A Workshop on Cognitive Aging and Impairment in the 9/11-Exposed Population
Abstract
:1. Introduction
2. Materials and Methods
- What is the evidence of causal associations between 9/11 exposure, PTSD, and the risk of adverse cognitive function?
- What is the potential health burden from MCI?
- What are the research gaps?
- What steps are needed to manage MCI risks and improve care?
3. Results
3.1. Session I: The Natural History of Cognitive Aging and Impairment
- Both dementia and MCI represent clinically observed significant declines in previously addressed cognitive function; the primary difference being impairment severity.
- The prevalence of MCI is significant, ranging from 4% to 19% of persons aged 65 or older.
- Approximately 40% of dementia is believed attributable to twelve modifiable risk factors: lower educational attainment, hypertension, obesity, hearing loss, depression, diabetes, physical inactivity, smoking, social isolation, traumatic brain injury, excess alcohol consumption, and air pollution.
- Causes of MCI are varied and have different impacts (e.g., clinical profile, trajectory of decline, interaction with neurodegenerative disease, and success of preventions and interventions).
- The effects of MCI and/or dementia on cognitive domains overlap, making it difficult to robustly define patterns of cognition.
3.2. Session II: Novel Identifiable Markers in the Pathway of Neurodegenerative Disease
- A framework comprising imaging and cerebrospinal fluid (CSF) biomarkers that are grouped by three pathologic processes of amyloid, tauopathy, and neurodegeneration/injury is recommended for brain aging research.
- Positron emission tomography (PET) has been used to measure neuroinflammation, a proposed pathogenic contributor to Alzheimer’s disease and other cognitive disorders, but only one reliable biomarker has been identified thus far.
- Emerging plasma or serum-based biomarkers offer a lower-cost, less-invasive alternative to imaging and CSF. These peripheral markers provide a measure of severity but do not indicate the location of the effect.
3.2.1. Neuroimaging
3.2.2. Biomarker Research Framework
3.2.3. Other Potential Biomarkers
3.3. Session III: Neuropathological Changes Associated with Hazardous Exposures and Brain Aging
- Exposures potentially associated with neuropathological changes include air pollution and some of its components, toxic emissions from burn pits and other warzone exposures, head trauma, and stress-related disorders (e.g., PTSD).
- Potential neurodegenerative mechanisms associated with air pollution exposures are neuroinflammatory responses, microglial activation, oxidative stress, and disrupted Aβ homeostasis, among others.
- At present, a pathological distinction between dust exposure-induced and stress-induced cognitive decline is not apparent.
- Toxic exposures experienced by World Trade Center responders may well be similar to those experienced by US veterans exposed to burn pits in Iraq and Afghanistan.
- Soldiers with mild traumatic brain injury associated with loss of consciousness also commonly have PTSD, with such co-occurrence reported at 44% in one study.
3.3.1. Air Pollution
3.3.2. Warzone Exposures
3.3.3. Head Trauma
3.3.4. PTSD
3.3.5. Biological Aging
3.4. Session IV: Cognitive Decline and Impairment in the 9/11-Exposed Population
- The 9/11-affected population is entering a time when aging is becoming more clinically significant.
- Epidemiologic data suggest an increased risk of cognitive impairment and functional limitations among persons directly affected by the terrorist attacks. However, most studies have been cross sectional and thus provide limited information on cause and effect.
- Mechanisms of WTC-related cognitive impairment remain elusive. A suggested mode of action is through PTSD and/or major depression. Exposure to WTC dust and particulate matter has also been suggested; however, there is less evidence supporting this pathway.
- Neuroimaging of WTC responders with cognitive impairment revealed patterns of reduced cortical thickness that were largely inconsistent with those for known neurodegenerative diseases.
- Research clarifying the causal pathway(s) may lead to more effective interventions and improvements in patient care.
3.4.1. General Responder Studies
Biomarker and Neuroimaging Studies
3.4.2. FDNY Firefighter/EMS Studies
3.4.3. WTC Health Registry Enrollees
3.5. Session V: Clinical Perspectives
- There are currently no proven interventions to reduce the risk, delay the onset, or slow the progression of MCI.
- Optimization of the management of associated comorbidities, including PTSD and hypertension, may be important in reducing the risk of MCI.
- Lifestyle modifications are proven strategies to improve overall well-being, health, and aging.
- Cognitive training is a promising tool for prevention and treatment of MCI and dementia, with clinically meaningful effects beyond cognition including other aspects of well-being.
- Reduce hypertension risk in the entire population.
- Encourage social, cognitive, and physical activity.
- Scrutinize the risks for hearing loss throughout the life course of WTCHP members.
- Reduce tobacco and alcohol use.
- Treating hypertension and aim for systolic blood pressure <130 mm Hg in midlife;
- Promoting the use of hearing aids for hearing loss;
- Avoiding drinking 21 or more units of alcohol per week;
- Preventing head trauma;
- Smoking cessation;
- Reducing obesity and the linked condition of diabetes by healthy food availability;
- Sustaining midlife, and late-life physical activity.
3.5.1. Lifestyle Modifications
3.5.2. Pharmacologic Interventions
3.5.3. Cognitive Training
3.6. Session VI: Monitoring and Surveillance
4. Discussion
- Cognitive Resilience and Impairment: Projects that describe the characteristic features of cognitive impairment in 9/11-exposed individuals and its progression and identify factors that influence the maintenance of cognitive performance or cognitive resilience in the face of environmental exposure and psychological trauma.
- Early Identification of Cognitive Decline: Projects that examine changes in non-cognitive domains (e.g., gait, audition, emotional expression, reactivity, and olfaction) that may serve as early markers of neurodegeneration.
- Pathophysiology of Cognitive Decline: Projects that focus on the neurobiological mechanisms underlying shifts in the nature and progression (trajectories) of age-related cognitive decline or cognitive impairment.
- Impact of Life Stressors on Cognition: Studies of association between individual and combined childhood and adulthood life stressors (adversity) on cognition in aging.
- Alzheimer’s Disease: Projects that examine the impact and trajectories of Alzheimer’s disease or Alzheimer’s disease-related dementias (AD/ADRD) among WTCHP members.
