A Targeted Multiomics Approach to Identify Biomarkers Associated with Rapid eGFR Decline in Type 1 Diabetes

Multi-omics analysis reveals drivers of loss of β-cell function after newly diagnosed autoimmune type 1 diabetes: An INNODIA multicenter study

AIMS

Heterogeneity in the rate of β-cell loss in newly diagnosed type 1 diabetes patients is poorly understood and creates a barrier to designing and interpreting disease-modifying clinical trials. Integrative analyses of baseline multi-omics data obtained after the diagnosis of type 1 diabetes may provide mechanistic insight into the diverse rates of disease progression after type 1 diabetes diagnosis.

METHODS

We collected samples in a pan-European consortium that enabled the concerted analysis of five different omics modalities in data from 97 newly diagnosed patients. In this study, we used Multi-Omics Factor Analysis to identify molecular signatures correlating with post-diagnosis decline in β-cell mass measured as fasting C-peptide.

RESULTS

Two molecular signatures were significantly correlated with fasting C-peptide levels. One signature showed a correlation to neutrophil degranulation, cytokine signalling, lymphoid and non-lymphoid cell interactions and G-protein coupled receptor signalling events that were inversely associated with a rapid decline in β-cell function. The second signature was related to translation and viral infection was inversely associated with change in β-cell function. In addition, the immunomics data revealed a Natural Killer cell signature associated with rapid β-cell decline.

CONCLUSIONS

Features that differ between individuals with slow and rapid decline in β-cell mass could be valuable in staging and prediction of the rate of disease progression and thus enable smarter (shorter and smaller) trial designs for disease modifying therapies as well as offering biomarkers of therapeutic effect.

Evaluation of changes in glycemic control and diabetic complications over time and factors associated with the progression of diabetic complications in Japanese patients with juvenile-onset type 1 diabetes mellitus

BACKGROUND

This study aimed to evaluate the changes in glycemic control and diabetic complications over time in Japanese patients with juvenile-onset type 1 diabetes mellitus and to clarify the factors associated with the progression of diabetic complications.

METHODS

We tracked 129 patients with type 1 diabetes mellitus (21.8 ± 4.1 years old [mean ± SD] with a diabetes duration of 12.6 ± 5.7 years) for up to 19 years and analyzed data on glycated hemoglobin (HbA1c) and indicators related to the severity of diabetic complications (estimated glomerular filtration rate [eGFR], urinary albumin excretion rate [UAE], carotid intima-media thickness [CIMT], and brachial-ankle pulse wave velocity [baPWV]) using linear mixed model and decision tree analysis.

RESULTS

Although the HbA1c and UAE levels improved over time, the eGFR, CIMT, and baPWV worsened. Decision tree analysis showed that HbA1c and the glycoalbumin/HbA1c ratio for eGFR; HbA1c and systolic blood pressure for UAE; low-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratio, glycoalbumin/HbA1c ratio, and body mass index (BMI) for CIMT; and HbA1c for baPWV were associated factors.

CONCLUSIONS

In this retrospective observational study, glycemic control and albuminuria improved; however, renal function and arteriosclerosis worsened over time. HbA1c levels, glycemic excursion, and blood pressure are associated with nephropathy progression. HbA1c levels, glycemic excursion, lipid levels, and BMI are associated with the progression of atherosclerosis.

Rate of Kidney Function Decline is Associated With Kidney and Heart Failure in Individuals With Type 1 Diabetes

Introduction

Diabetes is the most common cause of chronic kidney disease (CKD). Urinary albumin excretion rate (AER) and estimated glomerular filtration rate (eGFR) are commonly used to monitor the onset and progression of diabetic kidney disease (DKD). We studied if the preceding rate of kidney function decline, that is, the eGFR slope, is independently associated with incident clinical cardiorenal events.

Methods

This study included longitudinal data for 2498 Finnish individuals with type 1 diabetes (T1D). The eGFR slope was calculated from 5 years preceding the study visit. Data on kidney failure, coronary heart disease (CHD), stroke, 3-point major adverse cardiovascular events (MACE), heart failure, and death were obtained from national registries. The associations between the eGFR slope and incident events were assessed with multivariable competing risk models during the average follow-up of 9.2 years.

Results

The eGFR slopes were associated (P ≤ 0.001) with all outcomes when adjusted for age, sex, and HbA1c. However, eGFR slope remained associated only with the composite outcome of kidney failure or death when the albuminuria group and eGFR at the study visit were included in the model (P = 0.041). In addition, eGFR slope was independently associated with kidney failure in individuals without CKD (eGFR > 60 ml/min per 1.73 m2; P = 0.044), and with heart failure in those with CKD (P = 0.033). However, eGFR slope did not markedly improve the model C-index.

