Single-Cell RNA Sequencing Analysis Reveals a Crucial Role for CTHRC1 (Collagen Triple Helix Repeat Containing 1) Cardiac Fibroblasts After Myocardial Infarction.

BACKGROUND: Cardiac fibroblasts (CFs) have a central role in the ventricular remodeling process associated with different types of fibrosis. Recent studies have shown that fibroblasts do not respond homogeneously to heart injury. Because of the limited set of bona fide fibroblast markers, a proper characterization of fibroblast population heterogeneity in response to cardiac damage is lacking. The purpose of this study was to define CF heterogeneity during ventricular remodeling and the underlying mechanisms that regulate CF function. METHODS: Collagen1α1-GFP (green fluorescent protein)-positive CFs were characterized after myocardial infarction (MI) by single-cell and bulk RNA sequencing, assay for transposase-accessible chromatin sequencing, and functional assays. Swine and patient samples were studied using bulk RNA sequencing. RESULTS: We identified and characterized a unique CF subpopulation that emerges after MI in mice. These activated fibroblasts exhibit a clear profibrotic signature, express high levels of Cthrc1 (collagen triple helix repeat containing 1), and localize into the scar. Noncanonical transforming growth factor-ß signaling and different transcription factors including SOX9 are important regulators mediating their response to cardiac injury. Absence of CTHRC1 results in pronounced lethality attributable to ventricular rupture. A population of CFs with a similar transcriptome was identified in a swine model of MI and in heart tissue from patients with MI and dilated cardiomyopathy. CONCLUSIONS: We report CF heterogeneity and their dynamics during the course of MI and redefine the CFs that respond to cardiac injury and participate in myocardial remodeling. Our study identifies CTHRC1 as a novel regulator of the healing scar process and a target for future translational studies.

Upstream analysis of alternative splicing: a review of computational approaches to predict context-dependent splicing factors.

Alternative splicing (AS) has shown to play a pivotal role in the development of diseases, including cancer. Specifically, all the hallmarks of cancer (angiogenesis, cell immortality, avoiding immune system response, etc.) are found to have a counterpart in aberrant splicing of key genes. Identifying the context-specific regulators of splicing provides valuable information to find new biomarkers, as well as to define alternative therapeutic strategies. The computational models to identify these regulators are not trivial and require three conceptual steps: the detection of AS events, the identification of splicing factors that potentially regulate these events and the contextualization of these pieces of information for a specific experiment. In this work, we review the different algorithmic methodologies developed for each of these tasks. Main weaknesses and strengths of the different steps of the pipeline are discussed. Finally, a case study is detailed to help the reader be aware of the potential and limitations of this computational approach.

Graph theory analysis of resting-state functional magnetic resonance imaging in essential tremor.

Essential tremor (ET) is a neurological disease with both motor and nonmotor manifestations; however, little is known about its underlying brain basis. Furthermore, the overall organization of the brain network in ET remains largely unexplored. We investigated the topological properties of brain functional network, derived from resting-state functional magnetic resonance imaging (MRI) data, in 23 ET patients versus 23 healthy controls. Graph theory analysis was used to assess the functional network organization. At the global level, the functional network of ET patients was characterized by lower small-worldness values than healthy controls-less clustered functionality of the brain. At the regional level, compared with the healthy controls, ET patients showed significantly higher values of global efficiency, cost and degree, and a shorter average path length in the left inferior frontal gyrus (pars opercularis), right inferior temporal gyrus (posterior division and temporo-occipital part), right inferior lateral occipital cortex, left paracingulate, bilateral precuneus bilaterally, left lingual gyrus, right hippocampus, left amygdala, nucleus accumbens bilaterally, and left middle temporal gyrus (posterior part). In addition, ET patients showed significant higher local efficiency and clustering coefficient values in frontal medial cortex bilaterally, subcallosal cortex, posterior cingulate cortex, parahippocampal gyri bilaterally (posterior division), right lingual gyrus, right cerebellar flocculus, right postcentral gyrus, right inferior semilunar lobule of cerebellum and culmen of vermis. Finally, the right intracalcarine cortex and the left orbitofrontal cortex showed a shorter average path length in ET patients, while the left frontal operculum and the right planum polare showed a higher betweenness centrality in ET patients. In conclusion, the efficiency of the overall brain functional network in ET is disrupted. Further, our results support the concept that ET is a disorder that disrupts widespread brain regions, including those outside of the brain regions responsible for tremor.

