Incretin and glucagon receptor polypharmacology in chronic kidney disease.

Chronic kidney disease is a debilitating condition associated with significant morbidity and mortality. In recent years, the kidney effects of incretin-based therapies, particularly glucagon-like peptide-1 receptor agonists (GLP-1RAs), have garnered substantial interest in the management of type 2 diabetes and obesity. This review delves into the intricate interactions between the kidney, GLP-1RAs, and glucagon, shedding light on their mechanisms of action and potential kidney benefits. Both GLP-1 and glucagon, known for their opposing roles in regulating glucose homeostasis, improve systemic risk factors affecting the kidney, including adiposity, inflammation, oxidative stress, and endothelial function. Additionally, these hormones and their pharmaceutical mimetics may have a direct impact on the kidney. Clinical studies have provided evidence that incretins, including those incorporating glucagon receptor agonism, are likely to exhibit improved kidney outcomes. Although further research is necessary, receptor polypharmacology holds promise for preserving kidney function through eliciting vasodilatory effects, influencing volume and electrolyte handling, and improving systemic risk factors.

Unbiased kidney-centric molecular categorization of chronic kidney disease as a step towards precision medicine.

Current classification of chronic kidney disease (CKD) into stages using indirect systemic measures (estimated glomerular filtration rate (eGFR) and albuminuria) is agnostic to the heterogeneity of underlying molecular processes in the kidney thereby limiting precision medicine approaches. To generate a novel CKD categorization that directly reflects within kidney disease drivers we analyzed publicly available transcriptomic data from kidney biopsy tissue. A Self-Organizing Maps unsupervised artificial neural network machine-learning algorithm was used to stratify a total of 369 patients with CKD and 46 living kidney donors as healthy controls. Unbiased stratification of the discovery cohort resulted in identification of four novel molecular categories of disease termed CKD-Blue, CKD-Gold, CKD-Olive, CKD-Plum that were replicated in independent CKD and diabetic kidney disease datasets and can be further tested on any external data at kidneyclass.org. Each molecular category spanned across CKD stages and histopathological diagnoses and represented transcriptional activation of distinct biological pathways. Disease progression rates were highly significantly different between the molecular categories. CKD-Gold displayed rapid progression, with significant eGFR-adjusted Cox regression hazard ratio of 5.6 [1.01-31.3] for kidney failure and hazard ratio of 4.7 [1.3-16.5] for composite of kidney failure or a 40% or more eGFR decline. Urine proteomics revealed distinct patterns between the molecular categories, and a 25-protein signature was identified to distinguish CKD-Gold from other molecular categories. Thus, patient stratification based on kidney tissue omics offers a gateway to non-invasive biomarker-driven categorization and the potential for future clinical implementation, as a key step towards precision medicine in CKD.

Postoperative optimization of cochlear implantation for single sided deafness and asymmetric hearing loss: a systematic review.

OBJECTIVE: Identify and evaluate the effectiveness of methods for improving postoperative cochlear implant (CI) hearing performance in subjects with single-sided deafness (SSD) and asymmetric hearing loss (AHL). DATA SOURCES: Embase, PubMed, Scopus. REVIEW METHODS: Systematic review and narrative synthesis. English language studies of adult CI recipients with SSD and AHL reporting a postoperative intervention and comparative audiometric data pertaining to speech in noise, speech in quiet and sound localization were included. RESULTS: 32 studies met criteria for full text review and 6 (n = 81) met final inclusion criteria. Interventions were categorized as: formal auditory training, programming techniques, or hardware optimization. Formal auditory training (n = 10) found no objective improvement in hearing outcomes. Experimental CI maps did not improve audiologic outcomes (n = 9). Programed CI signal delays to improve synchronization demonstrated improved sound localization (n = 12). Hardware optimization, including multidirectional (n = 29) and remote (n = 11) microphones, improved sound localization and speech in noise, respectively. CONCLUSION: Few studies meeting inclusion criteria and small sample sizes highlight the need for further study. Formal auditory training did not appear to improve hearing outcomes. Programming techniques, such as CI signal delay, and hardware optimization, such as multidirectional and remote microphones, show promise to improve outcomes for SSD and AHL CI users.

