Discovering Disease-disease Associations by Fusing Systems-level Molecular Data

Overview

Journal Sci Rep

Specialty Science

Date 2013 Nov 16

PMID 24232732

Citations 52

Authors

Marinka Zitnik

Vuk Janjic

Chris Larminie

Blaz Zupan

Natasa Przulj

Affiliations

Soon will be listed here.

Abstract

The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on evidence from fusing all available molecular interaction and ontology data. We propose a multi-level hierarchy of disease classes that significantly overlaps with existing disease classification. In it, we find 14 disease-disease associations currently not present in Disease Ontology and provide evidence for their relationships through comorbidity data and literature curation. Interestingly, even though the number of known human genetic interactions is currently very small, we find they are the most important predictor of a link between diseases. Finally, we show that omission of any one of the included data sources reduces prediction quality, further highlighting the importance in the paradigm shift towards systems-level data fusion.

Citing Articles

KGRDR: a deep learning model based on knowledge graph and graph regularized integration for drug repositioning.

Luo H, Yang H, Zhang G, Wang J, Luo J, Yan C Front Pharmacol. 2025; 16:1525029.

PMID: 40008124 PMC: 11850324. DOI: 10.3389/fphar.2025.1525029.

A Multi-Dimensional Approach to Map Disease Relationships Challenges Classical Disease Views.

Mobus L, Serra A, Fratello M, Pavel A, Federico A, Greco D Adv Sci (Weinh). 2024; 11(30):e2401754.

PMID: 38840452 PMC: 11321629. DOI: 10.1002/advs.202401754.

DapBCH: a disease association prediction model Based on Cross-species and Heterogeneous graph embedding.

Shi W, Feng H, Li J, Liu T, Liu Z Front Genet. 2023; 14:1222346.

PMID: 37811150 PMC: 10556742. DOI: 10.3389/fgene.2023.1222346.

Re-Addressing Dementia by Network Medicine and Mechanism-Based Molecular Endotypes.

Pacheco Pachado M, Casas A, Elbatreek M, Nogales C, Guney E, Espay A J Alzheimers Dis. 2023; 96(1):47-56.

PMID: 37742653 PMC: 10657714. DOI: 10.3233/JAD-230694.

Discovering disease-disease associations using electronic health records in The Guideline Advantage (TGA) dataset.

Guo A, Khan Y, Langabeer 2nd J, Foraker R Sci Rep. 2021; 11(1):20969.

PMID: 34697328 PMC: 8547216. DOI: 10.1038/s41598-021-00345-z.

References

Osborne J, Flatow J, Holko M, Lin S, Kibbe W, Zhu L . Annotating the human genome with Disease Ontology. BMC Genomics. 2009; 10 Suppl 1:S6. PMC: 2709267. DOI: 10.1186/1471-2164-10-S1-S6. View

Brunet J, Tamayo P, Golub T, Mesirov J . Metagenes and molecular pattern discovery using matrix factorization. Proc Natl Acad Sci U S A. 2004; 101(12):4164-9. PMC: 384712. DOI: 10.1073/pnas.0308531101. View

Kim P, Tidor B . Subsystem identification through dimensionality reduction of large-scale gene expression data. Genome Res. 2003; 13(7):1706-18. PMC: 403744. DOI: 10.1101/gr.903503. View

Seal R, Gordon S, Lush M, Wright M, Bruford E . genenames.org: the HGNC resources in 2011. Nucleic Acids Res. 2010; 39(Database issue):D514-9. PMC: 3013772. DOI: 10.1093/nar/gkq892. View

Prieto C, Risueno A, Fontanillo C, De Las Rivas J . Human gene coexpression landscape: confident network derived from tissue transcriptomic profiles. PLoS One. 2008; 3(12):e3911. PMC: 2597745. DOI: 10.1371/journal.pone.0003911. View

Stark C, Breitkreutz B, Chatr-Aryamontri A, Boucher L, Oughtred R, Livstone M . The BioGRID Interaction Database: 2011 update. Nucleic Acids Res. 2010; 39(Database issue):D698-704. PMC: 3013707. DOI: 10.1093/nar/gkq1116. View

