The peripheral-blood transcriptome: new insights into disease and risk assessment

Peripheral blood RNA biomarkers can predict lesion severity in degenerative cervical myelopathy

JOURNAL/nrgr/04.03/01300535-202506000-00027/figure1/v/2024-08-05T133530Z/r/image-tiff Degenerative cervical myelopathy is a common cause of spinal cord injury, with longer symptom duration and higher myelopathy severity indicating a worse prognosis. While numerous studies have investigated serological biomarkers for acute spinal cord injury, few studies have explored such biomarkers for diagnosing degenerative cervical myelopathy. This study involved 30 patients with degenerative cervical myelopathy (51.3 ± 7.3 years old, 12 women and 18 men), seven healthy controls (25.7 ± 1.7 years old, one woman and six men), and nine patients with cervical spondylotic radiculopathy (51.9 ± 8.6 years old, three women and six men). Analysis of blood samples from the three groups showed clear differences in transcriptomic characteristics. Enrichment analysis identified 128 differentially expressed genes that were enriched in patients with neurological disabilities. Using least absolute shrinkage and selection operator analysis, we constructed a five-gene model (TBCD, TPM2, PNKD, EIF4G2, and AP5Z1) to diagnose degenerative cervical myelopathy with an accuracy of 93.5%. One-gene models (TCAP and SDHA) identified mild and severe degenerative cervical myelopathy with accuracies of 83.3% and 76.7%, respectively. Signatures of two immune cell types (memory B cells and memory-activated CD4+ T cells) predicted levels of lesions in degenerative cervical myelopathy with 80% accuracy. Our results suggest that peripheral blood RNA biomarkers could be used to predict lesion severity in degenerative cervical myelopathy.

Immunologic changes in the peripheral blood transcriptome of individuals with early-stage chronic Chagas cardiomyopathy: a cross-sectional study

Background

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, is a neglected disease that affects approximately 6 million individuals worldwide. Of those infected, 20-30% will go on to develop chronic Chagas cardiomyopathy (CCC), and many ultimately to advanced heart failure. The mechanisms by which this progression occurs are poorly understood. In this exploratory study, we sought to provide insight into the physiologic changes associated with the development of early CCC.

Methods

We used RNA sequencing to analyse the gene expression changes in the peripheral blood of six patients with Chagas disease with early structural heart disease, four patients with Chagas disease without any signs or symptoms of disease, thirteen patients without Chagas disease with early structural heart disease, and ten patients without Chagas disease or signs of heart disease. Pathway analyses and immune cell deconvolution were employed to further elucidate the biological processes underlying early CCC development.

Findings

Our analysis suggests that early CCC is associated with a downregulation of various peripheral immune response genes, including changes suggestive of reduced antigen presentation and T cell activation. Notably, these genes and processes appear to be distinct from those of non-Chagas cardiomyopathies.

Interpretation

This work highlights the potential importance of the immune response in early CCC, providing insight into the early pathogenesis of this disease and how it may differ from other cardiomyopathies. The changes we have identified may serve as biomarkers of early CCC and could inform future longitudinal cohort studies of markers of disease progression and strategies for the treatment of CCC in its early stages.

Funding

NIH, FONDECYT, IDSA, NSF.

Blood toxicogenomics reveals potential biomarkers for management of idiosyncratic drug-induced liver injury

Introduction: Accurate diagnosis, assessment, and prognosis of idiosyncratic drug-induced liver injury (IDILI) is problematic, in part due to the shortcomings of traditional blood biomarkers. Studies in rodents and healthy volunteers have supported that RNA transcript changes in whole blood may address some of these shortcomings. Methods: In this study, we conducted RNA-Seq analysis on peripheral blood samples collected from 55 patients with acute IDILI and 17 patients with liver injuries not attributed to IDILI. Results and discussion: Three differentially expressed genes (DEGs; CFD, SQLE, and INKA1) were identified as significantly associated with IDILI vs. other liver injuries. No DEGs were identified comparing IDILI patients to the 5 patients with autoimmune hepatitis, suggesting possible common underlying mechanisms. Two genes (VMO1 and EFNA1) were significantly associated with hepatocellular injury compared to mixed/cholestatic injury. When patients with severe vs. milder IDILI were compared, we identified over 500 DEGs. The top pathways identified from these DEGs had in common down regulation of multiple T-cell specific genes. Further analyses confirmed that these changes could largely be accounted for by a fall in the concentration of circulating T-cells during severe DILI, perhaps due to exhaustion or sequestration of these cells in the liver. Exploration of DEGs specific for the individual causal agents was largely unsuccessful, but isoniazid-induced IDILI demonstrated 25 DEGs compared to other non-isoniazid IDILI cases. Finally, among the 14 IDILI patients that had hepatocellular jaundice (i.e., Hy's Law cases), we identified 39 DEGs between the 4 patients with fatal or liver transplantation outcomes compared to those that recovered. These findings suggest the potential for blood-based transcriptomic biomarkers to aid in the diagnosis and prognostic stratification of IDILI.

MicroRNA Expression Profile Analysis in Blood During Giant Panda (Ailuropoda melanoleuca) Growth and Development

BACKGROUND/OBJECTIVES

Blood is an essential component of the immune system. As post-transcriptional regulators, miRNAs, abundant in blood, are necessary aspects in blood's immune and physiological functions. However, there is limited knowledge about the expression and function of miRNAs in the blood of giant pandas.

METHODS

We comparatively analyzed miRNA expression profiles in the blood of giant pandas of different ages using small-RNA sequencing technology.

RESULTS

We identified 393 known miRNAs, 219 conserved miRNAs, and 71 novel miRNAs in the blood of giant pandas, and functional enrichment analysis showed that the genes regulated by DE (differentially expressed) miRNAs were mainly enriched in the regulation of enzyme-linked receptor protein signaling pathways and the signaling pathways of MAPK, Hippo, and FoXO.

CONCLUSIONS

Our study clarified giant pandas' blood miRNA expression profiles at different developmental stages, which will help elucidate the blood immunity and regulation of blood cell physiological functions in giant pandas.

Symmetry as a Fundamental Principle in Defining Gene Expression and Phenotypic Traits

Symmetry refers to properties that remain invariant upon mathematical transformations. The principles of symmetry have guided numerous important discoveries in physics and chemistry but not in biology and medicine. Here, we aim to explore the presence of symmetry relationships at the gene expression level as a mean to distinguish between healthy and disease states. We deployed Learning-Based Invariant Feature Engineering - LIFE, a hybrid machine learning approach implemented with two symmetric invariant feature functions (IFFs) to identify Invariant Feature Genes (IFGs), which are gene pairs whose IFF single-value outputs remain invariant across individual samples in a given biological phenotype. Our multiclass classification results across the transcriptomes of 25 normal organs, 25 cancer types, and blood samples obtained from 4 different types of neurodegenerative diseases revealed the presence of unique phenotype-specific IFGs. We constructed networks using these IFGs (IF-Nets) and intriguingly, we demonstrated that the hubs could serve as information encoders, capable of reconstructing sample-wise expression values in relation to their counterpart genes. More importantly, we found that hubs of cancer IF-Nets were enriched with both approved and clinical trial drugs, highlighting "symmetry breaking" as a novel approach for treating diseases.

Dysregulation of c-Jun (JUN) and FBJ murine osteosarcoma viral oncogene homolog B (FOSB) in obese people and their predictive values for metabolic syndrome

The incidences of metabolic syndrome (MetS), denoting insulin resistance-associated various metabolic disorders, are increasing. This study aimed to identify new biomarkers for predicting MetS and provide a novel diagnostic approach. Herein, the expression profiles of c-Jun (JUN) and FBJ murine osteosarcoma viral oncogene homolog B (FOSB) in individuals with obesity and patients with MetS from the Gene Expression Omnibus database. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to evaluate the messenger RNA levels of JUN and FOSB in the peripheral blood of healthy volunteers (lean and obese) and patients with MetS (lean and obese), along with that in the adipose tissue and peripheral blood of obese mouse model. Furthermore, receiver operating characteristic (ROC) curve and logistic regression analyses were performed to determine the diagnostic value of JUN and FOSB in MetS. The expression profiles and RT-qPCR results showed that JUN and FOSB were highly expressed in individuals with obesity, obese mouse models, and patients with MetS. The ROC analysis results showed an area under the curve values of 0.872 and 0.879 for JUN, 0.802 and 0.962 for FOSB, and 0.946 and 0.979 for JUN-FOSB in the lean group and the group with obesity, respectively, in predicting MetS. Logistic regression analysis showed that the p-values of both JUN and FOSB as MetS-affecting factors were <0.05. Altogether, the findings of this study indicate that both JUN and FOSB, abnormally expressed in individuals with obesity, are good biomarkers of MetS.

