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

IF 4.1 Q2 ENDOCRINOLOGY & METABOLISM
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
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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.

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。
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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.
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