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Abstract Insulin secretion from pancreatic β cells is regulated by multiple stimuli, including nutrients, hormones, neuronal inputs, and local signalling. Amino acids modulate insulin secretion via amino acid transporters expressed on β cells. The granin protein VGF has dual roles in β cells: regulating secretory granule formation and functioning as a multiple peptide precursor. A VGF-derived peptide, neuroendocrine regulatory peptide-4 (NERP-4), increases Ca2+ influx in the pancreata of transgenic mice expressing apoaequorin, a Ca2+-induced bioluminescent protein complex. NERP-4 enhances glucose-stimulated insulin secretion from isolated human and mouse islets and β-cell–derived MIN6-K8 cells. NERP-4 administration reverses the impairment of β-cell maintenance and function in db/db mice by enhancing mitochondrial function and reducing metabolic stress. NERP-4 acts on sodium-coupled neutral amino acid transporter 2 (SNAT2), thereby increasing glutamine, alanine, and proline uptake into β cells and stimulating insulin secretion. SNAT2 deletion and inhibition abolish the protective effects of NERP-4 on β-cell maintenance. These findings demonstrate a novel autocrine mechanism of β-cell maintenance and function that is mediated by the peptide–amino acid transporter axis.

Summary: Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning β cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and β cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human β cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in β cells to maintain appropriate insulin release.

Abstract Background Prophylactic central neck dissection (pCND) remains controversial during the initial surgery for preoperative and intraoperative node‐negative (cN0) papillary thyroid carcinoma (PTC). Methods Patients undergoing thyroidectomy with or without pCND (Nx) for PTC in nine French surgical departments, registered in the EUROCRINE® national data in France between January 2015 and June 2021, were included in a cohort study. Demographic and clinicopathological characteristics, complications, and recurrence rates were compared using multivariate regression analysis. Results A total of 1905 patients with cN0 PTC were enrolled, including 1534 who had undergone pCND and 371 who hadn't (Nx). Of these, 1546 (81.2%) were female, and the median age was 49 years (range: 15–89 years). Patients who had undergone pCND were more likely to have multifocal tumors (n = 524 [34.2%] vs. n = 68 [18.3%], p .2). After adjusting for covariates (age, sex, multifocality, and pathological T stage) in a multivariable Cox PH model, the performance of lymph node dissection (pCND vs. no‐pCND) was not associated with PTC recurrence (p = .2). Conclusion pCND in PTC does not reduce recurrence and is associated with a two‐fold increase in the incidence of transient hypoparathyroidism. These data should be considered while issuing further guidelines regarding the treatment of patients with cN0 PTC.

Abstract We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

Abstract Background Non-coding genetic variants that influence gene transcription in pancreatic islets play a major role in the susceptibility to type 2 diabetes (T2D), and likely also contribute to type 1 diabetes (T1D) risk. For many loci, however, the mechanisms through which non-coding variants influence diabetes susceptibility are unknown. Results We examine splicing QTLs (sQTLs) in pancreatic islets from 399 human donors and observe that common genetic variation has a widespread influence on the splicing of genes with established roles in islet biology and diabetes. In parallel, we profile expression QTLs (eQTLs) and use transcriptome-wide association as well as genetic co-localization studies to assign islet sQTLs or eQTLs to T2D and T1D susceptibility signals, many of which lack candidate effector genes. This analysis reveals biologically plausible mechanisms, including the association of T2D with an sQTL that creates a nonsense isoform in ERO1B, a regulator of ER-stress and proinsulin biosynthesis. The expanded list of T2D risk effector genes reveals overrepresented pathways, including regulators of G-protein-mediated cAMP production. The analysis of sQTLs also reveals candidate effector genes for T1D susceptibility such as DCLRE1B, a senescence regulator, and lncRNA MEG3. Conclusions These data expose widespread effects of common genetic variants on RNA splicing in pancreatic islets. The results support a role for splicing variation in diabetes susceptibility, and offer a new set of genetic targets with potential therapeutic benefit.

BackgroundNon-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning.Methods and findingsWe utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (ConclusionsIn this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community.Trial registrationClinicalTrials.gov NCT03814915.

