基于加权基因共表达网络分析识别抑郁症的差异表达基因模块

doi:10.3969/j.issn.1674-8115.2021.06.004

上海交通大学学报(医学版) ›› 2021, Vol. 41 ›› Issue (6): 724-731.doi: 10.3969/j.issn.1674-8115.2021.06.004

基于加权基因共表达网络分析识别抑郁症的差异表达基因模块

耿瑞杰¹^,²(), 姚琳³(), 黄欣欣², 禹顺英², 苑成梅², 洪武², 吕钦谕², 王庆中⁴, 易正辉²(), 方贻儒²^,⁵^,⁶

^1.复旦大学附属中山医院心理医学科，上海 200032
^2.上海交通大学医学院附属精神卫生中心精神科，上海 200030
^3.上海市浦东新区南汇精神卫生中心精神科，上海 201399
^4.上海中医药大学中药研究所神经药理实验室，上海 201203
^5.中国科学院脑科学与智能技术卓越创新中心，上海 200031
^6.上海市重性精神病重点实验室，上海 201108

出版日期:2021-06-28 发布日期:2021-06-29
通讯作者: 姚琳,易正辉 E-mail:geng.ruijie@zs-hospital.sh.cn;yl950919@163.com;yizhenghui1971@163.com
作者简介:耿瑞杰(1992—)，女，住院医师，硕士；电子信箱：geng.ruijie@zs-hospital.sh.cn。
基金资助:
国家重点研发计划(2016YFC1307100);国家自然科学基金(81930033);上海交通大学遗传发育与精神神经疾病教育部重点实验室开放课题(2019GDND02);上海市浦东新区卫生系统重点专科建设资助项目(PWZzk2017-27);上海市卫生和计划生育委员会青年项目(20164Y0209)

Identification of differentially expressed gene modules in major depressive disorder based on weighted gene co-expression network analysis

Rui-jie GENG¹^,²(), Lin YAO³(), Xin-xin HUANG², Shun-ying YU², Cheng-mei YUAN², Wu HONG², Qin-yu LÜ², Qing-zhong WANG⁴, Zheng-hui YI²(), Yi-ru FANG²^,⁵^,⁶

^1.Department of Psychological Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
^2.Department of Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
^3.Department of Psychiatry, Nanhui Mental Health Center, Pudong New Area, Shanghai 201399, China
^4.Neuropharmacology Laboratory, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
^5.CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai 200031, China
^6.Shanghai Key Laboratory of Psychotic Disorders, Shanghai 201108, China

Online:2021-06-28 Published:2021-06-29
Contact: Lin YAO,Zheng-hui YI E-mail:geng.ruijie@zs-hospital.sh.cn;yl950919@163.com;yizhenghui1971@163.com
Supported by:
National Key R&D Program of China(2016YFC1307100);National Natural Science Foundation of China(81930033);Open Project of Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University(2019GDND02);Key Specialty Construction Project of Pudong Health and Family Planning Commission of Shanghai(PWZzk2017-27);Youth Program of Shanghai Health and Family Planning Commission(20164Y0209)

摘要/Abstract

摘要：

目的·采用加权基因共表达网络分析（weighted gene co-expression network analysis，WGCNA）探索抑郁症相关的差异基因模块及其枢纽基因，并对差异基因模块进行生物功能注释。方法·在之前对8例抑郁症患者及8名健康对照者（对照组）的外周血mRNA微阵列分析实验的基础上，应用t检验筛选抑郁症患者与对照组的差异表达基因，通过R软件WGCNA包进行分析；当关联系数阈值设定为0.9时，参数β=14，以此构建基因数据集的共表达网络。应用混合动态树切割方法切割网络产生基因模块。采用Pearson相关性检验评估基因模块和抑郁症之间的相关性，分别选取与抑郁症正相关性和负相关性最强的基因模块，并选择模块内连接性最强的前3个基因作为枢纽基因。最后利用GO功能富集分析和KEGG通路分析对2个模块进行功能注释。结果·从16个样品中获得4 125个差异表达基因，从中识别出9个基因模块，选择蓝色（blue）模块（R=－0.91，P=0.000）和青色（cyan）模块（R=0.76，P=0.000）进行后续研究。Blue模块的枢纽基因为JAM2（junctional adhesion molecule 2）、SCRN2（secernin 2）和IGHV7-81（immunoglobulin heavy variable 7-81）；cyan模块的枢纽基因为SCFD2（Sec1 family domain containing 2）、NR5A2（nuclear receptor subfamily 5 group A member 2）和KCNMA1（potassium calcium-activated channel subfamily M alpha 1）。生物功能注释发现，cyan模块的基因主要富集在胚胎发育、细胞生长、免疫及炎症等生物学过程，blue模块基因则主要在物质加工转运及感染等方面富集。结论·得到2个外周血mRNA基因模块和6个枢纽基因（JAM2、SCRN2、IGHV7-81、SCFD2、NR5A2和KCNMA1），可能与抑郁症显著相关；这2个基因模块可能在胚胎发育、免疫和炎症反应、物质加工转运等方面发挥作用。

关键词: 抑郁症, 加权基因共表达网络分析, 差异表达基因, 枢纽基因

Abstract:

Objective·To explore the differential gene modules and hub genes of major depressive disorder (MDD) by weighted gene co-expression network analysis (WGCNA), and annotate the biological functions of the differential gene modules.

