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Marcozzi S, Bigossi G, Giuliani ME, Lai G, Bartozzi B, Balietti M, Casoli T, Orlando F, Amoroso A, Giacconi R, Cardelli M, Piacenza F, Lattanzio F, Olivieri F, de Keizer PLJ, d'Adda di Fagagna F, Malavolta M. A Novel Cognitive Frailty Index for Geriatric Mice. Aging Cell 2025:e70056. [PMID: 40395103 DOI: 10.1111/acel.70056] [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: 09/27/2024] [Revised: 02/11/2025] [Accepted: 03/16/2025] [Indexed: 05/22/2025] Open
Abstract
Loss of cognitive function is a significant challenge in aging, and developing models to understand and target cognitive decline is crucial for the development of Geroscience-based interventions. Aged mice offer a valuable model as they share features of cognitive decline with humans. Despite numerous studies, knowledge of longitudinal age-related cognitive changes and cognitive frailty in naturally aging mice is limited, particularly in cohorts exceeding 30 months of age, where cognitive decline is more pronounced. Moreover, the impaired physical function of aged mice is known to affect latency-based strategies to measure cognitive performances. Here, we show a comprehensive longitudinal assessment using the Barnes Maze test in a large cohort of 424 aged (≥ 21 months) C57BL/6J mice. We introduced a new metric, the Cognitive Frailty Index (CoFI), which summarizes different age-associated Barnes Maze parameters into a unique function. CoFI strongly associates with advancing age and mortality, offering a reliable ability to discriminate long- and short-lived mice. We also established a CoFI cut-off and a physically adjusted CoFI, both of which can distinguish between physical and cognitive frailty. This is further supported by the enhanced predictive power when physical and cognitive frailty are combined to assess short-term mortality. Moreover, the computation method for CoFI is adaptable to various cognitive assessment tests, leveraging procedures akin to those used for calculating other frailty indices. In conclusion, through robust longitudinal tracking, CoFI has the potential to become an important ally in assessing the effectiveness of Geroscience-based interventions to counteract age-related cognitive impairment.
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Affiliation(s)
- Serena Marcozzi
- Advanced Technology Center for Aging Research and Geriatric Mouse Clinic, IRCCS INRCA, Ancona, Italy
| | - Giorgia Bigossi
- Advanced Technology Center for Aging Research and Geriatric Mouse Clinic, IRCCS INRCA, Ancona, Italy
| | - Maria Elisa Giuliani
- Advanced Technology Center for Aging Research and Geriatric Mouse Clinic, IRCCS INRCA, Ancona, Italy
| | - Giovanni Lai
- Advanced Technology Center for Aging Research and Geriatric Mouse Clinic, IRCCS INRCA, Ancona, Italy
| | - Beatrice Bartozzi
- Advanced Technology Center for Aging Research, IRCCS INRCA, Ancona, Italy
| | - Marta Balietti
- Center for Neurobiology of Aging, IRCCS INRCA, Ancona, Italy
| | - Tiziana Casoli
- Center for Neurobiology of Aging, IRCCS INRCA, Ancona, Italy
| | - Fiorenza Orlando
- Experimental Animal Models for Aging Unit, Scientific Technological Area, IRCCS INRCA, Ancona, Italy
| | | | - Robertina Giacconi
- Advanced Technology Center for Aging Research, IRCCS INRCA, Ancona, Italy
| | - Maurizio Cardelli
- Advanced Technology Center for Aging Research, IRCCS INRCA, Ancona, Italy
| | - Francesco Piacenza
- Advanced Technology Center for Aging Research, IRCCS INRCA, Ancona, Italy
| | | | - Fabiola Olivieri
- Advanced Technology Center for Aging Research, IRCCS INRCA, Ancona, Italy
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica Delle Marche, Ancona, Italy
| | - Peter L J de Keizer
- Center for Molecular Medicine, Division of Laboratories, Pharmacy and Biomedical Genetics, University Medical Center Utrecht, Utrecht, the Netherlands
- Cleara Biotech B.V., Utrecht, the Netherlands
| | - Fabrizio d'Adda di Fagagna
- IFOM ETS-The AIRC Institute of Molecular Oncology, Milan, Italy
- Institute of Molecular Genetics IGM-CNR "Luigi Luca Cavalli-Sforza", Pavia, Italy
| | - Marco Malavolta
- Advanced Technology Center for Aging Research and Geriatric Mouse Clinic, IRCCS INRCA, Ancona, Italy
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica Delle Marche, Ancona, Italy
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2
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Cavaco S, Martins da Silva A, Fernandes J, Sousa AP, Alves C, Neves Cardoso M, Teixeira-Pinto A, Coelho T. ATTRV30M amyloidosis post-liver transplant: cognition and long-term survival. Amyloid 2025:1-8. [PMID: 40205955 DOI: 10.1080/13506129.2025.2487822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2024] [Revised: 03/24/2025] [Accepted: 03/28/2025] [Indexed: 04/11/2025]
Abstract
