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A conserved complex lipid signature marks human muscle aging and responds to short-term exercise

Nature Aging (2024)Cite this article

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Abstract

Studies in preclinical models suggest that complex lipids, such as phospholipids, play a role in the regulation of longevity. However, identification of universally conserved complex lipid changes that occur during aging, and how these respond to interventions, is lacking. Here, to comprehensively map how complex lipids change during aging, we profiled ten tissues in young versus aged mice using a lipidomics platform. Strikingly, from >1,200 unique lipids, we found a tissue-wide accumulation of bis(monoacylglycero)phosphate (BMP) during mouse aging. To investigate translational value, we assessed muscle tissue of young and older people, and found a similar marked BMP accumulation in the human aging lipidome. Furthermore, we found that a healthy-aging intervention consisting of moderate-to-vigorous exercise was able to lower BMP levels in postmenopausal female research participants. Our work implicates complex lipid biology as central to aging, identifying a conserved aging lipid signature of BMP accumulation that is modifiable upon a short-term healthy-aging intervention.

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Fig. 1: Lipid classes measured in mouse tissues.
Fig. 2: BMP accumulation is a cross-tissue lipidomic signature of aging.
Fig. 3: BMP accumulation across tissues in aged mice.
Fig. 4: Age-related changes in lipid biosynthesis across tissues for lipid classes.
Fig. 5: Lysosomal and mitochondrial enzyme activity levels with age and BMP increases with age in an independent mouse cohort.
Fig. 6: BMP accumulation in female and male participants.
Fig. 7: Reduction of BMPs following exercise intervention in humans.

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Data availability

Lipidomics data are available as Supplementary Information accompanying this article as both summary statistics and processed abundance values (see Supplementary Tables 1–8). Specifically, the mouse ten-tissue aging lipidome is available in Supplementary Table 1, the female muscle aging lipidome is available in Supplementary Table 4, the man muscle aging lipidome is available in Supplementary Table 5, and the exercise intervention muscle lipidome is available in Supplementary Table 6. Physiological data from the human cohorts have been reported in our previous studies as part of a different analysis29,30. All other data supporting the findings of this study are available either in additional Supplementary tables or from the corresponding authors upon reasonable request.

Code availability

Code supporting the findings of this study is available from the corresponding authors upon reasonable request.

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Acknowledgements

Work in the R.H.H. group is financially supported by an ERC starting grant (no. 638290), by a VIDI grant from ZonMw (no. 91715305) and by the Velux Stiftung (no. 1063). G.E.J. is supported by a VENI grant from ZonMw, and AGEM Talent and Development grants. The project was supported by a Longevity Impetus Grant from Norn Group (to G.E.J. and R.H.H.). Human interventions were further financed by the TIFN research program Mitochondrial Health (ALWTF.2015.5) and the Netherlands Organization for Scientific Research (NWO). The funders had no role in data collection, analysis or decision to publish or in preparation of the paper.

Author information

Authors and Affiliations

  1. Laboratory Genetic Metabolic Diseases, Amsterdam UMC location, University of Amsterdam, Amsterdam, the Netherlands

    Georges E. Janssens, Marte Molenaars, Katharina Herzog, Martin A. T. Vervaart, Hyung L. Elfrink, Eric J. M. Wever, Bauke V. Schomakers, Simone W. Denis, Hans R. Waterham, Mia L. Pras-Raves, Michel van Weeghel, Sanne van der Rijt, Frédéric M. Vaz & Riekelt H. Houtkooper

  2. Amsterdam Gastroenterology, Endocrinology and Metabolism, Amsterdam, the Netherlands

    Georges E. Janssens, Marte Molenaars, Katharina Herzog, Hans R. Waterham, Sanne van der Rijt, Frédéric M. Vaz & Riekelt H. Houtkooper

  3. Department of Nutrition and Human Movement Sciences, School for Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University Medical Centre, Maastricht, the Netherlands

    Lotte Grevendonk, Carlijn M. E. Remie, Joris Hoeks & Patrick Schrauwen

  4. TI Food and Nutrition, Wageningen, the Netherlands

    Lotte Grevendonk, Joris Hoeks & Patrick Schrauwen

  5. Core Facility Metabolomics, Amsterdam UMC location, University of Amsterdam, Amsterdam, the Netherlands

    Martin A. T. Vervaart, Hyung L. Elfrink, Eric J. M. Wever, Bauke V. Schomakers, Mia L. Pras-Raves, Michel van Weeghel & Frédéric M. Vaz

  6. Epidemiology and Data Science, Amsterdam UMC location, University of Amsterdam, Amsterdam, the Netherlands

    Eric J. M. Wever, Mia L. Pras-Raves, Antoine H. C. van Kampen, Aldo Jongejan & Perry D. Moerland

  7. Amsterdam Public Health Methodology, Amsterdam, the Netherlands

    Antoine H. C. van Kampen, Aldo Jongejan & Perry D. Moerland

  8. Amsterdam Infection and Immunity, Inflammatory Diseases, Amsterdam, the Netherlands

    Antoine H. C. van Kampen, Aldo Jongejan & Perry D. Moerland

  9. Pathology Department, Amsterdam UMC location, University of Amsterdam, Amsterdam, the Netherlands

    Alessandra Tammaro, Loes M. Butter, Sanne van der Rijt & Sandrine Florquin

  10. Amsterdam Infection and Immunity, Amsterdam, the Netherlands

    Alessandra Tammaro, Loes M. Butter & Sandrine Florquin

  11. Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands

    Riekelt H. Houtkooper

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  1. Georges E. Janssens
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  2. Marte Molenaars
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  3. Katharina Herzog
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Contributions

