INTRODUCTION: Studies have correlated living close to major roads with Alzheimer's disease (AD) risk. However, the mechanisms responsible for this link remain unclear. METHODS: We exposed olfactory mucosa (OM) cells of healthy individuals and AD patients to diesel emissions (DE). Cytotoxicity of exposure was assessed, mRNA, miRNA expression, and DNA methylation analyses were performed. The discovered altered pathways were validated using data from the human population-based Rotterdam Study. RESULTS: DE exposure resulted in an almost four-fold higher response in AD OM cells, indicating increased susceptibility to DE effects. Methylation analysis detected different DNA methylation patterns, revealing new exposure targets. Findings were validated by analyzing data from the Rotterdam Study cohort and demonstrated a key role of nuclear factor erythroid 2-related factor 2 signaling in responses to air pollutants. DISCUSSION: This study identifies air pollution exposure biomarkers and pinpoints key pathways activated by exposure. The data suggest that AD individuals may face heightened risks due to impaired cellular defenses. HIGHLIGHTS: Healthy and AD olfactory cells respond differently to DE exposure. AD cells are highly susceptible to DE exposure. The NRF2 oxidative stress response is highly activated upon air pollution exposure. DE-exposed AD cells activate the unfolded protein response pathway. Key findings are also confirmed in a population-based study.

A 1 Virtanen Institute for Molecular Sciences University of Eastern Finland Kuopio Finland

Department Driving Assessment Neuro Centre Kuopio University Hospital Kuopio Finland

Department of Computer Science University of Verona Verona Italy

Department of Environmental and Biological Sciences University of Eastern Finland Kuopio Finland

Department of Epidemiology Erasmus MC University Medical Center Rotterdam The Netherlands

Department of Genetic Toxicology and Epigenetics Institute of Experimental Medicine of the Czech Academy of Sciences Prague Czech Republic

Department of Geriatrics Helsinki University Hospital Helsinki Finland

Department of Mechatronics and Computer Engineering the Technical University of Liberec Liberec Czech Republic

Department of Nanotoxicology and Molecular Epidemiology Institute of Experimental Medicine of the Czech Academy of Sciences Prague Czech Republic

Department of Neurosciences Faculty of Medicine University of Helsinki Helsinki Finland

Department of Otorhinolaryngology University of Eastern Finland and Kuopio University Hospital Kuopio Finland

Faculty of Mechanical Engineering Czech Technical University Prague Prague Czech Republic

Zobrazit více v PubMed

Yu W, Ye T, Zhang Y, et al. Global estimates of daily ambient fine particulate matter concentrations and unequal spatiotemporal distribution of population exposure: a machine learning modelling study. Lancet Planet Health. 2023;7(3):e209‐e218. doi:10.1016/S2542-5196(23)00008-6 PubMed DOI

Cory‐Slechta DA, Sobolewski M. Neurotoxic effects of air pollution: an urgent public health concern. Nat Rev Neurosci. 2023;24:129‐130. doi:10.1038/s41583-022-00672-8 PubMed DOI PMC

Ferreira APS, Ramos JMO, Gamaro GD, Gioda A, Gioda CR, Souza ICC. Experimental rodent models exposed to fine particulate matter (PM2.5) highlighting the injuries in the central nervous system: a systematic review. Atmos Pollut Res. 2022;13(5):101407. doi:10.1016/J.APR.2022.101407 DOI

Kilian J, Kitazawa M. The emerging risk of exposure to air pollution on cognitive decline and Alzheimer's disease—evidence from epidemiological and animal studies. Biomed J. 2018;41(3):141‐162. doi:10.1016/j.bj.2018.06.001 PubMed DOI PMC

Duchesne J, Gutierrez LA, Carrière I, et al. Exposure to ambient air pollution and cognitive decline: results of the prospective three‐city cohort study. Environ Int. 2022;161:107118. doi:10.1016/J.ENVINT.2022.107118 PubMed DOI

O'Piela DR, Durisek GR, Escobar YNH, Mackos AR, Wold LE. Particulate matter and Alzheimer's disease: an intimate connection. Trends Mol Med. 2022;28:770‐780. doi:10.1016/J.MOLMED.2022.06.004 PubMed DOI PMC

