Characterization of the peripheral blood transcriptome in a repeated measures design using a panel of healthy individuals

Peripheral blood RNA biomarkers for cardiovascular disease from bench to bedside: a position paper from the EU-CardioRNA COST action CA17129

Despite significant advances in the diagnosis and treatment of cardiovascular diseases, recent calls have emphasized the unmet need to improve precision-based approaches in cardiovascular disease. Although some studies provide preliminary evidence of the diagnostic and prognostic potential of circulating coding and non-coding RNAs, the complex RNA biology and lack of standardization have hampered the translation of these markers into clinical practice. In this position paper of the CardioRNA COST action CA17129, we provide recommendations to standardize the RNA development process in order to catalyse efforts to investigate novel RNAs for clinical use. We list the unmet clinical needs in cardiovascular disease, such as the identification of high-risk patients with ischaemic heart disease or heart failure who require more intensive therapies. The advantages and pitfalls of the different sample types, including RNAs from plasma, extracellular vesicles, and whole blood, are discussed in the sample matrix, together with their respective analytical methods. The effect of patient demographics and highly prevalent comorbidities, such as metabolic disorders, on the expression of the candidate RNA is presented and should be reported in biomarker studies. We discuss the statistical and regulatory aspects to translate a candidate RNA from a research use only assay to an in-vitro diagnostic test for clinical use. Optimal planning of this development track is required, with input from the researcher, statistician, industry, and regulatory partners.

Variability of multi-omics profiles in a population-based child cohort

BACKGROUND

Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood.

METHODS

We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability.

RESULTS

All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability.

CONCLUSIONS

Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both.

Peripheral Blood Cells from Patients with Hodgkin's and Diffuse Large B Cell Lymphomas May Be a Better Source of Candidate Diagnostic miRNAs Than Circulating miRNAs

Hodgkin lymphoma (HL) and diffuse large B cell lymphoma (DLBCL) represent 15% and 20%, respectively, of all lymphoma types. The aim of this study was to identify and compare circulating serum miRNA (c-miRNA) and peripheral whole blood miRNA (wb-miRNA) profiles in patients with these lymphomas. Serum samples (20 HL, 21 DLBCL, and 30 healthy controls) and whole blood samples (21 HL, 17 DLBCL patients, and 30 healthy controls) were collected at the time of diagnosis. Serum and whole blood were also collected from 18 HL/17 DLBCL and eight HL/nine DLBCL patients, respectively, after treatment. Pairwise comparisons identified 125 c-miRNAs (adjusted P value < 0.05) showing significant dysregulation between 30 healthy controls and patients; of these, 47 and 55 differentiated controls from pretherapeutic HL and DLBCL patients, respectively. In addition, 60 and 16 c-miRNAs differentiated controls from posttherapeutic HL and DLBCL, respectively. Pairwise comparisons identified 292 wb-miRNAs (adjusted P value < 0.05) showing significant dysregulation between 30 controls and patients; of these, 103 and 169 differentiated controls from pretherapeutic HL and DLBCL, respectively, and 142 and 151 wb-miRNAs differentiated controls from posttherapeutic HL and DLBCL, respectively. Thus, lymphoma-associated miRNAs may be a better source of noninvasive candidate biomarkers than miRNAs in serum. It is unclear whether miRNA alterations in lymphoma cells are similar to those observed in white blood cells.

Identifying and validating blood mRNA biomarkers for acute and chronic insufficient sleep in humans: a machine learning approach

Acute and chronic insufficient sleep are associated with adverse health outcomes and risk of accidents. There is therefore a need for biomarkers to monitor sleep debt status. None are currently available. We applied elastic net and ridge regression to transcriptome samples collected in 36 healthy young adults during acute total sleep deprivation and following 1 week of either chronic insufficient (<6 hr) or sufficient sleep (~8.6 hr) to identify panels of mRNA biomarkers of sleep debt status. The size of identified panels ranged from 9 to 74 biomarkers. Panel performance, assessed by leave-one-subject-out cross-validation and independent validation, varied between sleep debt conditions. Using between-subject assessments based on one blood sample, the accuracy of classifying "acute sleep loss" was 92%, but only 57% for classifying "chronic sleep insufficiency." A reasonable accuracy for classifying "chronic sleep insufficiency" could only be achieved by a within-subject comparison of blood samples. Biomarkers for sleep debt status showed little overlap with previously identified biomarkers for circadian phase. Biomarkers for acute and chronic sleep loss also showed little overlap but were associated with common functions related to the cellular stress response, such as heat shock protein activity, the unfolded protein response, protein ubiquitination and endoplasmic reticulum-associated protein degradation, and apoptosis. This characteristic response of whole blood to sleep loss can further aid our understanding of how sleep insufficiencies negatively affect health. Further development of these novel biomarkers for research and clinical practice requires validation in other protocols and age groups.

