Transcriptional analysis reveals distinct subtypes in amyotrophic lateral sclerosis: implications for personalized therapy

Amyotrophic lateral sclerosis (ALS) is an incurable disease, caused by the loss of the upper and lower motor neurons. The lack of therapeutic progress is mainly due to the insufficient understanding of complexity and heterogeneity underlying the pathogenic mechanisms of ALS. Recently, we analyzed whole-genome expression profiles of motor cortex of sporadic ALS patients, classifying them into two subgroups characterized by differentially expressed genes and pathways. Some of the deregulated genes encode proteins, which are primary targets of drugs currently in preclinical or clinical studies for several clinical conditions, including neurodegenerative diseases. In this review, we discuss in-depth the potential role of these candidate targets in ALS pathogenesis, highlighting their possible relevance for personalized ALS treatments

Orexin-A represses satiety-inducing POMC neurons and contributes to obesity via stimulation of endocannabinoid signaling

In the hypothalamic arcuate nucleus (ARC), proopiomelanocortin (POMC) neurons and the POMC-derived peptide α–melanocytestimulating hormone (α-MSH) promote satiety. POMC neurons receive orexin-A (OX-A)-expressing inputs and express both OX-A receptor type 1 (OX-1R) and cannabinoid receptor type 1 (CB1R) on the plasma membrane. OX-A is crucial for the control of wakefulness and energy homeostasis and promotes, in OX-1R–expressing cells, the biosynthesis of the endogenous counterpart of marijuana’s psychotropic and appetite-inducing component Δ9-tetrahydrocannabinol, i.e., the endocannabinoid 2-arachidonoylglycerol (2-AG), which acts at CB1R. We report that OX-A/OX-1R signaling at POMC neurons promotes 2-AG biosynthesis, hyperphagia, and weight gain by blunting α-MSH production via CB1R-induced and extracellularsignal- regulated kinase 1/2 activation- and STAT3 inhibitionmediated suppression of Pomc gene transcription. Because the systemic pharmacological blockade of OX-1R by SB334867 caused anorectic effects by reducing food intake and body weight, our results unravel a previously unsuspected role for OX-A in endocannabinoid-mediated promotion of appetite by combining OX-induced alertness with food seeking. Notably, increased OX-A trafficking was found in the fibers projecting to the ARC of obese mice (ob/ob and high-fat diet fed) concurrently with elevation of OX-A release in the cerebrospinal fluid and blood ofmice. Furthermore, a negative correlation between OX-A and α-MSH serum levels was found in obese mice as well as in human obese subjects (body mass index > 40), in combination with elevation of alanine aminotransferase and γ-glutamyl transferase, two markers of fatty liver disease. These alterations were counteracted by antagonism of OX-1R, thus providing the basis for a therapeutic treatment of these diseasesPeer Reviewe

A new look at Spitzer primary transit observations of the exoplanet HD189733b

Blind source separation techniques are used to reanalyse two exoplanetary transit lightcurves of the exoplanet HD189733b recorded with the IR camera IRAC on board the Spitzer Space Telescope at 3.6$\mu$m during the "cold" era. These observations, together with observations at other IR wavelengths, are crucial to characterise the atmosphere of the planet HD189733b. Previous analyses of the same datasets reported discrepant results, hence the necessity of the reanalyses. The method we used here is based on the Independent Component Analysis (ICA) statistical technique, which ensures a high degree of objectivity. The use of ICA to detrend single photometric observations in a self-consistent way is novel in the literature. The advantage of our reanalyses over previous work is that we do not have to make any assumptions on the structure of the unknown instrumental systematics. Such "admission of ignorance" may result in larger error bars than reported in the literature, up to a factor $1.6$. This is a worthwhile trade-off for much higher objectivity, necessary for trustworthy claims. Our main results are (1) improved and robust values of orbital and stellar parameters, (2) new measurements of the transit depths at 3.6$\mu$m, (3) consistency between the parameters estimated from the two observations, (4) repeatability of the measurement within the photometric level of $\sim 2 \times 10^{-4}$ in the IR, (5) no evidence of stellar variability at the same photometric level within 1 year.Comment: 43 pages, 18 figure

Molecular Taxonomy: Use of Transcriptional Profiles to Identify Different ALS Subtypes

