health and research journal impact factor

BMC Health Services Research

Latest collections open to submissions, new: digital health and the healthcare workforce.

Guest Edited by Karen Day, Kerryn Butler-Henderson & Clair Sullivan

New: Researching and measuring inequalities in healthcare

Guest Edited by Magdalena Szaflarski & Zhonghua Wang

Sustainability in health services

Guest Edited by Virginia McKay & Judith Singleton 

Rural health services research

Guest Edited by Birgit Abelsen and Selina Taylor

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Advancing epidemic preparedness of health systems  

Guest edited by Yibeltal Assefa Alemu, Carl Abelardo T. Antonio​​​​​, Julie ​​​Balen & Megan Schmidt-Sane

Health services for substance use disorders

Guest edited by Chaisiri Angkurawaranon, Berkeley Franz, João Pedro Silva

Health workforce planning

Guest edited by Madhan Balasubramanian and Sunny C. Okoroafor

• Most accessed
• Latest collections

Drawing up the public national Rational Pharmacotherapy Action Plan as part of social and health services reform in Finland: a bottom-up approach involving stakeholders

Authors: Heidi Tahvanainen, Liisa-Maria Voipio-Pulkki, Katri Hämeen-Anttila, Ulla Närhi, Taina Mäntyranta, Anna-Riia Holmström and Marja Airaksinen

Follow-up after major traumatic injury: a survey of services in Australian and New Zealand public hospitals

Authors: Elizabeth Wake, Jamie Ranse, Don Campbell, Belinda Gabbe and Andrea P. Marshall

“I do not know the advantages of having a general practitioner” - a qualitative study exploring the views of low-acuity emergency patients without a regular general practitioner toward primary care

Authors: Lisa Kümpel, Sarah Oslislo, Rebecca Resendiz Cantu, Martin Möckel, Christoph Heintze and Felix Holzinger

Developing comprehensive woman hand-held case notes to improve quality of antenatal care in low-income settings: participatory approach with maternal health stakeholders in Malawi

Authors: Leonard Mndala, Chifundo Kondoni, Luis Gadama, Catherine Bamuya, Annie Kuyere, Bertha Maseko, Fannie Kachale, Mtisunge Joshua Gondwe, David Lissauer and Alinane Linda Nyondo-Mipando

Care fragmentation and readmission mortality and length of stay before and during the COVID-19 pandemic: data from the National Readmissions Database, 2018–2020

Authors: Sara Turbow, Tiffany Walker, Steven Culler and Mohammed K. Ali

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Relationship between Organizational Culture, Leadership Behavior and Job Satisfaction

Authors: Yafang Tsai

How nurses and their work environment affect patient experiences of the quality of care: a qualitative study

Authors: Renate AMM Kieft, Brigitte BJM de Brouwer, Anneke L Francke and Diana MJ Delnoij

Proceedings of the 3rd IPLeiria’s International Health Congress

Authors: Catarina Cardoso Tomás, Emanuel Oliveira, D. Sousa, M. Uba-Chupel, G. Furtado, C. Rocha, A. Teixeira, P. Ferreira, Celeste Alves, Stefan Gisin, Elisabete Catarino, Nelma Carvalho, Tiago Coucelo, Luís Bonfim, Carina Silva, Débora Franco…

Characteristics of successful changes in health care organizations: an interview study with physicians, registered nurses and assistant nurses

Authors: Per Nilsen, Ida Seing, Carin Ericsson, Sarah A. Birken and Kristina Schildmeijer

PICO, PICOS and SPIDER: a comparison study of specificity and sensitivity in three search tools for qualitative systematic reviews

Authors: Abigail M Methley, Stephen Campbell, Carolyn Chew-Graham, Rosalind McNally and Sudeh Cheraghi-Sohi

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Innovations for better health and social justice Edited by: Dr. Magdalena Szaflarski Collection published: 30th May 2022

Advancing Dementia Care Edited by: Dr. Clarissa Giebel and Tillie Cryer Collection published: 13 May 2020

Health Services Research for Opioid Use Disorders Edited by: Dr. Kim Hoffman Collection published: 31 March 2020

Management of Infectious Diseases in Health Systems and Services Edited by: Tillie Cryer Collection published: 19 March 2020

Aims and scope

BMC Health Services Research  is an open access, peer-reviewed journal that considers articles on all aspects of health services research. The journal has a special focus on digital health, governance, health policy, health system quality and safety, healthcare delivery and access to healthcare, healthcare financing and economics, implementing reform, and the health workforce.  

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Highlights of the BMC Series – February 2024

21 March 2024

Highlights of the BMC Series – November 2023

22 December 2023

World AIDS Day 2023: Highlights from the BMC Series

01 December 2023

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Affiliated with

Journal of Public Health

Impact Factor 1.8 (2022)

5 Year Impact Factor 1.7 (2022)

Cite Score 6.3 (2022)

Social Media Mentions 1,550 (2022)

Downloads 459,887 (2022)

Health Services and Outcomes Research Methodology

Impact Factor 1.5 (2022)

5 Year Impact Factor 1.8 (2022)

Cite Score 2.7 (2022)

Social Media Mentions 122 (2022)

Downloads 77,410 (2022)

Journal of Contemporary Psychotherapy

Impact Factor 2.0 (2022)

Cite Score 3.7 (2022)

H5 Index 20 (2021)

Social Media Mentions 620 (2022)

Downloads 228,897 (2022)

Journal of the Egyptian Public Health Association

Impact Factor 3.7 (2022)

Cite Score 5.0 (2022)

H5 Index 17 (2021)

Social Media Mentions 120 (2022)

Downloads 256,236 (2022)

AIDS and Behavior

Impact Factor 4.4 (2022)

5 Year Impact Factor 4.1 (2022)

H5 Index 63 (2021)

Social Media Mentions 6,442 (2022)

Downloads 1,000,081 (2022)

International Journal of Mental Health and Addiction

Impact Factor 8.0 (2022)

5 Year Impact Factor 6.4 (2022)

Cite Score 14.2 (2022)

Social Media Mentions 2,529 (2022)

Downloads 1,253,475 (2022)

European Journal of Epidemiology

Impact Factor 13.6 (2022)

5 Year Impact Factor 11.9 (2022)

Cite Score 18.6 (2022)

H5 Index 62 (2021)

Social Media Mentions 120,827 (2022)

Downloads 1,616,738 (2022)

Chinese Journal of Integrative Medicine

Impact Factor 2.9 (2022)

5 Year Impact Factor 2.6 (2022)

Cite Score 5.3 (2022)

H5 Index 26 (2021)

Social Media Mentions 912 (2022)

Downloads 105,617 (2022)

Current Epidemiology Reports

Impact Factor 3.3 (2022)

H5 Index 28 (2021)

Social Media Mentions 1,338 (2022)

Downloads 121,778 (2022)

Current Medical Science

Impact Factor 2.4 (2022)

5 Year Impact Factor 2.3 (2022)

Cite Score 4.2 (2022)

H5 Index 25 (2021)

Social Media Mentions 353 (2022)

Downloads 123,042 (2022)

The Journal of Behavioral Health Services & Research

Impact Factor 1.9 (2022)

5 Year Impact Factor 2.1 (2022)

Cite Score 3.3 (2022)

H5 Index 21 (2021)

Social Media Mentions 442 (2022)

Downloads 170,583 (2022)

Impact Factor 3.2 (2022)

5 Year Impact Factor 3.3 (2022)

Cite Score 5.1 (2022)

H5 Index 30 (2021)

Downloads 171,278 (2022)

Journal of Prevention

Impact Factor 1.7 (2022)

Cite Score 2.8 (2022)

H5 Index 22 (2021)

Social Media Mentions 907 (2022)

Downloads 175,325 (2022)

Current HIV/AIDS Reports

Impact Factor 4.6 (2022)

5 Year Impact Factor 5.6 (2022)

Cite Score 8.5 (2022)

H5 Index 34 (2021)

Social Media Mentions 1,115 (2022)

Downloads 200,769 (2022)

Health Care Analysis

5 Year Impact Factor 2.2 (2022)

Cite Score 4.0 (2022)

Social Media Mentions 676 (2022)

Downloads 215,828 (2022)

Journal of Clinical Psychology in Medical Settings

Impact Factor 2.2 (2022)

Cite Score 3.5 (2022)

Social Media Mentions 493 (2022)

Downloads 221,837 (2022)

Impact Factor 2.5 (2022)

5 Year Impact Factor 2.9 (2022)

Cite Score 6.1 (2022)

Social Media Mentions 2,257 (2022)

Downloads 274,816 (2022)

Applied Health Economics and Health Policy

Impact Factor 3.6 (2022)

5 Year Impact Factor 3.5 (2022)

Cite Score 5.6 (2022)

Social Media Mentions 2,474 (2022)

Downloads 290,197 (2022)

International Journal of Behavioral Medicine

Impact Factor 2.7 (2022)

5 Year Impact Factor 2.7 (2022)

Social Media Mentions 1,628 (2022)

Downloads 325,069 (2022)

Administration and Policy in Mental Health and Mental Health Services Research

Impact Factor 2.6 (2022)

Cite Score 4.5 (2022)

H5 Index 38 (2021)

Social Media Mentions 1,803 (2022)

Downloads 396,280 (2022)

Journal of Behavioral Medicine

Impact Factor 3.1 (2022)

Cite Score 5.4 (2022)

H5 Index 41 (2021)

Social Media Mentions 4,117 (2022)

Downloads 408,484 (2022)

Canadian Journal of Public Health

Impact Factor 4.3 (2022)

H5 Index 31 (2021)

Social Media Mentions 264 (2022)

Downloads 415,196 (2022)

Journal of Cancer Survivorship

5 Year Impact Factor 4.4 (2022)

Cite Score 6.8 (2022)

H5 Index 42 (2021)

Social Media Mentions 3,708 (2022)

Downloads 432,215 (2022)

Lasers in Medical Science

Impact Factor 2.1 (2022)

5 Year Impact Factor 2.5 (2022)

Cite Score 4.4 (2022)

H5 Index 44 (2021)

Social Media Mentions 1,428 (2022)

Downloads 456,455 (2022)

Prevention Science

Impact Factor 3.5 (2022)

5 Year Impact Factor 4.2 (2022)

Cite Score 6.5 (2022)

H5 Index 50 (2021)

Social Media Mentions 2,557 (2022)

Downloads 512,415 (2022)

Journal of Urban Health

Impact Factor 6.6 (2022)

5 Year Impact Factor 5.2 (2022)

Cite Score 8.7 (2022)

Social Media Mentions 9,716 (2022)

Downloads 529,342 (2022)

Journal of Immigrant and Minority Health

H5 Index 40 (2021)

Social Media Mentions 1,356 (2022)

Downloads 542,048 (2022)

Journal of Community Health

Impact Factor 5.9 (2022)

5 Year Impact Factor 3.9 (2022)

Cite Score 8.1 (2022)

Social Media Mentions 2,570 (2022)

Downloads 569,790 (2022)

The European Journal of Health Economics

5 Year Impact Factor 4.0 (2022)

H5 Index 39 (2021)

Social Media Mentions 2,041 (2022)

Downloads 578,663 (2022)

Journal of Racial and Ethnic Health Disparities

Impact Factor 3.9 (2022)

5 Year Impact Factor 3.8 (2022)

Cite Score 5.9 (2022)

Social Media Mentions 4,520 (2022)

Downloads 590,047 (2022)

Journal of Epidemiology and Global Health

Impact Factor 7.3 (2022)

5 Year Impact Factor 5.9 (2022)

Cite Score 8.8 (2022)

Social Media Mentions 348 (2022)

Downloads 65,979 (2022)

International Journal of Health Economics and Management

5 Year Impact Factor 1.9 (2022)

Cite Score 3.0 (2022)

Social Media Mentions 142 (2022)

Downloads 66,434 (2022)

Maternal and Child Health Journal

Impact Factor 2.3 (2022)

5 Year Impact Factor 2.8 (2022)

Cite Score 3.2 (2022)

H5 Index 43 (2021)

Social Media Mentions 2,982 (2022)

Downloads 741,647 (2022)

Journal of Endocrinological Investigation

Impact Factor 5.4 (2022)

5 Year Impact Factor 4.6 (2022)

H5 Index 52 (2021)

Social Media Mentions 16,912 (2022)

Downloads 797,059 (2022)

Journal of Religion and Health

Impact Factor 2.8 (2022)

Cite Score 4.3 (2022)

H5 Index 47 (2021)

Social Media Mentions 5,689 (2022)

Downloads 803,935 (2022)

Frontiers of Medicine

Impact Factor 8.1 (2022)

Cite Score 16.0 (2022)

Social Media Mentions 809 (2022)

Downloads 87,781 (2022)

International Journal of Diabetes in Developing Countries

Impact Factor 0.9 (2022)

5 Year Impact Factor 0.8 (2022)

Cite Score 1.4 (2022)

H5 Index 15 (2021)

Social Media Mentions 106 (2022)

Downloads 98,936 (2022)

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Health Research Policy and Systems

Aims and scope.

Health Research Policy and Systems covers all aspects of the organisation and use of health research – including agenda setting, building health research capacity, and how research as a whole benefits decision makers, practitioners in health and related fields, and society at large.

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All Health Systems Global members receive a 20% discount on  Health Research Policy and Systems  Article Processing Charges (APCs). To claim the discount, please contact the Secretariat at  [email protected]  to obtain the BMC journals' discount code.

• Most accessed

Research outcomes informing the selection of public health interventions and strategies to implement them: A cross-sectional survey of Australian policy-maker and practitioner preferences

Authors: Luke Wolfenden, Alix Hall, Adrian Bauman, Andrew Milat, Rebecca Hodder, Emily Webb, Kaitlin Mooney, Serene Yoong, Rachel Sutherland and Sam McCrabb

The TransFORmation of IndiGEnous PrimAry HEAlthcare Delivery (FORGE AHEAD): economic analysis

Authors: Aleksandra Stanimirovic, Troy Francis, Susan Webster-Bogaert, Stewart Harris and Valeria Rac

Engaging communities as partners in health crisis response: a realist-informed scoping review for research and policy

Authors: Mateus Kambale Sahani, Harro Maat, Dina Balabanova, Mirkuzie Woldie, Paul Richards and Susannah Mayhew

Prioritization of maternal and newborn health policies and their implementation in the eastern conflict affected areas of the Democratic Republic of Congo: a political economy analysis

Authors: Rosine Nshobole Bigirinama, Mamothena Carol Mothupi, Pacifique Lyabayungu Mwene-Batu, Naoko Kozuki, Christian Zalinga Chiribagula, Christine Murhim’alika Chimanuka, Gaylord Amani Ngaboyeka and Ghislain Balaluka Bisimwa

What is context in knowledge translation? Results of a systematic scoping review

Authors: Tugce Schmitt, Katarzyna Czabanowska and Peter Schröder-Bäck

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The utilisation of health research in policy-making: concepts, examples and methods of assessment

Authors: Stephen R Hanney, Miguel A Gonzalez-Block, Martin J Buxton and Maurice Kogan

The application of systems thinking in health: why use systems thinking?

Authors: David H Peters

The role of NGOs in global health research for development

Authors: Hélène Delisle, Janet Hatcher Roberts, Michelle Munro, Lori Jones and Theresa W Gyorkos

How to engage stakeholders in research: design principles to support improvement

Authors: Annette Boaz, Stephen Hanney, Robert Borst, Alison O’Shea and Maarten Kok

The 10 largest public and philanthropic funders of health research in the world: what they fund and how they distribute their funds

Authors: Roderik F. Viergever and Thom C. C. Hendriks

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Featured article

Identifying priority technical and context-specific issues in improving the conduct, reporting and use of health economic evaluation in low- and middle-income countries

Health Research Policy and Systems (2018) 16 :4

The authors aim to identify the top priority issues that impede the conduct, reporting and use of economic evaluation as well as potential solutions as an input for future research topics by the international Decision Support Initiative and other movements.

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2022 Citation Impact 4.0 - 2-year Impact Factor 4.3 - 5-year Impact Factor 1.820 - SNIP (Source Normalized Impact per Paper) 1.353 - SJR (SCImago Journal Rank)

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Journal of Health Research , Open Access

Issue(s) available: 30 – From Volume: 32 Issue: 1 , to Volume: 36 Issue: 6

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The set of journals have been ranked according to their SJR and divided into four equal groups, four quartiles. Q1 (green) comprises the quarter of the journals with the highest values, Q2 (yellow) the second highest values, Q3 (orange) the third highest values and Q4 (red) the lowest values.

The SJR is a size-independent prestige indicator that ranks journals by their 'average prestige per article'. It is based on the idea that 'all citations are not created equal'. SJR is a measure of scientific influence of journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from It measures the scientific influence of the average article in a journal, it expresses how central to the global scientific discussion an average article of the journal is.

Evolution of the number of published documents. All types of documents are considered, including citable and non citable documents.

This indicator counts the number of citations received by documents from a journal and divides them by the total number of documents published in that journal. The chart shows the evolution of the average number of times documents published in a journal in the past two, three and four years have been cited in the current year. The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric.

Evolution of the total number of citations and journal's self-citations received by a journal's published documents during the three previous years. Journal Self-citation is defined as the number of citation from a journal citing article to articles published by the same journal.

Evolution of the number of total citation per document and external citation per document (i.e. journal self-citations removed) received by a journal's published documents during the three previous years. External citations are calculated by subtracting the number of self-citations from the total number of citations received by the journal’s documents.

International Collaboration accounts for the articles that have been produced by researchers from several countries. The chart shows the ratio of a journal's documents signed by researchers from more than one country; that is including more than one country address.

Not every article in a journal is considered primary research and therefore "citable", this chart shows the ratio of a journal's articles including substantial research (research articles, conference papers and reviews) in three year windows vs. those documents other than research articles, reviews and conference papers.

Ratio of a journal's items, grouped in three years windows, that have been cited at least once vs. those not cited during the following year.

Evolution of the percentage of female authors.

Evolution of the number of documents cited by public policy documents according to Overton database.

Evoution of the number of documents related to Sustainable Development Goals defined by United Nations. Available from 2018 onwards.

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Peer-reviewed

Research Article

Cardiovascular health and cancer risk associated with plant based diets: An umbrella review

Roles Conceptualization, Data curation, Formal analysis, Writing – original draft

Affiliations Department of Biomedical and Neuromotor Science, Alma Mater Studiorum–University of Bologna, Bologna, Italy, Interdisciplinary Research Center for Health Science, Sant’Anna School of Advanced Studies, Pisa, Tuscany, Italy

Roles Conceptualization, Formal analysis, Writing – review & editing

Affiliation Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom

Roles Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Biomedical and Neuromotor Science, Alma Mater Studiorum–University of Bologna, Bologna, Italy

Roles Conceptualization, Supervision, Writing – review & editing

Affiliation Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA, United States of America

Affiliation Department of Translational Medicine, University of Eastern Piedmont, (UNIUPO), Novara, Italy

Roles Conceptualization, Data curation, Writing – review & editing

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

Affiliation IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma Neurochirurgia Ipofisi—Pituitary Unit, Bologna, Italy

• Angelo Capodici, 
• Gabriele Mocciaro, 
• Davide Gori, 
• Matthew J. Landry, 
• Alice Masini, 
• Francesco Sanmarchi, 
• Matteo Fiore, 
• Angela Andrea Coa, 
• Gisele Castagna, 

• Published: May 15, 2024
• https://doi.org/10.1371/journal.pone.0300711
• Reader Comments

Cardiovascular diseases (CVDs) and cancer are the two main leading causes of death and disability worldwide. Suboptimal diet, poor in vegetables, fruits, legumes and whole grain, and rich in processed and red meat, refined grains, and added sugars, is a primary modifiable risk factor. Based on health, economic and ethical concerns, plant-based diets have progressively widespread worldwide.

