Publicaciones científicas

Se han encontrado 27 publicaciones con los criterios indicados.
Colli ML, Ramos-Rodríguez M, Nakayasu ES, Alvelos MI, Lopes M, Hill JLE, Turatsinze JV, Coomans de Brachène A, Russell MA, Raurell-Vila H, Castela A, Juan-Mateu J, Webb-Robertson BM, Krogvold L, Dahl-Jorgensen K, Marselli L, Marchetti P, Richardson SJ, Morgan NG, Metz TO, Pasquali L, Eizirik DL

An integrated multi-omics approach identifies the landscape of interferon-α-mediated responses of human pancreatic beta cells.

Nat Commun 22 May 2020, 11 (1) 2584. Epub 22 May 2020
Interferon-α (IFNα), a type I interferon, is expressed in the islets of type 1 diabetic individuals, and its expression and signaling are regulated by T1D genetic risk variants and viral infections associated with T1D. We presently characterize human beta cell responses to IFNα by combining ATAC-seq, RNA-seq and proteomics assays. The initial response to IFNα is characterized by chromatin remodeling, followed by changes in transcriptional and translational regulation. IFNα induces changes in alternative splicing (AS) and first exon usage, increasing the diversity of transcripts expressed by the beta cells. This, combined with changes observed on protein modification/degradation, ER stress and MHC class I, may expand antigens presented by beta cells to the immune system. Beta cells also up-regulate the checkpoint proteins PDL1 and HLA-E that may exert a protective role against the autoimmune assault. Data mining of the present multi-omics analysis identifies two compound classes that antagonize IFNα effects on human beta cells.
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Eizirik DL, Pasquali L, Cnop M

Pancreatic β-cells in type 1 and type 2 diabetes mellitus: different pathways to failure.

Nat Rev Endocrinol 12 May 2020, . Epub 12 May 2020
Loss of functional β-cell mass is the key mechanism leading to the two main forms of diabetes mellitus - type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Understanding the mechanisms behind β-cell failure is critical to prevent or revert disease. Basic pathogenic differences exist in the two forms of diabetes mellitus; T1DM is immune mediated and T2DM is mediated by metabolic mechanisms. These mechanisms differentially affect early β-cell dysfunction and eventual fate. Over the past decade, major advances have been made in the field, mostly delivered by studies on β-cells in human disease. These advances include studies of islet morphology and human β-cell gene expression in T1DM and T2DM, the identification and characterization of the role of T1DM and T2DM candidate genes at the β-cell level and the endoplasmic reticulum stress signalling that contributes to β-cell failure in T1DM (mostly IRE1 driven) and T2DM (mostly PERK-eIF2α dependent). Here, we review these new findings, focusing on studies performed on human β-cells or on samples obtained from patients with diabetes mellitus.
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Ferreira MSV, Kirschner M, Halfmeyer I, Estrada N, Xicoy B, Isfort S, Vieri M, Zamora L, Abels A, Bouillon AS, Begemann M, Schemionek M, Maurer A, Koschmieder S, Wilop S, Panse J, Brümmendorf TH, Beier F

Comparison of flow-FISH and MM-qPCR telomere length assessment techniques for the screening of telomeropathies.

