Elsevier

Neurobiology of Aging

Volume 35, Issue 5, May 2014, Pages 1086-1094
Neurobiology of Aging

Regular article
Cognitive decline is mediated by gray matter changes during middle age

https://doi.org/10.1016/j.neurobiolaging.2013.10.095Get rights and content

Abstract

The present theoretical framework of Alzheimer's disease proposes that pathophysiological changes occur 10–20 years before the diagnosis of dementia. We addressed the question of how age-related changes in gray matter mediate the cognitive performance during middle age. Eighty-two participants (40–50 years, ±2) were assessed with a comprehensive neuropsychological battery covering a broad spectrum of cognitive domains and components. Mediation effects were studied with hierarchical regression and bootstrapping analysis. Results showed that more vulnerable cognitive components were related to executive functioning and in a lesser degree to processing speed. Age-related differences in gray matter mainly involved the frontal lobes. Moreover, age-related differences in visuoconstructive, visuospatial functions, reaction time, and mental flexibility and executive control were mediated by several gray matter regions. It is important to increase the knowledge of the impact of brain changes on cognitive function during middle age. To define the early stages of the aging process may allow early detection of pathologic changes and therapeutic interventions.

Introduction

Aging is associated with decline in cognitive functioning and brain structural changes. Regarding age-related cognitive changes, broad life-span studies have reported cognitive decline in processing speed, executive functions, attention, episodic memory (especially delayed recall), and language (lexical access and word retrieval) (Keys and White, 2000, Luo and Craik, 2008, Nilsson, 2003, Salthouse, 2009, Tisserand and Jolles, 2003). Decline in visuoperceptive, visuospatial, and visuoconstructive functions have also been reported, although they seem to begin at older ages (65 or more years). With respect to the age-related neuroanatomical changes, neuroimaging studies have consistently reported a linear decline in the gray matter volume and cortical thickness starting in the early adulthood (Abe et al., 2008, Hutton et al., 2009, Salat et al., 2004). White matter tissue shows a nonlinear evolution. White matter volume increases until the early middle-age adulthood (aged 35 years), with a period of stability and an accelerated decline only after the late middle age (aged 55–60 years). Likewise, diffusion tensor imaging studies analyzing water movement along the fiber tracks have demonstrated changes in white matter integrity early in the adulthood, although showing greater decline after the age of 60 (Abe et al., 2008, Fjell et al., 2008, Grieve et al., 2007). Interestingly, age-related decline both in gray and white matter follow a pattern of anterior-posterior gradient, with the prefrontal cortex and its cortical and subcortical circuits as the most involved regions (Bennett et al., 2009, Jernigan et al., 1991). Nevertheless, some studies have also shown age-related degeneration in posterior sensory regions (Salat et al., 2004, Ziegler et al., 2010).

Age-related cognitive and neuroanatomical changes seem to be well documented in the literature. However, the relationship between them is still poorly investigated and results are inconsistent. Most studies have focused on the white matter, but only a few have analyzed the gray matter. Findings support that age-related neuroanatomical changes contribute to the cognitive decline in executive functions, processing speed, and episodic memory. More specifically, age-related changes in executive functions have been linked to decline in both frontal gray and white matter (Brickman et al., 2006, Davis et al., 2009, Gunning-Dixon and Raz, 2003, Raz et al., 1998, Ziegler et al., 2010, Zimmerman et al., 2006), and to posterior visual regions when executive tasks involve visual processing (Raz et al., 1998). Moreover, temporal and posterior white matter regions have been identified in tasks of flexibility and inhibition (Kennedy and Raz, 2009, Madden et al., 2009). Age-related changes in processing speed seem to be mainly explained by degeneration in frontal regions, either gray matter or white matter (Gautam et al., 2011, Gunning-Dixon and Raz, 2000, Kennedy and Raz, 2009). Finally, age-related memory impairment appears to be associated with the volume and integrity of frontal, temporal, and parietal white matter, and the inferior longitudinal fascicle (Brickman et al., 2006, Davis et al., 2009, Gautam et al., 2011, Gunning-Dixon and Raz, 2000, Ziegler et al., 2010). Moreover, individual variability in well preserved functions such as semantic or short-term memory is accounted by variability of global and regional gray matter volume in healthy elderly individuals (Taki et al., 2011). However, other cognitive functions as attention, visuospatial, visuoconstructive abilities, and language have received almost no attention. In addition, a critical issue in most of the previously mentioned studies is that correlation analyses may not be sufficient to establish a mediation effect of neuroanatomical changes on the relationship between age and cognitive performance (Madden et al., 2009). Few studies have proven such a mediation effect by conducting hierarchical regression analyses or other mathematical methods (e.g., path analyses in Gunning-Dixon and Raz, 2003). With regard to the gray matter, only Gunning-Dixon and Raz (2003) carried out a mediation analysis. However, these authors only included 2 gray matter regions (prefrontal cortex and fusiform gyrus), and 2 cognitive tasks (a verbal working memory task and the Wisconsin Card Sorting Test). Therefore, further studies are mandatory to determine the possible involvement of the age-related gray matter changes on the age-related decline in cognition.