Comparison of RNA-seq and microarray platforms for splice event detection using a cross-platform algorithm.

BACKGROUND: RNA-seq is a reference technology for determining alternative splicing at genome-wide level. Exon arrays remain widely used for the analysis of gene expression, but show poor validation rate with regard to splicing events. Commercial arrays that include probes within exon junctions have been developed in order to overcome this problem. We compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of transcript splicing events. Three different breast cancer cell lines were treated with CX-4945, a drug that severely affects splicing. To enable a direct comparison of the two platforms, we adapted EventPointer, an algorithm that detects and labels alternative splicing events using junction arrays, to work also on RNA-seq data. Common results and discrepancies between the technologies were validated and/or resolved by over 200 PCR experiments. RESULTS: As might be expected, RNA-seq appears superior in cases where the technologies disagree and is able to discover novel splicing events beyond the limitations of physical probe-sets. We observe a high degree of coherence between the two technologies, however, with correlation of EventPointer results over 0.90. Through decimation, the detection power of the junction arrays is equivalent to RNA-seq with up to 60 million reads. CONCLUSIONS: Our results suggest, therefore, that exon-junction arrays are a viable alternative to RNA-seq for detection of alternative splicing events when focusing on well-described transcriptional regions.

Tremor severity in Parkinson's disease and cortical changes of areas controlling movement sequencing: A preliminary study.

There remains much to learn about the changes in cortical anatomy that are associated with tremor severity in Parkinson's disease (PD). For this reason, we used a combination of structural neuroimaging to measure cortical thickness and neurophysiological studies to analyze whether PD tremor was associated with cortex integrity. Magnetic resonance imaging and neurophysiological assessment were performed in 13 nondemented PD patients (9 women, 69.2%) with a clearly tremor-dominant phenotype. Cortical reconstruction and volumetric segmentation were performed with the Freesurfer image analysis software. Assessment of tremor was performed by means of high-density surface electromyography (hdEMG) and inertial measurement units (IMUs). Individual motor unit discharge patterns were identified from surface hdEMG and tremor metrics quantifying motor unit synchronization from IMUs. Increased motor unit synchronization (i.e., more severe tremor) was associated with cortical changes (i.e., atrophy) in wide-spread cortical areas, including caudal middle frontal regions bilaterally (dorsal premotor cortices), left inferior parietal lobe (posterior parietal cortex), left lateral orbitofrontal cortex, cingulate cortex bilaterally, left posterior and transverse temporal cortex, and left occipital lobe, as well as reduced left middle temporal volume. Given that the majority of these areas are involved in controlling movement sequencing, our results support Albert's classic hypothesis that PD tremor may be the result of an involuntary activation of a program of motor behavior used in the genesis of rapid voluntary alternating movements.

The phase difference between neural drives to antagonist muscles in essential tremor is associated with the relative strength of supraspinal and afferent input.

The pathophysiology of essential tremor (ET), the most common movement disorder, is not fully understood. We investigated which factors determine the variability in the phase difference between neural drives to antagonist muscles, a long-standing observation yet unexplained. We used a computational model to simulate the effects of different levels of voluntary and tremulous synaptic input to antagonistic motoneuron pools on the tremor. We compared these simulations to data from 11 human ET patients. In both analyses, the neural drive to muscle was represented as the pooled spike trains of several motor units, which provides an accurate representation of the common synaptic input to motoneurons. The simulations showed that, for each voluntary input level, the phase difference between neural drives to antagonist muscles is determined by the relative strength of the supraspinal tremor input to the motoneuron pools. In addition, when the supraspinal tremor input to one muscle was weak or absent, Ia afferents provided significant common tremor input due to passive stretch. The simulations predicted that without a voluntary drive (rest tremor) the neural drives would be more likely in phase, while a concurrent voluntary input (postural tremor) would lead more frequently to an out-of-phase pattern. The experimental results matched these predictions, showing a significant change in phase difference between postural and rest tremor. They also indicated that the common tremor input is always shared by the antagonistic motoneuron pools, in agreement with the simulations. Our results highlight that the interplay between supraspinal input and spinal afferents is relevant for tremor generation.

