Biomarkers of COVID-19 severity may not serve patients with polycystic ovary syndrome

In a cohort of patients with differing severity of COVID-19 disease, including non-survivors, plasma proteomic analysis identified biomarkers of COVID-19 disease progression [1]. The top pathways identified by Shu et al. were those of platelet degranulation and the complement and coagulation cascades [1]. These identified pathways were complementary to another recent study comparing COVID-19 disease and control subjects, where proteomic panels also identified biological pathways involved in platelet degranulation and the coagulation cascade [2]. Whilst the comparison with absolute disease-free normality is relevant, an increasing proportion of the population have insulin resistant states with associated metabolic conditions; an example of such a metabolic condition is polycystic ovary syndrome (PCOS) where it has been shown that protein expression patterns may differ compared to those without PCOS [3]. Notably, in PCOS, platelet aggregation enhancement together with aberrant diminished plasma fibrinolytic activity potentially giving rise to enhanced thrombosis has been described [4, 5], with markers of coagulation being enhanced [6].

For a protein biomarker to be of value, there needs to be a clear discrimination between normal and disease condition levels. Therefore, platelet degranulation and the complement and coagulation cascade proteomic analysis was performed in women with and without PCOS to compare with these pathways described in COVID-19 disease [1].

243 subjects (146 PCOS and 97 control women) were recruited to the local PCOS biobank (ISRCTN70196169) [3] in the Department of Endocrinology, Hull and East Yorkshire Hospitals NHS Trust. The Rotterdam consensus diagnostic criteria were used to diagnose PCOS. Proteins that were described for platelet degranulation (18 of 27 proteins) and the complement and coagulation cascades (16 of 19 proteins) [1] were measured using the Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement [7], shown in Table 1. Statistics were performed using Graphpad Prism 8.0.

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Published in: Journal of Translational Medicine
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1186/s12967-021-02723-7