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Chauhan R, Dande S, Hood DB, Chirwa SS, Langston MA, Grady SK, Dojcsak L, Tabatabai M, Wilus D, Valdez RB, Al-Hamdan MZ, Im W, McCallister M, Alcendor DJ, Mouton CP, Ramesh A. Particulate matter 2.5 (PM 2.5) - associated cognitive impairment and morbidity in humans and animal models: a systematic review. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2025; 28:233-263. [PMID: 39827081 DOI: 10.1080/10937404.2025.2450354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2025]
Abstract
Particulate matter with an aerodynamic diameter of less than 2.5 µm (PM2.5) is one of the criteria air pollutants that (1) serve as an essential carrier of airborne toxicants arising from combustion-related events including emissions from industries, automobiles, and wildfires and (2) play an important role in transient to long-lasting cognitive dysfunction as well as several other neurological disorders. A systematic review was conducted to address differences in study design and various biochemical and molecular markers employed to elucidate neurological disorders in PM2.5 -exposed humans and animal models. Out of 340,068 scientific publications screened from 7 databases, 312 studies were identified that targeted the relationship between exposure to PM2.5 and cognitive dysfunction. Equivocal evidence was identified from pre-clinical (animal model) and human studies that PM2.5 exposure contributes to dementia, Parkinson disease, multiple sclerosis, stroke, depression, autism spectrum disorder, attention deficit hyperactivity disorder, and neurodevelopment. In addition, there was substantial evidence from human studies that PM2.5 also was associated with Alzheimer's disease, anxiety, neuropathy, and brain tumors. The role of exposome in characterizing neurobehavioral anomalies and opportunities available to leverage the neuroexposome initiative for conducting longitudinal studies is discussed. Our review also provided some areas that warrant consideration, one of which is unraveling the role of microbiome, and the other role of climate change in PM2.5 exposure-induced neurological disorders.
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Affiliation(s)
- Ritu Chauhan
- Department of Biochemistry, Cancer Biology, Neuroscience & Toxicology, School of Medicine, Meharry Medical College, Nashville, TN, USA
| | - Susmitha Dande
- Department of Family and Community Medicine, School of Medicine, Meharry Medical College, Nashville, TN, USA
| | - Darryl B Hood
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Sanika S Chirwa
- Department of Biochemistry, Cancer Biology, Neuroscience & Toxicology, School of Medicine, Meharry Medical College, Nashville, TN, USA
| | - Michael A Langston
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA
| | - Stephen K Grady
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA
| | - Levente Dojcsak
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA
| | - Mohammad Tabatabai
- Department of Public Health, School of Global Health, Meharry Medical College, Nashville, TN, USA
| | - Derek Wilus
- Department of Public Health, School of Global Health, Meharry Medical College, Nashville, TN, USA
| | - R Burciaga Valdez
- Agency for Healthcare Research and Quality, Department of Health and Human Services, Washington, DC, USA
| | - Mohammad Z Al-Hamdan
- National Center for Computational Hydroscience and Engineering (NCCHE) and Department of Civil Engineering and Department of Geology and Geological Engineering, School of Engineering, University of Mississippi, Oxford, MS, USA
| | - Wansoo Im
- Department of Public Health, School of Global Health, Meharry Medical College, Nashville, TN, USA
| | - Monique McCallister
- Department of Biological Sciences, College of Life & Physical Sciences, Tennessee State University, Nashville, TN, USA
| | - Donald J Alcendor
- Department of Microbiology, Immunology and Physiology, Center for AIDS Health Disparities Research, School of Medicine, Meharry Medical College, Nashville, TN, USA
| | - Charles P Mouton
- Department of Family Medicine, John Sealy School of Medicine, The University of Texas Medical Branch, Galveston, TX, USA
| | - Aramandla Ramesh
- Department of Biochemistry, Cancer Biology, Neuroscience & Toxicology, School of Medicine, Meharry Medical College, Nashville, TN, USA
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Zhu J, Wang S, Li P, Li F, Li B, Ma L, Rong S, Liao J. The impact of particulate matter exposure on global and domain-specific cognitive function: evidence from the Chinese Square Dancer Study. BMC Public Health 2025; 25:1289. [PMID: 40188325 PMCID: PMC11971882 DOI: 10.1186/s12889-025-22126-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2025] [Accepted: 02/27/2025] [Indexed: 04/07/2025] Open
Abstract
BACKGROUND There is growing evidence that exposure to particulate matter (PM) is associated with impaired cognitive function. However, limited studies have specifically examined the relationship between PM exposure and domain-specific cognitive function. METHODS This study involved 2,668 female participants from the Lifestyle and Healthy Aging of Chinese Square Dancer Study. Global cognitive function was assessed using a composite Z-score derived from four tests: the Auditory Verbal Learning Test (AVLT), Verbal Fluency Test (VFT), Digit Symbol Substitution Test (DSST), and Trail Making Test-B (TMT-B). These tests evaluated specific cognitive subdomains: memory (AVLT), language (VFT), attention (DSST), and executive function (TMT-B). PM concentrations were estimated using a Random Forest (RF) model, which calculated the average concentrations over 1-year and 3-year periods at a high grid resolution of 1 × 1 km. Mixed linear regression was employed to explore the association between PM exposure and cognitive function. RESULTS After adjusting for basic socio-demographic factors, a 10 mg/m3 increase in 3-year exposure to PM10 was significantly associated with a decrease in the DSST score by -0.05 (95% confidence interval [CI]: -0.11, 0) and an increase in the TMT-B score by 0.05 (95% CI: 0.01, 0.1). When further adjusting for gaseous pollutants (SO₂, NO₂, and O₃), even stronger associations were observed between 3-year exposure to either PM2.5 or PM10 and performance in both global cognition and specific cognitive subdomains. Specifically, in the DSST subdomain, a 10 µg/m³ increase in 1-year PM10 exposure was associated with a decrease in the score by -0.10 (95% CI: -0.15, -0.04). Age-stratified analyses further indicated that older participants were consistently more vulnerable to PM exposure. Notably, 3-year exposure to both PM2.5 and PM10 was linked to declines in DSST scores across both middle-aged and older age groups. CONCLUSION Ambient PM exposure was significantly associated with performance in global cognitive function and specific cognitive domains among Chinese females. Female populations over 65 years old were more susceptible to the adverse effects of PM2.5 and PM10. Among the four subdomains, the DSST showed the strongest association with PM exposure, even at earlier ages, suggesting that impaired attention may serve as an early warning sign of cognitive decline. CLINICAL TRIAL NUMBER Not applicable.