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Disclaimer
References
- Clouston, S.A.; Kotov, R.; Pietrzak, R.H.; Luft, B.J.; Gonzalez, A.; Richards, M.; Ruggero, C.J.; Spiro, A., 3rd; Bromet, E.J. Cognitive impairment among World Trade Center responders: Long-term implications of re-experiencing the 9/11 terrorist attacks. Alzheimers Dement. 2016, 4, 67–75. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Singh, A.; Zeig-Owens, R.; Hall, C.B.; Liu, Y.; Rabin, L.; Schwartz, T.; Webber, M.P.; Appel, D.; Prezant, D.J. World Trade Center exposure, post-traumatic stress disorder, and subjective cognitive concerns in a cohort of rescue/recovery workers. Acta Psychiatry Scand. 2020, 141, 275–284. [Google Scholar] [CrossRef] [PubMed]
- Clouston, S.; Pietrzak, R.H.; Kotov, R.; Richards, M.; Spiro, A.; Scott, S.; Deri, Y.; Mukherjee, S.; Stewart, C.; Bromet, E.; et al. Traumatic exposures, posttraumatic stress disorder, and cognitive functioning in World Trade Center responders. Alzheimers Dement. Transl. Res. Clin. Interv. 2017, 3, 593–602. [Google Scholar] [CrossRef] [PubMed]
- Clouston, S.A.P.; Deri, Y.; Diminich, E.; Kew, R.; Kotov, R.; Stewart, C.; Yang, X.; Gandy, S.; Sano, M.; Bromet, E.J.; et al. Posttraumatic stress disorder and total amyloid burden and amyloid-β 42/40 ratios in plasma: Results from a pilot study of World Trade Center responders. Alzheimers Dement. Diagn. Assess. Dis. Monit. 2019, 11, 216–220. [Google Scholar] [CrossRef] [PubMed]
- Clouston, S.A.P.; Diminich, E.D.; Kotov, R.; Pietrzak, R.H.; Richards, M.; Spiro, A., 3rd; Deri, Y.; Carr, M.; Yang, X.; Gandy, S.; et al. Incidence of mild cognitive impairment in World Trade Center responders: Long-term consequences of re-experiencing the events on 9/11/2001. Alzheimers Dement. 2019, 11, 628–636. [Google Scholar] [CrossRef]
- Nasreddine, Z.S.; Phillips, N.A.; Bédirian, V.; Charbonneau, S.; Whitehead, V.; Collin, I.; Cummings, J.L.; Chertkow, H. The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. J. Am. Geriatr. Soc. 2005, 53, 695–699. [Google Scholar] [CrossRef] [PubMed]
- Schuitevoerder, S.; Rosen, J.W.; Twamley, E.W.; Ayers, C.R.; Sones, H.; Lohr, J.B.; Goetter, E.M.; Fonzo, G.A.; Holloway, K.J.; Thorp, S.R. A meta-analysis of cognitive functioning in older adults with PTSD. J. Anxiety Disord. 2013, 27, 550–558. [Google Scholar] [CrossRef] [PubMed]
- Veitch, D.P.; Friedl, K.E.; Weiner, M.W. Military risk factors for cognitive decline, dementia and Alzheimer’s disease. Curr. Alzheimer Res. 2013, 10, 907–930. [Google Scholar] [CrossRef] [PubMed]
- Liu, B.; Tarigan, L.H.; Bromet, E.J.; Kim, H. World Trade Center disaster exposure-related probable posttraumatic stress disorder among responders and civilians: A meta-analysis. PLoS ONE 2014, 9, e101491. [Google Scholar] [CrossRef] [Green Version]
- Block, M.L.; Calderón-Garcidueñas, L. Air pollution: Mechanisms of neuroinflammation and CNS disease. Trends Neurosci. 2009, 32, 506–516. [Google Scholar] [CrossRef] [Green Version]
- Calderon-Garciduenas, L.; Solt, A.C.; Henriquez-Roldan, C.; Torres-Jardon, R.; Nuse, B.; Herritt, L.; Villarreal-Calderon, R.; Osnaya, N.; Stone, I.; Garcia, R.; et al. Long-term air pollution exposure is associated with neuroinflammation, an altered innate immune response, disruption of the blood-brain barrier, ultrafine particulate deposition, and accumulation of amyloid beta-42 and alpha-synuclein in children and young adults. Toxicol. Pathol. 2008, 36, 289–310. [Google Scholar]
- Weuve, J.; Puett, R.C.; Schwartz, J.; Yanosky, J.D.; Laden, F.; Grodstein, F. Exposure to particulate air pollution and cognitive decline in older women. Arch. Intern. Med. 2012, 172, 219–227. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Calderón-Garcidueñas, L.; Mora-Tiscareño, A.; Ontiveros, E.; Gómez-Garza, G.; Barragán-Mejía, G.; Broadway, J.; Chapman, S.; Valencia-Salazar, G.; Jewells, V.; Maronpot, R.R.; et al. Air pollution, cognitive deficits and brain abnormalities: A pilot study with children and dogs. Brain Cogn. 2008, 68, 117–127. [Google Scholar] [CrossRef] [PubMed]
- Chen, J.C.; Schwartz, J. Neurobehavioral effects of ambient air pollution on cognitive performance in US adults. Neurotoxicology 2009, 30, 231–239. [Google Scholar] [CrossRef]
- Tonne, C.; Elbaz, A.; Beevers, S.; Singh-Manoux, A. Traffic-related air pollution in relation to cognitive function in older adults. Epidemiology 2014, 25, 674–681. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Shou, Y.; Zhu, X.; Zhu, D.; Yin, H.; Shi, Y.; Chen, M.; Lu, L.; Qian, Q.; Zhao, D.; Hu, Y.; et al. Ambient PM2.5 chronic exposure leads to cognitive decline in mice: From pulmonary to neuronal inflammation. Toxicol. Lett. 2020, 331, 208–217. [Google Scholar] [CrossRef]
- Morgan, T.E.; Davis, D.A.; Iwata, N.; Tanner, J.A.; Snyder, D.; Ning, Z.; Kam, W.; Hsu, Y.T.; Winkler, J.W.; Chen, J.C.; et al. Glutamatergic neurons in rodent models respond to nanoscale particulate urban air pollutants in vivo and in vitro. Environ. Health Perspect. 2011, 119, 1003–1009. [Google Scholar] [CrossRef] [PubMed]
- Santiago-Colón, A.; Daniels, R.; Reissman, D.; Anderson, K.; Calvert, G.; Caplan, A.; Carreón, T.; Katruska, A.; Kubale, T.; Liu, R.; et al. World Trade Center health program: First decade of research. Int. J. Environ. Res. Public Health 2020, 17, 7290. [Google Scholar] [CrossRef]
- Boyle, P.A.; Wilson, R.S.; Yu, L.; Barr, A.M.; Honer, W.G.; Schneider, J.A.; Bennett, D.A. Much of late life cognitive decline is not due to common neurodegenerative pathologies. Ann. Neurol. 2013, 74, 478–489. [Google Scholar] [CrossRef] [Green Version]
