Protein Microarrays Discover Angiotensinogen and PRKRIP1 as Novel Targets for Autoantibodies in Chronic Renal Disease
ABSTRACT Biomarkers for early detection of chronic kidney disease are needed, as millions of patients suffer from chronic diseases predisposing them to kidney failure. Protein microarrays may also hold utility in the discovery of auto-antibodies in other conditions not commonly considered auto-immune diseases. We hypothesized that proteins are released as a consequence of damage at a cellular level during end-organ damage from renal injury, not otherwise recognized as self-antigens, and an adaptive humoral immune response to these proteins might be detected in the blood, as a noninvasive tracker of this injury. The resultant antibodies (Ab) detected in the blood would serve as effective biomarkers for occult renal injury, enabling earlier clinical detection of chronic kidney disease than currently possible, because of the redundancy of the serum creatinine as a biomarker for early kidney injury. To screen for novel autoantibodies in chronic kidney disease, 24 protein microarrays were used to compare serum Ab from patients with chronic kidney disease against matched controls. From a panel of 38 antigens with increased Ab binding, four were validated in 71 individuals, with (n=50) and without (n=21) renal insufficiency. Significant elevations in the titer of novel auto-Ab were noted against angiotensinogen and PRKRIP1 in renal insufficiency. Current validation is underway to evaluate if these auto-Ab can provide means to follow the evolution of chronic kidney disease in patients with early stages of renal insufficiency, and if these rising titers of these auto-Ab correlate with the rate of progression of chronic kidney disease.
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ABSTRACT: Biomedical research is growing increasingly enamored of the promise of translational medicine. In an era of increasing costs and difficulties in the process of drug discovery, bioinformatics has taken on special importance as a tool to advance translational medicine and make it more efficient.1 Here we discuss the potential role of translational bioinformatics in addressing current and future needs, specifically in the field of transplantation with its unmet diagnostic and therapeutic needs.Clinical Pharmacology & Therapeutics (2011) 90 2, 323-327. doi:10.1038/clpt.2011.120Clinical Pharmacology & Therapeutics 06/2011; 90(2):323-7. DOI:10.1038/clpt.2011.120 · 7.39 Impact Factor
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ABSTRACT: Chronic allograft injury (CAI) results from a humoral response to mismatches in immunogenic epitopes between the donor and recipient. Although alloantibodies against HLA antigens contribute to the pathogenesis of CAI, alloantibodies against non-HLA antigens likely contribute as well. Here, we used high-density protein arrays to identify non-HLA antibodies in CAI and subsequently validated a subset in a cohort of 172 serum samples collected serially post-transplantation. There were 38 de novo non-HLA antibodies that significantly associated with the development of CAI (P<0.01) on protocol post-transplant biopsies, with enrichment of their corresponding antigens in the renal cortex. Baseline levels of preformed antibodies to MIG (also called CXCL9), ITAC (also called CXCL11), IFN-γ, and glial-derived neurotrophic factor positively correlated with histologic injury at 24 months. Measuring levels of these four antibodies could help clinicians predict the development of CAI with >80% sensitivity and 100% specificity. In conclusion, pretransplant serum levels of a defined panel of alloantibodies targeting non-HLA immunogenic antigens associate with histologic CAI in the post-transplant period. Validation in a larger, prospective transplant cohort may lead to a noninvasive method to predict and monitor for CAI.Journal of the American Society of Nephrology 02/2012; 23(4):750-63. DOI:10.1681/ASN.2011060596 · 9.47 Impact Factor
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