Conclusion

The eGFR slope was independently associated with kidney failure in those without CKD, and with heart failure in those with CKD. However, it is unlikely to have major relevance for clinical practice when the current eGFR and albuminuria status are known.

Precision Medicine and/or Biomarker Based Therapy in T2DM: Ready for Prime Time?

Approximately 30-40% of people with type 2 diabetes mellitus develop chronic kidney disease. This is characterised by elevated blood pressure, declining kidney function and enhanced cardiovascular morbidity and mortality. Increased albuminuria and decreasing estimated glomerular function has to be evaluated regularly to diagsnose kidney disease. New biomarkers may facilitate early diagnosis and provide infomation on undlying pathology thereby supporting early precision intervention for the optimal benefit. A number of biomarkers have been suggested but are not yet implemented in clinical practice. iI the future such bimarkers may pave the way for personalized treatment.

Therapeutic Role of Curcumin in Diabetes: An Analysis Based on Bioinformatic Findings

BACKGROUND

Diabetes is an increasingly prevalent global disease caused by the impairment in insulin production or insulin function. Diabetes in the long term causes both microvascular and macrovascular complications that may result in retinopathy, nephropathy, neuropathy, peripheral arterial disease, atherosclerotic cardiovascular disease, and cerebrovascular disease. Considerable effort has been expended looking at the numerous genes and pathways to explain the mechanisms leading to diabetes-related complications. Curcumin is a traditional medicine with several properties such as being antioxidant, anti-inflammatory, anti-cancer, and anti-microbial, which may have utility for treating diabetes complications. This study, based on the system biology approach, aimed to investigate the effect of curcumin on critical genes and pathways related to diabetes.

METHODS

We first searched interactions of curcumin in three different databases, including STITCH, TTD, and DGIdb. Subsequently, we investigated the critical curated protein targets for diabetes on the OMIM and DisGeNET databases. To find important clustering groups (MCODE) and critical hub genes in the network of diseases, we created a PPI network for all proteins obtained for diabetes with the aid of a string database and Cytoscape software. Next, we investigated the possible interactions of curcumin on diabetes-related genes using Venn diagrams. Furthermore, the impact of curcumin on the top scores of modular clusters was analysed. Finally, we conducted biological process and pathway enrichment analysis using Gene Ontology (GO) and KEGG based on the enrichR web server.

RESULTS

We acquired 417 genes associated with diabetes, and their constructed PPI network contained 298 nodes and 1651 edges. Next, the analysis of centralities in the PPI network indicated 15 genes with the highest centralities. Additionally, MCODE analysis identified three modular clusters, which highest score cluster (MCODE 1) comprises 19 nodes and 92 edges with 10.22 scores. Screening curcumin interactions in the databases identified 158 protein targets. A Venn diagram of genes related to diabetes and the protein targets of curcumin showed 35 shared proteins, which observed that curcumin could strongly interact with ten of the hub genes. Moreover, we demonstrated that curcumin has the highest interaction with MCODE1 among all MCODs. Several significant biological pathways in KEGG enrichment associated with 35 shared included the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, PI3K-Akt signaling pathway, TNF signaling, and JAK-STAT signaling pathway. The biological processes of GO analysis were involved with the cellular response to cytokine stimulus, the cytokine-mediated signaling pathway, positive regulation of intracellular signal transduction and cytokine production in the inflammatory response.

CONCLUSION

Curcumin targeted several important genes involved in diabetes, supporting the previous research suggesting that it may have utility as a therapeutic agent in diabetes.

Urinary Proteomics Identifies Cathepsin D as a Biomarker of Rapid eGFR Decline in Type 1 Diabetes

OBJECTIVE

Understanding mechanisms underlying rapid estimated glomerular filtration rate (eGFR) decline is important to predict and treat kidney disease in type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

We performed a case-control study nested within four T1D cohorts to identify urinary proteins associated with rapid eGFR decline. Case and control subjects were categorized based on eGFR decline ≥3 and <1 mL/min/1.73 m2/year, respectively. We used targeted liquid chromatography-tandem mass spectrometry to measure 38 peptides from 20 proteins implicated in diabetic kidney disease. Significant proteins were investigated in complementary human cohorts and in mouse proximal tubular epithelial cell cultures.