Unraveling the Complexity of Chikungunya Virus Infection Immunological and Genetic Insights in Acute and Chronic Patients

Background: The chikungunya virus (CHIKV), transmitted by infected Aedes mosquitoes, has caused a significant number of infections worldwide. In Brazil, the emergence of the CHIKV-ECSA genotype in 2014 posed a major public health challenge due to its association with more severe symptoms. Objectives/Methods: This study aimed to shed new light on the host immune response by examining the whole-blood transcriptomic profile of both CHIKV-acute and chronically infected individuals from Feira de Santana, Bahia, Brazil, a region heavily affected by CHIKV, Dengue, and Zika virus epidemics. Results: Our data reveal complex symptomatology characterized by arthralgia and post-chikungunya neuropathy in individuals with chronic sequelae, particularly affecting women living in socially vulnerable situations. Analysis of gene modules suggests heightened metabolic processes, represented by an increase in NADH, COX5A, COA3, CYC1, and cap methylation in patients with acute disease. In contrast, individuals with chronic manifestations exhibit a distinct pattern of histone methylation, probably mediated by NCOA3 in the coactivation of different nuclear receptors, KMT2 genes, KDM3B and TET2, and with alterations in the immunological response, majorly led by IL-17RA, IL-6R, and STAT3 Th17 genes. Conclusion: Our results emphasize the complexity of CHIKV disease progression, demonstrating the heterogeneous gene expression and symptomatologic scenario across both acute and chronic phases. Moreover, the identification of specific gene modules associated with viral pathogenesis provides critical insights into the molecular mechanisms underlying these distinct clinical manifestations.

Decoding the Immune Response and Its Biomarker B2M for High Altitude Pulmonary Edema in Rat: Implications for Diagnosis and Prognosis

Purpose

We aimed to investigate whether peripheral blood biomarkers B2M related to immune response can serve as indicators of HAPE pathophysiological characteristics or disease progression.

Patients and Methods

Bioinformatics technology was used to explore the peripheral blood pathophysiological mechanisms and immune hub genes related to the occurrence of HAPE. The hub gene was verified through animal experiments, and its function and correlation between its expression level and the diagnosis, treatment effect and prognosis of HAPE were explored.

Results

The GSVA results showed that the occurrence of HAPE was related to the down-regulation of immune response pathways by RUNX3 and STING. WGCNA results showed that the peripheral blood immune gene module related to the development of HAPE was related to the decrease of immune function and the increase of immune checkpoint molecule PD-L1 gene expression, and the expression of immune checkpoint genes LILRB2 and SIGLEC15 increased. Cytoscape software, RT-qPCR and WB confirmed that the hub gene B2M is a specific peripheral blood biomarker of HAPE. ROC, DCA, RT-qPCR, HE and Masson results showed that the expression of peripheral blood B2M has the ability to indicate the diagnosis, treatment effect and prognosis of HAPE. The decreased expression of B2M protein in peripheral blood leukocytes may be a marker of HAPE. Single-gene GSEA confirmed that the reduced expression of B2M in peripheral blood may be involved in the down-regulation of the antigen presentation pathway mediated by MHC class I molecules, was positively correlated with the down-regulation of the TNF signaling pathway, and was negatively correlated with the expression of LILRB2 and SIGLEC15.

Conclusion

The occurrence of HAPE may be related to decreased immune function and immune tolerance. Peripheral blood B2M may be involved in the related pathways, its expression level can prompt the diagnosis, treatment and prognosis of HAPE.

Short time-series expression transcriptome data reveal the gene expression patterns and potential biomarkers of blood infection with LPS and poly (I:C) in Mandarin fish (Siniperca chuatsi)

Blood transcriptomics has emerged as a vital tool for tracking the immune system and supporting disease diagnosis, prognosis, treatment, and research. The present study was conducted to analyze the gene expression profile and potential biomarker candidates using the whole blood of mandarin fish (Siniperca chuatsi) infected with LPS or poly (I:C) at 0 h, 3 h, 6 h, and 12 h. Our data suggest that 310 shared differentially expressed genes (DEGs) were identified among each comparison group after LPS infection, and 137 shared DEGs were identified after poly (I:C) infection. A total of 62 shared DEGs were differentially expressed in all compared groups after LPS or poly (I:C) infection. Pathways analysis for DEGs in all different compared groups showed that cytokine-cytokine receptor interaction was the most enrichment pathway. The expression levels of genes C-X-C chemokine receptor type 2-like (cxcr2), chemokine (C-C motif) receptor 9a (ccr9a), chemokine (C-C motif) receptor 9b (ccr9b), chemokine (C-X-C motif) receptor 4b (cxcr4b), and interleukin 10 receptor alpha (il10ra) were significantly different in all compared groups and most enriched in cytokine-cytokine receptor interaction pathway. The protein-protein interactions analysis among all shared DEGs showed that cxcr4 was the hub gene with the highest degree. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring mandarin fish diseases.

Multiomics reveals blood differential metabolites and differential genes in the early onset of ketosis in dairy cows

Ketosis-a metabolic state characterized by elevated levels of ketone bodies in the blood or urine-reduces the performance and health of dairy cows and causes substantial economic losses for the dairy industry. Currently, beta-hydroxybutyric acid is the gold standard for determining ketosis in cows; however, as this method is only applicable postpartum, it is not conducive to the early intervention of ketosis in dairy cows. In this study, the sera of dry, periparturient, postpartum ketotic, and healthy cows were analyzed by both transcriptomics and metabolomics techniques. Moreover, changes of gene expression and metabolites were observed, and serum physiological and biochemical indexes were detected by ELISA. The purpose was to screen biomarkers that can be used to detect the incidence of dry or periparturient ketosis in cows. The results showed that ketotic cows had increased levels of glycolipid metabolism indexes, oxidizing factors, and inflammatory factors during dry periods and liver damage, which could be used as early biomarkers to predict the onset of ketosis. Transcriptomic results yielded 20 differentially expressed genes (DEGs) between ketotic and healthy cows during dry, peripartum, and postpartum periods. GO and KEGG enrichment analyses indicated that these DEGs were involved in amino acid metabolism, energy metabolism, and disease-related signaling pathways. The metabolomics sequencing results showed that ketotic cows mainly showed enrichment in tricarboxylic acid cycle, butyric acid metabolism, carbon metabolism, lysine degradation, fatty acid degradation, and other signaling pathways. Metabolites differed between ketotic and healthy cows in dry, pre-parturition, and post-parturition periods. Combined transcriptomics and metabolomics analyses identified significant enrichment in the glucagon signaling pathway and the lysine degradation signaling pathway in dry, periparturient, and postpartum ketotic cows. PRKAB2 and SETMAR-key DEGs of the glucagon signaling pathway and lysine degradation signaling pathway, respectively-can be used as key marker genes for determining the early onset of ketosis in dairy cows.

Higher peripheral blood mitochondrial DNA copy number and relative telomere length in under 48 years Indonesian breast cancer patients

OBJECTIVE

Breast cancer is the leading cause of cancer incidence and mortality among Indonesian women. A comprehensive investigation is required to enhance the early detection of this disease. Mitochondrial DNA copy number (mtDNA-CN) and relative telomere length (RTL) have been proposed as potential biomarkers for several cancer risks, as they are linked through oxidative stress mechanisms. We conducted a case-control study to examine peripheral blood mtDNA-CN and RTL patterns in Indonesian breast cancer patients (n = 175) and healthy individuals (n = 181). The relative ratios of mtDNA-CN and RTL were determined using quantitative real-time PCR (qPCR).

RESULTS

Median values of mtDNA-CN and RTL were 1.62 and 0.70 in healthy subjects and 1.79 and 0.73 in breast cancer patients, respectively. We found a positive association between peripheral blood mtDNA-CN and RTL (p < 0.001). In under 48 years old breast cancer patients, higher peripheral blood mtDNA-CN (mtDNA-CN ≥ 1.73 (median), p = 0.009) and RTL (continuous variable, p = 0.010) were observed, compared to the corresponding healthy subjects. We also found a significantly higher 'High-High' pattern of mtDNA-CN and RTL in breast cancer patients under 48 years old (p = 0.011). Our findings suggest that peripheral blood mtDNA-CN and RTL could serve as additional minimally invasive biomarkers for breast cancer risk evaluation.

Plasma-Free Blood as a Potential Alternative to Whole Blood for Transcriptomic Analysis

RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics, and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples that are generally considered less useful byproducts during the processes of plasma and serum separation, respectively. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the suitability of employing PFB or SFB samples as an alternative RNA source in transcriptomic analysis. We performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples than SFB samples in terms of protein-coding gene expression patterns, detection of differentially expressed genes, and immunological characterizations, suggesting that PFB can serve as a viable alternative to WB for transcriptomic analysis. Our study contributes to the optimization of blood sample utilization and the advancement of precision medicine research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00121-1.

Uncovering transcriptomic biomarkers for enhanced diagnosis of methamphetamine use disorder: a comprehensive review

Introduction

Methamphetamine use disorder (MUD) is a chronic relapsing disorder characterized by compulsive Methamphetamine (MA) use despite its detrimental effects on physical, psychological, and social well-being. The development of MUD is a complex process that involves the interplay of genetic, epigenetic, and environmental factors. The treatment of MUD remains a significant challenge, with no FDA-approved pharmacotherapies currently available. Current diagnostic criteria for MUD rely primarily on self-reporting and behavioral assessments, which have inherent limitations owing to their subjective nature. This lack of objective biomarkers and unidimensional approaches may not fully capture the unique features and consequences of MA addiction.

Methods

We performed a literature search for this review using the Boolean search in the PubMed database.

Results

This review explores existing technologies for identifying transcriptomic biomarkers for MUD diagnosis. We examined non-invasive tissues and scrutinized transcriptomic biomarkers relevant to MUD. Additionally, we investigated transcriptomic biomarkers identified for diagnosing, predicting, and monitoring MUD in non-invasive tissues.

Discussion

Developing and validating non-invasive MUD biomarkers could address these limitations, foster more precise and reliable diagnostic approaches, and ultimately enhance the quality of care for individuals with MA addiction.

