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Metabolic characterization of menopause: cross-sectional and longitudinal evidence
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Abstract
BACKGROUND: Women who experience menopause are at higher cardiometabolic risk and often display adverse changes in metabolic biomarkers compared with pre-menopausal women. It remains elusive whether the changes in cardiometabolic biomarkers during the menopausal transition are due to ovarian aging or chronological aging. Well-conducted longitudinal studies are required to determine this. The aim of this study was to explore the cross-sectional and longitudinal associations of reproductive status, defined according to the 2012 Stages of Reproductive Aging Workshop criteria, with 74 metabolic biomarkers, and establish whether any associations are independent of age-related changes. METHODS: We determined cross-sectional associations of reproductive status with metabolic profiling in 3,312 UK midlife women. In a subgroup of 1,492 women who had repeat assessments after 2.5 years, we assessed how the change in reproductive status was associated with the changes in metabolic biomarkers. Metabolic profiles were measured by high-throughput quantitative nuclear magnetic resonance metabolomics. In longitudinal analyses, we compared the change in metabolic biomarkers for each reproductive-status category change to that of the reference of being pre-menopausal at both time points. As all women aged by a similar amount during follow-up, these analyses contribute to distinguishing age-related changes from those related to change in reproductive status. RESULTS: Consistent cross-sectional and longitudinal associations of menopause with a wide range of metabolic biomarkers were observed, suggesting the transition to menopause induces multiple metabolic changes independent of chronological aging. The metabolic changes included increased concentrations of very small very low-density lipoproteins, intermediate-density lipoproteins, low-density lipoproteins (LDLs), remnant, and LDL cholesterol, and reduced LDL particle size, all toward an atherogenic lipoprotein profile. Increased inflammation was suggested via an inflammatory biomarker, glycoprotein acetyls, but not via C-reactive protein. Also, levels of glutamine and albumin increased during the transition. Most of these metabolic changes seen at the time of becoming post-menopausal remained or became slightly stronger during the post-menopausal years. CONCLUSIONS: The transition to post-menopause has effects on multiple circulating metabolic biomarkers, over and above the underlying age trajectory. The adverse changes in multiple apolipoprotein-B-containing lipoprotein subclasses and increased inflammation may underlie women's increased cardiometabolic risk in their post-menopausal years.
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“Hormonal patterns during the luteal phase of the menstrual cycle also show changes with age, with greater absences of ovulatory cycles, while reductions in luteal phase progesterone become more common [107–109].”
From International society of sports nutrition position stand: nutritional concerns of the female athlete (2023) · cites this paper as [109]
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Cites
Mostly Harmless Econometrics: An Empiricist's Companion
Angrist, J. D., & Pischke, J.-S. (2008) · doi:10.2307/j.ctvcm4j72 · Cited by 5,051
Boyd, A., Golding, J., Macleod, J., Lawlor, D. A., Fraser, A., Henderson, J., Molloy, L., Ness, A., Ring, S., & Davey Smith, G. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dys064 · Cited by 2,996
Self-citationCohort Profile: The Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort
Fraser, A., Macdonald-Wallis, C., Tilling, K., Boyd, A., Golding, J., Davey Smith, G., Henderson, J., Macleod, J., Molloy, L., Ness, A., et al. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dys066 · Cited by 2,494
