Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies

Anne Julie Tessier; Fenglei Wang; Liming Liang; Clemens Wittenbecher; Danielle E. Haslam; A. Heather Eliassen; Deirdre K. Tobias; Jun Li; Oana A. Zeleznik; Alberto Ascherio; Qi Sun; Meir J. Stampfer; Francine Grodstein; Kathryn M. Rexrode; Jo Ann E. Manson; Raji Balasubramanian; Clary B. Clish; Miguel A. Martínez-González; Jorge E. Chavarro; Frank B. Hu; Marta Guasch-Ferré

doi:10.1016/j.medj.2024.01.010

Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies

Anne Julie Tessier^*, Fenglei Wang, Liming Liang, Clemens Wittenbecher, Danielle E. Haslam, A. Heather Eliassen, Deirdre K. Tobias, Jun Li, Oana A. Zeleznik, Alberto Ascherio, Qi Sun, Meir J. Stampfer, Francine Grodstein, Kathryn M. Rexrode, Jo Ann E. Manson, Raji Balasubramanian, Clary B. Clish, Miguel A. Martínez-González, Jorge E. Chavarro, Frank B. HuMarta Guasch-Ferré^*

^*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

5 Citationer (Scopus)

6 Downloads (Pure)

Abstract

Background: A healthy lifestyle is associated with a lower premature mortality risk and with longer life expectancy. However, the metabolic pathways of a healthy lifestyle and how they relate to mortality and longevity are unclear. We aimed to identify and replicate a healthy lifestyle metabolomic signature and examine how it is related to total and cause-specific mortality risk and longevity. Methods: In four large cohorts with 13,056 individuals and 28-year follow-up, we assessed five healthy lifestyle factors, used liquid chromatography mass spectrometry to profile plasma metabolites, and ascertained deaths with death certificates. The unique healthy lifestyle metabolomic signature was identified using an elastic regression. Multivariable Cox regressions were used to assess associations of the signature with mortality and longevity. Findings: The identified healthy lifestyle metabolomic signature was reflective of lipid metabolism pathways. Shorter and more saturated triacylglycerol and diacylglycerol metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were positively associated. Participants with a higher healthy lifestyle metabolomic signature had a 17% lower risk of all-cause mortality, 19% for cardiovascular disease mortality, and 17% for cancer mortality and were 25% more likely to reach longevity. The healthy lifestyle metabolomic signature explained 38% of the association between the self-reported healthy lifestyle score and total mortality risk and 49% of the association with longevity. Conclusions: This study identifies a metabolomic signature that measures adherence to a healthy lifestyle and shows prediction of total and cause-specific mortality and longevity. Funding: This work was funded by the NIH, CIHR, AHA, Novo Nordisk Foundation, and SciLifeLab.

Originalsprog	Engelsk
Tidsskrift	Med
Vol/bind	5
Udgave nummer	3
Sider (fra-til)	224-238.e5
Antal sider	21
ISSN	2666-6359
DOI	https://doi.org/10.1016/j.medj.2024.01.010
Status	Udgivet - 2024

Bibliografisk note

Funding Information:
This work is supported by the research grant R21 AG070375 from the National Institutes of Health to M.G.-F. The NHS, NHSII, HPFS, and WHI are supported by grants from the National Institutes of Health (UM1 CA186107, U01 CA176726, U01 CA167552, U01 HL145386, R01 CA49449, R01 HL034594, R01 HL088521, R01 CA67262, R01 HL35464, R01 HL60712, R01 CA50385, P01 CA87969, R01 DK112940, R01 DK119268, R01 DK120870, P30 DK046200, HHSN268201300008C, HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C). A.-J.T. is supported by the Canadian Institutes of Health Research (CIHR) Fellowship Award. F.W. is supported by the American Heart Association Postdoctoral Fellowship (grant number: 897161). M.G.-F. is supported by Novo Nordisk Foundation grant NNF18CC0034900. C.W. is supported by the SciLifeLab and Wallenberg Data Driven Life Science Program (grant KAW 2020.0239). None of the funding sources played a role in the design, collection, analysis, or interpretation of the data or in the decision to submit the manuscript for publication. The authors would like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention's National Program of Cancer Registries (NPCR) and/or the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) Program. Central registries may also be supported by state agencies, universities, and cancer centers. Participating central cancer registries include the following: Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kentucky, Louisiana, Massachusetts, Maine, Maryland, Michigan, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, Rhode Island, Seattle SEER Registry, South Carolina, Tennessee, Texas, Utah, Virginia, West Virginia, and Wyoming. A.-J.T. M.G.-F. and F.B.H. designed the research and had unrestricted access to all data. A.-J.T. and F.W. conducted analyses. A.H.E. and C.B.C. participated in acquisition of data. L.L. and O.Z. provided statistical expertise. A.-J.T. prepared tables and figures and wrote the manuscript. All authors contributed to the interpretation of the results and critical revision of the manuscript for important intellectual content. All authors approved the final version of the manuscript. The authors declare no competing interests.

