Aim 1? ? Much of the effort during the past year focused on statistical genetic analysis in collaborative studies.? ? Familial Idiopathic Scoliosis.? ? Several analyses focusing on candidate regions and phenotypic subsets have been completed and manuscripts have either been submitted or are in preparation. These include:? ? 1) In this study of susceptibility loci in FIS families with at least one individual with a triple curve, candidate regions have been identified on chromosomes 6 and 10 Marosy et al. submitted.? ? 2) Statistical genetic analysis of a replication sample of families with familial idiopathic scoliosis with characteristics nearly identical to those of the sample analyzed in Miller et al. 2005 suggest that of the 11 regions identified in the original study, at least 7 of these regions can be considered to be true replications Behnemann et al. in preparation.? ? 3) A study based on the presence of males with surgery.? ? ? Genetic analysis of drug treatment response in the Sequenced Treatment Alternatives for Depression (STAR*D). ? ? As part of collaborations with investigators from the Southwestern Medical Center (John Rush) and NIMH (Francis McMahon), statistical analyses have focused on several candidate genes. In addition to the 5HTR2A receptor reported in McMahon et al. Am J Hum Genet, 2006 other associations reported include antidepressant treatment and the GRIK4 locus Paddock et al. Am J Psychiatry, 2007, and genetic markers associated with suicidal ideation Laje et al. Am J Psychiatry, 2007.? ? Statistical genetic analysis of the QIDS-C as a quantitative trait is ongoing. Analysis of variance corroborates the association with rs7997012, and to a lesser extent, other SNPs in intron 2 of 5HTR2A, although the locus specific heritability attributable to rs7997012 is estimated to be only .013. A number of other SNPs have non-zero locus-specific heritabilities, but they were not as highly ranked as rs7997012 in the remitter/response analyses. Although highly significant, the proportion of the total variance attributable to rs7997012 is quite small.? ? GeneSTAR? ? The Genetic STudy of Aspirin Responsiveness (GeneSTAR) is a study designed to investigate gene-environment determinants of platelet reactivity in response to low-dose aspirin (ASA) therapy. The families in this study are expansions of the Johns Hopkins Sibling Study families and comprise 1231 Caucasian in 398 families and 846 African American individuals in 243 families. Phenotypes include measurements on 87 agonist-induced platelet function phenotypes before and after a two week trial of aspirin (81mg/day). Genotyping has included the Decode 550 STRP marker set for a linkage screen, a 3000 SNP marker set for a candidate gene linkage and association screen and a high density SNP panel for a Genome Wide Association Study. Publications include the estimation of the heritability of platelet responsiveness to aspirin Faraday et al. 2007, Bray et al. 2007 and the identification of a variant in the platelet endothelial aggregation receptor (PEAR1) Herrera et al. 2008.? ? ? Aim 2? ? Theoretical work during the past year focused on linear regression based tests of associations for quantitative traits and issues related to intra-familial tests of association. The manuscript on the revised Regression of Offspring on Mid-Parent (ROMP_rev) method has been published. Like the original ROMP method, ROMP_rev is a hybrid of the traditional regression of offspring on mid-parent model used to estimate heritability and the ANOVA model used to test for association. ROMP_rev was developed within the context of collapsibility in linear regression models in order to determine the standard error of the difference between two regressions. The ROMP_rev method provides a test of association between a quantitative trait and a marker locus and also provides an estimate of the locus-specific heritability. Unlike the TDT for qualitative traits, ROMP_rev requires phenotype data on parents and offspring, but genotype data for the offspring only. This method was developed for studies where phenotype, but not genotype, data are available for the parents Roy-Gagnon et al., Ann Hum Genet 2008.? ? ? Aim 3? ? Computer simulation has been used in two projects to investigate the statistical properties of the methods involved.? ? 1) Lack of agreement among methods used to test for intra-familial association.? ? In a study of platelet aggregation in the GeneSTAR project, Herrera-Galeano et al. 2007 used several different intra-familial association methods and found little correlation between results. Computer simulation was used to investigate the lack of agreement among methods. The Genetic Analysis Simulation Program G.A.S.P. was used to generate 500 samples, each with 200 nuclear families with sibship size three. A quantitative trait was simulated based on a single biallelic locus with equally frequent alleles. The underlying genetic model was additive and heritabilities considered included 0 (the null hypothesis), .01 and .05. Four tests of association were performed: ASSOC, FBAT, linear regression with GEE (SASGEE) and ROMP. Pair-wise Pearson correlations of resulting p-values and Spearman rank correlations were calculated. McNemar tests using 0.001 as cutoff value were performed to test for significant differences between the results of each pair of methods.? ? When the heritability attributable to the locus was .05 or greater, there was fairly good agreement between SASGEE and ASSOC, somewhat lesser agreement between ROMP and ASSOC, and little agreement between FBAT and ASSOC. The results under the null hypothesis were somewhat correlated for the SASGEE-ASSOC pair, less correlated for the ROMP-ASSOC pair and almost completely uncorrelated for the FBAT-ASSOC pair. Clearly, the kind of information being used by ROMP and FBAT is different than that used by ASSOC and a linear regression with generalized estimating equations. In general, pair-wise Spearman rank correlations were higher than Pearson correlations.? ? 2) Intra-familial tests of association in the present of genetic heterogeneity? ? In this study the statistical power of methods of intra-familial tests of association are compared in the presence of genetic heterogeneity. G.A.S.P. v3.3 was used to simulate two subpopulations. In the first, denoted the association subpopulation, the trait was due to a single causative SNP with equal allele frequencies and additive allelic effects. In the second, the non-association subpopulation, the trait was due to a random effect. The two subpopulations were combined in different proportions (100:0%, 50:50% and 30:70%) for the association:non-association subpopulations. Three study designs were considered: 2000 unrelated individuals, 400 nuclear families with sibship size 3, and 117 extended three generation families, each with 17 individuals. The trait heritability was fixed to be .05. Two thousand replications were generated for each experiment. The power of three intra-familial tests of association (ASSOC, FBAT, ROMP) were compared to an analysis of variance of the unrelated individuals for each combination of the two subpopulations.? ? For combinations of 100:0%, 50:50% and 30:70% the power of ASSOC and ROMP was quite good, with ASSOC performing better than the ANOVA for all combinations. The power for ROMP improved from the nuclear to extended family sample, because each extended family was comprised of four nuclear families, but closely approximated that of the likelihood based ASSOC. When a combination of 10:90% association:non-association subpopulations was considered, ASSOC performed considerably better than the ANOVA of unrelated individuals, which performed better than ROMP, which performed better than FBAT.
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