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Heger I, van Boxtel M, Deckers K, Bosma H, Verhey F, Köhler S. Socioeconomic position, modifiable dementia risk and cognitive decline: results of 12-year Maastricht Aging Study. Int Psychogeriatr 2023:1-13. [PMID: 37905417 DOI: 10.1017/s1041610223000819] [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] [Indexed: 11/02/2023]
Abstract
OBJECTIVES This study investigated whether the association between modifiable dementia risk and rate of cognitive decline differs across socioeconomic status (SES) strata. DESIGN, SETTING AND PARTICIPANTS Data were used from Maastricht Aging Study, a prospective cohort study with a 12-year follow-up. The baseline sample consisted of 1023 adults over 40 years old. MEASUREMENTS The "LIfestyle for BRAin health" (LIBRA) index was used to assess modifiable dementia risk. Cognitive performance was assessed at baseline, 6 and 12 years, and measured in the domains of information processing speed, executive functioning and verbal memory function. An SES score was calculated from equivalent income and educational level (tertiles). Linear mixed models were used to study the association between LIBRA, SES and their interaction on the rate of cognitive decline. RESULTS Participants in the lowest SES tertile displayed more decline in information processing speed (vs. middle SES: X2 = 7.08, P = 0.029; vs. high SES: X2 = 9.49, P = 0.009) and verbal memory (vs. middle SES: X2 = 9.28, P < 0.001; vs. high SES: X2 = 16.68, P < 0.001) over 6 years compared to their middle- and high-SES counterparts. Higher (unhealthier) LIBRA scores were associated with more decline in information processing speed (X2 = 12.66, P = 0.002) over 12 years and verbal memory (X2 = 4.63, P = 0.032) over 6 years. No consistent effect modification by SES on the association between LIBRA and cognition was found. CONCLUSIONS Results suggest that lifestyle is an important determinant of cognitive decline across SES groups. Yet, people with low SES had a more unfavorable modifiable risk score suggesting more potential for lifestyle-based interventions.
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Affiliation(s)
- Irene Heger
- School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - Martin van Boxtel
- School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - Kay Deckers
- School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - Hans Bosma
- Care and Public Health Research Institute (CAPHRI), Department of Social Medicine, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Frans Verhey
- School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - Sebastian Köhler
- School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
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2
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Mohanannair Geethadevi G, Quinn TJ, George J, Anstey KJ, Bell JS, Sarwar MR, Cross AJ. Multi-domain prognostic models used in middle-aged adults without known cognitive impairment for predicting subsequent dementia. Cochrane Database Syst Rev 2023; 6:CD014885. [PMID: 37265424 PMCID: PMC10239281 DOI: 10.1002/14651858.cd014885.pub2] [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] [Indexed: 06/03/2023]
Abstract
BACKGROUND Dementia, a global health priority, has no current cure. Around 50 million people worldwide currently live with dementia, and this number is expected to treble by 2050. Some health conditions and lifestyle behaviours can increase or decrease the risk of dementia and are known as 'predictors'. Prognostic models combine such predictors to measure the risk of future dementia. Models that can accurately predict future dementia would help clinicians select high-risk adults in middle age and implement targeted risk reduction. OBJECTIVES Our primary objective was to identify multi-domain prognostic models used in middle-aged adults (aged 45 to 65 years) for predicting dementia or cognitive impairment. Eligible multi-domain prognostic models involved two or more of the modifiable dementia predictors identified in a 2020 Lancet Commission report and a 2019 World Health Organization (WHO) report (less education, hearing loss, traumatic brain injury, hypertension, excessive alcohol intake, obesity, smoking, depression, social isolation, physical inactivity, diabetes mellitus, air pollution, poor diet, and cognitive inactivity). Our secondary objectives were to summarise the prognostic models, to appraise their predictive accuracy (discrimination and calibration) as reported in the development and validation studies, and to identify the implications of using dementia prognostic models for the management of people at a higher risk for future dementia. SEARCH METHODS We searched MEDLINE, Embase, PsycINFO, CINAHL, and ISI Web of Science Core Collection from inception until 6 June 2022. We performed forwards and backwards citation tracking of included studies using the Web of