Unraveling phenotypic variance in metabolic syndrome through multi-omics

Complex multi-omics effects drive the clustering of cardiometabolic risk factors, underscoring the imperative to comprehend how individual and combined omics shape phenotypic variation. Our study partitions phenotypic variance in metabolic syndrome (MetS), blood glucose (GLU), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and blood pressure through genome, transcriptome, metabolome, and exposome (i.e., lifestyle exposome) analyses. Our analysis included a cohort of 62,822 unrelated individuals with white British ancestry, sourced from the UK biobank. We employed linear mixed models to partition phenotypic variance using the restricted maximum likelihood (REML) method, implemented in MTG2 (v2.22). We initiated the analysis by individually modeling omics, followed by subsequent integration of pairwise omics in a joint model that also accounted for the covariance and interaction between omics layers. Finally, we estimated the correlations of various omics effects between the phenotypes using bivariate REML. Significant proportions of the MetS variance were attributed to distinct data sources: genome (9.47%), transcriptome (4.24%), metabolome (14.34%), and exposome (3.77%). The phenotypic variances explained by the genome, transcriptome, metabolome, and exposome ranged from 3.28% for GLU to 25.35% for HDL-C, 0% for GLU to 19.34% for HDL-C, 4.29% for systolic blood pressure (SBP) to 35.75% for TG, and 0.89% for GLU to 10.17% for HDL-C, respectively. Significant correlations were found between genomic and transcriptomic effects for TG and HDL-C. Furthermore, significant interaction effects between omics data were detected for both MetS and its components. Interestingly, significant correlation of omics effect between the phenotypes was found. This study underscores omics' roles, interaction effects, and random-effects covariance in unveiling phenotypic variation in multi-omics domains.

Genetic Testing for Successful Cancer Treatment

Cancer genetic testing is a revolutionary medical approach that involves the assessment of genetic markers in asymptomatic individuals to predict their future susceptibility to cancer. This paradigm shift in early detection and intervention has the potential to profoundly alter our strategies for cancer prevention and treatment. One pivotal area where genetic testing can have a significant impact is among families with a hereditary predisposition to cancer. Recent research has seen a surge in the exploration of how individuals perceive their cancer risk within the realm of cancer genetics. This proactive approach to genetic testing allows healthcare professionals to identify family members who may carry the same cancer-related genetic mutations, empowering them to make informed decisions regarding their healthcare and cancer risk management. Genetic testing for cancer-related disorders has significantly improved in accuracy and affordability, potentially revolutionizing monitoring and treatment methods. The expanding knowledge of genetic mutations associated with cancer susceptibility has driven significant progress in cancer therapy. Identifying numerous major cancer susceptibility genes has propelled predictive genetic testing, providing individuals with valuable insights into their genetic predisposition to cancer. While perceived risk plays a vital role in genetic counseling, it is equally essential to offer comprehensive information about the advantages and potential risks associated with genetic testing. Ensuring that individuals have a clear understanding of the benefits and potential drawbacks of genetic testing is imperative for making informed healthcare decisions. In our comprehensive review, researchers explored several critical aspects of genetic testing in the context of cancer, including awareness and knowledge, the communication of cancer genetic risk, genetic testing for inherited cancer syndromes, and the challenges and limitations linked to genetic testing. Through this examination, we aim to illuminate the transformative potential of genetic testing in cancer prevention and treatment.

F-box protein 43 promoter methylation as a novel biomarker for hepatitis B virus-associated hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) has a high prevalence and poor prognosis worldwide. Therefore, it is urgent to find effective and timely diagnostic markers. The objective of this study was to evaluate the diagnostic value of F-box protein 43 promoter methylation in peripheral blood mononuclear cells (PBMCs) for HCC.

METHOD

A total of 247 participants were included in this study, comprising individuals with 123 hepatitis B virus-associated HCC, 79 chronic hepatitis B, and 45 healthy controls. F-box protein 43 methylation and mRNA levels in PBMCs were detected by MethyLight and quantitative real-time PCR.

RESULT

F-box protein 43 promoter methylation levels were significantly lower in HCC PBMCs than the chronic hepatitis B (P < 0.001) and healthy control PBMCs (P < 0.001). Relative mRNA expression levels of F-box protein 43 in HCC PBMCs were significantly higher than those in chronic hepatitis B (P < 0.001) and healthy control PBMCs (P < 0.001). Receiver operating characteristic analysis of F-box protein 43 promoter methylation levels yielded an area under curve (AUC) of 0.793 with 76.42% sensitivity and 68.35% specificity when differentiating HCC from chronic hepatitis. These values for the F-box protein 43 promoter methylation level were superior to those of the alpha-fetoprotein serum (AFP) level (AUC: 0.780, sensitivity: 47.97%, and specificity: 96.20%), with increments in values for the combination of F-box protein 43 promoter methylation AFP levels (AUC: 0.888, sensitivity: 76.42%, and specificity: 86.08%).

CONCLUSION

Hypomethylation of the F-box protein 43 promoter in PBMCs is a promising biochemical marker for HBV-associated HCC.

Harnessing Genomics and Transcriptomics Approaches to Improve Female Fertility in Beef Cattle-A Review

Female fertility is the foundation of the cow-calf industry, impacting both efficiency and profitability. Reproductive failure is the primary reason why beef cows are sold in the U.S. and the cause of an estimated annual gross loss of USD 2.8 billion. In this review, we discuss the status of the genomics, transcriptomics, and systems genomics approaches currently applied to female fertility and the tools available to cow-calf producers to maximize genetic progress. We highlight the opportunities and limitations associated with using genomic and transcriptomic approaches to discover genes and regulatory mechanisms related to beef fertility. Considering the complex nature of fertility, significant advances in precision breeding will rely on holistic, multidisciplinary approaches to further advance our ability to understand, predict, and improve reproductive performance. While these technologies have advanced our knowledge, the next step is to translate research findings from bench to on-farm applications.

Blood-Based Transcriptomic Biomarkers Are Predictive of Neurodegeneration Rather Than Alzheimer's Disease

Alzheimer's disease (AD) is a growing global health crisis affecting millions and incurring substantial economic costs. However, clinical diagnosis remains challenging, with misdiagnoses and underdiagnoses being prevalent. There is an increased focus on putative, blood-based biomarkers that may be useful for the diagnosis as well as early detection of AD. In the present study, we used an unbiased combination of machine learning and functional network analyses to identify blood gene biomarker candidates in AD. Using supervised machine learning, we also determined whether these candidates were indeed unique to AD or whether they were indicative of other neurodegenerative diseases, such as Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS). Our analyses showed that genes involved in spliceosome assembly, RNA binding, transcription, protein synthesis, mitoribosomes, and NADH dehydrogenase were the best-performing genes for identifying AD patients relative to cognitively healthy controls. This transcriptomic signature, however, was not unique to AD, and subsequent machine learning showed that this signature could also predict PD and ALS relative to controls without neurodegenerative disease. Combined, our results suggest that mRNA from whole blood can indeed be used to screen for patients with neurodegeneration but may be less effective in diagnosing the specific neurodegenerative disease.

Immunologic changes are detectable in the peripheral blood transcriptome of clinically asymptomatic Chagas cardiomyopathy patients

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, is a neglected parasitic disease that affects approximately 6 million individuals worldwide. Of those infected, 20-30% will go on to develop chronic Chagas cardiomyopathy (CCC), and ultimately many of these individuals will progress to advanced heart failure. The mechanism by which this progression occurs is poorly understood, as few studies have focused on early CCC. In this study, we sought to understand the physiologic changes associated with T. cruzi infection and the development of CCC. We analyzed gene expression in the peripheral blood of asymptomatic Chagas patients with early structural heart disease, Chagas patients without any signs or symptoms of disease, and Chagas-negative patients with and without early structural heart disease. Our analysis shows that early CCC was associated with a downregulation of various peripheral immune response genes, with gene expression changes suggestive of reduced antigen presentation and T cell activation. Notably, these genes and processes were distinct from those of early cardiomyopathy in Chagas-negative patients, suggesting that the processes mediating CCC may be unique from those mediating progression to other cardiomyopathies. This work highlights the importance of the immune response in early CCC, providing insight into the early pathogenesis of this disease. The changes we have identified may serve as biomarkers of progression and could inform strategies for the treatment of CCC in its early stages, before significant cardiac damage has occurred.

Multifaceted analysis of cross-tissue transcriptomes reveals phenotype-endotype associations in atopic dermatitis

Atopic dermatitis (AD) is a skin disease that is heterogeneous both in terms of clinical manifestations and molecular profiles. It is increasingly recognized that AD is a systemic rather than a local disease and should be assessed in the context of whole-body pathophysiology. Here we show, via integrated RNA-sequencing of skin tissue and peripheral blood mononuclear cell (PBMC) samples along with clinical data from 115 AD patients and 14 matched healthy controls, that specific clinical presentations associate with matching differential molecular signatures. We establish a regression model based on transcriptome modules identified in weighted gene co-expression network analysis to extract molecular features associated with detailed clinical phenotypes of AD. The two main, qualitatively differential skin manifestations of AD, erythema and papulation are distinguished by differential immunological signatures. We further apply the regression model to a longitudinal dataset of 30 AD patients for personalized monitoring, highlighting patient heterogeneity in disease trajectories. The longitudinal features of blood tests and PBMC transcriptome modules identify three patient clusters which are aligned with clinical severity and reflect treatment history. Our approach thus serves as a framework for effective clinical investigation to gain a holistic view on the pathophysiology of complex human diseases.

