The association between higher order abilities, processing speed, and age are variably mediated by white matter integrity during typical aging

Borghesani, Paul R.; Madhyastha, Tara M.; Aylward, Elizabeth H.; Reiter, M.; Swarny, Bruce R.; Schaie, K. Warner; Willis, Sherry L.

doi:10.1016/j.neuropsychologia.2013.03.005

Cited by 92 publications

(92 citation statements)

References 85 publications

(130 reference statements)

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“…There is evidence that late‐myelinating white matter is more susceptible to the age‐related degeneration (Bartzokis, 2004), thus our data may capture this process by showing that older individuals rely more on the integrity of such incipiently deteriorating WM tracts. Overall, our results are well in line with earlier reports on the role of white matter integrity in cognitive processing speed (Kochunov et al, 2010) and more in general executive functions (Borghesani et al, 2013; Kochunov et al, 2009), and further extend previous findings to the macrostructural properties of white matter fiber bundles.…”

Section: Discussionsupporting

confidence: 93%

“…To this respect, previous studies reported that reduced processing speed was related to impaired white matter, as indexed by both micro and macrostructural integrity (Borghesani et al, 2013; Kochunov et al, 2010). In another study, Kochunov et al (2009) further demonstrated a positive association between white matter span and executive control.…”

Section: Introductionmentioning

confidence: 96%

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Episodic memory and executive functions in cognitively healthy individuals display distinct neuroanatomical correlates which are differentially modulated by aging

Cacciaglia

Molinuevo

Sánchez‐Benavides

et al. 2018

Human Brain Mapping

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The neuroanatomical bases of episodic memory (EM) and executive functions (EFs) have been widely addressed in patients with brain damage and in individuals with neurologic disorders. These studies reported that larger brain structures support better outcomes in both cognitive domains, thereby supporting the “bigger is better” account. However, relatively few studies have explored the cerebral morphological properties underlying EM and EFs in cognitively healthy individuals and current findings indicate no unitary theoretical explanation for the structure–function relationship. Moreover, existing studies have typically restricted the analyses to a priori defined regions of interest. Here we conducted unbiased voxel‐wise analysis of the associations between regional gray as well as white matter volumes (GMv; WMv) and performance in both cognitive domains in a sample of 463 cognitively intact individuals. We found that efficiency in EM was predicted by lower GMv in brain areas belonging to the default‐mode network (DMN). By contrast, EFs performance was predicted by larger GMv in a distributed set of regions, which overlapped with the executive control network (ECN). Volume of white matter bundles supporting both cross‐cortical and interhemispheric connections was positively related to processing speed. Furthermore, aging modulated the relationship between regional volumes and cognitive performance in several areas including the hippocampus and frontal cortex. Our data extend the critical role of the DMN and ECN by showing that variability in their morphological properties, and not only their activation patterns, affects EM and EFs, respectively. Moreover, our finding that aging reverts these associations supports previously advanced theories of cognitive neurodevelopment.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 96%

Episodic memory and executive functions in cognitively healthy individuals display distinct neuroanatomical correlates which are differentially modulated by aging

Cacciaglia

Molinuevo

Sánchez‐Benavides

et al. 2018

Human Brain Mapping

View full text Add to dashboard Cite

show abstract

“…Also, consistent with the literature, we found evidence for modest phenotypic correlations between neurocognitive and white-matter integrity, particularly for tests of speed of processing (27,38,39), working and declarative memory (12,13), and IQ (14,25). However, our findings extend this work by Fig.…”

Section: Discussionsupporting

confidence: 92%

“…However, reports associating white-matter integrity and cognitive aging are inconsistent, with some suggesting localized effects (13)(14)(15)(16)(17) and others pointing to global white-matter changes as the best predictors of agerelated cognitive changes (18). Evidence for pleiotropy between neurocognitive and white-matter traits is sparse (19,20), raising the possibility that age-related declines in these two classes of phenotypes may reflect independent genetic pathways.…”

