A. O'Shea

Abnormal resting state functional connectivity in patients with chronic fatigue syndrome: an arterial spin-labeling fMRI study ☆

BACKGROUND Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disorder characterized by severe fatigue and neurocognitive dysfunction. Recent work from our laboratory and others utilizing arterial spin labeling functional magnetic resonance imaging (ASL) indicated that ME/CFS patients have lower resting state regional cerebral blood flow (rCBF) in several brain areas associated with memory, cognitive, affective, and motor function. This hypoperfusion may underlie ME/CFS pathogenesis and may result in alterations of functional relationships between brain regions. The current report used ASL to compare functional connectivity of regions implicated in ME/CFS between patients and healthy controls (HC). METHODS Participants were 17 ME/CFS patients (Mage=48.88years, SD=12) fulfilling the 1994 CDC criteria and 17 age/sex matched HC (Mage=49.82years, SD=11.32). All participants underwent T1-weighted structural MRI as well as a 6-min pseudo-continuous arterial spin labeling (pCASL) sequence, which quantifies CBF by magnetically labeling blood as it enters the brain. Imaging data were preprocessed using SPM 12 and ASL tbx, and seed-to-voxel functional connectivity analysis was conducted using the CONN toolbox. All effects noted below are significant at p<0.05 with cluster-wise FDR correction for multiple comparisons. RESULTS ME/CFS patients demonstrated greater functional connectivity relative to HC in bilateral superior frontal gyrus, ACC, precuneus, and right angular gyrus to regions including precuneus, right postcentral gyrus, supplementary motor area, posterior cingulate gyrus, and thalamus. In contrast, HC patients had greater functional connectivity than ME/CFS in ACC, left parahippocampal gyrus, and bilateral pallidum to regions including right insula, right precentral gyrus, and hippocampus. Connectivity of the left parahippocampal gyrus correlated strongly with overall clinical fatigue of ME/CFS patients. CONCLUSION This is the first ASL based connectivity analysis of patients with ME/CFS. Our results demonstrate altered functional connectivity of several regions associated with cognitive, affective, memory, and higher cognitive function in ME/CFS patients. Connectivity to memory related brain areas (parahippocampal gyrus) was correlated with clinical fatigue ratings, providing supporting evidence that brain network abnormalities may contribute to ME/CFS pathogenesis.

Abnormal Resting-State Functional Connectivity in Patients with Chronic Fatigue Syndrome: Results of Seed and Data-Driven Analyses

Although altered resting-state functional connectivity (FC) is a characteristic of many chronic pain conditions, it has not yet been evaluated in patients with chronic fatigue. Our objective was to investigate the association between fatigue and altered resting-state FC in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Thirty-six female subjects, 19 ME/CFS and 17 healthy controls, completed a fatigue inventory before undergoing functional magnetic resonance imaging. Two methods, (1) data driven and (2) model based, were used to estimate and compare the intraregional FC between both groups during the resting state (RS). The first approach using independent component analysis was applied to investigate five RS networks: the default mode network, salience network (SN), left frontoparietal networks (LFPN) and right frontoparietal networks, and the sensory motor network (SMN). The second approach used a priori selected seed regions demonstrating abnormal regional cerebral blood flow (rCBF) in ME/CFS patients at rest. In ME/CFS patients, Method-1 identified decreased intrinsic connectivity among regions within the LFPN. Furthermore, the FC of the left anterior midcingulate with the SMN and the connectivity of the left posterior cingulate cortex with the SN were significantly decreased. For Method-2, five distinct clusters within the right parahippocampus and occipital lobes, demonstrating significant rCBF reductions in ME/CFS patients, were used as seeds. The parahippocampal seed and three occipital lobe seeds showed altered FC with other brain regions. The degree of abnormal connectivity correlated with the level of self-reported fatigue. Our results confirm altered RS FC in patients with ME/CFS, which was significantly correlated with the severity of their chronic fatigue.

