- Qin P, Wu X, Huang Z, et al. How are different neural networks related to consciousness? Annal of Neurology 2015; 78: 594-605.
This is an important study using resting state-functional MR analysis in a large sample of neurological patients with impairment of consciousness ranging from unresponsive wakefulness to minimally conscious state, compared to brain damaged conscious subjects. The main result is that the salience network connectivity correlates with behavioural signs of consciousness, while the status of default mode network connectivity is a predictor of consciousness recovery. Besides the clinical implications, the paper offers novel insights into the neural networks correlated to the conscious state.
Stefano F. Cappa, MD, Prof
2nd Department of Neurology
Ospedale San Raffaele – Vita-Salute San Raffaele University
Co-chair, EAN Scientific Panel Higher cortical functions
- Nalls MA, McLean CY, Rick J, et al. Diagnosis of Parkinson’s disease on the basis of clinical and genetic classification: a population-based modelling study. Lancet Neurology 2015; 14: 1002-9.
Parkinson disease (PD) is currently diagnosed at an advanced neuropathological stage, when a vast amount of neurons has already been lost, thus precluding the success of any disease-modifying interventions (DMIs). Consequently, there is mounting interest in strategies leading to an earlier diagnosis of PD. A research conducted by the Parkinson’s Disease Biomarkers Program and Parkinson’s Progression Marker Initiative investigators aimed at developing an algorithm that would correctly distinguish PD patients from controls, without incorporating the disease motor symptoms. The authors performed a case-control study and used logistic regression in order to come up with the final model, which included olfactory testing (using the UPSIT), family history of PD, age, gender, and a composite genetic risk score. The algorithm was tested on five diverse PD cohorts, and SWEDD (scans without evidence of dopaminergic deficits) patients were also studied. The authors demonstrated high accuracy of the classification model (area under curve of 0.9 or more). The detection of PD among SWEDD patients was less effective, and a clear bimodal distribution was shown in this group. An important limitation relates to the fact that the individuals included in the research were from European ancestry only, thus validation is warranted in genetically diverse populations. Prospective cohort studies could demonstrate the potential usefulness of this method to detect preclinical and premotor PD, and could clarify how it might contribute to research on disease biomarkers and DMIs.
- Rose SJ, Yu XY, Heinzer AK, et al. A new knock-in mouse model of l-DOPA-responsive dystonia. Brain 2015; 138: 2987-3002.
Despite clinical evidence that dopamine transmission is linked to the development of dystonia, it is unknown how this deficit produces dystonic symptoms. This study add an important piece of information on the neurochemical mechanism underlying the development of dystonia. The authors generated a knock-in mouse model of DOPA-responsive dystonia (DRD) introducing a mutation in the tyrosine hydroxylase (TH) gene of the mouse which is homologous to the TH mutation causing DRD in humans. In this knock-in mouse model which displayed the core features of the human disorder, the authors clearly demonstrate pre-synaptic and post-synaptic abnormalities at striatal level: dopamine turnover was about four times higher than normal at the beginning of the active period, but fell to normal levels at the beginning of the inactive period; D1 dopamine receptors were supersensitive whereas response to D2 dopamine receptors activation was altered in valence. This study suggests that dystonia may result from a combined deficit at striatal level, involving reduction of dopamine transmission and abnormal response of dopamine receptors.
Francesca Morgante, MD, PhD
Department of Clinical and Experimental Medicine, Movement Disorder Unit
University of Messina
Department of Neurology, Hospital Pedro Hispano/ULS Matosinhos
Department of Clinical Neurosciences and Mental Health
Faculty of Medicine University of Porto
EAN Scientific Panel Movement disorders
- Rovira À, Wattjes MP, Tintoré M, et al. MAGNIMS study group. Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis-clinical implementation in the diagnostic process. Nature Reviews Neurology 2015; 11: 471-82.
- Wattjes MP, Rovira À, Miller D, et al. MAGNIMS study group. Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis-establishing disease prognosis and monitoring patients. Nature Reviews Neurology 2015; 11: 597-606.
With the arrival of the new therapeutic agents with high efficacy but also potential side-effects, the management of Multiple Sclerosis (MS) has become increasingly challenging for clinicians. Against this background, the role of magnetic resonance imaging (MRI) has become strengthened, both with respect to obtaining an early diagnosis and estimating the prognosis of MS, as well as concerning monitoring the efficacy and safety of treatments. Two consensus guidelines of the MAGNIMS (Magnetic Resonance Imaging in MS) group, a European network of academics that share a common interest in the study of MS using MRI techniques, tackle these issues in the form of evidence-based guidelines. The two papers, recently published in Nature Reviews Neurology and available for free via open-access, provide practical recommendations for the use of MRI in the diagnostic process and for establishing disease prognosis and monitoring patients with MS and thus deserve to be recommended to the Neuropenews readers.
Christian Enzinger, MD
Research Unit for Neuronal Plasticity & Repair
University Clinic of Neurology
Medical University of Graz
Co-chair, EAN Scientific Panel Neuroimaging
- Bennet DA, Brayne C, Feigin VL, et al. Explanation and Elaboration of the Standards of Reporting of Neurological Disorders Checklist: A Guideline for the Reporting of Incidence and Prevalence Studies in Neuroepidemiology. Neuroepidemiology 2015; 45: 113-137.
Descriptive epidemiological studies can play a significant role in quantifying the burden of diseases by helping health care decision making, as well as in hypothesis generation. Yet, the impact of these studies is often reduced by the poor quality of reporting. The introduction and widespread use of this guideline (STROND) should lead to clear and standardized reporting of methodology and findings, providing researchers, doctors, and policy makers with clear, transparent and comparable data. The paper by Bennett et al. is available at the Journal website free of charge.
Ilaria Casetta, MD, Assist. Prof
Section of Neurological, Psychiatric and Psychological Sciences
Department of Biomedical and Specialty Surgical Sciences
EAN Scientific Panel Neuroepidemiology
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