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Dear Colleagues,

We are pleased to announce that the REST-meta-MDD data entered unrestricted sharing phase since January 1, 2020. The researchers can perform any analyses of interest while not violating ethics.

Major Depressive Disorder (MDD) is the second leading-cause of disability world-wide, with point prevalence exceeding 4% (1). The pathophysiology of MDD remains unknown despite intensive efforts, including neuroimaging studies. However, the small sample size of most MDD neuroimaging studies entails low sensitivity and reliability (2, 3).

Inconsistencies may reflect limited statistical power (2) from small samples, but data analysis flexibility may also contribute, as a large number of preprocessing and analysis operations with many different parameter combinations have been used in fMRI analyses (4). MDD studies have used diverse multiple comparison correction methods, most likely inadequate (5). Data analysis flexibility also impedes large-scale meta-analysis (6, 7). Moreover, clinical characteristics such as number and type of episodes, medication status and illness duration vary across studies, further contributing to heterogeneous results.

To address limited statistical power and analytic heterogeneity, we initiated the REST-meta-MDD Project. We implemented a standardized preprocessing protocol on Data Processing Assistant for Resting-State fMRI (DPARSF) (8) at local sites with only final indices provided to the consortium (please see the SI Appendix, Supplementary Methods of the original PNAS paper for details).

Contributions were requested from users of DPARSF, a MATLAB- and SPM-based R-fMRI preprocessing pipeline (8). Twenty-five research groups from 17 hospitals in China formed the REST-meta-MDD consortium and agreed to share final R-fMRI indices from patients with MDD and matched normal controls (see Supplementary Table; henceforth “site” refers to each cohort for convenience) from studies approved by local Institutional Review Boards. The consortium contributed 2428 previously collected datasets (1300 MDDs and 1128 NCs). On average, each site contributed 52.0±52.4 patients with MDD (range 13-282) and 45.1±46.9 NCs (range 6-251). Most MDD patients were female (826 vs. 474 males), as expected. The 562 patients with first episode MDD included 318 first episode drug-naïve (FEDN) MDD and 160 scanned while receiving antidepressants (medication status unavailable for 84). Of 282 with recurrent MDD, 121 were scanned while receiving antidepressants and 76 were not being treated with medication (medication status unavailable for 85). Episodicity (first or recurrent) and medication status were unavailable for 456 patients.

To improve transparency and reproducibility, our analysis code has been openly shared at https://github.com/Chaogan-Yan/PaperScripts/tree/master/Yan_2019_PNAS. In addition, we would like to share the R-fMRI indices of the 1300 MDD patients and 1128 NCs through the R-fMRI Maps Project ( http://rfmri.org/REST-meta-MDD). These data derivatives will allow replication, secondary analyses and discovery efforts while protecting participant privacy and confidentiality.

According to the agreement of the REST-meta-MDD consortium, there would be 2 phases for sharing the brain imaging data and phenotypic data of the 1300 MDD patients and 1128 NCs. *1) Phase 1: coordinated sharing, before January 1, 2020.* To reduce conflict of the researchers, the consortium will review and coordinate the proposals submitted by interested researchers. The interested researchers first send a letter of intent to rfmrilab@gmail.com. Then the consortium will send all the approved proposals to the applicant. The applicant should submit a new innovative proposal while avoiding conflict with approved proposals. This proposal would be reviewed and approved by the consortium if no conflict. Once approved, this proposal would enter the pool of approved proposals and prevent future conflict. *2) Phase 2: unrestricted sharing, after January 1, 2020.* The researchers can perform any analyses of interest while not violating ethics.

The REST-meta-MDD data entered unrestricted sharing phase since January 1, 2020. The researchers can perform any analyses of interest while not violating ethics. Please sign the Data Use Agreement http://rfmri.org/sites/default/files/REST-meta-MDD_Data_Use_Agreement.pdf and email the scanned signed copy to rfmrilab@gmail.com to get access credentials of the REST-meta-MDD data on the FTP server.

http://rfmri.org/sites/default/files/REST-meta-MDD_Data_Use_Agreement.pdf

*ACKNOWLEDGEMENTS*

This work was supported by the National Key R&D Program of China (2017YFC1309902), the National Natural Science Foundation of China (81671774, 81630031, 81471740 and 81371488), the Hundred Talents Program and the 13th Five-year Informatization Plan (XXH13505) of Chinese Academy of Sciences, Beijing Municipal Science & Technology Commission (Z161100000216152, Z171100000117016, Z161100002616023 and Z171100000117012), Department of Science and Technology, Zhejiang Province (2015C03037) and the National Basic Research (973) Program (2015CB351702).

