Browsing by Author "Harris-Kawano, Arianna"

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    Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review
    (Springer Nature, 2024-04-06) Felton, Jamie L.; Redondo, Maria J.; Oram, Richard A.; Speake, Cate; Long, S. Alice; Onengut-Gumuscu, Suna; Rich, Stephen S.; Monaco, Gabriela S. F.; Harris-Kawano, Arianna; Perez, Dianna; Saeed, Zeb; Hoag, Benjamin; Jain, Rashmi; Evans-Molina, Carmella; DiMeglio, Linda A.; Ismail, Heba M.; Dabelea, Dana; Johnson, Randi K.; Urazbayeva, Marzhan; Wentworth, John M.; Griffin, Kurt J.; Sims, Emily K.; ADA/EASD PMDI; Pediatrics, School of Medicine
    Background: Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies. Methods: We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment. Results: Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation. Conclusions: Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.
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    A novel Cre-enabled tetracycline-inducible transgenic system for tissue-specific cytokine expression in the zebrafish: CETI-PIC3
    (The Company of Biologists, 2020-06-26) Ibrahim, Sara; Harris-Kawano, Arianna; Haider, Isra; Mirmira, Raghavendra G.; Sims, Emily K.; Anderson, Ryan M.; Pediatrics, School of Medicine
    Maladaptive signaling by pro-inflammatory cytokines (PICs), such as TNFα, IL1β and IFNɣ, can activate downstream signaling cascades that are implicated in the development and progression of multiple inflammatory diseases. Despite playing critical roles in pathogenesis, the availability of in vivo models in which to model tissue-specific induction of PICs is limited. To bridge this gap, we have developed a novel multi-gene expression system dubbed Cre-enabled and tetracycline-inducible transgenic system for conditional, tissue-specific expression of pro-inflammatory cytokines (CETI-PIC3). This binary transgenic system permits the stoichiometric co-expression of proteins Tumor necrosis factor a (Tnfa), Interleukin-1 beta (Il1b) and Interferon gamma (Ifng1), and H2B-GFP fluorescent reporter in a dose-dependent manner. Furthermore, cytokine misexpression is enabled only in tissue domains that can be defined by Cre recombinase expression. We have validated this system in zebrafish using an insulin:cre line. In doubly transgenic fish, quantitative real-time polymerase chain reaction demonstrated increased expression levels of tnfa, il1b and ifng1 mRNA. Moreover, specific expression in pancreatic β cells was demonstrated by both Tnfa immunofluorescence and GFP fluorescence. Cytokine-overexpressing islets elicited specific responses: β cells exhibited increased expression of genes associated with reactive oxidative species-mediated stress and endoplasmic reticulum stress, surveilling and infiltrating macrophages were increased, and β cell death was promoted. This powerful and versatile model system can be used for modeling, analysis and therapy development of diseases with an underlying inflammatory etiology.
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    Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
