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Fania A, Monaco A, Amoroso N, Bellantuono L, Cazzolla Gatti R, Firza N, Lacalamita A, Pantaleo E, Tangaro S, Velichevskaya A, Bellotti R. Machine learning and XAI approaches highlight the strong connection between O 3 and N O 2 pollutants and Alzheimer's disease. Sci Rep 2024; 14:5385. [PMID: 38443419 DOI: 10.1038/s41598-024-55439-1] [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: 09/06/2023] [Accepted: 02/23/2024] [Indexed: 03/07/2024] Open
Abstract
Alzheimer's disease (AD) is the most common type of dementia with millions of affected patients worldwide. Currently, there is still no cure and AD is often diagnosed long time after onset because there is no clear diagnosis. Thus, it is essential to study the physiology and pathogenesis of AD, investigating the risk factors that could be strongly connected to the disease onset. Despite AD, like other complex diseases, is the result of the combination of several factors, there is emerging agreement that environmental pollution should play a pivotal role in the causes of disease. In this work, we implemented an Artificial Intelligence model to predict AD mortality, expressed as Standardized Mortality Ratio, at Italian provincial level over 5 years. We employed a set of publicly available variables concerning pollution, health, society and economy to feed a Random Forest algorithm. Using methods based on eXplainable Artificial Intelligence (XAI) we found that air pollution (mainly O 3 and N O 2 ) contribute the most to AD mortality prediction. These results could help to shed light on the etiology of Alzheimer's disease and to confirm the urgent need to further investigate the relationship between the environment and the disease.
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Affiliation(s)
- Alessandro Fania
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
| | - Alfonso Monaco
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy.
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy.
| | - Nicola Amoroso
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
- Dipartimento di Farmacia - Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125, Bari, Italy
| | - Loredana Bellantuono
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
- Dipartimento di Biomedicina Traslazionale e Neuroscienze (DiBraiN), Università degli Studi di Bari Aldo Moro, 70124, Bari, Italy
| | - Roberto Cazzolla Gatti
- Department of Biological Sciences, Geological and Environmental (BiGeA), Alma Mater Studiorum - University of Bologna, 40126, Bologna, Italy
| | - Najada Firza
- Dipartimento di Economia e Finanza, Università degli Studi di Bari Aldo Moro, 70124, Bari, Italy
- Catholic University Our Lady of Good Counsel, 1031, Tirana, Albania
| | - Antonio Lacalamita
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
| | - Ester Pantaleo
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
| | - Sabina Tangaro
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
- Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università degli Studi di Bari Aldo Moro, 70126, Bari, Italy
| | | | - Roberto Bellotti
- Dipartimento Interateneo di Fisica M. Merlin, Universitá degli Studi di Bari Aldo Moro, 70125, Bari, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Bari, 70125, Bari, Italy
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Ge R, Wang Y, Zhang Z, Sun H, Chang J. Association of long-term exposure to various ambient air pollutants, lifestyle, and genetic predisposition with incident cognitive impairment and dementia. BMC Public Health 2024; 24:179. [PMID: 38225615 PMCID: PMC10788974 DOI: 10.1186/s12889-024-17702-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: 11/23/2023] [Accepted: 01/08/2024] [Indexed: 01/17/2024] Open
Abstract
BACKGROUND Long-term exposure to air pollution has been found to contribute to the development of cognitive decline. Our study aimed to assess the association between various air pollutants and cognitive impairment and dementia. Additionally, explore the modification effects of lifestyle and genetic predisposition. METHODS The exposure levels to various air pollutants, including particulate matter (PM) with diameters ≤ 2.5 (PM2.5), ≤ 10 (PM10), and between 2.5 and 10 μm (PM2.5-10) and nitrogen oxides (NO and NO2) were identified. An air pollution score (APS) was calculated to evaluate the combined exposure to these five air pollutants. A genetic risk estimate and healthy lifestyle score (HLS) were also generated. The Cox regression model adjusted by potential confounders was adopted to access the association between pollution exposure and cognitive decline, and several sensitivity analyses were additionally conducted to test the robustness. RESULTS The combined exposure to air pollutants was associated with an increased risk of incident cognitive decline. Compared with the low exposure group, the hazard ratio (HR) and 95% confidence interval (CI) for all-cause dementia, Alzheimer's dementia, vascular dementia, and mild cognitive impairment (MCI) in those exposed to the highest levels of air pollutants were respectively 1.07 (95% CI: 1.04 to 1.09), 1.08 (95% CI: 1.04 to 1.12), 1.07 (95% CI: 1.02 to 1.13), and 1.19 (95% CI: 1.12 to 1.27). However, the modification effects from genetic predisposition were not widely observed, while on the contrary for the healthy lifestyle. Our findings were proven to be reliable and robust based on the results of sensitivity analyses. CONCLUSIONS Exposure to air pollution was found to be a significant contributing factor to cognitive impairment and dementia, and this association was not easily modified by an individual's genetic predisposition. However, adopting a healthy lifestyle may help to manage the risk of cognitive decline related to air pollution.
