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Lipidomic risk scores are independent of polygenic risk scores and can predict incidence of diabetes and cardiovascular disease in a large population cohort

Lauber, Chris (author)
Lipotype GmbH,Hannover Medical School
Gerl, Mathias J. (author)
Lipotype GmbH
Klose, Christian (author)
Lipotype GmbH
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Ottosson, Filip (author)
Lund University,Lunds universitet,Kardiovaskulär forskning - hypertoni,Forskargrupper vid Lunds universitet,Cardiovascular Research - Hypertension,Lund University Research Groups
Melander, Olle (author)
Lund University,Lunds universitet,Kardiovaskulär forskning - hypertoni,Forskargrupper vid Lunds universitet,Cardiovascular Research - Hypertension,Lund University Research Groups
Simons, Kai (author)
Lipotype GmbH
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 (creator_code:org_t)
2022-03-03
2022
English.
In: PLoS Biology. - : Public Library of Science (PLoS). - 1544-9173 .- 1545-7885. ; 20:3
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Type 2 diabetes (T2D) and cardiovascular disease (CVD) represent significant disease burdens for most societies and susceptibility to these diseases is strongly influenced by diet and lifestyle. Physiological changes associated with T2D or CVD, such has high blood pressure and cholesterol and glucose levels in the blood, are often apparent prior to disease incidence. Here we integrated genetics, lipidomics, and standard clinical diagnostics to assess future T2D and CVD risk for 4,067 participants from a large prospective population-based cohort, the Malmö Diet and Cancer-Cardiovascular Cohort. By training Ridge regression-based machine learning models on the measurements obtained at baseline when the individuals were healthy, we computed several risk scores for T2D and CVD incidence during up to 23 years of follow-up. We used these scores to stratify the participants into risk groups and found that a lipidomics risk score based on the quantification of 184 plasma lipid concentrations resulted in a 168% and 84% increase of the incidence rate in the highest risk group and a 77% and 53% decrease of the incidence rate in lowest risk group for T2D and CVD, respectively, compared to the average case rates of 13.8% and 22.0%. Notably, lipidomic risk correlated only marginally with polygenic risk, indicating that the lipidome and genetic variants may constitute largely independent risk factors for T2D and CVD. Risk stratification was further improved by adding standard clinical variables to the model, resulting in a case rate of 51.0% and 53.3% in the highest risk group for T2D and CVD, respectively. The participants in the highest risk group showed significantly altered lipidome compositions affecting 167 and 157 lipid species for T2D and CVD, respectively. Our results demonstrated that a subset of individuals at high risk for developing T2D or CVD can be identified years before disease incidence. The lipidomic risk, which is derived from only one single mass spectrometric measurement that is cheap and fast, is informative and could extend traditional risk assessment based on clinical assays.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Endokrinologi och diabetes (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Endocrinology and Diabetes (hsv//eng)

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By the author/editor
Lauber, Chris
Gerl, Mathias J.
Klose, Christian
Ottosson, Filip
Melander, Olle
Simons, Kai
About the subject
MEDICAL AND HEALTH SCIENCES
MEDICAL AND HEAL ...
and Clinical Medicin ...
and Endocrinology an ...
Articles in the publication
PLoS Biology
By the university
Lund University

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