Long term conservation of human metabolic phenotypes and link to heritability

Noha A Yousri, Gabi Kastenmüller, Christian Gieger, So-Youn Shin, Idil Erte, Cristina Menni, Annette Peters, Christa Meisinger, Robert P Mohney, Thomas Illig, Jerzy Adamski, Nicole Soranzo, Tim D Spector, Karsten Suhre

Research output: Contribution to journalArticle (Academic Journal)peer-review

55 Citations (Scopus)

Abstract

Changes in an individual's human metabolic phenotype (metabotype) over time can be indicative of disorder-related modifications. Studies covering several months to a few years have shown that metabolic profiles are often specific for an individual. This "metabolic individuality" and detected changes may contribute to personalized approaches in human health care. However, it is not clear whether such individual metabotypes persist over longer time periods. Here we investigate the conservation of metabotypes characterized by 212 different metabolites of 818 participants from the Cooperative Health Research in the Region of Augsburg; Germany population, taken within a 7-year time interval. For replication, we used paired samples from 83 non-related individuals from the TwinsUK study. Results indicated that over 40 % of all study participants could be uniquely identified after 7 years based on their metabolic profiles alone. Moreover, 95 % of the study participants showed a high degree of metabotype conservation (>70 %) whereas the remaining 5 % displayed major changes in their metabolic profiles over time. These latter individuals were likely to have undergone important biochemical changes between the two time points. We further show that metabolite conservation was positively associated with heritability (rank correlation 0.74), although there were some notable exceptions. Our results suggest that monitoring changes in metabotypes over several years can trace changes in health status and may provide indications for disease onset. Moreover, our study findings provide a general reference for metabotype conservation over longer time periods that can be used in biomarker discovery studies.

Original languageEnglish
Pages (from-to)1005-1017
Number of pages13
JournalMetabolomics
Volume10
Issue number5
DOIs
Publication statusPublished - 2014

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