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Serum markers of biological ageing provide long-term prediction of life expectancy—a longitudinal analysis in middle-aged and older German adults

Abstract Background lifestyle behaviours and chronic co-morbidities are leading risk factors for premature mortality and collectively predict wide variability in individual life expectancy (LE). We investigated whether a pre-selected panel of five serum markers of biological ageing could improve pre...

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Published in:Age and ageing 2022-02, Vol.51 (2)
Main Authors: Srour, Bernard, Hynes, Lucas Cory, Johnson, Theron, Kühn, Tilman, Katzke, Verena A, Kaaks, Rudolf
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container_title Age and ageing
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creator Srour, Bernard
Hynes, Lucas Cory
Johnson, Theron
Kühn, Tilman
Katzke, Verena A
Kaaks, Rudolf
description Abstract Background lifestyle behaviours and chronic co-morbidities are leading risk factors for premature mortality and collectively predict wide variability in individual life expectancy (LE). We investigated whether a pre-selected panel of five serum markers of biological ageing could improve predicting the long-term mortality risk and LE in middle-aged and older women and men. Methods we conducted a case-cohort study (n = 5,789 among which there were 2,571 deaths) within the European Prospective Investigation into Cancer-Heidelberg cohort, a population cohort of middle-aged and older individuals, followed over a median duration of 18 years. Gompertz models were used to compute multi-adjusted associations of growth differentiation factor-15, N-terminal pro-brain natriuretic peptide, glycated haemoglobin A1c, C-reactive protein and cystatin-C with mortality risk. Areas under estimated Gompertz survival curves were used to estimate the LE of individuals using a model with lifestyle-related risk factors only (smoking history, body mass index, waist circumference, alcohol, physical inactivity, diabetes and hypertension), or with lifestyle factors plus the ageing-related markers. Results a model including only lifestyle-related factors predicted a LE difference of 16.8 [95% confidence interval: 15.9; 19.1] years in men and 9.87 [9.20; 13.1] years in women aged ≥60 years by comparing individuals in the highest versus the lowest quintiles of estimated mortality risk. Including the ageing-related biomarkers in the model increased these differences up to 22.7 [22.3; 26.9] years in men and 14.00 [12.9; 18.2] years in women. Conclusions serum markers of ageing are potentially strong predictors for long-term mortality risk in a general population sample of older and middle-aged individuals and may help to identify individuals at higher risk of premature death, who could benefit from interventions to prevent further ageing-related health declines.
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We investigated whether a pre-selected panel of five serum markers of biological ageing could improve predicting the long-term mortality risk and LE in middle-aged and older women and men. Methods we conducted a case-cohort study (n = 5,789 among which there were 2,571 deaths) within the European Prospective Investigation into Cancer-Heidelberg cohort, a population cohort of middle-aged and older individuals, followed over a median duration of 18 years. Gompertz models were used to compute multi-adjusted associations of growth differentiation factor-15, N-terminal pro-brain natriuretic peptide, glycated haemoglobin A1c, C-reactive protein and cystatin-C with mortality risk. Areas under estimated Gompertz survival curves were used to estimate the LE of individuals using a model with lifestyle-related risk factors only (smoking history, body mass index, waist circumference, alcohol, physical inactivity, diabetes and hypertension), or with lifestyle factors plus the ageing-related markers. Results a model including only lifestyle-related factors predicted a LE difference of 16.8 [95% confidence interval: 15.9; 19.1] years in men and 9.87 [9.20; 13.1] years in women aged ≥60 years by comparing individuals in the highest versus the lowest quintiles of estimated mortality risk. Including the ageing-related biomarkers in the model increased these differences up to 22.7 [22.3; 26.9] years in men and 14.00 [12.9; 18.2] years in women. Conclusions serum markers of ageing are potentially strong predictors for long-term mortality risk in a general population sample of older and middle-aged individuals and may help to identify individuals at higher risk of premature death, who could benefit from interventions to prevent further ageing-related health declines.