EventPointer: an effective identification of alternative splicing events using junction arrays.

BACKGROUND: Alternative splicing (AS) is a major source of variability in the transcriptome of eukaryotes. There is an increasing interest in its role in different pathologies. Before sequencing technology appeared, AS was measured with specific arrays. However, these arrays did not perform well in the detection of AS events and provided very large false discovery rates (FDR). Recently the Human Transcriptome Array 2.0 (HTA 2.0) has been deployed. It includes junction probes. However, the interpretation software provided by its vendor (TAC 3.0) does not fully exploit its potential (does not study jointly the exons and junctions involved in a splicing event) and can only be applied to case-control studies. New statistical algorithms and software must be developed in order to exploit the HTA 2.0 array for event detection. RESULTS: We have developed EventPointer, an R package (built under the aroma.affymetrix framework) to search and analyze Alternative Splicing events using HTA 2.0 arrays. This software uses a linear model that broadens its application from plain case-control studies to complex experimental designs. Given the CEL files and the design and contrast matrices, the software retrieves a list of all the detected events indicating: 1) the type of event (exon cassette, alternative 3', etc.), 2) its fold change and its statistical significance, and 3) the potential protein domains affected by the AS events and the statistical significance of the possible enrichment. Our tests have shown that EventPointer has an extremely low FDR value (only 1 false positive within the tested top-200 events). This software is publicly available and it has been uploaded to GitHub. CONCLUSIONS: This software empowers the HTA 2.0 arrays for AS event detection as an alternative to RNA-seq: simplifying considerably the required analysis, speeding it up and reducing the required computational power.

Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single-cell resolution.

Early hematopoiesis is a continuous process in which hematopoietic stem and progenitor cells (HSPCs) gradually differentiate toward specific lineages. Aging and myeloid malignant transformation are characterized by changes in the composition and regulation of HSPCs. In this study, we used single-cell RNA sequencing (scRNA-seq) to characterize an enriched population of human HSPCs obtained from young and elderly healthy individuals.Based on their transcriptional profile, we identified changes in the proportions of progenitor compartments during aging, and differences in their functionality, as evidenced by gene set enrichment analysis. Trajectory inference revealed that altered gene expression dynamics accompanied cell differentiation, which could explain aging-associated changes in hematopoiesis. Next, we focused on key regulators of transcription by constructing gene regulatory networks (GRNs) and detected regulons that were specifically active in elderly individuals. Using previous findings in healthy cells as a reference, we analyzed scRNA-seq data obtained from patients with myelodysplastic syndrome (MDS) and detected specific alterations of the expression dynamics of genes involved in erythroid differentiation in all patients with MDS such as TRIB2. In addition, the comparison between transcriptional programs and GRNs regulating normal HSPCs and MDS HSPCs allowed identification of regulons that were specifically active in MDS cases such as SMAD1, HOXA6, POU2F2, and RUNX1 suggesting a role of these transcription factors (TFs) in the pathogenesis of the disease.In summary, we demonstrate that the combination of single-cell technologies with computational analysis tools enable the study of a variety of cellular mechanisms involved in complex biological systems such as early hematopoiesis and can be used to dissect perturbed differentiation trajectories associated with perturbations such as aging and malignant transformation. Furthermore, the identification of abnormal regulatory mechanisms associated with myeloid malignancies could be exploited for personalized therapeutic approaches in individual patients.

