Potential Predictive Biomarkers for the Development and Outcomes of Inhibitors in Hemophilia A Patients
Authors: Fan Meng-Ni , Shen Tangliang , Cai Xiaohe , Chao Ting-Yen , Manco-Johnson Marilyn , Xiao Weidong , Konkle Barbara A. , Li Lei , Miao Carol H. 
Published: December 2023

Introduction
Inhibitor development poses a significant challenge in the treatment of hemophilia A (HA). Approximately 30% of HA patients develop inhibitors in response to FVIII infusion therapy. While the risk is highest early in treatment days, patients are at risk throughout their lifetime. Regardless of certain known risk factors, the lack of biomarkers for inhibitor development hampers efforts to prevent their occurrence. Since inflammation is a well-known risk factor, one of our goals is to identify potential biomarkers among inflammatory cytokines. Another focus is glycosylation-related biomarkers, which has drawn great attention in biomarker discovery of various diseases including cancers. By analyzing the association of cytokines and plasma glycosylation with inhibitor formation, this research aims to provide valuable references for clinical care.
Methods
Plasma samples from 60 HA patients, and 23 healthy donors were analyzed to detect the levels of G-CSF, IFN-γ, IL-1β, IL-2, IL-6, IL-8, IL-10, IL12p70, IP-10 and TNF. The HA samples were divided into inhibitor negative (InhNeg, BU &lt; 0.6, n = 26) and inhibitor positive (InhPos, BU ≥ 0.6, n = 34) groups. A predictive model of inhibitor development was established using logistic regression analysis. To investigate the correlation between cytokine levels and high inhibitor titers, the inhibitor-positive samples were further categorized into good risk (&lt; 10 BU, n = 14) and poor risk (≥ 10 BU, n = 20) groups based on immune tolerance induction therapy prognosis.
Total plasma N-glycans were released, methylated, and analyzed by using MALDI-TOF MS/MS. A synthesized N-glycan was spiked in to quantify each glycoform. The study evaluated the correlation between HA sample groups and various glycosylation ratios, including for sialylation, core-fucosylation, galactosylation and galactose. The cut-off value of each glycosylation ratio was based on the median of the inhibitor-negative group.
Results
The adjusted odds ratio of inhibitor development for elevated G-CSF, IL-6 and decreased IL-10 were 2.84 (95% CI: 1.45-8.48; p = 0.021), 1.50 (95% CI: 1.14-2.42; p = 0.069), and 0.28 (95% CI: 0.10-0.61; p = 0.006), respectively in HA patients. Among InhPos HA patients, the levels of G-CSF, IL-2, IL-6, IL-8, and IL-10 in poor risk group were significantly higher than in good risk group (p-value &lt; 0.05, ANOVA).
Since aging also causes glycosylation changes, we analyzed adult (≥ 18 years old, n = 31) and pediatric (&lt; 18 years old, n = 17) HA patients separately. Among analyzed glycan ratios, 80% of adult HA patients with inhibitors had a higher core-fucosylation ratio. All pediatric patients with inhibitors had significant lower sialylation and higher galactosylation ratios. Strikingly, pediatric patients with inhibitors exhibited around 2-fold higher core-fucosylation than those without inhibitor.
Conclusion
Our finding of elevated levels of G-CSF and IL-6 along with decreased levels of IL-10 associated with the presence of inhibitors, suggests the potential for prediction of inhibitor development. Moreover, high levels of G-CSF, IL-2, IL-6, IL-8 and IL-10 in patients with high inhibitor titers (≥ 10 BU, poor risk group) but not in good risk group imply they could be explored in future studies as prognostic factors in immune tolerance therapy. Glycan ratios can also hold promise as biomarkers including higher core-fucosylation in adult patients. Additionally, significant lower sialyation, higher galactosylation and core-fucosylation ratios indicate higher possibility of inhibitor development in pediatric patients.