</description><identifier>ISSN: 0002-0729</identifier><identifier>EISSN: 1468-2834</identifier><identifier>DOI: 10.1093/ageing/afab271</identifier><identifier>PMID: 35150586</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Aged ; Aging ; Biological markers ; Biomarkers ; Body mass index ; Brain natriuretic peptide ; C-reactive protein ; Cancer ; Cohort analysis ; Cohort Studies ; Diabetes ; Diabetes mellitus ; Differentiation ; Female ; Hemoglobin ; Humans ; Hypertension ; Life Expectancy ; Life span ; Lifestyles ; Male ; Middle age ; Middle Aged ; Mortality ; Older people ; Older women ; Physical activity ; Premature mortality ; Prospective Studies ; Risk Factors ; Serum ; Smoking ; Women</subject><ispartof>Age and ageing, 2022-02, Vol.51 (2)</ispartof><rights>The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com 2021</rights><rights>The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.</rights><rights>The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c352t-759bc283e407eb89e87f034c5eb8ecea764712a58db76c62411db9d7c8a7c6a33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,778,782,27907,27908,30982</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35150586$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Srour, Bernard</creatorcontrib><creatorcontrib>Hynes, Lucas Cory</creatorcontrib><creatorcontrib>Johnson, Theron</creatorcontrib><creatorcontrib>Kühn, Tilman</creatorcontrib><creatorcontrib>Katzke, Verena A</creatorcontrib><creatorcontrib>Kaaks, Rudolf</creatorcontrib><title>Serum markers of biological ageing provide long-term prediction of life expectancy—a longitudinal analysis in middle-aged and older German adults</title><title>Age and ageing</title><addtitle>Age Ageing</addtitle><description>Abstract Background lifestyle behaviours and chronic co-morbidities are leading risk factors for premature mortality and collectively predict wide variability in individual life expectancy (LE). We investigated whether a pre-selected panel of five serum markers of biological ageing could improve predicting the long-term mortality risk and LE in middle-aged and older women and men. Methods we conducted a case-cohort study (n = 5,789 among which there were 2,571 deaths) within the European Prospective Investigation into Cancer-Heidelberg cohort, a population cohort of middle-aged and older individuals, followed over a median duration of 18 years. Gompertz models were used to compute multi-adjusted associations of growth differentiation factor-15, N-terminal pro-brain natriuretic peptide, glycated haemoglobin A1c, C-reactive protein and cystatin-C with mortality risk. Areas under estimated Gompertz survival curves were used to estimate the LE of individuals using a model with lifestyle-related risk factors only (smoking history, body mass index, waist circumference, alcohol, physical inactivity, diabetes and hypertension), or with lifestyle factors plus the ageing-related markers. Results a model including only lifestyle-related factors predicted a LE difference of 16.8 [95% confidence interval: 15.9; 19.1] years in men and 9.87 [9.20; 13.1] years in women aged ≥60 years by comparing individuals in the highest versus the lowest quintiles of estimated mortality risk. Including the ageing-related biomarkers in the model increased these differences up to 22.7 [22.3; 26.9] years in men and 14.00 [12.9; 18.2] years in women. 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Hynes, Lucas Cory ; Johnson, Theron ; Kühn, Tilman ; Katzke, Verena A ; Kaaks, Rudolf</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c352t-759bc283e407eb89e87f034c5eb8ecea764712a58db76c62411db9d7c8a7c6a33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Aged</topic><topic>Aging</topic><topic>Biological markers</topic><topic>Biomarkers</topic><topic>Body mass index</topic><topic>Brain natriuretic peptide</topic><topic>C-reactive protein</topic><topic>Cancer</topic><topic>Cohort analysis</topic><topic>Cohort Studies</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Differentiation</topic><topic>Female</topic><topic>Hemoglobin</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Life