The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

Enabling personalised disease diagnosis by combining a patient's time-specific gene expression profile with a biomedical knowledge base

BACKGROUND

Recent developments in the domain of biomedical knowledge bases (KBs) open up new ways to exploit biomedical knowledge that is available in the form of KBs. Significant work has been done in the direction of biomedical KB creation and KB completion, specifically, those having gene-disease associations and other related entities. However, the use of such biomedical KBs in combination with patients' temporal clinical data still largely remains unexplored, but has the potential to immensely benefit medical diagnostic decision support systems.

RESULTS

We propose two new algorithms, LOADDx and SCADDx, to combine a patient's gene expression data with gene-disease association and other related information available in the form of a KB, to assist personalized disease diagnosis. We have tested both of the algorithms on two KBs and on four real-world gene expression datasets of respiratory viral infection caused by Influenza-like viruses of 19 subtypes. We also compare the performance of proposed algorithms with that of five existing state-of-the-art machine learning algorithms (k-NN, Random Forest, XGBoost, Linear SVM, and SVM with RBF Kernel) using two validation approaches: LOOCV and a single internal validation set. Both SCADDx and LOADDx outperform the existing algorithms when evaluated with both validation approaches. SCADDx is able to detect infections with up to 100% accuracy in the cases of Datasets 2 and 3. Overall, SCADDx and LOADDx are able to detect an infection within 72 h of infection with 91.38% and 92.66% average accuracy respectively considering all four datasets, whereas XGBoost, which performed best among the existing machine learning algorithms, can detect the infection with only 86.43% accuracy on an average.

CONCLUSIONS

We demonstrate how our novel idea of using the most and least differentially expressed genes in combination with a KB can enable identification of the diseases that a patient is most likely to have at a particular time, from a KB with thousands of diseases. Moreover, the proposed algorithms can provide a short ranked list of the most likely diseases for each patient along with their most affected genes, and other entities linked with them in the KB, which can support health care professionals in their decision-making.

Increased expression of individual genes in whole blood is associated with late-stage lung cancer at and close to diagnosis

Lung cancer (LC) mortality rates are still increasing globally. As survival is linked to stage, there is a need to identify markers for earlier LC diagnosis and individualized treatment. The whole blood transcriptome of LC patients represents a source of potential LC biomarkers. We compared expression of > 60,000 genes in whole blood specimens taken from LC cases at diagnosis (n = 128) and controls (n = 62) using genome-wide RNA sequencing, and identified 14 candidate genes associated with LC. High expression of ANXA3, ARG1 and HP was strongly associated with lower survival in late-stage LC cases (hazard ratios (HRs) = 2.81, 2.16 and 2.54, respectively). We validated these markers in two independent population-based studies with pre-diagnostic whole blood specimens taken up to eight years prior to LC diagnosis (n = 163 cases, 184 matched controls). ANXA3 and ARG1 expression was strongly associated with LC in these specimens, especially with late-stage LC within two years of diagnosis (odds ratios (ORs) = 3.47 and 5.00, respectively). Additionally, blood CD4 T cells, NK cells and neutrophils were associated with LC at diagnosis and improved LC discriminative ability beyond candidate genes. Our results indicate that in whole blood, increased expression levels of ANXA3, ARG1 and HP are diagnostic and prognostic markers of late-stage LC.

Ectopic Expression of MADS-Box Transcription Factor VvAGL12 from Grape Promotes Early Flowering, Plant Growth, and Production by Regulating Cell-Wall Architecture in Arabidopsis

The MADS-box family, a substantial group of plant transcription factors, crucially regulates plant growth and development. Although the functions of AGL12-like subgroups have been elucidated in Arabidopsis, rice, and walnut, their roles in grapes remain unexplored. In this study, we isolated VvAGL12, a member of the grape MADS-box group, and investigated its impact on plant growth and biomass production. VvAGL12 was found to localize in the nucleus and exhibit expression in both vegetative and reproductive organs. We introduced VvAGL12 into Arabidopsis thaliana ecotype Columbia-0 and an agl12 mutant. The resulting phenotypes in the agl12 mutant, complementary line, and overexpressed line underscored VvAGL12's ability to promote early flowering, augment plant growth, and enhance production. This was evident from the improved fresh weight, root length, plant height, and seed production, as well as the reduced flowering time. Subsequent transcriptome analysis revealed significant alterations in the expression of genes associated with cell-wall modification and flowering in the transgenic plants. In summary, the findings highlight VvAGL12's pivotal role in the regulation of flowering timing, overall plant growth, and development. This study offers valuable insights, serving as a reference for understanding the influence of the VvAGL12 gene in other plant species and addressing yield-related challenges.

Novel mRNA Signature for Anti-TNF-α Therapy Primary Response in Patients With Ulcerative Colitis

BACKGROUND

Ulcerative colitis (UC), an idiopathic, chronic inflammatory disorder of the colonic mucosa, is commonly treated with antitumor necrosis factor α (anti-TNF-α) agents. However, only approximately two-thirds have an initial response to these therapies.

METHODS

We integrated gene expression profiling from 3 independent data sets of 79 UC patients before they began anti-TNF-α therapy and calculated the differentially expressed genes between patient response and nonresponse to anti-TNF-α therapy and developed a de novo response-associated transcription signature score (logOR_Score) to demonstrate the predictive capability of anti-TNF-α therapy for therapeutic efficacy. Furthermore, we performed association analysis of the logOR_Score and clinical features, such as disease activity and immune microenvironment.

RESULTS

A total of 2522 responsive and 1824 nonresponsive genes were identified from the integrated data set. Responsive genes were significantly enriched in metabolism-related pathways, whereas nonresponsive ones were associated with immune response-related pathways. The logOR_Score enabled the accurate prediction of the therapeutic efficacy of anti-TNF-α in 4 independent patient cohorts and outperformed the predictions made based on 6 transcriptome-based signatures. In terms of clinical features, the logOR_Score correlated highly with the activity of UC. From an immune microenvironment perspective, logOR_Scores of CD8+IL-17+ T cells, follicular B cells, and innate lymphoid cells significantly decreased in inflamed UC tissue.

CONCLUSIONS

The de novo response-associated transcription signature may provide novel insights into the personalized treatment of patients with UC. Comprehensive analyses of the response-related subtypes and the association between logOR_Score and clinical features and immune microenvironment may provide insights into the underlying UC pathogenesis.

High-Intensity interval training reduces transcriptomic age: A randomized controlled trial

While the relationship between exercise and life span is well-documented, little is known about the effects of specific exercise protocols on modern measures of biological age. Transcriptomic age (TA) predictors provide an opportunity to test the effects of high-intensity interval training (HIIT) on biological age utilizing whole-genome expression data. A single-site, single-blinded, randomized controlled clinical trial design was utilized. Thirty sedentary participants (aged 40-65) were assigned to either a HIIT group or a no-exercise control group. After collecting baseline measures, HIIT participants performed three 10 × 1 HIIT sessions per week for 4 weeks. Each session lasted 23 min, and total exercise duration was 276 min over the course of the 1-month exercise protocol. TA, PSS-10 score, PSQI score, PHQ-9 score, and various measures of body composition were all measured at baseline and again following the conclusion of exercise/control protocols. Transcriptomic age reduction of 3.59 years was observed in the exercise group while a 3.29-years increase was observed in the control group. Also, PHQ-9, PSQI, BMI, body fat mass, and visceral fat measures were all improved in the exercise group. A hypothesis-generation gene expression analysis suggested exercise may modify autophagy, mTOR, AMPK, PI3K, neurotrophin signaling, insulin signaling, and other age-related pathways. A low dose of HIIT can reduce an mRNA-based measure of biological age in sedentary adults between the ages of 40 and 65 years old. Other changes in gene expression were relatively modest, which may indicate a focal effect of exercise on age-related biological processes.

STAGEs: A web-based tool that integrates data visualization and pathway enrichment analysis for gene expression studies

Gene expression profiling has helped tremendously in the understanding of biological processes and diseases. However, interpreting processed data to gain insights into biological mechanisms remain challenging, especially to the non-bioinformaticians, as many of these data visualization and pathway analysis tools require extensive data formatting. To circumvent these challenges, we developed STAGEs (Static and Temporal Analysis of Gene Expression studies) that provides an interactive visualisation of omics analysis outputs. Users can directly upload data created from Excel spreadsheets and use STAGEs to render volcano plots, differentially expressed genes stacked bar charts, pathway enrichment analysis by Enrichr and Gene Set Enrichment Analysis (GSEA) against established pathway databases or customized gene sets, clustergrams and correlation matrices. Moreover, STAGEs takes care of Excel gene to date misconversions, ensuring that every gene is considered for pathway analysis. Output data tables and graphs can be exported, and users can easily customize individual graphs using widgets such as sliders, drop-down menus, text boxes and radio buttons. Collectively, STAGEs is an integrative platform for data analysis, data visualisation and pathway analysis, and is freely available at https://kuanrongchan-stages-stages-vpgh46.streamlitapp.com/ . In addition, developers can customise or modify the web tool locally based on our existing codes, which is publicly available at https://github.com/kuanrongchan/STAGES .

