A Distance-Based Test of Association Between Paired Heterogeneous Genomic Data

Due to rapid technological advances, a wide range of different measurements can be obtained from a given biological sample including single nucleotide polymorphisms, copy number variation, gene expression levels, DNA methylation and proteomic profiles. Each of these distinct measurements provides the means to characterize a certain aspect of biological diversity, and a fundamental problem of broad interest concerns the discovery of shared patterns of variation across different data types. Such data types are heterogeneous in the sense that they represent measurements taken at very different scales or described by very different data structures. We propose a distance-based statistical test, the generalized RV (GRV) test, to assess whether there is a common and non-random pattern of variability between paired biological measurements obtained from the same random sample. The measurements enter the test through distance measures which can be chosen to capture particular aspects of the data. An approximate null distribution is proposed to compute p-values in closed-form and without the need to perform costly Monte Carlo permutation procedures. Compared to the classical Mantel test for association between distance matrices, the GRV test has been found to be more powerful in a number of simulation settings. We also report on an application of the GRV test to detect biological pathways in which genetic variability is associated to variation in gene expression levels in ovarian cancer samples, and present results obtained from two independent cohorts

Adaptive Mantel Test for AssociationTesting in Imaging Genetics Data

Mantel's test (MT) for association is conducted by testing the linear relationship of similarity of all pairs of subjects between two observational domains. Motivated by applications to neuroimaging and genetics data, and following the succes of shrinkage and kernel methods for prediction with high-dimensional data, we here introduce the adaptive Mantel test as an extension of the MT. By utilizing kernels and penalized similarity measures, the adaptive Mantel test is able to achieve higher statistical power relative to the classical MT in many settings. Furthermore, the adaptive Mantel test is designed to simultaneously test over multiple similarity measures such that the correct type I error rate under the null hypothesis is maintained without the need to directly adjust the significance threshold for multiple testing. The performance of the adaptive Mantel test is evaluated on simulated data, and is used to investigate associations between genetics markers related to Alzheimer's Disease and heatlhy brain physiology with data from a working memory study of 350 college students from Beijing Normal University

Lung volumes identify an at-risk group in persons with prolonged secondhand tobacco smoke exposure but without overt airflow obstruction.

IntroductionExposure to secondhand smoke (SHS) is associated with occult obstructive lung disease as evident by abnormal airflow indices representing small airway disease despite having preserved spirometry (normal forced expiratory volume in 1 s-to-forced vital capacity ratio, FEV1/FVC). The significance of lung volumes that reflect air trapping in the presence of preserved spirometry is unclear.MethodsTo investigate whether lung volumes representing air trapping could determine susceptibility to respiratory morbidity in people with SHS exposure but without spirometric chronic obstructive pulmonary disease, we examined a cohort of 256 subjects with prolonged occupational SHS exposure and preserved spirometry. We elicited symptom prevalence by structured questionnaires, examined functional capacity (maximum oxygen uptake, VO2max) by exercise testing, and estimated associations of those outcomes with air trapping (plethysmography-measured residual volume-to-total lung capacity ratio, RV/TLC), and progressive air trapping with exertion (increase in fraction of tidal breathing that is flow limited on expiration during exercise (per cent of expiratory flow limitation, %EFL)).ResultsRV/TLC was within the predicted normal limits, but was highly variable spanning 22%±13% and 16%±8% across the increments of FEV1/FVC and FEV1, respectively. Respiratory complaints were prevalent (50.4%) with the most common symptom being ≥2 episodes of cough per year (44.5%). Higher RV/TLC was associated with higher OR of reporting respiratory symptoms (n=256; r2=0.03; p=0.011) and lower VO2max (n=179; r2=0.47; p=0.013), and %EFL was negatively associated with VO2max (n=32; r2=0.40; p=0.017).ConclusionsIn those at risk for obstruction due to SHS exposure but with preserved spirometry, higher RV/TLC identifies a subgroup with increased respiratory symptoms and lower exercise capacity