Insights Into Diabetic Kidney Disease Using Urinary Proteomics and Bioinformatics
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BRIEF REVIEW www.jasn.org Insights into Diabetic Kidney Disease Using Urinary Proteomics and Bioinformatics † † Julie A.D. Van,* James W. Scholey,* and Ana Konvalinka* *Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; and †Department of Medicine, Division of Nephrology, University Health Network, Toronto, Ontario, Canada ABSTRACT A number of proteomic and peptidomic analyses of urine from diabetic subjects changes in protein expression, deposi- have been published in the quest for a biomarker that predicts progression of ne- tion, or turnover in the diabetic kidney. phropathy. Less attention has been paid to the relationships between urinary pro- We reviewed the literature on urinary teins and the underlying biological processes revealed by the analyses. In this proteomics/peptidomics, biomarkers, review, we focus on the biological processes identified by studying urinary proteins and diabetic kidney disease in humans and protein-protein interactions at each stage of diabetic nephropathy to provide (Figure 1A, Supplemental Table 1). We an overview of the events underlying progression of kidney disease reflected in the selected the most robust candidate urine. In uncomplicated diabetes, proteomic/peptidomic analyses indicate that markers at each stage of diabetic kidney early activation of fibrotic pathways in the kidney occurs before the onset of micro- disease and then highlighted their roles albuminuria. In incipient nephropathy, when albumin excretion rates are abnormal, in biological processes that may contrib- proteomic/peptidomic analyses suggest that changes in glomerular permselectivity ute to progression from uncomplicated and tubular reabsorption account, at least in part, for the proteins and peptides that diabetes to incipient diabetic nephropa- appear in the urine. Finally, overt nephropathy is characterized by proteins involved thy to overt diabetic nephropathy (Table in wound healing, ongoing fibrosis, and inflammation. These findings suggest that 1). Although reviews on similar topics there is a spectrum of biological processes in the diabetic kidney and that assessing exist, none integrate findings across protein networks may be more informative than individual markers with respect to studies and assess their biological impli- the stage of disease and the risk of progression. cations on mechanisms underlying dia- betic kidney disease progression. J Am Soc Nephrol 28: 1050–1061, 2017. doi: 10.1681/ASN.2016091018 INTEGRATING DATA WITH Microalbuminuria is currently the most Advances in mass spectrometry have BIOINFORMATICS reliable predictor of diabetic nephrop- enhanced our ability to identify thou- – athy.1 3 However, recent evidence chal- sands of proteins and peptides in urine Proteins and peptides are interconnected lenges this notion. The Joslin Study of in a single analysis—some of which may in large networks, which can be altered in Natural History of Microalbuminuria serve as new markers. This large-scale disease. Expression profiles vary accord- demonstrated that the likelihood of re- study of proteins is termed proteomics, ing to the type of cell, tissue, organ, or gression from microalbuminuria to whereas the study of naturally occurring specimen, which can shed light on normal urinary albumin excretion out- peptides generated by endogenous pro- the location of injury.11,12 Further- weighs the likelihood of progression tease activity is termed peptidomics. more, multiple datasets of potential to overt proteinuria.4 Other longitudi- Urinary proteomics and peptidomics biological markers can be more useful nal, observational studies have repli- add different dimensions to the investi- cated these results in children and gation of underlying biology. Their ap- Published online ahead of print. Publication date adults, in type 1 and type 2 diabetes, plication in urine has important clinical available at www.jasn.org. and in individuals from North Amer- implications for diabetic kidney disease, ica, Asia, and Europe.5–9 Taken to- given that urine can be collected nonin- Correspondence: Ms. Julie Van, Division of Nephrology, Toronto General Hospital, University gether, these studies provide strong vasively with relative ease and is directly Health Network, 11-PMB-189, Toronto, ON M5G evidence that microalbuminuria may produced by the kidneys.10 As such, 2N2, Canada. Email: [email protected] not be the ideal marker of progression changes in the relative abundance of uri- Copyright © 2017 by the American Society of after all. nary proteins and peptides may reflect Nephrology 1050 ISSN : 1046-6673/2804-1050 JAmSocNephrol28: 1050–1061, 2017 www.jasn.org BRIEF REVIEW AB Figure 1. Summary of literature search and bioinformatic