Effects of Tirzepatide Versus Insulin Glargine on Cystatin C-Based Kidney Function: A SURPASS-4 Post Hoc Analysis.

OBJECTIVE: Tirzepatide reduces HbA1c and body weight, and creatinine-based estimated glomerular filtration rate (eGFR) decline. Unlike creatine-derived eGFR (eGFR-creatinine), cystatin C-derived eGFR (eGFR-cystatin C) is unaffected by muscle mass changes. We assessed effects of tirzepatide on eGFR-creatinine and eGFR-cystatin C. RESEARCH DESIGN AND METHODS: Our primary outcome was eGFR change from baseline at 52 weeks with pooled tirzepatide (5, 10, and 15 mg) and titrated insulin glargine in adults with type 2 diabetes and high cardiovascular risk (SURPASS-4). RESULTS: Least squares mean (SE) eGFR-creatinine (mL/min/1.73 m2) changes from baseline with tirzepatide and insulin glargine were -2.5 (0.38) and -3.9 (0.38) (between-group difference, 1.4 [95% CI 0.3-2.4]) and -3.5 (0.37) and -5.3 (0.37) (between-group difference, 1.8 [95% CI 0.8-2.8]) for eGFR-cystatin C. Baseline, 1-year, and 1-year change from baseline values significantly correlated between eGFR-cystatin C and eGFR-creatinine. Measures of eGFR changes did not correlate with body weight changes. CONCLUSIONS: Tirzepatide slows the eGFR decline rate, supporting a kidney-protective effect.

Identification of biomarkers for glycaemic deterioration in type 2 diabetes.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study.

BACKGROUND AND AIMS: Detecting NASH remains challenging, while at-risk NASH (steatohepatitis and F≥ 2) tends to progress and is of interest for drug development and clinical application. We developed prediction models by supervised machine learning techniques, with clinical data and biomarkers to stage and grade patients with NAFLD. APPROACH AND RESULTS: Learning data were collected in the Liver Investigation: Testing Marker Utility in Steatohepatitis metacohort (966 biopsy-proven NAFLD adults), staged and graded according to NASH CRN. Conditions of interest were the clinical trial definition of NASH (NAS ≥ 4;53%), at-risk NASH (NASH with F ≥ 2;35%), significant (F ≥ 2;47%), and advanced fibrosis (F ≥ 3;28%). Thirty-five predictors were included. Missing data were handled by multiple imputations. Data were randomly split into training/validation (75/25) sets. A gradient boosting machine was applied to develop 2 models for each condition: clinical versus extended (clinical and biomarkers). Two variants of the NASH and at-risk NASH models were constructed: direct and composite models.Clinical gradient boosting machine models for steatosis/inflammation/ballooning had AUCs of 0.94/0.79/0.72. There were no improvements when biomarkers were included. The direct NASH model produced AUCs (clinical/extended) of 0.61/0.65. The composite NASH model performed significantly better (0.71) for both variants. The composite at-risk NASH model had an AUC of 0.83 (clinical and extended), an improvement over the direct model. Significant fibrosis models had AUCs (clinical/extended) of 0.76/0.78. The extended advanced fibrosis model (0.86) performed significantly better than the clinical version (0.82). CONCLUSIONS: Detection of NASH and at-risk NASH can be improved by constructing independent machine learning models for each component, using only clinical predictors. Adding biomarkers only improved the accuracy of fibrosis.

Different roles of protein biomarkers predicting eGFR trajectories in people with chronic kidney disease and diabetes mellitus: a nationwide retrospective cohort study.

