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Browsing by Author "Krischer, Jeffrey P."
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Item Creating a multi-center rare disease consortium - the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR)(IOS Press, 2017-12-18) Cheng, Katherine; Gupta, Sandeep K.; Kantor, Susanna; Kuhl, Jonathan T.; Aceves, Seema S.; Bonis, Peter A.; Capocelli, Kelley E.; Carpenter, Christina; Chehade, Mirna; Collins, Margaret H.; Dellon, Evan S.; Falk, Gary W.; Gopal-Srivastava, Rashmi; Gonsalves, Nirmala; Hirano, Ikuo; King, Eileen C.; Leung, John; Krischer, Jeffrey P.; Mukkada, Vincent A.; Schoepfer, Alain; Spergel, Jonathan M.; Straumann, Alex; Yang, Guang-Yu; Furuta, Glenn T.; Rothenberg, Marc E.; Pediatrics, School of MedicineEosinophilic gastrointestinal disorders (EGIDs) affect various segments of the gastrointestinal tract. Since these disorders are rare, collaboration is essential to enroll subjects in clinical studies and study the broader population. The Rare Diseases Clinical Research Network (RDCRN), a program of the National Center for Advancing Translational Sciences (NCATS), funded the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR) in 2014 to advance the field of EGIDs. CEGIR facilitates collaboration among various centers, subspecialties, patients, professional organizations and patient-advocacy groups and includes 14 clinical sites. It has successfully initiated two large multi-center clinical studies looking to refine EGID diagnoses and management. Several pilot studies are underway that focus on various aspects of EGIDs including novel therapeutic interventions, diagnostic and monitoring methods, and the role of the microbiome in pathogenesis. CEGIR currently nurtures five physician-scholars through a career training development program and has published more than 40 manuscripts since its inception. This review focuses on CEGIR's operating model and progress and how it facilitates a framework for exchange of ideas and stimulates research and innovation. This consortium provides a model for progress on other potential clinical areas.Item 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 MedicineThe 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.Item Primary Ciliary Dyskinesia: Longitudinal Study of Lung Disease by Ultrastructure Defect and Genotype(American Thoracic Society, 2019-01-15) Davis, Stephanie D.; Rosenfeld, Margaret; Lee, Hye-Seung; Ferkol, Thomas W.; Sagel, Scott D.; Dell, Sharon D.; Milla, Carlos; Pittman, Jessica E.; Shapiro, Adam J.; Sullivan, Kelli M.; Nykamp, Keith R.; Krischer, Jeffrey P.; Zariwala, Maimoona A.; Knowles, Michael R.; Leigh, Margaret W.; Pediatrics, School of MedicineRATIONALE: In primary ciliary dyskinesia, factors leading to disease heterogeneity are poorly understood. OBJECTIVES: To describe early lung disease progression in primary ciliary dyskinesia and identify associations between ultrastructural defects and genotypes with clinical phenotype. METHODS: This was a prospective, longitudinal (5 yr), multicenter, observational study. Inclusion criteria were less than 19 years at enrollment and greater than or equal to two annual study visits. Linear mixed effects models including random slope and random intercept were used to evaluate longitudinal associations between the ciliary defect group (or genotype group) and clinical features (percent predicted FEV1 and weight and height z-scores). MEASUREMENTS AND MAIN RESULTS: A total of 137 participants completed 732 visits. The group with absent inner dynein arm, central apparatus defects, and microtubular disorganization (IDA/CA/MTD) (n = 41) were significantly younger at diagnosis and in mixed effects models had significantly lower percent predicted FEV1 and weight and height z-scores than the isolated outer dynein arm defect (n = 55) group. Participants with CCDC39 or CCDC40 mutations (n = 34) had lower percent predicted FEV1 and weight and height z-scores than those with DNAH5 mutations (n = 36). For the entire cohort, percent predicted FEV1 decline was heterogeneous with a mean (SE) decline of 0.57 (0.25) percent predicted/yr. Rate of decline was different from zero only in the IDA/MTD/CA group (mean [SE], -1.11 [0.48] percent