Abstract: Background: Given the association of diabetic retinopathy (DR) to diabetic kidney disease, we investigated the urinary proteome to the presence and deterioration of DR in type 1 and type 2 diabetes in a post-hoc analysis of studies investigating the effect of candesartan on the progression of DR. Methods: Baseline urinary proteomic analysis was performed in 783 and 792 randomly chosen subjects from two RCTs: DIRECT-Protect 1 and 2. Endpoints were two-step and three-step change in DR score according to the Early Treatment of Diabetic Retinopathy Study protocol. Peptide levels were correlated to baseline DR score, using Spearman rank correlation (association presented as Rho), in a discovery set of 2/3 of participants in DIRECT-Protect 1. Identified peptide fragments were then tested cross-sectionally in a validation set of the remaining 1/3 in DIRECT-Protect 1. Thereafter, peptides identified in the discovery set were assessed in the entire DIRECT-Protect 1 and 2 cohorts in relation to baseline DR. Finally, peptides validated in the entire cohorts were tested longitudinally. Adjustment included sex, age, diabetes duration, smoking, total cholesterol, HbA1c, SBP, UAER, serum creatinine, and randomization group. Results: Follow-up ranged from 4.0-4.7 years. 24 out of 427 investigated peptide fragments were associated with baseline DR in the discovery set after adjustment for multiple testing. Two of these (COL3A1 (seq: NTG~) and COL4A1 (seq: DGA~) were also associated to baseline DR in the validation set (Rho: -0.22, p & lt;0.001 and Rho: -0.14, p=0.024). Neither was associated with the development of endpoints. Investigating the discovered fragments in the full cohorts, several collagen fragments were associated with baseline DR and endpoints, in both type 1 and type 2 diabetes, however without overlap. Conclusions: Several urinary peptide fragments (mainly collagen) were associated with the presence of DR, however, they were not conclusively associated with worsening of DR. Disclosure V. Rotbain curovic: None. P. Magalhães: None. T. He: Employee; Self; Mosaiques Diagnostics GmbH. T. W. Hansen: Stock/Shareholder; Self; Novo Nordisk A/S. H. Mischak: Stock/Shareholder; Self; Mosaiques Diagnostics. P. Rossing: Advisory Panel; Self; Astellas Pharma Inc., AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Gilead Sciences, Inc., Merck KGaA, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi, Vifor Pharma Management Ltd.

Abstract: Renin–angiotensin system (RAS) inhibitors decrease the urinary albumin to creatinine ratio (UACR) but are ineffective in up to 40% of patients. We hypothesized that rotation through different drug classes overcomes RAS inhibitor resistance and tested this in a randomized crossover trial. RESEARCH DESIGN AND METHODS We assigned 26 adults with type 1 diabetes and 37 with type 2 diabetes and UACR between 30 and 500 mg/g and estimated glomerular filtration rate & gt;45 mL/min/1.73 m2 to 4-week treatment periods with telmisartan 80 mg, empagliflozin 10 mg, linagliptin 5 mg, and baricitinib 2 mg in random order, separated by 4-week washout periods. Each participant was then re-exposed for 4 weeks to the drug that induced that individual’s largest UACR reduction. Primary outcome was the difference in UACR response to the best-performing drug during the confirmation period versus UACR response to the other three drugs. RESULTS There was substantial variation in the best-performing drug. Telmisartan was best performing for 33 participants (52%), empagliflozin and linagliptin in 11 (17%), and baricitinib in 8 participants (13%). The individuals’ best-performing drug changed UACR from baseline during the first and confirmatory exposures by a mean of −39.6% (95% CI −44.8, −33.8; P & lt; 0.001) and −22.4% (95% CI −29.7, −12.5; P & lt; 0.001), respectively. The Pearson correlation for first versus confirmatory exposure was 0.39 (P = 0.017). The mean change in UACR with the other three drugs was +1.6% (95% CI −4.3%, 8.0%; P = 0.593 versus baseline; difference versus individuals’ best-performing drug at confirmation, 30.9% [95% CI 18.0, 45.3]; P & lt; 0.001). CONCLUSIONS We demonstrated a large and reproducible variation in participants’ responses to different UACR-lowering drug classes. These data support systematic rotation through different drug classes to overcome therapy resistance to RAS inhibition.

