Apolipoprotein L genes are novel mediators of inflammation in beta cells.

AIMS/HYPOTHESIS: Inflammation induces beta cell dysfunction and demise but underlying molecular mechanisms remain unclear. The apolipoprotein L (APOL) family of genes has been associated with innate immunity and apoptosis in non-pancreatic cell types, but also with metabolic syndrome and type 2 diabetes mellitus. Here, we hypothesised that APOL genes play a role in inflammation-induced beta cell damage. METHODS: We used single-cell transcriptomics datasets of primary human pancreatic islet cells to study the expression of APOL genes upon specific stress conditions. Validation of the findings was carried out in EndoC-ßH1 cells and primary human islets. Finally, we performed loss- and gain-of-function experiments to investigate the role of APOL genes in beta cells. RESULTS: APOL genes are expressed in primary human beta cells and APOL1, 2 and 6 are strongly upregulated upon inflammation via the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway. APOL1 overexpression increases endoplasmic reticulum stress while APOL1 knockdown prevents cytokine-induced beta cell death and interferon-associated response. Furthermore, we found that APOL genes are upregulated in beta cells from donors with type 2 diabetes compared with donors without diabetes mellitus. CONCLUSIONS/INTERPRETATION: APOLs are novel regulators of islet inflammation and may contribute to beta cell damage during the development of diabetes. DATA AVAILABILITY: scRNAseq data generated by our laboratory and used in this study are available in the Gene Expression Omnibus (GEO; www.ncbi.nlm.nih.gov/geo/ ), accession number GSE218316.

Comparison of an oral mixed meal plus arginine and intravenous glucose, GLP-1 plus arginine to unmask residual islet function in longstanding type 1 diabetes.

Residual beta cells are present in most patients with longstanding type 1 diabetes but it is unknown whether these beta cells react normally to different stimuli. Moreover a defect in proinsulin conversion and abnormal alpha cell response are also part of the islet dysfunction. A three-phase [euglycemia, hyperglycemia, and hyperglycemia + glucagon-like peptide 1 (GLP-1)] clamp was performed in patients with longstanding type 1 diabetes. Intravenous arginine boluses were administered at the end of each phase. On another day, a mixed meal stimulation test with a subsequent intravenous arginine bolus was performed. C-peptide was detectable in a subgroup of subjects at baseline (2/15) or only after stimulation (3/15). When detectable, C-peptide increased 2.9-fold [95% CI: 1.2-7.1] during the hyperglycemia phase and 14.1-fold [95% CI: 3.1-65.2] during the hyperglycemia + GLP-1 phase, and 22.3-fold [95% CI: 5.6-89.1] during hyperglycemia + GLP-1 + arginine phase when compared with baseline. The same subset of patients with a C-peptide response were identified during the mixed meal stimulation test as during the clamp. There was an inhibition of glucagon secretion (0.72-fold, [95% CI: 0.63-0.84]) during the glucose clamp irrespective of the presence of detectable beta cell function. Proinsulin was only present in a subset of subjects with detectable C-peptide (3/15) and proinsulin mimicked the C-peptide response to the different stimuli when detectable. Residual beta cells in longstanding type 1 diabetes respond adequately to different stimuli and could be of clinical benefit.NEW & NOTEWORTHY If beta cell function is detectable, the beta cells react relatively normal to the different stimuli except for the first phase response to intravenous glucose. An oral mixed meal followed by an intravenous arginine bolus can identify residual beta cell function/mass as well as the more commonly used glucose potentiated arginine-induced insulin secretion during a hyperglycemic clamp.

Impact of a Public Health Emergency on Behavior, Stress, Anxiety and Glycemic Control in Patients With Pancreas or Islet Transplantation for Type 1 Diabetes.

