Higher education is not associated with greater cortical thickness in brain areas related to literacy or intelligence in normal aging or mild cognitive impairment

Pillai, Jagan A.; McEvoy, Linda K.; Hagler, Donald J.; Holland, Dominic; Dale, Anders M.; Salmon, David P.; Galasko, Douglas; Fennema-Notestine, Christine; Initiative, Alzheimer’s Disease Neuroimaging

doi:10.1080/13803395.2012.702733

Cited by 19 publications

(19 citation statements)

References 50 publications

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“…This evidence is consistent with the early increase in Aβ levels and subsequent later increase in cerebral atrophy in the disease progression model of Jack et al [14]. Further evidence that cognitive reserve buffers the effects of the disease comes from studies by Ewers et al [460] and Pillai et al [461]. In cognitively normal patients identified as having preclinical AD by the abnormal levels of Aβ42, higher education was associated with lower glucose metabolism in the posterior cingulate and angular gyrus [460].…”

Section: Studies Of the Adni Cohortsupporting

confidence: 81%

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Weiner

Veitch

Aisen

et al. 2015

Alzheimer's & Dementia

282

224

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The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer’s disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer’s Dis 2006;9(Suppl 3):151–3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [18F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding ...

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Section: Studies Of the Adni Cohortsupporting

confidence: 81%

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Weiner

Veitch

Aisen

et al. 2015

Alzheimer's & Dementia

282

224

View full text Add to dashboard Cite

show abstract

“…While some studies have found slower rates of amyloid-beta deposition in normal controls with high CR and slower progression of hypometabolism on fluorodeoxyglucose-PET longitudinally in patients with AD with higher CR,35 others have shown no difference in cortical atrophy over time in low versus high CR patients with MCI and AD 32. Additionally, while prospective studies in non-demented older individuals have shown that patients with higher CR determined by education, occupational status and leisure activities have lower risk of progressing to dementia,2 3 36 those with high CR who are diagnosed with AD show faster rates of decline in memory function37 38 as well as processing speed and global cognitive function 39 40.…”

Section: Discussionmentioning

confidence: 99%

Effects of cognitive reserve depend on executive and semantic demands of the task

Darby

Brickhouse

Wolk

et al. 2017

J Neurol Neurosurg Psychiatry

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Background Cognitive reserve (CR) is one factor that helps to maintain cognitive function in patients with Alzheimer’s disease (AD). Whether the effects of CR depend on the semantic/executive components of the task remains unknown. Methods 470 patients (138 with AD, 332 with mild cognitive impairment (MCI)) were selected from the Alzheimer’s Disease Neuroimaging Initiative database. Linear regression models were used to determine the effects of CR (years of education) on cognitive performance after controlling for demographic factors and regional cortical atrophy. First, we assessed memory tasks with low (Auditory Verbal Learning Test (AVLT) discriminability), moderate (AVLT delayed recall) and high (Logical Memory Test (LMT) delayed recall) executive/semantic components. Next, we assessed tasks with lower (digit span forward, Trails A) or higher (digit span backwards, Trails B) executive demands, and lower (figure copying) or higher (naming, semantic fluency) semantic demands. Results High CR was significantly associated with performance on the LMT delayed recall, approached significance in the AVLT delayed recall and was not significantly associated with performance on AVLT discriminability. High CR was significantly associated with performance on the Trails B and digit span backwards, mildly associated with Trails A performance and was not associated with performance on digit span forwards. High CR was associated with performance on semantic but not visuospatial tasks. High CR was associated with semantic tasks in patients with both MCI and AD, but was only associated with executive functions in patients with MCI. Conclusion CR may relate to executive functioning and semantic knowledge, leading to preserved cognitive performance in patients with AD pathology.

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“…occupation and leisure activities) education was the only measure associated with brain structure (Foubert-Samier et al, 2010), and another study (Pillai et al, 2012) showed that education was not related to brain regions associated to intelligence.…”

Section: Discussionmentioning

confidence: 99%

Relationships between years of education and gray matter volume, metabolism and functional connectivity in healthy elders

et al. 2013

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More educated elders are less susceptible to age-related or pathological cognitive changes. We aimed at providing a comprehensive contribution to the neural mechanism underlying this effect thanks to a multimodal approach. Thirtysix healthy elders were selected based on neuropsychological assessments and cerebral amyloid imaging, i.e. as presenting normal cognition and a negative florbetapir-PET scan. All subjects underwent structural MRI, FDG-PET and resting-state functional MRI scans. We assessed the relationships between years of education and i) gray matter volume, ii) gray matter metabolism and iii) functional connectivity in the brain areas showing associations with both volume and metabolism. Higher years of education were related to greater volume in the superior temporal gyrus, insula and anterior cingulate cortex and to greater metabolism in the anterior cingulate cortex. The latter thus showed both volume and metabolism increases with education. Seed connectivity analyses based on this region showed that education was positively related to the functional connectivity between the anterior cingulate cortex and the hippocampus as well as the inferior frontal lobe, posterior cingulate cortex and angular gyrus. Increased connectivity was in turn related with improved cognitive performances. Reinforcement of the connectivity of the anterior cingulate cortex with distant cortical areas of the frontal, temporal and parietal lobes appears as one of the mechanisms underlying education-related reserve in healthy elders.

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Higher education is not associated with greater cortical thickness in brain areas related to literacy or intelligence in normal aging or mild cognitive impairment

Cited by 19 publications

References 50 publications

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Effects of cognitive reserve depend on executive and semantic demands of the task

Relationships between years of education and gray matter volume, metabolism and functional connectivity in healthy elders

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