Advances in diagnostic techniques and high-throughput biotechnologies provide a compelling opportunity to improve the diagnosis and treatment of diseases by developing a “New Taxonomy” that defines diseases on the basis of their underlying molecular and environmental factors rather than on traditional physical signs and symptoms. Oncology represents the first interesting example of how genomic medicine has changed the understanding of diseases and their therapy. However, much work remains to be completed on the molecular characterization and classification of complex and multifactorial diseases, including neurodegenerative disorders. Our research group has recently shown the genomic heterogeneity of sporadic amyotrophic lateral sclerosis (SALS), identifying two divergent subtypes associated with differentially expressed genes and pathways and providing several potential biomarkers and therapeutic targets. This chapter reviews the results emerged from our work, highlighting how molecular characterization of SALS patients may provide a framework for developing a more precise and accurate classification of diseases that could revolutionize the diagnosis, therapy, and clinical decisions of diseases, leading to more individualized treatments and improved outcomes for patients

Molecular classification of amyotrophic lateral sclerosis by unsupervised clustering of gene expression in motor cortex

AbstractAmyotrophic lateral sclerosis (ALS) is a rapidly progressive and ultimately fatal neurodegenerative disease, caused by the loss of motor neurons in the brain and spinal cord. Although 10% of ALS cases are familial (FALS), the majority are sporadic (SALS) and probably associated to a multifactorial etiology. Currently there is no cure or prevention for ALS. A prerequisite to formulating therapeutic strategies is gaining understanding of its etio-pathogenic mechanisms. In this study we analyzed whole-genome expression profiles of 41 motor cortex samples of control (10) and sporadic ALS (31) patients. Unsupervised hierarchical clustering was able to separate control from SALS patients. In addition, SALS patients were subdivided in two different groups that were associated to different deregulated pathways and genes, some of which were previously associated to familiar ALS. These experiments are the first to highlight the genomic heterogeneity of sporadic ALS and reveal new clues to its pathogenesis and potential therapeutic targets

A Diagnostic Gene-Expression Signature in Fibroblasts of Amyotrophic Lateral Sclerosis

myotrophic lateral sclerosis (ALS) is a fatal, progressive neurodegenerative disease with limited treatment options. Diagnosis can be difficult due to the heterogeneity and non-specific nature of the initial symptoms, resulting in delays that compromise prompt access to effective therapeutic strategies. Transcriptome profiling of patient-derived peripheral cells represents a valuable benchmark in overcoming such challenges, providing the opportunity to identify molecular diagnostic signatures. In this study, we characterized transcriptome changes in skin fibroblasts of sporadic ALS patients (sALS) and controls and evaluated their utility as a molecular classifier for ALS diagnosis. Our analysis identified 277 differentially expressed transcripts predominantly involved in transcriptional regulation, synaptic transmission, and the inflammatory response. A support vector machine classifier based on this 277-gene signature was developed to discriminate patients with sALS from controls, showing significant predictive power in both the discovery dataset and in six independent publicly available gene expression datasets obtained from different sALS tissue/cell samples. Taken together, our findings support the utility of transcriptional signatures in peripheral cells as valuable biomarkers for the diagnosis of ALS

Taxonomy Meets Neurology, the Case of Amyotrophic Lateral Sclerosis

Recent landmark publications from our research group outline a transformative approach to defining, studying and treating amyotrophic lateral sclerosis (ALS). Rather than approaching ALS as a single entity, we advocate targeting therapies to distinct “clusters” of patients based on their specific genomic and molecular features. Our findings point to the existence of a molecular taxonomy for ALS, bringing us a step closer to the establishment of a precision medicine approach in neurology practice

Correcting Exoplanet Transmission Spectra for Stellar Activity with an Optimised Retrieval Framework

The chromatic contamination that arises from photospheric heterogeneities e.g. spots and faculae on the host star presents a significant noise source for exoplanet transmission spectra. If this contamination is not corrected for, it can introduce substantial bias in our analysis of the planetary atmosphere. We utilise two stellar models of differing complexity, StARPA and ASteRA, to explore the biases introduced by stellar contamination in retrieval under differing degrees of stellar activity. We use the retrieval framework TauREx3 and a grid of 27 synthetic, spot-contaminated transmission spectra to investigate potential biases and to determine how complex our stellar models must be in order to accurately extract the planetary parameters from transmission spectra. The input observation is generated using the more complex model (StARPA), in which the spot latitude is an additional, fixable parameter. This observation is then fed into a combined stellar-planetary retrieval which contains a simplified stellar model (ASteRA). Our results confirm that the inclusion of stellar activity parameters in retrieval minimises bias under all activity regimes considered. ASteRA performs very well under low to moderate activity conditions, retrieving the planetary parameters with a high degree of accuracy. For the most active cases, characterised by larger, higher temperature contrast spots, some minor residual bias remains due to ASteRA neglecting the interplay between the spot and the limb darkening effect. As a result of this, we find larger errors in retrieved planetary parameters for central spots (0 degrees) and those found close to the limb (60 degrees) than those at intermediate latitudes (30 degrees).Comment: 34 pages, 20 figures, accepted for publication in Ap