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.
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.
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.
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.
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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.
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.
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.
Introduction Association between elevated cytokeratin 18 (CK-18) levels and hepatocyte death has made circulating CK-18 a candidate biomarker to differentiate non-alcoholic fatty liver from ...non-alcoholic steatohepatitis (NASH). Yet studies produced variable diagnostic performance. We aimed to provide summary estimates with increased precision for the accuracy of CK-18 (M30, M65) in detecting NASH and fibrosis among non-alcoholic fatty liver disease (NAFLD) adults. Methods We searched five databases to retrieve studies evaluating CK-18 against a liver biopsy in NAFLD adults. Reference screening, data extraction and quality assessment (QUADAS-2) were independently conducted by two authors. Meta-analyses were performed for five groups based on the CK-18 antigens and target conditions, using one of two methods: linear mixed-effects multiple thresholds model or bivariate logit-normal random-effects model. Results We included 41 studies, with data on 5,815 participants. A wide range of disease prevalence was observed. No study reported a pre-defined cut-off. Thirty of 41 studies provided sufficient data for inclusion in any of the meta-analyses. Summary AUC 95% CI were: 0.75 0.69-0.82 (M30) and 0.82 0.69-0.91 (M65) for NASH; 0.73 0.57-0.85 (M30) for fibrotic NASH; 0.68 (M30) for significant (F2-4) fibrosis; and 0.75 (M30) for advanced (F3-4) fibrosis. Thirteen studies used CK-18 as a component of a multimarker model. Conclusions For M30 we found lower diagnostic accuracy to detect NASH compared to previous meta-analyses, indicating a limited ability to act as a stand-alone test, with better performance for M65. Additional external validation studies are needed to obtain credible estimates of the diagnostic accuracy of multimarker models.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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).
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.
Tirzepatide slows the eGFR decline rate, supporting a kidney-protective effect.
The AWARD-7 clinical trial of patients with type 2 diabetes (T2D) and chronic kidney disease (CKD) reported a slower decline in estimated glomerular filtration rate (eGFR) and decreased urinary ...albumin-to-creatinine ratio (UACR) in patients treated with dulaglutide, a glucagon-like peptide-1 (GLP-1) receptor agonist, compared to insulin glargine over one year. Previous studies identified 21 circulating plasma risk proteins highly associated with progression to end stage kidney disease (ESKD) in patients with diabetes (Joslin Kidney Panel). The aim of this study was to determine the longitudinal changes of these proteins in AWARD-7 to evaluate their predictive performance as biomarkers of kidney disease progression. Plasma samples were obtained from patients with T2D and CKD stages 3-4 who received dulaglutide 1.5 mg (n=124) or insulin glargine as basal therapy (n=125) for 52 weeks. Using the Olink custom platform we measured the concentration of 21 proteins at baseline, 26-weeks, and 52-weeks of treatment. At baseline all 21 proteins were correlated with eGFR (r=-0.2 to -0.8; all p<0.0003) and UACR (r=0.2 to 0.6; all p<0.0001). After 26 weeks of treatment, 13 risk proteins significantly increased in glargine group (3 to 13%; all p<0.05) whereas no significant change was observed in dulaglutide group at 26 weeks. By 52 weeks, 5 proteins remained significantly elevated in the glargine group compared to dulaglutide. Several proteins were correlated with declining kidney function (change of eGFR) and increasing UACR in patients with glargine, but not in patients treated with dulaglutide. In this study, the increase of plasma risk proteins associated with ESKD was slowed in dulaglutide-treated patients and is consistent with the hypothesis that several proteins within the Joslin Kidney Panel can serve as predictive biomarkers of treatment efficacy.
Disclosure
B.E.Mcfarlin: Employee; Eli Lilly and Company. E.Satake: None. Z.Md dom: None. J.Ricca: None. A.V.Kechter: Employee; Eli Lilly and Company. J.M.Wilson: Employee; Eli Lilly and Company. K.L.Duffin: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company, Pfizer Inc. A.Krolewski: None.
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.
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The role of fibrosis in early progressive renal decline in type 2 diabetes is unknown. Circulating WFDC2 (WAP four-disulfide core domain protein 2) and matrix metalloproteinase 7 (MMP-7; Matrilysin) ...are postulated to be biomarkers of renal fibrosis. This study examined an association of circulating levels of these proteins with early progressive renal decline.
Individuals with type 2 diabetes enrolled in the Joslin Kidney Study with an estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m
were monitored for 6-12 years to ascertain fast early progressive renal decline, defined as eGFR loss ≥5 mL/min/1.73 m
/year.
