Brain age as a surrogate marker for cognitive performance in multiple sclerosis

Background: Data from neuro-imaging techniques allow us to estimate a brain's age. Brain age is easily interpretable as "how old the brain looks", and could therefore be an attractive communication tool for brain health in clinical practice. This study aimed to investigate its clinical utility by investigating the relationship between brain age and cognitive performance in multiple sclerosis (MS). Methods: A linear regression model was trained to predict age from brain MRI volumetric features and sex in a healthy control dataset (HC_train, n=1673). This model was used to predict brain age in two test sets: HC_test (n=50) and MS_test (n=201). Brain-Predicted Age Difference (BPAD) was calculated as BPAD=brain age minus chronological age. Cognitive performance was assessed by the Symbol Digit Modalities Test (SDMT). Results: Brain age was significantly related to SDMT scores in the MS_test dataset (r=-0.46, p<.001), and contributed uniquely to variance in SDMT beyond chronological age, reflected by a significant correlation between BPAD and SDMT (r=-0.24, p<.001) and a significant weight (-0.25, p=0.002) in a multivariate regression equation with age. Conclusions: Brain age is a candidate biomarker for cognitive dysfunction in MS and an easy to grasp metric for brain health

The squares test as a measure of hand function in multiple sclerosis

Deterioration of hand function can be important in multiple sclerosis (MS). The standard way of assessing hand function in MS is the 9-hole peg test (9HPT), one of the three components of the MS functional composite measure. In this study we examine the squares test (ST), a test of hand function that is used extensively in handedness research. We evaluated reproducibility of the ST in 49 healthy controls, and both discriminatory power and concurrent validity of the ST in 38 MS patients and 18 age and gender matched controls. The ST proved to be a reliable and easy to administrate paper-and-pencil test of hand function. The ST showed a high and highly significant correlation with the standard 9HPT over a broad range of Expanded Disability Status Scale (EDSS) scores, and had high discriminatory power, also comparable to the 9HPT. Therefore, the ST is a candidate test for use in composite measures of MS related functional deficits for clinical practice and in clinical trials. (C) 2014 Elsevier B.V. All rights reserved

Do advanced statistical techniques really help in the diagnosis of the Metabolic Syndrome in patients treated with second-generation anti-psychotics?

Objective Metabolic and cardiovascular diseases in patients with schizophrenia have gained a lot of interest in recent years. Developing an algorithm to detect the metabolic syndrome based on readily available variables would eliminate the need for blood sampling, which is considered as expensive and inconvenient in this population. Methods We used logistic regression and optimized artificial neural networks and support vector machines to detect the metabolic syndrome in a cohort of schizophrenia patients of the UPC Kortenberg, KU Leuven. Testing was done on one third of the included cohort (202 patients), training was performed using a tenfold stratified cross-validation scheme. Results All three methods yielded similar results with satisfying accuracies of about 80 %. However, none of the advanced statistical methods could improve on the results obtained using a very simple and naïve model including only central obesity and information on blood pressure. Conclusion Although so-called patter recognition techniques bear high promise in improving clinical decision making, the results should be presented with caution and preferably in comparison with some lowtech technique. Runningstatus: publishe

The Symbol Digit Modalities Test as sentinel test for cognitive impairment in multiple sclerosis

Background and purpose: Cognitive impairment (CI) is found in about half of the multiple sclerosis (MS) population and is an important contributor to employment status and social functioning. CI is encountered in all disease stages and correlates only moderately with disease duration or Expanded Disability Status Scale scores. Most present neuropsychological test batteries are time-demanding and expensive. The Symbol Digit Modalities Test (SDMT) has been suggested as a screening tool for CI in MS. In this paper, we aim to assess the performance of the SDMT in predicting the outcome of an extensive battery. Methods: Neuropsychological test results from 359 patients were assessed in a multidisciplinary MS center (National MS Center Melsbroek, Belgium). Using receiver operating characteristic curves, the performance of the SDMT in predicting the general cognitive outcome of the extensive Neuropsychological Screening Battery for MS (NSBMS) could be assessed. The performance of the SDMT was assessed for different levels of CI and compared with other cognitive tests. Finally, useful covariates were included in a logistic regression model. Results: At a specificity of 0.60 a high sensitivity (0.91) was obtained indicating the potential of the SDMT as a sentinel test for CI in MS. The SDMT outperformed the individual tests included in the NSBMS, used as benchmark. As the logistic regression model did not result in a relevant improvement, it is concluded that most clinical variables influence both the SDMT and the NSBMS in a similar way. Excluding patients with possible practice effects, an optimal cutoff of 40 was found for the SDMT. Conclusion: As the SDMT is an easy, low-cost and fast test, this result may help to detect CI in everyday clinical practice

The role of hippocampal theta oscillations in working memory impairment in multiple sclerosis