Livingston G, Huntley J, Sommerlad A, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396(10248):413‐446. doi:10.1016/S0140-6736(20)30367-6 PubMed DOI PMC

Ajmani GS, Suh HH, Pinto JM. Effects of ambient air pollution exposure on olfaction: a review. Environ Health Perspect. 2016;124(11):1683‐1693. doi:10.1289/EHP136 PubMed DOI PMC

Liang C, Jiang Y, Zhang T, et al. Atmospheric particulate matter impairs cognition by modulating synaptic function via the nose‐to‐brain route. Sci Total Environ. 2022;857:159600. doi:10.1016/J.SCITOTENV.2022.159600 PubMed DOI

Kim SJ, Kim N, Park SH, et al. Genomic approach to explore altered signaling networks of olfaction in response to diesel exhaust particles in mice. Sci Rep. 2020;10(1):16972. doi:10.1038/S41598-020-74109-6 PubMed DOI PMC

Vondráček J, Pěnčíková K, Neča J, et al. Assessment of the aryl hydrocarbon receptor‐mediated activities of polycyclic aromatic hydrocarbons in a human cell‐based reporter gene assay. Environ Pollut. 2017;220(Pt A):307‐316. doi:10.1016/J.ENVPOL.2016.09.064 PubMed DOI

Kanninen KM, Lampinen R, Rantanen LM, et al. Olfactory cell cultures to investigate health effects of air pollution exposure: implications for neurodegeneration. Neurochem Int. 2020;136:104729. doi:10.1016/j.neuint.2020.104729 PubMed DOI

Lampinen R, Fazaludeen MF, Avesani S, et al. Single‐Cell RNA‐seq analysis of olfactory mucosal cells of Alzheimer's disease patients. Cells. 2022;11(4):676. doi:10.3390/CELLS11040676 PubMed DOI PMC

Lampinen R, Górová V, Avesani S, et al. Biometal Dyshomeostasis in olfactory mucosa of Alzheimer's disease patients. Int J Mol Sci. 2022;23(8):4123. doi:10.3390/IJMS23084123 PubMed DOI PMC

Mussalo L, Avesani S, Shahbaz MA, et al. Emissions from modern engines induce distinct effects in human olfactory mucosa cells, depending on fuel and aftertreatment. Sci Total Environ. 2023;905:167038. doi:10.1016/j.scitotenv.2023.167038 PubMed DOI

Rossner P, Cervena T, Vojtisek‐Lom M. In vitro exposure to complete engine emissions—a mini‐review. Toxicology. 2021;462:152953. doi:10.1016/J.TOX.2021.152953 PubMed DOI

Rossner P, Cervena T, Vojtisek‐Lom M, et al. The biological effects of complete gasoline engine emissions exposure in a 3d human airway model (MucilAirTM) and in human bronchial epithelial cells (BEAS‐2B). Int J Mol Sci. 2019;20(22):5710. doi:10.3390/IJMS20225710 PubMed DOI PMC

Vojtisek‐Lom M, Pechout M, MacOun D, et al. Assessing exhaust toxicity with biological detector: configuration of portable air‐liquid interface human lung cell model exposure system, sampling train and test conditions. SAE Int J Adv Curr Pract Mobil. 2019;2(2):520‐534. doi:10.4271/2019-24-0050 DOI

Cervena T, Vojtisek‐Lom M, Vrbova K, et al. Ordinary gasoline emissions induce a toxic response in bronchial cells grown at air‐liquid interface. Int J Mol Sci. 2020;22(1):79. doi:10.3390/IJMS22010079 PubMed DOI PMC

Libalova H, Rossner P, Vrbova K, et al. Comparative analysis of toxic responses of organic extracts from diesel and selected alternative fuels engine emissions in human lung BEAS‐2B cells. Int J Mol Sci. 2016;17(11):1833. doi:10.3390/IJMS17111833 PubMed DOI PMC

Dobin A, Davis CA, Schlesinger F, et al. STAR: ultrafast universal RNA‐seq aligner. Bioinformatics. 2013;29(1):15‐21. doi:10.1093/BIOINFORMATICS/BTS635 PubMed DOI PMC

Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26(1):139‐140. doi:10.1093/BIOINFORMATICS/BTP616 PubMed DOI PMC

