Validation in genetic association studies

Risk estimation and risk prediction using machine-learning methods

After an association between genetic variants and a phenotype has been established, further study goals comprise the classification of patients according to disease risk or the estimation of disease probability. To accomplish this, different statistical methods are required, and specifically machine-learning approaches may offer advantages over classical techniques. In this paper, we describe methods for the construction and evaluation of classification and probability estimation rules. We review the use of machine-learning approaches in this context and explain some of the machine-learning algorithms in detail. Finally, we illustrate the methodology through application to a genome-wide association analysis on rheumatoid arthritis.

Association genetics in Corymbia citriodora subsp. variegata identifies single nucleotide polymorphisms affecting wood growth and cellulosic pulp yield

Wood is an important biological resource which contributes to nutrient and hydrology cycles through ecosystems, and provides structural support at the plant level. Thousands of genes are involved in wood development, yet their effects on phenotype are not well understood. We have exploited the low genomic linkage disequilibrium (LD) and abundant phenotypic variation of forest trees to explore allelic diversity underlying wood traits in an association study. Candidate gene allelic diversity was modelled against quantitative variation to identify SNPs influencing wood properties, growth and disease resistance across three populations of Corymbia citriodora subsp. variegata, a forest tree of eastern Australia. Nine single nucleotide polymorphism (SNP) associations from six genes were identified in a discovery population (833 individuals). Associations were subsequently tested in two smaller populations (130-160 individuals), 'validating' our findings in three cases for actin 7 (ACT7) and COP1 interacting protein 7 (CIP7). The results imply a functional role for these genes in mediating wood chemical composition and growth, respectively. A flip in the effect of ACT7 on pulp yield between populations suggests gene by environment interactions are at play. Existing evidence of gene function lends strength to the observed associations, and in the case of CIP7 supports a role in cortical photosynthesis.

Non-replication study of a genome-wide association study for hypertension and blood pressure in African Americans

Background

A recent genome wide association study in 1017 African Americans identified several single nucleotide polymorphisms that reached genome-wide significance for systolic blood pressure. We attempted to replicate these findings in an independent sample of 2474 unrelated African Americans in the Milwaukee metropolitan area; 53% were women and 47% were hypertensives.

Methods

We evaluated sixteen top associated SNPs from the above genome wide association study for hypertension as a binary trait or blood pressure as a continuous trait. In addition, we evaluated eight single nucleotide polymorphisms located in two genes (STK-39 and CDH-13) found to be associated with systolic and diastolic blood pressures by other genome wide association studies in European and Amish populations. TaqMan MGB-based chemistry with fluorescent probes was used for genotyping. We had an adequate sample size (80% power) to detect an effect size of 1.2-2.0 for all the single nucleotide polymorphisms for hypertension as a binary trait, and 1% variance in blood pressure as a continuous trait. Quantitative trait analyses were performed both by excluding and also by including subjects on anti-hypertensive therapy (after adjustments were made for anti-hypertensive medications).

Results

For all 24 SNPs, no statistically significant differences were noted in the minor allele frequencies between cases and controls. One SNP (rs2146204) showed borderline association (p = 0.006) with hypertension status using recessive model and systolic blood pressure (p = 0.02), but was not significant after adjusting for multiple comparisons. In quantitative trait analyses, among normotensives only, rs12748299 was associated with SBP (p = 0.002). In addition, several nominally significant associations were noted with SBP and DBP among normotensives but none were statistically significant.

Conclusions

This study highlights the importance of replication to confirm the validity of genome wide association study results.