Working memory (WM) problems are frequently present in people with multiple sclerosis (MS). Even though hippocampal damage has been repeatedly shown to play an important role, the underlying neurophysiological mechanisms remain unclear. This study aimed to investigate the neurophysiological underpinnings of WM impairment in MS using magnetoencephalography (MEG) data from a visual‐verbal 2‐back task. We analysed MEG recordings of 79 MS patients and 38 healthy subjects through event‐related fields and theta (4–8 Hz) and alpha (8–13 Hz) oscillatory processes. Data was source reconstructed and parcellated based on previous findings in the healthy subject sample. MS patients showed a smaller maximum theta power increase in the right hippocampus between 0 and 400 ms than healthy subjects (p = .014). This theta power increase value correlated negatively with reaction time on the task in MS (r = −.32, p = .029). Evidence was provided that this relationship could not be explained by a ‘common cause’ confounding relationship with MS‐related neuronal damage. This study provides the first neurophysiological evidence of the influence of hippocampal dysfunction on WM performance in MS

Do the posterior midline cortices belong to the electrophysiological default-mode network?

The default-mode network (DMN) and its principal core hubs in the posterior midline cortices (PMC), i.e., the precuneus and the posterior cingulate cortex, play a critical role in the human brain structural and functional architecture. Because of their centrality, they are affected by a wide spectrum of brain disorders, e.g., Alzheimer's disease. Non-invasive electrophysiological techniques such as magnetoencephalography (MEG) are crucial to the investigation of the neurophysiology of the DMN and its alteration by brain disorders. However, MEG studies relying on band-limited power envelope correlation diverge in their ability to identify the PMC as a part of the DMN in healthy subjects at rest. Since these works were based on different MEG recording systems and different source reconstruction pipelines, we compared DMN functional connectivity estimated with two distinct MEG systems (Elekta, now MEGIN, and CTF) and two widely used reconstruction algorithms (Minimum Norm Estimation and linearly constrained minimum variance Beamformer). Our results identified the reconstruction method as the critical factor influencing PMC functional connectivity, which was significantly dampened by the Beamformer. On this basis, we recommend that future electrophysiological studies on the DMN should rely on Minimum Norm Estimation (or close variants) rather than on the classical Beamformer. Crucially, based on analytic knowledge about these two reconstruction algorithms, we demonstrated with simulations that this empirical observation could be explained by the existence of a spontaneous linear, approximately zero-lag synchronization structure between areas of the DMN or among multiple sources within the PMC. This finding highlights a novel property of the neural dynamics and functional architecture of a core human brain network at rest

Altered transient brain dynamics in multiple sclerosis: treatment or pathology?

Multiple sclerosis (MS) is a demyelinating, neuroinflammatory, and ‐degenerative disease that affects the brain's neurophysiological functioning through brain atrophy, a reduced conduction velocity and decreased connectivity. Currently, little is known on how MS affects the fast temporal dynamics of activation and deactivation of the different large‐scale, ongoing brain networks. In this study, we investigated whether these temporal dynamics are affected in MS patients and whether these changes are induced by the pathology or by the use of benzodiazepines (BZDs), an important symptomatic treatment that aims at reducing insomnia, spasticity and anxiety and reinforces the inhibitory effect of GABA. To this aim, we employed a novel method capable of detecting these fast dynamics in 90 MS patients and 46 healthy controls. We demonstrated a less dynamic frontal default mode network in male MS patients and a reduced activation of the same network in female MS patients, regardless of BZD usage. Additionally, BZDs strongly altered the brain's dynamics by increasing the time spent in the deactivating sensorimotor network and the activating occipital network. Furthermore, BZDs induced a decreased power in the theta band and an increased power in the beta band. The latter was strongly expressed in those states without activation of the sensorimotor network. In summary, we demonstrate gender‐dependent changes to the brain dynamics in the frontal DMN and strong effects from BZDs. This study is the first to characterise the effect of multiple sclerosis and BZDs in vivo in a spatially, temporally and spectrally defined way

Altered transient brain dynamics in multiple sclerosis: Treatment or pathology?

Multiple sclerosis (MS) is a demyelinating, neuroinflammatory, and ‐degenerative disease that affects the brain's neurophysiological functioning through brain atrophy, a reduced conduction velocity and decreased connectivity. Currently, little is known on how MS affects the fast temporal dynamics of activation and deactivation of the different large‐scale, ongoing brain networks. In this study, we investigated whether these temporal dynamics are affected in MS patients and whether these changes are induced by the pathology or by the use of benzodiazepines (BZDs), an important symptomatic treatment that aims at reducing insomnia, spasticity and anxiety and reinforces the inhibitory effect of GABA. To this aim, we employed a novel method capable of detecting these fast dynamics in 90 MS patients and 46 healthy controls. We demonstrated a less dynamic frontal default mode network in male MS patients and a reduced activation of the same network in female MS patients, regardless of BZD usage. Additionally, BZDs strongly altered the brain's dynamics by increasing the time spent in the deactivating sensorimotor network and the activating occipital network. Furthermore, BZDs induced a decreased power in the theta band and an increased power in the beta band. The latter was strongly expressed in those states without activation of the sensorimotor network. In summary, we demonstrate gender‐dependent changes to the brain dynamics in the frontal DMN and strong effects from BZDs. This study is the first to characterise the effect of multiple sclerosis and BZDs in vivo in a spatially, temporally and spectrally defined way