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Protein-protein interaction analysis highlights additional loci of interest for multiple sclerosis.

Ragnedda G, Disanto G, Giovannoni G, Ebers GC, Sotgiu S, Ramagopalan SV - PLoS ONE (2012)

Bottom Line: Using the Disease Association Protein-Protein Link Evaluator tool we found that direct interactions among genetic products were significantly higher than expected by chance when considering both significant regions alone (p<0.0002) and significant plus suggestive (p<0.007).Using the gene portal BioGPS, we tested the expression of these genes in 24 different tissues and found the highest values among immune-related cells as compared to non-immune tissues (p<0.001).A gene ontology analysis confirmed the immune-related functions of these genes.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.

ABSTRACT
Genetic factors play an important role in determining the risk of multiple sclerosis (MS). The strongest genetic association in MS is located within the major histocompatibility complex class II region (MHC), but more than 50 MS loci of modest effect located outside the MHC have now been identified. However, the relative candidate genes that underlie these associations and their functions are largely unknown. We conducted a protein-protein interaction (PPI) analysis of gene products coded in loci recently reported to be MS associated at the genome-wide significance level and in loci suggestive of MS association. Our aim was to identify which suggestive regions are more likely to be truly associated, which genes are mostly implicated in the PPI network and their expression profile. From three recent independent association studies, SNPs were considered and divided into significant and suggestive depending on the strength of the statistical association. Using the Disease Association Protein-Protein Link Evaluator tool we found that direct interactions among genetic products were significantly higher than expected by chance when considering both significant regions alone (p<0.0002) and significant plus suggestive (p<0.007). The number of genes involved in the network was 43. Of these, 23 were located within suggestive regions and many of them directly interacted with proteins coded within significant regions. These included genes such as SYK, IL-6, CSF2RB, FCLR3, EIF4EBP2 and CHST12. Using the gene portal BioGPS, we tested the expression of these genes in 24 different tissues and found the highest values among immune-related cells as compared to non-immune tissues (p<0.001). A gene ontology analysis confirmed the immune-related functions of these genes. In conclusion, loci currently suggestive of MS association interact with and have similar expression profiles and function as those significantly associated, highlighting the fact that more common variants remain to be found to be associated to MS.

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Related in: MedlinePlus

Expression values of candidate genes (genes to prioritize) in all 23 tissues and cell types tested.
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pone-0046730-g003: Expression values of candidate genes (genes to prioritize) in all 23 tissues and cell types tested.

Mentions: In order to further investigate the nature of our findings we assessed in which tissues these genes were mostly expressed. We used the gene portal BioGPS which contains gene expression data on a variety of human tissues and cell types [17]. For our analysis we considered 10 immune cell types and 14 non-immune tissues. We submitted the full list of candidate genes (n = 43) obtained from the significant plus suggestive DAPPLE analysis and for each gene we obtained a different genetic expression value in every tissue or cell type tested. Because of different background characteristics between each probe set, a direct comparison of expression across different genes was not possible. Therefore, we decided to standardize the expression values of each single gene across different tissues and used the obtained z-values for all subsequent analyses. Figure 3 shows the standardized expression values in the 24 tissues and cell types tested. Expression appeared particularly high in whole blood as well as in most of immune-related cell types (in particular B-cells, plasmacytoid dendritic cells (pDCs), natural killer (NK) cells, CD4+ and CD8+ T cells). An independent-sample Kruskal-Wallis test confirmed that gene expression was significantly different across tissues (p<0.001). When tissues were divided into immune and non-immune, expression was substantially different between the two groups (p<0.001) (Figure 4). When compared to average expression across tissues, candidate genes were significantly overexpressed in B-lymphoblasts, pDCs, monocytes, B cells, NK cells, CD4+ T cells (p<0.001), CD34+ hematopoietic cells (p = 0.001) and CD8+ T cells (p = 0.003). Expression patterns were similar for significantly and suggestively associated loci.


