Technological advances continue to expand the use of proteomics in medicine. In this Review, the authors discuss proteomics research findings in nephrology and the potential, as well as the limitations, of using proteomics techniques to uncover disease mechanisms and develop new therapeutic strategies.
Tools and technologies
Important advances in our understanding of kidney development and renal function and disease have been aided by the use of new technologies and by studies in model organisms. In this article series, Nature Reviews Nephrology presents articles that explore the tools and techniques that are improving our understanding of renal development, physiology and disease mechanisms as well as contributing to advances in the screening, diagnosis and management of kidney diseases.
Reviews and Perspectives
This Review provides an overview of fluorescence-based microscopy techniques that have been used to study molecular processes within the kidney. The authors describe how the development of cutting-edge technologies has enabled high spatiotemporal resolution of molecular interactions and processes, and how these approaches have aided our understanding of kidney dynamics.
Ontologies are powerful tools that facilitate the integration of large and disparate data sets. Here, researchers from the Kidney Precision Medicine Project provide an introduction to ontologies, including those developed by the consortium, describing how these will be used to improve the annotation of kidney-relevant data, eventually leading to new definitions of kidney disease in support of precision medicine.
Developments in digital pathology and computational image analysis have the potential to identify new disease mechanisms, improve disease classification and prognostication, and ultimately aid the identification of targeted therapies. In this Review, the authors provide an outline of the digital ecosystem in nephropathology and describe potential applications and challenges associated with the emerging armamentarium of technologies for image analysis.
Classification of kidney diseases according to their molecular mechanisms has potential to improve patient outcomes through the identification of targeted therapeutic approaches. This Review provides an overview of the ways in which omics and other data types can be integrated to enhance our understanding of the mechanisms underlying kidney function and failure.
Sullivan and Susztak examine the process of translating data on genetic variants associated with common kidney diseases into information about the underlying disease mechanisms. The authors propose that identification of causal variants, genetic regulatory mechanisms, target-gene products and disease-associated phenotypes is crucial to this process.
This Review provides the non-expert reader with an overview of the different steps involved in the analysis of single-cell RNA sequencing data. The authors also provide insight into the strengths and pitfalls of available analysis tools.
Design and application of single-cell RNA sequencing to study kidney immune cells in lupus nephritis
Applying single-cell RNA sequencing (scRNA-seq) to human tissues can reveal the phenotypic diversity of resident and infiltrating cells at high resolution. In this Review, the authors examine important design considerations for applying this technology to kidney cells and discuss current findings from scRNA-seq studies of lupus nephritis.
In this Review, Stewart and colleagues describe how single-cell technologies, in particular single-cell RNA sequencing, can be used to map the complex immune landscape within organs, and how such technologies might provide insights into the role of the immune system in kidney health and disease pathogenesis.
The field of nephrology has conducted fewer trials than other medical specialties. Here, the authors discuss how innovations in trial design and conduct could help achieve the goal of conducting a greater number of larger renal trials.
Kidney organoids have the potential to advance the field of nephrology. Here, the author discusses progress in the development of kidney organoids and describes remaining challenges to the use of these cultures for the study of kidney physiology and disease.
The application of precision gene editing has great potential to accelerate basic research and advance clinical practice in nephrology. Here, the authors discuss this technology and the challenges and potential of genome editing in the kidney.
Technological advances are providing unprecedented opportunities to analyse biological systems at the single-cell level. This Review describes the fundamental concepts of single-cell RNA analysis and specific applications of the technology for the study of development, cancer and normal and diseased kidneys.
Current in vitro nephrotoxicity screens are poorly predictive of toxicity in humans. Here, the authors describe mechanisms of nephrotoxic injury, the functional features of tubular cell models that are essential for predicting the toxicity of pharmaceutical compounds, and novel in vitro cell models under development.
News and comment
The drug development pipeline for kidney diseases is plagued with challenges ranging from an insufficient understanding of disease mechanisms to a lack of robust preclinical models. Bioengineering approaches have the potential to streamline preclinical drug discovery efforts and improve the success of clinical trials for kidney disease.
Artificial intelligence is increasingly being used to improve diagnosis and prognostication for acute and chronic kidney diseases. Studies with this objective published in 2019 relied on a variety of available data sources, including electronic health records, intraoperative physiological signals, kidney ultrasound imaging, and digitized biopsy specimens.
Single-cell genomics provide a powerful approach to investigate the intrinsic complexity of the kidney and understand the diverse cell types and states that exist during kidney development, homeostasis and disease. Several advances were made in 2019 that enhance our understanding of kidney immune cell states in health and disease and the quality of current kidney organoid model systems for studying human diseases.
2019 saw advances in the generation of induced pluripotent stem cell (iPSC)-derived nephron progenitors and in our understanding of how nephrons form in a kidney organoid. Fundamental studies of regeneration in zebrafish continue to provide vital clues as to how we might use iPSC-derived cells to regenerate a human nephron in vivo.
Once confined to the world of science fiction, advances in information technology, particularly in computational and storage resources, have enabled use of artificial intelligence in medicine to become a reality. Two new studies report the use of deep learning — currently the most promising algorithmic artificial intelligence approach — in kidney pathology.
A new study of deep learning based on electronic health records promises to forecast acute kidney injury up to 48 hours before it can be diagnosed clinically. However, employing data science to predict acute kidney injury might be more challenging than it seems.
To advance kidney discovery, our community is driven to maximize the utility of genomic data that we all generate. We can best accomplish this through excellence in appropriately incorporating publicly available genomic data into our research efforts and by enthusiastically embracing widespread data sharing in a manner that facilitates its broad use.
Discoveries in 2018 using single-cell sequencing and gene-editing technologies have revealed their transformative potential for the investigation of kidney physiology and disease. Their promise is matched by the speed of their evolution.
A new study discovered thousands of expression quantitative trait loci (eQTLs) in the renal glomerular and tubulointerstitial compartments and integrated these data with other omics data sets to identify genes with roles in the pathogenesis of chronic kidney disease. This report reinforces the necessity of using compartment-derived eQTLs to advance kidney genomic discovery.
Technologies such as proteomics provide a snapshot of a specific cellular state but are unable to directly record successive signalling events. Two new CRISPR-mediated analogue multi-event recording apparatus (CAMERA) systems enable sequential recording of endogenous and exogenous signalling events by targeted DNA modifications, thereby allowing systematic interrogation of different cellular states.