Arffman, R.K., Saraswat, M., Joenväärä, S. et al. Thromboinflammatory changes in plasma proteome of pregnant women with PCOS detected by quantitative label-free proteomics. Sci Rep 9, 17578 (2019). https://doi.org/10.1038/s41598-019-54067-4
Thromboinflammatory changes in plasma proteome of pregnant women with PCOS detected by quantitative label-free proteomics
|Author:||Arffman, R. K.1; Saraswat, M.2,3; Joenväärä, S.2,3;|
1Department of Obstetrics and Gynecology, PEDEGO Research Unit, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland
2Transplantation Laboratory, Haartman Institute, University of Helsinki, Helsinki, Finland
3HUSLAB, Helsinki University Hospital, Helsinki, Finland
4Department of Reproductive biology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, 110029, India
5Department for Women’s and Children’s Health, Uppsala University, Uppsala, Sweden
|Online Access:||PDF Full Text (PDF, 3.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202002125188
|Publish Date:|| 2020-02-12
Polycystic ovary syndrome (PCOS) is the most common endocrinological disorder of fertile-aged women. Several adverse pregnancy outcomes and abnormalities of the placenta have been associated with PCOS. By using quantitative label-free proteomics we investigated whether changes in the plasma proteome of pregnant women with PCOS could elucidate the mechanisms behind the pathologies observed in PCOS pregnancies. A total of 169 proteins with ≥2 unique peptides were detected to be differentially expressed between women with PCOS (n = 7) and matched controls (n = 20) at term of pregnancy, out of which 35 were significant (p-value < 0.05). A pathway analysis revealed that networks related to humoral immune responses, inflammatory responses, cardiovascular disease and cellular growth and proliferation were affected by PCOS. Classification of cases and controls was carried out using principal component analysis, orthogonal projections on latent structure-discriminant analysis (OPLS-DA), hierarchical clustering, self-organising maps and ROC-curve analysis. The most significantly enriched proteins in PCOS were properdin and insulin-like growth factor II. In the dataset, properdin had the best predictive accuracy for PCOS (AUC = 1). Additionally, properdin abundances correlated with AMH levels in pregnant women.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
3123 Gynaecology and paediatrics
The work was supported by the Sigrid Juselius Foundation, Academy of Finland, Finnish Medical Foundation and the Northern Osthrobothnia Regional Fund.
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