Differentially expressed gene transcripts using RNA sequencing from the blood of immunosuppressed kidney allograft recipients

Clinical Validation of an Immune Quiescence Gene Expression Signature in Kidney Transplantation

Background

Despite advances in immune suppression, kidney allograft rejection and other injuries remain a significant clinical concern, particularly with regards to long-term allograft survival. Evaluation of immune activity can provide information about rejection status and help guide interventions to extend allograft life. Here, we describe the validation of a blood gene expression classifier developed to differentiate immune quiescence from both T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR).

Methods

A five-gene classifier (DCAF12, MARCH8, FLT3, IL1R2, and PDCD1) was developed on 56 peripheral blood samples and validated on two sample sets independent of the training cohort. The primary validation set comprised 98 quiescence samples and 18 rejection samples: seven TCMR, ten ABMR, and one mixed rejection. The second validation set included eight quiescence and 11 rejection samples: seven TCMR, two ABMR, and two mixed rejection. AlloSure donor-derived cell-free DNA (dd-cfDNA) was also evaluated.

Results

AlloMap Kidney classifier scores in the primary validation set differed significantly between quiescence (median, 9.49; IQR, 7.68-11.53) and rejection (median, 13.09; IQR, 11.25-15.28), with P<0.001. In the second validation set, the cohorts were statistically different (P=0.03) and the medians were similar to the primary validation set. The AUC for discriminating rejection from quiescence was 0.786 for the primary validation and 0.800 for the second validation. AlloMap Kidney results were not significantly correlated with AlloSure, although both were elevated in rejection. The ability to discriminate rejection from quiescence was improved when AlloSure and AlloMap Kidney were used together (AUC, 0.894).

Conclusion

Validation of AlloMap Kidney demonstrated the ability to differentiate between rejection and immune quiescence using a range of scores. The diagnostic performance suggests that assessment of the mechanisms of immunologic activity is complementary to allograft injury information derived from AlloSure dd-cfDNA. Together, these biomarkers offer a more comprehensive assessment of allograft health and immune quiescence.

TMEM205 Is an Independent Prognostic Factor and Is Associated With Immune Cell Infiltrates in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide despite the availability of diverse treatment strategies. Much research progress has been made regarding immunotherapy but the effects remain unsatisfactory, highlighting the urgent need for novel immune-related therapy targets. In recent years, more and more studies have pointed out the associations between certain transmembrane (TMEM) family proteins and tumor progression, but the role of TMEM205 remains unclear. In this study, we analyzed the RNA-seq and clinical data of 371 patients from The Cancer Genome Atlas (TCGA) and found significant differential expression of TMEM205 between normal and tumor tissues (P < 0.001). Low TMEM205 expression was also found to be independently associated with poor overall survival (OS; p = 0.032) and poor disease-specific survival (DSS; p = 0.002) in multivariate Cox regression analyses. RNA-seq and clinical data from hepatocellular carcinoma patients in the International Cancer Genome Consortium (ICGC) also showed significant differential expression of TMEM205 (P < 0.001) and association between low TMEM205 expression and poor survival (P < 0.001). We also used the Estimate the Proportion of Immune and Cancer cells (EPIC) tool to estimate the proportions of various immune cells in the tumor tissues. A correlation analysis was conducted, and TMEM205 expression in tumor tissues was found to be significantly associated with the proportion of macrophages (Pearson r = 0.45, p < 0.0001). A negative correlation was found between TMEM205 expression and M2 macrophage markers (CD163, EGR2, and MS4A4A) and between TMEM205 expression and regulatory T cell (Treg) markers (CCR8, STAT5B, and IL2RA), while a positive correlation was found between TMEM205 expression and the proportion of CD8+ T cells (Pearson r = 0.26, p < 0.0001). In conclusion, TMEM205 might improve HCC patients’ prognosis by reducing the levels of immunosuppressive cells (M2 macrophages and Tregs) and facilitating the infiltration of cytotoxic T cells into the tumor microenvironment. Therefore, TMEM205 has potential as a prognostic biomarker and immunotherapy agent in combination therapy regimens for HCC.

Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection

Introduction

Peripheral blood (PB) molecular patterns characterizing the different effector immune pathways driving distinct kidney rejection types remain to be fully elucidated. We hypothesized that transcriptome analysis using RNA sequencing (RNAseq) in samples of kidney transplant patients would enable the identification of unique protein-coding and noncoding genes that may be able to segregate different rejection phenotypes.

Methods

We evaluated 37 biopsy-paired PB samples from the discovery cohort, with stable (STA), antibody-mediated rejection (AMR), and T cell-mediated rejection (TCMR) by RNAseq. Advanced machine learning tools were used to perform 3-way differential gene expression analysis to identify gene signatures associated with rejection. We then performed functional in silico analysis and validation by Fluidigm (San Francisco, CA) in 62 samples from 2 independent kidney transplant cohorts.

Results

We found 102 genes (63 coding genes and 39 noncoding genes) associated with AMR (54 upregulated), TCMR (23 upregulated), and STA (25 upregulated) perfectly clustered with each rejection phenotype and highly correlated with main histologic lesions (ρ = 0.91). For the genes associated with AMR, we found enrichment in regulation of endoplasmic reticulum stress, adaptive immunity, and Ig class-switching. In the validation, we found that the SIGLEC17P pseudogene and 9 SIGLEC17P-related coding genes were highly expressed among AMR but not in TCMR and STA samples.

Conclusions

This analysis identifies a critical gene signature in PB in kidney transplant patients undergoing AMR, sufficient to differentiate them from patients with TCMR and immunologically quiescent kidney allografts. Our findings provide the basis for new studies dissecting the role of noncoding genes in the pathophysiology of kidney allograft rejection and their potential value as noninvasive biomarkers of the rejection process.

Molecular Pathways Underlying Adaptive Repair of the Injured Kidney: Novel Donation After Cardiac Death and Acute Kidney Injury Platforms

OBJECTIVE

To test the hypothesis that gene expression profiling in peripheral blood from patients who have undergone kidney transplantation (KT) will provide mechanistic insights regarding graft repair and regeneration.

BACKGROUND

Renal grafts obtained from living donors (LD) typically function immediately, whereas organs from donation after cardiac death (DCD) or acute kidney injury (AKI) donors may experience delayed function with eventual recovery. Thus, recipients of LD, DCD, and AKI kidneys were studied to provide a more complete understanding of the molecular basis for renal recovery.

METHODS

Peripheral blood was collected from LD and DCD/AKI recipients before transplant and throughout the first 30 days thereafter. Total RNA was isolated and assayed on whole genome microarrays.

RESULTS

Comparison of longitudinal gene expression between LD and AKI/DCD revealed 2 clusters, representing 141 differentially expressed transcripts. A subset of 11 transcripts was found to be differentially expressed in AKI/DCD versus LD. In all recipients, the most robust gene expression changes were observed in the first day after transplantation. After day 1, gene expression profiles differed depending upon the source of the graft. In patients receiving LD grafts, the expression of most genes did not remain markedly elevated beyond the first day post-KT. In the AKI/DCD groups, elevations in gene expression were maintained for at least 5 days post-KT. In all recipients, the pattern of coordinate gene overexpression subsided by 28 to 30 days.

CONCLUSIONS

Gene expression in peripheral blood of AKI/DCD recipients offers a novel platform to understand the potential mechanisms and timing of kidney repair and regeneration after transplantation.

Bioinformatic analysis of peripheral blood RNA-sequencing sensitively detects the cause of late graft loss following overt hyperglycemia in pig-to-nonhuman primate islet xenotransplantation

