Blood Transcriptome Profiling Research Articles

Whole blood transcriptome profiles of trypanotolerant and trypanosusceptible cattle highlight a differential modulation of metabolism and immune response during infection by Trypanosoma congolense

Animal African trypanosomosis, caused by blood protozoan parasites transmitted mainly by tsetse flies, represents a major constraint for millions of cattle in sub-Saharan Africa. Exposed cattle include trypanosusceptible indicine breeds, severely affected by the disease, and West African taurine breeds called trypanotolerant owing to their ability to control parasite development, survive and grow in enzootic areas. Until now the genetic basis of trypanotolerance remains unclear. Here, to improve knowledge of the biological processes involved in trypanotolerance versus trypanosusceptibility, we identified bovine genes differentially expressed in five West African cattle breeds during an experimental infection by Trypanosoma congolense and their biological functions. To this end, whole blood genome-wide transcriptome of three trypanotolerant taurine breeds (N’Dama, Lagune and Baoulé), one susceptible zebu (Zebu Fulani) and one African taurine x zebu admixed breed (Borgou) were profiled by RNA sequencing at four time points, one before and three during infection. As expected, infection had a major impact on cattle blood transcriptome regardless of the breed. The functional analysis of differentially expressed genes over time in each breed confirmed an early activation of the innate immune response, followed by an activation of the humoral response and an inhibition of T cell functions at the chronic stage of infection. More importantly, we highlighted overlooked features, such as a strong disturbance in host metabolism and cellular energy production that differentiates trypanotolerant and trypanosusceptible breeds. N’Dama breed showed the earliest regulation of immune response, associated with a strong activation of cellular energy production, also observed in Lagune, and to a lesser extent in Baoulé. Susceptible Zebu Fulani breed differed from other breeds by the strongest modification in lipid metabolism regulation. Overall, this study provides a better understanding of the biological mechanisms at work during infection, especially concerning the interplay between immunity and metabolism that seems differentially regulated depending on the cattle breeds.

Whole blood transcriptomic profiling in the interpretation of variable phenotype presentation in Fabry disease

Whole blood transcriptomic profiling in the interpretation of variable phenotype presentation in Fabry disease

Next-generation whole blood transcriptome-based assay for advanced adenoma detection.

77 Background: Colorectal Cancer (CRC) is the second leading cause of cancer mortality worldwide although highly curable if detected early. An accurate liquid biopsy test for early cancer and precancerous lesion, detection is key to promote prevention and reduce mortality. We previously developed a liquid biopsy test based on immune cells response to the tumor, commercialised under the name of Colox, with best-in-class clinical performances for AA detection (52% sensitivity and 92% specificity) (Ciarloni L et al, Clin Cancer Res, 2016). An improved second generation of the test, leveraging transcriptome profiling and advanced machine learning tools, is under development and first results are presented. Methods: Prospective peripheral whole-blood (PAXgene) samples from subjects diagnosed with CRC, advanced adenoma (AA), non-advanced adenoma, other types of cancer as well as controls without colorectal neoplasia (CON) were divided into discovery and validation sets. Transcriptome profiles were generated by RNA-seq and gene expression signatures identified leveraging Novigenix’s proprietary LITOseek platform, which integrates several advanced Machine Learning (ML) methods into a ranking systems. Biological functional analysis was performed by over-representation (ORA), gene set enrichment (GSEA) and gene network analyses (STRINGdb). Results: Significant changes in the whole blood transcriptome profile of AA compared to CON were identified. Functional analysis highlighted upregulation of fatty acid derivative biosynthesis, interferon signaling, tryptophan catabolism to kynurenine, and downregulation of DNA repair in AA blood samples compared to CON. A novel gene classifier was generated, showing for AA detection 71% sensitivity, 94% specificity and an AUC of 74% by cross-validation on the discovery set. Validation of the gene classifier in an independent set is currently ongoing and will be presented at the congress. Conclusions: Capturing immune-related information using whole blood trascriptome profiling and applying cutting-edge machine learning technologies demonstrated to be valuable for identifying gene signatures for advanced adenoma detection. This differentiated solution has demonstrated best-in-class potential to significantly improve patient outcomes by detecting precancerous lesions with a simple non-invasive blood test.

Sex and prior exposure jointly shape innate immune responses to a live herpesvirus vaccine.