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Affiliation(s)
- Jingyi Zhu
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China
| | - Shuaibo Wang
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China
| | - Peizheng Li
- Department of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, 430071, China
| | - Fengping Li
- Department of Food and Nutrition Health, School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Benchao Li
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China
| | - Lu Ma
- Department of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, 430071, China
- Global Health Institute, Wuhan University, Wuhan, 430071, China
| | - Shuang Rong
- Department of Clinical Nutrition, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, China
| | - Jingling Liao
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China.
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Qin M, Liu X, Wang L, Huang T, Zuo X, Zou Y. Level of elderly-supportive infrastructure, fine particulate matter and cardiovascular disease hospitalisations: a time-stratified case-crossover study in Wuhan. Glob Health Action 2024; 17:2447651. [PMID: 39819469 PMCID: PMC11748890 DOI: 10.1080/16549716.2024.2447651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2024] [Accepted: 12/23/2024] [Indexed: 01/19/2025] Open
Abstract
BACKGROUND Amid rapid urbanisation, the health effects of the built-environment have been widely studied, while research on elderly-supportive infrastructure and its interaction with PM2.5 (PM, Particulate Matter) exposure remains limited. OBJECTIVES To examine the effect of PM2.5 on cardiovascular hospitalisation risk among the elderly and the moderating role of elderly-supportive infrastructure in Wuhan, a city undergoing rapid urbanisation. METHODS A time-stratified case-crossover design was adopted in which the K-means cluster analysis was applied to categorize elderly-supportive infrastructure. The correlation of PM2.5 with cardiovascular hospitalisations and the moderating role of elderly-supportive infrastructure were elucidated through the conditional logistic regression and z-test. Nonlinear relationships among variables were determined using restricted cubic splines. RESULTS 173,486 case days and 589,188 control days were included. The cumulative lag effect of PM2.5 increased over time, peaking at 5 days. For every 10 µg/m3 increase in PM2.5, the risk of hospitalisation rose by 1.5% (OR = 1.0150, 95% CI: 1.0113-1.0190). The aforementioned effect of PM2.5 exposure on health did not differ among varying levels of elderly-supportive infrastructure within a 300 m buffer zone. When the buffer zone was extended to 500 and 1000 m, a higher level of elderly-supportive infrastructure mitigated the adverse effects of short-term PM2.5 exposure on cardiovascular hospitalisations (p = 0.013), particularly for stroke (p = 0.017) and ischaemic heart disease (p = 0.026). CONCLUSIONS Our findings suggest that high-level elderly-supportive infrastructure may protect against the adverse effects of PM2.5 on cardiovascular hospitalisation, highlighting the need to optimize elderly-supportive infrastructure for its health benefits in the elderly.
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Affiliation(s)
- Mengxue Qin
- Center of Health Management, School of Public Health, Wuhan University, Wuhan, China
| | - Xingyuan Liu
- Statistics Department, Wuhan Health Information Center, Wuhan, China
| | - Luyao Wang
- Center of Health Management, School of Public Health, Wuhan University, Wuhan, China
| | - Tengchong Huang
- Center of Health Management, School of Public Health, Wuhan University, Wuhan, China
| | - Xiuran Zuo
- Wuhan Health Information Center, Wuhan, China
| | - Yuliang Zou
- Center of Health Management, School of Public Health, Wuhan University, Wuhan, China
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Acharyya S, Kumar SH, Chouksey A, Soni N, Nazeer N, Mishra PK. The enigma of mitochondrial epigenetic alterations in air pollution-induced neurodegenerative diseases. Neurotoxicology 2024; 105:158-183. [PMID: 39374796 DOI: 10.1016/j.neuro.2024.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 09/13/2024] [Accepted: 10/02/2024] [Indexed: 10/09/2024]
Abstract
The incidence of neurodegenerative diseases is a growing concern worldwide, affecting individuals from diverse backgrounds. Although these pathologies are primarily associated with aging and genetic susceptibility, their severity varies among the affected population. Numerous studies have indicated air pollution as a significant contributor to the increasing prevalence of neurodegeneration. Cohort studies have provided compelling evidence of the association between prolonged exposure to different air toxicants and cognitive decline, behavioural deficits, memory impairment, and overall neuronal health deterioration. Furthermore, molecular research has revealed that air pollutants can disrupt the body's protective mechanisms, participate in neuroinflammatory pathways, and cause neuronal epigenetic modifications. The mitochondrial epigenome is particularly interesting to the scientific community due to its potential to significantly impact our understanding of neurodegenerative diseases' pathogenesis and their release in the peripheral circulation. While protein hallmarks have been extensively studied, the possibility of using circulating epigenetic signatures, such as methylated DNA fragments, miRNAs, and genome-associated factors, as diagnostic tools and therapeutic targets requires further groundwork. The utilization of circulating epigenetic signatures holds promise for developing novel prognostic strategies, creating paramount point-of-care devices for disease diagnosis, identifying therapeutic targets, and developing clinical data-based disease models utilizing multi-omics technologies and artificial intelligence, ultimately mitigating the threat and prevalence of neurodegeneration.
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Affiliation(s)
- Sayanti Acharyya
- Division of Environmental Biotechnology, Genetics & Molecular Biology (EBGMB), ICMR-National Institute for Research in Environmental Health (NIREH), Bhopal, India
| | - Sruthy Hari Kumar
- Division of Environmental Biotechnology, Genetics & Molecular Biology (EBGMB), ICMR-National Institute for Research in Environmental Health (NIREH), Bhopal, India
| | - Apoorva Chouksey
- Division of Environmental Biotechnology, Genetics & Molecular Biology (EBGMB), ICMR-National Institute for Research in Environmental Health (NIREH), Bhopal, India
| | - Nikita Soni
- Division of Environmental Biotechnology, Genetics & Molecular Biology (EBGMB), ICMR-National Institute for Research in Environmental Health (NIREH), Bhopal, India
| | - Nazim Nazeer
- Division of Environmental Biotechnology, Genetics & Molecular Biology (EBGMB), ICMR-National Institute for Research in Environmental Health (NIREH), Bhopal, India
| | - Pradyumna Kumar Mishra
- Division of Environmental Biotechnology, Genetics & Molecular Biology (EBGMB), ICMR-National Institute for Research in Environmental Health (NIREH), Bhopal, India; Faculty of Medical Research, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.
