<i>C9orf72 </i>Repeat Expansion Discordance in 6 Multigenerational Kindreds

Background and Objectives:A hexanucleotide repeat expansion in the noncoding region of the C9orf72 gene is the most common genetically identifiable cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia in populations of European ancestry. Pedigrees associated with this expansion exhibit phenotypic heterogeneity and incomplete disease penetrance, the basis of which is poorly understood. Relatives of those carrying the C9orf72 repeat expansion exhibit a characteristic cognitive endophenotype independent of carrier status. To examine whether additional shared genetic or environmental risks within kindreds could compel this observation, we have conducted a detailed cross-sectional study of the inheritance within multigenerational Irish kindreds carrying the C9orf72 repeat expansion.Methods:One hundred thirty-one familial ALS pedigrees, 59 of which carried the C9orf72 repeat expansion (45.0% [95% CI 36.7–53.5]), were identified through the Irish population-based ALS register. C9orf72 genotyping was performed using repeat-primed PCR with amplicon fragment length analysis. Pedigrees were further investigated using SNP, targeted sequencing data, whole-exome sequencing, and whole-genome sequencing.Results:We identified 21 kindreds where at least 1 family member with ALS carried the C9orf72 repeat expansion and from whom DNA was available from multiple affected family members. Of these, 6 kindreds (28.6% [95% CI 11.8–48.3]) exhibited discordant segregation. The C9orf72 haplotype was studied in 2 families and was found to segregate with the C9orf72-positive affected relative but not the C9orf72-negative affected relative. No other ALS pathogenic variants were identified within these discordant kindreds.Discussion:Family members of kindreds associated with the C9orf72 repeat expansion may carry an increased risk of developing ALS independent of their observed carrier status. This has implications for assessment and counseling of asymptomatic individuals regarding their genetic risk

Localization of brain networks engaged by the sustained attention to response task provides quantitative markers of executive impairment in amyotrophic lateral sclerosis

Objective: To identify cortical regions engaged during the sustained attention to response task (SART) and characterize changes in their activity associated with the neurodegenerative condition amyotrophic lateral sclerosis (ALS). Methods: High-density electroencephalography (EEG) was recorded from 33 controls and 23 ALS patients during a SART paradigm. Differences in associated event-related potential peaks were measured for Go and NoGo trials. Sources active during these peaks were localized, and ALS-associated differences were quantified. Results: Go and NoGo N2 and P3 peak sources were localized to the left primary motor cortex, bilateral dorsolateral prefrontal cortex (DLPFC), and lateral posterior parietal cortex (PPC). NoGo trials evoked greater bilateral medial PPC activity during N2 and lesser left insular, PPC and DLPFC activity during P3. Widespread cortical hyperactivity was identified in ALS during P3. Changes in the inferior parietal lobule and insular activity provided very good discrimination (AUROC > 0.75) between patients and controls. Activation of the right precuneus during P3 related to greater executive function in ALS, indicative of a compensatory role. Interpretation: The SART engages numerous frontal and parietal cortical structures. SART–EEG measures correlate with specific cognitive impairments that can be localized to specific structures, aiding in differential diagnosis

Cognitive network hyperactivation and motor cortex decline correlate with ALS prognosis

We aimed to quantitatively characterize progressive brain network disruption in Amyotrophic Lateral Sclerosis (ALS) during cognition using the mismatch negativity (MMN), an electrophysiological index of attention switching. We measured the MMN using 128-channel EEG longitudinally (2–5 timepoints) in 60 ALS patients and cross-sectionally in 62 healthy controls. Using dipole fitting and linearly constrained minimum variance beamforming we investigated cortical source activity changes over time. In ALS, the inferior frontal gyri (IFG) show significantly lower baseline activity compared to controls. The right IFG and both superior temporal gyri (STG) become progressively hyperactive longitudinally. By contrast, the left motor and dorsolateral prefrontal cortices are initially hyperactive, declining progressively. Baseline motor hyperactivity correlates with cognitive disinhibition, and lower baseline IFG activities correlate with motor decline rate, while left dorsolateral prefrontal activity predicted cognitive and behavioural impairment. Shorter survival correlates with reduced baseline IFG and STG activity and later STG hyperactivation. Source-resolved EEG facilitates quantitative characterization of symptom-associated and symptom-preceding motor and cognitive-behavioral cortical network decline in ALS