Ann. N. Y. Acad. Sci. Abr 2020, 1466 (1) 93-103. Epub 24 Oct 2019
Assessment of telomere length (TL) in peripheral blood leukocytes is part of the diagnostic algorithm applied to patients with acquired bone marrow failure syndromes (BMFSs) and dyskeratosis congenita (DKC). Monochrome multiplex-quantitative polymerase chain reaction (MM-qPCR) and fluorescence in situ hybridization (flow-FISH) are methodologies available for TL screening. Dependent on TL expressed in relation to percentiles of healthy controls, further genetic testing for inherited mutations in telomere maintenance genes is recommended. However, the correct threshold to trigger this genetic workup is still under debate. Here, we prospectively compared MM-qPCR and flow-FISH regarding their capacity for accurate identification of DKC patients. All patients (n = 105) underwent genetic testing by next-generation sequencing and in 16 patients, mutations in DKC-relevant genes were identified. Whole leukocyte TL of patients measured by MM-qPCR was found to be moderately correlated with lymphocyte TL measured by flow-FISH (r² = 0.34; P < 0.0001). The sensitivity of both methods was high, but the specificity of MM-qPCR (29%) was significantly lower compared with flow-FISH (58%). These results suggest that MM-qPCR of peripheral blood cells is inferior to flow-FISH for clinical routine screening for suspected DKC in adult patients with BMFS due to lower specificity and a higher rate of false-positive results.
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Bueno-Costa A, Piñeyro D, Soler M, Javierre BM, Raurell-Vila H, Subirana-Granés M, Pasquali L, Martinez-Climent JA, Esteller M

B-cell leukemia transdifferentiation to macrophage involves reconfiguration of DNA methylation for long-range regulation.

Leukemia 12 Nov 2019, . Epub 12 Nov 2019Más información
Ramos-Rodríguez M, Raurell-Vila H, Colli ML, Alvelos MI, Subirana-Granés M, Juan-Mateu J, Norris R, Turatsinze JV, Nakayasu ES, Webb-Robertson BM, Inshaw JRJ, Marchetti P, Piemonti L, Esteller M, Todd JA, Metz TO, Eizirik DL, Pasquali L

The impact of proinflammatory cytokines on the β-cell regulatory landscape provides insights into the genetics of type 1 diabetes.

Nat. Genet. 1 Nov 2019, . Epub 1 Nov 2019
The early stages of type 1 diabetes (T1D) are characterized by local autoimmune inflammation and progressive loss of insulin-producing pancreatic β cells. Here we show that exposure to proinflammatory cytokines reveals a marked plasticity of the β-cell regulatory landscape. We expand the repertoire of human islet regulatory elements by mapping stimulus-responsive enhancers linked to changes in the β-cell transcriptome, proteome and three-dimensional chromatin structure. Our data indicate that the β-cell response to cytokines is mediated by the induction of new regulatory regions as well as the activation of primed regulatory elements prebound by islet-specific transcription factors. We find that T1D-associated loci are enriched with newly mapped cis-regulatory regions and identify T1D-associated variants disrupting cytokine-responsive enhancer activity in human β cells. Our study illustrates how β cells respond to a proinflammatory environment and implicate a role for stimulus response islet enhancers in T1D.
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Miguel-Escalada I, Bonàs-Guarch S, Cebola I, Ponsa-Cobas J, Mendieta-Esteban J, Atla G, Javierre BM, Rolando DMY, Farabella I, Morgan CC, García-Hurtado J, Beucher A, Morán I, Pasquali L, Ramos-Rodríguez M, Appel EVR, Linneberg A, Gjesing AP, Witte DR, Pedersen O, Grarup N, Ravassard P, Torrents D, Mercader JM, Piemonti L, Berney T, de Koning EJP, Kerr-Conte J, Pattou F, Fedko IO, Groop L, Prokopenko I, Hansen T, Marti-Renom MA, Fraser P, Ferrer J

Human pancreatic islet three-dimensional chromatin architecture provides insights into the genetics of type 2 diabetes.

Nat. Genet. Jul 2019, 51 (7) 1137-1148. Epub 28 Jun 2019
Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer clusters or super-enhancers. So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in three-dimensional (3D) space. Furthermore, their target genes are often unknown. We have created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers to their target genes, often located hundreds of kilobases away. It also revealed >1,300 groups of islet enhancers, super-enhancers and active promoters that form 3D hubs, some of which show coordinated glucose-dependent activity. We demonstrate that genetic variation in hubs impacts insulin secretion heritability, and show that hub annotations can be used for polygenic scores that predict T2D risk driven by islet regulatory variants. Human islet 3D chromatin architecture, therefore, provides a framework for interpretation of T2D genome-wide association study (GWAS) signals.
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Mularoni L, Ramos-Rodríguez M, Pasquali L

The Pancreatic Islet Regulome Browser.

