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Heart failure with preserved ejection fraction (HFpEF) has become as a major public health problem worldwide, with increasing prevalence due to the aging of the population and the epidemic in obesity, hypertension and diabetes mellitus. HFpEF is a syndrome defined by the presence of clinical signs and/or symptoms of left heart failure, diastolic dysfunction leading to increased left ventricular (LV) filling pressure, LV hypertrophy and elevated blood levels of natriuretic peptides, associated with a preserved LV ejection fraction (>50%). HFpEF accounts for about half of heart failure cases and frequently leads to pulmonary hypertension (PH) and right ventricular (RV) failure, both known to increase morbidity-mortality in these patients. The presence of renal dysfunction is also frequently described in these patients and associated with a poor prognosis. Despite recent findings showing beneficial effects of gliflozins inhibitors of the sodium/glucose co-transporter (SGLT-2) in patients with HFpEF, no curative therapeutic strategy has shown beneficial effects on mortality in these patients, making this issue an urgent need in cardiology. The lack of preclinical experimental models recapitulating the complex pathophysiology of HFpEF as observed in patients represents a real obstacle to therapeutic innovation. Moreover, the mechanisms underlying the pathogenesis of HFpEF, as well as PH, RV dysfunction and renal failure associated with HFpEF, remain largely unknown. In this context, the aim of the present work was to develop a model of HFpEF associated with multiple comorbidities, by subjecting a strain of rats prone to develop obesity (obesity-prone rats or OP rats) to a high-fat diet and to characterize the development of HFpEF over time (after 4 and 12 months on specific dieting) (1) to study the pathogenesis of PH and RV-pulmonary artery (un)coupling (2), as well as renal function (3) in these rats, by comparing them to control rats (obesity-resistant rats on stand, Doctorat en Sciences biomédicales et pharmaceutiques (Médecine), info:eu-repo/semantics/nonPublished

High-throughput omics technologies have generated a wealth of large protein, gene, and transcript datasets that have exacerbated the need for new methods to analyse and compare big datasets. Rank–rank hypergeometric overlap is an important threshold-free method to combine and visualize two ranked lists of P -values or fold-changes, usually from differential gene expression analyses. Here, we introduce a new rank–rank hypergeometric overlap-based method aimed at gene level and alternative splicing analyses at transcript or exon level, hitherto unreachable as transcript numbers are an order of magnitude larger than gene numbers. We tested the tool on synthetic and real datasets at gene and transcript levels to detect correlation and anticorrelation patterns and found it to be fast and accurate, even on very large datasets thanks to an evolutionary algorithm-based minimal P -value search. The tool comes with a ready-to-use permutation scheme allowing the computation of adjusted P -values at low time cost. The package compatibility mode is a drop-in replacement to previous packages. RedRibbon holds the promise to accurately extricate detailed information from large comparative analyses., SCOPUS: ar.j, info:eu-repo/semantics/published

Introduction Most of the disease-associated single nucleotide polymorphisms (SNPs) lie in non- coding regions of the human genome. Many of these variants have been predicted to impact the expression and function of long non-coding RNAs (lncRNA), but the contribution of these molecules to the development of complex diseases remains to be clarified. Methods Here, we performed a genetic association study between a SNP located in a lncRNA known as LncTGM2 and the risk of developing type 2 diabetes (T2D), and analyzed its implication in disease pathogenesis at pancreatic beta cell level. Genetic association study was performed on human samples linking the rs2076380 polymorphism with T2D and glycemic traits. The pancreatic beta cell line EndoC-bH1 was employed for functional studies based on LncTGM2 silencing and overexpression experiments. Human pancreatic islets were used for eQTL analysis. Results We have identified a genetic association between LncTGM2 and T2D risk. Functional characterization of the LncTGM2 revealed its implication in the transcriptional regulation of TGM2, coding for a transglutaminase. The T2Dassociated risk allele in LncTGM2 disrupts the secondary structure of this lncRNA, affecting its stability and the expression of TGM2 in pancreatic beta cells. Diminished LncTGM2 in human beta cells impairs glucose-stimulated insulin release. Conclusions These findings provide novel information on the molecular mechanisms by which T2D-associated SNPs in lncRNAs may contribute to disease, paving the way for the development of new therapies based on the modulation of lncRNAs., SCOPUS: ar.j, info:eu-repo/semantics/published

