Obesity-Related Kidney Disease: Current Understanding and Future Perspectives.

Obesity is a serious chronic disease and an independent risk factor for the new onset and progression of chronic kidney disease (CKD). CKD prevalence is expected to increase, at least partly due to the continuous rise in the prevalence of obesity. The concept of obesity-related kidney disease (OKD) has been introduced to describe the still incompletely understood interplay between obesity, CKD, and other cardiometabolic conditions, including risk factors for OKD and cardiovascular disease, such as diabetes and hypertension. Current therapeutics target obesity and CKD individually. Non-pharmacological interventions play a major part, but the efficacy and clinical applicability of lifestyle changes and metabolic surgery remain debatable, because the strategies do not benefit everyone, and it remains questionable whether lifestyle changes can be sustained in the long term. Pharmacological interventions, such as sodium-glucose co-transporter 2 inhibitors and the non-steroidal mineralocorticoid receptor antagonist finerenone, provide kidney protection but have limited or no impact on body weight. Medicines based on glucagon-like peptide-1 (GLP-1) induce clinically relevant weight loss and may also offer kidney benefits. An urgent medical need remains for investigations to better understand the intertwined pathophysiologies in OKD, paving the way for the best possible therapeutic strategies in this increasingly prevalent disease complex.

Liraglutide protects ß-cells in novel human islet spheroid models of type 1 diabetes.

To enable accurate, high-throughput and longer-term studies of the immunopathogenesis of type 1 diabetes (T1D), we established three in-vitro islet-immune injury models by culturing spheroids derived from primary human islets with proinflammatory cytokines, activated peripheral blood mononuclear cells or HLA-A2-restricted preproinsulin-specific cytotoxic T lymphocytes. In all models, ß-cell function declined as manifested by increased basal and decreased glucose-stimulated insulin release (GSIS), and decreased intracellular insulin content. Additional hallmarks of T1D progression such as loss of the first-phase insulin response (FFIR), increased proinsulin-to-insulin ratios, HLA-class I expression, and inflammatory cytokine release were also observed. Using these models, we show that liraglutide, a glucagon-like peptide 1 receptor agonist, prevented loss of GSIS under T1D-relevant stress, by preserving the FFIR and decreasing immune cell infiltration and cytokine secretion. Our results corroborate that liraglutide mediates an anti-inflammatory effect that aids in protecting ß-cells from the immune-mediated attack that leads to T1D.

Efficacy and safety of liraglutide in type 1 diabetes by baseline characteristics in the ADJUNCT ONE and ADJUNCT TWO randomized controlled trials.

AIM: To evaluate 26 weeks of liraglutide treatment in type 1 diabetes (T1D) by subgroups in the ADJUNCT ONE and ADJUNCT TWO trials. MATERIALS AND METHODS: ADJUNCT ONE and ADJUNCT TWO were randomized controlled phase 3 trials in 1398 and 835 participants with T1D treated with liraglutide (1.8, 1.2, or 0.6 mg) or placebo (adjuncts to insulin). This post hoc analysis evaluated treatment effects by subgroups: HbA1c (< or ≥8.5%), body mass index (BMI; < or ≥27 kg/m2 ), and insulin regimen (basal bolus or continuous subcutaneous insulin infusion). RESULTS: In both trials at week 26, reductions in HbA1c, body weight, and daily insulin dose did not differ significantly (P > .05) by baseline HbA1c or BMI. Risk of clinically significant hypoglycaemia or hyperglycaemia with ketosis did not differ significantly (P > .05) by baseline HbA1c, BMI, or insulin regimen. At week 26 in ADJUNCT ONE, these risks did not differ (P > .05) between treatment groups. Placebo-adjusted reductions in HbA1c, body weight, and insulin dose (-0.30%-points, -5.0 kg, and -12%, respectively, with liraglutide 1.8 mg), were significant (P < .05), greater than at week 52, and similar to those in ADJUNCT TWO (-0.35%, -4.8 kg, and -10%, respectively, with liraglutide 1.8 mg). CONCLUSIONS: In ADJUNCT ONE and ADJUNCT TWO, the efficacy and glycaemic safety of liraglutide did not depend on subgroups, leaving residual beta-cell function as the only identified variable impacting the effect of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in T1D. These findings support a role for GLP-1 RAs as adjuncts to insulin in T1D, warranting further study.

Current and future therapies for type 1 diabetes.

In type 1 diabetes, insulin remains the mature therapeutic cornerstone; yet, the increasing number of individuals developing type 1 diabetes (predominantly children and adolescents) still face severe complications. Fortunately, our understanding of type 1 diabetes is continuously being refined, allowing for refocused development of novel prevention and management strategies. Hitherto, attempts based on immune suppression and modulation have been only partly successful in preventing the key pathophysiological feature in type 1 diabetes: the immune-mediated derangement or destruction of beta cells in the pancreatic islets of Langerhans, leading to low or absent insulin secretion and chronic hyperglycaemia. Evidence now warrants a focus on the beta cell itself and how to avoid its dysfunction, which is putatively caused by cytokine-driven inflammation and other stress factors, leading to low insulin-secretory capacity, autoantigen presentation and immune-mediated destruction. Correspondingly, beta cell rescue strategies are being pursued, which include antigen vaccination using, for example, oral insulin or peptides, as well as agents with suggested benefits on beta cell stress, such as verapamil and glucagon-like peptide-1 receptor agonists. Whilst autoimmune-focused prevention approaches are central in type 1 diabetes and will be a requirement in the advent of stem cell-based replacement therapies, managing the primarily cardiometabolic complications of established type 1 diabetes is equally essential. In this review, we outline selected recent and suggested future attempts to address the evolving profile of the person with type 1 diabetes.

Validation of distinct type 2 diabetes clusters and their association with diabetes complications in the DEVOTE, LEADER and SUSTAIN-6 cardiovascular outcomes trials.

AIMS: To validate the clusters of Swedish individuals with recent-onset diabetes at differential risk of complications, which were identified in a previous study, in three global populations with long-standing type 2 diabetes (T2D) who were at high cardiovascular risk, and to test for differences in the risk of major diabetes complications and survival endpoints. MATERIALS AND METHODS: We assigned participants from recent global outcomes trials (DEVOTE [n = 7637], LEADER [n = 9340] and SUSTAIN-6 [n = 3297]) to the previously defined clusters according to age at diabetes diagnosis, baseline glycated haemoglobin (HbA1c) and body mass index (BMI). Outcomes were assessed using Kaplan-Meier analysis and log-rank tests. RESULTS: The T2D clusters were consistently replicated across the three trial cohorts. The risk of major adverse cardiovascular events and cardiovascular death differed significantly, in all trials, across clusters over a median follow-up duration of 2.0, 3.8 and 2.1 years, respectively, and was highest for the cluster of participants with high HbA1c and low BMI (P < 0.05 in DEVOTE and LEADER). In LEADER and SUSTAIN-6, the risk of nephropathy differed across clusters (P < 0.0001 and P = 0.003, respectively). The risk of severe hypoglycaemia differed in DEVOTE (P = 0.006). CONCLUSIONS: Previously identified clusters can be replicated in three geographically diverse cohorts of long-standing T2D and are associated with cluster-specific risk profiles for additional clinical and survival outcomes, providing further validation of the clustering methodology. The external validity and stability of clusters across cohorts provides a premise for future work to optimize the clustering approach to yield T2D subgroups with maximum predictive validity who may benefit from subtype-specific treatment paradigms.