A total of 1,181 individuals were studied: 681 without and 500 with albuminuria. Median eGFR and albumin-to-creatinine ratio (ACR) at baseline were 97 mL/min/1.73 m
and 24 mg/g, respectively. During follow-up, 152 individuals experienced fast early progressive renal decline: 6.9% in those with normoalbuminuria and 21% with albuminuria. In both subgroups, the risk of renal decline increased with increasing baseline levels of WFDC2 (
< 0.0001) and MMP-7 (
< 0.0001). After adjustment for relevant clinical characteristics and known biomarkers, an increase by one quartile in the fibrosis index (combination of levels of WFDC2 and MMP-7) was associated with higher risk of renal decline (odds ratio 1.63; 95% CI 1.30-2.04). The association was similar and statistically significant among patients with and without albuminuria.
Elevation of circulating profibrotic proteins is associated with the development of early progressive renal decline in type 2 diabetes. This association is independent from albuminuria status and points to the importance of the fibrotic process in the development of early renal decline.
Metabolic-associated fatty liver disease is common, with fibrosis the major determinant of adverse outcomes. Population-based screening tools with high diagnostic accuracy for the staging of fibrosis ...are lacking.
Three independent cohorts, 2 with both liver biopsy and liver stiffness measurements (LSMs, n = 254 and 65) and a population sample (n = 713), were studied. The performance of a recently developed noninvasive algorithm (ADAPT age, diabetes, PRO-C3 and platelets panel) as well as aspartate aminotransferase-to-platelet ratio index, fibrosis-4, nonalcoholic fatty liver disease fibrosis score, and LSM was used to stage patients for significant (≥F2) and advanced (≥F3) fibrosis.
In the hospital-based cohorts, the N-terminal propeptide of type 3 collagen (Pro-C3) increased with fibrosis stage (P < 0.0001) and independently associated with advanced fibrosis (odds ratio = 1.091, 95% confidence interval CI: 1.053-1.113, P = 0.0001). ADAPT showed areas under the receiver operating characteristics curve of 0.831 (95% CI: 0.779-0.875) in the derivation and 0.879 (95% CI: 0.774-0.946) in the validation cohort for advanced fibrosis. This was superior to the existing fibrosis scores, aspartate aminotransferase-to-platelet ratio index, fibrosis-4, BARD (BMI, aspartate aminotransferase to alanine aminotransferase ratio AAR, diabetes), and nonalcoholic fatty liver disease fibrosis score in most comparisons and comparable with LSM. Serial use of ADAPT and LSM had diagnostic accuracy of 92.5%, with 98% and 100% negative predictive value in the derivation and validation cohorts, respectively. In the population cohort, PRO-C3 associated with advanced fibrosis (P = 0.04), while ADAPT had a negative predictive value of 98% for excluding advanced fibrosis.
PRO-C3 and ADAPT reliably exclude advanced fibrosis in low-risk populations. The serial combination of ADAPT with LSM has high diagnostic accuracy with a low requirement for liver biopsy. The proposed algorithm would help stratify those who need biopsies and narrow down those patients who would need to be referred to specialty clinics.
The decline of estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes is variable, and early interventions would likely be cost-effective. We elucidated the contribution of 17 ...plasma biomarkers to the prediction of eGFR loss on top of clinical risk factors.
We studied participants in PROVALID (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers), a prospective multinational cohort study of patients with type 2 diabetes and a follow-up of more than 24 months (
= 2,560; baseline median eGFR, 84 mL/min/1.73 m
; urine albumin-to-creatinine ratio, 8.1 mg/g). The 17 biomarkers were measured at baseline in 481 samples using Luminex and ELISA. The prediction of eGFR decline was evaluated by linear mixed modeling.
In univariable analyses, 9 of the 17 markers showed significant differences in median concentration between stable and fast-progressing patients. A linear mixed model for eGFR obtained by variable selection exhibited an adjusted
of 62%. A panel of 12 biomarkers was selected by the procedure and accounted for 34% of the total explained variability, of which 32% was due to 5 markers. The individual contribution of each biomarker to the prediction of eGFR decline on top of clinical predictors was generally low. When included into the model, baseline eGFR exhibited the largest explained variability of eGFR decline (
of 79%), and the contribution of each biomarker dropped below 1%.
In this longitudinal study of patients with type 2 diabetes and maintained eGFR at baseline, 12 of the 17 candidate biomarkers were associated with eGFR decline, but their predictive power was low.
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