Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/154140 |
Resumo: | Background: Allostatic load (AL) is a multi-system composite index for quantifying physiological dysregulation caused by life course stressors. For over 30 years, an extensive body of research has drawn on the AL framework but has been hampered by the lack of a consistent definition.Methods: This study analyses data for 67,126 individuals aged 40-111 years participating in 13 different cohort studies and 40 biomarkers across 12 physiological systems: hypothalamic-pituitary-adrenal (HPA) axis, sympathetic-adrenal-medullary (SAM) axis, parasympathetic nervous system functioning, oxidative stress, immunological/inflammatory, cardiovascular, respiratory, lipidemia, anthropometric, glucose metabolism, kidney, and liver. We use individual-participant-data meta-analysis and exploit natural heterogeneity in the number and type of biomarkers that have been used across studies, but a common set of health outcomes (grip strength, walking speed, and self-rated health), to determine the optimal configuration of parameters to define the concept.Results: There was at least one biomarker within 9/12 physiological systems that was reliably and consistently associated in the hypothesised direction with the three health outcomes in the meta-analysis of these cohorts: dehydroepiandrosterone sulfate (DHEAS), low frequency-heart rate variability (LF-HRV), C-reactive protein (CRP), resting heart rate (RHR), peak expiratory flow (PEF), high density lipoprotein cholesterol (HDL-C), waist -to-height ratio (WtHR), HbA1c, and cystatin C. An index based on five biomarkers (CRP, RHR, HDL-C, WtHR and HbA1c) available in every study was found to predict an independent outcome - mortality - as well or better than more elaborate sets of biomarkers.Discussion: This study has identified a brief 5-item measure of AL that arguably represents a universal and efficient set of biomarkers for capturing physiological 'wear and tear' and a further biomarker (PEF) that could usefully be included in future data collection. |
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Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysisAllostatic loadCumulative physiological dysregulationCohort studyBiomarkerIndividual participant data meta -analysisBackground: Allostatic load (AL) is a multi-system composite index for quantifying physiological dysregulation caused by life course stressors. For over 30 years, an extensive body of research has drawn on the AL framework but has been hampered by the lack of a consistent definition.Methods: This study analyses data for 67,126 individuals aged 40-111 years participating in 13 different cohort studies and 40 biomarkers across 12 physiological systems: hypothalamic-pituitary-adrenal (HPA) axis, sympathetic-adrenal-medullary (SAM) axis, parasympathetic nervous system functioning, oxidative stress, immunological/inflammatory, cardiovascular, respiratory, lipidemia, anthropometric, glucose metabolism, kidney, and liver. We use individual-participant-data meta-analysis and exploit natural heterogeneity in the number and type of biomarkers that have been used across studies, but a common set of health outcomes (grip strength, walking speed, and self-rated health), to determine the optimal configuration of parameters to define the concept.Results: There was at least one biomarker within 9/12 physiological systems that was reliably and consistently associated in the hypothesised direction with the three health outcomes in the meta-analysis of these cohorts: dehydroepiandrosterone sulfate (DHEAS), low frequency-heart rate variability (LF-HRV), C-reactive protein (CRP), resting heart rate (RHR), peak expiratory flow (PEF), high density lipoprotein cholesterol (HDL-C), waist -to-height ratio (WtHR), HbA1c, and cystatin C. An index based on five biomarkers (CRP, RHR, HDL-C, WtHR and HbA1c) available in every study was found to predict an independent outcome - mortality - as well or better than more elaborate sets of biomarkers.Discussion: This study has identified a brief 5-item measure of AL that arguably represents a universal and efficient set of biomarkers for capturing physiological 'wear and tear' and a further biomarker (PEF) that could usefully be included in future data collection.Elsevier20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/154140eng0306-453010.1016/j.psyneuen.2023.106117McCrory, CMcLoughlin, SLayte, RNiCheallaigh, CO'Halloran, AMBarros, HBerkman, LFBochud, MCrimmins, EMFarrell, MTFraga, SGrundy, EKelly-Irving, MPetrovic, DSeeman, TStringhini, SVollenveider, PKenny, RAinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T15:55:53Zoai:repositorio-aberto.up.pt:10216/154140Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:35:28.277981Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis |
title |
Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis |
spellingShingle |
Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis McCrory, C Allostatic load Cumulative physiological dysregulation Cohort study Biomarker Individual participant data meta -analysis |
title_short |
Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis |
title_full |
Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis |
title_fullStr |
Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis |
title_full_unstemmed |
Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis |
title_sort |
Towards a consensus definition of allostatic load: a multi-cohort, multi-system, multi-biomarker individual participant data (IPD) meta-analysis |
author |
McCrory, C |
author_facet |
McCrory, C McLoughlin, S Layte, R NiCheallaigh, C O'Halloran, AM Barros, H Berkman, LF Bochud, M Crimmins, EM Farrell, MT Fraga, S Grundy, E Kelly-Irving, M Petrovic, D Seeman, T Stringhini, S Vollenveider, P Kenny, RA |
author_role |
author |
author2 |
McLoughlin, S Layte, R NiCheallaigh, C O'Halloran, AM Barros, H Berkman, LF Bochud, M Crimmins, EM Farrell, MT Fraga, S Grundy, E Kelly-Irving, M Petrovic, D Seeman, T Stringhini, S Vollenveider, P Kenny, RA |
author2_role |
author author author author author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
McCrory, C McLoughlin, S Layte, R NiCheallaigh, C O'Halloran, AM Barros, H Berkman, LF Bochud, M Crimmins, EM Farrell, MT Fraga, S Grundy, E Kelly-Irving, M Petrovic, D Seeman, T Stringhini, S Vollenveider, P Kenny, RA |
dc.subject.por.fl_str_mv |
Allostatic load Cumulative physiological dysregulation Cohort study Biomarker Individual participant data meta -analysis |
topic |
Allostatic load Cumulative physiological dysregulation Cohort study Biomarker Individual participant data meta -analysis |
description |
Background: Allostatic load (AL) is a multi-system composite index for quantifying physiological dysregulation caused by life course stressors. For over 30 years, an extensive body of research has drawn on the AL framework but has been hampered by the lack of a consistent definition.Methods: This study analyses data for 67,126 individuals aged 40-111 years participating in 13 different cohort studies and 40 biomarkers across 12 physiological systems: hypothalamic-pituitary-adrenal (HPA) axis, sympathetic-adrenal-medullary (SAM) axis, parasympathetic nervous system functioning, oxidative stress, immunological/inflammatory, cardiovascular, respiratory, lipidemia, anthropometric, glucose metabolism, kidney, and liver. We use individual-participant-data meta-analysis and exploit natural heterogeneity in the number and type of biomarkers that have been used across studies, but a common set of health outcomes (grip strength, walking speed, and self-rated health), to determine the optimal configuration of parameters to define the concept.Results: There was at least one biomarker within 9/12 physiological systems that was reliably and consistently associated in the hypothesised direction with the three health outcomes in the meta-analysis of these cohorts: dehydroepiandrosterone sulfate (DHEAS), low frequency-heart rate variability (LF-HRV), C-reactive protein (CRP), resting heart rate (RHR), peak expiratory flow (PEF), high density lipoprotein cholesterol (HDL-C), waist -to-height ratio (WtHR), HbA1c, and cystatin C. An index based on five biomarkers (CRP, RHR, HDL-C, WtHR and HbA1c) available in every study was found to predict an independent outcome - mortality - as well or better than more elaborate sets of biomarkers.Discussion: This study has identified a brief 5-item measure of AL that arguably represents a universal and efficient set of biomarkers for capturing physiological 'wear and tear' and a further biomarker (PEF) that could usefully be included in future data collection. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023 2023-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/154140 |
url |
https://hdl.handle.net/10216/154140 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0306-4530 10.1016/j.psyneuen.2023.106117 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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