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Search: (WFRF:(Stringham Heather M.)) pers:(Barroso Ines) pers:(Froguel Philippe) > (2014) > Impact of type 2 di...

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  • Dimas, Antigone S (author)

Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity.

  • Article/chapterEnglish2014

Publisher, publication year, extent ...

  • 2014-05-15
  • American Diabetes Association,2014

Numbers

  • LIBRIS-ID:oai:gup.ub.gu.se/196064
  • https://gup.ub.gu.se/publication/196064URI
  • https://doi.org/10.2337/db13-0949DOI
  • http://kipublications.ki.se/Default.aspx?queryparsed=id:129091865URI
  • https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-228006URI

Supplementary language notes

  • Language:English

Part of subdatabase

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  • Subject category:ref swepub-contenttype
  • Subject category:art swepub-publicationtype

Notes

  • De fem sista författarna delar sistaförfattarskapet.
  • Patients with established type 2 diabetes display both beta-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci and indices of proinsulin processing, insulin secretion and insulin sensitivity. We included data from up to 58,614 non-diabetic subjects with basal measures, and 17,327 with dynamic measures. We employed additive genetic models with adjustment for sex, age and BMI, followed by fixed-effects inverse variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (including TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without detectable change in fasting glucose. The final group contained twenty risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.

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  • Barker, Adam (author)
  • Knowles, Joshua W (author)
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  • Jackson, Anne U (author)
  • Stringham, Heather M (author)
  • Song, CiUppsala universitet,Science for Life Laboratory, SciLifeLab,Molekylär epidemiologi(Swepub:uu)ciaso492 (author)
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  • Barroso, Inês (author)
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  • Froguel, Philippe (author)
  • Meyre, David (author)
  • Schwarz, Peter E H (author)
  • Häring, Hans-Ulrich (author)
  • Smith, Ulf,1943Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för molekylär och klinisk medicin,Institute of Medicine, Department of Molecular and Clinical Medicine(Swepub:gu)xsmiul (author)
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  • Ingelsson, ErikUppsala universitet,Molekylär epidemiologi,Science for Life Laboratory, SciLifeLab(Swepub:uu)ering425 (author)
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  • MAGIC Investigators, (author)
  • Uppsala universitetScience for Life Laboratory, SciLifeLab (creator_code:org_t)

Related titles

  • In:Diabetes: American Diabetes Association63:6, s. 2158-21711939-327X0012-1797

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