Potential Renal Damage Biomarkers in Alport Syndrome—A Review of the Literature

Abstract

Alport syndrome (AS) is the second most common cause of inherited chronic kidney disease. This disorder is caused by genetic variants on COL4A3, COL4A4 and COL4A5 genes. These genes encode the proteins that constitute collagen type IV of the glomerular basement membrane (GBM). The heterodimer COL4A3A4A5 constitutes the majority of the GBM, and it is essential for the normal function of the glomerular filtration barrier (GFB). Alterations in any of collagen type IV constituents cause disruption of the GMB structure, allowing leakage of red blood cells and albumin into the urine, and compromise the architecture of the GFB, inducing inflammation and fibrosis, thus resulting in kidney damage and loss of renal function. The advances in DNA sequencing technologies, such as next-generation sequencing, allow an accurate diagnose of AS. Due to the important risk of the development of progressive kidney disease in AS patients, which can be delayed or possibly prevented by timely initiation of therapy, an early diagnosis of this condition is mandatory. Conventional biomarkers such as albuminuria and serum creatinine increase relatively late in AS. A panel of biomarkers that might detect early renal damage, monitor therapy, and reflect the prognosis would have special interest in clinical practice. The aim of this systematic review is to summarize the biomarkers of renal damage in AS as described in the literature. We found that urinary Podocin and Vascular Endothelial Growth Factor A are important markers of podocyte injury. Urinary Epidermal Growth Factor has been related to tubular damage, interstitial fibrosis and rapid progression of the disease. Inflammatory markers such as Transforming Growth Factor Beta 1, High Motility Group Box 1 and Urinary Monocyte Chemoattractant Protein- 1 are also increased in AS and indicate a higher risk of kidney disease progression. Studies suggest that miRNA-21 is elevated when renal damage occurs. Novel techniques, such as proteomics and microRNAs, are promising.