This umbrella review aims at assessing the impact of animal-free and animal-products-free diets (A/APFDs) on the risk factors associated with the development of cardiometabolic diseases, cancer and their related mortalities.

Data sources

PubMed and Scopus were searched for reviews, systematic reviews, and meta-analyses published from 1st January 2000 to 31st June 2023, written in English and involving human subjects of all ages. Primary studies and reviews/meta-analyses based on interventional trials which used A/APFDs as a therapy for people with metabolic diseases were excluded.

Data extraction

The umbrella review approach was applied for data extraction and analysis. The revised AMSTAR-R 11-item tool was applied to assess the quality of reviews/meta-analyses.

Overall, vegetarian and vegan diets are significantly associated with better lipid profile, glycemic control, body weight/BMI, inflammation, and lower risk of ischemic heart disease and cancer. Vegetarian diet is also associated with lower mortality from CVDs. On the other hand, no difference in the risk of developing gestational diabetes and hypertension were reported in pregnant women following vegetarian diets. Study quality was average. A key limitation is represented by the high heterogeneity of the study population in terms of sample size, demography, geographical origin, dietary patterns, and other lifestyle confounders.

Conclusions

Plant-based diets appear beneficial in reducing cardiometabolic risk factors, as well as CVDs, cancer risk and mortality. However, caution should be paid before broadly suggesting the adoption of A/AFPDs since the strength-of-evidence of study results is significantly limited by the large study heterogeneity alongside the potential risks associated with potentially restrictive regimens.

Citation: Capodici A, Mocciaro G, Gori D, Landry MJ, Masini A, Sanmarchi F, et al. (2024) Cardiovascular health and cancer risk associated with plant based diets: An umbrella review. PLoS ONE 19(5): e0300711. https://doi.org/10.1371/journal.pone.0300711

Editor: Melissa Orlandin Premaor, Federal University of Minas Gerais: Universidade Federal de Minas Gerais, BRAZIL

Received: January 8, 2024; Accepted: March 4, 2024; Published: May 15, 2024

Copyright: © 2024 Capodici et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Cardiovascular diseases (CVDs) and cancer currently represent the leading causes of death and disability worldwide. Studies performed on large cohorts worldwide have identified several modifiable and non-modifiable risk factors. Among them, robust evidence supports diet as a major modifiable risk factor [ 1 ].

A suboptimal diet, marked by insufficient consumption of fruits, vegetables, legumes, and whole grains, coupled with an excessive intake of meat (particularly red and processed), salt, refined grains and sugar, has been shown to notably elevate both mortality rates and disability-adjusted life years. Over time, these dietary choices have led to a concerning increase in health-related issues [ 1 , 2 ].

Additionally, the reduction of products of animal origin in favor of vegetarian ones has been suggested to reduce CVD and cancer risk [ 3 , 4 ]. Several major professional and scientific organizations encourage the adoption of vegetarian and vegan diets for the prevention and treatment of a range of chronic metabolic diseases such as atherosclerosis, type 2 diabetes, hypertension and obesity [ 5 , 6 ]. Ethical, environmental, and socio-economic concerns have contributed to the widespread growth of plant-based diets, particularly vegetarian and vegan options [ 7 – 9 ]. 2014 cross-national governmental survey estimated that approximately 75 million people around the globe deliberately followed a vegetarian diet, while an additional 1,45 million were obliged to because of socio-economic factors [ 10 , 11 ].

At the same time, study heterogeneity in terms of plant-based dietary regimens (from limitation of certain types to the total exclusion of animal products), their association with other lifestyle factors, patient demographic and geographical features, associated diseases, as well as study design and duration, significantly limit the assessment of the real benefits associated with animal-free and animal-products-free diets (A/APFDs). Finally, an increasing number of studies have highlighted the potential threatening consequences of chronic vitamin and mineral deficiencies induced by these diets (e.g., megaloblastic anemia due to vitamin B12 deficiency), especially more restrictive ones and in critical periods of life, like pregnancy and early childhood [ 5 ].

Based on these premises, our umbrella review aims at assessing the impact of animal-free and animal-products-free diets (A/APFDs) on the risk factors associated with the development of cardiometabolic diseases, cancer and their related mortalities in both the adult and the pediatric population, as well as pregnant women.

Search strategy

PubMed ( https://pubmed.ncbi.nlm.nih.gov/ ) and Scopus ( https://www.scopus.com/search/form.uri?display=basic#basic ) databases were searched for reviews, systematic reviews and meta-analyses published from 1st January 2000 to 31st June 2023. We considered only articles written in English, involving human subjects, with an available abstract, and answering to the following PICO question: P (population): people of all ages; I (intervention) and C (comparison): people adopting A/APFDs vs. omnivores; O (outcome): impact of A/APFD on health parameters associated with CVDs, metabolic disorders or cancer.

Articles not specifying the type of A/APFD regimen were excluded. If not detailed, the A/APFDs adopted by study participants was defined as “mixed diet”. Vegetarian diets limiting but not completely excluding certain types of meat/fish (i.e. pesco- or pollo-vegetarian diet) were excluded. Studies focusing on subjects with specific nutritional needs (i.e., athletes or military personnel) -except pregnant women-, or with known underlying chronic diseases (i.e., chronic kidney disease), as well as articles focusing on conditions/health parameters related to disorders different from CVDs or cancer, and, finally, reviews/meta-analyses including interventional studies assessing A/APFDs comparing it with pharmacological interventions were excluded.

Ad hoc literature search strings, made of a broad selection of terms related to A/APFDs, including PubMed MeSH-terms, free-text words and their combinations, combined by proper Boolean operators, were created to search PubMed database: ((vegetari* OR vegan OR Diet , Vegetarian[MH] OR fruitar* OR veganism OR raw-food* OR lacto-veget* OR ovo-vege* OR semi-veget* OR plant-based diet* OR vegetable-based diet* OR fruit-based diet* OR root-based diet OR juice-based diet OR non-meat eate* OR non-meat diet*) AND ((review[Publication Type]) OR (meta-analysis[Publication Type]))) AND (("2000/01/01"[Date—Publication] : "2023/06/31"[Date—Publication])) and Scopus database: ALL(vegetari* OR vegan OR Diet , Vegetarian OR fruitar* OR veganism OR raw-food* OR lacto-veget* OR ovo-vege* OR semi-veget* OR plant-based diet* OR vegetable-based diet* OR fruit-based diet* OR root-based diet OR juice-based diet OR non-meat eate* OR non-meat diet) AND SUBJAREA(MEDI OR NURS OR VETE OR DENT OR HEAL OR MULT) PUBYEAR > 1999 AND (LIMIT-TO (DOCTYPE , "re"))

Research design and study classification

An umbrella review approach [ 12 ] was applied to systematically assess the effect of A/APFDs on risk factors related to CVDs, metabolic disorders and cancer as derived from literature reviews, systematic reviews and meta-analyses ( Table 1 ).

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https://doi.org/10.1371/journal.pone.0300711.t001

Study selection

The list of articles identified by literature search was split into 5 equivalent parts, each assigned to a couple of readers (AC, DG, CW, ML, AM, FS, MF, AAC, GC and FG), who independently and blindly read the title and then the abstract of each article to define its pertinence. Papers included in the umbrella review had to focus on one/some of the following A/APFDs: vegans, lacto-vegetarians, ovo-vegetarians, lacto-ovo-vegetarians. No restriction was applied for age, gender, ethnicity, geographical origin, nor socio economic status. Primary studies, reviews/meta-analyses not written in English, or focusing on non-previously mentioned dietary regimens (including the Mediterranean diet) were excluded. Abstract meetings, editorials, letters to the editor, and study protocols were also excluded. To reduce study heterogeneity, at least in terms of dietary regimens, we excluded studies based on vegetarian regimens limiting but not avoiding fish or poultry, and prospective trials directly comparing A/AFPDs to pharmacological interventions.

In case of discordance between readers, we resorted to discussion amongst the authors to resolve it, based on the article’s abstract or, if not decisive, the full text. The study selection process is summarized in Fig 1 .

https://doi.org/10.1371/journal.pone.0300711.g001

This review was registered on PROSPERO (Record ID: 372913 https://www.crd.york.ac.uk /prospero/display_record.php?RecordID=372913 ).

Quality literature analysis

Three raters (AC, DG, FS) independently and blindly assessed the quality of the systematic reviews and meta-analyses using the revised AMSTAR-R 11-item tool, developed by the PEROSH group [ 13 ]. In case of disagreement, the score of each item and the final decision were discussed among the three raters.

Data extraction and reporting

Ten investigators (AC, DG, GM, ML, AM, FS, MF, AAC, GC, FG) independently extracted data from eligible articles. Disagreements in data extraction were resolved by consensus. Using a predefined protocol and a Microsoft Excel sheet, the following data were extracted: first author’s affiliation country; type of review; type of diet; target population; number of aggregated participants; total cholesterol; HDL-cholesterol; LDL-cholesterol; triglycerides; apolipoprotein B; C-Reactive Protein (CRP); Body Mass Index (BMI); body weight; fasting glucose; glycosylated hemoglobin (HbA1c); systolic blood pressure; diastolic blood pressure; cardiac events (type; risk); cardiovascular diseases (type; risk); gestational diabetes; gestational hypertension; cancer (type; risk); death due to CVDs/cancer (risk). Data were reported as mean difference (MD), weighted mean difference (WMD), standardized mean difference (SMD), and 95%CI, while the estimated risk could be reported as relative risk (RR), odds ratio (OR), or hazard ratio (HR), according to the data reported by the study authors. Articles assessing the risk of gestational diabetes and hypertension, as well as risk of low birth weight, and their determinants were examined separately.

Results from studies focusing on both vegetarian and vegan diets were analyzed and reported separately if authors had stratified the results according to the type of diet. On the contrary, if data from vegan and vegetarian subjects were mixed, we arbitrarily considered all of them as “vegetarian”.

Group 1: Cardiovascular endpoints and risk factors

I. total cholesterol (tc)..

Eight studies examined the levels of total serum cholesterol (TC) in vegetarians. Two focused on the general population and included 5,561 [ 14 ] and 576 [ 15 ] respectively, and, based on data meta-analysis, found a significant reduction in TC among vegetarians and people who assumed plant-based proteins (MD: -1.56 mmol/L; 95%CI: −1.73, −1.39; and -0.11 mmol/L; 95%CI: −0.22, −0.01, respectively).

Data were confirmed by Wang et al. (N = 832 total; Ovolacto/lacto-vegetarians: 291) [ 16 ], showing a greater dietary effect in subjects with a BMI ranging from 18.5 to 25 kg/m 2 (mean TC reduction: −0.94 mmol/L; 95%CI: −1.33, −0.55), and from 25 to 30 kg/m 2 (−0.58 mmol/L; 95%CI: −0.89, −0.27), than in those with a BMI >30 kg/m 2 (−0.16 mmol/L; 95%CI: −0.30, −0.01), and by Xu et al. (N = 783) [ 17 ], reporting lower TC in overweight and obese people (WMD: −0.37 mmol/L; 95%CI: −0.52, −0.22) adopting a vegetarian diet.

Another systematic review by Elliott et al., including 27 randomized controlled trials on plant based vs. normal western diets [ 18 ], found lower TC levels in vegetarians. These results were in line with other two descriptive reviews, the first including 2,890 overweight/obese adults [ 19 ], the second 8,969 vegetarian children aged 0–18 years [ 20 ]. Furthermore, a meta-analysis by Liang et al. described significantly lower TC (from -0.36 to -0.24 mmol/L) in people adopting plant based diets vs. people adopting western habitual diets [ 21 ].

Moreover, the review and meta-analysis by Dinu et al. [ 14 ], based on 19 studies for a total of 1,272 adults, reported significantly lower levels of TC among vegans than in omnivores (WMD: −1.72 mmol/L; 95%CI: −1.93, −1.51).

II. High-density lipoprotein cholesterol (HDL-C).

Eight reviews focused on the effects of vegetarian diet on serum high-density lipoprotein cholesterol (HDL-C) levels. Six [ 15 , 17 , 18 , 21 – 23 ] found no significant difference between vegetarians and omnivores, when considering normal weight and overweight/obese people. On the contrary, the study by Dinu et al. [ 14 ], based on 51 studies, for a total of 6,194 vegetarian adults, reported a WMD −0.15 mmol/L (95%CI: −0.19, −0.11). Liang et al. [ 21 ] analyzed 4 studies and reported a pooled estimated MD of −0.10 mmol/L (95%CI: −0.14, −0.05; p<0.001) in vegetarian diet adopters vs. western diets adopters. Finally, Zhang et al. [ 22 ] did not find any statistically significant differences in HDL-C levels when assessing vegetarian diets compared to non-vegetarians; on the same note Dinu et al. [ 14 ], analyzing data from 15 studies, for a total of 1,175 adults, found no significant differences in HDL-C levels between vegans and people following other dietary regimens.

III. Low-density lipoprotein cholesterol (LDL-C).

Ten reviews summarized the effect of vegetarian diets on serum levels of low-density lipoprotein cholesterol (LDL-C). Seven [ 14 – 18 , 21 , 23 ] found significantly lower LDL-C levels associated with vegetarian diet, both in the general population and in diabetic patients. In particular, Elliot et al. [ 18 ], analyzing 43 observational and interventional studies, described lower LDL-C in people adopting plant based diets; a significant difference was reported by the study of Liang et al. [ 21 ] based on 68 studies (MD: -0.29 to -0.17), and similar to data by Lamberg et al. [ 15 ], based on 13 RCTs including for a total of 576 participants (MD: -0.14 mmol/L; 95%CI: -0.25, -0.02). The impact of vegetarian diet appeared even greater in overweight or obese people, according to the analysis by Xu et al. [ 17 ], based on 7 RCTs (N = 783; MD: -0.31 mmol/L; 95%CI: -0.46, -0.16). Two reviews [ 19 , 20 ] reported similar results in overweight/obese patients and children aged 0–18 years, but no meta-analyses were conducted. Wang et al. [ 16 ] reported a MD of −0.34 mmol/L (95%CI: −0.57, −0.11; p<0.001) in the general adult population. Ferdowsian et al. [ 23 ] reported an overall reduction of LDL-C associated with vegetarian diet, but no synthesis analyses were performed. Dinu et al. [ 14 ] analyzed 46 studies encompassing 5,583 vegetarians and found a WMD of -1.18 mmol/L (95%CI: -1.34, -1.01). Finally, Viguiliouk et al. [ 24 ] reported a MD of −0.12 mmol/L (95%CI: −0.20, −0.04) in 6 trials involving 602 diabetic patients.

Four reviews identified a significant reduction in LDL-C in vegans as compared to omnivores [ 14 , 19 , 23 , 25 ]. Benatar et al. [ 25 ] analyzed 31 studies, for a total of 3,355 healthy vegan adults and 53,393 non-vegan controls and found MD of -0.49 mmol/L (95%CI: -0.62, -0.36; p<0.0001). Ferdowsian et al. [ 23 ] reported a reduction of LDL-C in healthy vegans, and Ivanova et al. [ 19 ] in overweight patients, but no meta-analysis was performed. Finally, Dinu et al. [ 14 ] analyzed 13 studies, for a total of 728 healthy vegan adults, and found a significant LDL-C reduction (WMD: −1.27 mmol/L; 95%CI: −1.66, −0.88).

IV. Triglycerides (TG).

Seven systematic reviews [ 14 , 16 – 18 , 20 , 23 , 26 ] analyzed serum triglycerides (TG) in vegetarians vs. omnivores. Specifically, Wang et al. [ 16 ] described no differences between the two, with a pooled estimated effect of 0.04 mmol/L (95%CI: −0.05, 0.13; p = 0.4). Zhang et al. [ 26 ] analyzing 12 studies for a total of 1,300 subjects, found a MD of −1.28 mmol/L (95%CI; −2.14, −0.42). Schürmann et al. and Ferdowsian et al. [ 20 , 23 ] reported lower TG in vegetarians in both children and adults but did not perform data meta-analysis. Dinu et al. [ 14 ] analyzed 55 studies including 4,008 vegetarians and found a WMD of −0.63 mmol/L (95%CI: −0.97, −0.30; p = 0.02). Conversely, in the review by Elliott et al. [ 18 ] no differences were reported in triglycerides. Xu et al. [ 17 ] reported a significant increase of TG (WMD: 0.29 mmol/L; 95%CI: 0.11, 0.47) in vegetarians as compared to meat eaters.

The effect of vegan diet on TG remains debated as one review [ 23 ] reported significative changes in TGs (-0.14 mmol/L, CI -0.24 to -0.05), while another [ 14 ] did not find any differences between vegans and omnivores since, after having analyzed 13 studies for 483 vegans, they reported a WMD of -0.52 mmol/L (95%CI: -1.13; 0.09).

V. C-reactive protein (CRP).

Three studies reported lower C-reactive protein (CRP) levels in normal weight, overweight and obese vegetarians as compared to non-vegetarians. Craddock et al. and Menzel et al. reported a WMD of -0.61 mg/L (95%CI: -0.91, -0.32; p = 0.0001) [ 27 ]; -0.25 mg/L (95%CI: -0.49, 0; p = 0.05) [ 28 ], respectively.

Data derived from the analysis by Menzel et al. [ 28 ] in vegan subjects were in line with previously mentioned studies performed in vegetarians (WMD: -0.54 mg/L; 95%CI: -0.79, -0.28; p<0.0001).

Two reviews [ 29 , 30 ] focused on the effects of mixed vegetarian diets on CRP levels. The first [ 29 ] included 2,689 obese patients and found a WMD of -0.55 mg/L (95%CI: -0.78, -0.32; I 2 = 94.4%), while the other [ 30 ], based on 2,398 normal weight subjects found no significant differences between vegetarians and omnivores in the primary analysis; alas, when considering a minimum duration of two years vegetarianism they described lower CRP levels vs. omnivores (Hedges’ g = -0.29; 95%CI: -0.59, 0.01).

VI. Plant-based diets and lipids.

Three studies [ 23 , 26 , 31 ] assessed the lipid profile in people following plant-based diets (without differentiating among diet subtypes) in comparison with omnivores. All of them found significantly lower levels of TC, HDL-C and LDL-C in subjects following plant-based diets. Specifically, Yokoyama et al. [ 31 ] reported a WMD of −1.62 mmol/L (95%CI: −1.92, −1.32; p< 0.001; I 2 = 81.4) for TC, −1.27 mmol/L (95%CI: −1.55, −0.99; p< 0.001; I 2 = 83.3) for LDL-C, −0.2 mmol/L (95%CI: −0.26, −0.14; p< 0.001; I 2 = 49.7) for HDL-C, and −0.36 mmol/L; 95%CI: −0.78, 0.06; p = 0.092; I 2 = 83.0) for TG when considering observational studies, and of −0.69 mmol/L (95%CI: −0.99, −0.4; p<0.001; I 2 = 54.8) for TC, −0.69 mmol/L (95%CI: −0.98, −0.37; p<0.001; I 2 = 79.2) for LDL-C, −0.19 mmol/L (95%CI: −0.24, −0.14; p<0.001; I 2 = 8.5) for HDL-C, and a non-statistically significant increase of TG based on prospective cohort studies. Additionally, Zhang et al. [ 26 ] in their meta-analysis, including 1,300 subjects, found a SMD of -1.28 mmol/L in TG (95% CI -2.14 to -0.42).

