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Pearson MJ, Wagstaff R, Williams RJ. Choroid plexus volumes and auditory verbal learning scores are associated with conversion from mild cognitive impairment to Alzheimer's disease. Brain Behav 2024; 14:e3611. [PMID: 38956818 PMCID: PMC11219301 DOI: 10.1002/brb3.3611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 05/30/2024] [Accepted: 06/01/2024] [Indexed: 07/04/2024] Open
Abstract
PURPOSE Mild cognitive impairment (MCI) can be the prodromal phase of Alzheimer's disease (AD) where appropriate intervention might prevent or delay conversion to AD. Given this, there has been increasing interest in using magnetic resonance imaging (MRI) and neuropsychological testing to predict conversion from MCI to AD. Recent evidence suggests that the choroid plexus (ChP), neural substrates implicated in brain clearance, undergo volumetric changes in MCI and AD. Whether the ChP is involved in memory changes observed in MCI and can be used to predict conversion from MCI to AD has not been explored. METHOD The current study used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to investigate whether later progression from MCI to AD (progressive MCI [pMCI], n = 115) or stable MCI (sMCI, n = 338) was associated with memory scores using the Rey Auditory Verbal Learning Test (RAVLT) and ChP volumes as calculated from MRI. Classification analyses identifying pMCI or sMCI group membership were performed to compare the predictive ability of the RAVLT and ChP volumes. FINDING The results indicated a significant difference between pMCI and sMCI groups for right ChP volume, with the pMCI group showing significantly larger right ChP volume (p = .01, 95% confidence interval [-.116, -.015]). A significant linear relationship between the RAVLT scores and right ChP volume was found across all participants, but not for the two groups separately. Classification analyses showed that a combination of left ChP volume and auditory verbal learning scores resulted in the most accurate classification performance, with group membership accurately predicted for 72% of the testing data. CONCLUSION These results suggest that volumetric ChP changes appear to occur before the onset of AD and might provide value in predicting conversion from MCI to AD.
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Affiliation(s)
- Michael J. Pearson
- Faculty of HealthCharles Darwin UniversityDarwinNorthern TerritoryAustralia
| | - Ruth Wagstaff
- Faculty of HealthCharles Darwin UniversityDarwinNorthern TerritoryAustralia
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Koppelmans V, Ruitenberg MFL, Schaefer SY, King JB, Jacobo JM, Silvester BP, Mejia AF, van der Geest J, Hoffman JM, Tasdizen T, Duff K. Classification of Mild Cognitive Impairment and Alzheimer's Disease Using Manual Motor Measures. NEURODEGENER DIS 2024; 24:54-70. [PMID: 38865972 PMCID: PMC11381162 DOI: 10.1159/000539800] [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: 03/18/2024] [Accepted: 06/09/2024] [Indexed: 06/14/2024] Open
Abstract
INTRODUCTION Manual motor problems have been reported in mild cognitive impairment (MCI) and Alzheimer's disease (AD), but the specific aspects that are affected, their neuropathology, and potential value for classification modeling is unknown. The current study examined if multiple measures of motor strength, dexterity, and speed are affected in MCI and AD, related to AD biomarkers, and are able to classify MCI or AD. METHODS Fifty-three cognitively normal (CN), 33 amnestic MCI, and 28 AD subjects completed five manual motor measures: grip force, Trail Making Test A, spiral tracing, finger tapping, and a simulated feeding task. Analyses included (1) group differences in manual performance; (2) associations between manual function and AD biomarkers (PET amyloid β, hippocampal volume, and APOE ε4 alleles); and (3) group classification accuracy of manual motor function using machine learning. RESULTS Amnestic MCI and AD subjects exhibited slower psychomotor speed and AD subjects had weaker dominant hand grip strength than CN subjects. Performance on these measures was related to amyloid β deposition (both) and hippocampal volume (psychomotor speed only). Support vector classification well-discriminated control and AD subjects (area under the curve of 0.73 and 0.77, respectively) but poorly discriminated MCI from controls or AD. CONCLUSION Grip strength and spiral tracing appear preserved, while psychomotor speed is affected in amnestic MCI and AD. The association of motor performance with amyloid β deposition and atrophy could indicate that this is due to amyloid deposition in and atrophy of motor brain regions, which generally occurs later in the disease process. The promising discriminatory abilities of manual motor measures for AD emphasize their value alongside other cognitive and motor assessment outcomes in classification and prediction models, as well as potential enrichment of outcome variables in AD clinical trials.
