Using genome-Wwide complex trait analysis to quantify 'missing heritability' in Parkinson's disease

Keller, M. F., Saad, M., Bras, J., Bettella, F., Nicolaou, N., Simón-Sánchez, J., Mittag, F., Büchel, F., Sharma, M., Gibbs, J. R., Schulte, C., Moskvina, V., Durr, A., Holmans, P., Kilarski, L. L., Guerreiro, R., Hernandez, D. G., Brice, A., Ylikotila, P., Stefánsson, H., Majamaa, K., Morris, H. R., Williams, N., Gasser, T., Heutink, P., Wood, N. W., Hardy, J., Martinez, M., Singleton, A. B., Nalls, M. A., Plagnol, V., Sheerin, U. M., Lesage, S., Sveinbjörnsdóttir, S., Arepalli, S., Barker, R., Ben-Shlomo, Y., Berendse, H. W., Berg, D., Bhatia, K., de Bie, R. M. A., Biffi, A., Bloem, B., Bochdanovits, Z., Bonin, M., Brockmann, K., Brooks, J., Burn, D. J., Charlesworth, G., Chen, H., Chinnery, P. F., Chong, S., Clarke, C. E., Cookson, M. R., Cooper, J. M., Corvol, J. C., Counsell, C., Damier, P., Dartigues, J. F., Deloukas, P., Deuschl, G., Dexter, D. T., van Dijk, K. D., Dillman, A., Durif, F., Dürr, A., Edkins, S., Evans, J. R., Foltynie, T., Gao, J., Gardner, M., Goate, A., Gray, E., Gústafsson, Ó, Harris, C., van Hilten, J. J., Hofman, A., Hollenbeck, A., Holton, J., Hu, M., Huang, X., Huber, H., Hudson, G., Hunt, S. E., Huttenlocher, J., Illig, T., Jónsson, P. V., Lambert, J. C., Langford, C., Lees, A., Lichtner, P., Limousin, P., Lopez, G., Lorenz, D., McNeill, A., Moorby, C., Moore, M., Morrison, K. E., Mudanohwo, E., O'Sullivan, S. S., Pearson, J., Perlmutter, J. S., Pétursson, H., Pollak, P., Post, B., Potter, S. C., Ravina, B., Revesz, T., Riess, O., Rivadeneira, F., Rizzu, P., Ryten, M., Sawcer, S. J., Schapira, A., Scheffer, H., Shaw, K., Shoulson, I., Sidransky, E., Smith, C., Spencer, C. C. A., Steinberg, S., Stockton, J. D., Strange, A., Talbot, K., Tanner, C. M., Tashakkori-Ghanbaria, A., Tison, F., Trabzuni, D., Traynor, B. J., Uitterlinden, A. G., Velseboer, D., Vidailhet, M., Walker, R., van de Warrenburg, B., Wickremaratchi, M., Williams-Gray, C. H., Winder-Rhodes, S., Stefánsson, K., Donnelly, P., Barroso, I., Blackwell, J. M., Bramon, E., Brown, M. A., Casas, J. P., Corvin, A., Duncanson, A., Jankowski, J., Markus, H. S., Mathew, C. G., Palmer, C. N. A., Plomin, R., Rautanen, A., Trembath, R. C., Viswanathan, A. C., Band, G., Bellenguez, C., Freeman, C., Hellenthal, G., Giannoulatou, E., Pirinen, M., Pearson, R., Su, Z., Vukcevic, D., Gwilliam, R., Blackburn, H., Bumpstead, S. J., Dronov, S., Gillman, M., Hammond, N., Jayakumar, A., McCann, O. T., Liddle, J., Ravindrarajah, R., Ricketts, M., Waller, M., Weston, P., Widaa, S., Whittaker, P., & McCarthy, M. I. (2012) Using genome-Wwide complex trait analysis to quantify 'missing heritability' in Parkinson's disease. Human Molecular Genetics, 21(22), pp. 4996-5009.

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Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered. © Published by Oxford University Press 2012.

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ID Code: 89333
Item Type: Journal Article
Refereed: Yes
Additional Information: Cited By :34 Export Date: 21 September 2015 CODEN: HMGEE Correspondence Address: Nalls, M.A.; Molecular Genetics Section, Laboratory of Neurogenetics, NIA, NIH Building 35, 35 Convent Drive, Bethesda, MD 20892, United States; email:
Keywords: adult, article, case control study, cohort analysis, controlled study, disease course, European American, gene locus, genetic association, genetic trait, genome analysis, genome wide complex trait analysis, heritability, human, major clinical study, mathematical model, meta analysis (topic), Parkinson disease, phenotypic variation, priority journal, single nucleotide polymorphism, statistical analysis, Aged, Aged, 80 and over, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Male, Middle Aged, Multifactorial Inheritance, Quantitative Trait, Heritable
DOI: 10.1093/hmg/dds335
ISSN: 0964-6906
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Deposited On: 21 Oct 2015 00:16
Last Modified: 24 Feb 2016 02:48

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