    (Springer Nature, 2023) Tobias, Deirdre K.; Merino, Jordi; Ahmad, Abrar; Aiken, Catherine; Benham, Jamie L.; Bodhini, Dhanasekaran; Clark, Amy L.; Colclough, Kevin; Corcoy, Rosa; Cromer, Sara J.; Duan, Daisy; Felton, Jamie L.; Francis, Ellen C.; Gillard, Pieter; Gingras, Véronique; Gaillard, Romy; Haider, Eram; Hughes, Alice; Ikle, Jennifer M.; Jacobsen, Laura M.; Kahkoska, Anna R.; Kettunen, Jarno L. T.; Kreienkamp, Raymond J.; Lim, Lee-Ling; Männistö, Jonna M. E.; Massey, Robert; Mclennan, Niamh-Maire; Miller, Rachel G.; Morieri, Mario Luca; Most, Jasper; Naylor, Rochelle N.; Ozkan, Bige; Patel, Kashyap Amratlal; Pilla, Scott J.; Prystupa, Katsiaryna; Raghavan, Sridharan; Rooney, Mary R.; Schön, Martin; Semnani-Azad, Zhila; Sevilla-Gonzalez, Magdalena; Svalastoga, Pernille; Takele, Wubet Worku; Tam, Claudia Ha-Ting; Thuesen, Anne Cathrine B.; Tosur, Mustafa; Wallace, Amelia S.; Wang, Caroline C.; Wong, Jessie J.; Yamamoto, Jennifer M.; Young, Katherine; Amouyal, Chloé; Andersen, Mette K.; Bonham, Maxine P.; Chen, Mingling; Cheng, Feifei; Chikowore, Tinashe; Chivers, Sian C.; Clemmensen, Christoffer; Dabelea, Dana; Dawed, Adem Y.; Deutsch, Aaron J.; Dickens, Laura T.; DiMeglio, Linda A.; Dudenhöffer-Pfeifer, Monika; Evans-Molina, Carmella; Fernández-Balsells, María Mercè; Fitipaldi, Hugo; Fitzpatrick, Stephanie L.; Gitelman, Stephen E.; Goodarzi, Mark O.; Grieger, Jessica A.; Guasch-Ferré, Marta; Habibi, Nahal; Hansen, Torben; Huang, Chuiguo; Harris-Kawano, Arianna; Ismail, Heba M.; Hoag, Benjamin; Johnson, Randi K.; Jones, Angus G.; Koivula, Robert W.; Leong, Aaron; Leung, Gloria K. W.; Libman, Ingrid M.; Liu, Kai; Long, S. Alice; Lowe, William L., Jr.; Morton, Robert W.; Motala, Ayesha A.; Onengut-Gumuscu, Suna; Pankow, James S.; Pathirana, Maleesa; Pazmino, Sofia; Perez, Dianna; Petrie, John R.; Powe, Camille E.; Quinteros, Alejandra; Jain, Rashmi; Ray, Debashree; Ried-Larsen, Mathias; Saeed, Zeb; Santhakumar, Vanessa; Kanbour, Sarah; Sarkar, Sudipa; Monaco, Gabriela S. F.; Scholtens, Denise M.; Selvin, Elizabeth; Sheu, Wayne Huey-Herng; Speake, Cate; Stanislawski, Maggie A.; Steenackers, Nele; Steck, Andrea K.; Stefan, Norbert; Støy, Julie; Taylor, Rachael; Tye, Sok Cin; Ukke, Gebresilasea Gendisha; Urazbayeva, Marzhan; Van der Schueren, Bart; Vatier, Camille; Wentworth, John M.; Hannah, Wesley; White, Sara L.; Yu, Gechang; Zhang, Yingchai; Zhou, Shao J.; Beltrand, Jacques; Polak, Michel; Aukrust, Ingvild; de Franco, Elisa; Flanagan, Sarah E.; Maloney, Kristin A.; McGovern, Andrew; Molnes, Janne; Nakabuye, Mariam; Njølstad, Pål Rasmus; Pomares-Millan, Hugo; Provenzano, Michele; Saint-Martin, Cécile; Zhang, Cuilin; Zhu, Yeyi; Auh, Sungyoung; de Souza, Russell; Fawcett, Andrea J.; Gruber, Chandra; Mekonnen, Eskedar Getie; Mixter, Emily; Sherifali, Diana; Eckel, Robert H.; Nolan, John J.; Philipson, Louis H.; Brown, Rebecca J.; Billings, Liana K.; Boyle, Kristen; Costacou, Tina; Dennis, John M.; Florez, Jose C.; Gloyn, Anna L.; Gomez, Maria F.; Gottlieb, Peter A.; Greeley, Siri Atma W.; Griffin, Kurt; Hattersley, Andrew T.; Hirsch, Irl B.; Hivert, Marie-France; Hood, Korey K.; Josefson, Jami L.; Kwak, Soo Heon; Laffel, Lori M.; Lim, Siew S.; Loos, Ruth J. F.; Ma, Ronald C. W.; Mathieu, Chantal; Mathioudakis, Nestoras; Meigs, James B.; Misra, Shivani; Mohan, Viswanathan; Murphy, Rinki; Oram, Richard; Owen, Katharine R.; Ozanne, Susan E.; Pearson, Ewan R.; Perng, Wei; Pollin, Toni I.; Pop-Busui, Rodica; Pratley, Richard E.; Redman, Leanne M.; Redondo, Maria J.; Reynolds, Rebecca M.; Semple, Robert K.; Sherr, Jennifer L.; Sims, Emily K.; Sweeting, Arianne; Tuomi, Tiinamaija; Udler, Miriam S.; Vesco, Kimberly K.; Vilsbøll, Tina; Wagner, Robert; Rich, Stephen S.; Franks, Paul W.; Pediatrics, School of Medicine
    Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.