Blood Transcriptome Profiling Research Articles

SARS-CoV-2 variants induce increased inflammatory gene expression but reduced interferon responses and heme synthesis as compared with wild type strains

SARS-CoV-2 variants of concern (VOC) have been associated with increased viral transmission and disease severity. We investigated the mechanisms of pathogenesis caused by variants using a host blood transcriptome profiling approach. We analysed transcriptional signatures of COVID-19 patients comparing those infected with wildtype (wt), alpha, delta or omicron strains seeking insights into infection in Asymptomatic cases.Comparison of transcriptional profiles of Symptomatic and Asymptomatic COVID-19 cases showed increased differentially regulated gene (DEGs) of inflammatory, apoptosis and blood coagulation pathways, with decreased T cell and Interferon stimulated genes (ISG) activation. Between SARS-CoV-2 strains, an increasing number of DEGs occurred in comparisons between wt and alpha (196), delta (1425) or, omicron (2313) infections. COVID-19 cases with alpha or, delta variants demonstrated suppression transcripts of innate immune pathways. EGR1 and CXCL8 were highly upregulated in those infected with VOC; heme biosynthetic pathway genes (ALAS2, HBB, HBG1, HBD9) and ISGs were downregulated. Delta and omicron infections upregulated ribosomal pathways, reflecting increased viral RNA translation. Asymptomatic COVID-19 cases infected with delta infections showed increased cytokines and ISGs expression. Overall, increased inflammation, with reduced host heme synthesis was associated with infections caused by VOC infections, with raised type I interferon in cases with less severe disease.

An integrative network-based approach to identify driving gene communities in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is an etiologically complex disease characterized by acute exacerbations and stable phases. We aimed to identify biological functions modulated in specific COPD conditions, using whole blood samples collected in the AERIS clinical study (NCT01360398). Considered conditions were exacerbation onset, severity of airway obstruction, and presence of respiratory pathogens in sputum samples. With an integrative multi-network gene community detection (MNGCD) approach, we analyzed expression profiles to identify communities of correlated genes. The approach combined different layers of gene interactions for each explored condition/subset of samples: gene expression similarity, protein-protein interactions, transcription factors, and microRNAs validated regulons. Heme metabolism, interferon-alpha, and interferon-gamma pathways were modulated in patients at both exacerbation and stable-state visits, but with the involvement of distinct sets of genes. An important gene community was enriched with G2M checkpoint, E2F targets, and mitotic spindle pathways during exacerbation. Targets of TAL1 regulator and hsa−let−7b − 5p microRNA were modulated with increasing severity of airway obstruction. Bacterial infections with Moraxella catarrhalis and, particularly, Haemophilus influenzae triggered a specific cellular and inflammatory response in acute exacerbations, indicating an active reaction of the host to infections. In conclusion, COPD is a complex multifactorial disease that requires in-depth investigations of its causes and features during its evolution and whole blood transcriptome profiling can contribute to capturing some relevant regulatory mechanisms associated with this disease. In this work, we explored multi-network modeling that integrated diverse layers of regulatory gene networks and enhanced our comprehension of the biological functions implicated in the COPD pathogenesis.

Blood transcriptome profiling reveals distinct gene networks induced by mRNA vaccination against COVID-19.

Messenger RNA (mRNA) vaccines represent a new class of vaccines that has been shown to be highly effective during the COVID-19 pandemic and that holds great potential for other preventative and therapeutic applications. While it is known that the transcriptional activity of various genes is altered following mRNA vaccination, identifying and studying gene networks could reveal important scientific insights that might inform future vaccine designs. In this study, we conducted an in-depth weighted gene correlation network analysis of the blood transcriptome before and 24h after the second and third vaccination with licensed mRNA vaccines against COVID-19 in humans, following a prime vaccination with either mRNA or ChAdOx1 vaccines. Utilizing this unsupervised gene network analysis approach, we identified distinct modular networks of co-varying genes characterized by either an expressional up- or downregulation in response to vaccination. Downregulated networks were associated with cell metabolic processes and regulation of transcription factors, while upregulated networks were associated with myeloid differentiation, antigen presentation, and antiviral, interferon-driven pathways. Within this interferon-associated network, we identified highly connected hub genes such as STAT2 and RIGI and associated upstream transcription factors, potentially playing important regulatory roles in the vaccine-induced immune response. The expression profile of this network significantly correlated with S1-specific IgG levels at the follow-up visit in vaccinated individuals. Those findings could be corroborated in a second, independent cohort of mRNA vaccine recipients. Collectively, results from this modular gene network analysis enhance the understanding of mRNA vaccines from a systems immunology perspective. Influencing specific gene networks could lead to optimized vaccines that elicit augmented vaccine responses.

