Variability of urinary albumin to creatinine ratio and eGFR are independently associated with eGFR slope in Japanese with type 2 diabetes: a three-year, single-center, retrospective cohort study.

BACKGROUND: To evaluate the seasonal variability of urinary albumin to creatinine ratio (UACR) and eGFR and these effects on three-year eGFR slope in persons with type 2 diabetes (T2D). METHODS: A total of 1135 persons with T2D were analyzed in this single-center, retrospective cohort study in Japan. The standard deviation (SD) of UACR (SD [UACR]) and SD of eGFR (SD [eGFR]) were calculated for each person's 10-point data during the three years, and a multiple linear regression analysis was performed to evaluate associations with eGFR slope. A sensitivity analysis was performed in a group with no medication changes (n = 801). RESULTS: UACR exhibited seasonal variability, being higher in winter and lower in spring, early summer, and autumn especially in the UACR ≥ 30 mg/g subgroup, while eGFR showed no seasonal variability. The eGFR slope was significantly associated with SD (eGFR) (regression coefficient -0.170 [95% CI -0.189--0.151]) and SD (UACR) (0.000 [-0.001-0.000]). SGLT-2 inhibitors, baseline eGFR, and baseline systolic blood pressure (SBP) were also significantly associated. These associated factors, except baseline SBP, were still significant in the sensitivity analysis. CONCLUSIONS: The UACR showed clear seasonal variability. Moreover, SD (UACR) and SD (eGFR) were independently associated with a three-year eGFR slope in persons with T2D. TRIAL REGISTRATION: This study was not registered for clinical trial registration because it was a retrospective observational study.

Practicalities and importance of assessing urine albumin excretion in type 2 diabetes: A cutting-edge update.

Type 2 diabetes (T2D) is associated with increased risk for chronic kidney disease (CKD). It is estimated that 40 % of people with diabetes have CKD, which consequently leads to increase in morbidity and mortality from cardiovascular diseases (CVDs). Diabetic kidney disease (DKD) is leading cause of CKD and end-stage renal disease (ESRD) globally. On the other hand, DKD is independent risk factor for CVDs, stroke and overall mortality. According to the guidelines, using spot urine sample and assessing urine albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR) are both mandatory methods for screening of CKD in T2D at diagnosis and at least annually thereafter. Diagnosis of CKD is confirmed by persistent albuminuria followed by a progressive decline in eGFR in two urine samples at an interval of 3 to 6 months. However, many patients with T2D remain underdiagnosed and undertreated, so there is an urgent need to improve the screening by detection of albuminuria at all levels of health care. This review discusses the importance of albuminuria as a marker of CKD and cardiorenal risk and provides insights into the practical aspects of methods for determination of albuminuria in routine clinical care of patients with T2D.

Association of urinary creatinine excretion and body mass index with diabetic retinopathy in patients with type 2 diabetes.

This study aimed to determine whether urinary creatinine excretion rate (CER), a marker of muscle mass, is associated with diabetic retinopathy in individuals with type 2 diabetes and to ascertain whether this putative association depends on body mass index (BMI). This cross sectional study evaluated 2035 individuals with type 2 diabetes. Twenty-four-hour urine was collected. Individuals with diabetic retinopathy had lower CER and BMI values than those without. Patients in higher CER quartiles had higher BMI values and a lower prevalence of diabetic retinopathy. A significant relationship between CER and diabetic retinopathy persisted, even after adjusting for traditional risk factors, including glycated hemoglobin, diabetes duration, and hypertension, in multivariable analysis. Further adjustment for BMI did not significantly alter the association between CER and diabetic retinopathy. This study suggests that CER is inversely associated with diabetic retinopathy in individuals with type 2 diabetes, and this association is independent of BMI.

Urine biomarkers in type 2 diabetes mellitus with or without microvascular complications.