Fibromyalgia patients have reduced hippocampal volume compared with healthy controls

Objective Fibromyalgia patients frequently report cognitive abnormalities. As the hippocampus plays an important role in learning and memory, we determined whether individuals with fibromyalgia had smaller hippocampal volume compared with healthy control participants. Methods T1-weighted structural magnetic resonance imaging (MRI) scans were acquired from 40 female participants with fibromyalgia and 22 female healthy controls. The volume of the hippocampus was estimated using the software FreeSurfer. An analysis of covariance model controlling for potentially confounding factors of age, whole brain size, MRI signal quality, and Beck Depression Inventory scores were used to determine significant group differences. Results Fibromyalgia participants had significantly smaller hippocampi in both left (F[1,56]=4.55, P=0.037, η2p=0.08) and right hemispheres (F[1,56]=5.89, P=0.019, η2p=0.10). No significant effect of depression was observed in either left or right hemisphere hippocampal volume (P=0.813 and P=0.811, respectively). Discussion Potential mechanisms for reduced hippocampal volume in fibromyalgia include abnormal glutamate excitatory neurotransmission and glucocorticoid dysfunction; these factors can lead to neuronal atrophy, through excitotoxicity, and disrupt neurogenesis in the hippocampus. Hippocampal atrophy may play a role in memory and cognitive complaints among fibromyalgia patients.

Effective connectivity predicts future placebo analgesic response: A dynamic causal modeling study of pain processing in healthy controls.

A better understanding of the neural mechanisms underlying pain processing and analgesia may aid in the development and personalization of effective treatments for chronic pain. Clarification of the neural predictors of individual variability in placebo analgesia (PA) could aid in this process. The present study examined whether the strength of effective connectivity (EC) among pain-related brain regions could predict future placebo analgesic response in healthy individuals. In Visit 1, fMRI data were collected from 24 healthy subjects (13 females, mean age=22.56, SD=2.94) while experiencing painful thermal stimuli. During Visit 2, subjects were conditioned to expect less pain via a surreptitiously lowered temperature applied at two of the four sites on their feet. They were subsequently scanned again using the Visit 1 (painful) temperature. Subjects used an electronic VAS to rate their pain following each stimulus. Differences in ratings at conditioned and unconditioned sites were used to measure placebo response (PA scores). Dynamic causal modeling was used to estimate the EC among a set of brain regions related to pain processing at Visit 1 (periaqueductal gray, thalamus, rostral anterior cingulate cortex, dorsolateral prefrontal cortex). Individual PA scores from Visit 2 were regressed on salient EC parameter estimates from Visit 1. Results indicate that both greater left hemisphere modulatory DLPFC➔PAG connectivity and right hemisphere, endogenous thalamus➔DLPFC connectivity were significantly predictive of future placebo response (R(2)=0.82). To our knowledge, this is the first study to identify the value of EC in understanding individual differences in PA, and may suggest the potential modifiability of endogenous pain modulation.

Cognitive Aging and the Hippocampus in Older Adults.

The hippocampus is one of the most well studied structures in the human brain. While age-related decline in hippocampal volume is well documented, most of our knowledge about hippocampal structure-function relationships was discovered in the context of neurological and neurodegenerative diseases. The relationship between cognitive aging and hippocampal structure in the absence of disease remains relatively understudied. Furthermore, the few studies that have investigated the role of the hippocampus in cognitive aging have produced contradictory results. To address these issues, we assessed 93 older adults from the general community (mean age = 71.9 ± 9.3 years) on the Montreal Cognitive Assessment (MoCA), a brief cognitive screening measure for dementia, and the NIH Toolbox-Cognitive Battery (NIHTB-CB), a computerized neurocognitive battery. High-resolution structural magnetic resonance imaging (MRI) was used to estimate hippocampal volume. Lower MoCA Total (p = 0.01) and NIHTB-CB Fluid Cognition (p < 0.001) scores were associated with decreased hippocampal volume, even while controlling for sex and years of education. Decreased hippocampal volume was significantly associated with decline in multiple NIHTB-CB subdomains, including episodic memory, working memory, processing speed and executive function. This study provides important insight into the multifaceted role of the hippocampus in cognitive aging.

Depressive symptom severity is associated with increased cortical thickness in older adults.

Structural neuroimaging studies in older adults have consistently shown volume reductions in both major and subthreshold depression. Cortical thickness, another measure of brain structure, has not been well studied in this population. We examined cortical thickness in older adults across a range of depressive symptom (DS) severity.

