Disruption of Locus Coeruleus Related Functional Networks in Parkinson’s Disease

doi:10.21203/rs.3.rs-2216946/v1

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Disruption of Locus Coeruleus Related Functional Networks in Parkinson’s Disease

https://doi.org/10.21203/rs.3.rs-2216946/v1

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Locus coeruleus (LC) is severely affected in Parkinson’s Disease (PD). However, the alterations of LC-related resting-state networks (RSNs) in PD remain unclear. We used resting-state functional MRI to investigate the alterations of functional connectivity (FC) of LC-related RSNs and the associations between RSNs changes and clinical features in idiopathic rapid eye movement sleep behavior disorder (iRBD), and PD patients with (PD^RBD+) and without RBD (PD^RBD−). There was a similarly disrupted FC pattern of LC-related RSNs in iRBD and PD^RBD+ patients, while the LC-related RSNs were less damaged in PD^RBD− patients compared with iRBD and PD^RBD+ patients. The FC of LC-related RSNs correlated with cognition and duration in iRBD, with depression in PD^RBD−, and with cognition and severity of RBD in PD^RBD+ patients. Our findings demonstrate that LC-related RSNs are significantly disrupted in the prodromal stage of α-synucleinopathies and proposed body-first PD (PD^RBD+), but are less affected in brain-first PD (PD^RBD−).

Biological sciences/Neuroscience/Diseases of the nervous system

Biological sciences/Neuroscience/Diseases of the nervous system/Parkinson's disease

Parkinson’s disease (PD) is one of the prevalent α-synucleinopathies¹. Progressive loss of dopaminergic neurons in the substantia nigra (SN) and the appearance of intraneuronal α-synuclein inclusions (Lewy body) are recognized as the pathological hallmarks of PD^1,2. In addition, there are also 21–94% loss of locus coeruleus (LC) neurons in PD patients^3,4. Based on the Braak staging⁵, Lewy pathology in LC precedes SN and even appears in the prodromal stage of PD⁶. Growing evidence suggests that impaired LC contributes to multiple clinical symptoms of PD, like depression, cognition, and especially rapid eye movement sleep behavior disorder (RBD)^7,8.

Recently, a dual-hit hypothesis of the origin of PD pathology (body-first vs. brain-first) has been proposed^9–11. According to this hypothesis, in the body-first PD, the initial Lewy pathology originates in the peripheral enterovagal system with subsequent caudorostral propagation to the central nervous system (e.g. LC, SN, and cerebral cortex), while the initial Lewy pathology of brain-first PD emerges in the central nervous system, and propagates gradually to SN and LC. It has been suggested that body-first PD patients tend to be RBD positive (PD^RBD+), whereas brain-first PD patients are more likely to be RBD negative (PD^RBD−)¹¹.

As up to 94% of idiopathic RBD (iRBD) patients have Lewy pathology¹², and eventually develop into synucleinopathies^13,14, mostly PD, iRBD is considered an ideal cohort for researching the prodromal stage of PD¹⁵. Moreover, a similar impairment of LC has been detected by neuromelanin-sensitive MRI in iRBD¹⁶ and PD^RBD+ patients^17–19. In contrast, the LC is less affected in PD^RBD− patients compared to PD^RBD+ patients¹⁷. While these findings indicate that LC is already damaged in the prodromal stage of PD, and is differently affected in the body-first and brain-first PD, the alterations of LC-related functional networks in the prodromal stage and different phenotypes of PD remain unclear. LC sends efferent noradrenergic fibers projected to the limbic system, midbrain, thalamus, basal forebrain, and neocortex²⁰. Dysregulation of noradrenergic circuits has been related to various neurological and neuropsychiatric conditions, such as depression and cognitive impairment^21,22. Loss of noradrenergic nerve terminals originating in the LC has been detected in multiple brain regions in PD patients with ¹¹C-MeNER PET^18,19. Thus, we defined LC-related resting-state networks (RSNs) on the whole-brain scale, including the default mode (DMN), executive control (ECN), salience (SAL), sensorimotor (SMN), and visual networks (VIS). The investigation of LC-related RSNs will be helpful in understanding the neural mechanisms in PD.