Our blood contains many different types of cells; red blood cells carry oxygen through the body, platelets help to stop bleeding and a variety of white blood cells fight infections. All of these critical components come from a pool of immature cells in bone marrow, which can develop and specialise into any of these. However, as we get older, these immature cells can accumulate damage, including mutations in specific genes. This increases the risk of diseases such as myelodysplastic syndromes (MDS), a type of cancer in which the cells cannot develop and the patient does not have enough healthy mature blood cells. The changes in gene activity in the immature cells have previously been studied using samples from young and elderly people, as well as individuals with MDS. These studies examined large numbers of cells together, revealing differences between young and elderly people, and individuals with MDS. However, this does not describe how the different types alter their behaviour. To address this, Ainciburu, Ezponda et al. used a technique called single-cell RNA sequencing to study the gene activity in individual immature blood cells. This revealed changes associated with maturation that may account for the different combinations of cell populations in younger and older people. The results confirmed findings from previous studies and suggested new genes involved in ageing or MDS. Ainciburu, Ezponda et al. used these results to create an analytical system that highlights gene activity differences in individual MDS patients that are independent of age-related changes. These results provide new insights that could help further research into the development of MDS and the ageing process. In addition, scientists could study other diseases using this approach of analysing individual patients' gene activity. In future, this could help to personalise clinical decisions on diagnosis and treatment.

TCR-induced FOXP3 expression by CD8+ T cells impairs their anti-tumor activity.

Adoptive cell transfer therapy using CD8+ T lymphocytes showed promising results eradicating metastatic malignancies. However, several regulatory mechanisms limit its efficacy. We studied the role of the expression of the transcription factor FOXP3 on CD8+ T cell function and anti-tumor immunity. Here we show that suboptimal T cell receptor stimulation of CD8+ T cells upregulates FOXP3 in vitro. Similarly, CD8 T cells transferred into tumor-bearing mice upregulate FOXP3 in vivo. Cell-intrinsic loss of FOXP3 by CD8+ T cells resulted in improved functionality after TCR stimulation and better antitumor responses in vivo. Inhibition of the FOXP3/NFAT interaction likewise improved CD8+ T cell functionality. Transcriptomic analysis of cells after TCR stimulation revealed an enrichment of genes implicated in the response to IFN-γ, IFN-α, inflammatory response, IL-6/JAK/STAT, G2M checkpoint and IL-2/STAT signaling in FOXP3-deficient CD8+ T cells with respect to FOXP3-wt CD8+ T cells. Our results suggest that transient expression of FOXP3 by CD8+ T cells in the tumor microenvironment restrains their anti-tumor activity, with clear implications for improving T cell responses during immunotherapy.

Deconvolution of the hematopoietic stem cell microenvironment reveals a high degree of specialization and conservation.

Understanding the regulation of normal and malignant human hematopoiesis requires comprehensive cell atlas of the hematopoietic stem cell (HSC) regulatory microenvironment. Here, we develop a tailored bioinformatic pipeline to integrate public and proprietary single-cell RNA sequencing (scRNA-seq) datasets. As a result, we robustly identify for the first time 14 intermediate cell states and 11 stages of differentiation in the endothelial and mesenchymal BM compartments, respectively. Our data provide the most comprehensive description to date of the murine HSC-regulatory microenvironment and suggest a higher level of specialization of the cellular circuits than previously anticipated. Furthermore, this deep characterization allows inferring conserved features in human, suggesting that the layers of microenvironmental regulation of hematopoiesis may also be shared between species. Our resource and methodology is a stepping-stone toward a comprehensive cell atlas of the BM microenvironment.

The bone marrow niche regulates redox and energy balance in MLL::AF9 leukemia stem cells.