- Malek-Ahmadi, M. Reversion from mild cognitive impairment to normal cognition: A meta-analysis. Alzheimer Dis. Assoc. Disord. 2016, 30, 324–330. [Google Scholar] [CrossRef]
- Aerts, L.; Heffernan, M.; Kochan, N.A.; Crawford, J.D.; Draper, B.; Trollor, J.N.; Sachdev, P.S.; Brodaty, H. Effects of MCI subtype and reversion on progression to dementia in a community sample. Neurology 2017, 88, 2225–2232. [Google Scholar] [CrossRef] [PubMed]
- Roberts, R.O.; Knopman, D.S.; Mielke, M.M.; Cha, R.H.; Pankratz, V.S.; Christianson, T.J.H.; Geda, Y.E.; Boeve, B.F.; Ivnik, R.J.; Tangalos, E.G.; et al. Higher risk of progression to dementia in mild cognitive impairment cases who revert to normal. Neurology 2014, 82, 317–325. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Petersen, R.C.; Doody, R.; Kurz, A.; Mohs, R.C.; Morris, J.C.; Rabins, P.V.; Ritchie, K.; Rossor, M.; Thal, L.; Winblad, B. Current concepts in mild cognitive impairment. Arch. Neurol. 2001, 58, 1985–1992. [Google Scholar] [CrossRef] [PubMed]
- Livingston, G.; Sommerlad, A.; Orgeta, V.; Costafreda, S.G.; Huntley, J.; Ames, D.; Ballard, C.; Banerjee, S.; Burns, A.; Cohen-Mansfield, J.; et al. Dementia prevention, intervention, and care. Lancet 2017, 390, 2673–2734. [Google Scholar] [CrossRef] [Green Version]
- Winblad, B.; Palmer, K.; Kivipelto, M.; Jelic, V.; Fratiglioni, L.; Wahlund, L.O.; Nordberg, A.; Bäckman, L.; Albert, M.; Almkvist, O.; et al. Mild cognitive impairment—Beyond controversies, towards a consensus: Report of the International Working Group on mild cognitive impairment. J. Intern. Med. 2004, 256, 240–246. [Google Scholar] [CrossRef] [PubMed]
- Jack, C.R., Jr.; Bennett, D.A.; Blennow, K.; Carrillo, M.C.; Dunn, B.; Haeberlein, S.B.; Holtzman, D.M.; Jagust, W.; Jessen, F.; Karlawish, J.; et al. NIA-AA research framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018, 14, 535–562. [Google Scholar] [CrossRef]
- Glymour, M.M.; Brickman, A.M.; Kivimaki, M.; Mayeda, E.R.; Chêne, G.; Dufouil, C.; Manly, J.J. Will biomarker-based diagnosis of Alzheimer’s disease maximize scientific progress? Evaluating proposed diagnostic criteria. Eur. J. Epidemiol. 2018, 33, 607–612. [Google Scholar] [CrossRef] [Green Version]
- Blennow, K.; Mattsson, N.; Schöll, M.; Hansson, O.; Zetterberg, H. Amyloid biomarkers in Alzheimer’s disease. Trends Pharmacol. Sci. 2015, 36, 297–309. [Google Scholar] [CrossRef]
- Hansson, O.; Zetterberg, H.; Buchhave, P.; Londos, E.; Blennow, K.; Minthon, L. Association between CSF biomarkers and incipient Alzheimer’s disease in patients with mild cognitive impairment: A follow-up study. Lancet Neurol. 2006, 5, 228–234. [Google Scholar] [CrossRef] [Green Version]
- Mattsson, N.; Zetterberg, H.; Hansson, O.; Andreasen, N.; Parnetti, L.; Jonsson, M.; Herukka, S.K.; van der Flier, W.M.; Blankenstein, M.A.; Ewers, M.; et al. CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. J. Am. Med. Assoc. 2009, 302, 385–393. [Google Scholar] [CrossRef]
- Livingston, G.; Huntley, J.; Sommerlad, A.; Ames, D.; Ballard, C.; Banerjee, S.; Brayne, C.; Burns, A.; Cohen-Mansfield, J.; Cooper, C.; et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet 2020, 396, 413–446. [Google Scholar] [CrossRef]
- Jack, C.R., Jr.; Bennett, D.A.; Blennow, K.; Carrillo, M.C.; Feldman, H.H.; Frisoni, G.B.; Hampel, H.; Jagust, W.J.; Johnson, K.A.; Knopman, D.S.; et al. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology 2016, 87, 539–547. [Google Scholar] [CrossRef] [PubMed]
- Mattsson, N.; Andreasson, U.; Zetterberg, H.; Blennow, K.; Weiner, M.W.; Aisen, P.; Toga, A.W.; Petersen, R.; Jack, C.R., Jr.; Jagust, W.; et al. Association of plasma neurofilament light with neurodegeneration in patients with Alzheimer disease. JAMA Neurol. 2017, 74, 557–566. [Google Scholar] [CrossRef] [PubMed]
- Hanon, O.; Vidal, J.S.; Lehmann, S.; Bombois, S.; Allinquant, B.; Tréluyer, J.M.; Gelé, P.; Delmaire, C.; Blanc, F.; Mangin, J.F.; et al. Plasma amyloid levels within the Alzheimer’s process and correlations with central biomarkers. Alzheimers Dement. 2018, 14, 858–868. [Google Scholar] [CrossRef]
- Tsai, C.L.; Liang, C.S.; Yang, C.P.; Lee, J.T.; Ho, T.H.; Su, M.W.; Lin, G.Y.; Lin, Y.K.; Chu, H.T.; Hsu, Y.W.; et al. Indicators of rapid cognitive decline in amnestic mild cognitive impairment: The role of plasma biomarkers using magnetically labeled immunoassays. J. Psychiatr. Res. 2020, 129, 66–72. [Google Scholar] [CrossRef]
- Song, F.; Poljak, A.; Valenzuela, M.; Mayeux, R.; Smythe, G.A.; Sachdev, P.S. Meta-analysis of plasma amyloid-β levels in alzheimer’s disease. J. Alzheimers Dis. 2011, 26, 365–375. [Google Scholar] [CrossRef] [Green Version]
- Chen, T.B.; Lee, Y.J.; Lin, S.Y.; Chen, J.P.; Hu, C.J.; Wang, P.N.; Cheng, I.H. Plasma Aβ42 and total tau predict cognitive decline in amnestic mild cognitive impairment. Sci. Rep. 2019, 9, 13984. [Google Scholar] [CrossRef] [Green Version]
- Mattsson, N.; Cullen, N.C.; Andreasson, U.; Zetterberg, H.; Blennow, K. Association between longitudinal plasma neurofilament light and neurodegeneration in patients with Alzheimer Disease. JAMA Neurol. 2019, 76, 791–799. [Google Scholar] [CrossRef]
- Mielke, M.M.; Hagen, C.E.; Xu, J.; Chai, X.; Vemuri, P.; Lowe, V.J.; Airey, D.C.; Knopman, D.S.; Roberts, R.O.; Machulda, M.M.; et al. Plasma phospho-tau181 increases with Alzheimer’s disease clinical severity and is associated with tau- and amyloid-positron emission tomography. Alzheimers Dement. 2018, 14, 989–997. [Google Scholar] [CrossRef]