Correlation between immune-related genes and depression-like features in an animal model and in humans

A growing body of evidence suggests that immune-related genes play pivotal roles in the pathophysiology of depression. In the present study, we investigated a plausible connection between gene expression, DNA methylation, and brain structural changes in the pathophysiology of depression using a combined approach of murine and human studies. We ranked the immobility behaviors of 30 outbred Crl:CD1 (ICR) mice in the forced swim test (FST) and harvested their prefrontal cortices for RNA sequencing. Of the 24,532 analyzed genes, 141 showed significant correlations with FST immobility time, as determined through linear regression analysis with p ≤ 0.01. The identified genes were mostly involved in immune responses, especially interferon signaling pathways. Moreover, induction of virus-like neuroinflammation in the brains of two separate mouse cohorts (n = 30 each) using intracerebroventricular polyinosinic:polycytidylic acid injection resulted in increased immobility during FST and similar expression of top immobility-correlated genes. In human blood samples, candidate gene (top 5%) expression profiling using DNA methylation analysis found the interferon-related USP18 (cg25484698, p = 7.04 × 10-11, Δβ = 1.57 × 10-2; cg02518889, p = 2.92 × 10-3, Δβ =  - 8.20 × 10-3) and IFI44 (cg07107453, p = 3.76 × 10-3, Δβ =  - 4.94 × 10-3) genes to be differentially methylated between patients with major depressive disorder (n = 350) and healthy controls (n = 161). Furthermore, cortical thickness analyses using T1-weighted images revealed that the DNA methylation scores for USP18 were negatively correlated with the thicknesses of several cortical regions, including the prefrontal cortex. Our results reveal the important role of the interferon pathway in depression and suggest USP18 as a potential candidate target. The results of the correlation analysis between transcriptomic data and animal behavior carried out in this study provide insights that could enhance our understanding of depression in humans.

Variability in donor leukocyte counts confound the use of common RNA sequencing data normalization strategies in transcriptomic biomarker studies performed with whole blood

Gene expression data generated from whole blood via next generation sequencing is frequently used in studies aimed at identifying mRNA-based biomarker panels with utility for diagnosis or monitoring of human disease. These investigations often employ data normalization techniques more typically used for analysis of data originating from solid tissues, which largely operate under the general assumption that specimens have similar transcriptome composition. However, this assumption may be violated when working with data generated from whole blood, which is more cellularly dynamic, leading to potential confounds. In this study, we used next generation sequencing in combination with flow cytometry to assess the influence of donor leukocyte counts on the transcriptional composition of whole blood specimens sampled from a cohort of 138 human subjects, and then subsequently examined the effect of four frequently used data normalization approaches on our ability to detect inter-specimen biological variance, using the flow cytometry data to benchmark each specimens true cellular and molecular identity. Whole blood samples originating from donors with differing leukocyte counts exhibited dramatic differences in both genome-wide distributions of transcript abundance and gene-level expression patterns. Consequently, three of the normalization strategies we tested, including median ratio (MRN), trimmed mean of m-values (TMM), and quantile normalization, noticeably masked the true biological structure of the data and impaired our ability to detect true interspecimen differences in mRNA levels. The only strategy that improved our ability to detect true biological variance was simple scaling of read counts by sequencing depth, which unlike the aforementioned approaches, makes no assumptions regarding transcriptome composition.

Transcriptomic and Metabolomic Changes Reveal the Immunomodulatory Function of Casein Phosphopeptide-Selenium Chelate in Beagle Dogs

Casein phosphopeptide-selenium chelate (CPP-Se) is an organic compound produced by the chelation of casein phosphopeptide with selenium. This compound showed the ability to modulate canine immune response in our previous study; but its effect on the peripheral blood transcriptome and serum metabolome was unknown. This study aims to reveal the potential mechanism behind the immunomodulatory function of CPP-Se. We have identified 341 differentially expressed genes (DEGs) in CPP-Se groups as compared to the control group which comprised 110 up-regulated and 231 down-regulated genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis found that DEGs were mainly involved in immune-related signaling pathways. Moreover, the immune-related DEGs and hub genes were identified. Similarly, metabolomics identified 53 differentially expressed metabolites (DEMs) in the CPP-Se group, of which 17 were up-regulated and 36 were down-regulated. The pathways mainly enriched by DEMs were primary bile acid biosynthesis, tryptophan metabolism, and other amino acids metabolic pathways. Combined analysis of transcriptomic and metabolomic data showed that the DEGs and DEMs were commonly enriched in fatty acid biosynthesis, pyrimidine metabolism, glutathione metabolism, and glycerolipid metabolic pathways. Taken together, our findings provided a theoretical basis for further understanding of the immunomodulatory function of CPP-Se as well as a scientific reference for the future use of CPP-Se in pet foods as a dietary supplement to modulate the immunity.

Transcriptomic analyses of patient peripheral blood with hemoglobin depletion reveal glioblastoma biomarkers

Peripheral blood is gaining prominence as a noninvasive alternative to tissue biopsy to develop biomarkers for glioblastoma (GBM); however, widely utilized blood-based biomarkers in clinical settings have not yet been identified due to the lack of a robust detection approach. Here, we describe the application of globin reduction in RNA sequencing of whole blood (i.e., WBGR) and perform transcriptomic analysis to identify GBM-associated transcriptomic changes. By using WBGR, we improved the detection sensitivity of informatic reads and identified differential gene expression in GBM blood. By analyzing tumor tissues, we identified transcriptomic traits of GBM blood. Further functional enrichment analyses retained the most changed genes in GBM. Subsequent validation elicited a 10-gene panel covering mRNA, long noncoding RNA, and microRNA (i.e., GBM-Dx panel) that has translational potential to aid in the early detection or clinical management of GBM. Here, we report an integrated approach, WBGR, with comprehensive analytic capacity for blood-based marker identification.

Species interactions, stability, and resilience of the gut microbiota - Helminth assemblage in horses

The nature and strength of interactions entertained among helminths and their host gut microbiota remain largely unexplored. Using 40 naturally infected Welsh ponies, we tracked the gut microbiota-cyathostomin temporal dynamics and stability before and following anthelmintic treatment and the associated host blood transcriptomic response. High shedders harbored 14 species of cyathostomins, dominated by Cylicocyclus nassatus. They exhibited a highly diverse and temporal dynamic gut microbiota, with butyrate-producing Clostridia likely driving the ecosystem steadiness and host tolerance toward cyathostomins infection. However, anthelmintic administration sharply bent the microbial community. It disrupted the ecosystem stability and the time-dependent network of interactions, affecting longer term microbial resilience. These observations highlight how anthelmintic treatments alter the triangular relationship of parasite, host, and gut microbiota and open new perspectives for adding nutritional intervention to current parasite management strategies.

Involvement of the E3 ubiquitin ligase Cblb in host defense and evaluation of transcriptome during Trueperella pyogenes infection

Trueperella pyogenes (T. pyogenes) is a versatile and ingenious bacterium that causes severe suppurative injuries in lots of economically important ruminants. The underlying pathogenesis of T. pyogenes infection remains poorly understood. In the current study, we performed transcriptome sequencing of mouse blood tissue infected with T. pyogenes. A total of 36.73 G clean data were collected, and 136 differentially expressed genes were obtained in the infection group compared to the control group. In addition, we found that the E3 ubiquitin ligase Cblb exhibited significant upregulation in the infection groups compared to the control group. Mechanistically, T. pyogenes infection markedly enhanced the expression of Cblb and regulated the host defense response. Inhibiting Cblb expression with Cblb siRNA impaired the inflammatory response and reduced the effect of phagocytosis in RAW264.7 murine macrophages. Intriguingly, overexpression of Cblb induced a strong inflammatory response and enhanced phagocytosis against T. pyogenes infection in macrophages. More importantly, the overexpression of Cblb significantly reduced the bacterial load and protected mice from the T. pyogenes infections. Therefore, our findings reveal that Cblb is a novel and potential regulator in response to T. pyogenes infection and shed new light on the development of promising treatments against T. pyogenes-related diseases.

miR-146a-5p Promotes the Inflammatory Response in PBMCs Induced by Microcystin-Leucine-Arginine

Background

Microcystin-leucine-arginine (MC-LR) is the most abundant and most toxic variant of microcystin isomers. Various experiments have clearly shown that MC-LR has hepatotoxicity and carcinogenicity, but there are relatively few studies on its immune damage effect. In addition, numerous studies have shown that microRNAs (miRNAs) are involved in a wide range of biological processes. Do miRNAs also play a role in inflammatory response caused by microcystin exposure? This is the question to be answered in this study. Moreover, this study can also provides experimental evidence for the significance of miRNA applications.

Objective

To investigate the effect of MC-LR on the expressions of miR-146a and pro/anti-inflammatory cytokines in human peripheral blood mononuclear cells (PBMCs) and to further explore the role of miR-146a in the inflammatory responses caused by MC-LR.

Methods

Serum samples from 1789 medical examiners were collected and detect the concentrations of MCs, and 30 serum samples with concentrations of MCs around P₂₅, P₅₀, and p₇₅ were randomly selected for the detection of inflammatory factors. PBMCs from fresh peripheral blood extracted from these 90 medical examiners were subsequently tested for relative miR-146a expression. In vitro, the MC-LR were exposed to the PBMCs to detect the levels of inflammatory factors as well as the relative expression of miR-146a-5p. Then, a miRNA transfection assay was performed to verify the regulation of inflammatory factors by miR-146a-5p.