Eradicating leukemia requires a deep understanding of the interaction between leukemic cells and their protective microenvironment. The CXCL12/CXCR4 axis has been postulated as a critical pathway dictating leukemia stem cell (LSC) chemoresistance in AML due to its role in controlling cellular egress from the marrow. Nevertheless, the cellular source of CXCL12 in the acute myeloid leukemia (AML) microenvironment and the mechanism by which CXCL12 exerts its protective role in vivo remain unresolved. Here, we show that CXCL12 produced by Prx1+ mesenchymal cells but not by mature osteolineage cells provide the necessary cues for the maintenance of LSCs in the marrow of an MLL::AF9-induced AML model. Prx1+ cells promote survival of LSCs by modulating energy metabolism and the REDOX balance in LSCs. Deletion of Cxcl12 leads to the accumulation of reactive oxygen species and DNA damage in LSCs, impairing their ability to perpetuate leukemia in transplantation experiments, a defect that can be attenuated by antioxidant therapy. Importantly, our data suggest that this phenomenon appears to be conserved in human patients. Hence, we have identified Prx1+ mesenchymal cells as an integral part of the complex niche-AML metabolic intertwining, pointing towards CXCL12/CXCR4 as a target to eradicate parenchymal LSCs in AML.

The transcription factor DDIT3 is a potential driver of dyserythropoiesis in myelodysplastic syndromes.

Myelodysplastic syndromes (MDS) are hematopoietic stem cell (HSC) malignancies characterized by ineffective hematopoiesis, with increased incidence in older individuals. Here we analyze the transcriptome of human HSCs purified from young and older healthy adults, as well as MDS patients, identifying transcriptional alterations following different patterns of expression. While aging-associated lesions seem to predispose HSCs to myeloid transformation, disease-specific alterations may trigger MDS development. Among MDS-specific lesions, we detect the upregulation of the transcription factor DNA Damage Inducible Transcript 3 (DDIT3). Overexpression of DDIT3 in human healthy HSCs induces an MDS-like transcriptional state, and dyserythropoiesis, an effect associated with a failure in the activation of transcriptional programs required for normal erythroid differentiation. Moreover, DDIT3 knockdown in CD34+ cells from MDS patients with anemia is able to restore erythropoiesis. These results identify DDIT3 as a driver of dyserythropoiesis, and a potential therapeutic target to restore the inefficient erythroid differentiation characterizing MDS patients.

The Nuclear Receptor ESRRA Protects from Kidney Disease by Coupling Metabolism and Differentiation.

Kidney disease is poorly understood because of the organ's cellular diversity. We used single-cell RNA sequencing not only in resolving differences in injured kidney tissue cellular composition but also in cell-type-specific gene expression in mouse models of kidney disease. This analysis highlighted major changes in cellular diversity in kidney disease, which markedly impacted whole-kidney transcriptomics outputs. Cell-type-specific differential expression analysis identified proximal tubule (PT) cells as the key vulnerable cell type. Through unbiased cell trajectory analyses, we show that PT cell differentiation is altered in kidney disease. Metabolism (fatty acid oxidation and oxidative phosphorylation) in PT cells showed the strongest and most reproducible association with PT cell differentiation and disease. Coupling of cell differentiation and the metabolism was established by nuclear receptors (estrogen-related receptor alpha [ESRRA] and peroxisomal proliferation-activated receptor alpha [PPARA]) that directly control metabolic and PT-cell-specific gene expression in mice and patient samples while protecting from kidney disease in the mouse model.

Cannabinoid CB2 receptor agonists protect the striatum against malonate toxicity: relevance for Huntington's disease.