OBJECTIVE: To investigate the distribution of nine (9) urine biomarkers in people living with type 2 diabetes mellitus (T2DM), with or without microvascular complications. METHODS: In total, 407 people with T2DM were enrolled from 2021 to 2022. According to diabetic retinopathy (DR) and urinary albumin-creatinine ratio (UACR), the 407 people were divided into four (4) groups, DR(-)UACR(-), DR(+)UACR(-), DR(-)UACR(+), and DR( + )UACR(+). In addition, 112 healthy volunteers were enrolled during the same period. The nine (9) urine markers included α1-microglobulin (u-α1MG), immunoglobulin G (u-IgG), neutrophil gelatinase-associated lipid carrier protein (u-NGAL), cystatin C (u-CysC), retinol-binding protein (u-RBP), ß2-microglobulin (u-ß2MG), N-acetyl-ß-D-glucosaminidase (u-NAG), transferrin (u-Trf), and collagen type IV (u-Col). For each marker, the respective level of 97.5 percentile in healthy volunteers was taken as an upper reference limit. RESULTS: Among the 407 people, 248 individuals (61%) were DR(-)UACR(-), 100 (25%) were DR(-)UACR(+), 37 (9%) were DR(+)UACR(-), and 22 (5%) were DR(+)UACR(+). The u-NAG/Cr biomarker level showed a significant difference between healthy participants and people with T2DM. In the DR(-)UACR(-)group, u-Trf/Cr showed the highest positive rate (21.37%), followed by u-IgG/Cr (14.52%); u-NAG/Cr (10.48%); u-ß2MG/Cr (4.44%); u-CysC/Cr (4.03%); u-NGAL/Cr (4.03%); u-RBP/Cr (2.82%); u-α1MG/Cr (2.42%); 17.34% of people with T2DM showed multiple biomarkers positive (≥2 biomarkers). The positive rates of one biomarker (21.33%) and two biomarkers (18.67%) in people who have less than five (5) years of T2DM were almost close to those of the DR(-)UACR(-) group (21.37%, and 12.10%, respectively). CONCLUSION: Renal tubule biomarkers may be used as an indicator in the early detection and monitoring of renal injury in diabetes mellitus. The u-NAG biomarker should be measured for the people with T2DM of the first-time diagnosis.

Application of Proteomics and Machine Learning Methods to Study the Pathogenesis of Diabetic Nephropathy and Screen Urinary Biomarkers.

Diabetic nephropathy (DN) has become the main cause of end-stage renal disease worldwide, causing significant health problems. Early diagnosis of the disease is quite inadequate. To screen urine biomarkers of DN and explore its potential mechanism, this study collected urine from 87 patients with type 2 diabetes mellitus (which will be classified into normal albuminuria, microalbuminuria, and macroalbuminuria groups) and 38 healthy subjects. Twelve individuals from each group were then randomly selected as the screening cohort for proteomics analysis and the rest as the validation cohort. The results showed that humoral immune response, complement activation, complement and coagulation cascades, renin-angiotensin system, and cell adhesion molecules were closely related to the progression of DN. Five overlapping proteins (KLK1, CSPG4, PLAU, SERPINA3, and ALB) were identified as potential biomarkers by machine learning methods. Among them, KLK1 and CSPG4 were positively correlated with the urinary albumin to creatinine ratio (UACR), and SERPINA3 was negatively correlated with the UACR, which were validated by enzyme-linked immunosorbent assay (ELISA). This study provides new insights into disease mechanisms and biomarkers for early diagnosis of DN.

Comparative Determination of Glomerular Filtration Rate Estimation Formulae in Type 2 Diabetic Patients: An Observational Study.

Assessing glomerular filtration rate (GFR) involves collecting timed urine samples for 24 hours, requiring significant time and resources in the clinical setting. Using predictive GFR formulae to assess renal function may be a better alternative. Our goal was to determine which predictive GFR formula had the highest level of concordance with the GFR that has been measured in a resource-poor setting. This is an observational study. We selected fifty (50) individuals diagnosed with type 2 diabetes (T2DM) in Kumasi, Ghana. The sociodemographic and clinical characteristics were obtained using a structured questionnaire. Urine was obtained from each subject over 24 hours. The levels of glucose (FBG) and creatinine in patients' blood, as well as the levels of creatinine in their urine, were measured after the patients had fasted overnight. Participants had a mean age of 57.4 ± 10.7 (years), BMI of 27.8 ± 4.1 (kg/m2), FBG of 9.0 ± 3.1 (mmol/L), and creatinine concentrations of 95.6 ± 29.1 (µmol/L). A Krouwer plot was used to compare the measured GFR with three formulae: Chronic Kidney Disease Epidemiology (CKD-EPI), Modification of Diet in Renal Disease (MDRD), and Cockroft-Gault (CG) for GFR prediction. Among the 3 estimates, CG showed nonsignificance (p > 0.05) with the measured GFR. The primary finding was that the GFR calculated using the CG formula was not different from the GFR measured, suggesting that CG is the most appropriate alternative GFR estimate among a cross-section of T2DM patients in Ghana.

Association between Urine Specific Gravity as a Measure of Hydration Status and Risk of Type 2 Diabetes: The Kailuan Prospective Cohort Study.

