English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The plasma metabolome is associated with multiple phenotypes and diseases. However, a systematic study investigating clinical determinants that control the metabolome has not yet been conducted. In the present study, therefore, we aimed to identify the major determinants of the plasma metabolite profile. We used ultra-high performance liquid chromatography (UHPLC) coupled to quadrupole time of flight mass spectrometry (QTOF-MS) to determine 106 metabolites in plasma samples from 2503 subjects in a cross-sectional study. We investigated the correlation structure of the metabolite profiles and generated uncorrelated metabolite factors using principal component analysis (PCA) and varimax rotation. Finally, we investigated associations between these factors and 34 clinical covariates. Our results suggest that liver function, followed by kidney function and insulin resistance show the strongest associations with the plasma metabolite profile. The association of specific phenotypes with several components may suggest multiple independent metabolic mechanisms, which is further supported by the composition of the associated factors.

Population-Level Analysis to Determine Parameters That Drive Variation in the Plasma Metabolite Profiles