Long noncoding RNA profile of the intracranial artery in patients with moyamoya disease

OBJECTIVE

Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by progressive stenosis of the internal carotid artery (ICA) and secondary formation of collateral vessels. Revascularization surgery is performed in patients with MMD to prevent stroke; however, the pathogenesis of MMD remains unknown. Recently, long noncoding RNAs (lncRNAs) have been found to play a key role in gene regulation and are implicated in various vascular diseases. However, the lncRNA expression profile in MMD lesions has not been investigated. In this study the authors aimed to determine the characteristics of lncRNA expression in MMD lesions.

METHODS

The authors collected microsamples of the middle cerebral artery (MCA) from patients with MMD (n = 21) and patients with control conditions (n = 11) who underwent neurosurgical treatment. Using microarray experiments, the authors compared the profiles of lncRNA expression in the MCAs of the MMD and control patient groups and identified differentially expressed lncRNAs (fold change > 2, q < 0.05). In addition, the neighboring coding genes, whose transcription can be regulated in cis by the identified differentially expressed lncRNAs, were investigated and Gene Ontology (GO) analysis was applied to predict associated biological functions.

RESULTS

The authors detected 308 differentially expressed lncRNAs (fold change > 2, q < 0.05), including 306 upregulated and 2 downregulated lncRNAs in the MCA from patients with MMD. Regarding the prediction of biological function, GO analyses with possible coding genes whose transcription was regulated in cis by the identified differentially expressed lncRNAs suggested involvement in the antibacterial humoral response, T-cell receptor signaling pathway, positive regulation of cytokine production, and branching involved in blood vessel morphogenesis.

CONCLUSIONS

The profile of lncRNA expression in MMD lesions was different from that in the normal cerebral artery, and differentially expressed lncRNAs were identified. This study provides new insights into the pathophysiology of MMD.

The role of inflammation in acute psychosocial stress-induced modulation of reward processing in healthy female adults

Background

Anhedonia, or loss of interest and pleasure, is a pernicious symptom of depression that involves deficits in reward processing. Stress-induced inflammation is a plausible biopsychosocial mechanism of reward deficits, but little is known whether stress-induced inflammation alters reward behavior. The present study (a secondary analysis of a completed randomized controlled trial) tested whether acute stress activated a key pro-inflammatory transcription control pathway, NF-κB, and whether this activation was associated with acute stress-induced modulation of reward processing.

Methods

Healthy female adults (age 18-25) were randomized to undergo an acute psychosocial stressor (Trier Social Stress Test; n = 36) or a no-stress active control (n = 16). The Probabilistic Reward Task (PRT) (n = 30 stress; n = 12 control) was administered at baseline and at 90 min post-stress, coinciding with the peak of the stress-induced inflammatory response. Genome-wide expression profiling and bioinformatics analyses of NF-kB transcription factor activity were used to assess pro-inflammatory gene regulation.

Results

Relative to the control condition, stress increased bioinformatic measures of NF-κB transcription factor activity (p = .01) and increased reward response bias scores on the PRT (p = .03). Within the stress condition, greater NF-κB activity was associated with greater increases in PRT scores (p = .01), whereas in the control condition greater NF-κB activity was associated with decreases in PRT scores (p = .002).

Conclusions

Acute stress increases inflammatory signaling, and this effect is associated with increased reward processing. This demonstrates the reward system to be highly sensitive to inflammatory signaling, including the relatively mild alterations that occur following a single episode of acute psychosocial stress.

msmsEDA & msmsTests: Label-Free Differential Expression by Spectral Counts

msmsTests is an R/Bioconductor package providing functions for statistical tests in label-free LC-MS/MS data by spectral counts. These functions aim at discovering differentially expressed proteins between two biological conditions. Three tests are available: Poisson GLM regression, quasi-likelihood GLM regression, and the negative binomial of the edgeR package. The three models admit blocking factors to control for nuisance variables. To assure a good level of reproducibility a post-test filter is available, where (1) a minimum effect size considered biologically relevant, and (2) a minimum expression of the most abundant condition, may be set. A companion package, msmsEDA, proposes functions to explore datasets based on msms spectral counts. The provided graphics help in identifying outliers, the presence of eventual batch factors, and check the effects of different normalizing strategies. This protocol illustrates the use of both packages on two examples: A purely spike-in experiment of 48 human proteins in a standard yeast cell lysate; and a cancer cell-line secretome dataset requiring a biological normalization.

Synthesizing genome regulation data with vote-counting

The increasing availability of high-throughput datasets allows amalgamating research information across a large body of genome regulation studies. Given the recent success of meta-analyses on transcriptional regulators, epigenetic marks, and enhancer:gene associations, we expect that such surveys will continue to provide novel and reproducible insights. However, meta-analyses are severely hampered by the diversity of available data, concurring protocols, an eclectic amount of bioinformatics tools, and myriads of conceivable parameter combinations. Such factors can easily bar life scientists from synthesizing omics data and substantially curb their interpretability. Despite statistical challenges of the method, we would like to emphasize the advantages of joining data from different sources through vote-counting and showcase examples that achieve a simple but highly intuitive data integration.

Recent developments and future directions in meta-analysis of differential gene expression in livestock RNA-Seq

Decreases in the costs of high-throughput sequencing technologies have led to continually increasing numbers of livestock RNA-Seq studies in the last decade. Although the number of studies has increased dramatically, most livestock RNA-Seq experiments are limited by cost to a small number of biological replicates. Meta-analysis procedures can be used to integrate and jointly analyze data from multiple independent studies. Meta-analyses increase the sample size, which in turn increase both statistical power and robustness of the results. In this work, we discuss cutting edge approaches to combining results from multiple independent RNA-Seq studies to improve livestock transcriptomics research. We review currently published RNA-Seq meta-analyses in livestock, describe many of the key issues specific to RNA-Seq meta-analysis in livestock species, and discuss future perspectives.

The collagenase of the bacterium Clostridium histolyticum does not favor metastasis of breast cancer

BACKGROUND

Breast cancer is the most common malignancy among women worldwide. As survival rates increase, breast reconstruction and quality of life gain importance. Of all women undergoing breast reconstruction, approximately, 70% opt for silicone implants and 50% of those develop capsular contracture, the most prevalent long-term complication. The collagenase of the bacterium Clostridium histolyticum (CCH) showed promising results in the therapy of capsule contracture; however, its influence on residual cancer cells is unknown. The aim of this study was to investigate whether CCH-treatment negatively impacts breast cancer cells in vitro and in vivo.

METHODS

MDA-MB-231 and MCF-7 cells were used in this study. In vitro, we tested the influence of CCH on proliferation, wound healing, migration and cell cycle by MTT-assay, scratch-assay, transwell-migration-assay, and flow cytometry. In vivo, solid tumors were induced in immune-deficient mice. CCH was injected into the tumors and tumor growth and metastasis formation was monitored by caliper measurement, in vivo bioluminescence imaging and histology. Gene expression analysis was performed by microarray including 27,190 genes.

RESULTS

CCH-incubation led to a dose-dependent reduction in proliferation for both cell lines, while wound healing was reduced only in MDA-MB-231 cells. No morphological alterations were monitored in cell cycle or apoptosis. In vivo, bioluminescence imaging and histology did not show any evidence of metastasis. Although CCH led to changes in gene expression of breast cancer cells, no relevant alterations in metastasis-related genes were monitored.

CONCLUSION

CCH has no impact on tumor growth or metastasis formation in vitro and in vivo. This paves the way for first clinical trials.

Prospective associations between neighborhood violence and monocyte pro-inflammatory transcriptional activity in children

Individuals exposed to persistent neighborhood violence are at increased risk for developing mental and physical health problems across the lifespan. The biological mechanisms underlying this phenomenon are not well understood. Thus, we examined the relationship between children's exposure to neighborhood violence and inflammatory activity, a process involved in the pathogenesis of multiple health problems. 236 children from the Chicago area participated in a two-year longitudinal study (mean age at baseline, 13.9 years; 67% female; 39% White, 34% Black, 33% Hispanic). Neighborhood violence was measured as the homicide frequency in a child's Census block group in the five years before study entry. Fasting blood was drawn at study entry and two years later (in eighth and tenth grade). The blood was used to quantify protein biomarkers of systemic inflammatory activity and perform genome-wide expression profiling of isolated monocytes. Neighborhood violence was associated with higher systemic inflammatory activity at both assessments. It also was associated with a monocyte transcriptional profile indicative of increased signaling along the nuclear factor-kappa B (NF-κB) and activator protein 1 (AP-1) control pathways, which are key orchestrators of pro-inflammatory effector functions. Neighborhood violence also was associated with transcriptional indications of higher beta-adrenergic and lower glucocorticoid signaling, which could function as neuroendocrine conduits linking threatening experiences with inflammatory activity. Neighborhood violence was not associated with two-year changes in protein biomarkers, although it did presage a transcriptional profile indicative of increasing AP-1 and declining glucocorticoid signaling over follow-up. Collectively, these observations highlight cellular and molecular pathways that could underlie health risks associated with neighborhood violence.

