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Review
. 2018 Mar;25(2):192-201.
doi: 10.1053/j.ackd.2017.11.004.

Role of Kidney Biopsies for Biomarker Discovery in Diabetic Kidney Disease

Helen C Looker  1 , Michael Mauer  1 , Robert G Nelson  2
Affiliations
Review

Role of Kidney Biopsies for Biomarker Discovery in Diabetic Kidney Disease

Helen C Looker et al. Adv Chronic Kidney Dis. 2018 Mar.

Abstract

Although estimated glomerular filtration rate and albuminuria are well-established biomarkers of diabetic kidney disease (DKD), additional biomarkers are needed, especially for the early stages of the disease when both albuminuria and estimated glomerular filtration rate may still be in the normal range and are less helpful for identifying those at risk of progression. Traditional biomarker studies for early DKD are challenging because of a lack of good early clinical end points, and most rely on changes in existing imprecise biomarkers to assess the value of new biomarkers. There are well-characterized changes in kidney structure, however, that are highly correlated with kidney function, always precede the clinical findings of DKD and, at preclinical stages, predict DKD progression. These structural parameters may thus serve as clinically useful end points for identifying new biomarkers of early DKD. In addition, investigators are analyzing tissue transcriptomic data to identify pathways involved in early DKD which may have associated candidate biomarkers measurable in blood or urine, and differentially expressed microRNAs and epigenetic modifications in kidney tissue are beginning to yield important observations which may be useful in identifying new clinically useful biomarkers. This review examines the emerging literature on the use of kidney tissue in biomarker discovery in DKD.

Keywords: Biomarkers; Diabetic kidney disease; Imaging; Kidney biopsy; Morphometry.

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Figures

Figure 1
Figure 1
Prognosis of CKD by GFR and albuminuria category. Green, low risk (if no other markers of kidney disease, no CKD); Yellow, moderately increased risk; Orange, high risk; Red, very high risk. CKD, chronic kidney disease; GFR, glomerular filtration rate; KDIGO, Kidney Disease: Improving Global Outcomes. Reprinted with permission from Definition and classification of CKD Kidney Int Suppl (2011). 2013 Jan;3(1):19–62.
Figure 2
Figure 2
Partial regression residual plot of the associations between tumor necrosis factor receptors (TNFRs), percent of normal endothelial cell fenestration (ECF), and mesangial fractional volume (VvMes). The residuals were computed from regressing each of the following variables: age, sex, diabetes duration, hemoglobin A1c, body mass index, and mean arterial pressure. Exclusion of the single outlier did not change the significance of associations between 2 morphometric variables. Reprinted with permission from Pavkov ME, Weil EJ, Fufaa GD, et al. Tumor necrosis factor receptors 1 and 2 are associated with early glomerular lesions in type 2 diabetes. Kidney Int. 2016;89:226–234. Copyright © International Society of Nephrology. Reprinted with permission from Looker HC and Nelson RG. Reading the tree leaves – how to enrich clinical trials of diabetic kidney disease Kidney Int. 2017;92:23–25.
Figure 3
Figure 3
Peripheral glomerular capillaries from a Pima Indian with type 2 diabetes. Arrows point to projections extending from the WBC to the adjacent endothelium within the glomerular capillary lumen. Transmission electron microscopy, ×3,000. WBC, white blood cell; GBM, glomerular basement membrane; P, podocyte foot processes; E, endothelial cell body; FE, fenestrated endothelium; CL, capillary lumen. Reprinted with permission from Wheelock KM, Saulnier PJ, Tanamas SK et al. White blood cell fractions correlate with lesions of diabetic kidney disease and predict loss of kidney function in type 2 diabetes. Nephrol Dial Transplant doi: 10.1093/ndt/gfx231.
Figure 4
Figure 4
Comparison of enriched biological processes in uncomplicated diabetes and incipient diabetic nephropathy. Significantly enriched biological processes were identified for each stage using Biological Networks Gene Ontology with Benjamini and Hochberg multiple testing correction (P<0.05) and then run on Enrichment Map with Jaccard coefficient of 0.5 (P value cut-off = 0.001; false discovery rate Q-value cut-off = 0.05). Each node represents an enriched biological process. Red node colors correspond to high enrichment, whereas gray node colors correspond to no enrichment. As shown in the figure legend, the outer circle color corresponds to the level of enrichment in uncomplicated diabetes, whereas the inner circle color corresponds to that in incipient diabetic nephropathy. Edge thickness denotes the number of overlapping markers between two connected nodes within uncomplicated diabetes (blue) and within incipient diabetic nephropathy (green). DM, diabetes mellitus; DN, diabetic nephropathy. Reprinted with permission from Van JAD, Scholey JW, Konvalinka. J Am Soc Nephrol. 2017 Apr;28(4):1050–1061.
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