Both sex and prior exposure to pathogens are known to influence responses to immune challenges, but their combined effects are not well established in humans, particularly in early innate responses critical for shaping subsequent outcomes. We employed systems immunology approaches to study responses to a replication-defective, herpes simplex virus (HSV) 2 vaccine in men and women either naive or previously exposed to HSV. Blood transcriptomic and cell population profiling showed substantial changes on day 1 after vaccination, but the responses depended on sex and whether the vaccinee was naive or previously exposed to HSV. The magnitude of early transcriptional responses was greatest in HSV naive women where type I interferon (IFN) signatures were prominent and associated negatively with vaccine-induced neutralizing antibody titers, suggesting that a strong early antiviral response reduced the uptake of this replication-defective virus vaccine. While HSV seronegative vaccine recipients had upregulation of gene sets in type I IFN (IFN-α/β) responses, HSV2 seropositive vaccine recipients tended to have responses focused more on type II IFN (IFN-γ) genes. These results together show that prior exposure and sex interact to shape early innate responses that then impact subsequent adaptive immune phenotypes. Intramural Research Program of the NIH, the National Institute of Allergy and Infectious Diseases, and other institutes supporting the Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation. The vaccine trial was supported through a clinical trial agreement between the National Institute of Allergy and Infectious Diseases and Sanofi Pasteur. Clinical trial number: NCT01915212.

High-temporal resolution profiling reveals distinct immune trajectories following the first and second doses of COVID-19 mRNA vaccines.

Knowledge of the mechanisms underpinning the development of protective immunity conferred by mRNA vaccines is fragmentary. Here, we investigated responses to coronavirus disease 2019 (COVID-19) mRNA vaccination via high-temporal resolution blood transcriptome profiling. The first vaccine dose elicited modest interferon and adaptive immune responses, which peaked on days 2 and 5, respectively. The second vaccine dose, in contrast, elicited sharp day 1 interferon, inflammation, and erythroid cell responses, followed by a day 5 plasmablast response. Both post-first and post-second dose interferon signatures were associated with the subsequent development of antibody responses. Yet, we observed distinct interferon response patterns after each of the doses that may reflect quantitative or qualitative differences in interferon induction. Distinct interferon response phenotypes were also observed in patients with COVID-19 and were associated with severity and differences in duration of intensive care. Together, this study also highlights the benefits of adopting high-frequency sampling protocols in profiling vaccine-elicited immune responses.

Large 22q13.3 deletions perturb peripheral transcriptomic and metabolomic profiles in Phelan-McDermid syndrome.

SummaryPhelan-McDermid syndrome (PMS) is a rare neurodevelopmental disorder caused at least in part by haploinsufficiency of the SHANK3 gene, due to sequence variants in SHANK3 or subtelomeric 22q13.3 deletions. Phenotypic differences have been reported between PMS participants carrying small “class I” mutations and large “class II” mutations; however, the molecular perturbations underlying these divergent phenotypes remain obscure. Using peripheral blood transcriptome and serum metabolome profiling, we examined the molecular perturbations in the peripheral circulation associated with a full spectrum of PMS genotypes spanning class I (n = 37) and class II mutations (n = 39). Transcriptomic data revealed 52 genes with blood expression profiles that tightly scale with 22q.13.3 deletion size. Furthermore, we uncover 208 underexpressed genes in PMS participants with class II mutations, which were unchanged in class I mutations. These genes were not linked to 22q13.3 and were strongly enriched for glycosphingolipid metabolism, NCAM1 interactions, and cytotoxic natural killer (NK) immune cell signatures. In silico predictions estimated a reduction in CD56+ CD16– NK cell proportions in class II mutations, which was validated by mass cytometry time of flight. Global metabolomics profiling identified 24 metabolites that were significantly altered in PMS participants with class II mutations and confirmed a general reduction in sphingolipid metabolism. Collectively, these results provide new evidence linking PMS participants carrying class II mutations with decreased expression of cytotoxic cell signatures, reduced relative proportions of NK cells, and lower sphingolipid metabolism. These findings highlight alternative avenues for therapeutic development and offer new mechanistic insights supporting genotype-to-phenotype associations in PMS.

855P Whole blood transcriptomic profiling to predict response to immunotherapy in metastatic melanoma

While immune checkpoint inhibitors (ICI) have revolutionized treatment of metastatic melanoma (MM) patients, still 40–60% of patients do not achieve a clinical benefit. Tissue-based predictive biomarkers are not validated in MM, and non-invasive liquid biomarkers can be an alternative source. Whole-blood transcriptome has shown to identify early response to ICI in urothelial cancer, thus have a potential in the context of MM.

Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis

Chronic non-bacterial osteomyelitis (CNO) is a rare and severe inflammatory bone disorder that can occur in the jaw. It is often associated with systemic conditions including autoimmune deficiency. Medical management of patients and establishment of a correct diagnosis are difficult as the etiology of the disease remains unknown. Therefore, little is known about the disease characteristics at the gene expression level. Here, we explored aspects of CNO based on whole blood RNA sequencing (>6 Gb per sample) of 11 patients and 9 healthy controls in Japan and on a recently developed method that is applicable to small datasets, can estimate a directed gene network, and extract a subnetwork of genes underlying patient characteristics. We identified nine subnetworks, comprising 26 differentially regulated edges and 36 genes, with the gene encoding glycophorin C (GYPC) presenting the highest discrimination ability. The expression of the gene was mostly lower in patients with CNO than in the healthy controls, suggesting an abnormal status of red cells in patients with CNO. This study enhances our understanding of CNO at the transcriptome level and further provides a framework for whole blood RNA sequencing and analysis of data obtained for a better diagnosis of the disease.

Transcriptional profiles predict treatment outcome in patients with tuberculosis and diabetes at diagnosis and at two weeks after initiation of anti-tuberculosis treatment.

SummaryBackgroundGlobally, the tuberculosis (TB) treatment success rate is approximately 85%, with treatment failure, relapse and death occurring in a significant proportion of pulmonary TB patients. Treatment success is lower among people with diabetes mellitus (DM). Predicting treatment outcome early after diagnosis, especially in TB-DM patients, would allow early treatment adaptation for individuals and may improve global TB control.MethodsSamples were collected in a longitudinal cohort study of adult TB patients from South Africa (n = 94) and Indonesia (n = 81), who had concomitant DM (n = 59), intermediate hyperglycaemia (n = 79) or normal glycaemia/no DM (n = 37). Treatment outcome was monitored, and patients were categorized as having a good (cured) or poor (failed, recurrence, died) outcome during treatment and 12 months follow-up. Whole blood transcriptional profiles before, during and at the end of TB treatment were characterized using unbiased RNA-Seq and targeted gene dcRT-MLPA.FindingsWe report differences in whole blood transcriptome profiles, which were observed before initiation of treatment and throughout treatment, between patients with a good versus poor TB treatment outcome. An eight-gene and a 22-gene blood transcriptional signature distinguished patients with a good TB treatment outcome from patients with a poor TB treatment outcome at diagnosis (AUC = 0·815) or two weeks (AUC = 0·834) after initiation of TB treatment, respectively. High accuracy was obtained by cross-validating this signature in an external cohort (AUC = 0·749).InterpretationThese findings suggest that transcriptional profiles can be used as a prognostic biomarker for treatment failure and success, even in patients with concomitant DM.FundingThe research leading to these results, as part of the TANDEM Consortium, received funding from the European Community's Seventh Framework Programme (FP7/2007-2013 Grant Agreement No. 305279) and the Netherlands Organization for Scientific Research (NWO-TOP Grant Agreement No. 91214038). The research leading to the results presented in the Indian validation cohort was supported by Research Council of Norway Global Health and Vaccination Research (GLOBVAC) projects: RCN 179342, 192534, and 248042, the University of Bergen (Norway).

Whole blood transcriptomic profiling identifies molecular pathways related to cardiovascular mortality in heart failure.

AimsChronic heart failure (CHF) is a systemic syndrome with a poor prognosis and a need for novel therapies. We investigated whether whole blood transcriptomic profiling can provide new mechanistic insights into cardiovascular (CV) mortality in CHF.Methods and resultsTranscriptome profiles were generated at baseline from 944 CHF patients from the BIOSTAT‐CHF study, of whom 626 survived and 318 died from a CV cause during a follow‐up of 21 months. Multivariable analysis, including adjustment for cell count, identified 1153 genes (6.5%) that were differentially expressed between those that survived or died and strongly related to a validated clinical risk score for adverse prognosis. The differentially expressed genes mainly belonged to five non‐redundant pathways: adaptive immune response, proteasome‐mediated ubiquitin‐dependent protein catabolic process, T‐cell co‐stimulation, positive regulation of T‐cell proliferation, and erythrocyte development. These five pathways were selectively related (RV coefficients >0.20) with seven circulating protein biomarkers of CV mortality (fibroblast growth factor 23, soluble ST2, adrenomedullin, hepcidin, pentraxin‐3, WAP 4‐disulfide core domain 2, and interleukin‐6) revealing an intricate relationship between immune and iron homeostasis. The pattern of survival‐associated gene expression matched with 29 perturbagen‐induced transcriptome signatures in the iLINCS drug‐repurposing database, identifying drugs, approved for other clinical indications, that were able to reverse in vitro the molecular changes associated with adverse prognosis in CHF.ConclusionSystematic modelling of the whole blood protein‐coding transcriptome defined molecular pathways that provide a link between clinical risk factors and adverse CV prognosis in CHF, identifying both established and new potential therapeutic targets.

Biological pathways and comparison with biopsy signals and cellular origin of peripheral blood transcriptomic profiles during kidney allograft pathology

Kidney transplant injury processes are associated with molecular changes in kidney tissue, primarily related to immune cell activation and infiltration. How these processes are reflected in the circulating immune cells, whose activation is targeted by strong immunosuppressants, is poorly understood. To study this, we analyzed the molecular alterations in 384 peripheral blood samples from four European transplant centers, taken at the time of a kidney allograft biopsy, selected for their phenotype, using RNA-sequencing. In peripheral blood, differentially expressed genes in 136 rejection and 248 no rejection samples demonstrated upregulation of glucocorticoid receptor and nucleotide oligomerization domain-like receptor signaling pathways. Pathways enriched in antibody-mediated rejection (ABMR) were strongly immune-specific, whereas pathways enriched in T cell-mediated rejection were less immune related. In polyomavirus infection, upregulation of mitochondrial dysfunction and interferon signaling pathways was seen. Next, we integrated the blood results with transcriptomics of 224 kidney allograft biopsies which showed consistently upregulated genes per phenotype in both blood and biopsy. In single-cell RNASeq (scRNASeq) analysis of seven kidney allograft biopsies, the consistently overexpressed genes in ABMR were mostly expressed by infiltrating leukocytes in the allograft. Similarly, in peripheral blood scRNASeq analysis, these genes were overexpressed in ABMR in immune cell subtypes. Furthermore, overexpression of these genes in ABMR was confirmed in independent cohorts in blood and biopsy. Thus, our results highlight the immune activation pathways in peripheral blood leukocytes at the time of kidney allograft pathology, despite the use of current strong immunosuppressants, and provide a framework for future therapeutic interventions.

Risk factors, transcriptomics, and outcomes of myocardial injury following lower extremity revascularization

Myocardial injury after non-cardiac surgery (MINS) is common. We investigated the incidence and outcomes of MINS, and mechanistic underpinnings using pre-operative whole blood gene expression profiling in a prospective cohort study of individuals undergoing lower extremity revascularization (LER) for peripheral artery disease (PAD). Major adverse cardiovascular and limb events (MACLE) were defined as a composite of death, myocardial infarction, stroke, major lower extremity amputation or reoperation. Among 226 participants undergoing LER, MINS occurred in 53 (23.5%). Patients with MINS had a greater incidence of major adverse cardiovascular events (49.1% vs. 22.0%, adjusted HR 1.87, 95% CI 1.07–3.26) and MACLE (67.9% vs. 44.5%; adjusted HR 1.66, 95% CI 1.08–2.55) at median 20-month follow-up. Pre-operative whole blood transcriptome profiling of a nested matched MINS case–control cohort (n = 41) identified upregulation of pathways related to platelet alpha granules and coagulation in patients who subsequently developed MINS. Thrombospondin 1 (THBS1) mRNA expression was 60% higher at baseline in patients who later developed MINS, and was independently associated with long-term cardiovascular events in the Duke Catheterization Genetics biorepository cohort. In conclusion, pre-operative THBS1 mRNA expression is higher in patients who subsequently develop MINS and is associated with incident cardiovascular events. Pathways related to platelet activity and coagulation associated with MINS provide novel insights into mechanisms of myocardial injury.

Prediction of treatment response: Personalized medicine in the management of rheumatoid arthritis.

Highly efficacious drugs are widely available for treating rheumatoid arthritis (RA). However, accurately selecting a likely effective drug for individual RA patients has been challenging. Biomarkers are required since clinical phenotypes are not reliable to guide the choice of drugs. Previously identified genetic variants for predicting treatment response have failed in replication in independent cohorts of RA patients. Recent studies aimed at the discovery of biomarkers to predict treatment response have focused on integrative omics analysis, expanded to the microbiome, and further finer definition of synovial pathotypes. Treatment responders and non-responders of RA patients can be distinguished by distinct signatures at baseline in their gut microbiota compositions, peripheral blood transcriptome profiling or histomorphological and molecular pathotypes of synovitis. These distinct biological signatures are promising for developing clinically applicable tools for decision in the selection of drugs for RA, albeit further validations in independent cohorts are required.

Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8+ T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis.

BackgroundTuberculosis (TB) is a major infectious disease, where incomplete information about host genetics and immune responses is hindering the development of transformative therapies. This study characterized the immune cell landscape and blood transcriptomic profile of patients with pulmonary TB (PTB) to identify the potential therapeutic biomarkers.MethodsThe blood transcriptome profile of patients with PTB and controls were used for fractionating immune cell populations with the CIBERSORT algorithm and then to identify differentially expressed genes (DEGs) with R/Bioconductor packages. Later, systems biology investigations (such as semantic similarity, gene correlation, and graph theory parameters) were implemented to prioritize druggable genes contributing to the immune cell alterations in patients with TB. Finally, real time-PCR (RT-PCR) was used to confirm gene expression levels.ResultsPatients with PTB had higher levels of four immune subpopulations like CD8+ T cells (P = 1.9 × 10−8), natural killer (NK) cells resting (P = 6.3 × 10−5), monocytes (P = 6.4 × 10−6), and neutrophils (P = 1.6 × 10−7). The functional enrichment of 624 DEGs identified in the blood transcriptome of patients with PTB revealed major dysregulation of T cell-related ontologies and pathways (q ≤ 0.05). Of the 96 DEGs shared between transcriptome and immune cell types, 39 overlapped with TB meta-profiling genetic signatures, and their semantic similarity analysis with the remaining 57 genes, yielded 45 new candidate TB markers. This study identified 9 CD8+ T cell-associated genes (ITK, CD2, CD6, CD247, ZAP70, CD3D, SH2D1A, CD3E, and IL7R) as potential therapeutic targets of PTB by combining computational druggability and co-expression (r2 ≥ |0.7|) approaches.ConclusionThe changes in immune cell proportion and the downregulation of T cell-related genes may provide new insights in developing therapeutic compounds against chronic TB.

Raspberry consumption: identification of distinct immune-metabolic response profiles by whole blood transcriptome profiling

Numerous studies have reported that diets rich in phenolic compounds are beneficial to immune-metabolic health, yet these effects are heterogeneous and the underlying mechanisms are poorly understood. To investigate the inter-individual variability of the immune-metabolic response to raspberry consumption, whole-blood RNAseq data from 24 participants receiving 280 g/d of raspberries for 8 weeks were used for the identification of responsiveness subgroups by using partial least squares-discriminant analysis (PLSDA) and hierarchical clustering. Transcriptomic-based clustering regrouped participants into two distinct subgroups of 13 and 11 participants, so-called responders and non-responders, respectively. Following raspberry consumption, a significant decrease in triglycerides, cholesterol and C-reactive protein levels were found in responders, as compared to non-responders. Two major gene expression components of 100 and 220 genes were identified by sparse PLSDA as those better discriminating responders from non-responders, and functional analysis identified pathways related to cytokine production, leukocyte activation and immune response as significantly enriched with most discriminant genes. As compared to non-responders, the plasma lipidomic profile of responders was characterized by a significant decrease in triglycerides and an increase in phosphatidylcholines following raspberry consumption. Prior to the intervention, a distinct metagenomic profile was identified by PLSDA between responsiveness subgroups, and the Firmicutes-to-Bacteroidota ratio was found significantly lower in responders, as compared to non-responders. Findings point to this transcriptomic-based clustering approach as a suitable tool to identify distinct responsiveness subgroups to raspberry consumption. This approach represents a promising framework to tackle the issue of inter-individual variability in the understanding of the impact of foods on immune-metabolic health.

Longevity-Associated Transcription Factor ATF7 Promotes Healthspan by Suppressing Cellular Senescence and Systematic Inflammation.

Aging is characterized by persistent low-grade systematic inflammation, which is largely responsible for the occurrence of various age-associated diseases. We and others have previously reported that long-lived people (such as centenarians) can delay the onset of or even escape certain major age-related diseases. Here, by screening blood transcriptome and inflammatory profiles, we found that long-lived individuals had a relatively lower inflammation level (IL6, TNFα), accompanied by up-regulation of activating transcription factor 7 (ATF7). Interestingly, ATF7 expression was gradually reduced during cellular senescence. Loss of ATF7 induced cellular senescence, while overexpression delayed senescence progress and senescence-associated secretory phenotype (SASP) secretion. We showed that the anti-senescence effects of ATF7 were achieved by inhibiting nuclear factor kappa B (NF-κB) signaling and increasing histone H3K9 dimethylation (H3K9me2). In Caenorhabditis elegans, ATF7 overexpression significantly suppressed aging biomarkers and extended lifespan. Our findings suggest that ATF7 is a longevity-promoting factor that lowers cellular senescence and inflammation in long-lived individuals.

Smoking and Acute Myocardial Infarction: Blood Transcriptome Profiling Captures Common Links

Smoking and Acute Myocardial Infarction: Blood Transcriptome Profiling Captures Common Links

An interferon-related signature characterizes the whole blood transcriptome profile of insulin-resistant individuals\u2014the CODAM study

BackgroundWorldwide, the prevalence of obesity and insulin resistance has grown dramatically. Gene expression profiling in blood represents a powerful means to explore disease pathogenesis, but the potential impact of inter-individual differences in a cell-type profile is not always taken into account. The objective of this project was to investigate the whole blood transcriptome profile of insulin-resistant as compared to insulin-sensitive individuals independent of inter-individual differences in white blood cell profile.ResultsWe report a 3% higher relative amount of monocytes in the insulin-resistant individuals. Furthermore, independent of their white blood cell profile, insulin-resistant participants had (i) higher expression of interferon-stimulated genes and (ii) lower expression of genes involved in cellular differentiation and remodeling of the actin cytoskeleton.ConclusionsWe present an approach to investigate the whole blood transcriptome of insulin-resistant individuals, independent of their DNA methylation-derived white blood cell profile. An interferon-related signature characterizes the whole blood transcriptome profile of the insulin-resistant individuals, independent of their white blood cell profile. The observed signature indicates increased systemic inflammation possibly due to an innate immune response and whole-body insulin resistance, which can be a cause or a consequence of insulin resistance. Altered gene expression in specific organs may be reflected in whole blood; hence, our results may reflect obesity and/or insulin resistance-related organ dysfunction in the insulin-resistant individuals.

Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes

Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); however, features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown. We hypothesized that genetic and environmental risk factors can both contribute to T1D through dynamic alterations of molecular interactions in physiologic networks. To test this hypothesis, we utilized longitudinal blood transcriptomic profiles in The Environmental Determinants of Diabetes in the Young (TEDDY) study to generate gene co-expression networks. In network modules that contain immune response genes associated with T1D, we observed highly dynamic differences in module connectivity in the 600 days (~ 2 years) preceding clinical diagnosis of T1D. Our results suggest that gene co-expression is highly plastic and that connectivity differences in T1D-associated immune system genes influence the timing and development of clinical disease.

Robust Virus-Specific Adaptive Immunity in COVID-19 Patients with SARS-CoV-2 \u0394382 Variant Infection

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) that have become dominant as the pandemic progresses bear the ORF8 mutation together with multiple spike mutations. A 382-nucleotide deletion (Δ382) in the ORF7b and ORF8 regions has been associated with milder disease phenotype and less systemic inflammation in COVID-19 patients. However, its impact on host immunity against SARS-CoV-2 remains undefined. Here, RNA-sequencing was performed to elucidate whole blood transcriptomic profiles and identify contrasting immune signatures between patients infected with either wildtype or Δ382 SARS-CoV-2 variant. Interestingly, the immune landscape of Δ382 SARS-CoV-2 infected patients featured an increased adaptive immune response, evidenced by enrichment of genes related to T cell functionality, a more robust SARS-CoV-2-specific T cell immunity, as well as a more rapid antibody response. At the molecular level, eukaryotic initiation factor 2 signaling was found to be upregulated in patients bearing Δ382, and its associated genes were correlated with systemic levels of T cell-associated and pro-inflammatory cytokines. This study provides more in-depth insight into the host–pathogen interactions of ORF8 with great promise as a therapeutic target to combat SARS-CoV-2 infection.