Treatment With the CSF1R Antagonist GW2580, Sensitizes Microglia to Reactive Oxygen Species

Microglia activation and proliferation are hallmarks of many neurodegenerative disorders and may contribute to disease pathogenesis. Neurons actively regulate microglia survival and function, in part by secreting the microglia mitogen interleukin (IL)-34. Both IL-34 and colony stimulating factor (CSF)-1 bind colony stimulating factor receptor (CSFR)1 expressed on microglia. Systemic treatment with central nervous system (CNS) penetrant, CSFR1 antagonists, results in microglia death in a dose dependent matter, while others, such as GW2580, suppress activation during disease states without altering viability. However, it is not known how treatment with non-penetrant CSF1R antagonists, such as GW2580, affect the normal physiology of microglia. To determine how GW2580 affects microglia function, C57BL/6J mice were orally gavaged with vehicle or GW2580 (80mg/kg/d) for 8 days. Body weights and burrowing behavior were measured throughout the experiment. The effects of GW2580 on circulating leukocyte populations, brain microglia morphology, and the transcriptome of magnetically isolated adult brain microglia were determined. Body weights, burrowing behavior, and circulating leukocytes were not affected by treatment. Analysis of Iba-1 stained brain microglia indicated that GW2580 treatment altered morphology, but not cell number. Analysis of RNA-sequencing data indicated that genes related to reactive oxygen species (ROS) regulation and survival were suppressed by treatment. Treatment of primary microglia cultures with GW2580 resulted in a dose-dependent reduction in viability only when the cells were concurrently treated with LPS, an inducer of ROS. Pre-treatment with the ROS inhibitor, YCG063, blocked treatment induced reductions in viability. Finally, GW2580 sensitized microglia to hydrogen peroxide induced cell death. Together, these data suggest that partial CSF1R antagonism may render microglia more susceptible to reactive oxygen and nitrogen species.

Flimma: a federated and privacy-aware tool for differential gene expression analysis

Aggregating transcriptomics data across hospitals can increase sensitivity and robustness of differential expression analyses, yielding deeper clinical insights. As data exchange is often restricted by privacy legislation, meta-analyses are frequently employed to pool local results. However, the accuracy might drop if class labels are inhomogeneously distributed among cohorts. Flimma ( https://exbio.wzw.tum.de/flimma/ ) addresses this issue by implementing the state-of-the-art workflow limma voom in a federated manner, i.e., patient data never leaves its source site. Flimma results are identical to those generated by limma voom on aggregated datasets even in imbalanced scenarios where meta-analysis approaches fail.

Oxford Nanopore MinION Direct RNA-Seq for Systems Biology

Long-read direct RNA sequencing developed by Oxford Nanopore Technologies (ONT) is quickly gaining popularity for transcriptome studies, while fast turnaround time and low cost make it an attractive instrument for clinical applications. There is a growing interest to utilize transcriptome data to unravel activated biological processes responsible for disease progression and response to therapies. This trend is of particular interest for precision medicine which aims at single-patient analysis. Here we evaluated whether gene abundances measured by MinION direct RNA sequencing are suited to produce robust estimates of pathway activation for single sample scoring methods. We performed multiple RNA-seq analyses for a single sample that originated from the HepG2 cell line, namely five ONT replicates, and three replicates using Illumina NovaSeq. Two pathway scoring methods were employed-ssGSEA and singscore. We estimated the ONT performance in terms of detected protein-coding genes and average pairwise correlation between pathway activation scores using an exhaustive computational scheme for all combinations of replicates. In brief, we found that at least two ONT replicates are required to obtain reproducible pathway scores for both algorithms. We hope that our findings may be of interest to researchers planning their ONT direct RNA-seq experiments.

Parasympathetic neural activity and the reciprocal regulation of innate antiviral and inflammatory genes in the human immune system

The vagus nerve mediates parasympathetic nervous system control of peripheral physiological processes including cardiovascular activity and immune response. In mice, tonic vagal activation down-regulates inflammation via nicotinic acetylcholine receptor-mediated inhibition of the pro-inflammatory transcription factor NF-κB in monocyte/macrophages. Because Type I interferon and pro-inflammatory genes are regulated reciprocally at the level of transcription factor activation and cell differentiation, we hypothesized that vagal activity would up-regulate Type I interferon response genes concurrently with inflammatory downregulation in human immune cells. We mapped empirical individual differences in the circulating leukocyte transcriptome and vagal activity indexed by high frequency (0.15-0.40 Hz) heart rate variability (HF-HRV) in 380 participants in the Midlife in the US study. Here we show that promoter-based bioinformatics analyses linked greater HF-HRV to reduced NF-κB activity and increased activity of IRF transcription factors involved in Type I interferon response (independent of β-antagonists, BMI, smoking, heavy alcohol consumption, and demographic factors). Transcript origin analyses implicated myeloid lineage immune cells as targets, representing per-cell alterations in gene transcription as HF-HRV was not associated with differential prevalence of leukocyte subsets. These findings support the concept of parasympathetic inhibition of pro-inflammatory gene expression in humans and up-regulation of Type I interferons that could augment host defense against viral infections.

Transcriptome-wide analysis of intracranial artery in patients with moyamoya disease showing upregulation of immune response, and downregulation of oxidative phosphorylation and DNA repair

OBJECTIVE

Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by progressive occlusion of the internal carotid artery and the secondary formation of collateral vessels. Patients with MMD have ischemic attacks or intracranial bleeding, but the disease pathophysiology remains unknown. In this study, the authors aimed to identify a gene expression profile specific to the intracranial artery in MMD.

METHODS

This was a single-center, prospectively sampled, retrospective cohort study. Microsamples of the middle cerebral artery (MCA) were collected from patients with MMD (n = 11) and from control patients (n = 9). Using microarray techniques, transcriptome-wide analysis was performed.

RESULTS

Comparison of MCA gene expression between patients with MMD and control patients detected 62 and 26 genes whose expression was significantly (p < 0.001 and fold change > 2) up- or downregulated, respectively, in the MCA of MMD. Gene set enrichment analysis of genes expressed in the MCA of patients with MMD revealed positive correlations with genes involved in antigen processing and presentation, the dendritic cell pathway, cytokine pathway, and interleukin-12 pathway, and negative correlations with genes involved in oxidative phosphorylation and DNA repair. Microarray analysis was validated by quantitative polymerase chain reaction.

CONCLUSIONS

Transcriptome-wide analysis showed upregulation of genes for immune responses and downregulation of genes for DNA repair and oxidative phosphorylation within the intracranial artery of patients with MMD. These findings may represent clues to the pathophysiology of MMD.

A novel 4-gene signature model simultaneously predicting malignant risk of oral potentially malignant disorders and oral squamous cell carcinoma prognosis

OBJECTIVE

Oral squamous cell carcinoma (OSCC) is often diagnosed at late stage with a poor prognosis. The study hereunder aimed to construct a multi-gene model to simultaneously promote early diagnosis of OSCC by evaluating malignant risk of oral potentially malignant disorders (OPMDs) and predict prognosis.

MATERIALS AND METHODS

3 GEO datasets including OPMDs and OSCC samples were obtained for overlapping differentially expressed genes (DEGs) being screened. The predictive model was built with optimal DEGs by SVM algorithm, estimated by receiver operator characteristic curves and validated for double prediction via oral cancer-free survival (for malignant risk of OPMDs) and overall survival time (for OSCC) analysis respectively compared to other models. The protein expression of biomarkers in the model was validated in human samples by immunohistochemistry.

RESULTS

A novel predictive model of 4-gene signature was built based on 12 common DEGs revealed from 3 GEO datasets. It could well distinguish OSCC from OPMDs and normal tissues. Both oral cancer-free survival and overall survival time analysis were significantly poorer in high-risk patients than in low-risk ones in Kaplan Meier survival curve respectively. The protein expression of biomarkers in OSCC was with significant difference compared to normal and OPMDs.

CONCLUSIONS

The novel 4-gene signature model presents strong ability in simultaneous prediction of the malignant risk of OPMDs and OSCC progression, potentially benefiting both the early diagnosis and therapeutic outcomes of OSCC.

Multisystem inflammatory syndrome in children: a microcosm of challenges and opportunities for translational bioinformatics in pediatric research

PURPOSE OF REVIEW

Despite significant progress in our understanding and clinical management of multisystem inflammatory syndrome in children (MIS-C), significant challenges remain. Here, we review recently published studies on the clinical diagnosis, risk stratification, and treatment of MIS-C, highlighting key gaps in research progress that are a microcosm for challenges in translational pediatric research. We then discuss potential solutions in the realm of translational bioinformatics.

