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

Magnetoencephalography (MEG), a direct measure of neuronal activity, is an underexplored tool in the search for biomarkers of Alzheimer's disease (AD). In this study, we used MEG source estimates of auditory gating generators, nonlinear correlations with neuropsychological results, and multivariate analyses to examine the sensitivity and specificity of gating topology modulation to detect AD. Our results demonstrated the use of MEG localization of a medial prefrontal (mPFC) gating generator as a discrete (binary) detector of AD at the individual level and resulted in recategorizing the participant categories in: (1) controls with mPFC generator localized in response to both the standard and deviant tones; (2) a possible preclinical stage of AD participants (a lower functioning group of controls) in which mPFC activation was localized to the deviant tone only; and (3) symptomatic AD in which mPFC activation was not localized to either the deviant or standard tones. This approach showed a large effect size (0.9) and high accuracy, sensitivity, and specificity (100%) in identifying symptomatic AD patients within a limited research sample. The present results demonstrate high potential of mPFC activation as a noninvasive biomarker of AD pathology during putative preclinical and clinical stages. Hum Brain Mapp 38:5180-5194, 2017. © 2017 Wiley Periodicals, Inc.

Modulatory role of the prefrontal generator within the auditory M50 network.

The amplitude variability of the M50 component of neuromagnetic responses is commonly used to explore the brain's ability to modulate its response to incoming repetitive or novel auditory stimuli, a process conceptualized as a gating mechanism. The goal of this study was to identify the spatial and temporal characteristics of the cortical sources underlying the M50 network evoked by tones in a passive oddball paradigm. Twenty elderly subjects [10 patients diagnosed with mild cognitive impairment (MCI) or probable Alzheimer disease (AD) and 10 age-matched controls] were examined using magnetoencephalographic (MEG) recordings and the multi-dipole Calibrated Start Spatio-Temporal (CSST) source localization method. We identified three cortical regions underlying the M50 network: prefrontal cortex (PF) in addition to bilateral activation of the superior temporal gyrus (STG). The cortical dynamics of the PF source within the 30-100 ms post-stimulus interval was characterized and was found to be comprised of two subcomponents, Mb1c and Mb2c. The PF source was localized for 10/10 healthy subjects, whereas 9/10 MCI/AD patients were lacking the PF source for both tone conditions. The selective activation of the PF source in healthy controls along with the inactivation of the PF region for MCI/AD patients, enabled us to examine the dynamics of this network of activity when it was functional and dysfunctional, respectively. We found significantly enhanced activity of the STG sources in response to both tone conditions for all subjects who lacked a PF source. The reported results provide novel insights into the topology and neurodynamics of the M50 auditory network, which suggest an inhibitory role of the PF source that normally suppresses activity of the STG sources.

Same task, different strategies: how brain networks can be influenced by memory strategy.

Previous functional neuroimaging studies demonstrated that different neural networks underlie different types of cognitive processing by engaging participants in particular tasks, such as verbal or spatial working memory (WM) tasks. However, we report here that even when a WM task is defined as verbal or spatial, different types of memory strategies may be used to complete it, with concomitant variations in brain activity. We developed a questionnaire to characterize the type of strategy used by individual members in a group of 28 young healthy participants (18-25 years) during a spatial WM task. A cluster analysis was performed to differentiate groups. We acquired functional magnetoencephalography and structural diffusion tensor imaging measures to characterize the brain networks associated with the use of different strategies. We found two types of strategies were used during the spatial WM task, a visuospatial and a verbal strategy, and brain regions and time courses of activation differed between participants who used each. Task performance also varied by type of strategy used with verbal strategies showing an advantage. In addition, performance on neuropsychological tests (indices from Wechsler Adult Intelligence Scale-IV, Rey Complex Figure Test) correlated significantly with fractional anisotropy measures for the visuospatial strategy group in white matter tracts implicated in other WM and attention studies. We conclude that differences in memory strategy can have a pronounced effect on the locations and timing of brain activation and that these differences need further investigation as a possible confounding factor for studies using group averaging as a means for summarizing results.

