webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study

The development of transcriptome-wide association studies (TWAS) has enabled researchers to better identify and interpret causal genes in many diseases. However, there are currently no resources providing a comprehensive listing of gene-disease associations discovered by TWAS from published GWAS summary statistics. TWAS analyses are also difficult to conduct due to the complexity of TWAS software pipelines. To address these issues, we introduce a new resource called webTWAS, which integrates a database of the most comprehensive disease GWAS datasets currently available with credible sets of potential causal genes identified by multiple TWAS software packages. Specifically, a total of 235 064 gene-diseases associations for a wide range of human diseases are prioritized from 1298 high-quality downloadable European GWAS summary statistics. Associations are calculated with seven different statistical models based on three popular and representative TWAS software packages. Users can explore associations at the gene or disease level, and easily search for related studies or diseases using the MeSH disease tree. Since the effects of diseases are highly tissue-specific, webTWAS applies tissue-specific enrichment analysis to identify significant tissues. A user-friendly web server is also available to run custom TWAS analyses on user-provided GWAS summary statistics data. webTWAS is freely available at http://www.webtwas.net.

Induction of zidovudine glucuronidation and amination pathways by rifampicin in HIV-infected patients

AIMS

The objective of the study was to determine the effect of multiple doses of rifampicin on the steady-state pharmacokinetics of zidovudine and its 5'-glucuronosyl (GZDV) and 3'-amino (AMT) metabolites.

METHODS

Eight asymptomatic HIV-infected patients (seven male, one female) participated in this three-period longitudinal study. Each patient received zidovudine (200 mg every 8 h) for 14 days (period 1), followed by rifampicin (600 mg every 24 h) with zidovudine for 14 days (period 2), and then zidovudine alone for a further 14 days (period 3). Blood and urine samples were collected over 6 h on the last day of each period for measurements of zidovudine and GZDV by h.p.l.c.-u.v. and AMT by h.p.l.c.-m.s-m.s.

RESULTS

Compared with zidovudine-alone values in period 1, 14 days of coadministration with rifampicin significantly increased zidovudine oral clearance (89%) and formation clearances to GZDV (100%) and AMT (82%). Correspondingly, there were decreases in maximum plasma concentration (43%), AUC (47%) and urine recovery (37%) of zidovudine. GZDV/zidovudine and AMT/zidovudine AUC ratios increased by 99% and 36%, respectively, despite a significant 29% decrease in AMT AUC. After stopping rifampicin for 14 days, values of these pharmacokinetic parameters returned to within 26% of baseline. Over the three periods AMT plasma levels were <18 ng ml-1 (n=6) and <40 ng ml-1 (n=2), and molar AMT/zidovudine AUC ratios ranged from 1.7% to 4.5%.

CONCLUSIONS

Rifampicin induced zidovudine glucuronidation and amination pathways resulting in decreased plasma and urine exposures to zidovudine. AMT plasma exposure decreased because induction was more pronounced for the major GZDV metabolite. The magnitude of the residual inductive effect was minimal at 14 days after stopping rifampicin.

Chronic exposure to dietary sterol glucosides is neurotoxic to motor neurons and induces an ALS-PDC phenotype

Epidemiological studies of the Guamanian variants of amyotrophic lateral sclerosis (ALS) and parkinsonism, amyotrophic lateral sclerosis-parkinsonism dementia complex (ALS-PDC), have shown a positive correlation between consumption of washed cycad seed flour and disease occurrence. Previous in vivo studies by our group have shown that the same seed flour induces ALS and PDC phenotypes in out bred adult male mice. In vitro studies using isolated cycad compounds have also demonstrated that several of these are neurotoxic, specifically, a number of water insoluble phytosterol glucosides of which beta-sitosterol beta-D: -glucoside (BSSG) forms the largest fraction. BSSG is neurotoxic to motor neurons and other neuronal populations in culture. The present study shows that an in vitro hybrid motor neuron (NSC-34) culture treated with BSSG undergoes a dose-dependent cell loss. Surviving cells show increased expression of HSP70, decreased cytosolic heavy neurofilament expression, and have various morphological abnormalities. CD-1 mice fed mouse chow pellets containing BSSG for 15 weeks showed motor deficits and motor neuron loss in the lumbar and thoracic spinal cord, along with decreased glutamate transporter labelling, and increased glial fibrillary acid protein reactivity. Other pathological outcomes included increased caspase-3 labelling in the striatum and decreased tyrosine-hydroxylase labelling in the striatum and substantia nigra. C57BL/6 mice fed BSSG-treated pellets for 10 weeks exhibited progressive loss of motor neurons in the lumbar spinal cord that continued to worsen even after the BSSG exposure ended. These results provide further support implicating sterol glucosides as one potential causal factor in the motor neuron pathology previously associated with cycad consumption and ALS-PDC.