G.E.J. and R.H.H. conceived and designed lipidomics experiments and analyses; R.H.H. designed and performed mouse experiments; L.G., J.H., C.M.E.R. and P.S. designed and performed human experiments; G.E.J., K.H., M.A.T.V., B.V.S., H.L.E., E.J.M.W., P.D.M., H.R.W., M.L.P.-R., M.v.W., A.H.C.v.K., F.M.V., A.J., A.T., L.M.B., S.F. and M.M. performed lipidomics sample preparation, data generation, bioinformatics or consultation; S.W.D. and S.v.d.R. performed enzymatic assays and statistics; G.E.J. designed and performed analyses and integration of all datasets; G.E.J. and R.H.H. interpreted the data and wrote the paper with contributions from all authors.

Corresponding authors

Correspondence to Georges E. Janssens, Frédéric M. Vaz or Riekelt H. Houtkooper.

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Nature Aging thanks Luigi Ferrucci, Jørn Wulff Helge and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Characteristics of cohorts used in this study.

Cohorts are shown for both the Aging study (pertaining to Fig. 6) and Sitless study (pertaining to Fig. 7). * Values are averages (mean) ± standard deviation (SD). Sex data are presented as the number of participants. Source data can be found in the original study cohort descriptions, see Grevendonk et al.29 and Remie et al.30.

Extended Data Fig. 2 Comparison of lipid changes in muscle biopsies of aging men and women.

a, Principal component analysis (PCA) of muscle lipidomes of either men (top panel) or women (bottom panel) from this study. b, correlation between the fold change of lipids induced by aging in either women (y-axis) or men (x-axis) shows significant correlation of age-related lipid changes (r = 0.53, p = 1.66e-111, Pearson’s correlation). c, Volcano plot highlighting significantly altered BMP species in men reveals accumulation of many BMP lipid species. The horizontal line indicates significance (p < 0.05) where significance was determined using an empirical Bayes moderated t-test (two sided). d, Fisher′s exact test (one sided) showing enrichment of individual BMPs in the significantly accumulated fraction of lipids (p = 1e-4), pertaining to panel c. e, comparison of lipid changes between men and women where changes are evaluated as p values in –log10 scale, multiplied by the sign of the fold change (such that depleted lipids are having a negative value and accumulating lipids a positive value). BMPs significantly accumulated in both men and women are highlighted in red. Significance was determined using a Student’s t test (two sided). f, Top Venn diagram: overlap of significantly accumulated lipids in men and women, used for bottom Venn diagram, left circle. Bottom Venn diagram: overlap of lipids accumulated in both men and women and BMPs, used for Fisher’s exact test (one sided). Reveals enrichment of BMPs in the fraction of lipids accumulating in common between men and women (p = 2e-05). g-h, Assessment of all lipid classes for enrichment of lipid species in the depleted fraction of changes (Fisher′s exact test, one sided) in g, women and h, men. Corresponds to main Fig. 3d,e. For source data file see: Supplementary Data Table 4 (women) and 5 (men).

Extended Data Fig. 3 Human intervention lipidome with and without randomization scheme in statistical analysis.

Assessment of the human intervention lipidome at the lipid class level, both without (x axis) and with (y axis) taking into account the order in which the participants underwent a regimen. Scatterplots compare the fold changes (log2 scale) of a, exercise vs sit, b, sitless vs sit, and c, exercise vs sitless derived from both statistical comparisons (where significance was determined using an empirical Bayes moderated t-test, two sided). High Pearson’s correlations observed between both statistical approaches (>0.9) and significance values (p < e-10) indicates that the order in which a participant underwent an intervention did not greatly impact the lipidomics analyses. For Source Data file see Supplementary Data Table 7.

Supplementary information

Supplementary Information

Lipidomicstandard.org reporting summaries for (1) aging mouse, (2) aging human (man and woman) and (3) exercise intervention lipidomics data.

Reporting Summary

Supplementary Table 1

Mouse aging lipidomics data (for Fig. 1 and Extended Data Fig. 1).

Supplementary Table 2

Mouse pathway lipidomics data (for Fig. 32).

Supplementary Table 3

Mouse enzyme assay data (for Extended Data Fig. 3).

Supplementary Table 4

Female aging lipidomics data (for Fig. 3 and Extended Data Fig. 5).

Supplementary Table 5

Male aging lipidomics data (also for Fig. 3 and Extended Data Fig. 5)

Supplementary Table 6

Exercise intervention lipidomics data (for Fig. 4).

Supplementary Table 7

Exercise intervention washout comparison (for Extended Data Fig. 6).

Supplementary Table 8

Pooled control in lipidomics with coefficient of variation measures per lipid species (for Methods section).

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Janssens, G.E., Molenaars, M., Herzog, K. et al. A conserved complex lipid signature marks human muscle aging and responds to short-term exercise. Nat Aging (2024). https://doi.org/10.1038/s43587-024-00595-2

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