Differential transcript usage analysis incorporating quantification uncertainty via compositional measurement error regression modeling.

Differential transcript usage (DTU) occurs when the relative expression of multiple transcripts arising from the same gene changes between different conditions. Existing approaches to detect DTU often rely on computational procedures that can have speed and scalability issues as the number of samples increases. Here we propose a new method, CompDTU, that uses compositional regression to model the relative abundance proportions of each transcript that are of interest in DTU analyses. This procedure leverages fast matrix-based computations that make it ideally suited for DTU analysis with larger sample sizes. This method also allows for the testing of and adjustment for multiple categorical or continuous covariates. Additionally, many existing approaches for DTU ignore quantification uncertainty in the expression estimates for each transcript in RNA-seq data. We extend our CompDTU method to incorporate quantification uncertainty leveraging common output from RNA-seq expression quantification tool in a novel method CompDTUme. Through several power analyses, we show that CompDTU has excellent sensitivity and reduces false positive results relative to existing methods. Additionally, CompDTUme results in further improvements in performance over CompDTU with sufficient sample size for genes with high levels of quantification uncertainty, while also maintaining favorable speed and scalability. We motivate our methods using data from the Cancer Genome Atlas Breast Invasive Carcinoma data set, specifically using RNA-seq data from primary tumors for 740 patients with breast cancer. We show greatly reduced computation time from our new methods as well as the ability to detect several novel genes with significant DTU across different breast cancer subtypes.

Tumor Immunogenomic Features Determine Outcomes in Patients with Metastatic Colorectal Cancer Treated with Standard-of-Care Combinations of Bevacizumab and Cetuximab.

PURPOSE: CALGB/SWOG 80405 was a randomized phase III trial in first-line patients with metastatic colorectal cancer treated with bevacizumab, cetuximab, or both, plus chemotherapy. We tested the effect of tumor immune features on overall survival (OS). EXPERIMENTAL DESIGN: Primary tumors (N = 554) were profiled by RNA sequencing. Immune signatures of macrophages, lymphocytes, TGFß, IFNγ, wound healing, and cytotoxicity were measured. CIBERSORTx scores of naive and memory B cells, plasma cells, CD8+ T cells, resting and activated memory CD4+ T cells, M0 and M2 macrophages, and activated mast cells were measured. RESULTS: Increased M2 macrophage score [HR, 6.30; 95% confidence interval (CI), 3.0-12.15] and TGFß signature expression (HR, 1.35; 95% CI, 1.05-1.77) were associated with shorter OS. Increased scores of plasma cells (HR, 0.55; 95% CI, 0.38-0.87) and activated memory CD4+ T cells (HR, 0.34; 95% CI, 0.16-0.65) were associated with longer OS. Using optimal cutoffs from these four features, patients were categorized as having either 4, 3, 2, or 0-1 beneficial features associated with longer OS, and the median (95% CI) OS decreased from 42.5 (35.8-47.8) to 31.0 (28.8-34.4), 25.2 (20.6-27.9), and 17.7 (13.5-20.4) months respectively (P = 3.48e-11). CONCLUSIONS: New immune features can be further evaluated to improve patient response. They provide the rationale for more effective immunotherapy strategies.

Compression of quantification uncertainty for scRNA-seq counts.

MOTIVATION: Quantification estimates of gene expression from single-cell RNA-seq (scRNA-seq) data have inherent uncertainty due to reads that map to multiple genes. Many existing scRNA-seq quantification pipelines ignore multi-mapping reads and therefore underestimate expected read counts for many genes. alevin accounts for multi-mapping reads and allows for the generation of 'inferential replicates', which reflect quantification uncertainty. Previous methods have shown improved performance when incorporating these replicates into statistical analyses, but storage and use of these replicates increases computation time and memory requirements. RESULTS: We demonstrate that storing only the mean and variance from a set of inferential replicates ('compression') is sufficient to capture gene-level quantification uncertainty, while reducing disk storage to as low as 9% of original storage, and memory usage when loading data to as low as 6%. Using these values, we generate 'pseudo-inferential' replicates from a negative binomial distribution and propose a general procedure for incorporating these replicates into a proposed statistical testing framework. When applying this procedure to trajectory-based differential expression analyses, we show false positives are reduced by more than a third for genes with high levels of quantification uncertainty. We additionally extend the Swish method to incorporate pseudo-inferential replicates and demonstrate improvements in computation time and memory usage without any loss in performance. Lastly, we show that discarding multi-mapping reads can result in significant underestimation of counts for functionally important genes in a real dataset. AVAILABILITY AND IMPLEMENTATION: makeInfReps and splitSwish are implemented in the R/Bioconductor fishpond package available at https://bioconductor.org/packages/fishpond. Analyses and simulated datasets can be found in the paper's GitHub repo at https://github.com/skvanburen/scUncertaintyPaperCode. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chronic E-Cigarette Exposure Alters the Human Bronchial Epithelial Proteome.