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Affiliation(s)
- Vincent Koppelmans
- Department of Psychiatry, University of Utah, Salt Lake City, Utah, USA
- Huntsman Mental Health Institute, University of Utah, Salt Lake City, Utah, USA
| | - Marit F L Ruitenberg
- Department of Health, Medical and Neuropsychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Sydney Y Schaefer
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, USA
| | - Jace B King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Jasmine M Jacobo
- Department of Psychiatry, University of Utah, Salt Lake City, Utah, USA
- Huntsman Mental Health Institute, University of Utah, Salt Lake City, Utah, USA
| | - Benjamin P Silvester
- Department of Psychiatry, University of Utah, Salt Lake City, Utah, USA
- Huntsman Mental Health Institute, University of Utah, Salt Lake City, Utah, USA
| | - Amanda F Mejia
- Department of Statistics, University of Indiana, Bloomington, Indiana, USA
| | | | - John M Hoffman
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
- Center for Quantitative Cancer Imaging, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
| | - Tolga Tasdizen
- Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah, USA
| | - Kevin Duff
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
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Lai YLL, Hsu FT, Yeh SY, Kuo YT, Lin HH, Lin YC, Kuo LW, Chen CY, Liu HS. Atrophy of the cholinergic regions advances from early to late mild cognitive impairment. Neuroradiology 2024; 66:543-556. [PMID: 38240769 DOI: 10.1007/s00234-024-03290-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 01/10/2024] [Indexed: 03/14/2024]
Abstract
PURPOSE We investigated the volumetric changes in the components of the cholinergic pathway for patients with early mild cognitive impairment (EMCI) and those with late mild cognitive impairment (LMCI). The effect of patients' apolipoprotein 4 (APOE-ε4) allele status on the structural changes were analyzed. METHODS Structural magnetic resonance imaging data were collected. Patients' demographic information, plasma data, and validated global cognitive composite scores were included. Relevant features were extracted for constructing machine learning models to differentiate between EMCI (n = 312) and LMCI (n = 541) and predict patients' neurocognitive function. The data were analyzed primarily through one-way analysis of variance and two-way analysis of covariance. RESULTS Considerable differences were observed in cholinergic structural changes between patients with EMCI and LMCI. Cholinergic atrophy was more prominent in the LMCI cohort than in the EMCI cohort (P < 0.05 family-wise error corrected). APOE-ε4 differentially affected cholinergic atrophy in the LMCI and EMCI cohorts. For LMCI cohort, APOE-ε4 carriers exhibited increased brain atrophy (left amygdala: P = 0.001; right amygdala: P = 0.006, and right Ch123, P = 0.032). EMCI and LCMI patients showed distinctive associations of gray matter volumes in cholinergic regions with executive (R2 = 0.063 and 0.030 for EMCI and LMCI, respectively) and language (R2 = 0.095 and 0.042 for EMCI and LMCI, respectively) function. CONCLUSIONS Our data confirmed significant cholinergic atrophy differences between early and late stages of mild cognitive impairment. The impact of the APOE-ε4 allele on cholinergic atrophy varied between the LMCI and EMCI groups.
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Affiliation(s)
- Ying-Liang Larry Lai
- Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University and National Health Research Institutes, Taipei, Taiwan
| | - Fei-Ting Hsu
- Department of Biological Science and Technology, China Medical University, Taichung, Taiwan
| | - Shu-Yi Yeh
- School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan
| | - Yu-Tzu Kuo
- School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan
| | - Hui-Hsien Lin
- CT/MR Division, Rotary Trading CO., LTD, Taipei, Taiwan
| | - Yi-Chun Lin
- School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan
| | - Li-Wei Kuo
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan
- Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Cheng-Yu Chen
- Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
- Department of Medical Imaging, Taipei Medical University Hospital, Medical University, Taipei, Taiwan.
| | - Hua-Shan Liu
- School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan.