RECENT FINDINGS

Current case definitions are inconsistent and do not capture the underlying pathophysiology of MIS-C, which remains poorly understood. Although overall mortality is low, some patients rapidly decompensate, and a test to identify those at risk for severe outcomes remains an unmet need. Treatment consists of various combinations of immunoglobulins, corticosteroids, and biologics, based on extrapolated data and expert opinion, while the benefits remain unclear as we await the completion of clinical trials.

SUMMARY

The small size and heterogeneity of the pediatric population contribute to unmet needs because of financial and logistical constraints of the current research infrastructure focused on eliminating most sources of heterogeneity, leading to ungeneralizable results. Data sharing and meta-analysis of gene expression shows promise to accelerate progress in the field of MIS-C as well as other childhood diseases beyond the current pandemic.

Benchmark Concentrations for Untargeted Metabolomics Versus Transcriptomics for Liver Injury Compounds in In Vitro Liver Models

Interpretation of untargeted metabolomics data from both in vivo and physiologically relevant in vitro model systems continues to be a significant challenge for toxicology research. Potency-based modeling of toxicological responses has served as a pillar of interpretive context and translation of testing data. In this study, we leverage the resolving power of concentration-response modeling through benchmark concentration (BMC) analysis to interpret untargeted metabolomics data from differentiated cultures of HepaRG cells exposed to a panel of reference compounds and integrate data in a potency-aligned framework with matched transcriptomic data. For this work, we characterized biological responses to classical human liver injury compounds and comparator compounds, known to not cause liver injury in humans, at 10 exposure concentrations in spent culture media by untargeted liquid chromatography-mass spectrometry analysis. The analyte features observed (with limited metabolites identified) were analyzed using BMC modeling to derive compound-induced points of departure. The results revealed liver injury compounds produced concentration-related increases in metabolomic response compared to those rarely associated with liver injury (ie, sucrose, potassium chloride). Moreover, the distributions of altered metabolomic features were largely comparable with those observed using high throughput transcriptomics, which were further extended to investigate the potential for in vitro observed biological responses to be observed in humans with exposures at therapeutic doses. These results demonstrate the utility of BMC modeling of untargeted metabolomics data as a sensitive and quantitative indicator of human liver injury potential.

Improvement of Free Fatty Acid Secretory Productivity in Aspergillus oryzae by Comprehensive Analysis on Time-Series Gene Expression

Aspergillus oryzae is a filamentous fungus that has historically been utilized in the fermentation of food products. In recent times, it has also been introduced as a component in the industrial biosynthesis of consumable compounds, including free fatty acids (FFAs), which are valuable and versatile products that can be utilized as feedstocks in the production of other commodities, such as pharmaceuticals and dietary supplements. To improve the FFA secretory productivity of A. oryzae in the presence of Triton X-100, we analyzed the gene expression of a wild-type control strain and a disruptant strain of an acyl-CoA synthetase gene, faaA, in a time-series experiment. We employed a comprehensive analysis strategy using the baySeq, DESeq2, and edgeR algorithms to clarify the vital pathways for FFA secretory productivity and select genes for gene modification. We found that the transport and metabolism of inorganic ions are crucial in the initial stages of FFA production and revealed 16 candidate genes to be modified in conjunction with the faaA disruption. These genes were verified through the construction of overexpression strains, and showed that the manipulation of reactions closer to the FFA biosynthesis step led to a higher increase in FFA secretory productivity. This resulted in the most successful overexpression strains to have an FFA secretory productivity more than two folds higher than that of the original faaA disruptant. Our study provides guidance for further gene modification for FFA biosynthesis in A. oryzae and for enhancing the productivity of other metabolites in other microorganisms through metabolic engineering.

PGAM1 and TP53 mRNA levels in canine mammary carcinomas - Short communication

TP53 and PGAM1 genes play a key role in glycolysis which is an essential metabolic pathway of cancer cells for obtaining energy. The purpose of this work was to evaluate PGAM1 and TP53 mRNA expressions in canine mammary carcinomas (CMC) and to correlate them with animal data and tumour histological features. None of the nine samples analysed revealed PGAM1 DNA sequence variations. PGAM1 and TP53 RNA expressions from 21 CMC were analysed using a one-step reverse transcription-PCR kit and its platform system. Most CMC samples had low levels of PGAM1 mRNA (71.5%) and normal expression of TP53 mRNA (95.2%). Our results suggest a different feature of the Warburg effect on canine mammary cancer cells compared to human cells.

Feeding a Saccharomyces cerevisiae fermentation product improves udder health and immune response to a Streptococcus uberis mastitis challenge in mid-lactation dairy cows

Background

We aimed to characterize the protective effects and the molecular mechanisms of action of a Saccharomyces cerevisiae fermentation product (NTK) in response to a mastitis challenge. Eighteen mid-lactation multiparous Holstein cows (n = 9/group) were fed the control diet (CON) or CON supplemented with 19 g/d NTK for 45 d (phase 1, P1) and then infected in the right rear quarter with 2500 CFU of Streptococcus uberis (phase 2, P2). After 36-h, mammary gland and liver biopsies were collected and antibiotic treatment started until the end of P2 (9 d post challenge). Cows were then followed until day 75 (phase 3, P3). Milk yield (MY) and dry matter intake (DMI) were recorded daily. Milk samples for somatic cell score were collected, and rectal and udder temperature, heart and respiration rate were recorded during the challenge period (P2) together with blood samples for metabolite and immune function analyses. Data were analyzed by phase using the PROC MIXED procedure in SAS. Biopsies were used for transcriptomic analysis via RNA-sequencing, followed by pathway analysis.

Results

DMI and MY were not affected by diet in P1, but an interaction with time was recorded in P2 indicating a better recovery from the challenge in NTK compared with CON. NTK reduced rectal temperature, somatic cell score, and temperature of the infected quarter during the challenge. Transcriptome data supported these findings, as NTK supplementation upregulated mammary genes related to immune cell antibacterial function (e.g., CATHL4, NOS2), epithelial tissue protection (e.g. IL17C), and anti-inflammatory activity (e.g., ATF3, BAG3, IER3, G-CSF, GRO1, ZFAND2A). Pathway analysis indicated upregulation of tumor necrosis factor α, heat shock protein response, and p21 related pathways in the response to mastitis in NTK cows. Other pathways for detoxification and cytoprotection functions along with the tight junction pathway were also upregulated in NTK-fed cows.

Conclusions

Overall, results highlighted molecular networks involved in the protective effect of NTK prophylactic supplementation on udder health during a subclinical mastitic event.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40104-021-00560-8.

Leukocyte transcriptome indicators of development of infection in kidney transplant recipients

After kidney transplantation, infection and death are important clinical complications, especially for the growing numbers of older patients with limited resilience to withstand adverse events. Evaluation of changes in gene expression in immune cells can reveal the underlying mechanisms behind vulnerability to infection. A cohort of 60 kidney transplant recipients was evaluated. Gene expression in peripheral blood mononuclear cells 3 months after kidney transplantation was analyzed to compare differences between patients with infection and those who were infection-free in the first-year post-transplant. Pro-inflammatory genes such as IL1B, CCL4, and TNF were found to be downregulated in post-transplant PBMC from patients who developed infection. In contrast, genes involved in metabolism, HLA genes, and transcripts involved in type I interferon innate antiviral responses were found to be upregulated. Promoter-based bioinformatic analyses implicated increased activity of interferon regulatory factors, erythroid nuclear factor (E2), and CCAAT-enhancer-binding protein (C/EBP) in patients who developed infections. Differential patterns of gene expression were observed in patients who developed infection after kidney transplantation, with patterns distinct from changes associated with patient age, suggesting possible mechanisms behind vulnerability to infection. Assessment of gene expression in blood may offer an approach for patient risk stratification and monitoring after transplantation.

Combined vaccination and immunostimulatory antibodies provides durable cure of murine melanoma and induces transcriptional changes associated with positive outcome in human melanoma patients

We have developed a recombinant adenovirus vaccine encoding dopachrome tautomerase (rHuAd5-hDCT) that produces robust DCT-specific immunity, but only provides modest suppression of murine melanoma. In the current study, an agonist antibody against 4-1BB was shown to enhance rHuAd5-hDCT efficacy and evoke tumor regression, but most tumors ultimately relapsed. The vaccine triggered upregulation of the immune inhibitory PD-1 signaling pathway and PD-1 blockade dramatically enhanced the rHuAd5-hDCT + anti-4-1BB strategy, resulting in complete regression of growing tumors in > 70% of recipients. The impact of the combined anti-4-1BB/anti-PD-1 treatment did not manifest as a dramatic enhancement in either the magnitude or functionality of DCT-specific tumor infiltrating lymphocytes relative to either treatment alone. Rather, a synergistic enhancement in intratumoral cytokine expression was observed, suggesting that the benefit of the combined therapy was a local event within the tumor. Global transcriptional analysis revealed immunological changes within the tumor following the curative vaccination, which extended beyond the T cell compartment. We identified an immune signature of 85 genes associated with clearance of murine melanoma that correlated with improved survival outcome in two independent cohorts of human melanoma patients. Our data reinforce the concept that successful vaccination must overcome local hurdles in the tumor microenvironment that are not manifest within the periphery. Further, tumor rejection following vaccination involves more than simply T cells. Finally, the association of our immune signature with positive survival outcome in human melanoma patients suggests that similar vaccination strategies may be promising for melanoma treatment.

