Childhood obesity is constantly increasing around the world, and it has become a major public health issue. Considerable evidence indicates that overweight and obesity are important risk factors for the development of comorbidities such as cognitive decline, neuroinflammation and neurodegenerative diseases. It is known that during obesity, adipose tissue undergoes immune, metabolic and functional changes which could induce a neuroinflammatory response of the central nervous system (CNS). In this context, to inspect if obesity can start to trigger the neuroinflammation from a pediatric age, we surgically collected and analyzed adipose tissue from the periumbilical area of three obese children (AT-OB) and two normal-weight children (AT-Ctrl). We considered the transcriptomic profile of our samples to detect alterations in different biological processes that might be also involved in the inflammatory and neuroinflammatory response. Our results show alterations of lipid and fatty acids metabolism in AT-OB compared to the AT-Ctrl. We also observed an onset of inflammatory response in AT-OB. Interestingly, among the genes involved in neuroinflammation, GRN and SMO were upregulated, while IFNGR1 and SNCA were downregulated. Our study highlights that obesity may trigger inflammation and neuroinflammation from a pediatric age.

Alzheimer’s disease (AD) is an incurable neurodegenerative disease diagnosed by clinicians through healthcare records and neuroimaging techniques. These methods lack sensitivity and specificity, so new antemortem non-invasive strategies to diagnose AD are needed. Herein, we designed a machine learning predictor based on transcriptomic data obtained from the blood of AD patients and individuals without dementia (non-AD) through an 8 × 60 K microarray. The dataset was used to train different models with different hyperparameters. The support vector machines method allowed us to reach a Receiver Operating Characteristic score of 93% and an accuracy of 89%. High score levels were also achieved by the neural network and logistic regression methods. Furthermore, the Gene Ontology enrichment analysis of the features selected to train the model along with the genes differentially expressed between the non-AD and AD transcriptomic profiles shows the “mitochondrial translation” biological process to be the most interesting. In addition, inspection of the KEGG pathways suggests that the accumulation of β-amyloid triggers electron transport chain impairment, enhancement of reactive oxygen species and endoplasmic reticulum stress. Taken together, all these elements suggest that the oxidative stress induced by β-amyloid is a key feature trained by the model for the prediction of AD with high accuracy.

Multiple Sclerosis (MS) is, to date, an incurable disease of the nervous system characterized by demyelination. Several genetic mutations are associated with the disease but they are not able to explain all the diagnosticated cases. Thus, it is suggested that altered gene expression may play a role in human pathologies. In this review, we explored the role of the transcriptomic profile in MS to investigate the main altered biological processes and pathways involved in the disease. Herein, we focused our attention on RNA-seq methods that in recent years are producing a huge amount of data rapidly replacing microarrays, both with bulk and single-cells. The studies evidenced that different MS stages have specific molecular signatures and non-coding RNAs may play a key role in the disease. Sex-dependence was observed before and after treatments used to alleviate symptomatology activating different biological processes in a drug-dependent manner. New pathways, such as neddylation, were found deregulated in MS and inflammation was linked to neuron degeneration areas through spatial transcriptomics. It is evident that the use of RNA-seq in the study of complex pathologies, such as MS, is a valid strategy to shed light on new involved mechanisms.

Phytocannabinoids, with their variety of beneficial effects, represent a valid group of substances that could be employed as neurogenesis-enhancers or neuronal differentiation inducers. We focused our attention on the neuronal-related potential of cannabichromene (CBC) when administered to undifferentiated NSC-34 for 24 h. Transcriptomic analysis showed an upregulation of several neuronal markers, such as Neurod1 and Tubb3, as well as indicators of neuronal differentiation process progression, such as Pax6. An in-depth investigation of the processes involved in neuronal differentiation indicates positive cytoskeleton remodeling by upregulation of Cfl2 and Tubg1, and active differentiation-targeted transcriptional program, suggested by Phox2b and Hes1. After 48 h of treatment, the markers previously examined in the transcriptomic analysis are still overexpressed, like Ache and Hes1, indicating that the differentiation process is still in progress. The lack of GFAP protein suggests that no astroglial differentiation is taking place, and it is reasonable to indicate the neuronal one as the ongoing one. These results indicate CBC as a potential neuronal differentiation inducer for NSC-34 cells.

Background and objectives: Alzheimer’s disease (AD) is the most common form of dementia characterized by memory loss and executive dysfunction. To date, no markers can effectively predict the onset of AD and an early diagnosis is increasingly necessary. Age represents an important risk factor for the disease but it is not known whether it is the trigger event. Materials and Methods: We downloaded transcriptomic data related to post-mortem brain of thirty samples gathered as young without AD (Young), old without AD (Old), and old suffering from AD (OAD) groups. Results: Our results showed that steroid biosynthesis was enriched and associated with aging, while sphingolipid metabolism was related to both aging and AD. Specifically, sphingolipid metabolism is involved in the deregulation of CERS2, UGT8, and PLPP2. These genes are downregulated in Young and Old groups as compared with upregulated between Old and OAD groups. Moreover, the analysis of the interaction networks revealed that GABAergic synapse and Hippo signaling pathways were altered in AD condition along with mitochondrial metabolism and RNA processing. Conclusions: Observing the particular trend of genes related to sphingolipid metabolism that are downregulated during normal aging and start to be upregulated with the onset of AD, we suppose that sphingolipids could be early markers for the disease.