Air pollution, comprising a complex mixture of gaseous and particulate pollutants, remains a major global health concern that disproportionately affects vulnerable populations. In this scoping review, we aim to systematically investigate the role of genetic susceptibility in health outcomes associated with exposure to air pollution, with a particular emphasis on fine particulate matter (PM2.5), particulate matter (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx); key pollutants consistently linked to adverse health effects. By exploring the gene-environment interactions underlying air pollution-related conditions, this review offers new insights into how genetic factors may modulate individual responses to air pollutants and their implications for precision health. Analyzing 16 peer-reviewed studies published in the last decade, we highlight genetic markers and pathways involved in regulating oxidative stress, inflammation, and DNA repair, which are thought to influence individual variation in responses to PM2.5, PM10, NO2, and NOx. Although none of the included studies entailed multi-omics or machine learning approaches, we identified these tools as promising directions for future research aimed at elucidating mechanistic pathways and informing personalized strategies. These techniques could significantly improve the understanding of gene-environment interactions, and are suggested as emerging methodologies for future studies. However, the scarcity of longitudinal studies and the underrepresentation of diverse populations limit the generalizability of the current findings. Addressing these gaps will be essential for advancing research, improving environmental health equity, and informing policy in the context of air pollution and genetic susceptibility.
Citation: Hari Krismanuel. Exploring genetic susceptibility to air pollution and its implications for disease risk and precision health: A scoping review[J]. AIMS Public Health, 2025, 12(3): 916-951. doi: 10.3934/publichealth.2025046
Air pollution, comprising a complex mixture of gaseous and particulate pollutants, remains a major global health concern that disproportionately affects vulnerable populations. In this scoping review, we aim to systematically investigate the role of genetic susceptibility in health outcomes associated with exposure to air pollution, with a particular emphasis on fine particulate matter (PM2.5), particulate matter (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx); key pollutants consistently linked to adverse health effects. By exploring the gene-environment interactions underlying air pollution-related conditions, this review offers new insights into how genetic factors may modulate individual responses to air pollutants and their implications for precision health. Analyzing 16 peer-reviewed studies published in the last decade, we highlight genetic markers and pathways involved in regulating oxidative stress, inflammation, and DNA repair, which are thought to influence individual variation in responses to PM2.5, PM10, NO2, and NOx. Although none of the included studies entailed multi-omics or machine learning approaches, we identified these tools as promising directions for future research aimed at elucidating mechanistic pathways and informing personalized strategies. These techniques could significantly improve the understanding of gene-environment interactions, and are suggested as emerging methodologies for future studies. However, the scarcity of longitudinal studies and the underrepresentation of diverse populations limit the generalizability of the current findings. Addressing these gaps will be essential for advancing research, improving environmental health equity, and informing policy in the context of air pollution and genetic susceptibility.
