Testing gene-environment interactions for rare and/or common variants in sequencing association studies.

The risk of many complex diseases is determined by a complex interplay of genetic and environmental factors. Advanced next generation sequencing technology makes identification of gene-environment (GE) interactions for both common and rare variants possible. However, most existing methods focus on testing the main effects of common and/or rare genetic variants. There are limited methods developed to test the effects of GE interactions for rare variants only or rare and common variants simultaneously. In this study, we develop novel approaches to test the effects of GE interactions of rare and/or common risk, and/or protective variants in sequencing association studies. We propose two approaches: 1) testing the effects of an optimally weighted combination of GE interactions for rare variants (TOW-GE); 2) testing the effects of a weighted combination of GE interactions for both rare and common variants (variable weight TOW-GE, VW-TOW-GE). Extensive simulation studies based on the Genetic Analysis Workshop 17 data show that the type I error rates of the proposed methods are well controlled. Compared to the existing interaction sequence kernel association test (ISKAT), TOW-GE is more powerful when there are GE interactions\u27 effects for rare risk and/or protective variants; VW-TOW-GE is more powerful when there are GE interactions\u27 effects for both rare and common risk and protective variants. Both TOW-GE and VW-TOW-GE are robust to the directions of effects of causal GE interactions. We demonstrate the applications of TOW-GE and VW-TOW-GE using an imputed data from the COPDGene Study

Testing optimally weighted combination of variants for hypertension

© 2014 Zhao et al.; licensee BioMed Central Ltd. Testing rare variants directly is possible with next-generation sequencing technology. In this article, we propose a sliding-window-based optimal-weighted approach to test for the effects of both rare and common variants across the whole genome. We measured the genetic association between a disease and a combination of variants of a single-nucleotide polymorphism window using the newly developed tests TOW and VW-TOW and performed a sliding-window technique to detect disease-susceptible windows. By applying the new approach to unrelated individuals of Genetic Analysis Workshop 18 on replicate 1 chromosome 3, we detected 3 highly susceptible windows across chromosome 3 for diastolic blood pressure and identified 10 of 48,176 windows as the most promising for both diastolic and systolic blood pressure. Seven of 9 top variants influencing diastolic blood pressure and 8 of 9 top variants influencing systolic blood pressure were found in or close to our top 10 windows

Prenatal disruption of blood–brain barrier formation via cyclooxygenase activation leads to lifelong brain inflammation

Gestational maternal immune activation (MIA) in mice induces persistent brain microglial activation and a range of neuropathologies in the adult offspring. Although long-term phenotypes are well documented, how MIA in utero leads to persistent brain inflammation is not well understood. Here, we found that offspring of mothers treated with polyriboinosinic–polyribocytidylic acid [poly(I:C)] to induce MIA at gestational day 13 exhibit blood–brain barrier (BBB) dysfunction throughout life. Live MRI in utero revealed fetal BBB hyperpermeability 2 d after MIA. Decreased pericyte–endothelium coupling in cerebral blood vessels and increased microglial activation were found in fetal and 1- and 6-mo-old offspring brains. The long-lasting disruptions result from abnormal prenatal BBB formation, driven by increased proliferation of cyclooxygenase-2 (COX2; Ptgs2)-expressing microglia in fetal brain parenchyma and perivascular spaces. Targeted deletion of the Ptgs2 gene in fetal myeloid cells or treatment with the inhibitor celecoxib 24 h after immune activation prevented microglial proliferation and disruption of BBB formation and function, showing that prenatal COX2 activation is a causal pathway of MIA effects. Thus, gestational MIA disrupts fetal BBB formation, inducing persistent BBB dysfunction, which promotes microglial overactivation and behavioral alterations across the offspring life span. Taken together, the data suggest that gestational MIA disruption of BBB formation could be an etiological contributor to neuropsychiatric disorders

Multi-view information fusion using multi-view variational autoencoders to predict proximal femoral strength