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Filippini T, Costanzini S, Chiari A, Urbano T, Despini F, Tondelli M, Bedin R, Zamboni G, Teggi S, Vinceti M. Light at night exposure and risk of dementia conversion from mild cognitive impairment in a Northern Italy population. Int J Health Geogr 2024; 23:25. [PMID: 39580439 PMCID: PMC11585219 DOI: 10.1186/s12942-024-00384-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 11/19/2024] [Indexed: 11/25/2024] Open
Abstract
BACKGROUND A few studies have suggested that light at night (LAN) exposure, i.e. lighting during night hours, may increase dementia risk. We evaluated such association in a cohort of subjects diagnosed with mild cognitive impairment (MCI). METHODS We recruited study participants between 2008 and 2014 at the Cognitive Neurology Clinic of Modena Hospital, Northern Italy and followed them for conversion to dementia up to 2021. We collected their residential history and we assessed outdoor artificial LAN exposure at subjects' residences using satellite imagery data available from the Visible Infrared Imaging Radiometer Suite (VIIRS) for the period 2014-2022. We assessed the relation between LAN exposure and cerebrospinal fluid biomarkers. We used a Cox-proportional hazards model to compute the hazard ratio (HR) of dementia with 95% confidence interval (CI) according to increasing LAN exposure through linear, categorical, and non-linear restricted-cubic spline models, adjusting by relevant confounders. RESULTS Out of 53 recruited subjects, 34 converted to dementia of any type and 26 converted to Alzheimer's dementia. Higher levels of LAN were positively associated with biomarkers of tau pathology, as well as with lower concentrations of amyloid β1-42 assessed at baseline. LAN exposure was positively associated with dementia conversion using linear regression model (HR 1.04, 95% CI 1.01-1.07 for 1-unit increase). Using as reference the lowest tertile, subjects at both intermediate and highest tertiles of LAN exposure showed increased risk of dementia conversion (HRs 2.53, 95% CI 0.99-6.50, and 3.61, 95% CI 1.34-9.74). In spline regression analysis, the risk linearly increased for conversion to both any dementia and Alzheimer's dementia above 30 nW/cm2/sr of LAN exposure. Adding potential confounders including traffic-related particulate matter, smoking status, chronic diseases, and apolipoprotein E status to the multivariable model, or removing cases with dementia onset within the first year of follow-up did not substantially alter the results. CONCLUSION Our findings suggest that outdoor artificial LAN may increase dementia conversion, especially above 30 nW/cm2/sr, although the limited sample size suggests caution in the interpretation of the results, to be confirmed in larger investigations.
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Affiliation(s)
- Tommaso Filippini
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, Section of Public Health, University of Modena and Reggio Emilia, 287 Via Campi, Modena, 41125, Italy.
- School of Public Health, University of California Berkeley, Berkeley, CA, USA.
| | - Sofia Costanzini
- DIEF - Department of Engineering 'Enzo Ferrari', University of Modena and Reggio Emilia, Modena, Italy
| | - Annalisa Chiari
- Neurology Unit, University Hospital of Modena, Modena, Italy
| | - Teresa Urbano
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, Section of Public Health, University of Modena and Reggio Emilia, 287 Via Campi, Modena, 41125, Italy
| | - Francesca Despini
- DIEF - Department of Engineering 'Enzo Ferrari', University of Modena and Reggio Emilia, Modena, Italy
| | - Manuela Tondelli
- Neurology Unit, University Hospital of Modena, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Roberta Bedin
- Neurology Unit, University Hospital of Modena, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Giovanna Zamboni
- Neurology Unit, University Hospital of Modena, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Sergio Teggi
- DIEF - Department of Engineering 'Enzo Ferrari', University of Modena and Reggio Emilia, Modena, Italy
| | - Marco Vinceti
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, Section of Public Health, University of Modena and Reggio Emilia, 287 Via Campi, Modena, 41125, Italy
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
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Urbano T, Maramotti R, Tondelli M, Gallingani C, Carbone C, Iacovino N, Vinceti G, Zamboni G, Chiari A, Bedin R. Comparison of Serum and Cerebrospinal Fluid Neurofilament Light Chain Concentrations Measured by Ella™ and Lumipulse™ in Patients with Cognitive Impairment. Diagnostics (Basel) 2024; 14:2408. [PMID: 39518375 PMCID: PMC11544876 DOI: 10.3390/diagnostics14212408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2024] [Revised: 10/17/2024] [Accepted: 10/24/2024] [Indexed: 11/16/2024] Open
Abstract
OBJECTIVE Neurofilament light chain proteins (NfLs) are considered a promising biomarker of neuroaxonal damage in several neurological diseases. Their measurement in the serum and cerebrospinal fluid (CSF) of patients with dementia may be especially useful. Our aim was to compare the NfL measurement performance of two advanced technologies, specifically the Ella™ microfluidic platform and the Lumipulse™ fully automated system, in patients with cognitive disorders. METHODS Thirty subjects with neurodegenerative cognitive disorders (10 with Alzheimer's Disease, 10 with Frontotemporal Dementia, and 10 with non-progressive Mild Cognitive Impairment) seen at the Cognitive Neurology Clinic of Modena University Hospital (Italy) underwent CSF and serum NfL measurement with both the Ella™ microfluidic platform (Bio-Techne, Minneapolis, MN, USA)) and the Lumipulse™ fully automated system for the CLEIA (Fujirebio Inc., Ghent, Belgium). Correlation and regression analyses were applied to assess the association between NfL concentrations obtained with the two assays in CSF and serum. The Passing-Bablok regression method was employed to evaluate the agreement between the assays. RESULTS There were high correlations between the two assays (r = 0.976, 95% CI. 0.950-0.989 for CSF vs. r = 0.923, 95% CI 0.842-0.964 for serum). A Passing-Bablok regression model was estimated to explain the relationship between the two assays, allowing us to switch from one to the other when only one assay was available. CONCLUSIONS We found a good degree of correlation between the two methods in patients with neurocognitive disorders. We also established a method that will allow comparisons between results obtained with either technique, allowing for meta-analyses and larger sample sizes.
