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Lua CZB, Gao Y, Li J, Cao X, Lyu X, Tu Y, Jin S, Liu Z. Influencing Factors of Healthy Aging Risk Assessed Using Biomarkers: A Life Course Perspective. China CDC Wkly 2024; 6:219-224. [PMID: 38532748 PMCID: PMC10961214 DOI: 10.46234/ccdcw2024.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 01/23/2024] [Indexed: 03/28/2024] Open
Abstract
Assessing individual risks of healthy aging using biomarkers and identifying associated factors have become important areas of research. In this study, we conducted a literature review of relevant publications between 2018 and 2023 in both Chinese and English databases. Previous studies have predominantly used single biomarkers, such as C-reactive protein, or focused on specific life course stages and factors such as socioeconomic status, mental health, educational levels, and unhealthy lifestyles. By summarizing the progress in this field, our study provides valuable insights and future directions for promoting healthy aging from a life course perspective.
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Affiliation(s)
- Cedric Zhang Bo Lua
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Yajie Gao
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Jinming Li
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Xingqi Cao
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Xinwei Lyu
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Yinuo Tu
- College of Chemical and Biological Engineering, Zhejiang University, Hangzhou City, Zhejiang Province, China
| | - Shuyi Jin
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
| | - Zuyun Liu
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou City, Zhejiang Province, China
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2
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Ravi S, Shanahan MJ, Levitt B, Harris KM, Cole SW. Socioeconomic inequalities in early adulthood disrupt the immune transcriptomic landscape via upstream regulators. Sci Rep 2024; 14:1255. [PMID: 38218990 PMCID: PMC10787749 DOI: 10.1038/s41598-024-51517-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 01/06/2024] [Indexed: 01/15/2024] Open
Abstract
Disparities in socio-economic status (SES) predict many immune system-related diseases, and previous research documents relationships between SES and the immune cell transcriptome. Drawing on a bioinformatically-informed network approach, we situate these findings in a broader molecular framework by examining the upstream regulators of SES-associated transcriptional alterations. Data come from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative sample of 4543 adults in the United States. Results reveal a network-of differentially expressed genes, transcription factors, and protein neighbors of transcription factors-that shows widespread SES-related dysregulation of the immune system. Mediational models suggest that body mass index (BMI) plays a key role in accounting for many of these associations. Overall, the results reveal the central role of upstream regulators in socioeconomic differences in the molecular basis of immunity, which propagate to increase risk of chronic health conditions in later-life.
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Affiliation(s)
- Sudharshan Ravi
- Jacobs Center for Productive Youth Development, University of Zürich, Andreasstrasse 15, 8050, Zürich, Switzerland.
| | - Michael J Shanahan
- Jacobs Center for Productive Youth Development, University of Zürich, Andreasstrasse 15, 8050, Zürich, Switzerland
- Department of Sociology, University of Zürich, 8050, Zürich, Switzerland
| | - Brandt Levitt
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27516, USA
| | - Kathleen Mullan Harris
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27516, USA
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-3210, USA
| | - Steven W Cole
- School of Medicine, University of California, Los Angeles, CA, 90095, USA
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3
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McDade TW. Three common assumptions about inflammation, aging, and health that are probably wrong. Proc Natl Acad Sci U S A 2023; 120:e2317232120. [PMID: 38064531 PMCID: PMC10740363 DOI: 10.1073/pnas.2317232120] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 11/02/2023] [Indexed: 12/18/2023] Open
Abstract
Chronic inflammation contributes to the onset and progression of cardiovascular disease and other degenerative diseases of aging. But does it have to? This article considers the associations among inflammation, aging, and health through the lens of human population biology and suggests that chronic inflammation is not a normal nor inevitable component of aging. It is commonly assumed that conclusions drawn from research in affluent, industrialized countries can be applied globally; that aging processes leading to morbidity and mortality begin in middle age; and that inflammation is pathological. These foundational assumptions have shifted focus away from inflammation as a beneficial response to infection or injury and toward an understanding of inflammation as chronic, dysregulated, and dangerous. Findings from community-based studies around the world-many conducted in areas with relatively high burdens of infectious disease-challenge these assumptions by documenting substantial variation in levels of inflammation and patterns of association with disease. They also indicate that nutritional, microbial, and psychosocial environments in infancy and childhood play important roles in shaping inflammatory phenotypes and their contributions to diseases of aging. A comparative, developmental, and ecological approach has the potential to generate novel insights into the regulation of inflammation and how it relates to human health over the life course.
