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Gender-specific pathway differences in the human serum metabolome.

ABSTRACT: The susceptibility for various diseases as well as the response to treatments differ considerably between men and women. As a basis for a gender-specific personalized healthcare, an extensive characterization of the molecular differences between the two genders is required. In the present study, we conducted a large-scale metabolomics analysis of 507 metabolic markers measured in serum of 1756 participants from the German KORA F4 study (903 females and 853 males). One-third of the metabolites show significant differences between males and females. A pathway analysis revealed strong differences in steroid metabolism, fatty acids and further lipids, a large fraction of amino acids, oxidative phosphorylation, purine metabolism and gamma-glutamyl dipeptides. We then extended this analysis by a network-based clustering approach. Metabolite interactions were estimated using Gaussian graphical models to get an unbiased, fully data-driven metabolic network representation. This approach is not limited to possibly arbitrary pathway boundaries and can even include poorly or uncharacterized metabolites. The network analysis revealed several strongly gender-regulated submodules across different pathways. Finally, a gender-stratified genome-wide association study was performed to determine whether the observed gender differences are caused by dimorphisms in the effects of genetic polymorphisms on the metabolome. With only a single genome-wide significant hit, our results suggest that this scenario is not the case. In summary, we report an extensive characterization and interpretation of gender-specific differences of the human serum metabolome, providing a broad basis for future analyses.

SUBMITTER: Krumsiek J

PROVIDER: S-EPMC4605991 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Gender-specific pathway differences in the human serum metabolome.

Krumsiek Jan J Mittelstrass Kirstin K Do Kieu Trinh KT Stückler Ferdinand F Ried Janina J Adamski Jerzy J Peters Annette A Illig Thomas T Kronenberg Florian F Friedrich Nele N Nauck Matthias M Pietzner Maik M Mook-Kanamori Dennis O DO Suhre Karsten K Gieger Christian C Grallert Harald H Theis Fabian J FJ Kastenmüller Gabi G

Metabolomics : Official journal of the Metabolomic Society 20150804 6

The susceptibility for various diseases as well as the response to treatments differ considerably between men and women. As a basis for a gender-specific personalized healthcare, an extensive characterization of the molecular differences between the two genders is required. In the present study, we conducted a large-scale metabolomics analysis of 507 metabolic markers measured in serum of 1756 participants from the German KORA F4 study (903 females and 853 males). One-third of the metabolites sh ...[more]

PMID: 26491425

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Project description:ObjectiveTo compare the variability in metabolomes between the serum and follicular fluid, as well as across 3 dominant follicles.DesignProspective cohort study.SettingAn academic fertility clinic in the northeastern United States, 2005-2015.PatientsOne hundred thirty-five women undergoing in vitro fertilization treatment who provided a serum sample during ovarian stimulation and up to 3 follicular fluid samples during oocyte retrieval.Intervention(s)None.Main outcome measure(s)Samples were analyzed using liquid chromatography with high-resolution mass spectrometry and 2 chromatography columns (C18 hydrophobic negative and hydrophilic interaction chromatography [HILIC] positive). We calculated overall, feature-specific, and subject-specific correlation coefficients to describe how strongly the intensity of overlapping metabolic features were associated between the serum and follicular fluid and between the 1st-2nd, 1st-3rd, and 2nd-3rd follicles. Feature-specific correlations were adjusted for age, body mass index, infertility diagnosis, ovarian stimulation protocol, and year.Result(s)From the C18-negative column and the high-resolution mass spectrometry, 7,830 serum features and 10,790 follicular fluid features were detected in ≥20% of samples. After screening retention times and checking for 1:1 matching, 1,928 features overlapped between the 2 metabolomes. From the HILIC-positive column and the high-resolution mass spectrometry, after applying the same exclusion criteria, there were 9,074 serum features, 5,542 follicular fluid features, and 1,149 features that overlapped. When comparing the feature intensity of overlapping metabolites in the serum and the follicular fluid, the overall (C18, 0.45; HILIC, 0.63), median feature-specific (C18, 0.35; HILIC, 0.37), and median subject-specific (C18, 0.42; HILIC, 0.59) correlations were low to moderate. In contrast, among the overlapping features across all 3 follicles, the overall (C18, all 0.99; HILIC, all 0.99), median feature-specific (C18, 0.74-0.81; HILIC, 0.79-0.85), and median subject-specific (C18, 0.88-0.89; HILIC, 0.90-0.91) correlations between follicular fluid metabolomics features within a woman were high.Conclusion(s)We observed minimal overlap and weak-to-moderate correlation between metabolomic features in the serum and follicular fluid but a large overlap and strong correlation between metabolomic features across follicles within a woman. The follicular fluid appears to represent a novel matrix, distinct from serum, which may be a rich source of biologic predictors of female fertility and reproductive outcomes.

Dataset Information

Gender-specific pathway differences in the human serum metabolome.

Publications

Gender-specific pathway differences in the human serum metabolome.

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