Cargando…
Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes
AIMS/HYPOTHESIS: We sought to subtype South East Asian patients with type 2 diabetes by de novo cluster analysis on clinical variables, and to determine whether the novel subgroups carry distinct genetic and lipidomic features as well as differential cardio-renal risks. METHODS: Analysis by k-means...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630229/ https://www.ncbi.nlm.nih.gov/pubmed/35763031 http://dx.doi.org/10.1007/s00125-022-05741-2 |
_version_ | 1784823556186570752 |
---|---|
author | Wang, Jiexun Liu, Jian-Jun Gurung, Resham L. Liu, Sylvia Lee, Janus M, Yiamunaa Ang, Keven Shao, Yi Ming Tang, Justin I-Shing Benke, Peter I. Torta, Federico Wenk, Markus R. Tavintharan, Subramaniam Tang, Wern Ee Sum, Chee Fang Lim, Su Chi |
author_facet | Wang, Jiexun Liu, Jian-Jun Gurung, Resham L. Liu, Sylvia Lee, Janus M, Yiamunaa Ang, Keven Shao, Yi Ming Tang, Justin I-Shing Benke, Peter I. Torta, Federico Wenk, Markus R. Tavintharan, Subramaniam Tang, Wern Ee Sum, Chee Fang Lim, Su Chi |
author_sort | Wang, Jiexun |
collection | PubMed |
description | AIMS/HYPOTHESIS: We sought to subtype South East Asian patients with type 2 diabetes by de novo cluster analysis on clinical variables, and to determine whether the novel subgroups carry distinct genetic and lipidomic features as well as differential cardio-renal risks. METHODS: Analysis by k-means algorithm was performed in 687 participants with recent-onset diabetes in Singapore. Genetic risk for beta cell dysfunction was assessed by polygenic risk score. We used a discovery–validation approach for the lipidomics study. Risks for cardio-renal complications were studied by survival analysis. RESULTS: Cluster analysis identified three novel diabetic subgroups, i.e. mild obesity-related diabetes (MOD, 45%), mild age-related diabetes with insulin insufficiency (MARD-II, 36%) and severe insulin-resistant diabetes with relative insulin insufficiency (SIRD-RII, 19%). Compared with the MOD subgroup, MARD-II had a higher polygenic risk score for beta cell dysfunction. The SIRD-RII subgroup had higher levels of sphingolipids (ceramides and sphingomyelins) and glycerophospholipids (phosphatidylethanolamine and phosphatidylcholine), whereas the MARD-II subgroup had lower levels of sphingolipids and glycerophospholipids but higher levels of lysophosphatidylcholines. Over a median of 7.3 years follow-up, the SIRD-RII subgroup had the highest risks for incident heart failure and progressive kidney disease, while the MARD-II subgroup had moderately elevated risk for kidney disease progression. CONCLUSIONS/INTERPRETATION: Cluster analysis on clinical variables identified novel subgroups with distinct genetic, lipidomic signatures and varying cardio-renal risks in South East Asian participants with type 2 diabetes. Our study suggests that this easily actionable approach may be adapted in other ethnic populations to stratify the heterogeneous type 2 diabetes population for precision medicine. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-022-05741-2. |
format | Online Article Text |
id | pubmed-9630229 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-96302292022-11-04 Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes Wang, Jiexun Liu, Jian-Jun Gurung, Resham L. Liu, Sylvia Lee, Janus M, Yiamunaa Ang, Keven Shao, Yi Ming Tang, Justin I-Shing Benke, Peter I. Torta, Federico Wenk, Markus R. Tavintharan, Subramaniam Tang, Wern Ee Sum, Chee Fang Lim, Su Chi Diabetologia Article AIMS/HYPOTHESIS: We sought to subtype South East Asian patients with type 2 diabetes by de novo cluster analysis on clinical variables, and to determine whether the novel subgroups carry distinct genetic and lipidomic features as well as differential cardio-renal risks. METHODS: Analysis by k-means algorithm was performed in 687 participants with recent-onset diabetes in Singapore. Genetic risk for beta cell dysfunction was assessed by polygenic risk score. We used a discovery–validation approach for the lipidomics study. Risks for cardio-renal complications were studied by survival analysis. RESULTS: Cluster analysis identified three novel diabetic subgroups, i.e. mild obesity-related diabetes (MOD, 45%), mild age-related diabetes with insulin insufficiency (MARD-II, 36%) and severe insulin-resistant diabetes with relative insulin insufficiency (SIRD-RII, 19%). Compared with the MOD subgroup, MARD-II had a higher polygenic risk score for beta cell dysfunction. The SIRD-RII subgroup had higher levels of sphingolipids (ceramides and sphingomyelins) and glycerophospholipids (phosphatidylethanolamine and phosphatidylcholine), whereas the MARD-II subgroup had lower levels of sphingolipids and glycerophospholipids but higher levels of lysophosphatidylcholines. Over a median of 7.3 years follow-up, the SIRD-RII subgroup had the highest risks for incident heart failure and progressive kidney disease, while the MARD-II subgroup had moderately elevated risk for kidney disease progression. CONCLUSIONS/INTERPRETATION: Cluster analysis on clinical variables identified novel subgroups with distinct genetic, lipidomic signatures and varying cardio-renal risks in South East Asian participants with type 2 diabetes. Our study suggests that this easily actionable approach may be adapted in other ethnic populations to stratify the heterogeneous type 2 diabetes population for precision medicine. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-022-05741-2. Springer Berlin Heidelberg 2022-06-28 2022 /pmc/articles/PMC9630229/ /pubmed/35763031 http://dx.doi.org/10.1007/s00125-022-05741-2 Text en © The Author(s) 2022, corrected publication 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Jiexun Liu, Jian-Jun Gurung, Resham L. Liu, Sylvia Lee, Janus M, Yiamunaa Ang, Keven Shao, Yi Ming Tang, Justin I-Shing Benke, Peter I. Torta, Federico Wenk, Markus R. Tavintharan, Subramaniam Tang, Wern Ee Sum, Chee Fang Lim, Su Chi Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes |
title | Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes |
title_full | Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes |
title_fullStr | Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes |
title_full_unstemmed | Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes |
title_short | Clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in Asian patients with recent-onset type 2 diabetes |
title_sort | clinical variable-based cluster analysis identifies novel subgroups with a distinct genetic signature, lipidomic pattern and cardio-renal risks in asian patients with recent-onset type 2 diabetes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630229/ https://www.ncbi.nlm.nih.gov/pubmed/35763031 http://dx.doi.org/10.1007/s00125-022-05741-2 |
work_keys_str_mv | AT wangjiexun clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT liujianjun clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT gurungreshaml clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT liusylvia clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT leejanus clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT myiamunaa clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT angkeven clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT shaoyiming clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT tangjustinishing clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT benkepeteri clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT tortafederico clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT wenkmarkusr clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT tavintharansubramaniam clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT tangwernee clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT sumcheefang clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes AT limsuchi clinicalvariablebasedclusteranalysisidentifiesnovelsubgroupswithadistinctgeneticsignaturelipidomicpatternandcardiorenalrisksinasianpatientswithrecentonsettype2diabetes |