Assessing behavioural changes in ALS: cross-validation of ALS-specific measures

Objective: The Beaumont Behavioural Inventory (BBI) is a behavioural proxy report for the assessment of behavioural changes in ALS. This tool has been validated against the FrSBe, a non-ALS specific behavioural assessment, and further comparison of the BBI against a disease-specific tool was considered. This study cross-validates the BBI against the ALS-FTD-Q. Methods: 60 ALS patients, 8% also meeting criteria for FTD, were recruited. All patients were evaluated using the BBI and the ALS-FTD-Q, completed by a carer. Correlational analysis was performed to assess construct validity. Precision, sensitivity, specificity and overall accuracy of the BBI, when compared to the ALS-FTD-Q, were obtained. Results: The mean score of the whole sample on the BBI was 11.45±13.06. ALS-FTD patients scored significantly higher than non-demented ALS patients (31.6±14.64, 9.62±11.38; p<.0001). A significant large positive correlation between the BBI and the ALS-FTD-Q was observed (r=.807, p<.0001), and no significant correlations between the BBI and other clinical/demographic characteristics, indicating good convergent and discriminant validity, respectively. 72% of overall concordance was observed. Precision, sensitivity and specificity for the classification of severely impaired patients were adequate. However, lower concordance in the classification of mild behavioural changes was observed, with higher sensitivity using the BBI, most likely secondary to BBI items which endorsed behavioural aspects not measured by the ALS-FTD-Q. Discussion: Good construct validity has been further confirmed when the BBI is compared to an ALS-specific tool. Furthermore, the BBI is a more comprehensive behavioural assessment for ALS, as it measures the whole behavioural spectrum in this condition

Resting-state EEG reveals four subphenotypes of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a devastating disease characterized primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. Amyotrophic lateral sclerosis is both clinically and biologically heterogeneous. Subgrouping is currently undertaken using clinical parameters, such as site of symptom onset (bulbar or spinal), burden of disease (based on the modified El Escorial Research Criteria) and genomics in those with familial disease. However, with the exception of genomics, these subcategories do not take into account underlying disease pathobiology, and are not fully predictive of disease course or prognosis. Recently, we have shown that resting-state EEG can reliably and quantitatively capture abnormal patterns of motor and cognitive network disruption in amyotrophic lateral sclerosis. These network disruptions have been identified across multiple frequency bands, and using measures of neural activity (spectral power) and connectivity (comodulation of activity by amplitude envelope correlation and synchrony by imaginary coherence) on source-localized brain oscillations from high-density EEG. Using data-driven methods (similarity network fusion and spectral clustering), we have now undertaken a clustering analysis to identify disease subphenotypes and to determine whether different patterns of disruption are predictive of disease outcome. We show that amyotrophic lateral sclerosis patients (n = 95) can be subgrouped into four phenotypes with distinct neurophysiological profiles. These clusters are characterized by varying degrees of disruption in the somatomotor (α-band synchrony), frontotemporal (β-band neural activity and γl-band synchrony) and frontoparietal (γl-band comodulation) networks, which reliably correlate with distinct clinical profiles and different disease trajectories. Using an in-depth stability analysis, we show that these clusters are statistically reproducible and robust, remain stable after reassessment using a follow-up EEG session, and continue to predict the clinical trajectory and disease outcome. Our data demonstrate that novel phenotyping using neuroelectric signal analysis can distinguish disease subtypes based exclusively on different patterns of network disturbances. These patterns may reflect underlying disease neurobiology. The identification of amyotrophic lateral sclerosis subtypes based on profiles of differential impairment in neuronal networks has clear potential in future stratification for clinical trials. Advanced network profiling in amyotrophic lateral sclerosis can also underpin new therapeutic strategies that are based on principles of neurobiology and designed to modulate network disruption