Diabetes, especially type 2 diabetes (T2D), poses an unprecedented challenge to global public health. Hydration status also plays a fundamental role in human health, especially in people with T2D, which is often overlooked. This study aimed to explore the longitudinal associations between hydration status and the risk of T2D among the Chinese population. This study used data from the large community-based Kailuan cohort, which included adults who attended physical examinations from 2006 to 2007 and were followed until 2020. A total of 71,526 participants who eventually met the standards were divided into five hydration-status groups based on their levels of urine specific gravity (USG). Multivariable and time-dependent Cox proportional hazards models were employed to evaluate the associations of baseline and time-dependent hydration status with T2D incidence. Restricted cubic splines (RCS) analysis was used to examine the dose-response relationship between hydration status and the risk of T2D. Over a median 12.22-year follow-up time, 11,804 of the participants developed T2D. Compared with the optimal hydration-status group, participants with dehydration and severe dehydration had a significantly increased risk of diabetes, with adjusted hazard ratios (95% CI) of 1.30 (1.04-1.63) and 1.38 (1.10-1.74). Time-dependent analyses further confirmed the adverse effects of impending dehydration, dehydration, and severe dehydration on T2D incidence by 16%, 26%, and 33% compared with the reference group. Inadequate hydration is significantly associated with increased risks of T2D among Chinese adults. Our findings provided new epidemiological evidence and highlighted the potential role of adequate hydration status in the early prevention of T2D development.

Urinary SIRT2 Reflects Kidney Injury in Type 2 Diabetes.

INTRODUCTION: The early diagnosis of kidney injury in type 2 diabetes (T2DM) is important to prevent the long-term damaging effects of kidney loss and is decisive for patient outcomes. While SIRT2 is implicated in diabetes pathogenesis, its correlation with diabetic nephropathy remains unexplored. This study was designed to evaluate the association of urine SIRT2 levels with diabetic kidney injury, as well as potential underlying mechanisms. METHODS: In T2DM patients, db/db mice, and high glucose plus palmitic acid treated HK2 cell models, ELISA, Immunoturbidimetry, Immunohistochemistry, Western blot, and Quantitative real-time polymerase chain reaction were used to detect SIRT2 levels and kidney damage. According to urinary albumin/creatinine ratio (UACR), 163 T2DM patients were divided into three groups. Spearman correlation analysis was used to investigate the relationship between urinary sirtuin2/creatinine ratio (USCR) and biomarkers of kidney injury. The influencing factors of albuminuria in T2DM patients were analyzed by logistic regression model. RESULTS: In our findings, the Macro group exhibited the highest USCR levels as UACR increased. There was a positive association between USCR and UACR, α1-microglobulin/creatinine ratio (UαCR), ß2-microglobulin/creatinine ratio (UßCR), and retinol-binding protein/creatinine ratio (URCR), with a negative correlation observed with eGFR. Logistic ordered multiclassification regression analysis, adjusting for confounding variables, confirmed that USCR remained a significant risk factor for the severity of albuminuria in T2DM patients. In the db/db mice kidney SIRT2 protein level increased significantly. Increased SIRT2 protein levels were also observed in renal tubular epithelial cells treated with high glucose plus palmitic acid. Moreover, SIRT2 promotes the expression of proinflammatory factors TNF-α and IL-6 by modulating the phosphorylation of p38 MAPK and p-JNK in renal tubular cells induced by high glucose and palmitic acid. CONCLUSION: Urinary SIRT2 is closely related to eGFR, renal tubule injury, and urinary albumin excretion in T2DM patients, which is expected to be an important indicator to comprehensively reflect renal injury.

Isocitrate dehydrogenase 1 upregulation in urinary extracellular vesicles from proximal tubules of type 2 diabetic rats.

Diabetic nephropathy (DN) is a major cause of chronic kidney disease. Microalbuminuria is currently the most common non-invasive biomarker for the early diagnosis of DN. However, renal structural damage may have advanced when albuminuria is detected. In this study, we sought biomarkers for early DN diagnosis through proteomic analysis of urinary extracellular vesicles (uEVs) from type 2 diabetic model rats and normal controls. Isocitrate dehydrogenase 1 (IDH1) was significantly increased in uEVs from diabetic model rats at the early stage despite minimal differences in albuminuria between the groups. Calorie restriction significantly suppressed the increase in IDH1 in uEVs and 24-hour urinary albumin excretion, suggesting that the increase in IDH1 in uEVs was associated with the progression of DN. Additionally, we investigated the origin of IDH1-containing uEVs based on their surface sugar chains. Lectin affinity enrichment and immunohistochemical staining showed that IDH1-containing uEVs were derived from proximal tubules. These findings suggest that the increase in IDH1 in uEVs reflects pathophysiological alterations in the proximal tubules and that IDH1 in uEVs may serve as a potential biomarker of DN in the proximal tubules.