Blood transcriptomics reveal systemic eosinophilic and neutrophilic inflammation patterns in patients with nasal polyps.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a chronic sinonasal disease characterized by heterogeneous inflammation. However, the presence of systemic inflammation heterogeneity in CRSwNP patients remains unknown. This study aims to profile transcriptomic alterations in the blood of CRSwNP patients and characterize the CRSwNP heterogeneity based on blood transcriptomic biomarkers. Patients with CRSwNP were prospectively recruited from three hospitals and chronologically divided into exploratory (n=123) and independent validation (n=46) cohorts. Transcriptomic profiles were generated by whole blood mRNA sequencing and subjected to patient clustering, differential expression, and pathway analysis. Differences in immune pattern and clinicopathologic features between clusters were assessed. A transcriptomic signature was defined and applied to an independent cohort to validate the findings. CRSwNP patients showed diverse blood transcriptomic profiles versus healthy controls, or when stratified by tissue and blood eosinophils and asthma comorbidity. Transcriptome-wide correlation analysis revealed a transcriptional signature associated with blood eosinophil levels, consisting of nine T2-related genes (CLC, SIGLEC8, ALOX15, IL5RA, PTGDR2, CCL23, CCR3, EPX and IL1RL1). Three distinct clusters with differing systemic eosinophilic and neutrophilic inflammation patterns and asthma comorbidity were identified based on transcriptomic profiling of T2 and T1/3-related blood biomarkers. A 36-gene signature was developed by machine learning and accurately predicted the three CRSwNP subtypes. Validation on an independent cohort confirmed the prediction robustness. There is heterogeneous systemic inflammation associated with eosinophilic and neutrophilic patterns in patients with CRSwNP. Endotyping based on blood transcriptomic biomarkers might lead to more personalized treatment strategies for CRSwNP in the future.

IBS stress reactivity phenotype is associated with blood transcriptome profiles and microstructural and functional brain changes.

Clinical evidence suggests significant interindividual differences in stress reactivity (SR), but biological mechanisms and therapeutic implications of these differences are poorly understood. We aimed to identify the biological basis of increased SR by investigating associations between a psychometric-based phenotype with blood transcriptomics profiles of increased sympathetic nervous system (SNS) activation and brain imaging phenotypes in irritable bowel syndrome (IBS) participants and healthy controls (HCs). A cross-sectional observational study design, transcriptomics profiling, multimodal brain imaging, and psychosocial assessments were obtained in 291 female and male IBS participants and HCs. Prior to analyses, unsupervised clustering was applied to derive high and low SR subgroups across participants based on two measures of SR. General linear models tested for SR group differences in clinical and biological parameters. Exploratory analyses examined associations between SR group-specific brain alterations and gene expression. The high, compared to low SR group showed greater cyclic AMP response element-binding protein (CREB) gene expression consistent with tonic SNS activity and proinflammatory changes in whole blood. Brain imaging showed neuroplastic changes in the high SR group consistent with an upregulation of ascending arousal systems and sensory processing and integration regions, and functional connectivity changes in the central autonomic network. SR moderated the sex difference in extraintestinal symptoms. The findings support a model of tonically increased SNS activity as a plausible risk factor for increased autonomic reactivity to psychosocial stressors and low grade immune activation in both IBS and HCs, with a greater prevalence in IBS. These findings may have important implications for personalized treatment interventions in IBS.

Early blood immune molecular alterations in cynomolgus monkeys with a PSEN1 mutation causing familial Alzheimer's disease.

More robust non-human primate models of Alzheimer's disease (AD) will provide new opportunities to better understand the pathogenesis and progression of AD. We designed a CRISPR/Cas9 system to achieve precise genomic deletion of exon 9 in cynomolgus monkeys using two guide RNAs targeting the 3' and 5' intron sequences of PSEN1 exon 9. We performed biochemical, transcriptome, proteome, and biomarker analyses to characterize the cellular and molecular dysregulations of this non-human primate model. We observed early changes of AD-related pathological proteins (cerebrospinal fluid Aβ42 and phosphorylated tau) in PSEN1 mutant (ie, PSEN1-ΔE9) monkeys. Blood transcriptome and proteome profiling revealed early changes in inflammatory and immune molecules in juvenile PSEN1-ΔE9 cynomolgus monkeys. PSEN1 mutant cynomolgus monkeys recapitulate AD-related pathological protein changes, and reveal early alterations in blood immune signaling. Thus, this model might mimic AD-associated pathogenesis and has potential utility for developing early diagnostic and therapeutic interventions. A dual-guide CRISPR/Cas9 system successfully mimics AD PSEN1-ΔE9 mutation by genomic excision of exon 9. PSEN1 mutant cynomolgus monkey-derived fibroblasts exhibit disrupted PSEN1 endoproteolysis and increased Aβ secretion. Blood transcriptome and proteome profiling implicate early inflammatory and immune molecular dysregulation in juvenile PSEN1 mutant cynomolgus monkeys. Cerebrospinal fluid from juvenile PSEN1 mutant monkeys recapitulates early changes of AD-related pathological proteins (increased Aβ42 and phosphorylated tau).

