Seasonal changes in gene expression represent cell-type composition in whole blood

A guide to systems-level immunomics

The immune system is highly complex and distributed throughout an organism, with hundreds to thousands of cell states existing in parallel with diverse molecular pathways interacting in a highly dynamic and coordinated fashion. Although the characterization of individual genes and molecules is of the utmost importance for understanding immune-system function, high-throughput, high-resolution omics technologies combined with sophisticated computational modeling and machine-learning approaches are creating opportunities to complement standard immunological methods with new insights into immune-system dynamics. Like systems immunology itself, immunology researchers must take advantage of these technologies and form their own diverse networks, connecting with researchers from other disciplines. This Review is an introduction and 'how-to guide' for immunologists with no particular experience in the field of omics but with the intention to learn about and apply these systems-level approaches, and for immunologists who want to make the most of interdisciplinary networks.

Impacts of seasonality on gene expression in the Chinese horseshoe bat

Seasonality can cause changes in many environmental factors which potentially affects gene expression. Here, we used a bat species (Rhinolophus sinicus) from eastern China as a model to explore the molecular mechanisms of seasonal effects, in particular during phenological shifts in the spring and autumn. Based on the analysis of 45 RNA‐seq samples, we found strong seasonal effects on gene expression, with a large number of genes identified as either specific or biased to each season. Weighted gene co‐expression network analysis also identified multiple modules significantly associated with each season. These seasonal genes were further enriched into different functional categories. Consistent with effects of phenological shifts on bats, we found that genes related to promoting food intake were highly expressed in both autumn and spring. In addition, immunity genes were also highly expressed in both seasons although this seasonal immune response had tissue specificity in different seasons. In female bats, genes related to the delay of ovulation (e.g., NPPC, natriuretic peptide precursor type C) were highly expressed in October, while genes associated with the promotion of reproduction (e.g., DIO2, iodothyronine deiodinase 2) were biasedly expressed in April. Lastly, we found multiple known core clock genes in both October‐biased and April‐biased expressed genes, which may be involved in regulating the start and end of hibernation, respectively. Overall, together with studies in other land and aquatic animals, our work supports that seasonal gene expression variations may be a general evolutionary response to environmental changes in wild animals.

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.

Whole blood gene expression signature in patients with obstructive sleep apnea and effect of continuous positive airway pressure treatment

The molecular mechanisms of obstructive sleep apnea (OSA), in particular the gene expression patterns in whole blood of patients with OSA, can shed more light on the underlying pathophysiology of OSA and suggest potential biomarkers. In the current study, we have enrolled thirty patients with untreated moderate-severe OSA together with 20 BMI, age, and sex-matched controls and 15 normal-weight controls. RNA-sequencing of whole blood and home sleep apnea testing were performed in the untreated state and after three and twelve months of continuous positive airway pressure (CPAP) treatment. Analysis of the whole blood transcriptome of the patients with OSA revealed a unique pattern of differential expression with a significant number of downregulated immune-related genes including many heavy and light chain immunoglobulins and interferon-inducible genes. This was confirmed by the gene ontology analysis demonstrating enrichment with the biological processes associated with various immune functions. Expression of these genes was recovered after three months of CPAP treatment. After 12 months of CPAP treatment, the overall gene expression profile returns to the initial, untreated level. In addition, we have confirmed the importance of choosing BMI-matched controls as a reference group as opposed to normal-weight healthy individuals based on the significantly different gene expression signatures between these two groups.

