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Comparative analysis of biomarker profiles in chronic kidney disease with and without hepatitis B co-infection in Iraq

Comput Biol Chem. 2026 May 1;124(Pt 1):109099. doi: 10.1016/j.compbiolchem.2026.109099. Online ahead of print.

ABSTRACT

BACKGROUND: Chronic kidney disease (CKD) and hepatitis B virus (HBV) infection are major health challenges. While both individually disrupt systemic homeostasis, their potential synergistic effects on hematological, lipid, and renal function profiles remain poorly defined in specific demographics.

OBJECTIVE: This study aims to comparatively analyze key hematological, lipid, and renal function biomarkers among Iraqi CKD patients with HBV co-infection, CKD patients without HBV, and healthy controls.

METHODS: A cross-sectional study was conducted with 150 participants (50 CKD, 50 CKD+HBV, 50 controls). Hematological parameters (WBCs, Hb, PCV, RBCs, PLTs, iron, ferritin), lipid profiles (cholesterol, triglycerides, LDL, VLDL, HDL), and renal function markers (urea, creatinine) were measured. Statistical analyses included one-way ANOVA with post-hoc tests to assess group differences, Chi-square tests for categorical distributions, and Pearson correlations to evaluate linear relationships between independent biomarkers, with P ≤ 0.05 considered significant.

RESULTS: Compared to healthy controls, both CKD and CKD+HBV groups exhibited significantly lower WBCs, Hb, PCV, RBCs, PLTs, and iron, and higher ferritin, cholesterol, triglycerides, and renal markers (P < 0.05). Notably, there were no statistically significant differences in these biomarkers between the CKD-only and CKD+HBV groups.

CONCLUSIONS: Both CKD and CKD+HBV profoundly alter hematological and biochemical profiles compared to healthy controls. However, HBV co-infection did not significantly exacerbate these abnormalities in this cohort. These findings suggest that the profound metabolic and hematological disruptions driven by uremia may overshadow the secondary physiological effects of HBV infection, highlighting the need for future longitudinal studies incorporating viral load and multivariable modeling.

PMID:42070332 | DOI:10.1016/j.compbiolchem.2026.109099

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