Miscarriages affect 50–70% of all conceptions and 15–20% of clinically recognized pregnancies. Recurrent pregnancy loss (RPL, ≥2 miscarriages) affects 1–5% of recognized pregnancies. Nevertheless, our knowledge about the etiologies and pathophysiology of RPL is incomplete, and thus, reliable diagnostic/preventive tools are not yet available. Here, we aimed to define the diagnostic value of three placental proteins for RPL: human chorionic gonadotropin free beta-subunit (free-β-hCG), pregnancy-associated plasma protein-A (PAPP-A), and placental growth factor (PlGF). Blood samples were collected from women with RPL (n = 14) and controls undergoing elective termination of pregnancy (n = 30) at the time of surgery. Maternal serum protein concentrations were measured by BRAHMS KRYPTOR Analyzer. Daily multiple of median (dMoM) values were calculated for gestational age-specific normalization. To obtain classifiers, logistic regression analysis was performed, and ROC curves were calculated. There were differences in changes of maternal serum protein concentrations with advancing healthy gestation. Between 6 and 13 weeks, women with RPL had lower concentrations and dMoMs of free β-hCG, PAPP-A, and PlGF than controls. PAPP-A dMoM had the best discriminative properties (AUC = 0.880). Between 9 and 13 weeks, discriminative properties of all protein dMoMs were excellent (free β-hCG: AUC = 0.975; PAPP-A: AUC = 0.998; PlGF: AUC = 0.924). In conclusion, free-β-hCG and PAPP-A are valuable biomarkers for RPL, especially between 9 and 13 weeks. Their decreased concentrations indicate the deterioration of placental functions, while lower PlGF levels indicate problems with placental angiogenesis after 9 weeks.

Introduction: Miscarriages affect 50-70% of all gestations and 15-20% of clinically recognized pregnancies. Recurrent pregnancy loss (RPL) occurs in 1-5% of clinical pregnancies and has an enormous demographic impact. However, the etiologies and molecular pathways of RPL are scarcely understood, and therefore, reliable diagnostic and preventive methods are not yet available. Here, we aimed to discover novel biomarkers for RPL using next-generation proteomics technology to help develop early and effective diagnostic tools. Methods: First-trimester blood samples were collected from women with RPL (n=11) and controls with elective termination of pregnancy (n=11) between 6–13 weeks of gestation. After immunodepleting 14 highly abundant proteins, plasma samples were reduced, alkylated, and trypsin digested. For the separation of peptides, nano-flow reversed-phase chromatography was applied, and then mass spectrometric analysis was performed. Differentially abundant (DA) proteins were identified using strict criteria and analyzed by protein network and Gene Ontology (GO) enrichment analyses, and two biomarker candidates (CGB and PAPPA) were validated by immunoassay. Biomarker predictive properties were demonstrated using Receiver Operating Characteristic (ROC) curves. Assessments were performed for all cases and then for two gestational age groups, before and after the start of placental circulation [“early RPL”: gestational weeks (GW) 6–9, “late RPL”: GW 9–13]. Results: Altogether, 651 proteins were identified and quantified across all samples. When comparing “early control” and “late control” samples, 60 proteins [11 predominantly placenta-expressed (PPE)] were DA. When analyzing all cases, 50 DA proteins were found in RPL (top 3 down: PZP, PSG9, CGB; top 3 up: C4BPA, HBA, HBB), among which 11 PPE proteins were found, all downregulated. Enriched GO terms included ‘placental function’, ‘oxidative processes’, ‘immune function’, and ‘blood coagulation’ related biological processes. When cases were split into early and late RPL groups, 40 DA proteins were identified in early RPL (top 3 down: SHBG, CGB, CGA; top 3 up: C4BPA, SAMP, C4BPB) and 90 in late RPL (top 3 down: PZP, PAPPA, PSG9; top 3 up: THBS1, ECM1, HBB), among which only 15 were shared by both RPL groups. In early RPL, only ‘placental function’ and ‘immune function’ related biological processes were enriched, while in late RPL the top enriched GO terms included ‘placental function’, ‘oxidative processes’, ‘immune function’, ‘blood coagulation’, ‘angiogenesis’, ‘cell migration’, and ‘blood circulation’ related biological processes. Among GO terms, only ‘placental function’ related biological processes were enriched when early- and late RPL DA proteins were analyzed together. Furthermore, the areas under the ROC curves were >0.9 for two protein candidates in all RPL, for five proteins in early RPL, and for ten proteins in late RPL. Among these candidates, CGB and PAPPA were validated by immunoassay which showed a good correlation with MS data (RCGB=0.795 and RPAPPA=0.965). Conclusion: We discovered distinct as well as shared molecular pathways associated with RPL pathogenesis before and after the start of placental circulation and identified novel biomarkers for these pathways which have outstanding discriminative properties. Our results may facilitate a better understanding of the molecular pathways of RPL. However, larger clinical studies are needed to investigate whether the identified biomarkers also have predictive power for RPL before pregnancies fail and to test drugs for the modulation of the identified disease pathways and the prevention of RPL. Our findings highlight the importance of the maternal immune system in maintaining successful pregnancy and suggest that targeting immune pathways may offer novel therapeutic approaches for RPL.