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Affiliation(s)
- Teresa Urbano
- Neuroimmunology Laboratory, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Baggiovara Hospital, 41126 Modena, Italy; (T.U.); (R.B.)
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy
| | - Riccardo Maramotti
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (R.M.); (C.G.); (C.C.); (N.I.); (G.Z.)
- Department of Physics, Informatics and Mathematics, University of Modena and Reggio Emilia, 41125 Modena, Italy
- Department of Mathematics and Computer Science, University of Ferrara, 44121 Ferrara, Italy
| | - Manuela Tondelli
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (R.M.); (C.G.); (C.C.); (N.I.); (G.Z.)
- Neurology Unit, Baggiovara Hospital, 41126 Modena, Italy; (G.V.); (A.C.)
| | - Chiara Gallingani
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (R.M.); (C.G.); (C.C.); (N.I.); (G.Z.)
- Neurology Unit, Baggiovara Hospital, 41126 Modena, Italy; (G.V.); (A.C.)
| | - Chiara Carbone
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (R.M.); (C.G.); (C.C.); (N.I.); (G.Z.)
- Neurology Unit, Baggiovara Hospital, 41126 Modena, Italy; (G.V.); (A.C.)
| | - Najara Iacovino
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (R.M.); (C.G.); (C.C.); (N.I.); (G.Z.)
- Neurology Unit, Baggiovara Hospital, 41126 Modena, Italy; (G.V.); (A.C.)
| | - Giulia Vinceti
- Neurology Unit, Baggiovara Hospital, 41126 Modena, Italy; (G.V.); (A.C.)
| | - Giovanna Zamboni
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (R.M.); (C.G.); (C.C.); (N.I.); (G.Z.)
- Neurology Unit, Baggiovara Hospital, 41126 Modena, Italy; (G.V.); (A.C.)
| | - Annalisa Chiari
- Neurology Unit, Baggiovara Hospital, 41126 Modena, Italy; (G.V.); (A.C.)
| | - Roberta Bedin
- Neuroimmunology Laboratory, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Baggiovara Hospital, 41126 Modena, Italy; (T.U.); (R.B.)
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy; (R.M.); (C.G.); (C.C.); (N.I.); (G.Z.)
- Neurology Unit, Baggiovara Hospital, 41126 Modena, Italy; (G.V.); (A.C.)
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Soeterboek J, Deckers K, van Boxtel MPJ, Backes WH, Eussen SJPM, van Greevenbroek MMJ, Jansen JFA, Koster A, Schram MT, Stehouwer CDA, Wesselius A, Lakerveld J, Bosma H, Köhler S. Association of ambient air pollution with cognitive functioning and markers of structural brain damage: The Maastricht study. ENVIRONMENT INTERNATIONAL 2024; 192:109048. [PMID: 39383768 DOI: 10.1016/j.envint.2024.109048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 10/01/2024] [Accepted: 10/02/2024] [Indexed: 10/11/2024]
Abstract
INTRODUCTION Given the absence of curative interventions and the rising global incidence of dementia, research is increasingly focusing on lifestyle factors for prevention. However, identifying shared environmental risk for dementia, next to individual factors, is crucial for optimal risk reduction strategies. Therefore, in the present study we investigated the association between air pollution, cognitive functioning, and markers of structural brain damage. METHODS We used cross-sectional data from 4,002 participants of The Maastricht Study on volumetric markers of brain integrity (white and grey matter volume, cerebrospinal fluid volume, white matter hyperintensities volume, presence of cerebral small vessel disease) and cognitive functioning (memory, executive functioning and attention, processing speed, overall cognition). Individuals were matched by postal code of residence to nationwide data on air pollution exposure (particulate matter < 2.5 μm (PM2.5), particulate matter <10 μm (PM10), nitrogen dioxide (NO2), soot). Potentia linear and non-linear associations were investigated with linear, logistic, and restricted cubic splines regression. All analyses were adjusted for demographic characteristics and a compound score of modifiable dementia risk and protective factors. RESULTS Exposure to air pollutants was not related to cognitive functioning and most brain markers. We found curvilinear relationships between high PM2.5 exposures and grey matter and cerebrospinal fluid volume. Participants in the low and high range of exposure had lower grey matter volume. Higher cerebrospinal fluid volumes were only associated with high range of exposure, independent of demographic and individual modifiable dementia risk factors. After additional post hoc analyses, controlling for urbanicity, the associations for grey matter volume became non-significant. In men only, higher exposure to all air pollutants was associated with lower white matter volumes. No significant associations with white matter hyperintensities volume or cerebral small vessel disease were observed. DISCUSSION Our findings suggest that higher PM2.5 exposure is associated with more brain atrophy.
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Affiliation(s)
- J Soeterboek
- Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, the Netherlands; Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands.
| | - K Deckers
- Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, the Netherlands; Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
| | - M P J van Boxtel
- Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, the Netherlands; Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
| | - W H Backes
- Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - S J P M Eussen
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands; Care and Public Health Research Institute (CAPHRI), Maastricht University, the Netherlands; Department of Epidemiology, Maastricht University, Maastricht, the Netherlands
| | - M M J van Greevenbroek
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands; Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - J F A Jansen
- Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - A Koster
- Care and Public Health Research Institute (CAPHRI), Maastricht University, the Netherlands; Department of Social Medicine, Maastricht University, Maastricht, the Netherlands
| | - M T Schram
- Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, the Netherlands; Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands; Heart and Vascular Center, Maastricht University Medical Center, Maastricht, the Netherlands; Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - C D A Stehouwer
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, the Netherlands; Heart and Vascular Center, Maastricht University Medical Center, Maastricht, the Netherlands; Department of Internal Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - A Wesselius
- Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University, Maastricht, the Netherlands
| | - J Lakerveld
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam UMC, VU University Amsterdam, Amsterdam, the Netherlands; Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - H Bosma
- Care and Public Health Research Institute (CAPHRI), Maastricht University, the Netherlands; Department of Social Medicine, Maastricht University, Maastricht, the Netherlands
| | - S Köhler
- Mental Health and Neuroscience Research Institute (MHeNs), Maastricht University, Maastricht, the Netherlands; Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands.
