Translating Mendelian and complex inheritance of Alzheimer's disease genes for predicting unique personal genome variants

Journal of the American Medical Informatics Association

Volumn 19, Issue 2, 2012, Pages 306-316

  Regan, Kelly ^a,b,c   Wang, Kanix ^d   Doughty, Emily ^e   Li, Haiquan ^a,b,c   Li, Jianrong ^a,b,c   Lee, Younghee ^c   Kann, Maricel G ^e   Lussier, Yves A ^a,b,c,d  

^a UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

^b University of Illinois at Chicago   (United States)

^c UNIVERSITY OF CHICAGO   (United States)

^d UNIVERSITY OF CHICAGO   (United States)

^e UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMYLOID BETA PROTEIN; APOLIPOPROTEIN E; EPHRIN RECEPTOR A1;

ALZHEIMER DISEASE; ARTICLE; GENETIC ASSOCIATION; GENETIC VARIABILITY; GENOME; HUMAN; INHERITANCE; PHENOTYPE; PROTEIN PROTEIN INTERACTION; SINGLE NUCLEOTIDE POLYMORPHISM;

ALZHEIMER DISEASE; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; HEREDITY; HUMANS; INHERITANCE PATTERNS; MULTIFACTORIAL INHERITANCE; POLYMORPHISM, GENETIC; PROTEIN INTERACTION MAPS;

EID: 84863166280     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1136/amiajnl-2011-000656     Document Type: Article

References (58)

