Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium (PREDICT)

Michael E. McCullough; Lisa R. Letourneau-Freiberg; Rochelle N. Naylor; Siri Atma W. Greeley; David T. Broome; Mustafa Tosur; Raymond J. Kreienkamp; Erin Cobry; Neda Rasouli; Toni I. Pollin; Miriam S. Udler; Liana K. Billings; Cyrus Desouza; Carmella Evans-Molina; Suzi Birz; Brian Furner; Michael Watkins; Kaitlyn Ott; Samuel L. Volchenboum; Louis H. Philipson

doi:10.1177/19322968241310896

Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium (PREDICT)

Michael E. McCullough, Lisa R. Letourneau-Freiberg, Rochelle N. Naylor, Siri Atma W. Greeley, David T. Broome, Mustafa Tosur, Raymond J. Kreienkamp, Erin Cobry, Neda Rasouli, Toni I. Pollin, Miriam S. Udler, Liana K. Billings, Cyrus Desouza, Carmella Evans-Molina, Suzi Birz, Brian Furner, Michael Watkins, Kaitlyn Ott, Samuel L. Volchenboum, Louis H. Philipson

Research output: Contribution to journal › Comment/debate › peer-review

1 Scopus citations

Abstract

Monogenic diabetes mellitus (MDM) is a group of relatively rare disorders caused by pathogenic variants in key genes that result in hyperglycemia. Lack of identified cases, along with absent data standards, and limited collaboration across institutions have hindered research progress. To address this, the UChicago Monogenic Diabetes Registry (UCMDMR) and UChicago Data for the Common Good (D4CG) created a national consortium of MDM research institutions called the PREcision DIabetes ConsorTium (PREDICT). Following the D4CG model, PREDICT has successfully established a multicenter MDM data commons. PREDICT has created a consensus data dictionary that will be utilized to address critical gaps in understanding of these rare types of diabetes. This approach may be useful for other rare conditions that would benefit from access to harmonized pooled data.

Original language	English (US)
Journal	Journal of Diabetes Science and Technology
DOIs	https://doi.org/10.1177/19322968241310896
State	Accepted/In press - 2025

Keywords

data commons
data dictionary
data governance
data sharing
data standards
monogenic diabetes

ASJC Scopus subject areas

Internal Medicine
Endocrinology, Diabetes and Metabolism
Bioengineering
Biomedical Engineering

Access to Document

10.1177/19322968241310896

Cite this

McCullough, M. E., Letourneau-Freiberg, L. R., Naylor, R. N., Greeley, S. A. W., Broome, D. T., Tosur, M., Kreienkamp, R. J., Cobry, E., Rasouli, N., Pollin, T. I., Udler, M. S., Billings, L. K., Desouza, C., Evans-Molina, C., Birz, S., Furner, B., Watkins, M., Ott, K., Volchenboum, S. L., & Philipson, L. H. (Accepted/In press). Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium (PREDICT). Journal of Diabetes Science and Technology. https://doi.org/10.1177/19322968241310896

McCullough, ME, Letourneau-Freiberg, LR, Naylor, RN, Greeley, SAW, Broome, DT, Tosur, M, Kreienkamp, RJ, Cobry, E, Rasouli, N, Pollin, TI, Udler, MS, Billings, LK, Desouza, C, Evans-Molina, C, Birz, S, Furner, B, Watkins, M, Ott, K, Volchenboum, SL & Philipson, LH 2025, 'Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium (PREDICT)', Journal of Diabetes Science and Technology. https://doi.org/10.1177/19322968241310896

