Blood RNA Samples Research Articles

Characterizing Non-T2 Asthma: Key Pathways and Molecular Implications Indicative of Attenuated Th2 Response.

Non-Type 2 (non-T2) asthma is characterized by a lack of allergic sensitization and normal to low total IgE levels. We aimed to explore molecular mechanisms and pathways differentiating non-T2 from T2-high pediatric asthma. We analyzed peripheral blood RNA samples from 11 non-T2 and 17 T2-high pediatric asthma patients using bulk RNA sequencing. Differentially expressed genes (DEGs) were identified, followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, and Protein-Protein Interaction (PPI) network construction. Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA) were employed to explore significance of these DEGs. We utilized independent public datasets GSE145505 to validate our findings. We investigated Th cytokine profiles in an independent cohort of pediatric patients with non-T2 asthma (n = 38) and T2-high asthma (n = 64). We demonstrated that the total serum IgE levels of children with non-T2 asthma (128.4 ± 159.5IU/mL) was significantly lower than that of those with T2-high asthma (405.8 ± 252.1IU/mL). Our analysis revealed 136 DEGs distinguishing non-T2 from T2-high asthma. IPA identified predicted inhibition of IgE-FcεRI signaling pathways in non-T2 asthma. Our DEG data showed the expression of IGHV4-39, IGLV1-40, IGLV1-47, IGLV1-44, IGHV1-69, IGLV6-57, IGLV3-19, IGLV3-1, and IGLC7 were downregulated in our non-T2 asthma patient. The non-T2 group exhibited significantly higher concentrations of IL-2, IFN-γ, IL-6, and IL-17A compared to the T2-high group. Our integrated analysis differentiated non-T2 from T2-high asthma by revealing downregulation of specific immunoglobulin genes influencing FcεRI signaling, elevated Th1 cytokines and Th17 cytokines might affect IgE associated sensitization and alter Th2 allergic response.

B cell immune repertoire sequencing in tobacco cigarette smoking, vaping, and chronic obstructive pulmonary disease in the COPDGene cohort.

Cigarette smoking (CS) impairs B cell function and antibody production, increasing infection risk. The impact of e-cigarette use ('vaping') and combined CS and vaping ('dual-use') on B cell activity is unclear. To examine B cell receptor sequencing (BCR-seq) profiles associated with CS, vaping, dual-use, COPD-related outcomes, and demographic factors. BCR-seq was performed on blood RNA samples from 234 participants in the COPDGene study. We assessed multivariable associations of B cell function measures (immunoglobulin heavy chain (IGH) subclass expression and usage, class-switching, V-segment usage, and clonal expansion) with CS, vaping, dual-use, COPD severity, age, sex, and race. We adjusted for multiple comparisons using the Benjamini-Hochberg method, identifying significant associations at 5% FDR and suggestive associations at 10% FDR. Among 234 non-Hispanic white (NHW) and African American (AA) participants, CS and dual-use were significantly positively associated with increased secretory IgA production, with dual-use showing the strongest associations. Dual-use was positively associated with class switching and B cell clonal expansion, indicating increased B cell activation, with similar trends in those only smoking or only vaping. We observed significant associations between race and IgG antibody usage. AA participants had higher IgG subclass proportions and lower IgM usage compared to NHW participants. CS and vaping additively enhance B cell activation, most notably in dual-users. Self-reported race was strongly associated with IgG isotype usage. These findings highlight associations between B cell activation and antibody transcription, suggesting potential differences in immune and vaccine responses linked to CS, vaping, and race.

Machine learning-driven diagnosis of multiple sclerosis from whole blood transcriptomics

Multiple sclerosis (MS) is a neurological disorder characterized by immune dysregulation. It begins with a first clinical manifestation, a clinically isolated syndrome (CIS), which evolves to definite MS in case of further clinical and/or neuroradiological episodes. Here we evaluated the diagnostic value of transcriptional alterations in MS and CIS blood by machine learning (ML).Deep sequencing of more than 200 blood RNA samples comprising CIS, MS and healthy subjects, generated transcriptomes that were analyzed by the binary classification workflow to distinguish MS from healthy subjects and the Time-To-Event pipeline to predict CIS conversion to MS along time. To identify optimal classifiers, we performed algorithm benchmarking by nested cross-validation with the train set in both pipelines and then tested models generated with the train set on an independent dataset for final validation.The binary classification model identified a blood transcriptional signature classifying definite MS from healthy subjects with 97% accuracy, indicating that MS is associated with a clear predictive transcriptional signature in blood cells. When analyzing CIS data with ML survival models, prediction power of CIS conversion to MS was about 72% when using paraclinical data and 74.3% when using blood transcriptomes, indicating that blood-based classifiers obtained at the first clinical event can efficiently predict risk of developing MS.Coupling blood transcriptomics with ML approaches enables retrieval of predictive signatures of CIS conversion and MS state, thus introducing early non-invasive approaches to MS diagnosis.