BACKGROUND: Chronic kidney disease (CKD) is a common comorbidity in people with diabetes mellitus, and a key risk factor for further life-threatening conditions such as cardiovascular disease. The early prediction of progression of CKD therefore is an important clinical goal, but remains difficult due to the multifaceted nature of the condition. We validated a set of established protein biomarkers for the prediction of trajectories of estimated glomerular filtration rate (eGFR) in people with moderately advanced chronic kidney disease and diabetes mellitus. Our aim was to discern which biomarkers associate with baseline eGFR or are important for the prediction of the future eGFR trajectory. METHODS: We used Bayesian linear mixed models with weakly informative and shrinkage priors for clinical predictors (n = 12) and protein biomarkers (n = 19) to model eGFR trajectories in a retrospective cohort study of people with diabetes mellitus (n = 838) from the nationwide German Chronic Kidney Disease study. We used baseline eGFR to update the models' predictions, thereby assessing the importance of the predictors and improving predictive accuracy computed using repeated cross-validation. RESULTS: The model combining clinical and protein predictors had higher predictive performance than a clinical only model, with an [Formula: see text] of 0.44 (95% credible interval 0.37-0.50) before, and 0.59 (95% credible interval 0.51-0.65) after updating by baseline eGFR, respectively. Only few predictors were sufficient to obtain comparable performance to the main model, with markers such as Tumor Necrosis Factor Receptor 1 and Receptor for Advanced Glycation Endproducts being associated with baseline eGFR, while Kidney Injury Molecule 1 and urine albumin-creatinine-ratio were predictive for future eGFR decline. CONCLUSIONS: Protein biomarkers only modestly improve predictive accuracy compared to clinical predictors alone. The different protein markers serve different roles for the prediction of longitudinal eGFR trajectories potentially reflecting their role in the disease pathway.

Biomarkers for staging fibrosis and non-alcoholic steatohepatitis in non-alcoholic fatty liver disease (the LITMUS project): a comparative diagnostic accuracy study.

BACKGROUND: The reference standard for detecting non-alcoholic steatohepatitis (NASH) and staging fibrosis-liver biopsy-is invasive and resource intensive. Non-invasive biomarkers are urgently needed, but few studies have compared these biomarkers in a single cohort. As part of the Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS) project, we aimed to evaluate the diagnostic accuracy of 17 biomarkers and multimarker scores in detecting NASH and clinically significant fibrosis in patients with non-alcoholic fatty liver disease (NAFLD) and identify their optimal cutoffs as screening tests in clinical trial recruitment. METHODS: This was a comparative diagnostic accuracy study in people with biopsy-confirmed NAFLD from 13 countries across Europe, recruited between Jan 6, 2010, and Dec 29, 2017, from the LITMUS metacohort of the prospective European NAFLD Registry. Adults (aged ≥18 years) with paired liver biopsy and serum samples were eligible; those with excessive alcohol consumption or evidence of other chronic liver diseases were excluded. The diagnostic accuracy of the biomarkers was expressed as the area under the receiver operating characteristic curve (AUC) with liver histology as the reference standard and compared with the Fibrosis-4 index for liver fibrosis (FIB-4) in the same subgroup. Target conditions were the presence of NASH with clinically significant fibrosis (ie, at-risk NASH; NAFLD Activity Score ≥4 and F≥2) or the presence of advanced fibrosis (F≥3), analysed in all participants with complete data. We identified thres holds for each biomarker for reducing the number of biopsy-based screen failures when recruiting people with both NASH and clinically significant fibrosis for future trials. FINDINGS: Of 1430 participants with NAFLD in the LITMUS metacohort with serum samples, 966 (403 women and 563 men) were included after all exclusion criteria had been applied. 335 (35%) of 966 participants had biopsy-confirmed NASH and clinically significant fibrosis and 271 (28%) had advanced fibrosis. For people with NASH and clinically significant fibrosis, no single biomarker or multimarker score significantly reached the predefined AUC 0·80 acceptability threshold (AUCs ranging from 0·61 [95% CI 0·54-0·67] for FibroScan controlled attenuation parameter to 0·81 [0·75-0·86] for SomaSignal), with accuracy mostly similar to FIB-4. Regarding detection of advanced fibrosis, SomaSignal (AUC 0·90 [95% CI 0·86-0·94]), ADAPT (0·85 [0·81-0·89]), and FibroScan liver stiffness measurement (0·83 [0·80-0·86]) reached acceptable accuracy. With 11 of 17 markers, histological screen failure rates could be reduced to 33% in trials if only people who were marker positive had a biopsy for evaluating eligibility. The best screening performance for NASH and clinically significant fibrosis was observed for SomaSignal (number needed to test [NNT] to find one true positive was four [95% CI 4-5]), then ADAPT (six [5-7]), MACK-3 (seven [6-8]), and PRO-C3 (nine [7-11]). INTERPRETATION: None of the single markers or multimarker scores achieved the predefined acceptable AUC for replacing biopsy in detecting people with both NASH and clinically significant fibrosis. However, several biomarkers could be applied in a prescreening strategy in clinical trial recruitment. The performance of promising markers will be further evaluated in the ongoing prospective LITMUS study cohort. FUNDING: The Innovative Medicines Initiative 2 Joint Undertaking.