Power analysis of transcriptome-wide association study: Implications for practical protocol choice

The transcriptome-wide association study (TWAS) has emerged as one of several promising techniques for integrating multi-scale 'omics' data into traditional genome-wide association studies (GWAS). Unlike GWAS, which associates phenotypic variance directly with genetic variants, TWAS uses a reference dataset to train a predictive model for gene expressions, which allows it to associate phenotype with variants through the mediating effect of expressions. Although effective, this core innovation of TWAS is poorly understood, since the predictive accuracy of the genotype-expression model is generally low and further bounded by expression heritability. This raises the question: to what degree does the accuracy of the expression model affect the power of TWAS? Furthermore, would replacing predictions with actual, experimentally determined expressions improve power? To answer these questions, we compared the power of GWAS, TWAS, and a hypothetical protocol utilizing real expression data. We derived non-centrality parameters (NCPs) for linear mixed models (LMMs) to enable closed-form calculations of statistical power that do not rely on specific protocol implementations. We examined two representative scenarios: causality (genotype contributes to phenotype through expression) and pleiotropy (genotype contributes directly to both phenotype and expression), and also tested the effects of various properties including expression heritability. Our analysis reveals two main outcomes: (1) Under pleiotropy, the use of predicted expressions in TWAS is superior to actual expressions. This explains why TWAS can function with weak expression models, and shows that TWAS remains relevant even when real expressions are available. (2) GWAS outperforms TWAS when expression heritability is below a threshold of 0.04 under causality, or 0.06 under pleiotropy. Analysis of existing publications suggests that TWAS has been misapplied in place of GWAS, in situations where expression heritability is low.

kTWAS: integrating kernel machine with transcriptome-wide association studies improves statistical power and reveals novel genes

The power of genotype-phenotype association mapping studies increases greatly when contributions from multiple variants in a focal region are meaningfully aggregated. Currently, there are two popular categories of variant aggregation methods. Transcriptome-wide association studies (TWAS) represent a set of emerging methods that select variants based on their effect on gene expressions, providing pretrained linear combinations of variants for downstream association mapping. In contrast to this, kernel methods such as sequence kernel association test (SKAT) model genotypic and phenotypic variance use various kernel functions that capture genetic similarity between subjects, allowing nonlinear effects to be included. From the perspective of machine learning, these two methods cover two complementary aspects of feature engineering: feature selection/pruning and feature aggregation. Thus far, no thorough comparison has been made between these categories, and no methods exist which incorporate the advantages of TWAS- and kernel-based methods. In this work, we developed a novel method called kernel-based TWAS (kTWAS) that applies TWAS-like feature selection to a SKAT-like kernel association test, combining the strengths of both approaches. Through extensive simulations, we demonstrate that kTWAS has higher power than TWAS and multiple SKAT-based protocols, and we identify novel disease-associated genes in Wellcome Trust Case Control Consortium genotyping array data and MSSNG (Autism) sequence data. The source code for kTWAS and our simulations are available in our GitHub repository (https://github.com/theLongLab/kTWAS).

CNTO 530: molecular pharmacology in human UT-7EPO cells and pharmacokinetics and pharmacodynamics in mice

CNTO 530 is a 58 kD antibody Fc domain fusion protein, created using Centocor's MIMETIBODY platform, that contains two EMP1 sequences as a pharmacophore. CNTO 530 has no sequence homology with EPO but acts as a novel erythropoietin receptor agonist. In UT-7(EPO) cells, CNTO 530 caused protein phosporylation of the erythropoietin receptor associated signaling pathway (Jak2, STAT5, AKT and ERK1/2). CNTO 530 also rescued these cells from apoptosis and mediated proliferation. In mice, pharmacokinetic analysis showed that CNTO 530 was slowly cleared from circulation with a t(1/2) approximately 40 h. Pharmacodynamic analysis in mice showed that a single sc dose of CNTO 530 caused a long-lived stimulation of erythropoiesis that translated into increases in red blood cell counts and hemoglobin values that were maintained for at least 28 d. In conclusion, CNTO 530 is a long-lived EPO-R agonist that stimulates erythropoiesis in a manner similar to epoetin-alpha. These data suggest that CNTO 530 may be an effective treatment of anemia in humans.