Cytokine levels in children and adults with wheezing and asthma show specific patterns of variability over time

Levels of cytokines are used for in-depth characterization of patients with asthma; however, the variability over time might be a critical confounder. To analyze the course of serum cytokines in children, adolescents and adults with asthma and in healthy controls and to propose statistical methods to control for seasonal effects. Of 532 screened subjects, 514 (91·5%) were included in the All Age Asthma Cohort (ALLIANCE). The cohort included 279 children with either recurrent wheezing bronchitis (more than two episodes) or doctor-diagnosed asthma, 75 healthy controls, 150 adult asthmatics and 31 adult healthy controls. Blood samples were collected and 25 μl serum was used for analysis with the Bio-Plex Pr human cytokine 27-Plex assay. Mean age, body mass index and gender in the three groups of wheezers, asthmatic children and adult asthmatics were comparable to healthy controls. Wheezers (34·5%), asthmatic children (78·7%) and adult asthmatics (62·8%) were significantly more often sensitized compared to controls (4·5, 22 and 22·6%, respectively). Considering the entire cohort, interleukin (IL)-1ra, IL-4, IL-9, IL-17, macrophage inflammatory protein (MIP)-1- α and tumor necrosis factor (TNF)- α showed seasonal variability, whereas IL-1β, IL-7, IL-8, IL-13, eotaxin, granulocyte colony-stimulating factor (G-CSF), interferon gamma-induced protein (IP)-10, MIP-1 β and platelet-derived growth factor (PDGF)-BB did not. Significant differences between wheezers/asthmatics and healthy controls were observed for IL-17 and PDGF-BB, which remained stable after adjustment for the seasonality of IL-17. Seasonality has a significant impact on serum cytokine levels in patients with asthma. Because endotyping has achieved clinical importance to guide individualized patient-tailored therapy, it is important to account for seasonal effects.

The Human Blood Transcriptome in a Large Population Cohort and Its Relation to Aging and Health

Background: The blood transcriptome is expected to provide a detailed picture of an organism's physiological state with potential outcomes for applications in medical diagnostics and molecular and epidemiological research. We here present the analysis of blood specimens of 3,388 adult individuals, together with phenotype characteristics such as disease history, medication status, lifestyle factors, and body mass index (BMI). The size and heterogeneity of this data challenges analytics in terms of dimension reduction, knowledge mining, feature extraction, and data integration.

Methods: Self-organizing maps (SOM)-machine learning was applied to study transcriptional states on a population-wide scale. This method permits a detailed description and visualization of the molecular heterogeneity of transcriptomes and of their association with different phenotypic features.

Results: The diversity of transcriptomes is described by personalized SOM-portraits, which specify the samples in terms of modules of co-expressed genes of different functional context. We identified two major blood transcriptome types where type 1 was found more in men, the elderly, and overweight people and it upregulated genes associated with inflammation and increased heme metabolism, while type 2 was predominantly found in women, younger, and normal weight participants and it was associated with activated immune responses, transcriptional, ribosomal, mitochondrial, and telomere-maintenance cell-functions. We find a striking overlap of signatures shared by multiple diseases, aging, and obesity driven by an underlying common pattern, which was associated with the immune response and the increase of inflammatory processes.

Conclusions: Machine learning applications for large and heterogeneous omics data provide a holistic view on the diversity of the human blood transcriptome. It provides a tool for comparative analyses of transcriptional signatures and of associated phenotypes in population studies and medical applications.

Seasonal variation of human physiology does not influence the harvest of peripheral blood CD34+ cells from unrelated hematopoietic stem cell donors

There are many reports on factors predicting the outcome of PBSC (peripheral blood stem cell) mobilization, such as the donor's gender, age, weight, white blood cell count, platelets pre apheresis, LDH and iron status. Although there are reports of seasonal variation in the physiology of the human immune system and hematopoiesis there are no data that such differences play a role in the response to G-CSF in healthy hematopoietic stem cell donors. The response to G-CSF could also impact the collection results during different seasons. To assess the possible impact of seasonal variation we performed a retrospective, single-center analysis of mobilization and harvest of PBSC in 330 healthy unrelated donors. We found no significant differences in the number of CD34+ cells in peripheral blood after G-CSF mobilization and in collection results when all donors were analyzed. In the subgroup of male donors the number of CD34+ stem cells after G-CSF mobilization was higher than average in summer and autumn (p = 0.036), however, it did not translate into clinically relevant differences in stem cell harvest. We conclude that although there is possible seasonal variation in the response to G-CSF in male donors there is no impact on PBSC harvest in healthy unrelated donors.