- Karikari, T.K.; Pascoal, T.A.; Ashton, N.J.; Janelidze, S.; Benedet, A.L.; Rodriguez, J.L.; Chamoun, M.; Savard, M.; Kang, M.S.; Therriault, J.; et al. Blood phosphorylated tau 181 as a biomarker for Alzheimer’s disease: A diagnostic performance and prediction modelling study using data from four prospective cohorts. Lancet Neurol. 2020, 19, 422–433. [Google Scholar] [CrossRef]
- Janelidze, S.; Mattsson, N.; Palmqvist, S.; Smith, R.; Beach, T.G.; Serrano, G.E.; Chai, X.; Proctor, N.K.; Eichenlaub, U.; Zetterberg, H.; et al. Plasma P-tau181 in Alzheimer’s disease: Relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer’s dementia. Nat. Med. 2020, 26, 379–386. [Google Scholar] [CrossRef]
- Mielke, M.M.; Syrjanen, J.A.; Blennow, K.; Zetterberg, H.; Vemuri, P.; Skoog, I.; Machulda, M.M.; Kremers, W.K.; Knopman, D.S.; Jack, C.; et al. Plasma and CSF neurofilament light: Relation to longitudinal neuroimaging and cognitive measures. Neurology 2019, 93, E252–E260. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hampel, H.; O’Bryant, S.E.; Molinuevo, J.L.; Zetterberg, H.; Masters, C.L.; Lista, S.; Kiddle, S.J.; Batrla, R.; Blennow, K. Blood-based biomarkers for Alzheimer disease: Mapping the road to the clinic. Nat. Rev. Neurol. 2018, 14, 639–652. [Google Scholar] [CrossRef] [PubMed]
- Zetterberg, H.; Blennow, K. From cerebrospinal fluid to blood: The third wave of fluid biomarkers for Alzheimer’s Disease. J. Alzheimers Dis. 2018, 64, S271–S279. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Molinuevo, J.L.; Ayton, S.; Batrla, R.; Bednar, M.M.; Bittner, T.; Cummings, J.; Fagan, A.M.; Hampel, H.; Mielke, M.M.; Mikulskis, A.; et al. Current state of Alzheimer’s fluid biomarkers. Acta Neuropathol. 2018, 136, 821–853. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chen, T.B.; Lai, Y.H.; Ke, T.L.; Chen, J.P.; Lee, Y.J.; Lin, S.Y.; Lin, P.C.; Wang, P.N.; Cheng, I.H. Changes in plasma amyloid and tau in a longitudinal study of normal aging, mild cognitive impairment, and Alzheimer’s Disease. Dement. Geriatr. Cogn. Disord. 2020, 48, 180–195. [Google Scholar] [CrossRef]
- Toledo, J.B.; Vanderstichele, H.; Figurski, M.; Aisen, P.S.; Petersen, R.C.; Weiner, M.W.; Jack, C.R., Jr.; Jagust, W.; Decarli, C.; Toga, A.W.; et al. Factors affecting Aβ plasma levels and their utility as biomarkers in ADNI. Acta Neuropathol. 2011, 122, 401–413. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Donohue, M.C.; Moghadam, S.H.; Roe, A.D.; Sun, C.K.; Edland, S.D.; Thomas, R.G.; Petersen, R.C.; Sano, M.; Galasko, D.; Aisen, P.S.; et al. Longitudinal plasma amyloid beta in Alzheimer’s disease clinical trials. Alzheimers Dement. 2015, 11, 1069–1079. [Google Scholar] [CrossRef] [Green Version]
- Seppälä, T.T.; Herukka, S.K.; Hänninen, T.; Tervo, S.; Hallikainen, M.; Soininen, H.; Pirttilä, T. Plasma Aβ42 and Aβ40 as markers of cognitive change in follow-up: A prospective, longitudinal, population-based cohort study. J. Neurol. Neurosurg. Psychiatry 2010, 81, 1123–1127. [Google Scholar] [CrossRef]
- Hopperton, K.E.; Mohammad, D.; Trépanier, M.O.; Giuliano, V.; Bazinet, R.P. Markers of microglia in post-mortem brain samples from patients with Alzheimer’s disease: A systematic review. Mol. Psychiatry 2018, 23, 177–198. [Google Scholar] [CrossRef]
- Knezevic, D.; Verhoeff, N.P.L.G.; Hafizi, S.; Strafella, A.P.; Graff-Guerrero, A.; Rajji, T.; Pollock, B.G.; Houle, S.; Rusjan, P.M.; Mizrahi, R. Imaging microglial activation and amyloid burden in amnestic mild cognitive impairment. J. Cereb. Blood Flow Metab. 2018, 38, 1885–1895. [Google Scholar] [CrossRef] [PubMed]
- ElAli, A.; Rivest, S. Microglia in Alzheimer’s disease: A multifaceted relationship. Brain Behav. Immun. 2016, 55, 138–150. [Google Scholar] [CrossRef] [PubMed]
- Heneka, M.T.; Carson, M.J.; Khoury, J.E.; Landreth, G.E.; Brosseron, F.; Feinstein, D.L.; Jacobs, A.H.; Wyss-Coray, T.; Vitorica, J.; Ransohoff, R.M.; et al. Neuroinflammation in Alzheimer’s disease. Lancet Neurol. 2015, 14, 388–405. [Google Scholar] [CrossRef] [Green Version]
- Rupprecht, R.; Papadopoulos, V.; Rammes, G.; Baghai, T.C.; Fan, J.; Akula, N.; Groyer, G.; Adams, D.; Schumacher, M. Translocator protein (18 kDa) (TSPO) as a therapeutic target for neurological and psychiatric disorders. Nat. Rev. Drug Discov. 2010, 9, 971–988. [Google Scholar] [CrossRef] [PubMed]
- Bradburn, S.; Murgatroyd, C.; Ray, N. Neuroinflammation in mild cognitive impairment and Alzheimer’s disease: A meta-analysis. Ageing Res. Rev. 2019, 50, 1–8. [Google Scholar] [CrossRef]
- Cisbani, G.; Koppel, A.; Knezevic, D.; Suridjan, I.; Mizrahi, R.; Bazinet, R.P. Peripheral cytokine and fatty acid associations with neuroinflammation in AD and aMCI patients: An exploratory study. Brain Behav. Immun. 2020, 87, 679–688. [Google Scholar] [CrossRef]
- Finch, C.E.; Tanzi, R.E. Genetics of aging. Science 1997, 278, 407–411. [Google Scholar] [CrossRef]
- Mufson, E.J.; Binder, L.; Counts, S.E.; Dekosky, S.T.; Detoledo-Morrell, L.; Ginsberg, S.D.; Ikonomovic, M.D.; Perez, S.E.; Scheff, S.W. Mild cognitive impairment: Pathology and mechanisms. Acta Neuropathol. 2012, 123, 13–30. [Google Scholar] [CrossRef] [Green Version]
- Power, M.C.; Adar, S.D.; Yanosky, J.D.; Weuve, J. Exposure to air pollution as a potential contributor to cognitive function, cognitive decline, brain imaging, and dementia: A systematic review of epidemiologic research. Neurotoxicology 2016, 56, 235–253. [Google Scholar] [CrossRef] [Green Version]
- Block, M.L.; Elder, A.; Auten, R.L.; Bilbo, S.D.; Chen, H.; Chen, J.-C.; Cory-Slechta, D.A.; Costa, D.; Diaz-Sanchez, D.; Dorman, D.C.; et al. The outdoor air pollution and brain health workshop. Neurotoxicology 2012, 33, 972–984. [Google Scholar] [CrossRef] [Green Version]
