Structural Basis and Genotype-Phenotype Correlations of INSR Mutations Causing Severe Insulin Resistance.
Jun HosoeHiroko KadowakiFuyuki MiyaKatsuya AizuTomoyuki KawamuraIchiro MiyataKenichi SatomuraTakeru ItoKazuo HaraMasaki TanakaHiroyuki IshiuraShoji TsujiKen SuzukiMinaka TakakuraKeith A BoroevichTatsuhiko TsunodaToshimasa YamauchiNobuhiro ShojimaTakashi KadowakiPublished in: Diabetes (2017)
The insulin receptor (INSR) gene was analyzed in four patients with severe insulin resistance, revealing five novel mutations and a deletion that removed exon 2. A patient with Donohue syndrome (DS) had a novel p.V657F mutation in the second fibronectin type III domain (FnIII-2), which contains the α-β cleavage site and part of the insulin-binding site. The mutant INSR was expressed in Chinese hamster ovary cells, revealing that it reduced insulin proreceptor processing and impaired activation of downstream signaling cascades. Using online databases, we analyzed 82 INSR missense mutations and demonstrated that mutations causing DS were more frequently located in the FnIII domains than those causing the milder type A insulin resistance (P = 0.016). In silico structural analysis revealed that missense mutations predicted to severely impair hydrophobic core formation and stability of the FnIII domains all caused DS, whereas those predicted to produce localized destabilization and to not affect folding of the FnIII domains all caused the less severe Rabson-Mendenhall syndrome. These results suggest the importance of the FnIII domains, provide insight into the molecular mechanism of severe insulin resistance, will aid early diagnosis, and will provide potential novel targets for treating extreme insulin resistance.
Keyphrases
- insulin resistance
- type diabetes
- adipose tissue
- high fat diet
- glycemic control
- metabolic syndrome
- polycystic ovary syndrome
- skeletal muscle
- type iii
- early onset
- high fat diet induced
- case report
- structural basis
- gene expression
- climate change
- genome wide
- machine learning
- signaling pathway
- autism spectrum disorder
- social media
- cell death
- big data
- cell cycle arrest
- single cell
- health information
- copy number
- molecular dynamics simulations
- weight loss
- human health
- transcription factor