinsonism); 2) Severe psychiatric disorders (e.g., schizophrenia); 3) Major systemic diseases (respiratory/cardiovascular/digestive); 4) Severe cognitive impairment precluding cooperation. HC inclusion criteria: 1) Absence of psychiatric/cognitive disorders; 2) No major systemic diseases; 3) Right-handedness; 4) No structural abnormalities on brain MRI.\u003c/p\u003e\u003cp\u003e This study was approved by the Ethics Committee of Suzhou Hospital of Anhui Medical University (Approval No. A2023026). Written informed consent was obtained from all participants.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eClinical characteristic measurement\u003c/h3\u003e\n\u003cp\u003eDemographic and clinical information was collected for all PD patients and control subjects. Motor severity and disease severity were assessed using the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) and the Hoehn \u0026amp; Yahr (H\u0026amp;Y) stage. The severity of depression in PD patients was quantified using HAMD-17. Patients with HAMD-17 scores\u0026thinsp;\u0026ge;\u0026thinsp;14 points were defined as the DPD group, while those with scores\u0026thinsp;\u0026lt;\u0026thinsp;14 points were defined as the NDPD group.\u003c/p\u003e\n\u003ch3\u003eImage data acquisition\u003c/h3\u003e\n\u003cp\u003ePrior to neuroimaging, all participants underwent a\u0026thinsp;\u0026gt;\u0026thinsp;12-hour withdrawal from oral antiparkinsonian agents. Scanning was performed on a Philips Ingenia 3T MRI system equipped with a standard head coil. Subjects were positioned supine with head immobilization using foam padding. During acquisition, participants were instructed to maintain rest with eyes closed, avoiding intentional cognitive or motor activities. Structural imaging: High-resolution T1-weighted volumes were acquired via 3D T1W-TFE sequence (Parameters: repetition time (TR)\u0026thinsp;=\u0026thinsp;6.6 ms, echo time (TE)\u0026thinsp;=\u0026thinsp;3 ms, flip angle (FA)\u0026thinsp;=\u0026thinsp;12\u0026deg;, number of slices\u0026thinsp;=\u0026thinsp;170, slice thickness\u0026thinsp;=\u0026thinsp;1 mm, slice gap\u0026thinsp;=\u0026thinsp;1 mm, field of view (FOV)\u0026thinsp;=\u0026thinsp;240 \u0026times; 240 mm\u0026sup2;, matrix size\u0026thinsp;=\u0026thinsp;512 \u0026times; 512, and voxel size\u0026thinsp;=\u0026thinsp;0.5 \u0026times; 0.5 \u0026times; 1 mm\u0026sup3;). Functional imaging: Resting-state fMRI data were obtained using gradient-echo EPI (8-minute duration; Parameters: TR\u0026thinsp;=\u0026thinsp;2000 ms, TE\u0026thinsp;=\u0026thinsp;30 ms, FA\u0026thinsp;=\u0026thinsp;90\u0026deg;, number of slices\u0026thinsp;=\u0026thinsp;33, slice thickness\u0026thinsp;=\u0026thinsp;3.5 mm, slice gap\u0026thinsp;=\u0026thinsp;0.7 mm, FOV\u0026thinsp;=\u0026thinsp;224 \u0026times; 224 mm\u0026sup2;, matrix size\u0026thinsp;=\u0026thinsp;128 \u0026times; 128, and voxel size\u0026thinsp;=\u0026thinsp;1.75 \u0026times; 1.75 \u0026times; 4.2 mm\u0026sup3;).\u003c/p\u003e\n\u003ch3\u003eData processing and ReHo index calculation\u003c/h3\u003e\n\u003cp\u003eRs-fMRI data were preprocessed using RESTplus v1.27 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.restfmri.net/forum/restplus\u003c/span\u003e\u003cspan address=\"http://www.restfmri.net/forum/restplus\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The preprocessing pipeline comprised: 1) Initial volume removal: Exclusion of the first 10 time points to achieve longitudinal magnetization equilibrium and mitigate scanner acclimatization effects. 2) Slice-timing correction: Temporal realignment for inter-slice acquisition delay compensation. 3) Motion correction: Rigid-body realignment to the first volume, with subjects excluded if exhibiting\u0026thinsp;\u0026gt;\u0026thinsp;3 mm maximum translation or \u0026gt;\u0026thinsp;3\u0026deg; rotation. 4) Spatial normalization: Coregistration to T1-weighted structural images, followed by tissue segmentation and nonlinear warping to the Montreal Neurological Institute (MNI) template via deformation fields. 5) Linear detrending: Elimination of signal trends associated with scanner drift artifacts. 6) Nuisance regression: Incorporation of covariates including Friston-24 motion parameters, cerebrospinal fluid (CSF), and white matter signals. 7) Bandpass filtering: Frequency-based noise reduction (0.01\u0026ndash;0.08 Hz) to suppress low-frequency drifts and physiological high-frequency noise.\u003c/p\u003e\u003cp\u003eReHo computation was performed as follows: 1) Kendall's Concordance Calculation: The ReHo value for each voxel was derived by computing KCC between its time series and those of its 26 nearest neighboring voxels. For standardization, individual voxel-wise ReHo values were normalized by dividing by the global mean ReHo across the whole brain. 2) Spatial Smoothing: The normalized ReHo maps were smoothed using a Gaussian kernel with a full-width at half-maximum (FWHM) of 4 mm.