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Zhu P, Gao S, Wu S, Li X, Huang C, Chen Y, Liu G. Causal relationships between dyslexia and the risk of eight dementias. Transl Psychiatry 2024; 14:371. [PMID: 39266518 PMCID: PMC11393330 DOI: 10.1038/s41398-024-03082-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 08/20/2024] [Accepted: 08/30/2024] [Indexed: 09/14/2024] Open
Abstract
Observational and genetic studies have reported the relationship between dyslexia and Alzheimer's disease (AD). Until now, the causal effect of dyslexia on AD risk has remained unclear. We conducted a two-sample univariable Mendelian randomization (MR) analysis to determine the causal association between dyslexia and the risk of AD, vascular dementia (VD), Lewy body dementia (LBD), and frontotemporal dementia (FTD) and its four subtypes. First, we selected 42 dyslexia genetic variants from a large-scale genome-wide association studies (GWAS) dataset and extracted their corresponding GWAS summary statistics from AD, VD, LBD, and FTD. Second, we selected four MR methods, including inverse-variance weighted (IVW), weighted median, MR-Egger, and MR-PRESSO. Heterogeneity, horizontal pleiotropy, and leave-one-out sensitivity analysis were then used to evaluate the reliability of all causal estimates. We also conducted multivariable MR (MVMR) and mediation analysis to assess the potential mediating role of cognitive performance (CP) or educational achievement (EA) on the causal association between dyslexia and AD. Two MVMR methods, including MV IVW and MV-Egger, and two-step MR were used to perform the analysis. Using IVW, we found a significant causal association between increased dyslexia and increased risk of AD (OR = 1.15, 95% CI: 1.04-1.28, P = 0.006), but not VD, LBD, FTD, or its four subtypes. MR-PRESSO further supported the statistically significant association between dyslexia and AD (OR = 1.15, 95% CI: 1.05-1.27, P = 0.006). All sensitivity analyses confirmed the reliability of causal estimates. Using MV IVW and mediation analysis, we found no causal relationship between dyslexia and AD after adjusting for CP but not EA, CP mediated the total effect of dyslexia on AD with a proportion of 46.32%. We provide genetic evidence to support a causal effect of increased dyslexia on increased risk of AD, which was largely mediated by CP. Reading activity may be a potential intervention strategy for AD by improving cognitive function.
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Affiliation(s)
- Ping Zhu
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, 100069, Beijing, China
| | - Shan Gao
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, 100069, Beijing, China
| | - Shiyang Wu
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, 100069, Beijing, China
| | - Xuan Li
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, 100069, Beijing, China
| | - Chen Huang
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Taipa, 999078, Macao SAR, China
| | - Yan Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wannan Medical College, No. 22, Wenchang Road, 241002, Wuhu, Anhui, China.
| | - Guiyou Liu
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, 100069, Beijing, China.
- Department of Epidemiology and Biostatistics, School of Public Health, Wannan Medical College, No. 22, Wenchang Road, 241002, Wuhu, Anhui, China.
- Brain Hospital, Shengli Oilfield Central Hospital, Dongying, China.
- Beijing Key Laboratory of Hypoxia Translational Medicine, National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, 100053, Beijing, China.
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Gao Y, Zhang Z, Song J, Gan T, Lin Y, Hu M, Wu IX. Combined healthy lifestyle behaviours and incident dementia: A systematic review and dose-response meta-analysis of cohort studies. Int J Nurs Stud 2024; 156:104781. [PMID: 38744152 DOI: 10.1016/j.ijnurstu.2024.104781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 04/25/2024] [Accepted: 04/26/2024] [Indexed: 05/16/2024]
Abstract
BACKGROUND The associations of combined healthy lifestyle behaviours and incident dementia have not been systematically reviewed and the dose-response relationship was uncertain. OBJECTIVES To evaluate the associations of combined healthy lifestyle behaviours with incident dementia and other cognitive outcomes, assess the dose-response relationship between the number of lifestyle behaviours and incident dementia, and summarise the adherence to healthy lifestyle behaviours. DESIGN Systematic review and meta-analysis. METHODS PubMed, EMBASE, Web of Science and PsycINFO were searched from inception to 20 Jan 2024. Cohort studies reporting associations of combined healthy lifestyle behaviours with incident dementia or other cognitive outcomes were included. We used the random-effects meta-analysis to pool the risk estimates and the robust error meta-regression method to examine the dose-response relationship. The methodological quality was assessed using the Newcastle-Ottawa Scale. RESULTS A total of 22 articles including 25 cohort studies mostly from high-income economics were included, with all assessed as high methodological quality. Adherence to a healthy lifestyle was associated with a decreased risk of incident dementia, either per healthy lifestyle behaviour increase (pooled hazard ratio 0.89, 95 % confidence interval 0.85-0.94) or the highest level versus the lowest level (pooled hazard ratio 0.61, 95 % confidence interval 0.49-0.76). An inverse, linear dose-response relationship (Pnon-linear = 0.845) between the number of healthy lifestyle behaviours and incident dementia was observed, with an 11 % risk reduction for each healthy behaviour increase. A relatively limited number of included studies indicated that adherence to a healthy lifestyle combination could yield benefits for cognitive decline, global cognition, memory and executive function. In addition, the adherence rates typically decreased as the number of healthy lifestyle behaviours increased. CONCLUSIONS Adherence to a healthy lifestyle was associated with a lower risk of incident dementia and other cognitive outcomes. It is important to find a subtle balance between the benefits and adherence. Further large cohort studies for combined lifestyle behaviours with specific cognitive outcomes and dose-response relationships are required, especially based on middle- and low-income populations. REGISTRATION The study was registered in PROSPERO (CRD42023418509). TWEETABLE ABSTRACT Engaging in a greater number of healthy lifestyle behaviours yields increased benefits in preventing dementia, albeit with lower adherence rates as a trade-off. Finding a delicate balance between the benefits and adherence is crucial.