Self-citationExecutive summary of the Stages of Reproductive Aging Workshop + 10
Harlow, S. D., Gass, M. L. S., Hall, J. E., Lobo, R. A., Maki, P. M., Rebar, R. W., Sherman, S., Sluss, P. M., & de Villiers, T. J. (2012) · Menopause The Journal of The North American Menopause Society · doi:10.1097/gme.0b013e31824d8f40 · Cited by 1,800
Harlow, S. D., Gass, M. L. S., Hall, J. E., Lobo, R. A., Maki, P. M., Rebar, R. W., Sherman, S., Sluss, P. M., de Villiers, T. J., & for the STRAW + 10 Collaborative Group (2012) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2011-3362 · Cited by 1,337
Chowdhury, R., Warnakula, S., Kunutsor, S., Crowe, F., Ward, H. A., Johnson, L., Franco, O. H., Butterworth, A. S., Forouhi, N. G., Thompson, S. G., et al. (2014) · Annals of Internal Medicine · doi:10.7326/m13-1788 · Cited by 1,139
Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis
Guasch‐Ferré, M., Hruby, A., Toledo, E., Clish, C. B., Martínez‐González, M. Á., Salas‐Salvadó, J., & Hu, F. B. (2016) · Diabetes Care · doi:10.2337/dc15-2251 · Cited by 916
Soininen, P., Kangas, A. J., Würtz, P., Suna, T., & Ala‐Korpela, M. (2015) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.114.000216 · Cited by 910
Self-citationAtsma, F., Bartelink, M.-L. E. L., Grobbee, D. E., & van der Schouw, Y. T. (2006) · Menopause · doi:10.1097/01.gme.0000218683.97338.ea · Cited by 744
Kettunen, J., Demirkan, A., Würtz, P., Draisma, H. H. M., Haller, T., Rawal, R., Vaarhorst, A., Kangas, A. J., Lyytikäinen, L.-P., Pirinen, M., et al. (2016) · Nature Communications · doi:10.1038/ncomms11122 · Cited by 738
Self-citationNelson, H. D. (2008) · The Lancet · doi:10.1016/s0140-6736(08)60346-3 · Cited by 728
Matthews, K. A., Crawford, S. L., Chae, C. U., Everson‐Rose, S. A., Sowers, M. F., Sternfeld, B., & Sutton-Tyrrell, K. (2009) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2009.10.009 · Cited by 686
Metabolite Profiling and Cardiovascular Event Risk
Würtz, P., Havulinna, A. S., Soininen, P., Tynkkynen, T., Prieto‐Merino, D., Tillin, T., Ghorbani, A., Artati, A., Wang, Q., Tiainen, M., et al. (2015) · Circulation · doi:10.1161/circulationaha.114.013116 · Cited by 680
Self-citationWürtz, P., Kangas, A. J., Soininen, P., Lawlor, D. A., Smith, G. D., & Ala‐Korpela, M. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx016 · Cited by 669
Self-citationBone Mineral Density Changes during the Menopause Transition in a Multiethnic Cohort of Women
Finkelstein, J. S., Brockwell, S. E., Mehta, V., Greendale, G. A., Sowers, M. R., Ettinger, B. B., Lo, J. C.-M., Johnston, J. M., Cauley, J. A., Danielson, M. E., et al. (2007) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2007-1876 · Cited by 625
High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism
Soininen, P., Kangas, A. J., Würtz, P., Tukiainen, T., Tynkkynen, T., Laatikainen, R., Järvelin, M., Kähönen, M. A. P., Lehtimäki, T. J., Viikari, J. S. A., et al. (2009) · The Analyst · doi:10.1039/b910205a · Cited by 591
Self-citationBranched-Chain and Aromatic Amino Acids Are Predictors of Insulin Resistance in Young Adults
Würtz, P., Soininen, P., Kangas, A. J., Rönnemaa, T., Lehtimäki, T. J., Kähönen, M. A. P., Viikari, J. S. A., Raitakari, O. T., & Ala‐Korpela, M. (2012) · Diabetes Care · doi:10.2337/dc12-0895 · Cited by 561
Self-citationSchoenaker, D. A., Jackson, C. A., Rowlands, J. V., & Mishra, G. D. (2014) · International Journal of Epidemiology · doi:10.1093/ije/dyu094 · Cited by 550
Menopause accelerates biological aging
Levine, M. E., Lu, A. T.-H., Chen, B. H., Hernandez, D. G., Singleton, A., Ferrucci, L., Bandinelli, S., Salfati, E., Manson, J. E., Quach, A., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1604558113 · Cited by 510
Age at Menopause, Cause-Specific Mortality and Total Life Expectancy