A public health emergency such as the COVID-19 pandemic has behavioral, mental and physical implications in patients with type 1 diabetes (T1D). To what extent the presence of a transplant further increases this burden is not known. Therefore, we compared T1D patients with an islet or pancreas transplant (ß-cell Tx; n = 51) to control T1D patients (n = 272). Fear of coronavirus infection was higher in those with ß-cell Tx than without (Visual Analogue Scale 5.0 (3.0-7.0) vs. 3.0 (2.0-5.0), p = 0.004) and social isolation behavior was more stringent (45.8% vs. 14.0% reported not leaving the house, p < 0.001). A previous ß-cell Tx was the most important predictor of at-home isolation. Glycemic control worsened in patients with ß-cell Tx, but improved in control patients (ΔHbA1c +1.67 ± 8.74 vs. -1.72 ± 6.15 mmol/mol, p = 0.006; ΔTime-In-Range during continuous glucose monitoring -4.5% (-6.0%-1.5%) vs. +3.0% (-2.0%-6.0%), p = 0.038). Fewer patients with ß-cell Tx reported easier glycemic control during lockdown (10.4% vs. 22.6%, p = 0.015). All T1D patients, regardless of transplantation status, experienced stress (33.4%), anxiety (27.9%), decreased physical activity (42.0%), weight gain (40.5%), and increased insulin requirements (29.7%). In conclusion, T1D patients with ß-cell Tx are increasingly affected by a viral pandemic lockdown with higher fear of infection, more stringent social isolation behavior and deterioration of glycemic control. This trial has been registered in the clinicaltrials.gov registry under identifying number NCT05977205 (URL: https://clinicaltrials.gov/study/NCT05977205).

Pancreatic ß-Cell Identity Change through the Lens of Single-Cell Omics Research.

The main hallmark in the development of both type 1 and type 2 diabetes is a decline in functional ß-cell mass. This decline is predominantly attributed to ß-cell death, although recent findings suggest that the loss of ß-cell identity may also contribute to ß-cell dysfunction. This phenomenon is characterized by a reduced expression of key markers associated with ß-cell identity. This review delves into the insights gained from single-cell omics research specifically focused on ß-cell identity. It highlights how single-cell omics based studies have uncovered an unexpected level of heterogeneity among ß-cells and have facilitated the identification of distinct ß-cell subpopulations through the discovery of cell surface markers, transcriptional regulators, the upregulation of stress-related genes, and alterations in chromatin activity. Furthermore, specific subsets of ß-cells have been identified in diabetes, such as displaying an immature, dedifferentiated gene signature, expressing significantly lower insulin mRNA levels, and expressing increased ß-cell precursor markers. Additionally, single-cell omics has increased insight into the detrimental effects of diabetes-associated conditions, including endoplasmic reticulum stress, oxidative stress, and inflammation, on ß-cell identity. Lastly, this review outlines the factors that may influence the identification of ß-cell subpopulations when designing and performing a single-cell omics experiment.

Patient-clinician collaboration in making care fit: A qualitative analysis of clinical consultations in diabetes care.

OBJECTIVE: To confirm described dimensions of making care fit and explore how patients and clinicians collaborate to make care fit in clinical practice. METHODS: As part of an ongoing study, we audiotaped and transcribed patient-clinician consultations in diabetes care. We purposively selected consultations based on participants' demographical, biomedical and biographical characteristics. We analysed transcripts using reflexive thematic analysis. We combined a deductive and inductive approach, using the pre-described dimensions of making care fit and adding new (sub-)dimensions when pertinent. RESULTS: We analysed 24 clinical consultations. Our data confirmed eight previously described dimensions and provided new sub-dimensions of making care fit with examples from clinical practice (problematic situation, influence of devices, sense of options, shared agenda setting, clinician context, adapting to changing organization of care, and possibility to reconsider). CONCLUSION: Our study confirmed, specified and enriched the conceptualization of making care fit through practice examples. We observed patient-clinician collaboration in exploration of patients' context, and by responsively changing, adapting or maintaining care plans. PRACTICE IMPLICATIONS: Our findings support clinicians and researchers with insights in important aspects of patient-clinician collaboration. Ultimately, this would lead to optimal design of care plans that fit well in each patient life.

Sleep duration and lipid metabolism in patients with diabetes mellitus: from the POWER2DM study.

This study assesses the association between sleep duration and plasma lipid profiles in people with diabetes mellitus (DM). Sleep duration data were obtained in 91 patients from the POWER2DM study (NCT03588104). The patients were divided in tertiles, based on their sleep duration, and blood samples were obtained at the beginning and after 9 months. Significant differences were found, specifically, patients in Tertile 3 (≥ 7.51 h) showed lower plasma levels of high-density lipoprotein cholesterol HDL-c (p < 0.05), apolipoprotein A1 (apo-A1; p < 0.05) and low HDL-c/apo-A1 ratio (p < 0.05). This study shows that sleep duration is associated with plasma lipid profiles in people with DM.