A novel multiplex polymerase chain reaction assay for profile analyses of gene expression in peripheral blood

The mechanisms underlying gender differences in stroke incidence, risk, and outcome are uncertain. We sought to determine whether transcriptional profiles of circulating blood cells of men and women differentially correlated with carotid artery intima-media thickness (CIMT), a predictor of atherosclerosis and stroke risk. Gene expression in whole blood was measured using Affymetrix expression arrays in men (n=17) and women (n=35), aged 45-64 years, with at least one risk factor for stroke. Mean average CIMT was measured using B-mode ultrasound. Expression levels of 746 genes positively and 292 genes negatively correlated with CIMT only in women (p<0.05); 881 genes positively and 597 genes negatively correlated with CIMT only in men (p<0.05). Forty-one genes correlated with CIMT in men and women, but in opposite directions. These genes were associated with estrogen, cholesterol and lipid metabolism, inflammation, coagulation, and vasoreactivity. This pilot study provides the first proof of principle that gene expression in blood cells correlates with CIMT. These results point to potential pathophysiological mechanisms underlying sex differences in stroke risk. Since the sample size is small, the findings are preliminary and need to be confirmed in independent, larger studies.

Molecular Pathways Underlying Adaptive Repair of the Injured Kidney Orlando G, Danger R, Okut H, et al. Ann Surg. Published online July 24, 2018. DOI:10.1097/SLA.0000000000002946. Previous studies have used kidney biopsies for gene expression profiling to gain insights on mechanisms of acute injury. Profiling gene expression in peripheral blood offers a viable alternative strategy. Here, the authors tested, if a noninvasive approach, the expression of genes in peripheral blood, will provide insights into mechanisms of renal transplant repair and regeneration. The authors identified 15 patients who received kidney transplants from either living donors, donors with AKI, or kidneys from donors procured after circulatory death (n = 5, for each group). Because of the nature of AKI and DCD organ donation, many of these allograft recipients experienced delayed graft function. The authors compared gene expression profiles comparing changes after AKI or DCD donation compared with those in LD kidney recipients. Total RNA was isolated from peripheral blood and evaluated for quantity and quality. A comparative analysis of longitudinal peripheral blood gene expression was performed. This analysis revealed 2 gene clusters known to be involved in kidney development and repair with significant differences between LD and AKI/DCD samples. Notably, gene expression clusters remained elevated through the first week after in recipients of AKI or DCD donor grafts, suggesting a role for additional repair and regeneration activities. An analysis of longitudinal patterns showed that a large number of genes were upregulated from pretransplantation to 5 days posttransplant. By day 28 to day 30, most of the transcripts' expression levels had decreased significantly. Eleven genes were differentially expressed in both AKI and DCD recipients. These transcripts may represent biologically relevant gene targets that differentiate the molecular response in DCD and AKI recipients compared with LD recipients. These data support that the pattern, magnitude, and duration of gene expression changes are graft and injury-specific while providing information regarding molecular pathways and specific transcripts that are involved in injury and repair. These results provide further evidence that measuring gene expression in whole blood may represent a convenient and biologically relevant approach to monitoring kidney transplant patients. Analyses of the Short- and Long-term Graft Survival After Kidney Transplantation in Europe Between 1986 and 2015 Coemans M, Susal C, Dohler B, et al. Kidney Int. Published online July 20, 2018. DOI:10.1016/j.kint.2018.05.018. This interesting article presents data on the evolution of kidney transplant outcomes in Europe over the last 3 decades. The authors report on 108 787 transplanted patients documented in the Collaborative Transplant Study, analyzed by a stratified Cox model with a flexible time-dependent effect. Three periods were compared: (1), 1986-1995, (2), 1996-2005 decade, and 3), 2006-2015 thus covering 3 complete decades (1986-2015), reporting the full history of transplant practice since the beginning of its widespread clinical use (after the introduction of cyclosporine). Analyzing survival per decade showed a gradual improvement over each decade reflecting the progress in global posttransplant management. Between 1986 and 1999 improvement was mainly linked to the availability and improved experience in using powerful and innovative immunosuppressive regimens translating into a vastly improved management of alloimmunity and decreasing acute rejection rates. Other factors improving outcomes included an improved control of hypertension, anemia, hypercholesterolemia, and hyperglycemia; more standardized histological evaluation of kidney biopsies; better donor management; improved kidney storage and preservation; updated allocation procedures and (cross) matching techniques; better detection, prevention, and treatment of infections; better management of cardiovascular and urologic complications; moreover, a growing team experience may have contributed to the improvement of graft outcomes. Interestingly, the age of the recipient was inversely related to the hazard of graft failure with younger recipients showing a higher risk of graft failure, indicating that both compliance and immune senescence. There have been striking improvements in graft outcome during the period of 1986 to 1999; more recent developments have shown significant, however, less impressive improvements.