Resting-state functional MRI (rs-fMRI) provides a powerful method to investigate the functional connectivity (FC) of neural networks in different disease states²³. Therefore, this study used rs-fMRI to investigate the alterations of LC-related RSNs in iRBD, PD^RBD− and PD^RBD+ patients. We hypothesized that the LC-related RSNs are functionally damaged in iRBD patients, and further deteriorated in PD^RBD+ patients (body-first PD), but are less impaired in PD^RBD− patients (brain-first PD). Our findings will help to understand the role of LC in pathogenesis of PD.

Demographic and clinical assessments

Fifty-three iRBD, 64 PD^RBD−, 58 PD^RBD+ patients and 69 healthy controls (HCs) were finally included in this study. There were no significant differences in age, gender, education, duration, and Hoehn and Yahr (H&Y) stage between groups. There were significant differences in scores of Montreal Cognitive Assessment (MoCA), the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) I, Π, and Ш, total Rapid Eye Movement Sleep Behavior Disorder Questionnaire-Hong Kong (RBDQ-HK), Q6-Q12 items of RBDQ-HK (RBD(Q6-Q12)), 17 items Hamilton Depression Scale (HAMD), and Brief Smell Identification Test (B-SIT) between-groups (p < 0.01) (Table 1). Between-group differences of clinical assessments are shown in Table 1. Moreover, the analysis of voxel-based morphometry (VBM), independent component analysis (ICA) and head motion were performed. We did not find significant differences in intracranial volume (ICV), grey matter volumes (GMV), retained ICA components and mean framewise displacement of head between groups (p < 0.01, Bonferroni correction, Supplementary Table 1).

Table 1

Demographic data of participants.
variables	HC (n = 69)	iRBD (n = 53)	PD^RBD− (n = 64)	PD^RBD+ (n = 58)	ANOVA	post-hoc test
variables	HC (n = 69)	iRBD (n = 53)	PD^RBD− (n = 64)	PD^RBD+ (n = 58)	ANOVA	HC vs iRBD	HC vs PD^RBD−	HC vs PD^RBD+	iRBD vs PD^RBD−	iRBD vs PD^RBD+	PD^RBD− vs PD^RBD+
age(years)^a	62.92 ± 6.89	65.49 ± 8.43	63.33 ± 7.82	63.14 ± 7.2	0.247	-	-	-	-	-	-
gender(M/F)^b	32/37	32/21	30/34	32/26	0.38	-	-	-	-	-	-
education(years) ^a	11.29 ± 3.41	11.6 ± 2.94	11.14 ± 3.55	11.07 ± 3.08	0.833	-	-	-	-Ш	-	-
UPDRS-I^a	-	4.58 ± 3.4	7.19 ± 4.22	10.75 ± 6.19	<0.001**	-	-	-	0.02	<0.001**	<0.001**
UPDRS-Π^a	-	1.21 ± 1.8	8.64 ± 4.72	11.42 ± 6.33	<0.001**	-	-	-	<0.001**	<0.001**	0.004*
UPDRS-Ш^a	-	4.23 ± 4.47	24.55 ± 12.5	30.37 ± 13.29	<0.001**	-	-	-	<0.001**	<0.001**	0.023
duration(months)^c	-	60(3-372)	45.88(1.5–254)	48(2-350.25)	0.017	-	-	-	-	-	-
H&Y(I:Π:Ш)	-	-	28:29:7	16:36:6	0.027	-	-	-	-	-	-
MoCA^a	26.46 ± 2.23	23.88 ± 3.03	24.05 ± 4.32	22.6 ± 3.43	<0.001**	<0.001**	<0.001**	<0.001**	1	0.287	0.11
RBDQ-HK^a	9.43 ± 6.29	36.83 ± 14.8	9.13 ± 7.86	37.11 ± 14.66	<0.001**	<0.001**	1	<0.001**	<0.001**	1	<0.001**
RBD(Q6-Q12)^c	0(0–16)	22(4–58)	0(0–16)	20(8–54)	<0.001**	<0.001**	1	<0.001**	<0.001**	1	<0.001**
HAMD^a	2.48 ± 2.94	5.38 ± 3.87	5.14 ± 3.87	7.8 ± 5.14	<0.001**	<0.001**	0.001*	<0.001**	1	0.012	0.002*
B-SIT^c	10(8–12)	8(2–11)	8(0–12)	7(0–11)	<0.001**	0.001*	0.001*	<0.001**	1	0.756	1
^aANOVA, analysis of variance, mean ± standard deviation; ^bPearson χ² test; ^cKruskale Wallis H test, median (range).
HC: healthy control; iRBD: idiopathic rapid eye movement sleep behavior disorder; PD^RBD−: Parkinson’s Disease without RBD; PD^RBD+: Parkinson’s Disease with RBD; M/F: male/female; UPDRS: United Parkinson’s disease rating scale; H&Y: Hoehn & Yahr, I:Π:Ш means 1 to 1.5: 2 to 2.5: 3; MoCA: Montreal Cognitive Assessment-Beijing Version; RBDQ-HK: Rapid Eye Movement Sleep Behavior Disorder Questionnaire-Hong Kong; HAMD: Hamilton Depression Scale; B-SIT: Brief Smell Identification Test;
*p < 0.001, p < 0.01.

