CoChat
Sign Up
Cited by 45

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Metabolomic profiles associated with all-cause mortality in the Women’s Health Initiative

Balasubramanian, Raji, Paynter, Nina P, Giulianini, Franco, Manson, JoAnn E, Zhao, Yibai, Chen, Jiu-Chiuan, Vitolins, Mara Z, Albert, Christine A, Clish, Clary, Rexrode, Kathryn M·2020·International Journal of Epidemiology
DOI 10.1093/ije/dyz211
Open this paper in CoChat — free account

Abstract

Background: Metabolomics profiling has shown promise in elucidating the biological pathways underpinning mortality, but there are limited data in female populations. Methods: We applied a liquid chromatography-tandem mass spectrometry metabolomics platform to EDTA-plasma to measure 470 metabolites at baseline in a discovery set of 943 postmenopausal women (including 417 incident deaths, median time to death of 10.6 years) with validation in an independent set of 1355 postmenopausal women (including 685 deaths, median time to death of 9.1 years) in the Women’s Health Initiative. Results: Eight new metabolites were discovered to be associated with all-cause mortality. Findings included protective effects of increased levels of three amino acids (asparagine, homoarginine and tryptophan) and docosatrienoic acid; and detrimental effects of increased levels of C4-OH-carnitine, hexadecanedioate and two purine/pyrimidines (N2, N2-dimethylguanosine and N4-acetylcytidine). In addition, a set of nine previously published metabolite associations were replicated. A metabolite score comprising 17 metabolites was associated with mortality (P < 10–8) after adjustment for risk factors, with a hazard ratio of 1.95 (95% CI: 1.46–2.62) for women in the highest quartile compared with the lowest quartile of metabolite score. The score was robust among younger women and older women, for both cardiovascular and non-cardiovascular mortality, and associated with both early deaths (within the first 10 years of baseline) and later deaths. Conclusions: Our study fills a gap in the literature by identifying eight novel metabolite associations with all-cause mortality in women, using a robust study design involving independent discovery and validation datasets.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/ije/dyz211