Science platform. SELECTION CRITERIA: We included development and validation studies of multi-domain prognostic models. The minimum eligible follow-up was five years. Our primary outcome was an incident clinical diagnosis of dementia based on validated diagnostic criteria, and our secondary outcome was dementia or cognitive impairment determined by any other method. DATA COLLECTION AND ANALYSIS Two review authors independently screened the references, extracted data using a template based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS), and assessed risk of bias and applicability of included studies using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). We synthesised the C-statistics of models that had been externally validated in at least three comparable studies. MAIN RESULTS: We identified 20 eligible studies; eight were development studies and 12 were validation studies. There were 14 unique prognostic models: seven models with validation studies and seven models with development-only studies. The models included a median of nine predictors (range 6 to 34); the median number of modifiable predictors was five (range 2 to 11). The most common modifiable predictors in externally validated models were diabetes, hypertension, smoking, physical activity, and obesity. In development-only models, the most common modifiable predictors were obesity, diabetes, hypertension, and smoking. No models included hearing loss or air pollution as predictors. Nineteen studies had a high risk of bias according to the PROBAST assessment, mainly because of inappropriate analysis methods, particularly lack of reported calibration measures. Applicability concerns were low for 12 studies, as their population, predictors, and outcomes were consistent with those of interest for this review. Applicability concerns were high for nine studies, as they lacked baseline cognitive screening or excluded an age group within the range of 45 to 65 years. Only one model, Cardiovascular Risk Factors, Ageing, and Dementia (CAIDE), had been externally validated in multiple studies, allowing for meta-analysis. The CAIDE model included eight predictors (four modifiable predictors): age, education, sex, systolic blood pressure, body mass index (BMI), total cholesterol, physical activity and APOEƐ4 status. Overall, our confidence in the prediction accuracy of CAIDE was very low; our main reasons for downgrading the certainty of the evidence were high risk of bias across all the studies, high concern of applicability, non-overlapping confidence intervals (CIs), and a high degree of heterogeneity. The summary C-statistic was 0.71 (95% CI 0.66 to 0.76; 3 studies; very low-certainty evidence) for the incident clinical diagnosis of dementia, and 0.67 (95% CI 0.61 to 0.73; 3 studies; very low-certainty evidence) for dementia or cognitive impairment based on cognitive scores. Meta-analysis of calibration measures was not possible, as few studies provided these data. AUTHORS' CONCLUSIONS We identified 14 unique multi-domain prognostic models used in middle-aged adults for predicting subsequent dementia. Diabetes, hypertension, obesity, and smoking were the most common modifiable risk factors used as predictors in the models. We performed meta-analyses of C-statistics for one model (CAIDE), but the summary values were unreliable. Owing to lack of data, we were unable to meta-analyse the calibration measures of CAIDE. This review highlights the need for further robust external validations of multi-domain prognostic models for predicting future risk of dementia in middle-aged adults.
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Affiliation(s)
| | - Terry J Quinn
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Johnson George
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
- Faculty of Medicine, Nursing and Health Sciences, School of Public Health and Preventive Medicine, Melbourne, Australia
| | - Kaarin J Anstey
- School of Psychology, The University of New South Wales, Sydney, Australia
- Ageing Futures Institute, The University of New South Wales, Sydney, Australia
| | - J Simon Bell
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
| | - Muhammad Rehan Sarwar
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
| | - Amanda J Cross
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
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3
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Gray M, Madero EN, Gills JL, Paulson S, Jones MD, Campitelli A, Myers J, Bott NT, Glenn JM. Intervention for a Digital, Cognitive, Multi-Domain Alzheimer Risk Velocity Study: Protocol for a Randomized Controlled Trial. JMIR Res Protoc 2022; 11:e31841. [PMID: 35119374 PMCID: PMC8857690 DOI: 10.2196/31841] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 10/04/2021] [Accepted: 10/26/2021] [Indexed: 01/09/2023] Open
Abstract
