Life-course determinants of cognitive reserve (CR) in cognitive aging and dementia – a systematic literature review

Chapko, Dorota; McCormack, Roisin; Black, Corri; Staff, Roger T.; Murray, Alison

doi:10.1080/13607863.2017.1348471

Cited by 132 publications

(137 citation statements)

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“…5 Cognitive reserve is modeled as a reflective indicator here, meaning that the measurement model treats observable factors whose shared covariation identifies the latent variable as downstream outcomes of the latent reserve construct. 26 A life course perspective to cognitive reserve in dementia has been suggested previously, 6 but only a handful of studies were able to implement it. This suggests that cognitive reserve is a formative, rather than a reflective latent indicator.…”

Section: Discussionmentioning

confidence: 99%

“…Even though several neuroimaging and clinicopathological studies have largely supported the presence of a neural basis for efficiency and compensation, 24,25 there is still much need for methodological development of the cognitive reserve concept. 26 A life course perspective to cognitive reserve in dementia has been suggested previously, 6 but only a handful of studies were able to implement it. 27 A recent study from our group has attempted to test the relevant importance of stages (early, mid-, and late life) at which cognitive reserve exerted the largest protection against dementia risk.…”

Section: Discussionmentioning

confidence: 99%

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Genetic risk of dementia mitigated by cognitive reserve: A cohort study

Dekhtyar

Marseglia

et al. 2019

Annals of Neurology

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Objective We investigated whether cognitive reserve modifies the risk of dementia attributable to apolipoprotein ε4 ( APOE‐ ε4), a well‐known genetic risk factor for dementia. Methods We followed 2,556 cognitively intact participants aged ≥60 years from the ongoing prospective community‐based Swedish National Study on Aging and Care in Kungsholmen (SNAC‐K). Dementia was ascertained through clinical and neuropsychological assessments and diagnosed according to Diagnostic and Statistical Manual of Mental Disorders, 4th edition criteria. Structural equation modeling was used to generate a cognitive reserve indicator from 4 previously validated contributors: early life education, midlife substantive work complexity, late life leisure activities, and late life social networks. Cox proportional hazard models estimated dementia risk in relation to cognitive reserve indicator. The interaction between the cognitive reserve indicator and APOE‐ ε4 was assessed on multiplicative and additive scales. Results After an average of 6.3 years (range = 2.1–10.7) of follow‐up, 232 dementia cases were ascertained. Relative to individuals in the lowest tertile of cognitive reserve indicator, those with moderate and high reserve were at a reduced risk of dementia. There was no multiplicative interaction between APOE‐ ε4 status and cognitive reserve indicator ( p = 0.113). Additive interaction was statistically significant. Relative to APOE‐ ε4 carriers with low cognitive reserve, ε4 carriers with high reserve had a reduced risk of dementia (hazard ratio [HR] = 0.28, 95% confidence interval [CI] = 0.13–0.59). The magnitude of risk reduction was similar in ε4 noncarriers with a high cognitive reserve indicator (HR = 0.24, 95% CI = 0.15–0.40). Interpretation Lifelong engagement in reserve‐enhancing activities attenuates the risk of dementia attributable to APOE ‐ε4. Promoting cognitive reserve might be especially effective in subpopulations with high genetic risk of dementia. ANN NEUROL 2019

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Genetic risk of dementia mitigated by cognitive reserve: A cohort study

Dekhtyar

Marseglia

et al. 2019

Annals of Neurology

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“…Far fewer studies examined risk factors for earlier onset of dementia (ie, age of dementia onset), especially in autopsy‐confirmed samples. Age of onset is often related to the notion of “cognitive reserve,” in which individuals may have hastened or delayed onset of cognitive impairments with similar brain pathology due to flexible factors such as education, premorbid intelligence, and occupational attainment . Evaluating age of onset not only may help elucidate how various risk factors differentially impact AD versus LBD, but also offer insights into areas of intervention that may delay cognitive onset.…”