Seasonally variant gene expression in full-term human placenta

Seasonal exposures influence human health and development. The placenta, as a mediator of the maternal and fetal systems and a regulator of development, is an ideal tissue to understand the biological pathways underlying relationships between season of birth and later life health outcomes. Here, we conducted a differential expression (DE) analysis of season of birth in full-term human placental tissue to evaluate whether the placenta may be influenced by seasonal cues. Of the analyzed transcripts, 583 displayed DE between summer and winter births (False Discovery Rate [FDR] q < .05); among these, BHLHE40, MIR210HG, and HILPDA had increased expression among winter births (Bonferroni P < .05). Enrichment analyses of the seasonally variant genes between summer and winter births indicated overrepresentation of transcription factors HIF1A, VDR, and CLOCK, among others, and of GO term pathways related to ribosomal activity and infection. Additionally, a cosinor analysis found rhythmic expression for approximately 11.9% of all 17 664 analyzed placental transcripts. These results suggest that the placenta responds to seasonal cues and add to the growing body of evidence that the placenta acts as a peripheral clock, which may provide a molecular explanation for the extensive associations between season of birth and health outcomes.

Genetic regulation of gene expression and splicing during a 10-year period of human aging

BACKGROUND

Molecular and cellular changes are intrinsic to aging and age-related diseases. Prior cross-sectional studies have investigated the combined effects of age and genetics on gene expression and alternative splicing; however, there has been no long-term, longitudinal characterization of these molecular changes, especially in older age.

RESULTS

We perform RNA sequencing in whole blood from the same individuals at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging at a population and individual level. We observe that individuals are more similar to their own expression profiles later in life than profiles of other individuals their own age. We identify 1291 and 294 genes differentially expressed and alternatively spliced with age, as well as 529 genes with outlying individual trajectories. Further, we observe a strong correlation of genetic effects on expression and splicing between the two ages, with a small subset of tested genes showing a reduction in genetic associations with expression and splicing in older age.

CONCLUSIONS

These findings demonstrate that, although the transcriptome and its genetic regulation is mostly stable late in life, a small subset of genes is dynamic and is characterized by a reduction in genetic regulation, most likely due to increasing environmental variance with age.

Spring peaks and autumn troughs identified in peripheral inflammatory markers during the peripartum period

Seasonal variations have recently been described in biomarkers, cell types, and gene expression associated with the immune system, but so far no studies have been conducted among women in the peripartum period. It is of note that pregnancy complications and outcomes, as well as autoimmune diseases, have also been reported to exhibit seasonal fluctuations. We report here a clear-cut seasonal pattern of 23 inflammatory markers, analysed using proximity-extension assay technology, in pregnant women. The inflammatory markers generally peaked in the spring and had a trough in the autumn. During the postpartum period we found seasonality in one inflammatory marker, namely monocyte chemotactic protein 4 (MCP-4). Our findings suggest that seasonal variations in peripheral inflammatory markers are only observed during pregnancy. The results of this study could be valuable to professionals working within the field of immunology-related areas, and provide insight for the understanding of obstetric complications.

Profound but Transient Changes in the Inflammatory Milieu of the Blood During Autologous Hematopoietic Stem Cell Transplantation

Little is known about the inflammatory milieu in the blood during autologous hematopoietic stem cell transplantation (AHSCT) and how it is affected by the stem cell mobilization, collection, and reinfusion and conditioning regimen. In this study, we analyzed 92 proteins connected to inflammation at 10 time points during and after AHSCT in 16 patients with multiple sclerosis (MS). Serum from 29 patients with newly diagnosed MS and 15 healthy controls were included for comparative analysis. There were no significant differences in inflammatory serum protein levels between patients with newly diagnosed MS and healthy controls, but 29 out of 73 detectable proteins were significantly altered between at least 2 adjacent sampling time points during AHSCT. The predominant changes occurred after the conditioning regimen had been administered, whereas stem cell mobilization, collection, and reinfusion appeared to have less impact. Two distinct response patterns could be discerned, likely representing loss of basal cytokine production and homeostasis. The analyzed serum proteins gradually returned to baseline levels after treatment, with no remaining differences at 3 months after AHSCT. We conclude that treatment with AHSCT has a major but transient impact on the inflammatory milieu of peripheral blood.