Tuberculosis among urban health care workers: a study using restriction fragment length polymorphism typing

Cases of tuberculosis identified during 1992-1994 through an active tuberculosis surveillance network among six hospitals that serve New York City (the TBNetwork) were analyzed according to the occupational status of the patients. Clinical data were obtained by review of medical records, and restriction fragment length polymorphism (RFLP) typing of Mycobacterium tuberculosis isolates was performed. No known nosocomial outbreaks of tuberculosis occurred at these hospitals in the study period. Occupational status was known for 142 of 201 patients whose isolates were available for strain typing. Patients infected by organisms with a clustered strain typing pattern, as determined by RFLP analysis, were presumed to have recently acquired disease. RFLP typing revealed that isolates from 13 (65%) of 20 health care workers and 50 (41%) of 122 non-health care workers had a clustered RFLP pattern. The strains infecting eight (89%) of nine health care workers seropositive for human immunodeficiency virus (HIV) had a clustered RFLP pattern. Multivariate analysis of 75 patients with known HIV and occupational status revealed that HIV status (P = .03) and health care worker status (P = .02; RR = 2.77) were independent risk factors for a clustered RFLP strain. These findings suggest that many of the apparently sporadic cases of tuberculosis among health care workers may be due to unrecognized occupational transmission.

Disentangling genetic feature selection and aggregation in transcriptome-wide association studies

The success of transcriptome-wide association studies (TWAS) has led to substantial research towards improving the predictive accuracy of its core component of Genetically Regulated eXpression (GReX). GReX links expression information with genotype and phenotype by playing two roles simultaneously: it acts as both the outcome of the genotype-based predictive models (for predicting expressions) and the linear combination of genotypes (as the predicted expressions) for association tests. From the perspective of machine learning (considering SNPs as features), these are actually two separable steps-feature selection and feature aggregation-which can be independently conducted. In this work, we show that the single approach of GReX limits the adaptability of TWAS methodology and practice. By conducting simulations and real data analysis, we demonstrate that disentangled protocols adapting straightforward approaches for feature selection (e.g., simple marker test) and aggregation (e.g., kernel machines) outperform the standard TWAS protocols that rely on GReX. Our development provides more powerful novel tools for conducting TWAS. More importantly, our characterization of the exact nature of TWAS suggests that, instead of questionably binding two distinct steps into the same statistical form (GReX), methodological research focusing on optimal combinations of feature selection and aggregation approaches will bring higher power to TWAS protocols.

Health-related quality of life after short segment instrumentation of lumbar burst fractures

Management of lumbar burst fractures remains controversial. Surgical reduction/stabilization is becoming more popular; however, the functional impact of operative intervention is not clear. The purpose of this study was to assess health-related quality of life and functional outcome after posterior fixation of lumbar burst fractures with either posterolateral or intrabody bone grafting. Twenty-four subjects were included. Radiographs and computed tomography scans were evaluated for deformity (kyphosis, vertebral compression, lateral angulation, lateral body height, and canal compromise) postoperatively, at 1 year, and at final follow-up (mean 3.2 years). Patients completed the SF 36 Health Survey and the Oswestry Low Back Pain Disability Questionnaire at final follow-up. Significant improvement was noted in midsagittal diameter compromise, vertebral compression, and kyphosis. The difference observed between the respondents mean scores on the SF 36 was not significantly different from those presented as the U.S. national average (p = 0.053). Data from the Oswestry questionnaire indicated a similarly high level of function. Overall, we found posterior spinal instrumentation to correlate with positive functional outcome based on both general health (SF 36) and joint-specific outcome scales (Oswestry). Posterior instrumentation provides sound canal decompression, kyphotic reduction, and maintains vertebral height with minimal transgression and long-term sequelae. In cases of severe initial deformity and neurologic compromise, intrabody bone grafting is most certainly indicated; the additional support provided by a posterolateral graft may also prove beneficial as an adjunct.

Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or "haplotypes." However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

RAVAR: a curated repository for rare variant-trait associations

Rare variants contribute significantly to the genetic causes of complex traits, as they can have much larger effects than common variants and account for much of the missing heritability in genome-wide association studies. The emergence of UK Biobank scale datasets and accurate gene-level rare variant-trait association testing methods have dramatically increased the number of rare variant associations that have been detected. However, no systematic collection of these associations has been carried out to date, especially at the gene level. To address the issue, we present the Rare Variant Association Repository (RAVAR), a comprehensive collection of rare variant associations. RAVAR includes 95 047 high-quality rare variant associations (76186 gene-level and 18 861 variant-level associations) for 4429 reported traits which are manually curated from 245 publications. RAVAR is the first resource to collect and curate published rare variant associations in an interactive web interface with integrated visualization, search, and download features. Detailed gene and SNP information are provided for each association, and users can conveniently search for related studies by exploring the EFO tree structure and interactive Manhattan plots. RAVAR could vastly improve the accessibility of rare variant studies. RAVAR is freely available for all users without login requirement at http://www.ravar.bio.

Aspiration cytology in the management of breast lesions

In a group of patients with breast lumps, diagnosis made by pre-operative aspiration cytology was compared with that obtained by histological section of excised specimens. Results showed that aspiration cytology correctly diagnosed 89% of malignant lesions and 92.6% of benign lesions based upon histological diagnosis. Cytological diagnosis of benign disease had a false negative rate of 6% while cytological diagnosis of malignant disease had a 2.7% false positive rate. Only 3.5% of cytologies returned an inadequate diagnosis. This study shows that aspiration cytology should be useful in allowing a better psychological preparation of patients before surgery as well as better utilization of operation theatre facilities.

EHR-HGCN: An Enhanced Hybrid Approach for Text Classification Using Heterogeneous Graph Convolutional Networks in Electronic Health Records

Text classification is a central part of natural language processing, with important applications in understanding the knowledge behind biomedical texts including electronic health records (EHR). In this article, we propose a novel heterogeneous graph convolutional network method for classifying EHR texts. Our method, called EHR-HGCN, is able to combine context-sensitive word and sentence embeddings with structural sentence-level and word-level relation information to perform text classification. EHR-HGCN reframes EHR text classification as a graph classification task to better capture structural information about the document using a heterogeneous graph. To mine contextual information from a document, EHR-HGCN first applies a bidirectional recurrent neural network (BiRNN) on word embeddings obtained via Global Vectors for word representation (GloVe) to obtain context-sensitive word-level and sentence-level embeddings. To mine structural relationships from the document, EHR-HGCN then constructs a heterogeneous graph over the word and sentence embeddings, where sentence-word and word-word relationships are represented by graph edges. Finally, a heterogeneous graph convolutional neural network is used to classify documents by their graph representation. We evaluate EHR-HGCN on a variety of standard text classification benchmarks and find that EHR-HGCN has higher accuracy and F1-score than other representative machine learning and deep learning methods. We also apply EHR-HGCN to the MedLit benchmark and find it performs with high accuracy and F1-score on the task of section classification in EHR texts. Our ablation experiments show that the heterogeneous graph construction and heterogeneous graph convolutional network are critical to the performance of EHR-HGCN.

Production of B cell growth factor(s) by neoplastic B cells from hairy cell leukemia patients

Recent studies have shown that normal human T cells contain a high-molecular-weight (mol wt) protein exhibiting B cell growth factor (BCGF) activity. Other studies have shown that virally transformed human B cells also secrete a high-mol-wt BCGF-like molecule in vitro. We have studied neoplastic B cells from patients with untreated hairy cell leukemia (HCL) to ascertain whether such cytoplasmic BCGF activity is present in the tumor cells. Studies on HCL cells from four patients indicated that BCGF-like activity was in fact present in the cytosolic extracts when tested on autochthonous HCL cells as well as on normal BCGF-dependent human B cell lines. Chromatographic analysis indicated that the BCGF activity from HCL cells was similar in mol wt as well as function to the normal T cell-derived cytosolic BCGF activity. These studies suggest that HCL cells contain and, in some cases, secrete a high-mol-wt growth factor that can be autostimulatory and appears to resemble a similar growth factor molecule found in normal human T cells.