Funding Information:
This work is supported by the research grant R21 AG070375 from the National Institutes of Health to M.G.-F. The NHS , NHSII , HPFS , and WHI are supported by grants from the National Institutes of Health ( UM1 CA186107 , U01 CA176726 , U01 CA167552 , U01 HL145386 , R01 CA49449 , R01 HL034594 , R01 HL088521 , R01 CA67262 , R01 HL35464 , R01 HL60712 , R01 CA50385 , P01 CA87969 , R01 DK112940 , R01 DK119268 , R01 DK120870 , P30 DK046200 , HHSN268201300008C , HHSN268201600018C , HHSN268201600001C , HHSN268201600002C , HHSN268201600003C , and HHSN268201600004C ). A.-J.T. is supported by the Canadian Institutes of Health Research ( CIHR ) Fellowship Award. F.W. is supported by the American Heart Association Postdoctoral Fellowship (grant number: 897161 ). M.G.-F. is supported by Novo Nordisk Foundation grant NNF18CC0034900 . C.W. is supported by the SciLifeLab and Wallenberg Data Driven Life Science Program (grant KAW 2020.0239 ). None of the funding sources played a role in the design, collection, analysis, or interpretation of the data or in the decision to submit the manuscript for publication. The authors would like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention’s National Program of Cancer Registries ( NPCR ) and/or the National Cancer Institute Surveillance, Epidemiology, and End Results ( SEER ) Program. Central registries may also be supported by state agencies, universities, and cancer centers. Participating central cancer registries include the following: Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kentucky, Louisiana, Massachusetts, Maine, Maryland, Michigan, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, Rhode Island, Seattle SEER Registry, South Carolina, Tennessee, Texas, Utah, Virginia, West Virginia, and Wyoming.

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© 2024 The Author(s)

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10.1016/j.medj.2024.01.010Licens: CC BY

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Citationsformater

Tessier, A. J., Wang, F., Liang, L., Wittenbecher, C., Haslam, D. E., Eliassen, A. H., Tobias, D. K., Li, J., Zeleznik, O. A., Ascherio, A., Sun, Q., Stampfer, M. J., Grodstein, F., Rexrode, K. M., Manson, J. A. E., Balasubramanian, R., Clish, C. B., Martínez-González, M. A., Chavarro, J. E., ... Guasch-Ferré, M. (2024). Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies. Med, 5(3), 224-238.e5. https://doi.org/10.1016/j.medj.2024.01.010

Plasma metabolites of a healthy lifestyle in relation to mortality and longevity : Four prospective US cohort studies. / Tessier, Anne Julie; Wang, Fenglei; Liang, Liming; Wittenbecher, Clemens; Haslam, Danielle E.; Eliassen, A. Heather; Tobias, Deirdre K.; Li, Jun; Zeleznik, Oana A.; Ascherio, Alberto; Sun, Qi; Stampfer, Meir J.; Grodstein, Francine; Rexrode, Kathryn M.; Manson, Jo Ann E.; Balasubramanian, Raji; Clish, Clary B.; Martínez-González, Miguel A.; Chavarro, Jorge E.; Hu, Frank B.; Guasch-Ferré, Marta.