Cannabinoid agonists might serve as neuroprotective agents in neurodegenerative disorders. Here, we examined this hypothesis in a rat model of Huntington's disease (HD) generated by intrastriatal injection of the mitochondrial complex II inhibitor malonate. Our results showed that only compounds able to activate CB2 receptors were capable of protecting striatal projection neurons from malonate-induced death. That CB2 receptor agonists are neuroprotective was confirmed by using the selective CB2 receptor antagonist, SR144528, and by the observation that mice deficient in CB2 receptor were more sensitive to malonate than wild-type animals. CB2 receptors are scarce in the striatum in healthy conditions, but they are markedly upregulated after the lesion with malonate. Studies of double immunostaining revealed a significant presence of CB2 receptors in cells labeled with the marker of reactive microglia OX-42, and also in cells labeled with GFAP (a marker of astrocytes). We further showed that the activation of CB2 receptors significantly reduced the levels of tumor necrosis factor-alpha (TNF-alpha) that had been increased by the lesion with malonate. In summary, our results demonstrate that stimulation of CB2 receptors protect the striatum against malonate toxicity, likely through a mechanism involving glial cells, in particular reactive microglial cells in which CB2 receptors would be upregulated in response to the lesion. Activation of these receptors would reduce the generation of proinflammatory molecules like TNF-alpha. Altogether, our results support the hypothesis that CB2 receptors could constitute a therapeutic target to slowdown neurodegeneration in HD.

A data mining approach for classification of orthostatic and essential tremor based on MRI-derived brain volume and cortical thickness.

OBJECTIVE: Orthostatic tremor (OT) is an extremely rare, misdiagnosed, and underdiagnosed disorder affecting adults in midlife. There is debate as to whether it is a different condition or a variant of essential tremor (ET), or even, if both conditions coexist. Our objective was to use data mining classification methods, using magnetic resonance imaging (MRI)-derived brain volume and cortical thickness data, to identify morphometric measures that help to discriminate OT patients from those with ET. METHODS: MRI-derived brain volume and cortical thickness were obtained from 14 OT patients and 15 age-, sex-, and education-matched ET patients. Feature selection and machine learning methods were subsequently applied. RESULTS: Four MRI features alone distinguished the two, OT from ET, with 100% diagnostic accuracy. More specifically, left thalamus proper volume (normalized by the total intracranial volume), right superior parietal volume, right superior parietal thickness, and right inferior parietal roughness (i.e., the standard deviation of cortical thickness) were shown to play a key role in OT and ET characterization. Finally, the left caudal anterior cingulate thickness and the left caudal middle frontal roughness allowed us to separate with 100% diagnostic accuracy subgroups of OT patients (primary and those with mild parkinsonian signs). CONCLUSIONS: A data mining approach applied to MRI-derived brain volume and cortical thickness data may differentiate between these two types of tremor with an accuracy of 100%. Our results suggest that OT and ET are distinct conditions.

Diffusion tensor imaging in orthostatic tremor: a tract-based spatial statistics study.

OBJECTIVE: The pathogenesis of orthostatic tremor (OT) is unknown. We investigated OT-related white matter changes and their correlations with scores from a neuropsychological testing battery. METHODS: Diffusion tensor imaging measures were compared between 14 OT patients and 14 age- and education-matched healthy controls, using whole-brain tract-based spatial statistics analysis. Correlations between altered diffusion metrics and cognitive performance in OT group were assessed. RESULTS: In all cognitive domains (attention, executive function, visuospatial ability, verbal memory, visual memory, and language), OT patients' cognitive performance was significantly worse than that of healthy controls. OT patients demonstrated altered diffusivity metrics not only in the posterior lobe of the cerebellum (left cerebellar lobule VI) and in its efferent cerebellar fibers (left superior cerebellar peduncle), but also in medial lemniscus bilaterally (pontine tegmentum), anterior limb of the internal capsule bilaterally, right posterior limb of the internal capsule, left anterior corona radiata, right insula, and the splenium of corpus callosum. No relationship was found between diffusion measures and disease duration in OT patients. Diffusion white matter changes, mainly those located in right anterior limb of the internal capsule, were correlated with poor performance on tests of executive function, visuospatial ability, verbal memory, and visual memory in OT patients. INTERPRETATION: White matter changes were preferentially located in the cerebellum, its efferent pathways, as well as in the pontine tegmentum and key components of the frontal-thalamic-cerebellar circuit. Further work needs to be done to understand the evolution of these white matter changes and their functional consequences.

Essential tremor severity and anatomical changes in brain areas controlling movement sequencing.