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Affiliation(s)
- Yinyan Gao
- Xiangya School of Public Health, Central South University, Changsha, China
| | - Zixuan Zhang
- Changsha Center for Disease Control and Prevention, Changsha, China
| | - Jinlu Song
- Xiangya School of Public Health, Central South University, Changsha, China
| | - Ting Gan
- School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia
| | - Yali Lin
- Shenzhen Center for Chronic Disease Control, Shenzhen, China
| | - Mingyue Hu
- Xiangya School of Nursing, Central South University, Changsha, China
| | - Irene Xinyin Wu
- Xiangya School of Public Health, Central South University, Changsha, China; Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, China.
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Wilson RS, Yu L, Stewart CC, Bennett DA, Boyle PA. Change in Decision-Making Analysis and Preferences in Old Age. J Gerontol B Psychol Sci Soc Sci 2023; 78:1659-1667. [PMID: 36856705 PMCID: PMC10561891 DOI: 10.1093/geronb/gbad037] [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: 02/22/2022] [Indexed: 03/02/2023] Open
Abstract
OBJECTIVES To test the hypotheses that decision making ability declines in old age and that a higher level of cognitive reserve is associated with a reduced rate of decline. METHODS As part of an ongoing cohort study, 982 older adults without dementia at study enrollment completed measures of purpose in life and cognitive activity which were used as markers of cognitive reserve. At annual intervals thereafter, they completed 6 tests of decision making. RESULTS In a factor analysis of baseline decision making scores, 3 measures (financial/health literacy, financial/health decision making, scam susceptibility) loaded on an "analytic" factor and 3 (temporal discounting small stakes, temporal discounting large stakes, risk aversion) loaded on a "preferences" (for temporal discounting and avoiding risk) factor. During a mean of 4.7 years of follow-up (standard deviation = 2.9), analytic factor scores decreased (mean = 0.042-unit per year, standard error [SE] = 0.006, p < .001) and preferences factor scores increased (mean = 0.021-unit per year, SE = 0.006, p < .001), with a correlation of 0.13 (p < .001) between rates of change. Evidence of an association between cognitive reserve and decision making was mixed with purpose in life related to change in analytic decision making, whereas past (but not current) cognitive activity was related to change in decision making preferences. DISCUSSION Decision making analysis and preferences change over time in late life. Change over time in decision making components is relatively independent and differentially related to age and cognitive reserve.
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Affiliation(s)
- Robert S Wilson
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Lei Yu
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Christopher C Stewart
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - David A Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Patricia A Boyle
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois, USA
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Mathys H, Peng Z, Boix CA, Victor MB, Leary N, Babu S, Abdelhady G, Jiang X, Ng AP, Ghafari K, Kunisky AK, Mantero J, Galani K, Lohia VN, Fortier GE, Lotfi Y, Ivey J, Brown HP, Patel PR, Chakraborty N, Beaudway JI, Imhoff EJ, Keeler CF, McChesney MM, Patel HH, Patel SP, Thai MT, Bennett DA, Kellis M, Tsai LH. Single-cell atlas reveals correlates of high cognitive function, dementia, and resilience to Alzheimer's disease pathology. Cell 2023; 186:4365-4385.e27. [PMID: 37774677 PMCID: PMC10601493 DOI: 10.1016/j.cell.2023.08.039] [Citation(s) in RCA: 79] [Impact Index Per Article: 79.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 05/20/2023] [Accepted: 08/29/2023] [Indexed: 10/01/2023]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia worldwide, but the molecular and cellular mechanisms underlying cognitive impairment remain poorly understood. To address this, we generated a single-cell transcriptomic atlas of the aged human prefrontal cortex covering 2.3 million cells from postmortem human brain samples of 427 individuals with varying degrees of AD pathology and cognitive impairment. Our analyses identified AD-pathology-associated alterations shared between excitatory neuron subtypes, revealed a coordinated increase of the cohesin complex and DNA damage response factors in excitatory neurons and in oligodendrocytes, and uncovered genes and pathways associated with high cognitive function, dementia, and resilience to AD pathology. Furthermore, we identified selectively vulnerable somatostatin inhibitory neuron subtypes depleted in AD, discovered two distinct groups of inhibitory neurons that were more abundant in individuals with preserved high cognitive function late in life, and uncovered a link between inhibitory neurons and resilience to AD pathology.