Results

In population samples, the expression of inflammatory factors and miR-146a-5p increased with increasing MCs concentration. In vitro experiments showed that the expression of inflammatory factors and miR-146a-5p in PBMCs increased with MC-LR exposure time or exposure dose too. In addition, inhibiting the expression of miR-146a-5p in PBMCs reduced inflammatory factor levels.

Conclusion

miR-146a-5p exerts a promoting effect on the MC-LR-induced inflammatory response by positively regulating inflammatory factor levels.

Blood-based DNA methylation signatures in cancer: A systematic review

DNA methylation profiles are in dynamic equilibrium via the initiation of methylation, maintenance of methylation and demethylation, which control gene expression and chromosome stability. Changes in DNA methylation patterns play important roles in carcinogenesis and primarily manifests as hypomethylation of the entire genome and the hypermethylation of individual loci. These changes may be reflected in blood-based DNA, which provides a non-invasive means for cancer monitoring. Previous blood-based DNA detection objects primarily included circulating tumor DNA/cell-free DNA (ctDNA/cfDNA), circulating tumor cells (CTCs) and exosomes. Researchers gradually found that methylation changes in peripheral blood mononuclear cells (PBMCs) also reflected the presence of tumors. Blood-based DNA methylation is widely used in early diagnosis, prognosis prediction, dynamic monitoring after treatment and other fields of clinical research on cancer. The reversible methylation of genes also makes them important therapeutic targets. The present paper summarizes the changes in DNA methylation in cancer based on existing research and focuses on the characteristics of the detection objects of blood-based DNA, including ctDNA/cfDNA, CTCs, exosomes and PBMCs, and their application in clinical research.

Literature review on the interdisciplinary biomarkers of multi-target and multi-time herbal medicine therapy to modulate peripheral systems in cognitive impairment

Alzheimer's disease (AD) is a chronic progressive neurodegenerative disease characterized by the deposition of amyloid-beta (Aβ) peptide and neurofibrillary tangles in the brain. The approved drug for AD has certain limitations such as a short period of cognitive improvement effect; moreover, the development of drug for AD therapeutic single target for Aβ clearance in brain ended in failure. Therefore, diagnosis and treatment of AD using a multi-target strategy according to the modulation of the peripheral system, which is not only limited to the brain, is needed. Traditional herbal medicines can be beneficial for AD based on a holistic theory and personalized treatment according to the time-order progression of AD. This literature review aimed to investigate the effectiveness of herbal medicine therapy based on syndrome differentiation, a unique theory of traditional diagnosis based on the holistic system, for multi-target and multi-time treatment of mild cognitive impairment or AD stage. Possible interdisciplinary biomarkers including transcriptomic and neuroimaging studies by herbal medicine therapy for AD were investigated. In addition, the mechanism by which herbal medicines affect the central nervous system in connection with the peripheral system in an animal model of cognitive impairment was reviewed. Herbal medicine may be a promising therapy for the prevention and treatment of AD through a multi-target and multi-time strategy. This review would contribute to the development of interdisciplinary biomarkers and understanding of the mechanisms of action of herbal medicine in AD.

Identification of intrinsic genes across general hypertension, hypertension with left ventricular remodeling, and uncontrolled hypertension

The purpose of the present article is to identify intrinsic genes across general hypertension (HT), hypertension with left ventricular remodeling (HT-LVR), and uncontrolled hypertension (UN-HT). In total, four microarray datasets (GSE24752, GSE75360, GSE74144, and GSE71994) were downloaded from the GEO database and were used to identify differentially expressed genes (DEGs), respectively. Furthermore, gene set enrichment analysis (GSEA) was utilized to screen for significantly enriched biological pathways across the four datasets above, respectively. Furthermore, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were applied to screen out gene modules of interest and potential biological functions, respectively. Finally, a Metascape-based multiple gene list meta-analysis was used to investigate intrinsic genes at different stages of the progression of hypertension. A total of 75 DEGs (63 upregulated genes and 12 downregulated genes, GSE24752) and 23 DEGs (2 upregulated genes and 21 downregulated genes, GSE74144) were identified. However, there were few DEGs identified in GSE75360, GSE71994, and part of the GSE74144 datasets. GSEA and functional enrichment of gene module of interest have indicated that "Heme metabolism," "TNF alpha/NFkB," and "interferon alpha response signaling," and MYC target v1/v2 were enriched significantly in different stages of hypertension progression. Significantly, findings from the multiple gene list meta-analysis suggested that FBXW4 and other 13 genes were unique to the hypertension group, and TRIM11 and other 40 genes were mainly involved in hypertension with the left ventricular remodeling group, while the other 18 genes including F13A1 significantly enriched in uncontrolled hypertension. Collectively, the precise switch of the "immune-metabolic-inflammatory" loop pathway was the most significant hallmark across different stages of hypertension, thereby providing a potential therapeutic target for uncontrolled hypertension treatment.

Genome-wide transcriptional profiling of pulmonary functional sequelae in ARDS- secondary to SARS-CoV-2 infection

BACKGROUND

Up to 80% of patients surviving acute respiratory distress syndrome (ARDS) secondary to SARS-CoV-2 infection present persistent anomalies in pulmonary function after hospital discharge. There is a limited understanding of the mechanistic pathways linked to post-acute pulmonary sequelae.

AIM

To identify the molecular underpinnings associated with severe lung diffusion involvement in survivors of SARS-CoV-2-induced ARDS.

METHODS

Survivors attended to a complete pulmonary evaluation 3 months after hospital discharge. RNA sequencing (RNA-seq) was performed using Illumina technology in whole-blood samples from 50 patients with moderate to severe diffusion impairment (D_LCO<60%) and age- and sex-matched individuals with mild-normal lung function (D_LCO≥60%). A transcriptomic signature for optimal classification was constructed using random forest. Transcriptomic data were analyzed for biological pathway enrichment, cellular deconvolution, cell/tissue-specific gene expression and candidate drugs.

RESULTS

RNA-seq identified 1357 differentially expressed transcripts. A model composed of 14 mRNAs allowed the optimal discrimination of survivors with severe diffusion impairment (AUC=0.979). Hallmarks of lung sequelae involved cell death signaling, cytoskeleton reorganization, cell growth and differentiation and the immune response. Resting natural killer (NK) cells were the most important immune cell subtype for the prediction of severe diffusion impairment. Components of the signature correlated with neutrophil, lymphocyte and monocyte counts. A variable expression profile of the transcripts was observed in lung cell subtypes and bodily tissues. One upregulated gene, TUBB4A, constitutes a target for FDA-approved drugs.

CONCLUSIONS

This work defines the transcriptional programme associated with post-acute pulmonary sequelae and provides novel insights for targeted interventions and biomarker development.

Impact of long-term exposure to PM2.5 on peripheral blood gene expression pathways involved in cell signaling and immune response

BACKGROUND

Exposure to ambient air pollution, even at low levels, is a major environmental health risk. The peripheral blood transcriptome provides a potential avenue for the elucidation of ambient air pollution related biological perturbations. We assessed the association between long-term estimates for seven priority air pollutants and perturbations in peripheral blood transcriptomics data collected in the Dutch National Twin Register (NTR) and Netherlands Study of Depression and Anxiety (NESDA) cohorts.

METHODS

In both the discovery (n = 2438) and replication (n = 1567) cohort, outdoor concentration of 7 air pollutants (NO₂, NO_x, particulate matter (PM_2.5, PM_2.5abs, PM₁₀, PM_coarse)_, and ultrafine particles) was predicted with land use regression models. Gene expression was assessed by Affymetrix U219 arrays. Multi-variable univariate mixed-effect models were applied to test for an association between the air pollutants and the transcriptome. Functional analysis was conducted in DAVID.

RESULTS

In the discovery cohort, we observed for 335 genes (374 probes with FDR < 5 %) a perturbation in peripheral blood gene expression that was associated with long-term average levels of PM_2.5. For 69 genes pooled effect estimates from the NTR and NESDA cohorts were significant. Identified genes play a role in biological pathways related to cell signaling and immune response. Sixty-two out of 69 genes had a similar direction of effect in an analysis in which we regressed the probes on differential PM_2.5 exposure within monozygotic twin pairs, indicating that the observed differences in gene expression were likely driven by differences in air pollution, rather than by confounding by genetic factors.

CONCLUSION

Our results indicate that PM_2.5 can elicit a response in cell signaling and the immune system, both hallmarks of environmental diseases. The differential effect that we observed between air pollutants may aid in the understanding of differential health effects that have been observed with these exposures.

