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.

Protein homodimers have been classified as three-state or two-state dimers depending on whether a folded monomer forms before association, but the details of the folding–binding mechanisms are poorly understood. Kinetic transition networks of conformational states have provided insight into the folding mechanisms of monomeric proteins, but extending such a network to two protein chains is challenging as all the relative positions and orientations of the chains need to be included, greatly increasing the number of degrees of freedom. Here, we present a simplification of the problem by grouping all states of the two chains into two layers: a dissociated and an associated layer. We combined our two-layer approach with the Wako–Saito–Muñoz–Eaton method and used Transition Path Theory to investigate the dimer formation kinetics of eight homodimers. The analysis reveals a remarkable diversity of dimer formation mechanisms. Induced folding, conformational selection, and rigid docking are often simultaneously at work, and their contribution depends on the protein concentration. Pre-folded structural elements are always present at the moment of association, and asymmetric binding mechanisms are common. Our two-layer network approach can be combined with various methods that generate discrete states, yielding new insights into the kinetics and pathways of flexible binding processes.