Connectivity patterns of cognitive control network in first episode medication-naive depression and remitted depression

Journal Pre-proof Connectivity patterns of cognitive control network in first episode medication-naive depression and remitted depression Kaili Jiao, Huazhen Xu, Changjun Teng, Xiu Song, Chaoyong Xiao, Peter T. Fo, Ning Zhang, Chun Wang, Yuan Zhong

PII:

S0166-4328(18)30998-7

DOI:

https://doi.org/10.1016/j.bbr.2019.112381

Reference:

BBR 112381

To appear in:

Behavioural Brain Research

Received Date:

12 July 2018

Revised Date:

19 November 2019

Accepted Date:

22 November 2019

Please cite this article as: Jiao K, Xu H, Teng C, Song X, Xiao C, Fo PT, Zhang N, Wang C, Zhong Y, Connectivity patterns of cognitive control network in first episode medication-naive depression and remitted depression, Behavioural Brain Research (2019), doi: https://doi.org/10.1016/j.bbr.2019.112381

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.

Connectivity patterns of cognitive control network in first episode medication-naive depression and remitted depression

Kaili Jiao1-2#, Huazhen Xu1#, Changjun Teng1-2, Xiu Song1-2, Chaoyong Xiao1,

1Nanjing

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Peter T. Fox,6-7, Ning Zhang1-3, Chun Wang1-4*, Yuan Zhong4-5*

Brain Hospital affiliated to Nanjing Medical University, Nanjing,

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Jiangsu, China. No.264, Guangzhou Road, Nanjing, 210029 P.R.C

Cognitive Behavioral Therapy Institute of Nanjing Medical University,

Nanjing, Jiangsu, China.

Brain Imaging Institute of Nanjing Medical University, Nanjing,

Jiangsu, China

of psychology, Nanjing normal university, Nanjing, China.

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4 School

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3 Functional

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2

No.122, Ninghai Road, Nanjing, 210029 P.R.C 5

Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing

6

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Normal University, Nanjing 210097, PR China South Texas Veterans Healthcare System; University of Texas Health

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Science Center at San Antonio, United States 7

Research Imaging Institute, University of Texas Health San Antonio,

United States.

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*Correspondence Ph.D., M.D., Chun Wang, Nanjing Brain Hospital affiliated to Nanjing Medical University, Nanjing, China. No.264, Guangzhou Road, Nanjing, 210029 P.R.C. e-mail: [email protected] Ph.D., Yuan Zhong, School of psychology, Nanjing normal university, Nanjing, China. No.122, Ninghai Road, Nanjing, 210029 P.R.China.

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e-mail: [email protected]

These authors contributed equally to this work and should be considered

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co-first authors

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Highlights

More widespread changes in functional connectivity within the CCN was

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obseved in both fMDD and rMDD patients.

Compared HC, altered distributions of CCN between fMDD and rMDD

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groups might underpin the cognitive disturbance. CCN may be potential neurobiological markers of cognitive performance in

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MDD.

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Abstract

Background: Cognitive dysfunctions, such as impaired cognitive control, are frequently observed in patients with major depressive disorder (MDD). Although the cognitive control network (CCN) is widely considered a core feature of major depressive disorder (MDD), the relationship between cognitive dysfunction and symptom dimensions remains unclear. This study investigated differences in resting-state functional connectivity of the cognitive control network (CCN) between first-episode medication-naive MDD patients and remitted MDD. 2 / 33

Methods: We collected resting-state functional MRI (rs-fMRI) data from 22 first-episode medication-naive major depressive disorder (fMDD) patients, 20 patients previously diagnosed with MDD in the remitted phase of depression (rMDD), and 20 healthy controls (HC). The CCN was derived from fMRI images using independent component analysis (ICA), a data-driven image analysis method. Results: Changes in functional connectivity (FC) within the CCN was mainly attenuated in the right dorsolateral prefrontal cortex and the left inferior parietal lobule, while strengthened in the right dorsal anterior cingulate cortex and the right insula in both fMDD and rMDD groups. Compared with the fMDD group, the rMDD group had decreased FC in the bilateral

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insula and the right dorsolateral prefrontal cortex. Further analysis explored that the FC in the bilateral insula, the right dorsal anterior cingulate cortex and the right inferior parietal lobule were correlated positively cognitive disturbance factor scores in both patients groups.

