Combination of Genetic Markers and Age Effectively Facilitates the Identification of People with High Risk of Preeclampsia in the Han Chinese Population. (19th July 2018)

• Record Type: Journal Article
• Authors: Zhou, Lu; Hui, Xinjie; Yuan, Huijuan; Liu, Yinglin; Wang, Yejun
• Other Names: Xiong Momiao Academic Editor.
• Is Part Of: BioMed research international. Volume 2018(2018)
• Publication Date: 2018-07-19
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2018/4808046
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Objective . This study aimed to analyze the possible association between known genetic risks and preeclampsia in a Han Chinese population. Methods . A total of 156 patients with preeclampsia and 286 healthy Han Chinese women were enrolled and genotyped for 27 genetic alleles associated with preeclampsia in different populations. The association between the genotypes of the individual alleles and preeclampsia and the possible interaction among the alleles were analyzed. Finally logistic models were trained with the genotypes of possible alleles contributing to preeclampsia. Results . Seven alleles were significantly or marginally significantly associated with preeclampsia, which involved six genes (rs4762 in AGT, rs1800896 in IL-10, rs1800629 and rs1799724 in TNF α, rs2070744 in NOS3, rs7412 in APOE, and rs2549782 in ERAP2 ). A multilocus interaction analysis further disclosed an interaction among seven alleles. A logistic model showing individual or synergetic contribution to preeclampsia could reach ~0.67 preeclampsia prediction accuracy in the Han Chinese population, while integration of age information could improve the performance to ~0.75 accuracy using a fivefold training-testing evaluation strategy. Conclusions . The genetic factors were closely associated with preeclampsia in the Han Chinese population despite large ethnicity heterogeneity. The genotypes of different alleles also had synergetic interactions.