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Affiliation(s)
- Thomas W. McDade
- Department of Anthropology, Northwestern University, Evanston, IL60208
- Institute for Policy Research, Northwestern University, Evanston, IL60208
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4
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Ravi S, Shanahan MJ, Levitt B, Harris KM, Cole SW. Socioeconomic inequalities in young adulthood disrupt the immune transcriptomic landscape via upstream regulators. RESEARCH SQUARE 2023:rs.3.rs-3295746. [PMID: 37720018 PMCID: PMC10503859 DOI: 10.21203/rs.3.rs-3295746/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/19/2023]
Abstract
Disparities in socio-economic status (SES) predict many immune system-related diseases, and previous research documents relationships between SES and the immune cell transcriptome. Drawing on a bioinformatically-informed network approach, we situate these findings in a broader molecular framework by examining the upstream regulators of SES-associated transcriptional alterations. Data come from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative sample of 4,543 adults in the United States. Results reveal a network-of differentially-expressed genes, transcription factors, and protein neighbors of transcription factors- that shows widespread SES-related dysregulation of the immune system. Mediational models suggest that body mass index plays a key role in accounting for many of these associations. Overall, the results reveal the central role of upstream regulators in socioeconomic differences in the molecular basis of immunity, which propagate to increase risk of chronic health conditions in later-life.
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5
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Cai A, Portengen L, Ertaylan G, Legler J, Vermeulen R, Lenters V, Remy S. Prenatal Exposure to Metabolism-Disrupting Chemicals, Cord Blood Transcriptome Perturbations, and Birth Weight in a Belgian Birth Cohort. Int J Mol Sci 2023; 24:ijms24087607. [PMID: 37108768 PMCID: PMC10141364 DOI: 10.3390/ijms24087607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/10/2023] [Accepted: 04/19/2023] [Indexed: 04/29/2023] Open
Abstract
Prenatal exposure to metabolism-disrupting chemicals (MDCs) has been linked to birth weight, but the molecular mechanisms remain largely unknown. In this study, we investigated gene expressions and biological pathways underlying the associations between MDCs and birth weight, using microarray transcriptomics, in a Belgian birth cohort. Whole cord blood measurements of dichlorodiphenyldichloroethylene (p,p'-DDE), polychlorinated biphenyls 153 (PCB-153), perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), and transcriptome profiling were conducted in 192 mother-child pairs. A workflow including a transcriptome-wide association study, pathway enrichment analysis with a meet-in-the-middle approach, and mediation analysis was performed to characterize the biological pathways and intermediate gene expressions of the MDC-birth weight relationship. Among 26,170 transcriptomic features, we successfully annotated five overlapping metabolism-related gene expressions associated with both an MDC and birth weight, comprising BCAT2, IVD, SLC25a16, HAS3, and MBOAT2. We found 11 overlapping pathways, and they are mostly related to genetic information processing. We found no evidence of any significant mediating effect. In conclusion, this exploratory study provides insights into transcriptome perturbations that may be involved in MDC-induced altered birth weight.