Biomarker Changes Associated With Both Dulaglutide and Cardiovascular Events in the REWIND Randomized Controlled Trial: A Nested Case-Control Post Hoc Analysis.

OBJECTIVE: The glucagon-like peptide-1 receptor agonist dulaglutide reduced MACE in the Researching Cardiovascular Events with a Weekly Incretin in Diabetes (REWIND) trial. This article expores the relationship of selected biomarkers to both dulaglutide and major adverse cardiovascular events (MACE). RESEARCH DESIGN AND METHODS: In this post hoc analysis, stored fasting baseline and 2-year plasma samples from 824 REWIND participants with MACE during follow-up and 845 matched non-MACE participants were analyzed for 2-year changes in 19 protein biomarkers. Two-year changes in 135 metabolites were also analyzed in 600 participants with MACE during follow-up and in 601 matched non-MACE participants. Linear and logistic regression models were used to identify proteins that were associated with both dulaglutide treatment and MACE. Similar models were used to identify metabolites that were associated with both dulaglutide treatment and MACE. RESULTS: Compared with placebo, dulaglutide was associated with a greater reduction or lesser 2-year rise from baseline in N-terminal prohormone of brain natriuretic peptide (NT-proBNP), growth differentiation factor 15 (GDF-15), high-sensitivity C-reactive protein, and a greater 2-year rise in C-peptide. Compared with placebo, dulaglutide was also associated with a greater fall from baseline in 2-hydroxybutyric acid and a greater rise in threonine (P < 0.001). Increases from baseline in two of the proteins (but neither metabolite) were associated with MACE, including NT-proBNP (OR 1.267; 95% CI 1.119, 1.435; P < 0.001) and GDF-15 (OR 1.937; 95% CI 1.424, 2.634; P < 0.001). CONCLUSIONS: Dulaglutide was associated with a reduced 2-year rise from baseline of NT-proBNP and GDF-15. Higher rises of these biomarkers were also associated with MACE.

Indicators of Kidney Fibrosis in Patients with Type 2 Diabetes and Chronic Kidney Disease Treated with Dulaglutide.

INTRODUCTION: In the AWARD-7 study in patients with type 2 diabetes and moderate-to-severe chronic kidney disease, once-weekly dulaglutide slowed the decline in estimated glomerular filtration rate (eGFR) and decreased the urine albumin/creatinine ratio compared to insulin glargine at the end of 52 weeks of treatment. In this exploratory post hoc analysis, changes in two fibrosis biomarkers, serum PRO-C6 (type VI collagen formation) and urine C3M (type III collagen degradation), were evaluated. METHODS: In the groups treated with dulaglutide 1.5 mg or insulin glargine (N = 330), serum PRO-C6 and urine C3M were measured using competitive enzyme-linked immunosorbent assays. Biomarker changes were assessed by a mixed-effects model for repeated measures. Pearson correlation analyses were conducted to determine associations between changes in kidney fibrosis biomarkers and eGFR measures at 52 weeks. RESULTS: At weeks 26 and 52 of treatment in the overall population, serum PRO-C6 levels were significantly lower in the dulaglutide group versus insulin glargine group with percent change from baseline of (least squares mean ± standard error) -4.6% ± 1.9 and -0.2% ± 2.2 versus 5.7% ± 2.0 and 8.0% ± 2.3 (p < 0.01), respectively, and urine C3M levels were significantly higher in the dulaglutide group versus insulin glargine group with percent change from baseline of 10.9% ± 8.2 and 20.7% ± 8.8 versus -10.0% ± 6.5 and -16.9% ± 6.4 (p < 0.05), respectively. These findings appeared greater in the subgroup with macroalbuminuria. Serum PRO-C6 negatively correlated with eGFR, while urine C3M positively correlated with eGFR. CONCLUSION: Dulaglutide treatment was associated with biomarker changes that indicated lower type VI collagen formation and higher type III collagen degradation compared to treatment with insulin glargine, suggesting a potential drug effect to reduce kidney fibrosis.