As we have mentioned previously, structural brain changes and some cognitive deficits start early in the middle age. Further research is warranted to improve the diagnosis, prevention, and prediction of pathologic aging at an early level. From a therapeutic point of view, to define the age at which brain structural and cognitive decline begins is also important to determine the most suitable window at which potential interventions can have greater benefits. In the case of Alzheimer's disease, the most widely validated biomarkers of Alzheimer's disease become abnormal in an ordered manner starting 10–20 years before the diagnosis of dementia (Jack et al., 2010), probably overlapping the middle-age period. In this sense, research on the middle-age adulthood is of great importance, given that it is the critical point when the first pathophysiological changes begin to take place. Therefore, it is the ideal point to implement early interventions (Center for Disease Control and Prevention, 2009).

In the present study, we examined the age-related changes in cognition and gray matter, and the relationship between them, in a large cohort of middle-aged participants. We carried out an in-depth analysis of both gray matter volume and cortical thickness through multiple structural regions covering the whole brain. Although volume and thickness are highly related markers, they represent different characteristics of the tissue, giving complementary information on processes occurring in the gray matter. Because cortical volume is a product of thickness and surface area, degenerative processes that selectively affect surface area (e.g., age-related sulcal expansion), could be related to changes in cortical volume but not in cortical thickness (Ziegler et al., 2010). A comprehensive neuropsychological battery was applied with the aim of covering the largest possible number of cognitive functions and components. Finally, hierarchical regression and bootstrapping analyses were used to investigate whether age-related gray matter changes mediated the effects of aging on cognitive functioning. We predicted a selective age-associated gray matter reduction, especially in anterior brain regions, and that this variability would be significantly associated with age-related cognitive decline, particularly in those functions mediated by more anterior brain regions such as executive functioning.

Section snippets

Participants

One hundred twenty-five early-middle-aged participants were initially enrolled. Personnel from local schools, and relatives and acquaintances of the research staff were recruited for the study. Participants initially underwent a telephonic interview to screen the following criteria: (1) age between 40 and 50 (±2); (2) preserved cognitive and functional status; (3) no neurologic or psychiatric disorders, systemic diseases with neuropsychological consequences, or substance abuse history. Once

Age-related differences in cognitive performance

Age was significantly correlated with performance on Reaction time, TMT-A, CTT-2, Visuospatial backward, TAVEC first learning trial, Block design (number of blocks in complex designs and total WAIS score), JLOT, and TGAAS (total and cognitive nouns with a morphologic derived action condition) (Table 2). Correlation coefficients were all in the predicted directions indicating worse performance with increasing age. Effect sizes were large in all cases.

Age-related differences in gray matter

Correlation between age and total gray matter

Discussion

In the present work we aimed to study how age-related changes in gray matter mediate age-related changes in cognition during the early stage of the middle-age adulthood. To isolate the age effect, we exerted a statistical control of the confounding effect of gender and education.

Results regarding age-related differences in cognitive performance could be explained by early deficits in the executive functioning (CTT-2, Visuospatial-Backward, TAVEC-Learning first trial, Block Design complex,

Disclosure statement

The authors have no actual or potential conflicts of interest.

Acknowledgements

This research made use of the Servicio de Resonancia Magnética para Investigaciones Biomédicas del SEGAI (University of La Laguna), and has been partially supported by a research grant from Ministerio de Ciencia e Innovación (BES-2007–15658), and from Fundación Canaria Dr Manuel Morales (convocatoria 2012). The authors also thank the Strategic Research Programme in Neuroscience at Karolinska Institutet and Swedish Brain Power.

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