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eDemographic and clinical data were analyzed using GraphPad Prism v9.0 (GraphPad Software, USA) across DPD, NDPD, and HC groups. Intergroup comparisons were performed as follows: One-way analysis of variance (ANOVA) for continuous variables among three groups; Pearson's chi-square test (χ\u0026sup2;) for categorical variables (sex); Continuous variables including age, H \u0026amp;Y stage, UPDRS-III scores, HAMD-17 scores, and levodopa equivalent daily dose (LEDD) were analyzed using independent samples \u003cem\u003et\u003c/em\u003e-test.\u003c/p\u003e\u003cp\u003eNeuroimaging analysis: ReHo statistical maps underwent analysis of covariance (ANCOVA) with post-hoc testing in REST 1.8 toolkit. Statistical significance was defined at a voxel-level threshold of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and cluster-level threshold of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (family-wise error corrected). Significant clusters were overlaid onto the standard CH2 template. Automated Anatomical Labeling (AAL) atlas identified anatomical labels of differential brain regions, with Montreal Neurological Institute (MNI) coordinates, cluster size (voxels), and peak \u003cem\u003et\u003c/em\u003e-values recorded.\u003c/p\u003e\u003cp\u003eCorrelational analysis and statistical validation: Mean ReHo values from significant clusters were extracted for Pearson correlation analysis with HAMD-17 scores in PD patients. Gaussian random field (GRF) theory correction addressed multiple comparisons (voxel \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, cluster \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, two-tailed).To evaluate the discriminative power between DPD and NDPD groups, receiver operating characteristic (ROC) curve analysis was employed, with diagnostic accuracy quantified by the area under the curve (AUC). Statistical significance was defined as \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-tailed).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eDemographic and clinical characteristics\u003c/h2\u003e\u003cp\u003eNo statistically significant differences were observed in gender distribution or age among the DPD, NDPD, and HC groups. The DPD and NDPD groups demonstrated comparable scores on the UPDRS-III, H\u0026amp;Y staging, and LEDD. The DPD group exhibited significantly higher HAMD-17 scores compared to both the NDPD and HC groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Demographic and Clinical Characteristics Across Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic and\u003c/p\u003e\u003cp\u003eclinical data\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDPD group\u003c/p\u003e\u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;23)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNDPD group\u003c/p\u003e\u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHC\u003c/p\u003e\u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e/\u003cem\u003eχ\u0026sup2;\u003c/em\u003e/\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge/year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65.78\u0026thinsp;\u0026plusmn;\u0026thinsp;9.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63.67\u0026thinsp;\u0026plusmn;\u0026thinsp;8.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.70\u0026thinsp;\u0026plusmn;\u0026thinsp;6.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.822\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex,male/female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12/11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12/12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10/10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.029\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.986\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUPDRS-III score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.39\u0026thinsp;\u0026plusmn;\u0026thinsp;12.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.38\u0026thinsp;\u0026plusmn;\u0026thinsp;10.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.704\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.485\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eH \u0026amp;Y stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.354\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.183\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHAMD-17 scores\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.00\u0026thinsp;\u0026plusmn;\u0026thinsp;6.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.17\u0026thinsp;\u0026plusmn;\u0026thinsp;3.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.83\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLEDD, mg/d\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e532.6\u0026thinsp;\u0026plusmn;\u0026thinsp;152.