- Peters, R.; Ee, N.; Peters, J.; Booth, A.; Mudway, I.; Anstey, K.J. Air pollution and dementia: A systematic review. J. Alzheimers Dis. 2019, 70, S145–S163. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fu, P.; Guo, X.; Cheung, F.M.H.; Yung, K.K.L. The association between PM 2.5 exposure and neurological disorders: A systematic review and meta-analysis. Sci. Total Environ. 2019, 655, 1240–1248. [Google Scholar] [CrossRef]
- Heusinkveld, H.J.; Wahle, T.; Campbell, A.; Westerink, R.H.S.; Tran, L.; Johnston, H.; Stone, V.; Cassee, F.R.; Schins, R.P.F. Neurodegenerative and neurological disorders by small inhaled particles. Neurotoxicology 2016, 56, 94–106. [Google Scholar] [CrossRef] [PubMed]
- Moulton, P.V.; Yang, W. Air pollution, oxidative stress, and Alzheimer’s Disease. J. Environ. Public Health 2012, 2012, 472751. [Google Scholar] [CrossRef] [PubMed]
- Cacciottolo, M.; Wang, X.; Driscoll, I.; Woodward, N.; Saffari, A.; Reyes, J.; Serre, M.L.; Vizuete, W.; Sioutas, C.; Morgan, T.E.; et al. Particulate air pollutants, APOE alleles and their contributions to cognitive impairment in older women and to amyloidogenesis in experimental models. Transl. Psychiatry 2017, 7, e1022. [Google Scholar] [CrossRef] [PubMed]
- Santos, C.Y.; Snyder, P.J.; Wu, W.C.; Zhang, M.; Echeverria, A.; Alber, J. Pathophysiologic relationship between Alzheimer’s disease, cerebrovascular disease, and cardiovascular risk: A review and synthesis. Alzheimers Dement. Diagn. Assess. Dis. Monit. 2017, 7, 69–87. [Google Scholar] [CrossRef] [Green Version]
- Loop, M.S.; Kent, S.T.; Al-Hamdan, M.Z.; Crosson, W.L.; Estes, S.M.; Estes, M.G., Jr.; Quattrochi, D.A.; Hemmings, S.N.; Wadley, V.G.; McClure, L.A. Fine particulate matter and incident cognitive impairment in the reasons for geographic and racial differences in stroke (REGARDS) cohort. PLoS ONE 2013, 8, e75001. [Google Scholar] [CrossRef]
- Gatto, N.M.; Henderson, V.W.; Hodis, H.N.; St. John, J.A.; Lurmann, F.; Chen, J.C.; Mack, W.J. Components of air pollution and cognitive function in middle-aged and older adults in Los Angeles. Neurotoxicology 2014, 40, 1–7. [Google Scholar] [CrossRef] [Green Version]
- Landrigan, P.J.; Lioy, P.J.; Thurston, G.; Berkowitz, G.; Chen, L.C.; Chillrud, S.N.; Gavett, S.H.; Georgopoulos, P.G.; Geyh, A.S.; Levin, S.; et al. Health and environmental consequences of the world trade center disaster. Environ. Health Perspect. 2004, 112, 731–739. [Google Scholar] [CrossRef]
- Kritikos, M.; Gandy, S.; Meliker, J.R.; Luft, B.J.; Clouston, S.A.P. Acute versus chronic exposures to inhaled particulate matter and neurocognitive dysfunction: Pathways to Alzheimer’s Disease or a related dementia. J. Alzheimers Dis. 2020, 78, 871–886. [Google Scholar] [CrossRef]
- Institute of Medicine. Chronic Multisymptom Illness in Gulf War Veterans: Case Definitions Reexamined; The National Academies Press: Washington, DC, USA, 2014. [Google Scholar] [CrossRef]
- White, R.F.; Steele, L.; O’Callaghan, J.P.; Sullivan, K.; Binns, J.H.; Golomb, B.A.; Bloom, F.E.; Bunker, J.A.; Crawford, F.; Graves, J.C.; et al. Recent research on Gulf War illness and other health problems in veterans of the 1991 Gulf War: Effects of toxicant exposures during deployment. Cortex 2016, 74, 449–475. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Janulewicz, P.A.; Krengel, M.H.; Maule, A.; White, R.F.; Cirillo, J.; Sisson, E.; Heeren, T.; Sullivan, K. Neuropsychological characteristics of Gulf War illness: A meta-analysis. PLoS ONE 2017, 12, e0177121. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Smith, B.N.; Wang, J.M.; Vogt, D.; Vickers, K.; King, D.W.; King, L.A. Gulf war illness: Symptomatology among veterans 10 years after deployment. J. Occup. Environ. Med. 2013, 55, 104–110. [Google Scholar] [CrossRef] [PubMed]
- Chao, L.L.; Abadjian, L.; Hlavin, J.; Meyerhoff, D.J.; Weiner, M.W. Effects of low-level sarin and cyclosarin exposure and Gulf War Illness on brain structure and function: A study at 4T. Neurotoxicology 2011, 32, 814–822. [Google Scholar] [CrossRef] [PubMed]
- Institute of Medicine. Long-Term Health Consequences of Exposure to Burn Pits in Iraq and Afghanistan; The National Academies Press: Washington, DC, USA, 2011. [Google Scholar] [CrossRef]
- National Academies of Sciences, Engineering, and Medicine. Respiratory Health Effects of Airborne Hazards Exposures in the Southwest Asia Theater of Military Operations; The National Academies Press: Washington, DC, USA, 2020. [Google Scholar] [CrossRef]
- Liu, J.; Lezama, N.; Gasper, J.; Kawata, J.; Morley, S.; Helmer, D.; Ciminera, P. Burn pit emissions exposure and respiratory and cardiovascular conditions among airborne hazards and open burn pit registry participants. J. Occup. Environ. Med. 2016, 58, e249–e255. [Google Scholar] [CrossRef]
- Poisson, C.; Boucher, S.; Selby, D.; Ross, S.P.; Jindal, C.; Efird, J.T.; Bith-Melander, P. A pilot study of airborne hazards and other toxic exposures in Iraq war veterans. Int. J. Environ. Res. Public Health 2020, 17, 3299. [Google Scholar] [CrossRef]
- Mayer, A.R.; Quinn, D.K.; Master, C.L. The spectrum of mild traumatic brain injury: A review. Neurology 2017, 89, 623–632. [Google Scholar] [CrossRef]
- Petrie, E.C.; Cross, D.J.; Yarnykh, V.L.; Richards, T.; Martin, N.M.; Pagulayan, K.; Hoff, D.; Hart, K.; Mayer, C.; Tarabochia, M.; et al. Neuroimaging, behavioral, and psychological sequelae of repetitive combined blast/impact mild traumatic brain injury in Iraq and Afghanistan war veterans. J. Neurotrauma 2014, 31, 425–436. [Google Scholar] [CrossRef] [Green Version]
