Power Boosting in Genome-Wide Studies Via Methods for Multivariate Outcomes

Whole-genome studies are becoming a mainstay of biomedical research. Examples include expression array experiments, comparative genomic hybridization analyses and large case-control studies for detecting polymorphism/disease associations. The tactic of applying a regression model to every locus to obtain test statistics is useful in such studies. However, this approach ignores potential correlation structure in the data that could be used to gain power, particularly when a Bonferroni correction is applied to adjust for multiple testing. In this article, we propose using regression techniques for misspecified multivariate outcomes to increase statistical power over independence-based modeling at each locus. Even when the outcome is not ordinarily regarded as multivariate, it is mathematically valid to view the outcome as a set of (identical) repeated measurements, one associated with each genetic locus. Rather than joint modeling of all observations, we propose to apply joint modeling to subgroups of data. The primary example in this article focuses on the use of generalized estimating equations (GEE) software to apply the method. We describe conditions under which the proposed method provides more power than applying independence-based methods. In simulation studies of plausible and interesting scenarios, power gains are as large as 35% compared to modeling the outcomes univariately with a one genetic covariate. In contrast, modeling the outcome as univariate with multiple genetic covariates performs very poorly when data are correlated. The proposed method is easy to apply, allows adjustment for confounding and can be combined with other methods for increasing power in multiple testing situations

A new mixture model approach to analyzing allelic-loss data using Bayes factors

BACKGROUND: Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor suppressor gene can lead to tumor development, one objective of these studies is to determine which, if any, chromosome arms harbor tumor suppressor genes. RESULTS: We propose a large class of mixture models for describing the data, and we suggest using Bayes factors to select a reasonable model from the class in order to classify the chromosome arms. Bayes factors are especially useful in the case of testing that the number of components in a mixture model is n(0 )versus n(1). In these cases, frequentist test statistics based on the likelihood ratio statistic have unknown distributions and are therefore not applicable. Our simulation study shows that Bayes factors favor the right model most of the time when tumor suppressor genes are present. When no tumor suppressor genes are present and background allelic-loss varies, the Bayes factors are often inconclusive, although this results in a markedly reduced false-positive rate compared to that of standard frequentist approaches. Application of our methods to three data sets of esophageal adenocarcinomas yields interesting differences from those results previously published. CONCLUSIONS: Our results indicate that Bayes factors are useful for analyzing allelic-loss data

Disruption of Protein Kinase A in Mice Enhances Healthy Aging

Mutations that cause a reduction in protein kinase A (PKA) activity have been shown to extend lifespan in yeast. Loss of function of mammalian RIIβ, a regulatory subunit of PKA expressed in brain and adipose tissue, results in mice that are lean and insulin sensitive. It was therefore hypothesized that RIIB null (RIIβ−/−) mice would express anti-aging phenotypes. We conducted lifespan studies using 40 mutant and 40 wild type (WT) littermates of equal gender numbers and found that both the median and maximum lifespans were significantly increased in mutant males compared to WT littermates. The median lifespan was increased from 884 days to 1005 days (p = 0.006 as determined by the log rank test) and the 80% lifespan (defined here as 80% deaths) was increased from 941 days to 1073 days (p = 0.004 as determined by the Wang-Allison test). There was no difference in either median or 80% lifespan in female genotypes. WT mice of both genders became increasingly obese with age, while mutant mice maintained their lean phenotype into old age. Adiposity was found to correlate with lifespan for males only. 50% of male mice between 30 and 35 g, corresponding to about 5% body fat, for either genotype lived over 1000 days. No male mouse outside of this weight range achieved this lifespan. During their last month of life, WT mice began losing weight (a total of 8% and 15% of body weight was lost for males and females, respectively), but RIIβ−/− male mice maintained their lean body mass to end of life. This attenuation of decline was not seen in female mutant mice. Old male mutant mice were insulin sensitive throughout their life. Both genders showed modestly lower blood glucose levels in old mutants compared to WT. Male mutants were also resistant to age-induced fatty liver. Pathological assessment of tissues from end of life male mutant mice showed a decrease in tumor incidence, decreased severity of renal lesions, and a trend towards a decrease in age-related cardiac pathology. These findings help establish the highly conserved nature of PKA and suggest that disruption of PKA affects physiological mechanisms known to be associated with healthy aging

Correction: Exome Sequencing of Phenotypic Extremes Identifies CAV2 and TMC6 as Interacting Modifiers of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis

Discovery of rare or low frequency variants in exome or genome data that are associated with complex traits often will require use of very large sample sizes to achieve adequate statistical power. For a fixed sample size, sequencing of individuals sampled from the tails of a phenotype distribution (i.e., extreme phenotypes design) maximizes power and this approach was recently validated empirically with the discovery of variants in DCTN4 that influence the natural history of P. aeruginosa airway infection in persons with cystic fibrosis (CF; MIM219700). The increasing availability of large exome/genome sequence datasets that serve as proxies for population-based controls affords the opportunity to test an alternative, potentially more powerful and generalizable strategy, in which the frequency of rare variants in a single extreme phenotypic group is compared to a control group (i.e., extreme phenotype vs. control population design). As proof-of-principle, we applied this approach to search for variants associated with risk for age-of-onset of chronic P. aeruginosa airway infection among individuals with CF and identified variants in CAV2 and TMC6 that were significantly associated with group status. These results were validated using a large, prospective, longitudinal CF cohort and confirmed a significant association of a variant in CAV2 with increased age-of-onset of P. aeruginosa airway infection (hazard ratio = 0.48, 95% CI=[0.32, 0.88]) and variants in TMC6 with diminished age-of-onset of P. aeruginosa airway infection (HR = 5.4, 95% CI=[2.2, 13.5]) A strong interaction between CAV2 and TMC6 variants was observed (HR=12.1, 95% CI=[3.8, 39]) for children with the deleterious TMC6 variant and without the CAV2 protective variant. Neither gene showed a significant association using an extreme phenotypes design, and conditions for which the power of an extreme phenotype vs. control population design was greater than that for the extreme phenotypes design were explored

Mice lacking the Cβ subunit of PKA are resistant to angiotensin II-induced cardiac hypertrophy and dysfunction

<p>Abstract</p> <p>Background</p> <p>PKA is a ubiquitous, multi-subunit cellular kinase that regulates a number of different physiological responses in response to cAMP, including metabolism, cell division, and cardiac function. Numerous studies have implicated altered PKA signaling in cardiac dysfunction. Recently, it has been shown that mice lacking the catalytic β subunit of PKA (PKA Cβ) are protected from age-related problems such as weight gain and enlarged livers, and we hypothesized that these mice might also be resistant to cardiomyopathy.</p> <p>Findings</p> <p>Angiotensin II (ang II) induced hypertension in both PKA Cβ null mice and their WT littermates. However, PKA Cβ null mice were resistant to a number of ang II-induced, cardiopathological effects observed in the WT mice, including hypertrophy, decreased diastolic performance, and enlarged left atria.</p> <p>Conclusion</p> <p>The Cβ subunit of PKA plays an important role in angiotensin-induced cardiac dysfunction. The Cβ null mouse highlights the potential of the PKA Cβ subunit as a pharmaceutical target for hypertrophic cardiac disease.</p

Antimetastatic gene expression profiles mediated by retinoic acid receptor beta 2 in MDA-MB-435 breast cancer cells

BACKGROUND: The retinoic acid receptor beta 2 (RARβ2) gene modulates proliferation and survival of cultured human breast cancer cells. Previously we showed that ectopic expression of RARβ2 in a mouse xenograft model prevented metastasis, even in the absence of the ligand, all-trans retinoic acid. We investigated both cultured cells and xenograft tumors in order to delineate the gene expression profiles responsible for an antimetastatic phenotype. METHODS: RNA from MDA-MB-435 human breast cancer cells transduced with RARβ2 or empty retroviral vector (LXSN) was analyzed using Agilent Human 1A Oligo microarrays. The one hundred probes with the greatest differential intensity (p < 0.004, jointly) were determined by selecting the top median log ratios from eight-paired microarrays. Validation of differences in expression was done using Northern blot analysis and quantitative RT-PCR (qRT-PCR). We determined expression of selected genes in xenograft tumors. RESULTS: RARβ2 cells exhibit gene profiles with overrepresentation of genes from Xq28 (p = 2 × 10(-8)), a cytogenetic region that contains a large portion of the cancer/testis antigen gene family. Other functions or factors impacted by the presence of exogenous RARβ2 include mediators of the immune response and transcriptional regulatory mechanisms. Thirteen of fifteen (87%) of the genes evaluated in xenograft tumors were consistent with differences we found in the cell cultures (p = 0.007). CONCLUSION: Antimetastatic RARβ2 signalling, direct or indirect, results in an elevation of expression for genes such as tumor-cell antigens (CTAG1 and CTAG2), those involved in innate immune response (e.g., RIG-I/DDX58), and tumor suppressor functions (e.g., TYRP1). Genes whose expression is diminished by RARβ2 signalling include cell adhesion functions (e.g, CD164) nutritional or metabolic processes (e.g., FABP6), and the transcription factor, JUN