Effects of tirzepatide versus insulin glargine on kidney outcomes in type 2 diabetes in the SURPASS-4 trial: post-hoc analysis of an open-label, randomised, phase 3 trial.

BACKGROUND: In the SURPASS-4 trial, the dual GIP and GLP-1 receptor agonist tirzepatide reduced HbA1c concentrations, bodyweight, and blood pressure more than titrated daily insulin glargine in people with type 2 diabetes inadequately controlled on oral diabetes treatments and with high cardiovascular risk. We aimed to compare the effects of tirzepatide and insulin glargine on kidney parameters and outcomes in people with type 2 diabetes. METHODS: We did a post-hoc analysis of data from SURPASS-4, a randomised, open-label, parallel-group, phase 3 study at 187 sites (including private practice, research institutes, and hospitals) in 14 countries. Eligible participants were adults (age ≥18 years), with type 2 diabetes treated with any combination of metformin, sulfonylurea, or SGLT2 inhibitor, and with baseline HbA1c of 7·5-10·5% (58-91 mmol/mol), BMI of 25 kg/m2 or greater, and established cardiovascular disease or a high risk of cardiovascular events. Randomisation via an interactive web-response system was 1:1:1:3 to a once-weekly subcutaneous injection of tirzepatide (5 mg, 10 mg, or 15 mg) or a once-daily subcutaneous injection of titrated insulin glargine (100 U/mL). The study included up to 104 weeks of treatment, with a median treatment duration of 85 weeks. We compared the rates of estimated glomerular filtration rate (eGFR) decline and the urine albumin-creatinine ratio (UACR) between the combined tirzepatide groups and the insulin glargine group in the modified intention-to-treat population. The kidney composite outcome was time to first occurrence of eGFR decline of at least 40% from baseline, end-stage kidney disease, death owing to kidney failure, or new-onset macroalbuminuria. This study is registered with ClinicalTrials.gov, NCT03730662. FINDINGS: Between Nov 20, 2018, and Dec 30, 2019, we screened 3045 people, of whom 1043 (34%) were ineligible, and 2002 (66%) were randomly assigned to a study drug (997 to tirzepatide and 1005 to insulin glargine). 1995 (>99%) of 2002 received at least one dose of tirzepatide (n=995) or insulin glargine (n=1000). At baseline, participants had a mean eGFR of 81·3 (SD 21·11) mL/min per 1·73 m2 and a median UACR of 15·0 mg/g (IQR 5·0-55·8). The mean rate of eGFR decline was -1·4 (SE 0·2) mL/min per 1·73 m2 per year in the combined tirzepatide groups and -3·6 (0·2) mL/min per 1·73 m2 per year in the insulin group (between-group difference 2·2 [95% CI 1·6 to 2·8]). Compared with insulin glargine, the reduction in the annual rate of eGFR decline induced by tirzepatide was more pronounced in participants with eGFR less than 60 mL/min per 1·73 m2 than in those with eGFR 60 mL/min per 1·73 m2 or higher (between-group difference 3·7 [95% CI 2·4 to 5·1]). UACR increased from baseline to follow-up with insulin glargine (36·9% [95% CI 26·0 to 48·7]) but not with tirzepatide (-6·8% [-14·1 to 1·1]; between-group difference -31·9% [-37·7 to -25·7]). Participants who received tirzepatide showed a significantly lower occurrence of the composite kidney endpoint compared with those who received insulin glargine (hazard ratio 0·58 [95% CI 0·43 to 0·80]). INTERPRETATION: Our analysis suggests that in people with type 2 diabetes and high cardiovascular risk, tirzepatide slowed the rate of eGFR decline and reduced UACR in clinically meaningful ways compared with insulin glargine. FUNDING: Eli Lilly and Company.