- American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th ed.; American Psychiatric Association: Washington, DC, USA, 2013. [Google Scholar] [CrossRef]
- Kilpatrick, D.G.; Resnick, H.S.; Milanak, M.E.; Miller, M.W.; Keyes, K.M.; Friedman, M.J. National estimates of exposure to traumatic events and PTSD prevalence using DSM-IV and DSM-5 criteria. J. Trauma. Stress 2013, 26, 537–547. [Google Scholar] [CrossRef] [Green Version]
- Bills, C.B.; Levy, N.A.; Sharma, V.; Charney, D.S.; Herbert, R.; Moline, J.; Katz, C.L. Mental health of workers and volunteers responding to events of 9/11: Review of the literature. Mt. Sinai J. Med. 2008, 75, 115–127. [Google Scholar] [CrossRef]
- Perrin, M.A.; DiGrande, L.; Wheeler, K.; Thorpe, L.; Farfel, M.; Brackbill, R. Differences in PTSD prevalence and associated risk factors among World Trade Center disaster rescue and recovery workers. Am. J. Psychiatry 2007, 164, 1385–1394. [Google Scholar] [CrossRef] [PubMed]
- Barrett, D.H.; Green, M.L.; Morris, R.; Giles, W.H.; Croft, J.B. Cognitive functioning and posttraumatic stress disorder. Am. J. Psychiatry 1996, 153, 1492–1494. [Google Scholar] [PubMed]
- Singh, A.; Zeig-Owens, R.; Rabin, L.; Schwartz, T.; Webber, M.P.; Appel, D.; Prezant, D.J.; Hall, C.B. PTSD and depressive symptoms as potential mediators of the association between world trade center exposure and subjective cognitive concerns in rescue/recovery workers. Int. J. Environ. Res. Public Health 2020, 17, 5683. [Google Scholar] [CrossRef] [PubMed]
- McKee, A.C.; Robinson, M.E. Military-related traumatic brain injury and neurodegeneration. Alzheimers Dement. 2014, 10, S242–S253. [Google Scholar] [CrossRef] [Green Version]
- Bryant, R. Post-traumatic stress disorder vs traumatic brain injury. Dialogues Clin. Neurosci. 2011, 13, 251–262. [Google Scholar]
- Bell, C.G.; Lowe, R.; Adams, P.D.; Baccarelli, A.A.; Beck, S.; Bell, J.T.; Christensen, B.C.; Gladyshev, V.N.; Heijmans, B.T.; Horvath, S.; et al. DNA methylation aging clocks: Challenges and recommendations. Genome Biol. 2019, 20, 249. [Google Scholar] [CrossRef] [Green Version]
- Horvath, S. DNA methylation age of human tissues and cell types. Genome Biol. 2013, 14, R115. [Google Scholar] [CrossRef] [Green Version]
- Fredrickson, J.; Maruff, P.; Woodward, M.; Moore, L.; Fredrickson, A.; Sach, J.; Darby, D. Evaluation of the usability of a brief computerized cognitive screening test in older people for epidemiological studies. Neuroepidemiology 2010, 34, 65–75. [Google Scholar] [CrossRef] [Green Version]
- Hammers, D.; Spurgeon, E.; Ryan, K.; Persad, C.; Heidebrink, J.; Barbas, N.; Albin, R.; Frey, K.; Darby, D.; Giordani, B. Reliability of repeated cognitive assessment of dementia using a brief computerized battery. Am. J. Alzheimers Dis. Dement. 2011, 26, 326–333. [Google Scholar] [CrossRef]
- Lim, Y.Y.; Ellis, K.A.; Harrington, K.; Ames, D.; Martins, R.N.; Masters, C.L.; Rowe, C.; Savage, G.; Szoeke, C.; Darby, D.; et al. Use of the CogState brief battery in the assessment of Alzheimer’s disease related cognitive impairment in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. J. Clin. Exp. Neuropsychol. 2012, 34, 345–358. [Google Scholar] [CrossRef]
- Lim, Y.Y.; Jaeger, J.; Harrington, K.; Ashwood, T.; Ellis, K.A.; Stöffler, A.; Szoeke, C.; Lachovitzki, R.; Martins, R.N.; Villemagne, V.L.; et al. Three-month stability of the CogState brief battery in healthy older adults, mild cognitive impairment, and Alzheimer’s Disease: Results from the Australian imaging, biomarkers, and lifestyle-rate of change substudy (AIBL-ROCS). Arch. Clin. Neuropsychol. 2013, 28, 320–330. [Google Scholar] [CrossRef] [PubMed]
- Maruff, P.; Thomas, E.; Cysique, L.; Brew, B.; Collie, A.; Snyder, P.; Pietrzak, R.H. Validity of the CogState brief battery: Relationship to standardized tests and sensitivity to cognitive impairment in mild traumatic brain injury, Schizophrenia, and AIDS dementia complex. Arch. Clin. Neuropsychol. 2009, 24, 165–178. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Clouston, S.A.P.; Guralnik, J.M.; Kotov, R.; Bromet, E.J.; Luft, B.J. Functional limitations among responders to the World Trade Center attacks 14 years after the disaster: Implications of chronic posttraumatic stress disorder. J. Trauma Stress 2017, 30, 443–452. [Google Scholar] [CrossRef] [PubMed]
- Mukherjee, S.; Clouston, S.; Kotov, R.; Bromet, E.; Luft, B. Handgrip strength of World Trade Center (WTC) responders: The role of re-experiencing posttraumatic stress disorder (PTSD) symptoms. Int. J. Environ. Res Public Health 2019, 16, 1128. [Google Scholar] [CrossRef] [Green Version]
- Kuan, P.F.; Waszczuk, M.A.; Kotov, R.; Clouston, S.; Yang, X.; Singh, P.K.; Glenn, S.T.; Gomez, E.C.; Wang, J.; Bromet, E.; et al. Gene expression associated with PTSD in World Trade Center responders: An RNA sequencing study. Transl. Psychiatry 2017, 7, 1297. [Google Scholar] [CrossRef] [Green Version]
- Kuan, P.F.; Yang, X.; Clouston, S.; Ren, X.; Kotov, R.; Waszczuk, M.; Singh, P.K.; Glenn, S.T.; Gomez, E.C.; Wang, J.; et al. Cell type-specific gene expression patterns associated with posttraumatic stress disorder in World Trade Center responders. Transl. Psychiatry 2019, 9, 1. [Google Scholar] [CrossRef]
- Kritikos, M.; Clouston, S.A.P.; Diminich, E.D.; Deri, Y.; Yang, X.; Carr, M.; Gandy, S.; Sano, M.; Bromet, E.J.; Luft, B.J. Pathway analysis for plasma beta-amyloid, tau and neurofilament light (ATN) in world trade center responders at midlife. Neurol. Ther. 2020, 9, 159–171. [Google Scholar] [CrossRef]