Finally, Picasso et al. [ 32 ] did not find any differences in triglycerides for mixed vegetarian diets (MD: 0.04 mmol/L; 95%CI: -0.09, 0.28), but did find statistically significant differences in HDL-C (MD: -0.05 mmol/L; 95%CI: -0.07, -0.03).

VII. Blood pressure.

A . Systolic blood pressure (SBP) . Various studies found significantly lower mean levels of systolic blood pressure (SBP) levels in vegetarians compared to the general population [ 33 – 36 ]. Specifically, Gibbs et al. [ 33 ] reported a SMD of -5.47 mmHg (95%CI: -7.60, -3.34; p<0.00001) in ovo-lacto-vegetarians, as did Lee et al. [ 34 ] reporting a SMD of -1.75 mmHg (95%CI: -5.38, 1.88; p = 0.05); furthermore, they reported a SBP decreased by -2.66 mmHg (95%CI: -3.76, -1.55), in people adopting generic vegetarian diets. Moreover, Garbett et al. [ 35 ] reported a 33% lower prevalence of hypertension in vegetarians vs. nonvegetarians. On the contrary, Schwingshackl et al. [ 36 ], analyzing data from 67 clinical trials overall including 17,230 pre-hypertensive and hypertensive adult patients with a BMI between 23.6 and 45.4 kg/m 2 , followed for 3 to 48 months, did not find any significant reductions in SBP associated with vegetarian diet.

Four reviews investigated the differences in SBP between vegans and non-vegans. Benatar et al. and Lee et al. [ 25 , 34 ] reported significantly lower mean SBP levels in vegans vs. omnivores (MD: -2.56 mmHg; 95%CI: -4.66, -0.45; and WMD: -3.12 mmHg; 95%CI: -4.54, -1.70; p<0.001, respectively). On the other hand, Gibbs et al. [-1.30 mmHg (95%CI: -3.90,1.29)] and Lopez et al. (-1.33 mmHg; 95%CI: −3.50, 0.84; P = 0.230) [ 33 , 37 ] did not find any significant difference in mean SBP levels between vegans and omnivores.

Both reviews [ 32 , 38 ] focusing on SBP in mixed-plant-based dietary patterns found significantly lower levels in vegetarians than in omnivores. The meta-analysis by Picasso et al. [ 32 ], based on 4 RCTs did not find any differences, alas, analyzing 42 cross sectional studies, they described a MD of -4.18 mmHg (95%CI -5.57, -2.80; p<0.00001), in agreement with Yokoyama et al. [ 38 ], who reported a MD of -4.8 mmHg (95%CI: -6.6, -3.1; p<0.001; I 2 = 0) according to the 7 controlled trials, 6 of which being randomized (311 participants), included in the analysis, and of -6.9 mmHg (95%CI: -9.1, -4.7; p<0.001; I 2 = 91.4) based on the other 32 observational studies (21,604 participants).

B . Diastolic blood pressure (DBP) . Garbett et al. [ 35 ] reported reduced mean diastolic blood pressure (DBP) values in vegetarians vs. omnivores, confirmed by the analysis of Gibbs et al. [ 33 ] (WMD: –2.49 mmHg; 95%CI: –4.17, –0.80; p = 0.004; I 2 = 0%) in ovo-lacto-vegetarians, by Lee et al. [ 34 ] [WMD: -1.69 mmHg (95%CI: -2.97, -0.41; p<0.001)] who included 15 randomized controlled trials (N = 856) performed in vegetarians; and by Yokoyama et al. [ 38 ], who highlighted a MD -2.2 mmHg (95%CI: -3.5, -1.0; p<0.001; I 2 = 0%) and -4.7 mmHg (95%CI: -6.3, -3.1; p<0.001; I 2 = 92.6%) according to data from 7 controlled trials (N = 311) and 32 observational studies (N = 21,604), respectively. Conversely, Schwingshackl et al. [ 36 ] did not find significant differences between vegetarians and non-vegetarians.

Three reviews [ 25 , 34 , 37 ] examined the impact of vegan vs. non-vegan diet on DBP and described statistically significant reductions. Benatar et al. described reduction of DBP, corresponding to a MD of -1.33 mmHg (95%CI: -2.67, -0.02) [ 25 ]. Lee et al. described a reduction in DBP of a WMD of -1.92 mmHg (95%CI: -3.18, -0.66; p<0.001) [ 34 ]. Finally, Lopez et al. [ 37 ] described the same reduction amounting to WMD: -4.10 mmHg (95%CI: -8.14, -0.06).

Four studies agreed upon the lower mean DBP levels in subjects following mixed vegetarian diets as compared to omnivores [ 32 – 34 , 38 ], quantified as MD -3.03 mmHg (95%CI: -4.93, 1.13; p = 0.002) by Picasso et al. [ 32 ], and −2.2 mmHg (95%CI: −3.5, −1.0; p<0.001) and −4.7 mmHg (95%CI: −6.3, −3.1; p <0.001) by the analysis performed on clinical trials and observational studies, respectively, by Yokoyama et al. [ 38 ].

VIII. Body weight and body mass index (BMI).

Berkow et al. [ 39 ] identified 40 observational studies comparing weight status of vegetarians vs. non-vegetarians: 29 reported that weight/BMI of vegetarians of both genders, different ethnicities (i.e., African Americans, Nigerians, Caucasians and Asians), and from widely separated geographic areas, was significantly lower than that of non-vegetarians, while the other 11 did not find significant differences between the two groups. In female vegetarians, weight was 2.9 to 10.6 kg (6% to 17%) and BMI 2.7% to 15.0% lower than female non-vegetarians, while the weight of male vegetarians was 4.6 to 12.6 kg (8% to 17%) lower and the BMI 4.6% to 16.3% lower than that of male non-vegetarians. The review by Schürmann et al. [ 20 ], focusing on 8,969 children aged 0–18 years old found similar body weight in both vegetarian and vegan children as compared to omnivore ones. Dinu et al. [ 14 ] analyzed data from 71 studies (including 57,724 vegetarians and 199,230 omnivores) and identified a WMD BMI of -1.49 kg/m 2 (95%CI: -1,72, -1,25; p<0.0001) in vegetarians when compared to omnivores.

Barnard et al. [ 40 ] found a significant reduction in weight in pure ovolactovegetarians (−2.9 kg; 95% CI −4.1 to −1.6; P<0.0001), compared to non-vegetarians from control groups; furthermore, they found in vegans the mean effect was of -3.2 kg (95% CI: -4.0;-2.4, P: <0.0001); overall they included 490 subjects in their analysis, excluding subjects who did not complete the trials.

Benatar et al. [ 25 ]–including 12,619 vegans and 179,630 omnivores from 40 observation studies–and Dinu et al. [ 14 ]–based on 19 cross sectional studies, for a total of 8,376 vegans and 123,292 omnivores–reported the same exact result, with a mean lower BMI in vegans vs omnivores, equal to -1.72 kg/m 2 (95%CI: -2.30, -1.16) and -1.72 kg/m 2 (95%CI: -2.21,-1.22; p<0.0001), respectively. The meta-analysis by Long et al. [ 41 ], performed on 27 studies, reported a MD of -0.70 kg/m 2 (95%CI: -1.38, -0.01) for BMI in vegans vs. omnivores. A systematic review and meta-analysis by Agnoli et al. [ 42 ] found mean BMI to be lower in subjects adhering to mixed vegetarian diets as compared to omnivores. Additionally, Tran et al. [ 43 ] described weight reductions in clinically healthy patients, as well as in people who underwent vegetarian diets as a prescription, but no meta-analysis was performed.

Finally, Huang et al. [ 44 ] found significant differences in both vegans and vegetarians, who were found to have lost weight after having adopted the diet as a consequence of being assigned to the intervention group in their randomized studies. For vegetarians the WMD was -2.02 kg (95%CI: -2.80 to -1.23), when compared to mixed diets, and for vegans the WMD was -2.52 kg (95%CI: -3.02 to -1.98), when compared to vegetarians.

IX. Glucose metabolism.

Viguiliouk et al. [ 24 ] found a significant reduction in HbA1c (MD: −0.29%; 95%CI: −0.45, −0.12) and fasting glucose (MD: −0.56 mmol/L; 95%CI: −0.99, −0.13) in vegetarians vs. non-vegetarians.

The meta-analysis by Dinu et al. [ 14 ], reported for vegetarians (2256) vs omnivores (2192) WMD: -0.28 mmol/L (95%CI: -0.33, -0.23) in fasting blood glucose.

These findings were confirmed by Picasso et al. [ 32 ] who found a MD of -0.26 mmol/L (95% CI: -0.35, -0.17) in fasting glucose in mixed-vegetarian diets as compared to omnivores.

A meta-analysis by Long et al. [ 41 ], based of 27 cross sectional studies, showed a MD for homeostasis model assessment of insulin resistance -measured as HOMA-IR, a unitless measure ideally less than one- of -0.75 (95%CI: -1.08, -0.42), fasting plasma glucose in vegetarians who adhered also to an exercise intervention as compared to omnivores.

Lee & Park [ 45 ] reported a significantly lower diabetes risk (OR 0.73; 95%CI: 0.61, 0.87; p<0.001) in vegetarians vs. non-vegetarians, being the association stronger in studies conducted in the Western Pacific region and Europe/North America than in those from Southeast Asia.

Regarding vegans, the review by Benatar et al. [ 25 ] determined a mean reduction of 0.23 mmol/L (95%CI: -0.35, -0.10) of fasting blood glucose in vegans (N = 12,619) as compared to omnivores (N = 179,630). The finding was in line with Dinu et al. [ 14 ], who reported a WMD of -0.35 mmol/L (95%CI: -0.69, -0.02; p = 0.04) of fasting blood glucose in vegans (n = 83) than omnivores (n = 125).

A systematic review, finally, including 61 studies [ 42 ] found mean values of fasting plasma glucose, and T2D risk to be lower in subjects following mixed vegetarian diets as compared to omnivores.

X. Cardiovascular events.

Huang et al. [ 46 ] found a significantly lower risk of ischemic heart disease (IHD) (RR: 0.71; 95%CI: 0.56, 0.87), but no significant differences for cerebrovascular mortality between vegetarians and non-vegetarians. The review by Remde et al. [ 47 ] was not conclusive, as only a few studies showed a reduction of the risk of CVDs for vegetarians versus omnivores, while the others did not find any significant results.

Dybvik et al. [ 48 ] based on 13 cohort studies for a total of 844,175 participants (115,392 with CVDs, 30,377 with IHD and 14,419 with stroke) showed that the overall RR for vegetarians vs. nonvegetarians was 0.85 (95%CI: 0.79–0.92, I 2 = 68%; 8 studies) for CVD, 0.79 (95%CI: 0.71–0.88, I 2 = 67%; 8 studies) for IHD, 0.90 (95%CI: 0.77–1.05, I 2 = 61%; 12 studies) for total stroke, while the RR of IHD in vegans vs. omnivores was 0.82 (95%CI: 0.68–1.00, I 2 = 0%; 6 studies).

The meta-analysis by Kwok et al. [ 49 ], based on 8 studies including 183,321 subjects comparing vegetarians versus non-vegetarians. They identified a significant reduction of IHD in the Seventh Day Adventist (SDA) cohort, who primarily follow ovo-lacto-vegetarian diets, while other non-SDA vegetarian diets were associated only with a modest reduction of IHD risk, raising the concern that other lifestyle factors typical of SDA and, thus not generalizable to other groups, play a primary role on outcomes. IHD was significantly reduced in both genders (RR: 0.60; 95%CI: 0.43, 0.83), while the risk of death and cerebrovascular disease and cardiovascular mortality risk reduction was significantly reduced only in men. No significant differences were detected for the risk of cerebrovascular events.

The meta-analysis by Lu et al. [ 50 ] -657,433 participants from cohort studies- reported a lower incidence of total stroke among vegetarians vs. nonvegetarians (HR = 0.66; 95%CI = 0.45–0.95; I 2 = 54%), while no differences were identified for incident stroke.

The descriptive systematic review by Babalola et al. [ 3 ] reported that adherence to a plant-based diet was inversely related to heart failure risk and advantageous for the secondary prevention of CHD, particularly if started from adolescence. Another review by Agnoli et al. [ 42 ], confirmed a lower incidence of CVDs associated with mixed vegetarian diets as compared to omnivorous diets. Finally, Chhabra et al. [ 51 ] found that vegetarian diet, particularly if started in adolescence and associated with vitamin B intake, can reduce the risk of stroke.

Gan et al. [ 52 ] described a lower risk of CVDs (RR 0.84; 95% CI 0.79 to 0.89; p < 0.05) in high, vs. low, adherence plant based diets, but the same association was not confirmed for stroke (RR 0.87; 95% CI: 0.73, 1.03).

Group 2: Pregnancy outcomes

The meta-analysis by Foster et al. [ 53 ], performed on 6 observational studies, found significantly lower zinc levels in vegetarians than in meat eaters (-1.53 ± 0.44 mg/day; p = 0.001), but no association with pregnancy outcomes, specifically no increase in low children birth weight. The finding was confirmed by Tan et al. [ 54 ], who similarly reported no specific risks, but reported that Asian (India/Nepal) vegetarian mothers exhibited increased risks to deliver a baby with Low Birth Weight (RR: 1.33 [95%CI:1.01, 1.76, p =  0.04, I 2 = 0%]; nonetheless, the WMD of neonatal birth weight in five studies they analyzed suggested no difference between vegetarians and omnivores.

To our knowledge, no reviews/meta-analyses have assessed the risk of zinc deficiency and its association with functional outcomes in pregnancy in relation to mixed or vegan diets.

Group 3: Cancer

The meta-analysis by Parra-Soto et al. [ 55 ], based on 409,110 participants from the UK Biobank study (mean follow-up 10.6 years), found a lower risk of liver, pancreatic, lung, prostate, bladder, colorectal, melanoma, kidney, non-Hodgkin lymphoma and lymphatic cancer as well as overall cancer (HR ranging from 0.29 to 0.70) determined by non-adjusted models in vegetarians vs. omnivores; when adjusted for sociodemographic and lifestyle factors, multimorbidity and BMI, the associations remained statistically significant only for prostate cancer (HR 0.57; 95%CI: 0.43, 0.76), colorectal cancer (HR 0.73; 95%CI: 0.54, 0.99), and all cancers combined (HR 0.87; 95%CI 0.79, 0.96). When colorectal cancer was stratified according to subtypes, a lower risk was observed for colon (HR 0.69; 95%CI: 0.48, 0.99) and proximal colon (HR 0.43; 95%CI: 0.22, 0.82), but not for rectal or distal cancer.

Similarly, the analysis by Huang et al. [ 46 ], based on 7 studies for a total of 124,706 subjects, reported a significantly lower overall/total cancer incidence in vegetarians than non-vegetarians (RR 0.82; 95%CI: 0.67, 0.97).

Zhao et al. [ 56 ] found a lower risk of digestive system cancer in plant-based dieters (RR = 0.82, 95%CI: 0.78–0.86; p< 0.001) and in vegans (RR: 0.80; 95%CI: 0.74, 0.86; p<0.001) as compared to meat eaters.

Additionally, DeClercq et al. [ 57 ] reported a decreased risk of overall cancer and colorectal cancer, but inconsistent results for prostate cancer and breast cancer; this was substantiated by Godos et al. [ 58 ] found no significant differences in breast, colorectal, and prostate cancer risk between vegetarians and non-vegetarians.

The umbrella review by Gianfredi et al. [ 59 ], did describe a lower risk of pancreatic cancer associated with vegetarian diets.

Dinu et al. [ 14 ] reported a reduction in the risk of total cancer of 8% in vegetarians, and of 15% in vegans, as compared to omnivores. They described lower risk of cancer among vegetarians (RR 0.92; 95%CI 0.87, 0.98) and vegans (RR: 0.85; 95%CI: 0.75,0.95); nonetheless, they also described non-significant reduced risk of mortality from colorectal, breast, lung and prostate cancers. Regarding the latter, a meta-analysis by Gupta et al. [ 60 ] on prostate cancer risk found a decreased hazard ratio for the incidence of prostate cancer (HR: 0.69; 95%CI: 0.54–0.89, P<0.001) in vegetarians as compared to omnivores from the evidence coming from 3 studies. In the vegan population, similar results were observed from the only included study (HR: 0.65; 95%CI: 0.49–0.85; p<0.001).

Group 4: Death by cardiometabolic diseases and cancer

According to Huang et al. [ 46 ], the mortality from IHD (RR: 0.71; 95%CI: 0.56, 0.87), circulatory diseases (RR: 0.84; 95%CI: 0.54, 1.14) and cerebrovascular diseases (RR: 0.88; 95%CI: 0.70, 1.06) was significantly lower in vegetarians than in non-vegetarians.

The analysis by Dinu et al. [ 14 ] performed on 7 prospective studies, overall including 65,058 vegetarians, reported a 25% reduced mortality risk from ischemic heart diseases (RR 0.75; 95%CI: 0.68, 0.82; p<0.001), but no significant differences were found analyzing 5 cohort studies in terms of mortality from CVDs, cerebrovascular diseases, nor colorectal, breast, prostate, and lung cancer. Regarding vegans, they analyzed 6 cohort studies, and found no differences in all-cause mortality, but significant differences in cancer incidence (RR: 0.85; 95%CI: 0.75, 0.95), indicating a protective effect of vegan diets.

The literature search did not identify studies focusing on mortality risk for cardiometabolic and cancer diseases in vegans.

Quality of the included studies

The quality of the 48 reviews and meta-analyses included in this umbrella review was assessed through the AMSTAR-R tool. Results are reported in S1 Table . Overall, the average quality score was 28, corresponding to mean quality. However, 36 studies (75%) scored between 60% and 90% of the maximum obtainable score, and can, therefore, be considered of good/very good quality. The least satisfied item on the R-AMSTAR grid was #8 -scientific quality of included studies used to draw conclusions-, where as many as 19 studies (39.6%) failed to indicate the use of study-related quality analysis to make recommendations. This finding should be read in conjunction with the missing quality analysis in 15 studies (31.3%)–Item #7 scientific quality of included studies assessed and documented-. Item #10, regarding publication bias, was the second least met item, in which 18 studies (37.5%) did not perform any analysis on this type of bias. 16 studies (33.3%) lacked to indicate careful exclusion of duplicates (Item #2), but also the presence of conflict of interest (Item #11). This point is certainly another important piece to consider in the overall quality assessment of these articles. All these considerations give us a picture of a general low quality of the publications found, lowering the strength of evidence as well as the external validity of the results.

This umbrella review provides an update on the benefits associated with the adoption of A/AFPDs in reducing risk factors associated with the development of cardiometabolic diseases and cancer, considering both the adult and the pediatric population, as well as pregnant women.