A trichotomy method for defining homogeneous subgroups in a dementia population.

INTRODUCTION: Diagnosis of dementia in the aging brain is confounded by the presence of multiple pathologies. Mixed dementia (MX), a combination of Alzheimer's disease (AD) proteins with vascular disease (VD), is frequently found at autopsy, and has been difficult to diagnose during life. This report develops a method for separating the MX group and defining preclinical AD (presence of AD factors with normal cognition) and preclinical VD subgroups (presence of white matter damage with normal cognition). METHODS: Clustering was based on three diagnostic axes: (1) AD factor (ADF) derived from cerebrospinal fluid proteins (Aß42 and pTau), (2) VD factor (VDF) calculated from mean free water and peak width of skeletonized mean diffusivity in the white matter, and (3) Cognition (Cog) based on memory and executive function. The trichotomy method was applied to an Alzheimer's Disease Neuroimaging Initiative cohort (N = 538). RESULTS: Eight biologically defined subgroups were identified which included the MX group with both high ADF and VDF (9.3%) and a preclinical VD group (3.9%), and a preclinical AD group (13.6%). Cog is significantly associated with both ADF and VDF, and the partial-correlation remains significant even when the effect of the other variable is removed (r(Cog, ADF/VDF removed) = 0.46, p < 10-28 and r(Cog, VDF/ADF removed) = 0.24, p < 10-7 ). DISCUSSION: The trichotomy method creates eight biologically characterized patient groups, which includes MX, preclinical AD, and preclinical VD subgroups. Further longitudinal studies are needed to determine the utility of the 3-way clustering method with multimodal biological biomarkers.

Blood-brain barrier disruption measured by albumin index correlates with inflammatory fluid biomarkers.

Blood-brain barrier (BBB) permeability can be measured by the ratio of albumin in cerebrospinal fluid (CSF) and blood and by dynamic contrast-enhanced MRI (DCEMRI). Albumin is a large molecule measured in CSF and blood to form the albumin index (Qalb), which is a global measure of BBB permeability, while the smaller Gadolinium molecule measures regional transfer (Ktrans); few studies have directly compared them in the same patients. We used both methods as part of a study of mechanisms of white matter injury in patients with different forms of dementia. In addition, we also measured biomarkers for inflammation, including proteases, angiogenic growth factors, and cytokines, and correlated them with the BBB results. We found that there was no correlation between Qalb and Ktrans. The Qalb was associated with the matrix metalloproteinases (MMP-2, MMP-3, and MMP-10), the angiogenic factors (VEGF-C and PlGF), and the cytokines (IL-6, IL-8 and TNF-α). On the other hand, Ktrans was associated with the diffusion measures, mean free water and PSMD, which indicate white matter injury. Our results show that the Qalb and Ktrans measure different aspects of BBB permeability, with albumin being a measure of inflammatory BBB opening and Ktrans indicating white matter injury.

Inflammatory Biomarkers Aid in Diagnosis of Dementia.

Dual pathology of Alzheimer's disease (AD) and vascular cognitive impairment and dementia (VCID) commonly are found together at autopsy, but mixed dementia (MX) is difficult to diagnose during life. Biological criteria to diagnose AD have been defined, but are not available for vascular disease. We used the biological criteria for AD and white matter injury based on MRI to diagnose MX. Then we measured multiple biomarkers in CSF and blood with multiplex biomarker kits for proteases, angiogenic factors, and cytokines to explore pathophysiology in each group. Finally, we used machine learning with the Random forest algorithm to select the biomarkers of maximal importance; that analysis identified three proteases, matrix metalloproteinase-10 (MMP-10), MMP-3 and MMP-1; three angiogenic factors, VEGF-C, Tie-2 and PLGF, and three cytokines interleukin-2 (IL-2), IL-6, IL-13. To confirm the clinical importance of the variables, we showed that they correlated with results of neuropsychological testing.