Objective: Aberrant hepatic glucose production contributes to the development of hyperglycemia and is a hallmark of type 2 diabetes. In a recent study, we showed that the transcription factor E2F1, a component of the cell cycle machinery, contributes to hepatic steatosis through the transcriptional regulation of key lipogenic enzymes. Here, we investigate if E2F1 contributes to hyperglycemia by regulating hepatic gluconeogenesis. Methods: We use different genetic models to investigate if E2F1 regulates gluconeogenesis in primary hepatocytes and in vivo. We study the impact of depleting E2F1 or inhibiting E2F1 activity in diabetic mouse models to evaluate if this transcription factor contributes to hyperglycemia during insulin resistance. We analyze E2F1 mRNA levels in the livers of human diabetic patients to assess the relevance of E2F1 in human pathophysiology. Results: Lack of E2F1 impaired gluconeogenesis in primary hepatocytes. Conversely, E2F1 overexpression increased glucose production in hepatocytes and in mice. Several genetic models showed that the canonical CDK4-RB1-E2F1 pathway is directly involved in this regulation. E2F1 mRNA levels were increased in the livers from human diabetic patients and correlated with the expression of the gluconeogenic enzyme Pck1. Genetic invalidation or pharmacological inhibition of E2F1 improved glucose homeostasis in diabetic mouse models. Conclusions: Our study unveils that the transcription factor E2F1 contributes to mammalian glucose homeostasis by directly controlling hepatic gluconeogenesis. Together with our previous finding that E2F1 promotes hepatic steatosis, the data presented here show that E2F1 contributes to both hyperlipidemia and hyperglycemia in diabetes, suggesting that specifically targeting E2F1 in the liver could be an interesting strategy for therapies against type 2 diabetes. Keywords: Gluconeogenesis, E2F1, Liver metabolism, Hyperglycemia, Diabetes, Cell cycle regulators

Reliable assessment of islet viability, mass, and purity must be met prior to transplanting an islet preparation into patients with type 1 diabetes. The standard method for quantifying human islet preparations is by direct microscopic analysis of dithizone-stained islet samples, but this technique may be susceptible to inter-/intraobserver variability, which may induce false positive/negative islet counts. Here we describe a simple, reliable, automated digital image analysis (ADIA) technique for accurately quantifying islets into total islet number, islet equivalent number (IEQ), and islet purity before islet transplantation. Islets were isolated and purified from n = 42 human pancreata according to the automated method of Ricordi et al. For each preparation, three islet samples were stained with dithizone and expressed as IEQ number. Islets were analyzed manually by microscopy or automatically quantified using Nikon's inverted Eclipse Ti microscope with built-in NIS-Elements Advanced Research (AR) software. The AIDA method significantly enhanced the number of islet preparations eligible for engraftment compared to the standard manual method ( p < 0.001). Comparisons of individual methods showed good correlations between mean values of IEQ number ( r 2 = 0.91) and total islet number ( r 2 = 0.88) and thus increased to r 2 = 0.93 when islet surface area was estimated comparatively with IEQ number. The ADIA method showed very high intraobserver reproducibility compared to the standard manual method ( p < 0.001). However, islet purity was routinely estimated as significantly higher with the manual method versus the ADIA method ( p < 0.001). The ADIA method also detected small islets between 10 and 50 μm in size. Automated digital image analysis utilizing the Nikon Instruments software is an unbiased, simple, and reliable teaching tool to comprehensively assess the individual size of each islet cell preparation prior to transplantation. Implementation of this technology to improve engraftment may help to advance the therapeutic efficacy and accessibility of islet transplantation across centers.

BackgroundIn-vitro expansion of functional beta cells from adult human islets is an attractive approach for generating an abundant source of cells for beta-cell replacement therapy of diabetes. Using genetic cell-lineage tracing we have recently shown that beta cells cultured from adult human islets undergo rapid dedifferentiation and proliferate for up to 16 population doublings. These cells have raised interest as potential candidates for redifferentiation into functional insulin-producing cells. Previous work has associated dedifferentiation of cultured epithelial cells with epithelial-mesenchymal transition (EMT), and suggested that EMT generates cells with stem cell properties. Here we investigated the occurrence of EMT in these cultures and assessed their stem cell potential.Methodology/principal findingsUsing cell-lineage tracing we provide direct evidence for occurrence of EMT in cells originating from beta cells in cultures of adult human islet cells. These cells express multiple mesenchymal markers, as well as markers associated with mesenchymal stem cells (MSC). However, we do not find evidence for the ability of such cells, nor of cells in these cultures derived from a non-beta-cell origin, to significantly differentiate into mesodermal cell types.Conclusions/significanceThese findings constitute the first demonstration based on genetic lineage-tracing of EMT in cultured adult primary human cells, and show that EMT does not induce multipotency in cells derived from human beta cells.

