Deep learning-based segmentation and quantification of podocyte foot process morphology suggests differential patterns of foot process effacement across kidney pathologies.

Autor:	Unnersjö-Jess D; Department II of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Center for Molecular Medicine Cologne (CMMC), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany; MedTechLabs, Karolinska University Hospital, Solna, Sweden; Division of Renal Medicine, Department of Clinical Sciences, Intervention and Technology, Karolinska Institute, Stockholm, Sweden; Science for Life Laboratory, Department of Applied Physics, Royal Institute of Technology, Solna, Sweden. Electronic address: daviduj@kth.se., Butt L; Department II of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Center for Molecular Medicine Cologne (CMMC), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. Electronic address: Linus.Butt@uk-koeln.de., Höhne M; Department II of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany., Sergei G; Center for Molecular Medicine Cologne (CMMC), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany., Fatehi A; Center for Molecular Medicine Cologne (CMMC), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany., Witasp A; Division of Renal Medicine, Department of Clinical Sciences, Intervention and Technology, Karolinska Institute, Stockholm, Sweden., Wernerson A; Division of Renal Medicine, Department of Clinical Sciences, Intervention and Technology, Karolinska Institute, Stockholm, Sweden., Patrakka J; KI/AZ Integrated CardioMetabolic Center, Department of Laboratory Medicine, Karolinska Institutet at Karolinska University Hospital Huddinge, Stockholm, Sweden., Hoyer PF; Pediatric Nephrology, Pediatrics II, University of Duisburg-Essen, Essen, Germany., Blom H; MedTechLabs, Karolinska University Hospital, Solna, Sweden; Science for Life Laboratory, Department of Applied Physics, Royal Institute of Technology, Solna, Sweden., Schermer B; Department II of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Center for Molecular Medicine Cologne (CMMC), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany., Bozek K; Center for Molecular Medicine Cologne (CMMC), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. Electronic address: k.bozek@uni-koeln.de., Benzing T; Department II of Internal Medicine, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Center for Molecular Medicine Cologne (CMMC), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany.
Jazyk:	angličtina
Zdroj:	Kidney international [Kidney Int] 2023 Jun; Vol. 103 (6), pp. 1120-1130. Date of Electronic Publication: 2023 Mar 27.
DOI:	10.1016/j.kint.2023.03.013
Abstrakt:	Morphological alterations at the kidney filtration barrier increase intrinsic capillary wall permeability resulting in albuminuria. However, automated, quantitative assessment of these morphological changes has not been possible with electron or light microscopy. Here we present a deep learning-based approach for segmentation and quantitative analysis of foot processes in images acquired with confocal and super-resolution fluorescence microscopy. Our method, Automatic Morphological Analysis of Podocytes (AMAP), accurately segments podocyte foot processes and quantifies their morphology. AMAP applied to a set of kidney diseases in patient biopsies and a mouse model of focal segmental glomerulosclerosis allowed for accurate and comprehensive quantification of various morphometric features. With the use of AMAP, detailed morphology of podocyte foot process effacement was found to differ between categories of kidney pathologies, showed detailed variability between diverse patients with the same clinical diagnosis, and correlated with levels of proteinuria. AMAP could potentially complement other readouts such as various omics, standard histologic/electron microscopy and blood/urine assays for future personalized diagnosis and treatment of kidney disease. Thus, our novel finding could have implications to afford an understanding of early phases of kidney disease progression and may provide supplemental information in precision diagnostics. (Copyright © 2023 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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