Abstract: Specific ceramides have been identified as risk markers for cardiovascular disease (CVD) years before onset of disease. Treatment with the glucagon-like peptide-1 receptor agonist (GLP-1RA) liraglutide has been shown to induce beneficial changes in the lipid profile and reduce the risk of CVD. Reducing lipotoxic lipids with an antidiabetic drug therapy could be a path towards precision medicine approaches for the treatment of complications to diabetes. In this post-hoc study, an investigation was carried out on the effect of liraglutide on CVD-risk associated ceramides in two randomized clinical trials including participants with type 2 diabetes (T2D). Methods This study analyzed plasma samples from two independent randomized placebo-controlled clinical trials. The first trial, Antiproteinuric Effects of Liraglutide Treatment (LirAlbu12) followed a crossover design where 27 participants were treated for 12 weeks with either liraglutide (1.8 mg/d) or placebo, followed by a four-week washout period, and then another 12 weeks of the other treatment. The second clinical trial, Effect of Liraglutide on Vascular Inflammation in Type-2 Diabetes (LiraFlame26), lasted for 26 weeks and followed a parallel design, where 102 participants were randomized 1:1 to either liraglutide or placebo. Heresix prespecified plasma ceramides were measured using liquid chromatography mass spectrometry and assessed their changes using linear mixed models. Possible confounders were assessed with mediation analyses. Results In the LiraFlame26 trial, 26-week treatment with liraglutide resulted in a significant reduction of two ceramides associated with CVD risk, C16 Cer and C24:1 Cer ( p   〈  0.05) compared to placebo. None of the remaining ceramides showed statistically significant changes in response to liraglutide treatment compared to placebo. Significant changes in ceramides were not found after 12-weeks of liraglutide treatment in the LirAlbu12 trial. Mediation analyses showed that weight loss did not affect ceramide reduction. Conclusions It was demonstrated that treatment with liraglutide resulted in a reduction in C16 Cer and C24:1 Cer after 26 weeks of treatment. These findings suggest the GLP-1RA can be used to modulate ceramides in addition to its other properties. Trial registration Clinicaltrial.gov identifier: NCT02545738 and NCT03449654.

Abstract: Quantification of vascular inflammation before and after treatment with glucagon-like peptide-1 receptor agonists (GLP-1 RAs) may help reveal mechanistic pathways underlying the cardiovascular benefits of these drugs. We assessed change in vascular inflammation in the carotid arteries over 26 weeks by copper-64-labeled [1,4,7,10-tetraazacyclododecane-N,N′,N″,N‴-tetraacetic acid]-D-Phe1, Tyr3-octreotate ([64Cu] DOTATATE) PET in 30 participants included in a substudy of a double-blind trial where persons with type 2 diabetes (T2D) were randomized to liraglutide (n = 15) or placebo (n = 15) for 26 weeks. Mean age (SD) was 66.4 (7.2) years, HbA1c 56.4 (9.2) mmol/mol and BMI 28.9 (4.6) kg/m2. Weight and HbA1c were significantly reduced by liraglutide vs. placebo (p ≤ 0.01). The [64Cu]DOTATATE uptake (mean standardized uptake values) was significantly reduced in the liraglutide-treated group (−0.11 [95% confidence interval −0.19 to −0.03] , p = 0.01) and not changed significantly in the placebo group (−0.07 [−0.14 to 0.01], p = 0.08). The mean difference between groups did not reach significance (−0.04 [−0.15 to 0.07] , p = 0.44). In conclusion, [64Cu]DOTATATE uptake was reduced in persons with T2D treated with liraglutide. However, the reduction compared to placebo did not reach statistical significance, perhaps due to limited power. A reduction in vascular inflammation with liraglutide could help explain the cardiovascular protection observed with GLP-1 RAs in outcome studies but warrants further and larger studies.

