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Menche J, Sharma A, Kitsak M, Ghiassian SD, Vidal M, Loscalzo J, Barabási AL. Disease networks. Uncovering disease-disease relationships through the incomplete interactome. Science 2015; 347:1257601. [PMID: 25700523 PMCID: PMC4435741 DOI: 10.1126/science.1257601] [Citation(s) in RCA: 858] [Impact Index Per Article: 95.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes.
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Affiliation(s)
- Jörg Menche
- Center for Complex Networks Research and Department of Physics, Northeastern University, 110 Forsyth Street, 111 Dana Research Center, Boston, MA 02115, USA. Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA. Center for Network Science, Central European University, Nador u. 9, 1051 Budapest, Hungary
| | - Amitabh Sharma
- Center for Complex Networks Research and Department of Physics, Northeastern University, 110 Forsyth Street, 111 Dana Research Center, Boston, MA 02115, USA. Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Maksim Kitsak
- Center for Complex Networks Research and Department of Physics, Northeastern University, 110 Forsyth Street, 111 Dana Research Center, Boston, MA 02115, USA. Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Susan Dina Ghiassian
- Center for Complex Networks Research and Department of Physics, Northeastern University, 110 Forsyth Street, 111 Dana Research Center, Boston, MA 02115, USA. Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA
| | - Marc Vidal
- Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA. Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Joseph Loscalzo
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA
| | - Albert-László Barabási
- Center for Complex Networks Research and Department of Physics, Northeastern University, 110 Forsyth Street, 111 Dana Research Center, Boston, MA 02115, USA. Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA. Center for Network Science, Central European University, Nador u. 9, 1051 Budapest, Hungary. Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA.
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Comparative studies of vertebrate lipoprotein lipase: a key enzyme of very low density lipoprotein metabolism. COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY D-GENOMICS & PROTEOMICS 2011; 6:224-34. [PMID: 21561822 DOI: 10.1016/j.cbd.2011.04.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2010] [Revised: 04/13/2011] [Accepted: 04/18/2011] [Indexed: 11/24/2022]
Abstract
Lipoprotein lipase (LIPL or LPL; E.C.3.1.1.34) serves a dual function as a triglyceride lipase of circulating chylomicrons and very-low-density lipoproteins (VLDL) and facilitates receptor-mediated lipoprotein uptake into heart, muscle and adipose tissue. Comparative LPL amino acid sequences and protein structures and LPL gene locations were examined using data from several vertebrate genome projects. Mammalian LPL genes usually contained 9 coding exons on the positive strand. Vertebrate LPL sequences shared 58-99% identity as compared with 33-49% sequence identities with other vascular triglyceride lipases, hepatic lipase (HL) and endothelial lipase (EL). Two human LPL N-glycosylation sites were conserved among seven predicted sites for the vertebrate LPL sequences examined. Sequence alignments, key amino acid residues and conserved predicted secondary and tertiary structures were also studied. A CpG island was identified within the 5'-untranslated region of the human LPL gene which may contribute to the higher than average (×4.5 times) level of expression reported. Phylogenetic analyses examined the relationships and potential evolutionary origins of vertebrate lipase genes, LPL, LIPG (encoding EL) and LIPC (encoding HL) which suggested that these have been derived from gene duplication events of an ancestral neutral lipase gene, prior to the appearance of fish during vertebrate evolution. Comparative divergence rates for these vertebrate sequences indicated that LPL is evolving more slowly (2-3 times) than for LIPC and LIPG genes and proteins.
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