Clinical Features of the Subjects
A total of 178 subjects, including 133 AIS patients and 45 healthy controls, were enrolled in this study. The discovery set contained 10 age- and sex- matched cases from each of the APIS, ANPIS and control groups. Basic clinical information showed that the APIS patients had higher incidence of atrial fibrillation, history of arrhythmias, and intracranial artery stenosis than the ANPIS patients (30% vs. 0%, 70% vs. 20%, and 70% vs. 30%, respectively). In addition, compared with the ANPIS patients, the APIS patients also had higher NIHSS scores at admission and discharge (7.5 vs. 2.2, 11.9 vs. 1.6, respectively). Noticeably, even receiving conventional treatments, APIS patients’ NHISS and mRS (modified Rankin Scale) scores have still remarkably increased (7.5→11.9), particularly during the worsening of stroke symptoms (NHISS=13.7). Consequently, the APIS patients required longer hospitalization than the ANPIS patients (19.2 vs. 9.3).
The APIS patients also exhibited elevated serum levels of (i) white blood cell, neutrophils ratio (%), erythrocyte sediment rate (ESR), C-reactive protein (CRP) and hs-CRP, indicative of more serious inflammation and stress condition during APIS; (ii) homocysteine, suggesting dysfunction or disturbance in coagulation, platelet aggregation, and blood lipid metabolism; and (iii) BUN and Cr, implying kidney dysfunction (Table 2). Therefore, clinically, the APIS patients had more critical conditions and worse prognosis than the ANPIS patients.
The validation set, which included 25 APIS patients, 88 ANPIS patients, and 35 controls, had similar clinical characters as their counterparts in the discovery set (Table1 and Table 2).
The basic results of proteomic analysis
Totally, 796 proteins were successfully identified in the serum samples of the subjects after removing the high-abundant proteins (Fig. 1). Of these, 161 proteins that had detailed quantitative information and annotation terms were used to screen DEPs (Table S1). As a result, 46 proteins were disturbed in AIPS, of these, 23 were common to ANPIS, and the other 23 were specific to APIS (Table 3).
APIS proteomic profile common to that of ANPIS
To obtain comprehensive insight into the proteomic feature of APIS that common to ANPIS, we made GO and pathway enrichment analyses of the common DEPs (13 were upregulated and 10 were downregulated) between these two groups. The significant terms in the enrichments are given in Fig. 2 and Table S2.
The significant BPs mainly focused on platelet degranulation, innate immune response, acute-phase response, oxygen transport, hydrogen peroxide catabolic process, neutrophil chemotaxis, cellular oxidant detoxification, phosphatidylcholine metabolic process, leukocyte migration involved in inflammatory response, and positive regulation of cell death (Fig. 2 and Table S2). Accordingly, the significant MFs mostly focused on oxygen transporter activity, oxygen binding, protease binding, aryl esterase activity, antioxidant activity, peroxidase activity, immunoglobulin receptor binding, and serine-type endopeptidase activity. The significant CCs were largely related to blood microparticle, exosome, platelet alpha granule lumen, extracellular matrix, and external side of plasma membrane. The network chart of enriched ontology cluster illustrates that hydrogen peroxide catabolic process, acute-phase response and humoral immune response are the most significant pathways (Fig. 3).
The proteomic feature specifically associated with APIS
The current study has found that 23 DEPs were specific to APIS; of these, 13 were upregulated and 10 were downregulated (Table 3). The crucial mechanistic factors leading to progressive quality of APIS were analyzed using the aforementioned strategy.
The significant terms included complement activation, proteolysis, positive regulation of fibrinolysis, negative regulation of very-low-density lipoprotein particle clearance, cholesterol transport, receptor-mediated endocytosis, plasminogen activation, phospholipid efflux, intrinsic pathway blood coagulation, serine-type endopeptidase activity, lipase inhibitor activity, complement binding, insulin-like growth factor binding, protein complex binding, and fibronectin binding, extracellular region, extracellular space, extracellular exosome, blood microparticle, membrane attack complex, chylomicron, and lipoprotein particle (Fig. 2 and Table S3). In addition, the network chart of enriched ontology clusters indicates complement and coagulation cascades, neutrophil degranulation, and blood coagulation response are the most significant functions involved in the worsening progress of AIS symptoms (Fig. 3).
Diagnostic potential of SAA1 and S100-A9
In this study, potential serum protein biomarkers were selected by the following strategies. Firstly, DEPs with high fold change between the APIS patients and controls were chosen. Then, those proteins that could reasonably explain the pathophysiological mechanism of APIS were given a priority consideration. As a result, SAA1 and S100-A9, both met the two requirements, were selected as potential biomarkers, and then their absolute concentrations were measured to analyze the diagnostic value. The mean concentrations of SAA1 in the APIS, ANPIS, and control groups were 373.59 ng/mL, 284.58 ng/mL, and 199.45 ng/mL, respectively, which were significantly different among these three groups (Fig. 4). The SAA1 contents in the AIS patients correlated with several clinical indicators (Table 4). The concentrations of S100-A9 in these three groups were 734.44 pg/mL, 658.74 pg/mL, and 607.05 pg/mL, respectively. SAA1 demonstrated good potential to identify APIS (AUC = 0.729, p=0.002, cut-off value > 386.72 ng/mL) and to distinguish APIS from ANPIS (AUC =0.635, p = 0.036, cut-off value > 233.25 ng/mL). Although the contents of S100-A9 were not significantly different among these three groups; however, its content in the APIS group was the highest among them, and it illustrated moderate potential to diagnose APIS (AUC = 0.675, p = 0.013). Lastly, to determine whether these biomarkers had synergetic effect to diagnose APIS or AIS, we performed a binary logistic regression analysis and found that they jointly yielded AUC of 0.799, sensitivity of 63.6%, and specificity of 92.6% to diagnose APIS; moreover, they jointly yielded AUC of 0.699, sensitivity of 72.7%, and specificity of 69.0% to distinguish APIS from ANPIS (Fig. 4).