## 1 Introduction  
Endometriosis is commonly known as a chronic condition that has been characterized by the growth of endometrial tissue in sites other than the endometrium [1]. This may result in the abnormal growth of endometrial cells outside the uterus and cause a painful condition. According to NHS-UK, symptoms include severe pelvic pain during periods, sex, urination and defacation. Major symptoms could be constipation, diarrhea, and even blood during urination. Women also face difficulties in getting pregnant ([[https://www.nhs.uk/conditions/endometriosis/](https://www.nhs.uk/conditions/endometriosis/)]([https://www.nhs.uk/conditions/endometriosis/](https://www.nhs.uk/conditions/endometriosis/)), accessed on 20 July 2020). After several years of research, the pathogenesis of endometriosis is still not clear [2]. The existence of endometriosis has been found from Mullerian or non-Mullerian stem cells, which may include those from bone marrow, the endometrial basal layer, the peritoneum, or Mullerian remnants [3]. In addition, scientists believe that dysregulation of the canonical Wnt/\(\beta\)-signaling pathway could be responsible for the endometricl lesions leading to the endometriosis condition [2]. Wnt/\(\beta\)-catenin signaling also has a role in governing the endometrial cells regulated by estrogen and progesterone. Any changes in the expression of estrogen and progesterone receptors may cause progesterone resistance in endometriosis patients [4]. Infertility problems may be caused due to recurrent pregnancy loss which has been found a major issue in endometriosis patients. Indeed, the loss of two or more pregnancies has also been reported by the European Society of Human Reproduction and Embryology Recurrent Pregnancy Loss (RPL) [5], where ectopic pregnancy and molar pregnancy has been excluded. Endometrosis-associated infertility could be identified by potential markers, such as inflammatory cytokines, iron and oxidative stress, oxidant-antioxidant imbalance, and iron-dependent progression of endometriosis [6]. A recent literature review suggested that endometrial immune dysregulation could be responsible for RPL and may also lead to endometriosis [7]. Thus far, the exact reason for endometriosis is still not clear and, therefore meta-data analysis may provide further knowledge to solve the molecular pathogenesis complexity of such condition(s). To find the genes involved in the loss of the hormonal functions and association with endometriosis, [PERSON] et al. [8] performed a large scale, 11 genome-wide case-control dataset meta-analysis and found that _FN1_, _CCDC170_, _ESR1_, _SYNE1_, and _FSHB_ are the 5 genes that could be responsible for the endometriosis risk. Therefore, computational system biology plays a major role in meta-data analysis. In combination with machine learning, many biomarker genes have been identified, including _NOTCH3_, _SNAPC2_, _BAGALNT1_, _SMAP2_, _DDB2_, _GT3C5_, and _PTOV1_ from the transcriptomic data analysis, and _TRPM6_, _RASSF2_, _TINP2_, _RP3-522J7_.6_, _FGD3_, and _MFSD14B_ from the methylomic data analysis [9]. The latest metadata investigation related to polymorphisms and endometriosis tried to find the genetic level reason behind endometriosis, where five polymorphisms have been associated with endometriosis [10]. They were glutathione S-transferase pi 1 (_GSTPI_) rs1695, interferon-gamma (_IFNG_) (CA) repeat, wingless-type MMTV integration site family member 4 (_WNT4_) rs16826658, rs2235529, and glutathione S-transferase mu 1 (_GSTM1_) null genotype. The present study aimed to identify the genes that are differentially expressed in endometriosis and RPL conditions, and to elucidate their involvement in protein-protein interactions, as well as their functional importance in biological pathways as potential biomarkers common to both endometriosis and RPL.