Jeffrey R. Schelling

Type 2 diabetes affects more than 38 million people in the United States, and a major complication is kidney disease. During the analysis of lipotoxicity in diabetic kidney disease, global fatty acid transport protein 2 (FATP2) gene deletion was noted to markedly reduce plasma glucose in db/db mice due to sustained insulin secretion. To identify the mechanism, we observed that islet FATP2 expression was restricted to α cells and that α cell FATP2 was functional. Basal glucagon and alanine-stimulated gluconeogenesis were reduced in FATP2-KO db/db mice compared with db/db mice. Direct evidence of FATP2-KO–induced α cell–mediated glucagon-like peptide 1 (GLP-1) secretion included increased GLP-1 ⁺ α cell mass in FATP2-KO db/db mice, small-molecule FATP2 inhibitor enhancement of GLP-1 secretion in αTC1-6 cells and human islets, and exendin[9-39]-inhibitable insulin secretion in FATP2 inhibitor–treated human islets. FATP2-dependent enteroendocrine GLP-1 secretion was excluded by demonstration of similar glucose tolerance and plasma GLP-1 concentrations in db/db FATP2-KO mice following oral versus i.p. glucose loading, nonoverlapping FATP2 and preproglucagon mRNA expression, and lack of FATP2 and GLP-1 coimmunolocalization in the intestines. We conclude that FATP2 deletion or inhibition exerts glucose-lowering effects through α cell–mediated GLP-1 secretion and paracrine β cell insulin release.

Under physiologic conditions, proximal tubules depend on basolateral fatty acid (FA) uptake for metabolism. In pathophysiologic conditions due to glomerular filtration barrier disruption, albumin-bound FA undergo filtration and proximal tubule reabsorption, which leads to lipotoxicity and tubular atrophy. Apical proximal tubule albumin uptake is accomplished by the megalin/cubilin complex and receptor-mediated endocytosis, whereas apical proximal tubule FA uptake is primarily mediated by apical fatty acid transport protein-2 (FATP2). However, a commonly proposed (but untested) alternative model is that intact albumin-FA complex is co-transported by megalin/cubilin-mediated endocytosis, similar to apolipoproteins. Microperfused mouse proximal tubules demonstrated divergent one- vs. two-phase albumin and FA uptake kinetics, with significantly faster albumin compared to FA uptake. LLC-PK1, HPCT and OK proximal tubule cell lines all expressed megalin, cubilin and FATP2 mRNA, though in varying amounts. LLC-PK1 cells showed similar one-phase kinetics of dual fluorescently-labeled albumin and FA uptake, whereas HPCT cells demonstrated one-phase albumin and two-phase FA uptake kinetics, with significantly faster albumin compared to FA uptake (similar to perfused proximal tubules). FATP2 inhibition blocked FA uptake, but had no effect on albumin uptake in LLC-PK1 and HPCT cells. Megalin and cubilin deletion in OK cells inhibited albumin uptake, but had no effect on FA uptake. We conclude that apical proximal tubule albumin and FA are transported by distinct mechanisms, implying that FAs dissociate from albumin within the proximal tubule lumen prior to uptake.

Key Points: Higher urine levels of kidney injury molecule-1 and monocyte chemoattractant protein-1 were associated with higher risk of CKD progression. Higher urine levels of EGF were associated with lower risk of CKD progression. Urine kidney injury molecule-1, monocyte chemoattractant protein-1, and EGF may noninvasively assess tubule and interstitial health in diabetes and identify those at higher risk of CKD progression. Background: Urine biomarkers of kidney tubular health and inflammation may provide a noninvasive way to identify individuals with diabetes at higher risk for CKD progression given that the extent of tubulointerstitial pathology is related to progression of diabetic kidney disease. Methods: We performed a case-cohort study among 898 participants in the Chronic Renal Insufficiency Cohort with diabetes and eGFR 2. Of these individuals, the subcohort (N=599) was randomly selected from participants with urine samples available 1 year or less after enrollment to assay for urine proteins. Cases were participants who developed CKD progression (incident ESKD, or eGFR decline of 40% or greater from baseline). The median follow-up was 7.35 years. We studied urinary biomarkers of tubulointerstitial inflammation (monocyte chemoattractant protein-1 [MCP-1]), proximal tubular injury (kidney injury molecule-1 [KIM-1]), tubular resorptive capacity (α1-microglobulin), and tubular synthetic capacity (EGF and uromodulin). Weighted Cox regression models related urine biomarkers, standardized to urine creatinine (Cr), with CKD progression and were adjusted for CKD risk factors, including eGFR, and urine albumin-to-creatinine ratio. Results: In fully adjusted models, higher urine KIM-1/Cr was associated with higher risk of CKD progression (hazard ratio [HR], 1.16 per two-fold higher; 95% confidence interval [CI], 1.05 to 1.29) and the highest quartiles of urine KIM-1/Cr and urine MCP-1/Cr, compared with the lowest quartile, were associated with higher risk of CKD progression (HR, 1.71; 95% CI, 1.15 to 2.55, and HR, 1.65; 95% CI, 1.10 to 2.47, respectively). Higher urine levels of EGF/Cr were associated with lower risk of CKD progression (HR, 0.81 per two-fold higher; 95% CI, 0.71 to 0.93), and the highest quartile of urine EGF/Cr, compared with lowest, associated with less CKD progression (HR, 0.57; 95% CI, 0.40 to 0.81). Conclusions: Urine MCP-1, KIM-1, and EGF may provide noninvasive ways to assess tubule and interstitial disease in diabetes and identify those at higher risk of CKD progression.