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Affiliation(s)
- Hansruedi Mathys
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA.
| | - Zhuyu Peng
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Carles A Boix
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Matheus B Victor
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Noelle Leary
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Sudhagar Babu
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Ghada Abdelhady
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Xueqiao Jiang
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Ayesha P Ng
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Kimia Ghafari
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Alexander K Kunisky
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Julio Mantero
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kyriaki Galani
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Vanshika N Lohia
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Gabrielle E Fortier
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Yasmine Lotfi
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Jason Ivey
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Hannah P Brown
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Pratham R Patel
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Nehal Chakraborty
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Jacob I Beaudway
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Elizabeth J Imhoff
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Cameron F Keeler
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Maren M McChesney
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Haishal H Patel
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Sahil P Patel
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Megan T Thai
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | | | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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Caldwell JZ, Isenberg N. The aging brain: risk factors and interventions for long term brain health in women. Curr Opin Obstet Gynecol 2023; 35:169-175. [PMID: 36912325 PMCID: PMC10023345 DOI: 10.1097/gco.0000000000000849] [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] [Indexed: 03/14/2023]
Abstract
PURPOSE OF REVIEW Poor cognitive aging and dementia pose a significant public health burden, and women face unique risks compared to men. Recent research highlights the role of genetics, menopause, chronic disease, and lifestyle in risk and resilience in women's cognitive aging. This work suggests avenues for clinical action at midlife that may change the course of brain health in aging. RECENT FINDINGS Studies indicate women's risk for poor cognitive aging relates in part to hormone changes at menopause, a time when memory, brain structure and function, and Alzheimer's pathology may be observed in women and not men. Medical and lifestyle risks including diabetes, hypertension, and low physical activity also contribute to women's unique risks. At the same time, literature on resilience suggests women may benefit from lifestyle and chronic disease intervention, possibly more than men. Current studies emphasize the importance of interacting genetic and lifestyle risks, and effects of social determinants of health. SUMMARY Women have greater risk than men for poor cognitive aging; however, by treating the whole person, including genetics, lifestyle, and social environment, clinicians have an opportunity to support healthy cognitive aging in women and reduce the future public health burden of dementia.
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Affiliation(s)
- Jessica Z.K. Caldwell
- Cleveland Clinic Lou Ruvo Center for Brain Health, 888 W. Bonneville Ave., Las Vegas, NV 89106
| | - Nancy Isenberg
- Providence Swedish Center for Healthy Aging, Swedish Neuroscience Institute, 1600 E. Jefferson St. A Level, Seattle, WA 98122
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Vaquero-Rodríguez A, Ortuzar N, Lafuente JV, Bengoetxea H. Enriched environment as a nonpharmacological neuroprotective strategy. Exp Biol Med (Maywood) 2023; 248:553-560. [PMID: 37309729 PMCID: PMC10350798 DOI: 10.1177/15353702231171915] [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] [Indexed: 06/14/2023] Open
Abstract
The structure and functions of the central nervous system are influenced by environmental stimuli, which also play an important role in brain diseases. Enriched environment (EE) consists of producing modifications in the environment of standard laboratory animals to induce an improvement in their biological conditions. This paradigm promotes transcriptional and translational effects that result in ameliorated motor, sensory, and cognitive stimulation. EE has been shown to enhance experience-dependent cellular plasticity and cognitive performance in animals housed under these conditions compared with animals housed under standard conditions. In addition, several studies claim that EE induces nerve repair by restoring functional activities through morphological, cellular, and molecular adaptations in the brain that have clinical relevance in neurological and psychiatric disorders. In fact, the effects of EE have been studied in different animal models of psychiatric and neurological diseases, such as Alzheimer's disease, Parkinson's disease, schizophrenia, ischemic brain injury, or traumatic brain injury, delaying the onset and progression of a wide variety of symptoms of these disorders. In this review, we analyze the action of EE focused on diseases of the central nervous system and the translation to humans to develop a bridge to its application.
