scholarly journals Network Properties of Complex Human Disease Genes Identified through Genome-Wide Association Studies

PLoS ONE ◽  
2009 ◽  
Vol 4 (11) ◽  
pp. e8090 ◽  
Author(s):  
Fredrik Barrenas ◽  
Sreenivas Chavali ◽  
Petter Holme ◽  
Reza Mobini ◽  
Mikael Benson
Keyword(s):  
Human Disease ◽  
Association Studies ◽  
Genome Wide Association ◽  
Disease Genes ◽  
Genome Wide Association Studies ◽  
Complex Human Disease ◽  
Genome Wide ◽  
Network Properties ◽  
Human Disease Genes

scholarly journals The impact of genome-wide association studies on biomedical research publications

2017 ◽  
Author(s):  
Travis J. Struck ◽  
Brian K. Mannakee ◽  
Ryan N. Gutenkunst
Keyword(s):  
Biomedical Research ◽  
Human Disease ◽  
Association Studies ◽  
Genome Wide Association ◽  
Disease Genes ◽  
Genome Wide Association Studies ◽  
Complex Human Disease ◽  
The Past ◽  
Research Publications ◽  
Genome Wide

AbstractThe past decade has seen major investment in genome-wide association studies (GWAS), with the goal of identifying and motivating research on novel genes involved in complex human disease. To assess whether this goal is being met, we quantified the effect of GWAS on the overall distribution of biomedical research publications and on the subsequent publication history of genes newly associated with complex disease. We found that the historical skew of publications toward genes involved in Mendelian disease has not changed since the advent of GWAS. Genes newly implicated by GWAS in complex disease do experience additional publications compared to control genes, and they are more likely to become exceptionally studied. But the magnitude of both effects has declined dramatically over the past decade. Our results suggest that reforms to encourage follow-up studies may be needed for GWAS to most successfully guide biomedical research toward the molecular mechanisms underlying complex human disease.Author summaryOver the past decade, thousands of genome-wide association studies (GWAS) have been performed to link genetic variation with complex human disease. A major goal of such studies is to identify novel disease genes, so they can be further studied. We tested whether this goal is being met, by studying patterns of scientific research publications on human genes. We found that publications are still concentrated on genes involved in simple Mendelian disease, even after the advent of GWAS. Compared to other genes, disease genes discovered by GWAS do experience additional publications, but that effect has declined dramatically since GWAS were first performed. Our results suggest that the ability of GWAS to stimulate research into novel disease genes is declining. To realize the full potential of GWAS to reveal the molecular mechanisms driving human disease, this decline and the reasons for it must be understood, so that it can be reversed.

scholarly journals The predictive power of the microbiome exceeds that of genome-wide association studies in the discrimination of complex human disease

2020 ◽  
Author(s):  
Braden T Tierney ◽  
Yixuan He ◽  
George M Church ◽  
Eran Segal ◽  
Aleksandar D Kostic ◽  
...  
Keyword(s):  
Association Study ◽  
Human Disease ◽  
Genome Wide Association Study ◽  
Human Genetics ◽  
Association Studies ◽  
Human Microbiome ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Genome Wide

AbstractOver the past decade, studies of the human genome and microbiome have deepened our understanding of the connections between human genes, environments, microbes, and disease. For example, the sheer number of indicators of the microbiome and human genetic common variants associated with disease has been immense, but clinical utility has been elusive. Here, we compared the predictive capabilities of the human microbiome versus human genomic common variants across 13 common diseases. We concluded that microbiomic indicators outperform human genetics in predicting host phenotype (overall Microbiome-Association-Study [MAS] area under the curve [AUC] = 0.79 [SE = 0.03], overall Genome-Wide-Association-Study [GWAS] AUC = 0.67 [SE = 0.02]). Our results, while preliminary and focused on a subset of the totality of disease, demonstrate the relative predictive ability of the microbiome, indicating that it may outperform human genetics in discriminating human disease cases and controls. They additionally motivate the need for population-level microbiome sequencing resources, akin to the UK Biobank, to further improve and reproduce metagenomic models of disease.

scholarly journals FORGE: multivariate calculation of gene-wide p-values from Genome-Wide Association Studies Authors and Affiliations

2015 ◽  
Author(s):  
Inti Inal Pedroso ◽  
Michael R Barnes ◽  
Anbarasu Lourdusamy ◽  
Ammar Al-Chalabi ◽  
Gerome Breen
Keyword(s):  
Statistical Power ◽  
Association Studies ◽  
Single Point ◽  
Genome Wide Association ◽  
P Value ◽  
Disease Genes ◽  
Snp Analysis ◽  
Genome Wide Association Studies ◽  
P Values ◽  
Genome Wide

Genome-wide association studies (GWAS) have proven a valuable tool to explore the genetic basis of many traits. However, many GWAS lack statistical power and the commonly used single-point analysis method needs to be complemented to enhance power and interpretation. Multivariate region or gene-wide association are an alternative, allowing for identification of disease genes in a manner more robust to allelic heterogeneity. Gene-based association also facilitates systems biology analyses by generating a single p-value per gene. We have designed and implemented FORGE, a software suite which implements a range of methods for the combination of p-values for the individual genetic variants within a gene or genomic region. The software can be used with summary statistics (marker ids and p-values) and accepts as input the result file formats of commonly used genetic association software. When applied to a study of Crohn's disease susceptibility, it identified all genes found by single SNP analysis and additional genes identified by large independent meta-analysis. FORGE p-values on gene-set analyses highlighted association with the Jak-STAT and cytokine signalling pathways, both previously associated with CD. We highlight the software's main features, its future development directions and provide a comparison with alternative available software tools. FORGE can be freely accessed at https://github.com/inti/FORGE.

scholarly journals Expression Sensitivity Analysis of Human Disease Related Genes

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Liang-Xiao Ma ◽  
Ya-Jun Wang ◽  
Jing-Fang Wang ◽  
Xuan Li ◽  
Pei Hao
Keyword(s):  
Profile Analysis ◽  
Association Studies ◽  
Enrichment Analysis ◽  
Genome Wide Association ◽  
Disease Genes ◽  
Genome Wide Association Studies ◽  
Expression Profile Analysis ◽  
Genome Wide ◽  
Disease Related Genes ◽  
Essential Function

Background. Genome-wide association studies (GWAS) have shown its revolutionary power in seeking the influenced loci on complex diseases genetically. Thousands of replicated loci for common traits are helpful in diseases risk assessment. However it is still difficult to elucidate the variations in these loci that directly cause susceptibility to diseases by disrupting the expression or function of a protein currently.Results. We evaluate the expression features of disease related genes and find that different diseases related genes show different expression perturbation sensitivities in various conditions. It is worth noting that the expression of some robust disease-genes doesn’t show significant change in their corresponding diseases, these genes might be easily ignored in the expression profile analysis.Conclusion. Gene ontology enrichment analysis indicates that robust disease-genes execute essential function in comparison with sensitive disease-genes. The diseases associated with robust genes seem to be relatively lethal like cancer and aging. On the other hand, the diseases associated with sensitive genes are apparently nonlethal like psych and chemical dependency diseases.

Genome-wide Association Studies and Human Disease

JAMA ◽  
2009 ◽  
Vol 302 (18) ◽  
pp. 2028 ◽  
Author(s):  
Peter M. Visscher ◽  
Grant W. Montgomery
Keyword(s):  
Human Disease ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide
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