| [1] | (2023) World Health OrganizationAir pollution: The invisible health threat. Geneva: World Health Organization. [cited 2025 May 17]. Available from: https://www.who.int/news-room/feature-stories/detail/air-pollution--the-invisible-health-threat. |
| [2] | (2025) World Bank GroupPollution. Washington, DC: World Bank Group. [cited 2025 May 17]. Available from: https://www.worldbank.org/en/topic/pollution. |
| [3] | Roser M Data review: How many people die from air pollution (2021). [cited 2025 May 17]. Available from: https://ourworldindata.org/data-review-air-pollution-deaths. |
| [4] | Liu SK, Cai S, Chen Y, et al. (2016) The effect of pollutional haze on pulmonary function. J Thorac Dis 8: E41-E56. http://doi.org/10.3978/j.issn.2072-1439.2016.01.18 |
| [5] | (2020) Health Protection Surveillance CentreHealth effects of air pollution. Dublin: Health protection surveillance centre. [cited 2025 May 17]. Available from: https://www.hpsc.ie/a-z/environmentand health/airquality/healtheffectsofairpollution/. |
| [6] | Orellano P, Reynoso J, Quaranta N, et al. (2020) Short-term exposure to particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), and ozone (O3) and all-cause and cause-specific mortality: Systematic review and meta-analysis. Environ Process 142: 105876. https://doi.org/10.1016/j.envint.2020.105876 |
| [7] | Nisticò F, Messina G, Quercioli C, et al. (2025) Can “fine scale” data on air pollution be an evaluation tool for public health professionals?. Atmos Pollut Res 16: 102487. https://doi.org/10.1016/j.apr.2025.102487 |
| [8] | Reif AAM, DM Reif, Akhtari FS, et al. (2024) Gene-environment interactions within a precision environmental health framework. Cell Genom 4: 100591. https://doi.org/10.1016/j.xgen.2024.100591 |
| [9] | Bouma F, Nyberg F, Olin AC, et al. (2023) Genetic susceptibility to airway inflammation and exposure to short-term outdoor air pollution. Environ Health 22: 50. https://doi.org/10.1186/s12940-023-00996-7 |
| [10] | Omolaoye TS, Skosana BT, Ferguson LM, et al. (2024) Implications of exposure to air pollution on male reproduction: The role of oxidative stress. Antioxidants (Basel) 13: 64. https://doi.org/10.3390/antiox13010064 |
| [11] | Manisalidis I, Stavropoulou E, Stavropoulou A, et al. (2020) Environmental and health impacts of air pollution: A review. Front Public Health 8: 14. https://doi.org/10.3389/fpubh.2020.00014 |
| [12] | World Health OrganizationAmbient (outdoor) air pollution (2024). [cited 2025 April 10]. Available from: https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health |
| [13] | Turner MC, Andersen ZJ, Baccarelli A, et al. (2020) Outdoor air pollution and cancer: An overview of the current evidence and public health recommendations. CA Cancer J Clin 25: 10.3322/caac.21632. https://doi.org/10.3322/caac.21632 |
| [14] | Lim EY, Kim GD (2024) Particulate matter-induced emerging health effects associated with oxidative stress and inflammation. Antioxidants 13: 1256. https://doi.org/10.3390/antiox13101256 |
| [15] | Breton CV, Landon R, Kahn LG, et al. (2021) Exploring the evidence for epigenetic regulation of environmental influences on child health across generations. Commun Biol 4: 769. https://doi.org/10.1038/s42003-021-02316-6 |
| [16] | Wu Y, Xie L (2025) AI-driven multi-omics integration for multi-scale predictive modeling of genotype-environment-phenotype relationships. Comput Struct Biotechnol J 27: 265-277. https://doi.org/10.1016/j.csbj.2024.12.030 |
| [17] | Liu X, Shi J, Jiao Y, et al. (2024) Integrated multi-omics with machine learning to uncover the intricacies of kidney disease. Brief Bioinform 25: bbae364. https://doi.org/10.1093/bib/bbae364 |
| [18] | Yetgin A (2025) Revolutionizing multi-omics analysis with artificial intelligence and data processing. Quant Biol 13: 1-16. https://doi.org/10.1002/qub2.70002 |
| [19] | Theodorakis N, Feretzakis G, Tzelves L, et al. (2024) Integrating machine learning with multi-omics technologies in geroscience: Towards personalized medicine. J Pers Med 14: 931. https://doi.org/10.3390/jpm14090931 |