RESULTS

The cohort study included 1,270 participants followed a median 8 years. In the discovery set, only cathepsin D peptide and protein were significant on full adjustment for clinical and laboratory variables. In the validation set, associations of cathepsin D with eGFR decline were replicated in minimally adjusted models but lost significance with adjustment for albuminuria. In a meta-analysis with combination of discovery and validation sets, the odds ratio for the association of cathepsin D with rapid eGFR decline was 1.29 per SD (95% CI 1.07-1.55). In complementary human cohorts, urine cathepsin D was associated with tubulointerstitial injury and tubulointerstitial cathepsin D expression was associated with increased cortical interstitial fractional volume. In mouse proximal tubular epithelial cell cultures, advanced glycation end product-BSA increased cathepsin D activity and inflammatory and tubular injury markers, which were further increased with cathepsin D siRNA.

CONCLUSIONS

Urine cathepsin D is associated with rapid eGFR decline in T1D and reflects kidney tubulointerstitial injury.

Analysis of inflammatory cytokines and estimated glomerular filtration rate decline in Japanese patients with diabetic kidney disease: a pilot study

Background: It is important to identify additional prognostic factors for diabetic kidney disease. Materials & methods: Baseline levels of ten cytokines (APRIL/TNFSF13, BAFF/TNFSF13B, chitinase 3-like 1, LIGHT/TNFSF14, TWEAK/TNFSF12, gp130/sIL-6Rβ, sCD163, sIL-6Rα, sTNF-R1, sTNF-R2) were measured in two cohorts of diabetic patients. In one cohort (n = 777), 156 individuals were randomly sampled after stratification and their plasma samples were analyzed; in the other cohort (n = 69), serum samples were analyzed in all the individuals. The levels of cytokines between rapid (estimated glomerular filtration rate decline >5 ml/min/1.73 m²/year) and non-rapid decliners were compared. Results: Multivariate analysis demonstrated significantly high levels of LIGHT/TNFSF14, TWEAK/TNFSF12 and sTNF-R2 in rapid decliners. Conclusion: These three cytokines can be potential biomarkers for the progression of diabetic kidney disease.

Acylcarnitines: Can They Be Biomarkers of Diabetic Nephropathy?

Diabetic nephropathy (DN), one of the most serious microvascular complications of diabetes mellitus (DM), may progress to end-stage renal disease (ESRD). Current biochemical biomarkers, such as urinary albumin excretion rate (UAER), have limitations for early screening and monitoring of DN. Recent studies have identified some metabolites as candidate biomarkers for early detection of DN. In this review, we summarize the role of dysregulated acylcarnitines (AcylCNs) in DN pathophysiology. Lower abundance of short- and medium-chain AcylCNs and higher long-chain AcylCNs often occurred in DM with normal albuminuria and microalbuminuria, compared with advanced stages of DN. The increase of long-chain AcylCNs was supposed to be an adaptive compensation in fat acids (FAs) oxidation in the early stage of DN. Conversely, the decrease of long-chain AcylCNs was due to incomplete oxidation of FAs in advanced stage of DN. Thus, AcylCNs may serve as sensitive biomarkers in predicting the risk of DN.

Circulating Free Fatty Acid and Phospholipid Signature Predicts Early Rapid Kidney Function Decline in Patients With Type 1 Diabetes

OBJECTIVES

Patients with type 1 diabetes (T1D) exhibit modest lipid abnormalities as measured by traditional metrics. This study aimed to identify lipidomic predictors of rapid decline of kidney function in T1D.

RESEARCH DESIGN AND METHODS

In a case-control study, 817 patients with T1D from three large cohorts were randomly split into training and validation subsets. Case was defined as >3 mL/min/1.73 m² per year decline in estimated glomerular filtration rate (eGFR), while control was defined as <1 mL/min/1.73 m² per year decline over a minimum 4-year follow-up. Lipids were quantified in baseline serum samples using a targeted mass spectrometry lipidomic platform.

RESULTS

At individual lipids, free fatty acid (FFA)20:2 was directly and phosphatidylcholine (PC)16:0/22:6 was inversely and independently associated with rapid eGFR decline. When examined by lipid class, rapid eGFR decline was characterized by higher abundance of unsaturated FFAs, phosphatidylethanolamine (PE)-Ps, and PCs with an unsaturated acyl chain at the sn1 carbon, and by lower abundance of saturated FFAs, longer triacylglycerols, and PCs, PEs, PE-Ps, and PE-Os with an unsaturated acyl chain at the sn1 carbon at eGFR ≥90 mL/min/1.73 m². A multilipid panel consisting of unsaturated FFAs and saturated PE-Ps predicted rapid eGFR decline better than individual lipids (C-statistic, 0.71) and improved the C-statistic of the clinical model from 0.816 to 0.841 (P = 0.039). Observations were confirmed in the validation subset.

CONCLUSIONS

Distinct from previously reported predictors of GFR decline in type 2 diabetes, these findings suggest differential incorporation of FFAs at the sn1 carbon of the phospholipids' glycerol backbone as an independent predictor of rapid GFR decline in T1D.