I: Med, Bind 5, Nr. 3, 2024, s. 224-238.e5.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Tessier, AJ, Wang, F, Liang, L, Wittenbecher, C, Haslam, DE, Eliassen, AH, Tobias, DK, Li, J, Zeleznik, OA, Ascherio, A, Sun, Q, Stampfer, MJ, Grodstein, F, Rexrode, KM, Manson, JAE, Balasubramanian, R, Clish, CB, Martínez-González, MA, Chavarro, JE, Hu, FB & Guasch-Ferré, M 2024, 'Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies', Med, bind 5, nr. 3, s. 224-238.e5. https://doi.org/10.1016/j.medj.2024.01.010

Tessier, Anne Julie ; Wang, Fenglei ; Liang, Liming ; Wittenbecher, Clemens ; Haslam, Danielle E. ; Eliassen, A. Heather ; Tobias, Deirdre K. ; Li, Jun ; Zeleznik, Oana A. ; Ascherio, Alberto ; Sun, Qi ; Stampfer, Meir J. ; Grodstein, Francine ; Rexrode, Kathryn M. ; Manson, Jo Ann E. ; Balasubramanian, Raji ; Clish, Clary B. ; Martínez-González, Miguel A. ; Chavarro, Jorge E. ; Hu, Frank B. ; Guasch-Ferré, Marta. / Plasma metabolites of a healthy lifestyle in relation to mortality and longevity : Four prospective US cohort studies. I: Med. 2024 ; Bind 5, Nr. 3. s. 224-238.e5.

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title = "Plasma metabolites of a healthy lifestyle in relation to mortality and longevity: Four prospective US cohort studies",

abstract = "Background: A healthy lifestyle is associated with a lower premature mortality risk and with longer life expectancy. However, the metabolic pathways of a healthy lifestyle and how they relate to mortality and longevity are unclear. We aimed to identify and replicate a healthy lifestyle metabolomic signature and examine how it is related to total and cause-specific mortality risk and longevity. Methods: In four large cohorts with 13,056 individuals and 28-year follow-up, we assessed five healthy lifestyle factors, used liquid chromatography mass spectrometry to profile plasma metabolites, and ascertained deaths with death certificates. The unique healthy lifestyle metabolomic signature was identified using an elastic regression. Multivariable Cox regressions were used to assess associations of the signature with mortality and longevity. Findings: The identified healthy lifestyle metabolomic signature was reflective of lipid metabolism pathways. Shorter and more saturated triacylglycerol and diacylglycerol metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were positively associated. Participants with a higher healthy lifestyle metabolomic signature had a 17% lower risk of all-cause mortality, 19% for cardiovascular disease mortality, and 17% for cancer mortality and were 25% more likely to reach longevity. The healthy lifestyle metabolomic signature explained 38% of the association between the self-reported healthy lifestyle score and total mortality risk and 49% of the association with longevity. Conclusions: This study identifies a metabolomic signature that measures adherence to a healthy lifestyle and shows prediction of total and cause-specific mortality and longevity. Funding: This work was funded by the NIH, CIHR, AHA, Novo Nordisk Foundation, and SciLifeLab.",

keywords = "alcohol, BMI, diet, lifestyle, longevity, metabolome, metabolomics, mortality, physical activity, smoking, Translation to population health",

author = "Tessier, {Anne Julie} and Fenglei Wang and Liming Liang and Clemens Wittenbecher and Haslam, {Danielle E.} and Eliassen, {A. Heather} and Tobias, {Deirdre K.} and Jun Li and Zeleznik, {Oana A.} and Alberto Ascherio and Qi Sun and Stampfer, {Meir J.} and Francine Grodstein and Rexrode, {Kathryn M.} and Manson, {Jo Ann E.} and Raji Balasubramanian and Clish, {Clary B.} and Mart{\'i}nez-Gonz{\'a}lez, {Miguel A.} and Chavarro, {Jorge E.} and Hu, {Frank B.} and Marta Guasch-Ferr{\'e}",

note = "Publisher Copyright: {\textcopyright} 2024 The Author(s)",

year = "2024",

doi = "10.1016/j.medj.2024.01.010",

language = "English",

volume = "5",

pages = "224--238.e5",

journal = "Med",

issn = "2666-6359",

publisher = "Elsevier",

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TY - JOUR

T1 - Plasma metabolites of a healthy lifestyle in relation to mortality and longevity

T2 - Four prospective US cohort studies

AU - Tessier, Anne Julie

AU - Wang, Fenglei

AU - Liang, Liming

AU - Wittenbecher, Clemens

AU - Haslam, Danielle E.