- Kuan, P.-F.; Clouston, S.; Yang, X.; Kotov, R.; Bromet, E.; Luft, B.J. Molecular linkage between post-traumatic stress disorder and cognitive impairment: A targeted proteomics study of World Trade Center responders. Transl. Psychiatry 2020, 10, 269. [Google Scholar] [CrossRef]
- Ganzel, B.L.; Kim, P.; Glover, G.H.; Temple, E. Resilience after 9/11: Multimodal neuroimaging evidence for stress-related change in the healthy adult brain. NeuroImage 2008, 40, 788–795. [Google Scholar] [CrossRef] [Green Version]
- Ganzel, B.; Casey, B.J.; Glover, G.; Voss, H.U.; Temple, E. The aftermath of 9/11: Effect of intensity and recency of trauma on outcome. Emotion 2007, 7, 227–238. [Google Scholar] [CrossRef] [Green Version]
- First, M.B.; Williams, J.B.W.; Karg, R.S.; Spitzer, R.L. Structured Clinical Interview for DSM-5; American Psychiatric Association: Arlington, VA, USA, 2015. [Google Scholar]
- Clouston, S. Reduced cortical thickness in World Trade Center responders with cognitive impairment. Alzheimers Dement. Diagn. Assess. Dis. Monit. 2020, 12, e12059. [Google Scholar]
- Cho, J.; Sohn, J.; Noh, J.; Jang, H.; Kim, W.; Cho, S.-K.; Seo, H.; Seo, G.; Lee, S.-K.; Noh, Y.; et al. Association between exposure to polycyclic aromatic hydrocarbons and brain cortical thinning: The Environmental Pollution-Induced Neurological EFfects (EPINEF) study. Sci. Total Environ. 2020, 737, 140097. [Google Scholar] [CrossRef] [PubMed]
- Seil, K.; Yu, S.; Alper, H. A Cognitive reserve and social support-focused latent class analysis to predict self-reported confusion or memory loss among middle-aged world trade center health registry enrollees. Int. J. Environ. Res. Public Health 2019, 16, 1401. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Russ, T.C.; Morling, J.R. Cholinesterase inhibitors for mild cognitive impairment. Cochrane Database Syst. Rev. 2012. [Google Scholar] [CrossRef] [PubMed]
- Cooper, C.; Li, R.; Lyketsos, C.; Livingston, G. Treatment for mild cognitive impairment: Systematic review. Br. J. Psychiatry 2013, 203, 255–264. [Google Scholar] [CrossRef] [Green Version]
- Orgeta, V.; Qazi, A.; Spector, A.; Orrell, M. Psychological treatments for depression and anxiety in dementia and mild cognitive impairment: Systematic review and meta-analysis. Br. J. Psychiatry 2015, 207, 293–298. [Google Scholar] [CrossRef] [Green Version]
- Hillman, C.H.; Erickson, K.I.; Kramer, A.F. Be smart, exercise your heart: Exercise effects on brain and cognition. Nat. Rev. Neurosci. 2008, 9, 58–65. [Google Scholar] [CrossRef]
- Landrigan, J.F.; Bell, T.; Crowe, M.; Clay, O.J.; Mirman, D. Lifting cognition: A meta-analysis of effects of resistance exercise on cognition. Psychol. Res. 2020, 84, 1167–1183. [Google Scholar] [CrossRef] [Green Version]
- Erickson, K.I.; Hillman, C.H.; Kramer, A.F. Physical activity, brain, and cognition. Curr. Opin. Behav. Sci. 2015, 4, 27–32. [Google Scholar] [CrossRef]
- Law, L.L.F.; Barnett, F.; Yau, M.K.; Gray, M.A. Effects of combined cognitive and exercise interventions on cognition in older adults with and without cognitive impairment: A systematic review. Ageing Res. Rev. 2014, 15, 61–75. [Google Scholar] [CrossRef]
- Hötting, K.; Röder, B. Beneficial effects of physical exercise on neuroplasticity and cognition. Neurosci. Biobehav. Rev. 2013, 37, 2243–2257. [Google Scholar] [CrossRef] [PubMed]
- Stillman, C.M.; Esteban-Cornejo, I.; Brown, B.; Bender, C.M.; Erickson, K.I. Effects of exercise on brain and cognition across age groups and health states. Trends Neurosci. 2020, 43, 533–543. [Google Scholar] [CrossRef] [PubMed]
- Young, J.; Angevaren, M.; Rusted, J.; Tabet, N. Aerobic exercise to improve cognitive function in older people without known cognitive impairment. Cochrane Database Syst. Rev. 2015. [Google Scholar] [CrossRef] [PubMed]
- McSween, M.P.; Coombes, J.S.; MacKay, C.P.; Rodriguez, A.D.; Erickson, K.I.; Copland, D.A.; McMahon, K.L. The immediate effects of acute aerobic exercise on cognition in healthy older adults: A systematic review. Sports Med. 2019, 49, 67–82. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Van Uffelen, J.G.Z.; Chin A Paw, M.J.M.; Hopman-Rock, M.; van Mechelen, W. The effects of exercise on cognition in older adults with and without cognitive decline: A systematic review. Clin. J. Sport Med. 2008, 18, 486–500. [Google Scholar] [CrossRef] [Green Version]
- Ridker, P.M.; Everett, B.M.; Thuren, T.; MacFadyen, J.G.; Chang, W.H.; Ballantyne, C.; Fonseca, F.; Nicolau, J.; Koenig, W.; Anker, S.D.; et al. Antiinflammatory therapy with canakinumab for atherosclerotic disease. N. Engl. J. Med. 2017, 377, 1119–1131. [Google Scholar] [CrossRef]
- Sloan, R.P.; Shapiro, P.A.; McKinley, P.S.; Bartels, M.; Shimbo, D.; Lauriola, V.; Karmally, W.; Pavlicova, M.; Choi, C.J.; Choo, T.H.; et al. Aerobic exercise training and inducible inflammation: Results of a randomized controlled trial in healthy, young adults. J. Am. Heart Assoc. 2018, 7, e010201. [Google Scholar] [CrossRef]
- Raskind, M.A.; Peterson, K.; Williams, T.; Hoff, D.J.; Hart, K.; Holmes, H.; Homas, D.; Hill, J.; Daniels, C.; Calohan, J.; et al. A trial of prazosin for combat trauma PTSD with nightmares in active-duty soldiers returned from Iraq and Afghanistan. Am. J. Psychiatry 2013, 170, 1003–1010. [Google Scholar] [CrossRef]
- Raskind, M.A.; Millard, S.P.; Petrie, E.C.; Peterson, K.; Williams, T.; Hoff, D.J.; Hart, K.; Holmes, H.; Hill, J.; Daniels, C.; et al. Higher pretreatment blood pressure is associated with greater posttraumatic stress disorder symptom reduction in soldiers treated with prazosin. Biol. Psychiatry 2016, 80, 736–742. [Google Scholar] [CrossRef] [Green Version]
