Abstract
For genome-wide association studies, it has been increasingly recognized that the popular locus-by-locus search for DNA variants associated with disease susceptibility may not be effective, especially when there are interactions between or among multiple loci, for which a multi-loci search strategy may be more productive. However, even if computationally feasible, a genome-wide search over all possible multiple loci requires exploring a huge model space and making costly adjustment for multiple testing, leading to reduced statistical power. On the other hand, there are accumulating data suggesting that protein products of many disease-causing genes tend to interact with each other, or cluster in the same biological pathway. To incorporate this prior knowledge and existing data on gene networks, we propose a gene network-based method to improve statistical power over that of the exhaustive search by giving higher weights to models involving genes nearby in a network. We use simulated data under realistic scenarios, including a large-scale human protein–protein interaction network and 23 known ataxia-causing genes, to demonstrate potential gain by our proposed method when disease-genes are clustered in a network.
Similar content being viewed by others
References
Alfarano C, Andrade CE, Anthony K, Bahroos N, Bajec M, Bantoft K, Betel D, Bobechko B, Boutilier K, Burgess E, Buzadzija K, Cavero R, D’Abreo C, Donaldson I, Dorairajoo D, Dumontier MJ, Dumontier MR, Earles V, Farrall R, Feldman H et al (2005) The biomolecular interaction network database and related tools 2005 update. Nucleic Acids Res 33:D418–D424
Barabasi AL, Oltvai ZN (2004) Network biology: understanding the cell’s functional organization. Nat Rev Genet 5:101–113
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 57:289–300
Chuang H-Y, Lee E, Liu Y-T, Lee D, Ideker T (2007) Network-based classification of breast cancer metastasis. Mol Syst Biol 3:140
Cui Q, Ma Y, Jaramillo M, Bari H, Awan A, Yang S, Zhang S, Liu L, Lu M, O’Connor-McCourt M, Purisima E, Wang E (2007) A map of human cancer signaling. Mol Syst Biol 3:152
Di Pietro SM, Dell’Angelica EC (2005) The cell biology of Hermansky-Pudlak syndrome: recent advances. Traffic 6:525–533
Dinu D, Miller P, Zhao H (2007) Evidence for association between multiple complement pathway genes and AMD. Genet Epidemiol 31:224–237
Frayling TM et al (2007) A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316:889–894
Gandhi TKB, Zhong J, Mathivanan S, Karthick L, Chandrika KN, Mohan SS, Sharma S, Pinkert S, Nagaraju S, Periaswamy B, Mishra G, Nandakumar K, Shen B, Deshpande N, Nayak R, Sarker M, Boeke JD, Parmigiani G, Schultz J, Bader JS, Pandey A (2006) Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets. Nat Genet 38:285–293
Genovese CR, Roeder K, Wasserman L (2006) False discovery control with p-value weighting. Biometrika 93:509–524
Ideker T, Sharan R (2008) Protein networks in disease. Genome Res 18:644–652
Ionita-Laza I, McQueen MB, Laird NM, Lange C (2007) Genomewide weighted hypothesis testing in family-based association studies, with an application to a 100K scan. Am J Hum Genet 81:607–614
Joshi-Tope G, Gillespie M, Vastrik I, D’Eustachio P, Schmidt E, de Bono B, Jassal B, Gopinath GR, Wu GR, Matthews L, Lewis S, Birney E, Stein L (2005) Reactome: a knowledgebase of biological pathways. Nucleic Acids Res 33:D428–D432
Lim J, Hao T, Shaw C, Patel AJ, Szabo G, Rual J-F, Fisk CJ, Li N, Smolyar A, Hill DE, Barabasi A-L, Vidal M, Zoghbi HY (2006) A protein-protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration. Cell 125:801–814
Lin J, Gan CM, Zhang X, Jones S, Sjoblom T, Wood LD, Parsons DW, Papadopoulos N, Kinzler KW, Vogelstein B, Parmigiani G, Velculescu VE (2007) A multidimensional analysis of genes mutated in breast and colorectal cancers. Genome Res. 17:1304–1318
Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN (2003) Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet 33:177–182
Mace G, Bogliolo M, Guervilly JH, Dugas du Villard JA, Rosselli F (2005) 3R coordination by Fanconi anemia proteins. Biochimie 87:647–658
Marchini J, Donnelly P, Cardon LR (2005) Genome-wide strategies for detecting multiple loci that influence complex diseases. Nat Genet 37:413–417
Oti M, Snel B, Huynen MA, Brunner HG (2006) Predicting disease genes using protein-protein interactions. J Med Genet 43:691–698
Peri S, Navarro JD, Amanchy R, Kristiansen TZ, Jonnalagadda CK, Surendranath V, Niranjan V, Muthusamy B, Gandhi TK, Gronborg M, Ibarrola N, Deshpande N, Shanker K, Shivashankar HN, Rashmi BP, Ramya MA, Zhao Z, Chandrika KN, Padma N, Harsha HC et al (2003) Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res 13:2363–2371
Ramani AK, Bunescu RC, Mooney RJ, Marcotte EM (2005) Consolidating the set of known human protein-protein interactions in preparation for large-scale mapping of the human interactome. Genome Biol 6:R40
Roeder K, Bacanu SA, Sonpar V, Zhang X, Devlin B (2005) Analysis of single-locus tests to detect gene/disease associations. Genet Epidemiol 28:207–219
Roeder K, Bacanu SA, Wasserman L, Devlin B (2006) Using linkage genome scans to improve power of association in genome scans. Am J Hum Genet 78:243–252
Roeder K, Devlin B, Wasserman L (2007) Improving power in genome-wide association studies: weights tip the scale. Genet Epidemiol 31:741–747
Rual JF, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N, Berriz GF, Gibbons FD, Dreze M, Ayivi-Guedehoussou N, Klitgord N, Simon C, Boxem M, Milstein S, Rosenberg J, Goldberg DS, Zhang LV, Wong SL, Franklin G, Li S et al (2005) Towards a proteome-scale map of the human protein-protein interaction network. Nature 437:1173–1178
Stelzl U, Worm U, Lalowski M, Haenig C, Brembeck FH, Goehler H, Stroedicke M, Zenkner M, Schoenherr A, Koeppen S, Timm J, Mintzlaff S, Abraham C, Bock N, Kietzmann S, Goedde A, Toksoz E, Droege A, Krobitsch S, Korn B et al (2005) A human protein-protein interaction network: a resource for annotating the proteome. Cell 122:957–968
Wang K, Li M, Bucan M (2007) Pathway-based approaches for analysis of genomewide association studies. Am J Hum Genet 81:1278–1283
Wood LD, Parsons DW, Jones S, Lin J, Sjoblom T, Leary RJ et al (2007) The genomic landscapes of human breast and colorectal cancers. Science 318:1108–1113
Acknowledgments
This research was partially supported by NIH grants GM081535 and HL65462. The author is grateful to Dr. Trey Ideker for providing the PPI network data, and thanks two reviewers for helpful comments.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Pan, W. Network-based model weighting to detect multiple loci influencing complex diseases. Hum Genet 124, 225–234 (2008). https://doi.org/10.1007/s00439-008-0545-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00439-008-0545-1