Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data

Since most analysis software for genome-wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even data sets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper we re-examine the computational bottlenecks and implement ultra-fast pedigree-based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (6 CPU cores at 2.67 GHz), analyzing a univariate HDL (high-density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1357 individuals in 124 pedigrees) takes less than 2 minutes and 1.5 GB of memory. Complete multivariate QTL analysis of the three time-points of the longitudinal HDL multivariate trait takes less than 5 minutes and 1.5 GB of memory

Vulvovaginal Trichosporonosis

Objective: Isolation of Trichosporon species from vaginal secretions is a rare event, and no data are available on its pathogenic role. A case series is presented to determine the pathogenic role of Trichosporon species in vulvovaginal infections. Methods: We performed a retrospective chart review of patients seen in the W.S.U. Vaginitis Clinic in order to identify patients from whom Trichosporon species were isolated. Results: Between 1986 and 2001, a total of 13 patients had a total of 18 positive vaginal cultures for Trichosporon species. All 18 vaginal isolates were T. inkin. In general, positive vaginal cultures were accompanied by low yeast colony counts. Four out of 18 positive T. inkin cultures were obtained from visits by asymptomatic patients. Of the remaining 14 positive T. inkin cultures from patients with symptoms, nine out of 14 cultures had other diagnoses (Candida albicans, six cases; bacterial vaginosis, two cases; Trichomonas, one case). Five positive T. inkin cultures were obtained from visits at which patients had symptoms and no associated diagnosis. In only one of the five episodes could we establish a clear pathogenic role for Trichosporon. In this case the patient was treated with boric acid and had resolution of symptoms and a negative culture at follow-up. In-vitro susceptibility tests revealed that T. inkin was resistant to flucytosine and susceptible to all topical and oral azoles. Conclusions: T. inkin is occasionally found in vulvovaginal cultures and is usually a non-pathogen. Transient colonization tended to occur in women, usually of African—American origin, with major perturbations in vaginal flora (bacterial vaginosis and trichomoniasis) and increased pH. Pathogenic consequences of Trichosporon colonization appear to be rare

The Quantitative-MFG Test: A linear mixed effect model to detect maternal-offspring gene interactions

Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the Quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT’s alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With GWAS data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered

Prevalence and risk factors for vaginal Candida colonization in women with type 1 and type 2 diabetes

BACKGROUND: Diabetes mellitus increases the rate of vaginal colonization and infection with Candida species METHODS: We surveyed women with diabetes receiving care at either an urban or suburban diabetes clinic to examine the relationship between vaginal Candida colonization, diabetes type and duration, and HbA(1c) level. 101 participants completed the self-administered questionnaire and self-collected a vaginal swab for Candida culture. Candida colonization was similar by age and race. RESULTS: Type 1 diabetics were three times as likely as type 2 diabetics to be colonized with any Candida species (OR = 3.4; 95% CI: 1.03, 11.41; p = 0.04); even after adjusting for abnormal HbA(1c), which had an independent effect (OR = 1.4; 95% CI: 1.04, 1.76; p = 0.02). Recent antibiotic use (OR = 4.5; 95% CI: 1.18, 16.79; p = 0.03), lifetime history of chlamydia (OR = 5.8; 95% CI: 1.09, 30.54; p = 0.04), and performing oral sex during the past 2 weeks (OR = 4.9; 95% CI:0.84, 28.27; p = 0.08) were also associated with Candida carriage after adjusting for diabetic type and abnormal HbA(1c). C. albicans was isolated from the majority of colonized type 1 participants (56%), while C. glabrata was the most common isolate among colonized type 2 participants (54%). CONCLUSIONS: Improving glucose control and possibly modifying sexual behavior may reduce risk of Candida colonization, and potentially symptomatic infection, among women with diabetes