Background In the United States, more than 6 million adults live with Alzheimer disease (AD) that affects 1 out of every 3 older adults. Although there is no cure for AD currently, lifestyle-based interventions aimed at slowing the rate of cognitive decline or delaying the onset of AD have shown promising results. However, most studies primarily focus on older adults (>55 years) and use in-person interventions. Objective The aim of this study is to determine the effects of a 2-year digital lifestyle intervention on AD risk among at-risk middle-aged and older adults (45-75 years) compared with a health education control. Methods The lifestyle intervention consists of a digitally delivered, personalized health coaching program that directly targets the modifiable risk factors for AD. The primary outcome measure is AD risk as determined by the Australian National University-Alzheimer Disease Risk Index; secondary outcome measures are functional fitness, blood biomarkers (inflammation, glucose, cholesterol, and triglycerides), and cognitive function (Repeatable Battery for the Assessment of Neuropsychological Status and Neurotrack Cognitive Battery). Screening commenced in January 2021 and was completed in June 2021. Results Baseline characteristics indicate no difference between the intervention and control groups for AD risk (mean −1.68, SD 7.31; P=.90). Conclusions The intervention in the Digital, Cognitive, Multi-domain Alzheimer Risk Velocity is uniquely designed to reduce the risk of AD through a web-based health coaching experience that addresses the modifiable lifestyle-based risk factors. Trial Registration ClinicalTrials.gov NCT04559789; https://clinicaltrials.gov/show/NCT04559789 International Registered Report Identifier (IRRID) DERR1-10.2196/31841
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Affiliation(s)
- Michelle Gray
- Exercise Science Research Center, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, United States
| | - Erica N Madero
- Neurotrack Technologies, Inc, Redwood City, CA, United States
| | - Joshua L Gills
- Exercise Science Research Center, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, United States
| | - Sally Paulson
- Exercise Science Research Center, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, United States
| | - Megan D Jones
- Exercise Science Research Center, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, United States
| | - Anthony Campitelli
- Exercise Science Research Center, Department of Health, Human Performance, and Recreation, University of Arkansas, Fayetteville, AR, United States
| | - Jennifer Myers
- Neurotrack Technologies, Inc, Redwood City, CA, United States
| | - Nicholas T Bott
- Neurotrack Technologies, Inc, Redwood City, CA, United States
| | - Jordan M Glenn
- Neurotrack Technologies, Inc, Redwood City, CA, United States
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4
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Anstey KJ, Zheng L, Peters R, Kootar S, Barbera M, Stephen R, Dua T, Chowdhary N, Solomon A, Kivipelto M. Dementia Risk Scores and Their Role in the Implementation of Risk Reduction Guidelines. Front Neurol 2022; 12:765454. [PMID: 35058873 PMCID: PMC8764151 DOI: 10.3389/fneur.2021.765454] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 12/07/2021] [Indexed: 12/24/2022] Open
Abstract
Dementia prevention is a global health priority. In 2019, the World Health Organisation published its first evidence-based guidelines on dementia risk reduction. We are now at the stage where we need effective tools and resources to assess dementia risk and implement these guidelines into policy and practice. In this paper we review dementia risk scores as a means to facilitate this process. Specifically, we (a) discuss the rationale for dementia risk assessment, (b) outline some conceptual and methodological issues to consider when reviewing risk scores, (c) evaluate some dementia risk scores that are currently in use, and (d) provide some comments about future directions. A dementia risk score is a weighted composite of risk factors that reflects the likelihood of an individual developing dementia. In general, dementia risks scores have a wide range of implementations and benefits including providing early identification of individuals at high risk, improving risk perception for patients and physicians, and helping health professionals recommend targeted interventions to improve lifestyle habits to decrease dementia risk. A number of risk scores for dementia have been published, and some are widely used in research and clinical trials e.g., CAIDE, ANU-ADRI, and LIBRA. However, there are some methodological concerns and limitations associated with the use of these risk scores and more research is needed to increase their effectiveness and applicability. Overall, we conclude that, while further refinement of risk scores is underway, there is adequate evidence to use these assessments to implement guidelines on dementia risk reduction.