Preliminary evidence for conserved transcriptional response to adversity in adults with temporomandibular disorder

Temporomandibular disorder (TMD) is one of the most common orofacial pain conditions. Alteration in immune functioning is one promising biological mechanism underlying pain in TMD. However, there is a gap in the understanding of molecular bases contributing to altered immune functioning in these patients.

OBJECTIVES

In the current study, we investigated whether individuals with TMD would exhibit differential activity of 3 specific transcription factors involved in inflammatory (nuclear factor-kappa B, NF-kB), antiviral (interferon-regulatory factors, IRF), and sympathetic (cAMP response element-binding protein, CREB) processes using a promoter-based bioinformatics analysis, which is characterized as the "Conserved Transcriptional Response to Adversity."

METHODS

Adults with TMD (n = 19) and without (n = 17) underwent a standardized clinical examination for TMD. A blood sample was collected for genome-wide transcriptional RNA profiling. Bioinformatic analyses tested for differential prevalence of proinflammatory and antiviral transcription factor activity in core promoter sequences from all genes showing >1.2-fold differential expression in TMD vs controls.

RESULTS

Promoter-based bioinformatic analyses of genome-wide transcriptome profiles confirmed upregulation of genes bearing response elements for proinflammatory transcription factor (NF-kB, P = 0.002) and downregulation of genes with response elements for IRF (P = 0.037) in patients with TMD relative to controls. Results also indicated upregulated activity of CREB in patients with TMD (P = 0.08), consistent with increased activity of the sympathetic nervous system.

CONCLUSION

These results provide initial support that the regulation of immune pathways is altered in individuals with TMD. A shift of transcriptional resources to a proinflammatory state may be driven by psychosocial stress and contributes to symptoms associated with TMD.

Glycolytic competence in gastric adenocarcinomas negatively impacts survival outcomes of patients treated with salvage paclitaxel-ramucirumab

INTRODUCTION

For energy production, cancer cells maintain a high rate of glycolysis instead of oxidative phosphorylation converting glucose into lactic acid. This metabolic shift is useful to survive in unfavorable microenvironments. We investigated whether a positive glycolytic profile (PGP) in gastric adenocarcinomas may be associated with unfavorable outcomes under an anticancer systemic therapy, including the anti-angiogenic ramucirumab.

MATERIALS AND METHODS

Normal mucosa (NM) and primary tumor (PT) of 40 metastatic gastric adenocarcinomas patients who received second-line paclitaxel-ramucirumab (PR) were analyzed for mRNA expression of the following genes: HK-1, HK-2, PKM-2, LDH-A, and GLUT-1. Patients were categorized with PGP when at least a doubling of mRNA expression (PT vs. NM) in all glycolytic core enzymes (HK-1 or HK-2, PKM-2, LDH-A) was observed. PGP was also related to TP53 mutational status.

RESULTS

Mean LDH-A, HK-2, PKM-2 mRNA expression levels were significantly higher in PT compared with NM. 18 patients were classified as PGP, which was associated with significantly worse progression-free and overall survival times. No significant association was observed between PGP and clinical-pathologic features, including TP53 positive mutational status, in 28 samples.

CONCLUSIONS

Glycolytic proficiency may negatively affect survival outcomes of metastatic gastric cancer patients treated with PR systemic therapy. TP53 mutational status alone does not seem to explain such a metabolic shift.

Population-based RNA profiling in Add Health finds social disparities in inflammatory and antiviral gene regulation to emerge by young adulthood

Health in later life varies significantly by individual demographic characteristics such as age, sex, and race/ethnicity, as well as by social factors including socioeconomic status and geographic region. This study examined whether sociodemographic variations in the immune and inflammatory molecular underpinnings of chronic disease might emerge decades earlier in young adulthood. Using data from 1,069 young adults from the National Longitudinal Study of Adolescent to Adult Health (Add Health)-the largest nationally representative and ethnically diverse sample with peripheral blood transcriptome profiles-we analyzed variation in the expression of genes involved in inflammation and type I interferon (IFN) response as a function of individual demographic factors, sociodemographic conditions, and biobehavioral factors (smoking, drinking, and body mass index). Differential gene expression was most pronounced by sex, race/ethnicity, and body mass index (BMI), but transcriptome correlates were identified for every demographic dimension analyzed. Inflammation-related gene expression showed the most pronounced variation as a function of biobehavioral factors (BMI and smoking) whereas type I IFN-related transcripts varied most strongly as a function of individual demographic characteristics (sex and race/ethnicity). Bioinformatic analyses of transcription factor and immune-cell activation based on transcriptome-wide empirical differences identified additional effects of family poverty and geographic region. These results identify pervasive sociodemographic differences in immune-cell gene regulation that emerge by young adulthood and may help explain social disparities in the development of chronic illness and premature mortality at older ages.

Population-based RNA profiling in Add Health finds social disparities in inflammatory and antiviral gene regulation to emerge by young adulthood

Health in later life varies significantly by individual demographic characteristics such as age, sex, and race/ethnicity, as well as by social factors including socioeconomic status and geographic region. This study examined whether sociodemographic variations in the immune and inflammatory molecular underpinnings of chronic disease might emerge decades earlier in young adulthood. Using data from 1,069 young adults from the National Longitudinal Study of Adolescent to Adult Health (Add Health)-the largest nationally representative and ethnically diverse sample with peripheral blood transcriptome profiles-we analyzed variation in the expression of genes involved in inflammation and type I interferon (IFN) response as a function of individual demographic factors, sociodemographic conditions, and biobehavioral factors (smoking, drinking, and body mass index). Differential gene expression was most pronounced by sex, race/ethnicity, and body mass index (BMI), but transcriptome correlates were identified for every demographic dimension analyzed. Inflammation-related gene expression showed the most pronounced variation as a function of biobehavioral factors (BMI and smoking) whereas type I IFN-related transcripts varied most strongly as a function of individual demographic characteristics (sex and race/ethnicity). Bioinformatic analyses of transcription factor and immune-cell activation based on transcriptome-wide empirical differences identified additional effects of family poverty and geographic region. These results identify pervasive sociodemographic differences in immune-cell gene regulation that emerge by young adulthood and may help explain social disparities in the development of chronic illness and premature mortality at older ages.

A survey of gene expression meta-analysis: methods and applications

The increasing use of high-throughput gene expression quantification technologies over the last two decades and the fact that most of the published studies are stored in public databases has triggered an explosion of studies available through public repositories. All this information offers an invaluable resource for reuse to generate new knowledge and scientific findings. In this context, great interest has been focused on meta-analysis methods to integrate and jointly analyze different gene expression datasets. In this work, we describe the main steps in the gene expression meta-analysis, from data preparation to the state-of-the art statistical methods. We also analyze the main types of applications and problems that can be approached in gene expression meta-analysis studies and provide a comparative overview of the available software and bioinformatics tools. Moreover, a practical guide for choosing the most appropriate method in each case is also provided.

Enhancing reproducibility of gene expression analysis with known protein functional relationships: The concept of well-associated protein

Identification of differentially expressed genes (DEGs) is well recognized to be variable across independent replications of genome-wide transcriptional studies. These are often employed to characterize disease state early in the process of discovery and prioritize novel targets aimed at addressing unmet medical need. Increasing reproducibility of biological findings from these studies could potentially positively impact the success rate of new clinical interventions. This work demonstrates that statistically sound combination of gene expression data with prior knowledge about biology in the form of large protein interaction networks can yield quantitatively more reproducible observations from studies characterizing human disease. The novel concept of Well-Associated Proteins (WAPs) introduced herein-gene products significantly associated on protein interaction networks with the differences in transcript levels between control and disease-does not require choosing a differential expression threshold and can be computed efficiently enough to enable false discovery rate estimation via permutation. Reproducibility of WAPs is shown to be on average superior to that of DEGs under easily-quantifiable conditions suggesting that they can yield a significantly more robust description of disease. Enhanced reproducibility of WAPs versus DEGs is first demonstrated with four independent data sets focused on systemic sclerosis. This finding is then validated over thousands of pairs of data sets obtained by random partitions of large studies in several other diseases. Conditions that individual data sets must satisfy to yield robust WAP scores are examined. Reproducible identification of WAPs can potentially benefit drug target selection and precision medicine studies.