Abstract Plasma growth differentiation factor-15 (GDF-15) levels increase with obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) but the underlying mechanism remains poorly defined. Using male mouse models of obesity and MASLD, and biopsies from carefully-characterized patients regarding obesity, type 2 diabetes (T2D) and MASLD status, we identify adipose tissue (AT) as the key source of GDF-15 at onset of obesity and T2D, followed by liver during the progression towards metabolic dysfunction-associated steatohepatitis (MASH). Obesity and T2D increase GDF15 expression in AT through the accumulation of macrophages, which are the main immune cells expressing GDF15. Inactivation of Gdf15 in macrophages reduces plasma GDF-15 concentrations and exacerbates obesity in mice. During MASH development, Gdf15 expression additionally increases in hepatocytes through stress-induced TFEB and DDIT3 signaling. Together, these results demonstrate a dual contribution of AT and liver to GDF-15 production in metabolic diseases and identify potential therapeutic targets to raise endogenous GDF-15 levels.

Abstract In patients with type 2 diabetes, pancreatic beta cells progressively degenerate and gradually lose their ability to produce insulin and regulate blood glucose. Beta cell dysfunction and loss is associated with an accumulation of aggregated forms of islet amyloid polypeptide (IAPP) consisting of soluble prefibrillar IAPP oligomers as well as insoluble IAPP fibrils in pancreatic islets. Here, we describe a human monoclonal antibody selectively targeting IAPP oligomers and neutralizing IAPP aggregate toxicity by preventing membrane disruption and apoptosis in vitro. Antibody treatment in male rats and mice transgenic for human IAPP, and human islet-engrafted mouse models of type 2 diabetes triggers clearance of IAPP oligomers resulting in beta cell protection and improved glucose control. These results provide new evidence for the pathological role of IAPP oligomers and suggest that antibody-mediated removal of IAPP oligomers could be a pharmaceutical strategy to support beta cell function in type 2 diabetes.

ObjectiveHelp public health decision-making requires a better understanding of the dynamics of obesity and type 2 diabetes and an assessement of different strategies to decrease their burdens.MethodsBased on 97,848 individual data, collected in the French Health, Health Care and Insurance Survey over 1998-2014, a Markov model was developed to describe the progression of being overweight to obesity, and the onset of type 2 diabetes. This model traces and predicts 2022-2027 burdens of obesity and type 2 diabetes, and lifetime risk of diabetes, according to different scenarios aiming at minimum to stabilize obesity at 5 years.ResultsEstimated risks of type 2 diabetes increase from 0.09% (normal weight) to 1.56% (obesity II-III). Compared to the before 1995 period, progression risks are estimated to have nearly doubled for obesity and tripled for type 2 diabetes. Consequently, over 2022-2027, the prevalence of obesity and type 2 diabetes will continue to increase from 17.3% to 18.2% and from 7.3% to 8.1%, respectively. Scenarios statibilizing obesity would require a 22%-decrease in the probability of move up (scenario 1) or a 33%-increase in the probability of move down (scenario 2) one BMI class. However, this stabilization will not affect the increase of diabetes prevalence whereas lifetime risk of diabetes would decrease (30.9% to 27.0%). Combining both scenarios would decrease obesity by 9.9%. Only the prevalence of obesity III shows early change able to predict the outcome of a strategy: for example, 6.7%-decrease at one year, 13.3%-decrease at two years with scenario 1 stabilizing obesity at 5 years.ConclusionsPrevalences of obesity and type 2 diabetes will still increase over the next 5 years. Stabilizing obesity may decrease lifetime risks of type 2 diabetes without affecting its short-term prevalence. Our study highlights that, to early assess the effectiveness of their program, public health policy makers should rely on the change in prevalence of obesity III.

