The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Unraveling the link between heavy metals, perfluoroalkyl substances and depression: Insights from epidemiological and bioinformatics strategies
Open accessAbstract
Heavy metals and per- and polyfluoroalkyl substances (PFASs) have become particularly important when studying the development of depression, a common illness that severely restricts psychosocial functioning and diminishes quality of life. Therefore, the potential joint effects of heavy metal and PFAS exposure on depression, as well as the underlying mechanisms involved, were investigated by using integrated epidemiological and bioinformatic approaches in the present study. A thorough analysis of 7301 samples from the National Health and Nutrition Examination Survey (NHANES) cycles that occurred between 2005 and 2018 was performed. Single-exposure studies have shown that cadmium exposure is positively associated with depression, whereas perfluorooctanesulfonic acid (PFOS) exposure and perfluorodecanoic acid (PFDE) exposure are negatively associated with depression. Furthermore, the Bayesian kernel machine regression (BKMR) and quantile g-computation (QGcomp) models were employed to investigate the collective impact of exposure to mixed metals on depression. Cadmium emerged as the principal contributor to depression. Moreover, the addition of PFAS to the metal mixture had an antagonistic effect on depression, with PFOS having the most prominent influence. Analysis of the effects of co-exposure to cadmium and PFOS confirmed the presence of an antagonistic effect. The inflection points of cadmium and PFOS were determined to be -1.11 and 2.27, respectively. Additionally, exposure to cadmium and PFOS had the opposite effects on two crucial pathways, namely, the rap1 and calcium signaling pathways, which involve core genes related to depression such as ADORA2A, FGF2, and FGFR1. These findings have significant implications for future studies and provide new strategies for exploring the mechanisms underlying co-exposure effects.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“These early-life exposures raise concern given established links between prenatal and postnatal PFASs exposure and adverse health outcomes, including low birth weight, fetal growth restriction, thyroid and kidney dysfunction, and neurodevelopmental issues such as ADHD and reduced cognitive performance [66].”
From Exposure to Per- and Polyfluoroalkyl Substances (PFASs) in Healthcare: Environmental and Clinical Insights (2025) · cites this paper as [66]
Citations
Cites
1 retracted
Yi, W., Xuan, L., Zakaly, H. M. H., Marković, V., Miszczyk, J. U., Guan, H., Zhou, P., & Huang, R. (2023) · Environmental Research · doi:10.1016/j.envres.2023.117188 · Cited by 55
RetractedWhelton, P. K., Carey, R. M., Aronow, W. S., Casey, D. E., Collins, K. J., Dennison Himmelfarb, C., DePalma, S. M., Gidding, S., Jamerson, K. A., Jones, D. W., et al. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2017.11.006 · Cited by 6,616
Grundy, S. M., Stone, N. J., Bailey, A. L., Beam, C., Birtcher, K. K., Blumenthal, R. S., Braun, L. T., de Ferranti, S., Faiella-Tommasino, J., Forman, D. E., et al. (2019) · Circulation · doi:10.1161/cir.0000000000000625 · Cited by 6,185
Diagnosis and classification of diabetes mellitus
American Diabetes Association (2010) · Diabetes Care · doi:10.2337/dc10-s062 · Cited by 5,491
Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic
Ettman, C. K., Abdalla, S. M., Cohen, G. H., Sampson, L., Vivier, P. M., & Galea, S. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.19686 · Cited by 2,138
Depression and cardiovascular disease: a clinical review
Hare, D. L., Toukhsati, S. R., Johansson, P., & Jaarsma, T. (2014) · European Heart Journal · doi:10.1093/eurheartj/eht462 · Cited by 1,362
The association between Diabetes mellitus and Depression.
