Evidence map›Paper›PMID 31198690›Full record

ArticleMethodsX2019

Molecular Interaction Network Approach (MINA) identifies association of novel candidate disease genes.

Sam Kara, Alaa Hanna, Gerardo A Pirela-Morillo, Conrad T Gilliam, George D Wilson

Abstract read
In one paragraph

Article in MethodsX, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Sam KaraUniversity of Chicago, Departments of Human Genetics, 920 East 58th St., Chicago, IL, 60637, USA.
Alaa HannaRadiation Oncology Department, 3811 W Thirteen Mile Road, Royal Oak, MI, 48073, USA.
Gerardo A Pirela-MorilloLa Universidad del Zulia, Computer Science Department, Laboratories for Computational Models & Languages, and Bioinformatics, Edif. Grano de Oro, Planta Baja, Departamento de Computación, Ave. Universidad con Ave. 22, Maracaibo, 4002, Venezuela.
Conrad T GilliamUniversity of Chicago, Departments of Human Genetics, 920 East 58th St., Chicago, IL, 60637, USA.
George D WilsonRadiation Oncology Department, 3811 W Thirteen Mile Road, Royal Oak, MI, 48073, USA.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Molecular Interaction Network Approach (MINA) was used to elucidate candidate disease genes. The approach was implemented to identify novel gene association with commonly known autoimmune diseases [1]. In MINA, we evaluated the hypothesis that "network proximity" within a whole genome molecular interaction network can be used to inform the search for multigene inheritance. There are now numerous examples of gene discoveries based upon network proximity between novel and previously identified disease genes (Yin et al., 2017 [2], Wang et al., 2011 [3], and Barrenas et al., 2009 [4]). This study extends the application of interaction networks to the interrogation of Genome Wide Association studies: first, by showing that a group of nine autoimmune diseases (AuD) genes "seed genes", are connected in a highly non-random manner within a whole genome network; and second, by showing that the minimal number of connecting genes required to connect a maximal number of AuD candidate genes are highly enriched as candidate genes for AuD predisposing mutations. The findings imply that a threshold number of candidate genes for any heritable disorder can be used to "seed" a molecular interaction network that •Serves to validate the disease status of closely associated seed genes•Identifies genes that are highly enriched as novel candidate disease genes•Provides a strategy for elucidation of epistatic gene x gene interactions The method could provide a critical toll for understanding the genetic architecture of common traits and disorders.

Indexed as

AssociationAutoimmune diseasesCeliac disease (CeD)Crohn’s disease (CD)MINAMolecular Interaction Network ApproachMolecular networkMultiple sclerosis (MS)Psoriasis (PSO)Rheumatoid arthritis (RA)Systemic lupus erythematosus (SLE)Type-1 diabetes (T1D)Type-2 diabetes (T2D)

Identifiers

PMID31198690
PMCPMC6555892

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.