Protein-protein interaction analysis highlights additional loci of interest for multiple sclerosis.

Ragnedda G, Disanto G, Giovannoni G, Ebers GC, Sotgiu S, Ramagopalan SV - PLoS ONE (2012)

Expression values of candidate genes (genes to prioritize) in all 23 tissues and cell types tested.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3475710&req=5

pone-0046730-g003: Expression values of candidate genes (genes to prioritize) in all 23 tissues and cell types tested.
Mentions: In order to further investigate the nature of our findings we assessed in which tissues these genes were mostly expressed. We used the gene portal BioGPS which contains gene expression data on a variety of human tissues and cell types [17]. For our analysis we considered 10 immune cell types and 14 non-immune tissues. We submitted the full list of candidate genes (n = 43) obtained from the significant plus suggestive DAPPLE analysis and for each gene we obtained a different genetic expression value in every tissue or cell type tested. Because of different background characteristics between each probe set, a direct comparison of expression across different genes was not possible. Therefore, we decided to standardize the expression values of each single gene across different tissues and used the obtained z-values for all subsequent analyses. Figure 3 shows the standardized expression values in the 24 tissues and cell types tested. Expression appeared particularly high in whole blood as well as in most of immune-related cell types (in particular B-cells, plasmacytoid dendritic cells (pDCs), natural killer (NK) cells, CD4+ and CD8+ T cells). An independent-sample Kruskal-Wallis test confirmed that gene expression was significantly different across tissues (p<0.001). When tissues were divided into immune and non-immune, expression was substantially different between the two groups (p<0.001) (Figure 4). When compared to average expression across tissues, candidate genes were significantly overexpressed in B-lymphoblasts, pDCs, monocytes, B cells, NK cells, CD4+ T cells (p<0.001), CD34+ hematopoietic cells (p = 0.001) and CD8+ T cells (p = 0.003). Expression patterns were similar for significantly and suggestively associated loci.

Bottom Line: Using the Disease Association Protein-Protein Link Evaluator tool we found that direct interactions among genetic products were significantly higher than expected by chance when considering both significant regions alone (p<0.0002) and significant plus suggestive (p<0.007).Using the gene portal BioGPS, we tested the expression of these genes in 24 different tissues and found the highest values among immune-related cells as compared to non-immune tissues (p<0.001).A gene ontology analysis confirmed the immune-related functions of these genes.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.

ABSTRACT
Genetic factors play an important role in determining the risk of multiple sclerosis (MS). The strongest genetic association in MS is located within the major histocompatibility complex class II region (MHC), but more than 50 MS loci of modest effect located outside the MHC have now been identified. However, the relative candidate genes that underlie these associations and their functions are largely unknown. We conducted a protein-protein interaction (PPI) analysis of gene products coded in loci recently reported to be MS associated at the genome-wide significance level and in loci suggestive of MS association. Our aim was to identify which suggestive regions are more likely to be truly associated, which genes are mostly implicated in the PPI network and their expression profile. From three recent independent association studies, SNPs were considered and divided into significant and suggestive depending on the strength of the statistical association. Using the Disease Association Protein-Protein Link Evaluator tool we found that direct interactions among genetic products were significantly higher than expected by chance when considering both significant regions alone (p<0.0002) and significant plus suggestive (p<0.007). The number of genes involved in the network was 43. Of these, 23 were located within suggestive regions and many of them directly interacted with proteins coded within significant regions. These included genes such as SYK, IL-6, CSF2RB, FCLR3, EIF4EBP2 and CHST12. Using the gene portal BioGPS, we tested the expression of these genes in 24 different tissues and found the highest values among immune-related cells as compared to non-immune tissues (p<0.001). A gene ontology analysis confirmed the immune-related functions of these genes. In conclusion, loci currently suggestive of MS association interact with and have similar expression profiles and function as those significantly associated, highlighting the fact that more common variants remain to be found to be associated to MS.

Show MeSH
Related in: MedlinePlus