BACKGROUND: While urinary biomarkers show promise in predicting diabetic kidney disease (DKD) progression, distal tubular markers remain understudied. We investigated the association of distal tubule markers, epidermal growth factor (EGF) and uromodulin (UMOD), with DKD progression in the Veterans Affairs Diabetes in Nephropathy (VA NEPHRON-D) clinical trial. METHODS: We used Cox regression models to evaluate the association between each biomarker and DKD progression and the relationship between change over time in biomarker and DKD progression. We used mixed models to investigate biomarker levels at baseline, 12 months, and over time and their relationships with longitudinal eGFR change. RESULTS: Participants ( n = 1,116) had type 2 diabetes, urine albumin-to-creatinine ratio (UACR) ≥ 300 mg/g, and eGFR 30–89.9 mL/min/1.73 m ² . Mean age was 65 years, mean eGFR was 56 (SD 19) mL/min/1.73 m ² , and median UACR was 840 (IQR 424–1,780) mg/g. One hundred forty-four participants (13%) had DKD progression over a median follow-up of 2.2 (1.3–3.1) years. Higher baseline EGF and UMOD were independently associated with a lower risk of DKD progression (adjusted HR 0.68, 95% CI 0.47, 0.99 and 0.85, [0.75, 0.98] per 2-fold higher concentration of EGF and UMOD, respectively). Serial biomarker measurements were performed at baseline and 12 months, and a slower decline in biomarkers was associated with a lower risk of DKD progression when adjusted for baseline biomarker levels. CONCLUSION: Urinary EGF and UMOD may serve as valuable prognostic biomarkers in DKD.TRIAL REGISTRATION. ClinicalTrials.gov NCT00555217.FUNDING. NIH U01DK102730, U01DK103225, K23 DK118198, R01DK137087, U01DK103225, R37DK039773, U01DK114866, U01DK106962, U01DK129984, and R01DK093770; National Institute of Diabetes and Digestive and Kidney Diseases contract U01DK106965.

Key Points: We identified three kidney health dimensions using 17 urine and plasma biomarkers across two cohorts of persons with diabetes and CKD. Worse scores for tubule injury, tubule function, and systemic inflammation/filtration were associated with a higher risk of CKD progression and death. A multibiomarker approach could help capture tubulointerstitial health in persons with diabetes and CKD. Background: Individual kidney tubule biomarkers are associated with risks of CKD progression and mortality in persons with diabetes. Integrating multiple kidney biomarkers using a latent variable method of exploratory factor analysis could define distinct dimensions of kidney health and their associations with adverse outcomes. Methods: We conducted a factor analysis of 17 candidate urine and plasma biomarkers in 1256 participants with diabetes and eGFR 2 from the Chronic Renal Insufficiency Cohort (CRIC; N=701) and the REasons for Geographic And Racial Differences in Stroke (REGARDS; N=555) studies. We used Cox proportional hazards models to evaluate the associations of identified factors with CKD progression and mortality, adjusting for baseline clinical risk factors, eGFR, and albuminuria. Results: Three factor scores comprising ten biomarkers were identified: systemic inflammation and filtration (plasma TNF receptor-1 and TNF receptor-2, plasma soluble urokinase plasminogen activator receptor, and plasma symmetric dimethylarginine), tubular function (urine EGF, urine asymmetric dimethylarginine, and urine symmetric dimethylarginine), and tubular damage (urine α-1 microglobulin, urine kidney injury molecule-1, and urine monocyte chemoattractant protein-1). In CRIC, there were 244 incident ESKD events, 102 with ≥40% eGFR decline from baseline, and 259 deaths; in REGARDS, there were 121 incident ESKD events and 462 deaths. In CRIC, lower tubular function (hazard ratio per 1-SD, 0.36; 95% confidence interval, 0.25 to 0.52) and higher tubular damage (1.45; 1.18 to 1.78) scores were independently associated with higher CKD progression risk. Associations in REGARDS were weaker but directionally consistent (tubular function score [0.81; 0.47 to 1.39] and tubular damage score [1.12; 0.73 to 1.72]). Higher tubular damage (1.47; 1.15 to 1.87) scores were associated with higher mortality risk in CRIC, but not REGARDS (1.15; 0.96 to 1.38). Higher systemic inflammation and filtration factor scores were associated with higher mortality risk in both cohorts (CRIC: 1.35; 1.07 to 1.71; REGARDS: 1.41; 1.20 to 1.65). Conclusions: Three distinct kidney health dimensions were identified, and each associated with CKD progression and/or all-cause mortality in persons with diabetes and CKD.

