Identification of early onset pre-eclampsia related key genes via bioinformatic analysis

Zhengrui Huang; Ruiping Chen; Yixuan Zhou; Yiling Wei; Haixia Liu; Ping Zhang; Jingyun Wang; Yuzhen Ding; Xiaofeng Yang; Lu Sun; Meiting Shi; Yudie Gao; Ruiman Li

Informatics in Medicine Unlocked (Jan 2022)

Identification of early onset pre-eclampsia related key genes via bioinformatic analysis

Zhengrui Huang,
Ruiping Chen,
Yixuan Zhou,
Yiling Wei,
Haixia Liu,
Ping Zhang,
Jingyun Wang,
Yuzhen Ding,
Xiaofeng Yang,
Lu Sun,
Meiting Shi,
Yudie Gao,
Ruiman Li

Affiliations

Zhengrui Huang: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; International Joint Laboratory for Embryonic Development & Prenatal Medicine, Division of Histology and Embryology, Medical College, Jinan University, Guangzhou, 510632, China
Ruiping Chen: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
Yixuan Zhou: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
Yiling Wei: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
Haixia Liu: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
Ping Zhang: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; International Joint Laboratory for Embryonic Development & Prenatal Medicine, Division of Histology and Embryology, Medical College, Jinan University, Guangzhou, 510632, China
Jingyun Wang: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; International Joint Laboratory for Embryonic Development & Prenatal Medicine, Division of Histology and Embryology, Medical College, Jinan University, Guangzhou, 510632, China
Yuzhen Ding: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; International Joint Laboratory for Embryonic Development & Prenatal Medicine, Division of Histology and Embryology, Medical College, Jinan University, Guangzhou, 510632, China
Xiaofeng Yang: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; International Joint Laboratory for Embryonic Development & Prenatal Medicine, Division of Histology and Embryology, Medical College, Jinan University, Guangzhou, 510632, China
Lu Sun: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; International Joint Laboratory for Embryonic Development & Prenatal Medicine, Division of Histology and Embryology, Medical College, Jinan University, Guangzhou, 510632, China
Meiting Shi: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; International Joint Laboratory for Embryonic Development & Prenatal Medicine, Division of Histology and Embryology, Medical College, Jinan University, Guangzhou, 510632, China
Yudie Gao: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
Ruiman Li: Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China; Corresponding author. Department of Obstetrics and Gynecology, The First Affiliated Hospital of Jinan University, No. 613, Huangpu Road west, Tianhe district, Guangzhou, Guangdong, China.

Journal volume & issue: Vol. 31
p. 100914

Abstract

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Background: Pre-eclampsia is a common pregnancy-specific disease. In this study, we used comprehensive bioinformatics to screen key genes related to the development of pre-eclampsia and explore their potential connections. Methods: Two data sets GSE44711 and GSE30186 from the GEO database were used. The experimental group data set GSE44711 includes 16 samples (8 normal group samples and 8 early-onset PE group samples); the validation group data set GSE30186 includes 12 samples (6 Samples from the normal group and 6 samples from the PE group). Use the limma R package to analyze the difference between the two data sets, perform enrichment analysis, GO and KEGG analysis on the experimental group data set GSE44711, then obtain the hub gene by cytoscape, and verify the Hub gene in the validation data set GES30186. Results: 826 DEGs were identified from GSE44711, including 458 up-regulated genes and 368 down-regulated genes; The 6 Hub genes (CXCR6, CD3D, CD8A, CD69, and IL5) identified are considered to have high credibility. Conclusion: Through our analysis, the functional difference between early onset preeclampsia and normal pregnancy patients was explained, and the Hub genes CXCR6, CD3D, CD8A, CD69 and IL5 were determined.

Published in Informatics in Medicine Unlocked

ISSN: 2352-9148 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics
Website: https://www.journals.elsevier.com/informatics-in-medicine-unlocked/

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