دانلود مقاله تعیین اثرات مولکولی در بافت‌های مغزی اختلال طیف اوتیسم
چکیده
مقدمه
مطالب و روش ها
نتایج
بحث ها
نتیجه گیری
منابع
Abstract
Introduction
Materials and methods
Results
Discussions
Conclusion
References
چکیده
اختلال طیف اوتیسم (ASD) مجموعه ای از ناتوانی های عصبی است که با مشکلات رفتاری، گفتاری، زبانی و تعامل مشخص می شود. این یک اختلال استاتیک پیچیده و تعریف شده از نظر رفتاری در مغز در حال رشد است. اخیراً در سراسر جهان به یک نگرانی جدی تبدیل شده است. هدف از این پروژه استفاده از ابزارهای بیوانفورماتیک و بیولوژی شبکه برای کشف علائم مولکولی و مسیرهای ASD بود. ما مجموعه داده‌های بیان ژن رونوشت‌شناسی مغز را بررسی کردیم و 47 ژن مشترک با بیان متفاوت تنظیم‌نشده را تعیین کردیم. در نتیجه این تحقیقات، چندین نوع مکانیسم مولکولی مرتبط با تخریب عصبی در ساختارهای سیگنالینگ تعیین شد. ما آنالیز غنی‌سازی مجموعه ژنی (GSEA) را با استفاده از مسیرهای دو مولکولی و اصطلاحات هستی‌شناسی ژن (GO) برای تعیین نقش این ژن‌های بیان‌شده متفاوت (DEGs)، و همچنین برهم‌کنش‌های پروتئین-پروتئین (PPI)، برهم‌کنش‌های فاکتور رونویسی و پس از آن اجرا کردیم. تعاملات فاکتور رونویسی شبکه PPI ده ژن هاب برتر شامل KIT، PIN1، GATA1، GRIN2A، PBX2، BLK، ATP6V1B1، TCF7L1، TRAF1 و HSPG2 را جمع آوری کرد. شبکه PPI نیز وجود دو شبکه فرعی را فاش کرد. علاوه بر این، چندین فاکتور رونویسی (NFIC، USF2، TFAP2A، RELA، FOXL1، GATA2، YY1، FOXC1، NFKB1، و E2F1) و فاکتورهای پس از رونویسی (mir-335-5p، mir-26b-5p، mir-124-3 ، mir-192-5p، mir-1-3p، mir-215-5p، mir-6825-5p، mir-146a-5p، mir-8485، و mir-93-5p) در سراسر این مطالعه یافت شدند. برخی از مولکول‌های دارو مانند نیز پیش‌بینی شده بودند که ممکن است اثر مفیدی در برابر ASD داشته باشند. ما پیوندهای بالقوه جدیدی را بین شرایط بیماری زا در بافت های مغزی بیمار ASD شناسایی کردیم. این کار نشانگرهای زیستی مولکولی را در سطح بیان ژن و پایه‌های پروتئینی ارائه می‌کند که می‌تواند به درک بهتر مسیرهای مولکولی، و همچنین رویکردهای دارویی و درمان‌های بالقوه برای توسعه درمان‌های موثر ASD کمک کند.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
Autism spectrum disorder (ASD) is a collection of neurological disabilities marked by difficulties with behavior, speech, language, and interaction. It is a complicated and behaviorally defined static disorder of the developing brain. Recently it has become a serious concern across the world. The goal of this project was to use bioinformatics tools and network biology to uncover the molecular signatures and pathways of ASD. We investigated brain transcriptomics gene expression datasets and determined 47 dysregulated differentially expressed common genes. Several kinds of crucial neurodegeneration-related molecular mechanisms in the signaling structures were determined as a result of these investigations. We implemented gene set enrichment analysis (GSEA) using bimolecular pathways and gene ontology (GO) terms to determine the role of these differentially expressed genes (DEGs), as well as protein-protein interactions (PPI), transcriptional factor interactions, and post-transcriptional factor interactions. PPI network collected the top ten hub genes including KIT, PIN1, GATA1, GRIN2A, PBX2, BLK, ATP6V1B1, TCF7L1, TRAF1, and HSPG2. The PPI network also revealed the existence of two sub-networks. Moreover, several transcription factors (NFIC, USF2, TFAP2A, RELA, FOXL1, GATA2, YY1, FOXC1, NFKB1, and E2F1) and post-transcription factors (mir-335-5p, mir-26b-5p, mir-124-3p, mir-192-5p, mir-1-3p, mir-215-5p, mir-6825-5p, mir-146a-5p, mir-8485, and mir-93-5p) were found throughout this study. Some drug-like molecules were also predicted that might have a beneficial effect against ASD. We detected potentially novel links between pathogenic conditions in ASD patient's brain tissues. This work offers molecular biomarkers at the gene expression level and protein bases that could aid in a better understanding of molecular pathways, as well as potential pharmacological approaches and therapies for developing effective ASD treatments.
Introduction
Autism spectrum disorder (ASD) is a term that has been accustomed to characterize a collection of initial socialization deformities and repeated neural activities that are linked to both a significant hereditary component and external factors. Kanner was the first who defined autism in 1943 through the study of 11 youngsters with comparable their odd behaviors [[1], [2], [3]]. The “American Psychiatric Association” changed the word ‘Autistic’ to Autism Spectrum Disorders (ASD) in 2013 [4]. ASD is a complicated mental condition indicated by problems in three areas: socializing, interaction, and confined as well as repetitious activity [5]. It has a significant genetic component with a complicated inheritance pattern [[6], [7], [8]]. ASD is four times as prevalent in men than it is in women (1 out of 34 men vs. 1 out of 144 women) [9]. Children with ASD may develop normally for the first few months or even years of their lives, but later on, they may become reclusive, aggressive, or lose language abilities that they had previously acquired [10,11]. Generally, the brain shapes and organization of autistic children differ from neurotypical children [12]. According to the experts, autistic children have an overgrowth of synapses or linkages throughout brain cells, and this overgrowth is caused by a disruption in the usual trimming mechanism that happens throughout brain growth [13].
Conclusion
One of the most prevalent neurodegenerative disorders in the world is ASD. It is a multifaceted disorder with a wide range of clinical and genetic variability. Approximately hundreds of genes have been discovered in recent decades that contribute to severe communication, social cognitive, and behavior impairments. In this study, we used a network-based method to identify important pathways and biomolecules in ASD to find common DEGs. These DEGs were used in pathway analysis and also used to uncover protein-protein interactions, transcription factors, post-transcriptional factors, and potential therapeutic compounds. We had collected some differentially expressed common genes. Between them, Several TFs and miRNAs have been discovered as candidate transcriptional and post-transcriptional factors of the DEGs. As a result, we identified some possible molecular signatures and pathways that are often dysregulated in ASD brain tissues. However, we hope that our observations will provide new insights on the molecular basis of ASD and aid in the identification of prospective medicines.