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Affiliation(s)
- Rongguang Ge
- School of Public Health, Suzhou Medical College, Soochow University, 199 Renai Road, Suzhou, Jiangsu, 215123, China
- Department of Neurology, Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215004, China
| | - Yue Wang
- School of Public Health, Suzhou Medical College, Soochow University, 199 Renai Road, Suzhou, Jiangsu, 215123, China
| | - Zengli Zhang
- School of Public Health, Suzhou Medical College, Soochow University, 199 Renai Road, Suzhou, Jiangsu, 215123, China
| | - Hongpeng Sun
- School of Public Health, Suzhou Medical College, Soochow University, 199 Renai Road, Suzhou, Jiangsu, 215123, China.
| | - Jie Chang
- School of Public Health, Suzhou Medical College, Soochow University, 199 Renai Road, Suzhou, Jiangsu, 215123, China.
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Wang X, Salminen LE, Petkus AJ, Driscoll I, Millstein J, Beavers DP, Espeland MA, Erus G, Braskie MN, Thompson PM, Gatz M, Chui HC, Resnick SM, Kaufman JD, Rapp SR, Shumaker S, Brown M, Younan D, Chen JC. Association between late-life air pollution exposure and medial temporal lobe atrophy in older women. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.28.23298708. [PMID: 38077091 PMCID: PMC10705610 DOI: 10.1101/2023.11.28.23298708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Background Ambient air pollution exposures increase risk for Alzheimer's disease (AD) and related dementias, possibly due to structural changes in the medial temporal lobe (MTL). However, existing MRI studies examining exposure effects on the MTL were cross-sectional and focused on the hippocampus, yielding mixed results. Method To determine whether air pollution exposures were associated with MTL atrophy over time, we conducted a longitudinal study including 653 cognitively unimpaired community-dwelling older women from the Women's Health Initiative Memory Study with two MRI brain scans (MRI-1: 2005-6; MRI-2: 2009-10; Mage at MRI-1=77.3±3.5years). Using regionalized universal kriging models, exposures at residential locations were estimated as 3-year annual averages of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) prior to MRI-1. Bilateral gray matter volumes of the hippocampus, amygdala, parahippocampal gyrus (PHG), and entorhinal cortex (ERC) were summed to operationalize the MTL. We used linear regressions to estimate exposure effects on 5-year volume changes in the MTL and its subregions, adjusting for intracranial volume, sociodemographic, lifestyle, and clinical characteristics. Results On average, MTL volume decreased by 0.53±1.00cm3 over 5 years. For each interquartile increase of PM2.5 (3.26μg/m3) and NO2 (6.77ppb), adjusted MTL volume had greater shrinkage by 0.32cm3 (95%CI=[-0.43, -0.21]) and 0.12cm3 (95%CI=[-0.22, -0.01]), respectively. The exposure effects did not differ by APOE ε4 genotype, sociodemographic, and cardiovascular risk factors, and remained among women with low-level PM2.5 exposure. Greater PHG atrophy was associated with higher PM2.5 (b=-0.24, 95%CI=[-0.29, -0.19]) and NO2 exposures (b=-0.09, 95%CI=[-0.14, -0.04]). Higher exposure to PM2.5 but not NO2 was also associated with greater ERC atrophy. Exposures were not associated with amygdala or hippocampal atrophy. Conclusion In summary, higher late-life PM2.5 and NO2 exposures were associated with greater MTL atrophy over time in cognitively unimpaired older women. The PHG and ERC - the MTL cortical subregions where AD neuropathologies likely begin, may be preferentially vulnerable to air pollution neurotoxicity.
