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

IF 4.1 Q2 ENDOCRINOLOGY & METABOLISM Journal of Diabetes Science and Technology Pub Date : 2025-01-09 DOI:10.1177/19322968241310896
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
{"title":"Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium (PREDICT).","authors":"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","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241310896"},"PeriodicalIF":4.1000,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11713946/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Diabetes Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/19322968241310896","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过创建数据共享推进单基因糖尿病研究和临床护理:精准糖尿病联盟(PREDICT)。
单基因糖尿病(Monogenic diabetes mellitus, MDM)是一组相对罕见的疾病,由关键基因的致病变异导致高血糖。缺乏确定的病例、缺乏数据标准以及机构间有限的合作阻碍了研究进展。为了解决这个问题,芝加哥大学单基因糖尿病注册中心(UCMDMR)和芝加哥大学公益数据中心(D4CG)创建了一个全国MDM研究机构联盟,称为精准糖尿病联盟(PREDICT)。按照D4CG模型,PREDICT成功地建立了一个多中心MDM数据共享。PREDICT已经创建了一个共识数据字典,将用于解决理解这些罕见类型糖尿病的关键空白。这种方法可能对其他罕见的情况有用,这些情况将受益于访问协调的池数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Diabetes Science and Technology
Journal of Diabetes Science and Technology Medicine-Internal Medicine
CiteScore
7.50
自引率
12.00%
发文量
148
期刊介绍: The Journal of Diabetes Science and Technology (JDST) is a bi-monthly, peer-reviewed scientific journal published by the Diabetes Technology Society. JDST covers scientific and clinical aspects of diabetes technology including glucose monitoring, insulin and metabolic peptide delivery, the artificial pancreas, digital health, precision medicine, social media, cybersecurity, software for modeling, physiologic monitoring, technology for managing obesity, and diagnostic tests of glycation. The journal also covers the development and use of mobile applications and wireless communication, as well as bioengineered tools such as MEMS, new biomaterials, and nanotechnology to develop new sensors. Articles in JDST cover both basic research and clinical applications of technologies being developed to help people with diabetes.
期刊最新文献
How to Provide Additional Oversight to Ensure That Remote Patient Monitoring for People With Diabetes is Being Used and Billed Appropriately. Impact of Recording Interval in Continuous Glucose Monitoring on Calculating the Metrics of Glycemic Control. Effectiveness of Mobile Health Applications for Cardiometabolic Risk Reduction in Urban and Rural India: A Pilot, Randomized Controlled Study. Efficacy and Safety of an Electronic Glycemic Management System for Optimizing Insulin Therapy in Noncritical Patients With Diabetes: A Randomized Trial. Using One-Shot Prompting of Non-Fine-Tuned Commercial Artificial Intelligence to Assess Nutrients from Photographs of Japanese Meals.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1