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Huo, Z.

Publications and source records attributed to Huo, Z..

14 recordsLinked to original sources

CosinorTest: An R Shiny App for Cosinor-model-based circadian and differential analysis in transcriptomic applications

Summary CosinorTest application is an interactive R Shiny tool designed to facilitate circadian and differential circadian analysis with transcriptomic data using Cosinor-model-based methods. This novel application integrates multiple major statistical algorithms to identify circadian rhythmicity in gene expression data and enables the comparison of differential circadian patterns between two experimental conditions. Key features of the CosinorTest app include circadian rhythmicity detection, differential patterns assessment, circadian and differential analyses with repeated measurement, and interactive data visualization, all contributing to a comprehensive understanding of underlying biological mechanisms. As the application doing all comprehensive circadian analysis using the Cosinor model, the CosinorTest app fills a crucial gap in the field of circadian biology and transcriptomics, providing a powerful and user-friendly platform for researchers, especially those without profound programming skills to explore the circadian gene expression regulation, and further advance circadian research. Availability and implementationCosinorTest is freely available at https://circadiananalysis.shinyapps.io/circadianapp/. Contacthading@augusta.edu Supplementary informationSupplementary files are available at bioR{chi}iv online.

bioinformatics↗

A Bayesian Framework for Genome-wide Circadian Rhythmicity Biomarker Detection

Circadian rhythms are endogenous [~]24-hour cycles that significantly influence physiological and behavioral processes. These rhythms are governed by a transcriptional-translational feedback loop of core circadian genes and are essential for maintaining overall health. The study of circadian rhythms has expanded into various omics datasets, necessitating accurate analytical methodology for circadian biomarker detection. Here, we introduce a novel Bayesian framework for the genome-wide detection of circadian rhythms that is capable of incorporating prior biological knowledge and adjusting for multiple testing issue via a false discovery rate approach. Our framework leverages a Bayesian hierarchical model and employs a reverse jump Markov chain Monte Carlo (rjMCMC) technique for model selection. Through extensive simulations, our method, BayesCircRhy, demonstrated superior false discovery rate control over competing methods, robustness against heavier-tailed error distributions, and better performance compared to existing approaches. The methods efficacy was further validated in two RNA-Sequencing data, including a human resitrcted feeding data and a mouse aging data, where it successfully identified known and novel circadian genes. R package "BayesianCircadian" for the method is publicly available on GitHub https://github.com/jxncdhc/BayesianCircadian.

bioinformatics↗

AB-free kava enhances resilience against the adverse health effects of tobacco smoke in mice

Tobacco smoke remains a serious global issue, resulting in serious health complications, contributing to the onsets of numerous preventive diseases, and imposing significant financial burdens. Despite regulatory policies and cessation measures aimed at curbing its usage, novel interventions are urgently needed for effective damage reduction. Our preclinical and pilot clinical studies showed that AB-free kava has the potential to reduce tobacco smoke-induced lung cancer risk, mitigate tobacco dependence, and reduce tobacco use. To understand the scope of its benefits in damage reduction and potential limitations, this study evaluated the effects of AB-free kava on a panel of health indicators in mice exposed to 2 - 4 weeks of daily tobacco smoke exposure. Our comprehensive assessments included global transcriptional profiling of the lung and liver tissues, analysis of lung inflammation, evaluation of lung function, exploration of tobacco nicotine withdrawal, and characterization of the causal PKA signaling pathway. As expected, Tobacco smoke exposure perturbed a wide range of biological processes and compromised multiple functions in mice. Remarkably, AB-free kava demonstrated the ability to globally mitigate tobacco smoke-induced deficits at the molecular and functional levels with promising safety profiles, offering a unique promise to mitigate tobacco smoke-related health damages. Further pre-clinical evaluation and clinical translation are warranted to fully harness the potential of AB-free kava in combating tobacco smoke-related harms. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/599576v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1f6ee4corg.highwire.dtl.DTLVardef@96e062org.highwire.dtl.DTLVardef@16579a0org.highwire.dtl.DTLVardef@1140a8e_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

New role of cardiomyocyte Bmal1 in the regulation of sex-specific heart transcriptomes

It has been well established that cardiovascular diseases exhibit significant differences between sexes in both preclinical models and humans. In addition, there is growing recognition that disrupted circadian rhythms can contribute to the onset and progression of cardiovascular diseases. However little is known about sex differences between the cardiac circadian clock and circadian transcriptomes in mice. Here, we show that the the core clock genes are expressed in common in both sexes but the circadian transcriptome of the mouse heart is very sex-specific. Hearts from female mice expressed significantly more rhythmically expressed genes (REGs) than male hearts and the temporal pattern of REGs was distinctly different between sexes. We next used a cardiomyocyte-specific knock out of the core clock gene, Bmal1, to investigate its role in sex-specific gene expression in the heart. All sex differences in the circadian transcriptomes were significantly diminished with cardiomyocyte-specific loss of Bmal1. Surprisingly, loss of cardiomyocyte Bmal1 also resulted in a roughly 8-fold reduction in the number of all the differentially expressed genes between male and female hearts. We conclude that cardiomyocyte-specific Bmal1, and potentially the core clock mechanism, is vital in conferring sex-specific gene expression in the adult mouse heart.

