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Relationships between predicted moonlighting proteins, human diseases, and comorbidities from a network perspective.

Zanzoni A, Chapple CE, Brun C - Front Physiol (2015)

Bottom Line: We found that disease-related genes are over-represented among those candidates.Here, by comparing moonlighting candidates to non-candidates as groups, we further show that (i) they are significantly involved in more than one disease, (ii) they contribute to complex rather than monogenic diseases, (iii) the diseases in which they are involved are phenotypically different according to their annotations, finally, (iv) they are enriched for diseases pairs showing statistically significant comorbidity patterns based on Medicare records.Altogether, our results suggest that some observed comorbidities between phenotypically different diseases could be due to a shared protein involved in unrelated biological processes.

View Article: PubMed Central - PubMed

Affiliation: INSERM, UMR_S1090 TAGC Marseille, France ; Aix-Marseille Université, UMR_S1090, TAGC Marseille, France.

ABSTRACT
Moonlighting proteins are a subset of multifunctional proteins characterized by their multiple, independent, and unrelated biological functions. We recently set up a large-scale identification of moonlighting proteins using a protein-protein interaction (PPI) network approach. We established that 3% of the current human interactome is composed of predicted moonlighting proteins. We found that disease-related genes are over-represented among those candidates. Here, by comparing moonlighting candidates to non-candidates as groups, we further show that (i) they are significantly involved in more than one disease, (ii) they contribute to complex rather than monogenic diseases, (iii) the diseases in which they are involved are phenotypically different according to their annotations, finally, (iv) they are enriched for diseases pairs showing statistically significant comorbidity patterns based on Medicare records. Altogether, our results suggest that some observed comorbidities between phenotypically different diseases could be due to a shared protein involved in unrelated biological processes.

No MeSH data available.


Shared disease phenotypes and pairs among MF-CAN, MCNC, and MONO proteins. (A) Most of the MF-CAN proteins are annotated with OMIM disease annotations also present in the other categories, whereas (B) they are associated with specific combination of diseases.
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Figure 2: Shared disease phenotypes and pairs among MF-CAN, MCNC, and MONO proteins. (A) Most of the MF-CAN proteins are annotated with OMIM disease annotations also present in the other categories, whereas (B) they are associated with specific combination of diseases.

Mentions: We next sought to verify whether MF-CAN, MCNC, and MONO proteins are associated with the same diseases. Figure 2A shows that most of the diseases (89%) in which the MF-CAN are involved, are also associated with at least one protein belonging to one of the other categories (compared to only 34% and 26% for MCNC and MONO, respectively). On the other hand, 86% of the disease pairs associated with MF-CAN are specific to this category (compared to ~68% for the other two categories) (Figure 2B). This, therefore, suggests that our EMF candidates are mainly involved in specific combinations of diseases. Moreover, the fact that diseases associated to MF-CAN are associated with several other genes/proteins as well (Figure 2A) suggests that EMF candidates are implicated in combinations of complex diseases rather than monogenic ones.


Relationships between predicted moonlighting proteins, human diseases, and comorbidities from a network perspective.

Zanzoni A, Chapple CE, Brun C - Front Physiol (2015)

Shared disease phenotypes and pairs among MF-CAN, MCNC, and MONO proteins. (A) Most of the MF-CAN proteins are annotated with OMIM disease annotations also present in the other categories, whereas (B) they are associated with specific combination of diseases.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4477069&req=5

Figure 2: Shared disease phenotypes and pairs among MF-CAN, MCNC, and MONO proteins. (A) Most of the MF-CAN proteins are annotated with OMIM disease annotations also present in the other categories, whereas (B) they are associated with specific combination of diseases.
Mentions: We next sought to verify whether MF-CAN, MCNC, and MONO proteins are associated with the same diseases. Figure 2A shows that most of the diseases (89%) in which the MF-CAN are involved, are also associated with at least one protein belonging to one of the other categories (compared to only 34% and 26% for MCNC and MONO, respectively). On the other hand, 86% of the disease pairs associated with MF-CAN are specific to this category (compared to ~68% for the other two categories) (Figure 2B). This, therefore, suggests that our EMF candidates are mainly involved in specific combinations of diseases. Moreover, the fact that diseases associated to MF-CAN are associated with several other genes/proteins as well (Figure 2A) suggests that EMF candidates are implicated in combinations of complex diseases rather than monogenic ones.

Bottom Line: We found that disease-related genes are over-represented among those candidates.Here, by comparing moonlighting candidates to non-candidates as groups, we further show that (i) they are significantly involved in more than one disease, (ii) they contribute to complex rather than monogenic diseases, (iii) the diseases in which they are involved are phenotypically different according to their annotations, finally, (iv) they are enriched for diseases pairs showing statistically significant comorbidity patterns based on Medicare records.Altogether, our results suggest that some observed comorbidities between phenotypically different diseases could be due to a shared protein involved in unrelated biological processes.

View Article: PubMed Central - PubMed

Affiliation: INSERM, UMR_S1090 TAGC Marseille, France ; Aix-Marseille Université, UMR_S1090, TAGC Marseille, France.

ABSTRACT
Moonlighting proteins are a subset of multifunctional proteins characterized by their multiple, independent, and unrelated biological functions. We recently set up a large-scale identification of moonlighting proteins using a protein-protein interaction (PPI) network approach. We established that 3% of the current human interactome is composed of predicted moonlighting proteins. We found that disease-related genes are over-represented among those candidates. Here, by comparing moonlighting candidates to non-candidates as groups, we further show that (i) they are significantly involved in more than one disease, (ii) they contribute to complex rather than monogenic diseases, (iii) the diseases in which they are involved are phenotypically different according to their annotations, finally, (iv) they are enriched for diseases pairs showing statistically significant comorbidity patterns based on Medicare records. Altogether, our results suggest that some observed comorbidities between phenotypically different diseases could be due to a shared protein involved in unrelated biological processes.

No MeSH data available.