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Affiliation(s)
- Andrea Vaquero-Rodríguez
- Department of Neurosciences, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), 48940 Leioa, Spain
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Spain
| | - Naiara Ortuzar
- Department of Neurosciences, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), 48940 Leioa, Spain
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Spain
| | - José Vicente Lafuente
- Department of Neurosciences, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), 48940 Leioa, Spain
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Spain
| | - Harkaitz Bengoetxea
- Department of Neurosciences, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), 48940 Leioa, Spain
- Neurodegenerative Diseases Group, Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Spain
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Lee AJ, Ma Y, Yu L, Dawe RJ, McCabe C, Arfanakis K, Mayeux R, Bennett DA, Klein HU, De Jager PL. Multi-region brain transcriptomes uncover two subtypes of aging individuals with differences in Alzheimer risk and the impact of APOEε4. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.25.524961. [PMID: 36747803 PMCID: PMC9900823 DOI: 10.1101/2023.01.25.524961] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
The heterogeneity of the older population suggests the existence of subsets of individuals which share certain brain molecular features and respond differently to risk factors for Alzheimer's disease, but this population structure remains poorly defined. Here, we performed an unsupervised clustering of individuals with multi-region brain transcriptomes to assess whether a broader approach, simultaneously considering data from multiple regions involved in cognition would uncover such subsets. We implemented a canonical correlation-based analysis in a Discovery cohort of 459 participants from two longitudinal studies of cognitive aging that have RNA sequence profiles in three brain regions. 690 additional participants that have data in only one or two of these regions were used in the Replication effort. These clustering analyses identified two meta-clusters, MC-1 and MC-2. The two sets of participants differ primarily in their trajectories of cognitive decline, with MC-2 having a delay of 3 years to the median age of incident dementia. This is due, in part, to a greater impact of tau pathology on neuronal chromatin architecture and to broader brain changes including greater loss of white matter integrity in MC-1. Further evidence of biological differences includes a significantly larger impact of APOEε4 risk on cognitive decline in MC-1. These findings suggest that our proposed population structure captures an aspect of the more distributed molecular state of the aging brain that either enhances the effect of risk factors in MC-1 or of protective effects in MC-2. These observations may inform the design of therapeutic development efforts and of trials as both become increasingly more targeted molecularly. One Sentence Summary: There are two types of aging brains, with one being more vulnerable to APOEε4 and subsequent neuronal dysfunction and cognitive loss.
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Liao H, Pan D, Deng Z, Jiang J, Cai J, Liu Y, He B, Lei M, Li H, Li Y, Xu Y, Tang Y. Association of shift work with incident dementia: a community-based cohort study. BMC Med 2022; 20:484. [PMID: 36522755 PMCID: PMC9753386 DOI: 10.1186/s12916-022-02667-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 11/17/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Some observational studies had found that shift work would increase risks of metabolic disorders, cancers, and cardiovascular diseases, but there was no homogeneous evidence of such an association between shift work and incident dementia. This study aimed to investigate whether shift work would increase the risk of dementia in a general population. METHODS One hundred seventy thousand seven hundred twenty-two employed participants without cognitive impairment or dementia at baseline recruited between 2006 and 2010 were selected from the UK Biobank cohort study. Follow-up occurred through June 2021. Shift work status at baseline was self-reported by participants and they were categorized as non-shift workers or shift workers. Among shift workers, participants were further categorized as night shift workers or shift but non-night shift workers. The primary outcome was all-cause dementia in a time-to-event analysis, and the secondary outcomes were subtypes of dementia, including Alzheimer's disease, vascular dementia, and other types of dementia. RESULTS In total, 716 dementia cases were observed among 170,722 participants over a median follow-up period of 12.4 years. Shift workers had an increased risk of all-cause dementia as compared with non-shift workers after multivariable adjustment (hazard ratio [HR], 1.30, 95% confidence interval [CI], 1.08-1.58); however, among shift workers, night shift work was not associated with the risk of dementia (HR, 1.04, 95% CI, 0.73-1.47). We found no significant interaction between shift work and genetic predisposition to dementia on the primary outcome (P for interaction = 0.77). CONCLUSIONS Shift work at baseline was associated with an increased risk of all-cause dementia. Among shift workers, there was no significant association between night shift work and the risk of dementia. The increased incidence of dementia in shift workers did not differ between participants in different genetic risk strata for dementia.