RATIONALE: E-cigarettes vaporize propylene glycol/vegetable glycerin (PG/VG), nicotine, and flavorings. However, the long-term health effects of exposing lungs to vaped e-liquids are unknown. OBJECTIVES: To determine the effects of chronic vaping on pulmonary epithelia. METHODS: We performed research bronchoscopies on healthy nonsmokers, cigarette smokers, and e-cigarette users (vapers) and obtained bronchial brush biopsies and lavage samples from these subjects for proteomic investigation. We further employed in vitro and murine exposure models to support our human findings. MEASUREMENTS AND MAIN RESULTS: Visual inspection by bronchoscopy revealed that vaper airways appeared friable and erythematous. Epithelial cells from biopsy samples revealed approximately 300 proteins that were differentially expressed in smoker and vaper airways, with only 78 proteins being commonly altered in both groups and 113 uniquely altered in vapers. For example, CYP1B1 (cytochrome P450 family 1 subfamily B member 1), MUC5AC (mucin 5 AC), and MUC4 levels were increased in vapers. Aerosolized PG/VG alone significantly increased MUC5AC protein in human airway epithelial cultures and in murine nasal epithelia in vivo. We also found that e-liquids rapidly entered cells and that PG/VG reduced membrane fluidity and impaired protein diffusion. CONCLUSIONS: We conclude that chronic vaping exerts marked biological effects on the lung and that these effects may in part be mediated by the PG/VG base. These changes are likely not harmless and may have clinical implications for the development of chronic lung disease. Further studies will be required to determine the full extent of vaping on the lung.

Longitudinal T1 relaxation rate (R1) captures changes in short-term Mn exposure in welders.

OBJECTIVES: We demonstrated recently that the T1 relaxation rate (R1) captured short-term Mn exposure in welders with chronic, relatively low exposure levels in a cross-sectional study. In the current study, we used a longitudinal design to examine whether R1 values reflect the short-term dynamics of Mn exposure. METHODS: Twenty-nine welders were evaluated at baseline and 12 months. Occupational questionnaires estimated short-term welding exposure using welding hours in the 90days prior to each study visit (HrsW90). In addition, blood Mn levels, the pallidal index (PI; globus pallidus T1-weighted intensity (T1WI)/frontal white matter T1WI), and R1 values in brain regions of interest (ROIs) were determined as Mn biomarkers at each visit. Associations between changes in estimated welding exposure and changes in purported Mn biomarkers were assessed by Spearman's correlations with adjustment for age and baseline R1, HrsW90, and blood Mn values. RESULTS: Changes in welding hours (HrsW90: the short-term welding exposure estimate), was associated significantly with changes in R1 values in the putamen (r=0.541, p=0.005), caudate (R=0.453, p=0.023), globus pallidus (R=0.430, p=0.032), amygdala (R=0.461, p=0.020), and hippocampus (R=0.447, p=0.025), but not with changes in blood Mn levels or the PI. DISCUSSION: Changes in R1 values correlated with changes in the short-term welding exposure estimate, but not with more traditional measures of Mn exposure (blood Mn levels or PI). These results suggest that R1 may serve as a useful marker to capture the short-term dynamics in Mn brain accumulation related to welding exposure.

Editor's Highlight: Lower Fractional Anisotropy in the Globus Pallidus of Asymptomatic Welders, a Marker for Long-Term Welding Exposure.