Blood plasma metabolic profiling of pregnant women with antenatal depressive symptoms

Antenatal depression affects ~9-19% of pregnant women and can exert persistent adverse effects on both mother and child. There is a need for a deeper understanding of antenatal depression mechanisms and the development of tools for reliable diagnosis and early identification of women at high risk. As the use of untargeted blood metabolomics in the investigation of psychiatric and neurological diseases has increased substantially, the main objective of this study was to investigate whether untargeted gas chromatography-mass spectrometry (GC-MS) plasma metabolomics in 45 women in late pregnancy, residing in Uppsala, Sweden, could indicate metabolic differences between women with and without depressive symptoms. Furthermore, seasonal differences in the metabolic profiles were explored. When comparing the profiles of cases with controls, independently of season, no differences were observed. However, seasonal differences were observed in the metabolic profiles of control samples, suggesting a favorable cardiometabolic profile in the summer vs. winter, as indicated by lower glucose and sugar acid concentrations and lactate to pyruvate ratio, and higher abundance of arginine and phosphate. Similar differences were identified between cases and controls among summer pregnancies, indicating an association between a stressed metabolism and depressive symptoms. No depression-specific differences were apparent among depressed and non-depressed women, in the winter pregnancies; this could be attributed to an already stressed metabolism due to the winter living conditions. Our results provide new insights into the pathophysiology of antenatal depression, and warrant further investigation of the use of metabolomics in antenatal depression in larger cohorts.

Systems Immunology: Learning the Rules of the Immune System

Given the many cell types and molecular components of the human immune system, along with vast variations across individuals, how should we go about developing causal and predictive explanations of immunity? A central strategy in human studies is to leverage natural variation to find relationships among variables, including DNA variants, epigenetic states, immune phenotypes, clinical descriptors, and others. Here, we focus on how natural variation is used to find patterns, infer principles, and develop predictive models for two areas: (a) immune cell activation-how single-cell profiling boosts our ability to discover immune cell types and states-and (b) antigen presentation and recognition-how models can be generated to predict presentation of antigens on MHC molecules and their detection by T cell receptors. These are two examples of a shift in how we find the drivers and targets of immunity, especially in the human system in the context of health and disease.

Spring is in the air: seasonal profiles indicate vernal change of miRNA activity

The envisioned application of miRNAs as diagnostic or prognostic biomarkers calls for an in-depth understanding of their distribution and variability in different physiological states. While effects with respect to ethnic origin, age, or gender are known, the inter-individual variability of miRNAs across the four seasons remained largely hidden. We sequentially profiled the complete repertoire of blood-borne miRNAs for 25 physiologically normal individuals in spring, summer, fall, and winter (altogether 95 samples) and validated the results on 292 individuals (919 samples collected with the Mitra home sampling device) by RT-qPCR. Principal variance component analysis suggests that the largest variability observed in miRNA expression is due to individual variability and the individuals' gender. But the results also highlight a deviation of miRNA activity in samples collected during spring time. Following adjustment for multiple testing, remarkable differences are observed between spring and fall (77 miRNAs). The two most dys-regulated miRNAs were miR-181c-5p and miR-106b-5p (adjusted p-value of 0.007). Other significant miRNAs include miR-140-3p, miR-21-3p, and let-7c-5p. The dys-regulation was validated by RT-qPCR. Systems biology analysis further provides strong evidence for the immunological origin of the signals: dys-regulated miRNAs are enriched in CD56 cells and belong to various signalling and immune-system-related pathways. Our data suggest that besides known confounding factors such as age and sex, also the season in which a test is conducted might have a considerable influence on the expression of blood-borne miRNAs and subsequently might interfere with diagnosis based on such signatures.