BACKGROUND Patients with hereditary amyloidosis related to transthyretin (ATTRv amyloidosis) treated with liver transplant (LTx) often have central nervous system (CNS) manifestations, including cognitive dysfunction. The aim of this study was to explore the long-term outcome associated with neuropsychological test performance. METHODS A retrospective longitudinal review was conducted in a cohort of 289 ATTRv amyloidosis patients with the Val30Met mutation (ATTRV30M amyloidosis) who underwent a neuropsychological assessment (T1) 1-23 years (median = 11) post-LTx and 20-189 months (median = 81) prior to the study review. Clinical records were reviewed. The Kaplan-Meier and Cox regression methods were used to estimate survival and adjusted hazard ratios for all-cause mortality. RESULTS Impaired performance on Dementia Rating Scale-2, Semantic Fluency, Phonemic Fluency and Trail Making Test Part B were predictive of shorter survival after neuropsychological assessment, even when demographic and clinical variables (i.e. education, age at disease onset ≥ 50, disease duration at LTx, interval between LTx and T1, age at T1, Modified Polyneuropathy Disability score at T1, and history of focal neurological episodes at T1) were taken into account. Measures of verbal learning and memory were not predictive of mortality. CONCLUSIONS Study results demonstrate that cognitive impairment in ATTRV30M amyloidosis patients treated with LTx predicts long-term survival.
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Affiliation(s)
- Sara Cavaco
- Neuropsychology Service, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
- Unit for Multidisciplinary Research in Biomedicine, Abel Salazar Biomedical Sciences Institute, University of Porto, Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, Porto, Portugal
| | - Ana Martins da Silva
- Unit for Multidisciplinary Research in Biomedicine, Abel Salazar Biomedical Sciences Institute, University of Porto, Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, Porto, Portugal
- Corino de Andrade Unit, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
- Neurology Service, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
| | - Joana Fernandes
- Corino de Andrade Unit, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
| | - Ana Paula Sousa
- Corino de Andrade Unit, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
- Neurophysiology Service, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
| | - Cristina Alves
- Corino de Andrade Unit, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
- Neurology Service, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
| | - Márcio Neves Cardoso
- Corino de Andrade Unit, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
- Neurophysiology Service, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
| | | | - Teresa Coelho
- Corino de Andrade Unit, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
- Neurophysiology Service, Centro Hospitalar Universitário de Santo António, Unidade Local de Saúde de Santo António, Porto, Portugal
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Wei Y, Zhang Y, Li Y, Meng F, Zhang R, You Z, Xie C, Zhou J. Trajectories of Cognitive Change and Their Association with All-Cause Mortality Among Chinese Older Adults: Results from the Chinese Longitudinal Healthy Longevity Survey. Behav Sci (Basel) 2025; 15:365. [PMID: 40150260 PMCID: PMC11939546 DOI: 10.3390/bs15030365] [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: 01/24/2025] [Revised: 03/08/2025] [Accepted: 03/11/2025] [Indexed: 03/29/2025] Open
Abstract
The analysis of cognitive trajectories is relatively underexplored in China. Furthermore, most previous studies examining the association between cognitive function and mortality have been limited to cross-sectional perspectives. This study aims to identify distinct cognitive trajectories and the corresponding influencing factors and investigate the impact of these trajectories on all-cause mortality in Chinese older adults. A total of 6232 subjects aged 65 years and above were drawn from the Chinese Longitudinal Healthy Longevity Survey. Growth mixture models were utilized to identify different cognitive trajectories, while Cox proportional hazards models were used to examine the association between the cognitive trajectories and all-cause mortality after adjusting for covariates. Four cognitive trajectories were identified: rapid decline group, slow decline group, low-level stable group, and high-level stable group. Some factors such as age, sex, and marital status were significantly associated with trajectories. Compared to the high-level stable group, adjusted hazard ratios and 95% confidence intervals (CIs) for the all-cause mortality were 3.87 (95% CI: 3.35-4.48), 1.41 (95% CI: 1.24-1.59), and 1.37 (95% CI: 1.18-1.58) for the rapid decline group, the slow decline group, and the low-level stable group, respectively, indicating that these three groups had a higher mortality risk. In summary, these findings facilitate the development of targeted health promotion measures, which have implications for reducing the social and economic burdens of cognitive decline.
