Browsing by Author "Anderson, Mark S."

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    A genomic data archive from the Network for Pancreatic Organ donors with Diabetes
    (Springer Nature, 2023-05-26) Perry, Daniel J.; Shapiro, Melanie R.; Chamberlain, Sonya W.; Kusmartseva, Irina; Chamala, Srikar; Balzano-Nogueira, Leandro; Yang, Mingder; Brant, Jason O.; Brusko, Maigan; Williams, MacKenzie D.; McGrail, Kieran M.; McNichols, James; Peters, Leeana D.; Posgai, Amanda L.; Kaddis, John S.; Mathews, Clayton E.; Wasserfall, Clive H.; Webb-Robertson, Bobbie-Jo M.; Campbell-Thompson, Martha; Schatz, Desmond; Evans-Molina, Carmella; Pugliese, Alberto; Concannon, Patrick; Anderson, Mark S.; German, Michael S.; Chamberlain, Chester E.; Atkinson, Mark A.; Brusko, Todd M.; Pediatrics, School of Medicine
    The Network for Pancreatic Organ donors with Diabetes (nPOD) is the largest biorepository of human pancreata and associated immune organs from donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, islet autoantibody positivity (AAb+), and without diabetes. nPOD recovers, processes, analyzes, and distributes high-quality biospecimens, collected using optimized standard operating procedures, and associated de-identified data/metadata to researchers around the world. Herein describes the release of high-parameter genotyping data from this collection. 372 donors were genotyped using a custom precision medicine single nucleotide polymorphism (SNP) microarray. Data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 donors were assessed for rare known and novel coding region variants via whole exome sequencing (WES). These data are publicly-available to enable genotype-specific sample requests and the study of novel genotype:phenotype associations, aiding in the mission of nPOD to enhance understanding of diabetes pathogenesis to promote the development of novel therapies.
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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.