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Affiliation(s)
- Kaarin J Anstey
- School of Psychology, University of New South Wales, Sydney, NSW, Australia.,Neuroscience Research Australia, Randwick, NSW, Australia
| | - Lidan Zheng
- School of Psychology, University of New South Wales, Sydney, NSW, Australia.,Neuroscience Research Australia, Randwick, NSW, Australia
| | - Ruth Peters
- School of Psychology, University of New South Wales, Sydney, NSW, Australia.,Neuroscience Research Australia, Randwick, NSW, Australia
| | - Scherazad Kootar
- School of Psychology, University of New South Wales, Sydney, NSW, Australia.,Neuroscience Research Australia, Randwick, NSW, Australia
| | - Mariagnese Barbera
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Ruth Stephen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Tarun Dua
- Brain Health Unit, Department of Mental Health and Substance Use, World Health Organization, Geneva, Switzerland
| | - Neerja Chowdhary
- Brain Health Unit, Department of Mental Health and Substance Use, World Health Organization, Geneva, Switzerland
| | - Alina Solomon
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, United Kingdom.,Division of Clinical Geriatrics, Department of Neurobiology, Center for Alzheimer's Research, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Miia Kivipelto
- The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, United Kingdom.,Division of Clinical Geriatrics, Department of Neurobiology, Center for Alzheimer's Research, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden.,Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
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5
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Solomon A, Stephen R, Altomare D, Carrera E, Frisoni GB, Kulmala J, Molinuevo JL, Nilsson P, Ngandu T, Ribaldi F, Vellas B, Scheltens P, Kivipelto M. Multidomain interventions: state-of-the-art and future directions for protocols to implement precision dementia risk reduction. A user manual for Brain Health Services-part 4 of 6. Alzheimers Res Ther 2021; 13:171. [PMID: 34635167 PMCID: PMC8507202 DOI: 10.1186/s13195-021-00875-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 07/06/2021] [Indexed: 11/28/2022]
Abstract
Although prevention of dementia and late-life cognitive decline is a major public health priority, there are currently no generally established prevention strategies or operational models for implementing such strategies into practice. This article is a narrative review of available evidence from multidomain dementia prevention trials targeting several risk factors and disease mechanisms simultaneously, in individuals without dementia at baseline. Based on the findings, we formulate recommendations for implementing precision risk reduction strategies into new services called Brain Health Services. A literature search was conducted using medical databases (MEDLINE via PubMed and SCOPUS) to select relevant studies: non-pharmacological multidomain interventions (i.e., combining two or more intervention domains), target population including individuals without dementia, and primary outcomes including cognitive/functional performance changes and/or incident cognitive impairment or dementia. Further literature searches covered the following topics: sub-group analyses assessing potential modifiers for the intervention effect on cognition in the multidomain prevention trials, dementia risk scores used as surrogate outcomes in multidomain prevention trials, dementia risk scores in relation to brain pathology markers, and cardiovascular risk scores in relation to dementia. Multidomain intervention studies conducted so far appear to have mixed results and substantial variability in target populations, format and intensity of interventions, choice of control conditions, and outcome measures. Most trials were conducted in high-income countries. The differences in design between the larger, longer-term trials that met vs. did not meet their primary outcomes suggest that multidomain intervention effectiveness may be dependent on a precision prevention approach, i.e., successfully identifying the at-risk groups who are most likely to benefit. One such successful trial has already developed an operational model for implementing the intervention into practice. Evidence on the efficacy of risk reduction interventions is promising, but not yet conclusive. More long-term multidomain randomized controlled trials are needed to fill the current evidence gaps, especially concerning low- and middle-income countries and integration of dementia prevention with existing cerebrovascular prevention programs. A precision risk reduction approach may be most effective for dementia prevention. Such an approach could be implemented in Brain Health Services.
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Affiliation(s)
- Alina Solomon
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.
- Division of Clinical Geriatrics, NVS, Karolinska Institutet, Stockholm, Sweden.
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK.