Objective: Although the cerebello-thalamo-cortical network has often been suggested to be of importance in the pathogenesis of essential tremor (ET), the origins of tremorgenic activity in this disease are not fully understood. We used a combination of cortical thickness imaging and neurophysiological studies to analyze whether the severity of tremor was associated with anatomical changes in the brain in ET patients. Methods: Magnetic resonance imaging (MRI) and a neurophysiological assessment were performed in 13 nondemented ET patients. High field structural brain MRI images acquired in a 3T scanner and analyses of cortical thickness and surface were carried out. Cortical reconstruction and volumetric segmentation was performed with the FreeSurfer image analysis software. We used high-density surface electromyography (hdEMG) and inertial measurement units (IMUs) to quantify the tremor severity in upper extrimities of patients. In particular, advanced computer tool was used to reliably identify discharge patterns of individual motor units from surface hdEMG and quantify motor unit synchronization. Results: We found significant association between increased motor unit synchronization (i.e., more severe tremor) and cortical changes (i.e., atrophy) in widespread cerebral cortical areas, including the left medial orbitofrontal cortex, left isthmus of the cingulate gyrus, right paracentral lobule, right lingual gyrus, as well as reduced left supramarginal gyrus (inferior parietal cortex), right isthmus of the cingulate gyrus, left thalamus, and left amygdala volumes. Interpretation: Given that most of these brain areas are involved in controlling movement sequencing, ET tremor could be the result of an involuntary activation of a program of motor behavior used in the genesis of voluntary repetitive movements.

Motor Unit-Driven Identification of Pathological Tremor in Electroencephalograms.

Background: Traditional studies on the neural mechanisms of tremor use coherence analysis to investigate the relationship between cortical and muscle activity, measured by electroencephalograms (EEG) and electromyograms (EMG). This methodology is limited by the need of relatively long signal recordings, and it is sensitive to EEG artifacts. Here, we analytically derive and experimentally validate a new method for automatic extraction of the tremor-related EEG component in pathological tremor patients that aims to overcome these limitations. Methods: We exploit the coupling between the tremor-related cortical activity and motor unit population firings to build a linear minimum mean square error estimator of the tremor component in EEG. We estimated the motor unit population activity by decomposing surface EMG signals into constituent motor unit spike trains, which we summed up into a cumulative spike train (CST). We used this CST to initialize our tremor-related EEG component estimate, which we optimized using a novel approach proposed here. Results: Tests on simulated signals demonstrate that our new method is robust to both noise and motor unit firing variability, and that it performs well across a wide range of spectral characteristics of the tremor. Results on 9 essential (ET) and 9 Parkinson's disease (PD) patients show a ~2-fold increase in amplitude of the coherence between the estimated EEG component and the CST, compared to the classical EEG-EMG coherence analysis. Conclusions: We have developed a novel method that allows for more precise and robust estimation of the tremor-related EEG component. This method does not require artifact removal, provides reliable results in relatively short datasets, and tracks changes in the tremor-related cortical activity over time.

A data mining approach using cortical thickness for diagnosis and characterization of essential tremor.

Essential tremor (ET) is one of the most prevalent movement disorders. Being that it is a common disorder, its diagnosis is considered routine. However, misdiagnoses may occur regularly. Over the past decade, several studies have identified brain morphometric changes in ET, but these changes remain poorly understood. Here, we tested the informativeness of measuring cortical thickness for the purposes of ET diagnosis, applying feature selection and machine learning methods to a study sample of 18 patients with ET and 18 age- and sex-matched healthy control subjects. We found that cortical thickness features alone distinguished the two, ET from controls, with 81% diagnostic accuracy. More specifically, roughness (i.e., the standard deviation of cortical thickness) of the right inferior parietal and right fusiform areas was shown to play a key role in ET characterization. Moreover, these features allowed us to identify subgroups of ET patients as well as healthy subjects at risk for ET. Since treatment of tremors is disease specific, accurate and early diagnosis plays an important role in tremor management. Supporting the clinical diagnosis with novel computer approaches based on the objective evaluation of neuroimage data, like the one presented here, may represent a significant step in this direction.