Clinical islet transplantation has recently been a promising treatment option for intractable type 1 diabetes patients. Although early graft loss has been well studied and controlled, the mechanisms of late graft loss largely remains obscure. Since long-term islet graft survival had not been achieved in islet xenotransplantation, it has been impossible to explore the mechanism of late islet graft loss. Fortunately, recent advances where consistent long-term survival (≥6 months) of adult porcine islet grafts was achieved in five independent, diabetic nonhuman primates (NHPs) enabled us to investigate on the late graft loss. Regardless of the conventional immune monitoring methods applied in the post-transplant period, the initiation of late graft loss could rarely be detected before the overt graft loss observed via uncontrolled blood glucose level. Thus, we retrospectively analyzed the gene expression profiles in 2 rhesus monkey recipients using peripheral blood RNA-sequencing (RNA-seq) data to find out the potential cause(s) of late graft loss. Bioinformatic analyses showed that highly relevant immunological pathways were activated in the animal which experienced late graft failure. Further connectivity analyses revealed that the activation of T cell signaling pathways was the most prominent, suggesting that T cell-mediated graft rejection could be the cause of the late-phase islet loss. Indeed, the porcine islets in the biopsied monkey liver samples were heavily infiltrated with CD3+ T cells. Furthermore, hypothesis test using a computational experiment reinforced our conclusion. Taken together, we suggest that bioinformatics analyses with peripheral blood RNA-seq could unveil the cause of insidious late islet graft loss.

Transcriptional dissection of differentially expressed long non-coding RNAs and messenger RNAs reveals the potential molecular mechanism after kidney transplantation

Background

Kidney transplantation has given benefits to patients, although the associated genetic mechanisms are unclear. The present study aimed to understand the changes in gene expression and genetic pathways after kidney transplantation with the administration of immunosuppressive drugs.

Methods

The transcriptome data of blood samples from kidney transplantation recipients, obtained by RNA-seq, were reannotated to a more complete human genome (GRCh38/hg38). We compared the differentially expressed genes (DEGs) at pretransplant and 1 week, 3 months and 6 months posttransplant; researched the temporal variation of the DEGs; and constructed a long non-coding RNA (lncRNA)-messenger RNA (mRNA) network.

Results

We found that compared to that at pretransplantation, 1,766 genes and 3,530 genes were upregulated and downregulated, respectively, at 1 week after kidney transplantation, and the number of DEGs declined over time. These DEGs were separated into 16 clusters, and the temporal variation expression was established by the average expression of the DEGs. A pathway analysis suggested that the immune reaction was attenuated and that the expression of ribosome-related proteins was reduced.

Conclusions

The lncRNA-mRNA network had 235 connections between 138 lncRNAs and 170 mRNAs. This work generated a gene profile based on temporal variation and revealed a significantly altered lncRNA-mRNA axis contributing to molecular regulation, suggesting the potential gene mechanism of kidney transplantation and the effects of immunosuppressive drugs.

A Peripheral Blood Gene Expression Signature to Diagnose Subclinical Acute Rejection

BACKGROUND

In kidney transplant recipients, surveillance biopsies can reveal, despite stable graft function, histologic features of acute rejection and borderline changes that are associated with undesirable graft outcomes. Noninvasive biomarkers of subclinical acute rejection are needed to avoid the risks and costs associated with repeated biopsies.

METHODS

We examined subclinical histologic and functional changes in kidney transplant recipients from the prospective Genomics of Chronic Allograft Rejection (GoCAR) study who underwent surveillance biopsies over 2 years, identifying those with subclinical or borderline acute cellular rejection (ACR) at 3 months (ACR-3) post-transplant. We performed RNA sequencing on whole blood collected from 88 individuals at the time of 3-month surveillance biopsy to identify transcripts associated with ACR-3, developed a novel sequencing-based targeted expression assay, and validated this gene signature in an independent cohort.

RESULTS

Study participants with ACR-3 had significantly higher risk than those without ACR-3 of subsequent clinical acute rejection at 12 and 24 months, faster decline in graft function, and decreased graft survival in adjusted Cox analysis. We identified a 17-gene signature in peripheral blood that accurately diagnosed ACR-3, and validated it using microarray expression profiles of blood samples from 65 transplant recipients in the GoCAR cohort and three public microarray datasets. In an independent cohort of 110 transplant recipients, tests of the targeted expression assay on the basis of the 17-gene set showed that it identified individuals at higher risk of ongoing acute rejection and future graft loss.

CONCLUSIONS

Our targeted expression assay enabled noninvasive diagnosis of subclinical acute rejection and inflammation in the graft and may represent a useful tool to risk-stratify kidney transplant recipients.