Investigation of LncRNA PVT1 and MiR-21-5p Expression as Promising Novel Biomarkers for Autism Spectrum Disorder.

The characteristics of ncRNA in children with autism spectrum disorder (ASD) were observed to disclose a theoretical basis for further research on molecular markers for early warning of ASD. Children with ASD and normal control children were recruited to collect peripheral blood RNA samples. The concentration of PVT1 and miR-21-5p was quantitatively analyzed by qRT-PCR. Pearson correlation coefficient method was used to evaluate the link between PVT1 level and miR-21-5p level of the children. Receiver operating characteristic (ROC) curves were applied to reckon the predictive value of PVT1, miR-21-5p, and their combination in ASD. The interconnection of PVT1 with miR-21-5p was represented by luciferase reporter assay. The targeted genes of miR-21-5p were predicted. The enrichment and protein interaction analysis of these genes was carried out to find the important core genes and analyze their value in ASD. In the disease group, the level of PVT1 was downregulated, while the content of miR-21-5p was upregulated. The expression level of serum miR-21-5p was negatively correlated with the level of PVT1. Luciferase reporter gene assay documented that PVT1 directly targeted miR-21-5p. ROC curve showed that PVT1, miR-21-5p, and their combination showed clinical value for disease diagnosis. The functional enrichment analysis showed that the targets of miR-21-5p participated in ASD by regulating related functions and pathways. Reduced expression of PVT1 and raised miR-21-5p were good diagnostic markers for ASD, which would provide a basis for effective prevention, early diagnosis, and early intervention of ASD.

Longitudinal whole blood transcriptomic analysis characterizes neutrophil activation and interferon signaling in moderate and severe COVID-19

A maladaptive inflammatory response has been implicated in the pathogenesis of severe COVID-19. This study aimed to characterize the temporal dynamics of this response and investigate whether severe disease is associated with distinct gene expression patterns. We performed microarray analysis of serial whole blood RNA samples from 17 patients with severe COVID-19, 15 patients with moderate disease and 11 healthy controls. All study subjects were unvaccinated. We assessed whole blood gene expression patterns by differential gene expression analysis, gene set enrichment, two clustering methods and estimated relative leukocyte abundance using CIBERSORT. Neutrophils, platelets, cytokine signaling, and the coagulation system were activated in COVID-19, and this broad immune activation was more pronounced in severe vs. moderate disease. We observed two different trajectories of neutrophil-associated genes, indicating the emergence of a more immature neutrophil phenotype over time. Interferon-associated genes were strongly enriched in early COVID-19 before falling markedly, with modest severity-associated differences in trajectory. In conclusion, COVID-19 necessitating hospitalization is associated with a broad inflammatory response, which is more pronounced in severe disease. Our data suggest a progressively more immature circulating neutrophil phenotype over time. Interferon signaling is enriched in COVID-19 but does not seem to drive severe disease.

Identification of a Novel Canonical Splice Site Variant TSC2 c.2967-1G>T That is Not Associated With Tuberous Sclerosis Pathogenesis

Tuberous sclerosis, also known as tuberous sclerosis complex (TSC), is an autosomal dominant defect characterized by hamartomas in multiple organ systems. Inactivating variants cause this defect in either the TSC1 gene or the TSC2 gene, leading to hamartin or tuberin protein dysfunction, thus resulting in TSC. The diagnostic criteria for TSC suggest that it can be diagnosed by identifying a heterozygous pathogenic variant of TSC1 or TSC2, even in the absence of clinical signs. In a 4-year-old girl, we identified a splicing variant (NM_000548.4: c.2967-1G>T) that she inherited from her father. Neither the girl (patient) nor her father showed typical features of TSC. This variant is located in a NAGNAG acceptor, which can produce mRNA isoforms that differ by a three-nucleotide indel. Reverse transcription polymerase chain reaction analysis of the patient and both parents’ blood RNA samples suggested two different splicing patterns, and these two splicing patterns differed in the presence or absence of the first codon of exon 27, thus providing two splicing products designated as isoforms A and B, respectively. Furthermore, the proportions of these two patterns varied between the patient and either parent. A minigene assay further confirmed that the c.2967-1G>T variant led to the absence of isoform A (including the first codon of exon 27). The finding of our study demonstrates this variant, c.2967-1G>T, disrupts the balance of an alternative splice event which involves the use of two tandem alternatives acceptors and is not associated with typical symptoms of tuberous sclerosis. Our finding is of importance for genetic counseling and suggests that we need to be vigilant to avoid misdiagnosis when we encounter such a site.