The prevalence of type 2 diabetes is increasing worldwide, and nearly 540 million people are already affected. This confers a significant burden on human health. The onset of type 2 diabetes is associated with genetic predisposition and environmental/lifestyle risk factors. Among the latter, a sedentary lifestyle and hypercaloric/ quality diets are crucial drivers of type 2 diabetes development. Type 2 diabetes is usually characterized by insulin resistance, in which the beta cells are exposed to an increased demand to secrete insulin. This increased demand causes stress on the beta cells and leads to compensation mechanisms in an attempt to maintain normal glucose levels. However, if these mechanisms fail, beta cell dysfunction will ultimately result in the onset of type 2 diabetes. This progressive beta cell failure leaves molecular footprints that account for the pathology of type 2 diabetes. Thus, I investigated the gene signatures of human islets from type 2 diabetes donors, from non-diabetic human islets upon exposure to metabolic stress (i.e. lipo- and/or glucolipotoxicity), and from human islets from type 2 diabetes patients manifesting functional recovery after culture in a non-diabetic milieu.Gene signatures related to augmented inflammatory responses and depressed beta cell function were identified in type 2 diabetes islets, in comparison with non-diabetic controls. These results were confirmed by comparing the global transcriptomes of type 2 diabetes with other inflammatory diseases, such as type 1 diabetes, Alzheimer’s disease and multiple sclerosis. Additionally, gene signatures of ER stress and inflammatory signaling were also observed in human islets exposed to lipo- and/or gluocolipotoxic conditions. Of particular interest, the ER function (i.e. protein folding and sorting) and mitochondrial function (i.e. TCA cycle, oxidative phosphorylation)-related genes are severely perturbed with opposite direction between type 2 diabetes islets and in vitro ex, La prévalence du diabète de type 2 augmente dans le monde entier et près de 540 millions de personnes en sont déjà atteintes. Cela représente un fardeau important pour la santé humaine. L'apparition du diabète de type 2 est associée à une prédisposition génétique et à des facteurs de risque liés à l'environnement et au mode de vie. Parmi ces derniers, un mode de vie sédentaire et une alimentation hypercalorique/de qualité sont des facteurs cruciaux du développement du diabète de type 2. Le diabète de type 2 est généralement caractérisé par une résistance à l'insuline, dans laquelle les cellules bêta sont exposées à une demande accrue de sécrétion d'insuline. Cette demande accrue provoque un stress sur les cellules bêta et conduit à des mécanismes de compensation pour tenter de maintenir des niveaux de glucose normaux. Toutefois, si ces mécanismes échouent, le dysfonctionnement des cellules bêta entraînera finalement l'apparition d'un diabète de type 2. Cette défaillance progressive des cellules bêta laisse des empreintes moléculaires qui expliquent la pathologie du diabète de type 2. J'ai donc étudié les signatures génétiques d'îlots humains provenant de donneurs atteints de diabète de type 2, d'îlots humains non diabétiques exposés à un stress métabolique (c'est-à-dire à une lipo- et/ou glucolipotoxicité) et d'îlots humains provenant de patients atteints de diabète de type 2 et manifestant une récupération fonctionnelle après culture dans un milieu non diabétique.Des signatures génétiques liées à des réponses inflammatoires accrues et à une fonction déprimée des cellules bêta ont été identifiées dans les îlots de patients atteints de diabète de type 2, en comparaison avec des témoins non diabétiques. Ces résultats ont été confirmés par la comparaison des transcriptomes globaux du diabète de type 2 avec ceux d'autres maladies inflammatoires, telles que le diabète de type 1, la maladie d'Alzheimer et la sclérose en plaques. En outre, des signatures génétiques du stre, Doctorat en Sciences biomédicales et pharmaceutiques (Médecine), info:eu-repo/semantics/nonPublished