Pro-inflammatory immune cell gene expression during the third trimester of pregnancy is associated with shorter gestational length and lower birthweight

PROBLEM

Altered maternal immune function predicts risk for shorter gestation and low birthweight. Few studies examine associations between prenatal immune cell gene expression and gestational length or birthweight. No studies examine which cell types drive associations. The purpose of this study is to explore associations between peripheral blood immune cell gene expression and gestational length and birthweight, using transcript origin analysis.

METHOD OF STUDY

Eighty-nine women were drawn from the Community Child Health Network cohort. Third trimester maternal dried blood spots were used for genome-wide transcriptional (mRNA) profiling. Gestational length and birthweight were obtained from medical charts. Covariates were age, race/ethnicity, pre-pregnancy body mass index, smoking, gestational age at blood sampling, and pregnancy infections. Associations between gene expression profiles and gestational length and birthweight were tested using general linear models. The Transcription Element Listening System (TELiS) bioinformatics analysis quantified upstream transcription factor activity. Transcript origin analysis identified leukocyte subsets mediating observed effects.

RESULTS

Shorter gestation was predicted by increased NF-kB (TFBM ratio = -0.582 ± 0.172, P < .001) and monocyte activity (diagnosticity score = 0.172 ± 0.054, P < .001). Longer gestation was associated with increased dendritic cell activity (diagnosticity score = 0.194 ± 0.039, P < .001). Increased AP-1 activity predicted lower birthweight (TFBM ratio = -0.240 ± 0.111, P = .031). Dendritic cells and CD4+ and CD8+ T cells predicted birthweight-related gene expression differences (diagnosticity score P's < 0.021).

CONCLUSION

Higher third trimester pro-inflammatory gene expression predicted shorter gestation and lower birthweight. Variations in monocyte and dendritic cell biology contributed to both effects, and T-cell biology contributed to higher birthweight. These analyses clarify the role of myeloid/lymphoid lineage immune regulation in pregnancy outcomes.

Testosterone Influence on Gene Expression in Lacrimal Glands of Mouse Models of Sjögren Syndrome

Purpose

Sjögren syndrome is an autoimmune disorder that occurs almost exclusively in women and is associated with extensive inflammation in lacrimal tissue, an immune-mediated destruction and/or dysfunction of glandular epithelial cells, and a significant decrease in aqueous tear secretion. We discovered that androgens suppress the inflammation in, and enhance the function of, lacrimal glands in female mouse models (e.g., MRL/MpJ-Tnfrsf6^lpr [MRL/lpr]) of Sjögren syndrome. In contrast, others have reported that androgens induce an anomalous immunopathology in lacrimal glands of nonobese diabetic/LtJ (NOD) mice. We tested our hypothesis that these hormone actions reflect unique, strain- and tissue-specific effects, which involve significant changes in the expression of immune-related glandular genes.

Methods

Lacrimal glands were obtained from age-matched, adult, female MRL/lpr and NOD mice after treatment with vehicle or testosterone for up to 3 weeks. Tissues were processed for analysis of differentially expressed mRNAs using CodeLink Bioarrays and Affymetrix GeneChips. Data were analyzed with bioinformatics and statistical software.

Results

Testosterone significantly influenced the expression of numerous immune-related genes, ontologies, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in lacrimal glands of MRL/lpr and NOD mice. The nature of this hormone-induced immune response was dependent upon the autoimmune strain, and was not duplicated within lacrimal tissues of nonautoimmune BALB/c mice. The majority of immune-response genes regulated by testosterone were of the inflammatory type.

Conclusions

Our findings support our hypothesis and indicate a major role for the lacrimal gland microenvironment in mediating androgen effects on immune gene expression.

Association Between Stress and Coping with DNA Methylation of Blood Pressure-Related Genes Among African American Women

Background

Exposure to psychosocial stress and employment of high effort coping strategies have been identified as risk factors that may partially explain the high prevalence of hypertension among African Americans. One biological mechanism through which stress and coping may affect risk of hypertension is via epigenetic modifications (e.g., DNA methylation) in blood pressure-related genes; however, this area remains understudied in African Americans.

Methods

We used data from the ongoing Intergenerational Blood Pressure Study, a longitudinal study designed to investigate factors that contribute to hypertension risk in African American women (n = 120) and their young children, to investigate the association between stress overload, problem-solving coping, avoidance coping, and social support coping with DNA methylation in 25 candidate genes related to blood pressure. Multivariable linear regression and multilevel modeling were used to conduct methylation site-level and gene-level analyses, respectively.

Results

In site-level analyses, stress overload, problem-solving coping, social support coping, and avoidance coping were associated with 47, 63, 66, and 61 sites, respectively, at p < 0.05. However, no associations were statistically significant after multiple testing correction. There were also no significant associations in gene-level analyses.

Conclusions

As human social epigenomics is an emerging, evolving area of research, there is much to be learned from studies with statistically significant findings as well as studies with null findings. Factors such as characteristics of the social stressor, source of DNA, and synchronization of exposure and outcome are likely important considerations as we move the field forward.

Molecular Correlates of Socioeconomic Status and Clinical Outcomes Following Hematopoietic Cell Transplantation for Leukemia

Background

Clinical outcomes among allogeneic hematopoietic cell transplant (HCT) recipients are negatively affected by low socioeconomic status (SES), yet the biological mechanisms accounting for this health disparity remain to be elucidated. Among unrelated donor HCT recipients with acute myelogenous leukemia, one recent pilot study linked low SES to increased expression of a stress-related gene expression profile known as the conserved transcriptional response to adversity (CTRA) in peripheral blood mononuclear cells, which involves up-regulation of pro-inflammatory genes and down-regulation of genes involved in type I interferon response and antibody synthesis.

Methods

This study examined these relationships using additional measures in a larger archival sample of 261 adults who received an unrelated donor HCT for acute myelogenous leukemia to 1) identify cellular and molecular mechanisms involved in SES-related differences in pre-transplant leukocyte transcriptome profiles, and 2) evaluate pre-transplant CTRA biology associations with clinical outcomes through multivariable analysis controlling for demographic-, disease-, and transplant-related covariates.

Results

Low SES individuals showed increases in classic monocyte activation and pro-inflammatory transcription control pathways as well as decreases in activation of nonclassic monocytes, all consistent with the CTRA biological pattern. Transplant recipients in the highest or lowest quartiles of the CTRA pro-inflammatory gene component had a more than 2-fold elevated hazard of relapse (hazard ratio [HR] = 2.47, 95% confidence interval [CI] = 1.44 to 4.24), P = .001; HR = 2.52, 95% CI = 1.46 to 4.34, P = .001) and more than 20% reduction in leukemia-free survival (HR = 1.57, 95% CI = 1.08 to 2.28, P = .012; HR = 1.49, 95% CI = 1.04 to 2.15, P = .03) compared with the middle quartiles.

Conclusions

These findings identify SES- and CTRA-associated myeloid- and inflammation-related transcriptome signatures in recipient pre-transplant blood samples as a potential novel predictive biomarker of HCT-related clinical outcomes.

Temporal dynamics of miRNAs in human DLPFC and its association with miRNA dysregulation in schizophrenia

Brain development is dependent on programmed gene expression, which is both genetically and epigenetically regulated. Post-transcriptional regulation of gene expression by microRNAs (miRNAs) is essential for brain development. As abnormal brain development is hypothesized to be associated with schizophrenia, miRNAs are an intriguing target for this disorder. The aims of this study were to determine the temporal dynamics of miRNA expression in the human dorsolateral prefrontal cortex (DLPFC), and the relationship between miRNA's temporal expression pattern and dysregulation in schizophrenia. This study used next-generation sequencing to characterize the temporal dynamics of miRNA expression in the DLPFC of 109 normal subjects (second trimester-74 years of age) and miRNA expression changes in 34 schizophrenia patients. Unlike mRNAs, the majority of which exhibits a wave of change in fetuses, most miRNAs are preferentially expressed during a certain period before puberty. It is noted that in schizophrenia patients, miRNAs normally enriched in infants tend to be upregulated, while those normally enriched in prepuberty tend to be downregulated, and the targets of these miRNAs are enriched for genes encoding synaptic proteins and those associated with schizophrenia. In addition, miR-936 and miR-3162 were found to be increased in the DLPFC of patients with schizophrenia. These findings reveal the temporal dynamics of miRNAs in the human DLPFC, implicate the importance of miRNAs in DLPFC development, and suggest a possible link between schizophrenia and dysregulation of miRNAs enriched in infancy and prepuberty.