Abstract: Background: Baseline risk variables and visit-to-visit variability (VV) of systolic blood pressure (SBP) , HbA1c, serum creatinine, and uric acid (UA) are potential risk markers of kidney function decline in type 1 diabetes. Methods: Post-hoc analysis of the PERL study (NCT02017171) - a double-blind randomized placebo-controlled clinical trial investigating allopurinol’s effect on iohexol-derived glomerular filtration rate (iGFR) in type 1 diabetes with elevated UA. Primary outcome was iGFR change over three years. Linear regression with backwards selection of baseline clinical variables was performed to identify an optimized model forecasting iGFR change. VV of SBP, HbA1c, serum creatinine, and UA were calculated as standard deviations of the residuals in individual linear regression models (LV) and coefficients of variation (CV) using all available measurements in the run-in period; thereafter assessed by linear regression, with iGFR change as the dependent variable. Adjustment included sex, baseline age, diabetes duration, BMI, HbA1c, SBP, kidney function (iGFR or eGFR, as appropriate) , urine albumin excretion rate (UAER) , smoking, and renin-angiotensin system inhibitor use. Results: 422 participants completed the trial, 4were included in this analysis. In the optimized baseline risk marker model, race other (including but not limited to Hawaiian/Pacific Islander) than White, Black, or Asian, higher HbA1c, UAER, and heart rate, and lower iGFR were associated with faster iGFR decline; Hispanic/Latino ethnicity was not. Assessing VV, higher LV and CV of SBP was associated with faster iGFR decline (adjusted LV β: -0.79, p=0.01; CV β: -0.79, p=0.04) ; VVs of HbA1c, creatinine, and UA were not. Conclusions: We identified several risk markers of faster iGFR decline in a high-risk population of individuals with type 1 diabetes. In addition to previously described associations, higher SBP VV was a risk marker for faster kidney function decline. Disclosure V.Rotbain curovic: None. S.Polsky: Advisory Panel; Medtronic, Other Relationship; diaTribe, Research Support; Dexcom, Inc., Eli Lilly and Company, Leona M. and Harry B. Helmsley Charitable Trust, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Sanofi-Aventis U.S. R.Pop-busui: Advisory Panel; Averitas Pharma, Inc., Boehringer Ingelheim International GmbH, Nevro Corp., Novo Nordisk, Reata Pharmaceuticals, Inc., Regenacy Pharmaceuticals, Inc. R.J.Sigal: Advisory Panel; Novo Nordisk Canada Inc., Research Support; Novo Nordisk Canada Inc. K.R.Tuttle: Advisory Panel; Boehringer Ingelheim International GmbH, Gilead Sciences, Inc., Consultant; AstraZeneca, Eli Lilly and Company, Research Support; Bayer AG, Goldfinch Bio, Inc., Novo Nordisk, Travere. G.E.Umpierrez: Research Support; AstraZeneca, Dexcom, Inc., Novo Nordisk. A.Wallia: Advisory Panel; Eli Lilly and Company, Research Support; Novo Nordisk, UnitedHealth Group. S.Rosas: Advisory Panel; AstraZeneca, Teladoc Health, Other Relationship; Bayer AG, Research Support; AstraZeneca, Bayer AG. P.Rossing: Consultant; Astellas Pharma Inc., AstraZeneca, Bayer AG, Gilead Sciences, Inc., Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi, Speaker's Bureau; Eli Lilly and Company. The perl study group: n/a. N.Roy: None. T.W.Hansen: Stock/Shareholder; Novo Nordisk A/S. L.Caramori: Advisory Panel; Bayer AG, Consultant; AstraZeneca, Boehringer Ingelheim International GmbH, Novo Nordisk, Research Support; Bayer AG, Novartis AG. D.Cherney: Other Relationship; AbbVie Inc., AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Janssen Research & Development, LLC, Lilly, Maze, BMS, CSL-Behring, Merck, Otsuka, Novartis and Novo-Nordisk , Mitsubishi Tanabe Pharma Corporation, Sanofi, Research Support; Boehringer Ingelheim-Lilly, Merck, Janssen, Sanofi, AstraZeneca and Novo-Nordisk. I.De boer: Advisory Panel; AstraZeneca, Bayer AG, Cyclerion Therapeutics, Inc., George Clinical, Goldfinch Bio, Inc., Other Relationship; American Society of Nephrology, Research Support; Dexcom, Inc. I.B.Hirsch: Consultant; Abbott Diabetes, Bigfoot Biomedical, Inc., GWave, Roche Diabetes Care, Research Support; Beta Bionics, Inc., Insulet Corporation, Medtronic. I.Lingvay: Advisory Panel; AstraZeneca, Boehringer Ingelheim International GmbH, Lilly, Mannkind, TARGET PharmaSolutions; Valeritas;; Altimmune; DataRevive; Click; Medscape Duke CRI; Janssen Pharma; Bayer; Intercept, Novo Nordisk, Sanofi, Zealand Pharma A/S, Consultant; Novo Nordisk, Research Support; NovoNordisk; Mylan; Merck, Sanofi. J.B.Mcgill: Advisory Panel; Gilead Sciences, Inc., Lilly Diabetes, MannKind Corporation, Novo Nordisk A/S, Provention Bio, Inc., Salix Pharmaceuticals, Consultant; Bayer AG, Boehringer Ingelheim International GmbH, Research Support; Dexcom, Inc., Novo Nordisk. Funding Supported by grants from the NIDDK (R03-DK-094484, R34-DK-097808, UC4-DK-101108, P30-DK-036836, and P30-DK-020572) , the JDRF (17-2012-377) , the National Center for Advancing Translational Sciences (UL1-TR-002494, UL1-TR- 001422, UL1-TR-002556, UL1-TR-002319, and UL1-TR- 001105) , and the National Institute on Aging (Claude Pepper Center grant number, P30-AG-024824)

