Hani Sabaie

The relationship between mitochondrial DNA copy number (mtDNA-CN) and multiple sclerosis (MS) progression remains unclear, as previous observational studies have reported conflicting results. This study aimed to clarify the association between mtDNA-CN and MS progression using a bidirectional two-sample Mendelian randomization (MR) approach. MR analyses were conducted using the latest summary statistics from genome-wide association studies (GWAS) on mtDNA-CN and MS progression. Single-nucleotide polymorphisms (SNPs) associated with mtDNA-CN were extracted from 383,476 participants of European ancestry in the UK Biobank, while SNPs associated with MS severity were obtained from the International Multiple Sclerosis Genetics Consortium (IMSGC), comprising 12,584 cases of European ancestry. The inverse variance weighted (IVW) method was used as the primary analysis. Potential heterogeneity and pleiotropy were evaluated, and sensitivity analyses were performed to ensure the robustness of the results. The forward MR analysis using the IVW method revealed no significant association between mtDNA-CN and MS progression (P = 0.487). However, reverse MR analysis identified a causal association between MS progression and mtDNA-CN (β =  − 0.010, 95% CI =  − 0.019 to − 0.001, P = 0.036). No evidence of heterogeneity or horizontal pleiotropy was found in the analyses. Sensitivity analyses yielded consistent results. Our findings suggest that MS progression may causally influence mtDNA-CN, highlighting the crucial role of mitochondria in the pathophysiology of MS. However, further research is needed to confirm mtDNA-CN as a reliable biomarker and a deeper understanding of the molecular mechanisms is necessary to develop targeted therapeutic interventions.

Alzheimer’s disease (AD) is a heterogeneous degenerative brain disorder with a rising prevalence worldwide. SHISA7 (CKAMP59) has emerged as one of the most intriguing new members of the SHISA family, in that, unlike other CKAMP counterparts, it exhibits a direct function in inhibitory synaptic GABAAR regulation. We used bioinformatics and experimental methods in this research to explore competing endogenous RNA (ceRNA) regulation of BCAS4 and SHISA7 in tau pathogenesis and their capacity as peripheral biomarkers linked to an abnormal inflammatory response in AD. The Gene Expression Omnibus database included two microarray datasets, including information on mRNAs (GSE106241) and miRNAs (GSE157239) from individuals with AD with different degrees of AD-associated neurofibrillary pathology in the temporal cortex (TC) tissue specimens and corresponding controls were downloaded from the Gene Expression Omnibus database. The limma package in the R software was used to identify differently expressed mRNAs (DEmRNAs) and miRNAs (DEmiRNAs) associated with AD-related neurofibrillary pathology. Additionally, we used the quantitative polymerase chain reaction technique to examine the expression of the BCAS4/hsa-miR-185-5p/SHISA7 ceRNA axis in the peripheral blood (PB) of fifty AD patients and fifty control subjects. BCAS4 was shown to act as a ceRNA to control the SHISA7 expression throughout AD-associated neurofibrillary pathology in TC tissue specimens by sponging hsa-miR-185-5p, based on our bioinformatics study. Furthermore, in PB specimens from individuals suffering from AD and normal controls, we found no substantial differences in BCAS4 expression patterns. SHISA7 expression in AD patients’ PB was found to be reduced, as was the case in the TC. On the other hand, we discovered reduced amounts of hsa-miR-185-5p in AD patients’ PB samples compared to control subjects, unlike in TC tissue, where it had been demonstrated to be overexpressed. BCAS4 and SHISA7 expression levels showed a strong positive correlation, suggesting the presence of an interconnected network, most likely as a result of ceRNA regulation among PB specimens. The present study is the first evidence to highlight the expression of the BCAS4/miR-185-5p/SHISA7 ceRNA axis in the brain and PB of AD patients, and offers a new viewpoint on molecular processes underlying AD pathogenic mechanisms.

Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein–protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.