Metabolic regulation in progression to autoimmune diabetes

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Sysi-Aho, Marko
dc.contributor.author Ermolov, Andrey
dc.contributor.author Gopalacharyulu, Peddinti V.
dc.contributor.author Tripathi, Abhishek
dc.contributor.author Seppänen-Laakso, Tuulikki
dc.contributor.author Maukonen, Johanna
dc.contributor.author Mattila, Ismo
dc.contributor.author Ruohonen, Suvi T.
dc.contributor.author Vähätalo, Laura
dc.contributor.author Yetukuri, Laxman
dc.contributor.author Härkönen, Taina
dc.contributor.author Lindfors, Erno
dc.contributor.author Nikkilä, Janne
dc.contributor.author Ilonen, Jorma
dc.contributor.author Simell, Olli
dc.contributor.author Saarela, Maria
dc.contributor.author Knip, Mikael
dc.contributor.author Kaski, Samuel
dc.contributor.author Savontaus, Eriika
dc.contributor.author Oresic, Matej
dc.date.accessioned 2017-10-15T20:41:23Z
dc.date.available 2017-10-15T20:41:23Z
dc.date.issued 2011
dc.identifier.citation Sysi-Aho , M , Ermolov , A , Gopalacharyulu , P V , Tripathi , A , Seppänen-Laakso , T , Maukonen , J , Mattila , I , Ruohonen , S T , Vähätalo , L , Yetukuri , L , Härkönen , T , Lindfors , E , Nikkilä , J , Ilonen , J , Simell , O , Saarela , M , Knip , M , Kaski , S , Savontaus , E & Oresic , M 2011 , ' Metabolic regulation in progression to autoimmune diabetes ' PLOS COMPUTATIONAL BIOLOGY , vol 7 , no. 10 , e1002257 , pp. 1-16 . DOI: 10.1371/journal.pcbi.1002257 en
dc.identifier.issn 1553-734X
dc.identifier.issn 1553-7358
dc.identifier.other PURE UUID: a00dab3c-4ce5-4a02-ba18-c54e36146e5d
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/metabolic-regulation-in-progression-to-autoimmune-diabetes(a00dab3c-4ce5-4a02-ba18-c54e36146e5d).html
dc.identifier.other PURE LINK: http://dx.doi.org/10.1371/journal.pcbi.1002257
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/14909482/journal.pcbi.1002257.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/28258
dc.description VK: airc hiit
dc.description.abstract Recent evidence from serum metabolomics indicates that specific metabolic disturbances precede β-cell autoimmunity in humans and can be used to identify those children who subsequently progress to type 1 diabetes. The mechanisms behind these disturbances are unknown. Here we show the specificity of the pre-autoimmune metabolic changes, as indicated by their conservation in a murine model of type 1 diabetes. We performed a study in non-obese prediabetic (NOD) mice which recapitulated the design of the human study and derived the metabolic states from longitudinal lipidomics data. We show that female NOD mice who later progress to autoimmune diabetes exhibit the same lipidomic pattern as prediabetic children. These metabolic changes are accompanied by enhanced glucose-stimulated insulin secretion, normoglycemia, upregulation of insulinotropic amino acids in islets, elevated plasma leptin and adiponectin, and diminished gut microbial diversity of the Clostridium leptum group. Together, the findings indicate thatautoimmune diabetes is preceded by a state of increased metabolic demands on the islets resulting in elevated insulin secretion and suggest alternative metabolic related pathways as therapeutic targets to prevent diabetes. en
dc.format.extent 1-16
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries PLOS COMPUTATIONAL BIOLOGY en
dc.relation.ispartofseries Volume 7, issue 10 en
dc.rights openAccess en
dc.subject.other 113 Computer and information sciences en
dc.subject.other 213 Electronic, automation and communications engineering, electronics en
dc.subject.other 112 Statistics and probability en
dc.subject.other 5141 Sociology en
dc.subject.other 515 Psychology en
dc.subject.other 518 Media and communications en
dc.title Metabolic regulation in progression to autoimmune diabetes en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Computer Science
dc.subject.keyword 113 Computer and information sciences
dc.subject.keyword 213 Electronic, automation and communications engineering, electronics
dc.subject.keyword 112 Statistics and probability
dc.subject.keyword 5141 Sociology
dc.subject.keyword 515 Psychology
dc.subject.keyword 518 Media and communications
dc.identifier.urn URN:NBN:fi:aalto-201710157118
dc.identifier.doi 10.1371/journal.pcbi.1002257
dc.type.version publishedVersion


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