AU - Eliassen, A. Heather

AU - Tobias, Deirdre K.

AU - Li, Jun

AU - Zeleznik, Oana A.

AU - Ascherio, Alberto

AU - Sun, Qi

AU - Stampfer, Meir J.

AU - Grodstein, Francine

AU - Rexrode, Kathryn M.

AU - Manson, Jo Ann E.

AU - Balasubramanian, Raji

AU - Clish, Clary B.

AU - Martínez-González, Miguel A.

AU - Chavarro, Jorge E.

AU - Hu, Frank B.

AU - Guasch-Ferré, Marta

PY - 2024

Y1 - 2024

N2 - Background: A healthy lifestyle is associated with a lower premature mortality risk and with longer life expectancy. However, the metabolic pathways of a healthy lifestyle and how they relate to mortality and longevity are unclear. We aimed to identify and replicate a healthy lifestyle metabolomic signature and examine how it is related to total and cause-specific mortality risk and longevity. Methods: In four large cohorts with 13,056 individuals and 28-year follow-up, we assessed five healthy lifestyle factors, used liquid chromatography mass spectrometry to profile plasma metabolites, and ascertained deaths with death certificates. The unique healthy lifestyle metabolomic signature was identified using an elastic regression. Multivariable Cox regressions were used to assess associations of the signature with mortality and longevity. Findings: The identified healthy lifestyle metabolomic signature was reflective of lipid metabolism pathways. Shorter and more saturated triacylglycerol and diacylglycerol metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were positively associated. Participants with a higher healthy lifestyle metabolomic signature had a 17% lower risk of all-cause mortality, 19% for cardiovascular disease mortality, and 17% for cancer mortality and were 25% more likely to reach longevity. The healthy lifestyle metabolomic signature explained 38% of the association between the self-reported healthy lifestyle score and total mortality risk and 49% of the association with longevity. Conclusions: This study identifies a metabolomic signature that measures adherence to a healthy lifestyle and shows prediction of total and cause-specific mortality and longevity. Funding: This work was funded by the NIH, CIHR, AHA, Novo Nordisk Foundation, and SciLifeLab.

AB - Background: A healthy lifestyle is associated with a lower premature mortality risk and with longer life expectancy. However, the metabolic pathways of a healthy lifestyle and how they relate to mortality and longevity are unclear. We aimed to identify and replicate a healthy lifestyle metabolomic signature and examine how it is related to total and cause-specific mortality risk and longevity. Methods: In four large cohorts with 13,056 individuals and 28-year follow-up, we assessed five healthy lifestyle factors, used liquid chromatography mass spectrometry to profile plasma metabolites, and ascertained deaths with death certificates. The unique healthy lifestyle metabolomic signature was identified using an elastic regression. Multivariable Cox regressions were used to assess associations of the signature with mortality and longevity. Findings: The identified healthy lifestyle metabolomic signature was reflective of lipid metabolism pathways. Shorter and more saturated triacylglycerol and diacylglycerol metabolite sets were inversely associated with the healthy lifestyle score, whereas cholesteryl ester and phosphatidylcholine plasmalogen sets were positively associated. Participants with a higher healthy lifestyle metabolomic signature had a 17% lower risk of all-cause mortality, 19% for cardiovascular disease mortality, and 17% for cancer mortality and were 25% more likely to reach longevity. The healthy lifestyle metabolomic signature explained 38% of the association between the self-reported healthy lifestyle score and total mortality risk and 49% of the association with longevity. Conclusions: This study identifies a metabolomic signature that measures adherence to a healthy lifestyle and shows prediction of total and cause-specific mortality and longevity. Funding: This work was funded by the NIH, CIHR, AHA, Novo Nordisk Foundation, and SciLifeLab.

KW - alcohol

KW - BMI

KW - diet

KW - lifestyle

KW - longevity

KW - metabolome

KW - metabolomics

KW - mortality

KW - physical activity

KW - smoking

KW - Translation to population health

U2 - 10.1016/j.medj.2024.01.010

DO - 10.1016/j.medj.2024.01.010

M3 - Journal article

C2 - 38366602

AN - SCOPUS:85186352652

VL - 5

SP - 224-238.e5

JO - Med

JF - Med

SN - 2666-6359

IS - 3

ER -