Expectancy</topic><topic>Life span</topic><topic>Lifestyles</topic><topic>Male</topic><topic>Middle age</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Older people</topic><topic>Older women</topic><topic>Physical activity</topic><topic>Premature mortality</topic><topic>Prospective Studies</topic><topic>Risk Factors</topic><topic>Serum</topic><topic>Smoking</topic><topic>Women</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Srour, Bernard</creatorcontrib><creatorcontrib>Hynes, Lucas Cory</creatorcontrib><creatorcontrib>Johnson, Theron</creatorcontrib><creatorcontrib>Kühn, Tilman</creatorcontrib><creatorcontrib>Katzke, Verena A</creatorcontrib><creatorcontrib>Kaaks, Rudolf</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Applied Social Sciences Index &amp; Abstracts (ASSIA)</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>Age and ageing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Srour, Bernard</au><au>Hynes, Lucas Cory</au><au>Johnson, Theron</au><au>Kühn, Tilman</au><au>Katzke, Verena A</au><au>Kaaks, Rudolf</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Serum markers of biological ageing provide long-term prediction of life expectancy—a longitudinal analysis in middle-aged and older German adults</atitle><jtitle>Age and ageing</jtitle><addtitle>Age Ageing</addtitle><date>2022-02-02</date><risdate>2022</risdate><volume>51</volume><issue>2</issue><issn>0002-0729</issn><eissn>1468-2834</eissn><abstract>Abstract Background lifestyle behaviours and chronic co-morbidities are leading risk factors for premature mortality and collectively predict wide variability in individual life expectancy (LE). We investigated whether a pre-selected panel of five serum markers of biological ageing could improve predicting the long-term mortality risk and LE in middle-aged and older women and men. Methods we conducted a case-cohort study (n = 5,789 among which there were 2,571 deaths) within the European Prospective Investigation into Cancer-Heidelberg cohort, a population cohort of middle-aged and older individuals, followed over a median duration of 18 years. Gompertz models were used to compute multi-adjusted associations of growth differentiation factor-15, N-terminal pro-brain natriuretic peptide, glycated haemoglobin A1c, C-reactive protein and cystatin-C with mortality risk. Areas under estimated Gompertz survival curves were used to estimate the LE of individuals using a model with lifestyle-related risk factors only (smoking history, body mass index, waist circumference, alcohol, physical inactivity, diabetes and hypertension), or with lifestyle factors plus the ageing-related markers. Results a model including only lifestyle-related factors predicted a LE difference of 16.8 [95% confidence interval: 15.9; 19.1] years in men and 9.87 [9.20; 13.1] years in women aged ≥60 years by comparing individuals in the highest versus the lowest quintiles of estimated mortality risk. Including the ageing-related biomarkers in the model increased these differences up to 22.7 [22.3; 26.9] years in men and 14.00 [12.9; 18.2] years in women. Conclusions serum markers of ageing are potentially strong predictors for long-term mortality risk in a general population sample of older and middle-aged individuals and may help to identify individuals at higher risk of premature death, who could benefit from interventions to prevent further ageing-related health declines.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>35150586</pmid><doi>10.1093/ageing/afab271</doi><oa>free_for_read</oa></addata></record>
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source Applied Social Sciences Index & Abstracts (ASSIA); Oxford Journals Online
subjects Aged
Aging
Biological markers
Biomarkers
Body mass index
Brain natriuretic peptide
C-reactive protein
Cancer
Cohort analysis
Cohort Studies
Diabetes
Diabetes mellitus
Differentiation
Female
Hemoglobin
Humans
Hypertension
Life Expectancy
Life span
Lifestyles
Male
Middle age
Middle Aged
Mortality
Older people
Older women
Physical activity
Premature mortality
Prospective Studies
Risk Factors
Serum
Smoking
Women
title Serum markers of biological ageing provide long-term prediction of life expectancy—a longitudinal analysis in middle-aged and older German adults
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