analyses. (A) Out of the 155 search results, 34 studies were screened and 31 relevant urinary proteomic/peptidomics studies in diabetes were included into our review. Reasons for study exclusion are shown for the initial screening and final inclusion. (B) The protein datasets, bioinformatic tools and software, and output figures are outlined for each of the bioinformatic analyses. when considered together, as opposed to in the progression of diabetic kidney glomerular basement membrane thick- in isolation, so that the most robust and disease using the Biological Networks ening, and podocyte loss.16,19 These consistent network of biological func- Gene Ontology13 and Enrichment Map14 functional and structural abnormalities tions may be identified. This “mechanis- plug-ins of Cytoscape software for the en- distinguish the diabetic kidney from a tic” approach can be used to explore and tire set of proteins associated with each healthykidneybeforetheonsetofmi- address the current gaps in knowledge stage of diabetic kidney disease (Figures 3 croalbuminuria. However, current uri- underlying the pathophysiology and and 4). For the purposes of this review, nary markers are not sensitive enough progression of diabetic nephropathy. we compared sequential stages of dia- to confidently detect these changes. We thus investigated the biological betic kidney disease to better understand Hence, there is a pressing need for accu- implications of differentially excreted transitions and progression, although we rate and reliable markers of early dia- urinary proteins in diabetic kidney dis- realize that this construct is somewhat betic kidney injury. ease by taking advantage of published, artificial. Furthermore, we constructed In healthy adolescents with type 1 di- relevant data (Figure 1B). Candidate protein-protein interaction networks abetes, Meier and colleagues identified a markers with differential excretion be- with the Search Tool for the Retrieval of urinary proteome profile, which was dif- tween cases and controls were extracted Interacting Genes/Proteins (Figure 5).15 ferent from that of healthy, age-matched from all 31 studies (Supplemental Table Overall, these analyses have enabled us to controls.20 Without the use of tandem 1). All candidates were weighted equally comprehensively identify common and mass spectrometry, differences could when inputted into the network analy- stage-specific biological processes in di- not be assigned to specific proteins. Nev- ses. However, we selected a handful of abetic kidney disease by including all ertheless, this study demonstrated that promising candidates for each stage proteins associated with a particular differences could be detected early in di- of diabetic kidney disease on the basis stage of disease. abetic kidney disease, setting the stage of (1) between-group differential excre- for later studies. In the largest urinary tion rates in at least two studies, (2) sup- peptidome study of diabetes to date, port from verification and validation, UNCOMPLICATED DIABETES Maahs and colleagues demonstrated and/or (3) high enrichment and/or spec- lower urinary levels of collagen and uro- ificity in the kidney (Table 1). For the Uncomplicated diabetes is the earliest modulin in diabetic cases with normal localization analysis, these promising stage of diabetic kidney disease. Some renal function compared with controls.21 candidates were mapped onto specific maladaptive changes such as renal hyper- Zhang and colleagues found two urinary nephron segments on the basis of their filtration and hypertrophy are often pre- fragments of fibrinogen a chain and renal expression in normal tissues using sent at time of diagnosis of diabetes.16 prothrombin—two important and closely the Human Protein Atlas11 and inferred Renal hyperfiltration has been linked to related players in coagulation—which site of injury using the existing literature the initiation and progression of diabetic were associated with type 2 diabetes (par- (Figure 2). For the functional analysis, we nephropathy.17,18 Many patients develop ticularly in those with high glycated hemo- deduced biological processes implicated lesionssuchasmesangialexpansion, globin, HbA1c).22 In total, 35 protein J Am Soc Nephrol 28: 1050–1061, 2017 Urinary Proteomics in Diabetes 1051 1052 BRIEF REVIEW Journal of the American Society of Nephrology Table 1. Characteristics of promising markers for each stage of diabetic kidney disease www.jasn.org Stage of Diabetic Direction of Nephron Protein Description Biological Processes Validated Kidney Disease Urinary Excretiona Segment Uncomplicated a1-antitrypsin (SERPINA1) 40-kD serine protease inhibitor ↑ (9 of 9) PT Coagulation, inflammation ELISA, SRM Diabetes Clusterin (CLU) 50-kD nuclear form ↑ (3 of 4) PT Complement activation, ELISA 75-kD secretory form inflammation,