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Affiliation(s)
- Anran Cai
- Department of Population Health Sciences, Institute for Risk Assessment Sciences, Utrecht University, 3584 CM Utrecht, The Netherlands
- VITO Health, Flemish Institute for Technological Research (VITO), 2400 Mol, Belgium
| | - Lützen Portengen
- Department of Population Health Sciences, Institute for Risk Assessment Sciences, Utrecht University, 3584 CM Utrecht, The Netherlands
| | - Gökhan Ertaylan
- VITO Health, Flemish Institute for Technological Research (VITO), 2400 Mol, Belgium
| | - Juliette Legler
- Department of Population Health Sciences, Institute for Risk Assessment Sciences, Utrecht University, 3584 CM Utrecht, The Netherlands
| | - Roel Vermeulen
- Department of Population Health Sciences, Institute for Risk Assessment Sciences, Utrecht University, 3584 CM Utrecht, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands
| | - Virissa Lenters
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3584 CG Utrecht, The Netherlands
| | - Sylvie Remy
- VITO Health, Flemish Institute for Technological Research (VITO), 2400 Mol, Belgium
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6
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Vineis P. Invited Perspective: The Mysterious Case of Social Determinants of Health. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:111303. [PMID: 36350666 PMCID: PMC9645432 DOI: 10.1289/ehp12030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/28/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Affiliation(s)
- Paolo Vineis
- Medical Research Council Centre for Environment and Health, Imperial College, London, UK
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7
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Lepamets M, Auwerx C, Nõukas M, Claringbould A, Porcu E, Kals M, Jürgenson T, Morris AP, Võsa U, Bochud M, Stringhini S, Wijmenga C, Franke L, Peterson H, Vilo J, Lepik K, Mägi R, Kutalik Z. Omics-informed CNV calls reduce false-positive rates and improve power for CNV-trait associations. HGG ADVANCES 2022; 3:100133. [PMID: 36035246 PMCID: PMC9399386 DOI: 10.1016/j.xhgg.2022.100133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 07/26/2022] [Indexed: 11/29/2022] Open
Abstract
Copy-number variations (CNV) are believed to play an important role in a wide range of complex traits, but discovering such associations remains challenging. While whole-genome sequencing (WGS) is the gold-standard approach for CNV detection, there are several orders of magnitude more samples with available genotyping microarray data. Such array data can be exploited for CNV detection using dedicated software (e.g., PennCNV); however, these calls suffer from elevated false-positive and -negative rates. In this study, we developed a CNV quality score that weights PennCNV calls (pCNVs) based on their likelihood of being true positive. First, we established a measure of pCNV reliability by leveraging evidence from multiple omics data (WGS, transcriptomics, and methylomics) obtained from the same samples. Next, we built a predictor of omics-confirmed pCNVs, termed omics-informed quality score (OQS), using only PennCNV software output parameters. Promisingly, OQS assigned to pCNVs detected in close family members was up to 35% higher than the OQS of pCNVs not carried by other relatives (p < 3.0 × 10−90), outperforming other scores. Finally, in an association study of four anthropometric traits in 89,516 Estonian Biobank samples, the use of OQS led to a relative increase in the trait variance explained by CNVs of up to 56% compared with published quality filtering methods or scores. Overall, we put forward a flexible framework to improve any CNV detection method leveraging multi-omics evidence, applied it to improve PennCNV calls, and demonstrated its utility by improving the statistical power for downstream association analyses.
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Affiliation(s)
- Maarja Lepamets
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia
- Corresponding author
| | - Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
| | - Margit Nõukas
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia
| | | | - Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
| | - Mart Kals
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki 00014, Finland
| | - Tuuli Jürgenson
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu 51009, Estonia
| | | | - Andrew Paul Morris
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester M13 9PL, UK
| | - Urmo Võsa
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
| | - Silvia Stringhini
- Unit of Population Epidemiology, Division of Primary Care, Geneva 1205, Switzerland
| | - Cisca Wijmenga
- University of Groningen, University Medical Center Groningen, Department of Genetics, 9713 AV Groningen, the Netherlands
| | - Lude Franke
- University of Groningen, University Medical Center Groningen, Department of Genetics, 9713 AV Groningen, the Netherlands
- Oncode Institute, 3521 AL Utrecht, the Netherlands
| | - Hedi Peterson
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Jaak Vilo
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Kaido Lepik
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
- Institute of Computer Science, University of Tartu, Tartu 51009, Estonia
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- Center for Primary Care and Public Health (Unisanté), Department of Epidemiology and Health Systems, University of Lausanne, Lausanne 1010, Switzerland
- Corresponding author
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8
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Fiorito G, Pedron S, Ochoa-Rosales C, McCrory C, Polidoro S, Zhang Y, Dugué PA, Ratliff S, Zhao WN, McKay GJ, Costa G, Solinas MG, Harris KM, Tumino R, Grioni S, Ricceri F, Panico S, Brenner H, Schwettmann L, Waldenberger M, Matias-Garcia PR, Peters A, Hodge A, Giles GG, Schmitz LL, Levine M, Smith JA, Liu Y, Kee F, Young IS, McGuinness B, McKnight AJ, van Meurs J, Voortman T, Kenny RA, Vineis P, Carmeli C. The Role of Epigenetic Clocks in Explaining Educational Inequalities in Mortality: A Multicohort Study and Meta-analysis. J Gerontol A Biol Sci Med Sci 2022; 77:1750-1759. [PMID: 35172329 PMCID: PMC10310990 DOI: 10.1093/gerona/glac041] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Indexed: 11/13/2022] Open
Abstract