A double-dichotomy clustering of dual pathology dementia patients.

INTRODUCTION: Subcortical ischemic vascular disease (SIVD) and Alzheimer's disease (AD) related dementia can coexist in older subjects, leading to mixed dementia (MX). Identification of dementia sub-groups is important for designing proper treatment plans and clinical trials. METHOD: An Alzheimer's disease severity (ADS) score and a vascular disease severity (VDS) score are calculated from CSF and MRI biomarkers, respectively. These scores, being sensitive to different Alzheimer's and vascular disease processes are combined orthogonally in a double-dichotomy plot. This formed an objective basis for clustering the subjects into four groups, consisting of AD, SIVD, MX and leukoaraiosis (LA). The relationship of these four groups is examined with respect to cognitive assessments and clinical diagnosis. RESULTS: Cluster analysis had at least 83% agreement with the clinical diagnosis for groups based either on Alzheimer's or on vascular sensitive biomarkers, and a combined agreement of 68.8% for clustering the four groups. The VDS score was correlated to executive function (r = -0.28, p < 0.01) and the ADS score to memory function (r = -0.35, p < 0.002) after adjusting for age, sex, and education. In the subset of patients for which the cluster scores and clinical diagnoses agreed, the correlations were stronger (VDS score-executive function: r = -0.37, p < 0.006 and ADS score-memory function: r = -0.58, p < 0.0001). CONCLUSIONS: The double-dichotomy clustering based on imaging and fluid biomarkers offers an unbiased method for identifying mixed dementia patients and selecting better defined sub-groups. Differential correlations with neuropsychological tests support the hypothesis that the categories of dementia represent different etiologies.

New-onset geriatric epilepsy care: Race, setting of diagnosis, and choice of antiepileptic drug.

PURPOSE: There is a growing movement to assess the quality of care provided to patients in the US, but few studies have examined initial care for epilepsy patients. We examined the relationships among patient race, setting of initial diagnosis, and initial treatment for older veterans newly diagnosed with epilepsy. METHODS: We used Department of Veterans Affairs (VA) inpatient, outpatient, pharmacy and Medicare data (1999-2004) to identify patients 66 years and older with new-onset epilepsy. High quality care was defined as avoiding a suboptimal agent (phenytoin, phenobarbital, primidone) as defined by experts. Predictors included demographic and clinical characteristics, and the context of the initial seizure diagnosis including the setting (e.g. emergency, neurology, hospital, primary care). We used mixed-effects multivariable logistic regression modeling to identify predictors of initial seizure diagnosis in a neurology setting, and receipt of a suboptimal AED. RESULTS: Of 9,682 patients, 27% were initially diagnosed in neurology and 70% received a suboptimal AED. Blacks and Hispanics were less likely to be diagnosed in neurology clinics (black OR = 0.7 95% CI 0.6-0.8; Hispanic OR = 0.6 95% CI 0.5-0.9). Diagnosis in a non-neurology setting increased the likelihood of receiving a suboptimal agent (e.g. Emergency Department OR = 2.3 95% CI 2.0-2.7). After controlling for neurology diagnosis, black race was independently associated with an increased risk of receiving a suboptimal agent. DISCUSSION: We demonstrated that differences in quality of care exist for both clinical setting of initial diagnosis and race. We discussed possible causes and implications of these findings.

Temporal dynamics of age-related differences in auditory incidental verbal learning.