Ossewaarde, M. E., Bots, M. L., Verbeek, A. L. M., Peeters, P. H. M., van der Graaf, Y., Grobbee, D. E., & van der Schouw, Y. T. (2005) · Epidemiology · doi:10.1097/01.ede.0000165392.35273.d4 · Cited by 443
The PRACTICAL Consortium, Day, F. R., kConFab Investigators, AOCS Investigators, Scotland, G., EPIC-InterAct Consortium, Study, L. C., Ruth, K. S., Thompson, D. J., Lunetta, K. L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3412 · Cited by 402
Randolph, J. F., Zheng, H. T., Sowers, M. R., Crandall, C. J., Crawford, S. L., Gold, E. B., & Vuga, M. (2010) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2010-1746 · Cited by 386
Effect of early menopause on bone mineral density and fractures
Gallagher, J. C. (2007) · Menopause The Journal of The North American Menopause Society · doi:10.1097/gme.0b013e31804c793d · Cited by 358
STRAW+10のエグゼクティブサマリー: 生殖年齢の評価における未完成の課題に対する取り組み
Sioban, D. H., Gass, M. L. S., Janet, E. H., ROGER, L. J., Pauline, M. F., Robert, W. M., Sherry, S., Patrick, M., & Tobie, J. (2012) · The Journal of Clinical Endocrinology & Metabolism · Cited by 354
Fischer, K., Kettunen, J., Würtz, P., Haller, T., Havulinna, A. S., Kangas, A. J., Soininen, P., Esko, T., Tammesoo, M.-L., Mägi, R., et al. (2014) · PLoS Medicine · doi:10.1371/journal.pmed.1001606 · Cited by 344
Self-citationDerby, C. A., Crawford, S. L., Pasternak, R. C., Sowers, M., Sternfeld, B., & Matthews, K. A. (2009) · American Journal of Epidemiology · doi:10.1093/aje/kwp043 · Cited by 340
Würtz, P., Wang, Q., Kangas, A. J., Richmond, R. C., Skarp, J., Tiainen, M., Tynkkynen, T., Soininen, P., Havulinna, A. S., Kaakinen, M., et al. (2014) · PLoS Medicine · doi:10.1371/journal.pmed.1001765 · Cited by 280
Self-citationA metabolic view on menopause and ageing
Auro, K. M., Joensuu, A., Fischer, K., Kettunen, J., Salo, P. P., Mattsson, H., Niironen, M., Kaprio, J. A., Eriksson, J. G., Lehtimäki, T. J., et al. (2014) · Nature Communications · doi:10.1038/ncomms5708 · Cited by 274
Self-citationRitchie, S. C., Würtz, P., Nath, A. P., Abraham, G., Havulinna, A. S., Fearnley, L. G., Sarin, A., Kangas, A. J., Soininen, P., Aalto, K., et al. (2015) · Cell Systems · doi:10.1016/j.cels.2015.09.007 · Cited by 255
Self-citationA Novel Protein Glycan Biomarker and Future Cardiovascular Disease Events
Akinkuolie, A. O., Buring, J. E., Ridker, P. M., & Mora, S. (2014) · Journal of the American Heart Association · doi:10.1161/jaha.114.001221 · Cited by 242
Long-term leisure-time physical activity and serum metabolome
Kujala, U. M., Mäkinen, V.-P., Heinonen, I., Soininen, P., Kangas, A. J., Leskinen, T. H., Rahkila, P., Würtz, P., Kovanen, V., Cheng, S., et al. (2013) · Circulation · doi:10.1161/circulationaha.112.105551 · Cited by 239
Self-citationMetabolic profiling of pregnancy: cross-sectional and longitudinal evidence
Wang, Q., Würtz, P., Auro, K. M., Mäkinen, V., Kangas, A. J., Soininen, P., Tiainen, M., Tynkkynen, T., Jokelainen, J. J., Santalahti, K., et al. (2016) · BMC Medicine · doi:10.1186/s12916-016-0733-0 · Cited by 207
Self-citationMetabolomic Profiling of Statin Use and Genetic Inhibition of HMG-CoA Reductase
Würtz, P., Wang, Q., Soininen, P., Kangas, A. J., Fatemifar, G., Tynkkynen, T., Tiainen, M., Perola, M., Tillin, T., Hughes, A. D., et al. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.12.060 · Cited by 188
Self-citationLongitudinal Study of Risk Factors for Coronary Heart Disease Across the Menopausal Transition
Do, K.-A., Green, A. C., Guthrie, J. R., DUDLEY, E. C., Burger, H., & Dennerstein, L. (2000) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a010246 · Cited by 172
Novel Protein Glycan Side-Chain Biomarker and Risk of Incident Type 2 Diabetes Mellitus
Akinkuolie, A. O., Pradhan, A. D., Buring, J. E., Ridker, P. M., & Mora, S. (2015) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.115.305635 · Cited by 125
Effects of hormonal contraception on systemic metabolism: cross-sectional and longitudinal evidence