INTRODUCTION: Welding fumes contain several metals including manganese (Mn), iron (Fe), and copper (Cu) that at high exposure may co-influence welding-related neurotoxicity. The relationship between brain accumulation of these metals and neuropathology, especially in welders with subclinical exposure levels, is unclear. This study examined the microstructural integrity of basal ganglia (BG) regions in asymptomatic welders using diffusion tensor imaging (DTI). METHODS: Subjects with (n = 43) and without (age- and gender-matched controls; n = 31) history of welding were studied. Occupational questionnaires estimated short-term (HrsW; welding hours and E90; cumulative exposure, past 90 days) and long-term (YrsW; total years welding and ELT; cumulative exposure, lifetime) exposure. Whole blood metal levels (Mn, Fe, and Cu) were obtained. Brain MRI pallidal index (PI), R1 (1/T1), and R2* (1/T2*) were measured to estimate Mn and Fe accumulation in BG [caudate, putamen, and globus pallidus (GP)]. DTI was used to assess BG microstructural differences, and related with exposure measurements. RESULTS: When compared with controls, welders had significantly lower fractional anisotropy (FA) in the GP. In welders, GP FA values showed non-linear relationships to YrsW, blood Mn, and PI. GP FA decreased after a critical level of YrsW or Mn was reached, whereas it decreased with increasing PI values until plateauing at the highest PI values. GP FA, however, did not show any relationship with short-term exposure measurements (HrsW, E90), blood Cu and Fe, or R(2)* values. CONCLUSION: GP FA captured microstructural changes associated with chronic low-level Mn exposure, and may serve as a biomarker for neurotoxicity in asymptomatic welders.

Increased R2* in the Caudate Nucleus of Asymptomatic Welders.

Welding has been associated with neurobehavioral disorders. Welding fumes contain several metals including copper (Cu), manganese (Mn), and iron (Fe) that may interact to influence welding-related neurotoxicity. Although welding-related airborne Fe levels are about 10-fold higher than Mn, previous studies have focused on Mn and its accumulation in the basal ganglia. This study examined differences in the apparent transverse relaxation rates [R2* (1/T2*), estimate of Fe accumulation] in the basal ganglia (caudate nucleus, putamen, and globus pallidus) between welders and controls, and the dose-response relationship between estimated Fe exposure and R2* values. Occupational questionnaires estimated recent and lifetime Fe exposure, and blood Fe levels and brain magnetic resonance imaging (MRI) were obtained. Complete exposure and MRI R2* and R1 (1/T1: measure to estimate Mn accumulation) data from 42 subjects with welding exposure and 29 controls were analyzed. Welders had significantly greater exposure metrics and higher whole-blood Fe levels compared with controls. R2* in the caudate nucleus was significantly higher in welders after controlling for age, body mass index, respirator use, caudate R1, and blood metals of Cu and Mn, whereas there was no difference in R1 values in the basal ganglia between groups. The R2* in the caudate nucleus was positively correlated with whole-blood Fe concentration. This study provides the first evidence of higher R2* in the caudate nucleus of welders, which is suggestive of increased Fe accumulation in this area. Further studies are needed to replicate the findings and determine the neurobehavioral relevance.

T1 Relaxation Rate (R1) Indicates Nonlinear Mn Accumulation in Brain Tissue of Welders With Low-Level Exposure.

Although the essential element manganese (Mn) is neurotoxic at high doses, the effects of lower exposure are unclear. MRI T1-weighted (TIW) imaging has been used to estimate brain Mn exposure via the pallidal index (PI), defined as the T1W intensity ratio in the globus pallidus (GP) versus frontal white matter (FWM). PI may not, however, be sensitive to Mn in GP because Mn also may accumulate in FWM. This study explored: (1) whether T1 relaxation rate (R1) could quantify brain Mn accumulation more sensitively; and (2) the dose-response relationship between estimated Mn exposure and T1 relaxation rate (R1). Thirty-five active welders and 30 controls were studied. Occupational questionnaires were used to estimate hours welding in the past 90 days (HrsW) and lifetime measures of Mn exposure. T1W imaging and T1-measurement were utilized to generate PI and R1 values in brain regions of interest (ROIs). PI did not show a significant association with any measure of Mn and/or welding-related exposure. Conversely, in several ROIs, R1 showed a nonlinear relationship to HrsW, with R1 signal increasing only after a critical exposure was reached. The GP had the greatest rate of Mn accumulation. Welders with higher exposure showed significantly higher R1 compared either with controls or with welders with lower exposure. Our data are additional evidence that Mn accumulation can be assessed more sensitively by R1 than by PI. Moreover, the nonlinear relationship between welding exposure and Mn brain accumulation should be considered in future studies and policies.