Common functional alterations identified in blood transcriptome of autoimmune cholestatic liver and inflammatory bowel diseases

Primary biliary cholangitis (PBC), primary sclerosing cholangitis (PSC), and inflammatory bowel diseases (IBDs), including Crohn’s disease (CD) and ulcerative colitis (UC), are heterogeneous chronic autoimmune diseases that may share underlying pathogenic mechanisms. Herein, we compared simultaneously analyzed blood transcriptomes from patients with PBC, PSC, and IBD. Microarray-based measurements were conducted using RNA isolated from whole blood samples from 90, 45, 95 and 93 patients with PBC, PSC, CD, and UC, respectively, and 47 healthy controls. Expression levels of selected transcripts were analyzed by quantitative reverse-transcribed PCR using an independent cohort of 292, 71 and 727 patients with PBC, PSC, and IBD, respectively. Of 4026, 2650 and 4967 probe sets differentially expressed (adjusted p-value < 0.05) in samples from patients with PBC, PSC, and IBD, respectively, compared with healthy controls, 1946 were common to all three comparisons. Functional analyses indicated that most terms enriched for genes differentially expressed in PBC, PSC, and IBD patients compared with healthy controls were related to mitochondrial function, the vesicle endomembrane system, and GTPase-mediated processes. This study indicates that microarray-based profiling of blood gene expression supports research into the molecular mechanisms underlying disease, rather than being useful for selection of diagnostic biomarkers for use in clinical practice.

Using Next-Generation Sequencing Transcriptomics To Determine Markers of Post-traumatic Symptoms: Preliminary Findings from a Post-deployment Cohort of Soldiers

Post-traumatic stress disorder is a concerning psychobehavioral disorder thought to emerge from the complex interaction between genetic and environmental factors. For soldiers exposed to combat, the risk of developing this disorder is twofold and diagnosis is often late, when much sequela has set in. To be able to identify and diagnose in advance those at “risk” of developing post-traumatic stress disorder, would greatly taper the gap between late sequelae and treatment. Therefore, this study sought to determine whether the transcriptome can be used to track the development of post-traumatic stress disorder in this unique and susceptible cohort of individuals. Gene expression levels in peripheral blood samples from 85 Canadian infantry soldiers (n = 58 participants negative for symptoms of post-traumatic stress disorder and n = 27 participants with symptoms of post-traumatic stress disorder) following return from deployment to Afghanistan were determined using RNA sequencing technology. Count-based gene expression quantification, normalization and differential analysis (with thorough correction for confounders) revealed genes associated to PTSD; LRP8 and GOLM1. These preliminary results provide a proof-of-principle for the diagnostic utility of blood-based gene expression profiles for tracking symptoms of post-traumatic stress disorder in soldiers returning from tour. It is also the first to report transcriptome-wide expression profiles alongside a post-traumatic symptom checklist.

Peripheral Blood Mononuclear Cell Metabolism Acutely Adapted to Postprandial Transition and Mainly Reflected Metabolic Adipose Tissue Adaptations to a High-Fat Diet in Minipigs

Although peripheral blood mononuclear cells (PBMCs) are widely used as a valuable tool able to provide biomarkers of health and diseases, little is known about PBMC functional (biochemistry-based) metabolism, particularly following short-term nutritional challenges. In the present study, the metabolic capacity of minipig PBMCs to respond to nutritional challenges was explored at the biochemical and molecular levels. The changes observed in enzyme activities following a control test meal revealed that PBMC metabolism is highly reactive to the arrival of nutrients and hormones in the circulation. The consumption, for the first time, of a high fat⁻high sucrose (HFHS) meal delayed or sharply reduced most of the observed postprandial metabolic features. In a second experiment, minipigs were subjected to two-month HFHS feeding. The time-course follow-up of metabolic changes in PBMCs showed that most of the adaptations to the new diet took place during the first week. By comparing metabolic (biochemical and molecular) PMBC profiles to those of the liver, skeletal muscle, and adipose tissue, we concluded that although PBMCs conserved common features with all of them, their response to the HFHS diet was closely related to that of the adipose tissue. As a whole, our results show that PBMC metabolism, particularly during short-term (postprandial) challenges, could be used to evaluate the whole-body metabolic status of an individual. This could be particularly interesting for early diagnosis of metabolic disease installation, when fasting clinical analyses fail to diagnose the path towards the pathology.