Biological variables influencing the estimation of reference limits

Reference limits (RLs) are required to evaluate laboratory results for medical decisions. The establishment of RL depends on the pre-analytical and the analytical conditions. Furthermore, biological characteristics of the sub-population chosen to provide the reference samples may influence the RL. The most important biological preconditions are gender, age, chronobiological influences, posture, regional and ethnic effects. The influence of these components varies and is often neglected. Therefore, a list of biological variables is collected from the literature and their influence on the estimation of RL is discussed. Biological preconditions must be specified if RL are reported as well for directly as for indirectly estimated RL. The influence of biological variables is especially important if RL established by direct methods are compared with those derived from indirect techniques. Even if these factors are not incorporated into the estimation of RL, their understanding can assist the interpretation of laboratory results of an individual.

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.

Modeling Seasonal and Spatiotemporal Variation: The Example of Respiratory Prescribing

Many measures of chronic diseases, including respiratory disease, exhibit seasonal variation together with residual correlation between consecutive time periods and neighboring areas. We demonstrate a strategy for modeling data that exhibit both seasonal trend and spatiotemporal correlation, using an application to respiratory prescribing. We analyzed 55 months (2002-2006) of prescribing data from the northeast of England, in the United Kingdom. We estimated the seasonal pattern of prescribing by fitting a dynamic harmonic regression (DHR) model to salbutamol prescribing in relation to temperature. We compared the output of DHR models to static sinusoidal regression models. We used the DHR-fitted values as an offset in mixed-effects models that aimed to account for the remaining spatiotemporal variation in prescribing rates. As diagnostic checks, we assessed spatial and temporal correlation separately and jointly. Our application of a DHR model resulted in a better fit to the seasonal variation of prescribing than was obtained with a static model. After adjusting for the fitted values from the DHR model, we did not detect any remaining spatiotemporal correlation in the model's residuals. Using a DHR model and temperature data to account for the periodicity of prescribing proved to be an efficient way to capture its seasonal variation. The diagnostic procedures indicated that there was no need to model any remaining correlation explicitly.

Host and Environmental Factors Influencing Individual Human Cytokine Responses

Differences in susceptibility to immune-mediated diseases are determined by variability in immune responses. In three studies within the Human Functional Genomics Project, we assessed the effect of environmental and non-genetic host factors of the genetic make-up of the host and of the intestinal microbiome on the cytokine responses in humans. We analyzed the association of these factors with circulating mediators and with six cytokines after stimulation with 19 bacterial, fungal, viral, and non-microbial metabolic stimuli in 534 healthy subjects. In this first study, we show a strong impact of non-genetic host factors (e.g., age and gender) on cytokine production and circulating mediators. Additionally, annual seasonality is found to be an important environmental factor influencing cytokine production. Alpha-1-antitrypsin concentrations partially mediate the seasonality of cytokine responses, whereas the effect of vitamin D levels is limited. The complete dataset has been made publicly available as a comprehensive resource for future studies. PAPERCLIP.

Values of apoptosis of lymphocytes and granulocytes in peripheral blood of Polish mixed-breed rabbits in the annual cycle