URINARY EXCRETION OF ALPHA-ACTININ-4 AND TIGHT JUNCTION PROTEIN 1 IN PATIENTS WITH TYPE 2 DIABETES AND DIFFERENT PATTERNS OF CHRONIC KIDNEY DISEASE.

Abnormalities of the cytoskeleton and the slit diaphragm of podocytes have been attributed to diabetic nephropathy. In this study, we assessed urinary excretion of alpha-actinin-4 (ACTN-4), a cytoskeleton protein and a component of the slit diaphragm, and tight junction protein 1 (TJP-1, or ZO-1), a peripheral membrane protein that forms molecular complexes with actin filaments, in patients with type 2 diabetes (T2D) and albuminuric or non-albuminuric chronic kidney disease (CKD). The study included 140 patients with long-term T2D (≥10 years) and 20 healthy subjects as control. Patterns of CKD were identified based on the estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (UACR). Urinary ACTN-4 and TJP-1 were assessed by ELISA. Patients with T2D had increased urinary excretion of ACTN-4 (p=0.03) and TJP-1 (p=0.006). In logistic regression models, both ACTN-4 and TJP-1 demonstrated associations with albuminuric CKD (UACR ≥3.0 mg/mmol and eGFR <60 mL/min×1.73 m2) after adjusting to age, sex, diabetes duration, HbA1c, and smoking. In ROC-analysis, TJP-1 excretion ≥70 pg/mmol was associated with albuminuric CKD (OR 5.45, 95% CI 1.96-15.18, p=0.001). The results demonstrate that elevated urinary ACTN-4 and TJP-1 are associated specifically with albuminuric CKD, but not with non-albuminuric CKD, in T2D patients.

Multiple urinary peptides are associated with hypertension: a link to molecular pathophysiology.

OBJECTIVES: Hypertension is a common condition worldwide; however, its underlying mechanisms remain largely unknown. This study aimed to identify urinary peptides associated with hypertension to further explore the relevant molecular pathophysiology. METHODS: Peptidome data from 2876 individuals without end-organ damage were retrieved from the Human Urinary Proteome Database, belonging to general population (discovery) or type 2 diabetic (validation) cohorts. Participants were divided based on systolic blood pressure (SBP) and diastolic BP (DBP) into hypertensive (SBP ≥140 mmHg and/or DBP ≥90 mmHg) and normotensive (SBP <120 mmHg and DBP <80 mmHg, without antihypertensive treatment) groups. Differences in peptide abundance between the two groups were confirmed using an external cohort ( n  = 420) of participants without end-organ damage, matched for age, BMI, eGFR, sex, and the presence of diabetes. Furthermore, the association of the peptides with BP as a continuous variable was investigated. The findings were compared with peptide biomarkers of chronic diseases and bioinformatic analyses were conducted to highlight the underlying molecular mechanisms. RESULTS: Between hypertensive and normotensive individuals, 96 (mostly COL1A1 and COL3A1) peptides were found to be significantly different in both the discovery (adjusted) and validation (nominal significance) cohorts, with consistent regulation. Of these, 83 were consistently regulated in the matched cohort. A weak, yet significant, association between their abundance and standardized BP was also observed. CONCLUSION: Hypertension is associated with an altered urinary peptide profile with evident differential regulation of collagen-derived peptides. Peptides related to vascular calcification and sodium regulation were also affected. Whether these modifications reflect the pathophysiology of hypertension and/or early subclinical organ damage requires further investigation.

Urinary non-albumin protein-creatinine ratio is an independent predictor of mortality in patients with type 2 diabetes: a retrospective cohort study.

Albuminuria is a well-known predictor of chronic kidney disease in patients with type 2 diabetes mellitus (DM). However, proteinuria is associated with chronic complications in patients without albuminuria. In this retrospective cohort study, we explored whether non-albumin proteinuria is associated with all-cause mortality and compared the effects of non-albumin proteinuria on all-cause mortality between patients with and without albuminuria. We retrospectively collected data from patients with type 2 DM for whom we had obtained measurements of both urinary albumin-to-creatinine ratio (UACR) and urinary protein-to-creatinine ratio (UPCR) from the same spot urine specimen. Urinary non-albumin protein-creatinine ratio (UNAPCR) was defined as UPCR-UACR. Of the 1809 enrolled subjects, 695 (38.4%) patients died over a median follow-up of 6.4 years. The cohort was separated into four subgroups according to UACR (30 mg/g) and UNAPCR (120 mg/g) to examine whether these indices are associated with all-cause mortality. Compared with the low UACR and low UNAPCR subgroup as the reference group, multivariable Cox regression analyses indicated no significant difference in mortality in the high UACR and low UNAPCR subgroup (hazard ratio [HR] 1.189, 95% confidence interval [CI] 0.889-1.589, P = 0.243), but mortality risks were significantly higher in the low UACR and high UNAPCR subgroup (HR 2.204, 95% CI 1.448-3.356, P < 0.001) and in the high UACR with high UNAPCR subgroup (HR 1.796, 95% CI 1.451-2.221, P < 0.001). In the multivariable Cox regression model with inclusion of both UACR and UNAPCR, UNAPCR ≥ 120 mg/g was significantly associated with an increased mortality risk (HR 1.655, 95% CI 1.324-2.070, P < 0.001), but UACR ≥ 30 mg/g was not significantly associated with mortality risk (HR 1.046, 95% CI 0.820-1.334, P = 0.717). In conclusion, UNAPCR is an independent predictor of all-cause mortality in patients with type 2 DM.