Predicting position along a looping immune response trajectory

When we get sick, we want to be resilient and recover our original health. To measure resilience, we need to quantify a host's position along its disease trajectory. Here we present Looper, a computational method to analyze longitudinally gathered datasets and identify gene pairs that form looping trajectories when plotted in the space described by these phases. These loops enable us to track where patients lie on a typical trajectory back to health. We analyzed two publicly available, longitudinal human microarray datasets that describe self-resolving immune responses. Looper identified looping gene pairs expressed by human donor monocytes stimulated by immune elicitors, and in YF17D-vaccinated individuals. Using loops derived from training data, we found that we could predict the time of perturbation in withheld test samples with accuracies of 94% in the human monocyte data, and 65-83% within the same cohort and in two independent cohorts of YF17D vaccinated individuals. We suggest that Looper will be useful in building maps of resilient immune processes across organisms.

De novo transcriptome assembly and RNA-Seq expression analysis in blood from beluga whales of Bristol Bay, AK

Assessing the health of marine mammal sentinel species is crucial to understanding the impacts of environmental perturbations on marine ecosystems and human health. In Arctic regions, beluga whales, Delphinapterus leucas, are upper level predators that may serve as a sentinel species, potentially forecasting impacts on human health. While gene expression profiling from blood transcriptomes has widely been used to assess health status and environmental exposures in human and veterinary medicine, its use in wildlife has been limited due to the lack of available genomes and baseline data. To this end we constructed the first beluga whale blood transcriptome de novo from samples collected during annual health assessments of the healthy Bristol Bay, AK stock during 2012-2014 to establish baseline information on the content and variation of the beluga whale blood transcriptome. The Trinity transcriptome assembly from beluga was comprised of 91,325 transcripts that represented a wide array of cellular functions and processes and was extremely similar in content to the blood transcriptome of another cetacean, the bottlenose dolphin. Expression of hemoglobin transcripts was much lower in beluga (25.6% of TPM, transcripts per million) than has been observed in many other mammals. A T12A amino acid substitution in the HBB sequence of beluga whales, but not bottlenose dolphins, was identified and may play a role in low temperature adaptation. The beluga blood transcriptome was extremely stable between sex and year, with no apparent clustering of samples by principle components analysis and <4% of genes differentially expressed (EBseq, FDR<0.05). While the impacts of season, sexual maturity, disease, and geography on the beluga blood transcriptome must be established, the presence of transcripts involved in stress, detoxification, and immune functions indicate that blood gene expression analyses may provide information on health status and exposure. This study provides a wealth of transcriptomic data on beluga whales and provides a sizeable pool of preliminary data for comparison with other studies in beluga whale.

Blood transcriptome based biomarkers for human circadian phase

Diagnosis and treatment of circadian rhythm sleep-wake disorders both require assessment of circadian phase of the brain’s circadian pacemaker. The gold-standard univariate method is based on collection of a 24-hr time series of plasma melatonin, a suprachiasmatic nucleus-driven pineal hormone. We developed and validated a multivariate whole-blood mRNA-based predictor of melatonin phase which requires few samples. Transcriptome data were collected under normal, sleep-deprivation and abnormal sleep-timing conditions to assess robustness of the predictor. Partial least square regression (PLSR), applied to the transcriptome, identified a set of 100 biomarkers primarily related to glucocorticoid signaling and immune function. Validation showed that PLSR-based predictors outperform published blood-derived circadian phase predictors. When given one sample as input, the R² of predicted vs observed phase was 0.74, whereas for two samples taken 12 hr apart, R² was 0.90. This blood transcriptome-based model enables assessment of circadian phase from a few samples.

DOI:http://dx.doi.org/10.7554/eLife.20214.001

RNA-Seq analysis of seasonal and individual variation in blood transcriptomes of healthy managed bottlenose dolphins

Background

The blood transcriptome can reflect both systemic exposures and pathological changes in other organs of the body because immune cells recirculate through the blood, lymphoid tissues, and affected sites. In human and veterinary medicine, blood transcriptome analysis has been used successfully to identify markers of disease or pathological conditions, but can be confounded by large seasonal changes in expression. In comparison, the use of transcriptomic based analyses in wildlife has been limited. Here we report a longitudinal study of four managed bottlenose dolphins located in Waikoloa, Hawaii, serially sampled (approximately monthly) over the course of 1 year to establish baseline information on the content and variation of the dolphin blood transcriptome.

Results

Illumina based RNA-seq analyses were carried out using both the Ensembl dolphin genome and a de novo blood transcriptome as guides. Overall, the blood transcriptome encompassed a wide array of cellular functions and processes and was relatively stable within and between animals over the course of 1 year. Principal components analysis revealed moderate clustering by sex associated with the variation among global gene expression profiles (PC1, 22 % of variance). Limited seasonal change was observed, with < 2.5 % of genes differentially expressed between winter and summer months (FDR < 0.05). Among the differentially expressed genes, cosinor analysis identified seasonal rhythmicity for the observed changes in blood gene expression, consistent with studies in humans. While the proportion of seasonally variant genes in these dolphins is much smaller than that reported in humans, the majority of those identified in dolphins were also shown to vary with season in humans. Gene co-expression network analysis identified several gene modules with significant correlation to age, sex, or hematological parameters.

Conclusions

This longitudinal analysis of healthy managed dolphins establishes a preliminary baseline for blood transcriptome analysis in this species. Correlations with hematological parameters, distinct from muted seasonal effects, suggest that the otherwise relatively stable blood transcriptome may be a useful indicator of health and exposure. A robust database of gene expression in free-ranging and managed dolphins across seasons with known adverse health conditions or contaminant exposures will be needed to establish predictive gene expression profiles suitable for biomonitoring.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3020-8) contains supplementary material, which is available to authorized users.

Genome-Wide Changes in Peripheral Gene Expression following Sports-Related Concussion

We conducted a prospective study to identify genome-wide changes in peripheral gene expression before and after sports-related concussion (SRC). A total of 253 collegiate contact athletes underwent collection of peripheral blood mononuclear cells (PBMCs) before the sport season (baseline). Sixteen athletes who subsequently developed an SRC, along with 16 non-concussed teammate controls, underwent repeat collection of PBMCs within 6 h of injury (acutely). Concussed athletes underwent additional sample collection at 7 days post-injury (sub-acutely). Messenger RNA (mRNA) expression at baseline was compared with mRNA expression acutely and sub-acutely post-SRC. To estimate the contribution of physical exertion to gene changes, baseline samples from athletes who subsequently developed an SRC were compared with samples from uninjured teammate controls collected at the acute time-point. Clinical outcome was determined by changes in post-concussive symptoms, postural stability, and cognition from baseline to the sub-acute time-point. SRC athletes had significant changes in mRNA expression at both the acute and sub-acute time-points. There were no significant expression changes among controls. Acute transcriptional changes centered on interleukins 6 and 12, toll-like receptor 4, and NF-κB. Sub-acute gene expression changes centered on NF-κB, follicle stimulating hormone, chorionic gonadotropin, and protein kinase catalytic subunit. All SRC athletes were clinically back to baseline by Day 7. In conclusion, acute post-SRC transcriptional changes reflect regulation of the innate immune response and the transition to adaptive immunity. By 7 days, transcriptional activity is centered on regulating the hypothalamic-pituitary-adrenal axis. Future efforts to compare expressional changes in fully recovered athletes with those who do not recover from SRC could suggest putative targets for therapeutic intervention.

Effects of genetic and early environmental risk factors for depression on serotonin transporter expression and methylation profiles

The serotonin transporter (SERT) gene-linked polymorphic region (5-HTTLPR) has been implicated in moderating the link between life stress and depression. However, respective molecular pathways of gene-environment (GxE) interaction are largely unknown. Sustained alterations in SERT gene expression profiles, possibly mediated by epigenetic modifications, are a frequent correlate of depression and may thus constitute a putative mediator of GxE interaction. Here, we aimed to investigate joint effects of 5-HTTLPR and self-reported environmental adversity throughout the lifespan (prenatal, early and recent stress/trauma) on in vivo SERT mRNA expression in peripheral blood cells. To further evaluate whether environmentally induced changes in SERT expression are mediated by epigenetic modifications, we analyzed 83 CpG sites within a 799-bp promoter-associated CpG island of the SERT gene using the highly sensitive method of bisulfite pyrosequencing. Participants were 133 healthy young adults. Our findings show that both the 5-HTTLPR S allele and maternal prenatal stress/child maltreatment are associated with reduced in vivo SERT mRNA expression in an additive manner. Remarkably, individuals carrying both the genetic and the environmental risk factors exhibited 32.8% (prenatal stress) and 56.3% (child maltreatment) lower SERT mRNA levels compared with those without any risk factor. Our data further indicated that changes in SERT mRNA levels were unlikely to be mediated by DNA methylation profiles within the SERT CpG island. It is thus conceivable that the persistent changes in SERT expression may in turn relate to altered serotonergic functioning and possibly convey differential disease vulnerability associated with 5-HTTLPR and early adversity.