Apolipoprotein E-e4, Processing Speed, and White Matter Volume in a Genetically Enriched Sample of Midlife Adults

Ready, Rebecca E.; Baran, Bengi; Chaudhry, Maheen; Schatz, Kelly C.; Gordon, Joseph A.; Spencer, Rebecca M. C.

doi:10.1177/1533317511421921

Cited by 17 publications

(12 citation statements)

References 37 publications

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“…Age is the most important risk factor for AD, but surprisingly, apoE4 genotype impacts cognition even in healthy, non-demented, and young individuals (9,10). Also, whereas longitudinal cognitive decline is steeper in apoE4 carriers (11,12,68), numerous reports have shown that the effect of apoE4 on cognition is actually greater in younger than in older subjects (45)(46)(47).…”

Section: Discussionmentioning

confidence: 99%

Cognitive Deficits and Disruption of Neurogenesis in a Mouse Model of Apolipoprotein E4 Domain Interaction

Adeosun

Hou

Zheng

et al. 2014

Journal of Biological Chemistry

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Background: Domain interaction may be the principal pathogenic feature of apoE4 in Alzheimer disease. Results: Young and old mice with mutations causing apoE4 domain interaction showed impaired cognition and a disruption in neurogenesis. Conclusion: Domain interaction mediates apoE4 neuro-pathologies and cognitive phenotype. Significance: Domain interaction is a viable prophylactic target against apoE4 cognitive phenotype and increased susceptibility to Alzheimer disease.

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Section: Discussionmentioning

confidence: 99%

Cognitive Deficits and Disruption of Neurogenesis in a Mouse Model of Apolipoprotein E4 Domain Interaction

Adeosun

Hou

Zheng

et al. 2014

Journal of Biological Chemistry

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“…This greater neural recruitment by the MS group relative to healthy controls was interpreted to be consistent with the neural efficiency hypothesis, further supporting the belief that more connections must be recruited to maintain performance in the presence of brain pathology. Similarly, Ready and colleagues (2011) noted decreased white matter volume to be significantly correlated with slower processing speed in a sample of healthy midlife children of a parent with Alzheimer's disease. The authors concluded PS and changes in white matter volume to be potential indicators of preclinical decline in Alzheimer’s disease.…”

Section: Introductionmentioning

confidence: 88%

NIH Toolbox Cognitive Battery (NIHTB-CB): The NIHTB Pattern Comparison Processing Speed Test

Carlozzi

Tulsky

Chiaravalloti

et al. 2014

J Int Neuropsychol Soc

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The NIH Toolbox (NIHTB) Pattern Comparison Processing Speed Test was developed to assess processing speed within the NIHTB for the Assessment of Neurological Behavior and Function Cognition Battery (NIHTB-CB). This study highlights validation data collected in adults ages 18–85 on this measure and reports descriptive data, test–retest reliability, construct validity, and preliminary work creating a composite index of processing speed. Results indicated good test–retest reliability. There was also evidence for both convergent and discriminant validity; the Pattern Comparison Processing Speed Test demonstrated moderate significant correlations with other processing speed tests (i.e., WAIS-IV Coding, Symbol Search and Processing Speed Index), small significant correlations with measures of working memory (i.e., WAIS-IV Letter-Number Sequencing and PASAT), and non-significant correlations with a test of vocabulary comprehension (i.e., PPVT-IV). Finally, analyses comparing and combining scores on the NIHTB Pattern Comparison Processing Speed Test with other measures of simple reaction time from the NIHTB-CB indicated that a Processing Speed Composite score performed better than any test examined in isolation. The NIHTB Pattern Comparison Processing Speed Test exhibits several strengths: it is appropriate for use across the lifespan (ages, 3–85 years), it is short and easy to administer, and it has high construct validity.

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“…Healthy individuals with ApoE4 are characterised by less white matter volume (Ready et al, 2011) (age = 53) and a higher rate of myelin breakdown in an older sample (Bartzokis et al, 2006) (age = 66). Furthermore, ApoE4 carriers have also showed decreased FA in widespread white matter tracts associated with temporal lobe structures, including the cingulum (Smith et al, 2010) (age = 58), corpus callosum, and longitudinal fasciculus (Heise et al, 2011;Lyall et al, 2014).…”

Section: Apolipoprotein E4 and Family Historymentioning

confidence: 99%

Structural neuroimaging in preclinical dementia: From microstructural deficits and grey matter atrophy to macroscale connectomic changes

Mak

Gabel

Habib

et al. 2017

Ageing Research Reviews

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The last decade has witnessed a proliferation of neuroimaging studies characterising brain changes associated with Alzheimer's disease (AD), where both widespread atrophy and 'signature' brain regions have been implicated. In parallel, a prolonged latency period has been established in AD, with abnormal cerebral changes beginning many years before symptom onset. This raises the possibility of early therapeutic intervention, even before symptoms, when treatments could have the greatest effect on disease-course modification. Two important prerequisites of this endeavour are (1) accurate characterisation or risk stratification and (2) monitoring of progression using neuroimaging outcomes as a surrogate biomarker in those without symptoms but who will develop AD, here referred to as preclinical AD. Structural neuroimaging modalities have been used to identify brain changes related to risk factors for AD, such as familial genetic mutations, risk genes (for example apolipoprotein epsilon-4 allele), and/or family history. In this review, we summarise structural imaging findings in preclinical AD. Overall, the literature suggests early vulnerability in characteristic regions, such as the medial temporal lobe structures and the precuneus, as well as white matter tracts in the fornix, cingulum and corpus callosum. We conclude that while structural markers are promising, more research and validation studies are needed before future secondary prevention trials can adopt structural imaging biomarkers as either stratification or surrogate biomarkers.

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Apolipoprotein E-e4, Processing Speed, and White Matter Volume in a Genetically Enriched Sample of Midlife Adults

Cited by 17 publications

References 37 publications

Cognitive Deficits and Disruption of Neurogenesis in a Mouse Model of Apolipoprotein E4 Domain Interaction

Cognitive Deficits and Disruption of Neurogenesis in a Mouse Model of Apolipoprotein E4 Domain Interaction

NIH Toolbox Cognitive Battery (NIHTB-CB): The NIHTB Pattern Comparison Processing Speed Test

Structural neuroimaging in preclinical dementia: From microstructural deficits and grey matter atrophy to macroscale connectomic changes

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