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8
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Kim BY, Sohn E, Lee MY, Jeon WY, Jo K, Kim YJ, Jeong SJ. Neurodegenerative pathways and metabolic changes in the hippocampus and cortex of mice exposed to urban particulate matter: Insights from an integrated interactome analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 945:173673. [PMID: 38839008 DOI: 10.1016/j.scitotenv.2024.173673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 05/22/2024] [Accepted: 05/29/2024] [Indexed: 06/07/2024]
Abstract
Recently, urban particulate matter (UPM) exposure has been associated with the development of brain disorders. This study uses bioinformatic analyses to elucidate the molecular unexplored mechanisms underlying the effects of UPM exposure on the brain. Mice are exposed to UPM (from 3 days to 20 weeks), and their behavioral patterns measured. We measure pathology and gene expression in the hippocampus and cortical regions of the brain. An integrated interactome of genes is established, which enriches information on metabolic processes. Using this network, we isolate the core genes that are differentially expressed in the samples. We observe cognitive loss and pathological changes in the brains of mice at 16 or 20 weeks of exposure. Through network analysis of core-differential genes and measurement of pathway activity, we identify differences in the response to UPM exposure between the hippocampus and cortex. However, neurodegenerative disease pathways are implicated in both tissues following short-term exposure to UPM. There were also significant changes in metabolic function in both tissues depending on UPM exposure time. Additionally, the cortex of UPM-exposed mice shows more similarities with psychiatric disorders than with neurodegenerative diseases. The connectivity map database is used to isolate genes contributing to changes in expression due to UPM exposure. New approaches for inhibiting or preventing the brain damage caused by UPM exposure can be developed by targeting the functions and selected genes identified in this study.
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Affiliation(s)
- Bu-Yeo Kim
- KM Convergence Research Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon 34054, Republic of Korea.
| | - Eunjin Sohn
- KM Convergence Research Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon 34054, Republic of Korea
| | - Mee-Young Lee
- KM Convergence Research Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon 34054, Republic of Korea
| | - Woo-Young Jeon
- KM Convergence Research Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon 34054, Republic of Korea
| | - Kyuhyung Jo
- KM Convergence Research Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon 34054, Republic of Korea
| | - Yu Jin Kim
- KM Convergence Research Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon 34054, Republic of Korea
| | - Soo-Jin Jeong
- KM Convergence Research Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon 34054, Republic of Korea.
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9
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Marchesiello WMV, Spadaccino G, Usman M, Nardiello D, Quinto M. Determination of volatile organic compounds (VOCs) in indoor work environments by solid phase microextraction-gas chromatography-mass spectrometry. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:52804-52814. [PMID: 39160406 PMCID: PMC11379745 DOI: 10.1007/s11356-024-34715-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 08/12/2024] [Indexed: 08/21/2024]
Abstract
Volatile organic compounds (VOCs) are continuously emitted into the atmosphere from natural and anthropogenic sources and rapidly spread from the atmosphere to different environments. A large group of VOCs has been included in the class of air pollutants; therefore, their determination and monitoring using reliable and sensitive analytical methods represents a key aspect of health risk assessment. In this work, an untargeted approach is proposed for the evaluation of the exposure to volatile organic compounds of workers in an engine manufacturing plant by GC-MS measurements, coupled with solid-phase microextraction (SPME). The analytical procedure was optimized in terms of SPME fiber, adsorption time, desorption time, and temperature gradient of the chromatographic run. For the microextraction of VOCs, the SPME fibers were exposed to the air in two different zones of the manufacturing factory, i.e., in the mixing painting chamber and the engine painting area. Moreover, the sampling was carried out with the painting system active and running (system on) and with the painting system switched off (system off). Overall, 212 compounds were identified, but only 17 were always present in both zones (mixing painting chamber and engine painting area), regardless of system conditions (on or off). Finally, a semi-quantitative evaluation was performed considering the peak area value of the potentially most toxic compounds by multivariate data analyses.
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Affiliation(s)
| | - Giuseppina Spadaccino
- Department of Agriculture, Food, Natural Resources, and Engineering (DAFNE), University of Foggia, Via Napoli, 25, 71122, Foggia, Italy
| | - Muhammad Usman
- Department of Agriculture, Food, Natural Resources, and Engineering (DAFNE), University of Foggia, Via Napoli, 25, 71122, Foggia, Italy
| | - Donatella Nardiello
- Department of Agriculture, Food, Natural Resources, and Engineering (DAFNE), University of Foggia, Via Napoli, 25, 71122, Foggia, Italy.
| | - Maurizio Quinto
- Department of Agriculture, Food, Natural Resources, and Engineering (DAFNE), University of Foggia, Via Napoli, 25, 71122, Foggia, Italy
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10
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Oudin A, Raza W, Flanagan E, Segersson D, Jalava P, Kanninen KM, Rönkkö T, Giugno R, Sandström T, Muala A, Topinka J, Sommar J. Exposure to source-specific air pollution in residential areas and its association with dementia incidence: a cohort study in Northern Sweden. Sci Rep 2024; 14:15521. [PMID: 38969679 PMCID: PMC11226641 DOI: 10.1038/s41598-024-66166-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 06/27/2024] [Indexed: 07/07/2024] Open
Abstract
The aim of this study was to investigate the relationship between source-specific ambient particulate air pollution concentrations and the incidence of dementia. The study encompassed 70,057 participants from the Västerbotten intervention program cohort in Northern Sweden with a median age of 40 years at baseline. High-resolution dispersion models were employed to estimate source-specific particulate matter (PM) concentrations, such as PM10 and PM2.5 from traffic, exhaust, and biomass (mainly wood) burning, at the residential addresses of each participant. Cox regression models, adjusted for potential confounding factors, were used for the assessment. Over 884,847 person-years of follow-up, 409 incident dementia cases, identified through national registers, were observed. The study population's average exposure to annual mean total PM10 and PM2.5 lag 1-5 years was 9.50 µg/m3 and 5.61 µg/m3, respectively. Increased risks were identified for PM10-Traffic (35% [95% CI 0-82%]) and PM2.5-Exhaust (33% [95% CI - 2 to 79%]) in the second exposure tertile for lag 1-5 years, although no such risks were observed in the third tertile. Interestingly, a negative association was observed between PM2.5-Wood burning and the risk of dementia. In summary, this register-based study did not conclusively establish a strong association between air pollution exposure and the incidence of dementia. While some evidence indicated elevated risks for PM10-Traffic and PM2.5-Exhaust, and conversely, a negative association for PM2.5-Wood burning, no clear exposure-response relationships were evident.
