A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets

Research output: Contribution to journalJournal articleResearchpeer-review

  • Jalal Taneera
  • Stefan Lang
  • Amitabh Sharma
  • Joao Fadista
  • Yuedan Zhou
  • Emma Ahlqvist
  • Valeriya Lyssenko
  • Petter Vikman
  • Ola Hansson
  • Hemang Parikh
  • Olle Korsgren
  • Arvind Soni
  • Ulrika Krus
  • Enming Zhang
  • Xing-Jun Jing
  • Jonathan L S Esguerra
  • Claes B Wollheim
  • Albert Salehi
  • Anders Rosengren
  • Erik Renström
  • Leif Groop
Close to 50 genetic loci have been associated with type 2 diabetes (T2D), but they explain only 15% of the heritability. In an attempt to identify additional T2D genes, we analyzed global gene expression in human islets from 63 donors. Using 48 genes located near T2D risk variants, we identified gene coexpression and protein-protein interaction networks that were strongly associated with islet insulin secretion and HbA(1c). We integrated our data to form a rank list of putative T2D genes, of which CHL1, LRFN2, RASGRP1, and PPM1K were validated in INS-1 cells to influence insulin secretion, whereas GPR120 affected apoptosis in islets. Expression variation of the top 20 genes explained 24% of the variance in HbA(1c) with no claim of the direction. The data present a global map of genes associated with islet dysfunction and demonstrate the value of systems genetics for the identification of genes potentially involved in T2D.
Original languageEnglish
JournalCell Metabolism
Volume16
Issue number1
Pages (from-to)122-34
Number of pages13
ISSN1550-4131
DOIs
Publication statusPublished - 3 Jul 2012

    Research areas

  • Aged, Animals, Case-Control Studies, Cell Line, Diabetes Mellitus, Type 2, Female, Gene Expression Profiling, Gene Regulatory Networks, Genome-Wide Association Study, Humans, Insulin, Islets of Langerhans, Male, Middle Aged, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Protein Interaction Maps, Rats, Receptors, G-Protein-Coupled, Systems Biology

ID: 46404026