Compared to omnivorous regimens, vegetarian and vegan diets appear to significantly improve the metabolic profile through the reduction of total and LDL cholesterol [ 14 – 21 , 23 , 25 ], fasting blood glucose and HbA1c [ 14 , 24 , 25 , 37 , 39 – 41 ], and are associated with lower body weight/BMI, as well as reduced levels of inflammation (evaluated by serum CRP levels [ 27 , 30 ]), while the effect on HDL cholesterol and triglycerides, systolic and diastolic blood pressure levels remains debated. A much more limited body of literature suggested vegetarian, but not vegan diets also reduce ApoB levels further improving the lipid profile [ 61 ].

It should be remarked that, in the majority of the cases, people adopting plant-based diets are more prone to engage in healthy lifestyles that include regular physical activity, reduction/avoidance of sugar-sweetened beverages, alcohol and tobacco, that, in association with previously mentioned modification of diet [ 62 ], lead to the reduction of the risk of ischemic heart disease and related mortality, and, to a lesser extent, of other CVDs.

The adoption of vegan diets is known to increase the risk of vitamin B-12 deficiency and consequent disorders–for which appropriate supplementation was recommended by a 2016 position paper of the Academy of Nutrition and Dietetics’ [ 5 ], but, apparently, does not modify the risk of pregnancy-induced hypertension nor gestational diabetes mellitus [ 53 , 54 ].

The three meta-analyses [ 46 , 55 , 57 ] that analyzed the overall risk of cancer incidence in any form concordantly showed a reduction in risk in vegetarians compared to omnivores. These general results were inconsistent in the stratified analyses for cancer types, which as expected involved smaller numbers of events and wider confidence intervals, especially for less prevalent types of cancers.

The stratified analyses in the different reviews did not show any significant difference for bladder, melanoma, kidney, lymphoma, liver, lung, or breast cancer. Conversely the three meta-analyses that addressed colorectal cancer [ 55 , 57 , 58 ] showed a decrease in risk in two out of three with one not showing a significant difference in vegetarians versus omnivores for the generic colorectal tract.

Interestingly, one review [ 55 ] showed how analysis with even more specific granularity could reveal significant differences in particular subsets of cancers, e.g., distal, and proximal colon. Also, another recent review found significant results for pancreatic cancer [ 59 ].

Our umbrella review seems consistent with other primary evidence that links the consumption of red processed meats to an increased risk of cancers of the gastro-intestinal tract [ 63 ]. The association certainly has two faces, because while a potential risk of cancer given by increased red meat consumption can be observed, the potential protective factor given by increased fruit and vegetable consumption, shown by other previous evidence, must also be considered [ 64 ].

It has also been described that vegetarians, in addition to reduced meat intake, ate less refined grains, added fats, sweets, snacks foods, and caloric beverages than did nonvegetarians and had increased consumption of a wide variety of plant foods [ 65 ]. Such a dietary pattern seems responsible for a reduction of hyperinsulinemia, one of the possible factors for colorectal cancer risk related to diet and food intake [ 66 , 67 ]. In the same manner, some research has suggested that insulin-like growth factors and its binding proteins may relate to cancer risk [ 68 , 69 ]. This dietary pattern should not be regarded as a universal principle, as varying tendencies have been observed among vegetarians and vegans in different studies. This pattern of consumption may potentially negate the anticipated beneficial effects of their diets.

Also, some protective patterns can be attributed to the effects of bioactive compounds of plant foods, these being primary sources of fiber, carotenoids, vitamins, minerals, and other compounds that have been associated with anti-cancer properties [ 70 , 71 ]. The protective patterns are likely attributed to the mechanistic actions of the many bioactives found in plant foods such as fiber, carotenoids, vitamins, and minerals with plausible anti-cancer properties. These ranged from epigenetic mechanisms [ 72 ], to immunoregulation, antioxidant and anti-inflammatory activity [ 73 , 74 ].

Finally, increased adiposity could be another pathway by which food intake is associated with these types of cancers. Since our umbrella review has demonstrated that vegetarian diets are associated with lower BMI, this might be another concurrent factor in the decreased risk for pancreatic and colorectal cancers in vegetarians.

Inflammatory biomarkers and adiposity play pivotal roles in the genesis of prostate cancer [ 75 , 76 ], hence the same etiological pathways might be hypothesized even for the increase of this type of cancer in people adopting an omnivorous diet.

The study presents several noteworthy strengths in its methodological approach and thematic focus. It has employed a rigorous and comprehensive search strategy involving two major databases, PubMed, and Scopus, spanning over two decades of research from 1 st January 2000 to 31 st June 2023, thereby ensuring a robust and exhaustive collection of pertinent literature. By utilizing an umbrella review, the research enables the synthesis of existing systematic reviews and meta-analyses, providing a higher level of evidence and summarizing a vast quantity of information. Furthermore, its alignment with current health concerns, specifically targeting cardiovascular diseases and cancer, makes the study highly relevant to ongoing public health challenges and positions it as a valuable resource for informing preventive measures and dietary guidelines. The deployment of blinded and independent assessments by multiple raters and investigators fortifies the research by minimizing bias and reinforcing the reliability of the selection, quality assessment, and data extraction processes. Quality assessment is standardized using the revised AMSTAR-R 11-item tool, and transparency is fostered through registration on PROSPERO, thus enhancing the credibility of the study. Lastly, the study’s detailed analysis and reporting, particularly the extraction of specific health measures such as cholesterol levels, glucose levels, blood pressure, and cancer risks, contribute to the comprehensiveness of the data synthesis, thereby underlining the overall integrity and significance of the research.

Main limitations to data analysis and interpretation are intrinsic to the original studies and consist in the wide heterogeneity in terms of sample size, demographic features, and geographical origin of included subjects, dietary patterns–not only in terms of quality, but, even more important and often neglected, quantity, distribution during the day, processing, cooking methods–and adherence, and other lifestyle confounders. In this regard, it is worth to mention that the impact of diet per se on the development of complex disorders (i.e. CVDs and cancer) and related mortality is extremely difficult to assess [ 71 ], especially in large populations, characterized by a highly heterogeneous lifestyle. It should also be considered the heterogeneity in dietary and lifestyle habits among countries, according to which the adoption of A/AFPDs could modify significantly habits in some countries, but not in others, and consequently have an extremely different impact on the risk of developing cardiometabolic disorders and cancer [ 25 ]. Furthermore, due to the nature of umbrella reviews, the present work may not include novel associations which were excluded from the analyzed reviews, as the main aim was to summarize secondary studies, such as reviews and meta-analyses. Finally, studies assessing the benefit of A/AFPDs on cancer risk are also limited by the heterogeneity in the timing of oncological evaluation and, therefore, disease progression, as well as in the histological subtypes and previous/concomitant treatments [ 72 – 75 ].

In conclusion, this umbrella review offers valuable insights on the estimated reduction of risk factors for cardiometabolic diseases and cancer, and the CVDs-associated mortality, offered by the adoption of plant-based diets through pleiotropic mechanisms. Through the improvement of glycolipid profile, reduction of body weight/BMI, blood pressure, and systemic inflammation, A/AFPDs significantly reduce the risk of ischemic heart disease, gastrointestinal and prostate cancer, as well as related mortality.

However, data should be taken with caution because of the important methodological limitation associated with the original studies. Moreover, potential risks associated with insufficient intake of vitamin and other elements due to unbalanced and/or extremely restricted dietary regimens, together with specific patient needs should be considered, while promoting research on new and more specific markers (i.e. biochemical, genetic, epigenetic markers; microbiota profile) recently associated with cardiometabolic and cancer risk, before suggesting A/AFPDs on large scale.

Supporting information

S1 table. r-amstar..

https://doi.org/10.1371/journal.pone.0300711.s001

S2 Table. PRISMA 2020 checklist.

https://doi.org/10.1371/journal.pone.0300711.s002

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Environmental and human health risk assessment of potentially toxic elements in soils around the largest coal-fired power station in Southern Russia

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• Volume 43 , pages 2285–2300, ( 2021 )

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• Tatiana Minkina   ORCID: orcid.org/0000-0003-3022-0883 1 ,
• Elizaveta Konstantinova   ORCID: orcid.org/0000-0002-9836-8721 1 ,
• Tatiana Bauer   ORCID: orcid.org/0000-0002-6751-8686 1 , 2 ,
• Saglara Mandzhieva   ORCID: orcid.org/0000-0001-6000-2209 1 ,
• Svetlana Sushkova   ORCID: orcid.org/0000-0003-3470-9627 1 ,
• Victor Chaplygin   ORCID: orcid.org/0000-0002-1142-7750 1 ,
• Marina Burachevskaya   ORCID: orcid.org/0000-0002-0533-0418 1 ,
• Olga Nazarenko 3 ,
• Rıdvan Kizilkaya 4 ,
• Coşkun Gülser 4 &
• Alexey Maksimov 1  

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The combustion of solid fuel at power plants pollutes adjacent areas with potentially toxic elements (PTEs), which increases risks to public health in the vicinity of these facilities. The proposed paper presents the results of a geochemical study of PTEs (Cr, Mn, Ni, Cu, Zn, Cd, and Pb) contamination in the vicinity of Novocherkassk Power Plant (NPP) as it relates to environmental and human health risks. The impact zone of NPP is pronounced for a distance of approximately 7 km northwest of the enterprise—the second largest coal power plant in Southern Russia. Data from monitoring sites lead us to conclude that spatial patterns of soil pollution are strongly influenced by the peculiarities of local atmospheric circulation, while the characteristics of soils within the study area play a secondary role. The highest levels of PTEs and their exchangeable forms exceed both regional background and sanitary and hygienic standards within a radius of 3 km to the west of the plant, which corresponds to a zone of soils contaminated with Cr, Ni, Cu, Zn, Cd, and Pb. The carcinogenic risk to human health slightly exceeds the permissible standard of 1 × 10 −6 for soils in close vicinity of the enterprise due to the potential human intake of Ni, Cd, and Pb. The results of the health risk assessment indicate no noncarcinogenic risks for adults, while for children, they are low.

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Adriano, D. C. (2001). Trace elements in terrestrial environments: Biogeochemistry, bioavailability, and risks of metals (2nd ed.). New York: Springer-Verlag. https://doi.org/10.1007/978-0-387-21510-5 .

Book   Google Scholar  

Asante-Duah, K. (2017). Public health risk assessment for human exposure to chemicals (2nd ed.). Dordrecht: Springer. https://doi.org/10.1007/978-94-024-1039-6 .

ATSDR (Agency for Toxic Substances and Disease Registry). (2019). Minimal risk levels (MRLs) list . Retrieved December 5, 2019, from https://www.atsdr.cdc.gov/mrls/mrllist.asp#15tag .

Barsova, N., Yakimenko, O., Tolpeshta, I., & Motuzova, G. (2019). Current state and dynamics of heavy metal soil pollution in Russian Federation—A review. Environmental Pollution, 249 , 200–207. https://doi.org/10.1016/j.envpol.2019.03.020 .

Article   CAS   Google Scholar  

Bogdanov, N. A. (2012). Analysis of the in formative value of integral indicators of chemical soil contamination in the evaluation of the status of areas. Gigiena i sanitaria, 91 (1), 10–13. (in Russian) .

Google Scholar  

Burachevskaya, M., Minkina, T., Mandzhieva, S., Bauer, T., Chaplygin, V., Zamulina, I., et al. (2019). Study of copper, lead, and zinc speciation in the Haplic Chernozem surrounding coal-fired power plant. Applied Geochemistry, 104 , 102–108. https://doi.org/10.1016/j.apgeochem.2019.03.016 .

CCME (Canadian Council of Ministers of the Environment). (1999). Canadian soil quality guidelines for the protection of environmental and human health: Chromium (total 1997) (VI 1999). In Canadian environmental quality guidelines . Winnipeg: Canadian Council of Ministers of the Environment. Retrieved December 5, 2019, from https://ceqg-rcqe.ccme.ca/download/en/262/ .

Chaplygin, V., Mandzhieva, S., Minkina, T., Sushkova, S., Kizilkaya, R., Gülser, C., et al. (2019). Sustainability of agricultural and wild cereals to aerotechnogenic exposure. Environmental Geochemistry and Health . https://doi.org/10.1007/s10653-019-00411-6 .

Article   Google Scholar  

Chaplygin, V., Minkina, T., Mandzhieva, S., Burachevskaya, M., Sushkova, S., Poluektov, E., et al. (2018). The effect of technogenic emissions on the heavy metals accumulation by herbaceous plants. Environmental Monitoring and Assessment, 190 , 124. https://doi.org/10.1007/s10661-018-6489-6 .

Chernova, O. V., & Beketskaya, O. V. (2011). Permissible and background concentrations of pollutants in environmental regulation (heavy metals and other chemical elements). Eurasian Soil Science, 44 (9), 1008–1017. https://doi.org/10.1134/S106422931109002X .

Crossgrove, J., & Zheng, W. (2004). Manganese toxicity upon overexposure. NMR in Biomedicine, 17 (8), 544–553. https://doi.org/10.1002/nbm.931 .

Ćujić, M., Dragović, S., Đorđević, M., Dragović, R., & Gajić, B. (2016). Environmental assessment of heavy metals around the largest coal fired power plant in Serbia. CATENA, 139 , 44–52. https://doi.org/10.1016/j.catena.2015.12.001 .

da Silva Júnior, F. M. R., Ramires, P. F., dos Santos, M., Seus, E. R., Soares, M. C. F., Muccillo-Baisch, A. L., et al. (2019). Distribution of potentially harmful elements in soils around a large coal-fired power plant. Environmental Geochemistry and Health, 41 , 2131–2143. https://doi.org/10.1007/s10653-019-00267-w .

D’yachenko, V. V., & Matasova, I. Y. (2016). Regional clarkes of chemical elements in soils of southern European Russia. Eurasian Soil Science, 49 , 1091–1098. https://doi.org/10.1134/S1064229316100069 .

Eisler, R. (2000). Cadmium. In R. Eisler (Ed.), Handbook of chemical risk assessment: Health hazards to humans, plants, and animals. Metals (Vol. 1, pp. 1–43). Boca Raton: Lewis Publishers.

Gad, S. C. (2014a). Chromium. In P. Wexler (Ed.), Encyclopedia of toxicology (3rd ed., Vol. 1, pp. 952–954). London, Burlington, San Diego: Elsevier. https://doi.org/10.1016/B978-0-12-386454-3.00828-9

Chapter   Google Scholar  

Gad, S. C. (2014). Copper. In P. Wexler (Ed.), Encyclopedia of toxicology (3rd ed., Vol. 1, pp. 1034–1036). London, Burlington, San Diego: Elsevier. https://doi.org/10.1016/B978-0-12-386454-3.00834-4

Gazprom. (2020). Power generation . Retrieved February 7, 2020, from https://www.gazprom.com/about/production/energetics/ .

GN 2.1.7.2041-06. (2006). Maximum allowable concentration (MAC) of chemicals in the soil . Moscow: Federal Center for Hygiene and Epidemiology of Rospotrebnadzor (in Russian) .

GN 2.1.7.2511-09. (2009). Tentative allowable concentrations (TAC) of chemicals in the soil . Moscow: Federal Center for Hygiene and Epidemiology of Rospotrebnadzor (in Russian) .

GOST 17.4.1.02-83. (1984). Nature protection. Soils. Classification of chemicals for pollution control . Moscow: Standardinform (in Russian) .

GOST 17.4.4.02-2017. (2018). Nature protection. Soils. Methods (or sampling and preparation of soil for chemical, bacteriological, helmintological analysis . Moscow: Standardinform (in Russian) .

Grigoriev, N. A. (2009). Chemical element distribution in the upper continental crust . Ekaterinburg: UB RAS. (in Russian) .

Guney, M., Zagury, G. J., Dogan, N., & Onay, T. T. (2010). Exposure assessment and risk characterization from trace elements following soil ingestion by children exposed to playgrounds, parks and picnic areas. Journal of Hazardous Materials, 182 , 656–664. https://doi.org/10.1016/j.jhazmat.2010.06.082 .

Huang, X., Hu, J., Qin, F., Quan, W., Cao, R., Fan, M., et al. (2017). Heavy metal pollution and ecological assessment around the Jinsha coal-fired power plant (China). International Journal of Environmental Research and Public Health, 14 (12), 1589. https://doi.org/10.3390/ijerph14121589 .

IARC. (2019). IARC monographs on the evaluation of carcinogenic risks to humans . Retrieved December 15, 2019, from https://monographs.iarc.fr/list-of-classifications .

ISO 10390:2005. (2005) Soil quality—Determination of pH .

IUSS Working Group WRB. (2015). World reference base of soil resources 2014, update 2015 international soil classification system for naming soils and creating legends for soil maps . World Soil Resources Reports no. 106. Rome: FAO.

Kabata-Pendias, A. (2011). Trace elements in soils and plants (4th ed.). Boca Raton: CRC Press Taylor & Francis Group. https://doi.org/10.1201/b10158 .

Kasimov, N. S., & Vlasov, D. V. (2015). Clarkes of chemical elements as comparison standards in ecogeochemistry. Vestnik Moskovskogo Universiteta. Seria 5, Geografia, 2 , 7–17. (in Russian) .

Kazakov, K. (2019). Climate of Rostov-on-Don . Retrieved November 22, 2019, from https://www.pogodaiklimat.ru/climate/34730.htm . (in Russian) .

Konstantinov, A., Novoselov, A., Konstantinova, E., Loiko, S., Kurasova, A., & Minkina, T. (2020). Composition and properties of soils developed within the ash disposal areas originated from peat combustion (Tyumen, Russia). Soil Science Annual, 71 (1), 3–14. https://doi.org/10.37501/soilsa/121487 .

Konstantinova, E., Minkina, T., Sushkova, S., Konstantinov, A., Rajput, V. D., & Sherstnev, A. (2019). Urban soil geochemistry of an intensively developing Siberian city: A case study of Tyumen, Russia. Journal of Environmental Management, 239 , 366–375. https://doi.org/10.1016/j.jenvman.2019.03.095 .

Kowalska, J. B., Mazurek, R., Gasiorek, M., & Zaleski, T. (2018). Pollution indices as useful tools for the comprehensive evaluation of the degree of soil contamination—A review. Environmental Geochemistry and Health, 40 , 2395–2420. https://doi.org/10.1007/s10653-018-0106-z .

Krechetov, P., Kostin, A., Chernitsova, O., & Terskaya, E. (2019). Environmental changes due to wet disposal of wastes from coal-fired heat power plant: A case study from the Tula Region, Central Russia. Applied Geochemistry, 105 , 105–113. https://doi.org/10.1016/j.apgeochem.2019.04.017 .

Lemly, A. D. (1996). Evaluation of the hazard quotient method for risk assessment of selenium. Ecotoxicology and Environmental Safety, 35 , 156–162.

Linnik, V. G., Minkina, T. M., Bauer, T. V., Saveliev, A. A., & Mandzhieva, S. S. (2019). Geochemical assessment and spatial analysis of heavy metals pollution around coal-fired power station. Environmental Geochemistry and Health . https://doi.org/10.1007/s10653-019-00361-z .

Mandzhieva, S. S., Goncharova, L Yu, Batukaev, A. A., Minkina, T. M., Bauer, T. V., Shertnev, A. K., et al. (2017). Current state of haplic chernozems in specially protected natural areas of the steppe zone. OnLine Journal of Biological Sciences, 17 (4), 363–371. https://doi.org/10.3844/ojbsci.2017.363.371 .

