Quantitative Oculomotor Assessment in Hereditary Ataxia: Discriminatory Power, Correlation with Severity Measures, and Recommended Parameters for Specific Genotypes

Characterizing bedside oculomotor deficits is a critical factor in defining the clinical presentation of hereditary ataxias. Quantitative assessments are increasingly available and have significant advantages, including comparability over time, reduced examiner dependency, and sensitivity to subtle changes. To delineate the potential of quantitative oculomotor assessments as digital-motor outcome measures for clinical trials in ataxia, we searched MEDLINE for articles reporting on quantitative eye movement recordings in genetically confirmed or suspected hereditary ataxias, asking which paradigms are most promising for capturing disease progression and treatment response. Eighty-nine manuscripts identified reported on 1541 patients, including spinocerebellar ataxias (SCA2, n = 421), SCA3 (n = 268), SCA6 (n = 117), other SCAs (n = 97), Friedreich ataxia (FRDA, n = 178), Niemann-Pick disease type C (NPC, n = 57), and ataxia-telangiectasia (n = 85) as largest cohorts. Whereas most studies reported discriminatory power of oculomotor assessments in diagnostics, few explored their value for monitoring genotype-specific disease progression (n = 2; SCA2) or treatment response (n = 8; SCA2, FRDA, NPC, ataxia-telangiectasia, episodic-ataxia 4). Oculomotor parameters correlated with disease severity measures including clinical scores (n = 18 studies (SARA: n = 9)), chronological measures (e.g., age, disease duration, time-to-symptom onset; n = 17), genetic stratification (n = 9), and imaging measures of atrophy (n = 5). Recurrent correlations across many ataxias (SCA2/3/17, FRDA, NPC) suggest saccadic eye movements as potentially generic quantitative oculomotor outcome. Recommendation of other paradigms was limited by the scarcity of cross-validating correlations, except saccadic intrusions (FRDA), pursuit eye movements (SCA17), and quantitative head-impulse testing (SCA3/6). This work aids in understanding the current knowledge of quantitative oculomotor parameters in hereditary ataxias, and identifies gaps for validation as potential trial outcome measures in specific ataxia genotypes.

Quantitative Oculomotor Assessment in Hereditary Ataxia: Systematic Review and Consensus by the Ataxia Global Initiative Working Group on Digital-motor Biomarkers

Oculomotor deficits are common in hereditary ataxia, but disproportionally neglected in clinical ataxia scales and as outcome measures for interventional trials. Quantitative assessment of oculomotor function has become increasingly available and thus applicable in multicenter trials and offers the opportunity to capture severity and progression of oculomotor impairment in a sensitive and reliable manner. In this consensus paper of the Ataxia Global Initiative Working Group On Digital Oculomotor Biomarkers, based on a systematic literature review, we propose harmonized methodology and measurement parameters for the quantitative assessment of oculomotor function in natural-history studies and clinical trials in hereditary ataxia. MEDLINE was searched for articles reporting on oculomotor/vestibular properties in ataxia patients and a study-tailored quality-assessment was performed. One-hundred-and-seventeen articles reporting on subjects with genetically confirmed (n=1134) or suspected hereditary ataxia (n=198), and degenerative ataxias with sporadic presentation (n=480) were included and subject to data extraction. Based on robust discrimination from controls, correlation with disease-severity, sensitivity to change, and feasibility in international multicenter settings as prerequisite for clinical trials, we prioritize a core-set of five eye-movement types: (i) pursuit eye movements, (ii) saccadic eye movements, (iii) fixation, (iv) eccentric gaze holding, and (v) rotational vestibulo-ocular reflex. We provide detailed guidelines for their acquisition, and recommendations on the quantitative parameters to extract. Limitations include low study quality, heterogeneity in patient populations, and lack of longitudinal studies. Standardization of quantitative oculomotor assessments will facilitate their implementation, interpretation, and validation in clinical trials, and ultimately advance our understanding of the evolution of oculomotor network dysfunction in hereditary ataxias.

Qualitative differences in the spatiotemporal brain states supporting configural face processing emerge in adolescence in autism

BACKGROUND

Studying the neural processing of faces can illuminate the mechanisms of compromised social expertise in autism. To resolve a longstanding debate, we examined whether differences in configural face processing in autism are underpinned by quantitative differences in the activation of typical face processing pathways, or the recruitment of non-typical neural systems.