- International Ph.D. Program in Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan.
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Lee AJ, Stark JH, Hayes SM. Baseline Frontoparietal Gray Matter Volume Predicts Executive Function Performance in Aging and Mild Cognitive Impairment at 24-Month Follow-Up. J Alzheimers Dis 2024; 100:357-374. [PMID: 38875035 DOI: 10.3233/jad-231468] [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: 06/16/2024]
Abstract
Background Executive dysfunction in mild cognitive impairment (MCI) has been associated with gray matter atrophy. Prior studies have yielded limited insight into associations between gray matter volume and executive function in early and late amnestic MCI (aMCI). Objective To examine the relative importance of predictors of executive function at 24 months and relationships between baseline regional gray matter volume and executive function performance at 24-month follow-up in non-demented older adults. Methods 147 participants from the Alzheimer's Disease Neuroimaging Initiative (mean age = 70.6 years) completed brain magnetic resonance imaging and neuropsychological testing and were classified as cognitively normal (n = 49), early aMCI (n = 60), or late aMCI (n = 38). Analyses explored the importance of demographic, APOEɛ4, biomarker (p-tau/Aβ42, t-tau/Aβ42), and gray matter regions-of-interest (ROI) variables to 24-month executive function, whether ROIs predicted executive function, and whether relationships varied by baseline diagnostic status. Results Across all participants, baseline anterior cingulate cortex and superior parietal lobule volumes were the strongest predictors of 24-month executive function performance. In early aMCI, anterior cingulate cortex volume was the strongest predictor and demonstrated a significant interaction such that lower volume related to worse 24-month executive function in early aMCI. Educational attainment and inferior frontal gyrus volume were the strongest predictors of 24-month executive function performance for cognitively normal and late aMCI groups, respectively. Conclusions Baseline frontoparietal gray matter regions were significant predictors of executive function performance in the context of aMCI and may identify those at risk of Alzheimer's disease. Anterior cingulate cortex volume may predict executive function performance in early aMCI.
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Affiliation(s)
- Ann J Lee
- Department of Psychology, The Ohio State University, Columbus, OH, USA
| | - Jessica H Stark
- Department of Psychology, The Ohio State University, Columbus, OH, USA
| | - Scott M Hayes
- Department of Psychology, The Ohio State University, Columbus, OH, USA
- Chronic Brain Injury Initiative, The Ohio State University, Columbus, OH, USA
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Hanyu H, Koyama Y, Umekida K, Watanabe S, Matsuda H, Koike R, Takashima A. Path Integration Detects Prodromal Alzheimer's Disease and Predicts Cognitive Decline. J Alzheimers Dis 2024; 101:651-660. [PMID: 39240637 DOI: 10.3233/jad-240347] [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: 09/07/2024]
Abstract
Background The entorhinal cortex is the very earliest involvement of Alzheimer's disease (AD). Grid cells in the medial entorhinal cortex form part of the spatial navigation system. Objective We aimed to determine whether path integration performance can be used to detect patients with mild cognitive impairment (MCI) at high risk of developing AD, and whether it can predict cognitive decline. Methods Path integration performance was assessed in 71 patients with early MCI (EMCI) and late MCI (LMCI) using a recently developed 3D virtual reality navigation task. Patients with LMCI were further divided into those displaying characteristic brain imaging features of AD, including medial temporal lobe atrophy on magnetic resonance imaging and posterior hypoperfusion on single-photon emission tomography (LMCI+), and those not displaying such features (LMCI-). Results Path integration performance was significantly lower in patients with LMCI+than in those with EMCI and LMCI-. A significantly lower performance was observed in patients who showed progression of MCI during 12 months, than in those with stable MCI. Path integration performance distinguished patients with progressive MCI from those with stable MCI, with a high classification accuracy (a sensitivity of 0.88 and a specificity of 0.70). Conclusions Our results suggest that the 3D virtual reality navigation task detects prodromal AD patients and predicts cognitive decline after 12 months. Our navigation task, which is simple, short (12-15 minutes), noninvasive, and inexpensive, may be a screening tool for therapeutic choice of disease-modifiers in individuals with prodromal AD.