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Affiliation(s)
- Anna Oudin
- Department of Public Health and Clinical Medicine, Sustainable Health, Umeå University, Umeå, Sweden.
- Division of Occupational and Environmental Medicine, Department of Laboratory Medicine, Lund University, Lund, Sweden.
| | - Wasif Raza
- Department of Public Health and Clinical Medicine, Sustainable Health, Umeå University, Umeå, Sweden
| | - Erin Flanagan
- Division of Occupational and Environmental Medicine, Department of Laboratory Medicine, Lund University, Lund, Sweden
| | - David Segersson
- Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
| | - Pasi Jalava
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, Finland
| | - Katja M Kanninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Topi Rönkkö
- Aerosol Physics Laboratory, Physics Unit, Tampere University, Tampere, Finland
| | - Rosalba Giugno
- Computer Science Department, University of Verona, Verona, Italy
| | - Thomas Sandström
- Division of Medicine/Respiratory Medicine, Department of Toxicology and Molecular Epidemiology, Umeå University, Umeå, Sweden
| | - Ala Muala
- Division of Medicine/Respiratory Medicine, Department of Toxicology and Molecular Epidemiology, Umeå University, Umeå, Sweden
| | - Jan Topinka
- Department of Genetic Toxicology and Epigenetics, Institute of Experimental Medicine of the CAS, Prague, Czech Republic
| | - Johan Sommar
- Department of Public Health and Clinical Medicine, Sustainable Health, Umeå University, Umeå, Sweden
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11
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Tondelli M, Chiari A, Vinceti G, Galli C, Salemme S, Filippini T, Carbone C, Minafra C, De Luca C, Prandi R, Tondelli S, Zamboni G. Greenness and neuropsychiatric symptoms in dementia. ENVIRONMENTAL RESEARCH 2024; 242:117652. [PMID: 37980996 DOI: 10.1016/j.envres.2023.117652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 11/10/2023] [Accepted: 11/11/2023] [Indexed: 11/21/2023]
Abstract
OBJECTIVES It is acknowledged that living in a green environment may help mental well-being and this may be especially true for vulnerable people. However, the relationship between greenness and neuropsychiatric symptoms in dementia has not been explored yet. METHODS We collected clinical, neuropsychiatric, and residential data from subjects with dementia living in the province of Modena, Northern Italy. Neuropsychiatric symptoms were measured with the Neuropsychiatry Inventory, a questionnaire administered to the caregiver who assesses the presence and severity of neuropsychiatric symptoms, including delusions, hallucinations, agitation/aggression, dysphoria/depression, anxiety, euphoria/elation, apathy/indifference, disinhibition, irritability/lability, aberrant motor behaviors, sleep disturbances, and appetite/eating changes. Normalized Difference Vegetation Index (NDVI) was used as a proxy of greenness. Regression models were constructed to study the association between greenness and neuropsychiatric features. RESULTS 155 patients with dementia were recruited. We found that greenness is variably associated with the risk of having neuropsychiatric symptoms. The risk of apathy was lower with lower levels of greenness (OR = 0.42, 95% CI 0.19-0.91 for NDVI below the median value). The risk of psychosis was higher with lower levels of greenness but with more imprecise values (OR = 1.77, 95% CI 0.84-3.73 for NDVI below the median value). CONCLUSION Our results suggest a possible association between greenness and neuropsychiatric symptoms in people with dementia. If replicated in larger samples, these findings will pave the road for identifying innovative greening strategies and interventions that can improve mental health in dementia.
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Affiliation(s)
- Manuela Tondelli
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Unit, Baggiovara Hospital, AOU Modena, Modena, Italy.
| | - Annalisa Chiari
- Neurology Unit, Baggiovara Hospital, AOU Modena, Modena, Italy
| | - Giulia Vinceti
- Neurology Unit, Baggiovara Hospital, AOU Modena, Modena, Italy
| | - Chiara Galli
- Primary Care Department, AUSL Modena, Modena, Italy
| | - Simone Salemme
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Tommaso Filippini
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; School of Public Health, University of California Berkeley, Berkeley, CA, USA
| | - Chiara Carbone
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Claudia Minafra
- Department of Architecture, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Claudia De Luca
- Department of Architecture, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Riccardo Prandi
- Department of Biological, Geological and Environmental Sciences (BiGeA), Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Simona Tondelli
- Department of Architecture, Alma Mater Studiorum University of Bologna, Bologna, Italy
| | - Giovanna Zamboni
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Unit, Baggiovara Hospital, AOU Modena, Modena, Italy
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12
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Calderón-Garcidueñas L, Stommel EW, Torres-Jardón R, Hernández-Luna J, Aiello-Mora M, González-Maciel A, Reynoso-Robles R, Pérez-Guillé B, Silva-Pereyra HG, Tehuacanero-Cuapa S, Rodríguez-Gómez A, Lachmann I, Galaz-Montoya C, Doty RL, Roy A, Mukherjee PS. Alzheimer and Parkinson diseases, frontotemporal lobar degeneration and amyotrophic lateral sclerosis overlapping neuropathology start in the first two decades of life in pollution exposed urbanites and brain ultrafine particulate matter and industrial nanoparticles, including Fe, Ti, Al, V, Ni, Hg, Co, Cu, Zn, Ag, Pt, Ce, La, Pr and W are key players. Metropolitan Mexico City health crisis is in progress. Front Hum Neurosci 2024; 17:1297467. [PMID: 38283093 PMCID: PMC10811680 DOI: 10.3389/fnhum.2023.1297467] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 12/08/2023] [Indexed: 01/30/2024] Open