The objective of the study was to determine values of apoptosis for peripheral blood lymphocytes and granulocytes, including dependency on the season of the year, in Polish mixed-breed rabbits and in mixed-breed rabbits with the addition of blood of meat-breed rabbits. The study was carried out in four seasons of the year (spring, summer, autumn, winter) involving 120 Polish mixed-breed rabbits - group I, and 120 Polish mixed-breed rabbits with addition of meat-breed rabbit blood - group II. Assessment of apoptosis of lymphocytes and granulocytes was performed using as FACScan cytometer by Becton Dickinson with FACSDiva software (USA), using as ApoFluor® Green Caspase reagent kit (MP Biomedicals, USA) to detect the activity of the total caspase pool 1, 3, 4, 5, 6, 7, 8, 9 in granulocytes and lymphocytes of rabbit peripheral blood. The results for apoptosis of lymphocytes and granulocytes in peripheral blood in the animals investigated (group I and II) were subjected to statistical analysis with the t'Student test at p=0.05. It was noted that, in rabbits from group I, the values for apoptosis of lymphocytes were the highest in winter and autumn (36.02% and 31.24%, respectively), and the lowest in spring and summer (26.73% and 22.72%, respectively), whereas in the case of granulocytes the highest values were in summer and spring (14.69% and 12.95%, respectively), and the lowest in winter and autumn (8.16% and 8.57%, respectively). In mixed-breed rabbits with the addition of meat-breed blood (group II), the values for apoptosis of lympocytes were the highest in spring (29.13%), and the lowest in summer (25.43%); whereas in the case of granulocytes the highest values were in summer and spring (14.0% and 11.15%, respectively), and the lowest in autumn and winter (7.46% and 7.64%, respectively).

Human immune system variation

The human immune system is highly variable between individuals but relatively stable over time within a given person. Recent conceptual and technological advances have enabled systems immunology analyses, which reveal the composition of immune cells and proteins in populations of healthy individuals. The range of variation and some specific influences that shape an individual's immune system is now becoming clearer. Human immune systems vary as a consequence of heritable and non-heritable influences, but symbiotic and pathogenic microbes and other non-heritable influences explain most of this variation. Understanding when and how such influences shape the human immune system is key for defining metrics of immunological health and understanding the risk of immune-mediated and infectious diseases.

Peripheral blood gene expression profiles linked to monoamine metabolite levels in cerebrospinal fluid

The blood-brain barrier separates circulating blood from the central nervous system (CNS). The scope of this barrier is not fully understood which limits our ability to relate biological measurements from peripheral to central phenotypes. For example, it is unknown to what extent gene expression levels in peripheral blood are reflective of CNS metabolism. In this study, we examine links between central monoamine metabolite levels and whole-blood gene expression to better understand the connection between peripheral systems and the CNS. To that end, we correlated the prime monoamine metabolites in cerebrospinal fluid (CSF) with whole-genome gene expression microarray data from blood (N=240 human subjects). We additionally applied gene-enrichment analysis and weighted gene co-expression network analyses (WGCNA) to identify modules of co-expressed genes in blood that may be involved with monoamine metabolite levels in CSF. Transcript levels of two genes were significantly associated with CSF serotonin metabolite levels after Bonferroni correction for multiple testing: THAP7 (P=2.8 × 10^-8, β=0.08) and DDX6 (P=2.9 × 10^-7, β=0.07). Differentially expressed genes were significantly enriched for genes expressed in the brain tissue (P=6.0 × 10^-52). WGCNA revealed significant correlations between serotonin metabolism and hub genes with known functions in serotonin metabolism, for example, HTR2A and COMT. We conclude that gene expression levels in whole blood are associated with monoamine metabolite levels in the human CSF. Our results, including the strong enrichment of brain-expressed genes, illustrate that gene expression profiles in peripheral blood can be relevant for quantitative metabolic phenotypes in the CNS.

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.

Seasonal Variations of Complete Blood Count and Inflammatory Biomarkers in the US Population - Analysis of NHANES Data

Background

Recent studies reported seasonal differences in gene expression in white blood cells, adipose tissue, and inflammatory biomarkers of the immune system. There is no data on the seasonal variations of these biomarkers in the US general population of both children and adults. Then aim of this study is to explore the seasonal trends in complete blood count (CBC), and C-reactive protein (CRP) in a large non-institutionalized US population.

Methods

Seven cross-sectional data collected in the National Health and Nutrition Examination Survey (NHANES) during 1999–2012 were aggregated; participants reporting recent use of prescribed steroids, chemotherapy, immunomodulators and antibiotics were excluded. Linear regression models were used to compare levels of CBC and CRP between winter-spring (November-April) and summer-fall (May-October), adjusting for demographics, personal behavioral factors, and chronic disease conditions.

Results

A total of 27,478 children and 36,644 adults (≥18 years) were included in the study. Levels of neutrophils, white blood cell count (WBC), and CRP were higher in winter-spring than summer-fall (p≤0.05). Red blood cell components were lower in winter-spring than in summer-fall, while the opposite was seen for platelets.

Conclusions

This large population-based study found notable seasonal variations in blood cell composition and inflammatory biomarkers, with a more pro-inflammatory immune system seen in winter-spring than summer-fall. The red blood cell patterns could have implications for the observed cardio-vascular seasonality.

Reduced gene expression levels after chronic exposure to high concentrations of air pollutants

We analyzed the ability of particulate matter (PM) and chemicals adsorbed onto it to induce diverse gene expression profiles in subjects living in two regions of the Czech Republic differing in levels and sources of the air pollution. A total of 312 samples from polluted Ostrava region and 154 control samples from Prague were collected in winter 2009, summer 2009 and winter 2010. The highest concentrations of air pollutants were detected in winter 2010 when the subjects were exposed to: PM of aerodynamic diameter <2.5μm (PM2.5) (70 vs. 44.9μg/m(3)); benzo[a]pyrene (9.02 vs. 2.56ng/m(3)) and benzene (10.2 vs. 5.5μg/m(3)) in Ostrava and Prague, respectively. Global gene expression analysis of total RNA extracted from leukocytes was performed using Illumina Expression BeadChips microarrays. The expression of selected genes was verified by quantitative real-time PCR (qRT-PCR). Gene expression profiles differed by locations and seasons. Despite lower concentrations of air pollutants a higher number of differentially expressed genes and affected KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways was found in subjects from Prague. In both locations immune response pathways were affected, in Prague also neurodegenerative diseases-related pathways. Over-representation of the latter pathways was associated with the exposure to PM2.5. The qRT-PCR analysis showed a significant decrease in expression of APEX, ATM, FAS, GSTM1, IL1B and RAD21 in subjects from Ostrava, in a comparison of winter 2010 and summer 2009. In Prague, an increase in gene expression was observed for GADD45A and PTGS2. In conclusion, high concentrations of pollutants in Ostrava were not associated with higher number of differentially expressed genes, affected KEGG pathways and expression levels of selected genes. This observation suggests that chronic exposure to air pollution may result in reduced gene expression response with possible negative health consequences.

Common Aging Signature in the Peripheral Blood of Vascular Dementia and Alzheimer's Disease

Alzheimer's disease (AD) and vascular dementia (VaD) are the two most dominant forms of dementia in elderly people. Due to the large overlap between AD and VaD in clinical observations, great controversies exist regarding the distinction and connection between these two types of senile dementia. Here for the first time, we resort to the gene expression pattern of the peripheral blood to compare AD and VaD objectively. In our previous work, we have demonstrated that the dysregulation of gene expression in AD is unique among the examined diseases including neurological diseases, cancer, and metabolic diseases. In this study, we found that the dysregulation of gene expression in AD and VaD is quite similar to each other at both functional and gene levels. Interestingly, the dysregulation started at the early stages of the diseases, namely mild cognitive impairment (MCI) and vascular cognitive impairment (VCI). We have also shown that this signature is distinctive from that of peripheral vascular diseases. Comparison with aging studies revealed that the most profound change in AD and VaD, namely ribosome, is consistent with the accelerated aging scenario. This study may have implications to the common mechanism between AD and VaD.