Educational inequalities in all-cause mortality have been observed for decades. However, the underlying biological mechanisms are not well known. We aimed to assess the role of DNA methylation changes in blood captured by epigenetic clocks in explaining these inequalities. Data were from 8 prospective population-based cohort studies, representing 13 021 participants. First, educational inequalities and their portion explained by Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, and DNAmGrimAge epigenetic clocks were assessed in each cohort via counterfactual-based mediation models, on both absolute (hazard difference) and relative (hazard ratio) scales, and by sex. Second, estimates from each cohort were pooled through a random effect meta-analysis model. Men with low education had excess mortality from all causes of 57 deaths per 10 000 person-years (95% confidence interval [CI]: 38, 76) compared with their more advantaged counterparts. For women, the excess mortality was 4 deaths per 10 000 person-years (95% CI: -11, 19). On the relative scale, educational inequalities corresponded to hazard ratios of 1.33 (95% CI: 1.12, 1.57) for men and 1.15 (95% CI: 0.96, 1.37) for women. DNAmGrimAge accounted for the largest proportion, approximately 50%, of the educational inequalities for men, while the proportion was negligible for women. Most of this mediation was explained by differential effects of unhealthy lifestyles and morbidities of the World Health Organization (WHO) risk factors for premature mortality. These results support DNA methylation-based epigenetic aging as a signature of educational inequalities in life expectancy emphasizing the need for policies to address the unequal social distribution of these WHO risk factors.
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Affiliation(s)
- Giovanni Fiorito
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- MRC Centre for Environment and Health, School of Public Health, Imperial College
London, London, UK
| | - Sara Pedron
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
- Professorship of Public Health and Prevention, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Carolina Ochoa-Rosales
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Centro de Vida Saludable de la Universidad de Conceptión, Conceptiòn, Chile
| | - Cathal McCrory
- Department of Medical Gerontology, Trinity College Dublin, Dublin, Ireland
| | | | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Munich, Germany
| | - Pierre-Antoine Dugué
- Cancer Epidemiology Division, Cancer Council Victoria, Victoria, Australia
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Scott Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Wei N Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Gareth J McKay
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
| | - Giuseppe Costa
- Epidemiology Unit, Regional Health Service TO3, Grugliasco, Italy
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | | | - Kathleen Mullan Harris
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP 7), Ragusa, Italy
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Fulvio Ricceri
- Epidemiology Unit, Regional Health Service TO3, Grugliasco, Italy
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, University of Naples Federico II, Naples, Italy
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Munich, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Lars Schwettmann
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
- Department of Economics, Martin Luther University, Halle-Wittenberg, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Pamela R Matias-Garcia
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Victoria, Australia
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Victoria, Australia
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Lauren L Schmitz
- Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Morgan Levine
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Jennifer A Smith
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Yongmei Liu
- Division of Cardiology, Department of Medicine, School of Medicine, Duke University, Durham, North Carolina, USA
| | - Frank Kee
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
| | - Ian S Young
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
| | | | - Amy Jayne McKnight
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
| | - Joyce van Meurs
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Rose A Kenny
- Department of Medical Gerontology, Trinity College Dublin, Dublin, Ireland
| | | | - Paolo Vineis
- MRC Centre for Environment and Health, School of Public Health, Imperial College
London, London, UK
| | - Cristian Carmeli
- Population Health Laboratory, University of Fribourg, Fribourg, Switzerland
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9
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Powell-Wiley TM, Baumer Y, Baah FO, Baez AS, Farmer N, Mahlobo CT, Pita MA, Potharaju KA, Tamura K, Wallen GR. Social Determinants of Cardiovascular Disease. Circ Res 2022; 130:782-799. [PMID: 35239404 PMCID: PMC8893132 DOI: 10.1161/circresaha.121.319811] [Citation(s) in RCA: 199] [Impact Index Per Article: 99.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Social determinants of health (SDoH), which encompass the economic, social, environmental, and psychosocial factors that influence health, play a significant role in the development of cardiovascular disease (CVD) risk factors as well as CVD morbidity and mortality. The COVID-19 pandemic and the current social justice movement sparked by the death of George Floyd have laid bare long-existing health inequities in our society driven by SDoH. Despite a recent focus on these structural drivers of health disparities, the impact of SDoH on cardiovascular health and CVD outcomes remains understudied and incompletely understood. To further investigate the mechanisms connecting SDoH and CVD, and ultimately design targeted and effective interventions, it is important to foster interdisciplinary efforts that incorporate translational, epidemiological, and clinical research in examining SDoH-CVD relationships. This review aims to facilitate research coordination and intervention development by providing an evidence-based framework for SDoH rooted in the lived experiences of marginalized populations. Our framework highlights critical structural/socioeconomic, environmental, and psychosocial factors most strongly associated with CVD and explores several of the underlying biologic mechanisms connecting SDoH to CVD pathogenesis, including excess stress hormones, inflammation, immune cell function, and cellular aging. We present landmark studies and recent findings about SDoH in our framework, with careful consideration of the constructs and measures utilized. Finally, we provide a roadmap for future SDoH research focused on individual, clinical, and policy approaches directed towards developing multilevel community-engaged interventions to promote cardiovascular health.