Section: Significancementioning

confidence: 99%

Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging

Glahn

Kent

Sprooten

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Identification of genes associated with brain aging should markedly improve our understanding of the biological processes that govern normal age-related decline. However, challenges to identifying genes that facilitate successful brain aging are considerable, including a lack of established phenotypes and difficulties in modeling the effects of aging per se, rather than genes that influence the underlying trait. In a large cohort of randomly selected pedigrees (n = 1,129 subjects), we documented profound aging effects from young adulthood to old age (18-83 y) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for pleiotropy between these classes of phenotypes was observed. Applying an advanced quantitative gene-by-environment interaction analysis where age is treated as an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration as a function of age. Furthermore, by decomposing gene-by-aging (G × A) interactions, we infer that different genes influence some neurocognitive traits as a function of age, whereas other neurocognitive traits are influenced by the same genes, but to differential levels, from young adulthood to old age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. These results clearly demonstrate that traits sensitive to the genetic influences on brain aging can be identified, a critical first step in delineating the biological mechanisms of successful aging.neurocognition | diffusion tensor imaging | fractional anisotropy | genetic correlation | gene x environment interaction P opulation projections suggest for the first time in human history there will be more individuals over the age of 65 than below the age of 14 by 2050 (1). This milestone reflects the dramatic increase of the average lifespan of people worldwide, rather than a reduction in the total number of children being born. Indeed, 25% of the US population is expected to be over the age of 60 midway through this century (1). The implications of our aging population are substantial, because aging is associated with decreased mental and physical ability coupled with increased health care utilization. Thus, there is considerable interest in delineating the biological mechanisms that influence age-related changes to facilitate successful aging (2), defined as avoidance of disease or disability, maintaining good physical and cognitive function, and engagement in social and productive activities. Because the brain appears to play a pivotal role in aging biology (3), one promising strategy is to define measures of brain structure and function that index concomitant aging outcomes (4). The observation that many measures of brain aging are heritable and can be localized to specific genomic regions (6) indicates that genetic factors play a crucial role in the brain's ability to either prosper or ...

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“…factor analysis | white matter | DTI | cognition | heritability I ndividual differences in white matter (WM) microstructure have been shown to be related to cognitive functions in adults (1,2) and children (3)(4)(5). Diffusion tensor imaging (DTI) parameters in different WM regions or tracts are variably associated with processing speed, general intelligence, and higher-order cognitive abilities (1)(2)(3)(4)(5).…”

mentioning

confidence: 99%

Common and heritable components of white matter microstructure predict cognitive function at 1 and 2 y

Lee

Steiner

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Previous studies indicate that the microstructure of individual white matter (WM) tracts is related to cognitive function. More recent studies indicate that the microstructure of individual tracts is highly correlated and that a property common across WM is related to overall cognitive function in adults. However, little is known about whether these common WM properties exist in early childhood development or how they are related to cognitive development. In this study, we used diffusion tensor imaging (DTI) to investigate common underlying factors in 12 fiber tracts, their relationship with cognitive function, and their heritability in a longitudinal sample of healthy children at birth (n = 535), 1 y (n = 322), and 2 y (n = 244) of age. Our data show that, in neonates, there is a highly significant correlation between major WM tracts that decreases from birth to 2 y of age. Over the same period, the factor structure increases in complexity, from one factor at birth to three factors at age 2 y, which explain 50% of variance. The identified common factors of DTI metrics in each age group are significantly correlated with general cognitive scores and predict cognitive ability in later childhood. These factors are moderately heritable. These findings illustrate the anatomical differentiation of WM fiber from birth to 2 y of age that correlate with cognitive development. Our results also suggest that the common factor approach is an informative way to study WM development and its relationship with cognition and is a useful approach for future imaging genetic studies.factor analysis | white matter | DTI | cognition | heritability I ndividual differences in white matter (WM) microstructure have been shown to be related to cognitive functions in adults (1, 2) and children (3-5). Diffusion tensor imaging (DTI) parameters in different WM regions or tracts are variably associated with processing speed, general intelligence, and higher-order cognitive abilities (1-5).To date, the majority of DTI studies of WM microstructure have analyzed each tract or WM region independently. However, more recent studies clearly demonstrate that fractional anisotropy (FA) and other DTI metrics of WM microstructure correlate highly across WM tracts and across a wide age range, including neonates, older children, and adults (6-8). Furthermore, studies indicate that a general factor derived by principal component analyses (PCA) describing common variance in FA across WM tracts is associated with information processing speed (9) as well as general intelligence (10), at least in older adults. In children ages 8 to 16 y, three principal components of FA have been identified; the one corresponding to the corpus callosum was significantly related to IQ (11).The identification of one or more common WM factors that influence variation in multiple WM tracts or regions is important for several reasons. Such factors could prove to be a good target for imaging genetic studies, as one would expect genetic variants influencing WM development and function ...

show abstract

The association between higher order abilities, processing speed, and age are variably mediated by white matter integrity during typical aging

Cited by 92 publications

References 85 publications

Episodic memory and executive functions in cognitively healthy individuals display distinct neuroanatomical correlates which are differentially modulated by aging

Episodic memory and executive functions in cognitively healthy individuals display distinct neuroanatomical correlates which are differentially modulated by aging

Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging

Common and heritable components of white matter microstructure predict cognitive function at 1 and 2 y

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