Integrative analysis of blood transcriptome profiles in small-cell lung cancer patients for identification of novel chemotherapy resistance-related biomarkers.

Chemoresistance constitutes a prevalent factor that significantly impacts thesurvival of patients undergoing treatment for smal-cell lung cancer (SCLC). Chemotherapy resistance in SCLC patients is generally classified as primary or acquired resistance, each governedby distinct mechanisms that remain inadequately researched. In this study, we performed transcriptome screening of peripheral blood plasma obtainedfrom 17 patients before and after receiving combined etoposide and platinum treatment. We firs testimated pseudo-single-cell analysis using xCell and ESTIMATE and identified differentially expressed genes (DEGs), then performed network analysis to discover key hub genes involved in chemotherapy resistance. Our analysis showed a significant increase in class-switched memory B cell scores acrossboth chemotherapy resistance patterns, indicating their potential crucial role in mediatingresistance. Moreover, network analysis identifed PRICKLE3, TNFSFI0, ACSLl and EP300 as potential contributors to primary resistance, with SNWl, SENP2 and SMNDCl emerging assignificant factors in acquired resistance, providing valuable insights into chemotherapy resistancein SCLC. These findings offer valuable insights for understanding chemotherapy resistance and related gene signatures in SCLC, which could help further biological validation studies.

Proteomic and transcriptomics profiles of serum selenium concentrations in patients with heart failure are associated with immunoregulatory processes

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Dutch Research Council, through the Open Competition ENW-KLEIN grant Background Low selenium concentrations are associated with worse outcomes in patients with heart failure (HF). However, the underlying pathophysiologic mechanisms remain incompletely understood. Therefore, we aimed to contrast serum selenium concentrations to blood proteomic and transcriptomic profiles in patients with HF. Methods Circulating proteins, whole blood transcriptomics and serum selenium measurements in a cohort of 2328 patients with worsening HF (BIOSTAT-CHF) were utilized to assess underlying pathophysiology. Penalized linear regression and gene expression analysis were used to assess proteins and transcriptomics profiles based on selenium concentrations, respectively. String database v11.5 was used for enrichment analyses. Additionally analyses of the association between genes encoding selenoproteins in relation to serum selenium and all-cause mortality were performed. Potential causality was investigated by supplementing human peripheral blood mononuclear cells (PBMCs) with selenium and measuring the concentrations of 18 different cytokines. Results From 356 biomarkers and 20 clinical features, the penalized linear regression model yielded 44 variables with <5% marginal false discovery rate as predictors of serum selenium. Biomarkers associated positively with selenium concentrations included: epidermal growth factor receptor (EGFR), IFN-gamma-R1, CD4, GDF15, and IL10. Biomarkers associated negatively with low selenium concentrations included: PCSK9, SPON2, TNFSF13, FGF21 and PAI. In addition, 148 RNA transcripts were found differentially expressed between high and low Se status (Padj.<0.05; fold change<|0.25|). Enrichment analyses of the selected biomarkers and the selected RNA transcripts identified similar enriched processes, including regulation processes of leukocyte differentiation and activation, as well as cytokines production. The expression of two gene encoding selenoproteins (MSRB1 and GPX4) were strongly correlated with serum selenium after multiple corrections, while GPX4, SELENOK, and SELENOS were associated with prognosis. In the in-vitro setting, PBMCs supplemented with selenium showed significantly lower abundance of several (pro-)inflammatory cytokines. Conclusion These data suggest that immunoregulation is an important mechanism through which selenium might have beneficial roles in heart failure. The beneficial effects of higher serum selenium concentrations are likely because of global immunomodulatory effects on the abundance of cytokines. MSRB1 and GPX4 are interesting targets as potential modulators of this immunoregulatory effect of selenium and should be pursued in future research.Cytokines concentrations