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 5 references

Research works printed but not linked: 37

  1. Weindruch, 1988, The Retardation of Aging and Disease by Dietary Restriction
  2. Fishbein, 1991, Biological Effects of Dietary Restriction., 10.1007/978-3-642-58181-6 · DOI
  3. Ala-Korpela, 2012, Quantitative high-throughput metabolomics: a new era in epidemiology and genetics, Genome Med, 4, 36., 10.1186/gm335 · DOI
  4. Sebastiani, 2012, The genetics of extreme longevity: lessons from the New England centenarian study, Front Genet, 3, 277, 10.3389/fgene.2012.00277 · DOI · Paper page
  5. Rogina, 2002, Longevity regulation by Drosophila Rpd3 deacetylase and caloric restriction, Science, 298, 1745., 10.1126/science.1078986 · DOI
  6. Ogg, 1997, The Fork head transcription factor DAF-16 transduces insulin-like metabolic and longevity signals in C. elegans, Nature, 389, 994, 10.1038/40194 · DOI
  7. Montoliu, 2014, Serum profiling of healthy aging identifies phospho- and sphingolipid species as markers of human longevity, Aging, 6, 9, 10.18632/aging.100630 · DOI
  8. Gonzalez-Covarrubias, 2013, Lipidomics of familial longevity, Aging Cell, 12, 426, 10.1111/acel.12064 · DOI
  9. Auro, 2014, A metabolic view on menopause and ageing, Nat Commun, 5, 4708., 10.1038/ncomms5708 · DOI
  10. Cheng, 2015, Distinct metabolomic signatures are associated with longevity in humans, Nat Commun, 6, 6791., 10.1038/ncomms7791 · DOI
  11. Zuo, 2016, Plasma biomarkers of inflammation, the Kynurenine pathway, and risks of all-cause, cancer, and cardiovascular disease mortality: The Hordaland Health Study, Am J Epidemiol, 183, 249, 10.1093/aje/kwv242 · DOI
  12. Yu, 2016, Associations between the serum metabolome and all-cause mortality among African Americans in the Atherosclerosis Risk In Communities (ARIC) study, Am J Epidemiol, 183, 650, 10.1093/aje/kwv213 · DOI
  13. Huang, 2018, Serum metabolomic profiling of all-cause mortality: A prospective analysis in the alpha-tocopherol, beta-carotene cancer prevention (ATBC) study cohort, Am J Epidemiol, 187, 1721, 10.1093/aje/kwy017 · DOI
  14. Krumsiek, 2015, Gender-specific pathway differences in the human serum metabolome, Metabolomics, 11, 1815, 10.1007/s11306-015-0829-0 · DOI
  15. Mittelstrass, 2011, Discovery of sexual dimorphisms in metabolic and genetic biomarkers, PLoS Genet, 7, e1002215., 10.1371/journal.pgen.1002215 · DOI
  16. Barford, 2006, Life expectancy: women now on top everywhere, BMJ, 332, 808., 10.1136/bmj.332.7545.808 · DOI
  17. 1998, The Women’s Health Initiative Study Writing Group. Design of the Women’s Health Initiative clinical trial and observational study, Controlled Clinical Trials, 19, 61, 10.1016/S0197-2456(97)00078-0 · DOI
  18. Pradhan, 2002, Inflammatory biomarkers, hormone replacement therapy, and incident coronary heart disease: prospective analysis from the Women's Health Initiative observational study, JAMA, 288, 980, 10.1001/jama.288.8.980 · DOI
  19. Rossouw, 2002, Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results from the Women's Health Initiative randomized controlled trial, JAMA, 288, 321, 10.1001/jama.288.3.321 · DOI · Paper page
  20. Vaughan, 2013, The rationale, design, and baseline characteristics of the Women's Health Initiative Memory Study of Younger Women (WHIMS-Y), Brain Res, 1514, 3, 10.1016/j.brainres.2013.03.047 · DOI
  21. 1998, The Women's Health Initiative Study Group. Design of the Women's Health Initiative Clinical Trial and Observational Study, Control Clin Trials, 19, 61, 10.1016/S0197-2456(97)00078-0 · DOI
  22. Anderson, 2004, Effects of conjugated equine estrogen in postmenopausal women with hysterectomy: the Women's Health Initiative randomized controlled trial, JAMA, 291, 1701, 10.1001/jama.291.14.1701 · DOI · Paper page
  23. Paynter, 2018, Metabolic predictors of incident coronary heart disease in women, Circulation, 137, 841, 10.1161/CIRCULATIONAHA.117.029468 · DOI
  24. Friedman JaH, 2010, Regularization paths for generalized linear models via coordinate descent, J Stat Softw, 33, 1
  25. Zheng, 2013, Associations between metabolomic compounds and incident heart failure among African Americans: the ARIC Study, Am J Epidemiol, 178, 534, 10.1093/aje/kwt004 · DOI
  26. Chyan, 1999, Potent neuroprotective properties against the Alzheimer beta-amyloid by an endogenous melatonin-related indole structure, indole-3-propionic acid, J Biol Chem, 274, 21937, 10.1074/jbc.274.31.21937 · DOI
  27. Rinaldo, 2008, Acylcarnitine profile analysis, Genet Med, 10, 151, 10.1097/GIM.0b013e3181614289 · DOI
  28. Schooneman, 2013, Acylcarnitines: reflecting or inflicting insulin resistance?, Diabetes, 62, 1, 10.2337/db12-0466 · DOI · Paper page
  29. Simon, 1999, Characterization of the mechanisms involved in the gender differences in hepatic taurocholate uptake, Am J Physiol, 276, G556
  30. Brock, 1984, Characterization of uptake of steroid glucuronides into isolated male and female rat hepatocytes, J Pharmacol Exp Ther, 229, 175
  31. Schlattjan, 2005, Gender differences in renal tubular taurocholate transport, Naunyn Schmiedebergs Arch Pharmacol, 371, 449, 10.1007/s00210-005-1081-3 · DOI
  32. Tabung, 2019, Identifying metabolomic profiles of insulinemic dietary patterns, Metabolites, 9, 120, 10.3390/metabo9060120 · DOI
  33. Kirchner, 2015, Emerging roles of tRNA in adaptive translation, signalling dynamics and disease, Nat Rev Genet, 16, 98, 10.1038/nrg3861 · DOI
  34. Rhodes, 2017, Plasma metabolomics implicates modified transfer RNAs and altered bioenergetics in the outcomes of pulmonary arterial hypertension, Circulation, 135, 460, 10.1161/CIRCULATIONAHA.116.024602 · DOI
  35. Tsikas, 2015, Homoarginine, arginine, and relatives: analysis, metabolism, transport, physiology, and pathology, Amino Acids, 47, 1697, 10.1007/s00726-015-2055-5 · DOI
  36. Zinellu, 2018, Homoarginine and all-cause mortality: a systematic review and meta-analysis, Eur J Clin Invest, 48, e12960., 10.1111/eci.12960 · DOI
  37. Gruppen, 2017, TMAO is associated with mortality: impact of modestly impaired renal function, Sci Rep, 7, 13781., 10.1038/s41598-017-13739-9 · DOI · Paper page

Cited by

Sorted by citations

See all 45

Metadata

Authors
Balasubramanian, R., Paynter, N. P., Giulianini, F., Manson, J. E., Zhao, Y., Chen, J.-C., Vitolins, M. Z., Albert, C. A., Clish, C., & Rexrode, K. M.
Venue
International Journal of Epidemiology
Publisher
Oxford University Press (OUP)
Published
2019-10-25
Volume
49
Issue
1
Pages
289-300
ISSN
  • 0300-5771
  • 1464-3685
DOI
10.1093/ije/dyz211
Cited by
45
References
5
Language
en
Licence
academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
Funders
  • National Heart, Lung, and Blood Institute
  • National Institutes of Health
  • Department of Health and Human Services (HHSN268201300008C, HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, HHSN268201600004C)
  • NHLBI (R01 HL122241)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Metabolomic profiles associated with all-cause mortality in the Women’s Health Initiative. https://app.cochat.ai/papers/10.1093/ije/dyz211
The paper
Balasubramanian, R., Paynter, N. P., Giulianini, F., Manson, J. E., Zhao, Y., Chen, J.-C., Vitolins, M. Z., Albert, C. A., Clish, C., & Rexrode, K. M. (2020). Metabolomic profiles associated with all-cause mortality in the Women’s Health Initiative. International Journal of Epidemiology. https://doi.org/10.1093/ije/dyz211