| | - Ruth Stephen
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Emmanuel Carrera
- Stroke Center, Department of Neurology, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Jenni Kulmala
- Division of Clinical Geriatrics, NVS, Karolinska Institutet, Stockholm, Sweden
- Department of Public Health Solutions, Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Peter Nilsson
- Department of Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden
| | - Tiia Ngandu
- Division of Clinical Geriatrics, NVS, Karolinska Institutet, Stockholm, Sweden
- Department of Public Health Solutions, Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), Saint John of God Clinical Research Centre, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Bruno Vellas
- Gérontopole of Toulouse, University Hospital of Toulouse (CHU-Toulouse), Toulouse, France
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Miia Kivipelto
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
- Division of Clinical Geriatrics, NVS, Karolinska Institutet, Stockholm, Sweden
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
- Department of Public Health Solutions, Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
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6
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Heger IS, Deckers K, Schram MT, Stehouwer CDA, Dagnelie PC, van der Kallen CJH, Koster A, Eussen SJPM, Jansen JFA, Verhey FRJ, van Boxtel MPJ, Köhler S. Associations of the Lifestyle for Brain Health Index With Structural Brain Changes and Cognition: Results From the Maastricht Study. Neurology 2021; 97:e1300-e1312. [PMID: 34433680 PMCID: PMC8480401 DOI: 10.1212/wnl.0000000000012572] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 07/01/2021] [Indexed: 11/15/2022] Open
Abstract
Background and Objectives Observational research has shown that a substantial proportion of all dementia cases worldwide are attributable to modifiable risk factors. Dementia risk scores might be useful to identify high-risk individuals and monitor treatment adherence. The objective of this study was to investigate whether a dementia risk score, the Lifestyle for Brain Health (LIBRA) index, is associated with MRI markers and cognitive functioning/impairment in the general population. Methods Cross-sectional data were used from the observational population-based cohort of The Maastricht Study. The weighted compound score of LIBRA (including 12 dementia risk and protective factors, e.g., hypertension, physical inactivity) was calculated, with higher scores indicating higher dementia risk. Standardized volumes of white matter, gray matter, and CSF (as proxy for general brain atrophy), white matter hyperintensities, and presence of cerebral small vessel disease were derived from 3T MRI. Cognitive functioning was tested in 3 domains: memory, information processing speed, and executive function and attention. Values ≤1.5 SDs below the average were defined as cognitive impairment. Multiple regression analyses and structural equation modeling were used, adjusted for age, sex, education, intracranial volume, and type 2 diabetes. Results Participants (n = 4,164; mean age 59 years; 49.7% men) with higher LIBRA scores (mean 1.19, range −2.7 to 9.2), denoting higher dementia risk, had higher volumes of white matter hyperintensities (β = 0.051, p = 0.002) and lower scores on information processing speed (β = −0.067, p = 0.001) and executive function and attention (β = −0.065, p = 0.004). Only in men, associations between LIBRA score and volumes of gray matter (β = −0.093, p < 0.001) and CSF (β = 0.104, p < 0.001) and memory (β = −0.054, p = 0.026) were found. White matter hyperintensities and CSF volume partly mediated the association between LIBRA score and cognition. Discussion Higher health- and lifestyle-based dementia risk is associated with markers of general brain atrophy, cerebrovascular pathology, and worse cognition, suggesting that LIBRA meaningfully summarizes individual lifestyle-related brain health. Improving LIBRA factors on an individual level might improve population brain health. Sex differences in lifestyle-related pathology and cognition need to be further explored. Classification of Evidence This study provides Class II evidence that higher LIBRA scores are significantly associated with lower scores in some cognitive domains and a higher risk of cognitive impairment.
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Affiliation(s)
- Irene S Heger
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands.