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Affiliation(s)
| | | | | | | | | | | | | | - Jiyuan Zhou
- Department of Biostatistics, School of Public Health (State Key Laboratory of Multi-Organ Injury Prevention and Treatment, and Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou 510515, China; (Y.W.); (Y.Z.); (Y.L.); (F.M.); (R.Z.); (Z.Y.); (C.X.)
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4
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Forbes M, Lotfaliany M, Mohebbi M, Reynolds CF, Woods RL, Orchard S, Chong T, Agustini B, O'Neil A, Ryan J, Berk M. Depressive symptoms and cognitive decline in older adults. Int Psychogeriatr 2024; 36:1039-1050. [PMID: 38623851 DOI: 10.1017/s1041610224000541] [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: 01/20/2024] [Revised: 03/15/2024] [Accepted: 03/23/2024] [Indexed: 04/17/2024]
Abstract
OBJECTIVES Few studies have examined the impact of late-life depression trajectories on specific domains of cognitive function. This study aims to delineate how different depressive symptom trajectories specifically affect cognitive function in older adults. DESIGN Prospective longitudinal cohort study. SETTING Australia and the United States of America. PARTICIPANTS In total, 11,035 community-dwelling older adults with a mean age of 75 years. MEASUREMENTS Depressive trajectories were modelled from depressive symptoms according to annual Centre for Epidemiological Studies Depression Scale 10 (CES-D-10) surveys. Four trajectories of depressive symptoms were identified: low ("nondepressed"), consistently mild ("subthreshold depression"), consistently moderate ("persistent depression"), and initially low but increasing ("emerging depression"). Global cognition (Modified Mini-Mental State Examination [3MS]), verbal fluency (Controlled Oral Word Association Test [COWAT]), processing speed (Symbol Digit Modalities Test [SDMT]), episodic memory (Hopkins Verbal Learning Test - Revised [HVLT-R]), and a composite z-score were assessed over a subsequent median 2 years. RESULTS Subthreshold depression predicted impaired performance on the SDMT (Cohen's d -0.04) and composite score (-0.03); emerging depression predicted impaired performance on the SDMT (-0.13), HVLT-R (-0.09), 3 MS (-0.08) and composite score (-0.09); and persistent depression predicted impaired performance on the SDMT (-0.08), 3 MS (-0.11), and composite score (-0.09). CONCLUSIONS Depressive symptoms are associated with later impaired processing speed. These effects are small. Diverse depression trajectories have different impacts on cognitive function.
