Neuroanatomical associations of the Edinburgh cognitive and Behavioural ALS screen (ECAS)

Cerebral glucose metabolic correlates of cognitive and behavioural impairments in amyotrophic lateral sclerosis

OBJECTIVE

Half of ALS patients are cognitively and/or behaviourally impaired. As cognition/behaviour and cerebral glucose metabolism can be correlated by means of 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET), we aimed to utilise FDG-PET, first, to replicate group-level differences in glucose metabolism between non-demented ALS patients separated into non-impaired (ALSni), cognitively impaired (ALSci), behaviourally impaired (ALSbi), and cognitively and behaviourally impaired (ALScbi) groups; second, to investigate glucose metabolism and performance in various cognitive domains; and third, to examine the impact of partial volume effects correction (PVEC) of the FDG-PET data on the results.

METHODS

We analysed neuropsychological, clinical, and imaging data from 67 ALS patients (30 ALSni, 21 ALSci, 5 ALSbi, and 11 ALScbi). Cognition was assessed with the Edinburgh Cognitive and Behavioural ALS Screen, and two social cognition tests. FDG-PET and structural MRI scans were acquired for each patient. Voxel-based statistical analyses were undertaken on grey matter volume (GMV) and non-corrected vs. PVE-corrected FDG-PET scans.

RESULTS

ALSci and ALScbi had lower cognitive scores than ALSni. In contrast to both ALSni and ALSci, ALScbi showed widespread hypometabolism in the superior- and middle-frontal gyri in addition to the right temporal pole. Correlations were observed between the GMV, the FDG-PET signal, and various cognitive scores. The FDG-PET results were largely unaffected by PVEC.

INTERPRETATION

Our study identified widespread differences in hypometabolism in the ALScbi-ni but not in the ALSci-ni group comparison, raising the possibility that cerebral metabolism may be more closely related to the presence of behavioural changes than to mild cognitive deficits.

Potential of neuroimaging as a biomarker in amyotrophic lateral sclerosis: from structure to metabolism

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by motor neuron degeneration. The development of ALS involves metabolite alterations leading to tissue lesions in the nervous system. Recent advances in neuroimaging have significantly improved our understanding of the underlying pathophysiology of ALS, with findings supporting the corticoefferent axonal disease progression theory. Current studies on neuroimaging in ALS have demonstrated inconsistencies, which may be due to small sample sizes, insufficient statistical power, overinterpretation of findings, and the inherent heterogeneity of ALS. Deriving meaningful conclusions solely from individual imaging metrics in ALS studies remains challenging, and integrating multimodal imaging techniques shows promise for detecting valuable ALS biomarkers. In addition to giving an overview of the principles and techniques of different neuroimaging modalities, this review describes the potential of neuroimaging biomarkers in the diagnosis and prognostication of ALS. We provide an insight into the underlying pathology, highlighting the need for standardized protocols and multicenter collaborations to advance ALS research.

A neurophysiological approach to mirror movements in amyotrophic lateral sclerosis

OBJECTIVE

To investigate mirror activity in amyotrophic lateral sclerosis (ALS) patients, using a simple paradigm of signal quantification.

METHODS

Patients were asked to perform a brief isometric maximum contraction of the abductor digiti minimi (ADM) or tibialis anterior (TA) on one side, while relaxing the contralateral side of the body. Both sides were investigated. Signals were stored and analyzed offline, for quantification of electromyographic signal. Clinical signs of upper motor neuron (UMN) dysfunction, transcranial magnetic stimulation (TMS) for the upper (UL) and lower limbs (LL), the ADM ipsilateral cortical silent period (iSP) and the Edinburgh Cognitive and Behavioral ALS Screen (ECAS) cognitive scale were also investigated.

RESULTS

42 ALS patients were included. In the 4 investigated muscles the amount of mirror activity was significantly higher than in the matched healthy group. The amount of mirror activity was similar between sides, but significantly higher in UL and LL with abnormal TMS results for ADM (p = 0.005) and TA (p = 0.002), as well as in UL with abnormal iSP values (p = 0.009). No association was found between mirror activity and clinical signs of UMN involvement.

CONCLUSIONS

Mirror activity is a common phenomenon in ALS. Mirror activity intensity corresponds to the severity of UMN dysfunction, as measured by TMS, and probably derives from the abnormal transcallosal inhibition as mirrored by iSP abnormality.