Type 2 diabetes affects more than 30 million people in the US, and a major complication is kidney disease. During the analysis of lipotoxicity in diabetic kidney disease, global fatty acid transport protein-2 (FATP2) gene deletion was noted to markedly reduce plasma glucose in db/db mice due to sustained insulin secretion. To identify the mechanism, we observed that islet FATP2 expression was restricted to α-cells, and α-cell FATP2 was functional. Direct evidence of FATP2KO-induced α-cell-mediated GLP-1 secretion included increased GLP-1-positive α-cell mass in FATP2KO db/db mice, small molecule FATP2 inhibitor enhancement of GLP-1 secretion in αTC1-6 cells and human islets, and exendin[9-39]-inhibitable insulin secretion in FATP2 inhibitor-treated human islets. FATP2-dependent enteroendocrine GLP-1 secretion was excluded by demonstration of similar glucose tolerance and plasma GLP-1 concentrations in db/db FATP2KO mice following oral versus intraperitoneal glucose loading, non-overlapping FATP2 and preproglucagon mRNA expression, and lack of FATP2/GLP-1 co-immunolocalization in intestine. We conclude that FATP2 deletion or inhibition exerts glucose-lowering effects through α-cell-mediated GLP-1 secretion and paracrine β-cell insulin release. Graphical

Key Points: Plasma biomarkers (kidney injury molecule-1, KIM-1), urine biomarkers (EGF/creatinine and urine albumin-creatinine ratio), and eGFR identified four prognostic groups in children with CKD progression. A panel of biomarkers may better capture the complexity of kidney disease in children and may allow for a broader assessment of kidney health. Background: We have previously studied biomarkers of tubular health (EGF), injury (kidney injury molecule-1 [KIM-1]), dysfunction ( α -1 microglobulin), and inflammation (TNF receptor-1, TNF receptor-2, monocyte chemoattractant protein-1, YKL-40, and soluble urokinase plasminogen activator receptor) and demonstrated that plasma KIM-1, TNF receptor-1, TNF receptor-2, urine KIM-1, EGF, monocyte chemoattractant protein-1, and urine α -1 microglobulin are each independently associated with CKD progression in children. In this study, we used bootstrapped survival trees to identify a combination of biomarkers to predict CKD progression in children. Methods: The Chronic Kidney Disease in Children (CKiD) Cohort Study prospectively enrolled children aged 6 months to 16 years with an eGFR of 30–90 ml/min per 1.73 m ² . We measured biomarkers in stored plasma and urine collected 5 months after study enrollment. The primary outcome of CKD progression was a composite of 50% eGFR decline or kidney failure. We constructed a regression tree–based model for predicting the time to the composite event, using a panel of clinically relevant biomarkers with empirically derived thresholds, in addition to conventional risk factors. Results: Of the 599 children included, the median age was 12 years (interquartile range [IQR], 8–15), 371 (62%) were male, baseline urine protein-creatinine ratio was 0.33 (IQR, 0.12–0.95) mg/mg, and baseline eGFR was 53 (IQR, 40–66) ml/min per 1.73 m ² . Overall, 205 children (34%) reached the primary outcome of CKD progression. A single regression tree–based model using the most informative predictors with data-driven biomarker thresholds suggested a final set of four prognosis groups. In the final model, urine albumin/creatinine was the variable with the highest importance and along with urine EGF/creatinine identified the highest risk group of 24 children, 100% of whom developed CKD progression at a median time of 1.3 years (95% confidence interval [CI], 1.0 to 1.7). When the regression tree–derived risk group classifications were added to prediction models including the clinical risk factors, the C-statistic increased from 0.76 (95% CI, 0.71 to 0.80) to 0.85 (95% CI, 0.81 to 0.88). Conclusions: Using regression tree–based methods, we identified a biomarker panel of urine albumin/creatinine, urine EGF/creatinine, plasma KIM-1, and eGFR, which significantly improved discrimination for CKD progression.