Ritchie ME, Phipson B, Wu D, et al. limma powers differential expression analyses for RNA‐sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47. doi:10.1093/NAR/GKV007 PubMed DOI PMC

Wu T, Hu E, Xu S, et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation. 2021;2(3):100141. doi:10.1016/J.XINN.2021.100141 PubMed DOI PMC

Krämer A, Green J, Pollard J, Tugendreich S. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics. 2014;30(4):523‐530. doi:10.1093/BIOINFORMATICS/BTT703 PubMed DOI PMC

Bioconductor . miRNAtap. 2024. Accessed September 25, 2023. https://bioconductor.org/packages/release/bioc/html/miRNAtap.html

Wong N, Wang X. miRDB: an online resource for microRNA target prediction and functional annotations. Nucleic Acids Res. 2015;43:D146‐D152. doi:10.1093/NAR/GKU1104 PubMed DOI PMC

Maragkakis M, Vergoulis T, Alexiou P, et al. DIANA‐microT Web server upgrade supports fly and worm miRNA target prediction and bibliographic miRNA to disease association. Nucleic Acids Res. 2011;39:W145‐W148. doi:10.1093/NAR/GKR294 PubMed DOI PMC

Reczko M, Maragkakis M, Alexiou P, Grosse I, Hatzigeorgiou AG. Functional microRNA targets in protein coding sequences. Bioinformatics. 2012;28(6):771‐776. doi:10.1093/BIOINFORMATICS/BTS043 PubMed DOI

Friedman RC, Farh KK, Burge CB, Bartel DP. Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2009;19(1):92‐105. doi:10.1101/GR.082701.108 PubMed DOI PMC

Lall S, Grün D, Krek A, et al. A genome‐wide map of conserved MicroRNA targets in C. elegans. Curr Biol. 2006;16(5):460‐471. doi:10.1016/j.cub.2006.01.050 PubMed DOI

Betel D, Koppal A, Agius P, Sander C, Leslie C. Comprehensive modeling of microRNA targets predicts functional non‐conserved and non‐canonical sites. Genome Biol. 2010;11(8):R90. doi:10.1186/GB-2010-11-8-R90/FIGURES/6 PubMed DOI PMC

John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS. Human MicroRNA targets. PLoS Biol. 2004;2(11):e363. doi:10.1371/JOURNAL.PBIO.0020363 PubMed DOI PMC

Enright AJ, John B, Gaul U, Tuschl T, Sander C, Marks DS. MicroRNA targets in drosophila. Genome Biol. 2003;5(1):R1. doi:10.1186/GB-2003-5-1-R1 PubMed DOI PMC

Ikram MA, Brusselle G, Ghanbari M, et al. Objectives, design and main findings until 2020 from the Rotterdam Study. Eur J Epidemiol. 2020;35(5):483‐517. doi:10.1007/S10654-020-00640-5 PubMed DOI PMC

de Crom TOE, Ginos BNR, Oudin A, Ikram MK, Voortman T, Ikram MA. Air pollution and the risk of dementia: the Rotterdam Study. J Alzheimers Dis. 2023;91(2):603‐613. doi:10.3233/JAD-220804 PubMed DOI PMC

Vojinovic D, van der Lee SJ, van Duijn CM, et al. Metabolic profiling of intra‐ and extracranial carotid artery atherosclerosis. Atherosclerosis. 2018;272:60‐65. doi:10.1016/j.atherosclerosis.2018.03.015 PubMed DOI

Richards J, Rivadeneira F, Inouye M, et al. Bone mineral density, osteoporosis, and osteoporotic fractures: a genome‐wide association study. Lancet. 2008;371(9623):1505‐1512. doi:10.1016/S0140-6736(08)60599-1 PubMed DOI PMC

van den Berg RA, Hoefsloot HCJ, Westerhuis JA, Smilde AK, van der Werf MJ. Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics. 2006;7:142. doi:10.1186/1471-2164-7-142 PubMed DOI PMC

Purcell S, Neale B, Todd‐Brown K, et al. PLINK: a tool set for whole‐genome association and population‐based linkage analyses. Am J Hum Genet. 2007;81(3):559‐579. doi:10.1086/519795 PubMed DOI PMC

Naj AC, Jun G, Beecham GW, et al. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late‐onset Alzheimer's disease. Nat Genet. 2011;43(5):436‐441. doi:10.1038/ng.801 PubMed DOI PMC