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Affiliation(s)
- Malcolm Forbes
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), Deakin University, Geelong, VIC, Australia
| | - Mojtaba Lotfaliany
- School of Medicine, Barwon Health, Deakin University, The Institute for Mental and Physical Health and Clinical Translation (IMPACT), Geelong, VC, Australia
| | - Mohammadreza Mohebbi
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), Deakin University, Geelong, VIC, Australia
| | | | - Robyn L Woods
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Suzanne Orchard
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Trevor Chong
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Bruno Agustini
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), Deakin University, Geelong, VIC, Australia
| | - Adrienne O'Neil
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), Deakin University, Geelong, VIC, Australia
| | - Joanne Ryan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Michael Berk
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), Deakin University, Geelong, VIC, Australia
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5
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Zang E, Zhang Y, Wang Y, Wu B, Fried TR, Becher RD, Gill TM. Association Between Cognitive Trajectories and Subsequent Health Status, Depressive Symptoms, and Mortality Among Older Adults in the United States: Findings From a Nationally Representative Study. J Gerontol A Biol Sci Med Sci 2024; 79:glae143. [PMID: 38845419 PMCID: PMC11212484 DOI: 10.1093/gerona/glae143] [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: 08/07/2023] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND Cognitive decline may be an early indicator of major health issues in older adults, though research using population-based data is lacking. Researchers objective was to assess the relationships between distinct cognitive trajectories and subsequent health outcomes, including health status, depressive symptoms, and mortality, using a nationally representative cohort. METHODS Data were drawn from the National Health and Aging Trends Study. Global cognition was assessed annually between 2011 and 2018. The health status of 4 413 people, depressive symptoms in 4 342 individuals, and deaths among 5 955 living respondents were measured in 2019. Distinct cognitive trajectory groups were identified using an innovative Bayesian group-based trajectory model. Ordinal logistic, Poisson, and logistic regression models were used to examine the associations between cognitive trajectories and subsequent health outcomes. RESULTS Researchers identified five cognitive trajectory groups with distinct baseline values and subsequent changes in cognitive function. Compared with the group with stably high cognitive function, worse cognitive trajectories (ie, lower baseline values and sharper declines) were associated with higher risks of poor health status, depressive symptoms, and mortality, even after adjusting for relevant covariates. CONCLUSIONS Among older adults, worse cognitive trajectories are strongly associated with subsequent poor health status, high depressive symptoms, and high mortality risks. Regular screening of cognitive function may help to facilitate early identification and interventions for older adults susceptible to adverse health outcomes.
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Affiliation(s)
- Emma Zang
- Department of Sociology, Yale University, New Haven, Connecticut, USA
| | - Yunxuan Zhang
- Department of Biostatistics, Yale University, New Haven, Connecticut, USA
| | - Yi Wang
- Department of Internal Medicine, School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Bei Wu
- Rory Meyers College of Nursing, New York University, New York, USA
| | - Terri R Fried
- Department of Internal Medicine, School of Medicine, Yale University, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Robert D Becher
- Division of General Surgery, Trauma, and Surgical Critical Care, Department of Surgery, School of Medicine, Yale University, New Haven, Connecticut, USA
| | - Thomas M Gill
- Department of Internal Medicine, School of Medicine, Yale University, New Haven, Connecticut, USA
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6
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Lobo E, Gracia-García P, Lobo A. Longitudinal trajectories of cognitive aging. Curr Opin Psychiatry 2024; 37:123-129. [PMID: 38226551 DOI: 10.1097/yco.0000000000000918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2024]
Abstract
PURPOSE OF REVIEW This review summarizes recent evidence related to the cognitive trajectories of aging, the factors associated with the different trajectories, and the effect of sex on cognitive decline. RECENT FINDINGS Trajectories of cognitive aging identified in different studies vary in number, in the proportion of individuals falling into each of the classes and in the predictors of class membership. Trajectories observed include types with 'rapid decline', those with 'gradual decline' and those with 'maintenance of high level' of cognitive performance. Predictors of decline and predictors of maintenance of cognitive performance may be different. While factors such as education were in general associated with high performance, and reversely with low performance, other factors, such as depression were predictors only for some groups, particularly the declining ones. Sex differences in cognitive trajectories and the associated predictive factors have also been identified. SUMMARY The findings on education may be particularly important in populations with low educational level, especially among women and the findings on depression have special interest in preventing cognitive decline in women. Further work is required to explain intriguing inconsistencies observed in the literature.