Self-reported smoking, urine cotinine, and risk of type 2 diabetes: Findings from the PREVEND prospective cohort study.

BACKGROUND: Smoking is a major risk factor for type 2 diabetes (T2D), but the evidence has mostly relied on self-reports. We aimed to compare the associations of smoking exposure as assessed by self-reports and urine cotinine with T2D. METHODS: Using the PREVEND prospective study, smoking status was assessed at baseline by self-reports and urine cotinine in 4708 participants (mean age, 53 years) without a history of diabetes. Participants were classified as never, former, light current and heavy current smokers according to self-reports and analogous cut-offs for urine cotinine. Hazard ratios (HRs) with 95% CIs were estimated for T2D. RESULTS: During a median follow-up of 7.3 years, 259 participants developed T2D. Compared with self-reported never smokers, the multivariable adjusted HRs (95% CI) of T2D for former, light current, and heavy current smokers were 1.02 (0.75-1.4), 1.41 (0.89-2.22), and 1.30 (0.88-1.93), respectively. The corresponding adjusted HRs (95% CI) were 0.84 (0.43-1.67), 1.61 (1.12-2.31), and 1.58 (1.08-2.32), respectively, as assessed by urine cotinine. Urine cotinine-assessed but not self-reported smoking status improved T2D risk prediction beyond established risk factors. CONCLUSION: Urine cotinine assessed smoking status may be a stronger risk indicator and predictor of T2D compared to self-reported smoking status.

Association of the longitudinal trajectory of urinary albumin/creatinine ratio in diabetic patients with adverse cardiac event risk: a retrospective cohort study.