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Affiliation(s)
- Haruo Hanyu
- Dementia Research Center, Tokyo General Hospital, Tokyo, Japan
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Yumi Koyama
- Department of Rehabilitation, Tokyo General Hospital, Tokyo, Japan
| | - Kazuki Umekida
- Department of Rehabilitation, Tokyo General Hospital, Tokyo, Japan
| | | | - Hiroshi Matsuda
- Department of Biofunctional Imaging, Fukushima Medical University, Fukushima, Japan
| | - Riki Koike
- Laboratory for Alzheimer's Disease, Department of Life Science, Faculty of Science, Gakushuin University, Tokyo, Japan
| | - Akihiko Takashima
- Laboratory for Alzheimer's Disease, Department of Life Science, Faculty of Science, Gakushuin University, Tokyo, Japan
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Lathe R, Schultek NM, Balin BJ, Ehrlich GD, Auber LA, Perry G, Breitschwerdt EB, Corry DB, Doty RL, Rissman RA, Nara PL, Itzhaki R, Eimer WA, Tanzi RE. Establishment of a consensus protocol to explore the brain pathobiome in patients with mild cognitive impairment and Alzheimer's disease: Research outline and call for collaboration. Alzheimers Dement 2023; 19:5209-5231. [PMID: 37283269 PMCID: PMC10918877 DOI: 10.1002/alz.13076] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 03/06/2023] [Indexed: 06/08/2023]
Abstract
Microbial infections of the brain can lead to dementia, and for many decades microbial infections have been implicated in Alzheimer's disease (AD) pathology. However, a causal role for infection in AD remains contentious, and the lack of standardized detection methodologies has led to inconsistent detection/identification of microbes in AD brains. There is a need for a consensus methodology; the Alzheimer's Pathobiome Initiative aims to perform comparative molecular analyses of microbes in post mortem brains versus cerebrospinal fluid, blood, olfactory neuroepithelium, oral/nasopharyngeal tissue, bronchoalveolar, urinary, and gut/stool samples. Diverse extraction methodologies, polymerase chain reaction and sequencing techniques, and bioinformatic tools will be evaluated, in addition to direct microbial culture and metabolomic techniques. The goal is to provide a roadmap for detecting infectious agents in patients with mild cognitive impairment or AD. Positive findings would then prompt tailoring of antimicrobial treatments that might attenuate or remit mounting clinical deficits in a subset of patients.
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Affiliation(s)
- Richard Lathe
- Division of Infection Medicine, Chancellor's Building, University of Edinburgh Medical School, Edinburgh, UK
| | | | - Brian J. Balin
- Department of Bio-Medical Sciences, Philadelphia College of Osteopathic Medicine, Philadelphia, PA 19131, USA
| | - Garth D. Ehrlich
- Center for Genomic Sciences, Institute for Molecular Medicine and Infectious Disease, Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA 19102, USA
| | | | - George Perry
- Department of Biology, The University of Texas at San Antonio, San Antonio, TX, USA
| | - Edward B. Breitschwerdt
- Intracellular Pathogens Research Laboratory, Comparative Medicine Institute, College of Veterinary Medicine, North Carolina State University, Raleigh, NC 27607, USA
| | - David B. Corry
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Richard L. Doty
- Smell and Taste Center, Department of Otorhinolaryngology: Head and Neck Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Robert A. Rissman
- Department of Neurosciences, University of California, San Diego and VA San Diego Healthcare System, La Jolla, CA
| | | | - Ruth Itzhaki
- Institute of Population Ageing, University of Oxford, Oxford, UK
| | - William A. Eimer
- Genetics and Aging Research Unit, Mass General Institute for Neurodegenerative Disease, Charlestown, MA 02129, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
- McCance Cancer Center for Brain Health, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Rudolph E. Tanzi
- Genetics and Aging Research Unit, Mass General Institute for Neurodegenerative Disease, Charlestown, MA 02129, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
- McCance Cancer Center for Brain Health, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Intracell Research Group Consortium Collaborators
- David L. Hahn (Intracell Research Group, USA), Benedict C. Albensi (Nova Southeastern, USA), James St John (Griffith University, Australia), Jenny Ekberg (Griffith University, Australia), Mark L. Nelson (Intracell Research Group, USA), Gerald McLaughlin (National Institutes of Health, USA), Christine Hammond (Philadelphia College of Osteopathic Medicine, USA), Judith Whittum-Hudson (Wayne State University, USA), Alan P. Hudson (Wayne State University, USA), Guillaume Sacco (Université Cote d’Azur, Centre Hospitalier Universitaire de Nice, CoBTek, France), Alexandra Konig (Université Cote d’Azur and CoBTek, France), Bruno Pietro Imbimbo (Chiesi Farmaceutici, Parma, Italy), Nicklas Linz (Ki Elements Ltd, Saarbrücken, Germany), Nicole Danielle Bell (Author, 'What Lurks in the Woods'), Shima T. Moein (Smell and Taste Center, Department of Otorhinolaryngology, Perelman School of Medicine, University of Philadelphia, USA), Jürgen G. Haas (Infection Medicine, University of Edinburgh Medical School, UK)
