Circulating biomarkers associated with pediatric sickle cell disease

Area of Science:

• Hematology
• Genetics
• Biomarker Discovery

Background:

• Sickle Cell Disease (SCD) is a genetic blood disorder affecting millions globally, particularly in sub-Saharan Africa, leading to severe complications and high mortality.
• Current diagnostic and management strategies for pediatric SCD, especially in regions like Ghana, are limited, highlighting the need for better predictive tools.
• Identifying reliable biomarkers is crucial for understanding SCD pathophysiology and improving patient outcomes, yet research in pediatric populations remains scarce.

Purpose of the Study:

• To explore and identify specific circulating biomarkers in pediatric patients with SCD in Ghana.
• To investigate the potential of inflammatory and neuronal injury markers in predicting disease outcomes in children with SCD.
• To establish a foundation for developing a predictive algorithm to enhance SCD management.

Main Methods:

• A cross-sectional study involving 377 children aged 3-8 years with various hemoglobin genotypes (SCD and SCT) was conducted in Accra, Ghana.
• Serum biomarkers, including cytokines, chemokines, vascular injury markers, and brain-derived neurotrophic factor (BDNF), were evaluated using a multiplexed immunoassay.
• Data were analyzed to correlate biomarker levels with clinical parameters and assess their predictive potential using Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC) analyses.

Main Results:

• Elevated levels of BDNF, Ang-2, CXCL10, CCL11, TNF-α, IL-6, IL-10, IL12p40, ICAM-1, VCAM-1, Tie-2, and VEGFA were observed in children with HbSS genotype.
• These elevated biomarkers correlated significantly with hemoglobin levels, leukocyte, and erythrocyte counts.
• Heme scavengers (HO-1, hemopexin, haptoglobin) also showed correlations with these parameters, and ROC/AUC analyses indicated their potential in predicting SCD outcomes.

Conclusions:

• Significant differences in biomarker expression exist among different SCD genotypes.
• A predictive algorithm utilizing these identified biomarkers could be developed and validated through longitudinal studies.
• This approach holds promise for personalized interventions and improved clinical care for pediatric SCD patients, potentially enhancing disease management and patient outcomes.