METHODS

We investigated spatial and temporal characteristics of event-related EEG responses to upright and inverted faces in a large sample of children, adolescents, and adults with and without autism. We examined topographic analyses of variance and global field power to identify group differences in the spatial and temporal response to face inversion. We then examined how quasi-stable spatiotemporal profiles - microstates - are modulated by face orientation and diagnostic group.

RESULTS

Upright and inverted faces produced distinct profiles of topography and strength in the topographical analyses. These topographical profiles differed between diagnostic groups in adolescents, but not in children or adults. In the microstate analysis, the autistic group showed differences in the activation strength of normative microstates during early-stage processing at all ages, suggesting consistent quantitative differences in the operation of typical processing pathways; qualitative differences in microstate topographies during late-stage processing became prominent in adults, suggesting the increasing involvement of non-typical neural systems with processing time and over development.

CONCLUSIONS

These findings suggest that early difficulties with configural face processing may trigger later compensatory processes in autism that emerge in later development.

Changes in brain activity with tominersen in early-manifest Huntington’s disease

It is unknown whether alterations in EEG brain activity caused by Huntington’s disease may be responsive to huntingtin-lowering treatment. We analysed EEG recordings of 46 patients (mean age = 47.02 years; standard deviation = 10.19 years; 18 female) with early-manifest Stage 1 Huntington’s disease receiving the huntingtin-lowering antisense oligonucleotide tominersen for 4 months or receiving placebo as well as 39 healthy volunteers (mean age = 44.48 years; standard deviation = 12.94; 22 female) not receiving treatment. Patients on tominersen showed increased resting-state activity within a 4–8 Hz frequency range compared with patients receiving placebo (cluster-based permutation test, P < 0.05). The responsive frequency range overlapped with EEG activity that was strongly reduced in Huntington’s disease compared with healthy controls (cluster-based permutation test, P < 0.05). The underlying mechanisms of the observed treatment-related increase are unknown and may reflect neural plasticity as a consequence of the molecular pathways impacted by tominersen treatment.

Hawellek et al. report that patients with Huntington’s disease treated with the huntingtin-lowering antisense oligonucleotide tominersen exhibited increased EEG power in the theta/alpha frequency range. The underlying mechanisms of the observed changes are unknown and may reflect neural plasticity as a consequence of the molecular pathways impacted by tominersen treatment.

A Graph Gaussian Embedding Method for Predicting Alzheimer's Disease Progression With MEG Brain Networks

Characterizing the subtle changes of functional brain networks associated with the pathological cascade of Alzheimer's disease (AD) is important for early diagnosis and prediction of disease progression prior to clinical symptoms. We developed a new deep learning method, termed multiple graph Gaussian embedding model (MG2G), which can learn highly informative network features by mapping high-dimensional resting-state brain networks into a low-dimensional latent space. These latent distribution-based embeddings enable a quantitative characterization of subtle and heterogeneous brain connectivity patterns at different regions, and can be used as input to traditional classifiers for various downstream graph analytic tasks, such as AD early stage prediction, and statistical evaluation of between-group significant alterations across brain regions. We used MG2G to detect the intrinsic latent dimensionality of MEG brain networks, predict the progression of patients with mild cognitive impairment (MCI) to AD, and identify brain regions with network alterations related to MCI.

Electrophysiological Phenotype in Angelman Syndrome Differs Between Genotypes

BACKGROUND

Angelman syndrome (AS) is a severe neurodevelopmental disorder caused by either disruptions of the gene UBE3A or deletion of chromosome 15 at 15q11-q13, which encompasses UBE3A and several other genes, including GABRB3, GABRA5, GABRG3, encoding gamma-aminobutyric acid type A receptor subunits (β3, α5, γ3). Individuals with deletions are generally more impaired than those with other genotypes, but the underlying pathophysiology remains largely unknown. Here, we used electroencephalography (EEG) to test the hypothesis that genes other than UBE3A located on 15q11-q13 cause differences in pathophysiology between AS genotypes.