Background & Aims: Liver homeostasis is ensured in part by time-of-day-dependent processes, many of them being paced by the molecular circadian clock. Liver functions are compromised in metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH), and clock disruption increases susceptibility to MASLD progression in rodent models. We therefore investigated whether the time-of-day-dependent transcriptome and metabolome are significantly altered in human steatotic and MASH livers. Methods: Liver biopsies, collected within an 8 h-window from a carefully phenotyped cohort of 290 patients and histologically diagnosed to be either normal, steatotic or MASH hepatic tissues, were analyzed by RNA sequencing and unbiased metabolomic approaches. Time-of-day-dependent gene expression patterns and metabolomes were identified and compared between histologically normal, steatotic and MASH livers. Results: Herein, we provide a first-of-its-kind report of a daytime-resolved human liver transcriptome-metabolome and associated alterations in MASLD. Transcriptomic analysis showed a robustness of core molecular clock components in steatotic and MASH livers. It also revealed stage-specific, time-of-day-dependent alterations of hundreds of transcripts involved in cell-to-cell communication, intracellular signaling and metabolism. Similarly, rhythmic amino acid and lipid metabolomes were affected in pathological livers. Both TNFα and PPARγ signaling were predicted as important contributors to altered rhythmicity. Conclusion: MASLD progression to MASH perturbs time-of-day-dependent processes in human livers, while the differential expression of core molecular clock components is maintained. Impact and implications: This work characterizes the rhythmic patterns of the transcriptome and metabolome in the human liver. Using a cohort of well-phenotyped patients (n = 290) for whom the time-of-day at biopsy collection was known, we show that time-of-day variations observed in histologically normal livers are gradually perturbed in liver steatosis and metabolic dysfunction-associated steatohepatitis. Importantly, these observations, albeit obtained across a restricted time window, provide further support for preclinical studies demonstrating alterations of rhythmic patterns in diseased livers. On a practical note, this study indicates the importance of considering time-of-day as a critical biological variable which may significantly affect data interpretation in animal and human studies of liver diseases.

In islet transplantation (ITx), primary graft function (PGF) or beta cell function measured early after last infusion is closely associated with long term clinical outcomes. We investigated the association between PGF and 5 year insulin independence rate in ITx and pancreas transplantation (PTx) recipients. This retrospective multicenter study included type 1 diabetes patients who underwent ITx in Lille and PTx in Nantes from 2000 to 2022. PGF was assessed using the validated Beta2-score and compared to normoglycemic control subjects. Subsequently, the 5 year insulin independence rates, as predicted by a validated PGF-based model, were compared to the actual rates observed in ITx and PTx patients. The study enrolled 39 ITx (23 ITA, 16 IAK), 209 PTx recipients (23 PTA, 14 PAK, 172 SPK), and 56 normoglycemic controls. Mean[SD] PGF was lower after ITx (ITA 22.3[5.2], IAK 24.8[6.4], than after PTx (PTA 38.9[15.3], PAK 36.8[9.0], SPK 38.7[10.5]), and lower than mean beta-cell function measured in normoglycemic control: 36.6[4.3]. The insulin independence rates observed at 5 years after PTA and PAK aligned with PGF predictions, and was higher after SPK. Our results indicate a similar relation between PGF and 5 year insulin independence in ITx and solitary PTx, shedding new light on long-term transplantation outcomes.

Summary: Background: Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develop a model using machine learning to provide individual preoperative prediction of 5-year weight loss trajectories after surgery. Methods: In this multinational retrospective observational study we enrolled adult participants (aged ≥18 years) from ten prospective cohorts (including ABOS [NCT01129297], BAREVAL [NCT02310178], the Swedish Obese Subjects study, and a large cohort from the Dutch Obesity Clinic [Nederlandse Obesitas Kliniek]) and two randomised trials (SleevePass [NCT00793143] and SM-BOSS [NCT00356213]) in Europe, the Americas, and Asia, with a 5 year follow-up after Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric band. Patients with a previous history of bariatric surgery or large delays between scheduled and actual visits were excluded. The training cohort comprised patients from two centres in France (ABOS and BAREVAL). The primary outcome was BMI at 5 years. A model was developed using least absolute shrinkage and selection operator to select variables and the classification and regression trees algorithm to build interpretable regression trees. The performances of the model were assessed through the median absolute deviation (MAD) and root mean squared error (RMSE) of BMI. Findings: 10 231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30 602 patient-years. Among participants in all 12 cohorts, 7701 (75·3%) were female, 2530 (24·7%) were male. Among 434 baseline attributes available in the training cohort, seven variables were selected: height, weight, intervention type, age, diabetes status, diabetes duration, and smoking status. At 5 years, across external testing cohorts the overall mean MAD BMI was 2·8 kg/m2 (95% CI 2·6–3·0) and mean RMSE BMI was 4·7 kg/m2 (4·4–5·0), and the mean difference between predicted and observed BMI was –0·3 kg/m2 (SD 4·7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery. Interpretation: We developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions. Funding: SOPHIA Innovative Medicines Initiative 2 Joint Undertaking, supported by the EU's Horizon 2020 research and innovation programme, the European Federation of Pharmaceutical Industries and Associations, Type 1 Diabetes Exchange, and the Juvenile Diabetes Research Foundation and Obesity Action Coalition; Métropole Européenne de Lille; Agence Nationale de la Recherche; Institut national de recherche en sciences et technologies du numérique through the Artificial Intelligence chair Apprenf; Université de Lille Nord Europe's I-SITE EXPAND as part of the Bandits For Health project; Laboratoire d’excellence European Genomic Institute for Diabetes; Soutien aux Travaux Interdisciplinaires, Multi-établissements et Exploratoires programme by Conseil Régional Hauts-de-France (volet partenarial phase 2, project PERSO-SURG).