The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion. Method: We developed new models using multi-view variational autoencoder (MVAE) for feature representation learning and a product of expert (PoE) model for multi-view information fusion. We applied the proposed models to an in-house Louisiana Osteoporosis Study (LOS) cohort with 931 male subjects, including 345 African Americans and 586 Caucasians. With an analytical solution of the product of Gaussian distribution, we adopted variational inference to train the designed MVAE-PoE model to perform common latent feature extraction. We performed genome-wide association studies (GWAS) to select 256 genetic variants with the lowest p-values for each proximal femoral strength and integrated whole genome sequence (WGS) features and DXA-derived imaging features to predict proximal femoral strength. Results: The best prediction model for fall fracture load was acquired by integrating WGS features and DXA-derived imaging features. The designed models achieved the mean absolute percentage error of 18.04%, 6.84% and 7.95% for predicting proximal femoral fracture loads using linear models of fall loading, nonlinear models of fall loading, and nonlinear models of stance loading, respectively. Compared to existing multi-view information fusion methods, the proposed MVAE-PoE achieved the best performance. Conclusion: The proposed models are capable of predicting proximal femoral strength using WGS features and DXA-derived imaging features. Though this tool is not a substitute for FEA using QCT images, it would make improved assessment of hip fracture risk more widely available while avoiding the increased radiation dosage and clinical costs from QCT.Comment: 16 pages, 3 figure

A New Hip Fracture Risk Index Derived from FEA-Computed Proximal Femur Fracture Loads and Energies-to-Failure

Hip fracture risk assessment is an important but challenging task. Quantitative CT-based patient specific finite element analysis (FEA) computes the force (fracture load) to break the proximal femur in a particular loading condition. It provides different structural information about the proximal femur that can influence a subject overall fracture risk. To obtain a more robust measure of fracture risk, we used principal component analysis (PCA) to develop a global FEA computed fracture risk index that incorporates the FEA-computed yield and ultimate failure loads and energies to failure in four loading conditions (single-limb stance and impact from a fall onto the posterior, posterolateral, and lateral aspects of the greater trochanter) of 110 hip fracture subjects and 235 age and sex matched control subjects from the AGES-Reykjavik study. We found that the first PC (PC1) of the FE parameters was the only significant predictor of hip fracture. Using a logistic regression model, we determined if prediction performance for hip fracture using PC1 differed from that using FE parameters combined by stratified random resampling with respect to hip fracture status. The results showed that the average of the area under the receive operating characteristic curve (AUC) using PC1 was always higher than that using all FE parameters combined in the male subjects. The AUC of PC1 and AUC of the FE parameters combined were not significantly different than that in the female subjects or in all subjectsComment: 27 pages, 4 figure

Fetal Metabolic Adaptations to Cardiovascular Stress in Twin-Twin Transfusion Syndrome

Monochorionic-diamniotic twin pregnancies are susceptible to unique complications arising from a single placenta shared by two fetuses. Twin-twin transfusion syndrome (TTTS) is a constellation of disturbances caused by unequal blood flow within the shared placenta giving rise to a major hemodynamic imbalance between the twins. Here, we applied TTTS as a model to uncover fetal metabolic adaptations to cardiovascular stress. We compared untargeted metabolomic analyses of amniotic fluid samples from severe TTTS cases vs. singleton controls. Amniotic fluid metabolites demonstrated alterations in fatty acid, glucose, and steroid hormone metabolism in TTTS. Among TTTS cases, unsupervised principal component analysis revealed two distinct clusters of disease defined by levels of glucose metabolites, amino acids, urea, and redox status. Our results suggest that the human fetal heart can adapt to hemodynamic stress by modulating its glucose metabolism and identify potential differences in the ability of individual fetuses to respond to cardiovascular stress

Identification and Characterization of Two Novel Compounds: Heterozygous Variants of Lipoprotein Lipase in Two Pedigrees With Type I Hyperlipoproteinemia