| [20] | Foreman AL, Warth B, Hessel EVS, et al. (2024) Adopting mechanistic molecular biology approaches in exposome research for causal understanding. Environ Sci Technol 58: 7256-7269. https://doi.org/10.1021/acs.est.3c07961 |
| [21] | Alemu R, Sharew NT, Arsano YY, et al. (2025) Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: Techniques, translation, and equity issues. Hum Genomics 19: 1-27. https://doi.org/10.1186/s40246-025-00718-9 |
| [22] | Arksey H, O'Malley L (2005) Scoping studies: Towards a Methodological Framework. Int J Soc Res Methodol 8: 19-32. https://doi.org/10.1080/1364557032000119616 |
| [23] | Levac D, Colquhoun H, O'Brien K (2010) Scoping studies: advancing the methodology. Implement Sci 5: 69. http://www.implementationscience.com/content/5/1/69 |
| [24] | Foster ED, Deardorff A (2017) Open Science Framework (OSF). J Med Libr Assoc 105: 203-206. https://doi.org/10.5195/jmla.2017.88 |
| [25] | Polanin JR, Pigott TD, Espelage DL, et al. (2019) Best practice guidelines for abstract screening large-evidence systematic reviews and meta-analyses. Res Synth Methods 10: 330-342. https://doi.org/10.1002/jrsm.1354 |
| [26] | Natukunda A, Muchene LK (2023) Unsupervised title and abstract screening for systematic review: A retrospective case-study using topic modelling methodology. Syst Rev 12: 1. https://doi.org/10.1186/s13643-022-02163-4 |
| [27] | Mengist W, Soromessa T, Legese G (2020) Method for conducting systematic literature review and meta-analysis for environmental science research. MethodsX 7: 100777. https://doi.org/10.1016/j.mex.2019.100777 |
| [28] | Tricco A, Lilie E, Sarin W, et al. (2018) PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Ann Intern Med 169: 467-473. https://doi.org/10.7326/M18-0850 |
| [29] | Page MJ, McKenzie JE, Bossuyt PM, et al. (2021) The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Syst Rev 10: 89. https://doi.org/10.1186/s13643-021-01626-4 |
| [30] | Page MJ, Moher D (2017) Evaluations of the uptake and impact of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement and extensions: A scoping review. Syst Rev 6: 263. https://doi.org/10.1186/s13643-017-0663-8 |
| [31] | Zhu X, Yang Y, Comi NL, et al. (2024) An approach to identify gene-environment interactions and reveal new biological insight in complex traits. Nat Commun 15: 3385. https://doi.org/10.1038/s41467-024-47806-3 |
| [32] | Melbourne CA, Erzurumluoglu AM, Shrine N, et al. (2022) Genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals. Environ Int 159: 107041. https://doi/org/10.1016/j.envint2021.107041 |
| [33] | Peters MD, Marnie C, Colcuhoun H, et al. (2021) Scoping reviews: reinforcing and advancing the methodology and application. Syst Rev 10: 263. https://doi.org/10.1186/s13643-021-01821-3 |
| [34] | Munn Z, Peters MDJ, Stern C, et al. (2018) Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol 18: 143. https://doi.org/10.1186/s12874-018-0611-x |
| [35] | Luchini C, Stubbs B, Solmi M, et al. (2017) Assessing the quality of studies in meta-analyses: Advantages and limitations of the Newcastle Ottawa Scale. World J Meta-Anal 5: 80-84. https://doi.org/10.13105/wjma.v5.i4.80 |
| [36] | Shea BJ, Reeves BC, Wells G, et al. (2017) AMSTAR 2: A critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ 358: j4008. https://doi.org/10.1136/bmj.j4008 |
| [37] | Joanna Briggs InstituteThe Joanna Briggs Institute Critical Appraisal tools for use in JBI systematic reviews: Checklist for case control studies (2017). [cited 2025 April 10]. Available from: https://jbi.global/sites/default/files/2019-05/JBI_Critical_Appraisal-Checklist_for_Case_Control_Studies2017_0.pdf |
| [38] | Gruzieva O, Xu CJ, Breton CV, et al. (2016) Epigenome-wide meta-analysis of methylation in children related to prenatal NO2 air pollution exposure. Environ Health Perspect 125: 104-110. https://doi.org/10.1289/EHP36 |
