Jie Chen

Analysis of multiple types of omics data facilitates a comprehensive revelation of molecular-level complexity and interactions among genomic features. This knowledge promotes the development of new therapies for treating different genomic diseases. An integrative study of multiple types of genomic data instead of a single type of genomic data will be more informative in understanding the complicated molecular activities and their interactions. In this work, we integrated RNA-sequencing (RNA-seq), methylation, and DNA copy number variation data, downloaded from the TCGA public repository, of glioblastoma multiforme (GBM), reduced the dimension of these high-dimensional genomic data using an autoencoder, a deep learning-based method, and then used Cox-PH model to select the autoencoder-transformed features that have a significant contribution to patient survival. We utilized the significant set of autoencoder-transformed features to classify the survival subtypes using the integrated data. We built a classification model with a penalization technique, sparse group LASSO, and evaluated the approach using cross-validation. As a result, two survival subgroups, with overall different survival profiles and linking to various genomic features, are discovered for respective GBM patients. Finally, the results are interpreted biologically by differential expression analysis and pathway analysis.

The aryl hydrocarbon receptor (AhR) is proposed to mediate the frailty-promoting effects of the tryptophan metabolite kynurenine, which increases with age in mice and humans. The goal of the current study was to test whether administration of pharmacological AhR inhibitors, BAY2416964 and CH-223191, could abrogate musculoskeletal decline in aging mice. Female C57BL/6 mice (18 months old) were treated with vehicle (VEH) or 30 mg/kg BAY2416964 (BAY) via daily oral gavage 5 days/week for 8 weeks. A second AhR antagonist, CH-223191, was administered to 16-month-old male and female C57BL/6 mice via intraperitoneal injections (3.3 mg/kg) 3 days/week for 12 weeks. While grip strength declined over time in VEH-treated mice, BAY preserved grip strength in part by improving integrity of neuromuscular junctions (NMJs), an effect replicated during in vitro studies with siRNA against AhR. Cortical bone mass was also greater in BAY- than VEH-treated mice. Similarly, CH-223191 treatment improved cortical bone and showed beneficial effects in skeletal muscle, including reducing oxidative stress as compared with VEH-treated animals. Transcriptomic and proteomic data from BAY-treated mice supported a positive impact of BAY on molecular targets that affect NMJ function. Taken together, these data support AhR as a therapeutic target for improving musculoskeletal health during aging.

BACKGROUND: Although combination antiretroviral therapy has increased life expectancy in people living with HIV, it has led to a marked increase in the prevalence of hypertension, the cause of which is unknown. Despite combination antiretroviral therapy, HIV-derived proteins remain expressed and produced by CD4 ⁺ T lymphocytes in people living with HIV. However, their contribution to HIV-associated hypertension and impaired endothelium-dependent relaxation remains ill defined. METHODS: Here, we tested the hypothesis that CD4 ⁺ T cells expressing viral proteins contribute to endothelial dysfunction and hypertension using the Tg26 mouse model of HIV that expresses 7 of the 9 HIV proteins under the long terminal repeat promoter. We used male and female mice, bone marrow transplantation (BMT), adoptive transfer of CD4 ⁺ T cells, and aorta specimen discarded from people living with HIV. RESULTS: We reported that intact Tg26 mice and mice receiving BMT (Tg26→WT) or CD4 ⁺ T cells from Tg26 mice display impaired endothelium-dependent relaxation and hypertension. Conversely, BMT from WT mice into Tg26 mice, inhibition of T cell activation, and CD4 ⁺ T cell depletion restored endothelial function and blood pressure in Tg26 mice. Cytokine profiling revealed that Tg26 mice, Tg26→WT, and Tg26 CD4 ⁺ T cells consistently exhibit high interleukin 1α (IL-1α) levels with no significant increase in other cytokines, whereas BMT from WT mice into Tg26 mice reduced IL-1α levels. IL-1α neutralization reduced blood pressure and restored endothelial function in Tg26 mice. To investigate the role of CD4 ⁺ T cells and IL-1α in endothelial dysfunction, we developed an aorta-immune cell coculture system. Exposure of WT aortas to Tg26 CD4 ⁺ T cells impaired endothelium-dependent relaxation, which was blocked by IL-1α–neutralizing antibody. While investigating the mechanisms of endothelial dysfunction, we reported that Tg26 mice, Tg26→WT aorta exhibit high NADPH oxidase (NOX) 1 expression. IL-1α exposure increased NOX1 in human microvascular endothelial cells, and NOX1 blockade restored endothelial function in Tg26 and Tg26→WT arteries, whereas NOX1 deficiency protected against Tg26 BMT-induced impaired endothelium-dependent relaxation and hypertension. Aortas from people living with HIV exhibit high NOX1 levels, and exposure of human aorta to Tg26 T cells increased NOX1 expression. CONCLUSIONS: We provide the first evidence that CD4 ⁺ T cells expressing HIV viral proteins induced hypertension through IL-1α–mediated increases in vascular NOX1, which impairs endothelial function in males and females.