Minkina, T. M., Mandzhieva, S. S., Burachevskaya, M. V., Bauer, T. V., & Sushkova, S. N. (2018). Method of determining loosely bound compounds of heavy metals in the soil. MethodsX, 5 , 217–226. https://doi.org/10.1016/j.mex.2018.02.007 .

Minkina, T. M., Nevidomskaya, D. G., Pol’shina, T. N., Fedorov, Y. A., Mandzhieva, S. S., Chaplygin, V. A., et al. (2017). Heavy metals in the soil-plant system of the Don River estuarine region and the Taganrog Bay coast. Journal of Soils and Sediments, 17 , 1474–1491. https://doi.org/10.1007/s11368-016-1381-x .

Minnikova, T. V., Denisova, T. V., Mandzhieva, S. S., Kolesnikov, S. I., Minkina, T. M., Chaplygin, V. A., et al. (2017). Assessing the effect of heavy metals from the Novocherkassk power station emissions on the biological activity of soils in the adjacent areas. Journal of Geochemical Exploration, 174 , 70–78. https://doi.org/10.1016/j.gexplo.2016.06.007 .

Minprirody of the Rostov Oblast (Ministry of Natural Resources and Ecology of the Rostov Oblast). (2019). Ecological bulletin of Don “On the state of the environment and natural resources of the Rostov region in 2018” . Rostov-on-Don: Ministry of Natural Resources and Ecology of the Rostov Oblast. (in Russian) .

MU 2.1.7.730-99. (1999). Hygienic evaluation of soil in residential areas. Methodological Instructive Regulations (approved by Russian Federation Chief Public Health Officer 07 February 1999). Moscow: Ministry of Health of the Russian Federation (in Russian) .

Müller, G. (1986). Schadstoffe in sedimenten—sedimente als schadstoffe. Mitteilungen der Österreichischen Geologischen Gesellschaft, 79 , 107–126. (in German) .

Nemerow, L. N. (1974). Scientific stream pollution analysis . Washington: Scripta Book Co.

Noli, F., & Tsamos, P. (2016). Concentration of heavy metals and trace elements in soils, waters and vegetables and assessment of health risk in the vicinity of a lignite-fired power plant. Science of The Total Environment, 563–564 , 377–385. https://doi.org/10.1016/j.scitotenv.2016.04.098 .

Nriagu, J. (2011). Zinc toxicity in humans. In J. O. Nriagu (Ed.), Encyclopedia of environmental health (pp. 500–508). Oxford: Elsevier.

OEHHA (California Office of Environmental Health Hazard Assessment). (2012). Air toxics hot spots program risk assessment guidelines. Technical support document for exposure assessment and stochastic analysis. Final . Oakland: Office of Environmental Health Hazard Assessment.

OEHHA (California Office of Environmental Health Hazard Assessment). (2019). Chemical database . Retrieved November 27, 2019, from https://oehha.ca.gov/chemicals .

OST 10-259-2000. (2001). Soil . X-ray fluorescence determination of the total content of heavy metals . Moscow: The Russian Federation Ministry of Agriculture (in Russian) .

Pandey, V. C. (2015). Assisted phytoremediation of fly ash dumps through naturally colonized plants. Ecological Engineering, 82 , 1–5. https://doi.org/10.1016/j.ecoleng.2015.04.002 .

Piersanti, A., Adani, M., Briganti, G., Cappelletti, A., Ciancarella, L., Cremona, G., et al. (2018). Air quality modeling and inhalation health risk assessment for a new generation coal-fired power plant in Central Italy. Science of The Total Environment, 644 , 884–898. https://doi.org/10.1016/j.scitotenv.2018.06.393 .

Rahman, I. M. M., & Begum, Z. A. (2019). Introductory chapter: How to assess metal contamination in soils? In Z. A. Begum, I. M. M. Rahman, & H. Hasegawa (Eds.), Metals in soil—Contamination and remediation (pp. 1–9). Rijeka: IntechOpen. https://doi.org/10.5772/intechopen.84979

RD 52.18.289-90. (1990). Guidelines. Methods for measuring the mass fraction of mobile forms of metals (copper, lead, zinc, nickel, cadmium, cobalt, chromium, manganese) in soil samples by atomic absorption analysis (approved by Governm. USSR Committee for Hydrometeorology 04 October 1989). Moscow: Goscomgidromet (in Russian) .

Reimann, C., & Garrett, R. G. (2005). Geochemical background—Concept and reality. Science of The Total Environment, 350 , 12–27. https://doi.org/10.1016/j.scitotenv.2005.01.047 .

RIVM (Netherlands National Institute for Public Health and the Environment). (2001). Re-evaluation of human-toxicological maximum permissible risk levels . (RIVM report 711701 025). Bilthoven: Rijksinstituut voor Volksgezondheid en Milieu (RIVM).

Rospotrebnadzor of Rostov Oblast (Rostov regional office of the Russian Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing). (2019). Report on the state of sanitary and epidemiological welfare of the population of the Rostov region in 2018 . Rostov-on-Don: Rospotrebnadzor of Rostov Oblast. (in Russian) .

Soil Survey Staff. (2011). Soil survey laboratory information manual . Soil survey investigations report No. 45, version 2.0. Linkoln: Department of Agriculture, Natural Resources Conservation Service.

Tang, Q., Liu, G., Zhou, C., Zhang, H., & Sun, R. (2013). Distribution of environmentally sensitive elements in residential soils near a coal-fired power plant: Potential risks to ecology and children’s health. Chemosphere, 93 (10), 2473–2479. https://doi.org/10.1016/j.chemosphere.2013.09.015 .

US EPA (US Environmental Protection Agency). (1989). Risk assessment guidance for superfund. Volume I: Human health evaluation manual (Part A). Interim Final . (EPA/540/1‐89/002). Washington, DC: Office of Emergency and Remedial Response.

US EPA (US Environmental Protection Agency). (2002). Supplemental guidance for developing soil screening levels for superfund sites . (OSWER 9355.4-24). Washington, DC: Office of Emergency and Remedial Response.

US EPA (US Environmental Protection Agency). (2011). Exposure factors handbook: 2011 edition . (EPA/600/R‐090/052F). Washington, DC: National Center for Environmental assessment.

US EPA (US Environmental Protection Agency). (2014). Human health evaluation manual, supplemental guidance: Update to standard default exposure factors . (OSWER 9200.1‐120). Washington, DC: National Center for Environmental assessment.

US EPA (US Environmental Protection Agency). (2019). IRIS assessments . Retrieved December 15, 2019, from https://cfpub.epa.gov/ncea/iris_drafts/AtoZ.cfm .

Vorobyova, L. A. (2006). Theory and practice of chemical analysis of soils . Moscow: GEOS. (in Russian) .

Youravong, N. (2011). Lead exposure and caries in children. In J. O. Nriagu (Ed.), Encyclopedia of environmental health (pp. 421–429). Oxford: Elsevier.

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This study was funded by the Russian Foundation of Basic Research (Project Nos. 19-05-50097 and 19-34-60041).

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Tatiana Minkina, Elizaveta Konstantinova, Tatiana Bauer, Saglara Mandzhieva, Svetlana Sushkova, Victor Chaplygin, Marina Burachevskaya & Alexey Maksimov

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Minkina, T., Konstantinova, E., Bauer, T. et al. Environmental and human health risk assessment of potentially toxic elements in soils around the largest coal-fired power station in Southern Russia. Environ Geochem Health 43 , 2285–2300 (2021). https://doi.org/10.1007/s10653-020-00666-4

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ORIGINAL RESEARCH article

Global research progress of gut microbiota and epigenetics: bibliometrics and visualized analysis.

• 1 School of Clinical Medicine, Chengdu University of Traditional Chinese Medicine (TCM), Chengdu, China
• 2 Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China

Background: Gut microbiota is an important factor affecting host health. With the further study of the mechanism of gut microbiota, significant progress has been made in the study of the link between gut microbiota and epigenetics. This study visualizes the body of knowledge and research priorities between the gut microbiota and epigenetics through bibliometrics.

Methods: Publications related to gut microbiota and epigenetics were searched in the Web of Science Core Collection (WoSCC) database. Vosviewer 1.6.17 and CiteSpace 6.1.R2 were used for bibliometric analysis.

Results: WoSCC includes 460 articles from 71 countries. The number of publications on gut microbiota and epigenetics has increased each year since 2011. The USA, PEOPLES R CHINA, and ITALY are at the center of this field of research. The University of California System, Harvard University, and the University of London are the main research institutions. Li, X, Yu, Q, Zhang, S X are the top authors in this research field. We found that current research hotspots and frontiers include short-chain fatty acids (SCFA) play an important role in gut microbiota and epigenetic mechanisms, gut microbiota and epigenetics play an important role in host obesity, diet, and metabolism. Gut microbiota and epigenetics are closely related to colorectal cancer, breast cancer, and inflammatory bowel disease. At the same time, we found that gut microbiota regulates epigenetics through the gut-brain axis and has an impact on psychiatric diseases. Therefore, probiotics can regulate gut microbiota, improve lifestyle, and reduce the occurrence and development of diseases.

Conclusion: This is the first comprehensive and in-depth bibliometric study of trends and developments in the field of gut microbiota and epigenetics research. This study helps to guide the direction of research scholars in their current field of study.

1 Introduction

Trillions of species of symbiotic microbes persist in the gastrointestinal tract, collectively known as the gut microbiota, and they are important factors affecting host health and disease ( 1 ). The human body and the microbiome are in a state of dynamic balance, and the microorganisms in the gut participate in many physiological functions of the human body, such as fermentation-related food components, vitamin synthesis, and maintenance of intestinal homeostasis ( 2 ). In recent years, with the deepening of the study of gut microbiota, it has been found that microbial signals can calibrate the transcriptional program of host cells through epigenetic modification without changing the underlying genetic code. DNA modification, histone modification, and regulation of non-coding RNA are forms of epigenetic changes to which the microbiome is sensitive ( 3 ). Studies have found that epigenetics is a key mechanism to regulate the development of host intestinal homeostasis and metabolic disorders. Epigenetic regulation of microbial communities can be influenced by host diet, antibiotic use, infection, etc ( 4 , 5 ). The effects of microbial metabolites on host health can be achieved by inducing epigenetic modifications, altering DNA methylation, and microRNAs expression ( 6 ).

With the in-depth study of the mechanism of gut microbiota, Research on gut microbiota and epigenetics has attracted more and more attention. However, this research area has not been thoroughly dissected using bibliometrics analysis. Bibliometrics analysis allows for quantitative analysis of literature in the field of study, using mathematical and statistical knowledge ( 7 ). Bibliometrics analysis can reflect the hot spots, emphases, and frontiers of the research field ( 8 ). In order to better grasp the knowledge of this research field, this study focuses on the hot spots, emphases, and trends of gut microbiota and epigenetics research.

2.1 Literature resources

We searched literature data related to the research field in the Web of Science Core Collection (WoSCC), a multidisciplinary and comprehensive database with a complete citation network ( 9 ). The search strategy is presented in Supplementary Material , which uses a combination of subject and free words for gut microbiota and epigenetics. The time for a literature search is no limit. The document type is set to Article or Review. The last step is to export and store all the retrieved documents as text files for further bibliometric research. On March 15, 2024, two researchers conducted an independent search of literature data. The complete retrieval process is shown in Figure 1 .

Figure 1 Flow diagram of the included articles.

2.2 Literature analysis

We used CiteSpace.6.1.R2, Vosviewer1.6.17, and Microsoft Office Excel 2010 for data analysis and management. Microsoft Office Excel 2010 software can manage data, tally annual publications, and create related tables. In addition, CiteSpace 6.1.R2 creates a visual map that provides a detailed summary analysis of annual publications by number, country, institution, author, keyword, and highly cited article. Vosviewer1.6.17 visualizes highly co-cited literature and co-occurrence of authors. The specific parameter Settings and results of CiteSpace are the same as those of previous Settings ( 8 ). Nodes can represent countries and institutions.

3.1 Analysis of annual publications and trends in publications

Until March 15, 2024, a total of 500 articles have been published in this field, including 164 articles and 296 review articles. Trends in a particular field of research can be measured by annual publications. The analysis shows that the number of papers in this field has increased year by year, from 4 papers in 2011 to a peak in 2022 and 2023 (n=85 papers) ( Figure 2 ). This indicates that the field is receiving increasing attention from researchers. In addition, the growth trend model shown in Figure 2 [coefficient of determination (R 2 ) = 0.5203] shows a positive correlation between publication year and publication, which means that the number of annual publications in the field will continue to rise.

Figure 2 Published trend chart concerning gut microbiota and epigenetics.

3.2 Analysis of the trend of countries, institutions, and authors

Articles were published in 71 countries/regions. The 71 nodes and 336 links represent countries and cooperation between countries in Figure 3 . The more a country has published in that area of study, the larger the nodes shown in the graph. If the centrality is greater than 0.1, the purple circle will appear outside the corresponding node on the network map. Table 1 lists the top 10 countries in terms of the number of published papers and their centrality. The United States published the most papers (168 publications, 32.81%), followed by China (77 publications, 15.04%) and Italy (54 publications, 10.55%), all of which are priority countries for gut microbiota and epigenetics research. Cooperation among countries is positively correlated with centrality. The results show that the United States (0.43), Italy (0.19), the People’s Republic of China (0.18), the United Kingdom (0.16) and India (0.14) are the five countries with the highest centrality.

Figure 3 Country/region collaboration network of research on gut microbiota and epigenetics. Created with CiteSpace.

Table 1 Countries/regions, institutions, and authors ranked by publications and centrality.

299 institutions contributed to the field of research. Figure 4 shows the collaboration between institutions, which includes 299 nodes and 693 connections. From Table 1 , We found that the top five universities with the highest number of published papers are the University of California System (17 publications, 16.83%), Harvard University (14 publications, 13.86%), the University of London (11 publications, 10.89%), and Baylor College of Science Medicine (10 publications, 9.90%), CIBER-Centro de Investigacion Biomedica en Red (9 publications, 8.91%). The University of California System (0.27), University of London (0.23), Harvard University (0.18), CIBER - Centre for Biomedical Research (0.15), and Karolinska Institutet (0.11) are the top five institutions with the most centricity, representing the most collaboration. The world’s top universities and institutions have made outstanding contributions to the development of the field.

Figure 4 Institution’ collaboration network of research on gut microbiota and epigenetics. Created with CiteSpace.

As shown in Figure 5 , 293 authors have published papers on gut microbiota and epigenetics. Table 1 lists the five authors with the highest number of published articles. Four authors, Li, X, Yu, Q, Zhang, S X, He, P F, contributed the most to the number of articles (4 publications per person, 21.05%), followed by Dinan, Timothy G (3 publications, 15.79%). These five authors play important roles in the field of gut microbiota and epigenetics research. The centrality of all authors is 0, indicating that the cooperation between authors still needs to be strengthened.

Figure 5 Authors’ collaboration network of research on gut microbiota and epigenetics. Created with VOSviewer.

3.3 Analysis of co-cited references

Co-cited references are those cited collectively by researchers. Through the analysis of co-cited references, VOSviewer visualizes the co-cited references, highlighting common research areas between gut microbiota and epigenetics. According to VOSviewer’s results, a total of 49,507 references were cited in this research area. When the number of citations is reduced to 18, 37 references remain. From Figure 6 , we can find that the co-cited references are divided into four clusters, corresponding to the four colors in the visualization diagram. The red cluster mainly shows the epigenetic regulation of host metabolism by intestinal microbes, including the epigenetic regulation of host obesity by gut microbiota ( 10 ), the interaction between diet and intestinal microbes mediates the epigenetic inheritance of host tissues or diseases ( 11 , 12 ), and the epigenetic regulation between gut microbiota and host metabolism ( 13 , 14 ). The literature on green clusters mainly introduces the research on the types and functions of gut microbiota and gene sequencing ( 15 – 17 ). Blue clusters of literature mainly focus on the basic studies on the regulation of intestinal inflammation and immune response by gut microbiota through derivative substances such as butyrate and receptor GPR43 ( 18 – 20 ). The literature in the yellow cluster mainly focuses on the link between diet and gut microbiota, including the key role of short-chain fatty acids (SFCAs) ( 21 – 23 ).

Figure 6 Visualization of a clustering map of co-cited references. Created with VOSviewer.

Table 2 lists the top 10 cited literature, most of which are from the world’s top journals, such as Nature, Science, etc. Therefore, the research on gut microbiota and epigenetics is the current research hotspot and frontier of the scientific community. “Diet-Microbiota Interactions Mediate Global Epigenetic Programming in Multiple Hosts Tissues “is the most widely cited paper in 2016 published in Molecular Cell ( 12 ). Among them, Krautkramer et al. proposed that microbial regulation of protein acetylation and methylation in host tissues through diet, as well as short-chain fatty acids fermented by gut microbes, can promote transcriptional responses to host epigenetic programming. In addition, it can be found from the top 10 most-cited papers that most of the cited papers come from high-quality journals such as Nature and Science, which indicates the cutting-edge and innovative nature of this research field. Secondly, most studies in the cited literature focus on how diet and obesity act on the epigenetic inheritance of multiple tissues through gut microbiota, and the regulation of inflammatory immunity by gut microbiota derivatives.

Table 2 Top 10 highly co-cited references.

The analysis of the top ten cited literature focused on the mechanism between the gut microbiota and epigenetics. In the first ten cited articles, Kimberly A Krautkramer found that short-chain fatty acid (SCFA), a major derivative of the gut microbiota, is able to influence host-related epigenetic phenotypes and is sensitive to host diet ( 10 ). Himanshu Kumar’s study found that the gut microbiota, as an epigenetic regulator, in the group dominated by Firmicutes, genes with differential methylation promoters are associated with disease risk, mainly associated with cardiovascular disease, especially with lipid metabolism, obesity, and inflammatory response ( 29 ). Patrick M Smith’s study found that short-chain fatty acids, the fermentation products of intestinal microbiota, can regulate Regulatory T cells (Tregs) and thus regulate intestinal inflammation ( 20 ). Yukihiro Furusawa’s study found that differentiation of colonic regulatory T cells is induced by butyrate derived from the gut microbiota to improve intestinal inflammation and immune response ( 19 ).

3.4 Analysis of highly cited literature

Table 3 shows the top 10 highly cited literature on gut microbiota and epigenetics, most of them come from the world’s top journals and represent the forefront of scientific development. The most cited article is titled “Diet-Microbiota Interactions Mediate Global Epigenetic Programming in Multiple Host Tissues “ ( 12 ) indicates that gut mediates the epigenetic state of host tissues and changes in chromatin status to the host and that SCFA influences host epigenetic programming. At the same time, the mechanism research of gut flora and epigenetics also ranked in the top 10.

Table 3 Top 10 highly cited references.

3.5 Analysis of keywords co-occurrence, clustering, burst

Keyword co-occurrence gives us an idea of the topic and scope of the research field ( Figure 7 ). The top 20 keywords in the co-occurrence rate and centrality of gut microbiota and epigenetics from 2011 to 2024 are shown in Table 4 . “gut microbiota” is the keyword of occurrence frequency, followed by “DNA methylation” and “chain fatty acids”. And more importantly, “gut microbiome”, “gene expression”, “intestinal microbiota”, “expression”, “oxidative stress”, and “colorectal” Keywords such as “cancer” are used more than 30 times, revealing the current research focus and topics in this field. Centrality is positively correlated with the degree of connection between keywords. In Table 4 , “gut microbiota” is the main intestinal microbiota, followed by “gut microbiome”, “dna methylation”, “association”, and “intestinal microbiota”. These keywords still focus on the link between gut microbiota and epigenetics and the relationship with DNA methylation.

