A Data-Driven Review of the Genetic Factors of Pregnancy Complications
by
Yury A. Barbitoff 1,2,3,†
, Alexander A. Tsarev 1,4,†, Elena S. Vashukova 3, Evgeniia M. Maksiutenko 2,5, Liudmila V. Kovalenko 6, Larisa D. Belotserkovtseva 7 and Andrey S. Glotov 3,8,*
Yury A. Barbitoff 1,2,3,†, Alexander A. Tsarev 1,4,†, Elena S. Vashukova 3, Evgeniia M. Maksiutenko 2,5, Liudmila V. Kovalenko 6, Larisa D. Belotserkovtseva 7 and Andrey S. Glotov 3,8,*
1
Bioinformatics Institute, 197342 St. Petersburg, Russia
2
Department of Genetics and Biotechnology, Saint-Petersburg State University, 199034 St. Petersburg, Russia
3
Department of Genomic Medicine, D.O.Ott Research Institute for Obstetrics, Gynaecology and Reproductology, 199034 St. Petersburg, Russia
4
Department of Biochemistry, Saint-Petersburg State University, 199034 St. Petersburg, Russia
5
St. Petersburg Branch, Vavilov Institute of General Genetics, Russian Academy of Sciences, 199034 St. Petersburg, Russia
6
Department of Pathology, Medical Institute, Surgut State University, 628416 Surgut, Russia
7
Department of Obstetrics, Gynecology and Perinatology, Medical Institute, Surgut State University, 628416 Surgut, Russia
8
Laboratory of Biobanking and Genomic Medicine, Saint-Petersburg State University, 199034 St. Petersburg, Russia
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Mol. Sci. 2020, 21(9), 3384; https://doi.org/10.3390/ijms21093384
Received: 18 April 2020 / Revised: 5 May 2020 / Accepted: 6 May 2020 / Published: 11 May 2020
(This article belongs to the Special Issue OMICs, Data Integration, and Applications in Personalized Medicine)
Over the recent years, many advances have been made in the research of the genetic factors of pregnancy complications. In this work, we use publicly available data repositories, such as the National Human Genome Research Institute GWAS Catalog, HuGE Navigator, and the UK Biobank genetic and phenotypic dataset to gain insights into molecular pathways and individual genes behind a set of pregnancy-related traits, including the most studied ones—preeclampsia, gestational diabetes, preterm birth, and placental abruption. Using both HuGE and GWAS Catalog data, we confirm that immune system and, in particular, T-cell related pathways are one of the most important drivers of pregnancy-related traits. Pathway analysis of the data reveals that cell adhesion and matrisome-related genes are also commonly involved in pregnancy pathologies. We also find a large role of metabolic factors that affect not only gestational diabetes, but also the other traits. These shared metabolic genes include IGF2, PPARG, and NOS3. We further discover that the published genetic associations are poorly replicated in the independent UK Biobank cohort. Nevertheless, we find novel genome-wide associations with pregnancy-related traits for the FBLN7, STK32B, and ACTR3B genes, and replicate the effects of the KAZN and TLE1 genes, with the latter being the only gene identified across all data resources. Overall, our analysis highlights central molecular pathways for pregnancy-related traits, and suggests a need to use more accurate and sophisticated association analysis strategies to robustly identify genetic risk factors for pregnancy complications.
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Keywords:
pregnancy complications; genome-wide association study; gestational diabetes; preeclampsia; preterm birth; placental abruption; genetic variant
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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MDPI and ACS Style
Barbitoff, Y.A.; Tsarev, A.A.; Vashukova, E.S.; Maksiutenko, E.M.; Kovalenko, L.V.; Belotserkovtseva, L.D.; Glotov, A.S. A Data-Driven Review of the Genetic Factors of Pregnancy Complications. Int. J. Mol. Sci. 2020, 21, 3384.
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