SIGNIFICANCE

Mirror activity is increased in ALS and is associated with abnormal transcallosal inhibition and UMN dysfunction.

Non-motor symptoms in motor neuron disease: prevalence, assessment and impact

People with motor neuron disease often experience non-motor symptoms that may occur secondary to, or distinct from, motor degeneration and that may significantly reduce quality of life, despite being under-recognized and evaluated in clinical practice. Non-motor symptoms explored in this population-based study include pain, fatigue, gastrointestinal issues, poor sleep, low mood, anxiety, problematic saliva, apathy, emotional lability, cognitive complaints and sexual dysfunction. People registered on the Clinical Audit Research and Evaluation of motor neuron disease platform, the Scottish Motor Neuron Disease Register, were invited to complete a questionnaire on non-motor symptoms and a self-reported Amyotrophic Lateral Sclerosis Functional Rating Scale. The questionnaire comprised a pre-defined list of 11 potential non-motor symptoms, with the opportunity to list additional symptoms. A total of 120 individuals participated in this cross-sectional study, a 39% response rate of those sent questionnaires (n = 311); 99% of participants recruited (n = 120) experienced at least one non-motor symptom, with 72% (n = 120) reporting five or more. The symptoms most often reported were pain and fatigue (reported by 76% of participants, respectively). The symptoms reported to be most impactful were gastrointestinal issues (reported as 'severe' by 54% of participants who experienced them), followed by pain and problematic saliva (51%, respectively). Lower Amyotrophic Lateral Sclerosis Functional Rating Scale scores, indicating more advanced disease and being a long survivor [diagnosed over 8 years ago; Black et al. (Genetic epidemiology of motor neuron disease-associated variants in the Scottish population. Neurobiol Aging. 2017;51:178.e11-178.e20.)], were significantly associated with reporting more symptoms; 73% of respondents were satisfied with the frequency that non-motor symptoms were discussed in clinical care; 80% of participants indicated they believe evaluation of non-motor symptom is important to include as outcomes in trials, independent of their personal experience of these symptoms. The preferred method of assessment was completing questionnaires, at home. The overwhelming majority of people with motor neuron disease report non-motor symptoms and these frequently co-occur. Pain, fatigue, gastrointestinal issues, sleep, mood, anxiety, problematic saliva, apathy, emotional lability, cognitive complaints and sexual dysfunction are prevalent. People with motor neuron disease who had worse physical function and those who were long survivors were more likely to report more symptoms. Where reported, these symptoms are frequent, impactful and a priority for people with motor neuron disease in clinical care and trial design.

Neuropsychological impairment in amyotrophic lateral sclerosis-frontotemporal spectrum disorder

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with a rapid course, characterized by motor neuron dysfunction, leading to progressive disability and death. This Review, which is aimed at neurologists, psychologists and other health professionals who follow evidence-based practice relating to ALS and frontotemporal dementia (FTD), examines the neuropsychological evidence that has driven the reconceptualization of ALS as a spectrum disorder ranging from a pure motor phenotype to ALS-FTD. It focuses on changes in cognition and behaviour, which vary in severity across the spectrum: around 50% individuals with ALS are within the normal range, 15% meet the criteria for ALS-FTD, and the remaining 35% are in the mid-spectrum range with milder and more focal impairments. The cognitive impairments include deficits in verbal fluency, executive functions, social cognition and language, and apathy is the most prevalent behavioural change. The pattern and severity of cognitive and behavioural change predicts underlying regional cerebral dysfunction from brain imaging and post-mortem pathology. Our increased recognition of cognition and behaviour as part of the ALS phenotype has led to the development and standardization of assessment tools, which have been incorporated into research and clinical care. Measuring change over the course of the disease is vital for clinical trials, and neuropsychology is proving to be a biomarker for the earliest preclinical changes.