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e500.0\u0026thinsp;\u0026plusmn;\u0026thinsp;153.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.730\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.469\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003eone-way ANOVA test ,\u003csup\u003eb\u003c/sup\u003eχ\u003csup\u003e2\u003c/sup\u003e test ,\u003csup\u003ec\u003c/sup\u003eTwo independent samples \u003cem\u003et\u003c/em\u003e test\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eReHo differences in brain regions\u003c/h3\u003e\n\u003cp\u003eANCOVA revealed significant inter-group differences in ReHo primarily localized to the left inferior temporal gyrus (ITG), right middle frontal gyrus (MFG), left insula and left hippocampus (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Post-hoc tests demonstrated that compared with the HC group:The DPD group exhibited significantly increased ReHo in the left ITG, but decreased ReHo in the right MFG, left insula and left hippocampus; the NDPD group showed elevated ReHo in the right precuneus and left ITG, with reduced ReHo in the right MFG, left insula. Furthermore, relative to the NDPD group, the DPD group displayed increased ReHo in the left ITG and decreased ReHo in the right MFG, left insula and left hippocampus (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Fig.\u0026nbsp;1A, Fig.\u0026nbsp;1B).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBrain regions with significant differences in ReHo among the three groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eBrain regions(ALL)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCluster\u003c/p\u003e\u003cp\u003esize\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003ePeak MNI coordinates\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eX\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eY\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemporal_Inf_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.0801\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrontal_Mid_R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.4113\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsula_L/Hippocampus_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.5336\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eAAL the automated anatomical labeling\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBrain regions with significant differences in ReHo between groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eComparison results and regions(AAL)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCluster\u003c/p\u003e\u003cp\u003esize\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003ePeak MNI coordinates\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003et\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eX\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eY\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDPD\u0026gt;HC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemporal_Inf_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.7282\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDPD\u0026lt;HC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrontal_Mid_R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e401\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-4.4273\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsula_L/Hippocampus_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-4.9027\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNDPD\u0026gt;HC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrecuneus_R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e167\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.1622\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemporal_Inf_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.8351\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNDPD\u0026lt;HC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrontal_Mid_R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-4.3867\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsula_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-4.5374\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDPD\u0026gt;NDPD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemporal_Inf_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.3718\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDPD\u0026lt; NDPD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrontal_Mid_R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e396\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-4.1428\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsula_L/Hippocampus_L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-3.2201\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eAAL the automated anatomical labeling\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eCorrelation