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*Supplementary Table. *Samples of the REST-meta-MDD project, consortium sites, contributors, sample size, data acquisition parameters, and published studies based on the present cohorts.

Serial Number

Sites (cohorts)

Principal investigators

Data organizer

N

Scanner

Receive (coil)

TR (ms)

TE (ms)

Flip Angle (∘)

Thickness/gap

Slice number

Time points

Voxel size

FOV

Published researches

MDD

NC

1

National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & Key Laboratory of Mental Health, Ministry of Health (Peking University)

Tian-Mei Si

Li Wang

74

74

Siemens Tim Trio 3T

32 channel

2000

30

90

4.0mm/0.8mm

30

210

3.28 × 3.28 × 4.80

210 × 210

Wang et al 2013 (9)/2015 (10)

2

Department of Clinical Psychology, Suzhou Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University

Yan-Song Liu

Yan-Song Liu

30

30

Philips Achieva 3T

8-channel

2000

30

90

4.0mm/0 mm

37

200

1.67 × 1.67 × 4.00

240 × 240

Liu et al., 2017 (11)

3

The Second Xiangya Hospital of Central South University

Shu-Qiao Yao / Xiang Wang

Chang Cheng

27

37

Siemens Magnetom Symphony scanner 1.5 T

16 channel

2000

40

90

5.0mm/1.25mm

26

150

3.75 × 3.75 × 6.25

240 × 240

Zhu et al., 2012 (12)

4

The Second Xiangya Hospital of Central South University

Wen-Bin Guo

Wen-Bin Guo

24

24

Siemens Skyra 3T

32 channel

2500

25

90

3.5mm/0mm

39

200

3.75 × 3.75 × 3.50

240 × 240

Guo et al., 2014 (13)/2017(14)

5

Department of Psychiatry, Shanghai Jiao Tong University School of Medicine

Yi-Ru Fang / Dai-Hui Peng

Ru-Bai Zhou

13

11

GE Signa 3T

32 channel

3000

30

90

5.0mm/0mm

22

100

3.75 × 3.75 × 5.00

240 × 240

Peng et al., 2014 (15)/2015 (16)

6

Department of Psychiatry, Shanghai Jiao Tong University School of Medicine

Yi-Ru Fang / Jun-Juan Zhu

Ru-Bai Zhou

15

15

Siemens Tim Trio 3T

32 channel

2000

30

70

4mm/0mm

33

180

3.59 × 3.59 × 4.00

230 × 230

Zhu et al., 2014 (17)

7

Sir Run Run Shaw Hospital, Zhejiang University School of Medicine

Wei Chen

Jia-Shu Yao

38

49

GE discovery MR750

8 channel

2000

30

90

3.2/0

37

184

2.29 × 2.29 × 3.20

220 × 220

Shen et al., 2015 (18)

8

Department of Psychiatry, First Affiliated Hospital, China Medical University

Fei Wang

Jia Duan

75

75

GE Signa 3T

8 channel

2000

30

90

3.0mm/0mm

35

200

3.75 × 3.75 × 3.00

240 × 240

Tang et al., 2013 (19)

9

The First Affiliated Hospital of Jinan University

Ying Wang

Guan-Mao Chen

50

50

GE Discovery MR750 3.0T

8-channel

2000

25

90

3.0/1.0 mm

35

200

3.75 × 3.75 × 4.00

240 × 240

N/A

10

First Hospital of Shanxi Medical University

Ke-Rang Zhang

Ai-Xia Zhang

50

33

Siemens Tim Trio 3T

32 channel

2000

30

90

3.0mm/1.52mm

32

212

3.75 × 3.75 × 4.52

240 × 240

Li et al., 2014 (20)

11

Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University

Qing-Hua Luo / Hua-Qing Meng

Hai-Tang Qiu

32

29

GE Signa 3T

8 channel

2000

30

90

5 mm

33

200

3.75 × 3.75 × 5.00

240 × 240

Du et al., 2016 (21)

12

Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University

Hua-Qing Meng / Qing-Hua Luo

Hai-Tang Qiu

32

6

GE Signa 3T

8 channel

2000

30

90

5 mm

33

240

3.75 × 3.75 × 4.00

240 × 240

N/A

13

The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an Central Hospital

Jian Yang / Xiao-Ping Wu

Hong Zhang

25

17

GE Excite 1.5T

16 channel

2500

35

90

4mm/0

36

150

4.00 × 4.00 × 4.00

256 × 256

Wu et al., 2016 (22)

14

The Second Xiangya Hospital of Central South University

Guang-Rong Xie

Xi-Long Cui

64

32

Siemens Tim Trio 3T

32 channel

2500

25

90

3.5/0

39

200

3.75 × 3.75 × 3.50

240 × 240

Yang et al., 2017 (23)