Sleep disorders and white matter integrity in patients with sporadic amyotrophic lateral sclerosis

This study aimed to explore the characteristics of sleep disorders and their relationship with abnormal white-matter integrity in patients with sporadic amyotrophic lateral sclerosis. One hundred and thirty-six patients and 80 healthy controls were screened consecutively, and 56 patients and 43 healthy controls were ultimately analyzed. Sleep disorders were confirmed using the Pittsburgh sleep quality index, the Epworth sleepiness scale, and polysomnography; patients were classified into those with poor and good sleep quality. White-matter integrity was assessed using diffusion tensor imaging and compared between groups to identify the white-matter tracts associated with sleep disorders. The relationship between scores on the Pittsburgh sleep quality index and impaired white-matter tracts was analyzed using multiple regression. Poor sleep quality was more common in patients (adjusted odds ratio, 4.26; p = 0.005). Compared to patients with good sleep quality (n = 30), patients with poor sleep quality (n = 26; 46.4%) showed decreased fractional anisotropy, increased mean diffusivity, and increased radial diffusivity of projection and commissural fibers, and increased radial diffusivity of the right thalamus. The Pittsburgh score showed the best fit with the mean fractional anisotropy of the right anterior limb of the internal capsule (r = - 0.355, p = 0.011) and the mean radial diffusivity of the right thalamus (r = 0.309, p = 0.028). We conclude that sleep disorders are common in patients with sporadic amyotrophic lateral sclerosis and are associated with reduced white-matter integrity. The pathophysiology of amyotrophic lateral sclerosis may contribute directly to sleep disorders.

CAPTURE ALS: the comprehensive analysis platform to understand, remedy and eliminate ALS

The absence of disease modifying treatments for amyotrophic lateral sclerosis (ALS) is in large part a consequence of its complexity and heterogeneity. Deep clinical and biological phenotyping of people living with ALS would assist in the development of effective treatments and target specific biomarkers to monitor disease progression and inform on treatment efficacy. The objective of this paper is to present the Comprehensive Analysis Platform To Understand Remedy and Eliminate ALS (CAPTURE ALS), an open and translational platform for the scientific community currently in development. CAPTURE ALS is a Canadian-based platform designed to include participants' voices in its development and through execution. Standardized methods will be used to longitudinally characterize ALS patients and healthy controls through deep clinical phenotyping, neuroimaging, neurocognitive and speech assessments, genotyping and multisource biospecimen collection. This effort plugs into complementary Canadian and international initiatives to share common resources. Here, we describe in detail the infrastructure, operating procedures, and long-term vision of CAPTURE ALS to facilitate and accelerate translational ALS research in Canada and beyond.

MRI Clustering Reveals Three ALS Subtypes With Unique Neurodegeneration Patterns

OBJECTIVE

The purpose of this study was to identify subtypes of amyotrophic lateral sclerosis (ALS) by comparing patterns of neurodegeneration using brain magnetic resonance imaging (MRI) and explore their phenotypes.

METHODS

We performed T1-weighted and diffusion tensor imaging in 488 clinically well-characterized patients with ALS and 338 control subjects. Measurements of whole-brain cortical thickness and white matter connectome fractional anisotropy were adjusted for disease-unrelated variation. A probabilistic network-based clustering algorithm was used to divide patients into subgroups of similar neurodegeneration patterns. Clinical characteristics and cognitive profiles were assessed for each subgroup. In total, 512 follow-up scans were used to validate clustering results longitudinally.

RESULTS

The clustering algorithm divided patients with ALS into 3 subgroups of 187, 163, and 138 patients. All subgroups displayed involvement of the precentral gyrus and are characterized, respectively, by (1) pure motor involvement (pure motor cluster [PM]), (2) orbitofrontal and temporal involvement (frontotemporal cluster [FT]), and (3) involvement of the posterior cingulate cortex, parietal white matter, temporal operculum, and cerebellum (cingulate-parietal-temporal cluster [CPT]). These subgroups had significantly distinct clinical profiles regarding male-to-female ratio, age at symptom onset, and frequency of bulbar symptom onset. FT and CPT revealed higher rates of cognitive impairment on the Edinburgh cognitive and behavioral ALS screen (ECAS). Longitudinally, clustering remained stable: at 90.4% of their follow-up visits, patients clustered in the same subgroup as their baseline visit.

INTERPRETATION

ALS can manifest itself in 3 main patterns of cerebral neurodegeneration, each associated with distinct clinical characteristics and cognitive profiles. Besides the pure motor and frontotemporal dementia (FTD)-like variants of ALS, a new neuroimaging phenotype has emerged, characterized by posterior cingulate, parietal, temporal, and cerebellar involvement. ANN NEUROL 2022;92:1030-1045.