Merico D, Isserlin R, Stueker O, Emili A, Bader GD. Enrichment map: a network‐based method for gene‐set enrichment visualization and interpretation. PLoS One. 2010;5(11):e13984. doi:10.1371/JOURNAL.PONE.0013984 PubMed DOI PMC

Kunkle BW, Grenier‐Boley B, Sims R, et al. Genetic meta‐analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat Genet. 2019;51(3):414‐430. doi:10.1038/s41588-019-0358-2 PubMed DOI PMC

Lambert JC, Ibrahim‐Verbaas CA, Harold D, et al. Meta‐analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet. 2013;45(12):1452‐1458. doi:10.1038/ng.2802 PubMed DOI PMC

Hollingworth P, Harold D, Sims R, et al. Common variants in ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease. Nat Genet. 2011;43(5):429‐435. doi:10.1038/NG.803 PubMed DOI PMC

Pai S, Weber P, Isserlin R, et al. netDx: software for building interpretable patient classifiers by multi‐’omic data integration using patient similarity networks. F1000Research. 2020;9:1239. doi:10.12688/f1000research.26429.2 PubMed DOI PMC

Pai S, Hui S, Isserlin R, et al. netDx: interpretable patient classification using integrated patient similarity networks. Mol Syst Biol. 2019;15(3):e8497. doi:10.15252/MSB.20188497 PubMed DOI PMC

Finckh U, van Hadeln K, Müller‐Thomsen T, et al. Association of late‐onset Alzheimer disease with a genotype of PLAU, the gene encoding urokinase‐type plasminogen activator on chromosome 10q22.2. Neurogenetics. 2003;4(4):213‐217. doi:10.1007/S10048-003-0157-9/FIGURES/1 PubMed DOI

Cuyvers E, van der Zee J, Bettens K, et al. Genetic variability in SQSTM1 and risk of early‐onset Alzheimer dementia: a European early‐onset dementia consortium study. Neurobiol Aging. 2015;36(5):2005.e15‐2005.e22. doi:10.1016/J.NEUROBIOLAGING.2015.02.014 PubMed DOI

Tramutola A, Di Domenico F, Barone E, Perluigi M, Butterfield DA. It is all about (U)biquitin: role of altered ubiquitin‐proteasome system and UCHL1 in alzheimer disease. Oxid Med Cell Longev. 2016;2016:2756068. doi:10.1155/2016/2756068 PubMed DOI PMC

Liu D, Wang Y, Jing H, Meng Q, Yang J. Mendelian randomization integrating GWAS and DNA methylation quantitative trait loci data identified novel pleiotropic DNA methylation loci for neuropathology of Alzheimer's disease. Neurobiol Aging. 2021;97:18‐27. doi:10.1016/J.NEUROBIOLAGING.2020.09.019 PubMed DOI PMC

Chen Y, Zhou H, binYin W, Ren H. Construction of a new protein–protein interaction and molecular biomarkers networks in Alzheimer's disease patients by bioinformatics screening. J Biomed Nanotechnol. 2023;19(1):154‐171. doi:10.1166/JBN.2023.3507 DOI

He F, Ru X, Wen T. NRF2, a transcription factor for stress response and beyond. Int J Mol Sci. 2020;21(13):4777. doi:10.3390/IJMS21134777 PubMed DOI PMC

Buendia I, Michalska P, Navarro E, Gameiro I, Egea J, León R. Nrf2‐ARE pathway: an emerging target against oxidative stress and neuroinflammation in neurodegenerative diseases. Pharmacol Ther. 2016;157:84‐104. doi:10.1016/J.PHARMTHERA.2015.11.003 PubMed DOI

Ngo V, Duennwald ML. Nrf2 and oxidative stress: a general overview of mechanisms and implications in human disease. Antioxidants. 2022;11(12):2345. doi:10.3390/ANTIOX11122345 PubMed DOI PMC

Morales‐Bárcenas R, Sánchez‐Pérez Y, Santibáñez‐Andrade M, Chirino YI, Soto‐Reyes E, García‐Cuellar CM. Airborne particulate matter (PM10) induces cell invasion through aryl hydrocarbon receptor and activator protein 1 (AP‐1) pathway deregulation in A549 lung epithelial cells. Mol Biol Rep. 2023;50(1):107‐119. doi:10.1007/S11033-022-07986-X/FIGURES/5 PubMed DOI

