Go to JCI Insight
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Alerts
  • Advertising/recruitment
  • Subscribe
  • Contact
  • Current Issue
  • Past Issues
  • By specialty
    • COVID-19
    • Cardiology
    • Gastroenterology
    • Immunology
    • Metabolism
    • Nephrology
    • Neuroscience
    • Oncology
    • Pulmonology
    • Vascular biology
    • All ...
  • Videos
    • Conversations with Giants in Medicine
    • Author's Takes
  • Reviews
    • View all reviews ...
    • 100th Anniversary of Insulin's Discovery (Jan 2021)
    • Hypoxia-inducible factors in disease pathophysiology and therapeutics (Oct 2020)
    • Latency in Infectious Disease (Jul 2020)
    • Immunotherapy in Hematological Cancers (Apr 2020)
    • Big Data's Future in Medicine (Feb 2020)
    • Mechanisms Underlying the Metabolic Syndrome (Oct 2019)
    • Reparative Immunology (Jul 2019)
    • View all review series ...
  • Viewpoint
  • Collections
    • Recently published
    • In-Press Preview
    • Commentaries
    • Concise Communication
    • Editorials
    • Viewpoint
    • Top read articles
  • Clinical Medicine
  • JCI This Month
    • Current issue
    • Past issues

  • Current issue
  • Past issues
  • Specialties
  • Reviews
  • Review series
  • Conversations with Giants in Medicine
  • Author's Takes
  • Recently published
  • In-Press Preview
  • Commentaries
  • Concise Communication
  • Editorials
  • Viewpoint
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Alerts
  • Advertising/recruitment
  • Subscribe
  • Contact

Usage Information

Gene loci associated with insulin secretion in islets from nondiabetic mice
Mark P. Keller, … , Gary A. Churchill, Alan D. Attie
Mark P. Keller, … , Gary A. Churchill, Alan D. Attie
Published July 25, 2019
Citation Information: J Clin Invest. 2019;129(10):4419-4432. https://doi.org/10.1172/JCI129143.
View: Text | PDF
Research Article Cell biology Genetics

Gene loci associated with insulin secretion in islets from nondiabetic mice

  • Text
  • PDF
Abstract

Genetic susceptibility to type 2 diabetes is primarily due to β cell dysfunction. However, a genetic study to directly interrogate β cell function ex vivo has never been previously performed. We isolated 233,447 islets from 483 Diversity Outbred (DO) mice maintained on a Western-style diet, and measured insulin secretion in response to a variety of secretagogues. Insulin secretion from DO islets ranged greater than 1000-fold even though none of the mice were diabetic. The insulin secretory response to each secretagogue had a unique genetic architecture; some of the loci were specific for one condition, whereas others overlapped. Human loci that are syntenic to many of the insulin secretion quantitative trait loci (QTL) from mice are associated with diabetes-related SNPs in human genome-wide association studies. We report on 3 genes, Ptpn18, Hunk, and Zfp148, where the phenotype predictions from the genetic screen were fulfilled in our studies of transgenic mouse models. These 3 genes encode a nonreceptor type protein tyrosine phosphatase, a serine/threonine protein kinase, and a Krϋppel-type zinc-finger transcription factor, respectively. Our results demonstrate that genetic variation in insulin secretion that can lead to type 2 diabetes is discoverable in nondiabetic individuals.

Authors

Mark P. Keller, Mary E. Rabaglia, Kathryn L. Schueler, Donnie S. Stapleton, Daniel M. Gatti, Matthew Vincent, Kelly A. Mitok, Ziyue Wang, Takanao Ishimura, Shane P. Simonett, Christopher H. Emfinger, Rahul Das, Tim Beck, Christina Kendziorski, Karl W. Broman, Brian S. Yandell, Gary A. Churchill, Alan D. Attie

×

Usage data is cumulative from January 2020 through January 2021.

Usage JCI PMC
Text version 2,078 205
PDF 288 213
Figure 420 0
Supplemental data 413 21
Citation downloads 95 0
Totals 3,294 439
Total Views 3,733

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement
Follow JCI:
Copyright © 2021 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

Sign up for email alerts