Peripheral blood transcriptomic profiling of molecular mechanisms commonly regulated by binge drinking and placebo effects

Molecular responses to alcohol consumption are dynamic, context-dependent, and arise from a complex interplay of biological and external factors. While many have studied genetic risk associated with drinking patterns, comprehensive studies identifying dynamic responses to pharmacologic and psychological/placebo effects underlying binge drinking are lacking. We investigated transcriptome-wide response to binge, medium, and placebo alcohol consumption by 17 healthy heavy social drinkers enrolled in a controlled, in-house, longitudinal study of up to 12 days. Using RNA-seq, we identified 251 and 13 differentially expressed genes (DEGs) in response to binge drinking and placebo, respectively. Eleven protein-coding DEGs had very large effect sizes in response to binge drinking (Cohen’s d > 1). Furthermore, binge dose significantly impacted the Cytokine-cytokine receptor interaction pathway (KEGG: hsa04060) across all experimental sequences. Placebo also impacted hsa04060, but only when administered following regular alcohol drinking sessions. Similarly, medium-dose and placebo commonly impacted KEGG pathways of Systemic lupus erythematosus, Neutrophil extracellular trap formation, and Alcoholism based on the sequence of drinking sessions. These findings together indicate the “dose-extending effects” of placebo at a molecular level. Furthermore, besides supporting alcohol dose-specific molecular changes, results suggest that the placebo effects may induce molecular responses within the same pathways regulated by alcohol.

Transcriptomic Changes and Regulatory Networks Associated with Resistance to Mastitis in Xinjiang Brown Cattle.

Xinjiang brown cattle are highly resistant to disease and tolerant of roughage feeding. The identification of genes regulating mastitis resistance in Xinjiang brown cattle is a novel means of genetic improvement. In this study, the blood levels of IL-1β, IL-6, IL-10, TNF-α, and TGF-β in Xinjiang brown cattle with high and low somatic cell counts (SCCs) were investigated, showing that cytokine levels were higher in cattle with high SCCs. The peripheral blood transcriptomic profiles of healthy and mastitis-affected cattle were constructed by RNA-seq. Differential expression analysis identified 1632 differentially expressed mRNAs (DE-mRNAs), 1757 differentially expressed lncRNAs (DE-lncRNAs), and 23 differentially expressed circRNAs (DE-circRNAs), which were found to be enriched in key pathways such as PI3K/Akt, focal adhesion, and ECM-receptor interactions. Finally, ceRNA interaction networks were constructed using the differentially expressed genes and ceRNAs. It was found that keynote genes or mRNAs were also enriched in pathways such as PI3K-Akt, cholinergic synapses, cell adhesion molecules, ion binding, cytokine receptor activity, and peptide receptor activity, suggesting that the key genes and ncRNAs in the network may play an important role in the regulation of bovine mastitis.

A data browsing application for accessing gene and module-level blood transcriptome profiles of healthy pregnant women from high- and low-resource settings.

Transcriptome profiling data, generated via RNA sequencing, are commonly deposited in public repositories. However, these data may not be easily accessible or usable by many researchers. To enhance data reuse, we present well-annotated, partially analyzed data via a user-friendly web application. This project involved transcriptome profiling of blood samples from 15 healthy pregnant women in a low-resource setting, taken at 6 consecutive time points beginning from the first trimester. Additional blood transcriptome profiles were retrieved from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) public repository, representing a cohort of healthy pregnant women from a high-resource setting. We analyzed these datasets using the fixed BloodGen3 module repertoire. We deployed a web application, accessible at https://thejacksonlaboratory.shinyapps.io/BloodGen3_Pregnancy/which displays the module-level analysis results from both original and public pregnancy blood transcriptome datasets. Users can create custom fingerprint grid and heatmap representations via various navigation options, useful for reports and manuscript preparation. The web application serves as a standalone resource for exploring blood transcript abundance changes during pregnancy. Alternatively, users can integrate it with similar applications developed for earlier publications to analyze transcript abundance changes of a given BloodGen3 signature across a range of disease cohorts. Database URL: https://thejacksonlaboratory.shinyapps.io/BloodGen3_Pregnancy/.