predicted/yr; P = 0.02). CONCLUSIONS: Participants with IDA/MTD/CA defects, which included individuals with CCDC39 or CCDC40 mutations, had worse lung function and growth indices compared with those with outer dynein arm defects and DNAH5 mutations, respectively. The only group with a significant lung function decline over time were participants with IDA/MTD/CA defects.Item Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation(Springer Nature, 2021) Nakayasu, Ernesto S.; Gritsenko, Marina; Piehowski, Paul D.; Gao, Yuqian; Orton, Daniel J.; Schepmoes, Athena A.; Fillmore, Thomas L.; Frohnert, Brigitte I.; Rewers, Marian; Krischer, Jeffrey P.; Ansong, Charles; Suchy-Dicey, Astrid M.; Evans-Molina, Carmella; Qian, Wei-Jun; Webb-Robertson, Bobbie-Jo M.; Metz, Thomas O.; Pediatrics, School of MedicineMass-spectrometry-based proteomic analysis is a powerful approach for discovering new disease biomarkers. However, certain critical steps of study design such as cohort selection, evaluation of statistical power, sample blinding and randomization, and sample/data quality control are often neglected or underappreciated during experimental design and execution. This tutorial discusses important steps for designing and implementing a liquid-chromatography-mass-spectrometry-based biomarker discovery study. We describe the rationale, considerations and possible failures in each step of such studies, including experimental design, sample collection and processing, and data collection. We also provide guidance for major steps of data processing and final statistical analysis for meaningful biological interpretations along with highlights of several successful biomarker studies. The provided guidelines from study design to implementation to data interpretation serve as a reference for improving rigor and reproducibility of biomarker development studies.Item β Cell dysfunction exists more than 5 years before type 1 diabetes diagnosis(American Society for Clinical Investigation, 2018-08-09) Evans-Molina, Carmella; Sims, Emily K.; DiMeglio, Linda A.; Ismail, Heba M.; Steck, Andrea K.; Palmer, Jerry P.; Krischer, Jeffrey P.; Geyer, Susan; Xu, Ping; Sosenko, Jay M.; Medicine, School of MedicineBACKGROUND: The duration and patterns of β cell dysfunction during type 1 diabetes (T1D) development have not been fully defined. METHODS: Metabolic measures derived from oral glucose tolerance tests (OGTTs) were compared between autoantibody-positive (aAb+) individuals followed in the TrialNet Pathway to Prevention study who developed diabetes after 5 or more years or less than 5 years of longitudinal follow-up (Progressors≥5, n = 75; Progressors<5, n = 474) and 144 aAb-negative (aAb-) relatives. RESULTS: Mean age at study entry was 15.0 ± 12.6 years for Progressors≥5; 12.0 ± 9.1 for Progressors<5; and 16.3 ± 10.4 for aAb- relatives. At baseline, Progressors≥5 already exhibited significantly lower fasting C-peptide (P < 0.01), C-peptide AUC (P < 0.001), and early C-peptide responses (30- to 0-minute C-peptide; P < 0.001) compared with aAb- relatives, while 2-hour glucose (P = 0.03), glucose AUC (<0.001), and Index60 (<0.001) were all higher. Despite significant baseline impairment, metabolic measures in Progressors≥5 were relatively stable until 2 years prior to T1D diagnosis, when there was accelerated C-peptide decline and rising glycemia from 2 years until diabetes diagnosis. Remarkably, patterns of progression within 3 years of diagnosis were nearly identical between Progressors≥5 and Progressors<5. CONCLUSION: These data provide insight into the chronicity of β cell dysfunction in T1D and indicate that β cell dysfunction may precede diabetes diagnosis by more than 5 years in a subset of aAb+ individuals. Even among individuals with varying lengths of aAb positivity, our findings indicate that patterns of metabolic decline are uniform within the last 3 years of progression to T1D. TRIAL REGISTRATION: Clinicaltrials.gov NCT00097292. FUNDING: The Type 1 Diabetes TrialNet Study Group is a clinical trials network currently funded by the NIH through the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Allergy and Infectious Diseases, and The Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Juvenile Diabetes Research Foundation.