15

Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Southeast University

Yong-Gui Yuan

Zheng-Hua Hou / Ying-ying Yin

50

50

Siemens Verio 3.0T MRI

12 channel

2000

25

90

4mm/0mm

36

240

3.75 × 3.75 × 4.00

240 × 240

Hou et al., 2018 (24)/2018 (25)

16

Huaxi MR Research Center, West China Hospital of Sichuan University

Qi-Yong Gong / Kai-Ming Li

Kai-Ming Li

31

31

GE Signa 3T

8 channel

2000

30

90

5mm/0mm

30

200

3.75 × 3.75 × 5.00

240 × 240

Chen et al., 2017 (26)

17

Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University

Li Kuang

Lan Hu

47

44

GE Signa 3T

8 channel

2000

40

90

4.0mm/0mm

33

240

3.75 × 3.75 × 4.00

240 × 240

Cao et al., 2016 (27)

18

Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University

Hong Yang

Yu-Shu Shi / Hai-Yan Xie

21

20

Philips Achieva 3.0 T scanner (Philips Healthcare, Netherlands)

8-channel SENSE head coil

2000

35

90

5.0/1.0 mm

24

200

1.67 × 1.67 × 6.00

240 × 240

N/A

19

Anhui Medical University

Kai Wang

Tong-Jian Bai

51

36

GE Signa 3T

8 channel

2000

22.5

30

4.0/0.6 mm

33

240

3.44 × 3.44 × 4.60

220 × 220

Wang et al., 2017 (28)

20

Faculty of Psychology, Southwest University

Jiang Qiu

Xin-Ran Wu

282

251

Siemens Tim Trio 3T

12 channel

2000

30

90

3.0mm/1.0mm

32

242

3.44 × 3.44 × 4.00

220 × 220

Cheng et al., 2016 (29)/Ye et al., 2015 (30)/Luo et al., 2015 (31)/Xue et al., 2016 (32)

21

Beijing Anding Hospital, Capital Medical University

Chuan-Yue Wang

Qi-Jing Bo / Feng Li

86

70

Siemens Tim Trio 3T

32 channel

2000

30ms

90

3.5mm/0.7mm

33

240

3.12 × 3.12 × 4.20

200 × 200

Zheng et al., 2018 (33)/Jing et al., 2013 (34)

22

The Institute of Mental Health, Second Xiangya Hospital of Central South University

Zhe-Ning Liu

Yi-Cheng Long

30

20

Philips Gyroscan Achieva 3.0T

32 channel

2000

30

90

4.0mm/0mm

36

250

1.67 × 1.67 × 4.00

240 × 240

N/A

23

Mental Health Center, West China Hospital, Sichuan University

Tao Li

Yi-Ting Zhou

32

30

Philips Achieva 3.0T TX

8 channal

2000

30

90

4.0mm/0mm

38

240

3.75 × 3.75 × 4.00

240 × 240

Yang et al., 2015 (35)

24

First Affiliated Hospital of Kunming Medical University

Xiu-Feng Xu / Yu-Qi Cheng

Chao-Jie Zou

32

31

GE Signa 1.5T

8 channel

2000

40

90

5/1mm

24

160

3.75 × 3.75 × 6.00

240 × 240

Cheng., et al. 2017 (36)

25

Department of Neurology, Affiliated ZhongDa Hospital of Southeast University

Zhi-Jun Zhang

Zhi-Jun Zhang

89

63

Siemens Verio 3T

12 channel head coil

2000

25

90

4.0mm/0mm

36

240

3.75 × 3.75 × 4.00

240 × 240

Yuan et al., 2008 (37)

Total

1300

1128

Abbreviations: MDD, major depressive disorder; NC, normal control.

*(Note: Part of the content of this post was adapted from the original REST-meta-MDD PNAS paper (http://www.pnas.org/cgi/doi/10.1073/pnas.1900390116 http://www.pnas.org/cgi/doi/10.1073/pnas.1900390116) under CC BY-NC-ND license.)*

Best,

Chao-Gan

-- Chao-Gan YAN, Ph.D. Professor, Principal Investigator Director, International Big-Data Center for Depression Research Deputy Director, Magnetic Resonance Imaging Research Center Institute of Psychology, Chinese Academy of Sciences 16 Lincui Road, Chaoyang District, Beijing 100101, China - Initiator DPABI http://rfmri.org/DPABI, http://dpabi.org/DPARSF http://rfmri.org/DPARSF, PRN http://rfmri.org/PRN and The R-fMRI Network http://rfmri.org/ (RFMRI.ORG http://rfmri.org/) http://rfmri.org/yan http://scholar.google.com/citations?user=lJQ9B58AAAAJ