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Plasma Lipidome and Prediction of Type 2 Diabetes in the Population-Based Malmö Diet and Cancer Cohort

Fernandez, Céline LU ; Surma, Michal A. ; Klose, Christian ; Gerl, Mathias J. ; Ottosson, Filip LU ; Ericson, Ulrika LU ; Oskolkov, Nikolay LU ; Ohro-Melander, Marju LU ; Simons, Kai and Melander, Olle LU orcid (2020) In Diabetes Care 43(2). p.366-373
Abstract

OBJECTIVE: Type 2 diabetes mellitus (T2DM) is associated with dyslipidemia, but the detailed alterations in lipid species preceding the disease are largely unknown. We aimed to identify plasma lipids associated with development of T2DM and investigate their associations with lifestyle. RESEARCH DESIGN AND METHODS: At baseline, 178 lipids were measured by mass spectrometry in 3,668 participants without diabetes from the Malmö Diet and Cancer Study. The population was randomly split into discovery (n = 1,868, including 257 incident cases) and replication (n = 1,800, including 249 incident cases) sets. We used orthogonal projections to latent structures discriminant analyses, extracted a predictive component for T2DM incidence... (More)

OBJECTIVE: Type 2 diabetes mellitus (T2DM) is associated with dyslipidemia, but the detailed alterations in lipid species preceding the disease are largely unknown. We aimed to identify plasma lipids associated with development of T2DM and investigate their associations with lifestyle. RESEARCH DESIGN AND METHODS: At baseline, 178 lipids were measured by mass spectrometry in 3,668 participants without diabetes from the Malmö Diet and Cancer Study. The population was randomly split into discovery (n = 1,868, including 257 incident cases) and replication (n = 1,800, including 249 incident cases) sets. We used orthogonal projections to latent structures discriminant analyses, extracted a predictive component for T2DM incidence (lipid-PCDM), and assessed its association with T2DM incidence using Cox regression and lifestyle factors using general linear models. RESULTS: A T2DM-predictive lipid-PCDM derived from the discovery set was independently associated with T2DM incidence in the replication set, with hazard ratio (HR) among subjects in the fifth versus first quintile of lipid-PCDM of 3.7 (95% CI 2.2-6.5). In comparison, the HR of T2DM among obese versus normal weight subjects was 1.8 (95% CI 1.2-2.6). Clinical lipids did not improve T2DM risk prediction, but adding the lipid-PCDM to all conventional T2DM risk factors increased the area under the receiver operating characteristics curve by 3%. The lipid-PCDM was also associated with a dietary risk score for T2DM incidence and lower level of physical activity. CONCLUSIONS: A lifestyle-related lipidomic profile strongly predicts T2DM development beyond current risk factors. Further studies are warranted to test if lifestyle interventions modifying this lipidomic profile can prevent T2DM.

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author
; ; ; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Diabetes Care
volume
43
issue
2
pages
8 pages
publisher
American Diabetes Association
external identifiers
  • pmid:31818810
  • scopus:85078370681
ISSN
1935-5548
DOI
10.2337/dc19-1199
language
English
LU publication?
yes
id
fb646999-f668-4b28-90b7-514538ab0770
date added to LUP
2020-02-04 16:07:11
date last changed
2024-03-20 03:50:48
@article{fb646999-f668-4b28-90b7-514538ab0770,
  abstract     = {{<p>OBJECTIVE: Type 2 diabetes mellitus (T2DM) is associated with dyslipidemia, but the detailed alterations in lipid species preceding the disease are largely unknown. We aimed to identify plasma lipids associated with development of T2DM and investigate their associations with lifestyle. RESEARCH DESIGN AND METHODS: At baseline, 178 lipids were measured by mass spectrometry in 3,668 participants without diabetes from the Malmö Diet and Cancer Study. The population was randomly split into discovery (n = 1,868, including 257 incident cases) and replication (n = 1,800, including 249 incident cases) sets. We used orthogonal projections to latent structures discriminant analyses, extracted a predictive component for T2DM incidence (lipid-PCDM), and assessed its association with T2DM incidence using Cox regression and lifestyle factors using general linear models. RESULTS: A T2DM-predictive lipid-PCDM derived from the discovery set was independently associated with T2DM incidence in the replication set, with hazard ratio (HR) among subjects in the fifth versus first quintile of lipid-PCDM of 3.7 (95% CI 2.2-6.5). In comparison, the HR of T2DM among obese versus normal weight subjects was 1.8 (95% CI 1.2-2.6). Clinical lipids did not improve T2DM risk prediction, but adding the lipid-PCDM to all conventional T2DM risk factors increased the area under the receiver operating characteristics curve by 3%. The lipid-PCDM was also associated with a dietary risk score for T2DM incidence and lower level of physical activity. CONCLUSIONS: A lifestyle-related lipidomic profile strongly predicts T2DM development beyond current risk factors. Further studies are warranted to test if lifestyle interventions modifying this lipidomic profile can prevent T2DM.</p>}},
  author       = {{Fernandez, Céline and Surma, Michal A. and Klose, Christian and Gerl, Mathias J. and Ottosson, Filip and Ericson, Ulrika and Oskolkov, Nikolay and Ohro-Melander, Marju and Simons, Kai and Melander, Olle}},
  issn         = {{1935-5548}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{366--373}},
  publisher    = {{American Diabetes Association}},
  series       = {{Diabetes Care}},
  title        = {{Plasma Lipidome and Prediction of Type 2 Diabetes in the Population-Based Malmö Diet and Cancer Cohort}},
  url          = {{http://dx.doi.org/10.2337/dc19-1199}},
  doi          = {{10.2337/dc19-1199}},
  volume       = {{43}},
  year         = {{2020}},
}