1. Holtzman DM, Morris JC, Goate AM. Alzheimer's disease: the challenge of the second century. Sci Transl Med 2011;3:77sr1.
2. Hollingworth P, Harold D, Sims R, et al. Common variants at ABCA7, MS4A6A/ MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease. Nat Genet 2011;43:429-35.
3. Bizzarro A, Seripa D, Acciarri A, et al. The complex interaction between APOE promoter and AD: an Italian case-control study. Eur J Hum Genet 2009;17:938-45.
4. Coon KD, Myers AJ, Craig DW, et al. A high-density whole-genome association study reveals that APOE is the major susceptibility gene for sporadic late-onset Alzheimer's disease. J Clin Psychiatry 2007;68:613-18.
5. Farrer LA, Cupples LA, Haines JL, et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A metaanalysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA 1997;278:1349-56.
6. Nussbaum RL, Mcinnes RR, Willard HF. Genetics of common disorders with complex inheritance. 7th edn. Philadelphia, PA: Saunders Elsevier, 2007:151-74.
7. St George-Hyslop PH, Petit A. Molecular biology and genetics of Alzheimer's disease. C R Biol 2005;328:119-30.
8. Zawia NH, Basha MR. Environmental risk factors and the developmental basis for Alzheimer's disease. Rev Neurosci 2005;16:325-37.
9. Ashley EA, Butte AJ, Wheeler WT, et al. Clinical assessment incorporating a personal genome. Lancet 2010;375:1525-35.
10. Van Den Heuvel C, Thorton E, Vink R. Traumatic brain injury and Alzheimer's disease: a review. Prog Brain Res 2007;161:303-16.
11. Francesconi M, Jeller R, Lehner B. Integrated genome-scale prediction of detrimental mutations in transcription networks. PLoS Genet 2011;7:e1002077.
12. Lage K, Karlberg EO, Størling ZM, et al. A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat Biotechnol 2007;25:309-16.
13. Lee Y, Li J, Gamazon E, et al. Biomolecular systems of disease buried across multiple GWAS unveiled by information theory and ontology. AMIA Summits Transl Sci Proc 2010;2010:31-5.
14. Chen J, Sam L, Huang Y, et al. Protein interaction network underpins concordant prognosis among heterogeneous breast cancer signatures. J Biomed Inform 2010;43:385-96.
15. Sam L, Liu Y, Li J, et al. Discovery of protein interaction networks shared by diseases. Pacific Symposium on Biocomputing, Hawaii, USA: World Scientific, 2007:76-87.
16. Zhong Q, Simonis N, Li QR, et al. Edgetic perturbations of human disease. Mol Syst Biol 2009;5:321.
17. Sarkar IN. A vector space model-based approach to identify genetically similar diseases. J Am Med Inform Assoc. In press.
18. Li H, Lee Y, Chen J, et al. Complex disease networks of trait-associated SNPs unveiled by information theory. JAMIA to appear.
19. Dickson SP, Wang K, Krantz I, et al. Rare variants create synthetic genome-wide associations. PLoS Biol 2010;8:e1000294.
20. Xu T, Du L, Zhou Y. Evaluation of GO-based functional similarity measures using S. cerevisiae protein interaction and expression profile data. BMC Bioinformatics 2008;9:472.
21. Barrenas F, Chavali S, Holme P, et al. Network properties of complex human disease genes identified through genome-wide association studies. PLoS One 2009;4:e8090.
22. Lee JH, Gonzalez GH. Towards integrative gene prioritization in Alzheimer's disease. Pacific Symposium on Biocomputing, Hawaii, USA: World Scientific, 2011:4-13.
23. Tao Y, Sam L, Li J, et al. Information theory applied to the sparse gene ontology annotations network to predict novel gene function. Bioinformatics 2007;23:i529-38.
24. Hindorff LA, Sethupathy P, Junkins HA, et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A 2009;106:9362-7.
25. Jensen LJ, Kuhn M, Stark M, et al. STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 2009;37:D412-16.
26. Naj AC, Jun G, Beecham GW, et al. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease. Nat Genet 2011;43:436-41.
27. Harold D, Abraham R, Hollingworth P, et al. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease. Nat Genet 2009;41:1088-93.
28. Lambert JC, Heath S, Even G, et al. Genome-wide association study identifies variants at CLU and CRI associated with Alzheimer's disease. Nat Genet 2009;41:1094-9.
29. Reiman EM, Webster JA, Myers AJ, et al. GAB2 alleles modify Alzheimer's risk in APOE epsilon4 carriers. Neuron 2007;54:713-20.
30. Petersen RC, Aisen PS, Beckett LA, et al. Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology 2010;74:201-9.
31. Lee Y, Yang X, Huang Y, et al. Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis. PLoS Comput Biol 2010;6:e1000730.
32. Falcon S, Gentleman R. Using GOstats to test gene lists for GO term association. Bioinformatics 2007;23:257-8.
33. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Statistical Society, Ser B 1995;57:289-300.
34. Yang X, Li J, Lee Y, et al. GO-Module: functional synthesis and improved interpretation of Gene Ontology patterns. Bioinformatics 2011;27:1444-6.
35. Pesquita C, Faria D, Falcao AO, et al. Semantic similarity in biomedical ontologies. PLoS Comput Biol 2009;5:e1000443.
36. Finn RD, Tate J, Mistry J, et al. The Pfam protein families database. Nucleic Acids Res 2008;36:D281-8.
37. Eddy SR. Hidden Markov models. Curr Opin Struct Biol 1996;6:361-5.
38. Peterson TA, Adadey A, Santana-Cruz I, et al. DMDM: domain mapping of disease mutations. Bioinformatics 2010;26:2458-9.
39. Raghavachari B, Tasneem A, Przytycka TM, et al. DOMINE: a database of protein domain interactions. Nucleic Acids Res 2008;36:D656-61.
40. Sprinzak E, Margalit H. Correlated sequence-signatures as markers of proteinprotein interaction. J Mol Biol 2001;311:681-92.
41. Deng M, Mehta S, Sun F, et al. Inferring domain-domain interactions from proteinprotein interactions. Genome Res 2002;12:1540-8.
42. Nye TM, Berzuini C, Gilks WR, et al. Statistical analysis of domains in interacting protein pairs. Bioinformatics 2005;21:993-1001.
43. Guimaraes KS, Jothi R, Zotenko E, et al. Predicting domain-domain interactions using a parsimony approach. Genome Biol 2006;7:R104.
44. Riley R, Lee C, Sabatti C, et al. Inferring protein domain interactions from databases of interacting proteins. Genome Biol 2005;6:R89.
45. Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003;11:2498-504.
46. Chen JL, Li J, Stadler WM, et al. Protein-network modeling of prostate cancer gene signatures reveals essential pathways in disease recurrence. J Am Med Inform Assoc 2011;18:392-402.
47. Yu H, Kim PM, Sprecher E, et al. The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput Biol 2007;3:e59.
48. Barabási AL, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet 2011;12:56-68.
49. Shi G, Boerwinkle E, Morrison AC, et al. Mining gold dust under the genome wide significance level: a two-stage approach to analysis of GWAS. Genet Epidemiol 2011;35:111-18.
50. Province MA, Borecki IB. Gathering the gold dust: methods for assessing the aggregate impact of small effect genes in genomic scans. Pacific Symposium on Biocomputing, Hawaii, USA: World Scientific, 2008:190-200.
51. Ge D, Ruzzo EK, Shianna KV, et al. SVA: software for annotating and visualizing sequenced human genomes. Bioinformatics 2011;27:1998-2000.
52. Lussier YA, Chen JL. The emergence of genome-based drug repositioning. Sci Transl Med 2011;3:96ps35.
53. Cacabelos R. Pharmacogenomics in Alzheimer's disease. Methods Mol Biol 2008;448:213-357.
54. Yildirim MA, Goh KI, Cusick ME, et al. Drug-target network. Nat Biotechnol 2007;25:1119-26.
55. Hansen NT, Brunak S, Altman RB. Generating genome-scale candidate gene lists for pharmacogenomics. Clin Pharmacol Ther 2009;86:183-9.
56. Gottlieb A, Stein GY, Ruppin E, et al. PREDICT: a method for inferring novel drug indications with application to personalized medicine. Mol Syst Biol 2011;7:496.
57. Sirota M, Dudley JT, Kim J, et al. Discovery and preclinical validation of drug indications using compendia of public gene expression data. Sci Transl Med 2011;3:96ra77.
58. Lamb J, Crawford ED, Peck D, et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 2006;313:1929-35.