Unveiling biomarkers and therapeutic targets in IgA nephropathy through large-scale blood transcriptome analysis

IntroductionIgA nephropathy (IgAN) is the most prevalent form of glomerulonephritis. Unfortunately, molecular biomarkers for IgAN derived from omics studies are still lacking. This research aims to identify critical genes associated with IgAN through large-scale blood transcriptome analysis. MethodsWe constructed novel blood transcriptome profiles from peripheral blood mononuclear cells (PBMCs) of 53 Chinese IgAN patients and 28 healthy individuals. Our analysis included GO, KEGG, and GSEA for biological pathways. We analyzed immune cell profiles with CIBERSORT and constructed PPI networks with STRING, visualized in Cytoscape. Key differentially expressed genes (DEGs) were identified using CytoHubba and MCODE. We assessed the correlation between gene expressions and clinical data to evaluate clinical significance and identified hub genes through machine learning, validated with an open-access dataset. Potential drugs were explored using the CMap database. ResultsWe identified 333 DEGs between IgAN patients and healthy controls, mainly related to immune response and inflammation. Key pathways included NK cell mediated cytotoxicity, complement and coagulation cascades, antigen processing, and B cell receptor signaling. Cytoscape revealed 16 clinically significant genes (including KIR2DL1, KIR2DL3, VISIG4, C1QB, and C1QC, associated with sub-phenotype and prognosis). Machine learning identified two hub genes (KLRC1 and C1QB) for a diagnostic model of IgAN with 0.92 accuracy, validated at 1.00 against the GSE125818 dataset. Sirolimus, calcifediol, and efaproxiral were suggested as potential therapeutic agents. ConclusionKey DEGs, particularly VISIG4, KLRC1, and C1QB, emerge as potential specific markers for IgAN, paving the way for future targeted personalized treatment options.

Brain and blood transcriptome profiles delineate common genetic pathways across suicidal ideation and suicide

Human genetic studies indicate that suicidal ideation and behavior are both heritable. Most studies have examined associations between aberrant gene expression and suicide behavior, but behavior risk is linked to the severity of suicidal ideation. Through a gene network approach, this study investigates how gene co-expression patterns are associated with suicidal ideation and severity using RNA-seq data in peripheral blood from 46 live participants with elevated suicidal ideation and 46 with no ideation. Associations with the presence of suicidal ideation were found within 18 co-expressed modules (p < 0.05), as well as in 3 co-expressed modules associated with suicidal ideation severity (p < 0.05, not explained by severity of depression). Suicidal ideation presence and severity-related gene modules with enrichment of genes involved in defense against microbial infection, inflammation, and adaptive immune response were identified and investigated using RNA-seq data from postmortem brain that revealed gene expression differences with moderate effect sizes in suicide decedents vs. non-suicides in white matter, but not gray matter. Findings support a role of brain and peripheral blood inflammation in suicide risk, showing that suicidal ideation presence and severity are associated with an inflammatory signature detectable in blood and brain, indicating a biological continuity between ideation and suicidal behavior that may underlie a common heritability.

Peripheral blood TCR clonotype diversity as an age-associated marker of breast cancer progression.

Immune escape is a prerequisite for tumor growth. We previously described a decline in intratumor activated cytotoxic T cells and T cell receptor (TCR) clonotype diversity in invasive breast carcinomas compared to ductal carcinoma in situ (DCIS), implying a central role of decreasing T cell responses in tumor progression. To determine potential associations between peripheral immunity and breast tumor progression, here, we assessed the peripheral blood TCR clonotype of 485 breast cancer patients diagnosed with either DCIS or de novo stage IV disease at younger (<45) or older (≥45) age. TCR clonotype diversity was significantly lower in older compared to younger breast cancer patients regardless of tumor stage at diagnosis. In the younger age group, TCR-α clonotype diversity was lower in patients diagnosed with de novo stage IV breast cancer compared to those diagnosed with DCIS. In the older age group, DCIS patients with higher TCR-α clonotype diversity were more likely to have a recurrence compared to those with lower diversity. Whole blood transcriptome profiles were distinct depending on the TCR-α Chao1 diversity score. There were more CD8+ T cells and a more active immune environment in DCIS tumors of young patients with higher peripheral blood TCR-α Chao1 diversity than in those with lower diversity. These results provide insights into the role that host immunity plays in breast cancer development across different age groups.