The Effect of Tropical Temperatures on the Quality of RNA Extracted from Stabilized Whole-Blood Samples

Whole-blood-derived transcriptional profiling is widely used in biomarker discovery, immunological research, and therapeutic development. Traditional molecular and high-throughput transcriptomic platforms, including molecular assays with quantitative PCR (qPCR) and RNA-sequencing (RNA-seq), are dependent upon high-quality and intact RNA. However, collecting high-quality RNA from field studies in remote tropical locations can be challenging due to resource restrictions and logistics of post-collection processing. The current study tested the relative performance of the two most widely used whole-blood RNA collection systems, PAXgene^® and Tempus™, in optimal laboratory conditions as well as suboptimal conditions in tropical field sites, including the effects of extended storage times and high storage temperatures. We found that Tempus™ tubes maintained a slightly higher RNA quantity and integrity relative to PAXgene^® tubes at suboptimal tropical conditions. Both PAXgene^® and Tempus™ tubes gave similar RNA purity (A260/A280). Additionally, Tempus^™ tubes preferentially maintained the stability of mRNA transcripts for two reference genes tested, Succinate dehydrogenase complex, subunit A (SDHA) and TATA-box-binding protein (TBP), even when RNA quality decreased with storage length and temperature. Both tube types preserved the rRNA transcript 18S ribosomal RNA (18S) equally. Our results suggest that Tempus^™ blood RNA collection tubes are preferable to PAXgene^® for whole-blood collection in suboptimal tropical conditions for RNA-based studies in resource-limited settings.

Transcriptome profiling of blood from common bottlenose dolphins (Tursiops truncatus) in the northern Gulf of Mexico to enhance health assessment capabilities

Following the 2010 Deepwater Horizon disaster and subsequent unusual mortality event, adverse health impacts have been reported in bottlenose dolphins in Barataria Bay, LA including impaired stress response and reproductive, pulmonary, cardiac, and immune function. These conditions were primarily diagnosed through hands-on veterinary examinations and analysis of standard diagnostic panels. In human and veterinary medicine, gene expression profiling has been used to identify molecular mechanisms underlying toxic responses and disease states. Identification of molecular markers of exposure or disease may enable earlier detection of health effects or allow for health evaluation when the use of specialized methodologies is not feasible. To date this powerful tool has not been applied to augment the veterinary data collected concurrently during dolphin health assessments. This study examined transcriptomic profiles of blood from 76 dolphins sampled in health assessments during 2013–2018 in the waters near Barataria Bay, LA and Sarasota Bay, FL. Gene expression was analyzed in conjunction with the substantial suite of health data collected using principal component analysis, differential expression testing, over-representation analysis, and weighted gene co-expression network analysis. Broadly, transcript profiles of Barataria Bay dolphins indicated a shift in immune response, cytoskeletal alterations, and mitochondrial dysfunction, most pronounced in dolphins likely exposed to Deepwater Horizon oiling. While gene expression profiles in Barataria Bay dolphins were altered compared to Sarasota Bay for all years, profiles from 2013 exhibited the greatest alteration in gene expression. Differentially expressed transcripts included genes involved in immunity, inflammation, reproductive failure, and lung or cardiac dysfunction, all of which have been documented in dolphins from Barataria Bay following the Deepwater Horizon oil spill. The genes and pathways identified in this study may, with additional research and validation, prove useful as molecular markers of exposure or disease to assist wildlife veterinarians in evaluating the health of dolphins and other cetaceans.

At-home blood collection and stabilization in high temperature climates using homeRNA

Expanding whole blood sample collection for transcriptome analysis beyond traditional phlebotomy clinics will open new frontiers for remote immune research and telemedicine. Determining the stability of RNA in blood samples exposed to high ambient temperatures (>30°C) is necessary for deploying home-sampling in settings with elevated temperatures (e.g., studying physiological response to natural disasters that occur in warm locations or in the summer). Recently, we have developed homeRNA, a technology that allows for self-blood sampling and RNA stabilization remotely. homeRNA consists of a lancet-based blood collection device, the Tasso-SST™ which collects up to 0.5 ml of blood from the upper arm, and a custom-built stabilization transfer tube containing RNAlater™. In this study, we investigated the robustness of our homeRNA kit in high temperature settings via two small pilot studies in Doha, Qatar (no. participants = 8), and the Western and South Central USA during the summer of 2021, which included a heatwave of unusually high temperatures in some locations (no. participants = 11). Samples collected from participants in Doha were subjected to rapid external temperature fluctuations from being moved to and from air-conditioned areas and extreme heat environments (up to 41°C external temperature during brief temperature spikes). In the USA pilot study, regions varied in outdoor temperature highs (between 25°C and 43.4°C). All samples that returned a RNA integrity number (RIN) value from the Doha, Qatar group had a RIN ≥7.0, a typical integrity threshold for downstream transcriptomics analysis. RIN values for the Western and South Central USA samples (n = 12 samples) ranged from 6.9-8.7 with 9 out of 12 samples reporting RINs ≥7.0. Overall, our pilot data suggest that homeRNA can be used in some regions that experience elevated temperatures, opening up new geographical frontiers in disseminated transcriptome analysis for applications critical to telemedicine, global health, and expanded clinical research. Further studies, including our ongoing work in Qatar, USA, and Thailand, will continue to test the robustness of homeRNA.

SARS-CoV-2 infection impairs the insulin/IGF signaling pathway in the lung, liver, adipose tissue, and pancreatic cells via IRF1

BACKGROUND

COVID-19 can cause multiple organ damages as well as metabolic abnormalities such as hyperglycemia, insulin resistance, and new onset of diabetes. The insulin/IGF signaling pathway plays an important role in regulating energy metabolism and cell survival, but little is known about the impact of SARS-CoV-2 infection. The aim of this work was to investigate whether SARS-CoV-2 infection impairs the insulin/IGF signaling pathway in the host cell/tissue, and if so, the potential mechanism and association with COVID-19 pathology.

METHODS

To determine the impact of SARS-CoV-2 on insulin/IGF signaling pathway, we utilized transcriptome datasets of SARS-CoV-2 infected cells and tissues from public repositories for a wide range of high-throughput gene expression data: autopsy lungs from COVID-19 patients compared to the control from non-COVID-19 patients; lungs from a human ACE2 transgenic mouse infected with SARS-CoV-2 compared to the control infected with mock; human pluripotent stem cell (hPSC)-derived liver organoids infected with SARS-CoV-2; adipose tissues from a mouse model of COVID-19 overexpressing human ACE2 via adeno-associated virus serotype 9 (AAV9) compared to the control GFP after SARS-CoV-2 infection; iPS-derived human pancreatic cells infected with SARS-CoV-2 compared to the mock control. Gain and loss of IRF1 function models were established in HEK293T and/or Calu3 cells to evaluate the impact on insulin signaling. To understand the mechanistic regulation and relevance with COVID-19 risk factors, such as older age, male sex, obesity, and diabetes, several transcriptomes of human respiratory, metabolic, and endocrine cells and tissue were analyzed. To estimate the association with COVID-19 severity, whole blood transcriptomes of critical patients with COVID-19 compared to those of hospitalized noncritical patients with COVID-19.

RESULTS

We found that SARS-CoV-2 infection impaired insulin/IGF signaling pathway genes, such as IRS, PI3K, AKT, mTOR, and MAPK, in the host lung, liver, adipose tissue, and pancreatic cells. The impairments were attributed to interferon regulatory factor 1 (IRF1), and its gene expression was highly relevant to risk factors for severe COVID-19; increased with aging in the lung, specifically in men; augmented by obese and diabetic conditions in liver, adipose tissue, and pancreatic islets. IRF1 activation was significantly associated with the impaired insulin signaling in human cells. IRF1 intron variant rs17622656-A, which was previously reported to be associated with COVID-19 prevalence, increased the IRF1 gene expression in human tissue and was frequently found in American and European population. Critical patients with COVID-19 exhibited higher IRF1 and lower insulin/IGF signaling pathway genes in the whole blood compared to hospitalized noncritical patients. Hormonal interventions, such as dihydrotestosterone and dexamethasone, ameliorated the pathological traits in SARS-CoV-2 infectable cells and tissues.

CONCLUSIONS

The present study provides the first scientific evidence that SARS-CoV-2 infection impairs the insulin/IGF signaling pathway in respiratory, metabolic, and endocrine cells and tissues. This feature likely contributes to COVID-19 severity with cell/tissue damage and metabolic abnormalities, which may be exacerbated in older, male, obese, or diabetic patients.

Blood transcriptome analysis revealing aging gene expression profiles in red panda

The red panda is an endangered forest species distributed on the edge of the Qinghai Tibet Plateau. The species has been conserved in ex-situ in many countries and its survival is threatened by many diseases. Its immune system is vulnerable to age-associated alterations, which accumulate and result in a progressive deterioration that leads to an increased incidence of diseases. We identified 2,219 differentially expressed genes (DEGs) between geriatric (11-16 years) and adult individuals (4-8 years), and 1690 DEGs between adults and juveniles (1 year). The gene expression and functional annotation results showed that the innate immunity of red pandas increases significantly in geriatric individuals, whereas its change remains unclear when comparing adults and juveniles. We found that the adaptive immunity of red pandas first increased and then decreased with age. We identified CXCR3, BLNK, and CCR4 as the hub genes in the age-related protein-protein interaction network, which showed their central role in age-related immune changes. Many DNA repair genes were down-regulated in geriatric red pandas, suggesting that the DNA repair ability of the blood tissue in geriatric red pandas is significantly reduced. The significantly up-regulated TLR5 in geriatric individuals also suggests the possibility of enhancing the vaccination immune response by incorporating flagellin, which could be used to address decreased vaccine responses caused by age-related declines in immune system function. This work provides an insight into gene expression changes associated with aging and paves the way for effective disease prevention and treatment strategies for red pandas in the future.