Methods·Based on the previous experiment of peripheral blood mRNA microarray analysis of 8 MDD patients and 8 healthy controls (control group), t-test statistical method was used to screen the differentially expressed genes between MDD and the control group. WGCNA package in R software was used to analyze the weighted gene co-expression network. The correlation coefficient threshold was set to 0.9 with β =14 to construct the co-expression network of the gene dataset. The hybrid dynamic tree cutting method was used to cut the network to generate gene modules. Pearson correlation test was used to evaluate the correlation between gene modules and MDD. The gene modules with the strongest positive correlation and the strongest negative correlation with depression were selected respectively, and the top three genes with the highest connectivity in the modules were defined as hub genes. Finally, GO functional enrichment analysis and KEGG pathway analysis were used to annotate the functions of the two modules.

Results·A total of 4 125 differentially expressed genes were obtained from 16 samples, and 9 gene modules were identified. The blue module (R=-0.91, P=0.000) and the cyan module (R=0.76, P=0.000) were selected for further study. The hub genes of blue module were JAM2 (junctional adhesion molecule 2), SCRN2 (secernin 2) and IGHV7-81 (immunoglobulin heavy variable 7-81). The hub genes of cyan module were SCFD2 (Sec1 family domain containing 2), NR5A2 (nuclear receptor subfamily 5 group A member 2) and KCNMA1 (potassium calcium-activated channel subfamily M alpha 1). It was found in the annotation of biological function that the genes of the cyan module were mainly enriched in the embryo development, cell growth and immune and inflammatory response, while the genes of the blue module were mainly enriched in material processing and transport and infection.

Conclusion·Two peripheral blood mRNA gene modules and six hub genes (JAM2, SCRN2, IGHV7-81, SCFD2, NR5A2 and KCNMA1) may be significantly associated with MDD. These two gene modules may play a role in the embryonic development, immune and inflammatory response, and material processing and transportation.

Key words: major depressive disorder (MDD), weighted gene co-expression network analysis (WGCNA), differentially expressed gene (DEG), hub gene

中图分类号:

R749.4

耿瑞杰, 姚琳, 黄欣欣, 禹顺英, 苑成梅, 洪武, 吕钦谕, 王庆中, 易正辉, 方贻儒. 基于加权基因共表达网络分析识别抑郁症的差异表达基因模块[J]. 上海交通大学学报(医学版), 2021, 41(6): 724-731.

Rui-jie GENG, Lin YAO, Xin-xin HUANG, Shun-ying YU, Cheng-mei YUAN, Wu HONG, Qin-yu LÜ, Qing-zhong WANG, Zheng-hui YI, Yi-ru FANG. Identification of differentially expressed gene modules in major depressive disorder based on weighted gene co-expression network analysis[J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(6): 724-731.

图/表 5

图1 基因聚类树Note:A total of 9 modules were obtained, which are represented by 9 different colors, and gray represents the genes that could not be incorporated into any of the modules.

Fig 1 Dendrogram of gene clustering

图2 9个基因模块的ME与抑郁症的关联图Note:The ribbon above represents 9 MEs. The color blocks in the middle represent the correlation between ME and depression; blue represents the negative correlation, and red represents the positive correlation; the values are the correlation coefficients (P values).

Fig 2 The association between 9 MEs of gene modules and depression

图3 Blue模块的基因相互作用网络Note:The genes in the figure are those with the top 50 kWithin values in the blue module, and the red dots represent the hub genes (top 3 kWithin values).

Fig 3 Gene interaction network of the blue module

图4 Cyan模块基因相互作用网络Note:The genes in the figure are those with the top 50 kWithin values in the cyan module, and the red dots represent the hub genes (top 3 kWithin values).

Fig 4 Gene interaction network of the cyan module

图5 Blue模块和cyan模块的生物注释Note:A. Blue module. B. Cyan module.

Fig 5 Biological annotation of blue module and cyan module

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基于加权基因共表达网络分析识别抑郁症的差异表达基因模块

Identification of differentially expressed gene modules in major depressive disorder based on weighted gene co-expression network analysis

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