Group testing with Random Pools: Phase Transitions and Optimal Strategy

The problem of Group Testing is to identify defective items out of a set of objects by means of pool queries of the form "Does the pool contain at least a defective?". The aim is of course to perform detection with the fewest possible queries, a problem which has relevant practical applications in different fields including molecular biology and computer science. Here we study GT in the probabilistic setting focusing on the regime of small defective probability and large number of objects, $p \to 0$ and $N \to \infty$. We construct and analyze one-stage algorithms for which we establish the occurrence of a non-detection/detection phase transition resulting in a sharp threshold, $\bar M$, for the number of tests. By optimizing the pool design we construct algorithms whose detection threshold follows the optimal scaling $\bar M\propto Np|\log p|$. Then we consider two-stages algorithms and analyze their performance for different choices of the first stage pools. In particular, via a proper random choice of the pools, we construct algorithms which attain the optimal value (previously determined in Ref. [16]) for the mean number of tests required for complete detection. We finally discuss the optimal pool design in the case of finite $p$

Thermally-driven morphing with high temperature composites

The thermal expansion mismatch between heat-resisting metals and high-temperature composite materials is explored as a method of achieving thermally-driven morphing in elevated-temperature environments, with an eye towards applications in variable-geometry hot structures in gas turbine engines. Three concepts are presented and demonstrated. The first thermal morphing system is a bimorph laminate which exploits the CTE mismatch between a titanium metal matrix composite and its parent titanium matrix material. The second concept is similar to the first, but uses a diffusion-bonded austenitic stainless steel alloy as the high expansion layer. The third concept utilizes a carbon fiber, silicon carbide matrix ceramic matrix composite joined to a stainless steel skin in a trailing-edge flap arrangement. Furnace-based experiments of cantilever-mounted specimens are performed to evaluate the displacement response of the metal-matrix and ceramic-matrix concepts at temperatures up to 606°C and 1035°C, respectively.</p

Tropical Intraseasonal Variability in Version 3 of the GFDL Atmosphere Model

Tropical intraseasonal variability is examined in version 3 of the Geophysical Fluid Dynamics Laboratory Atmosphere Model (AM3). In contrast to its predecessor AM2, AM3 uses a new treatment of deep and shallow cumulus convection and mesoscale clouds. The AM3 cumulus parameterization is a mass-flux-based scheme but also, unlike that in AM2, incorporates subgrid-scale vertical velocities; these play a key role in cumulus microphysical processes. The AM3 convection scheme allows multiphase water substance produced in deep cumuli to be transported directly into mesoscale clouds, which strongly influence large-scale moisture and radiation fields. The authors examine four AM3 simulations using a control model and three versions with different modifications to the deep convection scheme. In the control AM3, using a convective closure based on CAPE relaxation, both MJO and Kelvin waves are weak relative to those in observations. By modifying the convective closure and trigger assumptions to inhibit deep cumuli, AM3 produces reasonable intraseasonal variability but a degraded mean state. MJO-like disturbances in the modified AM3 propagate eastward at roughly the observed speed in the Indian Ocean but up to 2 times the observed speed in the west Pacific Ocean. Distinct differences in intraseasonal convective organization and propagation exist among the modified AM3 versions. Differences in vertical diabatic heating profiles associated with the MJO are also found. The two AM3 versions with the strongest intraseasonal signals have a more prominent “bottom heavy” heating profile leading the disturbance center and “top heavy” heating profile following the disturbance. The more realistic heating structures are associated with an improved depiction of moisture convergence and intraseasonal convective organization in AM3

A low energy optimization of the CERN-NGS neutrino beam for a theta_{13} driven neutrino oscillation search

The possibility to improve the CERN to Gran Sasso neutrino beam performances for theta_{13} searches is investigated. We show that by an appropriate optimization of the target and focusing optics of the present CNGS design, we can increase the flux of low energy neutrinos by about a factor 5 compared to the current tau optimized focalisation. With the ICARUS 2.35 kton detector at LNGS and in case of negative result, this would allow to improve the limit to sin^22 theta_{13} by an order of magnitude better than the current limit of CHOOZ at Delta m^2 approximately 3 times 10^{-3} eV^2 within 5 years of nominal CNGS running. This is by far the most sensitive setup of the currently approved long-baseline experiments and is competitive with the proposed JHF superbeam.Comment: 19 pages, 8 figure