Pichler S, Gu W, Hartl D, et al. The miRNome of Alzheimer's disease: consistent downregulation of the miR‐132/212 cluster. Neurobiol Aging. 2017;50:167.e1‐167.e10. doi:10.1016/J.NEUROBIOLAGING.2016.09.019 PubMed DOI

Lau P, Bossers K, Janky R, et al. Alteration of the microRNA network during the progression of Alzheimer's disease. EMBO Mol Med. 2013;5(10):1613‐1634. doi:10.1002/EMMM.201201974 PubMed DOI PMC

Song Y, He S, Zhuang J, et al. MicroRNA‐601 serves as a potential tumor suppressor in hepatocellular carcinoma by directly targeting PIK3R3. Mol Med Rep. 2023;27:36. doi:10.3892/MMR.2019.9857/HTML PubMed DOI PMC

Sun B, Hua J, Cui H, Liu H, Zhang K, Zhou H. MicroRNA‐1197 downregulation inhibits proliferation and migration in human non‐ small cell lung cancer cells by upregulating HOXC11. Biomed Pharmacother. 2019;117:109041. doi:10.1016/J.BIOPHA.2019.109041 PubMed DOI

Huang X, Tang F, Weng Z, Zhou M, Zhang Q. MiR‐591 functions as tumor suppressor in breast cancer by targeting TCF4 and inhibits Hippo‐YAP/TAZ signaling pathway. Cancer Cell Int. 2019;19(1):108. doi:10.1186/S12935-019-0818-X/FIGURES/6 PubMed DOI PMC

Song MK, Lee HS, Ryu JC. Integrated analysis of microRNA and mRNA expression profiles highlights aldehyde‐induced inflammatory responses in cells relevant for lung toxicity. Toxicology. 2015;334:111‐121. doi:10.1016/J.TOX.2015.06.007 PubMed DOI

Moore LD, Le T, Fan G. DNA methylation and its basic function. Neuropsychopharmacology. 2012;38(1):23‐38. doi:10.1038/npp.2012.112 PubMed DOI PMC

De Prins S, Koppen G, Jacobs G, et al. Influence of ambient air pollution on global DNA methylation in healthy adults: a seasonal follow‐up. Environ Int. 2013;59:418‐424. doi:10.1016/J.ENVINT.2013.07.007 PubMed DOI

Huo X, Sun H, Cao D, et al. Identification of prognosis markers for endometrial cancer by integrated analysis of DNA methylation and RNA‐Seq data. Sci Rep. 2019;9(1):9924. doi:10.1038/s41598-019-46195-8 PubMed DOI PMC

Huang SK, Tripathi P, Koneva LA, et al. Effect of concentration and duration of particulate matter exposure on the transcriptome and DNA methylome of bronchial epithelial cells. Environ Epigenet. 2021;7(1):dvaa022. doi:10.1093/EEP/DVAA022 PubMed DOI PMC

Zhu W, Gu Y, Li M, et al. Integrated single‐cell RNA‐seq and DNA methylation reveal the effects of air pollution in patients with recurrent spontaneous abortion. Clin Epigenetics. 2022;14(1):105. doi:10.1186/S13148-022-01327-2/TABLES/3 PubMed DOI PMC

Safe S, Jin UH, Morpurgo B, Abudayyeh A, Singh M, Tjalkens RB. Nuclear receptor 4A (NR4A) family—orphans no more. J Steroid Biochem Mol Biol. 2016;157:48‐60. doi:10.1016/J.JSBMB.2015.04.016 PubMed DOI PMC

Navarro JF, Croteau DL, Jurek A, et al. Spatial transcriptomics reveals genes associated with dysregulated mitochondrial functions and stress signaling in Alzheimer disease. iScience. 2020;23(10):101556. doi:10.1016/J.ISCI.2020.101556 PubMed DOI PMC

Zhao LG, Tang Y, Tan JZ, Wang JW, Chen GJ, Zhu BL. The effect of NR4A1 on APP metabolism and tau phosphorylation. Genes Dis. 2018;5(4):342‐348. doi:10.1016/J.GENDIS.2018.04.008 PubMed DOI PMC