Conclusions: These findings are in agreement with the previous findings that the cognitive

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control network are impaired in MDD. Furthermore, our results suggest that the alteration of

CCN might underpin the cognitive disturbance and the distinct patterns of the CCN between

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fMDD and rMDD patients may be an important target for effective cognitive

remediation in MDD.

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Keywords: first-episode medication-naive major depressive disorder, remitted phase of MDD,

MDD, major depression disorder; CCN, cognitive control network; DMN, default mode network; SN, salience

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cognitive control network, functional connectivity, Independent component analysis1

network; DLPFC, dorsolateral prefrontal cortex; dACC, dorsal anterior cingulate cortex; PPC, posterior parietal cortex; MFG, middle frontal gyrus; IPL, inferior prefrontal Lobes; SPL, superior parietal lobes; SMG, supramarginal gyrus; AG, angular gyrus; ICA, independent components analysis; GIFT, the Group ICA fMRI Toolbox; SCID-5, Structured Clinical Interview for the DSM-V; HAMD-17, 17-items -Hamilton Depression Rating Scale; GRE-EPI, a gradient- recalled echo-planar imaging; MNI, Montreal Neurological Institute; MDL, minimum description length.

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1 Introduction The World Health Organization (WHO) reports that over 300 million people worldwide suffer from major depressive disorder (MDD) with a lifetime prevalence of approximately 16%. MDD is one of the leading causes of disability and it is a significant burden for health care systems. MDD is characterized by persistent depressed mood, negative thoughts, and anhedonia [1-5]. Currently, antidepressant medication is recommended as the first course of treatment for patients with MDD However, about 30% of patients with MDD fail to respond to standard antidepressant

treatment

[7].

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[5-6].

In addition, patients who recover have an 80% probability of relapse

increased risk of future depressive episodes [13-14].

[4; 8-12]

and an

[55, 56]

as a core feature of MDD

[53, 54].

The impairment remains even when

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symptom severity

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Increasingly, studies have recognized cognitive control impairment and its relation to

symptoms are in remission, indicating a relatively stable intermediate phenotype that may

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provide some possible explanations for MDD’s recurrence [15,18, 56, 57, 65].

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Evidence from previous neuroimaging studies suggests that impairments in cognitive control occur due to alterations in neural networks [15, 16, 25, 56].

particularly the cognitive control network

As a frontoparietal circuit, the CCN consists mainly of the dorsolateral

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(CCN)

[11; 20-25],

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prefrontal cortex (DLPFC), the dorsal anterior cingulate cortex (dACC), and the posterior parietal cortex (PPC). In addition, the CCN encompasses a large area containing the inferior prefrontal cortex, extending to the bilateral insula and superior parietal lobes. The parietal lobe emphasizes the regulation of negative emotional arousal. The dorsal ACC monitors for errors or processing conflicts that can disrupt performance and recruits the DLPFC to reallocate attentional resources

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as needed [27, 72]. The DLPFC’s prominent role in attention and negative emotion [27, 29] qualifies it as a good starting point for understanding the functional aberrations of the CCN and the resulting cognitive deficits in MDD. In addition, resting-state fMRI is an established technique for identifying functional abnormalities in the brain, and many studies have used it to evaluate how neural nodes synchronize within a functional network [11, 20-25, 59].

A recent study has investigated state-related alterations of spontaneous neural activity in

analysis

[58].

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fMDD and rMDD during resting-state fMRI through amplitude of low-frequency fluctuation (ALFF) However, we are not aware of previous studies that have examined resting-state

connectivity within the CCN in first-episode medication-naive major depressive disorder (fMDD)

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and remitted MDD (rMDD). Therefore, the present study aimed to assess whether the distinction

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between fMDD and rMDD can improve the identification of neuroimaging markers for MDD in

2 Materials and Methods

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2.1 Participants

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mainland China using group independent component analysis (ICA) on resting-state fMRI data.