Figure 7 Keyword co-occurrence map of gut microbiota and epigenetics. Created with VOSviewer.

Table 4 Top 20 keywords in terms of frequency and centrality.

To understand the research frontiers of gut microbiota and epigenetics since 2011, CiteSpace was used to cluster keywords for gut microbiota and epigenetics. Nine clusters are shown in Table 5 , Figures 8 and 9 . In general, when Silhouette is greater than 0.5, the clustering effect is reasonable ( 8 ). Cluster #0 is labeled “inflammatory bowel disease”, followed by Cluster #1 “Precision nutrition”, Cluster #2 “Noncommunicable diseases”, Cluster #3 “Gut microbiota”, Cluster #4 “Allergy development”, Cluster #5 “Machine learning”, Cluster #6 “Breast cancer”, Cluster #7 “Psychiatric disorder”, Cluster #8 “Programmable epigenome”, representing the forefront of research since 2017.

Table 5 Keyword cluster analysis.

Figure 8 Keyword cluster map of gut microbiota and epigenetics. Created with CiteSpace.

Figure 9 Keyword timeline map of gut microbiota and epigenetics. Created with CiteSpace.

Keyword bursts sum up the sudden growth of research content over a period of time, which may indicate future trends in research. Figure 10 shows the top 25 items with the highest burst intensity in this research subject. The red line in the graph indicates the length of time the keyword bursts. As we observe from the chart, the keyword themes gradually changed from “intestinal microbiota”, “long noncoding RNAs”, “childhood asthma”, “genome-wide association” to the current “breast cancer “, “weight loss”, “sodium butyrate”, “protein” and “microbiota”. This suggests that the correlation between the gut microbiota and epigenetic effects on cancer, metabolism, and mechanisms is the main focus of this research now and in the future.

Figure 10 Top 25 keywords with the strongest citation bursts.

4 Discussion

4.1 general information discussion.

This study collected all WoSCC data related to the research field to identify research hotspots and frontiers. The number of publications each year has been steadily increasing. With 168 publications, the United States produced the most publications, followed by China and Italy. Because of its very strong economic strength and beneficial policy and scientific support, the United States is the largest country in this field of research. At the same time, although China is a developing country, it has an important position in the field of gut microbiota and epigenetics research.

In specific research areas, collaborations between authors, institutions, and countries can be evaluated using bibliometrics ( 32 ). Centrality represents the closeness of cooperation. The top five countries with the highest centrality are the United States, Italy, China, the United Kingdom, and India, meaning that these countries can actively cooperate with different countries. Collaboration between institutions shows that the University of California System, the University of London, Harvard University, CIBER - Centro de Investigacion Biomedica en Red, and Karolinska Institutet cooperate most closely and have the highest central position. Li, X, Yu, Q, and Zhang, S X have published the most papers in this field. However, the centrality of all authors is 0, indicating that there is no cooperation among authors, and cooperation among authors in the field needs to be strengthened. Cooperation among authors requires cooperation in related research fields and policy support from governments. We believe that close cooperation between States, institutions, and authors will help to achieve great progress in this area.

4.2 Research focus and hotspot

Bibliometrics analysis can reflect the hot spots and frontiers of this research field. Based on multiple analyses of references and keywords, we found that the hot spots and trends of gut microbiota and epigenetics are related to host metabolism and mechanisms, including obesity, diet, DNA methylation, and the role of SFCAs. In addition, through keyword burst analysis and keyword clustering, it can be seen that scholars have conducted more comprehensive and in-depth research on gut microbiota and epigenetics, and have begun to study the impact of this field on host diseases, such as cancer, inflammatory bowel disease, and mental disorders, as well as research on gut-brain axis theory.

4.3 Regulatory mechanisms between gut microbiota and epigenetics

A growing body of evidence supports the interaction of gut microbiota with epigenetic processes. Epigenetic modifications affect host health and disease development by altering the cell’s transcriptional machinery to reprogram the host genome ( 33 ). Through bibliometrics analysis, we can learn that the current mechanism between gut microbiota and epigenetics is mainly related to SCFAs, so we will discuss this in detail. The fermentation of complex carbohydrates or starches involves a number of pathways associated with microorganisms ( 34 , 35 ). After the initial fermentation of carbohydrates in the small intestine, the microbiome ferments it into SFCAs, in which butyrate, propionate, and acetate account for the largest proportion ( 31 ). SCFAs can reduce the activity of deacetylase and play an important role in modifying gene expression ( 36 ). In one study, SCFAs revealed microbially relevant chromatin modification states and transcriptional reactions, including the regulation of histone acetylation and methylation ( 12 ). In addition, propionate and butyrate can promote adipocyte differentiation, which may partially inhibit the effect of histone deacetylase activity ( 37 ). SCFAs produced by Akkermansia muciniphila in the mouse ileum can be involved in the expression of histone deacetylase, transcription factors, cellular lipid metabolism, and satiety genes ( 30 ). All the above experiments indicate that SCFAs produced by gut microbiota through fermentation have an important influence on host epigenetics.

4.4 Effects of interactions between gut microbiota and epigenetic on host metabolism

Based on the results of the bibliometrics analysis, we found that the role of gut microbiota and epigenetics may play an important role in host diet, obesity, and metabolism. The complex interplay between epigenetics, gut microbiota, and diet has important implications for host obesity risk and host metabolic syndrome ( 6 ). The study found that the microbial diversity and abundance of obese patients were decreased, the proportion of Bacteroides and Lactobacillus was different, and the methylation levels of FFAR3 gene (FFAR3) and TLR genes TLR4 and TLR2 were decreased. There was a correlation between BMI and methylation of FFAR3 and TLR genes TLR4 and TLR2 ( 28 ). In addition, deep sequencing DNA methylation revealed a clear association between gut microbiota and epigenetics ( 29 ). One study confirmed that fecal micro-RNA (miRNA) is an important component of the gut microbiome ( 27 ). miRNA can mediate bidirectional host-microbial interaction ( 38 ). These studies provide insights into the relationship between gut microbes and metabolism-related epigenetics. Based on relevant literature data, further discovery of dietary approaches for beneficial bacterial populations and epigenetic changes in energy homeostasis may have important implications for obesity and metabolism-related clinical manifestations.

4.5 Effects of interactions between gut microbiota and epigenetics on host disease

Based on the results of the bibliometrics analysis, we found that the role between gut microbiota and epigenetics may play an important role in inflammatory bowel disease, cancers (colorectal cancer and breast cancer), and psychiatric disorders Research evidence suggests that intestinal microbiota disturbances and alterations in carcinogenic and tumor suppressor genes can cause colorectal cancer ( 39 ). The gut microbiota ferments dietary residues, providing energy for the microbiota and ultimately releasing short-chain fatty acids, including butyrate. Butyrate inhibits inflammation and cancer by affecting immunity, gene expression, and epigenetic regulation ( 40 ). It was found that microbial fermentation products and activated phytochemicals (such as butyrate and polyphenols) can prevent tumor transformation by inhibiting epigenetic mechanisms such as histone deacetylase ( 26 , 41 , 42 ). The ERα gene and BRCA1 gene, which are strongly associated with breast cancer, have been observed in epigenetic programming ( 43 ). The production of butyrate by the gut flora has been shown to activate epigenetic genes in cancer cells such as p21 and BAK ( 44 ). However, although gut bacteria can facilitate, epigenetic reprogramming, and contribute to the tumor process, microbiome epigenetic induction of tumor formation has not been proven. Further experiments are needed to confirm this.

Many factors, such as genetic, environmental, intestinal microbiota and immune abnormalities, are related to the occurrence of IBD ( 45 ). Genome-wide association studies of IBD identified more than 200 genetic risk loci for IBD, providing important evidence for the role of microorganisms in the pathogenesis of IBD ( 46 ). The gut microbiota may regulate epigenetic mechanisms by regulating multiple micronutrients and food components, which may increase the risk of IBD ( 47 ).

Multiple evidence suggests that mental illness is related to gut flora and interacts with each other through the gut-brain axis ( 25 , 48 , 49 ). The bidirectional connection between the gut and the brain is called the gut-brain axis. The microbiome is an important part of the triangular conversation ( 50 ). Gut microbiota regulates brain function by stimulating neuronal responses or secreting metabolites associated with nerves ( 51 ). The gut-brain axis may be involved in the transmission of vagus nerve and hormone signals ( 52 ). The gut-brain axis may influence brain functions such as cognition and learning, so targeting a patient’s specific gut flora may reduce symptoms of neurodegenerative diseases ( 53 ). The modes of epigenetic regulation include DNA methylation, post-transcriptional histone modification, and gene expression regulation of non-coding RNA ( 54 ). DNA methylation is closely related to neurological diseases ( 24 ). Gut microbiota can secrete synthetic folic acid, vitamin B12, and choline to produce methyl donors (6-methyltetrahydrofolate) and to form S-adenosine methionine (SAM), which is the main methyl donor in DNA methylation ( 55 ). Choline is not only an important nutrient for the brain but also promotes SAM production and is a key methyl donor for DNA and histone methylation ( 56 ). The hypothalamic-pituitary-adrenal axis (HPA) is an important communication pathway in the gut-brain axis ( 51 ). The normal operation of the HPA axis requires the presence of GR (ligand-activated transcription factor). Studies have found that individuals with genetic abnormalities of the GR gene in the brain are associated with bipolar disorder and schizophrenia ( 57 ). Epigenetic modifications do not change the DNA sequence, so the DNA sequence is stable for a long time. The microbiome is capable of modifying the host epigenome via the gut-brain axis and causing visible behavioral or phenotypic changes in the host. Although epigenetic modification changes are more lasting, they are not permanent, so it is possible to restore the gut microbiota and make lifestyle changes (such as sleep, diet, exercise, etc.) through supplementation with probiotics and probiotics, which have important implications for the improvement of conditions such as diabetes, obesity, neurodegenerative diseases, and depression ( 57 ).

5 Advantages and limitations of research

Visual analysis of bibliometrics can comprehensively display the key points, hot spots, and frontiers of the current research field, and provide researchers with reference research directions. However, there are some limitations to our study. First, we did not search all the databases, which may have led to the omission of literature. In addition, we failed to ensure that every piece of literature fully met the requirements of the study. Finally, the quality of the retrieved articles cannot be completely guaranteed, which will affect the rigor of the analysis.

6 Conclusion

This study evaluated and visualized relevant publications on gut microbiota and epigenetics using bibliometrics and visualization analysis. The number of research publications in the field of gut microbiota and epigenetics is increasing every year. The country with the highest number of articles is the United States. The University of California System and Li, X are among the most influential institutions and authors in the field. In addition, our study provides a comprehensive analysis of the research hotspots and research directions of gut microbiota and epigenetics. Based on the bibliometric analysis of gut microbiota and epigenetics, we found that short-chain fatty acids are an important component of the mechanism between gut microbiota and epigenetics. The interaction between gut microbiota and epigenetics play an important role in host obesity, diet, and metabolism. Gut microbiota and epigenetics are closely related to colorectal cancer, breast cancer, and inflammatory bowel disease. At the same time, we found that gut microbiota regulates epigenetics through the gut-brain axis and has an impact on psychiatric diseases. Therefore, probiotics can regulate gut microbiota, improve lifestyle, and reduce the occurrence and development of diseases.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.

Author contributions

ST: Conceptualization, Data curation, Methodology, Software, Supervision, Visualization, Writing – original draft. MC: Conceptualization, Data curation, Methodology, Software, Writing – review & editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Funding was provided by the National Natural Science Foundation of China (number: 82274529) and the National Key Research and Development Program of China (number: 2019YFC1709004).

Acknowledgments

Thanks for the fund support provided by the National Natural Science Foundation of China and the National Key Research and Development Program.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2024.1412640/full#supplementary-material

Supplementary Material | Retrieval strategies for gut microbiota and epigenetics.

1. Marchesi JR, Adams DH, Fava F, Hermes GD, Hirschfield GM, Hold G, et al. The gut microbiota and host health: a new clinical frontier. Gut . (2016) 65:330–9. doi: 10.1136/gutjnl-2015–309990

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Qin Y, Wade PA. Crosstalk between the microbiome and epigenome: messages from bugs. J Biochem . (2018) 163:105–12. doi: 10.1093/jb/mvx080

3. Woo V, Alenghat T. Epigenetic regulation by gut microbiota. Gut Microbes . (2022) 14:2022407. doi: 10.1080/19490976.2021.2022407

4. Rodiño-Janeiro BK, Vicario M, Alonso-Cotoner C, Pascua-García R, Santos J. A review of microbiota and irritable bowel syndrome: future in therapies. Adv Ther . (2018) 35:289–310. doi: 10.1007/s12325–018-0673–5

5. Mochizuki K, Ishiyama S, Hariya N, Goda T. Regulation of carbohydrate-responsive metabolic genes by histone acetylation and the acetylated histone reader BRD4 in the gene body region. Front Mol Biosci . (2021) 8:682696. doi: 10.3389/fmolb.2021.682696

6. Cuevas-Sierra A, Ramos-Lopez O, Riezu-Boj JI, Milagro FI, Martinez JA. Diet, gut microbiota, and obesity: links with host genetics and epigenetics and potential applications. Adv Nutr . (2019) 10:S17–30. doi: 10.1093/advances/nmy078

7. Tian S, Zhang H, Chen S, Wu P, Chen M. Global research progress of visceral hypersensitivity and irritable bowel syndrome: bibliometrics and visualized analysis. Front Pharmacol . (2023) 14:1175057. doi: 10.3389/fphar.2023.1175057

8. Zou X, Sun Y. Bibliometrics analysis of the research status and trends of the association between depression and insulin from 2010 to 2020. Front Psychiatry . (2021) 12:683474. doi: 10.3389/fpsyt.2021.683474

9. Web of Science. (2024). Available online at: https://www.webofscience.com/wos/ (Accessed April 18, 2024).

Google Scholar

10. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature . (2006) 444:1027–31. doi: 10.1038/nature05414

11. Paul B, Barnes S, Demark-Wahnefried W, Morrow C, Salvador C, Skibola C, et al. Influences of diet and the gut microbiome on epigenetic modulation in cancer and other diseases. Clin Epigenetics . (2015) 7:112. doi: 10.1186/s13148–015-0144–7

12. Krautkramer KA, Kreznar JH, Romano KA, Vivas EI, Barrett-Wilt GA, Rabaglia ME, et al. Diet-microbiota interactions mediate global epigenetic programming in multiple host tissues. Mol Cell . (2016) 64:982–92. doi: 10.1016/j.molcel.2016.10.025

13. Takahashi K, Sugi Y, Nakano K, Tsuda M, Kurihara K, Hosono A, et al. Epigenetic control of the host gene by commensal bacteria in large intestinal epithelial cells. J Biol Chem . (2011) 286:35755–62. doi: 10.1074/jbc.M111.271007

14. Miro-Blanch J, Yanes O. Epigenetic regulation at the interplay between gut microbiota and host metabolism. Front Genet . (2019) 10:638. doi: 10.3389/fgene.2019.00638

15. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature . (2010) 464:59–65. doi: 10.1038/nature08821

16. Arumugam M, Raes J, Pelletier E, Le Paslier D, Yamada T, Mende DR, et al. Enterotypes of the human gut microbiome. Nature . (2011) 473:174–80. doi: 10.1038/nature09944

17. Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, et al. Human gut microbiome viewed across age and geography. Nature . (2012) 486:222–7. doi: 10.1038/nature11053

18. Maslowski KM, Vieira AT, Ng A, Kranich J, Sierro F, Yu D, et al. Regulation of inflammatory responses by gut microbiota and chemoattractant receptor GPR43. Nature . (2009) 461:1282–6. doi: 10.1038/nature08530

19. Furusawa Y, Obata Y, Fukuda S, Endo TA, Nakato G, Takahashi D, et al. Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells. Nature . (2013) 504:446–50. doi: 10.1038/nature12721

20. Smith PM, Howitt MR, Panikov N, Michaud M, Gallini CA, Bohlooly-Y M, et al. The microbial metabolites, short-chain fatty acids, regulate colonic Treg cell homeostasis. Science . (2013) 341:569–73. doi: 10.1126/science.1241165

21. Wu GD, Chen J, Hoffmann C, Bittinger K, Chen YY, Keilbaugh SA, et al. Linking long-term dietary patterns with gut microbial enterotypes. Science . (2011) 334:105–8. doi: 10.1126/science.1208344

22. David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature . (2014) 505:559–63. doi: 10.1038/nature12820

23. Koh A, De Vadder F, Kovatcheva-Datchary P, Bäckhed F. From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell . (2016) 165:1332–45. doi: 10.1016/j.cell.2016.05.041

24. Ladd-Acosta C, Hansen KD, Briem E, Fallin MD, Kaufmann WE, Feinberg AP. Common DNA methylation alterations in multiple brain regions in autism. Mol Psychiatry . (2014) 19:862–71. doi: 10.1038/mp.2013.114

25. Toledo ARL, Monroy GR, Salazar FE, Lee JY, Jain S, Yadav H, et al. Gut-brain axis as a pathological and therapeutic target for neurodegenerative disorders. Int J Mol Sci . (2022) 23:1184. doi: 10.3390/ijms23031184

26. Beyer-Sehlmeyer G, Glei M, Hartmann E, Hughes R, Persin C, Böhm V, et al. Butyrate is only one of several growth inhibitors produced during gut flora-mediated fermentation of dietary fiber sources. Br J Nutr . (2003) 90:1057–70. doi: 10.1079/bjn20031003

27. Liu S, da Cunha AP, Rezende RM, Cialic R, Wei Z, Bry L, et al. The host shapes the gut microbiota via fecal microRNA. Cell Host Microbe . (2016) 19:32–43. doi: 10.1016/j.chom.2015.12.005

28. Remely M, Lovrecic L, de la Garza AL, Migliore L, Peterlin B, Milagro FI, et al. Therapeutic perspectives of epigenetically active nutrients. Br J Pharmacol . (2015) 172:2756–68. doi: 10.1111/bph.12854

29. Kumar H, Lund R, Laiho A, Lundelin K, Ley RE, Isolauri E, et al. Gut microbiota as an epigenetic regulator: pilot study based on whole-genome methylation analysis. mBio . (2014) 5:e02113–14. doi: 10.1128/mBio.02113–14

30. Lukovac S, Belzer C, Pellis L, Keijser BJ, de Vos WM, Montijn RC, et al. Differential modulation by Akkermansia muciniphila and Faecalibacterium prausnitzii of host peripheral lipid metabolism and histone acetylation in mouse gut organoids. mBio . (2014) 5:e01438–14. doi: 10.1128/mBio.01438–14

31. Flint HJ, Duncan SH, Scott KP, Louis P. Links between diet, gut microbiota composition and gut metabolism. Proc Nutr Soc . (2015) 74:13–22. doi: 10.1017/S0029665114001463

32. Ma C, Su H, Li H. Global research trends on prostate diseases and erectile dysfunction: A bibliometric and visualized study. Front Oncol . (2021) 10:627891. doi: 10.3389/fonc.2020.627891

33. Bhat MI, Kapila R. Dietary metabolites derived from gut microbiota: critical modulators of epigenetic changes in mammals. Nutr Rev . (2017) 75:374–89. doi: 10.1093/nutrit/nux001

34. Cordain L, Eaton SB, Sebastian A, Mann N, Lindeberg S, Watkins BA, et al. Origins and evolution of the Western diet: health implications for the 21st century. Am J Clin Nutr . (2005) 81:341–54. doi: 10.1093/ajcn.81.2.341

35. Balter V, Braga J, Télouk P, Thackeray JF. Evidence for dietary change but not landscape use in South African early hominins. Nature . (2012) 489:558–60. doi: 10.1038/nature11349

36. Kasubuchi M, Hasegawa S, Hiramatsu T, Ichimura A, Kimura I. Dietary gut microbial metabolites, short-chain fatty acids, and host metabolic regulation. Nutrients . (2015) 7:2839–49. doi: 10.3390/nu7042839

37. Li G, Yao W, Jiang H. Short-chain fatty acids enhance adipocyte differentiation in the stromal vascular fraction of porcine adipose tissue. J Nutr . (2014) 144:1887–95. doi: 10.3945/jn.114.198531

38. Yuan C, Burns MB, Subramanian S, Blekhman R. Interaction between host microRNAs and the gut microbiota in colorectal cancer. mSystems . (2018) 3:e00205–17. doi: 10.1128/mSystems.00205–17

39. Tjalsma H, Boleij A, Marchesi JR, Dutilh BE. A bacterial driver-passenger model for colorectal cancer: beyond the usual suspects. Nat Rev Microbiol . (2012) 10:575–82. doi: 10.1038/nrmicro2819

40. O’Keefe SJ. Diet, microorganisms and their metabolites, and colon cancer. Nat Rev Gastroenterol Hepatol . (2016) 13:691–706. doi: 10.1038/nrgastro.2016.165

41. Fung KY, Cosgrove L, Lockett T, Head R, Topping DL. A review of the potential mechanisms for the lowering of colorectal oncogenesis by butyrate. Br J Nutr . (2012) 108:820–31. doi: 10.1017/S0007114512001948

42. Verma M. Cancer control and prevention: nutrition and epigenetics. Curr Opin Clin Nutr Metab Care . (2013) 16:376–84. doi: 10.1097/MCO.0b013e328361dc70

43. Toland A. Aberrant epigenetic regulation in breast cancer. In: Miranovitz J, Niller H, editors. Patho-Epigenetics of Disease . Springer, New York, NY, USA (2012). p. 91–122.