Abstract: Omics-based methods may provide new markers associated to diabetic retinopathy (DR). We investigated a wide omics panel of metabolites and lipids related to DR in type 1 diabetes. Metabolomic analyses were performed using two-dimensional gas chromatography with time-of-flight mass spectrometry and lipidomic analyses using an ultra-high-performance liquid chromatography quadruple time-of-flight mass spectrometry method in 648 individuals with type 1 diabetes. Subjects were subdivided into no DR, mild nonproliferative DR (NPDR), moderate NPDR, proliferative DR, and proliferative DR with fibrosis. End points were any progression of DR, onset of DR, and progression from mild to severe DR tracked from standard ambulatory care and investigated using Cox models. The cohort consisted of 648 participants aged a mean of 54.4 ± 12.8 years, 55.5% were men, and follow-up was 5.1–5.5 years. Cross-sectionally, 2,4-dihydroxybutyric acid (DHBA), 3,4-DHBA, ribonic acid, ribitol, and the triglycerides 50:1 and 50:2 significantly correlated (P & lt; 0.042) to DR stage. Longitudinally, higher 3,4-DHBA was a risk marker for progression of DR (n = 133) after adjustment (P = 0.033). We demonstrated multiple metabolites being positively correlated to a higher grade of DR in type 1 diabetes and several triglycerides being negatively correlated. Furthermore, higher 3,4-DHBA was an independent risk marker for progression of DR; however, confirmation is required.

Abstract: Kidney disease progression is characterized by extensive deposition of extracellular matrix components such as collagen. Therefore, we assessed the effect of spironolactone on collagen remodeling biomarkers and investigated the association between the markers and development of microalbuminuria in serum of persons with type 2 diabetes and normoalbuminuria. Method We measured collagen type III (PRO-C3), VI (PRO-C6; endotrophin), VII (PRO-C7), and XXVIII (PRO-C28) formation, and a fragment of degraded crosslinked collagen type III (CTX-III) in serum of persons with high-risk (stratified by a urinary proteomics classifier, CKD273) for development of microalbuminuria, randomized to either spironolactone 25 mg or placebo. Crude and adjusted Cox models were applied to investigate the association between baseline biomarker levels and development of the primary outcome, persistent microalbuminuria, and development of microalbuminuria in at least one morning void sample, used as a secondary outcome. Results In the PRIORITY trial, spironolactone treatment did not prevent progression to microalbuminuria compared to placebo. All biomarkers were measured in 154 participants at baseline and 117 at end-of-study (week 208). Treatment with spironolactone did not affect serum levels of any of the investigated collagen remodeling biomarkers compared to placebo, and there were no differences in delta-biomarker levels between baseline and end-of-study (p ranging 0.277-0.875). In crude analyses, serum endotrophin was associated with both the primary (n = 44) and secondary outcome (n = 74) (HR per two-fold higher level: 1.58, 95% CI: 1.03-2.44, p = 0.037 and 1.62, 1.12-2.35, p = 0.010), whereas serum PRO-C3 was only associated with the secondary outcome (1.89, 1.19-2.99, p = 0.007). After adjustment for sex, baseline age, systolic blood pressure, estimated glomerular filtration rate, urinary albumin-creatinine ratio, and HbA1c, serum endotrophin and PRO-C3 remained significantly associated with the secondary outcome (1.52, 1.03-2.24, p = 0.036 and 1.73, 1.08-2.78, p = 0.022). Levels of PRO-C7, PRO-C28, and CTX-III were not associated with the specified outcomes. Neither baseline levels of serum endotrophin nor PRO-C3 correlated with baseline CKD273 levels (R: 0.00-0.06, p & gt;0.47). Conclusion Treatment with spironolactone did not change serum levels of collagen remodeling biomarkers. Serum endotrophin, reflecting collagen type VI formation and the pro-fibrotic molecule endotrophin, and PRO-C3, a marker of collagen type III formation, were associated with development of microalbuminuria in at least one urine sample, suggesting that these biomarkers are relevant risk markers for kidney disease development in type 2 diabetes.