Associations between subclinical depressive symptoms and reduced brain volume in middle-aged to older adults

ABSTRACT Objectives: The associations between subclinical depressive symptoms, as well specific symptom subscales, on brain structure in aging are not completely elucidated. This study investigated the extent to which depressive symptoms were related to brain volumes in fronto-limbic structures in a sample of middle-aged to older adults. Method: Eighty participants underwent structural neuroimaging and completed the Beck Depression Inventory, 2nd Edition (BDI-II), which comprises separate affective, cognitive, and somatic subscales. Gray matter volumes were extracted from the caudal and rostral anterior cingulate, posterior cingulate, hippocampus, and amygdala. Hierarchical regression models examined the relationship between brain volumes and (i) total depressive symptoms and (ii) BDI-II subscales were conducted. Results: After adjusting for total intracranial volume, race, and age, higher total depressive symptoms were associated with smaller hippocampal volume (p = 0.005). For the symptom subscales, after controlling for the abovementioned covariates and the influence of the other symptom subscales, more somatic symptoms were related to smaller posterior cingulate (p = 0.025) and hippocampal (p < 0.001) volumes. In contrast, the affective and cognitive subscales were not associated with brain volumes in any regions of interest. Conclusion: Our data showed that greater symptomatology was associated with smaller volume in limbic brain regions. These findings provide evidence for preclinical biological markers of major depression and specifically advance knowledge of the relationship between subclinical depressive symptoms and brain volume. Importantly, we observed variations by specific depressive symptom subscales, suggesting a symptom-differential relationship between subclinical depression and brain volume alterations in middle-aged and older individuals.

Statistical Approaches for the Study of Cognitive and Brain Aging.

Neuroimaging studies of cognitive and brain aging often yield massive datasets that create many analytic and statistical challenges. In this paper, we discuss and address several limitations in the existing work. (1) Linear models are often used to model the age effects on neuroimaging markers, which may be inadequate in capturing the potential nonlinear age effects. (2) Marginal correlations are often used in brain network analysis, which are not efficient in characterizing a complex brain network. (3) Due to the challenge of high-dimensionality, only a small subset of the regional neuroimaging markers is considered in a prediction model, which could miss important regional markers. To overcome those obstacles, we introduce several advanced statistical methods for analyzing data from cognitive and brain aging studies. Specifically, we introduce semiparametric models for modeling age effects, graphical models for brain network analysis, and penalized regression methods for selecting the most important markers in predicting cognitive outcomes. We illustrate these methods using the healthy aging data from the Active Brain Study.

Vertex-wise examination of depressive symptom dimensions and brain volumes in older adults

Differences in brain volumes have commonly been reported in older adults with both subthreshold and major depression. Few studies have examined the association between specific symptom dimensions of depression and brain volumes. This study used vertex-wise analyses to examine the association between specific symptom dimensions of depression and brain volumes in older adults with subthreshold levels of depressive symptoms. Forty-three community-dwelling adults between the ages of 55 and 81 years underwent a structural Magnetic Resonance Imaging scan and completed the Center for Epidemiologic Studies Depression Scale (CES-D). Vertex-wise analyses were conducted using Freesurfer Imaging Suite to examine the relationship between CES-D subscale scores and gray matter volumes while controlling for sex, age, and education. We found distinct associations between depressed mood, somatic symptoms, and lack of positive affect subscales with regional volumes, including primarily positive relationships in temporal regions and a negative association with the lingual gyrus. The relationship between higher depressed mood subscale scores and larger volumes in the left inferior temporal lobe withstood Monte-Carlo correction for multiple comparisons. Results from this preliminary study highlight the importance of examining depression on a symptom dimension level and identify brain regions that may be important in larger studies of depression.

Precuneus abnormalities in middle-aged to older adults with depressive symptoms: An analysis of BDI-II symptom dimensions

We recently reported age-related increases in left precuneus cortical thickness (CT) in older adults with elevated total depressive symptoms. However, it is unclear whether abnormalities in precuneus surface area (SA) are also evident and whether specific symptom dimensions of depression moderated age effects on these measurements. Seventy-three adults completed the Beck Depression Inventory - 2nd edition (BDI-II) and underwent structural neuroimaging. Measures of CT and SA were extracted from the right and left precuneus via FreeSurfer. Regression models included regions of interest as dependent variables, with age, BDI-II subscale scores (e.g., affective, cognitive, and somatic symptoms), and their interactions as independent variables, controlling for mean hemispheric thickness (for CT) or total intracranial volume (for SA). A significant age × somatic symptom interaction was found for left precuneus CT, such that elevated levels of somatic symptoms were significantly associated with age-related cortical thinning. No depressive symptom dimensions moderated the relationship between age and SA, suggesting that CT may be a more sensitive measure of brain abnormalities in middle-aged to older adults with depressive symptoms.