44. Berni Canani R, Di Costanzo M, Leone L. The epigenetic effects of butyrate: potential therapeutic implications for clinical practice. Clin Epigenet . (2012) 4:4. doi: 10.1186/1868–7083-4–4

CrossRef Full Text | Google Scholar

45. Ray G, Longworth MS. Epigenetics, DNA organization, and inflammatory bowel disease. Inflammation Bowel Dis . (2019) 25:235–47. doi: 10.1093/ibd/izy330

46. Ahmed I, Roy BC, Khan SA, Septer S, Umar S. Microbiome, metabolome and inflammatory bowel disease. Microorganisms . (2016) 4:20. doi: 10.3390/microorganisms4020020

47. Rapozo DC, Bernardazzi C, de Souza HS. Diet and microbiota in inflammatory bowel disease: The gut in disharmony. World J Gastroenterol . (2017) 23:2124–40. doi: 10.3748/wjg.v23.i12.2124

48. Alharthi A, Alhazmi S, Alburae N, Bahieldin A. The human gut microbiome as a potential factor in autism spectrum disorder. Int J Mol Sci . (2022) 23:1363. doi: 10.3390/ijms23031363

49. Gong W, Guo P, Li Y, Liu L, Yan R, Liu S, et al. Role of the gut-brain axis in the shared genetic etiology between gastrointestinal tract diseases and psychiatric disorders: A genome-wide pleiotropic analysis. JAMA Psychiatry . (2023) 80:360–70. doi: 10.1001/jamapsychiatry.2022.4974

50. Agirman G, Yu KB, Hsiao EY. Signaling inflammation across the gut-brain axis. Science . (2021) 374:1087–92. doi: 10.1126/science.abi6087

51. Begum N, Mandhare A, Tryphena KP, Srivastava S, Shaikh MF, Singh SB, et al. Epigenetics in depression and gut-brain axis: A molecular crosstalk. Front Aging Neurosci . (2022) 14:1048333. doi: 10.3389/fnagi.2022.1048333

52. Quigley EMM. Microbiota-brain-gut axis and neurodegenerative diseases. Curr Neurol Neurosci Rep . (2017) 17:94. doi: 10.1007/s11910–017-0802–6

53. Tilocca B, Pieroni L, Soggiu A, Britti D, Bonizzi L, Roncada P, et al. Gut-brain axis and neurodegeneration: state-of-the-art of meta-omics sciences for microbiota characterization. Int J Mol Sci . (2020) 21:4045. doi: 10.3390/ijms21114045

54. Sharma M, Li Y, Stoll ML, Tollefsbol TO. The epigenetic connection between the gut microbiome in obesity and diabetes. Front Genet . (2020) 10:1329. doi: 10.3389/fgene.2019.01329

55. Mahmoud AM, Ali MM. Methyl donor micronutrients that modify DNA methylation and cancer outcome. Nutrients . (2019) 11:608. doi: 10.3390/nu11030608

56. Romano KA, Martinez-Del Campo A, Kasahara K, Chittim CL, Vivas EI, Amador-Noguez D, et al. Metabolic, epigenetic, and transgenerational effects of gut bacterial choline consumption. Cell Host Microbe . (2017) 22:279–290.e7. doi: 10.1016/j.chom.2017.07.021

57. Philibert R, Madan A, Andersen A, Cadoret R, Packer H, Sandhu H. Serotonin transporter mRNA levels are associated with the methylation of an upstream CpG island. Am J Med Genet B Neuropsychiatr Genet . (2007) 144B:101–5. doi: 10.1002/ajmg.b.30414

Keywords: gut microbiota, epigenetics, bibliometrics, mechanism, host diseases, gut-brain axis

Citation: Tian S and Chen M (2024) Global research progress of gut microbiota and epigenetics: bibliometrics and visualized analysis. Front. Immunol. 15:1412640. doi: 10.3389/fimmu.2024.1412640

Received: 05 April 2024; Accepted: 26 April 2024; Published: 13 May 2024.

Reviewed by:

Copyright © 2024 Tian and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Min Chen, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Introduction
• Conclusions
• Article Information

The process for inclusion and exclusion of participants is delineated for each study. A total of 23 338 participants were ultimately analyzed, including 754 carriers of the V142I variant. ARIC indicates Atherosclerosis Risk in Communities; HF, heart failure; MESA, Multi-Ethnic Study of Atherosclerosis; REGARDS, Reasons for Geographic and Racial Differences in Stroke; and WHI, Women’s Health Initiative.

Ten-year hazard ratios and 95% CIs (shaded areas) are estimated at each age between 50 and 90 years for carriers vs noncarriers. Analyses are adjusted for interactions between study genotyping platform and the first 10 principal components, while stratified by sex and study genotyping platform. HF indicates heart failure.

A, Estimated mean overall survival in carriers and noncarriers for every year between ages 50 and 95 years. B, The difference in mean years lost among carriers compared with noncarriers shown with the smoothed estimate (blue line), and 95% CI of the smoothed estimate (shaded area) after application of a locally weighted scatterplot smoothing procedure.

eFigure 1. Kaplan-Meier Curves for Heart Failure and Mortality Events by V142I Carrier Status

eFigure 2. Kaplan-Meier Curves for Heart Failure Events by V142I Carrier Status

eFigure 3. V142I Hazard Ratio for Heart Failure Events by Age

eFigure 4. V142I Hazard Ratio for Heart Failure Hospitalization or Death by Age and Sex

eFigure 5. V142I Hazard Ratio for Adverse Cardiovascular Events by Age Using 99%

eFigure 6. V142I Hazard Ratio for Heart Failure Events by Age Using 99% Confidence

eFigure 7. Relative Effect of V142I on Remaining Years of Life Compared With Noncarriers

eFigure 8. Effect of V142I on HFH-free Survival Compared With Noncarriers

eFigure 9. Relative Effect of V142I on Remaining Years of Life Free From HFH Compared With Noncarriers

eTable 1. Hazard Ratios for Heart Failure Hospitalization and Death by Carrier Status and Cardiovascular Risk Factors

eTable 2. Events and Hazard Ratios for Adverse Cardiovascular Outcomes by Number of Alleles

eTable 3. Interaction Analysis of the Variant With Select Variables for Study Outcomes

eTable 4. Estimated Survival Time Comparing Carriers and Noncarriers by Age for All-Cause Mortality With Extrapolation to the United State Population

eTable 5. Estimated Survival Time Comparing Carriers and Noncarriers by Age for Heart Failure Hospitalization or Death

eReferences

Data Sharing Statement

• Association of Transthyretin Val122Ile Variant With Incident Heart Failure Among Black Individuals JAMA Original Investigation April 12, 2022 This retrospective population-based cohort study compares carriers of the amyloidogenic Val122Ile TTR variant vs noncarriers to assess the association of having the variant with risk of heart failure and mortality in self-identified Black individuals living in the US. Vibhu Parcha, MD; Gargya Malla, MD, MPH, PhD; Marguerite R. Irvin, PhD; Nicole D. Armstrong, PhD; Suzanne E. Judd, PhD; Leslie A. Lange, PhD; Mathew S. Maurer, MD; Emily B. Levitan, ScD; Parag Goyal, MD, MSc; Garima Arora, MD; Pankaj Arora, MD
• Cardiac Amyloidosis Due to Transthyretin Protein JAMA Review March 5, 2024 This Review summarizes the clinical presentation, diagnosis, and treatment of amyloidosis from transthyretin (ATTR) protein cardiomyopathy. Frederick L. Ruberg, MD; Mathew S. Maurer, MD
• Heart Failure in African American Individuals, Version 2.0 JAMA Editorial May 12, 2024 Clyde W. Yancy, MD, MSc
• Addressing Health Disparities—The Case for Variant Transthyretin Cardiac Amyloidosis Grows Stronger JAMA Editorial May 12, 2024 Mathew S. Maurer, MD; Edward J. Miller, MD, PhD; Frederick L. Ruberg, MD

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Selvaraj S , Claggett B , Shah SH, et al. Cardiovascular Burden of the V142I Transthyretin Variant. JAMA. Published online May 12, 2024. doi:10.1001/jama.2024.4467

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Cardiovascular Burden of the V142I Transthyretin Variant

• 1 Division of Cardiology, Department of Medicine, Duke University Medical Center, Durham, North Carolina
• 2 Duke Molecular Physiology Institute, Durham, North Carolina
• 3 Division of Cardiology, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
• 4 Center for Public Health Genomics, University of Virginia, Charlottesville
• 5 Division of Cardiology, Department of Medicine and Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
• 6 The MIND Center, University of Mississippi Medical Center, Jackson
• 7 Department of Epidemiology, University of Alabama at Birmingham
• 8 Division of Cardiovascular Disease, University of Alabama at Birmingham
• 9 Department of Medicine, Weill Cornell Medicine, New York, New York
• 10 Department of Medicine III, Saarland University, Homburg, Saarland, Germany
• 11 Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York
• 12 Center for Primary Care and Prevention, Department of Family Medicine, Department of Epidemiology, Warren Alpert Medical Scholl of Brown University, Brown University School of Public Health, Providence, Rhode Island
• 13 Division of Cardiology, University of Washington, Seattle
• 14 Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
• 15 University College London, London, United Kingdom
• Editorial Heart Failure in African American Individuals, Version 2.0 Clyde W. Yancy, MD, MSc JAMA
• Editorial Addressing Health Disparities—The Case for Variant Transthyretin Cardiac Amyloidosis Grows Stronger Mathew S. Maurer, MD; Edward J. Miller, MD, PhD; Frederick L. Ruberg, MD JAMA
• Original Investigation Association of Transthyretin Val122Ile Variant With Incident Heart Failure Among Black Individuals Vibhu Parcha, MD; Gargya Malla, MD, MPH, PhD; Marguerite R. Irvin, PhD; Nicole D. Armstrong, PhD; Suzanne E. Judd, PhD; Leslie A. Lange, PhD; Mathew S. Maurer, MD; Emily B. Levitan, ScD; Parag Goyal, MD, MSc; Garima Arora, MD; Pankaj Arora, MD JAMA
• Review Cardiac Amyloidosis Due to Transthyretin Protein Frederick L. Ruberg, MD; Mathew S. Maurer, MD JAMA

Question   What is the natural history and cardiovascular burden of the V142I variant of the transthyretin ( TTR ) gene among US Black carriers across mid to late life?

Findings   Across 4 cohort studies, carriers (754/23 338) faced a substantially increased risk for heart failure (by age 63 years) and death (by age 72 years), similarly in men and women, which was estimated to contribute to approximately 1 million years of life lost among US Black individuals aged ≥50 years.

Meaning   These data show the large, age-dependent burden of V142I, which may guide discussions regarding the initiation and results of genetic screening, provide clinicians with risk estimates to share with patients, and inform strategies for early targeted therapy.

Importance   Individual cohort studies concur that the amyloidogenic V142I variant of the transthyretin ( TTR ) gene, present in 3% to 4% of US Black individuals, increases heart failure (HF) and mortality risk. Precisely defining carrier risk across relevant clinical outcomes and estimating population burden of disease are important given established and emerging targeted treatments.

Objectives   To better define the natural history of disease in carriers across mid to late life, assess variant modifiers, and estimate cardiovascular burden to the US population.

Design, Setting, and Participants   A total of 23 338 self-reported Black participants initially free from HF were included in 4 large observational studies across the US (mean [SD], 15.5 [8.2] years of follow-up). Data analysis was performed between May 2023 and February 2024.

Exposure   V142I carrier status (n = 754, 3.2%).

Main Outcomes and Measures   Hospitalizations for HF (including subtypes of reduced and preserved ejection fraction) and all-cause mortality. Outcomes were analyzed by generating 10-year hazard ratios for each age between 50 and 90 years. Using actuarial methods, mean survival by carrier status was estimated and applied to the 2022 US population using US Census data.

Results   Among the 23 338 participants, the mean (SD) age at baseline was 62 (9) years and 76.7% were women. Ten-year carrier risk increased for HF hospitalization by age 63 years, predominantly driven by HF with reduced ejection fraction, and 10-year all-cause mortality risk increased by age 72 years. Only age (but not sex or other select variables) modified risk with the variant, with estimated reductions in longevity ranging from 1.9 years (95% CI, 0.6-3.1) at age 50 to 2.8 years (95% CI, 2.0-3.6) at age 81. Based on these data, 435 851 estimated US Black carriers between ages 50 and 95 years are projected to cumulatively lose 957 505 years of life (95% CI, 534 475-1 380 535) due to the variant.

Conclusions and Relevance   Among self-reported Black individuals, male and female V142I carriers faced similar and substantial risk for HF hospitalization, predominantly with reduced ejection fraction, and death, with steep age-dependent penetrance. Delineating the individual contributions of, and complex interplay among, the V142I variant, ancestry, the social construct of race, and biological or social determinants of health to cardiovascular disease merits further investigation.

Transthyretin cardiac amyloidosis (ATTR-CA) is an increasingly recognized cardiomyopathy resulting from extracellular cardiac deposition of the misfolded transthyretin protein. ATTR-CA can occur in the presence of a detected genetic variant (ATTRv-CA, variant related) or its absence (ATTRwt-CA, wild-type related). The amyloidogenic V142I (legacy nomenclature V122I) variant of the transthyretin ( TTR ) gene has been reported to be present in a significant proportion of US Black individuals (3%-4%) (particularly in comparison with other ancestry groups), 1 , 2 is the most common cause of ATTRv-CA in the US, 3 and demonstrates age-dependent anatomic penetrance on autopsy analysis. 4 The American College of Medical Genetics recently classified the transthyretin variants as clinically actionable reportable secondary findings, 5 and individual epidemiologic studies concur that carriers face increased risk for heart failure (HF) and all-cause mortality. 1 , 6 - 10 The availability of several targeted treatments, which may be more effective earlier in the disease process, has heightened interest in identifying at-risk individuals. 11 , 12

Because testing for the V142I variant is typically performed after a carrier presents with disease, precise data are needed regarding long-term, and modifiers of, risk in unselected carriers. To better define the natural history of disease in V142I carriers, data from Black participants in 4 large observational studies based in the US were combined. Pooling data from geographically diverse cohorts facilitated more precise and generalizable risk estimation across mid to late life, the ability to assess less-frequent outcomes (including subtypes of HF), analysis of effect modifiers (particularly sex, which is thought to influence disease manifestations), 2 , 6 and estimation of years of life lost among V142I carriers.

We included 23 338 self-reported Black participants, including 754 carriers (3.2%) who were initially free of HF with available genotyping ( Figure 1 ). This study involved self-reported Black participants in keeping with prior cohort studies included in this analysis that studied risk stratification with the variant, although race is a social construct and should not be used as a proxy for ancestry. 1 , 8 , 10 Participants provided written informed consent, and institutional review board approval was received from all participating institutions. This study followed the reporting guidelines of the Strengthening the Reporting of Genetic Association Studies (STREGA, an extension of the STROBE Statement).

The Atherosclerosis Risk in Communities Study is a prospective study in 4 communities across the US composed of 15 792 participants, aged 45 to 64 years, recruited between 1987 and 1989. 13 A total of 3543 Black participants (including 112 participants who were heterozygous for V142I) were included for analysis.

The Multi-Ethnic Study of Atherosclerosis is a cohort study of 6 communities and recruited 6814 participants free of clinical cardiovascular disease aged 45 to 84 years between July 2000 and August 2002. 14 A total of 1584 Black participants, including 49 participants who were heterozygous for V142I, were included for analysis.

The Reasons for Geographic and Racial Differences in Stroke Study recruited 30 239 adults at least 45 years old between January 2003 and October 2007. 15 Participants were randomly selected from a commercially available list to create a sample balance on race and sex across the stroke buckle, the stroke belt, and the rest of the continental US. A total of 8527 Black participants (including 259 heterozygous and 3 homozygous for V142I) met inclusion criteria for the study. 10

Women were eligible to participate in the Women’s Health Initiative if they were 50 to 79 years of age, generally healthy, and postmenopausal at the time of enrollment. 16 A total of 161 808 participants were enrolled between 1993 and 1998 in the observational or clinical trial groups. A total of 9684 Black women (including 330 heterozygous and 1 homozygous for V142I) were included in this analysis.

The median African genetic ancestry percentage for each cohort was determined. Details regarding individual study cohorts, population descriptors, genotyping, ancestry analysis, comorbidities, and laboratory values are provided in the eMethods in Supplement 1 .

Longitudinal outcomes included first HF hospitalization, first HF hospitalization subtypes (HF with reduced ejection fraction [HFrEF] and HF with preserved ejection fraction [HFpEF]), all-cause mortality, and a composite of HF hospitalization or all-cause mortality. HFpEF was defined by an EF of 50% or greater or qualitatively normal EF, while HFrEF was defined by an EF less than 50% or a qualitatively low EF (eMethods in Supplement 1 ). This EF dichotomization facilitated inclusion of qualitative reports of EF.