| | - Kay Deckers
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Miranda T Schram
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Coen D A Stehouwer
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Pieter C Dagnelie
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Carla J H van der Kallen
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Annemarie Koster
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Simone J P M Eussen
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Jacobus F A Jansen
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Frans R J Verhey
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Martin P J van Boxtel
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
| | - Sebastian Köhler
- From the School for Mental Health and Neuroscience (I.S.H., K.D., M.T.S., J.F.A.J., F.R.J.V., M.P.J.v.B., S.K.), Department of Psychiatry and Neuropsychology (I.S.H., K.D., F.R.J.V., M.P.J.v.B., S.K.), School for Cardiovascular Diseases (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K., S.J.P.M.E.), Care and Public Health Research Institute (A.K.), Department of Social Medicine (A.K.), and Department of Epidemiology (S.J.P.M.E.), Maastricht University; and Heart and Vascular Center (M.T.S.), Department of Internal Medicine (M.T.S., C.D.A.S., P.C.D., C.J.H.v.d.K.), and Department of Radiology (J.F.A.J.), Maastricht University Medical Center+, the Netherlands
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7
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Stephen R, Ngandu T, Liu Y, Peltonen M, Antikainen R, Kemppainen N, Laatikainen T, Lötjönen J, Rinne J, Strandberg T, Tuomilehto J, Vanninen R, Soininen H, Kivipelto M, Solomon A. Change in CAIDE Dementia Risk Score and Neuroimaging Biomarkers During a 2-Year Multidomain Lifestyle Randomized Controlled Trial: Results of a Post-Hoc Subgroup Analysis. J Gerontol A Biol Sci Med Sci 2021; 76:1407-1414. [PMID: 33970268 PMCID: PMC8277089 DOI: 10.1093/gerona/glab130] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Indexed: 11/29/2022] Open
Abstract
The CAIDE (Cardiovascular Risk Factors, Aging and Dementia) Risk Score is a validated tool estimating dementia risk. It was previously associated with imaging biomarkers. However, associations between dementia risk scores (including CAIDE) and dementia-related biomarkers have not been studied in the context of an intervention. This study investigated associations between change in CAIDE score and change in neuroimaging biomarkers (brain magnetic resonance imaging [MRI] and Pittsburgh Compound B-positron emission tomography [PiB-PET] measures) during the 2-year Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) (post-hoc analyses). FINGER targeted at-risk older adults, aged 60–77 years, from the general population. Participants were randomized to either multidomain intervention (diet, exercise, cognitive training, and vascular risk management) or control group (general health advice). Neuroimaging (MRI and PiB-PET) data from baseline and 2-year visits were used. A toal of 112 participants had repeated brain MRI measures (hippocampal, total gray matter, and white matter lesion volumes, and Alzheimer’s disease signature cortical thickness). Repeated PiB-PET scans were available for 39 participants. Reduction in CAIDE score (indicating lower dementia risk) during the intervention was associated with less decline in hippocampus volume in the intervention group, but not the control group (Randomization group × CAIDE change interaction β coefficient = −0.40, p = .02). Associations for other neuroimaging measures were not significant. The intervention may have benefits on hippocampal volume in individuals who succeed in improving their overall risk level as indicated by a reduction in CAIDE score. This exploratory finding requires further testing and validation in larger studies.
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Affiliation(s)
- Ruth Stephen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
| | - Tiia Ngandu
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland.,Division of Clinical Geriatrics, Center for Alzheimer Research, NVS, Karolinska Institutet, Stockholm, Sweden
| | - Yawu Liu
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Clinical Radiology, Kuopio University Hospital, Finland
| | - Markku Peltonen
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Riitta Antikainen
- Center for Life Course Health Research/Geriatrics, University of Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital and Oulu City Hospital, Finland
| | - Nina Kemppainen
- Division of Clinical Neurosciences, Turku University Hospital, Finland.,Turku PET Centre, University of Turku, Finland
| | - Tiina Laatikainen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.,Joint Municipal Authority for North Karelia Social and Health Services, Joensuu, Finland.,Department of Public Health Solutions, National Institute for Health and Welfare Helsinki, Finland
| | | | - Juha Rinne
- Division of Clinical Neurosciences, Turku University Hospital, Finland.,Turku PET Centre, University of Turku, Finland
| | - Timo Strandberg
- Center for Life Course Health Research/Geriatrics, University of Oulu, Finland.,University of Helsinki, Clinicum, and Helsinki University Hospital, Finland
| | - Jaakko Tuomilehto
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland.,Department of Public Health, University of Helsinki, Finland.,South Ostrobothnia Central Hospital, Seinäjoki, Finland.,Department of Neurosciences and Preventive Medicine, Danube-University Krems, Austria.,Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ritva Vanninen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Clinical Radiology, Kuopio University Hospital, Finland
| | - Hilkka Soininen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.,Neurocenter, Neurology, Kuopio University Hospital, Finland
| | - Miia Kivipelto
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.,Division of Clinical Geriatrics, Center for Alzheimer Research, NVS, Karolinska Institutet, Stockholm, Sweden.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.,Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, UK