Auditory response profiles for a group of ten healthy young and ten healthy elderly subjects, evoked by implicit memory and delayed verbal recognition tasks, were evaluated to determine if effects of stimulus repetition could be identified in the superior temporal gyrus (STG) and prefrontal cortical regions. We hypothesized that effects of stimulus repetition should occur both early in time and at early levels of the nervous system (STG) followed by later effects in prefrontal regions. Magnetoencephalographic (MEG) responses were recorded using a whole-head MEG system and automated, multi-start analysis methods were applied to the data in order to characterize the temporal response profiles from distributed but focal, cortical regions engaged in memory-related tasks. The findings revealed a main effect of age for early activity ( approximately 50 ms) in STG which appeared to be nonspecific for Old/New words and an Age x Task interaction for late activity ( approximately 100-800 ms) in STG which was specific to Old/New words. Although the behavioral performance measures did not reveal traditional effects of response priming, the MEG measures did reveal a reduction in amplitude with stimulus repetition in young subjects. The elderly did not reveal a reduction in amplitude concomitant with stimulus repetition for either the global attributes of words or for specific Old/New words. Long duration effects of stimulus repetition noted in the present study raise the possibility that results from sensory gating, mismatch negativity and P300 paradigms may represent a continuum of stimulus repetition effects. Two of these paradigms evoke greater enhancement to novel or infrequent stimuli, or rather, greater reduction of amplitude with repetition.

Aging-related changes in auditory and visual integration measured with MEG.

As noted in the aging literature, processing delays often occur in the central nervous system with increasing age, which is often attributable in part to demyelination. In addition, differential slowing between sensory systems has been shown to be most discrepant between visual (up to 20ms) and auditory systems (<5ms). Therefore, we used MEG to measure the multisensory integration response in auditory association cortex in young and elderly participants to better understand the effects of aging on multisensory integration abilities. Results show a main effect for reaction times (RTs); the mean RTs of the elderly were significantly slower than the young. In addition, in the young we found significant facilitation of RTs to the multisensory stimuli relative to both unisensory stimuli, when comparing the cumulative distribution functions, which was not evident for the elderly. We also identified a significant interaction between age and condition in the superior temporal gyrus. In particular, the elderly had larger amplitude responses (∼100ms) to auditory stimuli relative to the young when auditory stimuli alone were presented, whereas the amplitude of responses to the multisensory stimuli was reduced in the elderly, relative to the young. This suppressed cortical multisensory integration response in the elderly, which corresponded with slower RTs and reduced RT facilitation effects, has not been reported previously and may be related to poor cortical integration based on timing changes in unisensory processing in the elderly.

Choice of initial antiepileptic drug for older veterans: possible pharmacokinetic drug interactions with existing medications.

OBJECTIVES: To identify clinically meaningful potential drug-drug interactions (PDIs) with antiepileptic drugs (AEDs), the AEDs and co-administered drugs commonly associated with AED-PDIs, and characteristics of patients with high likelihood of AED-PDI exposure. DESIGN: Five-year retrospective cohort study of veterans with new-onset epilepsy. SETTING: National Veterans Affairs and Medicare databases. PARTICIPANTS: Veterans aged 66 and older with a new diagnosis of epilepsy between October 1, 1999, and September 30, 2004 (N=9,682). MEASUREMENTS: AED-PDI was restricted to clinically meaningful PDIs identified using prior literature review. AED-PDIs were identified using participants' date of initial AED prescription and overlapping concomitant medications. Logistic regression analysis identified factors associated with AED-PDI, including demographic characteristics, chronic disease states, and diagnostic setting. RESULTS: AED-PDI exposure was found in 45.5% (4,406/9,682); phenytoin, a drug with many PDIs, was the most commonly prescribed AED. Cardiovascular drugs, lipid-lowering medications, and psychotropic agents were the most commonly co-administered AED-PDI medications. Individuals with AED-PDI exposure were more likely to have hypertension (odds ratio (OR)=1.46, 99% confidence interval (CI)=1.24-1.82) and hypercholesterolemia (OR=1.40, 99% CI=1.24-1.57) than those without and to be diagnosed in an emergency or primary care setting than a neurology setting (emergency: OR=1.30, 99% CI=1.08-1.58; primary care: OR=1.29 99% CI=1.12-1.49). CONCLUSION: Exposure to AED-PDI was substantial but less common in patients with epilepsy diagnosed in a neurology setting. Because potential outcomes associated with AED-PDI include stroke and myocardial infarction in a population already at high risk, clinicians should closely monitor blood pressure, coagulation, and lipid measures to minimize adverse effects of AED-PDIs. Interventions to reduce AED-PDIs may improve patient outcomes.