Bădescu, S., Tataru, C. I., Kobylinska, L., Margarint, E. L. G., Zahiu, D., Am, Z., & Zăgrean, A. (2016) · PubMed Central · Cited by 514
Dysregulation of the fibroblast growth factor system in major depression
Evans, S. J., Choudary, P. V., Neal, C. R., Li, J. Z., Vawter, M. P., Tomita, H., Lopez, J. F., Thompson, R. C., Meng, F., Stead, J. D., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0406788101 · Cited by 424
Consumption of added sugars is decreasing in the United States
Welsh, J. A., Sharma, A. J., Grellinger, L., & Vos, M. B. (2011) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.111.018366 · Cited by 420
Hahad, O., Prochaska, J. H., Daiber, A., & Münzel, T. F. (2019) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2019/4623109 · Cited by 300
Orgeta, V., Tabet, N., Nilforooshan, R., & Howard, R. (2017) · Journal of Alzheimer's Disease · doi:10.3233/jad-161247 · Cited by 203
Hippocampal FGF-2 and FGFR1 mRNA expression in major depression, schizophrenia and bipolar disorder
Gaughran, F., Payne, J., Sedgwick, P. M., Cotter, D., & Berry, M. (2006) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2006.04.008 · Cited by 178
Dassuncao, C., Pickard, H. M., Pfohl, M., Tokranov, A. K., Li, M., Mikkelsen, B., Slitt, A. L., & Sunderland, E. M. (2019) · Environmental Science & Technology Letters · doi:10.1021/acs.estlett.9b00031 · Cited by 164
The receptor hypothesis and the pathogenesis of depression: Genetic bases and biological correlates
Wang, H., Wang, Z., & Chen, N. (2021) · Pharmacological Research · doi:10.1016/j.phrs.2021.105542 · Cited by 122
Copper, Iron, and Manganese Toxicity in Neuropsychiatric Conditions
Tarnacka, B., Jopowicz, A., & Maślińska, M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22157820 · Cited by 119
Zhang, Y., Mustieles, V., Wang, Y., Sun, Y., Agudelo, J., Bibi, Z., Torres, N., Oulhote, Y., Slitt, A. L., & Messerlian, C. (2023) · The Lancet Planetary Health · doi:10.1016/s2542-5196(23)00088-8 · Cited by 102
Self-citationPennings, J. L. A., Jennen, D. G. J., Nygaard, U. C., Namork, E., Haug, L. S., Loveren, H. V., & Granum, B. B. (2015) · Journal of Immunotoxicology · doi:10.3109/1547691x.2015.1029147 · Cited by 100
Quantum dots trigger immunomodulation of the NFκB pathway in human skin cells
Romoser, A., Chen, P. L., Berg, J., Seabury, C., Ivanov, I., Criscitiello, M., & Sayes, C. (2011) · Molecular Immunology · doi:10.1016/j.molimm.2011.02.009 · Cited by 65
Bodo, M., Balloni, S., Lumare, E., Bacci, M., Calvitti, M., Dell’Omo, M., Murgia, N., & Marinucci, L. (2010) · Toxicology in Vitro · doi:10.1016/j.tiv.2010.05.020 · Cited by 64
Machado, N. J., Simões, A. P., Silva, H. B. L., Ardais, A. P., Kaster, M. P., Garção, P., Rodrigues, D. I., Pochmann, D., Santos, A. I., Araújo, I. M., et al. (2016) · Molecular Neurobiology · doi:10.1007/s12035-016-9774-9 · Cited by 60
Blood cadmium and depressive symptoms in young adults (aged 20–39 years)
Scinicariello, F., & Buser, M. C. (2014) · Psychological Medicine · doi:10.1017/s0033291714001883 · Cited by 52
Vuong, A. M., Yolton, K. A., Braun, J. M., Sjödin, A., Calafat, A. M., Xu, Y. Y., Dietrich, K. N., Lanphear, B. P., & Chen, A. (2020) · Environment International · doi:10.1016/j.envint.2020.105694 · Cited by 50
Cadmium, Lead, and Depressive Symptoms
Buser, M. C., & Scinicariello, F. (2016) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.15m10383 · Cited by 49
Deng, P., Durham, J., Liu, J., Zhang, X., Wang, C., Li, D., Gwag, T., Ma, M., & Hennig, B. (2022) · Environmental Health Perspectives · doi:10.1289/ehp11360 · Cited by 49
Baj, J., Bargieł, J., Cabaj, J., Skierkowski, B., Hunek, G., Portincasa, P., Flieger, J., & Smoleń, A. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms242015071 · Cited by 49