- Williamson, J.D.; Pajewski, N.M.; Auchus, A.P.; Bryan, R.N.; Chelune, G.; Cheung, A.K.; Cleveland, M.L.; Coker, L.H.; Crowe, M.G.; Cushman, W.C.; et al. Effect of intensive vs standard blood pressure control on probable dementia: A randomized clinical trial. J. Am. Med. Assoc. 2019, 321, 553–561. [Google Scholar]
- Edwards, J.D.; Fausto, B.A.; Tetlow, A.M.; Corona, R.T.; Valdés, E.G. Systematic review and meta-analyses of useful field of view cognitive training. Neurosci. Biobehav. Rev. 2018, 84, 72–91. [Google Scholar] [CrossRef] [PubMed]
- Rebok, G.W.; Ball, K.; Guey, L.T.; Jones, R.N.; Kim, H.Y.; King, J.W.; Marsiske, M.; Morris, J.N.; Tennstedt, S.L.; Unverzagt, F.W.; et al. Ten-year effects of the advanced cognitive training for independent and vital elderly cognitive training trial on cognition and everyday functioning in older adults. J. Am. Geriatr. Soc. 2014, 62, 16–24. [Google Scholar] [CrossRef] [PubMed]
- Edwards, J.D.; Xu, H.; Clark, D.O.; Guey, L.T.; Ross, L.A.; Unverzagt, F.W. Speed of processing training results in lower risk of dementia. Alzheimers Dement. Transl. Res. Clin. Interv. 2017, 3, 603–611. [Google Scholar] [CrossRef] [PubMed]
Session I: The Natural History of Cognitive Aging and Impairment |
1. What is the natural history of brain structure and function later in life (i.e., what occurs as individuals age)? |
2. What do we mean by cognitive impairment (narrowing our scope)? |
3. If you have MCI, what are the potential consequences of this (prognosis), especially with respect to debilitating disease like dementia? |
4. Other than aging, what are the predictors (risk factors) and causes of cognitive impairment, including nosology of vascular and neurodegenerative diseases and cognitive effects of medications used to treat other conditions? |
Session II: Novel Identifiable Markers in the Pathway of Neurodegenerative Disease |
5. What is the histopathology of MCI? |
6. What test(s) are the most promising at this point and that may be relevant for the 9/11-exposed population? |
7. What test(s) are the most sensitive and specific for clarifying disease diagnosis? |
Session III: Neuropathological Changes Associated with Hazardous Exposures and Brain Aging |
8. What types of agents are likely associated with neuropathological changes? |
9. What is the biologic plausibility for 9/11 agents to cause neuropathological change (mechanisms)? |
10. Is there a pathological distinction between dust exposure-induced and stress-induced MCI? |
Session IV: Cognitive Decline and Impairment in the 9/11-Exposed Populations |
11. Review of research (completed and current) involving the 9/11-exposed population. |
12. Is there a 9/11 phenotype, and how common are symptoms? |
13. Characterize who in the cohort is affected? |
14. Is it primarily a subset of individuals with PTSD? |
15. Are WTCHP members at increased risk for MCI? |
16. What are the predictors of MCI among WTCHP members? |
17. Address pathway modeling for 9/11 exposures and MCI, if possible. |
Session V: Clinical Perspectives on Aspects and Targets for Treatment |
18. How do we best characterize and treat MCI with and without psychiatric comorbidity? |
19. What are the most informative neurocognitive tests to detect and measure the course of MCI? |
20. Can MCI be prevented, or can decline in cognitive functioning be slowed? |
21. What are patient eligibility criteria for ongoing clinical trials? |
Session VI: Monitoring and Surveillance |
22. Role of screening for MCI in monitoring or using a subset of the cohort—and which tool? |
23. What (baseline) testing should be performed now that could be of value when doing longitudinal follow up? |
A: Aggregated Aβ or Associated Pathologic State |
CSF Aβ42, or Aβ42/Aβ40 ratio |
Amyloid PET |
T: Aggregated tau (neurofibrillary tangles) or associated pathologic state |
CSF phosphorylated tau |
Tau PET |
(N): Neurodegeneration or neuronal injury |
Anatomic MRI |
FDG PET |
CSF total tau |
CSF NfL |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Daniels, R.D.; Clouston, S.A.P.; Hall, C.B.; Anderson, K.R.; Bennett, D.A.; Bromet, E.J.; Calvert, G.M.; Carreón, T.; DeKosky, S.T.; Diminich, E.D.; et al. A Workshop on Cognitive Aging and Impairment in the 9/11-Exposed Population. Int. J. Environ. Res. Public Health 2021, 18, 681. https://doi.org/10.3390/ijerph18020681
Daniels RD, Clouston SAP, Hall CB, Anderson KR, Bennett DA, Bromet EJ, Calvert GM, Carreón T, DeKosky ST, Diminich ED, et al. A Workshop on Cognitive Aging and Impairment in the 9/11-Exposed Population. International Journal of Environmental Research and Public Health. 2021; 18(2):681. https://doi.org/10.3390/ijerph18020681
Chicago/Turabian StyleDaniels, Robert D., Sean A. P. Clouston, Charles B. Hall, Kristi R. Anderson, David A. Bennett, Evelyn J. Bromet, Geoffrey M. Calvert, Tania Carreón, Steven T. DeKosky, Erica D. Diminich, and et al. 2021. "A Workshop on Cognitive Aging and Impairment in the 9/11-Exposed Population" International Journal of Environmental Research and Public Health 18, no. 2: 681. https://doi.org/10.3390/ijerph18020681
APA StyleDaniels, R. D., Clouston, S. A. P., Hall, C. B., Anderson, K. R., Bennett, D. A., Bromet, E. J., Calvert, G. M., Carreón, T., DeKosky, S. T., Diminich, E. D., Finch, C. E., Gandy, S., Kreisl, W. C., Kritikos, M., Kubale, T. L., Mielke, M. M., Peskind, E. R., Raskind, M. A., Richards, M., ... Reissman, D. B. (2021). A Workshop on Cognitive Aging and Impairment in the 9/11-Exposed Population. International Journal of Environmental Research and Public Health, 18(2), 681. https://doi.org/10.3390/ijerph18020681