Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine

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.; 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.

doi:10.1038/s41591-023-02502-5

Cited by 63 publications

(9 citation statements)

References 59 publications

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“… 33 In fact, improvement of physical health with precision medicine approach has been specifically stated as a priority in a recent patient-led consensus statement. 34 Indeed, the high-risk approach has been adopted routinely for decades to facilitate cardiometabolic risk prediction in the general population (e.g., QRISK in the UK which is in NICE guidelines). Yet, existing tools are inaccurate for young people with psychosis and will lead to further health inequalities in this population.…”

Section: Discussionmentioning

confidence: 99%

Assessing the generalisability of the psychosis metabolic risk calculator (PsyMetRiC) for young people with first-episode psychosis with validation in a Hong Kong Chinese Han population: a 4-year follow-up study

Tse,

Khandaker,

Zhou

et al. 2024

The Lancet Regional Health - Western Pacific

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Section: Discussionmentioning

confidence: 99%

Assessing the generalisability of the psychosis metabolic risk calculator (PsyMetRiC) for young people with first-episode psychosis with validation in a Hong Kong Chinese Han population: a 4-year follow-up study

Tse,

Khandaker,

Zhou

et al. 2024

The Lancet Regional Health - Western Pacific

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“…This review is written on behalf of the American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) precision Medicine in Diabetes Initiative (PMDI) as part of a comprehensive evidence evaluation in support of the 2nd International Consensus Report on Precision Diabetes Medicine 43 . This study therefore aimed to investigate the effect of intervention characteristics on GDM prevention using the TIDieR framework to inform the implementation of precision prevention in healthcare and community settings.…”

Section: Introductionmentioning

confidence: 99%

Effective interventions in preventing gestational diabetes mellitus: A systematic review and meta-analysis

Takele,

Vesco,

Josefson

et al. 2024

Commun Med

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Background Lifestyle choices, metformin, and dietary supplements may prevent GDM, but the effect of intervention characteristics has not been identified. This review evaluated intervention characteristics to inform the implementation of GDM prevention interventions. Methods Ovid, MEDLINE/PubMed, and EMBASE databases were searched. The Template for Intervention Description and Replication (TIDieR) framework was used to examine intervention characteristics (who, what, when, where, and how). Subgroup analysis was performed by intervention characteristics. Results 116 studies involving 40,940 participants are included. Group-based physical activity interventions (RR 0.66; 95% CI 0.46, 0.95) reduce the incidence of GDM compared with individual or mixed (individual and group) delivery format (subgroup p-value = 0.04). Physical activity interventions delivered at healthcare facilities reduce the risk of GDM (RR 0.59; 95% CI 0.49, 0.72) compared with home-based interventions (subgroup p-value = 0.03). No other intervention characteristics impact the effectiveness of all other interventions. Conclusions Dietary, physical activity, diet plus physical activity, metformin, and myoinositol interventions reduce the incidence of GDM compared with control interventions. Group and healthcare facility-based physical activity interventions show better effectiveness in preventing GDM than individual and community-based interventions. Other intervention characteristics (e.g. utilization of e-health) don’t impact the effectiveness of lifestyle interventions, and thus, interventions may require consideration of the local context.

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“…The ADA/EASD PMDI includes global thought leaders in precision diabetes medicine who are working to address the burgeoning need for better diabetes prevention and care through precision medicine 3 . This T1D Diagnostics-focused Systematic Review is written on behalf of the ADA/EASD PMDI as part of a comprehensive evidence evaluation in support of the 2nd International Consensus Report on Precision Diabetes Medicine 4 .…”

Section: Introductionmentioning

confidence: 99%

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review

Felton,

Redondo,

Oram

et al. 2024

Commun Med

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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.

show abstract

Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine

Cited by 63 publications

References 59 publications

Assessing the generalisability of the psychosis metabolic risk calculator (PsyMetRiC) for young people with first-episode psychosis with validation in a Hong Kong Chinese Han population: a 4-year follow-up study

Assessing the generalisability of the psychosis metabolic risk calculator (PsyMetRiC) for young people with first-episode psychosis with validation in a Hong Kong Chinese Han population: a 4-year follow-up study

Effective interventions in preventing gestational diabetes mellitus: A systematic review and meta-analysis

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review

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