@article{751f81774d784a5f95e271501e51e65c,

title = "Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium (PREDICT)",

abstract = "Monogenic diabetes mellitus (MDM) is a group of relatively rare disorders caused by pathogenic variants in key genes that result in hyperglycemia. Lack of identified cases, along with absent data standards, and limited collaboration across institutions have hindered research progress. To address this, the UChicago Monogenic Diabetes Registry (UCMDMR) and UChicago Data for the Common Good (D4CG) created a national consortium of MDM research institutions called the PREcision DIabetes ConsorTium (PREDICT). Following the D4CG model, PREDICT has successfully established a multicenter MDM data commons. PREDICT has created a consensus data dictionary that will be utilized to address critical gaps in understanding of these rare types of diabetes. This approach may be useful for other rare conditions that would benefit from access to harmonized pooled data.",

keywords = "data commons, data dictionary, data governance, data sharing, data standards, monogenic diabetes",

author = "McCullough, {Michael E.} and Letourneau-Freiberg, {Lisa R.} and Naylor, {Rochelle N.} and Greeley, {Siri Atma W.} and Broome, {David T.} and Mustafa Tosur and Kreienkamp, {Raymond J.} and Erin Cobry and Neda Rasouli and Pollin, {Toni I.} and Udler, {Miriam S.} and Billings, {Liana K.} and Cyrus Desouza and Carmella Evans-Molina and Suzi Birz and Brian Furner and Michael Watkins and Kaitlyn Ott and Volchenboum, {Samuel L.} and Philipson, {Louis H.}",

note = "Publisher Copyright: {\textcopyright} 2025 Diabetes Technology Society.",

year = "2025",

doi = "10.1177/19322968241310896",

language = "English (US)",

journal = "Journal of Diabetes Science and Technology",

issn = "1932-2968",

publisher = "SAGE Publications Inc.",

}

TY - JOUR

T1 - Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons

T2 - The Precision Diabetes Consortium (PREDICT)

AU - McCullough, Michael E.

AU - Letourneau-Freiberg, Lisa R.

AU - Naylor, Rochelle N.

AU - Greeley, Siri Atma W.

AU - Broome, David T.

AU - Tosur, Mustafa

AU - Kreienkamp, Raymond J.

AU - Cobry, Erin

AU - Rasouli, Neda

AU - Pollin, Toni I.

AU - Udler, Miriam S.

AU - Billings, Liana K.

AU - Desouza, Cyrus

AU - Evans-Molina, Carmella

AU - Birz, Suzi

AU - Furner, Brian

AU - Watkins, Michael

AU - Ott, Kaitlyn

AU - Volchenboum, Samuel L.

AU - Philipson, Louis H.

PY - 2025

Y1 - 2025

N2 - Monogenic diabetes mellitus (MDM) is a group of relatively rare disorders caused by pathogenic variants in key genes that result in hyperglycemia. Lack of identified cases, along with absent data standards, and limited collaboration across institutions have hindered research progress. To address this, the UChicago Monogenic Diabetes Registry (UCMDMR) and UChicago Data for the Common Good (D4CG) created a national consortium of MDM research institutions called the PREcision DIabetes ConsorTium (PREDICT). Following the D4CG model, PREDICT has successfully established a multicenter MDM data commons. PREDICT has created a consensus data dictionary that will be utilized to address critical gaps in understanding of these rare types of diabetes. This approach may be useful for other rare conditions that would benefit from access to harmonized pooled data.

AB - Monogenic diabetes mellitus (MDM) is a group of relatively rare disorders caused by pathogenic variants in key genes that result in hyperglycemia. Lack of identified cases, along with absent data standards, and limited collaboration across institutions have hindered research progress. To address this, the UChicago Monogenic Diabetes Registry (UCMDMR) and UChicago Data for the Common Good (D4CG) created a national consortium of MDM research institutions called the PREcision DIabetes ConsorTium (PREDICT). Following the D4CG model, PREDICT has successfully established a multicenter MDM data commons. PREDICT has created a consensus data dictionary that will be utilized to address critical gaps in understanding of these rare types of diabetes. This approach may be useful for other rare conditions that would benefit from access to harmonized pooled data.

KW - data commons

KW - data dictionary

KW - data governance

KW - data sharing

KW - data standards

KW - monogenic diabetes

UR - http://www.scopus.com/inward/record.url?scp=85214681220&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85214681220&partnerID=8YFLogxK

U2 - 10.1177/19322968241310896

DO - 10.1177/19322968241310896

M3 - Comment/debate

C2 - 39781649

AN - SCOPUS:85214681220

SN - 1932-2968

JO - Journal of Diabetes Science and Technology

JF - Journal of Diabetes Science and Technology

ER -

Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium (PREDICT)

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this