Delayed processing of blood samples impairs the accuracy of mRNA-based biomarkers

The transcriptome of peripheral white blood cells (PWBCs) are indicators of an organism's physiological state, thus making them a prime biological sample for mRNA-based biomarker discovery. Here, we designed an experiment to evaluate the impact of delayed processing of whole blood samples on gene transcript abundance in PWBCs. We hypothesized that storing blood samples for 24 h at 4 °C would cause RNA degradation resulting in altered transcriptome profiles. There were no statistical differences in RNA quality parameters among samples processed after one, three, six, or eight hours post collection. Additionally, no significant differences were noted in RNA quality parameters or gene transcript abundance between samples collected from the jugular and coccygeal veins. However, samples processed after 24 h of storage had a lower RNA integrity number value (P = 0.03) in comparison to those processed after one hour of storage. Using RNA-sequencing, we identified four and 515 genes with differential transcript abundance in samples processed after storage for eight and 24 h, respectively, relative to samples processed after one hour. Sequencing coverage of transcripts was similar between samples from the 24-h and one-hour groups, thus showing no indication of RNA degradation. This alteration in transcriptome profiles can impair the accuracy of mRNA-based biomarkers, therefore, blood samples collected for mRNA-based biomarker discovery should be refrigerated immediately and processed within six hours post-sampling.

Genetic Association of rs1021188 and DNA Methylation Signatures of TNFSF11 in the Risk of Conductive Hearing Loss

Otosclerosis (OTSC) is a complex bone disorder of the otic capsule, which causes conductive hearing impairment in human adults. The dysregulation of the signaling axis mediated by the receptor activator of nuclear factor-kappa-B (RANK), RANK ligand (RANKL), and osteoprotegerin has been widely attributed to the context of metabolic bone disorders. While genetic associations and epigenetic alterations in the TNFSF11 gene (RANKL) have been well-linked to metabolic bone diseases of the skeleton, particularly osteoporosis, they have never been addressed in OTSC. This study aimed to assess whether the genetic association of rs1021188 polymorphism in the upstream of TNFSF11 and the DNA methylation changes in its promoter CpG-region reveal the susceptibility of OTSC. Peripheral blood DNA samples were collected from unrelated Tunisian-North African subjects for genotyping (109 cases and 120 controls) and for DNA methylation analysis (40 cases and 40 controls). The gender-stratified analysis showed that the TNFSF11 rs1021188 C/T was associated with OTSC in men (p = 0.023), but not in women (p = 0.458). Individuals with CC genotype were more susceptible to OTSC, suggesting an increased risk to disease development. Using publicly available data, the rs1021188 was within a cluster grouping the subpopulations with African ethnicity. Moreover, 26 loci in the TNFSF11 gene were in linkage disequilibrium with rs1021188, revealing relative similarities between different populations. Significant differences in both DNA methylation and unmethylation status were detected with 4.53- and 4.83-fold decreases in the global DNA methylation levels in female and male OTSC groups, respectively. These changes could contribute to an increased risk of OTSC development. Bioinformatic analyses indicated that each of the rs1021188 variations and the DNA methylation changes in the promoter CpG-sites within TNFSF11 may play an important role in its transcription regulation. To our knowledge, this is the first study that investigates an independent effect of the rs1021188 polymorphism and DNA hypomethylation of TNFSF11 promoter in OTSC. Genetic and epigenetic changes in the regulatory regions of TNFSF11 could offer new molecular insights into the understanding of the complexity of OTSC.

Whole blood transcriptome profiling identifies candidate genes associated with alopecia in male giant pandas (Ailuropoda melanoleuca)

Background

The giant panda (Ailuropoda melanoleuca) is a threatened species endemic to China. Alopecia, characterized by thinning and broken hair, mostly occurs in breeding males. Alopecia significantly affects the health and public image of the giant panda and the cause of alopecia is unclear.

Results

Here, we researched gene expression profiles of four alopecia giant pandas and seven healthy giant pandas. All pandas were approximately ten years old and their blood samples collected during the breeding season. A total of 458 up-regulated DEGs and 211 down-regulated DEGs were identified. KEGG pathway enrichment identified that upregulated genes were enriched in the Notch signaling pathway and downregulated genes were enriched in ribosome, oxidative phosphorylation, and thermogenesis pathways. We obtained 28 hair growth-related DEGs, and identified three hub genes NOTCH1, SMAD3, and TGFB1 in PPI analysis. Five hair growth-related signaling pathways were identified with abnormal expression, these were Notch, Wnt, TGF-β, Mapk, and PI3K-Akt. The overexpression of NOTCH1 delays inner root sheath differentiation and results in hair shaft abnormalities. The delayed hair regression was associated with a significant decrease in the expression levels of TGFB1.

Conclusions

Our data confirmed the abnormal expression of several hair-related genes and pathways and identified alopecia candidate genes in the giant panda. Results of this study provide theoretical basis for the establishment of prevention and treatment strategies for giant pandas with alopecia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08501-z.

Identification of Potential Diagnostic Biomarkers From Circulating Cells During the Course of Sleep Deprivation-Related Myocardial Infarction Based on Bioinformatics Analyses

Background

Myocardial infarction (MI) is the leading cause of death from non-infectious diseases worldwide and results in rapid deterioration due to the sudden rupture of plaques associated with atherosclerosis, a chronic inflammatory disease. Sleep is a key factor that regulates immune homeostasis of the body. The imbalance in circulating immune cells caused by sleep deprivation (SD) may represent a risk factor leading to the rapid deterioration of plaques and MI. Therefore, it is of profound significance to identify diagnostic biomarkers for preventing SD-related MI.

Methods

In the present study, we identified coexpressed differentially expressed genes (co-DEGs) between peripheral blood mononuclear cells from MI and SD samples (compared to controls) from a public database. LASSO regression analysis was applied to identify significant diagnostic biomarkers from co-DEGs. Moreover, receiver operating characteristic (ROC) curve analysis was performed to test biomarker accuracy and diagnostic ability. We further analyzed immune cell enrichment in MI and SD samples using the CIBERSORT algorithm, and the correlation between biomarkers and immune cell composition was assessed. We also investigated whether diagnostic biomarkers are involved in immune cell signaling pathways in SD-related MI processes.

Results

A total of 10 downregulated co-DEGs from the sets of MI-DEGs and SD-DEGs were overlapped. After applying LASSO regression analysis, SYTL2, KLRD1, and C12orf75 were selected and validated as diagnostic biomarkers using ROC analysis. Next, we found that resting NK cells were downregulated in both the MI samples and SD samples, which is similar to the changes noted for SYTL2. Importantly, SYTL2 was strongly positively correlated not only with resting NK cells but also with most genes related to NK cell markers in the MI and SD datasets. Moreover, SYTL2 was highly associated with genes in NK cell signaling pathways, including the MAPK signaling pathway, cytotoxic granule movement and exocytosis, and NK cell activation. Furthermore, GSEA and KEGG analyses provided evidence that the DEGs identified from MI samples with low vs. high SYTL2 expression exhibited a strong association with the regulation of the immune response and NK cell-mediated cytotoxicity.

Conclusion

In conclusion, SYTL2, KLRD1, and C12orf75 represent potential diagnostic biomarkers of MI. The association between SYTL2 and resting NK cells may be critically involved in SD-related MI development and occurrence.

Blood transcriptome analysis revealed the immune changes and immunological adaptation of wildness training giant pandas

The giant panda (Ailuropoda melanoleuca) is a global flagship species for biodiversity conservation. As the time for captive giant pandas to be released into the wild matures, wildness training is provided to allow adaptation to their natural environment. It is assumed that changes in the immune system would be integral in this adaptation from captive to wild, where many more pathogens would be encountered in their natural habitats. Therefore, this study aims to determine the expression changes of immune-related genes and their potential as immunoassay markers for adaptation monitoring in wildness training giant pandas, and then to understand the adaptation strategy of wildness training giant pandas to the wild environment, thereby improving the success rate of panda reintroduction. We obtained 300 differentially expressed genes (DEGs) by RNA-seq, with 239 up-regulated and 61 down-regulated DEGs in wildness training giant pandas compared to captive pandas. Functional enrichment analysis indicated that up-regulated DEGs were enriched in several immune-related terms and pathways. There were 21 immune-related DEGs, in which most of them were up-regulated in wildness training giant pandas, including several critical innate and cellular immune genes. IL1R2 was the most significantly up-regulated gene and is a signature of homeostasis within the immune system. In the protein-protein interaction (PPI) analysis, CXCL8, CXCL10, and CCL5 were identified as the hub immune genes. Our results suggested that wildness training giant pandas have stronger innate and cellular immunity than captive giant pandas, and we proposed that a gene set of CXCL8, CXCL10, CCL5, CD3D, NFKBIA, TBX21, IL12RB2, and IL1R2 may serve as potential immunoassay markers to monitor and assess the immune status of wildness training giant pandas. Our study offers the first insight into immune alterations of wildness training giant pandas, paving the way for monitoring and evaluating the immune status of giant pandas when reintroducing them into the wild.