Practical determination of LODP (limit of detection for microarray platform) for the evaluation of microarray platforms

The performance indicator called limit of detection for microarray platform (LODP) was defined in ISO 16578:2013. The methods to determine practical LODP were explored. In general, + 3 SD of the background is used as the signal strength of limit of detection and criteria for dividing positive and negative results. Since the negative signal had been defined differently for each microarray platform, signals obtained from Non-Probe Spots (NPS) installed on the microarrays were defined as the "background" of microarrays. LODP was determined as the lowest concentration of which the average signal exceeded Avg. + 3 SD of the background (NPS) and the signal was significantly different from those of the lower and higher adjacent concentration points measured with a diluted series of reference materials. For reliable qualitative analysis, the positive results can be defined as signals higher than those corresponding to LODP and negative results as lower signals, without determining limit of detection for all target probes. The use of LODP also enables comparisons of platform performances without checking sequence dependencies, and assists to select reliable and fitting platforms for experimental purposes.

Screening for Preterm Birth: Potential for a Metabolomics Biomarker Panel

The aim of this preliminary study was to investigate the potential of maternal serum to provide metabolomic biomarker candidates for the prediction of spontaneous preterm birth (SPTB) in asymptomatic pregnant women at 15 and/or 20 weeks’ gestation. Metabolomics LC-MS datasets from serum samples at 15- and 20-weeks’ gestation from a cohort of approximately 50 cases (GA < 37 weeks) and 55 controls (GA > 41weeks) were analysed for candidate biomarkers predictive of SPTB. Lists of the top ranked candidate biomarkers from both multivariate and univariate analyses were produced. At the 20 weeks’ GA time-point these lists had high concordance with each other (85%). A subset of 4 of these features produce a biomarker panel that predicts SPTB with a partial Area Under the Curve (pAUC) of 12.2, a sensitivity of 87.8%, a specificity of 57.7% and a p-value of 0.0013 upon 10-fold cross validation using PanelomiX software. This biomarker panel contained mostly features from groups already associated in the literature with preterm birth and consisted of 4 features from the biological groups of “Bile Acids”, “Prostaglandins”, “Vitamin D and derivatives” and “Fatty Acids and Conjugates”.

Genome-wide analysis of canine oral malignant melanoma metastasis-associated gene expression

Oral malignant melanoma (OMM) is the most common canine melanocytic neoplasm. Overlap between the somatic mutation profiles of canine OMM and human mucosal melanomas suggest a shared UV-independent molecular aetiology. In common with human mucosal melanomas, most canine OMM metastasise. There is no reliable means of predicting canine OMM metastasis, and systemic therapies for metastatic disease are largely palliative. Herein, we employed exon microarrays for comparative expression profiling of FFPE biopsies of 18 primary canine OMM that metastasised and 10 primary OMM that did not metastasise. Genes displaying metastasis-associated expression may be targets for anti-metastasis treatments, and biomarkers of OMM metastasis. Reduced expression of CXCL12 in the metastasising OMMs implies that the CXCR4/CXCL12 axis may be involved in OMM metastasis. Increased expression of APOBEC3A in the metastasising OMMs may indicate APOBEC3A-induced double-strand DNA breaks and pro-metastatic hypermutation. DNA double strand breakage triggers the DNA damage response network and two Fanconi anaemia DNA repair pathway members showed elevated expression in the metastasising OMMs. Cross-validation was employed to test a Linear Discriminant Analysis classifier based upon the RT-qPCR-measured expression levels of CXCL12, APOBEC3A and RPL29. Classification accuracies of 94% (metastasising OMMs) and 86% (non-metastasising OMMs) were estimated.

Identification of molecular genetic contributants to canine cutaneous mast cell tumour metastasis by global gene expression analysis

Cutaneous mast cell tumours are one of the most common canine cancers. Approximately 25% of the tumours metastasise. Activating c-kit mutations are present in about 20% of tumours, but metastases occur in the absence of mutations. Tumour metastasis is associated with significantly diminished survival in spite of adjuvant chemotherapy. Available prognostic tests do not reliably predict whether a tumour will metastasise. In this study we compared the global expression profiles of 20 primary cutaneous mast cell tumours that metastasised with those of 20 primary tumours that did not metastasise. The objective was to identify genes associated with mast cell tumour metastatic progression that may represent targets for therapeutic intervention and biomarkers for prediction of tumour metastasis. Canine Gene 1.1 ST Arrays were employed for genome-wide expression analysis of formalin-fixed, paraffin-embedded biopsies of mast cell tumours borne by dogs that either died due to confirmed mast cell tumour metastasis, or were still alive more than 1000 days post-surgery. Decreased gene expression in the metastasising tumours appears to be associated with a loss of cell polarity, reduced cell-cell and cell-ECM adhesion, and increased cell deformability and motility. Dysregulated gene expression may also promote extracellular matrix and base membrane degradation, suppression of cell cycle arrest and apoptosis, and angiogenesis. Down-regulation of gene expression in the metastasising tumours may be achieved at least in part by small nucleolar RNA-derived RNA and microRNA-effected gene silencing. Employing cross-validation, a linear discriminant analysis-based classifier featuring 19 genes that displayed two-fold differences in expression between metastasising and non-metastasising tumours was estimated to classify metastasising and non-metastasising tumours with accuracies of 90-100% and 70-100%, respectively. The differential expression of 9 of the discriminator genes was confirmed by quantitative reverse transcription-PCR.

RNA-Seq Meta-analysis identifies genes in skeletal muscle associated with gain and intake across a multi-season study of crossbred beef steers

Background

Feed intake and body weight gain are economically important inputs and outputs of beef production systems. The purpose of this study was to discover differentially expressed genes that will be robust for feed intake and gain across a large segment of the cattle industry. Transcriptomic studies often suffer from issues with reproducibility and cross-validation. One way to improve reproducibility is by integrating multiple datasets via meta-analysis. RNA sequencing (RNA-Seq) was performed on longissimus dorsi muscle from 80 steers (5 cohorts, each with 16 animals) selected from the outside fringe of a bivariate gain and feed intake distribution to understand the genes and pathways involved in feed efficiency. In each cohort, 16 steers were selected from one of four gain and feed intake phenotypes (n = 4 per phenotype) in a 2 × 2 factorial arrangement with gain and feed intake as main effect variables. Each cohort was analyzed as a single experiment using a generalized linear model and results from the 5 cohort analyses were combined in a meta-analysis to identify differentially expressed genes (DEG) across the cohorts.

Results

A total of 51 genes were differentially expressed for the main effect of gain, 109 genes for the intake main effect, and 11 genes for the gain x intake interaction (P_corrected < 0.05). A jackknife sensitivity analysis showed that, in general, the meta-analysis produced robust DEGs for the two main effects and their interaction. Pathways identified from over-represented genes included mitochondrial energy production and oxidative stress pathways for the main effect of gain due to DEG including GPD1, NDUFA6, UQCRQ, ACTC1, and MGST3. For intake, metabolic pathways including amino acid biosynthesis and degradation were identified, and for the interaction analysis the pathways identified included GADD45, pyridoxal 5’phosphate salvage, and caveolar mediated endocytosis signaling.

Conclusions

Variation among DEG identified by cohort suggests that environment and breed may play large roles in the expression of genes associated with feed efficiency in the muscle of beef cattle. Meta-analyses of transcriptome data from groups of animals over multiple cohorts may be necessary to elucidate the genetics contributing these types of biological phenotypes.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4769-8) contains supplementary material, which is available to authorized users.

Divergent transcriptional profiles in pediatric asthma patients of low and high socioeconomic status

AIM

There are marked socioeconomic disparities in pediatric asthma control, but the molecular origins of these disparities are not well understood. To fill this gap, we performed genome-wide expression profiling of monocytes and T-helper cells from pediatric asthma patients of lower and higher socioeconomic status (SES).

METHOD

Ninety-nine children with asthma participated in a cross-sectional assessment. Out of which 87% were atopic, and most had disease of mild (54%) or moderate (29%) severity. Children were from lower-SES (n = 49; household income <$50 000) or higher-SES (n = 50; household income >$140 000) families. Peripheral blood monocytes and T-helper cells were isolated for genome-wide expression profiling of mRNA.

RESULTS

Lower-SES children had worse asthma quality of life relative to higher-SES children, by both their own and their parents' reports. Although the groups had similar disease severity and potential confounds were controlled, their transcriptional profiles differed notably. The monocytes of lower-SES children showed transcriptional indications of up-regulated anti-microbial and pro-inflammatory activity. The T-helper cells of lower-SES children also had comparatively reduced expression of genes encoding γ-interferon and tumor necrosis factor-α, cytokines that orchestrate Type 1 responses. They also showed up-regulated activity of transcription factors that polarize cells towards Type 2 responses and promote Th17 cell maturation.

CONCLUSION

Collectively, these patterns implicate pro-inflammatory monocytes and Type 2 cytokine activity as mechanisms contributing to worse asthma control among lower-SES children.

