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Background: Deregulation of transcription in the pathogenesis of sporadic Amyotrophic Lateral Sclerosis (sALS) is taking central stage with RNA-sequencing analyses from sALS patients tissues highlighting numerous deregulated long non-coding RNAs (lncRNAs). The oncogenic lncRNA ZEB1-AS1 is strongly downregulated in peripheral blood mononuclear cells of sALS patients. In addition, in cancer-derived cell lines, ZEB1-AS1 belongs to a negative feedback loop regulation with hsa-miR-200c, acting as a molecular sponge for this miRNA. The role of the lncRNA ZEB1-AS1 in sALS pathogenesis has not been characterized yet, and its study could help identifying a possible disease-modifying target. Methods: the implication of the ZEB1-AS1/ZEB1/hsa-miR-200c/BMI1 pathway was investigated in multiple patients-derived cellular models (patients-derived peripheral blood mononuclear cells and induced pluripotent stem cells-derived neural stem cells) and in the neuroblastoma cell line SH-SY5Y, where its function was inhibited via RNA interference. Molecular techniques such as Real Time PCR, Western Blot and Immunofluorescence were used to assess the pathway dysregulation. Results: Our results show a dysregulation of a signaling pathway involving ZEB1-AS1/hsa-miR-200c/β-Catenin in peripheral blood mononuclear cells and in induced pluripotent stem cells-derived neural stem cells from sALS patients. These results were validated in vitro on the cell line SH-SY5Y with silenced expression of ZEB1-AS1. Moreover, we found an increase for ZEB1-AS1 during neural differentiation with an aberrant expression of β-Catenin, highlighting also its aggregation and possible impact on neurite length. Conclusions: Our results support and describe the role of ZEB1-AS1 pathway in sALS and specifically in neuronal differentiation, suggesting that an impairment of β-Catenin signaling and an alteration of the neuronal phenotype are taking place.

In this data article, we present the dataset from the RNA-Seq analysis of subcutaneous adipose tissue collected from 5 healthy normal weight women (NW, age 37 ± 6.7 years, BMI 24.3 ± 0.9 kg/m2) and 5 obese women (OBF, age 41 ± 12.5 years, BMI 38.2 ± 4.6 kg/m2). Raw data obtained from Illumina NextSeq 500 sequencer were processed through BlueBee® Genomics Platform while differential expression analysis was performed with the DESeq2 R package and deposited in the GEO public repository with GSE166047 as accession number. Specifically, 20 samples divided between NW (control), OBF (obese women), OBM (obese male) and OBT2D (obese women with diabetes) are deposited in the GSE166047. We hereby describe only 10 samples (5 healthy normal weight women reported as NW and 5 obese women reported as OBF) because we refer to the data published in the article “Transcriptional characterization of Subcutaneous Adipose Tissue in obesity affected women highlights metabolic dysfunction and implications for lncRNAs” (DOI: 10.1016/j.ygeno.2021.09.014). Pathways analyses were performed on g:Profiler, Enrichr, ClueGO and GSEA to gain biological insights on gene expression. Raw data reported in GEO database along with detailed methods description reported in this data article could be reused for comparisons with other datasets on the topic to obtain transcriptional differences in a wider co-hort. Moreover, detailed pathways analysis along with cross-referenced data with other datasets will allow to identify novel dysregulated pathways and genes responsible for this regulation. The biological interpretation of this dataset, along with related in vitro experiments, is reported by Rey et al., in Genomics (DOI: 10.1016/j.ygeno.2021.09.014).

Since the association of SARS-Cov-2 infection with Nervous System (NS) manifestations, we performed RNA-sequencing analysis in Frontal Cortex of COVID-19 positive or negative individuals and affected or not by Dementia individuals. We examined gene expression differences in individuals with COVID-19 and Dementia compared to Dementia only patients by collecting transcript counts in each sample and performing Differential Expression analysis. We found eleven genes satisfying our significance criteria, all of them being protein coding genes.These data are suitable for integration with supplemental samples and for analysis according to different individuals’ classification. Also, differential expression evaluation may be implemented with other scientific purposes, such as research of unannotated genes, mRNA splicing and genes isoforms.The analysis of Differential Expressed genes in COVID-19 positive patients compared to non-COVID-19 patients is published in: S. Gagliardi, E.T. Poloni, C. Pandini, M. Garofalo, F. Dragoni, V. Medici, A. Davin, S.D. Visonà, M. Moretti, D. Sproviero, O. Pansarasa, A. Guaita, M. Ceroni, L. Tronconi, C. Cereda, Detection of SARS-CoV-2 genome and whole transcriptome sequencing in frontal cortex of COVID-19 patients., Brain. Behav. Immun. (2021). https://doi.org/10.1016/j.bbi.2021.05.012.