Aims/hypothesis There is a growing need for markers that could help indicate the decline in beta cell function and recognise the need and efficacy of intervention in type 1 diabetes. Measurements of suitably selected serum markers could potentially provide a non-invasive and easily applicable solution to this challenge. Accordingly, we evaluated a broad panel of proteins previously associated with type 1 diabetes in serum from newly diagnosed individuals during the first year from diagnosis. To uncover associations with beta cell function, comparisons were made between these targeted proteomics measurements and changes in fasting C-peptide levels. To further distinguish proteins linked with the disease status, comparisons were made with measurements of the protein targets in age- and sex-matched autoantibody-negative unaffected family members (UFMs). Methods Selected reaction monitoring (SRM) mass spectrometry analyses of serum, targeting 85 type 1 diabetes-associated proteins, were made. Sera from individuals diagnosed under 18 years ( n =86) were drawn within 6 weeks of diagnosis and at 3, 6 and 12 months afterwards (288 samples in total). The SRM data were compared with fasting C-peptide/glucose data, which was interpreted as a measure of beta cell function. The protein data were further compared with cross-sectional SRM measurements from UFMs ( n =194). Results Eleven proteins had statistically significant associations with fasting C-peptide/glucose. Of these, apolipoprotein L1 and glutathione peroxidase 3 (GPX3) displayed the strongest positive and inverse associations, respectively. Changes in GPX3 levels during the first year after diagnosis indicated future fasting C-peptide/glucose levels. In addition, differences in the levels of 13 proteins were observed between the individuals with type 1 diabetes and the matched UFMs. These included GPX3, transthyretin, prothrombin, apolipoprotein C1 and members of the IGF family. Conclusions/interpretation The, Miriam Cnop appears as an author as part of the INNODIA Consortium, info:eu-repo/semantics/published

Cellular identity during development is under the control of transcription factors that form gene regulatory networks. However, the transcription factors and gene regulatory networks underlying cellular identity in the human adult pancreas remain largely unexplored. Here, we integrate multiple single-cell RNA-sequencing datasets of the human adult pancreas, totaling 7393 cells, and comprehensively reconstruct gene regulatory networks. We show that a network of 142 transcription factors forms distinct regulatory modules that characterize pancreatic cell types. We present evidence that our approach identifies regulators of cell identity and cell states in the human adult pancreas. We predict that HEYL, BHLHE41 and JUND are active in acinar, beta and alpha cells, respectively, and show that these proteins are present in the human adult pancreas as well as in human induced pluripotent stem cell (hiPSC)-derived islet cells. Using single-cell transcriptomics, we found that JUND represses beta cell genes in hiPSC-alpha cells. BHLHE41 depletion induced apoptosis in primary pancreatic islets. The comprehensive gene regulatory network atlas can be explored interactively online. We anticipate our analysis to be the starting point for a more sophisticated dissection of how transcription factors regulate cell identity and cell states in the human adult pancreas., Miriam Cnop and Vincent Pasque share last and corresponding authorship, SCOPUS: ar.j, info:eu-repo/semantics/published

Type 1 diabetes is a complex heterogenous autoimmune disease without therapeutic interventions available to prevent or reverse the disease. This study aimed to identify transcriptional changes associated with the disease progression in patients with recent-onset type 1 diabetes., 0, Miriam Cnop is in the author list as part of the INNODIA Consortium, info:eu-repo/semantics/published

info:eu-repo/semantics/published

IntroductionMost of the disease-associated single nucleotide polymorphisms (SNPs) lie in non- coding regions of the human genome. Many of these variants have been predicted to impact the expression and function of long non-coding RNAs (lncRNA), but the contribution of these molecules to the development of complex diseases remains to be clarified. MethodsHere, we performed a genetic association study between a SNP located in a lncRNA known as LncTGM2 and the risk of developing type 2 diabetes (T2D), and analyzed its implication in disease pathogenesis at pancreatic beta cell level. Genetic association study was performed on human samples linking the rs2076380 polymorphism with T2D and glycemic traits. The pancreatic beta cell line EndoC-bH1 was employed for functional studies based on LncTGM2 silencing and overexpression experiments. Human pancreatic islets were used for eQTL analysis. ResultsWe have identified a genetic association between LncTGM2 and T2D risk. Functional characterization of the LncTGM2 revealed its implication in the transcriptional regulation of TGM2, coding for a transglutaminase. The T2Dassociated risk allele in LncTGM2 disrupts the secondary structure of this lncRNA, affecting its stability and the expression of TGM2 in pancreatic beta cells. Diminished LncTGM2 in human beta cells impairs glucose-stimulated insulin release. ConclusionsThese findings provide novel information on the molecular mechanisms by which T2D-associated SNPs in lncRNAs may contribute to disease, paving the way for the development of new therapies based on the modulation of lncRNAs.