Changes in Whole Blood Transcriptome during Peanut-Induced Anaphylaxis and Correlation with Symptoms

AbstractComplex diseases are systemic, largely mediated via transcriptional dysregulation in multiple tissues. Thus, knowledge of tissue-specific transcriptome in an individual can provide important information about an individual’s health. Unfortunately, with a few exceptions such as blood, skin, and muscle, an individual’s tissue-specific transcriptome is not accessible through non-invasive means. However, due to shared genetics and regulatory programs between tissues, the transcriptome in blood may be predictive of those in other tissues, at least to some extent. Here, based on GTEx data, we address this question in a rigorous, systematic manner, for the first time. We find that an individual’s whole blood gene expression and splicing profile can predict tissue-specific expression levels in a significant manner (beyond demographic variables) for many genes. On average, across 32 tissues, the expression of about 60% of the genes is predictable from blood expression in a significant manner, with a maximum of 81% of the genes for the musculoskeletal tissue. Remarkably, the tissue-specific expression inferred from the blood transcriptome is almost as good as the actual measured tissue expression in predicting disease state for six different complex disorders, including Hypertension and Type 2 diabetes, substantially surpassing predictors built directly from the blood transcriptome. The code for our pipeline for tissue-specific gene expression prediction – TEEBoT, is provided, enabling others to study its potential translational value in other indications.

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Whole Blood Transcriptome Profiling Identifies DNA Replication and Cell Cycle Regulation as Early Marker of Response to Anti-PD-1 in Patients with Urothelial Cancer

Cancers ◽

10.3390/cancers13184660 ◽

2021 ◽

Vol 13 (18) ◽

pp. 4660

Author(s):

Sandra van Wilpe ◽

Victoria Wosika ◽

Laura Ciarloni ◽

Sahar Hosseinian Ehrensberger ◽

Rachel Jeitziner ◽

...

Keyword(s):

Cell Cycle ◽

Dna Replication ◽

Whole Blood ◽

Clinical Benefit ◽

Cell Cycle Regulation ◽

Urothelial Cancer ◽

Transcriptome Profiling ◽

Ki 67 ◽

Cycle Regulation ◽

Blood Transcriptome

Although immune checkpoint inhibitors improve median overall survival in patients with metastatic urothelial cancer (mUC), only a minority of patients benefit from it. Early blood-based response biomarkers may provide a reliable way to assess response weeks before imaging is available, enabling an early switch to other therapies. We conducted an exploratory study aimed at the identification of early markers of response to anti-PD-1 in patients with mUC. Whole blood RNA sequencing and phenotyping of peripheral blood mononuclear cells were performed on samples of 26 patients obtained before and after 2 to 6 weeks of anti-PD-1. Between baseline and on-treatment samples of patients with clinical benefit, 51 differentially expressed genes (DEGs) were identified, of which 37 were upregulated during treatment. Among the upregulated genes was PDCD1, the gene encoding PD-1. STRING network analysis revealed a cluster of five interconnected DEGs which were all involved in DNA replication or cell cycle regulation. We hypothesized that the upregulation of DNA replication/cell cycle genes is a result of T cell proliferation and we were able to detect an increase in Ki-67+ CD8+ T cells in patients with clinical benefit (median increase: 1.65%, range −0.63 to 7.06%, p = 0.012). In patients without clinical benefit, no DEGs were identified and no increase in Ki-67+ CD8+ T cells was observed. In conclusion, whole blood transcriptome profiling identified early changes in DNA replication and cell cycle regulation genes as markers of clinical benefit to anti-PD-1 in patients with urothelial cancer. Although promising, our findings require further validation before implementation in the clinic.

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963. Whole Blood Transcriptome Analysis Reveals Differences in Erythropoiesis and Neurologically Relevant Pathways Between Cerebral Malaria and Severe Malarial Anemia

Open Forum Infectious Diseases ◽

10.1093/ofid/ofy209.079 ◽

2018 ◽

Vol 5 (suppl_1) ◽

pp. S35-S35

Author(s):

Srinivas Nallandhighal ◽

Gregory Park ◽

Yen-Yi Ho ◽

Robert Opoka ◽

Chandy John ◽

...

Keyword(s):

Gene Expression ◽

Cerebral Malaria ◽

Severe Malaria ◽

Whole Blood ◽

Heme Oxygenase 1 ◽

Specific Gene ◽

Severe Malarial Anemia ◽

Specific Gene Expression ◽

Blood Transcriptome ◽

Malarial Anemia

Abstract Background Plasmodium falciparum malaria can rapidly progress to severe disease that can lead to death if left untreated. Severe malaria cases commonly present as severe malarial anemia (SMA), defined in children as hemoglobin (Hb) <5 g/dL with parasitemia, or as cerebral malaria (CM), which manifests as parasitemia with acute neurological deficits and has an inpatient mortality rate of ~20%. The molecular and cellular processes that lead to CM and SMA are unclear. Methods In a cross-sectional study, we compared genome-wide transcription profiles of whole blood obtained from Ugandan children with acute CM (n = 17) or SMA (n = 17) and community children without P. falciparum infection (n = 12) who were enrolled in a parent cohort study of severe malaria. We determined the relationships between gene expression, hematological indices, and plasma biomarkers, including inflammatory cytokines. Results Both CM and SMA demonstrated enrichment of dendritic cell activation, inflammatory/TLR/chemokines, monocyte, and neutrophil modules but depletion of lymphocyte modules. Neurodegenerative disease and neuroinflammation pathways were enriched in CM. Increased Nrf2 pathway gene expression corresponded with increased plasma heme oxygenase-1 and the heme catabolite bilirubin in a manner specific to children with both SMA and sickle cell disease. Reticulocyte-specific gene expression was markedly decreased in CM relative to SMA despite higher Hb levels and appropriate increases in plasma erythropoietin. Viral sensing/interferon regulatory factor (IRF) 2 module (M111) expression and plasma IP-10 levels both negatively correlated with reticulocyte-specific signatures, but only M111 expression independently predicted decreased reticulocyte-specific gene expression after controlling for leukocyte count, Hb level, parasitemia, and clinical syndrome by multiple regression. Conclusion Differences in the blood transcriptome of CM and SMA relate to neurologically relevant pathways and erythropoiesis. Erythropoietic suppression during severe malaria is more pronounced during CM versus SMA and is positively associated with IRF2 blood signatures. Future studies are needed to validate these findings. Disclosures All authors: No reported disclosures.

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