Intrapersonal Stability of Plasma Metabolomic Profiles over 10 Years among Women

In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in t...

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Main Authors: Avila-Pacheco, J. (Author), Clish, C.B (Author), Deik, A. (Author), Eliassen, A.H (Author), Hu, F.B (Author), Jeanfavre, S. (Author), Rexrode, K.M (Author), Rosner, B. (Author), Wittenbecher, C. (Author), Zeleznik, O.A (Author)
Format: Article
Language:English
Published: MDPI 2022
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Online Access:View Fulltext in Publisher
LEADER 02981nam a2200289Ia 4500
001 10.3390-metabo12050372
008 220706s2022 CNT 000 0 und d
020 |a 22181989 (ISSN) 
245 1 0 |a Intrapersonal Stability of Plasma Metabolomic Profiles over 10 Years among Women 
260 0 |b MDPI  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3390/metabo12050372 
520 3 |a In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in the Nurses’ Health Study (NHS): the primary dataset included 1880 women with 1184 repeated samples donated 10 years apart while the secondary dataset included 1456 women with 488 repeated samples donated 10 years apart. We quantified plasma metabolomics using two liquid chromatography mass spectrometry platforms (lipids and polar metabolites) at the Broad Institute (Cambridge, MA, USA). Intra-class correlations (ICC) were used to estimate long-term (10 years) within-person stability of metabolites and were calculated as the proportion of the total variability (within-person + between-person) attributable to between-person variability. Within-person variability was estimated among participants who donated two blood samples approximately 10 years apart while between-person variability was estimated among all participants. In the primary dataset, the median ICC was 0.43 (1st quartile (Q1): 0.36; 3rd quartile (Q3): 0.50) among known metabolites and 0.41 (Q1: 0.34; Q3: 0.48) among unknown metabolite features. The three most stable metabolites were N6,N6-dimethyllysine (ICC = 0.82), dimethylguanidino valerate (ICC = 0.72), and N-acetylornithine (ICC = 0.72). The three least stable metabolites were palmitoylethanolamide (ICC = 0.05), ectoine (ICC = 0.09), and trimethylamine-N-oxide (ICC = 0.16). Results in the secondary dataset were similar (Spearman correlation = 0.87) to corresponding results in the primary dataset. Within-person stability over 10 years is reasonable for lipid, lipid-related, and polar metabolites, and varies by metabolite class. Additional studies are required to estimate within-person stability over 10 years of other metabolites groups. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. 
650 0 4 |a lipids and lipid-related metabolites 
650 0 4 |a polar metabolites 
650 0 4 |a unknown metabolite features 
650 0 4 |a within-person stability 
700 1 0 |a Avila-Pacheco, J.  |e author 
700 1 0 |a Clish, C.B.  |e author 
700 1 0 |a Deik, A.  |e author 
700 1 0 |a Eliassen, A.H.  |e author 
700 1 0 |a Hu, F.B.  |e author 
700 1 0 |a Jeanfavre, S.  |e author 
700 1 0 |a Rexrode, K.M.  |e author 
700 1 0 |a Rosner, B.  |e author 
700 1 0 |a Wittenbecher, C.  |e author 
700 1 0 |a Zeleznik, O.A.  |e author 
773 |t Metabolites