Objective: The baseline urinary albumin/creatinine ratio (uACR) has been proven to be significantly associated with the risk of major adverse cardiac events (MACE). However, data on the association between the longitudinal trajectory patterns of uACR, changes in glycated hemoglobin A1c (HbA1c), and the subsequent risk of MACE in patients with diabetes are sparse. Methods: This is a retrospective cohort study including 601 patients with type 2 diabetes mellitus (T2DM; uACR < 300 mg/g) admitted to The First Hospital of Shanxi Medical University and The Second Hospital of Shanxi Medical University from January 2015 to December 2018. The uACR index was calculated as urinary albumin (in milligrams)/creatinine (in grams), and latent mixed modeling was used to identify the longitudinal trajectory of uACR during the exposure period (2016-2020). The deadline for follow-up was December 31, 2021. The primary outcome was the MACE [a composite outcome of cardiogenic death, hospitalization related to heart failure (HHF), non-fatal acute myocardial infarction, non-fatal stroke, and acute renal injury/dialysis indications]. The Kaplan-Meier survival analysis curve was used to compare the risk of MACE among four groups, while univariate and multivariate Cox proportional hazards models were employed to calculate the hazard ratio (HR) and 95% confidence interval (CI) for MACE risk among different uACR or HbA1c trajectory groups. The predictive performance of the model, both before and after the inclusion of changes in the uACR and HbA1c, was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). Results: Four distinct uACR trajectories were identified, namely, the low-stable group (uACR = 5.2-38.3 mg/g, n = 112), the moderate-stable group (uACR = 40.4-78.6 mg/g, n = 229), the high-stable group (uACR = 86.1-153.7 mg/g, n = 178), and the elevated-increasing group (uACR = 54.8-289.4 mg/g, n = 82). In addition, five distinct HbA1c trajectories were also identified: the low-stable group (HbA1c = 5.5%-6.8%, n = 113), the moderate-stable group (HbA1c = 6.0%-7.9%, n = 169), the moderate-decreasing group (HbA1c = 7.4%-6.1%, n = 67), the high-stable group (HbA1c = 7.7%-8.9%, n = 158), and the elevated-increasing group (HbA1c = 8.4%-10.3%, n = 94). Compared with the low-stable uACR group, patients in the high-stable and elevated-increasing uACR groups were more likely to be older, current smokers, and have a longer DM course, higher levels of 2-h plasma glucose (PG), HbA1c, N-terminal pro-B-type natriuretic peptide (NT-proBNP), uACR, and left ventricular mass index (LVMI), while featuring a higher prevalence of hypertension and a lower proportion of ß-receptor blocker treatment (p < 0.05). During a median follow-up of 45 months (range, 24-57 months), 118 cases (19.6%) of MACE were identified, including 10 cases (1.7%) of cardiogenic death, 31 cases (5.2%) of HHF, 35 cases (5.8%) of non-fatal acute myocardial infarction (AMI), 18 cases (3.0%) of non-fatal stroke, and 24 cases (4.0%) of acute renal failure/dialysis. The Kaplan-Meier survival curve showed that, compared with that in the low-stable uACR group, the incidence of MACE in the high-stable (HR = 1.337, 95% CI = 1.083-1.652, p = 0.007) and elevated-increasing (HR = 1.648, 95% CI = 1.139-2.387, p = 0.009) uACR groups significantly increased. Similar results were observed for HHF, non-fatal AMI, and acute renal injury/dialysis indications (p < 0.05). The multivariate Cox proportional hazards models indicated that, after adjusting for potential confounders, the HRs for the risk of MACE were 1.145 (p = 0.132), 1.337 (p = 0.007), and 1.648 (p = 0.009) in the moderate-stable, high-stable, and elevated-increasing uACR groups, respectively. In addition, the HRs for the risk of MACE were 1.203 (p = 0.028), 0.872 (p = 0.024), 1.562 (p = 0.033), and 2.218 (p = 0.002) in the moderate-stable, moderate-decreasing, high-stable, and elevated-increasing groups, respectively. The ROC curve showed that, after adding uACR, HbA1c, or both, the AUCs were 0.773, 0.792, and 0.826, which all signified statistically significant improvements (p = 0.021, 0.035, and 0.019, respectively). Conclusion: A long-term elevated uACR is associated with a significantly increased risk of MACE in patients with diabetes. This study implies that regular monitoring of uACR could be helpful in identifying diabetic patients with a higher risk of MACE.

Non-adherence to cardiometabolic medication as assessed by LC-MS/MS in urine and its association with kidney and cardiovascular outcomes in type 2 diabetes mellitus.

AIMS/HYPOTHESIS: Non-adherence to medication is a frequent barrier in the treatment of patients with type 2 diabetes mellitus, potentially limiting the effectiveness of evidence-based treatments. Previous studies have mostly relied on indirect adherence measures to analyse outcomes based on adherence. The aim of this study was to use LC-MS/MS in urine-a non-invasive, direct and objective measure-to assess non-adherence to cardiometabolic drugs and analyse its association with kidney and cardiovascular outcomes. METHODS: This cohort study includes 1125 participants from the PROVALID study, which follows patients with type 2 diabetes mellitus at the primary care level. Baseline urine samples were tested for 79 cardiometabolic drugs and metabolites thereof via LC-MS/MS. An individual was classified as totally adherent if markers for all drugs were detected, partially non-adherent when at least one marker for one drug was detected, and totally non-adherent if no markers for any drugs were detected. Non-adherence was then analysed in the context of cardiovascular (composite of myocardial infarction, stroke and cardiovascular death) and kidney (composite of sustained 40% decline in eGFR, sustained progression of albuminuria, kidney replacement therapy and death from kidney failure) outcomes. RESULTS: Of the participants, 56.3% were totally adherent, 42.0% were partially non-adherent, and 1.7% were totally non-adherent to screened cardiometabolic drugs. Adherence was highest to antiplatelet and glucose-lowering agents and lowest to lipid-lowering agents. Over a median (IQR) follow-up time of 5.10 (4.12-6.12) years, worse cardiovascular outcomes were observed with non-adherence to antiplatelet drugs (HR 10.13 [95% CI 3.06, 33.56]) and worse kidney outcomes were observed with non-adherence to antihypertensive drugs (HR 1.98 [95% CI 1.37, 2.86]). CONCLUSIONS/INTERPRETATION: This analysis shows that non-adherence to cardiometabolic drug regimens is common in type 2 diabetes mellitus and negatively affects kidney and cardiovascular outcomes.

Miniature mass spectrometer-based point-of-care assay for quantification of metformin and sitagliptin in human blood and urine.

