Warning: Undefined variable $zfal in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 525
Deprecated: str_replace(): Passing null to parameter #3 ($subject) of type array|string is deprecated in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 525
Warning: Undefined variable $sterm in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 530
 free
Warning: Undefined variable $sterm in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 531
 free
 free
Warning: file_get_contents(http://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=22076134&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
in C:\Inetpub\vhosts\kidney.de\httpdocs\mlpefetch.php on line 445
 
English Wikipedia
Nephropedia Template TP (
Twit Text
DeepDyve
Pubget Overpricing |  
lüll
Prediction of disease and phenotype associations from genome-wide association studies Lewis SN; Nsoesie E; Weeks C; Qiao D; Zhang LPLoS One 2011[]; 6 (11): e27175BACKGROUND: Genome wide association studies (GWAS) have proven useful as a method for identifying genetic variations associated with diseases. In this study, we analyzed GWAS data for 61 diseases and phenotypes to elucidate common associations based on single nucleotide polymorphisms (SNP). The study was an expansion on a previous study on identifying disease associations via data from a single GWAS on seven diseases. METHODOLOGY/PRINCIPAL FINDINGS: Adjustments to the originally reported study included expansion of the SNP dataset using Linkage Disequilibrium (LD) and refinement of the four levels of analysis to encompass SNP, SNP block, gene, and pathway level comparisons. A pair-wise comparison between diseases and phenotypes was performed at each level and the Jaccard similarity index was used to measure the degree of association between two diseases/phenotypes. Disease relatedness networks (DRNs) were used to visualize our results. We saw predominant relatedness between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis for the first three levels of analysis. Expected relatedness was also seen between lipid- and blood-related traits. CONCLUSIONS/SIGNIFICANCE: The predominant associations between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis can be validated by clinical studies. The diseases have been proposed to share a systemic inflammation phenotype that can result in progression of additional diseases in patients with one of these three diseases. We also noticed unexpected relationships between metabolic and neurological diseases at the pathway comparison level. The less significant relationships found between diseases require a more detailed literature review to determine validity of the predictions. The results from this study serve as a first step towards a better understanding of seemingly unrelated diseases and phenotypes with similar symptoms or modes of treatment.|*Genetic Predisposition to Disease[MESH]|*Genome-Wide Association Study[MESH]|Arthritis, Rheumatoid/*diagnosis/genetics[MESH]|Diabetes Mellitus, Type 1/*diagnosis/genetics[MESH]|Gene Regulatory Networks[MESH]|Genes/physiology[MESH]|Genome, Human[MESH]|Humans[MESH]|Multiple Sclerosis/*diagnosis/genetics[MESH]|Phenotype[MESH]|Polymorphism, Single Nucleotide/*genetics[MESH]|Principal Component Analysis[MESH]|Signal Transduction[MESH] |