Differential gene expression profiles of human periodontal ligament cells preserved in Hank's balanced salt solution and milk

BACKGROUND/AIM

Various types of storage media have been investigated to preserve avulsed teeth. However, the efficacies of storage media mainly focus on the aspect of cell viability. The aim of this study was to evaluate and compare the gene expression profiles of human periodontal ligament cells preserved in Hank's balanced salt solution (HBSS) and milk over different storage durations.

MATERIAL AND METHODS

Human periodontal ligament cells were cultured and preserved in HBSS and milk for 3 and 6 hours. Next, total RNA was isolated. QuantSeq 3' mRNA-Sequencing was used to examine differences in gene expression in HBSS- and milk-grown periodontal ligament cells. Bioinformatics analysis was also performed to predict the function of the differentially expressed genes.

RESULTS

The number of differentially expressed genes shared among all groups was 101. In gene set enrichment analysis, the shared differentially expressed genes in HBSS and milk were associated with the TNF-α signaling pathway (P = 1.07E^-7 ). Seven hallmark gene sets were also identified in HBSS. Moreover, hallmark gene sets associated with hypoxia (P = 7.26E^-5 ) and apoptosis (P = 4.06E^-4 ) were identified in HBSS. In milk, 10 hallmark gene sets along with gene sets for inflammatory response (P = 6.87E^-3 ) were identified.

CONCLUSIONS

Compared to those in milk, genes in HBSS were differentially expressed with increasing storage duration, suggesting that diverse and different gene expression may be involved in HBSS and milk. However, a more detailed functional analysis of these differentially expressed genes in storage solutions should be performed in the future.

Single nucleotide variant counts computed from RNA sequencing and cellular traffic into human kidney allografts

Advances in bioinformatics allow identification of single nucleotide polymorphisms (variants) from RNA sequence data. In an allograft biopsy, 2 genomes contribute to the RNA pool, 1 from the donor organ and the other from the infiltrating recipient's cells. We hypothesize that imbalances in genetic variants of RNA sequence data of kidney allograft biopsies provide an objective measure of cellular infiltration of the allograft. We performed mRNA sequencing of 40 kidney allograft biopsies, selected to represent a comprehensive range of diagnostic categories. We analyzed the sequencing reads of these biopsies and of 462 lymphoblastoid cell lines from the 1000 Genomes Project, for RNA variants. The ratio of heterozygous to nonreference genome homozygous variants (Het/Hom ratio) on all autosomes was determined for each sample, and the estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) score was computed as a complementary estimate of the degree of cellular infiltration into biopsies. The Het/Hom ratios (P = .02) and the ESTIMATE scores (P < .001) were associated with the biopsy diagnosis. Both measures correlated significantly (r = .67, P < .0001), even though the Het/Hom ratio is based on mRNA sequence variation, while the ESTIMATE score uses mRNA expression. Het/Hom ratio and the ESTIMATE score may offer unbiased and quantitative parameters for characterizing cellular traffic into human kidney allografts.

Variance component score test for time-course gene set analysis of longitudinal RNA-seq data

As gene expression measurement technology is shifting from microarrays to sequencing, the statistical tools available for their analysis must be adapted since RNA-seq data are measured as counts. It has been proposed to model RNA-seq counts as continuous variables using nonparametric regression to account for their inherent heteroscedasticity. In this vein, we propose tcgsaseq, a principled, model-free, and efficient method for detecting longitudinal changes in RNA-seq gene sets defined a priori. The method identifies those gene sets whose expression varies over time, based on an original variance component score test accounting for both covariates and heteroscedasticity without assuming any specific parametric distribution for the (transformed) counts. We demonstrate that despite the presence of a nonparametric component, our test statistic has a simple form and limiting distribution, and both may be computed quickly. A permutation version of the test is additionally proposed for very small sample sizes. Applied to both simulated data and two real datasets, tcgsaseq is shown to exhibit very good statistical properties, with an increase in stability and power when compared to state-of-the-art methods ROAST (rotation gene set testing), edgeR, and DESeq2, which can fail to control the type I error under certain realistic settings. We have made the method available for the community in the R package tcgsaseq.

Current status of alloimmunity

PURPOSE OF REVIEW

The present review aims to highlight the major recent advances in transplantation with regards to basic, translational, and clinical research.

RECENT FINDINGS

We describe new concepts in understanding allorecognition and allospecificity of T cells, and discuss current challenges in targeting memory T cells, including the limitation of rodent disease models. From a clinical perspective, we highlight the advances in molecular biopsy characterization, which have expanded our knowledge of potential drivers of injury and may provide better parameters for patient risk stratification. We also highlight the dual role of innate immunity in both stimulating and regulating adaptive immunity, as well as novel insights into environmental exposures that may affect immune regulation, such as high-salt diet. Finally, we discuss advances in understanding humoral response and novel technologies, such as chimeric antigen receptors-engineered T cells, microparticle-based drug delivery, and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated protein 9 (Cas9) gene editing, that may provide intriguing and promising approaches to restrain alloimmunity.

SUMMARY

Current advances in our understanding of the basic mechanisms of alloimmunity and their potential translation to clinical applications will permit the development of novel diagnostic and therapeutic strategies to improve long-term graft survival.

Genetics of acute rejection after kidney transplantation

Treatment of acute rejection (AR) following kidney transplantation has improved in recent years, but there are still limitations to successful outcomes. This review article covers literature in regard to recipient and donor genetics of AR kidney and secondarily of liver allografts. Many candidate gene and some genome-wide association studies (GWASs) have been conducted for AR in kidney transplantation. Genetic associations with AR in kidney and liver are mostly weak, and in most cases, the associations have not been reproducible. A limitation in the study of AR is the lack of sufficiently large populations that account for population stratification to study the AR phenotype which in this era occurs in <10% of transplants. Furthermore, the AR phenotype has been difficult to define and the definitions of classifications have evolved over time. Literature related to the pharmacogenomics of tacrolimus is robust and has been validated in many studies. Associations between gene expression and AR are emerging as markers of outcomes and AR classification. In the future, combinations of pretransplant genotype for AR risk prediction, genotype-based immune suppressant dosing, and pharmacogenomic markers to select AR maintenance or treatment and expression markers from biopsies may provide valuable clinical tools for guiding treatment.

Autoimmunity and autoinflammation: A systems view on signaling pathway dysregulation profiles

INTRODUCTION

Autoinflammatory and autoimmune disorders are characterized by aberrant changes in innate and adaptive immunity that may lead from an initial inflammatory state to an organ specific damage. These disorders possess heterogeneity in terms of affected organs and clinical phenotypes. However, despite the differences in etiology and phenotypic variations, they share genetic associations, treatment responses and clinical manifestations. The mechanisms involved in their initiation and development remain poorly understood, however the existence of some clear similarities between autoimmune and autoinflammatory disorders indicates variable degrees of interaction between immune-related mechanisms.

METHODS

Our study aims at contributing to a holistic, pathway-centered view on the inflammatory condition of autoimmune and autoinflammatory diseases. We have evaluated similarities and specificities of pathway activity changes in twelve autoimmune and autoinflammatory disorders by performing meta-analysis of publicly available gene expression datasets generated from peripheral blood mononuclear cells, using a bioinformatics pipeline that integrates Self Organizing Maps and Pathway Signal Flow algorithms along with KEGG pathway topologies.

RESULTS AND CONCLUSIONS

The results reveal that clinically divergent disease groups share common pathway perturbation profiles. We identified pathways, similarly perturbed in all the studied diseases, such as PI3K-Akt, Toll-like receptor, and NF-kappa B signaling, that serve as integrators of signals guiding immune cell polarization, migration, growth, survival and differentiation. Further, two clusters of diseases were identified based on specifically dysregulated pathways: one gathering mostly autoimmune and the other mainly autoinflammatory diseases. Cluster separation was driven not only by apparent involvement of pathways implicated in adaptive immunity in one case, and inflammation in the other, but also by processes not explicitly related to immune response, but rather representing various events related to the formation of specific pathophysiological environment. Thus, our data suggest that while all of the studied diseases are affected by activation of common inflammatory processes, disease-specific variations in their relative balance are also identified.