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Affiliation(s)
- Xinhui Wang
- Department of Neurology, University of Southern California, Los Angeles, California
| | - Lauren E Salminen
- Department of Neurology, University of Southern California, Los Angeles, California
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Andrew J Petkus
- Department of Neurology, University of Southern California, Los Angeles, California
| | - Ira Driscoll
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin
| | - Joshua Millstein
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California
| | - Daniel P Beavers
- Departments of Statistical Sciences, Wake Forest University, Winston-Salem, North Carolina
| | - Mark A Espeland
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Department of Biostatistics and Data Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Guray Erus
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, Pennsylvania
| | - Meredith N Braskie
- Department of Neurology, University of Southern California, Los Angeles, California
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Paul M Thompson
- Department of Neurology, University of Southern California, Los Angeles, California
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Margaret Gatz
- Center for Economic and Social Research, University of Southern California, Los Angeles, California
| | - Helena C Chui
- Department of Neurology, University of Southern California, Los Angeles, California
| | - Susan M Resnick
- The Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland
| | - Joel D Kaufman
- Departments of Environmental & Occupational Health Sciences, Medicine (General Internal Medicine), and Epidemiology, University of Washington, Seattle, Washington
| | - Stephen R Rapp
- Departments of Psychiatry and Behavioral Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Sally Shumaker
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Mark Brown
- Department of Biostatistics and Data Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Diana Younan
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California
| | - Jiu-Chiuan Chen
- Department of Neurology, University of Southern California, Los Angeles, California
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, California
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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: 0] [Impact Index Per Article: 0] [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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Hou K, Xu X. Ambient temperatures associated with reduced cognitive function in older adults in China. Sci Rep 2023; 13:17414. [PMID: 37833389 PMCID: PMC10575877 DOI: 10.1038/s41598-023-44776-2] [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: 07/19/2023] [Accepted: 10/12/2023] [Indexed: 10/15/2023] Open
Abstract
The cognitive function status of older adults determines the social function and living quality of older adults, which is related to the healthy development and stability of the society. However, the impact of high or low ambient temperature on cognitive function in older adults remains unclear. Based on data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), we comprehensively assessed the impact of ambient temperature on the cognitive function of older adults in this study. The findings exhibited that for each 1 °C ascent in monthly temperature of high temperature, the examination score of global cognitive function of older adults decreased by 0.48 (95% CI 0.21-0.74), which was greater than that of 0.14 (95% CI 0.06-0.25) for each 1 °C reduction in low temperature. Overall, the detrimental effect of high temperature on cognitive function in older adults was more significant than that of low temperature, including on the five sub-cognitive functions involved. Our research provides vital technical guidance and reference for the health protection and prevention of cognitive function of older adults in specific external environmental conditions under the current climatic variation and temperature rise.
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Affiliation(s)
- Kun Hou
- School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
| | - Xia Xu
- Jiangsu Province Hydrology and Water Resources Investigation Bureau, Nanjing, 210029, China
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Urbano T, Chiari A, Malagoli C, Cherubini A, Bedin R, Costanzini S, Teggi S, Maffeis G, Vinceti M, Filippini T. Particulate matter exposure from motorized traffic and risk of conversion from mild cognitive impairment to dementia: An Italian prospective cohort study. ENVIRONMENTAL RESEARCH 2023; 222:115425. [PMID: 36740156 DOI: 10.1016/j.envres.2023.115425] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Based on epidemiologic and laboratory studies, exposure to air pollutants has been linked to many adverse health effects including a higher risk of dementia. In this study, we aimed to evaluate the effect of long-term exposure to outdoor air pollution on risk of conversion to dementia in a cohort of subjects with mild cognitive impairment (MCI). METHODS We recruited 53 Italian subjects newly-diagnosed with MCI. Within a geographical information system, we assessed recent outdoor air pollutant exposure, by modeling air levels of particulate matter with equivalent aerodynamic diameter ≤10 μm (PM10) from motorized traffic at participants' residence. We investigated the relation of PM10 concentrations to subsequent conversion from MCI to any type of dementia. Using a Cox-proportional hazards model combined with a restricted cubic spline model, we computed the hazard ratio (HR) of dementia with its 95% confidence interval (CI) according to increasing PM10 exposure, adjusting for sex, age, and educational attainment. RESULTS During a median follow up of 47.3 months, 34 participants developed dementia, in 26 cases diagnosed as Alzheimer's dementia. In non-linear restricted spline regression analysis, mean and maximum annual PM10 levels positively correlated with cerebrospinal fluid total and phosphorylated tau proteins concentrations, while they were inversely associated with β-amyloid. Concerning the risk of dementia, we found a positive association starting from above 10 μg/m3 for mean PM10 levels and above 35 μg/m3 for maximum PM10 levels. Specific estimates for Alzheimer's dementia were substantially similar. Adding other potential confounders to the multivariable model or removing early cases of dementia onset during the follow-up had little effect on the estimates. CONCLUSIONS Our findings suggest that exposure to outdoor air pollutants, PM10 in particular, may non-linearly increase conversion from MCI to dementia above a certain ambient air concentration.
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Affiliation(s)
- Teresa Urbano
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Annalisa Chiari
- Neurology Unit, University Hospital of Modena, Modena, Italy
| | - Carlotta Malagoli
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), 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; Center for Neurosciences and Neurotechnology, Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Sofia Costanzini
- DIEF - Department of Engineering 'Enzo Ferrari', 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, University of Modena and Reggio Emilia, Modena, Italy; Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
| | - 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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