Nature Reviews Nephrology最新文献

Chronic kidney disease (CKD), defined as persistent (>3 months) kidney functional loss, has a growing prevalence (>10% worldwide population) and limited treatment options. Fibrosis driven by the aberrant accumulation of extracellular matrix is the final common pathway of nearly all types of chronic repetitive injury in the kidney and is considered a hallmark of CKD. Myofibroblasts are key extracellular matrix-producing cells that are activated by crosstalk between damaged tubules and immune cells. Emerging evidence indicates that metabolic alterations are crucial contributors to the pathogenesis of kidney fibrosis by affecting cellular bioenergetics and metabolite signalling. Immune cell functions are intricately connected to their metabolic characteristics, and kidney cells seem to undergo cell-type-specific metabolic shifts in response to damage, all of which can determine injury and repair responses in CKD. A detailed understanding of the heterogeneity in metabolic reprogramming of different kidney cellular subsets is essential to elucidating communication processes between cell types and to enabling the development of metabolism-based innovative therapeutic strategies against CKD.

Genome-wide association studies (GWAS) have uncovered thousands of risk variants that individually have small effects on the risk of human diseases, including chronic kidney disease, type 2 diabetes, heart diseases and inflammatory disorders, but cumulatively explain a substantial fraction of disease risk, underscoring the complexity and pervasive polygenicity of common disorders. This complexity poses unique challenges to the clinical translation of GWAS findings. Polygenic scores combine small effects of individual GWAS risk variants across the genome to improve personalized risk prediction. Several polygenic scores have now been developed that exhibit sufficiently large effects to be considered clinically actionable. However, their clinical use is limited by their partial transferability across ancestries and a lack of validated models that combine polygenic, monogenic, family history and clinical risk factors. Moreover, prospective studies are still needed to demonstrate the clinical utility and cost-effectiveness of polygenic scores in clinical practice. Here, we discuss evolving methods for developing polygenic scores, best practices for validating and reporting their performance, and the study designs that will empower their clinical implementation. We specifically focus on the polygenic scores relevant to nephrology and other chronic, complex diseases and review their key limitations, necessary refinements and potential clinical applications.

IgA nephropathy (IgAN) is a common form of primary glomerulonephritis and represents an important cause of chronic kidney disease globally, with observational studies indicating that most patients are at risk of developing kidney failure within their lifetime. Several research advances have provided insights into the underlying disease pathogenesis, framed by a multi-hit model whereby an increase in circulating IgA1 that lacks galactose from its hinge region — probably derived from the mucosal immune system — is followed by binding of specific IgG and IgA antibodies, generating immune complexes that deposit within the glomeruli, which triggers inflammation, complement activation and kidney damage. Although treatment options are currently limited, new therapies are rapidly emerging that target different pathways, cells and mediators involved in the disease pathogenesis, including B cell priming in the gut mucosa, the cytokines APRIL and BAFF, plasma cells, complement activation and endothelin pathway activation. As more treatments become available, there is a realistic possibility of transforming the long-term outlook for many individuals with IgAN.

Randomized controlled trials (RCT) are often regarded as the ‘gold standard’ of clinical evidence. However, their strict eligibility criteria can impact cohort diversity and limit the inclusion of some subgroups, including patients with comorbidities, older individuals or those from minority ethnic groups. Observational data, including data from electronic health records, can be used to bridge the gap in evidence but are subject to bias and confounding owing to the lack of randomization.

The ‘target trial’ emulation framework, which emulates the design of a hypothetical ‘target trial’ using observational data, has increasingly been used for causal inference^1,2. Despite this approach implementing design decisions to limit the effects of bias and confounding, uncertainty remains as to whether the observed result aligns with those which would have been obtained in RCT settings. Using a specified existing RCT (the ‘reference trial’) offers an opportunity to add further validity to inferences. This goal is achieved by basing the target trial design on the reference trial and benchmarking findings from the emulated study against the reference trial results. This approach adds confidence to the results obtained from the observational study before extending analysis to trial-underrepresented groups.

Amino acids form peptides and proteins and are therefore considered the main building blocks of life. The kidney has an important but under-appreciated role in the synthesis, degradation, filtration, reabsorption and excretion of amino acids, acting to retain useful metabolites while excreting potentially harmful and waste products from amino acid metabolism. A complex network of kidney transporters and enzymes guides these processes and moderates the competing concentrations of various metabolites and amino acid products. Kidney amino acid metabolism contributes to gluconeogenesis, nitrogen clearance, acid–base metabolism and provision of fuel for tricarboxylic acid cycle and urea cycle intermediates, and is thus a central hub for homeostasis. Conversely, kidney disease affects the levels and metabolism of a variety of amino acids. Here, we review the metabolic role of the kidney in amino acid metabolism and describe how different diseases of the kidney lead to aberrations in amino acid metabolism. Improved understanding of the metabolic and communication routes that are affected by disease could provide new mechanistic insights into the pathogenesis of kidney diseases and potentially enable targeted dietary or pharmacological interventions.

The hyaluronan (HA) matrix in the tissue microenvironment is crucial for maintaining homeostasis by regulating inflammatory signalling, endothelial-mesenchymal transition and cell migration. During development, covalent modifications and osmotic swelling of HA create mechanical forces that initiate midgut rotation, vascular patterning and branching morphogenesis. Together with its main cell surface receptor, CD44, HA establishes a physicochemical scaffold at the cell surface that facilitates the interaction and clustering of growth factors and receptors that is required for normal physiology. High-molecular-weight HA, tumour necrosis factor-stimulated gene 6, pentraxin 3 and CD44 form a stable pericellular matrix that promotes tissue regeneration and reduces inflammation. By contrast, breakdown of high-molecular-weight HA into depolymerized fragments by hyaluronidases triggers inflammatory signalling, leukocyte migration and angiogenesis, contributing to tissue damage and fibrosis in kidney disease. Targeting HA metabolism is challenging owing to its dynamic regulation and tissue-specific functions. Nonetheless, modulating HA matrix functions by targeting its binding partners holds promise as a therapeutic strategy for restoring tissue homeostasis and mitigating pathological processes. Further research in this area is warranted to enable the development of novel therapeutic approaches for kidney and other diseases characterized by dysregulated HA metabolism.