physiology↗

Proteomic Stratification of Prognosis and Treatment Options for Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a highly malignant and heterogeneous cancer with limited therapeutic options and prognosis prediction models. Here, we analyzed formalin-fixed, paraffin-embedded (FFPE) samples of surgical resections by proteomic profiling, and stratified SCLC into three proteomic subtypes (S-I, S-II, and S-III) with distinct clinical outcomes and chemotherapy responses. The proteomic subtyping was an independent prognostic factor and performed better than current TNM or Veterans Administration Lung Study Group (VALG) staging methods. The subtyping results could be further validated using FFPE biopsy samples from an independent center, extending the analysis to both surgical and biopsy samples. The signatures of the S-II subtype in particular suggest potential benefits from immunotherapy. Differentially overexpressed proteins in S-III, the worst prognostic subtype, allowed us to nominate potential therapeutic targets, indicating that patient selection may bring new hope for previously failed clinical trials. Finally, analysis of an independent cohort of SCLC patients who had received immunotherapy validated the prediction that the S-II patients had better Progression Free Survival (PFS) and Overall Survival (OS) after first-line immunotherapy. Collectively, our study provides the rationale for future clinical investigations to validate the current findings for more accurate prognosis prediction and precise treatments.

cancer biology↗

Profiling plasma extracellular vesicle-derived microRNAs for noninvasive diagnosis of alpha-1 antitrypsin deficiency associated liver disease

Alpha-1 antitrypsin deficiency (AATD) is a rare genetic disease characterized by reduced circulating levels of alpha-1 antitrypsin (AAT) due to the retention of misfolded AAT in the hepatocytes. The toxic AAT aggregates in hepatocytes cause liver fibrosis, cirrhosis, and hepatocellular carcinoma. Most patients remain asymptomatic until the final stage in which liver transplantation becomes the only treatment. Timely diagnosis of AATD liver disease plays a critical role in intervention and finding curative solutions. Assessing the prevalence and severity of AATD liver disease remains challenging due to limitations in current methods. Liver biopsy, the gold standard for evaluating the hepatic AAT accumulation, the initiating stage for AATD liver disease, is hindered by invasiveness and sampling errors. To address these limitations, we conducted a study using unique and precious clinical samples. We analyzed plasma extracellular vesicle (EV) derived miRNAs and liver transcriptomes from AATD individuals to develop a sensitive and noninvasive diagnostic approach for AATD liver disease. In the testing stage of our study, we enrolled 17 AATD individuals with different stages of liver disease, as determined by liver biopsy, and 20 controls. We identified differential expression of 178 miRNAs within the AATD group compared to controls by miRNA sequencing. Among those miRNAs, we selected miR-223-3p, miR-23a-3p, miR-15b-5p, let-7a-5p, let-7f-5p, and miR-374a-5p for further validation in an independent cohort of 45 AATD individuals. Using a logistic model that combined three miRNAs, we achieved an AUC of 0.737 for detecting AATD liver disease. Adding a fourth miRNA into this model increased the AUC to 0.751. The changes in EV miRNAs are correlated to dysregulated expression of liver mRNAs in AATD individuals with different stages of liver disease. We propose that plasma-circulating EV exhibit distinct miRNAs in AATD individuals and could serve as clinically significant biomarkers for the early detection of AATD liver disease.

molecular biology↗

Cortical gradient perturbation in attention deficit hyperactivity disorder correlates with neurotransmitter-, cell type-specific and chromosome- transcriptomic signatures

Neurofunctional dysregulations in spatially discrete areas or isolated pathways have been suggested as neural markers for attention deficit hyperactivity disorder (ADHD). However, multiscale perspectives into the neurobiological underpins of ADHD spanning multiple biological systems remain sparse. This points to the need of multi-levels of analysis encompassing brain functional organization and its correlation with molecular and cell-specific transcriptional signatures are stressed. Here, we capitalized on diffusion mapping embedding model to derive the functional connectome gradient, and deployed multivariate partial least square (PLS) method to uncover the enrichment of neurotransmitomic, cellular and chromosomal connectome-transcriptional signatures of ADHD. Compared to typical control, ADHD children presented connectopic cortical perturbations in lateral orbito-frontal and superior temporal regions, which had also been validated in another independent sample. This gradient-derived variants in ADHD further aligned spatially with distributions of GABAA/BZ and 5-HT2A receptors and co-varied with genetic transcriptional expression. Cognitive decoding and gene-expression annotation showed the correlates of these variants in memory, emotional regulation and spatial attention. Moreover, the gradient-derived transcriptional signatures of ADHD exhibited enriched expression of oligodendrocyte precursors and endothelial cells, and were mainly involved as variants of chromosome 18, 19 and X. In conclusion, our findings bridged in-vivo neuroimging assessed functional brain organization patterns to a multi-level molecular pathway in ADHD, possibly shedding light on the interrelation of biological systems that may coalesce to the emergence of this disorder.