The degree to which the level of genetic variation for gene expression is shared across multiple tissues has important implications for research investigating the role of expression on the etiology of complex human traits and diseases. In the last few years, several studies have been published reporting the extent of overlap in expression quantitative trait loci (eQTL) identified in multiple tissues or cell types. Although these studies provide important information on the regulatory control of genes across tissues, their limited power means that they can typically only explain a small proportion of genetic variation for gene expression. Here, using expression data from monozygotic twins (MZ), we investigate the genetic control of gene expression in lymphoblastoid cell lines (LCL) and whole blood (WB). We estimate the genetic correlation that represents the combined effects of all causal loci across the whole genome and is a measure of the level of common genetic control of gene expression between the two RNA sources. Our results show that, when averaged across the genome, mean levels of genetic correlation for gene expression in LCL and WB samples are close to zero. We support our results with evidence from gene expression in an independent sample of LCL, T-cells, and fibroblasts. In addition, we provide evidence that housekeeping genes, which maintain basic cellular functions, are more likely to have high genetic correlations between the RNA sources than non-housekeeping genes, implying a relationship between the transcript function and the degree to which a gene has tissue-specific genetic regulatory control.

The availability of an accessible tissue whose gene expression profile is similar to more inaccessible CNS tissues has the potential to advance research in neuropsychiatric disorders. We conducted secondary data analysis of transcriptional profiling of 79 human tissues for 33,698 genes using the Affymetrix U133A microarray augmented with a custom microarray (Affymetrix GNF1H), which were produced by the Genomics Institute of the Novartis Research Foundation (http://symatlas.gnf.org). Our analyses suggested that: (a) on a transcriptome level, whole blood shares significant gene expression similarities with multiple CNS tissues; (b) the median non-parametric correlation between transcripts present in both whole blood and CNS was around 0.5; (c) this correlation of 0.5 was intermediate relative to all tissues in the Novartis data set--less than for the maximum achievable value of 0.85, less than a set of immune tissues (0.64), comparable to a heterogeneous set of somatic tissues (0.57) but greater than muscle (0.48) and peripheral nervous system tissues (0.36); (d) about half of a set of candidate genes relevant to schizophrenia were expressed in both whole blood and prefrontal cortex; and (e) the expression levels of many classes of biologically relevant processes were not significantly different between whole blood and prefrontal cortex. These analyses suggest that gene expression in whole blood is neither perfectly correlated and useful nor perfectly uncorrelated and useless with gene expression in multiple brain tissues. This suggests that the cautious and thoughtful use of peripheral gene expression may be a useful surrogate for gene expression in the CNS when it has been determined that the relevant gene is expressed in both.