Transcriptomic Analysis Reveals the Messenger RNAs Responsible for the Progression of Alcoholic Cirrhosis.

Alcohol‐associated liver disease is the leading cause of chronic liver disease. We hypothesized that the expression of specific coding genes is critical for the progression of alcoholic cirrhosis (AC) from compensated to decompensated states. For the discovery phase, we performed RNA sequencing analysis of 16 peripheral blood RNA samples, 4 healthy controls (HCs) and 12 patients with AC. The DEGs from the discovery cohort were validated by quantitative polymerase chain reaction in a separate cohort of 17 HCs and 48 patients with AC (17 Child‐Pugh A, 16 Child‐Pugh B, and 15 Child‐Pugh C). We observed that the numbers of differentially expressed messenger RNAs (mRNAs) were more pronounced with worsening disease severity. Pathway analysis for differentially expressed genes for patients with Child‐Pugh A demonstrated genes involved innate immune responses; those in Child‐Pugh B belonged to genes related to oxidation and alternative splicing; those in Child‐Pugh C related to methylation, acetylation, and alternative splicing. We found significant differences in the expression of heme oxygenase 1 (HMOX1) and ribonucleoprotein, PTB binding 1 (RAVER1) in peripheral blood of those who died during the follow‐up when compared to those who survived. Conclusion: Unique mRNAs that may implicate disease progression in patients with AC were identified by using a transcriptomic approach. Future studies to confirm our results are needed, and comprehensive mechanistic studies on the implications of these genes in AC pathogenesis and progression should be further explored.

Isolation of RNA from Acute Ischemic Stroke Clots Retrieved by Mechanical Thrombectomy.

Mechanical thrombectomy (MT) for large vessel acute ischemic stroke (AIS) has enabled biologic analyses of resected clots. While clot histology has been well-studied, little is known about gene expression within the tissue, which could shed light on stroke pathophysiology. In this methodological study, we develop a pipeline for obtaining useful RNA from AIS clots. A total of 73 clot samples retrieved by MT were collected and stored in RNALater and in 10% phosphate-buffered formalin. RNA was extracted from all samples using a modified Chemagen magnetic bead extraction protocol on the PerkinElmer Chemagic 360. RNA was interrogated by UV–Vis absorption and electrophoretic quality control analysis. All samples with sufficient volume underwent traditional qPCR analysis and samples with sufficient RNA quality were subjected to next-generation RNA sequencing on the Illumina NovaSeq platform. Whole blood RNA samples from three patients were used as controls, and H&E-stained histological sections of the clots were used to assess clot cellular makeup. Isolated mRNA was eluted into a volume of 140 µL and had a concentration ranging from 0.01 ng/µL to 46 ng/µL. Most mRNA samples were partially degraded, with RNA integrity numbers ranging from 0 to 9.5. The majority of samples (71/73) underwent qPCR analysis, which showed linear relationships between the expression of three housekeeping genes (GAPDH, GPI, and HPRT1) across all samples. Of these, 48 samples were used for RNA sequencing, which had moderate quality based on MultiQC evaluation (on average, ~35 M reads were sequenced). Analysis of clot histology showed that more acellular samples yielded RNA of lower quantity and quality. We obtained useful mRNA from AIS clot samples stored in RNALater. qPCR analysis could be performed in almost all cases, while sequencing data could only be performed in approximately two-thirds of the samples. Acellular clots tended to have lower RNA quantity and quality.