Seasonal effects on gene expression

Many health conditions, ranging from psychiatric disorders to cardiovascular disease, display notable seasonal variation in severity and onset. In order to understand the molecular processes underlying this phenomenon, we have examined seasonal variation in the transcriptome of 606 healthy individuals. We show that 74 transcripts associated with a 12-month seasonal cycle were enriched for processes involved in DNA repair and binding. An additional 94 transcripts demonstrated significant seasonal variability that was largely influenced by blood cell count levels. These transcripts were enriched for immune function, protein production, and specific cellular markers for lymphocytes. Accordingly, cell counts for erythrocytes, platelets, neutrophils, monocytes, and CD19 cells demonstrated significant association with a 12-month seasonal cycle. These results demonstrate that seasonal variation is an important environmental regulator of gene expression and blood cell composition. Notable changes in leukocyte counts and genes involved in immune function indicate that immune cell physiology varies throughout the year in healthy individuals.

Widespread seasonal gene expression reveals annual differences in human immunity and physiology

Seasonal variations are rarely considered a contributing component to human tissue function or health, although many diseases and physiological process display annual periodicities. Here we find more than 4,000 protein-coding mRNAs in white blood cells and adipose tissue to have seasonal expression profiles, with inverted patterns observed between Europe and Oceania. We also find the cellular composition of blood to vary by season, and these changes, which differ between the United Kingdom and The Gambia, could explain the gene expression periodicity. With regards to tissue function, the immune system has a profound pro-inflammatory transcriptomic profile during European winter, with increased levels of soluble IL-6 receptor and C-reactive protein, risk biomarkers for cardiovascular, psychiatric and autoimmune diseases that have peak incidences in winter. Circannual rhythms thus require further exploration as contributors to various aspects of human physiology and disease.

An integrative multi-scale analysis of the dynamic DNA methylation landscape in aging

Recent studies have demonstrated that the DNA methylome changes with age. This epigenetic drift may have deep implications for cellular differentiation and disease development. However, it remains unclear how much of this drift is functional or caused by underlying changes in cell subtype composition. Moreover, no study has yet comprehensively explored epigenetic drift at different genomic length scales and in relation to regulatory elements.

Here we conduct an in-depth analysis of epigenetic drift in blood tissue. We demonstrate that most of the age-associated drift is independent of the increase in the granulocyte to lymphocyte ratio that accompanies aging and that enrichment of age-hypermethylated CpG islands increases upon adjustment for cellular composition. We further find that drift has only a minimal impact on in-cis gene expression, acting primarily to stabilize pre-existing baseline expression levels. By studying epigenetic drift at different genomic length scales, we demonstrate the existence of mega-base scale age-associated hypomethylated blocks, covering approximately 14% of the human genome, and which exhibit preferential hypomethylation in age-matched cancer tissue. Importantly, we demonstrate the feasibility of integrating Illumina 450k DNA methylation with ENCODE data to identify transcription factors with key roles in cellular development and aging. Specifically, we identify REST and regulatory factors of the histone methyltransferase MLL complex, whose function may be disrupted in aging.

In summary, most of the epigenetic drift seen in blood is independent of changes in blood cell type composition, and exhibits patterns at different genomic length scales reminiscent of those seen in cancer. Integration of Illumina 450k with appropriate ENCODE data may represent a fruitful approach to identify transcription factors with key roles in aging and disease.

Two well-known features of aging are the gradual decline of the body’s ability to regenerate tissues, as well as an increased incidence of diseases like cancer and Alzheimers. One of the most recent exciting findings which may underlie the aging process is a gradual modification of DNA, called epigenetic drift, which is effected by the covalent addition and removal of methyl groups, which in turn can deregulate the activity of nearby genes. However, this study presents the most convincing evidence to date that epigenetic drift acts to stabilize the activity levels of nearby genes. This study shows that instead, epigenetic drift may act primarly to disrupt DNA binding patterns of proteins which regulate the activity of many genes, and moreover identifies specific regulatory proteins with key roles in cancer and Alzheimers. The study also performs the most comprehensive analysis of epigenetic drift at different spatial scales, demonstrating that epigenetic drift on the largest length scales is highly reminiscent of those seen in cancer. In summary, this work substantially supports the view that epigenetic drift may contribute to the age-associated increased risk of diseases like cancer and Alzheimers, by disrupting master regulators of genomewide gene activity.