Brain metabolic signatures in patients with genetic and nongenetic amyotrophic lateral sclerosis

Factors associated with Edinburgh Cognitive and Behavioural ALS Screen (ECAS) alteration at time of diagnosis, in amyotrophic lateral sclerosis

BACKGROUND

Edinburgh Cognitive and Behavioral ALS Screen (ECAS) is a validated assessment designed to screen cognitive functions and behavioral disorders in amyotrophic lateral sclerosis (ALS). Objective of this study is to determine the factors associated with ECAS impairment in a cohort of ALS patients without a co-morbid diagnosis of dementia, at the time of diagnosis.

METHODS

We enrolled 71 non-demented ALS patient. We collected clinical and demographic data, ALS familiarity, analysis of the most commonly mutated genes in ALS, ALS Milano Torino Staging System and ALS Functional Rate Scale revised scores, progression rate; finally, we recorded whether symptoms onset involved spinal or bulbar area. The alteration of the ECAS was estimated based on age and education-adjusted-validated cut off for each of the items included in ECAS. A multivariable regression analysis was done.

RESULTS

The significant determinants of ECAS alterations were: bulbar onset in both ALS-specific test and total ECAS score; bulbar onset and familiarity in ALS-non-specific test; finally, familiarity and diagnosis delay in ALS-behavioral test. All the subjects carrying C9orf72 mutations had alteration of both total ECAS score and ALS-specific tests.

DISCUSSION

At diagnosis, bulbar-onset ALS, family history, diagnosis delay and C9orf72 hexanucleotide repeat expansion may contribute to impairment of ECAS.

Unraveling multi-scale neuroimaging biomarkers and molecular foundations for schizophrenia: A combined multivariate pattern analysis and transcriptome-neuroimaging association study

AIMS

Schizophrenia is characterized by alterations in resting-state spontaneous brain activity; however, it remains uncertain whether variations at diverse spatial scales are capable of effectively distinguishing patients from healthy controls. Additionally, the genetic underpinnings of these alterations remain poorly elucidated. We aimed to address these questions in this study to gain better understanding of brain alterations and their underlying genetic factors in schizophrenia.

METHODS

A cohort of 103 individuals with diagnosed schizophrenia and 110 healthy controls underwent resting-state functional MRI scans. Spontaneous brain activity was assessed using the regional homogeneity (ReHo) metric at four spatial scales: voxel-level (Scale 1) and regional-level (Scales 2-4: 272, 53, 17 regions, respectively). For each spatial scale, multivariate pattern analysis was performed to classify schizophrenia patients from healthy controls, and a transcriptome-neuroimaging association analysis was performed to establish connections between gene expression data and ReHo alterations in schizophrenia.

RESULTS

The ReHo metrics at all spatial scales effectively discriminated schizophrenia from healthy controls. Scale 2 showed the highest classification accuracy at 84.6%, followed by Scale 1 (83.1%) and Scale 3 (78.5%), while Scale 4 exhibited the lowest accuracy (74.2%). Furthermore, the transcriptome-neuroimaging association analysis showed that there were not only shared but also unique enriched biological processes across the four spatial scales. These related biological processes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity.

CONCLUSIONS

This study highlights the potential of multi-scale ReHo as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. By elucidating the complex molecular basis underlying the ReHo alterations of this disorder, this study not only enhances our understanding of its pathophysiology, but also pave the way for future advancements in genetic diagnosis and treatment of schizophrenia.

Cortical microstructural abnormalities in amyotrophic lateral sclerosis: a gray matter-based spatial statistics study

Background

Amyotrophic lateral sclerosis (ALS)-related white-matter microstructural abnormalities have received considerable attention; however, gray-matter structural abnormalities have not been fully elucidated. This study aimed to evaluate cortical microstructural abnormalities in ALS and determine their association with disease severity.

Methods

This study included 34 patients with ALS and 30 healthy controls. Diffusion-weighted data were used to estimate neurite orientation dispersion and density imaging (NODDI) parameters, including neurite density index (NDI) and orientation dispersion index (ODI). We performed gray matter-based spatial statistics (GBSS) in a voxel-wise manner to determine the cortical microstructure difference. We used the revised ALS Functional Rating Scale (ALSFRS-R) to assess disease severity and conducted a correlation analysis between NODDI parameters and ALSFRS-R.

Results

In patients with ALS, the NDI reduction involved several cortical regions [primarily the precentral gyrus, postcentral gyrus, temporal cortex, prefrontal cortex, occipital cortex, and posterior parietal cortex; family-wise error (FWE)-corrected P<0.05]. ODI decreased in relatively few cortical regions (including the precentral gyrus, postcentral gyrus, prefrontal cortex, and inferior parietal lobule; FWE-corrected P<0.05). The NDI value in the left precentral and postcentral gyrus was positively correlated with the ALS disease severity (FWE-corrected P<0.05).

Conclusions

The decreases in NDI and ODI involved both motor-related and extra-motor regions and indicated the presence of gray-matter microstructural impairment in ALS. NODDI parameters are potential imaging biomarkers for evaluating disease severity in vivo. Our results showed that GBSS is a feasible method for identifying abnormalities in the cortical microstructure of patients with ALS.

Cerebellum in Alzheimer's disease and other neurodegenerative diseases: an emerging research frontier

The cerebellum is crucial for both motor and nonmotor functions. Alzheimer's disease (AD), alongside other dementias such as vascular dementia (VaD), Lewy body dementia (DLB), and frontotemporal dementia (FTD), as well as other neurodegenerative diseases (NDs) like Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and spinocerebellar ataxias (SCA), are characterized by specific and non-specific neurodegenerations in central nervous system. Previously, the cerebellum's significance in these conditions was underestimated. However, advancing research has elevated its profile as a critical node in disease pathology. We comprehensively review the existing evidence to elucidate the relationship between cerebellum and the aforementioned diseases. Our findings reveal a growing body of research unequivocally establishing a link between the cerebellum and AD, other forms of dementia, and other NDs, supported by clinical evidence, pathological and biochemical profiles, structural and functional neuroimaging data, and electrophysiological findings. By contrasting cerebellar observations with those from the cerebral cortex and hippocampus, we highlight the cerebellum's distinct role in the disease processes. Furthermore, we also explore the emerging therapeutic potential of targeting cerebellum for the treatment of these diseases. This review underscores the importance of the cerebellum in these diseases, offering new insights into the disease mechanisms and novel therapeutic strategies.

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.

PET and SPECT Imaging of ALS: An Educational Review

Amyotrophic lateral sclerosis (ALS) is a disease leading to progressive motor degeneration and ultimately death. It is a complex disease that can take a significantly long time to be diagnosed, as other similar pathological conditions must be ruled out for a definite diagnosis of ALS. Noninvasive imaging of ALS has shed light on disease pathology and altered biochemistry in the ALS brain. Other than magnetic resonance imaging (MRI), two types of functional imaging, positron emission tomography (PET) and single photon emission computed tomography (SPECT), have provided valuable data about what happens in the brain of ALS patients compared to healthy controls. PET imaging has revealed a specific pattern of brain metabolism through [18F]FDG, while other radiotracers have uncovered neuroinflammation, changes in neuronal density, and protein aggregation. SPECT imaging has shown a general decrease in regional cerebral blood flow (rCBF) in ALS patients. This educational review summarizes the current state of ALS imaging with various PET and SPECT radiopharmaceuticals to better understand the pathophysiology of ALS.