Abstract
The neuropathological hallmarks of Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal lobar degeneration (FTLD), and amyotrophic lateral sclerosis (ALS) are present in urban children exposed to fine particulate matter (PM2.5), combustion and friction ultrafine PM (UFPM), and industrial nanoparticles (NPs). Metropolitan Mexico City (MMC) forensic autopsies strongly suggest that anthropogenic UFPM and industrial NPs reach the brain through the nasal/olfactory, lung, gastrointestinal tract, skin, and placental barriers. Diesel-heavy unregulated vehicles are a key UFPM source for 21.8 million MMC residents. We found that hyperphosphorylated tau, beta amyloid1-42, α-synuclein, and TAR DNA-binding protein-43 were associated with NPs in 186 forensic autopsies (mean age 27.45 ± 11.89 years). The neurovascular unit is an early NPs anatomical target, and the first two decades of life are critical: 100% of 57 children aged 14.8 ± 5.2 years had AD pathology; 25 (43.9%) AD+TDP-43; 11 (19.3%) AD + PD + TDP-43; and 2 (3.56%) AD +PD. Fe, Ti, Hg, Ni, Co, Cu, Zn, Cd, Al, Mg, Ag, Ce, La, Pr, W, Ca, Cl, K, Si, S, Na, and C NPs are seen in frontal and temporal lobes, olfactory bulb, caudate, substantia nigra, locus coeruleus, medulla, cerebellum, and/or motor cortical and spinal regions. Endothelial, neuronal, and glial damages are extensive, with NPs in mitochondria, rough endoplasmic reticulum, the Golgi apparatus, and lysosomes. Autophagy, cell and nuclear membrane damage, disruption of nuclear pores and heterochromatin, and cell death are present. Metals associated with abrasion and deterioration of automobile catalysts and electronic waste and rare earth elements, i.e., lanthanum, cerium, and praseodymium, are entering young brains. Exposure to environmental UFPM and industrial NPs in the first two decades of life are prime candidates for initiating the early stages of fatal neurodegenerative diseases. MMC children and young adults-surrogates for children in polluted areas around the world-exhibit early AD, PD, FTLD, and ALS neuropathological hallmarks forecasting serious health, social, economic, academic, and judicial societal detrimental impact. Neurodegeneration prevention should be a public health priority as the problem of human exposure to particle pollution is solvable. We are knowledgeable of the main emission sources and the technological options to control them. What are we waiting for?
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Affiliation(s)
| | - Elijah W. Stommel
- Department of Neurology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - Ricardo Torres-Jardón
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | | | - Mario Aiello-Mora
- Otorrinolaryngology Department, Instituto Nacional de Cardiología, Mexico City, Mexico
| | | | | | | | | | | | | | | | | | - Richard L. Doty
- Perelman School of Medicine, Smell and Taste Center, University of Pennsylvania, Philadelphia, PA, United States
| | - Anik Roy
- Interdisciplinary Statistical Research Unit, Indian Statistical Institute, Kolkata, India
| | - Partha S. Mukherjee
- Interdisciplinary Statistical Research Unit, Indian Statistical Institute, Kolkata, India
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13
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Xie XY, Huang LY, Cheng GR, Liu D, Hu FF, Zhang JJ, Han GB, Liu XC, Wang JY, Zhou J, Zeng DY, Liu J, Nie QQ, Song D, Yu YF, Hu CL, Fu YD, Li SY, Cai C, Cui YY, Cai WY, Li YQ, Fan RJ, Wan H, Xu L, Ou YM, Chen XX, Zhou YL, Chen YS, Li JQ, Wei Z, Wu Q, Mei YF, Tan W, Song SJ, Zeng Y. Association Between Long-Term Exposure to Ambient Air Pollution and the Risk of Mild Cognitive Impairment in a Chinese Urban Area: A Case-Control Study. J Alzheimers Dis 2024; 98:941-955. [PMID: 38489185 DOI: 10.3233/jad-231186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2024]
Abstract
Background As a prodromal stage of dementia, significant emphasis has been placed on the identification of modifiable risks of mild cognitive impairment (MCI). Research has indicated a correlation between exposure to air pollution and cognitive function in older adults. However, few studies have examined such an association among the MCI population inChina. Objective We aimed to explore the association between air pollution exposure and MCI risk from the Hubei Memory and Aging Cohort Study. Methods We measured four pollutants from 2015 to 2018, 3 years before the cognitive assessment of the participants. Logistic regression models were employed to calculate odds ratios (ORs) to assess the relationship between air pollutants and MCI risk. Results Among 4,205 older participants, the adjusted ORs of MCI risk for the highest quartile of PM2.5, PM10, O3, and SO2 were 1.90 (1.39, 2.62), 1.77 (1.28, 2.47), 0.56 (0.42, 0.75), and 1.18 (0.87, 1.61) respectively, compared with the lowest quartile. Stratified analyses indicated that such associations were found in both males and females, but were more significant in older participants. Conclusions Our findings are consistent with the growing evidence suggesting that air pollution increases the risk of mild cognitive decline, which has considerable guiding significance for early intervention of dementia in the older population. Further studies in other populations and broader geographical areas are warranted to validate these findings.