Functional connectivity

We found that the patients of iRBD, PD^RBD−, and PD^RBD+ all performed decreased FC patterns of bilateral LCs when compared with HCs (Fig. 1). Specifically, in iRBD patients, the left LC had decreased FC with all 5 RSNs, including DMN, ECN, SAL, SMN, and VIS, while the right LC had reduced FC with the DMN and ECN compared to HCs. PD^RBD− patients had significantly reduced FC between the left LC and DMN and SAL compared to HCs, but had no alteration of FC between the right LC and any RSNs. PD^RBD+ patients had reduced FC between the left LC and all 5 RSNs, while the right LC had reduced FC with the DMN, ECN, SAL, and SMN compared to HCs.

Different disease states exhibit different disrupted FC patterns of LC-related RSNs (Fig. 2). Compared to iRBD patients, PD^RBD+ patients had reduced FC between the left LC and DMN, and between the right LC and SMN. Compared to PD^RBD- patients, PD^RBD+ patients had reduced FC between the left LC and all 5 RSNs and reduced FC between the right LC and DMN, SAL and SMN. Interestingly, iRBD patients had reduced FC between the left LC and DMN, ECN and VIS, and reduced FC between the right LC and SMN when compared with PD^RBD- patients. The detailed results of FC calculation are shown in the Supplementary Tables 2 and 3.

Correlation analysis

In iRBD patients, the FC between the left LC and DMN (r = 0.4, p = 0.006) and ECN (r = 0.38, p = 0.008) was positively correlated with the MoCA scores (Fig. 3a); the left LC and DMN (r = -0.47, p = 0.001) and ECN (r = -0.42, p = 0.003) was negatively correlated with the disease duration (Fig. 3b), and the FC between the right LC and ECN was negatively correlated with the disease duration (r = -0.36, p = 0.008) (Fig. 3c).

In PD^RBD− patients, the FC between the left LC and DMN was negatively correlated with HAMD scores (r = -0.44, p = 0.003) (Fig. 4a). In PD^RBD+ patients, the FC between the left LC and DMN (r = 0.42, p = 0.002) and VIS (r = 0.39, p = 0.004) was positively correlated with the MoCA scores (Fig. 4b), while the FC between the right LC and SAL was negatively correlated with the total RBDQ-HK scores (r = -0.41, p = 0.003) (Fig. 4c), and negatively correlated with the RBD (Q6-Q12) scores (r = -0.37, p = 0.004) (Fig. 4d).