Metformin (MET) and sitagliptin (STG) are widely used as the first-line and long-term oral hypoglycemic agents for managing type 2 diabetes mellitus (T2DM). However, the current lack of convenient and rapid measurement methods poses a challenge for individualized management. This study developed a point-of-care (POC) assay method utilizing a miniature mass spectrometer, enabling rapid and accurate quantification of MET and STG concentrations in human blood and urine. By combining the miniature mass spectrometer with paper spray ionization, this method simplifies the process into three to four steps, requires minimal amounts of bodily fluids (50 µL of blood and 2 µL of urine), and is able to obtain quantification results within approximately 2 min. Stable isotope-labeled internal standards were employed to enhance the accuracy and stability of measurement. The MS/MS responses exhibited good linear relationship with concentration, with relative standard deviations (RSDs) below 25%. It has the potential to provide immediate treatment feedback and decision support for patients and healthcare professionals in clinical practice.

Soluble tumor necrosis factor receptor type 1 is an alternative marker of urinary albumin-creatinine ratio and estimated glomerular filtration rate for predicting the decline of renal function in subjects with type 2 diabetes mellitus.

BACKGROUND: Urinary albumin-creatinine ratio (UACR) and estimated glomerular filtration rates (eGFR) help predict worsening diabetic kidney disease (DKD) but have their limitations. Soluble tumor necrosis factor receptor type 1 (sTNFR1) is a biomarker of DKD. The predictive abilities of sTNFR1 and UACR plus eGFR have not been compared. METHODS: This prospective cohort study included patients with type 2 diabetes (T2D) to identify the risk factors of worsening DKD. Renal events were defined as > 30 % loss in eGFR based on consecutive tests after 6 months. The associations of sTNFR1, UACR, and eGFR levels and the risks of renal events were tested using a Cox regression model and the area under the curve (AUC) was compared between sTNFR1 levels and UACR plus eGFR using receiver-operating characteristic (ROC) analysis. The accuracy of stratification was evaluated using Kaplan-Meier analysis. RESULTS: Levels of sTNFR1 and UACR were associated with risks of > 30 % decline in eGFR after adjusting for relevant factors. The association between sTNFR1 levels and renal outcomes was independent of UACR and eGFR at baseline. The AUC of sTNFR1 level was comparable with that of combined UACR and eGFR (0.73 vs. 0.71, respectively, p = 0.72) and the results persisted for quartile groups of sTNFR1 and risk categories of Kidney Disease: Improving Global Outcomes (KDIGO) (0.70 vs. 0.71, respectively, p = 0.84). Both stratifications by sTNFR1 levels and KDIGO were accurate. CONCLUSION: sTNFR1 could be an alternative marker for identifying patients with diabetes at risk of declining renal function.

Dapagliflozin Reduces Urinary Kidney Injury Biomarkers in Chronic Kidney Disease Irrespective of Albuminuria Level.

The beneficial effects of sodium-glucose cotransporter 2 (SGLT2) inhibitors in patients with chronic kidney disease (CKD) with low albuminuria levels have not been established. This study aimed to compare the effects of dapagliflozin on kidney injury biomarkers in patients with CKD stratified by albuminuria level. We prospectively enrolled healthy volunteers (HVs; n = 20) and patients with CKD (n = 54) with and without diabetes mellitus. Patients with CKD were divided into two age-matched and sex-matched subgroups according to urinary albumin-creatinine ratio (uACR) levels (<300 mg/g and ≥300 mg/g). The CKD group received dapagliflozin (10 mg/day). Urine samples were collected before treatment and after 3 and 6 months of dapagliflozin. Urinary kidney injury molecule-1 (KIM-1), interleukin-1ß (IL-1ß), and mitochondrial DNA nicotinamide adenine dinucleotide dehydrogenase subunit-1 (mtND1) copy number were measured. The estimated glomerular filtration rate (eGFR) of patients with CKD was lower than that of HVs (P < 0.001). During the study period, eGFR decreased and uACR did not change in the CKD group. Kidney injury markers were significantly elevated in patients with CKD compared with those in HVs. Dapagliflozin reduced urinary KIM-1, IL-1ß, and mtDNA copy number in patients with CKD after 6 months of treatment. In further, the levels of urinary KIM-1 and IL-1ß, patients with CKD decreased after 6 months of dapagliflozin treatment regardless of albuminuria level. Dapagliflozin reduced urinary kidney injury biomarkers in patients with CKD, regardless of albuminuria level. These findings suggest that SGLT2 inhibitors may also attenuate the progression of low albuminuric CKD.

Association of urinary calcium excretion with chronic kidney disease in patients with type 2 diabetes.