62 participations were recruited from the Psychiatric Outpatient Clinic of Nanjing Brain

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Hospital, affiliated with Nanjing Medical University (Nanjing, China). Of these, 22 adults were

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first-episode treatment-naive depression patients, 20 adults were remitted depressed patients, and 20 adults were healthy controls (HCs). HCs were matched for age, sex, and education and were recruited by internet advertisements according to the inclusion and exclusion criteria. All patients received a clinical diagnosis of Major Depressive Episode (F32.0), Major Depressive Disorder in remission (F33.40), or healthy without complications. 5 / 33

Patient groups

The inclusion criteria for all subjects were: (1) between 20 and 50 years of age; (2) right-handed. Both patient groups were clinically diagnosed, respectively, as major depressive disorder according to the structured clinical interview for DSM-IV disorders - Patient Edition (SCID-P) by two experienced psychiatrists. Patients also completed the 17 - item Hamilton Depression Rating Scale (HAMD-17) for symptomatic assessment.

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The following are details of the inclusion criteria for both groups of MDD patients: (a) first

episode major depression as primary diagnosis, (b) unipolar subtype, (c) psychotropic drug-naive, (d) scores for the fMDD group were > 17 on HAMD-17 (Davis JM score), (e) Criteria for morbidity

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or remission required that symptoms be present or absent for a minimum of two weeks [2], (f)

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scores for the rMDD group were ≦ 7 on HAMD-17 after antidepressant treatment for first

other major physical diseases.

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episode, (g) duration of depression less than a year, and (h) no history of neurological illness or

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The exclusion criteria for patients were: (a) a history of antidepressant treatment including pharmacotherapy or psychotherapy, (b) meeting the DSM-V criteria for other psychiatric

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disorders/major chronic or acute medical or neurologic condition, (c) having a history of head

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injury, (d) symptoms of suicide or autotomy and so on.

2.1.1

Healthy controls

The healthy controls were interviewed according to the structured clinical interview for

DSM-V disorder, Non-patient edition (SCID-N). All HCs’ HAMD scores were ≦ 7. The exclusion criteria were the same as aforementioned. An absence of neurological illness, psychiatric 6 / 33

disorders, and no family history of major psychiatric disorders was confirmed for all HCs.

2.2 Demographics

All participants signed a written statement of informed consent. Patients were screened to make sure they had no other neurological illness or a history of head injury. Healthy controls were screened to exclude participants with any history of depression.

All participants were right-handed native Chinese speakers ranging in age from 20 to 50

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years old. Additionally, participants were matched for age and ethnicity (See Table 1). Due to

motion artifacts, 5 participants’ scans were discarded. This included 3 first-episode depressed

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patients, 1 patient with depression in remission, and 1 healthy control. Our final participant

population consisted of 19 first-episode depressed patients, 19 depressed patients in remission,

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and 19 healthy controls.

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Diagnoses were given by experienced psychiatrists using the Structured Clinical Interview for the DSM-V(SCID-5) and the 17-item Hamilton Depression Rating Scale (HAMD-17)

[30].

A

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HAMD-17 scale score of < 7 was considered normal, and a score > 7 was considered clinically depressed. Criteria for morbidity or remission required that symptoms be present or absent for a [2].

Cognitive disturbance factor scores consisted of Hamilton depression

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minimum of two weeks

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scale 2nd, 3rd, and 9th item scores from the 17-item Hamilton Depression Rating Scale (HAMD-17) [49, 50].

2.3 Data acquisition

2.1.2

Image acquisition

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All images were obtained on a Siemens 3.0-Tesla signal scanner (Siemens, Verio, Germany) with a standard head coil at the Magnetic Resonance Center of Nanjing Brain Hospital. All subjects were instructed to close their eyes, stay awake, and try not to think of anything during the scanning procedure. Resting- state fMRI Imaging data were collected transversely by using a gradient-recalled echo-planar imaging (GRE-EPI) pulse sequence with the following settings: TR/TE = 3000 ms / 40 ms, flip angle = 90°, slice thickness = 4.00 mm, field of view = 240 mm ×

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240 mm × 240 mm, matrix size = 64 × 64. The scan lasted 5.06 minutes for all subjects.

For spatial normalization and localization, a high-resolution T1 - weighted magnetization

prepared gradient echo image (MPRAGE) was obtained for each participant. T1 - weighted

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images were acquired with the following parameters: TR = 1900 ms, TE = 2.48 ms, slice

2.1.3

Image preprocessing

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resting-state scan lasted 4 minutes 18 seconds.

