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Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study
Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comp...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Diabetes Association
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564413/ https://www.ncbi.nlm.nih.gov/pubmed/34376475 http://dx.doi.org/10.2337/db20-1281 |
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author | Slieker, Roderick C. Donnelly, Louise A. Fitipaldi, Hugo Bouland, Gerard A. Giordano, Giuseppe N. Åkerlund, Mikael Gerl, Mathias J. Ahlqvist, Emma Ali, Ashfaq Dragan, Iulian Elders, Petra Festa, Andreas Hansen, Michael K. van der Heijden, Amber A. Mansour Aly, Dina Kim, Min Kuznetsov, Dmitry Mehl, Florence Klose, Christian Simons, Kai Pavo, Imre Pullen, Timothy J. Suvitaival, Tommi Wretlind, Asger Rossing, Peter Lyssenko, Valeriya Legido Quigley, Cristina Groop, Leif Thorens, Bernard Franks, Paul W. Ibberson, Mark Rutter, Guy A. Beulens, Joline W.J. ’t Hart, Leen M. Pearson, Ewan R. |
author_facet | Slieker, Roderick C. Donnelly, Louise A. Fitipaldi, Hugo Bouland, Gerard A. Giordano, Giuseppe N. Åkerlund, Mikael Gerl, Mathias J. Ahlqvist, Emma Ali, Ashfaq Dragan, Iulian Elders, Petra Festa, Andreas Hansen, Michael K. van der Heijden, Amber A. Mansour Aly, Dina Kim, Min Kuznetsov, Dmitry Mehl, Florence Klose, Christian Simons, Kai Pavo, Imre Pullen, Timothy J. Suvitaival, Tommi Wretlind, Asger Rossing, Peter Lyssenko, Valeriya Legido Quigley, Cristina Groop, Leif Thorens, Bernard Franks, Paul W. Ibberson, Mark Rutter, Guy A. Beulens, Joline W.J. ’t Hart, Leen M. Pearson, Ewan R. |
author_sort | Slieker, Roderick C. |
collection | PubMed |
description | Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic (N = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease. |
format | Online Article Text |
id | pubmed-8564413 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Diabetes Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-85644132021-11-15 Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study Slieker, Roderick C. Donnelly, Louise A. Fitipaldi, Hugo Bouland, Gerard A. Giordano, Giuseppe N. Åkerlund, Mikael Gerl, Mathias J. Ahlqvist, Emma Ali, Ashfaq Dragan, Iulian Elders, Petra Festa, Andreas Hansen, Michael K. van der Heijden, Amber A. Mansour Aly, Dina Kim, Min Kuznetsov, Dmitry Mehl, Florence Klose, Christian Simons, Kai Pavo, Imre Pullen, Timothy J. Suvitaival, Tommi Wretlind, Asger Rossing, Peter Lyssenko, Valeriya Legido Quigley, Cristina Groop, Leif Thorens, Bernard Franks, Paul W. Ibberson, Mark Rutter, Guy A. Beulens, Joline W.J. ’t Hart, Leen M. Pearson, Ewan R. Diabetes Genetics/Genomes/Proteomics/Metabolomics Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic (N = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease. American Diabetes Association 2021-11 2021-08-10 /pmc/articles/PMC8564413/ /pubmed/34376475 http://dx.doi.org/10.2337/db20-1281 Text en © 2021 by the American Diabetes Association https://www.diabetesjournals.org/content/licenseReaders may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at https://www.diabetesjournals.org/content/license. |
spellingShingle | Genetics/Genomes/Proteomics/Metabolomics Slieker, Roderick C. Donnelly, Louise A. Fitipaldi, Hugo Bouland, Gerard A. Giordano, Giuseppe N. Åkerlund, Mikael Gerl, Mathias J. Ahlqvist, Emma Ali, Ashfaq Dragan, Iulian Elders, Petra Festa, Andreas Hansen, Michael K. van der Heijden, Amber A. Mansour Aly, Dina Kim, Min Kuznetsov, Dmitry Mehl, Florence Klose, Christian Simons, Kai Pavo, Imre Pullen, Timothy J. Suvitaival, Tommi Wretlind, Asger Rossing, Peter Lyssenko, Valeriya Legido Quigley, Cristina Groop, Leif Thorens, Bernard Franks, Paul W. Ibberson, Mark Rutter, Guy A. Beulens, Joline W.J. ’t Hart, Leen M. Pearson, Ewan R. Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study |
title | Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study |
title_full | Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study |
title_fullStr | Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study |
title_full_unstemmed | Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study |
title_short | Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study |
title_sort | distinct molecular signatures of clinical clusters in people with type 2 diabetes: an imi-rhapsody study |
topic | Genetics/Genomes/Proteomics/Metabolomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564413/ https://www.ncbi.nlm.nih.gov/pubmed/34376475 http://dx.doi.org/10.2337/db20-1281 |
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