Myofibroblasts contribute to the development of liver fibrosis. Here, the authors report that the transcription factor Basonuclin 2 (BNC2) integrates fibrogenic signals and drives myofibroblastic transcriptional activation in liver fibrosis.

Abstract Introduction Nowadays, there are no strong diabetic pig models, yet they are required for various types of diabetes research. Using cutting‐edge techniques, we attempted to develop a type 2 diabetic minipig model in this study by combining a partial pancreatectomy (Px) with an energetic overload administered either orally or parenterally. Methods Different groups of minipigs, including Göttingen‐like (GL, n = 17) and Ossabaw (O, n = 4), were developed. Prior to and following each intervention, metabolic assessments were conducted. First, the metabolic responses of the Göttingen‐like (n = 3) and Ossabaw (n = 4) strains to a 2‐month High‐Fat, High‐Sucrose diet (HFHSD) were compared. Then, other groups of GL minipigs were established: with a single Px (n = 10), a Px combined with a 2‐month HFHSD (n = 6), and long‐term intraportal glucose and lipid infusions that were either preceded by a Px (n = 4) or not (n = 4). Results After the 2‐month HFHSD, there was no discernible change between the GL and O minipigs. The pancreatectomized group in GL minipigs showed a significantly lower Acute Insulin Response (AIR) (18.3 ± 10.0 IU/mL after Px vs. 34.9 ± 13.7 IU/mL before, p

Background. Severe or repeated hypoglycemia events may favor memory complaints in type 1 diabetes (T1D). Pancreatic islet transplantation (IT) is an alternative option to exogenous insulin therapy in case of labile T1D, implying a maintenance immunosuppression regimen based on sirolimus or mycophenolate, associated with tacrolimus, that may also have neurological toxicity. The objective of this study was to compare a cognitive rating scale Mini-Mental State Examination (MMSE) between T1D patients with or without IT and to identify parameters influencing MMSE. Methods. This retrospective cross-sectional study compared MMSE and cognitive function tests between islet-transplanted T1D patients and nontransplanted T1D controls who were transplant candidates. Patients were excluded if they refused. Results. Forty-three T1D patients were included: 9 T1D patients before IT and 34 islet-transplanted patients (14 treated with mycophenolate and 20 treated with sirolimus). Neither MMSE score (P = 0.70) nor higher cognitive function differed between islet versus non–islet-transplanted patients, whatever the type of immunosuppression. In the whole population (N = 43), MMSE score was negatively correlated to glycated hemoglobin (r = –0.30; P = 0.048) and the time spent in hypoglycemia on the continuous glucose monitoring (r = –0.32; P = 0.041). MMSE score was not correlated to fasting C-peptide level, time spent in hyperglycemia, average blood glucose, time under immunosuppression, duration of diabetes, or beta-score (success score of IT). Conclusions. This first study evaluating cognitive disorders in islet-transplanted T1D patients argues for the importance of glucose balance on cognitive function rather than of immunosuppressive treatment, with a favorable effect of glucose balance improvement on MMSE score after IT.

