Characterization of a normal control group: Are they healthy?

Abstract

We examined the health of a control group (18–81 years) in our aging study, which is similar to control groups used in other neuroimaging studies. The current study was motivated by our previous results showing that one third of the elder control group had moderate to severe white matter hyperintensities and/or cortical volume loss which correlated with poor performance on memory tasks. Therefore, we predicted that cardiovascular risk factors (e.g., hypertension, high cholesterol) within the control group would account for significant variance on working memory task performance. Fifty-five participants completed 4 verbal and spatial working memory tasks, neuropsychological exams, diffusion tensor imaging (DTI), and blood tests to assess vascular risk. In addition to using a repeated measures ANOVA design, a cluster analysis was applied to the vascular risk measures as a data reduction step to characterize relationships between conjoint risk factors. The cluster groupings were used to predict working memory performance. The results show that higher levels of systolic blood pressure were associated with: 1) poor spatial working memory accuracy; and 2) lower fractional anisotropy (FA) values in multiple brain regions. In contrast, higher levels of total cholesterol corresponded with increased accuracy in verbal working memory. An association between lower FA values and higher cholesterol levels were identified in different brain regions from those associated with systolic blood pressure. The conjoint risk analysis revealed that Risk Cluster Group 3 (the group with the greatest number of risk factors) displayed: 1) the poorest performance on the spatial working memory tasks; 2) the longest reaction times across both spatial and verbal memory tasks; and 3) the lowest FA values across widespread brain regions. Our results confirm that a considerable range of vascular risk factors are present in a typical control group, even in younger individuals, which have robust effects on brain anatomy and function. These results present a new challenge to neuroimaging studies both for defining a cohort from which to characterize `normative' brain circuitry and for establishing a control group to compare with other clinical populations.

Modulatory role of the prefrontal generator within the auditory M50 network

“…However, localization of an additional PF source in the M50 network may be related to compensatory processes often suggested in aging studies (i.e., an additional source(s) is invoked in elders to compensate for the degradation of a network(s) due to age) or it may result from the employment of different strategies reported previously with increasing age (Aine et al, 2006; 2011; 2014; Cabeza et al, 2002; Logan et al, 2002). For example, Aine et al (2005) revealed PF activation in elderly subjects twice as often as in younger participants in an auditory incidental learning paradigm.…”

MEG biomarker of Alzheimer's disease: Absence of a prefrontal generator during auditory sensory gating

“…Additionally, broad exclusion criteria provide greater likelihood that the pathology of control participants who are possibly in a preclinical phase of dementia (still nonsymptomatic), is likely due to Alzheimer's disease (i.e., lower likelihood of having other confounding medical conditions). Nevertheless, there is always a possibility that subclinical cardiovascular or metabolic disorder may be present in these participants, such as undetected small vessel disease, high blood pressure, or hypercholesterolemia and insulin resistance, which may contribute to cognitive decline as well [Aine et al, ]. However, our putative marker of AD pathology specifically underlies an auditory sensory gating deficit [Cheng et al, ; Thomas et al, ].…”

Low Cholesterol Level Linked to Reduced Semantic Fluency Performance and Reduced Gray Matter Volume in the Medial Temporal Lobe

“…However, while the relationship between cholesterol levels [TC and its subcomponents: low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides (TGs)] and cognitive functions has been extensively studied, the findings have been largely inconsistent. For example, while some studies have found higher TC and/or higher LDL was associated with poorer cognitive performance (Yaffe et al, 2002;Carlsson et al, 2009;Sparks et al, 2010;Meusel et al, 2017) or a higher risk of dementia such as Alzheimer's disease (AD) (Kivipelto et al, 2005;Hayden et al, 2006;Solomon et al, 2009), others have found no such effects (Mielke et al, 2010), or even the opposite pattern, i.e., higher TC and/or higher LDL levels were associated with better cognitive performance (Elias et al, 2005;West et al, 2008;van den Kommer et al, 2012;Aine et al, 2014;Lv et al, 2016) or lower risk of dementia/cognitive decline (Mielke et al, 2005;Reitz et al, 2005Reitz et al, , 2010van den Kommer et al, 2009). In addition, although many studies have suggested that HDL is positively correlated with cognitive functions (van den Kommer et al, 2012;Elias et al, 2014) and high HDL level is associated with reduced risk of future dementia (Reitz et al, 2010;Ancelin et al, 2013), exceptions can be found (Ancelin et al, 2014), in addition to null findings in many other studies.…”

“…However, using resting-state functional MRI (fMRI) techniques, Zhang et al (2016) found that higher TC was associated with both increased connectivity in the default mode network and reduced connectivity in the salience network, suggesting a more complicated picture (Zhang et al, 2016). Furthermore, in several recent studies, higher LDL or TC levels were linked to thicker cortical thickness (Leritz et al, 2011;Coutinho et al, 2017), increased GMv in the frontal cortex and the posterior cingulate cortex (PCC) (but only in hypertensive adults) (Chung et al, 2018), and white matter integrity (Aine et al, 2014), suggesting an opposite pattern, i.e., high cholesterol level could be potentially beneficial in middleaged to older adults.…”