Analysis Between Altered ReHo Values and HAMD Scores\u003c/h2\u003e\u003cp\u003eCorrelation analysis was performed between the ReHo values of brain regions showing significant differences between the DPD and NDPD groups and their HAMD scores. The results revealed a significant positive correlation between ReHo values in Cluster 1 (Temporal_Inf_L) and HAMD scores (r\u0026thinsp;=\u0026thinsp;0.4347, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0023). Conversely, significant negative correlations were observed between ReHo values in Cluster 2 (Frontal_Mid_R) and HAMD scores (\u003cem\u003er\u003c/em\u003e = -0.5262, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001), as well as between ReHo values in Cluster 3 (Insula_L/Hippocampus_L) and HAMD scores (r = -0.4049, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0048) (Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eDiagnostic Performance of ReHo Values in Discriminating DPD\u003c/h2\u003e\u003cp\u003eROC curve analysis was employed to evaluate the ability of altered ReHo values in the identified differential brain regions to distinguish DPD. The results demonstrated that the AUC for Cluster 1 (Temporal_Inf_L) was 0.7301. The AUC for Cluster 2 (Frontal_Mid_R) was 0.7971. The AUC for Cluster 3 (Insula_L/Hippocampus_L) was 0.8062 (95% CI: 0.683\u0026ndash;0.930, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study employed rs-fMRI with ReHo analysis to investigate the characteristics of brain functional activity in patients with DPD. The results demonstrated significant ReHo alterations in DPD patients within brain regions including the left ITG, right MFG, left insula, and left hippocampus. These alterations were significantly correlated with the severity of depressive symptoms in DPD. Furthermore, ReHo changes in the left insula and left hippocampus exhibited high discriminative power for diagnosing DPD (AUC\u0026thinsp;=\u0026thinsp;0.8062), suggesting their potential as neuroimaging biomarkers for DPD.\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e1. Neural Mechanisms of ReHo Alterations in DPD Patients\u003c/h2\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e1.1 Increased ReHo in the Left ITG and Impaired Emotion Regulation\u003c/h2\u003e\u003cp\u003eThis study revealed a significant increase in ReHo values within the left ITG in DPD patients compared to NDPD. The left ITG, belonging to the higher-order association cortex, is implicated in emotion processing, semantic memory, and social cognition. Hyperactivation within temporal lobe cortices, potentially reflecting aberrantly enhanced processing of negative emotions, is frequently observed in patients with major depressive disorder \u003csup\u003e21,22\u003c/sup\u003e. In PD patients, degeneration of the dopaminergic neurotransmitter system may disrupt functional connectivity within limbic circuits (e.g., the amygdala-temporal lobe circuit), contributing to impaired emotion regulation \u003csup\u003e23\u003c/sup\u003e. Existing research has linked metabolic abnormalities in this region to negative emotional biases in depression \u003csup\u003e24\u0026ndash;26\u003c/sup\u003e. The elevated ReHo observed here suggests a heightened processing bias toward negative emotional stimuli in DPD patients. This finding aligns with previous reports of hyperactivation in the posterior default mode network (DMN) in individuals with depressive disorders \u003csup\u003e8\u003c/sup\u003e. Our results support the view that increased ReHo in the left inferior temporal gyrus of DPD patients may represent aberrant neural compensation for depressive symptomatology, analogous to the pattern of temporal lobe hyperactivation observed in primary depression \u003csup\u003e27\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e1.2 Decreased ReHo in the Right MFG and Impairments in Emotion and Cognitive Control\u003c/h2\u003e\u003cp\u003eThis study demonstrated a significant decrease in ReHo values within the right MFG in DPD patients. As a key component of the dorsolateral prefrontal cortex (DLPFC), the MFG plays a crucial role in emotion regulation and cognitive control \u003csup\u003e28\u003c/sup\u003e. The observed reduction in its functional activity (as indicated by lower ReHo) may reflect an impairment in top-down emotion regulation in DPD patients. This finding aligns with the clinical characteristics of diminished executive control function commonly observed in individuals with depression \u003csup\u003e29,30\u003c/sup\u003e. Depressive symptoms in PD patients are frequently accompanied by \"executive dysfunction\" and \"negative cognitive bias\", manifesting as difficulties in suppressing negative thoughts and modulating emotional responses \u003csup\u003e31\u003c/sup\u003e. Our results suggest that the decreased ReHo in the right MFG may reflect