Identification of Biomarker Profile for Chronic Kidney Disease of uncertain aetiology in Sri Lanka

Abstract

Background: Chronic Kidney Disease of uncertain aetiology (CKDu) is a major health problem in Sri Lanka. Current laboratory markers are not sensitive enough for early detection of CKDu. It is evident that a more efficient, sensitive and specific diagnostic procedure is needed for early detection and to confirm the diagnosis of CKDu. Objectives: To identify a representative biomarker profile for CKDu, Sri Lanka and to study the applicability of these biomarkers in identifying at risk population for screening and diagnosis of CKDu, Sri Lanka Methods: Girandurukotte and Wilgamuwa which are considered as CKDu endemic areas were selected for the study to recruit definite non-dialysis CKDu cases (n = 119), endemic CKD (n = 82) and endemic healthy controls (n = 79). Non-endemic CKD group (n = 85) and healthy controls (n = 85) were recruited from Kandy. Routine markers and novel biomarkers for CKDu were measured using serum and random urine of CKDu patients. The eight selected renal biomarkers were measured using multiplex biomarker assay, and the data were analyzed using logistic regression algorithm aiming to extract the best marker combination that could distinctly identify the disease groups noninvasively from the healthy controls. Data were analyzed using SPSS and R software. Results: Among the selected patients, 97 (81.5%) were males while 22 (18.5%) were females. Under routine markers, hyperuricemia, acidosis, hypomagnesemia, vitamin D deficiency, anemia, increased level of serum osmolality, amylase, Lactate Dehydrogenase and Alkaline Phosphatase were identified. Alpha1 microglobulin (A1M) stood out as the single strong candidate marker that was highly specific (84.7%) in identifying CKDu from healthy controls. Combination of A1M+ Kidney Injury Molecule 1 (KIM1) + Retinol Binding Protein 4 (RBP4) was able to accurately differentiate the disease groups (CKDu/CKD), from healthy controls. Combination of Osteopontin + KIM1+ RBP4 accurately predicted CKDu with high performance from a CKD background. Higher mean (±SD) value (69587 ng/mL) of Transforming Growth factor beta 1was obtained from the CKDu group compared to the other controls with a significant negative correlation (r = -0.293, p <0.01) with the serum creatinine. Conclusions: A representative biomarker profile has been identified for identification of risk population for screening and diagnosis of CKDu. Biomarker combinations are helpful to diagnose CKDu effectively and non-invasively.