METHODS

We compared spectral power of clinical EEG recordings from children (1-18 years of age) with a deletion genotype (n = 37) or a nondeletion genotype (n = 21) and typically developing children without Angelman syndrome (n = 48).

RESULTS

We found elevated theta power (peak frequency: 5.3 Hz) and diminished beta power (peak frequency: 23 Hz) in the deletion genotype compared with the nondeletion genotype as well as excess broadband EEG power (1-32 Hz) peaking in the delta frequency range (peak frequency: 2.8 Hz), shared by both genotypes but stronger for the deletion genotype at younger ages.

CONCLUSIONS

Our results provide strong evidence for the contribution of non-UBE3A neuronal pathophysiology in deletion AS and suggest that hemizygosity of the GABRB3-GABRA5-GABRG3 gene cluster causes abnormal theta and beta EEG oscillations that may underlie the more severe clinical phenotype. Our work improves the understanding of AS pathophysiology and has direct implications for the development of AS treatments and biomarkers.

Patients with autism spectrum disorders display reproducible functional connectivity alterations

Despite the high clinical burden, little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here, we addressed these questions in four large ASD cohorts. Using rs-fMRI, we identified functional connectivity alterations associated with ASD. We tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status, and clinical symptom severity. Our results showed reproducible patterns of ASD-associated functional hyper- and hypoconnectivity. Hypoconnectivity was primarily restricted to sensory-motor regions, whereas hyperconnectivity hubs were predominately located in prefrontal and parietal cortices. Shifts in cortico-cortical between-network connectivity from outside to within the identified regions were shown to be a key driver of these abnormalities. This reproducible pathophysiological phenotype was partially associated with core ASD symptoms related to communication and daily living skills and was not affected by age, sex, or medication status. Although the large effect sizes in standardized cohorts are encouraging with respect to potential application as a treatment and for patient stratification, the moderate link to clinical symptoms and the large overlap with healthy controls currently limit the usability of identified alterations as diagnostic or efficacy readout.

The EU-AIMS Longitudinal European Autism Project (LEAP): design and methodologies to identify and validate stratification biomarkers for autism spectrum disorders

BACKGROUND

The tremendous clinical and aetiological diversity among individuals with autism spectrum disorder (ASD) has been a major obstacle to the development of new treatments, as many may only be effective in particular subgroups. Precision medicine approaches aim to overcome this challenge by combining pathophysiologically based treatments with stratification biomarkers that predict which treatment may be most beneficial for particular individuals. However, so far, we have no single validated stratification biomarker for ASD. This may be due to the fact that most research studies primarily have focused on the identification of mean case-control differences, rather than within-group variability, and included small samples that were underpowered for stratification approaches. The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study worldwide that aims to identify and validate stratification biomarkers for ASD.

METHODS

LEAP includes 437 children and adults with ASD and 300 individuals with typical development or mild intellectual disability. Using an accelerated longitudinal design, each participant is comprehensively characterised in terms of clinical symptoms, comorbidities, functional outcomes, neurocognitive profile, brain structure and function, biochemical markers and genomics. In addition, 51 twin-pairs (of which 36 had one sibling with ASD) are included to identify genetic and environmental factors in phenotypic variability.

RESULTS

Here, we describe the demographic characteristics of the cohort, planned analytic stratification approaches, criteria and steps to validate candidate stratification markers, pre-registration procedures to increase transparency, standardisation and data robustness across all analyses, and share some 'lessons learnt'. A clinical characterisation of the cohort is given in the companion paper (Charman et al., accepted).

CONCLUSION

We expect that LEAP will enable us to confirm, reject and refine current hypotheses of neurocognitive/neurobiological abnormalities, identify biologically and clinically meaningful ASD subgroups, and help us map phenotypic heterogeneity to different aetiologies.

Adamantinoma of the tibia: plain-film, computed tomography and magnetic resonance imaging appearance

The authors describe the computed tomography (CT) and magnetic resonance imaging (MRI) characteristics of adamantinoma of the tibia in a 29-year-old man. Adamantinoma is a rare, aggressive osteolytic lesion occurring primarily in the diaphyseal portion of long bones. Because of its rarity the MRI features have been infrequently reported. In this case MRI provided more accurate information about the extent and invasiveness of the tumour than either plain radiography or CT.