Transcriptomic Profiling to Understand Inhibitor Development in Previously Untreated Patients with Severe Hemophilia a

Background: When starting treatment with factor VIII (FVIII) concentrate in individuals with severe hemophilia A, minimizing the risk of FVIII inhibitor development is an important concern for clinicians, patients and their families. Despite increased understanding of some of the genetic and environmental risk factors for inhibitor formation from epidemiological studies, identification of previously untreated patients (PUPs) at risk of developing inhibitors remains a challenge. Prediction of inhibitor development may help optimize care in PUPs with hemophilia A. RNA sequencing (RNA-Seq) with next-generation sequencing (NGS) could be used to investigate the underlying mechanisms of inhibitor development. Aims: Toevaluate peripheral blood transcriptomic profiles prior to and during early FVIII treatment in severe hemophilia A patients who did or did not develop inhibitors to simoctocog alfain the prospective NuProtect study. Methods: The NuProtect study (NCT01712438; EudraCT 2012-002554-23) was a multicenter, multinational, open-label, non-controlled, phase III study that enrolled male PUPs with severe hemophilia A (FVIII:C &amp;lt;1%) of any age and ethnicity. Patients received simoctocog alfa for prophylaxis or on-demand treatment, as well as for surgical prophylaxis. RNA-Seq was performed on blood samples collected from baseline and every 3-4 exposure days (ED) up to 20 EDs or until inhibitor development to assess messenger RNA (mRNA) expression profiles. Bioinformatics analyses were performed for the following timepoints: baseline, early treatment and a later timepoint on treatment. Principal component analysis (PCA) was performed to identify differences in global mRNA expression profiles between inhibitor and non-inhibitor patients. Gene ontology (GO) analyses were performed to detect differences in GO clusters between inhibitor and non-inhibitor patients. Results: Within this first analysis of the full dataset, transcriptomic profiles from 78 of 108 severe hemophilia A PUPs were analyzed (inhibitors n=22, non-inhibitors n=56). Median (range) age at ED1 was 13 (0.5-146) months; 44.9% of patients had the intron 22 inversion F8 gene mutation. Although the PCA indicated no strong global signal for differential expression profiles between non-inhibitor and inhibitor patients, GO analyses demonstrated differences between these patient groups. Inhibitor patients demonstrated increased gene expression of metabolic processes (GO:0008152) and cellular processes (GO:0009987) at baseline. Upregulation of immune system processes (GO:0002376) was seen in inhibitor patients at the early timepoint compared with non-inhibitor patients. Expression of ribosomal proteins, including RPL17 and RPS8 were significantly upregulated at baseline in inhibitor patients (p&amp;lt;0.05). Inhibitor patients further demonstrated upregulation of proteins involved in adaptive immune responses: IGHV1-69-2 at all timepoints (p&amp;lt;0.01) and IGHV2-70D at baseline and the early timepoint (p&amp;lt;0.01) compared with non-inhibitor patients. Upregulation of the B-cell related factors DPP4 at baseline and the early timepoint (p&amp;lt;0.05) and CD20 at the late timepoint (p&amp;lt;0.05) was observed in inhibitor patients compared with non-inhibitor patients. Conclusion: Differential transcriptomic profiles were seen in severe hemophilia A patients who developed inhibitors compared with those who do not, even before commencing FVIII treatment. Inhibitor patients demonstrated alterations in ribosomal protein expression that could disrupt protein synthesis efficiency, protein folding and quality control processes, and trigger cellular stress responses. Inhibitor patients also showed an upregulation of B-cell mediated factors involved in adaptive immune mechanisms. Additional analyses are ongoing to evaluate dynamic changes in gene expression during commencement of FVIII replacement to further identify patients at risk of inhibitor development.

OR21-01 Pre-treatment Blood Transcriptome Predicts First-year Growth And IGF-I Response To Somapacitan Treatment In Children With GH Deficiency