Differential expression patterns of housekeeping genes increase diagnostic and prognostic value in lung cancer

BACKGROUND

Using DNA microarrays, we previously identified 451 genes expressed in 19 different human tissues. Although ubiquitously expressed, the variable expression patterns of these "housekeeping genes" (HKGs) could separate one normal human tissue type from another. Current focus on identifying "specific disease markers" is problematic as single gene expression in a given sample represents the specific cellular states of the sample at the time of collection. In this study, we examine the diagnostic and prognostic potential of the variable expressions of HKGs in lung cancers.

METHODS

Microarray and RNA-seq data for normal lungs, lung adenocarcinomas (AD), squamous cell carcinomas of the lung (SQCLC), and small cell carcinomas of the lung (SCLC) were collected from online databases. Using 374 of 451 HKGs, differentially expressed genes between pairs of sample types were determined via two-sided, homoscedastic t-test. Principal component analysis and hierarchical clustering classified normal lung and lung cancers subtypes according to relative gene expression variations. We used uni- and multi-variate cox-regressions to identify significant predictors of overall survival in AD patients. Classifying genes were selected using a set of training samples and then validated using an independent test set. Gene Ontology was examined by PANTHER.

RESULTS

This study showed that the differential expression patterns of 242, 245, and 99 HKGs were able to distinguish normal lung from AD, SCLC, and SQCLC, respectively. From these, 70 HKGs were common across the three lung cancer subtypes. These HKGs have low expression variation compared to current lung cancer markers (e.g., EGFR, KRAS) and were involved in the most common biological processes (e.g., metabolism, stress response). In addition, the expression pattern of 106 HKGs alone was a significant classifier of AD versus SQCLC. We further highlighted that a panel of 13 HKGs was an independent predictor of overall survival and cumulative risk in AD patients.

DISCUSSION

Here we report HKG expression patterns may be an effective tool for evaluation of lung cancer states. For example, the differential expression pattern of 70 HKGs alone can separate normal lung tissue from various lung cancers while a panel of 106 HKGs was a capable class predictor of subtypes of non-small cell carcinomas. We also reported that HKGs have significantly lower variance compared to traditional cancer markers across samples, highlighting the robustness of a panel of genes over any one specific biomarker. Using RNA-seq data, we showed that the expression pattern of 13 HKGs is a significant, independent predictor of overall survival for AD patients. This reinforces the predictive power of a HKG panel across different gene expression measurement platforms. Thus, we propose the expression patterns of HKGs alone may be sufficient for the diagnosis and prognosis of individuals with lung cancer.

Aptamer-Based Proteomics Identifies Mortality-Associated Serum Biomarkers in Dialysis-Dependent AKI Patients

Introduction

Currently, no effective therapies exist to reduce the high mortality associated with dialysis-dependent acute kidney injury (AKI-D). Serum biomarkers may be useful in understanding the pathophysiological processes involved with AKI and the severity of injury, and point to novel therapeutic targets.

Methods

Study day 1 serum samples from 100 patients and day 8 samples from 107 patients enrolled in the Veteran’s Affairs/National Institutes of Health Acute Renal Failure Trial Network study were analyzed by the slow off-rate modified aptamers scan proteomic platform to profile 1305 proteins in each sample. Patients in each cohort were classified into tertiles based on baseline biomarker measurements. Cox regression analyses were performed to examine the relationships between serum levels of each biomarker and mortality.

Results

Changes in the serum levels of 54 proteins, 33 of which increased and 21 of which decreased, were detected when comparing samples of patients who died in the first 8 days versus patients who survived >8 days. Among the 33 proteins that increased, higher serum levels of fibroblast growth factor-23 (FGF23), tissue plasminogen activator (tPA), neutrophil collagenase (matrix metalloproteinase-8), and soluble urokinase plasminogen activator receptor, when stratified by tertiles, were associated with higher mortality. The association with mortality persisted for each of these proteins after adjusting for other potential risk factors, including age, sex, cardiovascular sequential organ failure assessment score, congestive heart failure, and presence of diabetes. Upper tertile levels of FGF23, tPA, and interleukin-6 on day 8 were associated with increased mortality; however, FGF23 barely lost significance after multivariable adjustment.

Conclusions

Our results underscore an emerging proteomics tool capable of identifying low-abundance serum proteins important not only in the pathogenesis of AKI-D, but which is also helpful in discriminating AKI-D patients with high mortality.

Validation of the Sepsis MetaScore for Diagnosis of Neonatal Sepsis

WHAT’S KNOWN ON THIS SUBJECT

Neonates are at increased risk for developing sepsis, but this population often exhibits ambiguous clinical signs that complicate the diagnosis of infection. No biomarker has yet shown enough diagnostic accuracy to rule out sepsis at the time of clinical suspicion.

WHAT THIS STUDY ADDS

We show that a gene-expression-based signature is an accurate objective measure of the risk of sepsis in a neonate or preterm infant, and it substantially improves diagnostic accuracy over that of commonly used laboratory-based testing. Implementation might decrease inappropriate antibiotic use.

BACKGROUND

Neonatal sepsis can have devastating consequences, but accurate diagnosis is difficult. As a result, up to 200 neonates with suspected sepsis are treated with empiric antibiotics for every 1 case of microbiologically confirmed sepsis. These unnecessary antibiotics enhance bacterial antibiotic resistance, increase economic costs, and alter gut microbiota composition. We recently reported an 11-gene diagnostic test for sepsis (Sepsis MetaScore) based on host whole-blood gene expression in children and adults, but this test has not been evaluated in neonates.

METHODS

We identified existing gene expression microarray-based cohorts of neonates with sepsis. We then tested the accuracy of the Sepsis MetaScore both alone and in combination with standard diagnostic laboratory tests in diagnosing sepsis.

RESULTS

We found 3 cohorts with a total of 213 samples from control neonates and neonates with sepsis. The Sepsis MetaScore had an area under the receiver operating characteristic curve of 0.92-0.93 in all 3 cohorts. We also found that, as a diagnostic test for sepsis, it outperformed standard laboratory measurements alone and, when used in combination with another test(s), resulted in a significant net reclassification index (0.3-0.69) in 5 of 6 comparisons. The mean point estimates for sensitivity and specificity were 95% and 60%, respectively, which, if confirmed prospectively and applied in a high-risk cohort, could reduce inappropriate antibiotic usage substantially.

CONCLUSIONS

The Sepsis MetaScore had excellent diagnostic accuracy across 3 separate cohorts of neonates from 3 different countries. Further prospective targeted study will be needed before clinical application.

Gain-of-function miRNA signature by mutant p53 associates with poor cancer outcome

Missense mutation of p53 not only impairs its tumor suppression function, but also causes oncogenic gain of function (GOF). The molecular underpinning of mutant p53 (mutp53) GOF is not fully understood, especially for the potential roles of non-coding genes. Here we identify the microRNA expression profile (microRNAome) of mutp53 on Arg282 by controlled microarray experiments, and clarify the prognostic significance of mutp53-regulated miRNAs in cancers. A predominant repression effect on miRNA expression was found for mutant p53, with 183 significantly downregulated and only 12 upregulated miRNAs. Mutp53 and wild-type (wtp53) commonly upregulate let-7i, and other two miRNAs were upregulated by wtp53 but repressed by mutp53 (miR-610 and miR-3065–3p). Based the mutp53-regulated miRNA signature, a non-negative matrix factorization (NMF) model classified gastric cancer (GC) cases into subgroups with significantly different Disease-free survival (Kaplan-Meier test, P = 0.013). In contrast, the NMF model based on all miRNAs did not associate with cancer outcome. The mutp53 miRNA signature associated with the outcomes of breast cancer (P = 0.024) and hepatocellular cancer (P = 0.012). The miRPath analysis revealed that mutp53-suppressed miRNAs associate with Hippo, TGF-β and stem cell signaling pathways. Taken together, our results highlight a miRNA-mediated GOF mechanism of mutant p53 on Arg282, and suggest the prognostic potential of mutp53-associated miRNA signature.

A generic Transcriptomics Reporting Framework (TRF) for 'omics data processing and analysis

A generic Transcriptomics Reporting Framework (TRF) is presented that lists parameters that should be reported in 'omics studies used in a regulatory context. The TRF encompasses the processes from transcriptome profiling from data generation to a processed list of differentially expressed genes (DEGs) ready for interpretation. Included within the TRF is a reference baseline analysis (RBA) that encompasses raw data selection; data normalisation; recognition of outliers; and statistical analysis. The TRF itself does not dictate the methodology for data processing, but deals with what should be reported. Its principles are also applicable to sequencing data and other 'omics. In contrast, the RBA specifies a simple data processing and analysis methodology that is designed to provide a comparison point for other approaches and is exemplified here by a case study. By providing transparency on the steps applied during 'omics data processing and analysis, the TRF will increase confidence processing of 'omics data, and regulatory use. Applicability of the TRF is ensured by its simplicity and generality. The TRF can be applied to all types of regulatory 'omics studies, and it can be executed using different commonly available software tools.