| [39] | Huang Y, Zhu M, Ji M, et al. (2021) Air pollution, genetic factors, and the risk of lung cancer: a prospective study in the UK Biobank. Am J Respir Crit Care Med 204: 817-825. https://doi.org/10.1164/rccm.202011-4063OC |
| [40] | Ma Y, Li D, Cui F, et al. (2024) Air pollutants, genetic susceptibility, and abdominal aortic aneurysm risk: A prospective study. Eur Heart J 45: 1030-1039. https://doi.org/10.1093/eurheartj/ehad886 |
| [41] | Li D, Xie J, Wang L, et al. (2023) Genetic susceptibility and lifestyle modify the association of long-term air pollution exposure on major depressive disorder: A prospective study in UK Biobank. BMC Med 21: 67. https://doi.org/10.1186/s12916-023-02783-0 |
| [42] | Fu Z, Ma Y, Yang C, et al. (2023) Association of air pollution exposure and increased coronary artery disease risk: The modifying effect of genetic susceptibility. Environ Health 22: 85. https://doi.org/10.1186/s12940-023-01038-y |
| [43] | Ma Y, Zhang J, Li D, et al. (2024) genetic susceptibility modifies relationships between air pollutants and stroke risk: A large cohort study. Stroke 55: 113-121. https://doi.org/10.1161/strokeaha.123.044284 |
| [44] | Liu R, Li D, Ma Y, et al. (2024) Air pollutants, genetic susceptibility and the risk of schizophrenia: Large prospective study. Br J Psychiatry 225: 427-435. https://doi.org/10.1192/bjp.2024.118 |
| [45] | Huang YM, Ma YH, Gao PY, et al. (2024) Genetic susceptibility modifies the association of long-term air pollution exposure on Parkin-son's disease. NPJ Parkinsons Dis 10: 23. https://doi.org/10.1038/s41531-024-00633-1 |
| [46] | Wang L, Xie J, Hu Y, et al. (2022) Air pollution and risk of chronic obstructed pulmonary disease: The modifying effect of genetic susceptibility and lifestyle. EBioMedicine 79: 103994. https://doi.org/10.1016/j.ebiom.2022.103994 |
| [47] | Rhee TM, Ji Y, Yang S, et al. (2024) Combined effect of air pollution and genetic risk on incident cardiovascular diseases. J Am Heart Assoc 13: e033497. https://doi.org/10.1161/JAHA.123.033497 |
| [48] | Li J, Liang F, Liu F, et al. (2022) Genetic risk modifies the effect of long-term fine particulate matter exposure on coronary artery disease. Environ Int 170: 107624. https://doi.org/10.1016/j.envint.2022.107624 |
| [49] | Chen J, Zhang H, Fu T, et al. (2024) Exposure to air pollution increases susceptibility to ulcerative colitis through epigenetic alterations in CXCR2 and MHC class III region. EBioMedicine 110: 105443. https://doi.org/10.1093/eurjpc/zwad384 |
| [50] | Wu JH, Ma Y, Yang J, et al. (2024) exposure to air pollution, genetic susceptibility, and psoriasis risk in the UK. JAMA Netw Open 7: e2421665. https://doi.org/10.1001/jamanetworkopen.2024.21665 |
| [51] | Zhang YY, Lu Z, Sun Y, et al. (2024) Interactive effect of air pollution and genetic risk of depression on processing speed by resting-state functional connectivity of occipitoparietal network. BMC Med 22: 392. https://doi.org/10.1186/s12916-024-03614-6 |
| [52] | Gao X, Jiang M, Huang N, et al. (2023) Long-term air pollution, genetic susceptibility, and the risk of depression and anxiety: A prospective study in the UK biobank cohort. Environ Health Perspect 131: 17002. https://doi.org/10.1289/EHP10391 |
| [53] | Zhang S, Cao H, Chen K, et al. (2024) Joint exposure to multiple air pollutants, genetic susceptibility, and incident dementia: A prospective analysis in the UK biobank cohort. Int J Public Health 69: 1606868. https://doi.org/10.3389/ijph.2024.1606868 |
| [54] | Katikireddi SV, Green MJ, Taylor AE, et al. (2017) Assessing causal relationships using genetic proxies for exposures: An introduction to mendelian randomization. Addiction 113: 764-774. https://doi.org/10.1111/add.14038 |