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thickness = 1.00 mm, gap = 0.5 mm, slice number = 176, matrix size = 256 × 256. The

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All preprocessing was performed using the Data Processing Assistant for Resting-State fMRI (DPARSF) [31], which is based on Statistical Parametric Mapping (SPM12)

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(http://www.fil.ion.ucl.ac.uk/spm). Preprocessing of images, including time-slice correction, head

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motion correction, spatial normalization, and smoothing were performed with DPARSF in MATLAB R2013a. Scans with excessive head motion, cumulative translation >3mm and rotation > 3°, as well as mean point-to-point translation > .15 mm or rotation > .1° were excluded. Spatial normalization was achieved using the Montreal Neurological Institute (MNI) stereotaxic template, resampled to 3× 3× 3 mm voxels with a Gaussian Kernel of 6 × 6 × 6 mm for smoothing

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and to decrease spatial noise.

2.4 Group ICA and post-processing on functional data

To identify ICNs for all 57 participants, we performed an ICA of the rs - fMRI data using the Group ICA in the fMRI Toolbox (GIFT) v3.0 (http://mialab.mrn.org/software/gift, Calhoun, Adali, 2012). Group independent component analysis (ICA) has been considered the most successful method for identifying spatially independent brain networks [32, 33].

. CCNs were isolated using the

To determine the number of independent components (ICs),

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Infomax algorithm in GIFT

[60-62]

dimension estimation on the data sets of the three groups was performed using the minimum description length (MDL) criterion

[33].

Then, fMRI data from all subjects in each group were

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concatenated and the temporal dimension of the aggregate data set was reduced by means of

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estimation using the FastICA algorithm [34].

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principal component analysis (PCA), followed by an IC (with time-courses and spatial maps)

The number of ICs of the three groups (fMDD, rMDD and HC) was 47, 49, and 50 ICs,

groups

[33].

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respectively, ensuring that the resting-state networks had a similar spatial pattern in these three We employed standard methods of rejecting artifactual ICA networks and network

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components that clearly represented artifacts were eliminated. The components to be retained

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for further analysis among the 47/46/50 estimated ICs for the three groups were selected based on the largest spatial correlation with specific RSN templates, according to GIFT software guidelines. These templates came from previous investigations resting-state fMRI studies

[35, 61, 62]

[63]

and have been used in other

in combination with spatial correlation for RSN selection

criterion. Cluster - level significance was denoted by cFDR (false discovery rate correction).

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2.5 Statistical analysis

All analyses on demographic data and clinical datasets were performed by using IBM SPSS statistical software version 22.0, and fMRI imaging using the SPM12 toolbox. The spatial maps of each network were extracted from all participants. One sample t-tests (p < 0.01, corrected for multiple comparisons with FDR) were performed to moderate the spatial networks of the CCN within each group. To explore CCN differences among these three groups, an ANOVA was

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performed (p = .01, corrected for multiple comparisons with FDR). Head motion parameters, age, and gender scores were included as covariates. In addition, Bonferroni corrections were applied to each test to adjust for multiple testing.

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2.6 Relationship to clinical scores

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To investigate the association between clinical symptoms and aberrant functional

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connectivity in the CCN, correlations were calculated separately for HAMD-17 scores and cognitive function scores within the fMDD and rMDD groups. Correlation analysis was performed

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by using SPM12, and corrected for multiple comparisons with FDR.

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3 Results

3.1 Demographic and clinical status

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To assess group differences in demographic and clinical variables, we utilized ANOVA and

pot-hoc t-tests. Also, group differences in gender were assessed with chi‐ square tests. All of the analyses were performed in IBM SPSS Version 22.0.

As listed in Table 1, there were no significant differences in terms of age (F(2 ,54) = .126, P

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= .882), level of education (F(2, 54) = .985, P = .380), or gender (2=.140, p=.932) among the three groups. The clinical symptoms of the first-episode MDD group were significantly higher than the clinical behaviors of control groups (p < .001), particularly regarding disease duration and scores on the 17 item-Hamilton Depression Rating Scale. As expected, there were significant differences in disease duration ( t = 2.84, p = .008) and HAMD-17 scores (t = 20.60, p = .001) between fMDD and rMDD.

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.

3.2 Within-Group ICA Analyses

ICA results gleaned from the one-sample t-test displayed a typical spatial pattern in the CCN

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in each group (FDR corrected, p = .01, see Figure1). In rMDD compared to controls and fMDD,

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significantly higher connectivity scores were located in a large area of the right DLPFC including the middle frontal gyrus (MFG, BA9, BA10, BA46) and inferior prefrontal gyrus (IPG, BA47, BA45)

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extending to the bilateral IPL (BA40), insula (BA13), superior parietal lobes (SPL, BA5, BA7), and

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dorsal anterior cingulate cortex (dACC, BA32)

3.3 Between-Group ICA Analyses

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The significant influence of disease duration was treated as a regression covariate in the

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analysis. The results obtained from the one-way ANOVA clearly showed statistically significant differences in functional connectivity among the three groups (F = 6.48, p = .01, FDR corrected). The results provided a list of brain regions that displayed connectivity differences within the CCN, along with the MNI coordinates of the peak foci. (see Figure 2. Table 2). Altered connectivity differences were revealed in the bilateral Inferior parietal lobule (IPL), bilateral supramarginal

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gyrus (SMG), bilateral insula, right DLPFC, right dACC, and left superior parietal lobule (SPL).

3.4 Post hoc analyses

Two-sample post hoc t-tests were applied to determine connectivity differences between each of the three groups (p = .01, FDR corrected, see Table 3).

Compared to healthy controls, fMDD patients showed significantly higher connectivity scores in the right IPL (t = 4.00), the right dACC (t = 5.18), and the right Insula (t = 4.00). However, fMDD

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showed decreased connectivity in the right DLPFC (t = -3.29), left IPL (t = 2.93), and bilateral

supramarginal gyrus (SMG, t = -4.37, -3.34). Compared to healthy controls, depressed patients in

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remission showed decreased connectivity of the bilateral DLPFC (t =-3.53, -3.64), the IPL (t

=-7.92, -7.34), and the left SPL (t = -4.69). In contrast, increased connectivity in the right dACC (t

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= 4.24) and bilateral insula (t = 5.90, 7.05) was shown in the rMDD group. Compared to fMDD

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patients, rMDD patients showed a decrease in functional connectivity of the bilateral IPL (t = -7.30, t = -5.49) and the right SPL (t = -4.58) and an increase in functional connectivity in the right

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3.5 Correlation analyses

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DLPFC (t = 3.29) and bilateral insula (t =4.41, 5.38).

In the fMDD group, there was a positive correlation between cognitive disturbance factor

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scores (taken from HAMD-17) and aberrant functional connectivity of the IPL, insula, and the right dACC of the CCN (see Figure 3a, Table 4, p<0.01, FDR corrected). However, because the rMDD group reported a score of zero in cognitive disturbance factor from HAMD-17, we were unable to conduct the same correlation analysis.

In addition, we also explored the correlation between HAMD-17 scores and aberrant 12 / 33

functional connectivity of CCN in both fMDD and rMDD groups. There was a significant positive relationship between HAMD-17 scores and connectivity of the bilateral insula, right SMG, right DLPFC, right dACC, and bilateral IPL in the fMDD group (see Figure 3b, Table 5, p<0.01, FDR corrected). In the rMDD group, there was also a significant positive relationship between HAMD-17 scores and connectivity of the bilateral Insula, the right of IPL, bilateral SMG and the right of dACC (see Figure 3b, Table 5, p<0.01, FDR corrected).

Discussion

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We utilized ICA methodology to explore altered resting-state CCNs in fMDD and rMDD

patients compared to healthy controls. While we did find independent functional patterns in MDD,

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the global-level finding was that both fMDD and rMDD patients showed more widespread

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changes in functional connectivity (FC) values within the cognitive control network (CCN),

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localized mainly in the DLPFC, dACC, IPL, and insula. On a nodal level, compared to the HC group, we found that both patient groups displayed greater FC in the right dACC and right insula,

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as well as decreased FC in the right DLPFC and left IPL. In addition, compared to fMDD patients, rMDD patients showed decreased FC in the bilateral Insula and the right DLPFC. Overall, the

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MDD [25].

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aberrant FC results we identified converge with the generally agreed upon network alterations in

In line with our results, a previous study in remitted depression patients found decreased FC

in the DLPFC [56, 64,66], the SMG [38, 39], and the IPL [56,67], suggesting that these alterations may represent state-independent biomarkers of MDD. In fact, the rMDD group in our study displayed more widespread FC values than the fMDD group, suggesting that patients after treatment with

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SSRIs still had residual impairment. This supports the observation by Liao et al. [42] that not all patients who accept treatment respond well, and up to one-third fail to achieve remission. Progression of disease is also important, as Shen et al. [17] found that there are differences in CCN connectivity during early stages of MDD, evidenced by increased FC in parts of the frontal gyrus, parietal cortex, cingulate cortex, and left DLPFC.

At the same time, we found increased FC values in the right IPL, the right dACC, and

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bilateral insula in both patient groups compared to HCs, providing evidence of a compensatory response that maintains the dysfunctional cognitive control in MDD. According to prior work, information processing is one of the cognitive operations that is most disturbed by these FC

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abnormalities [12, 28, 36, 37]. The high connectivity score in the IPL provided additional differential

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prediction of remission on SSRIs through the use of a Go/No Go cognitive control task [40] . This comes as no surprise seeing as the IPL (sub-parietal district) has been involved in the perception

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of emotions in facial stimuli [41] and interpretation of sensory information. In the present study, fMDD patients showed higher FC values in the right dACC and the right IPL, and lower FC values

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in the bilateral insula than rMDD patients, further indicating that aberrant connectivity may predict

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eventual treatment response [46, 47] . However, this requires further investigation to explore a possible causal mechanism. In addition to the aberrant CCN connectivity we identified, our

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findings also include aberrant connectivity in the insula, precuneus, and Cingulate Gyrus (BA31), key brain areas that comprise the DMN and SN [25, 26, 45]. Similar to the function of the cognitive control network in behavioral measures such as cognitive processing, the activity of these networks suggests a “common core” recruited across diverse cognitive challenges [17, 19, 26].

An additional finding of our present study was that the abnormal CCN connectivity between 14 / 33

the bilateral insula, the right DLPFC, the right dACC, the right SMG, and the right IPL may be primarily associated with cognitive dysfunction in MDD patients. Wu X and Lin P[52] used the dACC as the seed region of interest and found abnormal connectivity in first-episode medication-naive patients between the dACC and the bilateral MFG, left angular gyrus (LAG), and precentral gyrus. Depression symptom severity (measured with HAMD) was also significantly correlated with the FC values of these areas; Increased connectivity in the dACC

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gave rise to disturbed cognitive control function. Interestingly, some of these regions, such as the DLPFC and SMG, are highly connected functionally. For example, the connectivity between the right SMG and lower DLPFC-rSMG has been previously linked to egocentricity[51] which can be

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related to depression in general[38]. Currently, there are few studies on altered connectivity and function of the CCN in MDD and results are largely inconsistent. Nonetheless, because both

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hypoconnectivity and hyperconnectivity have been reported between the CCN’s core region, the

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dorsolateral prefrontal cortex (DLPFC), and other brain regions [43], the connectivity of these regions might be involved in the underlying mechanisms of cognitive dysfunction in MDD [28, 44].

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Therefore, we speculate that patients with remitted MDD will still experience impaired cognitive function, but this requires further investigation to confirm the association and to explore a

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Conclusion

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possible causal mechanism.

In conclusion, this study revealed that in MDD and rMDD, aberrant functional connectivity in

the CCN during resting-state existed predominantly in prefrontal networks including the DLPFC, the SMG, the IPL, and the dACC, which play major roles in cognitive control of emotional processing and in other aspects of emotional and visceromotor modulation. These findings may 15 / 33

be used to guide our future studies aimed at identifying depressive episodes or remitted states in MDD on the basis of neurobiological markers.

Limitations

Recent works suggest that the extent to which MDD subjects experience cognitive impairments seems to depend on several different factors such as symptom severity [68], childhood adversity [69], antidepressant treatment [48, 70] and recurrence of episodes [71]. We

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acknowledge the following limitations of the current study: (1) We have presented a

cross-sectional study comparing three different groups including fMDD, rMDD, and HCs. Within

these groups, variables such as medication effects, family history, and childhood adversity were

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not measured and these factors may influence the current findings; (2) ICA was associated with

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methodological constraints, such as arbitrary selection of the model order and subjective bias in

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identification of the components of interest; (4) There were no objective reasons to confidently rule out psychiatric co-morbidities or be certain there was no family history of MDD; (5) Sample

Ethics Statement

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was relatively small; (6)The clinical scale data was not well-collected.

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This study was approved by the Ethic Committee of Nanjing Brain Hospital, affiliated with

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Nanjing Medical University. Written informed consent was obtained from all patients who took part in the study, in accordance with the Declaration of Helsinki. The protocol was approved by the Ethic Committee of Nanjing Brain Hospital which is affiliated with Nanjing Medical University.

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Conflict of Interest Statement

The authors declare that the research has been conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Conflict of interest

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All authors declare no conflicts of interest.

Acknowledgments

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This study was supported by National Natural Science Foundation of China (81571344,

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81871344,81201064); Natural Science Foundation of Jiangsu Province (BK20161109); the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province, China

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(18KJB190003); Key research and development program (Social Development) project of Jiangsu province (BE20156092015); The Postdoctoral Science Foundation of China

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(2014M552700); Six Talent Peak" High-Level Talent Selection and Training Plan of Jiangsu

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Province (2018-WSN-109).

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2017.

ro of -p re lP

Figure 1. One sample t-test results of group-level CCN for each group. Higher connectivity scores are shown in

na

groups. The color scale represents t values in CCN (maps thresholded at p < .01, FDR corrected). The left-hand

column is a three-dimensional (3D) graph performed by brain viewer, and the right is sagittal figure draw in micron

ur

software. Our procedure for independent component classification produced consistent ICNs. Colorbar presents t

Jo

value after FDR corrected.

26 / 33

ro of -p re lP

na

Figure 2. ANOVA results showed abnormal intra network connectivity among first-episode medication naive MDD

Jo

ur

groups, remitted depression and healthy control group (one-way ANOVA, p < .01, FDR corrected).

27 / 33

ro of -p

a Correlations between the aberrant functional connectivity in CCN and cognitive factor scores in fMDD

re

Figure 3

group (p < .01, FDR corrected). b Correlations between the aberrant functional connectivity in CCN and

Jo

ur

na

lP

HAMD-17(HDRS) scores in fMDD and rMDD groups (p < .01, FDR corrected).

28 / 33

Table 1

Demographic and clinical characteristics of total samples fisrt-episode

Demographics

rMDD*

HC

Mean(SD)

Mean(SD)

MDD

F value

P value

Mean(SD) Sex(male/female)

9/10

9/10

10/9

.140 a

.932

Age(years)

37.79(9.05)

36.42(8.62)

37.73(9.86)

.126

.882

Education(years)

14.47(2.27)

15.16(2.73)

14.05(2.32)

.985

.380

Disease duration（months）

7.74(5.39)

3.47(3.70)

2.84

.008

HAMD-17

25.47(4.74)

1.16(1.77)

20.60

.001

Cognitive function score

2.89(1.41)b

ro of

2.89(1.85)

N = 19; a = 2

Abbreviations: HC, healthy control; first-episode MDD, first-episode major depressive disorder; rMDD, remitted major depressive

-p

disorder; N, size; M, Mean; SD, standard deviation, HAMD-17:7 items -Hamilton Depression Rating Scale 17 Items; * All rMDD patients have received conventional drug therapy during and after hospitalization.

re

cognitive disturbance factor scores consist of Hamilton depression scale 2th, 3th and 9th item scores from HAMD-17.

Jo

ur

na

lP

b The

29 / 33

Comparisons of intra - network connectivity among groups

Cluster Regions

Side

MNI coordinates

BA

F value size

x

y

z

Inferior Parietal Lobule

R

40/3/2/1

386

54

-33

54

34.91

Inferior Parietal Lobule

L

40/3/2/1

186

-51

-36

51

38.48

SupraMarginal Gyrus

R

40

78

51

-18

24

18.23

Supramarginal Gyrus

L

40

29

-54

-30

21

23.50

Insula

R

13/45/47/44

201

36

Insula

L

13

28

-33

DLPFC

R

10

13

33

dACC

R

32

15

6

Superior Parietal Lobule

L

7

18

lP

Jo

ur

na

DLPFC, dorsolateral prefrontal cortex

30 / 33

6

9

24.92

9

12

15.24

57

24

10.23

3

42

14.15

-33

45

11.23

-p -15

re

L, left; R, right; BA, Brodman area; MNI, Montreal Neuroscience Institute template; dACC, Dorsal Anterior Cingulate Gyrus

ro of

Table 2

Table 3 Post-hoc comparison of intra-network connectivity among groups MNI coordinates Regions