Clayton P, Verrips A, Sistermans E, Mann A, Mieli-Vergani G, Wevers R . Mutations in the sterol 27-hydroxylase gene (CYP27A) cause hepatitis of infancy as well as cerebrotendinous xanthomatosis. J Inherit Metab Dis. 2003; 25(6):501-13. DOI: 10.1023/a:1021211520034. View

Goh K, Cusick M, Valle D, Childs B, Vidal M, Barabasi A . The human disease network. Proc Natl Acad Sci U S A. 2007; 104(21):8685-90. PMC: 1885563. DOI: 10.1073/pnas.0701361104. View

Loscalzo J, Kohane I, Barabasi A . Human disease classification in the postgenomic era: a complex systems approach to human pathobiology. Mol Syst Biol. 2007; 3:124. PMC: 1948102. DOI: 10.1038/msb4100163. View

10.

Lee D, Park J, Kay K, Christakis N, Oltvai Z, Barabasi A . The implications of human metabolic network topology for disease comorbidity. Proc Natl Acad Sci U S A. 2008; 105(29):9880-5. PMC: 2481357. DOI: 10.1073/pnas.0802208105. View

11.

Howell D, Bergsagel J, Chu R, Meacham L . Suppression of Hodgkin's disease in a patient with Cushing's syndrome. J Pediatr Hematol Oncol. 2004; 26(5):301-3. DOI: 10.1097/00043426-200405000-00008. View

12.

Valiyil R, Christopher-Stine L . Drug-related myopathies of which the clinician should be aware. Curr Rheumatol Rep. 2010; 12(3):213-20. PMC: 3092639. DOI: 10.1007/s11926-010-0104-3. View

13.

Dagli A, Buiting K, Williams C . Molecular and Clinical Aspects of Angelman Syndrome. Mol Syndromol. 2012; 2(3-5):100-112. PMC: 3366701. DOI: 10.1159/000328837. View

14.

Holst F, Hemmer C, Foth C, Seitz R, Egbring R, Dietrich M . Low levels of fibrin-stabilizing factor (factor XIII) in human Plasmodium falciparum malaria: correlation with clinical severity. Am J Trop Med Hyg. 1999; 60(1):99-104. DOI: 10.4269/ajtmh.1999.60.99. View

15.

Su T, Wu L, Lin C . The prevalence of dementia and depression in Taiwanese institutionalized leprosy patients, and the effectiveness evaluation of reminiscence therapy--a longitudinal, single-blind, randomized control study. Int J Geriatr Psychiatry. 2011; 27(2):187-96. DOI: 10.1002/gps.2707. View

16.

Schriml L, Arze C, Nadendla S, Chang Y, Mazaitis M, Felix V . Disease Ontology: a backbone for disease semantic integration. Nucleic Acids Res. 2011; 40(Database issue):D940-6. PMC: 3245088. DOI: 10.1093/nar/gkr972. View

17.

von Vietinghoff S, Schneider W, Luft F, Kettritz R . Crescentic glomerulonephritis and malignancy--guilty or guilt by association?. Nephrol Dial Transplant. 2006; 21(11):3324-6. DOI: 10.1093/ndt/gfl456. View

18.

Nelson S, Schopen M, Savage A, Schulman J, Arluk N . The MeSH translation maintenance system: structure, interface design, and implementation. Stud Health Technol Inform. 2004; 107(Pt 1):67-9. View

19.

Aerts S, Lambrechts D, Maity S, Van Loo P, Coessens B, De Smet F . Gene prioritization through genomic data fusion. Nat Biotechnol. 2006; 24(5):537-44. DOI: 10.1038/nbt1203. View

20.

van Vliet M, Horlings H, van de Vijver M, Reinders M, Wessels L . Integration of clinical and gene expression data has a synergetic effect on predicting breast cancer outcome. PLoS One. 2012; 7(7):e40358. PMC: 3394805. DOI: 10.1371/journal.pone.0040358. View