Wang, Q., Würtz, P., Auro, K., Morin-Papunen, L., Kangas, A. J., Soininen, P., Tiainen, M., Tynkkynen, T., Joensuu, A., Havulinna, A. S., et al. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw147 · Cited by 117
Self-citationWang, Q., Kangas, A. J., Soininen, P., Tiainen, M., Tynkkynen, T., Puukka, K. S., Ruokonen, A., Viikari, J. S. A., Kähönen, M. A. P., Lehtimäki, T. J., et al. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv093 · Cited by 102
Self-citationA population-based longitudinal study of cognitive functioning in the menopausal transition
Meyer, P., Powell, L. H., Wilson, R. S., Everson‐Rose, S. A., Kravitz, H. M., Luborsky, J. L., Madden, T. A., Pandey, D. K., & Evans, D. A. (2003) · Neurology · doi:10.1212/01.wnl.0000079051.91602.e2 · Cited by 97
Menopause, Age, and Cardiovascular Risk
Bittner, V. (2009) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2009.10.008 · Cited by 92
A Life Course Approach to Cardiovascular Aging
Hardy, R., Lawlor, D. A., & Kuh, D. J. (2015) · Future Cardiology · doi:10.2217/fca.14.67 · Cited by 83
Self-citationGenetics of reproductive lifespan
Hartge, P. A. (2009) · Nature Genetics · doi:10.1038/ng0609-637 · Cited by 76
Khoudary, S. R. E., Hutchins, P. M., Matthews, K. A., Brooks, M. M., Orchard, T. J., Ronsein, G. E., & Heinecke, J. W. (2016) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2016-2144 · Cited by 65
Li, S., Rosenberg, L. A., Wise, L. A., Boggs, D. A., LaValley, M. P., & Palmer, J. R. (2013) · Maturitas · doi:10.1016/j.maturitas.2013.04.003 · Cited by 54
Biology: risk factor modification by OCs and HRT lipids and lipoproteins
Godsland, I. F. (2004) · Maturitas · doi:10.1016/j.maturitas.2003.10.013 · Cited by 33
Løbo, R. A. (2019) · Elsevier eBooks · doi:10.1016/b978-0-323-47912-7.00014-7 · Cited by 33
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Ala‐Korpela, M. (2015) · Clinical Chemistry · doi:10.1373/clinchem.2015.238279 · Cited by 22
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Lawlor, D. A., & Hardy, R. (2013) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199656516.003.0011 · Cited by 8
Self-citationLøbo, R. A. (2013) · Elsevier eBooks · doi:10.1016/b978-1-4557-2758-2.00015-9 · Cited by 5
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Metadata
- Authors
- Wang, Q., Ferreira, D. L. S., Nelson, S. M., Sattar, N., Ala-Korpela, M., & Lawlor, D. A.
- Affiliations
- University of Oulu (FI)
- University of Bristol (GB)
- University of Glasgow (GB)
- Corresponding author
- Lawlor, Debbie A.
- Venue
- BMC Medicine
- Published
- 2018-02-06
- Volume
- 16
- Issue
- 1
- Pages
- 17-17
- ISSN
- 1741-7015 (ISSN-L)
- PMC
- PMC5800033
- OpenAlex
- W2757552189
- Cited by
- 134
- References
- 48
- Citations by year
- 2026: 10 · 2025: 15 · 2024: 14 · 2023: 18 · 2022: 23 · 2021: 20 · 2020: 18 · 2019: 12 · 2018: 4
- FWCI
- 10.75
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Medicine (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (publishedVersion, cc-by)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- UEF eRepo (University of Eastern Finland) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Explore Bristol Research (submittedVersion, cc-by)
- Funders
- British Heart Foundation (SP/07/008/24066)
- Wellcome (WT092830M)
- UK Medical Research Council (G1001357)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Menopause: Health Impacts and Treatments
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Hormonal and reproductive studies
- Keywords
- menopause, perimenopause, metabolic biomarkers, cardiometabolic risk, ovarian aging, chronological aging, lipoprotein profile, atherogenic lipoproteins, LDL particle size, remnant cholesterol, inflammation, glycoprotein acetyls, glutamine, albumin, postmenopausal women
- MeSH terms
- Adult, Aged, Cross-Sectional Studies, Female, Humans, Longitudinal Studies, Menopause, Middle Aged
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