| [55] | Zhao SS, Burgess S (2024) Use of mendelian randomization to assess the causal status of modifiable exposures for rheumatic diseases. Best Pract Res Clin Rheumatol 38: 101967. https://doi.org/10.1016/j.berh.2024.101967 |
| [56] | Sanderson E, Glymour MM, Holmes MV, et al. (2022) Mendelian randomization. Nat Rev Methods Primers 2: 6. https://doi.org/10.1038/s43586-021-00092-5 |
| [57] | Virolainen SJ, VonHandorf A, Viel KCMF, et al. (2022) Gene–environment interactions and their impact on human health. Genes Immun 24: 1-11. https://doi.org/10.1038/s41435-022-00192-6 |
| [58] | Wheelock CE, Rappaport SM (2020) The role of gene–environment interactions in lung disease: the urgent need for the exposome. Eur Respir J 55: 1902064. https://doi.org/10.1183/13993003.02064-2019 |
| [59] | Li P, Wang Y, Tian D, et al. (2024) Joint exposure to ambient air pollutants, genetic risk, and ischemic stroke: A prospective analysis in UK biobank. Stroke 55: 3. https://doi.org/10.1161/STROKEAHA.123.044935 |
| [60] | Babu M, Snyder M (2023) Multi-omics profiling for health. Mol Cell Proteomics 22: 100561. https://doi.org/10.1016/j.mcpro.2023.100561 |
| [61] | Fan BL, Chen LH, Chen LL, et al. (2025) Integrative multi-omics approaches for identifying and characterizing biological elements in crop traits: Current progress and future prospects. Int J Mol Sci 26: 1466. https://doi.org/10.3390/ijms26041466 |
| [62] | Zeng X, Vonk JM, van der Plaat DA, et al. (2019) Genome-wide interaction study of gene-by-occupational exposures on respiratory symptoms. Environ Process 122: 263-269. https://doi.org/10.1016/j.envint.2018.11.017 |
| [63] | Northen SM, Keers R, Munroe PB, et al. (2022) Gene–environment correlation over time: A longitudinal analysis of polygenic risk scores for schizophrenia and major depression in three British cohorts studies. Genes 13: 1136. https://doi.org/10.3390/genes13071136 |
| [64] | Zwicker A, Wright EMD, Uher R (2018) Gene–environment interplay in the etiology of psychosis. Psychol Med 48: 1925-1936. https://doi.org/10.1017/S003329171700383X |
| [65] | Vogel C, Van Winkle LS, Esser C, et al. (2020) The aryl hydrocarbon receptor as a target of environmental stressors – Implications for pollution mediated stress and inflammatory responses. Redox Biol 34: 101530. https://doi.org/10.1016/j.redox.2020.101530 |
| [66] | Ho CC, Wu WT, Lin YJ, et al. (2022) Aryl hydrocarbon receptor activation-mediated vascular toxicity of ambient fine particulate matter: Contribution of polycyclic aromatic hydrocarbons and osteopontin as a biomarker. Part Fibre Toxicol 19: 1-21. https://doi.org/10.1186/s12989-022-00482-x |
| [67] | Cox LA (2024) Objective causal predictions from observational data. Crit Rev Toxicol 54: 895-924. https://doi.org/10.1080/10408444.2024.2399856 |
| [68] | Sirugo G, Williams SM, Tishkoff SA (2019) The missing diversity in human genetic studies. Cell 177: 26-31. https://doi.org/10.1016/j.cell.2019.02.048 |
| [69] | Popejoy AB, Fullerton SM (2016) Genomics is failing on diversity. Nature 538: 161-164. http://www.doi.org/10.1038/538161a |
| [70] | Hecker J, Prokopenko D, Moll M, et al. (2022) A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables. PLoS Genet 18: e1010464. https://doi.org/10.1371/journal.pgen.1010464 |
| [71] | Rousseau CN (2025) Understanding and applying gene–environment interactions: A guide for nutrition professionals with an emphasis on integration in African research settings. Nutr Rev 83: e443-e463. https://doi.org/10.1093/nutrit/nuae015 |
| [72] | Cui Y, Eccles KM, Kwok RK, et al. (2022) Integrating multiscale geospatial environmental data into large population health studies: Challenges and opportunities. Toxics 10: 403. https://doi.org/10.3390/toxics10070403 |
| [73] | McCullough SD, Dhingra R, Fortin MC, et al. (2017) Air pollution and the epigenome: A model relationship for the exploration of toxicoepigenetics. Curr Opin Toxicol 6: 18-25. https://doi.org/10.1016/j.cotox.2017.07.001 |