Neuroblastoma suppressor of tumorigenicity 1 is a circulating protein associated with progression to end-stage kidney disease in diabetes.

Circulating proteins associated with transforming growth factor-ß (TGF-ß) signaling are implicated in the development of diabetic kidney disease (DKD). It remains to be comprehensively examined which of these proteins are involved in the pathogenesis of DKD and its progression to end-stage kidney disease (ESKD) in humans. Using the SOMAscan proteomic platform, we measured concentrations of 25 TGF-ß signaling family proteins in four different cohorts composed in total of 754 Caucasian or Pima Indian individuals with type 1 or type 2 diabetes. Of these 25 circulating proteins, we identified neuroblastoma suppressor of tumorigenicity 1 (NBL1, aliases DAN and DAND1), a small secreted protein known to inhibit members of the bone morphogenic protein family, to be most strongly and independently associated with progression to ESKD during 10-year follow-up in all cohorts. The extent of damage to podocytes and other glomerular structures measured morphometrically in 105 research kidney biopsies correlated strongly with circulating NBL1 concentrations. Also, in vitro exposure to NBL1 induced apoptosis in podocytes. In conclusion, circulating NBL1 may be involved in the disease process underlying progression to ESKD, and its concentration in circulation may identify subjects with diabetes at increased risk of progression to ESKD.

Results of untargeted analysis using the SOMAscan proteomics platform indicates novel associations of circulating proteins with risk of progression to kidney failure in diabetes.

This study applies a large proteomics panel to search for new circulating biomarkers associated with progression to kidney failure in individuals with diabetic kidney disease. Four independent cohorts encompassing 754 individuals with type 1 and type 2 diabetes and early and late diabetic kidney disease were followed to ascertain progression to kidney failure. During ten years of follow-up, 227 of 754 individuals progressed to kidney failure. Using the SOMAscan proteomics platform, we measured baseline concentration of 1129 circulating proteins. In our previous publications, we analyzed 334 of these proteins that were members of specific candidate pathways involved in diabetic kidney disease and found 35 proteins strongly associated with risk of progression to kidney failure. Here, we examined the remaining 795 proteins using an untargeted approach. Of these remaining proteins, 11 were significantly associated with progression to kidney failure. Biological processes previously reported for these proteins were related to neuron development (DLL1, MATN2, NRX1B, KLK8, RTN4R and ROR1) and were implicated in the development of kidney fibrosis (LAYN, DLL1, MAPK11, MATN2, endostatin, and ROR1) in cellular and animal studies. Specific mechanisms that underlie involvement of these proteins in progression of diabetic kidney disease must be further investigated to assess their value as targets for kidney-protective therapies. Using multivariable LASSO regression analysis, five proteins (LAYN, ESAM, DLL1, MAPK11 and endostatin) were found independently associated with risk of progression to kidney failure. Thus, our study identified proteins that may be considered as new candidate prognostic biomarkers to predict risk of progression to kidney failure in diabetic kidney disease. Furthermore, three of these proteins (DLL1, ESAM, and MAPK11) were selected as candidate biomarkers when all SOMAscan results were evaluated.

Effects of Tirzepatide, a Dual GIP and GLP-1 RA, on Lipid and Metabolite Profiles in Subjects With Type 2 Diabetes.

CONTEXT: Tirzepatide substantially reduced hemoglobin A1c (HbA1c) and body weight in subjects with type 2 diabetes (T2D) compared with the glucagon-like peptide 1 receptor agonist dulaglutide. Improved glycemic control was associated with lower circulating triglycerides and lipoprotein markers and improved markers of beta-cell function and insulin resistance (IR), effects only partially attributable to weight loss. OBJECTIVE: Assess plasma metabolome changes mediated by tirzepatide. DESIGN: Phase 2b trial participants were randomly assigned to receive weekly subcutaneous tirzepatide, dulaglutide, or placebo for 26 weeks. Post hoc exploratory metabolomics and lipidomics analyses were performed. SETTING: Post hoc analysis. PARTICIPANTS: 259 subjects with T2D. INTERVENTION(S): Tirzepatide (1, 5, 10, 15 mg), dulaglutide (1.5 mg), or placebo. MAIN OUTCOME MEASURE(S): Changes in metabolite levels in response to tirzepatide were assessed against baseline levels, dulaglutide, and placebo using multiplicity correction. RESULTS: At 26 weeks, a higher dose tirzepatide modulated a cluster of metabolites and lipids associated with IR, obesity, and future T2D risk. Branched-chain amino acids, direct catabolic products glutamate, 3-hydroxyisobutyrate, branched-chain ketoacids, and indirect byproducts such as 2-hydroxybutyrate decreased compared to baseline and placebo. Changes were significantly larger with tirzepatide compared with dulaglutide and directly proportional to reductions of HbA1c, homeostatic model assessment 2-IR indices, and proinsulin levels. Proportional to metabolite changes, triglycerides and diglycerides were lowered significantly compared to baseline, dulaglutide, and placebo, with a bias toward shorter and highly saturated species. CONCLUSIONS: Tirzepatide reduces body weight and improves glycemic control and uniquely modulates metabolites associated with T2D risk and metabolic dysregulation in a direction consistent with improved metabolic health.

The dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist tirzepatide improves cardiovascular risk biomarkers in patients with type 2 diabetes: A post hoc analysis.

In a phase 2 trial of once-weekly tirzepatide (1, 5, 10, or 15 mg), dulaglutide (1.5 mg), or placebo, the dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist tirzepatide dose-dependently reduced HbA1c and body weight in patients with type 2 diabetes. In this post hoc analysis, inflammation, endothelial dysfunction, and cellular stress biomarkers were measured at baseline, 4, 12, and 26 weeks to evaluate the additional effects of tirzepatide on cardiovascular risk factors. At 26 weeks, tirzepatide 10 and 15 mg decreased YKL-40 (also known as chitinase-3 like-protein-1), intercellular adhesion molecule 1 (ICAM-1), leptin, and growth differentiation factor 15 levels versus baseline, and YKL-40 and leptin levels versus placebo and dulaglutide. Tirzepatide 15 mg also decreased ICAM-1 levels versus placebo and dulaglutide, and high-sensitivity C-reactive protein (hsCRP) levels versus baseline and placebo, but not dulaglutide. GlycA, interleukin 6, vascular cell adhesion molecule 1, and N-terminal-pro hormone B-type natriuretic peptide levels were not significantly changed in any group. YKL-40, hsCRP, and ICAM-1 levels rapidly decreased within 4 weeks of treatment with tirzepatide 10 and 15 mg, whereas the decrease in leptin levels was more gradual and did not plateau by 26 weeks. In this hypothesis-generating exploratory analysis, tirzepatide decreased several biomarkers that have been associated with cardiovascular risk.

Elevated circulating follistatin associates with an increased risk of type 2 diabetes.

The hepatokine follistatin is elevated in patients with type 2 diabetes (T2D) and promotes hyperglycemia in mice. Here we explore the relationship of plasma follistatin levels with incident T2D and mechanisms involved. Adjusted hazard ratio (HR) per standard deviation (SD) increase in follistatin levels for T2D is 1.24 (CI: 1.04-1.47, p < 0.05) during 19-year follow-up (n = 4060, Sweden); and 1.31 (CI: 1.09-1.58, p < 0.01) during 4-year follow-up (n = 883, Finland). High circulating follistatin associates with adipose tissue insulin resistance and non-alcoholic fatty liver disease (n = 210, Germany). In human adipocytes, follistatin dose-dependently increases free fatty acid release. In genome-wide association study (GWAS), variation in the glucokinase regulatory protein gene (GCKR) associates with plasma follistatin levels (n = 4239, Sweden; n = 885, UK, Italy and Sweden) and GCKR regulates follistatin secretion in hepatocytes in vitro. Our findings suggest that GCKR regulates follistatin secretion and that elevated circulating follistatin associates with an increased risk of T2D by inducing adipose tissue insulin resistance.

Mapping the genetic architecture of human traits to cell types in the kidney identifies mechanisms of disease and potential treatments.

