Blood Gene Expression Signatures Research Articles

Autoinflammation in patients with leukocytic CBL loss of heterozygosity is caused by constitutive ERK-mediated monocyte activation.

Patients heterozygous for germline CBL loss-of-function (LOF) variants can develop myeloid malignancy, autoinflammation, or both, if some or all of their leukocytes become homozygous for these variants through somatic loss of heterozygosity (LOH) via uniparental isodisomy. We observed an upregulation of the inflammatory gene expression signature in whole blood from these patients, mimicking monogenic inborn errors underlying autoinflammation. Remarkably, these patients had constitutively activated monocytes that secreted 10 to 100 times more inflammatory cytokines than those of healthy individuals and CBL LOF heterozygotes without LOH. CBL-LOH hematopoietic stem and progenitor cells (HSPCs) outgrew the other cells, accounting for the persistence of peripheral monocytes homozygous for the CBL LOF variant. ERK pathway activation was required for the excessive production of cytokines by both resting and stimulated CBL-LOF monocytes, as shown in monocytic cell lines. Finally, we found that about 1 in 10,000 individuals in the UK Biobank were heterozygous for CBL LOF variants and that these carriers were at high risk of hematological and inflammatory conditions.

Gene expression signatures in blood from a West African sepsis cohort define host response phenotypes

Our limited understanding of the pathophysiological mechanisms that operate during sepsis is an obstacle to rational treatment and clinical trial design. There is a critical lack of data from low- and middle-income countries where the sepsis burden is increased which inhibits generalized strategies for therapeutic intervention. Here we perform RNA sequencing of whole blood to investigate longitudinal host response to sepsis in a Ghanaian cohort. Data dimensional reduction reveals dynamic gene expression patterns that describe cell type-specific molecular phenotypes including a dysregulated myeloid compartment shared between sepsis and COVID-19. The gene expression signatures reported here define a landscape of host response to sepsis that supports interventions via targeting immunophenotypes to improve outcomes.

Antiviral responses induced by Tdap-IPV vaccination are associated with persistent humoral immunity to Bordetella pertussis

Many countries continue to experience pertussis epidemics despite widespread vaccination. Waning protection after booster vaccination has highlighted the need for a better understanding of the immunological factors that promote durable protection. Here we apply systems vaccinology to investigate antibody responses in adolescents in the Netherlands (N = 14; NL) and the United Kingdom (N = 12; UK) receiving a tetanus-diphtheria-acellular pertussis-inactivated poliovirus (Tdap-IPV) vaccine. We report that early antiviral and interferon gene expression signatures in blood correlate to persistence of pertussis-specific antibody responses. Single-cell analyses of the innate response identified monocytes and myeloid dendritic cells (MoDC) as principal responders that upregulate antiviral gene expression and type-I interferon cytokine production. With public data, we show that Tdap vaccination stimulates significantly lower antiviral/type-I interferon responses than Tdap-IPV, suggesting that IPV may promote antiviral gene expression. Subsequent in vitro stimulation experiments demonstrate TLR-dependent, IPV-specific activation of the pro-inflammatory p38 MAP kinase pathway in MoDCs. Together, our data provide insights into the molecular host response to pertussis booster vaccination and demonstrate that IPV enhances innate immune activity associated with persistent, pertussis-specific antibody responses.

Prospective observational study to validate a next-generation sequencing blood RNA signature to predict early kidney transplant rejection

The objective of this study was to validate the performance of Tutivia, a peripheral blood gene expression signature, in predicting early acute rejection (AR) post–kidney transplant. Recipients of living or deceased donor kidney transplants were enrolled in a nonrandomized, prospective, global, and observational study (NCT04727788). The main outcome was validation of the area under the curve (AUC) of Tutivia vs serum creatinine at biopsy alone, or Tutivia + serum creatinine at biopsy. Of the 151 kidney transplant recipients, the mean cohort age was 53 years old, and 64% were male. There were 71% (107/151) surveillance/protocol biopsies and 29% (44/151) for-cause biopsies, with a 31% (47/151) overall rejection rate. Tutivia (AUC 0.69 [95% CI: 0.59-0.77]) and AUC of Tutivia + creatinine at biopsy (0.68 [95% CI: 0.59-0.77]) were greater than the AUC of creatinine at biopsy alone (0.51.4 [95% CI: 0.43-0.60]). Applying a model cut-off of 50 (scale 0-100) generated a high- and low-risk category for AR with a negative predictive value of 0.79 (95% CI: 0.71-0.86), a positive predictive value of 0.60 (95% CI: 0.45-0.74), and an odds ratio of 5.74 (95% CI: 2.63-12.54). Tutivia represents a validated noninvasive approach for clinicians to accurately predict early AR, beyond the current standard of care.

Post-COVID symptoms are associated with endotypes reflecting poor inflammatory and hemostatic modulation.

Persistent symptoms after COVID-19 infection ("long COVID") negatively affects almost half of COVID-19 survivors. Despite its prevalence, its pathophysiology is poorly understood, with multiple host systems likely affected. Here, we followed patients from hospital to discharge and used a systems-biology approach to identify mechanisms of long COVID. RNA-seq was performed on whole blood collected early in hospital and 4-12 weeks after discharge from 24 adult COVID-19 patients (10 reported post-COVID symptoms after discharge). Differential gene expression analysis, pathway enrichment, and machine learning methods were used to identify underlying mechanisms for post-COVID symptom development. Compared to patients with post-COVID symptoms, patients without post-COVID symptoms had larger temporal gene expression changes associated with downregulation of inflammatory and coagulation genes over time. Patients could also be separated into three patient endotypes with differing mechanistic trajectories, which was validated in another published patient cohort. The "Resolved" endotype (lowest rate of post-COVID symptoms) had robust inflammatory and hemostatic responses in hospital that resolved after discharge. Conversely, the inflammatory/hemostatic responses of "Suppressive" and "Unresolved" endotypes (higher rates of patients with post-COVID symptoms) were persistently dampened and activated, respectively. These endotypes were accurately defined by specific blood gene expression signatures (6-7 genes) for potential clinical stratification. This study allowed analysis of long COVID whole blood transcriptomics trajectories while accounting for the issue of patient heterogeneity. Two of the three identified and externally validated endotypes ("Unresolved" and "Suppressive") were associated with higher rates of post-COVID symptoms and either persistently activated or suppressed inflammation and coagulation processes. Gene biomarkers in blood could potentially be used clinically to stratify patients into different endotypes, paving the way for personalized long COVID treatment.

Diagnosis of childhood febrile illness using a multi-class blood RNA molecular signature

Appropriate treatment and management of children presenting with fever depend on accurate and timely diagnosis, but current diagnostic tests lack sensitivity and specificity and are frequently too slow to inform initial treatment. As an alternative to pathogen detection, host gene expression signatures in blood have shown promise in discriminating several infectious and inflammatory diseases in a dichotomous manner. However, differential diagnosis requires simultaneous consideration of multiple diseases. Here, we show that diverse infectious and inflammatory diseases can be discriminated by the expression levels of a single panel of genes in blood. A multi-class supervised machine-learning approach, incorporating clinical consequence of misdiagnosis as a "cost" weighting, was applied to a whole-blood transcriptomic microarray dataset, incorporating 12 publicly available datasets, including 1,212 children with 18 infectious or inflammatory diseases. The transcriptional panel identified was further validated in a new RNA sequencing dataset comprising 411 febrile children. We identified 161 transcripts that classified patients into 18 disease categories, reflecting individual causative pathogen and specific disease, as well as reliable prediction of broad classes comprising bacterial infection, viral infection, malaria, tuberculosis, or inflammatory disease. The transcriptional panel was validated in an independent cohort and benchmarked against existing dichotomous RNA signatures. Our data suggest that classification of febrile illness can be achieved with a single blood sample and opens the way for a new approach for clinical diagnosis. European Union's Seventh Framework no. 279185; Horizon2020 no. 668303 PERFORM; Wellcome Trust (206508/Z/17/Z); Medical Research Foundation (MRF-160-0008-ELP-KAFO-C0801); NIHR Imperial BRC.

Serum IL-8 as a Determinant of Response to Phosphodiesterase-4 Inhibition in Chronic Obstructive Pulmonary Disease.

Rationale: Phosphodiesterase-4 (PDE4) inhibitors have demonstrated increased efficacy in patients with chronic obstructive pulmonary disease who had chronic bronchitis or higher blood eosinophil counts. Further characterization of patients who are most likely to benefit is warranted. Objective: To identify determinants of response to the PDE4 inhibitor tanimilast. Methods: A PDE4 gene expression signature in blood was developed by unsupervised clustering of the ECLIPSE study dataset (ClinicalTrials.gov ID: NCT00292552; Gene Expression Omnibus Series ID: GSE76705). The signature was further evaluated using blood and sputum transcriptome data from the BIOMARKER study (NCT03004417; GSE133513), enabling validation of the association between PDE4 signaling and target biomarkers. Predictivity of the associated biomarkers against clinical response was then tested in the phase-2b PIONEER tanimilast study (NCT02986321). Measurements and Main Results: The PDE4 gene expression signature developed in the ECLIPSE dataset classified subgroups of patients associated with different PDE4 signaling in the BIOMARKER cohort with an area under the receiver operator curve of 98%. In the BIOMARKER study, serum IL-8 was the only variable that was consistently associated with PDE4 signaling, with lower levels associated with higher PDE4 activity. In the PIONEER study, the exacerbation rate reduction mediated by tanimilast treatment increased up to twofold in patients with lower IL-8 levels; 36% versus 18%, reaching statistical significance at ⩽20 pg/ml (P = 0.035). The combination with blood eosinophils ⩾150 μl-1 or chronic bronchitis provided further additive exacerbation rate reduction: 45% (P = 0.013) and 47% (P = 0.027), respectively. Conclusions: Using selected heterogeneous datasets, this analysis identifies IL-8 as an independent predictor of PDE4 inhibition, as tanimilast had a greater effect on exacerbation prevention in patients with chronic obstructive pulmonary disease who had lower baseline serum IL-8 levels. Testing of this biomarker in other datasets is warranted. Clinical trial registered with www.clinicaltrials.gov (NCT00292552 [Gene Expression Omnibus Series ID: GSE76705], NCT03004417 [GSE133513], and NCT02986321).

Patients with schizophrenia and bipolar disorder display a similar global gene expression signature in whole blood that reflects elevated proportion of immature neutrophil cells with association to lipid changes

Schizophrenia (SCZ) and bipolar disorder (BD) share clinical characteristics, genetic susceptibility, and immune alterations. We aimed to identify differential transcriptional patterns in peripheral blood cells of patients with SCZ or BD versus healthy controls (HC). We analyzed microarray-based global gene expression data in whole blood from a cohort of SCZ (N = 329), BD (N = 203) and HC (N = 189). In total, 65 genes were significantly differentially expressed in SCZ and 125 in BD, as compared to HC, with similar ratio of up- and downregulated genes in both disorders. Among the top differentially expressed genes, we found an innate immunity signature that was shared between SCZ and BD, consisting of a cluster of upregulated genes (e.g., OLFM4, ELANE, BPI and MPO) that indicate an increased fraction of immature neutrophils. Several of these genes displayed sex differences in the expression pattern, and post-hoc analysis demonstrated a positive correlation with triglyceride and a negative correlation with HDL cholesterol. We found that many of the downregulated genes in SCZ and BD were associated with smoking. These findings of neutrophil granulocyte-associated transcriptome signatures in both SCZ and BD point at altered innate immunity pathways with association to lipid changes and potential for clinical translation.

RNA-Sequencing Reveals Gene Expression and Pathway Signatures in Umbilical Cord Blood Affected by Birth Delivery Mode.

The online version contains supplementary material available at 10.1007/s43657-022-00086-7.

320 - Single Cell RNA Sequencing Identifies IL-17- and CSF-1-Associated Pathologic Gene Expression Signatures in Blood during Chronic Graft-Versus-Host Disease

320 - Single Cell RNA Sequencing Identifies IL-17- and CSF-1-Associated Pathologic Gene Expression Signatures in Blood during Chronic Graft-Versus-Host Disease

A temporal classifier predicts histopathology state and parses acute-chronic phasing in inflammatory bowel disease patients

Previous studies have conducted time course characterization of murine colitis models through transcriptional profiling of differential expression. We characterize the transcriptional landscape of acute and chronic models of dextran sodium sulfate (DSS) and adoptive transfer (AT) colitis to derive temporal gene expression and splicing signatures in blood and colonic tissue in order to capture dynamics of colitis remission and relapse. We identify sub networks of patient-derived causal networks that are enriched in these temporal signatures to distinguish acute and chronic disease components within the broader molecular landscape of IBD. The interaction between the DSS phenotype and chronological time-point naturally defines parsimonious temporal gene expression and splicing signatures associated with acute and chronic phases disease (as opposed to ordinary time-specific differential expression/splicing). We show these expression and splicing signatures are largely orthogonal, i.e. affect different genetic bodies, and that using machine learning, signatures are predictive of histopathological measures from both blood and intestinal data in murine colitis models as well as an independent cohort of IBD patients. Through access to longitudinal multi-scale profiling from disease tissue in IBD patient cohorts, we can apply this machine learning pipeline to generation of direct patient temporal multimodal regulatory signatures for prediction of histopathological outcomes.

Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19.

BackgroundThe COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information.MethodsGene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD.ResultsThe best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-β) signalling.ConclusionsGene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.

Cluster analysis of transcriptomic datasets to identify endotypes of idiopathic pulmonary fibrosis

BackgroundConsiderable clinical heterogeneity in idiopathic pulmonary fibrosis (IPF) suggests the existence of multiple disease endotypes. Identifying these endotypes would improve our understanding of the pathogenesis of IPF and could allow...

Blood and brain gene expression signatures of chronic intermittent ethanol consumption in mice.

Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heterogeneous set of behavioral signs and symptoms. There are no laboratory tests that provide direct objective evidence for diagnosis. Microarray and RNA-Seq technologies enable genome-wide transcriptome profiling at low costs and provide an opportunity to identify biomarkers to facilitate diagnosis, prognosis, and treatment of patients. However, access to brain tissue in living patients is not possible. Blood contains cellular and extracellular RNAs that provide disease-relevant information for some brain diseases. We hypothesized that blood gene expression profiles can be used to diagnose AUD. We profiled brain (prefrontal cortex, amygdala, and hypothalamus) and blood gene expression levels in C57BL/6J mice using RNA-seq one week after chronic intermittent ethanol (CIE) exposure, a mouse model of alcohol dependence. We found a high degree of preservation (rho range: [0.50, 0.67]) between blood and brain transcript levels. There was small overlap between blood and brain DEGs, and considerable overlap of gene networks perturbed after CIE related to cell-cell signaling (e.g., GABA and glutamate receptor signaling), immune responses (e.g., antigen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logistic regression, random forest, and partial least squares discriminant analysis), which were highly accurate at predicting alcohol dependence status (maximum AUC: 90.1%). These results suggest that gene expression profiles from peripheral blood samples contain a biological signature of alcohol dependence that can discriminate between CIE and Air subjects.

R code for publication : Huntington disease gene expression signatures in blood compared to brain of YAC128 mice as candidates for monitoring of pathology v3

R code for publication : Huntington disease gene expression signatures in blood compared to brain of YAC128 mice as candidates for monitoring of pathology v3

Huntington Disease Gene Expression Signatures in Blood Compared to Brain of YAC128 Mice as Candidates for Monitoring of Pathology.

While the genetic cause of Huntington disease (HD) is known since 1993, still no cure exists. Therapeutic development would benefit from a method to monitor disease progression and treatment efficacy, ideally using blood biomarkers. Previously, HD-specific signatures were identified in human blood representing signatures in human brain, showing biomarker potential. Since drug candidates are generally first screened in rodent models, we aimed to identify HD signatures in blood and brain of YAC128 HD mice and compare these with previously identified human signatures. RNA sequencing was performed on blood withdrawn at two time points and four brain regions from YAC128 and control mice. Weighted gene co-expression network analysis was used to identify clusters of co-expressed genes (modules) associated with the HD genotype. These HD-associated modules were annotated via text-mining to determine the biological processes they represented. Subsequently, the processes from mouse blood were compared with mouse brain, showing substantial overlap, including protein modification, cell cycle, RNA splicing, nuclear transport, and vesicle-mediated transport. Moreover, the disease-associated processes shared between mouse blood and brain were highly comparable to those previously identified in human blood and brain. In addition, we identified HD blood-specific pathology, confirming previous findings for peripheral pathology in blood. Finally, we identified hub genes for HD-associated blood modules and proposed a strategy for gene selection for development of a disease progression monitoring panel.

R code for publication : Huntington disease gene expression signatures in blood compared to brain of YAC128 mice as candidates for monitoring of pathology

R code for publication : Huntington disease gene expression signatures in blood compared to brain of YAC128 mice as candidates for monitoring of pathology

Zinc Supplementation with or without Additional Micronutrients Does Not Affect Peripheral Blood Gene Expression or Serum Cytokine Level in Bangladeshi Children.

Preventive zinc supplementation provided as a stand-alone dispersible tablet, or via home fortification as multiple micronutrient powders (MNPs), has been considered a potential strategy to prevent zinc deficiency and improve health (including immune) outcomes among children in low- and middle-income countries. However, the impact of zinc supplementation on immune profiles has not been well characterized. We sought to define the effect of zinc supplementation on peripheral blood gene expression and cytokine levels among young children in Dhaka, Bangladesh. In a sub-study of a large randomized, controlled, community-based efficacy trial where children 9–11 months of age received one of the following interventions on a daily basis for 24 weeks: (1) MNPs containing 10 mg of zinc; (2) dispersible tablet containing 10 mg zinc; or (3) placebo powder, we used RNA sequencing to profile the peripheral blood gene expression, as well as highly sensitive multiplex assays to detect cytokine profiles. We profiled samples from 100 children enrolled in the parent trial (zinc MNPs 28, zinc tablets 39, placebo 33). We did not detect an effect from either zinc intervention on differential peripheral blood gene expression at the end of the intervention, or an effect from the intervention on changes in gene expression from baseline. We also did not detect an effect from either intervention on cytokine concentrations. Exploratory analysis did not identify an association between undernutrition (defined as stunting, underweight or wasting) and peripheral blood gene expression. Zinc interventions in children did not produce a gene expression or cytokine signature in the peripheral blood. However, this study demonstrates a proof of principle that sensitive multi-omic techniques can be applied to samples collected in field studies.

Immunologic resilience and COVID-19 survival advantage

BackgroundThe risk of severe coronavirus disease 2019 (COVID-19) varies significantly among persons of similar age and is higher in males. Age-independent, sex-biased differences in susceptibility to severe COVID-19 may be ascribable to deficits in a sexually dimorphic protective attribute that we termed immunologic resilience (IR).ObjectiveWe sought to examine whether deficits in IR that antedate or are induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection independently predict COVID-19 mortality.MethodsIR levels were quantified with 2 novel metrics: immune health grades (IHG-I [best] to IHG-IV) to gauge CD8+ and CD4+ T-cell count equilibrium, and blood gene expression signatures. IR metrics were examined in a prospective COVID-19 cohort (n = 522); primary outcome was 30-day mortality. Associations of IR metrics with outcomes in non–COVID-19 cohorts (n = 13,461) provided the framework for linking pre–COVID-19 IR status to IR during COVID-19, as well as to COVID-19 outcomes.ResultsIHG-I, tracking high-grade equilibrium between CD8+ and CD4+ T-cell counts, was the most common grade (73%) among healthy adults, particularly in females. SARS-CoV-2 infection was associated with underrepresentation of IHG-I (21%) versus overrepresentation (77%) of IHG-II or IHG-IV, especially in males versus females (P < .01). Presentation with IHG-I was associated with 88% lower mortality, after controlling for age and sex; reduced risk of hospitalization and respiratory failure; lower plasma IL-6 levels; rapid clearance of nasopharyngeal SARS-CoV-2 burden; and gene expression signatures correlating with survival that signify immunocompetence and controlled inflammation. In non–COVID-19 cohorts, IR-preserving metrics were associated with resistance to progressive influenza or HIV infection, as well as lower 9-year mortality in the Framingham Heart Study, especially in females.ConclusionsPreservation of immunocompetence with controlled inflammation during antigenic challenges is a hallmark of IR and associates with longevity and AIDS resistance. Independent of age, a male-biased proclivity to degrade IR before and/or during SARS-CoV-2 infection predisposes to severe COVID-19.

Oral vitamin D supplementation induces transcriptomic changes in rectal mucosa that are linked to anti-tumour effects

BackgroundThe risk for several common cancers is influenced by the transcriptomic landscape of the respective tissue-of-origin. Vitamin D influences in vitro gene expression and cancer cell growth. We sought to determine whether oral vitamin D induces beneficial gene expression effects in human rectal epithelium and identify biomarkers of response.MethodsBlood and rectal mucosa was sampled from 191 human subjects and mucosa gene expression (HT12) correlated with plasma vitamin D (25-OHD) to identify differentially expressed genes. Fifty subjects were then administered 3200IU/day oral vitamin D3 and matched blood/mucosa resampled after 12 weeks. Transcriptomic changes (HT12/RNAseq) after supplementation were tested against the prioritised genes for gene-set and GO-process enrichment. To identify blood biomarkers of mucosal response, we derived receiver-operator curves and C-statistic (AUC) and tested biomarker reproducibility in an independent Supplementation Trial (BEST-D).ResultsSix hundred twenty-nine genes were associated with 25-OHD level (P < 0.01), highlighting 453 GO-term processes (FDR<0.05). In the whole intervention cohort, vitamin D supplementation enriched the prioritised mucosal gene-set (upregulated gene-set P < 1.0E−07; downregulated gene-set P < 2.6E−05) and corresponding GO terms (P = 2.90E−02), highlighting gene expression patterns consistent with anti-tumour effects. However, only 9 individual participants (18%) showed a significant response (NM gene-set enrichment P < 0.001) to supplementation. Expression changes in HIPK2 and PPP1CC expression served as blood biomarkers of mucosal transcriptomic response (AUC=0.84 [95%CI 0.66–1.00]) and replicated in BEST-D trial subjects (HIPK2 AUC=0.83 [95%CI 0.77–0.89]; PPP1CC AUC=0.91 [95%CI 0.86–0.95]).ConclusionsHigher plasma 25-OHD correlates with rectal mucosa gene expression patterns consistent with anti-tumour effects, and this beneficial signature is induced by short-term vitamin D supplementation. Heterogenous gene expression responses to vitamin D may limit the ability of randomised trials to identify beneficial effects of supplementation on CRC risk. However, in the current study blood expression changes in HIPK2 and PPP1CC identify those participants with significant anti-tumour transcriptomic responses to supplementation in the rectum. These data provide compelling rationale for a trial of vitamin D and CRC prevention using easily assayed blood gene expression signatures as intermediate biomarkers of response.