To the best of our knowledge, this study is the first to explore the alterations of LC-related functional networks in the prodromal stage and different phenotypes of PD. As expected, we found a similar disrupted pattern of LC-related RSNs in iRBD and PD^RBD+ patients, and the disruption in PD^RBD+ patients was even worse. However, the alterations of LC-related RSNs in PD^RBD− patients were less significant when compared to iRBD and PD^RBD+ patients. Moreover, the FC between LC and RSNs has relevance to the cognitive impairment and disease duration in iRBD and PD^RBD+ patients, the RBD severity in PD^RBD+ patients, and the depression in PD^RBD− patients. Our findings demonstrate that LC-related RSNs are already disrupted in the prodromal stage of α-synucleinopathies, and are differentially affected in body-first and brain-first PD.

Lesion of LC has been suggested responsible for RBD symptom^8,24,25. Previous imaging studies^17,18 have identified neuronal loss in the LC and noradrenergic denervation in iRBD patients. Compared with HCs, our iRBD patients exhibited a reduced FC pattern between LC and all 5 RSNs. The DMN and ECN are involved in complex cognitive ability such as memory retrieval, attention, and language^26–28. It has been shown that reduced noradrenalin level can impair cognitive flexibility and vigilant attention²⁹, while high noradrenaline level can restore the DMN integrity³⁰. Our iRBD patients had significantly worse MoCA scores compared to HCs (Table 1), and the FC of left LC-DMN and left LC-ECN was positively correlated to the cognitive function. These findings suggest that the disruption of LC-DMN and LC-ECN is associated with the cognitive impairment of iRBD patients. Previous imaging studies have reported decreased perfusion, metabolism and FC of hub regions of DMN^31–33 (e.g. medial frontal lobe, precuneus and cingulate), as well as ECN dysfunction³⁴, which are linked to cognitive impairment in iRBD patients. Furthermore, we found that FC of LC-DMN and LC-ECN was negatively correlated with disease duration, which indicates that the disruption of these networks will become worsen as the disorder progresses.

SAL plays a key role in regulating the dynamic interaction between inward tasks (DMN) and outward tasks (ECN)³⁵. SMN involves in action planning and execution³⁶, while VIS involves in visual processing³⁷. In iRBD patients, reduced noradrenergic transporter density³⁸ and dysfunction of SMN^34,39, as well as dynamic FC impairments within SMN⁴⁰ and VIS^40,41 has been reported. However, we did not find that the FC between LC and SAL, SMN and VIS were associated with clinical symptoms of iRBD patients. A possible reason is that SAL and VIS modulate the attentional and visuospatial system⁴², yet MoCA assesses global cognitive ability and is not sensitive to specific cognitive domains⁴³, such as visuospatial and executive function, and attentional function. More sensitive and specific cognitive tests are warranted in future studies to explore the association of disconnection of LC-SAL/VIS and manifestations of iRBD patients. In addition, our iRBD patients had subtle motor impairment (mean UPDRS Ш: 4.23). It has been suggested that iRBD patients with abnormal cognition and mild motor impairment have higher risk of converting to α-synucleinopathies¹³. Therefore, longitudinal studies are needed to explore the relationship between disrupted LC-SMN connectivity and motor symptom in iRBD, and whether disruption of LC-related RSNs can help to predict the conversion to α-synucleinopathies.

Our PD^RBD+ patients exhibited a similar disrupted FC pattern of LC-related RSNs as iRBD patients, even worse. Previous imaging studies also showed that iRBD patients have a similar FC pattern of basal ganglia network⁴⁴, reduced 11C-MeNER binding in the SMN^38,45 or hypometabolism in cortical areas^46,47 as that in PD patients. As Lewy pathology is supposed body-first origin, and severely affects LC in both iRBD and PD^RBD+ patients¹¹, it is reasonable that these two groups have the similar disrupted pattern of LC-related RSNs. Compared to iRBD patients, PD^RBD+ patients had more severe motor and cognitive impairments (Table 1), and decreased FC between the left LC and DMN, and between the right LC and SMN. It has been reported that PD^RBD+ patients had reduced noradrenergic function in SMN compared to iRBD patients³⁸. Our findings suggest that the disruption of LC-related RSNs is more pronounced in the clinical stage than in the prodromal stage of body-first PD, and may be associated with the progression of clinical symptoms.

