Objective:Autosomal recessive primary microcephaly (MCPH) is a neurodevelopmental and genetically heterogeneous disorder with decreased head circumference due to the abnormality in fetal brain growth. To date, nine loci and nine genes responsible for the situation have been identified. Mutations in the ASPM gene (MCPH5) is the most common cause of MCPH. The ASPM gene with 28 exons is essential for normal mitotic spindle function in embryonic neuroblasts.Materials d Methods:We have ascertained twenty-two consanguineous families with intellectual disability and different ethnic backgrounds from Iran. Ten out of twenty-two families showed primary microcephaly in clinical examination. We investigated MCPH5 locus using homozygosity mapping by microsatellite marker.Result:Sequence analysis of exon 8 revealed a deletion of nucleotide (T) in donor site of splicing site of ASPM in one family. The remaining nine families were not linked to any of the known loci .More investigation will be needed to detect the causative defect in these families.Conlusion:We detected a novel mutation in the donor splicing site of exon 8 of the ASPM gene. This deletion mutation can alter the ASPM transcript leading to functional impairment of the gene product.

Autosomal recessive primary microcephaly (MCPH) is a rare genetic disorder, leading to the defect of neurogenic brain development. Individuals with MCPH reveal reduced head circumference and intellectual disability. Several MCPH loci have been identified from several populations. Genetic heterogeneity of this disorder represents molecular testing challenge. An 8 yr old female, born from consanguineous parents, was attended to Fardis Central Lab, Alborz, Iran. Based on the reduced circumference and intellectual disability, MCPH was diagnosed. Whole exome sequencing of the patient identified a novel homozygous frameshift mutation (c. 2738dupT, p. Cys914fs) in exon 9 Abnormal Spindle-like Microcephaly )ASPM( gene. By Sanger sequencing, segregation analysis showed that both parents were heterozygous carriers for this variant. The novel frameshift mutation likely truncates the protein, resulting in loss of normal function ASPM in homozygous mutation carriers. The study might add a new pathogenic variant in mutations of the ASPM gene as a causative variant in patients with MCPH and might be helpful in genetic counseling of consanguineous families.

Background: The uncontrolled growth of abnormal cells in the cervix leads to cervical cancer (CC), the fourth most common gynecologic cancer. So far, many studies have been conducted on CC,however, it is still necessary to discover the hub gene, key pathways, and the exact underlying mechanisms involved in developing this disease. Objective: This study aims to use gene expression patterns and protein-protein interaction (PPI) network analysis to identify key pathways and druggable hub genes in CC. Materials and Methods: In this in silico analysis, 2 microarray gene expression datasets,GSE63514 (104 cancer and 24 normal samples), and GSE9750 (42 cancer and 24 normal samples) were extracted from gene expression omnibus to identify common differentially expressed genes between them. Gene ontology and Kyoto encyclopedia of genes and genomes pathway analysis were performed via the Enrichr database. STRING 12. 0 database and CytoHubba plugin in Cytoscape 3. 9. 1 software were implemented to create and analyze the PPI network. Finally, druggable hub genes were screened. Results: Based on the degree method, 10 key genes were known as the hub genes after the screening of PPI networks by the CytoHubba plugin. NCAPG, KIF11, TTK, PBK, MELK, ASPM, TPX2, BUB1, TOP2A, and KIF2C are the key genes, of which 5 genes (KIF11, TTK, PBK, MELK, and TOP2A) were druggable. Conclusion: This research provides a novel vision for designing therapeutic targets in patients with CC. However, these findings should be verified through additional experiments.

Introduction: Schaaf-Yang syndrome (SYS) is a rare autosomal dominant disorder, first identified in 2013, resulting from mutations in the paternal allele of the MAGEL2 gene. Schaaf-Yang syndrome exhibits clinical features similar to those of Prader-Willi syndrome (PWS), including hypotonia, joint contractures, developmental delay, and intellectual disability. However, SYS is also characterized by unique manifestations, such as recurrent hyperthermia, feeding difficulties, respiratory distress, and seizures. This case report describes the first SYS case identified in Iran. Case Presentation: A one-year-old female, born to consanguineous parents, presented with recurrent episodes of hyperthermia, respiratory distress, and seizures since the neonatal period. Despite initial empirical treatment with broad-spectrum antibiotics for suspected infections, her symptoms persisted. Physical examination revealed hypotonia, camptodactyly, and hand contractures. Genetic testing confirmed SYS with a MAGEL2 gene mutation (c.1923dupC, p.V643Gfs*70) and probable pathogenic variants in ASPM and KIF7. The hyperthermia was attributed to hypothalamic dysfunction, a hallmark of SYS, rather than an infectious cause. The patient remains under follow-up without specific pharmacological intervention. Conclusions: This case emphasizes the importance of considering SYS in patients presenting with unexplained fever, seizures, and neurodevelopmental delays. Early genetic testing is crucial for diagnosing SYS and differentiating it from conditions such as PWS or infection-related disorders. Timely diagnosis can improve management strategies and help reduce the risk of lasting neurological impairments associated with this genetic disorder.