PURPOSE: Herein, we investigated the correlation between urinary calcium excretion (UCaE) and chronic kidney disease (CKD) in patients with type 2 diabetes mellitus (T2DM). METHODS: From August 2018 to January 2023, a total of 2031 T2DM patients providing 24-h urine samples were included in the final analyses. Patients were separated into four cohorts, based on the UCaE quartiles. We then analyzed renal functional indicators like estimated glomerular filtration rate (eGFR) and urinary albumin excretion (UAE) among the four groups. Lastly, we utilized multivariable logistic regression models to investigate the correlation between UCaE and CKD. RESULTS: After adjusting for confounding factors, we observed a decreasing trend in CKD prevalence (36.3%, 13.0%, 7.5%, and 6.6%, respectively, P < 0.001) across the UCaE quartiles. Albuminuria (55.5% vs. 40.0%, 36.5%, 37.4%) and macroalbuminuria prevalence (20.0% vs. 9.3%, 5.2%, 5.7%) in the lowest quartile were markedly elevated, compared to the remaining three quartiles (P < 0.001). Meanwhile, the eGFR level (P < 0.001) showed a clearly increasing trend across the UCaE quartiles, and patients with moderate-to-severe decreases in eGFR levels (with cutoff limits at 30-59, 15-30, and < 15 mL/min/1.73m2) were mostly found in the lowest quartile (P < 0.001). Logistic regression analysis revealed that patients in the lowest quartile experienced an enhanced prevalence of CKD, relative to those in the highest quartile (odds ratio: 5.90, 95% confidence interval: 3.60-9.67, P < 0.001). CONCLUSION: Decreased UCaE was independently associated with the CKD prevalence in T2DM patients.

Urine Albumin-Creatinine Ratio Variability in People With Type 2 Diabetes: Clinical and Research Implications.

RATIONALE & OBJECTIVE: Evidence has demonstrated that albuminuria is a key diagnostic and prognostic marker of diabetic chronic kidney disease, but the impact of its day-to-day variability has not been adequately considered. This study quantified within-individual variability of albuminuria in people with type 2 diabetes to inform clinical albuminuria monitoring. STUDY DESIGN: Descriptive cross-sectional analysis. SETTING & PARTICIPANTS: People with type 2 diabetes (n=826, 67.1 [IQR, 60.3-72.4] years, 64.9% male) participating in the Progression of Diabetic Complications (PREDICT) cohort study. EXPOSURE: Four spot urine collections for measurement of urinary albumin-creatinine ratio (UACR) within 4 weeks. OUTCOME: Variability of UACR. ANALYTICAL APPROACH: We characterized within-individual variability (coefficient of variation [CV], 95% limits of random variation, intraclass correlation coefficient), developed a calculator displaying probabilities that any observed difference between a pair of UACR values truly exceeded a 30% difference, and estimated the ranges of diagnostic uncertainty to inform a need for additional UACR collections to exclude or confirm albuminuria. Multiple linear regression examined factors influencing UACR variability. RESULTS: We observed high within-individual variability (CV 48.8%; 95% limits of random variation showed a repeated UACR to be as high/low as 3.78/0.26 times the first). If a single-collection UACR increased from 2 to 5mg/mmol, the probability that UACR actually increased by at least 30% was only 50%, rising to 97% when 2 collections were obtained at each time point. The ranges of diagnostic uncertainty were 2.0-4.0mg/mmol after an initial UACR test, narrowing to 2.4-3.2 and 2.7-2.9mg/mmol for the mean of 2 and 3 collections, respectively. Some factors correlated with higher (female sex; moderately increased albuminuria) or lower (reduced estimated glomerular filtration rate and sodium-glucose cotransporter 2 inhibitor/angiotensin-converting enzyme inhibitor/angiotensin receptor blocker treatment) within-individual UACR variability. LIMITATIONS: Reliance on the mean of 4 UACR collections as the reference standard for albuminuria. CONCLUSIONS: UACR demonstrates a high degree of within-individual variability among individuals with type 2 diabetes. Multiple urine collections for UACR may improve capacity to monitor changes over time in clinical and research settings but may not be necessary for the diagnosis of albuminuria. PLAIN-LANGUAGE SUMMARY: Albuminuria (albumin in urine) is a diagnostic and prognostic marker of diabetic chronic kidney disease. However, albuminuria can vary within an individual from day to day. We compared 4 random spot urinary albumin-creatinine ratio (UACR) samples from 826 participants. We found that a second UACR collection may be as small as a fourth or as large as almost 4 times the first sample's UACR level. This high degree of variability presents a challenge to our ability to interpret changes in albuminuria. Multiple collections have been suggested as a solution. We have constructed tools that may aid clinicians in deciding how many urine collections are required to monitor and diagnose albuminuria. Multiple urine collections may be required for individual monitoring but not necessarily for diagnosis.