Front Genet 2017, 8 13. Epub 14 Feb 2017
The pancreatic islet is a highly specialized tissue embedded in the exocrine pancreas whose primary function is that of controlling glucose homeostasis. Thus, understanding the transcriptional control of islet-cell may help to puzzle out the pathogenesis of glucose metabolism disorders. Integrative computational analyses of transcriptomic and epigenomic data allows predicting genomic coordinates of putative regulatory elements across the genome and, decipher tissue-specific functions of the non-coding genome. We herein present the Islet Regulome Browser, a tool that allows fast access and exploration of pancreatic islet epigenomic and transcriptomic data produced by different labs worldwide. The Islet Regulome Browser is now accessible on the internet or may be installed locally. It allows uploading custom tracks as well as providing interactive access to a wealth of information including Genome-Wide Association Studies (GWAS) variants, different classes of regulatory elements, together with enhancer clusters, stretch-enhancers and transcription factor binding sites in pancreatic progenitors and adult human pancreatic islets. Integration and visualization of such data may allow a deeper understanding of the regulatory networks driving tissue-specific transcription and guide the identification of regulatory variants. We believe that such tool will facilitate the access to pancreatic islet public genomic datasets providing a major boost to functional genomics studies in glucose metabolism related traits including diabetes.
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Akerman I, Tu Z, Beucher A, Rolando DM, Sauty-Colace C, Benazra M, Nakic N, Yang J, Wang H, Pasquali L, Moran I, Garcia-Hurtado J, Castro N, Gonzalez-Franco R, Stewart AF, Bonner C, Piemonti L, Berney T, Groop L, Kerr-Conte J, Pattou F, Argmann C, Schadt E, Ravassard P, Ferrer J

Human Pancreatic β Cell lncRNAs Control Cell-Specific Regulatory Networks.

Cell Metab. 28 Dic 2016, . Epub 28 Dic 2016
Recent studies have uncovered thousands of long non-coding RNAs (lncRNAs) in human pancreatic β cells. β cell lncRNAs are often cell type specific and exhibit dynamic regulation during differentiation or upon changing glucose concentrations. Although these features hint at a role of lncRNAs in β cell gene regulation and diabetes, the function of β cell lncRNAs remains largely unknown. In this study, we investigated the function of β cell-specific lncRNAs and transcription factors using transcript knockdowns and co-expression network analysis. This revealed lncRNAs that function in concert with transcription factors to regulate β cell-specific transcriptional networks. We further demonstrate that the lncRNA PLUTO affects local 3D chromatin structure and transcription of PDX1, encoding a key β cell transcription factor, and that both PLUTO and PDX1 are downregulated in islets from donors with type 2 diabetes or impaired glucose tolerance. These results implicate lncRNAs in the regulation of β cell-specific transcription factor networks.
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Horikoshi M, Pasquali L, Wiltshire S, Huyghe JR, Mahajan A, Asimit JL, Ferreira T, Locke AE, Robertson NR, Wang X, Sim X, Fujita H, Hara K, Young R, Zhang W, Choi S, Chen H, Kaur I, Takeuchi F, Fontanillas P, Thuillier D, Yengo L, Below JE, Tam CH, Wu Y, Abecasis G, Altshuler D, Bell GI, Blangero J, Burtt NP, Duggirala R, Florez JC, Hanis CL, Seielstad M, Atzmon G, Chan JC, Ma RC, Froguel P, Wilson JG, Bharadwaj D, Dupuis J, Meigs JB, Cho YS, Park T, Kooner JS, Chambers JC, Saleheen D, Kadowaki T, Tai ES, Mohlke KL, Cox NJ, Ferrer J, Zeggini E, Kato N, Teo YY, Boehnke M, McCarthy MI, Morris AP

