Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules

نویسندگان

  • Ettore Mosca
  • Matteo Bersanelli
  • Matteo Gnocchi
  • Marco Moscatelli
  • Gastone Castellani
  • Luciano Milanesi
  • Alessandra Mezzelani
چکیده

Autism spectrum disorder (ASD) is marked by a strong genetic heterogeneity, which is underlined by the low overlap between ASD risk gene lists proposed in different studies. In this context, molecular networks can be used to analyze the results of several genome-wide studies in order to underline those network regions harboring genetic variations associated with ASD, the so-called "disease modules." In this work, we used a recent network diffusion-based approach to jointly analyze multiple ASD risk gene lists. We defined genome-scale prioritizations of human genes in relation to ASD genes from multiple studies, found significantly connected gene modules associated with ASD and predicted genes functionally related to ASD risk genes. Most of them play a role in synapsis and neuronal development and function; many are related to syndromes that can be in comorbidity with ASD and the remaining are involved in epigenetics, cell cycle, cell adhesion and cancer.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Exploring Gene Signatures in Different Molecular Subtypes of Gastric Cancer (MSS/ TP53+, MSS/TP53-): A Network-based and Machine Learning Approach

Gastric cancer (GC) is one of the leading causes of cancer mortality, worldwide. Molecular understanding of GC’s different subtypes is still dismal and it is necessary to develop new subtype-specific diagnostic and therapeutic approaches. Therefore developing comprehensive research in this area is demanding to have a deeper insight into molecular processes, underlying these subtypes. In this st...

متن کامل

Pathway-Dependent Effectiveness of Network Algorithms for Gene Prioritization

A network-based approach has proven useful for the identification of novel genes associated with complex phenotypes, including human diseases. Because network-based gene prioritization algorithms are based on propagating information of known phenotype-associated genes through networks, the pathway structure of each phenotype might significantly affect the effectiveness of algorithms. We systema...

متن کامل

Identification of Prognostic Genes in Her2-enriched Breast Cancer by Gene Co-Expression Net-work Analysis

Introduction: HER2-enriched subtype of breast cancer has a worse prognosis than luminal subtypes. Recently, the discovery of targeted therapies in other groups of breast cancer has increased patient survival. The aim of this study was to identify genes that affect the overall survival of this group of patients based on a systems biology approach. Methods: Gene expression data and clinical infor...

متن کامل

Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules

A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular ...

متن کامل

EPSILON: an eQTL prioritization framework using similarity measures derived from local networks

MOTIVATION When genomic data are associated with gene expression data, the resulting expression quantitative trait loci (eQTL) will likely span multiple genes. eQTL prioritization techniques can be used to select the most likely causal gene affecting the expression of a target gene from a list of candidates. As an input, these techniques use physical interaction networks that often contain high...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 8  شماره 

صفحات  -

تاریخ انتشار 2017