Browsing by Author "Atkinson, Mark A."

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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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    Dysglycemia and Index60 as Prediagnostic End Points for Type 1 Diabetes Prevention Trials
    (American Diabetes Association, 2017-11) Nathan, Brandon M.; Boulware, David; Geyer, Susan; Atkinson, Mark A.; Colman, Peter; Goland, Robin; Russell, William; Wentworth, John M.; Wilson, Darrell M.; Evans-Molina, Carmella; Wherrett, Diane; Skyler, Jay S.; Moran, Antoinette; Sosenko, Jay M.; Type 1 Diabetes TrialNet and Diabetes Prevention Trial–Type 1 Study Groups; Medicine, School of Medicine
    OBJECTIVE: We assessed dysglycemia and a T1D Diagnostic Index60 (Index60) ≥1.00 (on the basis of fasting C-peptide, 60-min glucose, and 60-min C-peptide levels) as prediagnostic end points for type 1 diabetes among Type 1 Diabetes TrialNet Pathway to Prevention Study participants. RESEARCH DESIGN AND METHODS: Two cohorts were analyzed: 1) baseline normoglycemic oral glucose tolerance tests (OGTTs) with an incident dysglycemic OGTT and 2) baseline Index60 <1.00 OGTTs with an incident Index60 ≥1.00 OGTT. Incident dysglycemic OGTTs were divided into those with (DYS/IND+) and without (DYS/IND-) concomitant Index60 ≥1.00. Incident Index60 ≥1.00 OGTTs were divided into those with (IND/DYS+) and without (IND/DYS-) concomitant dysglycemia. RESULTS: The cumulative incidence for type 1 diabetes was greater after IND/DYS- than after DYS/IND- (P < 0.01). Within the normoglycemic cohort, the cumulative incidence of type 1 diabetes was higher after DYS/IND+ than after DYS/IND- (P < 0.001), whereas within the Index60 <1.00 cohort, the cumulative incidence after IND/DYS+ and after IND/DYS- did not differ significantly. Among nonprogressors, type 1 diabetes risk at the last OGTT was greater for IND/DYS- than for DYS/IND- (P < 0.001). Hazard ratios (HRs) of DYS/IND- with age and 30- to 0-min C-peptide were positive (P < 0.001 for both), whereas HRs of type 1 diabetes with these variables were inverse (P < 0.001 for both). In contrast, HRs of IND/DYS- and type 1 diabetes with age and 30- to 0-min C-peptide were consistent (all inverse [P < 0.01 for all]). CONCLUSIONS: The findings suggest that incident dysglycemia without Index60 ≥1.00 is a suboptimal prediagnostic end point for type 1 diabetes. Measures that include both glucose and C-peptide levels, such as Index60 ≥1.00, appear better suited as prediagnostic end points.
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    Early and late C-peptide responses during oral glucose tolerance testing are oppositely predictive of type 1 diabetes in autoantibody-positive individuals
    (Wiley, 2020-01-31) Ismail, Heba M.; Becker, Dorothy J.; Libman, Ingrid; Herold, Kevan C.; Redondo, Maria J.; Atkinson, Mark A.; Cleves, Mario A.; Palmer, Jerry; Sosenko, Jay; Pediatrics, School of Medicine
    We examined whether the timing of the C-peptide response during an oral glucose tolerance test (OGTT) in relatives of patients with type 1 diabetes (T1D) is predictive of disease onset. We examined baseline 2-h OGTTs from 670 relatives participating in the Diabetes Prevention Trial-Type 1 (age: 13.8 ± 9.6 years; body mass index z score: 0.3 ± 1.1; 56% male) using univariate regression models. T1D risk increased with lower early C-peptide responses (30–0 min) (χ2 = 28.8, P < 0.001), and higher late C-peptide responses (120–60 min) (χ2 = 23.3, P < 0.001). When both responses were included in a proportional hazards model, they remained independently and oppositely associated with T1D, with a stronger overall association for the combined model than either response alone (χ2 = 41.1; P < 0.001). Using receiver operating characteristic curve analysis, the combined early and late C-peptide response was more accurately predictive of T1D than area under the curve C-peptide (P = 0.005). Our findings demonstrate that lower early and higher late C-peptide responses serve as indicators of increased T1D risk.