functional impairment within the prefrontal-striatal circuit in DPD patients, leading to a diminished capacity to regulate emotional information. This discovery is consistent with previous studies on PD-related depression \u003csup\u003e32\u0026ndash;34\u003c/sup\u003e, supporting the view that dysfunction within the prefrontal-limbic system represents one of the core neural mechanisms underlying DPD \u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e1.3 Reduced ReHo in the Left Insula and Left Hippocampus Related to Emotion-Somatic Integration Impairment\u003c/h2\u003e\u003cp\u003eAnother key finding of this study is the significantly reduced Regional Homogeneity (ReHo) values in the left insula and left hippocampus of patients with depression in Parkinson's disease (DPD). The insula, a critical hub of the Salience Network (SN), is responsible for integrating interoceptive signals (such as emotion, pain, and autonomic responses) and directing attentional resource allocation\u003csup\u003e7\u003c/sup\u003e. In patients with major depressive disorder (MDD), insular dysfunction is closely associated with emotional blunting and somatic symptoms\u003csup\u003e35\u003c/sup\u003e. Altered insular function in PD patients may involve dual dysregulation of the dopaminergic and serotonergic (5-HT) systems. Animal models demonstrate that PD-related substantia nigra degeneration can impact synaptic plasticity within the insula, while reductions in 5-HT neurotransmission may further exacerbate impairments in emotional perception \u003csup\u003e36\u003c/sup\u003e. Our findings support the hypothesis that reduced ReHo in the left insula of DPD patients may reflect impaired emotion-somatic integration function, potentially leading to the exacerbation of depressive symptoms such as anhedonia and fatigue. Notably, the reduced ReHo value in the left hippocampal region likely carries dual pathological significance. On the one hand, as a core structure of the limbic system, hippocampal hypofunction may directly contribute to the formation of depression-related affective disturbances\u003csup\u003e19\u003c/sup\u003e. On the other hand, considering the inherent neurodegenerative nature of PD, abnormalities in this region may simultaneously reflect the superimposed effects of damage to both dopaminergic and non-dopaminergic systems during disease progression\u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e2. Correlation Between Altered ReHo in Differential Brain Regions and Depression Severity in PD Patients\u003c/h2\u003e\u003cp\u003eAnother significant finding of this study is the significant correlation between ReHo values in these differential brain regions and HAMD scores in PD patients. A significant positive correlation was observed between ReHo values in the left ITG and HAMD scores in PD patients. This suggests that hyper-synchronization in this region may directly contribute to the neuropathological processes underlying depressive symptoms, consistent with previous research findings \u003csup\u003e38\u003c/sup\u003e. Conversely, ReHo values in the right MFG, left insula, and left hippocampus showed significant negative correlations with HAMD scores. This finding further supports the critical role of prefrontal-limbic neural circuitry imbalance in the development and progression of DPD \u003csup\u003e39\u003c/sup\u003e.This distinct pattern of bidirectional neural activity alterations may constitute a characteristic neural signature of DPD.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3. Clinical Significance of Left Insula and Left Hippocampus ReHo as Potential Biomarkers for DPD\u003c/h2\u003e\u003cp\u003eCurrently, the diagnosis of DPD primarily relies on clinical interviews and rating scales (e.g., HAMD), lacking objective biological markers. Through ROC analysis, this study demonstrated that alterations in ReHo within the left insula and left hippocampus possess moderate to high discriminatory power for identifying DPD (AUC\u0026thinsp;\u0026gt;\u0026thinsp;0.8), suggesting their potential utility as adjunctive diagnostic tools. The abnormal ReHo pattern identified provides a potential neuroimaging biomarker for the early detection of DPD. This finding holds significant clinical value: 1) Improved Diagnostic Accuracy: Depressive symptoms in some PD patients may be obscured by motor manifestations (e.g., hypomimia, bradykinesia), potentially leading to misdiagnosis. Objective measurement of left insula and left hippocampus ReHo could aid in distinguishing DPD from NDPD. 2) Guiding Personalized Treatment: If future research confirms that functional alterations in the insula and hippocampus correlate with the efficacy of specific antidepressants (e.g., SSRIs), ReHo analysis could potentially be used to predict treatment response.