1. Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease
- Author
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Keller, M. F., Saad, M., Bras, J., Bettella, F., Nicolaou, N., Simon-Sanchez, J., Mittag, F., Buchel, 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., Stefansson, H., Majamaa, K., Morris, H. R., Williams, N., Gasser, T., Heutink, P., Wood, N. W., Hardy, J., Martinez, M., Jankowski, Janusz, Nalls, M. A., Singleton, A. B., Keller, M. F., Saad, M., Bras, J., Bettella, F., Nicolaou, N., Simon-Sanchez, J., Mittag, F., Buchel, 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., Stefansson, H., Majamaa, K., Morris, H. R., Williams, N., Gasser, T., Heutink, P., Wood, N. W., Hardy, J., Martinez, M., Jankowski, Janusz, Nalls, M. A., and Singleton, A. B.
- Abstract
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
- 2012