BackgroundType I hyperlipoproteinemia, characterized by severe hypertriglyceridemia, is caused mainly by loss-of-function mutation of the lipoprotein lipase (LPL) gene. To date, more than 200 mutations in the LPL gene have been reported, while only a limited number of mutations have been evaluated for pathogenesis.ObjectiveThis study aims to explore the molecular mechanisms underlying lipoprotein lipase deficiency in two pedigrees with type 1 hyperlipoproteinemia.MethodsWe conducted a systematic clinical and genetic analysis of two pedigrees with type 1 hyperlipoproteinemia. Postheparin plasma of all the members was used for the LPL activity analysis. In vitro studies were performed in HEK-293T cells that were transiently transfected with wild-type or variant LPL plasmids. Furthermore, the production and activity of LPL were analyzed in cell lysates or culture medium.ResultsProband 1 developed acute pancreatitis in youth, and her serum triglycerides (TGs) continued to be at an ultrahigh level, despite the application of various lipid-lowering drugs. Proband 2 was diagnosed with type 1 hyperlipoproteinemia at 9 months of age, and his serum TG levels were mildly elevated with treatment. Two novel compound heterozygous variants of LPL (c.3G>C, p. M1? and c.835_836delCT, p. L279Vfs*3, c.188C>T, p. Ser63Phe and c.662T>C, p. Ile221Thr) were identified in the two probands. The postheparin LPL activity of probands 1 and 2 showed decreases of 72.22 ± 9.46% (p<0.01) and 54.60 ± 9.03% (p<0.01), respectively, compared with the control. In vitro studies showed a substantial reduction in the expression or enzyme activity of LPL in the LPL variants.ConclusionsTwo novel compound heterozygous variants of LPL induced defects in the expression and function of LPL and caused type I hyperlipoproteinemia. The functional characterization of these variants was in keeping with the postulated LPL mutant activity

Ubiquitous conservative interaction patterns between post-spliced introns and their mRNAs revealed by genome-wide interspecies comparison

Introns, as important vectors of biological functions, can influence many stages of mRNA metabolism. However, in recent research, post-spliced introns are rarely considered. In this study, the optimal matched regions between introns and their mRNAs in nine model organism genomes were investigated with improved Smith–Waterman local alignment software. Our results showed that the distributions of mRNA optimal matched frequencies were highly consistent or universal. There are optimal matched frequency peaks in the UTR regions, which are obvious, especially in the 3′-UTR. The matched frequencies are relatively low in the CDS regions of the mRNA. The distributions of the optimal matched frequencies around the functional sites are also remarkably changed. The centers of the GC content distributions for different sequences are different. The matched rate distributions are highly consistent and are located mainly between 60% and 80%. The most probable value of the optimal matched segments is about 20 bp for lower eukaryotes and 30 bp for higher eukaryotes. These results show that there are abundant functional units in the introns, and these functional units are correlated structurally with all kinds of sequences of mRNA. The interaction between the post-spliced introns and their corresponding mRNAs may play a key role in gene expression

Internal kinematics of groups of galaxies in the Sloan Digital Sky Survey data release 7

We present measurements of the velocity dispersion profile (VDP) for galaxy groups in the final data release of the Sloan Digital Sky Survey (SDSS). For groups of given mass we estimate the redshift-space cross-correlation function (CCF) with respect to a reference galaxy sample, xi(r_p, pi), the projected CCF, w_p(r_p), and the real-space CCF, xi(r). The VDP is then extracted from the redshift distortion in xi(r_p, pi), by comparing xi(r_p, pi) with xi(r). We find that the velocity dispersion (VD) within virial radius (R_200) shows a roughly flat profile, with a slight increase at radii below ~0.3 R_200 for high mass systems. The average VD within the virial radius, sigma_v, is a strongly increasing function of central galaxy mass. We apply the same methodology to N-body simulations with the concordance Lambda cold dark matter cosmology but different values of the density fluctuation parameter sigma_8, and we compare the results to the SDSS results. We show that the sigma_v-M_* relation from the data provides stringent constraints on both sigma_8 and sigma_ms, the dispersion in log M_* of central galaxies at fixed halo mass. Our best-fitting model suggests sigma_8 = 0.86 +/- 0.03 and sigma_ms = 0.16 +/- 0.03. The slightly higher value of sigma_8 compared to the WMAP7 result might be due to a smaller matter density parameter assumed in our simulations. Our VD measurements also provide a direct measure of the dark matter halo mass for central galaxies of different luminosities and masses, in good agreement with the results obtained by Mandelbaum et al. (2006) from stacking the gravitational lensing signals of the SDSS galaxies.Comment: 17 pages, 10 figures, 1 table, accepted for publication in ApJ, text slightly changed, abstract substantially shortened, two new panels added to Figs. 2 and 3 showing w_p and VDP as functions of r_p/R_200 instead of r_