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Plasma Lipidome and Prediction of Type 2 Diabetes in the Population-Based Malmö Diet and Cancer Cohort.
Fernandez, Céline; Surma, Michal A; Klose, Christian; Gerl, Mathias J; Ottosson, Filip; Ericson, Ulrika; Oskolkov, Nikolay; Ohro-Melander, Marju; Simons, Kai; Melander, Olle.
Affiliation
  • Fernandez C; Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden celine.fernandez@med.lu.se.
  • Surma MA; Lukasiewicz Research Network-PORT Polish Center for Technology Development, Wroclaw, Poland.
  • Klose C; Lipotype GmbH, Dresden, Germany.
  • Gerl MJ; Lipotype GmbH, Dresden, Germany.
  • Ottosson F; Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.
  • Ericson U; Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.
  • Oskolkov N; Department of Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Lund University, Lund, Sweden.
  • Ohro-Melander M; Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.
  • Simons K; Lipotype GmbH, Dresden, Germany.
  • Melander O; Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.
Diabetes Care ; 43(2): 366-373, 2020 02.
Article in En | MEDLINE | ID: mdl-31818810
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.
Subject(s)

Full text: 1 Database: MEDLINE Main subject: Diabetes Mellitus, Type 2 / Lipids / Neoplasms Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Diabetes Care Year: 2020 Type: Article Affiliation country: Sweden

Full text: 1 Database: MEDLINE Main subject: Diabetes Mellitus, Type 2 / Lipids / Neoplasms Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Diabetes Care Year: 2020 Type: Article Affiliation country: Sweden