DNA methylation and copy number may be associated with each other to some extent, in positive or negative ways. Whether differential methylation and copy number variation have combined effects on gene expression is largely unknown. We use a multivariate linear model to formulate the relationship among the three genomic measurements, gene expression, copy number, and methylation levels. We propose a method that combines a distance covariance measure and the group LASSO to analyze multiple types of genomic data collectively for the purpose of insightfully revealing how gene expression is potentially affected by both copy number variation and differential methylation levels in cellular process. Our approach is of two stages, the first is a variable screening process in which a variable selection method is utilized by employing the concept of joint distance covariance (JdCov) of random vectors, and the second is to implement a penalized regression approach, a group LASSO, on the screened data of much lower dimension. The two-stage approach is tested in extensive simulation studies and shown to be effective. The approach is then applied to the TCGA Melanoma data, which consists of gene expression, methylation and copy number measurements of more than 300 patients and relationship of some genes with methylation and copy number measurements were revealed for the involved subjects.

This study examines the influence of various individual demographic and risk factors on the use of unscheduled healthcare (emergency and inpatient visits) among pediatric outpatients with asthma over three retrospective timeframes (12, 18, and 24 months) at an academic health center. Out of a total of 410 children who visited an academic medical center for asthma outpatient care between 2019 and 2020, 105 (26%) were users of unscheduled healthcare for childhood asthma over the prior 12 months, 131 (32%) over the prior 18 months, and 147 (36%) over the prior 24 months. multiple logistic regression (MLR) analysis of the effect of individual risk factors revealed that asthma severity, age of child, and clinic no-shows were statistically significant predictors of unscheduled healthcare use for childhood asthma. Children with higher levels of asthma severity were significantly more likely to use unscheduled healthcare (compared to children with lower levels of asthma severity) across all three timeframes. Likewise, children with three to four clinic no-shows were significantly more likely to use unscheduled healthcare compared to children with zero clinic no-shows in the short term (12 and 18 months). In contrast, older children were significantly less likely to use unscheduled healthcare use compared to younger children in the longer term (24 months). By virtue of its scope and design, this study provides a foundation for addressing a need identified in the literature for short- and long-term strategies for improving supported self-management and reducing unscheduled healthcare use for childhood asthma at the patient, provider, and organizational levels, e.g., (1) implementing telehealth services for asthma outpatient care to reduce clinic no-shows across all levels of asthma severity in the short term; (2) developing a provider–patient partnership to enable patient-centered asthma control among younger children with higher asthma severity in the long term; and (3) identifying hospital–community linkages to address social risk factors influencing clinic no-shows and unscheduled healthcare use among younger children with higher asthma severity in the long term.

Trigger finger is a common yet vastly understudied fibroproliferative hand pathology, severely affecting patients’ quality of life. Consistent trauma due to inadequate positioning within the afflicted finger’s tendon/pulley system leads to cellular dysregulation and eventual fibrosis. While the genetic characteristics of the fibrotic tissue in the trigger finger have been studied, the pathways that govern the initiation and propagation of fibrosis are still unknown. The complete gene expression profile of the trigger finger has never been explored. Our study has used the Nanostring nCounter gene expression assay to investigate the molecular signaling involved in trigger finger pathogenesis. We collected samples from patients undergoing trigger finger (n = 4) release surgery and compared the gene expression to carpal tunnel tissue (n = 4). Nanostring nCounter analysis identified 165 genes that were differentially regulated; 145 of these genes were upregulated, whereas 20 genes were downregulated. We found that several collagen genes were significantly upregulated, and a regulatory matrix metalloproteinase (MMP), MMP-3, was downregulated. Bioinformatic analysis revealed that several known signaling pathways were dysregulated, such as the TGF-β1 and Wnt signaling pathways. We also found several novel signaling pathways (e.g., PI3K, MAPK, JAK-STAT, and Notch) differentially regulated in trigger finger. The outcome of our study helps in understanding the molecular signaling pathway involved in the pathogenesis of the trigger finger.

The next-generation sequencing (NGS) technology has revolutionized research in genetics and genomics, resulting in massive NGS data and opening more fronts to answer unresolved issues in genetics. NGS data are usually stored at three levels: image files, sequence tags, and alignment reads. The sizes of these types of data usually range from several hundreds of gigabytes to several terabytes. Biostatisticians and bioinformaticians are typically working with the aligned NGS read count data (hence the last level of NGS data) for data modeling and interpretation. To horn in on the use of NGS technology, researchers utilize it to profile the whole genome to study DNA copy number variations (CNVs) for an individual subject (or patient) as well as groups of subjects (or patients). The resulting aligned NGS read count data are then modeled by proper mathematical and statistical approaches so that the loci of CNVs can be accurately detected. In this book chapter, a summary of most popularly used statistical methods for detecting CNVs using NGS data is given. The goal is to provide readers with a comprehensive resource of available statistical approaches for inferring DNA copy number variations using NGS data.