Section: Introductionmentioning

confidence: 99%

“…Age of onset is often related to the notion of "cognitive reserve," in which individuals may have hastened or delayed onset of cognitive impairments with similar brain pathology due to flexible factors such as education, premorbid intelligence, and occupational attainment. 13 Evaluating age of onset not only may help elucidate how various risk factors differentially impact AD versus LBD, but also offer insights into areas of intervention that may delay cognitive onset. As such, it was our aim to investigate modifiable and non-modifiable factors, such as demographics, family history, genetic, mood, and cardiovascular variables, as risk factors for earlier dementia onset in autopsy-confirmed samples of AD, mixed AD + LBD, and pure LBD.…”

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confidence: 99%

Risk factors for earlier dementia onset in autopsy‐confirmed Alzheimer's disease, mixed Alzheimer's with Lewy bodies, and pure Lewy body disease

Schaffert

LoBue

White

et al. 2020

Alzheimer's & Dementia

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Introduction Clinical Alzheimer's disease (AD) and dementia with Lewy bodies often have mixed AD and Lewy pathology, making it difficult to delineate risk factors. Methods Six risk factors for earlier dementia onset due to autopsy‐confirmed AD (n = 647), mixed AD and Lewy body disease (AD + LBD; n = 221), and LBD (n = 63) were entered into multiple linear regressions using data from the National Alzheimer's Coordinating Center. Results In AD and AD + LBD, male sex and apolipoprotein E (APOE) ɛ4 alleles each predicted a 2‐ to 3‐year‐earlier onset and depression predicted a 3‐year‐earlier onset. In LBD, higher education predicted earlier onset and depression predicted a 5.5‐year‐earlier onset. Discussion Male sex and APOE ɛ4 alleles increase risk for earlier dementia onset in AD but not LBD. Depression increases risk for earlier dementia onset in AD, LBD, and AD + LBD, but evaluating the course, treatment, and severity is needed in future studies.

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“…[5][6][7][8][9] All of these factors contribute to increasing cognitive reserve (CR), defined as an active process whereby the brain adapts to a situation of deterioration by using cognitive processing resources to compensate for the deficits. [5][6][7][8][9] All of these factors contribute to increasing cognitive reserve (CR), defined as an active process whereby the brain adapts to a situation of deterioration by using cognitive processing resources to compensate for the deficits.…”

Section: Introductionmentioning

confidence: 99%

Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia

Facal

Valladares-Rodríguez

Lojo‐Seoane

et al. 2019

Int J Geriat Psychiatry

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Objectives The overall aim of the present study was to explore the role of cognitive reserve (CR) in the conversion from mild cognitive impairment (MCI) to dementia. We used traditional and machine learning (ML) techniques to compare converter and nonconverter participants. We also discuss the predictive value of CR proxies in relation to the ML model performance. Methods In total, 169 participants completed the longitudinal study. Participants were divided into a control group and three MCI subgroups, according to the Petersen criteria for diagnosis. Information about the participants was compared using nine ML classification techniques. Seven relevant performance metrics were computed in order to evaluate the accuracy of prediction regarding converter and nonconverter participants. Results ML algorithms applied to socio‐demographic, basic health, and CR proxy data enabled prediction of conversion to dementia. The best performing models were the gradient boosting classifier (accuracy (ACC) = 0.93; F1 = 0.86, and Cohen κ = 0.82) and random forest classifier (ACC = 0.92; F1 = 0.79, and Cohen κ = 0.71). Use of ML techniques corroborated the protective role of CR as a mediator of conversion to dementia, whereby participants with more years of education and higher vocabulary scores survived longer without developing dementia. Conclusions We used ML approaches to explore the role of CR in conversion from MCI to dementia. The findings indicate the potential value of ML algorithms for detecting risk of conversion to dementia in cognitive aging and CR studies. Further research is required to develop an ML‐based procedure that can be used to make robust predictions.

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Life-course determinants of cognitive reserve (CR) in cognitive aging and dementia – a systematic literature review

Abstract: Further research on modifiable determinants of CR beyond education/occupation including early-life factors and consensus on CR definition are warranted.

Cited by 132 publications

References 50 publications

Genetic risk of dementia mitigated by cognitive reserve: A cohort study

Genetic risk of dementia mitigated by cognitive reserve: A cohort study

Risk factors for earlier dementia onset in autopsy‐confirmed Alzheimer's disease, mixed Alzheimer's with Lewy bodies, and pure Lewy body disease

Machine learning approaches to studying the role of cognitive reserve in conversion from mild cognitive impairment to dementia

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