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Affiliation(s)
- Huanquan Liao
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
- Department of Neurology, the Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 517108, People's Republic of China
| | - Dong Pan
- Department of Neurology, the Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518033, People's Republic of China
| | - Zhenhong Deng
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
| | - Jingru Jiang
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
| | - Jinhua Cai
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
| | - Ying Liu
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
| | - Baixuan He
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
| | - Ming Lei
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
| | - Honghong Li
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
| | - Yi Li
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
| | - Yongteng Xu
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China
| | - Yamei Tang
- Department of Neurology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China.
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China.
- Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510062, People's Republic of China.
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Qiu Y, Sha L, Zhang X, Li G, Zhu W, Xu Q. Induction of A Disintegrin and Metalloproteinase with Thrombospondin motifs 1 by a rare variant or cognitive activities reduces hippocampal amyloid-β and consequent Alzheimer’s disease risk. Front Aging Neurosci 2022; 14:896522. [PMID: 36016856 PMCID: PMC9395645 DOI: 10.3389/fnagi.2022.896522] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 07/15/2022] [Indexed: 11/30/2022] Open
Abstract
Amyloid-β (Aβ) derived from amyloid precursor protein (APP) hydrolysis is acknowledged as the predominant hallmark of Alzheimer’s disease (AD) that especially correlates to genetics and daily activities. In 2019, meta-analysis of AD has discovered five new risk loci among which A Disintegrin and Metalloproteinase with Thrombospondin motifs 1 (ADAMTS1) has been further suggested in 2021 and 2022. To verify the association, we re-sequenced ADAMTS1 of clinical AD samples and subsequently identified a novel rare variant c.–2067A > C with watchable relevance (whereas the P-value was not significant after adjustment). Dual-luciferase assay showed that the variant sharply stimulated ADAMTS1 expression. In addition, ADAMTS1 was also clearly induced by pentylenetetrazol-ignited neuronal activity and enriched environment (EE). Inspired by the above findings, we investigated ADAMTS1’s role in APP metabolism in vitro and in vivo. Results showed that ADAMTS1 participated in APP hydrolysis and consequently decreased Aβ generation through inhibiting β-secretase-mediated cleavage. In addition, we also verified that the hippocampal amyloid load of AD mouse model was alleviated by the introduction of ADAMTS1, and thus spatial cognition was restored as well. This study revealed the contribution of ADAMTS1 to the connection of genetic and acquired factors with APP metabolism, and its potential in reducing hippocampal amyloid and consequent risk of AD.
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Affiliation(s)
- Yunjie Qiu
- State Key Laboratory of Medical Molecular Biology, School of Basic Medicine Peking Union Medical College, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, Beijing, China
| | - Longze Sha
- State Key Laboratory of Medical Molecular Biology, School of Basic Medicine Peking Union Medical College, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, Beijing, China
- Neuroscience Center, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiuneng Zhang
- State Key Laboratory of Medical Molecular Biology, School of Basic Medicine Peking Union Medical College, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, Beijing, China
| | - Guanjun Li
- State Key Laboratory of Medical Molecular Biology, School of Basic Medicine Peking Union Medical College, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, Beijing, China
| | - Wanwan Zhu
- State Key Laboratory of Medical Molecular Biology, School of Basic Medicine Peking Union Medical College, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, Beijing, China
- Neuroscience Center, Chinese Academy of Medical Sciences, Beijing, China
| | - Qi Xu
- State Key Laboratory of Medical Molecular Biology, School of Basic Medicine Peking Union Medical College, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, Beijing, China
- Neuroscience Center, Chinese Academy of Medical Sciences, Beijing, China
- *Correspondence: Qi Xu,
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10
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Pruzin JJ, Klein H, Rabin JS, Schultz AP, Kirn DR, Yang H, Buckley RF, Scott MR, Properzi M, Rentz DM, Johnson KA, Sperling RA, Chhatwal JP. Physical activity is associated with increased resting-state functional connectivity in networks predictive of cognitive decline in clinically unimpaired older adults. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12319. [PMID: 35821672 PMCID: PMC9261733 DOI: 10.1002/dad2.12319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 03/21/2022] [Accepted: 04/14/2022] [Indexed: 04/08/2023]
Abstract
Introduction Physical activity (PA) promotes resilience with respect to cognitive decline, although the underlying mechanisms are not well understood. We examined the associations between objectively measured PA and resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) across seven anatomically distributed neural networks. Methods rs-fcMRI, amyloid beta (Aβ) positron emission tomography (PET), PA (steps/day × 1 week), and longitudinal cognitive (Preclinical Alzheimer's Cognitive Composite) data from 167 cognitively unimpaired adults (ages 63 to 90) were used. We used linear and linear mixed-effects regression models to examine the associations between baseline PA and baseline network connectivity and between PA, network connectivity, and longitudinal cognitive performance. Results Higher PA was associated selectively with greater connectivity in three networks previously associated with cognitive decline (default, salience, left control). This association with network connectivity accounted for a modest portion of PA's effects on Aβ-related cognitive decline. Discussion Although other mechanisms are likely present, PA may promote resilience with respect to Aß-related cognitive decline, partly by increasing connectivity in a subset of cognitive networks.