Blood transcriptional biomarkers of acute viral infection for detection of pre-symptomatic SARS-CoV-2 infection: a nested, case-control diagnostic accuracy study

SummaryBackgroundWe hypothesised that host-response biomarkers of viral infections might contribute to early identification of individuals infected with SARS-CoV-2, which is critical to breaking the chains of transmission. We aimed to evaluate the diagnostic accuracy of existing candidate whole-blood transcriptomic signatures for viral infection to predict positivity of nasopharyngeal SARS-CoV-2 PCR testing.MethodsWe did a nested case-control diagnostic accuracy study among a prospective cohort of health-care workers (aged ≥18 years) at St Bartholomew's Hospital (London, UK) undergoing weekly blood and nasopharyngeal swab sampling for whole-blood RNA sequencing and SARS-CoV-2 PCR testing, when fit to attend work. We identified candidate blood transcriptomic signatures for viral infection through a systematic literature search. We searched MEDLINE for articles published between database inception and Oct 12, 2020, using comprehensive MeSH and keyword terms for “viral infection”, “transcriptome”, “biomarker”, and “blood”. We reconstructed signature scores in blood RNA sequencing data and evaluated their diagnostic accuracy for contemporaneous SARS-CoV-2 infection, compared with the gold standard of SARS-CoV-2 PCR testing, by quantifying the area under the receiver operating characteristic curve (AUROC), sensitivities, and specificities at a standardised Z score of at least 2 based on the distribution of signature scores in test-negative controls. We used pairwise DeLong tests compared with the most discriminating signature to identify the subset of best performing biomarkers. We evaluated associations between signature expression, viral load (using PCR cycle thresholds), and symptom status visually and using Spearman rank correlation. The primary outcome was the AUROC for discriminating between samples from participants who tested negative throughout the study (test-negative controls) and samples from participants with PCR-confirmed SARS-CoV-2 infection (test-positive participants) during their first week of PCR positivity.FindingsWe identified 20 candidate blood transcriptomic signatures of viral infection from 18 studies and evaluated their accuracy among 169 blood RNA samples from 96 participants over 24 weeks. Participants were recruited between March 23 and March 31, 2020. 114 samples were from 41 participants with SARS-CoV-2 infection, and 55 samples were from 55 test-negative controls. The median age of participants was 36 years (IQR 27–47) and 69 (72%) of 96 were women. Signatures had little overlap of component genes, but were mostly correlated as components of type I interferon responses. A single blood transcript for IFI27 provided the highest accuracy for discriminating between test-negative controls and test-positive individuals at the time of their first positive SARS-CoV-2 PCR result, with AUROC of 0·95 (95% CI 0·91–0·99), sensitivity 0·84 (0·70–0·93), and specificity 0·95 (0·85–0·98) at a predefined threshold (Z score >2). The transcript performed equally well in individuals with and without symptoms. Three other candidate signatures (including two to 48 transcripts) had statistically equivalent discrimination to IFI27 (AUROCs 0·91–0·95).InterpretationOur findings support further urgent evaluation and development of blood IFI27 transcripts as a biomarker for early phase SARS-CoV-2 infection for screening individuals at high risk of infection, such as contacts of index cases, to facilitate early case isolation and early use of antiviral treatments as they emerge.FundingBarts Charity, Wellcome Trust, and National Institute of Health Research.

Integrated analysis of microRNA and mRNA expression profiles in homozygous familial hypercholesterolemia patients and validation of atherosclerosis associated critical regulatory network

Homozygous familial hypercholesterolemia (HoFH) is a rare, life-threatening genetic disorder characterized by an extremely elevated serum level of low-density lipoprotein cholesterol (LDL-C) and accelerated premature atherosclerotic cardiovascular diseases (ASCVD). However, the detailed mechanism of how the pathogenic mutations of HoFH trigger the acceleration of ASCVD is not well understood. Therefore, we performed high-throughput RNA and small RNA sequencing on the peripheral blood RNA samples of six HoFH patients and three healthy controls. The gene and miRNA expression differences were analyzed, and seven miRNAs and six corresponding genes were screened out through regulatory network analysis. Validation through quantitative PCR of genes and miRNAs from 52 HoFH patients and 20 healthy controls revealed that the expression levels of hsa-miR-486-3p, hsa-miR-941, and BIRC5 were significantly upregulated in HoFH, while ID1, PLA2G4C, and CACNA2D2 were downregulated. Spearman correlation analysis found that the levels of ID1, hsa-miR-941, and hsa-miR-486-3p were significantly correlated with additional ASCVD risk factors in HoFH patients. This study represents the first integrated analysis of transcriptome and miRNA expression profiles in patients with HoFH, a rare disease, and as a result, six differentially expressed miRNAs/genes that may be related to atherosclerosis in HoFH are reported. The miRNA–mRNA regulatory network may be the critical regulation mechanism by which ASCVD is accelerated in HoFH.

