Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review

ADA/EASD PMDI

doi:10.1038/s43856-023-00357-y

Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review

ADA/EASD PMDI

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Background: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification. Methods: To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. Results: We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings. Conclusions: While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.

Original language	English (US)
Article number	130
Journal	Communications Medicine
Volume	3
Issue number	1
DOIs	https://doi.org/10.1038/s43856-023-00357-y
State	Published - Dec 2023

Funding

We thank Krister Aronsson and Maria Bjorklund from Lund University for assistance with database searches and Russell de Souza from McMaster University for advice on critical appraisal. The ADA/EASD Precision Diabetes Medicine Initiative, within which this work was conducted, has received the following support: The Covidence license was funded by Lund University (Sweden) for which technical support was provided by Maria Bj\u00F6rklund and Krister Aronsson (Faculty of Medicine Library, Lund University, Sweden). Administrative support was provided by Lund University (Malm\u00F6, Sweden), the University of Chicago (IL, USA), and the American Diabetes Association (Washington D.C., USA). The Novo Nordisk Foundation (Hellerup, Denmark) provided grant support for in-person writing group meetings (P.I.: L Phillipson, University of Chicago, IL). J.F.: DiabDocs K12 program 1K12DK133995-01 (DiMeglio, Maahs PIs), The Leona M. & Harry B. Helmsley CharitableTrust Grant #2307-06126 (Felton PI). KG: The Leona M. and Harry B. Helmsley Charitable Trust and Sanford Health. R.A.O.: RAO had a UK MRC confidence in concept award to develop a type 1 diabetes GRS biochip with Randox R&D and has ongoing research funding from Randox; and has research funding from a Diabetes UK Harry Keen Fellowship (16/0005529), National Institute of Diabetes and Digestive and Kidney Diseases grants (NIH R01 DK121843\u201301 and U01DK127382\u201301), JDRF (3-SRA-2019\u2013827-S-B, 2-SRA-2022\u20131261-S-B, 2-SRA-2002\u20131259-S-B, 3-SRA-2022\u20131241-S-B, and 2-SRA-2022\u20131258-M-B), and The Larry M and Leona B Helmsley Charitable Trust; and is supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the National Institutes for Health Research or the Department of Health and Social Care. L.A.D.: NIH for TrialNet U01DK106993/6163-1082-00-BO, DiabDocs K12 program 1K12DK133995-01, CTSI UL1TR001108-01, C.E.M.: R01DK093954, R01DK127236, U01DK127786, R01DK127308, and UC4DK104166, U54DK118638, P30 P30 DK097512), a US Department of Veterans Affairs Merit Award (I01BX001733), grants from the JDRF (3-IND-2022-1235-I-X) and Helmsley Charitable Trust (2207-05392), and gifts from the Sigma Beta Sorority, the Ball Brothers Foundation, and the George and Frances Ball Foundation. HI: K23DK129799; RJ: NIH R03-DK127472 and The Leona M. and Harry B. Helmsley Charitable Trust (2103-05094); S.A.L.: NIH NIAID R01 AI141952 (PI), NIH NCI R01 CA231226 (Other support), NIH NIAID 1 R01HL149676 (Other support), NIH NIDDK 1UC4DK117483 (subaward), JDRF 3-SRA-2019-851-M-B; S.O.G.: NIH R01 DK121843\u201301; S.R.: R01 DK122586, THE LEONA M AND HARRY B HELMSLEY CHARITABLE TRUST 2204-05134; J.W.: JDRF 2-SRA-2022-1282-M-X, 3-SRA-2022-1095-M-B, 4-SRA-2022-1246-M-N, 3-SRA-2023-1374-M-N.; M.R.: NIH NIDDK R01DK124395 and R01DK121843; R01DK121929A1, R01DK133881, U01DK127786, U01 DK127382 (E.K.S.). Effort from this grant (to E.K.S., H.I., J.F.) is also supported by Grant 2021258 from the Doris Duke Charitable Foundation through the COVID-19 Fund to Retain Clinical Scientists collaborative grant program and was made possible through the support of Grant 62288 from the John Templeton Foundation. No funders played any role in the design, implementation, or writing of this review. E.K.S. has received compensation for educational lectures from Medscape, ADA, and MJH Life Sciences and as a consultant for DRI Healthcare. C.E.M. reported serving on advisory boards for Provention Bio, Isla Technologies, MaiCell Technologies, Avotres, DiogenyX, and Neurodon; receiving in-kind research support from Bristol Myers Squibb and Nimbus Pharmaceuticals; and receiving investigator-initiated grants from Lilly Pharmaceuticals and Astellas Pharmaceuticals. L.A.D. reports research support to institutions from Dompe, Lilly, Mannkind, Provention, Zealand, and consulting relationships with Abata and Vertex. R.A.O. had a UK MRC Confidence in concept grant to develop a T1D GRS biochip with Randox Ltd and has ongoing research funding from Randox R & D. No other authors report any relevant conflicts of interest.