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Affiliation(s)
- Elena Lobo
- Department of Preventive Medicine and Public Health, Universidad de Zaragoza
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), Zaragoza
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, Madrid
| | - Patricia Gracia-García
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), Zaragoza
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, Madrid
- Department of Medicine and Psychiatry, Universidad de Zaragoza
- Psychiatry Service, Hospital Universitario Miguel Servet, Zaragoza, Spain
| | - Antonio Lobo
- Instituto de Investigación Sanitaria de Aragón (IIS Aragón), Zaragoza
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, Madrid
- Department of Medicine and Psychiatry, Universidad de Zaragoza
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7
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Mose A, Chen Y, Tan X, Ren Q, Ren X. Association of social integration with cognitive function trajectories among Chinese older adults: evidence from the China health and retirement longitudinal study (CHARLS). Front Aging Neurosci 2024; 15:1322974. [PMID: 38274988 PMCID: PMC10808469 DOI: 10.3389/fnagi.2023.1322974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 12/26/2023] [Indexed: 01/27/2024] Open
Abstract
Background The prevalence of cognitive impairment among older adults remains high. It has been proven that social integration is related to cognitive function. However, limited research has examined the association of social integration and its different dimensions with cognitive function trajectories of older adults. Methods The data were from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2013 (T1) to 2018 (T3). A total of 3,977 older adults were included in the final analysis. Cognitive function was measured with items from an adapted Chinese version of the Mini-Mini-Mental Mental State Examination (MMSE), while the measurement of social integration included three dimensions: economic integration, relational integration and community integration. A group-based trajectory model (GBTM) was used to identify cognitive trajectory groups among participants and an unordered multinomial logistic regression was employed to explore the association of baseline social integration and its three dimensions with cognitive function trajectories. Result Three cognitive function trajectory groups were identified: low-decline group (24.1%), medium-decline group (44.2%) and high-stable group (31.7%). Comparing to the medium-decline trajectory group, older adults with higher social integration scores were more likely to be in the high-stable trajectory group (OR = 1.087, 95%CI: 1.007 ~ 1.174), while less likely to be in the low-decline group (OR = 0.806, 95%CI: 0.736 ~ 0.882). Among the different dimensions of social integration, older adults with higher community integration scores were more likely to be in the high-stable trajectory group (OR = 1.222, 95%CI: 1.026 ~ 1.456); Older adults with higher relational integration scores were less likely to be in the low-decline trajectory group (OR = 0.816, 95%CI: 0.734 ~ 0.906). The economic integration was not found to correlate with the cognitive function trajectories. Stratified analyses revealed that the association between community integration and cognitive trajectories was only significant among older adults aged 60 to 69, and the association between relational integration and cognitive trajectories was only significant among older adults who was agricultural household registration. Conclusion The developmental trajectories of cognitive function among Chinese older adults are heterogeneous. Social integration is significantly related to the trajectories of cognitive function in Chinese older adults. Measures should be taken to promote social integration of Chinese older adults to reduce the decline of cognitive function.
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Affiliation(s)
- Amu Mose
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yanhong Chen
- The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Xiaoshuang Tan
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Qingman Ren
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiaohui Ren
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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8
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Du L, Hermann BP, Jonaitis EM, Cody KA, Rivera-Rivera L, Rowley H, Field A, Eisenmenger L, Christian BT, Betthauser TJ, Larget B, Chappell R, Janelidze S, Hansson O, Johnson SC, Langhough R. Harnessing cognitive trajectory clusterings to examine subclinical decline risk factors. Brain Commun 2023; 5:fcad333. [PMID: 38107504 PMCID: PMC10724051 DOI: 10.1093/braincomms/fcad333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 10/23/2023] [Accepted: 11/30/2023] [Indexed: 12/19/2023] Open
Abstract
Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling (n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [11C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [18F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 (n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups (K-means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ2, and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults.
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Affiliation(s)
- Lianlian Du
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bruce P Hermann
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Neurology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Karly Alex Cody
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Leonardo Rivera-Rivera
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Howard Rowley
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Aaron Field
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bret Larget
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Rick Chappell
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund 205 02, Sweden
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Rebecca Langhough
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
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