Abstract Disclosure: T. Garner: Grant Recipient; Self; Novo Nordisk. P.E. Clayton: Grant Recipient; Self; Novo Nordisk. M. Hojby: Employee; Self; Novo Nordisk. Stock Owner; Self; Novo Nordisk. P. Murray: Grant Recipient; Self; Novo Nordisk. A. Stevens: Grant Recipient; Self; Novo Nordisk. Background: Growth hormone (GH) replacement therapy often requires daily subcutaneous injections that can be burdensome for patients and their caregivers. Somapacitan is a long-acting, once-weekly GH derivative in development for treating GH deficiency (GHD) in children. Somapacitan reduces treatment burden and shows a similar efficacy and safety profile as daily GH in children with GHD. Here, we investigate the prediction of first-year growth and insulin-like growth factor-I (IGF-I) response based on baseline blood transcriptome in children with GHD treated with somapacitan or daily GH. Methods: 200 treatment-naïve prepubertal children with GHD were enrolled into REAL4, a randomised, multinational, open-labelled, and active-controlled phase 3 trial. 128 consented to a baseline blood transcriptome profile. Children were treated with once-weekly somapacitan (n=81) or daily GH (n=47) for 52 weeks and categorised based on treatment response: the upper quartile of height velocity (HV; cm/year) was defined as good responders, and the lower quartile as poor responders. We split the somapacitan group into training (70%) and testing (30%) sets for prediction validation of HV and the GH response marker: ΔIGF-I standard deviation score (SDS). Gene expression was assessed between the target quartile and the remaining quartiles for both HV and ΔIGF-I SDS to identify the top 100 differentially expressed genes by adjusted p-value. Classes were balanced using a synthetic minority oversampling technique and Boruta, a feature selection algorithm, was used to refine gene lists. We performed random forest and calculated “out of box” (OOB) area under the curve (AUC) and OOB error rate (ER), measures of predictive accuracy and robustness, respectively. Results: HV prediction from the transcriptome was excellent for both treatments (AUC range: 0.95-0.99). It was more robust for identifying good responders (ER: 7.0-7.5%) than poor responders (ER: 13.2-17.5%). Genes previously identified as predictive of growth response for daily GH (Stevens et al., 2021. The Pharmacogenomics J., 21:594-607) were demonstrated to have high predictive value for once-weekly somapacitan and daily GH treatment in this study (AUC range: 0.84-0.97, ER &amp;lt;22%). Using the somapacitan group for validation, HV prediction (AUC range: 0.78-0.81) was stronger than ΔIGF-I SDS prediction (AUC range: 0.63-0.72). Conclusions: We demonstrate pre-treatment blood transcriptome predicts first-year growth response for somapacitan. This represents an independent validation of earlier observations and shows that genes predictive of growth response for daily GH treatment in children with GHD are also predictive for once-weekly somapacitan. Further, we demonstrate that the pre-treatment blood transcriptome predicts growth response better than it predicts IGF-I SDS response. Presentation: Saturday, June 17, 2023

Genomic Variation, Population History, and Long-Term Genetic Adaptation to High Altitudes in Tibetan Partridge (Perdix hodgsoniae).

Species residing across elevational gradients display adaptations in response to environmental changes such as oxygen availability, ultraviolet radiation, and temperature. Here, we study genomic variation, gene expression, and long-term adaptation in Tibetan Partridge (Perdix hodgsoniae) populations residing across the elevational gradient of the Tibetan Plateau. We generated a high-quality draft genome and used it to carry out downstream population genomic and transcriptomic analysis. The P. hodgsoniae populations residing across various elevations were genetically distinct, and their phylogenetic clustering was consistent with their geographic distribution. We identified possible evidence of gene flow between populations residing in <3,000 and >4,200 m elevation that is consistent with known habitat expansion of high-altitude populations of P. hodgsoniae to a lower elevation. We identified a 60 kb haplotype encompassing the Estrogen Receptor 1 (ESR1) gene, showing strong genetic divergence between populations of P. hodgsoniae. We identified six single nucleotide polymorphisms within the ESR1 gene fixed for derived alleles in high-altitude populations that are strongly conserved across vertebrates. We also compared blood transcriptome profiles and identified differentially expressed genes (such as GAPDH, LDHA, and ALDOC) that correlated with differences in altitude among populations of P. hodgsoniae. These candidate genes from population genomics and transcriptomics analysis were enriched for neutrophil degranulation and glycolysis pathways, which are known to respond to hypoxia and hence may contribute to long-term adaptation to high altitudes in P. hodgsoniae. Our results highlight Tibetan Partridges as a useful model to study molecular mechanisms underlying long-term adaptation to high altitudes.

Guselkumab Modulates Differentially Expressed Genes in Blood of Patients With Psoriatic Arthritis: Results from Two Phase 3, Randomized, Placebo-Controlled Trials.

To evaluate gene expression in blood of patients with psoriatic arthritis (PsA) versus healthy controls and identify changes associated with guselkumab treatment. Whole blood transcriptome profiling via paired-end RNA sequencing was conducted using samples from DISCOVER-1 and DISCOVER-2 at baseline (n=673) and at weeks 4 and 24 from a representative subgroup that received placebo or guselkumab (n=227 [longitudinal PsA cohort]). Baseline samples were compared with demographically matched healthy controls (n=21). Guselkumab-mediated changes in gene expression were assessed in participants from the longitudinal PsA cohort who did versus did not achieve at least 20% improvement in American College of Rheumatology response criteria (ACR20) or at least 75% improvement in Psoriasis Area and Severity Index (PASI75). Differential gene expression was analyzed using edgeR. At baseline, 355 upregulated and 314 downregulated genes (PsA-associated genes) were identified in patients with PsA versus healthy controls. Upregulated genes were related to neutrophil, mononuclear cell, and CD11b+ gene sets. No cell type-specific gene sets were identified among downregulated genes. Most PsA-associated genes were modulated by guselkumab treatment. At week 24, genes downregulated by guselkumab were enriched with neutrophil, monocyte, eosinophil, and macrophage gene sets; genes upregulated by guselkumab were enriched with B cell, T cell, and natural killer cell gene sets. Reductions in expression of upregulated PsA-associated gene sets were more pronounced in ACR20 and PASI75 responders than in nonresponders. These findings suggest a dysregulation of immune cell profiles in blood from patients in the baseline PsA cohort that approached levels in healthy controls after guselkumab treatment.