OUP accepted manuscript

Type 2 diabetes is a complex, systemic disease affected by both genetic and environmental factors. Previous research has identified genetic variants associated with type 2 diabetes risk; however, gene regulatory changes underlying progression to metabolic dysfunction are still largely unknown. We investigated RNA expression changes that occur during diabetes progression using a two-stage approach. In our discovery stage, we compared changes in gene expression using two longitudinally collected blood samples from subjects whose fasting blood glucose transitioned to a level consistent with type 2 diabetes diagnosis between the time points against those who did not with a novel analytical network approach. Our network methodology identified 17 networks, one of which was significantly associated with transition status. This 822-gene network harbors many genes novel to the type 2 diabetes literature but is also significantly enriched for genes previously associated with type 2 diabetes. In the validation stage, we queried associations of genetically determined expression with diabetes-related traits in a large biobank with linked electronic health records. We observed a significant enrichment of genes in our identified network whose genetically determined expression is associated with type 2 diabetes and other metabolic traits and validated 31 genes that are not near previously reported type 2 diabetes loci. Finally, we provide additional functional support, which suggests that the genes in this network are regulated by enhancers that operate in human pancreatic islet cells. We present an innovative and systematic approach that identified and validated key gene expression changes associated with type 2 diabetes transition status and demonstrated their translational relevance in a large clinical resource.

Screening of Crucial Differentially-Methylated/Expressed Genes for Alzheimer's Disease

Background: We aimed to make an integrated analysis of published transcriptome and DNA methylation dataset to ascertain the key differentially methylated and differentially expressed genes for Alzherimer's disease (AD). Methods: Two gene expression microarrays and 1 gene methylation microarray were downloaded for identification of differentially expressed genes and differentially methylated genes. Then, we used various biological information databases to annotate the functions of the differentially-methylated/expressed genes, and screen out key genes and important signaling pathways. Finally, we validate the differentially-methylated/expressed genes in the additional online datasets and in blood from AD patients.Results: A total of 8 hub hypomethylated-high expression genes were obtained, including Rac family small GTPase 2, FGR proto-oncogene, Src family tyrosine kinase, LYN proto-oncogene, Src family tyrosine kinase, protein kinase C delta, myosin IF, integrin subunit alpha 5, semaphorin 4D, and growth arrest specific protein 7. Some enriched signaling pathways of hypomethylated-high expression genes were identified, including regulation of actin cytoskeleton, chemokine signaling pathway, Fc gamma R-mediated phagocytosis, and axon guidance. Conclusion: Differentially-methylated/expressed genes are likely to be associated with AD.

A transcriptome-wide association study identifies novel blood-based gene biomarker candidates for Alzheimer's disease risk

Alzheimer's disease (ad) adversely affects the health, quality of life and independence of patients. There is a critical need to identify novel blood gene biomarkers for ad risk assessment. We performed a transcriptome-wide association study to identify biomarker candidates for ad risk. We leveraged two sets of gene expression prediction models of blood developed using different reference panels and modeling strategies. By applying the prediction models to a meta-GWAS including 71 880 (proxy) cases and 383 378 (proxy) controls, we identified significant associations of genetically determined expression of 108 genes in blood with ad risk. Of these, 15 genes were differentially expressed between ad patients and controls with concordant directions in measured expression data. With evidence from the analyses based on both genetic instruments and directly measured expression levels, this study identifies 15 genes with strong support as biomarkers in blood for ad risk, which may enhance ad risk assessment and mechanism-focused studies.

RNA-Seq analysis in giant pandas reveals the differential expression of multiple genes involved in cataract formation

BACKGROUND

The giant panda (Ailuropoda melanoleuca) is an endangered mammalian species native to China. Fewer than 2500 giant pandas are known to exist, many of which are bred in captivity as a means to preserve and repopulate the species. Like other captive mammals, giant pandas acquire age-related cataracts, reducing their quality of life. Recent comparative genome-wide methylation analysis revealed 110 differentially methylated genes associated with cataract formation including six also associated with the formation of age-related cataracts in humans.

RESULTS

To investigate the pathological pathway in greater detail, here we used RNA-Seq analysis to investigate the differential expression profiles of genes in three giant pandas with cataracts and three healthy controls. We identified more than 700 differentially expressed genes, 29 of which were selected for further analysis based on their low q-value. We found that many of the genes encoded regulatory and signaling proteins associated with the control of cell growth, migration, differentiation and apoptosis, supporting previous research indicating a key role for apoptosis in cataract formation.

CONCLUSION

The identification of genes involved in the formation of age-related cataracts could facilitate the development of predictive markers, preventative measures and even new therapies to improve the life of captive animals.

Toxoplasma gondii could have a possible role in the cancer mechanism by modulating the host's cell response

Toxoplasma gondii, which manipulates many signaling pathways to achieve persistence in host cells, is intimately linked to immune and inflammation responses. However, there is still lack of information about the impact of T. gondii on cellular and immune responses. This study was designed to seek the impact of T. gondii infection causing life-long inflammation in brain, on cancer mechanism. To identify molecular effects of the T. gondii and understand the association between the functional perturbations occurring during infection and cancer development, the transcriptomic datasets obtained mice infected with T. gondii were downloaded from GEO. The differentially expressed genes (DEGs) were identified and functional enrichment analysis was performed using IPA platform, then all results were evaluated with comparison analyses. Subsequently, a T. gondii infection model with human neuroepithelioma cell culture was performed in order to validate top DEGs participated in common networks/pathways in cancer mechanism. Transcriptomic analyses of infected mice and in vitro cell culture model revealed a strong immune response and inflammation occurred by parasite-induced damage and parasite-associated immunopathology in host cell and tissue. T. gondii infection could modulate certain signaling pathways of host, which were also common to those perturbed in carcinogenesis. Interestingly, the network analysis of the data sets predicted an activation in development of solid cancer vice versa inhibition in hematological cancer during T. gondii infection. Parasite might also control the tumor growth due to its potent immune-stimulant effects. As result, T. gondii infection generating a continual inflammation in tissues might potentially contribute to cancer development by regulating critical host signaling pathways or reveal an anti-tumoral activity.

Immune-related gene expression signatures in colorectal cancer

The immune system is crucial in regulating colorectal cancer (CRC) tumorigenesis. Identification of immune-related transcriptomic signatures derived from the peripheral blood of patients with CRC would provide insights into CRC pathogenesis, and suggest novel clues to potential immunotherapy strategies for the disease. The present study collected blood samples from 59 patients with CRC and 62 healthy control patients and performed whole blood gene expression profiling using microarray hybridization. Immune-related gene expression signatures for CRC were identified from immune gene datasets, and an algorithmic predictive model was constructed for distinguishing CRC from controls. Model performance was characterized using an area under the receiver operating characteristic curve (ROC AUC). Functional categories for CRC-specific gene expression signatures were determined using gene set enrichment analyses. A Kaplan-Meier plotter survival analysis was also performed for CRC-specific immune genes in order to characterize the association between gene expression and CRC prognosis. The present study identified five CRC-specific immune genes [protein phosphatase 3 regulatory subunit Bα (PPP3R1), amyloid β precursor protein, cathepsin H, proteasome activator subunit 4 and DEAD-Box Helicase 3 X-Linked]. A predictive model based on this five-gene panel showed good discriminatory power (independent test set sensitivity, 83.3%; specificity, 94.7%, accuracy, 89.2%; ROC AUC, 0.96). The candidate genes were involved in pathways associated with ‘adaptive immune responses’, ‘innate immune responses’ and ‘cytokine signaling’. The survival analysis found that a high level of PPP3R1 expression was associated with a poor CRC prognosis. The present study identified five CRC-specific immune genes that were potential diagnostic biomarkers for CRC. The biological function analysis indicated a close association between CRC pathogenesis and the immune system, and may reveal more information about the immunogenic and pathogenic mechanisms driving CRC in the future. Overall, the association between PPP3R1 expression and survival of patients with CRC revealed potential new targets for CRC immunotherapy.

Blood Transcriptomics of Turbot Scophthalmus maximus: A Tool for Health Monitoring and Disease Studies

Simple Summary

The analysis of blood gene expression is emerging as a relevant source of information about the health status of an organism. While these investigations are increasingly performed in human and terrestrial animals, their potential is still underexplored in fish pathology. The aim of this work was to analyze the blood transcriptional profile of a commercially important flatfish species, turbot (Scophthalmus maximus), in healthy and diseased specimens. The analysis of the most expressed genes in healthy fish indicated that turbot red blood cells have important immunological functions. In diseased fish, parasitized by a myxozoan, the blood analysis reflected a broad inhibition of the immune response followed by intense inflammatory activation in heavy infections. The results showed that turbot response appears delayed, dysregulated and ineffective in stopping the infection. Particularly, a proper development of the adaptive immune response was lacking. This study points out that blood gene expression profiling is a reliable tool for health monitoring, as well as to advance in the knowledge of fish immunity and diseases.

Abstract

Blood transcriptomics is emerging as a relevant tool to monitor the status of the immune system and assist in diagnosis, prognosis, treatment and pathogenesis studies of diseases. In fish pathology, the potential of transcriptome profiling of blood is still poorly explored. Here, RNA sequencing was applied to analyze the blood transcriptional profile of turbot (Scophthalmus maximus), the most important farmed flatfish. The study was conducted in healthy specimens and specimens parasitized by the myxozoan Enteromyxum scophthalmi, which causes one of the most devastating diseases in turbot aquaculture. The blood of healthy turbot showed a transcriptomic profile mainly related to erythrocyte gas transportation function, but also to antigen processing and presentation. In moderately infected turbot, the blood reflected a broad inhibition of the immune response. Particularly, down-regulation of the B cell receptor signaling pathway was shared with heavily parasitized fish, which showed larger transcriptomic changes, including the activation of the inflammatory response. Turbot response to enteromyxosis proved to be delayed, dysregulated and ineffective in stopping the infection. The study evinces that blood transcriptomics can contribute to a better understanding of the teleost immune system and serve as a reliable tool to investigate the physiopathological status of fish.