Key Points: Higher plasma and urine kidney injury molecule-1, urine monocyte chemoattractant protein-1, and lower urine alpha-1-microglobulin were associated with left ventricular hypertrophy, even after adjustment for confounders. Biomarkers of tubular injury, dysfunction, and inflammation may indicate the severity of kidney pathology and are associated with left ventricular hypertrophy. Background: Left ventricular hypertrophy (LVH) is common in children with CKD and is associated with an increased risk of cardiovascular disease and mortality. We have shown that several plasma and urine biomarkers are associated with increased risk of CKD progression. As CKD is associated with LVH, we sought to investigate the association between the biomarkers and LVH. Methods: In the CKD in Children Cohort Study, children aged 6 months to 16 years with an eGFR of 30–90 ml/min per 1.73 m² were enrolled at 54 centers in the United States and Canada. We measured plasma biomarkers kidney injury molecule-1 (KIM-1), tumor necrosis factor receptor-1, tumor necrosis factor receptor-2, soluble urokinase-type plasminogen activator receptor and urine KIM-1, monocyte chemoattractant protein-1 (MCP-1), YKL-40, alpha-1-microglobulin (alpha-1m), and epidermal growth factor in stored plasma and urine collected 5 months after enrollment. Echocardiograms were performed 1 year after enrollment. We assessed the cross-sectional association between the log₂ biomarker levels and LVH (left ventricular mass index greater than or equal to the 95th percentile) using a Poisson regression model, adjusted for age, sex, race, body mass index, hypertension, glomerular diagnosis, urine protein-to-creatinine ratio, and eGFR at study entry. Results: Among the 504 children, LVH prevalence was 12% (n=59) 1 year after enrollment. In a multivariable-adjusted model, higher plasma and urine KIM-1 and urine MCP-1 concentrations were associated with a higher prevalence of LVH (plasma KIM-1 prevalence ratio [PR] per log₂: 1.27, 95% confidence interval [CI], 1.02 to 1.58; urine KIM-1 PR: 1.21, 95% CI, 1.11 to 1.48; and urine MCP-1 PR: 1.18, 95% CI, 1.04 to 1.34). After multivariable adjustment for covariates, lower urine alpha-1m was also associated with a higher prevalence of LVH (PR: 0.90, 95% CI, 0.82 to 0.99). Conclusions: Higher plasma and urine KIM-1, urine MCP-1, and lower urine alpha-1m were each associated with LVH prevalence in children with CKD. These biomarkers may better inform risk and help elucidate the pathophysiology of LVH in pediatric CKD.

Chronic kidney disease (CKD) is associated with atherosclerotic cardiovascular disease (ASCVD) risk, especially among those with diabetes. Altered metabolism of solutes that accumulate in CKD [asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), and trimethylamine N-oxide (TMAO)], may reflect pathways linking CKD with ASCVD. This case-cohort study included CRIC participants with baseline diabetes, estimated glomerular filtration rate 2, and without prior history for each outcome. The primary outcome was incident ASCVD (time to first myocardial infarction, stroke, or peripheral artery disease event) and secondary outcome was incident heart failure. The subcohort comprised randomly selected participants meeting entry criteria. Plasma and urine ADMA, SDMA and TMAO concentrations were determined by liquid chromatography-tandem mass spectrometry. Associations of uremic solute plasma concentrations and urinary fractional excretions with outcomes were evaluated by weighted multivariable Cox regression models, adjusted for confounding covariables. Higher plasma ADMA concentrations (per SD) were associated with ASCVD risk (HR 1.30, 95% CI: 1.01–1.68). Lower fractional excretion of ADMA (per SD) was associated with ASCVD risk (HR 1.42, 95% CI: 1.07–1.89). The lowest quartile of ADMA fractional excretion was associated with greater ASCVD risk (HR 2.25, 95% CI: 1.08–4.69) compared with the highest quartile. Plasma SDMA and TMAO concentration and fractional excretion were not associated with ASCVD. Neither plasma nor fractional excretion of ADMA, SDMA and TMAO were associated with incident heart failure. These data suggest that decreased kidney excretion of ADMA leads to increased plasma concentrations and ASCVD risk.