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Abbatantuono C, Alfeo F, Clemente L, Lancioni G, De Caro MF, Livrea P, Taurisano P. Current Challenges in the Diagnosis of Progressive Neurocognitive Disorders: A Critical Review of the Literature and Recommendations for Primary and Secondary Care. Brain Sci 2023; 13:1443. [PMID: 37891810 PMCID: PMC10605551 DOI: 10.3390/brainsci13101443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 09/27/2023] [Accepted: 10/02/2023] [Indexed: 10/29/2023] Open
Abstract
Screening for early symptoms of cognitive impairment enables timely interventions for patients and their families. Despite the advances in dementia diagnosis, the current nosography of neurocognitive disorders (NCDs) seems to overlook some clinical manifestations and predictors that could contribute to understanding the conversion from an asymptomatic stage to a very mild one, eventually leading to obvious disease. The present review examines different diagnostic approaches in view of neurophysiological and neuropsychological evidence of NCD progression, which may be subdivided into: (1) preclinical stage; (2) transitional stage; (3) prodromal or mild stage; (4) major NCD. The absence of univocal criteria and the adoption of ambiguous or narrow labels might complicate the diagnostic process. In particular, it should be noted that: (1) only neuropathological hallmarks characterize preclinical NCD; (2) transitional NCD must be assessed through proactive neuropsychological protocols; (3) prodromal/mild NCDs are based on cognitive functional indicators; (4) major NCD requires well-established tools to evaluate its severity stage; (5) insight should be accounted for by both patient and informants. Therefore, the examination of evolving epidemiological and clinical features occurring at each NCD stage may orient primary and secondary care, allowing for more targeted prevention, diagnosis, and/or treatment of both cognitive and functional impairment.
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Affiliation(s)
- Chiara Abbatantuono
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
| | - Federica Alfeo
- Department of Education, Communication and Psychology (For.Psi.Com), University of Bari “Aldo Moro”, 70121 Bari, Italy;
| | - Livio Clemente
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
| | - Giulio Lancioni
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
- Lega F D’Oro Research Center, 60027 Osimo, Italy
| | - Maria Fara De Caro
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
| | | | - Paolo Taurisano
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
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Listabarth S, Groemer M, Waldhoer T, Vyssoki B, Pruckner N, Vyssoki S, Glahn A, König-Castillo DM, König D. Cognitive decline and alcohol consumption in the aging population-A longitudinal analysis of the Survey of Health, Ageing and Retirement in Europe. Eur Psychiatry 2022; 65:e83. [PMID: 36398412 PMCID: PMC9748981 DOI: 10.1192/j.eurpsy.2022.2344] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Prevalence of cognitive decline and dementia is rising globally, with more than 10 million new cases every year. These conditions cause a significant burden for individuals, their caregivers, and health care systems. As no causal treatment for dementia exists, prevention of cognitive decline is of utmost importance. Notably, alcohol is among the most significant modifiable risk factors for cognitive decline. METHODS Longitudinal data across 15 years on 6,967 individuals of the Survey of Health, Ageing and Retirement in Europe were used to analyze the effect of alcohol consumption and further modifiable (i.e., smoking, depression, and educational obtainment) and non-modifiable risk factors (sex and age) on cognitive functioning (i.e., memory and verbal fluency). For this, a generalized estimating equation linear model was estimated for every cognitive test domain assessed. RESULTS Consistent results were revealed in all three regression models: A nonlinear association between alcohol consumption and cognitive decline was found-moderate alcohol intake was associated with overall better global cognitive function than low or elevated alcohol consumption or complete abstinence. Furthermore, female sex and higher educational obtainment were associated with better cognitive function, whereas higher age and depression were associated with a decline in cognitive functioning. No significant association was found for smoking. CONCLUSION Our data indicate that alcohol use is a relevant risk factor for cognitive decline in older adults. Furthermore, evidence-based therapeutic concepts to reduce alcohol consumption exist and should be of primary interest in prevention measures considering the aging European population.