Eick, S. M., Goin, D. E., Cushing, L. J., DeMicco, E., Smith, S. C., Park, J.-S., Padula, A. M., Woodruff, T. J., & Morello-Frosch, R. A. (2021) · Journal of Exposure Science & Environmental Epidemiology · doi:10.1038/s41370-021-00322-8 · Cited by 45
Jain, R. B. (2018) · Environmental Research · doi:10.1016/j.envres.2018.11.037 · Cited by 38
Kim, K., Lee, M.-R., Choi, Y., Lee, B.-E., & Hong, Y. (2016) · The Journals of Gerontology Series A · doi:10.1093/gerona/glw119 · Cited by 36
Cybulska, A. M., Grochans, S., Kamińska, M. S., Bosiacki, M., Skonieczna‐Żydecka, K., & Grochans, E. (2021) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2021.112211 · Cited by 31
Sun, X., Yang, X., Zhang, Y., Liu, Y., Xiao, F., Guo, H., & Liu, X. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.167639 · Cited by 30
Khan, E. A., Zhang, X., Hanna, E. M., Yadetie, F., Jonassen, I., Goksøyr, A., & Arukwe, A. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.142904 · Cited by 28
Guo, J., Huang, S., Yang, L., Zhou, J., Xu, X., Lin, S., Li, H., Xie, X., & Wu, S. (2023) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2023.114687 · Cited by 21
Garrett, S. H., Clarke, K., Sens, D. A., et al. (2013) · BMC Medical Genomics · doi:10.1186/1755-8794-6-s1-s2 · Cited by 18
Owsianowska, J., Kamińska, M. S., Bosiacki, M., Chlubek, D., Karakiewicz, B., Jurczak, A., Stanisławska, M., Barczak, K., & Grochans, E. (2020) · Journal of Trace Elements in Medicine and Biology · doi:10.1016/j.jtemb.2020.126501 · Cited by 15
Air Pollution and Perinatal Mental Health: A Comprehensive Overview
Surace, T., Quitadamo, C., Caldiroli, A., Capuzzi, E., Colmegna, F., Nosari, G., Borroni, E., Fedrizzi, L., Bollati, V., Pesatori, A. C., et al. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12093146 · Cited by 13
Dietary Selenium Intake and Kidney Stones in Old Adults: an Analysis from NHANES 2011 to 2018
Qi, Q., Hu, Y., Chen, Y., Xu, Y., & Hao, Z. (2022) · Biological Trace Element Research · doi:10.1007/s12011-022-03282-8 · Cited by 12
Prenatal Lead and Depression Exposures Jointly Influence Birth Outcomes and NR3C1 DNA Methylation
Appleton, A. A., Kiley, K., Schell, L. M., Holdsworth, E. A., Akinsanya, A., & Beecher, C. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182212169 · Cited by 8
Cited by
Sorted by citations
Briassoulis, G., Ilia, S., & Briassouli, E. (2025) · Life · doi:10.3390/life15071057 · Cited by 15
Metadata
- Authors
- Tang, C., Wang, Y., & Hong, H.
- Affiliations
- Ningbo University (CN)
- Corresponding author
- Hong, Hang
- Venue
- Ecotoxicology and Environmental Safety
- Publisher
- Elsevier BV
- Published
- 2024-07
- Volume
- 279
- Pages
- 116482
- ISSN
- 0147-6513 (ISSN-L)
- OpenAlex
- W4398155464
- Cited by
- 22
- References
- 37
- Citations by year
- 2026: 5 · 2025: 17
- FWCI
- 3.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Ecotoxicology and Environmental Safety (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Higher Education Discipline Innovation Project (D16013)
- Zhejiang Provincial Health Commission
- Ningbo University (HY202411)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Heavy Metal Exposure and Toxicity
- Physical Sciences › Environmental Science › Environmental Chemistry › Per- and polyfluoroalkyl substances research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Maternal Mental Health During Pregnancy and Postpartum
- Keywords
- depression, heavy metals, per- and polyfluoroalkyl substances, cadmium, PFOS, perfluorodecanoic acid, antagonistic effect, Bayesian kernel machine regression, quantile g-computation, inflection point, Rap1 signaling, calcium signaling, adenosine A2A receptor, FGF2, FGFR1, NHANES
- MeSH terms
- Bayes Theorem, Cadmium, Decanoic Acids, Depression, Environmental Exposure, Environmental Pollutants, Fluorocarbons, Humans, Nutrition Surveys, Alkanesulfonic Acids, Metals, Heavy, Computational Biology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