| [74] | Acosta CL, Fallin MD (2016) The role of epigenetics in genetic and environmental epidemiology. Epigenomics 8: 271-283. https://doi.org/10.2217/epi.15.102 |
| [75] | Poursafa P, Kamali Z, Fraszczyk E, et al. (2022) DNA methylation: A potential mediator between air pollution and metabolic syndrome. Clin Epigenetics 14: 82. https://doi.org/10.1186/s13148-022-01301-y |
| [76] | Jagirdhar GSK, Perez JA, Perez AB, et al. (2023) Integration and implementation of precision medicine in the multifaceted inflammatory bowel disease. World J Gastroenterol 29: 5211-5225. https://dx.doi.org/10.3748/wjg.v29.i36.5211 |
| [77] | Roberts MC, Holt KE, Del Fiol G, et al. (2024) Precision public health in the era of genomics and big data. Nat Med 30: 1865-1873. https://doi.org/10.1038/s41591-024-03098-0 |
| [78] | Denny JC, Collins FS (2021) Precision medicine in 2030—seven ways to transform healthcare. Cell 18: 1415-1419. https://doi.org/10.1016/j.cell.2021.01.015 |
| [79] | Porter KMP, Rutkov L, McGinty EE (2018) The importance of policy change for addressing public health problems. Public Health Rep 133: 9S-14S. https://doi.org/10.1177/0033354918788880 |
| [80] | Vilcassim R, Thurston GD (2023) Gaps and future directions in research on health effects of air pollution. EBiomedicine 93: 104668. https://doi.org/10.1016/j.ebiom.2023.104668 |
| [81] | Calluori S, Heimke KK, Caga-anan C, et al. (2024) Ethical, legal, and social implications of gene-environment interaction research. Genet Epidemiol 49: e22591. https://doi.org/10.1002/gepi.22591 |
| [82] | Reddam A, McLarnan S, Kupsco A (2022) Environmental chemical exposures and mitochondrial dysfunction: A review of recent literature. Curr Environ Health Rep 9: 631-649. https://doi.org/10.1007/s40572-022-00371-7 |
| [83] | Drăgoi CM, Diaconu CC, Nicolae AC, et al. (2024) Redox homeostasis and molecular biomarkers in precision therapy for cardiovascular diseases. Antioxidants 13: 1163. https://doi.org/10.3390/antiox13101163 |
| [84] | Sani G, Margoni S, Brugnami A, et al. (2023) The Nrf2 pathway in depressive disorders: A systematic review of animal and human studies. Antioxidants 12: 817. https://doi.org/10.3390/antiox12040817 |
| [85] | Gao W, Guo L, Yang Y, et al. (2022) Dissecting the crosstalk between Nrf2 and NF-κB response pathways in drug-induced toxicity. Front Cell Dev Biol 9: 809952. https://doi.org/10.3389/fcell.2021.809952 |
| [86] | Joo H, Min S, Cho SW (2024) Advanced lung organoids for respiratory system and pulmonary disease modeling. J Tissue Eng 15: 20417314241232502. https://doi.org/10.1177/20417314241232502 |
| [87] | Cheruku GR, Wilson CV, Raviendran S, et al. (2024) Recent advances and future perspectives in vascular organoids and vessel-on-chip. Organoids 3: 203-246. https://doi.org/10.3390/organoids3030014 |
| [88] | Liu X, Zhou Z, Zhang Y, et al. (2025) Recent progress on the organoids: Techniques, advantages and applications. Biomed Pharmacother 185: 117942. https://doi.org/10.1016/j.biopha.2025.117942 |
| [89] | Yang S, Hu H, Kung H, et al. (2023) Organoids: The current status and biomedical applications. MedComm 4: e274. https://doi.org/10.1002/mco2.274 |
| [90] | Huang F, Zhang Y, Feng Y, et al. (2023) The pathophysiological and molecular mechanisms of atmospheric PM2.5 affecting cardiovascular health: A review. Ecotoxicol Environ Saf 249: 114444. https://doi.org/10.1016/j.ecoenv.2022.114444 |
| [91] | Chen SAA, Kern AF, Ang RML, et al. (2023) Gene-by-environment interactions are pervasive among natural genetic variants. Cell Genom 3: 100273. https://doi.org/10.1016/j.xgen.2023.100273 |
 publichealth-12-03-046-s001.pdf |
 |
Figures(2) / Tables(4)
Hari Krismanuel. Exploring genetic susceptibility to air pollution and its implications for disease risk and precision health: A scoping review[J]. AIMS Public Health, 2025, 12(3): 916-951. doi: 10.3934/publichealth.2025046
DownLoad: