Individuality and variation in gene expression patterns in human blood

Systems Human Immunology and AI: Immune Setpoint and Immune Health

The immune system, critical for human health and implicated in many diseases, defends against pathogens, monitors physiological stress, and maintains tissue and organismal homeostasis. It exhibits substantial variability both within and across individuals and populations. Recent technological and conceptual progress in systems human immunology has provided predictive insights that link personal immune states to intervention responses and disease susceptibilities. Artificial intelligence (AI), particularly machine learning (ML), has emerged as a powerful tool for analyzing complex immune data sets, revealing hidden patterns across biological scales, and enabling predictive models for individualistic immune responses and potentially personalized interventions. This review highlights recent advances in deciphering human immune variation and predicting outcomes, particularly through the concepts of immune setpoint, immune health, and use of the immune system as a window for measuring health. We also provide a brief history of AI; review ML modeling approaches, including their applications in systems human immunology; and explore the potential of AI to develop predictive models and personal immune state embeddings to detect early signs of disease, forecast responses to interventions, and guide personalized health strategies.

An augmented GSNMF model for complete deconvolution of bulk RNA-seq data

Performing complete deconvolution analysis for bulk RNA-seq data to obtain both cell type specific gene expression profiles (GEP) and relative cell abundances is a challenging task. One of the fundamental models used, the nonnegative matrix factorization (NMF), is mathematically ill-posed. Although several complete deconvolution methods have been developed, and their estimates compared to ground truth for some datasets appear promising, a comprehensive understanding of how to circumvent the ill-posedness and improve solution accuracy is lacking. In this paper, we first investigated the necessary requirements for a given dataset to satisfy the solvability conditions in NMF theory. Even with solvability conditions, the "unique" solutions of NMF are subject to a rescaling matrix. Therefore, we provide estimates of the converged local minima and the possible rescaling matrix, based on informative initial conditions. Using these strategies, we developed a new pipeline of pseudo-bulk tissue data augmented, geometric structure guided NMF model (GSNMF+). In our approach, pseudo-bulk tissue data was generated, by statistical distribution simulated pseudo cellular compositions and single-cell RNA-seq (scRNA-seq) data, and then mixed with the original dataset. The constituent matrices of the hybrid dataset then satisfy the weak solvability conditions of NMF. Furthermore, an estimated rescaling matrix was used to adjust the minimizer of the NMF, which was expected to reduce mean square root errors of solutions. Our algorithms are tested on several realistic bulk-tissue datasets and showed significant improvements in scenarios with singular cellular compositions.

LungGENIE: the lung gene-expression and network imputation engine

BACKGROUND

Few cohorts have study populations large enough to conduct molecular analysis of ex vivo lung tissue for genomic analyses. Transcriptome imputation is a non-invasive alternative with many potential applications. We present a novel transcriptome-imputation method called the Lung Gene Expression and Network Imputation Engine (LungGENIE) that uses principal components from blood gene-expression levels in a linear regression model to predict lung tissue-specific gene-expression.

METHODS

We use paired blood and lung RNA sequencing data from the Genotype-Tissue Expression (GTEx) project to train LungGENIE models. We replicate model performance in a unique dataset, where we generated RNA sequencing data from paired lung and blood samples available through the SUNY Upstate Biorepository (SUBR). We further demonstrate proof-of-concept application of LungGENIE models in an independent blood RNA sequencing data from the Genetic Epidemiology of COPD (COPDGene) study.

RESULTS

We show that LungGENIE prediction accuracies have higher correlation to measured lung tissue expression compared to existing cis-expression quantitative trait loci-based methods (median Pearson's r = 0.25, IQR 0.19-0.32), with close to half of the reliably predicted transcripts being replicated in the testing dataset. Finally, we demonstrate significant correlation of differential expression results in chronic obstructive pulmonary disease (COPD) from imputed lung tissue gene-expression and differential expression results experimentally determined from lung tissue.

CONCLUSION

Our results demonstrate that LungGENIE provides complementary results to existing expression quantitative trait loci-based methods and outperforms direct blood to lung results across internal cross-validation, external replication, and proof-of-concept in an independent dataset. Taken together, we establish LungGENIE as a tool with many potential applications in the study of lung diseases.

Heterogeneity of OAS family expression in tuberculosis and the impact of different sample selection: a comprehensive analysis

The 2'-5' oligoadenylate synthetase (OAS)family, comprising OAS1, OAS2, OAS3, and OASL, has been shown to participate in the host immune response against Mycobacterium tuberculosis (Mtb). However, their expression profiles in tuberculosis (TB) remain inconsistent. In two TB-related datasets, the OAS family exhibits contrasting expression trends. To further investigate, we examined the expression of the OAS family in whole blood, peripheral blood mononuclear cells (PBMC), and pleural fluid mononuclear cells (PFMC) as study samples, focusing on pulmonary tuberculosis (PTB) and tuberculous pleuritis (TPE). The results revealed differing expression patterns of the OAS family in the two diseases. In PFMC samples from TPE patients, the OAS family showed overall upregulation. Additionally, matched samples from nine TPE patients indicated overlapping expression of the OAS family in both PBMC and PFMC samples.

Signature Proteins in Small Extracellular Vesicles of Granulocytes and CD4+ T-Cell Subpopulations Identified by Comparative Proteomic Analysis

Several studies have described the proteomic profile of different immune cell types, but only a few have also analysed the content of their delivered small extracellular vesicles (sEVs). The aim of the present study was to compare the protein signature of sEVs delivered from granulocytes (i.e., neutrophils and eosinophils) and CD4+ T cells (i.e., TH1, TH2, and TH17) to identify potential biomarkers of the inflammatory profile in chronic inflammatory diseases. Qualitative (DDA) and quantitative (DIA-SWATH) analyses of in vitro-produced sEVs revealed proteome variations depending on the cell source. The main differences were found between granulocyte- and TH cell-derived sEVs, with a higher abundance of antimicrobial proteins (e.g., LCN2, LTF, MPO) in granulocyte-derived sEVs and an enrichment of ribosomal proteins (RPL and RPS proteins) in TH-derived sEVs. Additionally, we found differentially abundant proteins between neutrophil and eosinophil sEVs (e.g., ILF2, LTF, LCN2) and between sEVs from different TH subsets (e.g., ISG15, ITGA4, ITGB2, or NAMPT). A "proof-of-concept" assay was also performed, with TH2 biomarkers ITGA4 and ITGB2 displaying a differential abundance in sEVs from T2high and T2low asthma patients. Thus, our findings highlight the potential use of these sEVs as a source of biomarkers for diseases where the different immune cell subsets studied participate, particularly chronic inflammatory pathologies such as asthma or chronic obstructive pulmonary disease (COPD).

Systemic lupus erythematosus genetics: insights into pathogenesis and implications for therapy

Systemic lupus erythematosus (SLE) is a prime example of how the interplay between genetic and environmental factors can trigger systemic autoimmunity, particularly in young women. Although clinical disease can take years to manifest, risk is established by the unique genetic makeup of an individual. Genome-wide association studies have identified almost 200 SLE-associated risk loci, yet unravelling the functional effect of these loci remains a challenge. New analytic tools have enabled researchers to delve deeper, leveraging DNA sequencing and cell-specific and immune pathway analysis to elucidate the immunopathogenic mechanisms. Both common genetic variants and rare non-synonymous mutations can interact to increase SLE risk. Notably, variants strongly associated with SLE are often located in genome super-enhancers that regulate MHC class II gene expression. Additionally, the 3D conformations of DNA and RNA contribute to genome regulation and innate immune system activation. Improved therapies for SLE are urgently needed and current and future knowledge from genetic and genomic research should provide new tools to facilitate patient diagnosis, enhance the identification of therapeutic targets and optimize testing of agents.

Regional European genetic ancestry predicts type I interferon level and risk of severe viral infection

BACKGROUND

Viral infection outcomes vary widely between individuals, ranging from mild symptoms to severe organ failure and death, and it is clear that host genetic factors play a role in this variability. Type I interferon (IFN) is a critical anti-viral cytokine, and we have previously noted differences in type I IFN levels between world populations.

METHODS

In this study, we investigate the interrelationship between regional European genetic ancestry, type I IFN levels and severe viral infection outcomes.

RESULTS

In cohorts of European ancestry lupus patients living in Europe, we noted higher IFN in the Northwestern populations as compared to Southeastern populations. In an independent cohort of European ancestry lupus patients from the USA with varying proportional regional European genetic admixture, we observed the same Northwest vs. Southeast European ancestry IFN gradient. We developed a model to predict type I IFN level based on regional European ancestry (Area under the curve (AUC) = 0.73, P = 6.1e-6). Examining large databases containing serious viral outcomes data, we found that lower predicted IFN in the corresponding European country was significantly correlated with increased viral infection fatality rate, including Coronavirus Disease 2019 (COVID-19), viral hepatitis and HIV [correlation coefficients: -0.79 (P = 4e-2), -0.94 (P = 6e-3) and -0.96 (P = 8e-2), respectively].

CONCLUSIONS

This association between predicted type I IFN level and viral outcome severity suggests a potential causal relationship, as greater intrinsic type I IFN is beneficial in host defense against viruses. Genetic testing could provide insight into individual and population level risk of fatality due to viruses prior to infection, across a wide range of viral pathogens.

Time- and sex-dependent delayed effects of acute radiation exposure manifest via miRNA dysregulation

The detrimental effects of high-dose ionizing radiation on human health are well-known, but the influence of sex differences on the delayed effects of acute radiation exposure (DEARE) remains unclear. Here, we conducted six-month animal experiments using escalating radiation doses (7-9 Gy) on male and female C57BL/6 mice. The results show that female mice exhibited greater resistance to radiation, showing increased survival at six months post-total body irradiation. LD50/30 (lethal dose expected to cause 50% lethality in 30 days) for female mice is 8.08 Gy, while for male mice it is 7.76 Gy. DEARE causes time- and sex-dependent dysregulation of microRNA expression, processing enzymes, and the HOTAIR regulatory pathway. Differential regulation of molecular patterns associated with growth, development, apoptosis, and cancer is also observed in male and female mice. These findings shed light on the molecular basis of age and sex differences in DEARE response and emphasize the importance of personalized medicine for mitigating radiation-induced injuries and diseases.

Early cellular and molecular signatures correlate with severity of West Nile virus infection

Infection with West Nile virus (WNV) drives a wide range of responses, from asymptomatic to flu-like symptoms/fever or severe cases of encephalitis and death. To identify cellular and molecular signatures distinguishing WNV severity, we employed systems profiling of peripheral blood from asymptomatic and severely ill individuals infected with WNV. We interrogated immune responses longitudinally from acute infection through convalescence employing single-cell protein and transcriptional profiling complemented with matched serum proteomics and metabolomics as well as multi-omics analysis. At the acute time point, we detected both elevation of pro-inflammatory markers in innate immune cell types and reduction of regulatory T cell activity in participants with severe infection, whereas asymptomatic donors had higher expression of genes associated with anti-inflammatory CD16+ monocytes. Therefore, we demonstrated the potential of systems immunology using multiple cell-type and cell-state-specific analyses to identify correlates of infection severity and host cellular activity contributing to an effective anti-viral response.

Extensive Alternative Splicing Patterns in Systemic Lupus Erythematosus Highlight Sexual Differences

Substantial evidence highlights divergences in immune responses between men and women. Women are more susceptible to autoimmunity, whereas men suffer from the more severe presentation of autoimmune disorders. The molecular mechanism of this sexual dimorphism remains elusive. Herein, we conducted a comprehensive analysis of sex differences in whole-blood gene expression focusing on alternative splicing (AS) events in systemic lupus erythematosus (SLE), which is a prototype sex-biased disease. This study included 79 SLE patients with active disease and 58 matched healthy controls who underwent whole-blood RNA sequencing. Sex differences in splicing events were widespread, existent in both SLE and a healthy state. However, we observed distinct gene sets and molecular pathways targeted by sex-dependent AS in SLE patients as compared to healthy subjects, as well as a notable sex dissimilarity in intron retention events. Sexually differential spliced genes specific to SLE patients were enriched for dynamic cellular processes including chromatin remodeling, stress and inflammatory responses. Remarkably, the extent of sexual differences in AS in the SLE patients and healthy individuals exceeded those in gene expression. Overall, this study reveals an unprecedent variation in sex-dependent splicing events in SLE and the healthy state, with potential implications for understanding the molecular basis of sexual dimorphism in autoimmunity.

Occupational exposure to potentially toxic elements alters gene expression profiles in formal and informal Brazilian workers

Chemical elements, such as toxic metals, have previously demonstrated their ability to alter gene expression in humans and other species. In this study, microarray analysis was used to compare the gene expression profiles of different occupational exposure populations: a) informal workers who perform soldering of jewelry inside their houses (n = 22) in São Paulo (SP) State; and b) formal workers from a steel company (n = 10) in Rio de Janeiro (RJ) state, Brazil. Control participants were recruited from the same neighborhoods without occupational chemical exposure (n = 19 in SP and n = 8 in RJ). A total of 68 blood samples were collected and RNA was extracted and hybridized using an Agilent microarray platform. Data pre-processing, statistical and pathway analysis were performed using GeneSpring software. Different expression was detected by fold-change analysis resulting in 16 up- and 33 down-regulated genes in informal workers compared to the control group. Pathway analysis revealed genes enriched in MAPK, Toll-like receptor, and NF-kappa B signaling pathways, involved in inflammatory and immune responses. In formal workers, 20 up- and 50 down-regulated genes were found related to antimicrobial peptides, defensins, neutrophil degranulation, Fc-gamma receptor-dependent phagocytosis, and pathways associated with atherosclerosis development, which is one of the main factors involved in the progression of cardiovascular diseases. The gene IFI27 was the only one commonly differentially expressed between informal and formal workers and is known to be associated with various types of cancer. In conclusion, differences in gene expression related to occupational exposure are mainly associated with inflammation and immune response. Previous research has identified a link between inflammation and immune responses and the development of chronic diseases, suggesting that prolonged occupational exposures to potentially toxic elements in Brazilian metal workers could lead to negative health outcomes. Further analysis should be carried out to investigate its direct effects and to validate causal associations.

Blood transcriptome sequencing identifies biomarkers able to track disease stages in spinocerebellar ataxia type 3

Transcriptional dysregulation has been described in spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD), an autosomal dominant ataxia caused by a polyglutamine expansion in the ataxin-3 protein. As ataxin-3 is ubiquitously expressed, transcriptional alterations in blood may reflect early changes that start before clinical onset and might serve as peripheral biomarkers in clinical and research settings. Our goal was to describe enriched pathways and report dysregulated genes, which can track disease onset, severity or progression in carriers of the ATXN3 mutation (pre-ataxic subjects and patients). Global dysregulation patterns were identified by RNA sequencing of blood samples from 40 carriers of ATXN3 mutation and 20 controls and further compared with transcriptomic data from post-mortem cerebellum samples of MJD patients and controls. Ten genes-ABCA1, CEP72, PTGDS, SAFB2, SFSWAP, CCDC88C, SH2B1, LTBP4, MEG3 and TSPOAP1-whose expression in blood was altered in the pre-ataxic stage and simultaneously, correlated with ataxia severity in the overt disease stage, were analysed by quantitative real-time PCR in blood samples from an independent set of 170 SCA3/MJD subjects and 57 controls. Pathway enrichment analysis indicated the Gαi signalling and the oestrogen receptor signalling to be similarly affected in blood and cerebellum. SAFB2, SFSWAP and LTBP4 were consistently dysregulated in pre-ataxic subjects compared to controls, displaying a combined discriminatory ability of 79%. In patients, ataxia severity was associated with higher levels of MEG3 and TSPOAP1. We propose expression levels of SAFB2, SFSWAP and LTBP4 as well as MEG3 and TSPOAP1 as stratification markers of SCA3/MJD progression, deserving further validation in longitudinal studies and in independent cohorts.

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.

Initial Weight Loss, Anthropometric Parameters, and Proinflammatory Transcript Levels in Patients with Class I Obesity

Research into early predictors of effective weight loss could help determine more effective therapeutic interventions. In this study, 106 subjects with class I obesity, genotyped with the fat mass and obesity-associated (FTO) rs9930506 gene variant, were enrolled into a 12-week weight loss program (WLP). Anthropometric and body composition measurements were controlled with bioelectrical impedance analysis (BIA) at baseline and after 4 and 12 weeks. Biopsies of abdominal subcutaneous adipose tissue (AT) and venous blood samples were collected to monitor changes in interleukin 6 (IL-6), tumor necrosis factor-alpha (TNF-α), and nuclear factor kappa B (NF-κB) mRNA levels in white blood cells (WBCs) and to assess if changes in WBC gene expression reflected changes in adipose tissue. The FTO rs9930506 variant had no effect on weight loss and no reduction in proinflammatory transcripts in WBCs or AT. Changes in anthropometric parameters were associated with changes in carbohydrate metabolism. A linear regression model showed that initial weight loss (after 4 weeks of the WLP) was the most predictive factor of weight loss success after 12 weeks of the WLP. Changes in plasma lipids or proinflammatory transcript levels in WBCs or AT were not associated with weight loss effectiveness. However, the gene expression in WBCs did reflect changes occurring in subcutaneous AT.

Gene expression profiling in whole blood stimulated ex vivo with lipopolysaccharide as a tool to predict post-stroke depressive symptoms: Proof-of-concept study

Prediction of post-stroke depressive symptoms (DSs) is challenging in patients without a history of depression. Gene expression profiling in blood cells may facilitate the search for biomarkers. The use of an ex vivo stimulus to the blood helps to reveal differences in gene profiles by reducing variation in gene expression. We conducted a proof-of-concept study to determine the usefulness of gene expression profiling in lipopolysaccharide (LPS)-stimulated blood for predicting post-stroke DS. Out of 262 enrolled patients with ischemic stroke, we included 96 patients without a pre-stroke history of depression and not taking any anti-depressive medication before or during the first 3 months after stroke. We assessed DS at 3 months after stroke using the Patient Health Questionnaire-9. We used RNA sequencing to determine the gene expression profile in LPS-stimulated blood samples taken on day 3 after stroke. We constructed a risk prediction model using a principal component analysis combined with logistic regression. We diagnosed post-stroke DS in 17.7% of patients. Expression of 510 genes differed between patients with and without DS. A model containing 6 genes (PKM, PRRC2C, NUP188, CHMP3, H2AC8, NOP10) displayed very good discriminatory properties (area under the curve: 0.95) with the sensitivity of 0.94 and specificity of 0.85. Our results suggest the potential utility of gene expression profiling in whole blood stimulated with LPS for predicting post-stroke DS. This method could be useful for searching biomarkers of post-stroke depression.

Pathogenesis of systemic lupus erythematosus: risks, mechanisms and therapeutic targets

Research elucidating the pathogenesis of systemic lupus erythematosus (SLE) has defined two critical families of mediators, type I interferon (IFN-I) and autoantibodies targeting nucleic acids and nucleic acid-binding proteins, as fundamental contributors to the disease. On the fertile background of significant genetic risk, a triggering stimulus, perhaps microbial, induces IFN-I, autoantibody production or most likely both. When innate and adaptive immune system cells are engaged and collaborate in the autoimmune response, clinical SLE can develop. This review describes recent data from genetic analyses of patients with SLE, along with current studies of innate and adaptive immune function that contribute to sustained IFN-I pathway activation, immune activation and autoantibody production, generation of inflammatory mediators and tissue damage. The goal of these studies is to understand disease mechanisms, identify therapeutic targets and stimulate development of therapeutics that can achieve improved outcomes for patients.

Long-Term Use of Amoxicillin Is Associated with Changes in Gene Expression and DNA Methylation in Patients with Low Back Pain and Modic Changes

Long-term antibiotics are prescribed for a variety of medical conditions, recently including low back pain with Modic changes. The molecular impact of such treatment is unknown. We conducted longitudinal transcriptome and epigenome analyses in patients (n = 100) receiving amoxicillin treatment or placebo for 100 days in the Antibiotics in Modic Changes (AIM) study. Gene expression and DNA methylation were investigated at a genome-wide level at screening, after 100 days of treatment, and at one-year follow-up. We identified intra-individual longitudinal changes in gene expression and DNA methylation in patients receiving amoxicillin, while few changes were observed in patients receiving placebo. After 100 days of amoxicillin treatment, 28 genes were significantly differentially expressed, including the downregulation of 19 immunoglobulin genes. At one-year follow-up, the expression levels were still not completely restored. The significant changes in DNA methylation (n = 4548 CpGs) were mainly increased methylation levels between 100 days and one-year follow-up. Hence, the effects on gene expression occurred predominantly during treatment, while the effects on DNA methylation occurred after treatment. In conclusion, unrecognized side effects of long-term amoxicillin treatment were revealed, as alterations were observed in both gene expression and DNA methylation that lasted long after the end of treatment.

The DNA damage response to radiological imaging: from ROS and γH2AX foci induction to gene expression responses in vivo

Candidate ionising radiation exposure biomarkers must be validated in humans exposed in vivo. Blood from patients undergoing positron emission tomography-computed tomography scan (PET-CT) and skeletal scintigraphy (scintigraphy) was drawn before (0 h) and after (2 h) the procedure for correlation analyses of the response of selected biomarkers with radiation dose and other available patient information. FDXR, CDKN1A, BBC3, GADD45A, XPC, and MDM2 expression was determined by qRT-PCR, DNA damage (γH2AX) by flow cytometry, and reactive oxygen species (ROS) levels by flow cytometry using the 2', 7'-dichlorofluorescein diacetate test in peripheral blood mononuclear cells (PBMC). For ROS experiments, 0- and 2-h samples were additionally exposed to UVA to determine whether diagnostic irradiation conditioned the response to further oxidative insult. With some exceptions, radiological imaging induced weak γH2AX foci, ROS and gene expression fold changes, the latter with good coherence across genes within a patient. Diagnostic imaging did not influence oxidative stress in PBMC successively exposed to UVA. Correlation analyses with patient characteristics led to low correlation coefficient values. γH2AX fold change, which correlated positively with gene expression, presented a weak positive correlation with injected activity, indicating a radiation-induced subtle increase in DNA damage and subsequent activation of the DNA damage response pathway. The exposure discrimination potential of these biomarkers in the absence of control samples as frequently demanded in radiological emergencies, was assessed using raw data. These results suggest that the variability of the response in heterogeneous populations might complicate identifying individuals exposed to low radiation doses.

Effect of Age and Sex on Gene Expression-Based Radiation Biodosimetry Using Mouse Peripheral Blood

Blood-based gene expression profiles that can reconstruct radiation exposure are being developed as a practical approach to radiation biodosimetry. However, age and sex could potentially limit the accuracy of the approach. In this study, we determined the impact of age on the peripheral blood cell gene expression profile of female mice exposed to radiation and identified differences and similarities with a previously obtained transcriptomic signature of male mice. Young (2 months) and old (24 months) female mice were irradiated with 4 Gy X-rays, total RNA was isolated from blood 24 hours later and subjected to whole-genome microarray analysis. Dose reconstruction analyses using a gene signature trained on gene expression data from irradiated young male mice showed accurate reconstruction of 0 or 4 Gy doses with root mean square error of ±0.75 Gy (R2 = 0.90) in young female mice. Although dose reconstruction for irradiated old female mice was less accurate than young female mice, the deviation from the actual radiation dose was not statistically significant. Pathway analysis of differentially expressed genes revealed that after irradiation, apoptosis-related functions were overrepresented, whereas functions related to quantities of various immune cell subtypes were underrepresented, among differentially expressed genes from young female mice, but not older animals. Furthermore, young mice significantly upregulated genes involved in phagocytosis, a process that eliminates apoptotic cells and preserves tissue homeostasis. Both functions were also overrepresented in young, but not old, male mice following 4 Gy X-irradiation. Lastly, functions associated with neutrophil activation that is essential for killing invading pathogens and regulating the inflammatory response were predicted to be uniquely enriched in young but not old female mice. This work supports the concept that peripheral blood gene expression profiles can be identified in mice that accurately predict physical radiation dose exposure irrespective of age and sex.

Overview of gene expression techniques with an emphasis on vitamin D related studies

Each cell controls when and how its genes must be expressed for proper function. Every function in a cell is driven by signaling molecules through various regulatory cascades. Different cells in a multicellular organism may express very different sets of genes, even though they contain the same DNA. The set of genes expressed in a cell determines the set of proteins and functional RNAs it contains, giving it its unique properties. Malfunction in gene expression harms the cell and can lead to the development of various disease conditions. The use of rapid high-throughput gene expression profiling unravels the complexity of human disease at various levels. Peripheral blood mononuclear cells (PBMC) have been used frequently to understand gene expression homeostasis in various disease conditions. However, more studies are required to validate whether PBMC gene expression patterns accurately reflect the expression of other cells or tissues. Vitamin D, which is responsible for a multitude of health consequences, is also an immune modulatory hormone with major biological activities in the innate and adaptive immune systems. Vitamin D exerts its diverse biological effects in target tissues by regulating gene expression and its deficiency, is recognized as a public health problem worldwide. Understanding the genetic factors that affect vitamin D has the potential benefit that it will make it easier to identify individuals who require supplementation. Different technological advances in gene expression can be used to identify and assess the severity of disease and aid in the development of novel therapeutic interventions. This review focuses on different gene expression approaches and various clinical studies of vitamin D to investigate the role of gene expression in identifying the molecular signature of the disease.

Integrated analysis of circulating cell free nucleic acids for cancer genotyping and immune phenotyping of tumor microenvironment

The circulating cell-free nucleic acids (ccfNAs) consist of a heterogenous cocktail of both single (ssNA) and double-stranded (dsNA) nucleic acids. These ccfNAs are secreted into the blood circulation by both healthy and malignant cells via various mechanisms including apoptosis, necrosis, and active secretion. The major source of ccfNAs are the cells of hematopoietic system under healthy conditions. These ccfNAs include fragmented circulating cell free DNA (ccfDNA), coding or messenger RNA (mRNA), long non-coding RNA (lncRNA), microRNA (miRNA), and mitochondrial DNA/RNA (mtDNA and mtRNA), that serve as prospective biomarkers in assessment of various clinical conditions. For, e.g., free fetal DNA and RNA migrate into the maternal plasma, whereas circulating tumor DNA (ctDNA) has clinical relevance in diagnostic, prognostic, therapeutic targeting, and disease progression monitoring to improve precision medicine in cancer. The epigenetic modifications of ccfDNA as well as circulating cell-free RNA (ccfRNA) such as miRNA and lncRNA show disease-related variations and hold potential as epigenetic biomarkers. The messenger RNA present in the circulation or the circulating cell free mRNA (ccf-mRNA) and long non-coding RNA (ccf-lncRNA) have gradually become substantial in liquid biopsy by acting as effective biomarkers to assess various aspects of disease diagnosis and prognosis. Conversely, the simultaneous characterization of coding and non-coding RNAs in human biofluids still poses a significant hurdle. Moreover, a comprehensive assessment of ccfRNA that may reflect the tumor microenvironment is being explored. In this review, we focus on the novel approaches for exploring ccfDNA and ccfRNAs, specifically ccf-mRNA as biomarkers in clinical diagnosis and prognosis of cancer. Integrating the detection of circulating tumor DNA (ctDNA) for cancer genotyping in conjunction with ccfRNA both quantitatively and qualitatively, may potentially hold immense promise towards precision medicine. The current challenges and future directions in deciphering the complexity of cancer networks based on the dynamic state of ccfNAs will be discussed.

Large Cancer Pedigree Involving Multiple Cancer Genes including Likely Digenic MSH2 and MSH6 Lynch Syndrome (LS) and an Instance of Recombinational Rescue from LS

Lynch syndrome (LS), caused by heterozygous pathogenic variants affecting one of the mismatch repair (MMR) genes (MSH2, MLH1, MSH6, PMS2), confers moderate to high risks for colorectal, endometrial, and other cancers. We describe a four-generation, 13-branched pedigree in which multiple LS branches carry the MSH2 pathogenic variant c.2006G>T (p.Gly669Val), one branch has this and an additional novel MSH6 variant c.3936_4001+8dup (intronic), and other non-LS branches carry variants within other cancer-relevant genes (NBN, MC1R, PTPRJ). Both MSH2 c.2006G>T and MSH6 c.3936_4001+8dup caused aberrant RNA splicing in carriers, including out-of-frame exon-skipping, providing functional evidence of their pathogenicity. MSH2 and MSH6 are co-located on Chr2p21, but the two variants segregated independently (mapped in trans) within the digenic branch, with carriers of either or both variants. Thus, MSH2 c.2006G>T and MSH6 c.3936_4001+8dup independently confer LS with differing cancer risks among family members in the same branch. Carriers of both variants have near 100% risk of transmitting either one to offspring. Nevertheless, a female carrier of both variants did not transmit either to one son, due to a germline recombination within the intervening region. Genetic diagnosis, risk stratification, and counseling for cancer and inheritance were highly individualized in this family. The finding of multiple cancer-associated variants in this pedigree illustrates a need to consider offering multicancer gene panel testing, as opposed to targeted cascade testing, as additional cancer variants may be uncovered in relatives.

Transcriptome Mining to Identify Molecular Markers for the Diagnosis of Staphylococcus epidermidis Bloodstream Infections

Bloodstream infections caused by Staphylococcus epidermidis are often misdiagnosed since no diagnostic marker found so far can unequivocally discriminate "true" infection from sample contamination. While attempts have been made to find genomic and/or phenotypic differences between invasive and commensal isolates, possible changes in the transcriptome of these isolates under in vivo-mimicking conditions have not been investigated. Herein, we characterized the transcriptome, by RNA sequencing, of three clinical and three commensal isolates after 2 h of exposure to whole human blood. Bioinformatics analysis was used to rank the genes with the highest potential to distinguish invasive from commensal isolates and among the ten genes identified as candidates, the gene SERP2441 showed the highest potential. A collection of 56 clinical and commensal isolates was then used to validate, by quantitative PCR, the discriminative power of the selected genes. A significant variation was observed among isolates, and the discriminative power of the selected genes was lost, undermining their potential use as markers. Nevertheless, future studies should include an RNA sequencing characterization of a larger collection of isolates, as well as a wider range of conditions to increase the chances of finding further candidate markers for the diagnosis of bloodstream infections caused by S. epidermidis.

Proteome expression profiling of red blood cells during the tumorigenesis of hepatocellular carcinoma

The early diagnosis of hepatocellular carcinoma (HCC) has not been clinically elucidated, leading to an increased mortality rate in patients with HCC. HCC is a systemic disease related to disorders of blood homeostasis, and the association between red blood cells (RBCs) and HCC tumorigenesis remains elusive. We performed data-independent acquisition proteomic analyses of 72 clinical RBC samples, including HCC (n = 30), liver cirrhosis (LC, n = 17), and healthy controls (n = 25), and characterized the clinical relevance of RBCs and tumorigenesis in HCC. We observed dynamic changes in RBCs during HCC tumorigenesis, and our findings indicate that, based on the protein expression profiles of RBCs, LC is a developmental stage closely approaching HCC. The expression of hemoglobin (HbA and HbF) in peripheral blood dynamically changed during HCC tumorigenesis, suggesting that immature erythroid cells exist in peripheral blood of HCC patients and that erythropoiesis is influenced by the onset of LC. We also identified the disrupted autophagy pathway in RBCs at the onset of LC, which persisted during HCC tumorigenesis. The oxytocin and GnRH pathways were disrupted and first identified during the development of LC into HCC. Significantly differentially expressed SMIM1, ANXA7, HBA1, and HBE1 during tumorigenesis were verified as promising biomarkers for the early diagnosis of HCC using parallel reaction monitoring technology. This study may enhance the understanding of HCC tumorigenesis from a different point of view and aid the early diagnosis of HCC.

RNA-sequencing for transcriptional profiling of whole blood in early stage and metastatic pancreatic cancer patients

We investigated the transcriptional profile of whole blood in early and metastatic stages of pancreatic cancer (PaC) patients to identify potential diagnostic factors for early diagnosis. Blood samples from 18 participants (6 healthy individuals, 6 patients in early stage (I/II) PaC, and 6 patients in metastatic PaC) were analyzed by RNA-sequencing. The expression levels of identified genes were subsequently compared with their expression in pancreatic tumor tissues based on TCGA data reported in UALCAN and GEPIA2 databases. Overall, 331 and 724 genes were identified as differentially expressed genes in early and metastatic stages, respectively. Of these, 146 genes were shared by early and metastatic stages. Upregulation of PTCD3 and UBA52 genes and downregulation of A2M and ARID1B genes in PaC patients were observed from early stage to metastasis. TCGA database showed increasing trend in expression levels of these genes from stage I to IV in pancreatic tumor tissue. Finally, we found that low expression of PTCD3, A2M, and ARID1B genes and high expression of UBA52 gene were positively correlated with PaC patients survival. We identified a four-gene set (PTCD3, UBA52, A2M, and ARID1B) expressed in peripheral blood of early stage and metastatic PaC patients that may be useful for PaC early diagnosis.

Emerging concepts of type I interferons in SLE pathogenesis and therapy

Type I interferons have been suspected for decades to have a crucial role in the pathogenesis of systemic lupus erythematosus (SLE). Evidence has now overturned several long-held assumptions about how type I interferons are regulated and cause pathological conditions, providing a new view of SLE pathogenesis that resolves longstanding clinical dilemmas. This evidence includes data on interferons in relation to genetic predisposition and epigenetic regulation. Importantly, data are now available on the role of interferons in the early phases of the disease and the importance of non-haematopoietic cellular sources of type I interferons, such as keratinocytes, renal tubular cells, glial cells and synovial stromal cells, as well as local responses to type I interferons within these tissues. These local effects are found not only in inflamed target organs in established SLE, but also in histologically normal skin during asymptomatic preclinical phases, suggesting a role in disease initiation. In terms of clinical application, evidence relating to biomarkers to characterize the type I interferon system is complex, and, notably, interferon-blocking therapies are now licensed for the treatment of SLE. Collectively, the available data enable us to propose a model of disease pathogenesis that invokes the unique value of interferon-targeted therapies. Accordingly, future approaches in SLE involving disease reclassification and preventative strategies in preclinical phases should be investigated.

GEOMETRIC STRUCTURE GUIDED MODEL AND ALGORITHMS FOR COMPLETE DECONVOLUTION OF GENE EXPRESSION DATA

Complete deconvolution analysis for bulk RNA-seq data is important and helpful to distinguish whether the differences of disease-associated GEPs (gene expression profiles) in tissues of patients and normal controls are due to changes in cellular composition of tissue samples, or due to GEPs changes in specific cells. One of the major techniques to perform complete deconvolution is nonnegative matrix factorization (NMF), which also has a wide-range of applications in the machine learning community. However, the NMF is a well-known strongly ill-posed problem, so a direct application of NMF to RNA-seq data will suffer severe difficulties in the interpretability of solutions. In this paper, we develop an NMF-based mathematical model and corresponding computational algorithms to improve the solution identifiability of deconvoluting bulk RNA-seq data. In our approach, we combine the biological concept of marker genes with the solvability conditions of the NMF theories, and develop a geometric structures guided optimization model. In this strategy, the geometric structure of bulk tissue data is first explored by the spectral clustering technique. Then, the identified information of marker genes is integrated as solvability constraints, while the overall correlation graph is used as manifold regularization. Both synthetic and biological data are used to validate the proposed model and algorithms, from which solution interpretability and accuracy are significantly improved.

PBMCs: a new source of diagnostic and prognostic biomarkers

There are various types of molecular biomarkers that are derived from distinct starting materials. Although many indirect biomarkers are found in blood, their detection remains a challenging issue because of the high degree of fragmentation, minute quantity and a vast amount of non-specific background. The present review points out the sensitivity and specificity of peripheral blood mononuclear cells (PBMCs) as an intact source of biomarkers in a variety of diseases. Multiple recent studies that have used PBMCs as a source of biomarkers reveal the alteration of mRNAs/microRNAs (miRNAs) signature and methylation profile in many kinds of disorders; for instance, dysregulation of mRNAs/miRNAs in schizophrenia, diabetes and different types of cancers and change in the methylation status of LINE-1 in neoplasms. In conclusion with a strong probability, PBMCs mimic conditions of some tissues which are in contact with them like the tumour cells, hence providing a non-invasive and suitable source of biomarkers.

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.

Impact of medication on blood transcriptome reveals off-target regulations of beta-blockers

Background

For many drugs, mechanisms of action with regard to desired effects and/or unwanted side effects are only incompletely understood. To investigate possible pleiotropic effects and respective molecular mechanisms, we describe here a catalogue of commonly used drugs and their impact on the blood transcriptome.

Methods and results

From a population-based cohort in Germany (LIFE-Adult), we collected genome-wide gene-expression data in whole blood using in Illumina HT12v4 micro-arrays (n = 3,378; 19,974 gene expression probes per individual). Expression profiles were correlated with the intake of active substances as assessed by participants’ medication. This resulted in a catalogue of fourteen substances that were identified as associated with differential gene expression for a total of 534 genes. As an independent replication cohort, an observational study of patients with suspected or confirmed stable coronary artery disease (CAD) or myocardial infarction (LIFE-Heart, n = 3,008, 19,966 gene expression probes per individual) was employed. Notably, we were able to replicate differential gene expression for three active substances affecting 80 genes in peripheral blood mononuclear cells (carvedilol: 25; prednisolone: 17; timolol: 38). Additionally, using gene ontology enrichment analysis, we demonstrated for timolol a significant enrichment in 23 pathways, 19 of them including either GPER1 or PDE4B. In the case of carvedilol, we showed that, beside genes with well-established association with hypertension (GPER1, PDE4B and TNFAIP3), the drug also affects genes that are only indirectly linked to hypertension due to their effects on artery walls or their role in lipid biosynthesis.

Conclusions

Our developed catalogue of blood gene expressions profiles affected by medication can be used to support both, drug repurposing and the identification of possible off-target effects.

Transmissible cancer influences immune gene expression in an endangered marsupial, the Tasmanian devil (Sarcophilus harrisii)

Understanding the effects of wildlife diseases on populations requires insight into local environmental conditions, host defence mechanisms, host life‐history trade‐offs, pathogen population dynamics, and their interactions. The survival of Tasmanian devils (Sarcophilus harrisii) is challenged by a novel, fitness limiting pathogen, Tasmanian devil facial tumour disease (DFTD), a clonally transmissible, contagious cancer. In order to understand the devils’ capacity to respond to DFTD, it is crucial to gain information on factors influencing the devils’ immune system. By using RT‐qPCR, we investigated how DFTD infection in association with intrinsic (sex and age) and environmental (season) factors influences the expression of 10 immune genes in Tasmanian devil blood. Our study showed that the expression of immune genes (both innate and adaptive) differed across seasons, a pattern that was altered when infected with DFTD. The expression of immunogbulins IgE and IgM:IgG showed downregulation in colder months in DFTD infected animals. We also observed strong positive association between the expression of an innate immune gene, CD16, and DFTD infection. Our results demonstrate that sampling across seasons, age groups and environmental conditions are beneficial when deciphering the complex ecoevolutionary interactions of not only conventional host‐parasite systems, but also of host and diseases with high mortality rates, such as transmissible cancers.

Emerging Role of Exosomal Long Non-coding RNAs in Spaceflight-Associated Risks in Astronauts

During spaceflight, astronauts are exposed to multiple unique environmental factors, particularly microgravity and ionizing radiation, that can cause a range of harmful health consequences. Over the past decades, increasing evidence demonstrates that the space environment can induce changes in gene expression and RNA processing. Long non-coding RNA (lncRNA) represent an emerging area of focus in molecular biology as they modulate chromatin structure and function, the transcription of neighboring genes, and affect RNA splicing, stability, and translation. They have been implicated in cancer development and associated with diverse cardiovascular conditions and associated risk factors. However, their role on astronauts' health after spaceflight remains poorly understood. In this perspective article, we provide new insights into the potential role of exosomal lncRNA after spaceflight. We analyzed the transcriptional profile of exosomes isolated from peripheral blood plasma of three astronauts who flew on various Shuttle missions between 1998-2001 by RNA-sequencing. Computational analysis of the transcriptome of these exosomes identified 27 differentially expressed lncRNAs with a Log2 fold change, with molecular, cellular, and clinical implications.

Single-cell expression quantitative trait loci (eQTL) analysis of SLE-risk loci in lupus patient monocytes

BACKGROUND

We performed expression quantitative trait locus (eQTL) analysis in single classical (CL) and non-classical (NCL) monocytes from patients with systemic lupus erythematosus (SLE) to quantify the impact of well-established genetic risk alleles on transcription at single-cell resolution.

METHODS

Single-cell gene expression was quantified using qPCR in purified monocyte subpopulations (CD14++CD16- CL and CD14dimCD16+ NCL) from SLE patients. Novel analysis methods were used to control for the within-person correlations observed, and eQTLs were compared between cell types and risk alleles.

RESULTS

The SLE-risk alleles demonstrated significantly more eQTLs in NCLs as compared to CLs (p = 0.0004). There were 18 eQTLs exclusive to NCL cells, 5 eQTLs exclusive to CL cells, and only one shared eQTL, supporting large differences in the impact of the risk alleles between these monocyte subsets. The SPP1 and TNFAIP3 loci were associated with the greatest number of transcripts. Patterns of shared influence in which different SNPs impacted the same transcript also differed between monocyte subsets, with greater evidence for synergy in NCL cells. IRF1 expression demonstrated an on/off pattern, in which expression was zero in all of the monocytes studied from some individuals, and this pattern was associated with a number of SLE risk alleles. We observed corroborating evidence of this IRF1 expression pattern in public data sets.

CONCLUSIONS

We document multiple SLE-risk allele eQTLs in single monocytes which differ greatly between CL and NCL subsets. These data support the importance of the SPP1 and TNFAIP3 risk variants and the IRF1 transcript in SLE patient monocyte function.

The psychosocial genomics paradigm of hypnosis and mind-body integrated psychotherapy: Experimental evidence

The psychosocial genomics paradigm first proposed by Ernest Rossi established an epistemological shift in our application of hypnosis. We present original experimental research conducted within this paradigm that highlights the mind-gene relationship and, in particular, the positive health effects associated with hypnosis and mind-body integrated psychotherapy. We document that these approaches can stimulate epigenetic modifications and the expression of genes related to anti-inflammatory processes. These strategies strengthen the immune system and reduce oxidative stress both in normal and in oncological participants.

Platform-independent approach for cancer detection from gene expression profiles of peripheral blood cells

Peripheral blood gene expression intensity-based methods for distinguishing healthy individuals from cancer patients are limited by sensitivity to batch effects and data normalization and variability between expression profiling assays. To improve the robustness and precision of blood gene expression-based tumour detection, it is necessary to perform molecular diagnostic tests using a more stable approach. Taking breast cancer as an example, we propose a machine learning-based framework that distinguishes breast cancer patients from healthy subjects by pairwise rank transformation of gene expression intensity in each sample. We showed the diagnostic potential of the method by performing RNA-seq for 37 peripheral blood samples from breast cancer patients and by collecting RNA-seq data from healthy donors in Genotype-Tissue Expression project and microarray mRNA expression datasets in Gene Expression Omnibus. The framework was insensitive to experimental batch effects and data normalization, and it can be simultaneously applied to new sample prediction.

Quantitative analysis of the blood transcriptome of young healthy pigs and its relationship with subsequent disease resilience

Background

Disease resilience, which is the ability of an animal to maintain performance under disease, is important for pigs in commercial herds, where they are exposed to various pathogens. Our objective was to investigate population-level gene expression profiles in the blood of 912 healthy F1 barrows at ~ 27 days of age for associations with performance and health before and after their exposure to a natural polymicrobial disease challenge at ~ 43 days of age.

Results

Most significant (q < 0.20) associations of the level of expression of individual genes in blood of young healthy pigs were identified for concurrent growth rate and subjective health scores prior to the challenge, and for mortality, a combined mortality-treatment trait, and feed conversion rate after the challenge. Gene set enrichment analyses revealed three groups of gene ontology biological process terms that were related to disease resilience: 1) immune and stress response-related terms were enriched among genes whose increased expression was unfavorably associated with both pre- and post-challenge traits, 2) heme-related terms were enriched among genes that had favorable associations with both pre- and post-challenge traits, and 3) terms related to protein localization and viral gene expression were enriched among genes that were associated with reduced performance and health traits after but not before the challenge.

Conclusions

Gene expression profiles in blood from young healthy piglets provide insight into their performance when exposed to disease and other stressors. The expression of genes involved in stress response, heme metabolism, and baseline expression of host genes related to virus propagation were found to be associated with host response to disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07912-8.

Early Prediction of Clinical Response to Anti-TNF Treatment using Multi-omics and Machine Learning in Rheumatoid Arthritis

Objectives

Advances in immunotherapy by blocking TNF have remarkably improved treatment outcomes for Rheumatoid arthritis (RA) patients. Although treatment specifically targets TNF, the downstream mechanisms of immune suppression are not completely understood. The aim of this study was to detect biomarkers and expression signatures of treatment response to TNF inhibition.

Methods

Peripheral blood mononuclear cells (PBMCs) from 39 female patients were collected before anti-TNF treatment initiation (day 0) and after 3 months. The study cohort included patients previously treated with MTX who failed to respond adequately. Response to treatment was defined based on the EULAR criteria and classified 23 patients as responders and 16 as non-responders. We investigated differences in gene expression in PBMCs, the proportion of cell types and cell phenotypes in peripheral blood using flow cytometry and the level of proteins in plasma. Finally, we used machine learning models to predict non-response to anti-TNF treatment.

Results

The gene expression analysis in baseline samples revealed notably higher expression of the gene EPPK1 in future responders. We detected the suppression of genes and proteins following treatment, including suppressed expression of the T cell inhibitor gene CHI3L1 and its protein YKL-40. The gene expression results were replicated in an independent cohort. Finally, machine learning models mainly based on transcriptomic data showed high predictive utility in classifying non-response to anti-TNF treatment in RA.

Conclusions

Our integrative multi-omics analyses identified new biomarkers for the prediction of response, found pathways influenced by treatment and suggested new predictive models of anti-TNF treatment in RA patients.

Development of a method for the determination of the JAK2 gene mRNA in venous blood and assessment of its diagnostic value in oncohematology

Overactive JAK pathway signaling is a hallmark of immune diseases and critically affects on inflammation and coagulation. A number of mutations in the JAK2 gene act as driving forces of myeloproliferative neoplasms (MPN), the pathogenesis of certain variants of acute leukemia, a number of solid malignancies and cardiovascular diseases. Assays for quantifying JAK2 mRNA in circulating blood cells can be used as a marker associated with the activity of this enzyme. Development of an original method for detecting JAK2 mRNA in venous blood and assessment of the possible diagnostic value in chronic oncohematological diseases. The development of an RT-PCR method for determining the expression of the JAK2 gene mRNA in venous blood samples was carried out in accordance with the MIQE requirements. Primers and TaqMan probes were designed using the Primer3 program, taking into account the possibility of excluding subsequent DNase treatment. The stability of the investigated mRNA was assessed in vacutainers with different anticoagulants and depending on the storage time of the samples. The study of the expression of JAK2 mRNA in blood leukocytes of 41 patients with B-CLL, 16 patients with CML, 12 patients with multiple myeloma and 39 donors using the developed "real-time" PCR method. The study revealed a decrease in the level of JAK2 mRNA in venous blood samples in patients with primary CLL, but not with CML or with multiple myeloma. The level of the marker in the majority of patients with CLL after the start of therapy returned to the range typical for healthy people. It has been shown that the values of the relative expression of JAK2 mRNA are most stable in the range of 2 - 7 hours after taking blood in a vacutainer with EDTA. An original RT-PCR method was developed for the quantitative determination of JAK2 mRNA in venous blood samples, which meets the requirements of the MIQE system. Determination of JAK2 mRNA can be useful for clarifying the pathogenesis features of certain diseases involving impaired Janus kinase activity and can become a promising marker for prognosis and assessment of the effectiveness of therapy.

Sex-specific gene expression in the blood of four primates

Blood is an important non-reproductive tissue, but little is known about the sex-specific gene expressions in the blood. Therefore, we investigated sex-specific gene expression differences in the blood tissues of four primates, rhesus macaques (Macaca mulatta), Tibetan macaques (M. thibetana), yellow baboons (Papio cynocephalus), and humans. We identified seven sex-specific differentially expressed genes (SDEGs) in each non-human primate and 31 SDEGs in humans. The four primates had only one common SDEG, MAP7D2. In humans, immune-related SDEGs were identified as up-regulated, but also down-regulated in females. We also found that most of the X-Y gene pairs had similar expression levels between species, except pair EIF1AY/EIF1AX. The expression level of X-Y gene pairs of rhesus and Tibetan macaques showed no significant differential expression levels, while humans had six significant XY-biased and three XX-biased X-Y gene pairs. Our observed sex differences in blood should increase understanding of sex differences in primate blood tissue.

Strategies for detecting and identifying biological signals amidst the variation commonly found in RNA sequencing data

BACKGROUND

RNA sequencing analysis focus on the detection of differential gene expression changes that meet a two-fold minimum change between groups. The variability present in RNA sequencing data may obscure the detection of valuable information when specific genes within certain samples display large expression variability. This paper develops methods that apply variance and dispersion estimates to intra-group data to identify genes with expression values that diverge from the group envelope. STRING database analysis of the identified genes characterize gene affiliations involved in physiological regulatory networks that contribute to biological variability. Individuals with divergent gene groupings within network pathways can thereby be identified and judiciously evaluated prior to standard differential analysis.

RESULTS

A three-step process is presented for evaluating biological variability within a group in RNA sequencing data in which gene counts were: (1) scaled to minimize heteroscedasticity; (2) rank-ordered to detect potentially divergent "trendlines" for every gene in the data set; and (3) tested with the STRING database to identify statistically significant pathway associations among the genes displaying marked trendline variability and dispersion. This approach was used to identify the "trendline" profile of every gene in three test data sets. Control data from an in-house data set and two archived samples revealed that 65-70% of the sequenced genes displayed trendlines with minimal variation and dispersion across the sample group after rank-ordering the samples; this is referred to as a linear trendline. Smaller subsets of genes within the three data sets displayed markedly skewed trendlines, wide dispersion and variability. STRING database analysis of these genes identified interferon-mediated response networks in 11-20% of the individuals sampled at the time of blood collection. For example, in the three control data sets, 14 to 26 genes in the defense response to virus pathway were identified in 7 individuals at false discovery rates ≤1.92 E-15.

CONCLUSIONS

This analysis provides a rationale for identifying and characterizing notable gene expression variability within a study group. The identification of highly variable genes and their network associations within specific individuals empowers more judicious inspection of the sample group prior to differential gene expression analysis.

Multimodal analysis for human ex vivo studies shows extensive molecular changes from delays in blood processing

Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMC up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states.

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Studies of human blood cells and plasma are highly sensitive to process variability

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Time variability distorts biology in cutting-edge single-cell and multiplex assays

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Longitudinal, multi-modal, and aligned data enable data qualification and exploration

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Dataset holds potential novel, multi-modal biological correlations and hypotheses

Role of blood derived cell fractions, temperature and sample transport on gene expression-based biological dosimetry

PURPOSE

For triage purposes following a nuclear accident or a terrorist event, gene expression biomarkers in blood have been demonstrated to be good bioindicators of ionizing radiation (IR) exposure and can be used to assess the dose received by exposed individuals. Many IR-sensitive genes are regulated by the DNA damage response pathway, and modulators of this pathway could potentially affect their expression level and therefore alter accurate dose estimations. In the present study, we addressed the potential influence of temperature, sample transport conditions and the blood cell fraction analyzed on the transcriptional response of the following radiation-responsive genes: FDXR, CCNG1, MDM2, PHPT1, APOBEC3H, DDB2, SESN1, P21, PUMA, and GADD45.

MATERIALS AND METHODS

Whole blood from healthy donors was exposed to a 2 Gy X-ray dose with a dose rate of 0.5 Gy/min (output 13 mA, 250 kV peak, 0.2 mA) and incubated for 24 h at either 37, 22, or 4 °C. For mimicking the effect of transport conditions at different temperatures, samples incubated at 37 °C for 24 h were kept at 37, 22 or 4 °C for another 24 h. Comparisons of biomarker responses to IR between white blood cells (WBCs), peripheral blood mononuclear cells (PBMCs) and whole blood were carried out after a 2 Gy X-ray exposure and incubation at 37 °C for 24 hours.

RESULTS

Hypothermic conditions (22 or 4 °C) following irradiation drastically inhibited transcriptional responses to IR exposure. However, sample shipment at different temperatures did not affect gene expression level except for SESN1. The transcriptional response to IR of specific genes depended on the cell fraction used, apart from FDXR, CCNG1, and SESN1.

CONCLUSION

In conclusion, temperature during the incubation period and cell fraction but not the storing conditions during transport can influence the transcriptional response of specific genes. However, FDXR and CCNG1 showed a consistent response under all the different conditions tested demonstrating their reliability as individual biological dosimetry biomarkers.

Human Inflammatory Neutrophils Express Genes Encoding Peptidase Inhibitors: Production of Elafin Mediated by NF-κB and CCAAT/Enhancer-Binding Protein β

The concept of plasticity of neutrophils is highlighted by studies showing their ability to transdifferentiate into APCs. In this regard, transdifferentiated neutrophils were found at inflammatory sites of autoimmune arthritis (AIA). Exposure of neutrophils to inflammatory stimuli prolongs their survival, thereby favoring the acquisition of pathophysiologically relevant phenotypes and functions. By using microarrays, quantitative RT-PCR, and ELISAs, we showed that long-lived (LL) neutrophils obtained after 48 h of culture in the presence of GM-CSF, TNF, and IL-4 differentially expressed genes related to apoptosis, MHC class II, immune response, and inflammation. The expression of anti-inflammatory genes mainly of peptidase inhibitor families is upregulated in LL neutrophils. Among these, the PI3 gene encoding elafin was the most highly expressed. The de novo production of elafin by LL neutrophils depended on a synergism between GM-CSF and TNF via the activation and cooperativity of C/EBPβ and NF-κB pathways, respectively. Elafin concentrations were higher in synovial fluids (SF) of patients with AIA than in SF of osteoarthritis. SF neutrophils produced more elafin than blood counterparts. These results are discussed with respect to implications of neutrophils in chronic inflammation and the potential influence of elafin in AIA.

Intergenerational trauma is associated with expression alterations in glucocorticoid- and immune-related genes

Offspring of trauma survivors are more likely to develop PTSD, mood, and anxiety disorders and demonstrate endocrine and molecular alterations compared to controls. This study reports the association between parental Holocaust exposure and genome-wide gene expression in peripheral blood mononuclear cells (PBMC) from 77 Holocaust survivor offspring and 15 comparison subjects. Forty-two differentially expressed genes (DEGs) were identified in association with parental Holocaust exposure (FDR-adjusted p < 0.05); most of these genes were downregulated and co-expressed in a gene network related to immune cell functions. When both parental Holocaust exposure and maternal age at Holocaust exposure shared DEGs, fold changes were in the opposite direction. Similarly, fold changes of shared DEGs associated with maternal PTSD and paternal PTSD were in opposite directions, while fold changes of shared DEGs associated with both maternal and paternal Holocaust exposure or associated with both maternal and paternal age at Holocaust exposure were in the same direction. Moreover, the DEGs associated with parental Holocaust exposure were enriched for glucocorticoid-regulated genes and immune pathways with some of these genes mediating the effects of parental Holocaust exposure on C-reactive protein. The top gene across all analyses was MMP8, encoding the matrix metalloproteinase 8, which is a regulator of innate immunity. To conclude, this study identified a set of glucocorticoid and immune-related genes in association with parental Holocaust exposure with differential effects based on parental exposure-related factors.

At the dawn of the transcriptomic medicine

Progress in genomic analytical technologies has improved our possibilities to obtain information regarding DNA, RNA, and their dynamic changes that occur over time or in response to specific challenges. This information describes the blueprint for cells, tissues, and organisms and has fundamental importance for all living organisms. This review focuses on the technological challenges to analyze the transcriptome and what is the impact of transcriptomics on precision medicine. The transcriptome is a term that covers all RNA present in cells and a substantial part of it will never be translated into protein but is nevertheless functional in determining cell phenotype. Recent developments in transcriptomics have challenged the fundamentals of the central dogma of biology by providing evidence of pervasive transcription of the genome. Such massive transcriptional activity is challenging the definition of a gene and especially the term "pseudogene" that has now been demonstrated in many examples to be both transcribed and translated. We also review the common sources of biomaterials for transcriptomics and justify the suitability of whole blood RNA as the current optimal analyte for clinical transcriptomics. At the end of the review, a brief overview of the clinical implications of transcriptomics in clinical trial design and clinical diagnosis is given. Finally, we introduce the transcriptome as a target for modern drug development as a tool for extending our capacity for precision medicine in multiple diseases.

Minimally Invasive Ways of Determining Circadian Rhythms in Humans

Circadian rhythm exerts a critical role in mammalian health and disease. A malfunctioning circadian clock can be a consequence, as well as the cause of several pathophysiologies. Clinical therapies and research may also be influenced by the clock. Since the most suitable manner of revealing this rhythm in humans is not yet established, we discuss existing methods and seek to determine the most feasible ones.

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study

Background

The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D.

Methods

Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts.

Results

We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling.

Conclusions

Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Single cell profiling of capillary blood enables out of clinic human immunity studies

An individual’s immune system is driven by both genetic and environmental factors that vary over time. To better understand the temporal and inter-individual variability of gene expression within distinct immune cell types, we developed a platform that leverages multiplexed single-cell sequencing and out-of-clinic capillary blood extraction to enable simplified, cost-effective profiling of the human immune system across people and time at single-cell resolution. Using the platform, we detect widespread differences in cell type-specific gene expression between subjects that are stable over multiple days.