\u003c/p\u003e\u003cp\u003eIn recent years, neuromodulation techniques, such as transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS), have shown promise for treatment-resistant depression \u003csup\u003e40\u0026ndash;42\u003c/sup\u003e. This study's finding of key functional abnormalities in the insula and left hippocampus in DPD suggests that targeted neuromodulation of the left insula, hippocampus, or their connected networks may alleviate DPD symptoms.\u003c/p\u003e\u003cp\u003eHowever, this study has several limitations. First, the cross-sectional design precludes the determination of a causal relationship between the observed ReHo alterations and depressive symptoms. Second, limitations include a relatively small sample size, a single-center setting, and reliance on a single neuroimaging metric (ReHo). Future studies employing larger, multi-center cohorts, longitudinal follow-up, and multimodal neuroimaging techniques are warranted to further elucidate the temporal dynamics of these neural activity characteristics during disease progression and their association with the evolution of clinical symptoms.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study employed rs-fMRI using the ReHo method and revealed characteristic ReHo alterations in patients with DPD. Functional changes in the left ITG, right MFG, left insula, and left hippocampus may underlie the neural mechanisms of DPD. The neural mechanisms underlying DPD may involve the synergistic impairment of networks responsible for emotional processing, cognitive control, and emotion-somatic integration. Altered ReHo in the left insula and left hippocampus shows promise as a neuroimaging biomarker to aid the clinical diagnosis of DPD and inform treatment decisions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data generated and analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Translational Medicine Project of the Science and Technology Department of Anhui Province (Project Number: 202204295107020063).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShihua Liu, Xvdong Zhu, Ping Zhong, Yan Chen, Chao Zhang and Xiaowei Zhu participated in study implementation and manuscript drafting/critical revision. Shihua Liu, Xvdong Zhu, Chao Zhang, Rumeng Zhang, Bin Li and Lei Chen contributed to clinical data collection. Shihua Liu, Chao Zhang, and Ping Zhong were involved in study conceptualization and coordination. Bin Li and Shihua Liu performed the image analysis. Shihua Liu, Xvdong Zhu and Xiaowei Zhu performed statistical analysis and participated in critical appraisal of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"Unsectioned Paragraphs","content":"\u003col\u003e\n\u003cli\u003ePostuma, R.B.\u003cem\u003e, et al.\u003c/em\u003e MDS clinical diagnostic criteria for Parkinson\u0026apos;s disease. \u003cem\u003eMovement disorders : official journal of the Movement Disorder Society\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, 1591-1601 (2015).\u003c/li\u003e\n\u003cli\u003eLubomski, M., Davis, R.L. \u0026amp; Sue, C.M. 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This study investigated depression in PD (DPD) using Regional Homogeneity (ReHo) analysis of resting-state functional magnetic resonance imaging (rs-fMRI). We enrolled 23 DPD patients, 24 non-depressed PD (NDPD) patients, and 20 healthy controls (HC). Results demonstrated that DPD patients exhibited increased ReHo in the left inferior temporal gyrus (ITG) and decreased ReHo in the right middle frontal gyrus (MFG), left insula, and left hippocampus compared to NDPD patients. These ReHo alterations significantly correlated with HAMD scores in PD patients. ROC analysis indicated that decreased ReHo in the left insula and left hippocampus demonstrates potential as a neuroimaging biomarker for distinguishing DPD (AUC\u0026thinsp;=\u0026thinsp;0.8062). Distinct ReHo patterns involving temporal, frontal, and limbic regions may underlie DPD, with left insular and hippocampal changes showing diagnostic biomarker potential.\u003c/p\u003e","manuscriptTitle":"Altered Regional Homogeneity in Parkinson's Disease with Depression: A Resting-State fMRI Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-31 16:11:03","doi":"10.21203/rs.3.rs-6957749/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d4e8abd-fb01-4d12-9c79-63585ad3248b","owner":[],"postedDate":"July 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52327869,"name":"Health sciences/Neurology"},{"id":52327870,"name":"Health sciences/Neurology/Neurological disorders"},{"id":52327871,"name":"Health sciences/Neurology/Neurological disorders/Parkinsons disease"}],"tags":[],"updatedAt":"2025-09-09T16:23:42+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-31 16:11:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6957749","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6957749","identity":"rs-6957749","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}