Introduction: Systems Biology of Kidney Disease

The progression from linear hypothesis testing to a broad, unbiased view of biological disturbances is fast upon us. Nephrology has been somewhat slow to move from a strict physiology- and hemodynamic-based discipline to the molecular age and has lagged behind with respect to novel therapeutics and diagnostics. However, in the past few years, nephrology has been moving forward rapidly to embrace Big Data and multi-omic tools. Moving toward a systems biology perspective is a major step forward. In September 2016, the ISN presented a Forefronts Program entitled “The Metabolome and Microbiome in Kidney Disease” in San Diego, CA, which captured many of the features of Big Data and systems biology.

The Forefronts Symposium was well attended and had a lively and exciting program. The major theme of the Symposium was understanding the metabolic basis of the onset and progression of kidney disease and the role of gut microbiota in accelerating this process. Major topics addressed during the Symposium included the impact of systems biology tools on experimental models of kidney disease and the application to human data using transcriptomics and metabolomics.

The mitochondrion recently has emerged as a key organelle that has been identified to be important in pathophysiological processes via multiple unbiased omics approaches from human and animal studies. Mitochondrial dysfunction is likely to be of critical significance in the development and progression of chronic kidney disease (CKD) and acute kidney injury. Indeed, because the kidney takes up 25% of the cardiac blood flow and up to 40% of oxygen uptake, it is not surprising that mitochondrial function will be closely connected with the workload capacity of the kidney. Metabolic stressors such as hyperglycemia have been shown to have major effects on mitochondrial function in animal models, as discussed by Forbes et al in this issue. The metabolic disturbances that characterize mitochondrial function have been viewed as a Warburg-type effect by Sharma et al and thus share similar metabolic disturbances with cancer metabolism. Indeed, an oncometabolite, fumarate, recently was found to be increased in animal models of diabetic kidney disease (DKD) and in patients with DKD.

Transcriptomic studies performed on patient and mouse samples with CKD or fibrosis have reproducibly identified the dysregulation of metabolism-associated genes. Renal tubule cells mostly depend on mitochondrial fatty acid oxidation for energy generation. Peroxisome proliferator–activated receptor γ coactivator 1α is a key transcriptional regulator of mitochondrial biogenesis and function. Studies from Susztak’s laboratory and several other laboratories have shown that manipulating peroxisome proliferator–activated receptor γ coactivator 1α expression has a significant effect on kidney fibrosis development.

Metabolomic studies in nephrology research seeks to identify novel markers and causal participants in the pathogenesis of kidney disease and its complications. Technological advances in mass spectrometry–based metabolomic and lipidomic platforms have provided the opportunity for comprehensive profiling of metabolites and lipids in biofluids and kidney tissue and shown alterations in the metabolome and lipidome that occur in CKD and DKD. Drs. Afshinnia and Pennathur describe the workflow of lipidomic profiling, data processing, and analysis, as well as the application of lipidomic platforms in identifying biomarkers of CKD progression as well as understanding disease mechanisms in model systems. Dr. Rhee discusses the kidney’s broad and heterogeneous impact on circulating metabolites, with progressive loss of kidney function resulting in a multitude of small molecule alterations. Dr. Rhee and others also highlight that an increasing number of circulating metabolites have been shown to possess functional roles. Drs. Kottgen and Karsten-muller illustrate how the coupling of genomics and metabolomics in genome-wide association analyses of metabolites can be used to illuminate mechanisms underlying human metabolism, with a special focus on insights relevant to nephrology.

Dr. Weiss discussed changes in metabolic pathways in renal cell cancer mediated by oncogenes that alter cellular bioenergetics and metabolism. This adaptation of classic biochemical pathways to the tumor’s growth advantage, a process termed “metabolic reprogramming,” is discussed. Dr. Shayman’s work has focused on the role of sphingolipids in normal physiology and pathophysiology. Roles of these bioactive lipids in the context of a monogenic lysosomal storage disease, Fabry disease, and more common renal disorders such as DKD and polycystic kidney disease, are discussed. The targeting of these pathways with orally available small molecule inhibitors such as eluglistat for lysosomal storage diseases are expanding treatment options for rare diseases as well as raise the possibility of broader applicability for more common kidney diseases. Finally, Dr. Tang provides a broad overview on the emerging role of gut microbiota in fueling systemic inflammation in a variety of disorders including CKD. Importantly, work from his group and others highlight the intricate balance among diet, gut microbial metabolism, and the accumulation of circulating downstream metabolic products that affect pathophysiology. Potential approaches targeting gut microbiota for cardiovascular risk reduction in CKD are discussed.

Taken together, these themes emphasize the importance of viewing systemic and renal metabolomics and lipidomics at the systems level, recognizing the diverse origins, and of blood and tissue metabolites and their contribution to pathophysiology. The exciting path of systems biology tools using metabolomics and the microbiome has led to many initiatives that investigators in the field of nephrology will pursue in the near future. The Kidney Precision Medicine Program and the TRIDENT initiative are independent efforts to query the human kidney biopsy with a variety of metabolomics tools. Integrating the data sets with prospective, longitudinal studies will bring new targets for therapeutics and redefine kidney diseases with a molecular signature, similar to what has been performed in oncology. The potential for nephrologists to lead the way in precision medicine and develop new therapeutics will be exciting for young physicians entering the field. Clearly, a systems approach incorporating metabolomics and the microbiome is critical to embrace the new era of Big Data.