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      Agricultural activities and risk of Alzheimer’s disease: the TRACTOR project, a nationwide retrospective cohort study

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          Abstract

          Data regarding Alzheimer’s disease (AD) occurrence in farming populations is lacking. This study aimed to investigate whether, among the entire French farm manager (FM) workforce, certain agricultural activities are more strongly associated with AD than others, using nationwide data from the TRACTOR (Tracking and monitoring occupational risks in agriculture) project. Administrative health insurance data (digital electronic health/medical records and insurance claims) for the entire French agricultural workforce, over the period 2002–2016, on the entire mainland France were used to estimate the risk of AD for 26 agricultural activities with Cox proportional hazards model. For each analysis (one for each activity), the exposed group included all FMs that performed the activity of interest (e.g. crop farming), while the reference group included all FMs who did not carry out the activity of interest (e.g. FMs that never farmed crops between 2002 and 2016). There were 5067 cases among 1,036,069 FMs who worked at least one year between 2002 and 2016. Analyses showed higher risks of AD for crop farming (hazard ratio (HR) = 3.72 [3.47–3.98]), viticulture (HR = 1.29 [1.18–1.42]), and fruit arboriculture (HR = 1.36 [1.15–1.62]). By contrast, lower risks of AD were found for several animal farming types, in particular for poultry and rabbit farming (HR = 0.29 [0.20–0.44]), ovine and caprine farming (HR = 0.50 [0.41–0.61]), mixed dairy and cow farming (HR = 0.46 [0.37–0.57]), dairy farming (HR = 0.67 [0.61–0.73]), and pig farming (HR = 0.30 [0.18–0.52]). This study shed some light on the association between a wide range of agricultural activities and AD in the entire French FMs population.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s10654-023-01079-0.

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          NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

          In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.
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            Preclinical Alzheimer's disease: Definition, natural history, and diagnostic criteria.

            During the past decade, a conceptual shift occurred in the field of Alzheimer's disease (AD) considering the disease as a continuum. Thanks to evolving biomarker research and substantial discoveries, it is now possible to identify the disease even at the preclinical stage before the occurrence of the first clinical symptoms. This preclinical stage of AD has become a major research focus as the field postulates that early intervention may offer the best chance of therapeutic success. To date, very little evidence is established on this "silent" stage of the disease. A clarification is needed about the definitions and lexicon, the limits, the natural history, the markers of progression, and the ethical consequence of detecting the disease at this asymptomatic stage. This article is aimed at addressing all the different issues by providing for each of them an updated review of the literature and evidence, with practical recommendations.
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              Comprehensive Review on Alzheimer’s Disease: Causes and Treatment

              Alzheimer’s disease (AD) is a disorder that causes degeneration of the cells in the brain and it is the main cause of dementia, which is characterized by a decline in thinking and independence in personal daily activities. AD is considered a multifactorial disease: two main hypotheses were proposed as a cause for AD, cholinergic and amyloid hypotheses. Additionally, several risk factors such as increasing age, genetic factors, head injuries, vascular diseases, infections, and environmental factors play a role in the disease. Currently, there are only two classes of approved drugs to treat AD, including inhibitors to cholinesterase enzyme and antagonists to N-methyl d-aspartate (NMDA), which are effective only in treating the symptoms of AD, but do not cure or prevent the disease. Nowadays, the research is focusing on understanding AD pathology by targeting several mechanisms, such as abnormal tau protein metabolism, β-amyloid, inflammatory response, and cholinergic and free radical damage, aiming to develop successful treatments that are capable of stopping or modifying the course of AD. This review discusses currently available drugs and future theories for the development of new therapies for AD, such as disease-modifying therapeutics (DMT), chaperones, and natural compounds.
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                Author and article information

                Contributors
                pascal.petit@univ-grenoble-alpes.fr
                Journal
                Eur J Epidemiol
                Eur J Epidemiol
                European Journal of Epidemiology
                Springer Netherlands (Dordrecht )
                0393-2990
                1573-7284
                10 January 2024
                10 January 2024
                2024
                : 39
                : 3
                : 271-287
                Affiliations
                [1 ]GRID grid.450307.5, ISNI 0000 0001 0944 2786, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, CHU Grenoble Alpes, TIMC, , Univ. Grenoble Alpes, ; 38000 Grenoble, France
                [2 ]GRID grid.410529.b, ISNI 0000 0001 0792 4829, Present Address: Centre Régional de Pathologies Professionnelles et Environnementales, , CHU Grenoble Alpes, ; 38000 Grenoble, France
                [3 ]Present Address: AGEIS, Univ. Grenoble Alpes, ( https://ror.org/02rx3b187) 38000 Grenoble, France
                [4 ]GRID grid.410529.b, ISNI 0000 0001 0792 4829, Centre Mémoire de Ressources et de Recherche, , CHU Grenoble Alpes, ; 38000 Grenoble, France
                [5 ]GRID grid.462771.1, ISNI 0000 0004 0410 8799, Laboratoire de Psychologie et Neurocognition, UMR 5105, CNRS, LPNC, , Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, ; 38000 Grenoble, France
                Author information
                http://orcid.org/0000-0001-9015-5230
                http://orcid.org/0000-0002-2267-3420
                http://orcid.org/0000-0003-3778-1245
                http://orcid.org/0000-0002-7004-8777
                http://orcid.org/0000-0001-5551-7929
                http://orcid.org/0000-0003-2353-7102
                Article
                1079
                10.1007/s10654-023-01079-0
                10995077
                38195954
                a84c10d5-93bf-465d-938a-930167912345
                © The Author(s) 2023, corrected publication 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 January 2023
                : 2 November 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100021790, Fondation pour la Recherche sur Alzheimer;
                Award ID: 2020-A-01
                Funded by: MIAI@Grenoble Alpes
                Award ID: ANR-19-P3IA-0003
                Funded by: FundRef http://dx.doi.org/10.13039/501100001665, Agence Nationale de la Recherche;
                Award ID: ANR-10-AIRT-05
                Award ID: ANR-15-IDEX-02
                Categories
                Neuro-Epidemiology
                Custom metadata
                © Pietro Paolo Sanna 2024

                Public health
                administrative health database,digital electronic health/medical record,insurance claims,agriculture,farming,alzheimer’s disease,dementia,health surveillance,occupational activity,big data,data mining,cohort,epidemiology,population-based,nationwide,france,europe

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