Abstract Islet transplantation is a unique paradigm in organ transplantation, since multiple donors are required to achieve complete insulin-independence. Preformed or de novo Donor Specific Antibodies (DSA) may target one or several donor islets, which adds complexity to the analysis of their impact. Adult patients with type 1 diabetes transplanted with pancreatic islets between 2005 and 2018 were included in a single-center observational study. Thirty-two recipients with available sera tested by solid-phase assays for anti-HLA antibodies during their whole follow-up were analyzed. Twenty-five recipients were islet-transplantation-alone recipients, and 7 islet-after-kidney recipients. Seven recipients presented with DSA at any time during follow-up (two with preformed DSA only, one with preformed and de novo DSA, 4 with de novo DSA only). Only islet-transplantation-alone recipients presented with de novo DSA. Three clinical trajectories were identified according to: 1/the presence of preformed DSA, 2/early de novo DSA or 3/late de novo DSA. Only late de novo DSA were associated with unfavorable outcomes, depicted by a decrease of the β-score. Islet transplantation with preformed DSA, even with high MFI values, is associated with favorable outcomes in our experience. On the contrary, de novo DSA, and especially late de novo DSA, may be associated with allograft loss.

Summary: Metformin (MET) is the most prescribed antidiabetic drug, but its mechanisms of action remain elusive. Recent data point to the gut as MET’s primary target. Here, we explored the effect of MET on the gut glucose transport machinery. Using human enterocytes (Caco-2/TC7 cells) in vitro, we showed that MET transiently reduced the apical density of sodium-glucose transporter 1 (SGLT1) and decreased the absorption of glucose, without changes in the mRNA levels of the transporter. Administered 1 h before a glucose challenge in rats (Wistar, GK), C57BL6 mice and mice pigs, oral MET reduced the post-prandial glucose response (PGR). This effect was abrogated in SGLT1-KO mice. MET also reduced the luminal clearance of 2-(18F)-fluoro-2-deoxy-D-glucose after oral administration in rats. In conclusion, oral metformin transiently lowers post-prandial glucose response by reducing the apical expression of SGLT1 in enterocytes, which may contribute to the clinical effects of the drug.

Context: Recent guidelines have provided recommendations for the care of patients with chronic hypoparathyroidism. Very little is known about actual physicians’ practices or their adherence to such guidelines. Objective: To describe the physicians’ practice patterns and their compliance with international guidelines. Design: The cohort studies included were Épi-Hypo (118 physicians and 107 patients, from September 2016 to December 2019) and ePatients (110 patients, November 2019). Methods: Internet-based cohorts involving all settings at a nationwide level (France). Participants were (i) physicians treating patients with chronic hypoparathyroidism and patients with chronic hypoparathyroidism either participating in the (ii) Épi-Hypo study (Épi-Hypo 2019 patients), or (iii) Hypoparathyroidism France, the national representative association (ePatients).

Abstract Background Knowledge of age‐related DNA methylation changes in skeletal muscle is limited, yet this tissue is severely affected by ageing in humans. Methods We conducted a large‐scale epigenome‐wide association study meta‐analysis of age in human skeletal muscle from 10 studies (total n = 908 muscle methylomes from men and women aged 18–89 years old). We explored the genomic context of age‐related DNA methylation changes in chromatin states, CpG islands, and transcription factor binding sites and performed gene set enrichment analysis. We then integrated the DNA methylation data with known transcriptomic and proteomic age‐related changes in skeletal muscle. Finally, we updated our recently developed muscle epigenetic clock (https://bioconductor.org/packages/release/bioc/html/MEAT.html). Results We identified 6710 differentially methylated regions at a stringent false discovery rate

The purpose of this study was to evaluate the implementation of the European Calcified Tissue Society (ECTS) 2022 recommendations on the prevention and treatment of osteoporosis secondary to bariatric surgery. The ECTS 2022 recommendations were applied in a retrospective cohort of postmenopausal women and men aged 50 years and older who were undergoing or had already undergone bariatric surgery. Osteoporosis medication was indicated if any of the following criteria were met: (i) history of recent (within 2 years) fragility fracture after the age of 40 years, (ii) BMD T score ≤ −2 at any of the sites of measurement, and (iii) FRAX® ≥ 20% for major osteoporotic fractures and/or ≥3% for hip fractures. Of the 170 patients (144 women, mean age 59 (55 to 63) years) included between February 2019 and March 2022, 33 were eligible for osteoporosis medication based on the ECTS 2022 recommendations, i.e., a prevalence of 19.6% [CI95%: 13.9%; 26.5%]. Most patients met the BMD T score ≤ −2 criterion (n = 25/170, 14.7% [CI95%: 9.7%; 20.9%]) and/or the history of recent fragility fracture criterion (n = 12/170, 7.1% [CI95%: 3.7%; 12.0%]). In this study, a fifth of our population was found to be eligible for osteoporosis medication after the application of the ECTS 2022 recommendations.