The functional interpretation of genome-wide association studies (GWAS) is challenging due to the cell-type-dependent influences of genetic variants. Here, we generated comprehensive maps of expression quantitative trait loci (eQTLs) for 659 microdissected human kidney samples and identified cell-type-eQTLs by mapping interactions between cell type abundances and genotypes. By partitioning heritability using stratified linkage disequilibrium score regression to integrate GWAS with single-cell RNA sequencing and single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing data, we prioritized proximal tubules for kidney function and endothelial cells and distal tubule segments for blood pressure pathogenesis. Bayesian colocalization analysis nominated more than 200 genes for kidney function and hypertension. Our study clarifies the mechanism of commonly used antihypertensive and renal-protective drugs and identifies drug repurposing opportunities for kidney disease.

Circulating proteins protect against renal decline and progression to end-stage renal disease in patients with diabetes.

Diabetic kidney disease (DKD) and its major clinical manifestation, progressive renal decline that leads to end-stage renal disease (ESRD), are a major health burden for individuals with diabetes. The disease process that underlies progressive renal decline comprises factors that increase risk as well as factors that protect against this outcome. Using untargeted proteomic profiling of circulating proteins from individuals in two independent cohorts with type 1 and type 2 diabetes and varying stages of DKD followed for 7 to 15 years, we identified three elevated plasma proteins-fibroblast growth factor 20 (OR, 0.69; 95% CI, 0.54 to 0.88), angiopoietin-1 (OR, 0.72; 95% CI, 0.57 to 0.91), and tumor necrosis factor ligand superfamily member 12 (OR, 0.75; 95% CI, 0.59 to 0.95)-that were associated with protection against progressive renal decline and progression to ESRD. The combined effect of these three protective proteins was demonstrated by very low cumulative risk of ESRD in those who had baseline concentrations above median for all three proteins, whereas the cumulative risk of ESRD was high in those with concentrations below median for these proteins at the beginning of follow-up. This protective effect was shown to be independent from circulating inflammatory proteins and clinical covariates and was confirmed in a third cohort of diabetic individuals with normal renal function. These three protective proteins may serve as biomarkers to stratify diabetic individuals according to risk of progression to ESRD and might also be investigated as potential therapeutics to delay or prevent the onset of ESRD.

Comprehensive Search for Novel Circulating miRNAs and Axon Guidance Pathway Proteins Associated with Risk of ESKD in Diabetes.

BACKGROUND: Mechanisms underlying the pro gression of diabetic kidney disease to ESKD are not fully understood. METHODS: We performed global microRNA (miRNA) analysis on plasma from two cohorts consisting of 375 individuals with type 1 and type 2 diabetes with late diabetic kidney disease, and targeted proteomics analysis on plasma from four cohorts consisting of 746 individuals with late and early diabetic kidney disease. We examined structural lesions in kidney biopsy specimens from the 105 individuals with early diabetic kidney disease. Human umbilical vein endothelial cells were used to assess the effects of miRNA mimics or inhibitors on regulation of candidate proteins. RESULTS: In the late diabetic kidney disease cohorts, we identified 17 circulating miRNAs, represented by four exemplars (miR-1287-5p, miR-197-5p, miR-339-5p, and miR-328-3p), that were strongly associated with 10-year risk of ESKD. These miRNAs targeted proteins in the axon guidance pathway. Circulating levels of six of these proteins-most notably, EFNA4 and EPHA2-were strongly associated with 10-year risk of ESKD in all cohorts. Furthermore, circulating levels of these proteins correlated with severity of structural lesions in kidney biopsy specimens. In contrast, expression levels of genes encoding these proteins had no apparent effects on the lesions. In in vitro experiments, mimics of miR-1287-5p and miR-197-5p and inhibitors of miR-339-5p and miR-328-3p upregulated concentrations of EPHA2 in either cell lysate, supernatant, or both. CONCLUSIONS: This study reveals novel mechanisms involved in progression to ESKD and points to the importance of systemic factors in the development of diabetic kidney disease. Some circulating miRNAs and axon guidance pathway proteins represent potential targets for new therapies to prevent and treat this condition.