The effect of lower airway inflammation on inflammatory cytokine gene expression in bronchoalveolar lavage fluid and whole blood in racing Thoroughbreds

Objective: The identification of stroke-associated biomarkers represents a means by which prehospital triage could be expedited to increase the probability of successful intervention. Thus, the objective of this work was to use high-throughput transcriptomics in combination with basic machine learning techniques to identify a pattern of gene expression in peripheral whole blood which could be used to identify acute ischemic stroke (AIS) in the acute care setting. Methods: A two-stage study design was used which included a discovery cohort and an independent validation cohort. In the discovery cohort, peripheral whole blood samples were obtained from 39 AIS patients upon emergency department admission, and from 24 neurologically asymptomatic controls. Microarray was used to measure the expression of over 22,000 genes and a pattern recognition technique known as genetic algorithm k-nearest neighbors (GA/kNN) identified a pattern of gene expression that optimally discriminated between AIS and controls. In an independent validation cohort, the gene expression pattern was tested for its ability to discriminate between 39 AIS patients and each of two different control groups, one consisting of 30 neurologically asymptomatic controls, and the other consisting of 15 stroke mimics, with gene expression levels being assessed by qRT-PCR. Results: In the discovery cohort, GA/kNN identified ten transcripts (ANTXR2, STK3, PDK4, CD163, MAL, GRAP, ID3, CTSZ, KIF1B, and PLXDC2) whose coordinate pattern of expression correctly identified 98.4% of subjects (97.4% sensitive, 100% specific). In the validation cohort, the same 10 transcripts correctly identified 95.6% of subjects when comparing AIS patients to asymptomatic controls (92.3% sensitive, 100% specific), and 96.3% of subjects when comparing AIS patients to stroke mimics (97.4% specific, 93.3% sensitive). Conclusion: These results demonstrate that a highly accurate RNA-based companion diagnostic for AIS is plausible using a relatively small number of markers. The pattern of gene expression identified in this study shows strong diagnostic potential, and warrants further evaluation to determine true clinical efficacy.

Catecholamine-related gene expression in blood correlates with tic severity in tourette syndrome

The rs6647 variant G allele in SERPINA1 gene was reported to be associated with the risk of large artery atherosclerotic stroke (LAS), however, the mechanism remains unclear. Here, we performed a functional annotation of the rs6647 variant by using the software HaploReg version 4.1 (HaploReg v4.1). Next, the expression quantitative trait loci (eQTLs) analysis of multiple datasets was conducted for determining the association between the rs6647 and SERPINA1 expression in various tissues. Then, a case-control gene expression analysis was done using two independent ischemic stroke (IS) gene expression datasets. Finally, SERPINA1 expression in whole blood samples from 8 LAS patients and 14 healthy persons were compared. The functional annotation suggested that the rs6647 regulates gene expression in multiple human tissues especially in brain and blood. The eQTLs analysis revealed a significant association of the rs6647 G allele with increased expression of SERPINA1 gene only in whole blood. Compared with the controls, there was an increased expression of SERPINA1 gene in whole blood in both IS patients and LAS patients. SERPINA1 gene expression in whole blood bridges the rs6647 variant G allele with increased LAS risk, providing new insights into the mechanisms underlying role of the rs6647 in determining LAS risk.

BackgroundComparative analysis of gene expression in human tissues is important for understanding the molecular mechanisms underlying tissue-specific control of gene expression. It can also open an avenue for using gene expression in blood (which is the most easily accessible human tissue) to predict gene expression in other (less accessible) tissues, which would facilitate the development of novel gene expression based models for assessing disease risk and progression. Until recently, direct comparative analysis across different tissues was not possible due to the scarcity of paired tissue samples from the same individuals.MethodsIn this study we used paired whole blood/lung gene expression data from the Genotype-Tissue Expression (GTEx) project. We built a generalized linear regression model for each gene using gene expression in lung as the outcome and gene expression in blood, age and gender as predictors.ResultsFor ~18 % of the genes, gene expression in blood was a significant predictor of gene expression in lung. We found that the number of single nucleotide polymorphisms (SNPs) influencing expression of a given gene in either blood or lung, also known as the number of quantitative trait loci (eQTLs), was positively associated with efficacy of blood-based prediction of that gene’s expression in lung. This association was strongest for shared eQTLs: those influencing gene expression in both blood and lung.ConclusionsIn conclusion, for a considerable number of human genes, their expression levels in lung can be predicted using observable gene expression in blood. An abundance of shared eQTLs may explain the strong blood/lung correlations in the gene expression.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-015-0152-7) contains supplementary material, which is available to authorized users.

Periodic assessment of gene expression for diagnosis and monitoring in rheumatoid arthritis (RA) may provide a readily available and useful method to detect subclinical disease progression and follow responses to therapy with disease modifying anti-rheumatic agents (DMARDs) or anti-TNF-α therapy. We used quantitative real-time PCR to compare peripheral blood gene expression profiles in active (“unstable”) RA patients on DMARDs, stable RA patients on DMARDs, and stable RA patients treated with a combination of a disease-modifying anti-rheumatoid drug (DMARD) and an anti-TNF-α agent (infliximab or etanercept) to healthy human controls. The expression of 48 inflammatory genes were compared between healthy controls (N = 122), unstable DMARD patients (N = 18), stable DMARD patients (N = 26), and stable patients on combination therapy (N = 20). Expression of 13 genes was very low or undetectable in all study groups. Compared to healthy controls, patients with unstable RA on DMARDs exhibited increased expression of 25 genes, stable DMARD patients exhibited increased expression of 14 genes and decreased expression of five genes, and combined therapy patients exhibited increased expression of six genes and decreased expression of 10 genes. These findings demonstrate that active RA is associated with increased expression of circulating inflammatory markers whereas increases in inflammatory gene expression are diminished in patients with stable disease on either DMARD or anti-TNF-α therapy. Furthermore, combination DMARD and anti-TNF-α therapy is associated with greater reductions in circulating inflammatory gene expression compared to DMARD therapy alone. These results suggest that assessment of peripheral blood gene expression may prove useful to monitor disease progression and response to therapy.

Uroplakins (UPs), urothelium-specific transmembrane proteins, are present only in urothelia and may be good candidates as tumor markers specific for transitional cell carcinomas (TCCs). We investigated the expression of UP genes in the tissues and peripheral blood of patients with TCCs. We determined the nucleotide sequences of UPs by a polymerase chain reaction (PCR)-based method. We then investigated UP gene expression in tissues from 12 patients with TCC by reverse transcription (RT)-PCR. We also investigated UP gene expression in peripheral blood of 12 other patients with TCC by nested RT-PCR. Polyclonal and monoclonal antibodies against UPs were generated using synthesized polypeptides and recombinant protein, respectively, as immunogens. We determined the nucleotide sequence of human UP-Ib, UP-II, and UP-III cDNAs and produced gene-specific primer pairs for each and for UP-Ia. UP genes were expressed in both cancerous and non-cancerous urothelia taken from all patients examined (as detected by RT-PCR). The detection sensitivity of our assay system was such that 1 cancer cell could be detected in 5 mL of peripheral blood. UP gene-expression was also detected in the peripheral blood of 3 patients with metastatic TCC, but not from 9 patients with non-metastatic TCC or from 3 healthy volunteers. Antibodies against both UP-Ia and UP-Ib reacted with the cell membrane of TCCs. UPs may be employed as tumor markers for TCCs, because they are highly conserved and well expressed in non-cancerous and cancerous cells. Furthermore, detection of UP gene expression in blood by nested RT-PCR may provide helpful information in the diagnosis and management of TCCs. We are currently expanding an immunohistochemical study by targeting a larger number of patients to examine the clinical usefulness of these antibodies.

