Low progesterone levels and their role in the co-existence of polycystic ovary syndrome and rheumatoid arthritis: a comprehensive analysis among Iraqi patient.

Abstract

Polycystic ovarian syndrome (PCOS) is a low-grade and chronic inflammation defined by irregular hormonal status that primarily triggers females in their reproductive age. Multi cysts are a primary manifestation of PCOS; a high level of androgen production characterizes the condition via ovaries. Rheumatoid arthritis (RA) is a chronic, systemic, and symmetrical inflammatory autoimmune disease that affects 1-2% of adults. Females are more likely to generate RA. During the inflammatory activity, immune cells attack the synovium and the synovial space. This invasion is essential in releasing many cytokines in the synovial and joint spaces, leading to joint damage and pain, stiffens, heat, and tenderness in the joint. To evaluate the strength of the link between PCOS and RA, the cross-sectional study examined hormonal, metabolic, and autoantibodies in PCOS, RA as a positive control and the study groups. Statistical analysis Shapiro-Wilk test, student t-test, one-way ANOVA, and multi-linear regression analysis were used to evaluate the results. The data highlights significant values for the BMI, WHR, and hirsutism of PCOS and RA groups in comparison to the negative control. The ANOVA results of these parameters also showed a significant p<0.05 among the groups. According to the negative control, the levels of insulin, HOMA-IR, testosterone, LH, estradiol, and CRP showed a substantial increase in the PCOS group. Also, the RA group showed a significant p<0.05 rise in CRP, RF, and Ani-CCP, and the ANOVA results showed significant value among the groups under investigation. Progesterone D as a model showed a correlation with Anti-CCP B, RF C, Anti-CCP C, CRP D, RF D, and Anti-CCP D with the highest level of f² between other models. In addition, statistical tests show that progesterone D with R²=0.565 and RMSE equal to 0.996 have heteroscedasticity, which means that low levels of progesterone are associated inversely with high levels of RF and Anit-CCP. There is a relative association between the progesterone D model and corresponding predictions. Regardless of solid f², only 56% of the sample shows an association between the model and predictors; this relation may differ if we consider the study's limitations.