The frontline of immune response in peripheral blood

Abstract

Peripheral blood is an attractive source for the discovery of disease biomarkers. Gene expression profiling of whole blood or its components has been widely conducted for various diseases. However, due to population heterogeneity and the dynamic nature of gene expression, certain biomarkers discovered from blood transcriptome studies could not be replicated in independent studies. In the meantime, it’s also important to know whether a reliable biomarker is shared by several diseases or specific to certain health conditions. We hypothesized that common mechanism of immune response in blood may be shared by different diseases. Under this hypothesis, we surveyed publicly available transcriptome data on infectious and autoimmune diseases derived from peripheral blood. We examined to which extent common gene dys-regulation existed in different diseases. We also investigated whether the commonly dys-regulated genes could serve as reliable biomarkers. First, we found that a limited number of genes are frequently dys-regulated in infectious and autoimmune diseases, from which we selected 10 genes co-dysregulated in viral infections and another set of 10 genes co-dysregulated in bacterial infections. In addition to its ability to distinguish viral infections from bacterial infections, these 20 genes could assist in disease classification and monitoring of treatment effect for several infectious and autoimmune diseases. In some cases, a single gene is sufficient to serve this purpose. It was interesting that dys-regulation of these 20 genes were also observed in other types of diseases including cancer and stroke where certain genes could also serve as biomarkers for diagnosis or prognosis. Furthermore, we demonstrated that this set of 20 genes could also be used in continuous monitoring of personal health. The rich information from these commonly dys-regulated genes may find its wide application in clinical practice and personal healthcare. More validation studies and in-depth investigations are warranted in the future.

Failed immune responses across multiple pathologies share pan-tumor and circulating lymphocytic targets

“…Thus, the transcript isoform repertoire of CD8 + ptPBLs is much larger than that of CD8 + TIL, likely due to similarities for tissue infiltrates but with a few notable dif-identifying pan-pathology genes. We thus compared our pan-cancer DEGs to data sets from another study aimed at identifying frontline biomarkers common to numerous pathologies (30). Strikingly, 82.1% of our ptPBL-based and 42.8% of our TIL-based top 200 pan-cancer FIR-DEGs were confirmed by their findings, with 51% of 467 pan-cancer DEGs and 59% of the top 100 pan-cancer DEGs present ( Figure 6F).…”

“…Transcriptomic data sets from patients with melanoma and non-small-cell lung cancer (NSCLC) treated with anti-PD-1 therapy are available from Hugo et al (31) and Rizvi et al (32). The HIV-1 elite controllers data set is available from Zhang et al (29), and the bacterial data sets are listed in Song et al (30). Comprehensive pathway enrichment analysis and PPI analyses are available as Supplemental Data.…”

Gene dysregulation in peripheral blood of moyamoya disease and comparison with other vascular disorders

“…Mean age tended to be older in MMD patients than in healthy controls (34.61 ± 14.81 vs 44.35 ± 8.42, p = 0.01) from the qRT-PCR group. However, our previous study has shown that effect of age on gene expression in peripheral blood was so weak that expression of only six genes including NELL2 , CCR2 , CCR7 , MYC , LTB and FAM102A displayed weak negative correlation (Pearson correlation coefficients varying from -0.29 to -0.47) with age in four public datasets[48]. Baseline characteristics of all participants were shown in Table 1 .…”

A host-based two-gene model for the identification of bacterial infection in general clinical settings

“…In the past decade, host transcriptional response has emerged as a promising alternative for identifying infection (Ahn et al, 2013;Heinonen et al, 2016;Kaforou et al, 2013;Pankla et al, 2009;Zhai et al, 2015). A consistent signature for respiratory viral infection has been reported, a group of interferon-stimulated genes (ISGs) (Liu et al, 2016;Song et al, 2017;Zaas et al, 2013;Zhai et al, 2015). Several studies have attempted to distinguish bacterial infection from viral or other sources of infection.…”