Interestingly, the LC-related RSNs in PD^RBD− patients are less affected compared to iRBD and PD^RBD+ patients in this study. It is consistent with previous reports that PD^RBD− patients showed less reduced LC neuromelanin signal and noradrenergic transporter density compared to HCs and PD^RBD+ patients^11,17,19. In brain-first PD (PD^RBD−) patients, Lewy pathology is proposed originating in the amygdala and olfactory bulb, while the LC is less affected than body-first PD(PD^RBD+)^10,11. Besides, our PD^RBD− patients had significant higher HAMD scores than HCs and the FC of left LC-DMN was associated with depression. Reduced FC of DMN has been detected in patients with depression⁴⁸ or in PD patients with depression⁴⁹. It suggests that the dysfunction of DMN associated with noradrenergic denervation might be one of the reasons of depression in PD^RBD− patients.

Although our iRBD and PD patients showed smell loss, no correlation between B-SIT scores and FC of LC-related RSNs was observed. LC sends noradrenergic projections to the olfactory bulb and olfaction-related forebrain cortex, such as piriform, entorhinal and orbitofrontal cortex²⁰, and impaired LC is associated with olfactory dysfunction⁵⁰. However, it is known that multiple reasons are involved in olfactory dysfunction in PD, such as the deficiency of dopamine and acetylcholine^51,52. Thus, we will consider combining multiple transmitter (such as dopamine and noradrenaline) related neural networks in the future to investigate neural mechanisms underlying olfactory dysfunction in PD.

We found the disruption of FC between the left LC-related RSNs was more severe than right LC in all three patient groups. As most of our PD patients (76/122) exhibited right-side dominant motor symptoms, damage of the left hemisphere is more pronounced. The fiber projections of LC neurons performed an ipsilateral predominance^53,54. Our finding is consistent with previous reports of the left-hemispheric dominance of nigrostriatal deficit in right-handed iRBD^32,55. This finding suggests that the neurodegenerative process may begin asymmetrically in the prodromal stage of α-synucleinopathies, initially in the dominant hemisphere. In addition, there were no significant differences of brain volumes among the groups, and we have used the VBM results as variables of no interest in statistical analysis. Thus, our findings are unlikely confounded by the structural changes in iRBD and PD patients.

There are some limitations should be acknowledged. First, this is a cross-sectional study, a longitudinal study is necessary to assess whether disruption of LC-related RSNs in iRBD is associated with conversion to PD, and whether the progression of LC impairments is different in PD^RBD+ and PD^RBD− patients. Second, some non-motor symptoms (like autonomic dysfunction and anxiety) are not included in the current study. Future studies are needed to clarified the associations of LC impairments and these manifestations in iRBD and PD patients.

In conclusion, our work explored the FC pattern of LC-related RSNs in iRBD and PD patients. LC-related RSNs are significantly disrupted in the prodromal and proposed body-first PD (PD^RBD+), but are less affected in the brain-first PD (PD^RBD−). The dysfunction of LC-related RSNs may contribute to clinical symptoms in iRBD and PD patients.

