Non-invasive assessment of exfoliated kidney cells extracted from urine using multispectral autofluorescence features

Mahbub, Saabah B.; Nguyen, Long T.; Habibalahi, Abbas; Campbell, Jared M.; Anwer, Ayad G.; Qadri, Uzair M.; Gill, Anthony J.; Chou, Angela; Gosnell, Martin E.; Pollock, Carol; Saad, Sonia; Goldys, Ewa M.

doi:10.1038/s41598-021-89758-4

Cited by 12 publications

(24 citation statements)

References 40 publications

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“…The utility of exfoliated PTCs from urine has proven to be clinically valuable in prognosticating the degree of disease for various tubular diseases that are associated with CKD, including conditions with a genetic predisposition [ 22 , 50 , 51 ]. It is suggested that exfoliated PTCs from urine may represent the degree of pathology in the kidneys [ 22 , 52 ]. Previous studies noted the number of exfoliated PTCs correlating with kidney function decline in DKD, though this may not correspond to the degree of kidney injury in all cases [ 52 , 53 ].…”

Section: Exfoliated Proximal Tubule Cellsmentioning

confidence: 99%

Exfoliated Kidney Cells from Urine for Early Diagnosis and Prognostication of CKD: The Way of the Future?

Goldys

Pollock

et al. 2022

IJMS

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Chronic kidney disease (CKD) is a global health issue, affecting more than 10% of the worldwide population. The current approach for formal diagnosis and prognostication of CKD typically relies on non-invasive serum and urine biomarkers such as serum creatinine and albuminuria. However, histological evidence of tubulointerstitial fibrosis is the ‘gold standard’ marker of the likelihood of disease progression. The development of novel biomedical technologies to evaluate exfoliated kidney cells from urine for non-invasive diagnosis and prognostication of CKD presents opportunities to avoid kidney biopsy for the purpose of prognostication. Efforts to apply these technologies more widely in clinical practice are encouraged, given their potential as a cost-effective approach, and no risk of post-biopsy complications such as bleeding, pain and hospitalization. The identification of biomarkers in exfoliated kidney cells from urine via western blotting, enzyme-linked immunosorbent assay (ELISA), immunofluorescence techniques, measurement of cell and protein-specific messenger ribonucleic acid (mRNA)/micro-RNA and other techniques have been reported. Recent innovations such as multispectral autofluorescence imaging and single-cell RNA sequencing (scRNA-seq) have brought additional dimensions to the clinical application of exfoliated kidney cells from urine. In this review, we discuss the current evidence regarding the utility of exfoliated proximal tubule cells (PTC), podocytes, mesangial cells, extracellular vesicles and stem/progenitor cells as surrogate markers for the early diagnosis and prognostication of CKD. Future directions for development within this research area are also identified.

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Section: Exfoliated Proximal Tubule Cellsmentioning

confidence: 99%

Exfoliated Kidney Cells from Urine for Early Diagnosis and Prognostication of CKD: The Way of the Future?

Goldys

Pollock

et al. 2022

IJMS

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“…Proximal tubule cells (PTCs) were extracted from the urine (100ml) of the above 2 groups using immunomagnetic separation with antibodies against aminopeptidase N (CD13) and sodium/glucose co-transporter 2 (SGLT2) as we have previously described (8). Briefly, urine was spun at 3000/4000 rpm for 20 min (at 4 o C) to pellet the urinary exfoliated cells, which were then washed twice with phosphate buffered saline (PBS).…”

Section: Renal Proximal Tubule Cell Isolation From Urinementioning

confidence: 99%

“…To confirm specific isolation of PTCs, an aliquot of isolated cells was incubated with antibodies against CD13, SGLT2 and angiotensinogen (AGT) at 4°C overnight as we have previously described (8). They were then washed with PBS and stained with the relevant secondary antibodies.…”

Section: Confocal Microscopymentioning

confidence: 99%

“…Kidney cells including podocytes, tubular epithelial cells, urothelial cells, and other cell types are continuously shed into urine even in a healthy state (7) and their condition is likely to reflect the changing physiology of the kidneys in CKD, e.g. tubulointerstitial fibrosis (8). To date, there have been few studies using urinary cells as a potential diagnostic tool to assess kidney functional and structural abnormalities (8).…”