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    Expression of SARS-CoV-2 Entry Factors in the Pancreas of Normal Organ Donors and Individuals with COVID-19
    (Elsevier, 2020-11-13) Kusmartseva, Irina; Wu, Wenting; Syed, Farooq; Van Der Heide, Verena; Jorgensen, Marda; Joseph, Paul; Tang, Xiaohan; Candelario-Jalil, Eduardo; Yang, Changjun; Nick, Harry; Harbert, Jack L.; Posgai, Amanda L.; Paulsen, John David; Lloyd, Richard; Cechin, Sirlene; Pugliese, Alberto; Campbell-Thompson, Martha; Vander Heide, Richard S.; Evans-Molina, Carmella; Homann, Dirk; Atkinson, Mark A.; Medical and Molecular Genetics, School of Medicine
    Diabetes is associated with increased mortality from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Given literature suggesting a potential association between SARS-CoV-2 infection and diabetes induction, we examined pancreatic expression of angiotensin-converting enzyme 2 (ACE2), the key entry factor for SARS-CoV-2 infection. Specifically, we analyzed five public scRNA-seq pancreas datasets and performed fluorescence in situ hybridization, western blotting, and immunolocalization for ACE2 with extensive reagent validation on normal human pancreatic tissues across the lifespan, as well as those from coronavirus disease 2019 (COVID-19) cases. These in silico and ex vivo analyses demonstrated prominent expression of ACE2 in pancreatic ductal epithelium and microvasculature, but we found rare endocrine cell expression at the mRNA level. Pancreata from individuals with COVID-19 demonstrated multiple thrombotic lesions with SARS-CoV-2 nucleocapsid protein expression that was primarily limited to ducts. These results suggest SARS-CoV-2 infection of pancreatic endocrine cells, via ACE2, is an unlikely central pathogenic feature of COVID-19-related diabetes.
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    Index60 as an additional diagnostic criterion for type 1 diabetes
    (Springer, 2021) Redondo, Maria J.; Nathan, Brandon M.; Jacobsen, Laura M.; Sims, Emily; Bocchino, Laura E.; Pugliese, Alberto; Schatz, Desmond A.; Atkinson, Mark A.; Skyler, Jay; Palmer, Jerry; Geyer, Susan; Sosenko, Jay M.; Type 1 diabetes TrialNet Study Group; Pediatrics, School of Medicine
    Aims/hypothesis: We aimed to compare characteristics of individuals identified in the peri-diagnostic range by Index60 (composite glucose and C-peptide measure) ≥2.00, 2 h OGTT glucose ≥11.1 mmol/l, or both. Methods: We studied autoantibody-positive participants in the Type 1 Diabetes TrialNet Pathway to Prevention study who, at their baseline OGTT, had 2 h blood glucose ≥11.1 mmol/l and/or Index60 ≥2.00 (n = 354, median age = 11.2 years, age range = 1.7-46.6; 49% male, 83% non-Hispanic White). Type 1 diabetes-relevant characteristics (e.g., age, C-peptide, autoantibodies, BMI) were compared among three mutually exclusive groups: 2 h glucose ≥11.1 mmol/l and Index60 <2.00 [Glu(+), n = 76], 2 h glucose <11.1 mmol/l and Index60 ≥2.00 [Ind(+), n = 113], or both 2 h glucose ≥11.1 mmol/l and Index60 ≥2.00 [Glu(+)/Ind(+), n = 165]. Results: Participants in Glu(+), vs those in Ind(+) or Glu(+)/Ind(+), were older (mean ages = 22.9, 11.8 and 14.7 years, respectively), had higher early (30-0 min) C-peptide response (1.0, 0.50 and 0.43 nmol/l), higher AUC C-peptide (2.33, 1.13 and 1.10 nmol/l), higher percentage of overweight/obesity (58%, 16% and 30%) (all comparisons, p < 0.0001), and a lower percentage of multiple autoantibody positivity (72%, 92% and 93%) (p < 0.001). OGTT-stimulated C-peptide and glucose patterns of Glu(+) differed appreciably from Ind(+) and Glu(+)/Ind(+). Progression to diabetes occurred in 61% (46/76) of Glu(+) and 63% (71/113) of Ind(+). Even though Index60 ≥2.00 was not a Pathway to Prevention diagnostic criterion, Ind(+) had a 4 year cumulative diabetes incidence of 95% (95% CI 86%, 98%). Conclusions/interpretation: Participants in the Ind(+) group had more typical characteristics of type 1 diabetes than participants in the Glu(+) did and were as likely to be diagnosed. However, unlike Glu(+) participants, Ind(+) participants were not identified at the baseline OGTT.
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    The Influence of Type 2 Diabetes–Associated Factors on Type 1 Diabetes
    (American Diabetes Association, 2019-08-01) Redondo, Maria J.; Evans-Molina, Carmella; Steck, Andrea K.; Atkinson, Mark A.; Sosenko, Jay; Pediatrics, School of Medicine
    Current efforts to prevent progression from islet autoimmunity to type 1 diabetes largely focus on immunomodulatory approaches. However, emerging data suggest that the development of diabetes in islet autoantibody–positive individuals may also involve factors such as obesity and genetic variants associated with type 2 diabetes, and the influence of these factors increases with age at diagnosis. Although these factors have been linked with metabolic outcomes, particularly through their impact on β-cell function and insulin sensitivity, growing evidence suggests that they might also interact with the immune system to amplify the autoimmune response. The presence of factors shared by both forms of diabetes contributes to disease heterogeneity and thus has important implications. Characteristics that are typically considered to be nonimmune should be incorporated into predictive algorithms that seek to identify at-risk individuals and into the designs of trials for disease prevention. The heterogeneity of diabetes also poses a challenge in diagnostic classification. Finally, after clinically diagnosing type 1 diabetes, addressing nonimmune elements may help to prevent further deterioration of β-cell function and thus improve clinical outcomes. This Perspectives in Care article highlights the role of type 2 diabetes–associated genetic factors (e.g., gene variants at transcription factor 7-like 2 [TCF7L2]) and obesity (via insulin resistance, inflammation, β-cell stress, or all three) in the pathogenesis of type 1 diabetes and their impacts on age at diagnosis. Recognizing that type 1 diabetes might result from the sum of effects from islet autoimmunity and type 2 diabetes–associated factors, their interactions, or both affects disease prediction, prevention, diagnosis, and treatment.
