Clinical proteomics in kidney disease as an exponential technology: heading towards the disruptive phase

Abstract

Exponential technologies double in power or processing speed every year, whereas their cost halves. Deception and disruption are two key stages in the development of exponential technologies. Deception occurs when, after initial introduction, technologies are dismissed as irrelevant, while they continue to progress, perhaps not as fast or with so many immediate practical applications as initially thought. Twenty years after the first publications, clinical proteomics is still not available in most hospitals and some clinicians have felt deception at unfulfilled promises. However, there are indications that clinical proteomics may be entering the disruptive phase, where, once refined, technologies disrupt established industries or procedures. In this regard, recent manuscripts in CKJ illustrate how proteomics is entering the clinical realm, with applications ranging from the identification of amyloid proteins in the pathology lab, to a new generation of urinary biomarkers for chronic kidney disease (CKD) assessment and outcome prediction. Indeed, one such panel of urinary peptidomics biomarkers, CKD273, recently received a Food and Drug Administration letter of support, the first ever in the CKD field. In addition, a must-read resource providing information on kidney disease-related proteomics and systems biology databases and how to access and use them in clinical decision-making was also recently published in CKJ.

Fig. 1.

The CKD blind spot. (A) Car mirror blind spot. (B) CKD blind spot. The most frequently used diagnostic and staging criteria for CKD, based on GFR and UACR, are late events, allowing a blind spot that may last years, characterized by progression of undiagnosed kidney injury. As is the case with driving, a blind spot may be fatal, since specific therapy may be initiated too late to prevent the need for renal replacement therapy or premature death. (C) Imaging addresses the blind spot in ADPKD, allowing the diagnosis of CKD decades before GFR or UACR values allow diagnosing CKD. A key research priority is the search for biomarkers that allow closing the blind spot in other causes of CKD.

Fig. 2.

Clinical proteomics for assessment of CKD aetiology and major molecular pathways involved. (A) Since the 1960s, the initial diagnostic approach to CKD has been 3D, based on the assessment of a limited number of parameters (mainly albuminuria/proteinuria, glomerular haematuria, GFR) that summarize, in perhaps too simple a way, the interplay of diverse aetiologies and diverse molecular pathways of kidney injury. The result has been a considerable delay in the diagnosis of CKD and also in the development of novel therapeutic approaches to kidney disease. (B) Systems biology and, specifically, clinical proteomics allow the nephrologist to embrace complexity in order to develop personalized medicine approaches that provide information within a single diagnostic test that leads to the diagnosis of CKD, to identification of aetiology and molecular pathways (and, thus, of the most appropriate therapy) and outcome prediction.