Background: Liver hepatocellular carcinoma (LIHC) is a common cancer with a poor prognosis and high recurrence rate. We aimed to identify potential biomarkers for LIHC by investigating the involvement of hub genes, microRNAs (miRNAs), transcription factors (TFs), and protein kinases (PKs) in its occurrence. Methods: we conducted a bioinformatics analysis using microarray datasets, the TCGA-LIHC dataset, and text mining to identify differentially expressed genes (DEGs) associated with LIHC. They then performed functional enrichment analysis and gene-disease association analysis. The protein-protein interaction network of the genes was established, and hub genes were identified. The expression levels and survival analysis of these hub genes were evaluated, and their association with miRNAs, TFs, and PKs was assessed. Results: The analysis identified 122 common genes involved in LIHC pathogenesis. Ten hub genes were filtered out, including CDK1, CCNB1, CCNB2, CCNA2, ASPM, NCAPG, BIRC5, RRM2, KIF20A, and CENPF. The expression level of all hub genes was confirmed, and high expression levels of all hub genes were correlated with poor overall survival of LIHC patients. Conclusion: Identifying potential biomarkers for LIHC can aid in the design of targeted treatments and improve the survival of LIHC patients. The findings of this study provide a basis for further research in the field of LIHC and contribute to the understanding of its molecular pathogenesis.

Background: Growing evidence strongly indicates pivotal roles of gender differences in the occurrence and survival rate of patients with bladder cancer, with a higher incidence in males and poorer prognosis in females. Nevertheless, the molecular basis underlying gender-specific differences in bladder cancer remains unknown. The current study has tried to detect key genes contributing to gender differences in bladder cancer patients. Materials and Methods: The gene expression profile of GSE13507 was firstly obtained from the Gene Expression Omnibus (GEO) database. Further, differentially expressed genes (DEGs) were screened between males and females using R software. Protein–protein interactive (PPI) network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Kaplan–Meier survival analyses were also performed. Results: We detected six hub genes contributing to gender differences in bladder cancer patients, containing IGF2, CCL5, ASPM, CDC20, BUB1B, and CCNB1. Our analyses demonstrated that CCNB1 and BUB1B were upregulated in tumor tissues of female subjects with bladder cancer. Other genes, such as IGF2 and CCL5, were associated with a poor outcome in male patients with bladder cancer. Additionally, three signaling pathways (focal adhesion, rheumatoid arthritis, and human T-cell leukemia virus infection) were identified to be differentially downregulated in bladder cancer versus normal samples in both genders. Conclusion: Our findings suggested that gender differences may modulate the expression of key genes that contributed to bladder cancer occurrence and prognosis.

Background: Intellectual disability (ID) is a genetically heterogeneous condition, and so far, 1679 human genes have been identified for this phenotype. Countries with a high rate of parental consanguinity, such as Iran, provide an excellent opportunity to identify the remaining novel ID genes, especially those with an autosomal recessive (AR) mode of inheritance. This study aimed to investigate the most prevalent ID genes identified via next-generation sequencing (NGS) in a large ID cohort at the Genetics Research Center (GRC) of the University of Social Welfare and Rehabilitation Sciences. Methods: First, we surveyed the epidemiological data of 619 of 1295 families in our ID cohort, who referred to the Genetics Research Center from all over the country between 2004 and 2021 for genetic investigation via the NGS pipeline. We then compared our data with those of several prominent studies conducted in consanguineous countries. Data analysis, including cohort data extraction, categorization, and comparison, was performed using the R program version 4. 1. 2. Results: We categorized the most common ID genes that were mutated in more than two families into 17 categories. The most common syndromic ID in our cohort was AP4 deficiency syndrome, and the most common non-syndromic autosomal recessive intellectual disability (ARID) gene was ASPM. We identified two unrelated families for the 36 ID genes. We found 14 genes in common between our cohort and the Arab and Pakistani groups, of which three genes (AP4M1, AP4S1, and ADGRG1) were repeated more than once. Conclusion: To date, there has been no comprehensive targeted NGS platform for the detection of ID genes in our country. Due to the large sample size of our study, our data may provide the initial step toward designing an indigenously targeted NGS platform for the diagnosis of ID, especially common ARID in our population.

Background: In cancer-related diseases, early detection and control of disease progression are very important for successful treatment. Breast cancer is a significant problem due to its high mortality rate in the female population worldwide. By the early diagnosis of breast cancer, the 5-year survival rate reaches 93 to 98%. In this study, to identify breast cancer biomarkers, we construct new protein-protein interaction (PPI) and miRNAs-mRNAs networks by analyzing upregulated and downregulated genes in breast cancer patients.Method: In this in silico study, two gene expression profile datasets, with the accession numbers GSE42568 and GSE154255, were downloaded from the GEO database. GEO2R was used to obtain differentially expressed mRNA (DEMs) and miRNAs (DEMIs) based on |logFC|>2 and adjusted P-value <0.05. Gene Ontology and KEGG Pathway Enrichment Analysis were performed by EnrichR. STRING v9. 1 and cytoHubba plugin in Cytoscape (v3.9.1) were used to investigate PPI network construction and identification of hub genes. Finally, key microRNAs (miRNAs) were predicted.Results: After protein-protein interaction analysis, a total of 10 upregulated DEMs (DLGAP5, CCNB1, TTK, NUSAP1, RRM2, BUB1B, CDK1, CENPF, TOP2A, and ASPM) and 10 downregulated DEMs (PPARG, LIPE, CD36, FABP4, SCD, LPL, DGAT2, PNPLA2, ACSL1, and LEP) were screened as hub genes. Based on miRNAs-mRNAs networks, 4 key miRNAs including hsa-miR-182-5p, hsa-miR-96-5p, hsa-miR-335-3p, and hsa-miR-32-5p play a critical role in network regulation.Conclusion: Our study presents PPI and miRNAs-mRNAs networks for identifying molecular biomarkers in breast cancer. The introduced biomarkers open a new approach to diagnostic and therapeutic indicators for clinical applications.