| | - Alina Solomon
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.,Division of Clinical Geriatrics, Center for Alzheimer Research, NVS, Karolinska Institutet, Stockholm, Sweden.,Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, UK
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8
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Anstey KJ, Cherbuin N, Kim S, McMaster M, D'Este C, Lautenschlager N, Rebok G, McRae I, Torres SJ, Cox KL, Pond CD. An Internet-Based Intervention Augmented With a Diet and Physical Activity Consultation to Decrease the Risk of Dementia in At-Risk Adults in a Primary Care Setting: Pragmatic Randomized Controlled Trial. J Med Internet Res 2020; 22:e19431. [PMID: 32969833 PMCID: PMC7545332 DOI: 10.2196/19431] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 07/28/2020] [Accepted: 08/03/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND There is a need to develop interventions to reduce the risk of dementia in the community by addressing lifestyle factors and chronic diseases over the adult life course. OBJECTIVE This study aims to evaluate a multidomain dementia risk reduction intervention, Body Brain Life in General Practice (BBL-GP), targeting at-risk adults in primary care. METHODS A pragmatic, parallel, three-arm randomized trial involving 125 adults aged 18 years or older (86/125, 68.8% female) with a BMI of ≥25 kg/m2 or a chronic health condition recruited from general practices was conducted. The arms included (1) BBL-GP, a web-based intervention augmented with an in-person diet and physical activity consultation; (2) a single clinician-led group, Lifestyle Modification Program (LMP); and (3) a web-based control. The primary outcome was the Australian National University Alzheimer Disease Risk Index Short Form (ANU-ADRI-SF). RESULTS Baseline assessments were conducted on 128 participants. A total of 125 participants were randomized to 3 groups (BBL-GP=42, LMP=41, and control=42). At immediate, week 18, week 36, and week 62 follow-ups, the completion rates were 43% (18/42), 57% (24/42), 48% (20/42), and 48% (20/42), respectively, for the BBL-GP group; 71% (29/41), 68% (28/41), 68% (28/41), and 51% (21/41), respectively, for the LMP group; and 62% (26/42), 69% (29/42), 60% (25/42), and 60% (25/42), respectively, for the control group. The primary outcome of the ANU-ADRI-SF score was lower for the BBL-GP group than the control group at all follow-ups. These comparisons were all significant at the 5% level for estimates adjusted for baseline differences (immediate: difference in means -3.86, 95% CI -6.81 to -0.90, P=.01; week 18: difference in means -4.05, 95% CI -6.81 to -1.28, P<.001; week 36: difference in means -4.99, 95% CI -8.04 to -1.94, P<.001; and week 62: difference in means -4.62, 95% CI -7.62 to -1.62, P<.001). CONCLUSIONS A web-based multidomain dementia risk reduction program augmented with allied health consultations administered within the general practice context can reduce dementia risk exposure for at least 15 months. This study was limited by a small sample size, and replication on a larger sample with longer follow-up will strengthen the results. TRIAL REGISTRATION Australian clinical trials registration number (ACTRN): 12616000868482; https://anzctr.org.au/ACTRN12616000868482.aspx.
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Affiliation(s)
- Kaarin J Anstey
- School of Psychology, University of New South Wales, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia.,Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, Australia
| | - Nicolas Cherbuin
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, Australia
| | - Sarang Kim
- Wicking Dementia Resaerch & Education Centre, University of Tasmania, Hobart, Australia
| | - Mitchell McMaster
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, Australia
| | - Catherine D'Este
- National Centre for Epidemiology and Public Health, Australian National University, Canberra, Australia.,School of Medicine and Public Health, University of Newcastle, Newcastle, Australia
| | - Nicola Lautenschlager
- Academic Unit for Psychiatry of Old Age, University of Melbourne, Melbourne, Australia
| | - George Rebok
- Johns Hopkins Centre on Aging and Health, Johns Hopkins University, Baltimore, MD, United States
| | - Ian McRae
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, Australia
| | - Susan J Torres
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, Australia
| | - Kay L Cox
- Medical School, University of Western Australia, Perth, Australia
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9
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Leocadi M, Canu E, Calderaro D, Corbetta D, Filippi M, Agosta F. An update on magnetic resonance imaging markers in AD. Ther Adv Neurol Disord 2020; 13:1756286420947986. [PMID: 33747128 PMCID: PMC7903819 DOI: 10.1177/1756286420947986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 07/09/2020] [Indexed: 12/22/2022] Open
Abstract
The purpose of the present review is to provide an update of the available recent scientific literature on the use of magnetic resonance imaging (MRI) in Alzheimer's disease (AD). MRI is playing an increasingly important role in the characterization of the AD signatures, which can be useful in both the diagnostic process and monitoring of disease progression. Furthermore, this technique is unique in assessing brain structure and function and provides a deep understanding of in vivo evolution of cerebral pathology. In the reviewing process, we established a priori criteria and we thoroughly searched the very recent scientific literature (January 2018-March 2020) for relevant articles on this topic. In summary, we selected 73 articles out of 1654 publications retrieved from PubMed. Based on this selection, this review summarizes the recent application of MRI in clinical trials, defining the predementia stages of AD, the clinical utility of MRI, proposal of novel biomarkers and brain regions of interest, and assessing the relationship between MRI and cognitive features, risk and protective factors of AD. Finally, the value of a multiparametric approach in clinical and preclinical stages of AD is discussed.