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

Hum. Mol. Genet. 15 May 2016, 25 (10) 2070-2081. Epub 23 Feb 2016
To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci.
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Gaulton KJ, Ferreira T, Lee Y, Raimondo A, Mägi R, Reschen ME, Mahajan A, Locke A, William Rayner N, Robertson N, Scott RA, Prokopenko I, Scott LJ, Green T, Sparso T, Thuillier D, Yengo L, Grallert H, Wahl S, Frånberg M, Strawbridge RJ, Kestler H, Chheda H, Eisele L, Gustafsson S, Steinthorsdottir V, Thorleifsson G, Qi L, Karssen LC, van Leeuwen EM, Willems SM, Li M, Chen H, Fuchsberger C, Kwan P, Ma C, Linderman M, Lu Y, Thomsen SK, Rundle JK, Beer NL, van de Bunt M, Chalisey A, Kang HM, Voight BF, Abecasis GR, Almgren P, Baldassarre D, Balkau B, Benediktsson R, Blüher M, Boeing H, Bonnycastle LL, Bottinger EP, Burtt NP, Carey J, Charpentier G, Chines PS, Cornelis MC, Couper DJ, Crenshaw AT, van Dam RM, Doney AS, Dorkhan M, Edkins S, Eriksson JG, Esko T, Eury E, Fadista J, Flannick J, Fontanillas P, Fox C, Franks PW, Gertow K, Gieger C, Gigante B, Gottesman O, Grant GB, Grarup N, Groves CJ, Hassinen M, Have CT, Herder C, Holmen OL, Hreidarsson AB, Humphries SE, Hunter DJ, Jackson AU, Jonsson A, Jørgensen ME, Jørgensen T, Kao WH, Kerrison ND, Kinnunen L, Klopp N, Kong A, Kovacs P, Kraft P, Kravic J, Langford C, Leander K, Liang L, Lichtner P, Lindgren CM, Lindholm E, Linneberg A, Liu CT, Lobbens S, Luan J, Lyssenko V, Männistö S, McLeod O, Meyer J, Mihailov E, Mirza G, Mühleisen TW, Müller-Nurasyid M, Navarro C, Nöthen MM, Oskolkov NN, Owen KR, Palli D, Pechlivanis S, Peltonen L, Perry JR, Platou CG, Roden M, Ruderfer D, Rybin D, van der Schouw YT, Sennblad B, Sigurðsson G, Stančáková A, Steinbach G, Storm P, Strauch K, Stringham HM, Sun Q, Thorand B, Tikkanen E, Tonjes A, Trakalo J, Tremoli E, Tuomi T, Wennauer R, Wiltshire S, Wood AR, Zeggini E, Dunham I, Birney E, Pasquali L, Ferrer J, Loos RJ, Dupuis J, Florez JC, Boerwinkle E, Pankow JS, van Duijn C, Sijbrands E, Meigs JB, Hu FB, Thorsteinsdottir U, Stefansson K, Lakka TA, Rauramaa R, Stumvoll M, Pedersen NL, Lind L, Keinanen-Kiukaanniemi SM, Korpi-Hyövälti E, Saaristo TE, Saltevo J, Kuusisto J, Laakso M, Metspalu A, Erbel R, Jöcke KH, Moebus S, Ripatti S, Salomaa V, Ingelsson E, Boehm BO, Bergman RN, Collins FS, Mohlke KL, Koistinen H, Tuomilehto J, Hveem K, Njølstad I, Deloukas P, Donnelly PJ, Frayling TM, Hattersley AT, de Faire U, Hamsten A, Illig T, Peters A, Cauchi S, Sladek R, Froguel P, Hansen T, Pedersen O, Morris AD, Palmer CN, Kathiresan S, Melander O, Nilsson PM, Groop LC, Barroso I, Langenberg C, Wareham NJ, O'Callaghan CA, Gloyn AL, Altshuler D, Boehnke M, Teslovich TM, McCarthy MI, Morris AP

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

Nat. Genet. Dic 2015, 47 (12) 1415-25. Epub 9 Nov 2015
We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
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