RNA sequencing and high-density genotyping or whole genome sequencing can be used in tandem to identify genomic regions associated with the control of gene expression, also known as expression quantitative trait loci (eQTL) mapping. Whole blood is a convenient tissue for many purposes due to its ease of collection and relation to health. Whole blood RNA-seq data and high-density SNP array genotypes were generated on ~1,600 healthy nursery pigs as part of a study of resilience to a polymicrobial disease challenge. This data was used for genotype imputation to whole genome sequence with the reference panel and bioinformatics pipeline developed by the PigGTEx consortium to identify cis-eQTL. Cis-eQTL were typically associated with expression of one or two genes. Chromosome 12 was enriched for cis-eQTL. The results provide insights into the control of gene expression in whole blood, allowing further study of its relationship with disease resilience.

Assessment of gene expression in peripheral blood using RNAseq before and after weight restoration in anorexia nervosa

The metabolic health benefits of fermented milks have already been investigated using clinical biomarkers but the development of transcriptomic analytics in blood offers an alternative approach that may help to sensitively characterise such effects. We aimed to assess the effects of probiotic yoghurt intake, compared to non-fermented, acidified milk intake, on clinical biomarkers and gene expression in peripheral blood. To this end, a randomised, crossover study was conducted in fourteen healthy, young men to test the two dairy products. For a subset of seven subjects, RNA sequencing was used to measure gene expression in blood collected during postprandial tests and after two weeks daily intake. We found that the postprandial response in insulin was different for probiotic yoghurt as compared to that of acidified milk. Moreover changes in several clinical biomarkers were associated with changes in the expression of genes representing six metabolic genesets. Assessment of the postprandial effects of each dairy product on gene expression by geneset enrichment analysis revealed significant, similar modulation of inflammatory and glycolytic genes after both probiotic yoghurt and acidified milk intake, although distinct kinetic characteristics of the modulation differentiated the dairy products. The aryl hydrocarbon receptor was a major contributor to the down-regulation of the inflammatory genesets and was also positively associated with changes in circulating insulin at 2h after yoghurt intake (p = 0.05). Daily intake of the dairy products showed little effect on the fasting blood transcriptome. Probiotic yoghurt and acidified milk appear to affect similar gene pathways during the postprandial phase but differences in the timing and the extent of this modulation may lead to different physiological consequences. The functional relevance of these differences in gene expression is supported by their associations with circulating biomarkers.

BackgroundShift work is common in healthcare, especially in emergency and intensive care, to maintain the quality of patient care. Night shifts are linked to health risks such as cardiovascular disease, metabolic disorders, and poor mental health. It has been suggested that inflammatory responses due to the disruption of circadian rhythm may contribute to health risks, but the detailed mechanisms remain unclear. This study aimed to analyze changes in gene expression in whole blood of healthcare workers before and after a night shift and investigate the molecular pathogenesis of these changes and their impact on health.MethodsThis was a single-center, prospective, observational study of four medical doctors working night shifts in the emergency department. Blood samples from the subjects were collected before and after the night shift, and RNA sequencing was performed to analyze changes in gene expression in whole blood. The data obtained were analyzed via Ingenuity Pathway Analysis (IPA) core analysis that included canonical pathway analysis, upstream regulator analysis, and functional network analysis. RNA bulk deconvolution was performed to estimate the relative abundance of immune cells. The IPA analysis match feature was also used to assess similarities of gene expression patterns with other diseases.ResultsWe identified 302 upregulated and 78 downregulated genes (p < 0.05, |log2-fold change|> 0.5) as genes whose expression changed after the night shift. Canonical pathway analysis revealed that Toll-like receptors and other innate immune response pathways were activated. Upstream regulator analysis and functional network analysis also consistently indicated a predicted activation of innate immune and inflammatory responses. RNA bulk deconvolution showed changes in the proportions of several immune cells. IPA analysis match indicated that gene expression patterns after night shifts were highly correlated with several diseases, including major depressive disorder, in terms of immune and inflammatory responses.ConclusionThe results revealed that innate immune and inflammatory responses are elicited after night shifts in healthcare workers and that gene expression patterns correlate with several diseases in terms of immune and inflammatory responses. These findings suggest that shift work may affect health risks through innate immune and inflammatory responses.