Identification of Potential Biomarkers and Immune Features of Sepsis Using Bioinformatics Analysis.

Sepsis remains a major global concern and is associated with high mortality and morbidity despite improvements in its management. Markers currently in use have shortcomings such as a lack of specificity and failures in the early detection of sepsis. In this study, we aimed to identify key genes involved in the molecular mechanisms of sepsis and search for potential new biomarkers and treatment targets for sepsis using bioinformatics analyses. Three datasets (GSE95233, GSE57065, and GSE28750) associated with sepsis were downloaded from the public functional genomics data repository Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified using R packages (Affy and limma). Functional enrichment of the DEGs was analyzed with the DAVID database. Protein-protein interaction networks were derived using the STRING database and visualized using Cytoscape software. Potential biomarker genes were analyzed using receiver operating characteristic (ROC) curves in the R package (pROC). The three datasets included 156 whole blood RNA samples from 89 sepsis patients and 67 healthy controls. Between the two groups, 568 DEGs were identified, among which 315 were upregulated and 253 were downregulated in the septic group. These genes were enriched for pathways mainly involved in the innate immune response, T-cell biology, antigen presentation, and natural killer cell function. ROC analyses identified nine genes—LRG1, ELANE, TP53, LCK, TBX21, ZAP70, CD247, ITK, and FYN—as potential new biomarkers for sepsis. Real-time PCR confirmed that the expression of seven of these genes was in accordance with the microarray results. This study revealed imbalanced immune responses at the transcriptomic level during early sepsis and identified nine genes as potential biomarkers for sepsis.

Abstract 4492: Characterization of the T-Cell receptor repertoire in patients with acute myeloid leukemia treated with 5-Azacytidine plus chemotherapy

Abstract Acute Myeloid Leukemia (AML) is a hematological malignancy with a 5 year overall survival of less than 30%. DNA hypomethylating agents such as 5-Azacytidine (5-Aza) have been increasingly used in AML therapy. The effect of hypomethylating agents on T-cell driven anti-leukemia responses remains unclear. For anti-leukemia responses, T-cells must express a T-cell receptor (TCR) with specificity for cancer antigens. TCR recombination, the rearrangement of V, D (beta only) and J segments across the TCR alpha and beta loci into a mature TCR locus, shapes the antigen specificity of TCRs. DNA methylation across the TCR loci may limit the rearrangement of particular V, D, J segments and impact TCR repertoire composition. Whether 5-Aza can alter TCR loci methylation patterns, increase TCR diversity and enhance T-cell driven anti-leukemia responses is unknown. In a cohort of 23 patient with AML, we performed TCR-seq on pre- (diagnostic) and post-therapy (day 5 post 5-Aza) peripheral blood RNA samples obtained from 13 responders and 10 non-responders. Illumina compatible libraries were generated from patient samples using a 5'RACE like approach and sequenced on the MiSeq platform, generating 300x2bp reads. Reads were processed and analyzed using MiXCR and VDJTools, respectively. GraphPad Prism 8 (Two-sided T test) was used for statistical comparisons, P values < 0.05 were considered significant after adjusting for multiple comparisons using the Bonferroni-Dunn method. We obtained an average of 1,146,043 (SD± 767,216) reads and identified an average of 15,732 (SD ± 17,388) clones per sample. We compared pre- and post-therapy TCR diversity among both outcome groups using the Shannon diversity index. TCR diversity did not significantly change following 5-Aza treatment (4827 vs 6159, P= 0.55). Also, TCR diversity was not significantly different between outcome groups pre- and post-therapy. We designated clones as minor (< 10 reads) or major (> 10 reads). We compared pre- and post-therapy minor clone TRBV exon patterns and discovered a 2.2 fold increase in unique clones containing TRBV16 among responders post therapy (P = 0.017). We also observed a 2.5 fold increase in unique clones containing TRBV7-4 in non-responders post therapy (P = 0.034). There were no significant exon pattern changes in non-stratified analysis. When pre-therapy minor clone exon patterns were compared between outcome groups, a higher frequency of unique clones containing TRBV12-2 in responders versus non-responders was observed (2.8 fold, P < 0.001). In addition, we observed a higher frequency of major clones containing TRBV12-5 among responders post therapy (2.4 fold, P = 0.0558). In the pre-therapy samples, there was a higher frequency of clones containing TRBV5-4 among responders compared to non-responders (2.7 fold, P =0.045). In conclusion, changes in TCR repertoire features such as the utilization of specific V exons may associate with response to 5-Azacytidine therapy. Citation Format: John Beckford, Noreen Fulton, Toyosi Odenike, Wendy Stock, Houda Alachkar. Characterization of the T-Cell receptor repertoire in patients with acute myeloid leukemia treated with 5-Azacytidine plus chemotherapy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4492.

Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance

PurposeDiagnosis of genetic disorders is hampered by large numbers of variants of uncertain significance (VUSs) identified through next-generation sequencing. Many such variants may disrupt normal RNA splicing. We examined effects on splicing of a large cohort of clinically identified variants and compared performance of bioinformatic splicing prediction tools commonly used in diagnostic laboratories. MethodsTwo hundred fifty-seven variants (coding and noncoding) were referred for analysis across three laboratories. Blood RNA samples underwent targeted reverse transcription polymerase chain reaction (RT-PCR) analysis with Sanger sequencing of PCR products and agarose gel electrophoresis. Seventeen samples also underwent transcriptome-wide RNA sequencing with targeted splicing analysis based on Sashimi plot visualization. Bioinformatic splicing predictions were obtained using Alamut, HSF 3.1, and SpliceAI software. ResultsEighty-five variants (33%) were associated with abnormal splicing. The most frequent abnormality was upstream exon skipping (39/85 variants), which was most often associated with splice donor region variants. SpliceAI had greatest accuracy in predicting splicing abnormalities (0.91) and outperformed other tools in sensitivity and specificity. ConclusionSplicing analysis of blood RNA identifies diagnostically important splicing abnormalities and clarifies functional effects of a significant proportion of VUSs. Bioinformatic predictions are improving but still make significant errors. RNA analysis should therefore be routinely considered in genetic disease diagnostics.

A retrospective case control study identifies peripheral blood mononuclear cell albumin RNA expression as a biomarker for non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) improves after bariatric surgery. The aim of this study was to determine whether peripheral blood mononuclear cell albumin gene expression was related to NAFLD and whether albumin (ALB) and alpha fetoprotein (AFP) expression could be detected in whole blood and visceral adipose tissue. Using a retrospective case control study design, RNA isolated from peripheral blood mononuclear cells from patients prior to undergoing bariatric surgery was used for pooled microarray analysis. Quantitative polymerase chain reaction (QPCR) was used to analyze whole blood and visceral adipose tissue. Liver histology was obtained via intra-operative biopsy and clinical data extracted from the electronic health record. The albumin (ALB) gene was the second most up-regulated found in microarray analysis of peripheral blood mononuclear cell RNA from patients with hepatic lobular inflammation versus normal liver histology. Transcript levels of ALB were significantly different across those with normal (n = 50), steatosis (n = 50), lobular inflammation (n = 50), and peri-sinusoidal fibrosis (n = 50) liver histologies, with lobular inflammation 3.9 times higher than those with normal histology (p < 0.017). Albumin expression levels decreased in 11/13 patients in paired samples obtained prior to and at 1year after Roux-en-Y gastric bypass surgery. ALB expression could be detected in 23 visceral adipose tissue samples obtained intra-operatively and in 18/19 available paired whole blood samples. No significant correlation was found between ALB expression in visceral adipose tissue and whole blood RNA samples. Alpha fetoprotein expression as a marker of early hepatocytic differentiation was detected in 17/17 available VAT RNA samples, but in only 2/17 whole blood RNA samples. Albumin RNA expression from blood cells may serve as a biomarker of NAFLD. Albumin and alpha fetoprotein appear to be ubiquitously expressed in visceral adipose tissue in patients with extreme obesity.

Protocol for the first large-scale emergency care-based longitudinal cohort study of recovery after sexual assault: the Women’s Health Study

IntroductionWorldwide, an estimated 10%–27% of women are sexually assaulted during their lifetime. Despite the enormity of sexual assault as a public health problem, to our knowledge, no large-scale prospective studies...