Participants

One hundred and twenty-nine idiopathic PD patients (60 PD^RBD+ and 69 PD^RBD−) and 55 iRBD patients were recruited. PD patients were diagnosed according to the MDS Clinical Diagnostic Criteria². Sixty PD patients were defined as PD^RBD+ according to the following criteria⁵⁶: (1) patients or their bedmates had clear complaints of abnormal behavior during nocturnal sleep; (2) total score of RBDQ-HK ≥ 19; and (3) score ≥ 8 on RBD (Q6-Q12). Remaining 69 PD patients who did not meet the above criteria were defined as PD^RBD−. iRBD patients were screened with the international diagnostic criteria⁵⁷. Positive RBD patients were confirmed by polysomnography. In addition, 72 age and gender matched HCs were recruited. The inclusion criteria for HCs were no obvious neuropsychiatric symptoms or structural MRI abnormalities or subjective memory complaints. All participants were right-handed. This study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Beijing Tiantan Hospital, Capital Medical University. All participants signed informed consents prior to the experiment.

Clinical assessments

All participants were evaluated with the scores of MoCA, 17-items HAMD and B-SIT. The patients were assessed using the MDS-UPDRS and RBDQ-HK. In addition, the H&Y stage was evaluated in PD patients. PD patients were evaluated while not taking any anti-parkinsonian medication for a minimum of 12 hours.

MRI data acquisition

The MRI data were acquired on a 3.0T scanner (Siemens, skyra, Germany). Preparation of participants before scanning included: stabilize the head with foam pads, reduce audible noise with earplugs, and close eyes but remain awake during scanning. Three-dimensional T1-weighted images were obtained with magnetization prepared rapid acquisition gradient echo (MP-RAGE) sequence: repetition time (TR) = 2530ms, echo time (TE) = 2.98 ms, flip angle (FA) = 7◦, field of view (FOV) = 224mm × 256mm, matrix = 256 × 256, voxel size = 1 × 1 × 1mm³, slice thickness = 1mm, number of slices = 192 (sagittal), no gap, scanning time = 5 min and 13 s. The rs-fMRI data were obtained with gradient echo planar imaging (EPI) sequence: TR = 2000ms, TE = 30ms, FA = 90 °, FOV = 220mm × 220mm, matrix = 64 × 64, voxel size = 3.4 × 3.4 × 3.6mm³, number of slices = 35 (axial), slice thickness = 3.5mm, no gap, time points = 176, scanning time = 5 min 52 s.

MRI data preprocessing

First, the CAT12 (Computational Anatomy toolbox) was used for the analysis of VBM with T1-weighted images (http://dbm.neuro.uni-jena.de/cat12/), which is based on the MATLAB R2018b platform (http://www.mathworks.com). The analysis process mainly includes: spatial normalization, bias field correction, tissue segmentation and modulation. Then the ICV and GMV of all participants were measured in normalized space.

The preprocessing of rs-fMRI data was performed with the DPARSF6.0 toolbox (Data Processing Assistant for Resting-State fMRI, version 6.0) (http://www.restfmri.net) based on MATLAB 2018b, including removal of the first 10 time points, slice-timing, realign, regressing off cerebrospinal fluid and global signals and Friston-24 head motion parameters, and normalization (voxel size 3 × 3 × 3mm³) with DARTEL (Diffeomorphic Anatomical Registration using Exponentiated Lie algebra) algorithm. Participants with excessive head motion (more than 2.5mm of maximal translation in any direction or 2.5° of maximal rotation, or mean framewise displacement more than 0.25mm) were excluded⁵⁸. We excluded 2 iRBD, 5 PD^RBD−, 2 PD^RBD+ patients and 3 HCs.

As LC is located in the brainstem, and is adjacent to the fourth ventricle, fMRI signals of LC may be confounded by physiological noise (cardiac and respiratory cycles). Thus, we used MELODIC (Multivariate Exploratory Linear Optimized Decomposition into Independent Components)

(https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/MELODIC), a toolbox included in FSL (FMRIB’s Software Library), to perform an ICA analysis on the normalized rs-fMRI images for removing physiological noises⁵⁹. To accurately identify the signal components of LC, we performed the ICA analysis twice according to the hand classification of fMRI ICA noise components⁶⁰ and the average retained ICA components are shown in Supplementary Table 1.