ASJC Scopus subject areas

Public Health, Environmental and Occupational Health
Internal Medicine
Epidemiology
Medicine (miscellaneous)
Assessment and Diagnosis

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s43856-023-00357-y

Cite this

@article{4edd6e378eb143398d19537f98672d1c,

title = "Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review",

abstract = "Background: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification. Methods: To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. Results: We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings. Conclusions: While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.",

author = "{ADA/EASD PMDI} and Felton, {Jamie L.} and Griffin, {Kurt J.} and Oram, {Richard A.} and Cate Speake and Long, {S. Alice} and Suna Onengut-Gumuscu and Rich, {Stephen S.} and Monaco, {Gabriela S.F.} and Carmella Evans-Molina and DiMeglio, {Linda A.} and Ismail, {Heba M.} and Steck, {Andrea K.} and Dana Dabelea and Johnson, {Randi K.} and Marzhan Urazbayeva and Stephen Gitelman and Wentworth, {John M.} and Redondo, {Maria J.} and Sims, {Emily K.} and Franks, {Paul W.} and Rich, {Stephen S.} and Robert Wagner and Tina Vilsb{\o}ll and Vesco, {Kimberly K.} and Udler, {Miriam S.} and Tiinamaija Tuomi and Arianne Sweeting and Sims, {Emily K.} and Sherr, {Jennifer L.} and Semple, {Robert K.} and Reynolds, {Rebecca M.} and Redman, {Leanne M.} and Pratley, {Richard E.} and Rodica Pop-Busui and Pollin, {Toni I.} and Wei Perng and Pearson, {Ewan R.} and Ozanne, {Susan E.} and Owen, {Katharine R.} and Richard Oram and Rinki Murphy and Viswanathan Mohan and Shivani Misra and Meigs, {James B.} and Nestoras Mathioudakis and Chantal Mathieu and Josefson, {Jami L.} and Scholtens, {Denise M.} and Lowe, {William L.} and Katherine Young",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2023.",

year = "2023",

month = dec,

doi = "10.1038/s43856-023-00357-y",

language = "English (US)",

volume = "3",

journal = "Communications Medicine",

issn = "2730-664X",

publisher = "Springer Nature",

number = "1",

}

TY - JOUR

T1 - Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention

T2 - a systematic review

AU - ADA/EASD PMDI

AU - Felton, Jamie L.

AU - Griffin, Kurt J.

AU - Oram, Richard A.

AU - Speake, Cate

AU - Long, S. Alice

AU - Onengut-Gumuscu, Suna

AU - Rich, Stephen S.

AU - Monaco, Gabriela S.F.

AU - Evans-Molina, Carmella

AU - DiMeglio, Linda A.

AU - Ismail, Heba M.

AU - Steck, Andrea K.

AU - Dabelea, Dana

AU - Johnson, Randi K.

AU - Urazbayeva, Marzhan

AU - Gitelman, Stephen

AU - Wentworth, John M.

AU - Redondo, Maria J.

AU - Sims, Emily K.

AU - Franks, Paul W.

AU - Rich, Stephen S.

AU - Wagner, Robert

AU - Vilsbøll, Tina

AU - Vesco, Kimberly K.

AU - Udler, Miriam S.

AU - Tuomi, Tiinamaija

AU - Sweeting, Arianne

AU - Sims, Emily K.

AU - Sherr, Jennifer L.

AU - Semple, Robert K.

AU - Reynolds, Rebecca M.

AU - Redman, Leanne M.

AU - Pratley, Richard E.

AU - Pop-Busui, Rodica

AU - Pollin, Toni I.

AU - Perng, Wei

AU - Pearson, Ewan R.

AU - Ozanne, Susan E.

AU - Owen, Katharine R.

AU - Oram, Richard

AU - Murphy, Rinki

AU - Mohan, Viswanathan

AU - Misra, Shivani

AU - Meigs, James B.

AU - Mathioudakis, Nestoras

AU - Mathieu, Chantal

AU - Josefson, Jami L.

AU - Scholtens, Denise M.

AU - Lowe, William L.

AU - Young, Katherine

PY - 2023/12

Y1 - 2023/12

N2 - Background: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification. Methods: To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. Results: We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings. Conclusions: While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.

AB - Background: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification. Methods: To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. Results: We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings. Conclusions: While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.

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DO - 10.1038/s43856-023-00357-y

M3 - Article

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AN - SCOPUS:85173487646

SN - 2730-664X

VL - 3

JO - Communications Medicine

JF - Communications Medicine

IS - 1

M1 - 130

ER -

Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review

Abstract

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ASJC Scopus subject areas

UN SDGs

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