neuroscience↗

Statistical Methods for Detecting Circadian Rhythmicity and Differential Circadian Patterns with Repeated Measurement in Transcriptomic Applications

Circadian analysis via transcriptomic data has been successful in revealing the clock output changes underlying many diseases and physiological processes. Repeated measurement design in a circadian study is prevalent, in which the same subject is repeatedly measured over time. Several methods are currently available to perform circadian analysis, however, none of them take advantage of the repeated measurement design. And ignoring the within-subject correlation from the repeated measurement could result in lower statistical power. To address this issue, we developed linear mixed model based methods to detect (i) circadian rhythmicity (i.e., Rpt_rhythmicity) and (ii) differential circadian patterns comparing two experimental conditions (i.e., Rpt_diff). Our model includes a subject-specific random effect, which will account for the within-subject correlation. Via simulations, we showed our method not only could control the type I error rate around the nominal level, but also achieve higher statistical power compared to other methods that cannot model repeated measurement. The superior performance of Rpt_rhythmicity and Rpt_diff were also demonstrated in two real data applications, including a human restricted feeding data and a human sleep restriction data. An R package for our methods is publicly available on GitHub to promote the application of our methods.

bioinformatics↗

Defining the age-dependent and tissue-specific circadian transcriptome in male mice

Cellular circadian clocks direct a daily transcriptional program that supports homeostasis and resilience. Emerging evidence supports age-associated changes in circadian functions. To define age-dependent changes at the systems level, we profiled the circadian transcriptome in the hypothalamus, lung, heart, kidney, skeletal muscle, and adrenal gland in 3 age groups. We found age-dependent and tissue-specific clock output changes. Aging reduced the number of rhythmically expressed genes (REGs), indicative of weakened circadian control. Many genes gained rhythmicity in old tissues, reflecting an adaptive response. REGs were enriched for the hallmarks of aging, adding a new dimension to our understanding of aging. Differential gene expression analysis found that there were temporally distinct clusters of genes in tissue-specific manner. Increased daily gene expression variability is a common feature of aged tissues. This novel analysis extends the landscape of the understanding of aging and highlights the impact of aging on circadian clock function and temporal changes in gene expression. HIGHLIGHTS- Rhythmically expressed genes (REGs) in Young, but not Old mice, are enriched for the aging hallmarks across all tissues. - The numbers of REGs decline across all tissues with age implicating the circadian clock in altered homeostasis. - Age- and tissue-specific differentially expressed genes (DEGs) cluster at specific times of the day. - Increase in gene expression variability over a day is a common feature of aging tissues.

genomics↗

Experimental Design and Power Calculation in Omics Circadian Rhythmicity Detection

Circadian clocks are 24-hour endogenous oscillators in physiological and behavioral processes. Though recent transcriptomic studies have been successful in revealing the circadian rhythmicity in gene expression, the power calculation for omics circadian analysis have not been fully explored. In this paper, we develop a statistical method, namely CircaPower, to perform power calculation for circadian pattern detection. Our theoretical framework is determined by three key factors in circadian gene detection: sample size, intrinsic effect size and sampling design. Via simulations, we systematically investigate the impact of these key factors on circadian power calculation. We not only demonstrate that CircaPower is fast and accurate, but also show its underlying cosinor model is robust against variety of violations of model assumptions. In real applications, we demonstrate the performance of CircaPower using mouse pan-tissue data and human post-mortem brain data, and illustrate how to perform circadian power calculation using mouse skeleton muscle RNA-Seq pilot as case study. Our method CircaPower has been implemented in an R package, which is made publicly available on GitHub (https://github.com/circaPower/circaPower).

genomics↗

Disrupted circadian core-clock oscillations in Type 2 Diabetes are linked to altered rhythmic mitochondrial metabolism