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Affiliation(s)
- Jeremy J. Pruzin
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Banner Alzheimer's InstitutePhoenixArizonaUSA
| | - Hannah Klein
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Jennifer S. Rabin
- Hurvitz Brain Sciences ProgramSunnybrook Research InstituteTorontoOntarioCanada
- Harquail Centre for NeuromodulationSunnybrook Health Sciences CentreTorontoCanada
- Division of NeurologyDepartment of MedicineSunnybrook Health Sciences CentreUniversity of TorontoTorontoCanada
- Rehabilitation Sciences InstituteUniversity of TorontoTorontoCanada
| | - Aaron P. Schultz
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical ImagingDepartment of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Dylan R. Kirn
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Center for Alzheimer Research and TreatmentDepartment of NeurologyBrigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Hyun‐Sik Yang
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Rachel F. Buckley
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Center for Alzheimer Research and TreatmentDepartment of NeurologyBrigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Florey InstituteUniversity of MelbourneParkvilleVictoriaAustralia
- Melbourne School of Psychological SciencesUniversity of MelbourneParkvilleVictoriaAustralia
| | - Mathew R. Scott
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Department of BiostatisticsBoston UniversityBostonMAUSA
| | - Michael Properzi
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Dorene M. Rentz
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Center for Alzheimer Research and TreatmentDepartment of NeurologyBrigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Keith A. Johnson
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical ImagingDepartment of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Center for Alzheimer Research and TreatmentDepartment of NeurologyBrigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Reisa A. Sperling
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical ImagingDepartment of RadiologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Center for Alzheimer Research and TreatmentDepartment of NeurologyBrigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Jasmeer P. Chhatwal
- Department of NeurologyMassachusetts General HospitalMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Center for Alzheimer Research and TreatmentDepartment of NeurologyBrigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
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11
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Voits T, DeLuca V, Abutalebi J. The Nuance of Bilingualism as a Reserve Contributor: Conveying Research to the Broader Neuroscience Community. Front Psychol 2022; 13:909266. [PMID: 35814120 PMCID: PMC9263506 DOI: 10.3389/fpsyg.2022.909266] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/07/2022] [Indexed: 11/25/2022] Open
Abstract
The neurological notion of "reserve" arises from an individually observable dissociation between brain health and cognitive status. According to the cognitive reserve hypothesis, high-reserve individuals experience functional compensation for neural atrophy and, thus, are able to maintain relatively stable cognitive functioning with no or smaller-than-expected impairment. Several lifestyle factors such as regular physical exercise, adequate and balanced nutrition, and educational attainment have been widely reported to contribute to reserve and, thus, lead to more successful trajectories of cognitive aging (CA). In recent years, it has become clear that bilingualism is also a potential reserve contributor. Yet, there is little communication between the neuroscience of bilingualism research community and researchers working in the field of CA more generally, despite compelling reasons for it. In fact, bilingualism tends to be overlooked as a contributory factor in the CA literature, or reduced to a dichotomous trait, despite it being a complex experience. Herein, we discuss issues that are preventing recognition of bilingualism as a reserve contributor across all literatures, highlight the benefits of including language experiences as a factor of interest across research disciplines, and suggest a roadmap to better integrate bilingualism and aging moving forward. We close with calls toward a model of aging that examines the contributions across lifestyle factors, including that of bilingual experience.