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Affiliation(s)
- Xin-Yan Xie
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
| | - Lin-Ya Huang
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Gui-Rong Cheng
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
| | - Dan Liu
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
| | - Fei-Fei Hu
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Jing-Jing Zhang
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Gang-Bin Han
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Xiao-Chang Liu
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Jun-Yi Wang
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Juan Zhou
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - De-Yang Zeng
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Jing Liu
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Qian-Qian Nie
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Dan Song
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Ya-Fu Yu
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Chen-Lu Hu
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Yi-Di Fu
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Shi-Yue Li
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Cheng Cai
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Yu-Yang Cui
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Wan-Ying Cai
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Yi-Qing Li
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Ren-Jia Fan
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Hong Wan
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
| | - Lang Xu
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
| | - Yang-Ming Ou
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
| | - Xing-Xing Chen
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Yan-Ling Zhou
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Yu-Shan Chen
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
| | - Jin-Quan Li
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
| | - Zhen Wei
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
| | - Qiong Wu
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Yu-Fei Mei
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Wei Tan
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Shao-Jun Song
- Reproductive Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Zeng
- Brain Science and Advanced Technology Institute, Wuhan University of Science and Technology, Wuhan, China
- Geriatric Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
- School of Public Health, Wuhan University of Science and Technology, Wuhan, China
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14
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Lee J, Weerasinghe-Mudiyanselage PDE, Kim B, Kang S, Kim JS, Moon C. Particulate matter exposure and neurodegenerative diseases: A comprehensive update on toxicity and mechanisms. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 266:115565. [PMID: 37832485 DOI: 10.1016/j.ecoenv.2023.115565] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/30/2023] [Accepted: 10/08/2023] [Indexed: 10/15/2023]
Abstract
Exposure to particulate matter (PM) has been associated with a range of health impacts, including neurological abnormalities that affect neurodevelopment, neuroplasticity, and behavior. Recently, there has been growing interest in investigating the possible relationship between PM exposure and the onset and progression of neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis. However, the precise mechanism by which PM affects neurodegeneration is still unclear, even though several epidemiological and animal model studies have provided mechanistic insights. This article presents a review of the current research on the neurotoxicity of PM and its impact on neurodegenerative diseases. This review summarizes findings from epidemiological and animal model studies collected through searches in Google Scholar, PubMed, Web of Science, and Scopus. This review paper also discusses the reported effects of PM exposure on the central nervous system and highlights research gaps and future directions. The information presented in this review may inform public health policies aimed at reducing PM exposure and may contribute to the development of new treatments for neurodegenerative diseases. Further mechanistic and therapeutic research will be needed to fully understand the relationship between PM exposure and neurodegenerative diseases.
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Affiliation(s)
- Jeongmin Lee
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR program, Chonnam National University, Gwangju 61186, South Korea
| | - Poornima D E Weerasinghe-Mudiyanselage
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR program, Chonnam National University, Gwangju 61186, South Korea
| | - Bohye Kim
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR program, Chonnam National University, Gwangju 61186, South Korea
| | - Sohi Kang
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR program, Chonnam National University, Gwangju 61186, South Korea
| | - Joong-Sun Kim
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR program, Chonnam National University, Gwangju 61186, South Korea
| | - Changjong Moon
- Department of Veterinary Anatomy and Animal Behavior, College of Veterinary Medicine and BK21 FOUR program, Chonnam National University, Gwangju 61186, South Korea.
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Mazzoleni E, Vinceti M, Costanzini S, Garuti C, Adani G, Vinceti G, Zamboni G, Tondelli M, Galli C, Salemme S, Teggi S, Chiari A, Filippini T. Outdoor artificial light at night and risk of early-onset dementia: A case-control study in the Modena population, Northern Italy. Heliyon 2023; 9:e17837. [PMID: 37455959 PMCID: PMC10339013 DOI: 10.1016/j.heliyon.2023.e17837] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 05/15/2023] [Accepted: 06/28/2023] [Indexed: 07/18/2023] Open
Abstract
Background Dementia is a neurological syndrome characterized by severe cognitive impairment with functional impact on everyday life. It can be classified as young onset dementia (EOD) in case of symptom onset before 65, and late onset dementia (LOD). The purpose of this study is to assess the risk of dementia due to light pollution, and specifically outdoor artificial light at night (LAN). Methods Using a case-control design, we enrolled dementia patients newly-diagnosed in the province of Modena in the period 2017-2019 and a referent population from their caregivers. We geo-referenced the address of residence on the date of recruitment, provided it was stable for the previous five years. We assessed LAN exposure through 2015 nighttime luminance satellite images from the Visible Infrared Imaging Radiometer Suite (VIIRS). Using a logistic regression model adjusted for age, sex, and education, we calculated the risk of dementia associated with increasing LAN exposure, namely using <10 nW/cm2/sr as reference and considering ≥10-<40 nW/cm2/sr intermediate and ≥40 nW/cm2/sr high exposure, respectively We also implemented non-linear assessment using a spline regression model. Results We recruited 58 EOD cases, 34 LOD cases and 54 controls. Average LAN exposure levels overlapped for EOD cases and controls, while LOD cases showed higher levels. Compared with the lowest exposure, the risk of EOD associated with LAN was higher in the intermediate exposure (OR = 1.36, 95% CI 0.54-3.39), but not in the high exposure category (OR = 1.04, 95% CI 0.32-3.34). In contrast, the risk of LOD was positively associated with LAN exposure, with ORs of 2.58 (95% CI 0.26-25.97) and 3.50 (95% CI 0.32-38.87) in the intermediate and high exposure categories, respectively. The spline regression analysis showed substantial lack of association between LAN and EOD, while almost linear although highly imprecise association emerged for LOD. Conclusions Although the precision of the estimates was affected by the limited sample size and the study design did not allow us to exclude the presence of residual confounding, these results suggest a possible role of LAN in the etiology of dementia, particularly of its late-onset form.
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Affiliation(s)
- Elena Mazzoleni
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Marco Vinceti
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Sofia Costanzini
- DIEF Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, Modena, Italy
| | - Caterina Garuti
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Department of Medical and Surgical Sciences for Mothers, Children and Adults, Post Graduate School of Pediatrics, University of Modena and Reggio Emilia, Modena, Italy
| | - Giorgia Adani
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Giulia Vinceti
- Department Center for Neurosciences and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Modena Policlinico-University Hospital, Modena, Italy
| | - Giovanna Zamboni
- Department Center for Neurosciences and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Modena Policlinico-University Hospital, Modena, Italy
| | - Manuela Tondelli
- Neurology Unit, Modena Policlinico-University Hospital, Modena, Italy
- Primary Care Department, Modena Local Health Authority, Modena, Italy
| | - Chiara Galli
- Neurology Unit, Modena Policlinico-University Hospital, Modena, Italy
- Primary Care Department, Modena Local Health Authority, Modena, Italy
- Department of Neuroscience, Psychology, Pharmacology and Child Health (NeuroFARBA), University of Florence, Florence, Italy
| | - Simone Salemme
- Department Center for Neurosciences and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Modena Policlinico-University Hospital, Modena, Italy
| | - Sergio Teggi
- DIEF Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, Modena, Italy
| | - Annalisa Chiari
- Neurology Unit, Modena Policlinico-University Hospital, Modena, Italy
| | - Tommaso Filippini
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- School of Public Health, University of California Berkeley, Berkeley, CA, USA
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