Side

BA

Cluster size

T value x

y

z

first-episode medication-naive MDD>HC Inferior Parietal Lobule

R

40

52

48

-33

21

4.00

dACC

R

32

109

6

3

42

5.18

Insula

R

13

12

39

-3

-12

4.00

42

36

-3.29

-48

39

-2.93

-24

48

-3.34

-24

42

-4.37

R

10/9

16

33

Inferior Parietal Lobule

L

40

16

-42

SupraMarginal Gyrus

R

2

21

54

SupraMarginal Gyrus

L

3/2/1

58

-57

DLPFC

R

10/9/46

101

DLPFC

L

9/10/46

Inferior Parietal Lobule

L

40/3/2/1

Inferior Parietal Lobule

R

superior parietal lobe

L

24

-3.64

45

-42

45

27

-3.52

250

-51

-39

48

-7.92

lP

R

ur

Insula

57

40/3/2/1/4

439

54

-27

48

-7.34

7

32

-15

-33

45

-4.69

13/45/47

389

36

6

9

7.05

na

rMDD>HC

30

re

rMDD
-p

DLPFC

ro of

first-episode medication-naive MDD
L

13

57

-33

9

12

5.90

dACC

R

32

27

6

3

42

4.24

Jo

Insula

first-episode medication-naive MDD>rMDD Inferior Parietal Lobule

R

40/3/2/1

419

54

-33

54

7.30

Inferior Parietal Lobule

L

40/3/2/1

163

-51

-36

57

5.49

superior parietal lobe

R

5/7

95

-9

-39

45

4.58

first-episode medication-naive MDD
31 / 33

insula

R

13/47/45

175

39

24

0

-5.38

Insula

L

13/45

30

-33

9

12

-4.41

DLPFC

R

10

10

33

51

12

-3.29

Abbreviations: L left, R right, HC healthy controls, first-episode MDD first-episode medication naive major depression patients, rMDD remitted depression patients, MNI, Montreal Neurological Institute. dACC, Dorsal Anterior Cingulate Gyrus. DLPFC, dorsolateral

Table 4

-p

ro of

prefrontal cortex.

Correlations between aberrant functional connectivity of CCN and cognitive

re

disturbance factor scores

Cluster

ations: L, Regions

BA,

Insula

z

13

20

48

6

9

6.13

L

13

7

-33

15

6

5.00

dACC

R

32

8

9

24

33

4.63

Inferior Parietal Lobule

L

40/2/3/1

64

-48

-42

48

7.55

R

40

79

51

-36

54

10.48

Insula

Jo

template.

y

R

ur

e Institute

T value x

Cognitive factors vs first-episode mdd

Montreal Neuroscienc

MNI coordinates

BA

na

area; MNI,

Side

size

left; R, right;

Brodman

lP

Abbrevi

Inferior Parietal Lobule

32 / 33

Table5 Correlations between aberrant functional connectivity of CCN and HAMD-17 scores MNI coordinates Regions

Side

BA

Cluster size

T value x

y

z

first-episode MDD R

13

118

48

3

9

8.03

Insula

L

13

16

-33

15

6

6.71

Supramarginal Gyrus

R

40

39

54

-21

24

7.07

DLPFC

R

10

9

49

54

21

4.05

dACC

R

32

11

6

24

27

5.10

Inferior Parietal Lobule

L

40/3/2/1

172

-51

-39

51

10.23

Inferior Parietal Lobule

R

40/2/1/3

385

60

-24

45

19.80

R

13/45/47

186

Insula

L

13

28

Inferior Parietal Lobule

R

40

Supramarginal Gyrus

L

40/2

Supramarginal Gyrus

R

dACC

R

42

6

15

14.56

-36

6

9

7.59

re

Insula

-p

remitted MDD

ro of

Insula

51

-24

21

11.64

55

-60

-21

36

9.56

lP

78

144

63

-24

36

9.65

32

12

6

9

36

6.39

na

40/2/1/3

Jo

ur

Abbreviations: L, left; R, right; BA, Brodman area; MNI, Montreal Neuroscience Institute template.

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