Circadian rhythms are generated by an auto-regulatory feedback loop composed of transcriptional activators and repressors. Disruption of circadian rhythms contributes to Type 2 diabetes (T2D) pathogenesis. We elucidated whether altered circadian rhythmicity of clock genes is associated with metabolic dysfunction in T2D. Transcriptional cycling of core clock genes ARNTL, CLOCK, CRY1 and NR1D1 was altered in skeletal muscle from individuals with T2D and this was coupled with reduced number and amplitude of cycling genes and disturbed circadian oxygen consumption. Mitochondrial associated genes were enriched for differential circadian amplitudes in T2D, and positively correlated with insulin sensitivity. ChIP- sequencing identified CLOCK and BMAL1 binding to circadian mitochondrial genes associated with insulin sensitivity, implicating regulation by the core clock. Mitochondria disruption altered core-clock gene expression and free-radical production, phenomena that were restored by resveratrol treatment. We identify bi-directional communication between mitochondrial function and rhythmic gene expression, processes which are disturbed in diabetes.

physiology↗

Likelihood-based Tests for Detecting CircadianRhythmicity and Differential Circadian Patterns in Transcriptomic Applications

Circadian rhythmicity in transcriptomic profiles has been shown in many physiological processes, and the disruption of circadian patterns has been founded to associate with several diseases. In this paper, we developed a series of likelihood-based methods to detect (i) circadian rhythmicity (denoted as LR rhythmicity) and (ii) differential circadian patterns comparing two experimental conditions (denoted as LR diff). In terms of circadian rhythmicity detection, we demonstrated that our proposed LR rhythmicity could better control the type I error rate compared to existing methods under a wide variety of simulation settings. In terms of differential circadian patterns, we developed methods in detecting differential amplitude, differential phase, differential basal level, and differential fit, which also successfully controlled the type I error rate. In addition, we demonstrated that the proposed LR diff could achieve higher statistical power in detecting differential fit, compared to existing methods. The superior performance of LR rhythmicity and LR diff was demonstrated in two real data applications, including a brain aging data (gene expression microarray data of human postmortem brain) and a time-restricted feeding data (RNA sequencing data of human skeletal muscles). An R package for our methods is publicly available on GitHub https://github.com/diffCircadian/diffCircadian.

bioinformatics↗

The DAXX-SREBP axis promotes oncogenic lipogenesis and tumorigenesis

De novo lipogenesis produces lipids for membrane biosynthesis and cell signaling. Elevated lipogenesis is a major metabolic feature in cancer cells. In breast and other cancer types, genes involved in lipogenesis are highly upregulated, but the mechanisms that control their expression remain poorly understood. DAXX modulates gene expression through binding to diverse transcription factors although the functional impact of these diverse interactions remains to be defined. Our recent analysis indicates that DAXX is overexpressed in diverse cancer types. However, mechanisms underlying DAXXs oncogenic function remains elusive. Using global integrated transcriptomic and lipidomic analyses, we show that DAXX plays a key role in lipid metabolism. DAXX depletion attenuates, while its overexpression enhances, lipogenic gene expression, lipid synthesis and tumor growth. Mechanistically, DAXX interacts with SREBP1 and SREBP2 and activates SREBP-mediated transcription. DAXX associates with lipogenic gene promoters through SREBPs. Underscoring the critical roles for the DAXX-SREBP interaction for lipogenesis, SREBP2 knockdown attenuates tumor growth in cells with DAXX overexpression, and a DAXX mutant unable to bind SREBPs are incapable of promoting lipogenesis and tumor growth. Our results identify the DAXX-SREBP axis as an important pathway for tumorigenesis.

cancer biology↗

NF-κB modifies the mammalian circadian clock through interaction with the core clock protein BMAL1

In mammals, the circadian clock coordinates various cell physiological processes, including the inflammatory response. Recent studies suggested a crosstalk between these two pathways. However, the mechanism of how inflammation affects the circadian clock is not well understood. Here, we investigated the role of the proinflammatory transcription factor NF-{kappa}B in regulating clock function. Using a combination of genetic and pharmacological approaches, we show that perturbation of the canonical NF-{kappa}B subunit RELA in the U2OS cellular model altered core clock gene expression. While RELA activation shortened period length and dampened amplitude in these cells, its inhibition lengthened period length and caused amplitude phenotypes. NF-{kappa}B perturbation also altered circadian rhythms in the master suprachiasmatic nucleus (SCN) clock and locomotor activity. We show that RELA, like the clock repressor CRY1, potently repressed the transcriptional activity of BMAL1/CLOCK at the circadian E-box cis-element. Biochemical and biophysical analysis showed that RELA competes with coactivator CBP/p300 for binding to the transactivation domain of BMAL1. This mechanism is further supported by chromatin immunoprecipitation analysis showing that the binding sites of RELA, BMAL1 and CLOCK converge on the E-boxes of clock genes. Taken together, these data support a significant role for NF-{kappa}B in directly regulating circadian clock function and highlight mutual regulation between the circadian and inflammatory pathways.

molecular biology↗