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Affiliation(s)
- Tiffany M Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD.,Intramural Research Program, National Institute on Minority Health and Health Disparities (T.M.P.-W.), National Institutes of Health, Bethesda, MD
| | - Yvonne Baumer
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Foster Osei Baah
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Andrew S Baez
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Nicole Farmer
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, MD (N.F., G.R.W.)
| | - Christa T Mahlobo
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD.,The Pennsylvania State University (C.T.M.)
| | - Mario A Pita
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Kameswari A Potharaju
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Kosuke Tamura
- Neighborhood Social and Geospatial Determinants of Health Disparities Laboratory, Population and Community Sciences Branch, Intramural Research Program, National Institute on Minority Health and Health Disparities (K.T.), National Institutes of Health, Bethesda, MD
| | - Gwenyth R Wallen
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, MD (N.F., G.R.W.)
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Melchior M. Invited Commentary: Is the Long Shadow of Childhood Disadvantage on Lifelong Health Getting Worse Over Time? Am J Epidemiol 2021; 190:2294-2296. [PMID: 34100079 DOI: 10.1093/aje/kwab168] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 03/31/2021] [Accepted: 04/05/2021] [Indexed: 12/17/2022] Open
Abstract
Social inequalities in health and their early-life origins have been extensively documented. Although the complex direct and intermediate mechanisms linking early-life disadvantage to later health are not yet fully understood, new findings on biological markers distinctly related with early-life experiences suggest a causal relationship. In this issue, Fuller-Rowell et al. (Am J Epidemiol. 2021:190(11):2284-2293) step back to examine the role of childhood disadvantage in the United States in different periods, observing that the relationship with later health seems to have strengthened over time. The main explanation the authors bring up has to do with increased income segregation and changes in labor market composition that limit opportunities for persons with low educational attainment. In other words, while the rich get richer, the poor get poorer, the middle class shrinks, and there are fewer interactions across different socioeconomic groups and the social ladder is blocked. Other evidence suggests that investments in children, through early education and academic support programs, could help reduce the consequences of childhood disadvantage on long-term health.
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Boardman JD, Fletcher JM. Evaluating the Continued Integration of Genetics into Medical Sociology. JOURNAL OF HEALTH AND SOCIAL BEHAVIOR 2021; 62:404-418. [PMID: 34355610 PMCID: PMC8771926 DOI: 10.1177/00221465211032581] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The 2010 special issue of Journal of Health and Social Behavior, titled "Fifty Years of Medical Sociology," defined the contours of the medical sociological perspective. We use this as a backdrop to outline and assess the continued integration of genetics into medical sociology research. We contend that the explosion of genetic and epigenetic data in population health data sources has made the medical sociological perspective increasingly relevant to researchers outside of sociology, including public health, epidemiology, and quantitative genetics. We describe vast, underappreciated, and mostly unsolved challenges that limit the scientifically appropriate interest in incorporating genetics into existing paradigms. It is our hope that medical sociologists continue this integration but redouble efforts to maintain the core insights in social science research, such as the importance of environmental and structural (i.e., nonbiological) factors in determining health processes and outcomes and the use of rich, integrated, and rigorous empirical analyses.
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