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Affiliation(s)
- Stephan Listabarth
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Magdalena Groemer
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Thomas Waldhoer
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria
| | - Benjamin Vyssoki
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Nathalie Pruckner
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Sandra Vyssoki
- Department of Health Sciences, St. Pölten University of Applied Sciences, Sankt Pölten, Austria
| | - Alexander Glahn
- Department for Psychiatry, Social Psychiatry and Psychotherapy, Medical University of Hannover, Hannover, Germany
| | | | - Daniel König
- Clinical Division of Social Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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Guo M, Jia J, Zhang J, Zhou M, Wang A, Chen S, Zhao X. Association of β-cell function and cognitive impairment in patients with abnormal glucose metabolism. BMC Neurol 2022; 22:232. [PMID: 35739484 PMCID: PMC9219116 DOI: 10.1186/s12883-022-02755-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 06/16/2022] [Indexed: 12/23/2022] Open
Abstract
Background Insulin has been demonstrated to play an important role in the occurrence and development of Alzheimer’s disease, especially in those with diabetes. β cells are important insulin-producing cells in human pancreas. This study aimed to investigate the association between β-cell dysfunction and cognitive impairment among patients over 40-year-old with abnormal glucose metabolism in Chinese rural communities. Methods A sample of 592 participants aged 40 years or older from the China National Stroke Prevention Project (CSPP) between 2015 and 2017 were enrolled in this study. Abnormal glucose metabolism was defined when hemoglobin Alc ≥ 5.7%. Cognitive function was assessed by the Beijing edition of the Montreal Cognitive Assessment scale. Homeostasis assessment of β-cell function was performed and classified into 4 groups according to the quartiles. A lower value of HOMA-β indicated a worse condition of β-cell function. Multivariate logistic regression was used to analyze the association between β-cell function and cognitive impairment. Results In a total of 592 patients with abnormal glucose metabolism, the average age was 60.20 ± 7.63 years and 60.1% patients had cognitive impairment. After adjusting for all potential risk factors, we found the first quartile of β-cell function was significantly associated with cognitive impairment (OR: 2.27, 95%CI: 1.32–3.92), especially at the domains of language (OR: 1.64, 95%CI: 1.01–2.65) and abstraction (OR: 2.29, 95%CI: 1.46–3.58). Conclusions Our study showed that worse β-cell function is associated with cognitive impairment of people over 40-year-old with abnormal glucose metabolism in Chinese rural communities, especially in the cognitive domains of abstraction and language.
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Affiliation(s)
- Mengyi Guo
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurology, Beijing Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Jiaokun Jia
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jia Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Mingyue Zhou
- Department of Neurology, Beijing Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shengyun Chen
- Department of Neurology, Beijing Sanbo Brain Hospital, Capital Medical University, Beijing, China. .,Department of Neurology of Shenzhen Second People's Hospital, First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, China.
| | - Xingquan Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China. .,China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China. .,Research Unit of Artificial Intelligence in Cerebrovascular Disease, Chinese Academy of Medical Sciences, Beijing, China.
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