Comparative analysis of whole blood transcriptomics between European and local Caribbean pigs in response to feed restriction in a tropical climate

BackgroundFeed restriction occurs frequently during pig growth, either due to economic reasons or stressful environmental conditions. Local breeds are suggested to have better tolerance to periods of feed restriction. However, the mechanisms underlying the response to feed restriction in different breeds is largely unknown. The aims of the present study were (1) to compare the blood transcriptome profile in response to feed restriction and refeeding of two contrasted breeds, Large White (LW), which has been selected for high performance, and Creole (CR), which is adapted to tropical conditions, and (2) to investigate the effect of a moderate feed restriction and refeeding on whole blood transcriptome. Analysis of blood transcriptome allows to study the response to feed restriction and refeeding in a dynamic way. RNAseq was performed on blood samples of growing LW and CR pigs at two time points: after 3 weeks of feed restriction and after 3 weeks of refeeding. The data was compared with samples from control animals offered the same diet on an ad libitum basis throughout the whole experiment.ResultsIn terms of performance (body weight and feed efficiency), CR pigs were less impacted by feed restriction than LW. The transcriptional response to feed restriction and refeeding between CR and LW was contrasted both in terms of number of DEGs and enriched pathways. CR demonstrated a stronger transcriptional response to feed restriction whereas LW had a stronger response to refeeding. Differences in the transcriptional response to feed restriction between CR and LW were related to cell stress response (Aldosterone Signalling, Protein ubiquitination, Unfolded Protein Signalling) whereas after refeeding, differences were linked to thermogenesis, metabolic pathways and cell proliferation (p38 MAPK, ERK/MAPK pathway). In both breeds, transcriptional changes related to the immune response were found after restriction and refeeding.ConclusionsAltogether, the present study indicates that blood transcriptomics can be a useful tool to study differential genetic response to feed restriction in a dynamic way. The results indicate a differential response of blood gene expression to feed restriction and refeeding between breeds, affecting biological pathways that are in accordance with performance and thermoregulatory results.

Categorization of patients with systemic lupus erythematosus using disease activity, patient-reported outcomes, and transcriptomic signatures.

Patients with systemic lupus erythematosus (SLE) display symptoms that are not always related to disease activity and may distort clinical trial results. Recently, a clinical categorization based on the presence of type 1 (inflammatory manifestations) and/or type 2 (widespread pain, fatigue, depression) symptoms has been proposed in SLE. Our aim was to develop a type 2 score derived from the Short-Form health survey (SF-36) to categorize SLE patients and to compare immunological and transcriptomic profiles between groups. Seventeen items from the SF-36 were selected to build a type 2 score for 50 SLE patients (100 visits; LUPUCE cohort), and the SLEDAI was used to define type 1 symptoms. Patients were categorized into four groups: minimal (no symptoms), type 1, type 2, and mixed (both type 1 and type 2 symptoms). Clinical, immunological, and transcriptomic profiles were compared between the groups. Type 2 scores ranged from 0 to 31, with a cutoff value of 14 (75th percentile). The sample categorization was minimal in 39%, type 1 in 37%, and type 2 in 9%, and mixed in 15%. Type 2 patients were older than minimal patients and had a longer disease duration than type 1 and mixed patients. Immunological data and modular interferon signatures did not differ between the groups. Patients with SLE can be categorized into four clinical groups using the SLEDAI score and our SF-36-derived type 2 score. This categorization is non-redundant with immunological or transcriptomic profiles and could prove useful to stratify patients in clinical trials. Key Points • A score derived from selected items of the SF-36 can be used to identify SLE patients with type 2 symptoms according to the Duke University categorization. • Using the SLEDAI and this type 2 score, SLE patients can be categorized into four clinical groups. • This categorization is not related to immunological activity or blood transcriptome profiles (and not to the interferon signature in particular). • This categorization could be useful in the daily care of patients as well as in clinical trials, for upstream patient stratification or for the interpretation of results.