Cognitive reserve protects ALS-typical cognitive domains: A longitudinal study

BACKGROUND AND OBJECTIVES

To determine whether cognitive reserve (CR) as measured by verbal intelligence quotient, educational length, and achievement protects amyotrophic lateral sclerosis (ALS) patients' verbal fluency, executive functioning, and memory against brain volume loss over a period of 12 months.

METHODS

This cohort study was completed between 2013 and 2016 with a follow-up duration of 12 months. ALS patients were recruited from two specialist out-patient clinics in Rostock and Magdeburg in Germany. Participants underwent cognitive testing and magnetic resonance imaging both at baseline and again after 12 months. The cognitive domains assessed included verbal memory in addition to executive functions such as verbal fluency, working memory, shifting and selective attention.

RESULTS

Thirty-eight ALS patients took part; 25 patients had no cognitive impairment (ALSni), and 13 were cognitively impaired (ALSci). On average, patients lost 294 mm3 in their superior frontal gyri, 225 mm3 in their orbitofrontal gyri, and 15.97 mm3 in their hippocampi over 12 months. There was strong evidence that CR protected letter fluency from further decline (Bayes factor [BF] >10) and moderate evidence that it supported learning effects in letter flexibility (BF >3). However, there is a lack of evidence supporting the notion that working memory, shifting, selective attention or verbal memory (BF = 1) are protected.

DISCUSSION

As CR is easily determined and protects ALS-specific cognitive domains over time, it should be regarded as a valuable predictive marker.

Differential Tractography and Correlation Tractography Findings on Patients With Mild Traumatic Brain Injury: A Pilot Study

Differential tractography and correlation tractography are new tractography modalities to study neuronal changes in brain diseases, but their performances in detecting neuronal injuries are yet to be investigated in patients with mild traumatic brain injury (mTBI). Here we investigated the white matter injury in mTBI patients using differential and correlation tractography. The diffusion MRI was acquired at 33 mTBI patients and 31 health controls. 7 of the mTBI patients had one-year follow-up scans, and differential tractography was used to evaluate injured fiber bundles on these 7 patients. All subjects were evaluated using digital symbol substitution test (DSST) and trail making test A (TMT-A), and the correlation tractography was performed to explore the exact pathways related to the cognitive performance. Our results showed that differential tractography revealed neuronal changes in the corpus callosum in all 7 follow-up mTBI patients with FDR between 0.007 and 0.17. Further, the correlation tractography showed that the splenium of the corpus callosum, combined with the right superior longitudinal fasciculus and right cingulum, were correlated with DSST (FDR = 0.001669) in the acute mTBI patients. The cognitive impairment findings in the acute stage and the longitudinal findings in the corpus callosum in the chronic stage of mTBI patients suggest that differential tractography and correlation tractography are valuable tools in the diagnostic and prognostic evaluation of neuronal injuries in mTBI patients.

Feature selection from magnetic resonance imaging data in ALS: a systematic review

Background:

With the advances in neuroimaging in amyotrophic lateral sclerosis (ALS), it has been speculated that multiparametric magnetic resonance imaging (MRI) is capable to contribute to early diagnosis. Machine learning (ML) can be regarded as the missing piece that allows for the useful integration of multiparametric MRI data into a diagnostic classifier. The major challenges in developing ML classifiers for ALS are limited data quantity and a suboptimal sample to feature ratio which can be addressed by sound feature selection.

Methods:

We conducted a systematic review to collect MRI biomarkers that could be used as features by searching the online database PubMed for entries in the recent 4 years that contained cross-sectional neuroimaging data of subjects with ALS and an adequate control group. In addition to the qualitative synthesis, a semi-quantitative analysis was conducted for each MRI modality that indicated which brain regions were most commonly reported.

Results:

Our search resulted in 151 studies with a total of 221 datasets. In summary, our findings highly resembled generally accepted neuropathological patterns of ALS, with degeneration of the motor cortex and the corticospinal tract, but also in frontal, temporal, and subcortical structures, consistent with the neuropathological four-stage model of the propagation of pTDP-43 in ALS.

Conclusions:

These insights are discussed with respect to their potential for MRI feature selection for future ML-based neuroimaging classifiers in ALS. The integration of multiparametric MRI including DTI, volumetric, and texture data using ML may be the best approach to generate a diagnostic neuroimaging tool for ALS.