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Affiliation(s)
- Michela Leocadi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Davide Calderaro
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Davide Corbetta
- Laboratory of Movement Analysis, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Neurology and Neurophysiology Units, IRCCS San Raffaele Scientific Institute, and Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, and Vita-Salute San Raffaele University, Via Olgettina 60, Milan 20132, Italy
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10
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Stephen R, Soininen H. Biomarker validation of a dementia risk prediction score. Nat Rev Neurol 2020; 16:135-136. [DOI: 10.1038/s41582-020-0316-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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11
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Giannakopoulos P, Rodriguez C, Montandon ML, Garibotto V, Haller S, Herrmann FR. Personality Factors' Impact on the Structural Integrity of Mentalizing Network in Old Age: A Combined PET-MRI Study. Front Psychiatry 2020; 11:552037. [PMID: 33312132 PMCID: PMC7704441 DOI: 10.3389/fpsyt.2020.552037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 10/16/2020] [Indexed: 11/13/2022] Open
Abstract
The mentalizing network (MN) treats social interactions based on our understanding of other people's intentions and includes the medial prefrontal cortex (mPFC), temporoparietal junction (TPJ), posterior cingulate cortex (PCC), precuneus (PC), and amygdala. Not all elders are equally affected by the aging-related decrease of mentalizing abilities. Personality has recently emerged as a strong determinant of functional connectivity in MN areas. However, its impact on volumetric changes across the MN in brain aging is still unknown. To address this issue, we explored the determinants of volume decrease in MN components including amyloid burden, personality, and APOE genotyping in a previously established cohort of 130 healthy elders with a mean follow-up of 54 months. Personality was assessed with the Neuroticism Extraversion Openness Personality Inventory-Revised. Regression models corrected for multiple comparisons were used to identify predictors of volume loss including time, age, sex, personality, amyloid load, presence of APOE epsilon 4 allele, and cognitive evolution. In cases with higher Agreeableness scores, there were lower volume losses in PCC, PC, and amygdala bilaterally. This was also the case for the right mPFC in elders displaying lower Agreeableness and Conscientiousness. In multiple regression models, the effect of Agreeableness was still observed in left PC and right amygdala and that of Conscientiousness was still observed in right mPFC volume loss (26.3% of variability, significant age and sex). Several Agreeableness (Modesty) and Conscientiousness (order, dutifulness, achievement striving, and self-discipline) facets were positively related to increased volume loss in cortical components of the MN. In conclusion, these data challenge the beneficial role of higher levels of Agreeableness and Conscientiousness in old age, showing that they are associated with an increased rate of volume loss within the MN.
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Affiliation(s)
- Panteleimon Giannakopoulos
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Medical Direction, Geneva University Hospitals, Geneva, Switzerland
| | - Cristelle Rodriguez
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Medical Direction, Geneva University Hospitals, Geneva, Switzerland
| | - Marie-Louise Montandon
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Medical Direction, Geneva University Hospitals, Geneva, Switzerland.,Department of Readaptation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals, Geneva, Switzerland.,Faculty of Medicine of the University of Geneva, Geneva, Switzerland
| | - Sven Haller
- Faculty of Medicine of the University of Geneva, Geneva, Switzerland.,CIRD - Centre d'Imagerie Rive Droite, Geneva, Switzerland.,Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
| | - François R Herrmann
- Department of Readaptation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
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