New-onset epilepsy risk factors in older veterans.

OBJECTIVES: To identify risk factors for new-onset geriatric epilepsy that may trigger clinicians to consider a differential diagnosis of epilepsy at symptom onset. DESIGN: Retrospective cohort study. SETTING: National Veterans Affairs (VA) databases. PARTICIPANTS: Veterans aged 66 and older in fiscal year 2000 (FY00) who received VA care in FY99 and FY00. Individuals with new-onset epilepsy based on a validated algorithm constituted the epilepsy cohort (n=1,843), and individuals without epilepsy constituted the geriatric cohort (n=1,023,376). MEASUREMENTS: Age, sex, and race were derived from VA databases. Clinical conditions associated with new-onset geriatric epilepsy (e.g., cerebrovascular disease, dementia, brain tumor) and stroke risk-factors (e.g., hypertension, diabetes mellitus, cardiovascular disease) were identified using validated International Classification of Diseases, Ninth Revision, Clinical Modification, codes before epilepsy onset (epilepsy cohort) and in FY00 (geriatric cohort). RESULTS: Multivariable logistic regression analysis indicated that patients with cerebrovascular disease (odds ratio (OR)=3.50, 95% confidence interval (CI)=3.13-3.91), cerebrovascular disease and dementia (OR=4.14, 95% CI=3.46-4.96), brain tumor (OR=2.14, 95% CI=1.46-3.13), head injury (OR=2.11, 95% CI=1.41-3.14), and other central nervous system (CNS) conditions (OR=1.57, 95% CI=1.32-1.88) were more likely to experience new-onset epilepsy. Statin prescription (OR=0.64, 95% CI=0.56-0.73), older age (> or =85 vs 66-74, OR=0.66, 95% CI=0.50-0.87), obesity (OR=0.74, 95% CI=0.62-0.87), and hypercholesterolemia (OR=0.87, 95% CI=0.76-0.98) were associated with a lower likelihood of epilepsy. CONCLUSION: These data suggest greater epilepsy risk for older individuals with CNS insult and an additive effect of cerebrovascular disease and dementia. The statin finding requires further exploration but points to a possible target for prevention of geriatric epilepsy.

Aging: compensation or maturation?

Neuroimaging studies of healthy aging often reveal differences in neural activation patterns between young and elderly groups for episodic memory tasks, even though there are no differences in behavioral performance. One explanation typically offered is that the elderly compensate for their memory deficiencies through the recruitment of additional prefrontal regions. The present study of healthy aging compared magnetoencephalographic (MEG) time-courses localized to specific cortical regions in two groups of subjects (20-29 years and >or=65 years) during a visual delayed-match-to-sample (DMS) task. MR morphometrics and neuropsychological test results were also examined with the hope of providing insight into the nature of the age-related differences. The behavioral results indicated no differences in performance between young and elderly groups. Although there was a main effect of age on the latency of the initial peak in primary/secondary visual cortex, these longer latencies were not correlated with the performance of elderly on the DMS task. The lateral occipital gyrus (LOG) revealed qualitatively different patterns of activity for the two age groups corroborated by neuropsychological test results. Morphometric results for the young versus elderly groups revealed less white (WM) and gray matter (GM) volumes in the frontal lobes of the elderly. When a group of middle-aged subjects (33-43 years) was included in the morphometric analyses, the middle-aged subjects revealed statistically greater WM volumes in frontal and parietal cortex suggesting immature WM tracts in the young. Perhaps our elderly utilized a different strategy compared to the young due to the different brain maturation levels of these groups.