Diabetes is associated with altered cellular metabolism, but how altered metabolism contributes to the development of diabetic complications is unknown. We used the BKS db/db diabetic mouse model to investigate changes in carbohydrate and lipid metabolism in kidney cortex, peripheral nerve, and retina. A systems approach using transcriptomics, metabolomics, and metabolic flux analysis identified tissue-specific differences, with increased glucose and fatty acid metabolism in the kidney, a moderate increase in the retina, and a decrease in the nerve. In the kidney, increased metabolism was associated with enhanced protein acetylation and mitochondrial dysfunction. To confirm these findings in human disease, we analyzed diabetic kidney transcriptomic data and urinary metabolites from a cohort of Southwestern American Indians. The urinary findings were replicated in 2 independent patient cohorts, the Finnish Diabetic Nephropathy and the Family Investigation of Nephropathy and Diabetes studies. Increased concentrations of TCA cycle metabolites in urine, but not in plasma, predicted progression of diabetic kidney disease, and there was an enrichment of pathways involved in glycolysis and fatty acid and amino acid metabolism. Our findings highlight tissue-specific changes in metabolism in complication-prone tissues in diabetes and suggest that urinary TCA cycle intermediates are potential prognostic biomarkers of diabetic kidney disease progression.

Studies of lipids in CKD, including ESRD, have been limited to measures of conventional lipid profiles. We aimed to systematically identify 17 different lipid classes and associate the abundance thereof with alterations in acylcarnitines, a metric of β -oxidation, across stages of CKD. From the Clinical Phenotyping Resource and Biobank Core (CPROBE) cohort of 1235 adults, we selected a panel of 214 participants: 36 with stage 1 or 2 CKD, 99 with stage 3 CKD, 61 with stage 4 CKD, and 18 with stage 5 CKD. Among participants, 110 were men (51.4%), 64 were black (29.9%), and 150 were white (70.1%), and the mean (SD) age was 60 (16) years old. We measured plasma lipids and acylcarnitines using liquid chromatography-mass spectrometry. Overall, we identified 330 different lipids across 17 different classes. Compared with earlier stages, stage 5 CKD associated with a higher abundance of saturated C16–C20 free fatty acids (FFAs) and long polyunsaturated complex lipids. Long-chain–to–intermediate-chain acylcarnitine ratio, a marker of efficiency of β -oxidation, exhibited a graded decrease from stage 2 to 5 CKD ( P <0.001). Additionally, multiple linear regression revealed that the long-chain–to–intermediate-chain acylcarnitine ratio inversely associated with polyunsaturated long complex lipid subclasses and the C16–C20 FFAs but directly associated with short complex lipids with fewer double bonds. We conclude that increased abundance of saturated C16–C20 FFAs coupled with impaired β -oxidation of FFAs and inverse partitioning into complex lipids may be mechanisms underpinning lipid metabolism changes that typify advancing CKD.

Diabetes is characterized by altered metabolism of key molecules and regulatory pathways. The phenotypic expression of diabetes and associated complications encompasses complex interactions between genetic, environmental, and tissue-specific factors that require an integrated understanding of perturbations in the network of genes, proteins, and metabolites. Metabolomics attempts to systematically identify and quantitate small molecule metabolites from biological systems. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled identification of complex metabolic phenotypes. Continued development of bioinformatics and analytical strategies has facilitated the discovery of causal links in understanding the pathophysiology of diabetes and its complications. Here, we summarize the metabolomics workflow, including analytical, statistical, and computational tools, highlight recent applications of metabolomics in diabetes research, and discuss the challenges in the field.

Primary cilia dysfunction alters renal tubular cell proliferation and differentiation and associates with accelerated cyst formation in polycystic kidney disease. However, the mechanism leading from primary ciliary dysfunction to renal cyst formation is unknown. We hypothesize that primary cilia prevent renal cyst formation by suppressing pathologic tubular cell hypertrophy and proliferation. Unilateral nephrectomy initiates tubular cell hypertrophy and proliferation in the contralateral kidney and provides a tool to examine primary cilia regulation of renal hypertrophy. Conditional knockout of the primary cilia ift88 gene leads to delayed, adult-onset renal cystic disease, which provides a window of opportunity to conduct unilateral nephrectomy and examine downstream kinetics of renal hypertrophy and cyst formation. In wild-type animals, unilateral nephrectomy activated the mTOR pathway and produced appropriate structural and functional hypertrophy without renal cyst formation. However, in ift88 conditional knockout animals, unilateral nephrectomy triggered increased renal hypertrophy and accelerated renal cyst formation, leading to renal dysfunction. mTOR signaling also increased compared with wild-type animals, suggesting a mechanistic cascade starting with primary ciliary dysfunction, leading to excessive mTOR signaling and renal hypertrophic signaling and culminating in cyst formation. These data suggest that events initiating hypertrophic signaling, such as structural or functional loss of renal mass, may accelerate progression of adult polycystic kidney disease toward end-stage renal disease.

Lipid accumulation is a pathological feature of every type of kidney injury. Despite this striking histological feature, physiological accumulation of lipids in the kidney is poorly understood. We studied whether the accumulation of lipids in the fasted kidney are derived from lipoproteins or NEFAs. With overnight fasting, kidneys accumulated triglyceride, but had reduced levels of ceramide and glycosphingolipid species. Fasting led to a nearly 5-fold increase in kidney uptake of plasma [¹⁴C]oleic acid. Increasing circulating NEFAs using a β adrenergic receptor agonist caused a 15-fold greater accumulation of lipid in the kidney, while mice with reduced NEFAs due to adipose tissue deficiency of adipose triglyceride lipase had reduced triglycerides. Cluster of differentiation (Cd)36 mRNA increased 2-fold, and angiopoietin-like 4 (Angptl4), an LPL inhibitor, increased 10-fold. Fasting-induced kidney lipid accumulation was not affected by inhibition of LPL with poloxamer 407 or by use of mice with induced genetic LPL deletion. Despite the increase in CD36 expression with fasting, genetic loss of CD36 did not alter fatty acid uptake or triglyceride accumulation. Our data demonstrate that fasting-induced triglyceride accumulation in the kidney correlates with the plasma concentrations of NEFAs, but is not due to uptake of lipoprotein lipids and does not involve the fatty acid transporter, CD36.

Lipids are ubiquitous metabolites with diverse functions; abnormalities in lipid metabolism appear related to complications from multiple diseases, including type 2 diabetes. Through technological advances, the entire lipidome has been characterized, and researchers now need computational approaches to better understand lipid network perturbations in different diseases. Using a mouse model of type 2 diabetes with microvascular complications, we examined lipid levels in plasma and in renal, neural, and retinal tissues to identify shared and distinct lipid abnormalities. We used correlation analysis to construct interaction networks in each tissue, to associate changes in lipids with changes in enzymes of lipid metabolism, and to identify overlap of co-regulated lipid subclasses between plasma and each tissue to define subclasses of plasma lipids to use as surrogates of tissue lipid metabolism. Lipid metabolism alterations were mostly tissue specific in the kidney, nerve and retina; no lipid changes correlated between the plasma and all three tissue types. However, alterations in diacylglycerol and in lipids containing arachidonic acid, an inflammatory mediator, were shared among the tissue types, and the highly saturated cholesterol esters were similarly co-regulated between plasma and each tissue type in the diabetic mouse. Our results identified several patterns of altered lipid metabolism that may help identify pathogenic alterations in different issues and could be used as biomarkers in future research into diabetic microvascular tissue damage.