Browsing by Author "Peakman, Mark"

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    A set of circulating microRNAs belonging to the 14q32 chromosome locus identifies two subgroups of individuals with recent-onset type 1 diabetes
    (Elsevier, 2024) Sebastiani, Guido; Grieco, Giuseppina Emanuela; Bruttini, Marco; Auddino, Stefano; Mori, Alessia; Toniolli, Mattia; Fignani, Daniela; Licata, Giada; Aiello, Elena; Nigi, Laura; Formichi, Caterina; Fernandez-Tajes, Juan; Pugliese, Alberto; Evans-Molina, Carmella; Overbergh, Lut; Tree, Timothy; Peakman, Mark; Mathieu, Chantal; Dotta, Francesco; INNODIA investigators; Pediatrics, School of Medicine
    Circulating microRNAs (miRNAs) are linked to the onset and progression of type 1 diabetes mellitus (T1DM), thus representing potential disease biomarkers. In this study, we employed a multiplatform sequencing approach to analyze circulating miRNAs in an extended cohort of prospectively evaluated recent-onset T1DM individuals from the INNODIA consortium. Our findings reveal that a set of miRNAs located within T1DM susceptibility chromosomal locus 14q32 distinguishes two subgroups of individuals. To validate our results, we conducted additional analyses on a second cohort of T1DM individuals, confirming the identification of these subgroups, which we have named cluster A and cluster B. Remarkably, cluster B T1DM individuals, who exhibit increased expression of a set of 14q32 miRNAs, show better glycemic control and display a different blood immunomics profile. Our findings suggest that this set of circulating miRNAs can identify two different T1DM subgroups with distinct blood immunomics at baseline and clinical outcomes during follow-up.
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    Introducing the Endotype Concept to Address the Challenge of Disease Heterogeneity in Type 1 Diabetes
    (American Diabetes Association, 2020-01) Battaglia, Manuela; Ahmed, Simi; Anderson, Mark S.; Atkinson, Mark A.; Becker, Dorothy; Bingley, Polly J.; Bosi, Emanuele; Brusko, Todd M.; DiMeglio, Linda A.; Evans-Molina, Carmella; Gitelman, Stephen E.; Greenbaum, Carla J.; Gottlieb, Peter A.; Herold, Kevan C.; Hessner, Martin J.; Knip, Mikael; Jacobsen, Laura; Krischer, Jeffrey P.; Long, S. Alice; Lundgren, Markus; McKinney, Eoin F.; Morgan, Noel G.; Oram, Richard A.; Pastinen, Tomi; Peters, Michael C.; Petrelli, Alessandra; Qian, Xiaoning; Redondo, Maria J.; Roep, Bart O.; Schatz, Desmond; Skibinski, David; Peakman, Mark; Pediatrics, School of Medicine
    The clinical diagnosis of new-onset type 1 diabetes has, for many years, been considered relatively straightforward. Recently, however, there is increasing awareness that within this single clinical phenotype exists considerable heterogeneity: disease onset spans the complete age range; genetic susceptibility is complex; rates of progression differ markedly, as does insulin secretory capacity; and complication rates, glycemic control, and therapeutic intervention efficacy vary widely. Mechanistic and immunopathological studies typically show considerable patchiness across subjects, undermining conclusions regarding disease pathways. Without better understanding, type 1 diabetes heterogeneity represents a major barrier both to deciphering pathogenesis and to the translational effort of designing, conducting, and interpreting clinical trials of disease-modifying agents. This realization comes during a period of unprecedented change in clinical medicine, with increasing emphasis on greater individualization and precision. For complex disorders such as type 1 diabetes, the option of maintaining the "single disease" approach appears untenable, as does the notion of individualizing each single patient's care, obliging us to conceptualize type 1 diabetes less in terms of phenotypes (observable characteristics) and more in terms of disease endotypes (underlying biological mechanisms). Here, we provide our view on an approach to dissect heterogeneity in type 1 diabetes. Using lessons from other diseases and the data gathered to date, we aim to delineate a roadmap through which the field can incorporate the endotype concept into laboratory and clinical practice. We predict that such an effort will accelerate the implementation of precision medicine and has the potential for impact on our approach to translational research, trial design, and clinical management.