Parra‐Damas A, Valero J, Chen M, et al. Crtc1 activates a transcriptional program deregulated at early Alzheimer's disease‐related stages. J Neurosci. 2014;34(17):5776‐5787. doi:10.1523/JNEUROSCI.5288-13.2014 PubMed DOI PMC

Montarolo F, Perga S, Martire S, et al. Altered NR4A subfamily gene expression level in peripheral blood of Parkinson's and Alzheimer's disease patients. Neurotox Res. 2016;30(3):338‐344. doi:10.1007/S12640-016-9626-4/TABLES/2 PubMed DOI

Jeon SG, Yoo A, Chun DW, et al. The critical role of nurr1 as a mediator and therapeutic target in Alzheimer's disease‐related pathogenesis. Aging Dis. 2020;11(3):705‐724. doi:10.14336/AD.2019.0718 PubMed DOI PMC

Jardim MJ. microRNAs: implications for air pollution research. Mutat Res. 2011;717(1‐2):38‐45. doi:10.1016/J.MRFMMM.2011.03.014 PubMed DOI

Krauskopf J, van Veldhoven K, Chadeau‐Hyam M, et al. Short‐term exposure to traffic‐related air pollution reveals a compound‐specific circulating miRNA profile indicating multiple disease risks. Environ Int. 2019;128:193‐200. doi:10.1016/J.ENVINT.2019.04.063 PubMed DOI

Haghani A, Cacciottolo M, Doty KR, et al. Mouse brain transcriptome responses to inhaled nanoparticulate matter differed by sex and APOE in Nrf2‐Nfkb interactions. Elife. 2020;9:e54822. doi:10.7554/eLife.54822 PubMed DOI PMC

Kampa M, Castanas E. Human health effects of air pollution. Environ Pollut. 2008;151(2):362‐367. doi:10.1016/J.ENVPOL.2007.06.012 PubMed DOI

Lepers C, André V, Dergham M, et al. Xenobiotic metabolism induction and bulky DNA adducts generated by particulate matter pollution in BEAS‐2B cell line: geographical and seasonal influence. J Appl Toxicol. 2014;34(6):703‐713. doi:10.1002/JAT.2931 PubMed DOI

Líbalová H, Krčková S, Uhlířová K, et al. Analysis of gene expression changes in A549 cells induced by organic compounds from respirable air particles. Mutat Res. 2014;770:94‐105. doi:10.1016/J.MRFMMM.2014.10.002 PubMed DOI

Andersson H, Piras E, Demma J, Hellman B, Brittebo E. Low levels of the air pollutant 1‐nitropyrene induce DNA damage, increased levels of reactive oxygen species and endoplasmic reticulum stress in human endothelial cells. Toxicology. 2009;262(1):57‐64. doi:10.1016/J.TOX.2009.05.008 PubMed DOI

Laing S, Wang G, Briazova T, et al. Airborne particulate matter selectively activates endoplasmic reticulum stress response in the lung and liver tissues. Am J Physiol Cell Physiol. 2010;299(4):C736‐C749. doi:10.1152/AJPCELL.00529.2009 PubMed DOI PMC

Hu C, Yang J, Qi Z, et al. Heat shock proteins: biological functions, pathological roles, and therapeutic opportunities. MedComm. 2022;3(3):e161. doi:10.1002/MCO2.161 PubMed DOI PMC

Moreira‐de‐Sousa C, de Souza RB, Fontanetti CS. HSP70 as a biomarker: an excellent tool in environmental contamination analysis—a review. Water Air Soil Pollut. 2018;229(8):264. doi:10.1007/S11270-018-3920-0/TABLES/1 DOI

Smeester L, Rager JE, Bailey KA, et al. Epigenetic changes in individuals with arsenicosis. Chem Res Toxicol. 2011;24(2):165‐167. doi:10.1021/TX1004419/SUPPL_FILE/TX1004419_SI_001.PDF PubMed DOI PMC

Lee JY, Tokumoto M, Fujiwara Y, et al. Accumulation of p53 via down‐regulation of UBE2D family genes is a critical pathway for cadmium‐induced renal toxicity. Sci Rep. 2016;6(1):21968. doi:10.1038/srep21968 PubMed DOI PMC