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Affiliation(s)
- Toms Voits
- PoLaR Lab, AcqVA Aurora Centre, UiT The Arctic University of Norway, Tromsø, Norway
| | - Vincent DeLuca
- PoLaR Lab, AcqVA Aurora Centre, UiT The Arctic University of Norway, Tromsø, Norway
| | - Jubin Abutalebi
- PoLaR Lab, AcqVA Aurora Centre, UiT The Arctic University of Norway, Tromsø, Norway
- Centre for Neurolinguistics and Psycholinguistics (CNPL), Vita-Salute San Raffaele University, Milan, Italy
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12
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Ashford JW, Schmitt FA, Bergeron MF, Bayley PJ, Clifford JO, Xu Q, Liu X, Zhou X, Kumar V, Buschke H, Dean M, Finkel SI, Hyer L, Perry G. Now is the Time to Improve Cognitive Screening and Assessment for Clinical and Research Advancement. J Alzheimers Dis 2022; 87:305-315. [DOI: 10.3233/jad-220211] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Alzheimer’s disease (AD) is the only cause of death ranked in the top ten globally without precise early diagnosis or effective means of prevention or treatment. Further, AD was identified as a pandemic [1] well before COVID-19 was dubbed a 21st century pandemic [2]. And now, with the realization of the prominent secondary impacts of pandemics, there is a growing, widespread recognition of the tremendous magnitude of the impending burden from AD in an aging world population in the coming decades [3]. This appreciation has amplified the growing and pressing need for a new, efficacious, and practical platform to detect and track cognitive decline, beginning in the preliminary (prodromal) phases of the disease, sensitively, accurately, effectively, reliably, efficiently, and remotely [4–7]. Moreover, the parallel necessity of clarifying and understanding risk factors, developing successful prevention strategies [8–17], and discovering and monitoring viable and effective treatments could all benefit from accurate and efficient screening and assessment platforms. Modern recognition of AD [18] as a common affliction of the elderly began in 1968 with a paper by Blessed, Tomlinson, & Roth [19] in which two tests, one a brief assessment of cognitive function and the other a measure of daily function, demonstrated impairment which was associated with the postmortem counts of neurofibrillary tangles, composed mainly of microtubule-associated protein-tau (tau), in the brain, though not to senile plaques, composed mainly of amyloid-β (Aβ). Even in more recent analyses, the tangles correspond with the severity of dementia more than the plaques [20, 21]. Since 1960, a plethora of cognitive tests, paper and pencil [22, 23], simple screening models [24], and computerized [25–27], have been developed to assess the dysfunction associated with AD. However, there has been limited application of Modern Test Theory, which includes Item Characteristic Curve Analysis, used in the technological development of such tools [28–31], along with widespread failure to understand the underlying AD pathological process to guide test development [32, 33]. The lack of such development has likely been a major contributor to the failure of the field to develop timely screening approaches for AD [34, 35], inaccurate assessment of the progression of AD [36], and even now, failure to find an effective approach to stopping AD.
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Affiliation(s)
- J. Wesson Ashford
- War Related Illness and Injury Study Center, VA Palo Alto HCS, Palo Alto, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
| | - Frederick A. Schmitt
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- Departments of Neurology, Psychiatry, Neurosurgery, Psychology, Behavioral Science; Sanders-Brown Center on Aging, Spinal Cord & Brain Injury Research Center, University of Kentucky, Sanders-Brown Center on Aging, Lexington, KY, USA
| | | | - Peter J. Bayley
- War Related Illness and Injury Study Center, VA Palo Alto HCS, Palo Alto, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
| | | | - Qun Xu
- Health Management Center, Department of Neurology, Renji Hospital of Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaolei Liu
- Department of Neurology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
- Yunnan Provincial Clinical Research Center for Neurological Diseases, Yunnan, China
| | - Xianbo Zhou
- Center for Alzheimer’s Research, Washington Institute of Clinical Research, Vienna, VA, USA
- Zhongze Therapeutics, Shanghai, China
| | | | - Herman Buschke
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- The Saul R. Korey Department of Neurology and Dominick P. Purpura Department of Neuroscience, Lena and Joseph Gluck Distinguished Scholar in Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Margaret Dean
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- Geriatric Division, Internal Medicine, Texas Tech Health Sciences Center, Amarillo, TX, USA
| | - Sanford I. Finkel
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- University of Chicago Medical School, Chicago, IL, USA
| | - Lee Hyer
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- Gateway Behavioral Health, Mercer University, School of Medicine, Savannah, GA, USA
| | - George Perry
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- Brain Health Consortium, Department Biology and Chemistry, University of Texas at San Antonio, San Antonio, TX, USA
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13
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Grodstein F, Wang T, Leurgans SE, Wilson RS, Bennett DA. Modifiable psychosocial risk factors and delayed onset of dementia in older populations: analysis of two prospective US cohorts. BMJ Open 2022; 12:e059317. [PMID: 35379643 PMCID: PMC8981290 DOI: 10.1136/bmjopen-2021-059317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 03/16/2022] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVE Preventing Alzheimer's dementia (AD) fundamentally equates to delaying onset. Thus, we quantified associations of modifiable, psychosocial risk factors to years of delayed onset of dementia. DESIGN Two prospective cohorts (n=2860) with negative and positive psychosocial factors measured at baseline (depressive symptoms, neuroticism, cognitive activity). SETTING AND PARTICIPANTS Religious Orders Study of older priests, nuns and brothers across the USA, initiated in 1994; Rush Memory and Aging Project, of older persons in Chicago area, initiated in 1997. OUTCOME MEASURE We conducted annual neurological and neuropsychological assessments to identify AD (n=785 incident cases). We compared age at diagnosis of AD across psychosocial risk factor groups, controlling for confounders, using accelerated failure time models. RESULTS We found strong relations of three or more depressive symptoms with age at AD diagnosis; estimated mean age at diagnosis was 86.9 years with significant symptoms versus 92.1 years with no symptoms (p=0.001). In addition, neuroticism was inversely related to age at AD diagnosis; estimated mean age at diagnosis was 88.8 years for the highest neuroticism tertile and 93.1 years in the lowest tertile (p<0.001). Participants with higher cognitive activity (such as reading books) had later AD diagnosis; estimated mean age at diagnosis was 89.2 years for the lowest cognitive activity group and 92.6 years for the highest activity group (p<0.001). CONCLUSIONS Higher depressive symptoms were associated with 5-year acceleration in AD; higher neuroticism with 4-year acceleration and higher cognitive activity with a 3.5-year delay. To translate findings, prior health services research in the USA indicates delaying dementia 5 years could add 3 years of life and reduce individual costs of care >$60 000. These results provide a rigorous, easily translatable metric for communicating and evaluating the potential public health impact of psychosocial and experiential interventions.