Integrated genome-wide methylation and expression analyses reveal functional predictors of response to antidepressants

Major depressive disorder (MDD) is primarily treated with antidepressants, yet many patients fail to respond adequately, and identifying antidepressant response biomarkers is thus of clinical significance. Some hypothesis-driven investigations of epigenetic markers for treatment response have been previously made, but genome-wide approaches remain unexplored. Healthy participants (n = 112) and MDD patients (n = 211) between 18–60 years old were recruited for an 8-week trial of escitalopram treatment. Responders and non-responders were identified using differential Montgomery-Åsberg Depression Rating Scale scores before and after treatment. Genome-wide DNA methylation and gene expression analyses were assessed using the Infinium MethylationEPIC Beadchip and HumanHT-12 v4 Expression Beadchip, respectively, on pre-treatment peripheral blood DNA and RNA samples. Differentially methylated positions (DMPs) located in regions of differentially expressed genes between responders (n = 82) and non-responders (n = 95) were identified, and technically validated using a targeted sequencing approach. Three DMPs located in the genes CHN2 (cg23687322, p = 0.00043 and cg06926818, p = 0.0014) and JAK2 (cg08339825, p = 0.00021) were the most significantly associated with mRNA expression changes and subsequently validated. Replication was then conducted with non-responders (n = 76) and responders (n = 71) in an external cohort that underwent a similar antidepressant trial. One CHN2 site (cg06926818; p = 0.03) was successfully replicated. Our findings indicate that differential methylation at CpG sites upstream of the CHN2 and JAK2 TSS regions are possible peripheral predictors of antidepressant treatment response. Future studies can provide further insight on robustness of our candidate biomarkers, and greater characterization of functional components.

BMI-intracerebral hemorrhage paradox: The role of inflammatory cytokines and microrna profile

Obesity, classified as BMI>30.0, is a known risk factor for cardiovascular disease. Obesity is associated with a chronic inflammatory state due to increased adiposity. In this study, we compare circulating miRNA profile and expression pattern with inflammatory cytokines in patients with and without obesity following acute intracerebral hemorrhage (ICH). After informed consent, patients with acute spontaneous ICH (n=16) were consented and blood samples collected within 48 hrs of admission. Samples were grouped according to BMI-Low (<30) v BMI-High (>30). Total RNA containing small RNA were isolated from Paxgene Blood RNA samples and used to profile 2,515 known miRNA using uParaflo Microfluidic Biochip. Gene expression was carried out using RNAseq and EgdeR. Gene set enrichment analysis (GSEA) for KEGG pathways and Gene Ontology (GO) were done using GAGE and miRWalk 2.0. In plasma, we found 23 highly expressed miRNA, 11 of which were downregulated in BMI-H. GSEA for KEGG pathways and GO showed enrichment for protein translation and ribosome biogenesis for upregulated genes in BMI-H. Conversely, GSEA of downregulated genes in BMI-H favored inflammation and recruitment of cytokines and signaling. Importantly, KEGG pathway analysis identified TNF signaling and cytokine-cytokine receptor interaction. However, pro-inflammatory cytokines were higher in BMI-H vs BMI-L, notably CXCL1, MMP-9, PF4V1, IL-18R1. In our study, there was a paradoxical lower expression of pro-inflammatory genes in BMI-H compared to BMI-L. However, protein levels were higher in BMI-H suggesting a possible epigenetic effect from miRNA expression.

Decreased expression of microRNAs targeting type-2 diabetes susceptibility genes in peripheral blood of patients and predisposed individuals.

Certain microRNA molecules (miRNAs) that target genes involved in beta-cell growth and insulin resistance are found deregulated in patients with type-2 diabetes mellitus (T2D) and correlate with its complications. However, the expression profile of miRNAs that regulate genes bearing T2D-related single-nucleotide polymorphisms has been hardly studied. We recently reported that the mRNA patterns of specific T2D-susceptibility genes are impaired in patients, and associate with disease parameters and risk factors. The aim of this study was to explore the levels of miRNAs that target those genes, in peripheral blood of patients versus controls. A panel of 14 miRNAs validated to target the CDKN2A, CDK5, IGF2BP2, KCNQ1, and TSPAN8 genes, was developed upon combined search throughout the DIANNA TarBase v7.0, miRTarBase, miRSearch v3.0-Exiqon, miRGator v3.0, and miRTarget Link Human algorithms. Specifically developed poly(A)polyadenylation(PAP)-reverse transcription(RT)-qPCR protocols were applied in peripheral blood RNA samples from patients and controls. Possible correlations with the disease, clinicopathological parameters and/or risk factors were evaluated. T2D patients expressed decreased levels of let-7b-5p, miR-1-3p, miR-24-3p, miR-34a-5p, miR-98-5p, and miR-133a-3p, compared with controls. Moreover, these levels correlated with certain disease features including insulin and % HbA1c levels in patients, as well as BMI, triglycerides' levels and family history in controls. A T2D-specific expression profile of miRNAs that target disease-susceptibility genes is for the first time described. Future studies are needed to elucidate the associated transcription-regulatory mechanisms, perchance involved in T2D pathogenesis, and to evaluate the potential of these molecules as possible biomarkers for this disorder.

