We have used Gene Ontology (GO) and pathway analyses to uncover the common functions associated to the genes overlapping Copy Number Variants (CNVs) in autistic patients. Our source of data were four published studies [1-4]. We first applied a two-step enrichment strategy for autism-specific genes. We fished out from the four mentioned studies a list of 2928 genes overall overlapping 328 CNVs in patients and we first selected a sub-group of 2044 genes after excluding those ones that are also involved in CNVs reported in the Database of Genomic Variants (enrichment step 1). We then selected from the step 1-enriched list a sub-group of 514 genes each of which was found to be deleted or duplicated in at least two patients (enrichment step 2). The number of statistically significant processes and pathways identified by the Database for Annotation, Visualization and Integrated Discovery and Ingenuity Pathways Analysis softwares with the step 2-enriched list was significantly higher compared to the step 1-enriched list. In addition, statistically significant GO terms, biofunctions and pathways related to nervous system development and function were exclusively identified by the step 2-enriched list of genes. Interestingly, 21 genes were associated to axon growth and pathfinding. The latter genes and other ones associated to nervous system in this study represent a new set of autism candidate genes deserving further investigation. In summary, our results suggest that the autism's "connectivity genes" in some patients affect very early phases of neurodevelopment, i.e., earlier than synaptogenesis.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2874223PMC
http://dx.doi.org/10.2174/138920210790886880DOI Listing

Publication Analysis

Top Keywords

genes overlapping
12
genes
10
overlapping copy
8
copy number
8
number variants
8
autistic patients
8
enrichment step
8
step 1-enriched
8
1-enriched list
8
step 2-enriched
8

Similar Publications

Exploring the shared mechanism of fatigue between systemic lupus erythematosus and myalgic encephalomyelitis/chronic fatigue syndrome: monocytic dysregulation and drug repurposing.

Front Immunol

January 2025

Key Laboratory of Chinese Medicine Rheumatology of Zhejiang Province, Research Institute of Chinese Medical Clinical Foundation and Immunology, College of Basic Medical Science, Zhejiang Chinese Medical University, Hangzhou, China.

Background: SLE and ME/CFS both present significant fatigue and share immune dysregulation. The mechanisms underlying fatigue in these disorders remain unclear, and there are no standardized treatments. This study aims to explore shared mechanisms and predict potential therapeutic drugs for fatigue in SLE and ME/CFS.

View Article and Find Full Text PDF

Gene Expression Signatures of Smoking and Acute Myocardial Infarction: A Blood Transcriptome Analysis.

Mediators Inflamm

January 2025

Department of Blood Transfusion, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.

Tobacco smoke is known to contain numerous harmful chemicals, and epidemiological evidence has firmly established smoking as a potent risk factor for hypertension and myocardial infarction (MI). However, the precise mechanisms by which smoking contributes to cardiovascular disease are not fully understood. The aim of this study is to identify common molecular signatures in blood that link smoking to acute MI (AMI).

View Article and Find Full Text PDF

Objective: The aim of this paper is to discover differentially expressed genes related to ferroptosis (DEFRGs) in patients with ST-segment elevation myocardial infarction (STEMI) and to construct a reliable prognostic signature that incorporates key DEFRGs and easily accessible clinical factors.

Methods: We did a systematic review of Gene Expression Omnibus datasets and picked datasets SE49925, GSE60993, and GSE61144 for analysis. We applied GEO2R to find DEFRGs and overlapped them among the picked datasets.

View Article and Find Full Text PDF

Exploration of metastasis-related signatures in osteosarcoma based on tumor microenvironment by integrated bioinformatic analysis.

Heliyon

January 2025

Center for Plastic & Reconstructive Surgery, Department of Orthopedics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, 310014, China.

Background: The present study aims to explore the metastasis-related signatures in connection with tumor microenvironment (TME), revealing new molecular targets promising in improving osteosarcoma (OS) patients' outcomes.

Methods: The high-throughput sequencing data was downloaded from the TARGET database and performed the ESTIMATE algorithm. Metastasis-related information was obtained from the GSE21257 dataset.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!