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Affiliation(s)
- Francine Grodstein
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Tianhao Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Sue E Leurgans
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Robert S Wilson
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
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14
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Krauss H. Reader Response: Cognitive Activity and Onset Age of Incident Alzheimer Disease Dementia. Neurology 2022. [DOI: 10.1212/wnl.0000000000013131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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15
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Wilson RS. Author Response: Cognitive Activity and Onset Age of Incident Alzheimer Disease Dementia. Neurology 2022. [DOI: 10.1212/wnl.0000000000013133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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16
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Koebele SV, Quihuis AM, Lavery CN, Plumley ZMT, Castaneda AJ, Bimonte-Nelson HA. Oestrogen treatment modulates the impact of cognitive experience and task complexity on memory in middle-aged surgically menopausal rats. J Neuroendocrinol 2021; 33:e13002. [PMID: 34378820 PMCID: PMC9124643 DOI: 10.1111/jne.13002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 06/10/2021] [Accepted: 06/12/2021] [Indexed: 11/28/2022]
Abstract
Menopause has been linked to changes in memory. Oestrogen-containing hormone therapy is prescribed to treat menopause-related symptoms and can ameliorate memory changes, although the parameters impacting oestrogen-related memory efficacy are unclear. Cognitive experience and practice have been shown to be neuroprotective and to improve learning and memory during ageing, with the type of task playing a role in subsequent cognitive outcomes. Whether task complexity matters, and whether these outcomes interact with menopause and oestrogen status, remains unknown. To investigate this, we used a rat model of surgical menopause to systematically assess whether maze task complexity, as well as order of task presentation, impacts spatial learning and memory during middle age when rats received vehicle, low-17β-oestradiol (E2 ) or high-E2 treatment. The direction, and even presence, of the effects of prior maze experience differed depending on the E2 dose. Surgical menopause without E2 treatment yielded the least benefit, as prior maze experience did not have a substantial effect on subsequent task performance for vehicle treated rats regardless of task demand level during the first exposure to maze experience or final testing. High-dose E2 yielded a variable benefit, and low-dose E2 produced the greatest benefit. Specifically, low-dose E2 broadly enhanced learning and memory in surgically menopausal rats that had prior experience on another task, regardless of the complexity level of this prior experience. These results demonstrate that E2 dose influences the impact of prior cognitive experience on learning and memory during ageing, and highlights the importance of prior cognitive experience in subsequent learning and memory outcomes.
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Affiliation(s)
- Stephanie V. Koebele
- Department of Psychology, Arizona State University, Tempe, AZ, USA
- Arizona Alzheimer’s Consortium, Phoenix, AZ, USA
| | - Alicia M. Quihuis
- Department of Psychology, Arizona State University, Tempe, AZ, USA
- Arizona Alzheimer’s Consortium, Phoenix, AZ, USA
| | - Courtney N. Lavery
- Department of Psychology, Arizona State University, Tempe, AZ, USA
- Arizona Alzheimer’s Consortium, Phoenix, AZ, USA
| | - Zachary M. T. Plumley
- Department of Psychology, Arizona State University, Tempe, AZ, USA
- Arizona Alzheimer’s Consortium, Phoenix, AZ, USA
| | - Arthur J. Castaneda
- Department of Psychology, Arizona State University, Tempe, AZ, USA
- Arizona Alzheimer’s Consortium, Phoenix, AZ, USA
| | - Heather A. Bimonte-Nelson
- Department of Psychology, Arizona State University, Tempe, AZ, USA
- Arizona Alzheimer’s Consortium, Phoenix, AZ, USA
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