Genome-wide analysis of gene expression after one year of venom immunotherapy

Background Insect venom immunotherapy (VIT) is used to protect patients against Hymenoptera insects’ venom allergy (HVA), which can result in severe systemic or even life-threatening conditions. Molecular mechanisms triggered by VIT remain largely unknown.Objective To compare genome-wide gene expression of patients with severe HVA prior to VIT and 12 months after.Methods Whole blood RNA samples were analyzed on an expression array. Results from differential expression obtained on a microarray platform were confirmed by quantitative real -time PCR (qRT-PCR). Subsequently we applied unsupervised clustering. Relative blood cell proportions and gene expression profiles were used as an input to csSAM to compute cell specific differential gene expression. Finally, transcription factor enrichment analysis was performed in MotifLab.Results & conclusions Comparison of genome-wide expression patterns for whole blood and qRT-PCR experiments revealed no significantly up and/or down regulated genes. This has been corroborated by unsupervised clustering. We found a significant upregulation of 26 genes in macrophages, of 15 genes in monocytes and 2 genes in T regulatory cells (Tregs). Analysis of the promoter sequences of these upregulated genes revealed a significant over-representation of binding motifs specific for kruppel-like factor 4, retinoic acid receptor gamma, and vitamin D receptor.Our results indicate that changes of gene expression invoked by VIT in peripheral blood may have a too small effect to be detected by conventional biostatistical approaches. When blood cell composition was taken into account we uncovered numerous changes of cell-specific gene expression. Given the regulatory implications we hypothesize that above-mentioned alterations may contribute to activation of anti-inflammatory signals in the innate branch of the immune system.

Transcription factor motif enrichment in whole transcriptome analysis identifies STAT4 and BCL6 as the most prominent binding motif in systemic juvenile idiopathic arthritis

BackgroundThe term systemic juvenile idiopathic arthritis (sJIA) describes an autoinflammatory condition characterized by arthritis and severe systemic inflammation, which in later stages can transform into interleukin (IL)-17-driven autoimmune arthritis. IL-1 antagonists have been used with good efficacy in the early stages of sJIA.MethodsA whole transcriptome analysis of peripheral blood RNA samples was performed in six patients with sJIA and active systemic disease, before initiating treatment with the IL-1β receptor antagonist anakinra, and after induction of inactive disease, compared with a single-sample control cohort of 21 patients in several clinical stages of sJIA activity. Whole transcriptomes were compared longitudinally and interindividually including gene ontology and motif enrichment analysis of differentially expressed genes.ResultsThere were 741 transcripts were identified using a threshold with a p value <0.01 and a fold change > 2. HLADRB1 and CD74 were identified as the most strongly upregulated genes in inactive compared to active disease; CD177 expression was significantly enhanced in active disease compared to inactive disease. Motif enrichment analysis revealed STAT4, BCL6, and STAT3 as the most prominent transcription factors that were present during active disease. In addition, strong upregulation of the major histocompatability complex II (MHCII) ligand CD74 was found in both active and inactive sJIA compared to healthy controls.ConclusionUsing transcription factor motif enrichment, this study identifies novel putative pathways in sJIA (STAT4, BCL6) implicating B cell activation at an earlier stage than predicted in refractory disease. The implication of BCL-6 dependent pathways argues for occurrence of autoimmunity early within the process of sJIA chronification. Transcriptional regulation of HLA-DRB1, a recently described independent genetic risk factor, in combination with its cooperating partner CD74 in patients where sJIA is confirmed, supports pathogenic involvement in alterations in antigen presentation during sJIA.