Measuring reliable change in cognition using the Edinburgh Cognitive and Behavioural ALS Screen (ECAS)

doi:https://doi.org/10.1080/21678421.2017.1407794Background: Cognitive impairment affects approximately 50% of people with amyotrophic lateral sclerosis (ALS). Research has indicated that impairment may worsen with disease progression. The Edinburgh Cognitive and Behavioural ALS Screen (ECAS) was designed to measure neuropsychological functioning in ALS, with its alternate forms (ECAS-A, B, and C) allowing for serial assessment over time. Objective: The aim of the present study was to establish reliable change scores for the alternate forms of the ECAS, and to explore practice effects and test-retest reliability of the ECAS?s alternate forms. Method: Eighty healthy participants were recruited, with 57 completing two and 51 completing three assessments. Participants were administered alternate versions of the ECAS serially (A-B-C) at four-month intervals. Intra-class correlation analysis was employed to explore test-retest reliability, while analysis of variance was used to examine the presence of practice effects. Reliable change indices (RCI) and regression-based methods were utilized to establish change scores for the ECAS alternate forms. Results: Test-retest reliability was excellent for ALS Specific, ALS Non-Specific, and ECAS Total scores of the combined ECAS A, B, and C (all?>?.90). No significant practice effects were observed over the three testing sessions. RCI and regression-based methods produced similar change scores. Conclusion: The alternate forms of the ECAS possess excellent test-retest reliability in a healthy control sample, with no significant practice effects. The use of conservative RCI scores is recommended. Therefore, a change of ?8, ?4, and ?9 for ALS Specific, ALS Non-Specific, and ECAS Total score is required for reliable chang

Functional network dynamics revealed by EEG microstates reflect cognitive decline in amyotrophic lateral sclerosis

Recent electroencephalography (EEG) studies have shown that patterns of brain activity can be used to differentiate amyotrophic lateral sclerosis (ALS) and control groups. These differences can be interrogated by examining EEG microstates, which are distinct, reoccurring topographies of the scalp's electrical potentials. Quantifying the temporal properties of the four canonical microstates can elucidate how the dynamics of functional brain networks are altered in neurological conditions. Here we have analysed the properties of microstates to detect and quantify signal-based abnormality in ALS. High-density resting-state EEG data from 129 people with ALS and 78 HC were recorded longitudinally over a 24-month period. EEG topographies were extracted at instances of peak global field power to identify four microstate classes (labelled A-D) using K-means clustering. Each EEG topography was retrospectively associated with a microstate class based on global map dissimilarity. Changes in microstate properties over the course of the disease were assessed in people with ALS and compared with changes in clinical scores. The topographies of microstate classes remained consistent across participants and conditions. Differences were observed in coverage, occurrence, duration, and transition probabilities between ALS and control groups. The duration of microstate class B and coverage of microstate class C correlated with lower limb functional decline. The transition probabilities A to D, C to B and C to B also correlated with cognitive decline (total ECAS) in those with cognitive and behavioural impairments. Microstate characteristics also significantly changed over the course of the disease. Examining the temporal dependencies in the sequences of microstates revealed that the symmetry and stationarity of transition matrices were increased in people with late-stage ALS. These alterations in the properties of EEG microstates in ALS may reflect abnormalities within the sensory network and higher-order networks. Microstate properties could also prospectively predict symptom progression in those with cognitive impairments

Working in the Public Interest Law Conference

Entirely student organized, WIPI seeks to bring together eminent practitioners in their respective fields, students, and faculty to discuss practical approaches to lawyering which can best serve the poor. Practical methods of challenging poverty are often not covered in traditional law school courses. This conference seeks to remedy that and provide dynamic, creative ways to combat poverty through the vehicle of the law