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    Insulin Receptor-Expressing T Cells Appear in Individuals at Risk for Type 1 Diabetes and Can Move into the Pancreas in C57BL/6 Transgenic Mice
    (American Association of Immunologists, 2021) Nandedkar-Kulkarni, Neha; Esakov, Emily; Gregg, Brigid; Atkinson, Mark A.; Rogers, Douglas G.; Horner, James D.; Singer, Kanakadurga; Lundy, Steven K.; Felton, Jamie L.; Al-Huniti, Tasneem; Kalinoski, Andrea Nestor; Morran, Michael P.; Gupta, Nirdesh K.; Bretz, James D.; Balaji, Swapnaa; Chen, Tian; McInerney, Marcia F.; Pediatrics, School of Medicine
    Insulin receptor (IR) expression on the T cell surface can indicate an activated state; however, the IR is also chemotactic, enabling T cells with high IR expression to physically move toward insulin. In humans with type 1 diabetes (T1D) and the NOD mouse model, a T cell-mediated autoimmune destruction of insulin-producing pancreatic β cells occurs. In previous work, when purified IR+ and IR- T cells were sorted from diabetic NOD mice and transferred into irradiated nondiabetic NOD mice, only those that received IR+ T cells developed insulitis and diabetes. In this study, peripheral blood samples from individuals with T1D (new onset to 14 y of duration), relatives at high-risk for T1D, defined by positivity for islet autoantibodies, and healthy controls were examined for frequency of IR+ T cells. High-risk individuals had significantly higher numbers of IR+ T cells as compared with those with T1D (p < 0.01) and controls (p < 0.001); however, the percentage of IR+ T cells in circulation did not differ significantly between T1D and control subjects. With the hypothesis that IR+ T cells traffic to the pancreas in T1D, we developed a (to our knowledge) novel mouse model exhibiting a FLAG-tagged mouse IR on T cells on the C57BL/6 background, which is not susceptible to developing T1D. Interestingly, these C57BL/6-CD3FLAGmIR/mfm mice showed evidence of increased IR+ T cell trafficking into the islets compared with C57BL/6 controls (p < 0.001). This transgenic animal model provides a (to our knowledge) novel platform for investigating the influence of IR expression on T cell trafficking and the development of insulitis.
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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.
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    Peripheral immune circadian variation, synchronisation and possible dysrhythmia in established type 1 diabetes
    (Springer, 2021-08) Beam, Craig A.; Beli, Eleni; Wasserfall, Clive H.; Woerner, Stephanie E.; Legge, Megan T.; Evans-Molina, Carmella; McGrail, Kieran M.; Silk, Ryan; Grant, Maria B.; Atkinson, Mark A.; DiMeglio, Linda A.; Pediatrics, School of Medicine
    Aims/hypothesis: The circadian clock influences both diabetes and immunity. Our goal in this study was to characterise more thoroughly the circadian patterns of immune cell populations and cytokines that are particularly relevant to the immune pathology of type 1 diabetes and thus fill in a current gap in our understanding of this disease. Methods: Ten individuals with established type 1 diabetes (mean disease duration 11 years, age 18-40 years, six female) participated in a circadian sampling protocol, each providing six blood samples over a 24 h period. Results: Daily ranges of population frequencies were sometimes large and possibly clinically significant. Several immune populations, such as dendritic cells, CD4 and CD8 T cells and their effector memory subpopulations, CD4 regulatory T cells, B cells and cytokine IL-6, exhibited statistically significant circadian rhythmicity. In a comparison with historical healthy control individuals, but using shipped samples, we observed that participants with type 1 diabetes had statistically significant phase shifts occurring in the time of peak occurrence of B cells (+4.8 h), CD4 and CD8 T cells (~ +5 h) and their naive and effector memory subsets (~ +3.3 to +4.5 h), and regulatory T cells (+4.1 h). An independent streptozotocin murine experiment confirmed the phase shifting of CD8 T cells and suggests that circadian dysrhythmia in type 1 diabetes might be an effect and not a cause of the disease. Conclusions/interpretation: Future efforts investigating this newly described aspect of type 1 diabetes in human participants are warranted. Peripheral immune populations should be measured near the same time of day in order to reduce circadian-related variation.
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    Response to Comment on Dunne et al. The Women's Leadership Gap in Diabetes: A Call for Equity and Excellence. Diabetes Care 2021;44:1734-1743
    (American Diabetes Association, 2022) Dunne, Jessica L.; Maizel, Jennifer L.; Posgai, Amanda L.; Atkinson, Mark A.; DiMeglio, Linda A.; Pediatrics, School of Medicine