Section: Introductionmentioning

confidence: 99%

“…tubulointerstitial fibrosis (8). To date, there have been few studies using urinary cells as a potential diagnostic tool to assess kidney functional and structural abnormalities (8). This is largely due lack of sensitive diagnostic methods to identify disease-related properties of these cells.…”

Section: Introductionmentioning

confidence: 99%

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moRphology - dEep Learning Imaging Cells (RELIC) - to Differentiate Between Normal and Pathological Kidney Exfoliated Cells

Habibalahi

Campbell

Mahbub

et al. 2022

Preprint

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Chronic kidney disease (CKD) is characterised by progressive loss of kidney function leading to kidney failure. Significant kidney damage can occur before symptoms are detected. Currently, kidney tissue biopsy is the gold standard for evaluation of renal damage and CKD severity. This study explores how to precisely quantify morphology characteristics of kidney cells exfoliated into urine, with a view to establish a future urine-based non-invasive diagnostic for CKD. We report the development of a novel deep learning method, which was able to discover a RELIC (moRphology dEep Learning Imaging Cells) signature that can differentiate between kidney cells exfoliated in human urine of and CKD patients with varying degree of kidney damage and non-CKD controls. Exfoliated proximal tubule cells (PTCs) originating from kidneys were isolated from the urine of patients with different levels of kidney damage using previously published methods. An advanced combination of artificial intelligence techniques, deep learning, swarm intelligence, and discriminative analysis was used to discover a RELIC signature in brightfield microscopy images of exfoliated PTCs. Kidney damage in the study subjects was characterised by assessing kidney tissues obtained through a nephrectomy or kidney biopsy. A special deep learning algorithm was developed and trained to create a predictive tool. The algorithm was then used to analyse data from patients with normal and fibrotic kidneys. Data were then classified according to different groups (healthy or fibrosis) and clustering of the training and validation cells was determined for model validation. We developed a novel deep learning method, to obtain RELIC signatures and identify specific deep morphological features which can be used to differentiate urinary PTC cells shed by people with CKD (confirmed by tissue histology obtained from an invasive kidney biopsy) from those without CKD, with a discriminatory accuracy of 82%. We identified a RELIC signature which can be used on a collection of bright field images of exfoliated urinary PTCs to create a predictive tool and differentiate between normal and pathological kidney cells. This study, for the first time, provides a proof of concept that urinary exfoliated tubule cells in patients with kidney fibrosis and healthy controls differ in appearance (morphology) as observed under a basic brightfield microscope. The results suggest that morphological signatures of exfoliated PTCs have the potential to serve as a non-invasive marker of kidney fibrosis.

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Label‐Free Assessment of Key Biological Autofluorophores: Material Characteristics and Opportunities for Clinical Applications

Campbell,

Gosnell,

Agha

et al. 2024

Advanced Materials

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Autofluorophores are endogenous fluorescent compounds that naturally occur in the intra and extracellular spaces of all tissues and organs. Most have vital biological functions – like the metabolic cofactors NAD(P)H and FAD+, as well as the structural protein collagen. Others have been considered to be waste products – like lipofuscin and advanced glycation end products – which accumulate with age and are associated with cellular dysfunction. Due to their natural fluorescence these materials have great utility for enabling non‐invasive, label‐free assays with direct ties to biological function. Numerous technologies, with different advantages and drawbacks, have been applied to their assessment, including fluorescence lifetime imaging microscopy, hyperspectral microscopy, and flow cytometry. Here, we review the applications of label‐free autofluorophore assessment for clinical and health‐research applications, with specific attention to biomaterials, disease detection, surgical guidance, treatment monitoring and tissue assessment – fields which greatly benefit from non‐invasive methodologies capable of continuous, in vivo characterisation.This article is protected by copyright. All rights reserved

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Non-invasive assessment of exfoliated kidney cells extracted from urine using multispectral autofluorescence features

Cited by 12 publications

References 40 publications

Exfoliated Kidney Cells from Urine for Early Diagnosis and Prognostication of CKD: The Way of the Future?

Exfoliated Kidney Cells from Urine for Early Diagnosis and Prognostication of CKD: The Way of the Future?

moRphology - dEep Learning Imaging Cells (RELIC) - to Differentiate Between Normal and Pathological Kidney Exfoliated Cells

Label‐Free Assessment of Key Biological Autofluorophores: Material Characteristics and Opportunities for Clinical Applications

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