Dietary intake alters gene expression in colon tissue: possible underlying mechanism for the influence of diet on disease

Supplemental Digital Content is available in the text.

Background

Although the association between diet and disease is well documented, the biologic mechanisms involved have not been entirely elucidated. In this study, we evaluate how dietary intake influences gene expression to better understand the underlying mechanisms through which diet operates.

Methods

We used data from 144 individuals who had comprehensive dietary intake and gene expression data from RNAseq using normal colonic mucosa. Using the DESeq2 statistical package, we identified genes that showed statistically significant differences in expression between individuals in high-intake and low-intake categories for several dietary variables of interest adjusting for age and sex. We examined total calories, total fats, vegetable protein, animal protein, carbohydrates, trans-fatty acids, mutagen index, red meat, processed meat, whole grains, vegetables, fruits, fiber, folate, dairy products, calcium, and prudent and western dietary patterns.

Results

Using a false discovery rate of less than 0.1, meat-related foods were statistically associated with 68 dysregulated genes, calcium with three dysregulated genes, folate with four dysregulated genes, and nonmeat-related foods with 65 dysregulated genes. With a more stringent false discovery rate of less than 0.05, there were nine meat-related dysregulated genes and 23 nonmeat-related genes. Ingenuity pathway analysis identified three major networks among genes identified as dysregulated with respect to meat-related dietary variables and three networks among genes identified as dysregulated with respect to nonmeat-related variables. The top networks (Ingenuity Pathway Analysis network score >30) associated with meat-related genes were (i) cancer, organismal injury, and abnormalities, tumor morphology, and (ii) cellular function and maintenance, cellular movement, cell death, and survival. Among genes related to nonmeat consumption variables, the top networks were (i) hematological system development and function, nervous system development and function, tissue morphology and (ii) connective tissue disorders, organismal injury, and abnormalities.

Conclusion

Several dietary factors were associated with gene expression in our data. These findings provide insight into the possible mechanisms by which diet may influence disease processes.

Transplant genetics and genomics

Ever since the discovery of the major histocompatibility complex, scientific and clinical understanding in the field of transplantation has been advanced through genetic and genomic studies. Candidate-gene approaches and recent genome-wide association studies (GWAS) have enabled a deeper understanding of the complex interplay of the donor-recipient interactions that lead to transplant tolerance or rejection. Genetic analysis in transplantation, when linked to demographic and clinical outcomes, has the potential to drive personalized medicine by enabling individualized risk stratification and immunosuppression through the identification of variants associated with immune-mediated complications, post-transplant disease or alterations in drug-metabolizing genes.

Transcriptomic Profile of Whole Blood Cells from Elderly Subjects Fed Probiotic Bacteria Lactobacillus rhamnosus GG ATCC 53103 (LGG) in a Phase I Open Label Study

We examined gene expression of whole blood cells (WBC) from 11 healthy elderly volunteers participating on a Phase I open label study before and after oral treatment with Lactobacillus rhamnosus GG-ATCC 53103 (LGG)) using RNA-sequencing (RNA-Seq). Elderly patients (65–80 yrs) completed a clinical assessment for health status and had blood drawn for cellular RNA extraction at study admission (Baseline), after 28 days of daily LGG treatment (Day 28) and at the end of the study (Day 56) after LGG treatment had been suspended for 28 days. Treatment compliance was verified by measuring LGG-DNA copy levels detected in host fecal samples. Normalized gene expression levels in WBC RNA were analyzed using a paired design built within three analysis platforms (edgeR, DESeq2 and TSPM) commonly used for gene count data analysis. From the 25,990 transcripts detected, 95 differentially expressed genes (DEGs) were detected in common by all analysis platforms with a nominal significant difference in gene expression at Day 28 following LGG treatment (FDR<0.1; 77 decreased and 18 increased). With a more stringent significance threshold (FDR<0.05), only two genes (FCER2 and LY86), were down-regulated more than 1.5 fold and met the criteria for differential expression across two analysis platforms. The remaining 93 genes were only detected at this threshold level with DESeq2 platform. Data analysis for biological interpretation of DEGs with an absolute fold change of 1.5 revealed down-regulation of overlapping genes involved with Cellular movement, Cell to cell signaling interactions, Immune cell trafficking and Inflammatory response. These data provide evidence for LGG-induced transcriptional modulation in healthy elderly volunteers because pre-treatment transcription levels were restored at 28 days after LGG treatment was stopped. To gain insight into the signaling pathways affected in response to LGG treatment, DEG were mapped using biological pathways and genomic data mining packages to indicate significant biological relevance.