Baseline characteristics were summarized using descriptive statistics, stratified by carrier status. We performed Cox proportional hazards models, stratifying by age, sex, and genotype platform, while adjusting for interactions between genotyping platform and the first 10 principal components, 8 , 10 using time from the baseline visit as the time scale to describe the relationship between the variant and adverse outcomes. Proportional hazards were assessed via Schoenfeld residuals.

We assessed for interactions between carrier status and several variables for HF hospitalization, all-cause mortality, and the combined outcome (HF hospitalization or all-cause mortality). Given strong effect modification by age, subsequent modeling focused on using sequences of 10-year age windows (eg, beginning age 50 through 59 years), generating 10-year adjusted hazard ratios using Cox regression, stratifying by sex and genotype platform while adjusting for the interactions between genotyping platform and principal components. 9 To better visualize these resulting estimates, we applied locally weighted scatterplot smoothing (LOWESS). 9 , 17 , 18 For LOWESS, tricube weighting was used with bandwidth of 0.8 (80% of observations used at each point). 19 This process was repeated for starting years between ages 50 and 90 years for HF hospitalization and death analyses, and between 58 and 90 years for HFpEF and HFrEF hospitalization (given fewer events at the lower age range). We reported age at first nominally statistically significant risk in each outcome. We performed post hoc sensitivity analyses using nominal statistical significance at α = .01 to acknowledge multiple age ranges tested. Participants were censored if they died (for HF hospitalization analyses) or were lost to follow-up, while participants were administratively censored at the time of last follow-up. For incident HFpEF hospitalization analyses, participants experiencing HF hospitalization with undetermined EF or reduced EF were censored (with parallel considerations for incident HFrEF hospitalization).

To estimate years of life lost among carriers compared with noncarriers, we used previously validated actuarial (age-based) methods to calculate nonparametric Kaplan-Meier estimates of overall survival and HF hospitalization–free survival at every year of age specified. 17 , 18 This method uses age (at a given starting age and at the time of death) as the time component. The area under the survival curve reflected projected event-free survival and overall survival. For each age between 50 and 95 years, we compared survival estimates of carriers and noncarriers. Estimates of survival gains were smoothed with LOWESS.

Finally, we applied these actuarial estimates of years of life lost at each age to the US population of Black individuals. For each age between 50 and 95 years, we extracted data on the estimated number of living Black individuals from the US Census Bureau’s American Community Survey 5-Year Estimates from 2022, which was then multiplied by the carrier frequency observed in the current analysis to estimate the number of carriers at each age in the US (accounting for decreasing frequency of the variant aging given increasing mortality risk). The years of life lost at each age among carriers was multiplied by the number of estimated carriers in the population to generate total years lost at each age, which was then summed to estimate the numbers of years lost among carriers at least age 50 years. Analyses were performed using Stata version 18 (StataCorp LLC). For interaction testing, a 2-sided P value <.05 divided by 9 (ie, number of subgroups) was considered significant. For other analyses, a 2-sided P value <.05 was considered significant.

The mean (SD) age at visit 1 was 62 (9) years, 76.7% were women (due to the large sample size included from WHI), 62.9% had hypertension, and 21.9% had diabetes ( Table 1 ). Carrier percentages were similar between men (3.0%) and women (3.3%). Characteristics were generally balanced across V142I carrier status.

Total events and hazard ratios are shown in Table 2 and Kaplan-Meier event curves are displayed in eFigures 1 and 2 in Supplement 1 . With a mean (SD) 15.5 (8.2) years of follow-up, carriers faced an increased risk for all study outcomes, though the association with HFpEF hospitalization did not reach statistical significance. Carrier risks for HF and death were comparable with several traditional cardiovascular risk factors (eTable 1 in Supplement 1 ). Risk for HF hospitalization or death was significantly increased among the 4 homozygotes compared with heterozygotes (hazard ratio, 7.75 [95% CI, 2.24-26.79]) (eTable 2 in Supplement 1 ). eTable 3 in Supplement 1 shows interaction P values between carrier status and select variables, including study cohort, age, sex, hypertension, diabetes, systolic blood pressure, heart rate, body mass index, and African ancestry with study outcomes. Of these, only age was identified as a significant modifier of variant risk.

To further accommodate the age-related effects on outcomes, we used 10-year rolling hazard ratios ( Figure 2 ; and eFigure 3 in Supplement 1 ). The risk for all outcomes generally increased between middle to late life. Statistically significant increased 10-year risk was first detected at age 63 years for HF, 65 for HF or death, and 72 for death. The increased HF risk was driven predominantly by an increased risk of HFrEF, with an elevated 10-year risk detected at age 65 years that strongly increased over time, in contrast to a later modest signal for HFpEF hospitalization emerging at age 76 years. Risk for HF hospitalization or death was similar between men and women (eFigure 4 in Supplement 1 ), in keeping with the lack of interaction reported by sex (eTable 3 in Supplement 1 ). Sensitivity analyses using 99% CIs were largely similar, noting modestly longer time to statistical significance (eFigures 5-6 in Supplement 1 ). Within analyses using 10-year intervals, there were still some indications of proportional hazards violations with respect to age.

To describe the effect of the variant on years of life lost without relying on modeling assumptions, we provided several model-free estimates. Figure 3 A shows expected overall survival at each age between 50 and 95 years by carrier status (additional details in eTable 4 in Supplement 1 ). Carriers lived 2 to 2.5 fewer years compared with noncarriers until approximately age 85 years, when differences in longevity began to attenuate ( Figure 3 B). Because the survival loss difference between carriers and noncarriers remained relatively constant across ages 50 to 85 years, while expected survival decreased, the relative (percentage) loss in expected remaining carrier longevity generally increased over time (eFigure 7 in Supplement 1 ). Specifically, carriers at age 50 years subsequently lived 1.9 fewer years (95% CI, 0.6-3.1) than noncarriers, representing a 6% reduction (95% CI, 2%-10%) in expected longevity. This longevity disparity increased to a maximum of 2.8 years (95% CI, 2.0-3.6) at age 81 years. The maximum relative reduction in longevity was 34% (95% CI, 11%-56%), achieved at age 90 years. Parallel findings were demonstrated using event-free survival (eTable 5 and eFigures 8-9 in Supplement 1 ).

We applied carrier rates derived from this analysis to US population data to estimate the burden of disease in the US Black population. Among the 13 284 819 estimated Black adults aged 50 to 95 years, there are an estimated 435 851 carriers (eTable 4 in Supplement 1 ). Based on the expected loss of longevity at each age among carriers compared with noncarriers, US Black individuals at least 50 years old are projected to cumulatively lose 957 505 years of life (95% CI, 534 475-1 380 535) compared with noncarriers.

Leveraging individual-level participant data from 4 large observational cohort studies facilitated several analyses highlighting risk encountered by carriers of the amyloidogenic V142I variant of the TTR gene. First, this study provided more precise estimates of cardiovascular risk across mid to late life (>90 years old) than were previously available. These risks strongly related to age, but were not modified by sex, suggesting underdiagnosis of ATTRv-CA in women, as some clinical studies have reported male predominance of phenotypic penetration. Second, the earliest statistically significant increase in 10-year risk was identified at earlier ages than previously shown (age 63 years for HF hospitalization and age 72 years for mortality), likely due to the inclusion of a larger sample size. 9 Third, the risk for HF hospitalization was driven by HFrEF, in contrast with its typical HFpEF association, a more modest signal that emerged in later life. Fourth, at each age from mid to late life, carriers died 2 to 2.5 years earlier than noncarriers until age 85 years (when differences began to attenuate), leading to an overall significant decrease in percentage expected longevity with increasing age. Fifth, accounting for the age-dependent frequency of the variant, Black carriers at least 50 years old are projected to live nearly 1 million fewer years than noncarriers. Given established and emerging treatment strategies, which may be more effective earlier in disease course, 11 , 12 early identification and treatment of V142I carriers with ATTRv-CA may have significant public health impact.

Population studies, including several included here, individually have shown significantly higher risk among V142I carriers for HF hospitalization and death, though the risk of homozygotes in these studies has remained unclear. 1 , 7 - 10 , 20 The small group of homozygotes (n = 4) in this study was at substantially elevated risk even in comparison with heterozygotes (demonstrating allele dose dependence), albeit with wide confidence intervals. These findings were overall consistent with data from clinical populations. 21 Pooling data importantly allowed for greater power to evaluate for interactions between clinical characteristics and variant status that might account for incomplete phenotypic penetrance. Only age was consistently identified as a strong modifier of risk. Clinical studies have demonstrated a greater risk for ATTRv-CA among male carriers, 2 , 6 which has been postulated to relate to less-aggressive disease trajectory in women. 22 However, sex did not significantly modify risk in this study with very similar estimates of HF hospitalization or death in men and women, suggesting that previous reports may be explained by underdiagnosis of ATTRv-CA in women. 2 , 6 , 8 , 23 , 24 Women with ATTRv-CA present with thinner left ventricular walls compared with men, and not accounting for differences in body size may engender underdiagnosis. 23 Without clear alternative modifiers of risk, age may currently be the most reliable clinical marker to identify risk for progressive disease.

Additionally, this larger study enabled more precise risk estimation and earlier detection of phenotypic penetrance. Previous research in the Atherosclerosis Risk in Communities Study alone identified inflection points in 10-year risk around age 70 years for HF hospitalization and 75 years for mortality. 9 The greater sample size in the current study showed that risk increased at even earlier ages (63 and 72 years, respectively). Defining these ages is clinically impactful and relevant when considering initiation of treatments such as stabilizers, silencers, or even in vivo gene editing, where treatment prior to the onset of symptoms might be most effective, though further data are needed to clarify the impact of early treatment. 11 , 25 , 26

Notably, the risk for HF hospitalization in this study was driven by incident HFrEF hospitalization. While ATTR-CA has traditionally been associated with HFpEF, V142I carriers are more likely to experience HFrEF events. Indeed, V142I-associated ATTRv-CA presents with greater disease severity (including lower left ventricular EF) and faster disease progression compared with both ATTRwt-CA and non-V142I ATTRv-CA. 27 , 28 Recent data from a clinical trial in ATTR-CA supported the presence of reduced EF in a significant proportion of patients with a tendency to progress in ATTR-CA. 29 Therefore, among Black hospitalized patients with HFrEF, suspicion for ATTR-CA should be heightened and not restricted to patients with preserved EF. 30 - 33 It is important to note that not all carriers with HFrEF have ATTRv-CA because carriers are at risk for other causes of cardiomyopathy as well (such as coronary artery disease), emphasizing the importance of further cardiovascular evaluation for etiology. Identification of ATTR-CA in the HFrEF population is also important because implementation of some guideline-directed medical therapies may not be well tolerated in ATTR-CA. 34 The more modest association with increased HFpEF hospitalization in late life may represent a survivor bias, whereby those carriers who survive to late life may have an inherently more benign form of the disease.

Our actuarial analyses demonstrated that carriers die approximately 2 to 2.5 years earlier than noncarriers. Because these findings were consistent until approximately 85 years of age, the relative reduction in longevity of carriers compared with noncarriers significantly increased with aging, further reflecting the steep age-dependent penetrance of the variant. Because the variant is relatively common (3%-4% among US Black individuals), these years of life lost at the individual level translate to a substantial burden at the population level. The approximately 435 000 living carriers between ages 50 and 95 years will collectively lose nearly 1 million years of life. Because targeted therapies are either available, emerging, or promising in ATTR-CA, 11 , 25 , 26 , 35 these results suggest that identification of disease and implementation of efficacious therapies might extend longevity in this large population. 11 These results may be increasingly relevant with greater access to genetic testing in the population, whether accomplished through biobanks, direct-to-consumer testing, or broad population assessments (including the All of Us Research Program 36 ). Additionally, these results support the inclusion of the variant as a clinically actionable secondary finding. 5

There are several limitations of this study. First, specific phenotypic markers or diagnoses of cardiac amyloidosis were not broadly available in these studies, and therefore understanding which individual carriers have ATTR-CA (as opposed to other causes of HF) is limited. However, at a population level, the absolute difference estimates of HF events provide understanding of the burden of ATTRv-CA. Second, despite pooling studies, interaction analyses may still be underpowered to detect modifiers of variant risk. Third, extrapolation of the current estimates to the US population assumes that the cohorts studied here are broadly representative, and these data may not accurately inform estimates in other parts of the world where variant prevalence and event rates may vary. 2 Fourth, participants who self-reported as Black were included, although race does not capture the significant genetic diversity within Black individuals in the US and worldwide. Delineating the individual contributions of, and complex interplay between, the V142I variant, ancestry, race as a social construct, and biological or social determinants of health to cardiovascular disease merits further investigation. Fifth, adjudication of HFrEF and HFpEF events varied by study and were obtained through available medical record review.

Among self-reported Black individuals, male and female V142I carriers faced similar and substantial risk for HF hospitalization, predominantly with reduced ejection fraction, and all-cause death later in life, with steep age-dependent penetrance. Delineating the individual contributions of, and complex interplay among, the V142I variant, ancestry, the social construct of race, and biological or social determinants of health to cardiovascular disease merits further investigation.

Accepted for Publication: February 20, 2024.

Published Online: May 12, 2024. doi:10.1001/jama.2024.4467

Corresponding Author: Scott D. Solomon, MD, Brigham and Women’s Hospital, 75 Francis St, Boston, MA 02115 ( [email protected] ).

Author Contributions: Drs Selvaraj and Claggett had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Selvaraj, Haring, Solomon.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Selvaraj, Manichaikul, Haring, Cheng.

Critical review of the manuscript for important intellectual content: Claggett, Shah, Mentz, Khouri, Manichaikul, Khan, Rich, Mosley, Levitan, Arora, Goyal, Haring, Eaton, Cheng, Wells, Manson, Fontana, Solomon.

Statistical analysis: Selvaraj, Claggett, Manichaikul, Haring.

Obtained funding: Mosley, Levitan, Eaton, Manson, Solomon.

Administrative, technical, or material support: Manichaikul, Rich, Levitan, Arora, Goyal, Eaton, Manson, Fontana.

Supervision: Claggett, Shah, Mentz, Haring, Manson, Solomon.

Conflict of Interest Disclosures: Dr Selvaraj reported receiving grants from the National Heart, Lung, and Blood Institute (NHLBI), American Heart Association, Doris Duke Foundation, Institute for Translational Medicine and Therapeutics, American Society of Nuclear Cardiology, Mandel Foundation, Duke Heart Center Leadership Council, and Foundation for Sarcoidosis Research and personal fees from AstraZeneca outside the submitted work. Dr Claggett reported receiving personal fees from Alnylam Pharmaceuticals, Cardurion, Corvia, Cytokinetics, Intellia, Rocket, and CVRx outside the submitted work. Dr Mentz reported receiving personal fees from Novartis and AstraZeneca during the conduct of the study; personal fees from Merck, Boehringer Ingelheim/Lilly, Bayer, Medtronic, Novo Nordisk, Pharmacosmos, and Rocket and grants from American Regent outside the submitted work. Dr Khouri reported receiving personal fees from Alnylam Pharmaceuticals, BridgeBio Pharma, and PRIME Education and grants from Alnylam Pharmaceuticals, BridgeBio Pharma, Ionis Pharmaceuticals, and Pfizer outside the submitted work. Dr Khan reported receiving grants from the NHLBI (U01HL160279 and R01HL159250) during the conduct of the study and grants from NHLBI (HL161514) outside the submitted work. Dr Levitan reported receiving grants from the NHLBI during the conduct of the study and grants from Amgen Inc and personal fees from the University of Pittsburgh outside the submitted work. Dr Arora reported receiving grants from Bristol Myers Squibb, Merck Sharp & Dohme LLC, and National Institutes of Health (NIH) and personal fees from Bristol Myers Squibb outside the submitted work. Dr Eaton reported receiving grants from the NIH during the conduct of the study. Dr Manson reported receiving grants from the NIH during the conduct of the study. Dr Fontana reported receiving grants from the British Heart Foundation, Pfizer, AstraZeneca, and BridgeBio and personal fees from Alnylam, AstraZeneca, Attralus, BridgeBio, Ionis, Intellia, Pfizer, Lexeo, Prothena, Janssen, and Akcea outside the submitted work. Dr Solomon reported receiving grants from Alexion, Actelion, Alnylam, Amgen, AstraZeneca, Bellerophon, Bayer, Bristol Myers Squibb, Boston Scientific, Celladon, Cytokinetics, Eidos, Gilead, GlaxoSmithKline, Ionis, Lilly, Mesoblast, MyoKardia, NIH/NHLBI, Neurotronik, Novartis, Novo Nordisk, Respicardia, Sanofi Pasteur, Theracos, Us2.AI, and Edgewise and personal fees from Abbott, Action, Akros, Alexion, Alnylam, Amgen, Arena, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi Sankyo, GlaxoSmithKline, Lilly, Merck, Myokardia, Novartis, Roche, Theracos, Quantum Genomics, Janssen, Cardiac Dimensions, Tenaya, Sanofi Pasteur, Dinaqor, Tremeau, CellProthera, Moderna, American Regent, Sarepta, Lexicon, Anacardio, Akros, and Valo outside the submitted work. No other disclosures were reported.

Funding/Support: The Atherosclerosis Risk in Communities (ARIC) study was funded in whole or in part with federal funds from the NHLBI, NIH, and US Department of Health and Human Services (contract No. HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I). The Reasons for Geographic and Racial Differences in Stroke Study (REGARDS) is supported by cooperative agreement U01 NS041588 co-funded by the National Institute of Neurological Disorders and Stroke (NINDS) and the National Institute on Aging (NIA), NIH, and Department of Health and Human Services. The Multi-Ethnic Study of Atherosclerosis (MESA) and the MESA SHARe Project were supported by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, and N01-HC-95169 from the NHLBI and by grants UL1-TR-000040, UL1-TR-001079, and UL1-TR-001420 from the National Center for Advancing Translational Sciences. Funding for SHARe genotyping was provided by NHLBI contract N02-HL-64278. Genotyping was performed at Affymetrix and the Broad Institute of Harvard and MIT using the Affymetrix Genome-Wide Human SNP Array 6.0. Provision of exome chip genotyping was provided in part by support of NHLBI contract N02-HL-64278 and University of California, Los Angeles Clinical and Translational Science Institute (UL1-TR001881), and the Diabetes Research Center (DK063491). The Women’s Health Initiative (WHI) program is funded by the NHLBI, NIH, and Department of Health and Human Services through 75N92021D00001, 75N92021D00002, 75N92021D00003, 75N92021D00004, and 75N92021D00005. The WHI study was also supported by grant U01HG007376 from the NIH.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Representatives from each study cohort were involved in the review and approval of the manuscript.

Disclaimer: The opinions expressed in this article are those of the authors and do not necessarily reflect the views of the Department of Health and Human Services or NIH, NINDS, or NIA.

Meeting Presentation: This paper was presented at the Heart Failure 2024 Meeting of the European Society of Cardiology; May 12, 2024; Lisbon, Portugal.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: We thank the staff and participants of each study for their important contributions. A list of ARIC investigators is available at https://aric.cscc.unc.edu/aric9/about/aric_structure . A list of participating MESA investigators and institutions can be found at https://www.mesa-nhlbi.org/ . A list of participating REGARDS investigators and institutions can be found at https://www.uab.edu/soph/regardsstudy/ . A list of WHI investigators is available at https://www.whi.org/doc/WHI-Investigator-Short-List.pdf .

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