Then, the rs-fMRI images were low-pass filtered (0.01 ~ 0.1Hz). Considering the small volume of LC, rs-fMRI images were smoothed with a 3mm full width at half maximum (FWHM) Gaussian kernel⁶¹. We defined bilateral LCs according to a high-resolution probability atlas (threshold 5%) based on ultra-high field 7T neuromelanin-sensitive MRI data from healthy elderly people⁶². As LC projects to extensive brain regions²⁰ and RSNs derived from the older adults are spatiotemporal configuration different from young adults^63,64, we defined the five LC-related RSNs according to the Atlas55+, a brain functional atlas for late adulthood⁶³. The DMN mainly includes the medial prefrontal cortex/ventral anterior cingulate cortex, the precuneus/posterior cingulate cortex, the inferior frontal cortex and the middle temporal cortex; the ECN contains parts of the dorsolateral prefrontal cortex, the lateral and medial parietal cortex, the posterior inferior temporal cortex and part of cerebellum; the SAL is comprised of the dorsal anterior cingulate cortex, the anterior supplementary motor area, the supramarginal gyri, part of subcortical regions and cerebellum; the SMN covers the sensory and motor regions (precentral and postcentral gyrus and supplementary motor area) and the thalamus; VIS largely covers the occipital lobe⁶³. Of these, DMN, ECN and SAL involve in higher order cognitive and psychological functions as part of the intrinsic system, while VIS and SMN support specialized visual, sensory and motor processing as part of the extrinsic system. FC between the bilateral resampled LCs and these RSNs was analyzed with the seed-to-voxel correlation analysis. Correlation coefficients were converted to z values using Fisher's r-to-z transformation.

Statistical analysis

IBM-SPSS v25.0 software (Armonk, New York, USA) was used for variable analysis. For neuropsychological assessments, the normality of variables was confirmed by Q-Q plots and Kolmogorov-Smirnov tests. The continuous variables were analyzed by one-way analysis of variance (ANOVA) and expressed as mean ± SD (standard deviation). Other variables were analyzed using non-parametric tests and expressed as median (range). Pearson χ² test was used to analyze gender difference. The Bonferroni correction was used for multiple comparisons (p < 0.01).

One-way analysis of covariance (ANCOVA) was used to calculate the differences of FC among the groups, with age, gender, education, mean framewise displacement, ICV, and GMV of participants as covariates of no interest. Post-hoc tests (with same covariates as those for ANCOVA analysis were performed to explore the between-group differences of FC. Family wise error (FWE) correction was used for multiple comparisons (permutation test set to 20,000, cluster p < 0.05, with a cluster extent of ≥ 10 voxels, and voxel p < 0.001). Partial correlation analysis (with same covariates as those for ANCOVA analysis) was used to test the relationship between FC and clinical assessments (p < 0.01, Bonferroni corrected).

DATA AVAILABILITY

Data supporting the results in this paper are available upon request to the corresponding author by qualified researchers (i.e., affiliated to a respected university or research institution/hospital). The software (CAT12, DPABI, SPM12, FSL, SPSS) and atlas (bilateral LC, five RSNs) used in this paper are open sources.

ACKNOWLEDGEMENTS

This research was supported by the National Natural Science Foundation of China (no. 82071423)

AUTHOR CONTRIBUTIONS

Research project: (A) Conception and Organization: Tao Wu, and Tao Feng; (B) Execution: Junyan Sun. Statistical analysis: (A) Design, Execution, Review, and Critique: Junyan Sun. Manuscript preparation: (A) The inclusion of participants: Junyan Sun, Jinghong Ma, Linlin Gao, Junling Wang, Dongling zhang, and Lili Chen. (B) The acquisition of MRI data: Jiliang Fang; (C) Writing of the first draft: Junyan Sun. (D) Review, Critique, and Polish: Tao Wu, and Tao Feng.

COMPETING INTERESTS

Prof. Wu and Prof. Feng reported no competing interests.

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Disruption of Locus Coeruleus Related Functional Networks in Parkinson’s Disease

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Functional connectivity

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