Trial Registration: ClinicalTrials.gov NCT01274598

Differential Gene Expression in Colon Tissue Associated With Diet, Lifestyle, and Related Oxidative Stress

Several diet and lifestyle factors may impact health by influencing oxidative stress levels. We hypothesize that level of cigarette smoking, alcohol, anti-inflammatory drugs, and diet alter gene expression. We analyzed RNA-seq data from 144 colon cancer patients who had information on recent cigarette smoking, recent alcohol consumption, diet, and recent aspirin/non-steroidal anti-inflammatory use. Using a false discovery rate of 0.1, we evaluated gene differential expression between high and low levels of exposure using DESeq2. Ingenuity Pathway Analysis (IPA) was used to determine networks associated with de-regulated genes in our data. We identified 46 deregulated genes associated with recent cigarette use; these genes enriched causal networks regulated by TEK and MAP2K3. Different differentially expressed genes were associated with type of alcohol intake; five genes were associated with total alcohol, six were associated with beer intake, six were associated with wine intake, and four were associated with liquor consumption. Recent use of aspirin and/or ibuprofen was associated with differential expression of TMC06, ST8SIA4, and STEAP3 while a summary oxidative balance score (OBS) was associated with SYCP3, HDX, and NRG4 (all up-regulated with greater oxidative balance). Of the dietary antioxidants and carotenoids evaluated only intake of beta carotene (1 gene), Lutein/Zeaxanthine (5 genes), and Vitamin E (4 genes) were associated with differential gene expression. There were similarities in biological function of de-regulated genes associated with various dietary and lifestyle factors. Our data support the hypothesis that diet and lifestyle factors associated with oxidative stress can alter gene expression. However genes altered were unique to type of alcohol and type of antioxidant. Because of potential differences in associations observed between platforms these findings need replication in other populations.

Evaluating the Stability of RNA-Seq Transcriptome Profiles and Drug-Induced Immune-Related Expression Changes in Whole Blood

Methods were developed to evaluate the stability of rat whole blood expression obtained from RNA sequencing (RNA-seq) and assess changes in whole blood transcriptome profiles in experiments replicated over time. Expression was measured in globin-depleted RNA extracted from the whole blood of Sprague-Dawley rats, given either saline (control) or neurotoxic doses of amphetamine (AMPH). The experiment was repeated four times (paired control and AMPH groups) over a 2-year span. The transcriptome of the control and AMPH-treated groups was evaluated on: 1) transcript levels for ribosomal protein subunits; 2) relative expression of immune-related genes; 3) stability of the control transcriptome over 2 years; and 4) stability of the effects of AMPH on immune-related genes over 2 years. All, except one, of the 70 genes that encode the 80s ribosome had levels that ranked in the top 5% of all mean expression levels. Deviations in sequencing performance led to significant changes in the ribosomal transcripts. The overall expression profile of immune-related genes and genes specific to monocytes, T-cells or B-cells were well represented and consistent within treatment groups. There were no differences between the levels of ribosomal transcripts in time-matched control and AMPH groups but significant differences in the expression of immune-related genes between control and AMPH groups. AMPH significantly increased expression of some genes related to monocytes but down-regulated those specific to T-cells. These changes were partially due to changes in the two types of leukocytes present in blood, which indicate an activation of the innate immune system by AMPH. Thus, the stability of RNA-seq whole blood transcriptome can be verified by assessing ribosomal protein subunits and immune-related gene expression. Such stability enables the pooling of samples from replicate experiments to carry out differential expression analysis with acceptable power.