Geographical, environmental and pathophysiological influences on the human blood transcriptome

Human blood cell transcriptomics unveils dynamic systemic immune modulation along colorectal cancer progression

BACKGROUND

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC deaths can be reduced with prevention and early diagnosis. Circulating tumor DNA-based liquid biopsies, are emerging tools for cancer detection. However, the tumor-signal-dependent nature of this approach results in low sensitivity in precancerous and early CRC stages. Here we propose the host immune response to the onset of cancer as an alternative approach for early detection of CRC.

METHODS

We perform whole transcriptome analysis of peripheral blood mononuclear cells (PBMCs) isolated from individuals with CRC, precancerous lesions or negative colonoscopy in two independent cohorts using next-generation sequencing.

RESULTS

We discover and validate novel early CRC RNA biomarkers. Taking into account, and adjusting for, the sensitivity of PBMCs transcriptomes to processing times, we report distinct transcriptomic changes in the periphery related to specific CRC stages. Activation of innate immunity is already detectable in the peripheral blood of individuals with pre-malignant advanced adenomas. This immune response is followed by signs of transient B-cell activation and sustained inhibition of T-cell responses along CRC progression, whereby at late stages, protumoral myeloid cells, wound healing and coagulation processes prevail. Moreover, some biomarkers show similar dysregulation in tumors and are implicated in known pathways of CRC pathophysiology.

CONCLUSIONS

The strong systemic immune modulation triggered during CRC progression leads to previously unnoticed alterations detectable in PBMCs, paving the way for the development of an early CRC screening blood test, incorporating 226 validated biomarkers identified through immunotranscriptomics.

Expression of Survivin, CK7, ASH1, HMGB3, L587S, and CLCA2 in Peripheral Blood of Lung Cancer Patients by Real-Time Polymerase Chain Reaction

Introduction The objective of the present study was to identify gene expression in peripheral blood by a real-time polymerase chain reaction (PCR) technique in patients who have lung carcinoma. Material and methods Peripheral blood samples of patients with non-small cell and small cell lung cancer were collected. Target genes included survivin, CK7, ASH1, HMGB3, L587S, and CLCA2. β-Actin was the reference gene. If the mean CT (threshold cycle) value for a target gene is ≥40, the gene expression is considered undetectable. Results Fifty patients with lung carcinoma were included and 30 healthy controls. Out of the six genes, survivin showed 26.8 times fold change as compared to controls; ASH1 and L587S were 0.54 and 0.06, respectively; and HMGB3, CLCA2, and CK7 had non-significant fold change in comparison to controls. The overall detection rate of the six target genes examined in lung cancer was 84%, with 42 out of 50 patients testing positive. Higher stages and ASH1 (p = 0.031), CK7 (p = <0.001), and HMGB3, p = 0.011 were associated significantly. CLCA2 had higher expression in patients without adrenal metastases (p = 0.044). Conclusions Lifestyle and geographical variation might be a probable cause of variable gene expression as compared to other studies. However, further research is needed to determine the clinical implication of these markers, especially in larger groups of early-stage patients.

Sleep disturbances and inflammatory gene expression among pregnant women: Differential responses by race

Excessive inflammation in pregnancy predicts adverse birth outcomes, including shortened gestational length and lower birthweight, with African American women at greater risk. As substantial racial disparities in sleep quality, and evidence that African Americans have increased vulnerability for sleep-induced inflammatory dysregulation, sleep may be a critical, modifiable health behavior that contributes to racial disparities in birth outcomes. The present study examined sleep disturbance as a predictor of genome-wide transcriptome profiles of peripheral blood samples from 103 pregnant women (33 African American, 70 white) assessed at 18.7 ± 7.2 weeks gestation. We hypothesized that pregnant women with significant sleep disturbances would have gene expression profiles indicating over-expression of inflammatory pathways, with greater effects among African American compared to white women. Promoter-based bioinformatics analyses of differentially expressed genes indicated greater activation of NF-кB, AP1, and CREB transcription factors among African American women with sleep disturbances (all p < 0.05), and enhanced activation of AP1, but not NF-кB and reduced CREB activity among white women with sleep disturbances (p < 0.05). Differences in glucocorticoid receptor (GR) activity were also observed, in which African American women with sleep disturbances had reduced GR activity (p < 0.05), but white women with sleep disturbances showed a trend for enhanced GR activity (p = 0.11). Similarly, Interferon Response Factor (IRF) activity was reduced in African American women while increased in white women with sleep disturbances (p < 0.05). The current study provides novel evidence for gene expression related to inflammation, glucocorticoids, and anti-viral immunity among pregnant women with sleep disturbances, with differential effects by race. African Americans showed greater breadth and magnitude in these proinflammatory and anti-viral pathways than whites, with divergence in anti-inflammatory glucocorticoid, proinflammatory adrenergic-mediated cAMP, and anti-viral interferon responses. These data elucidate the role of sleep disturbances in intracellular inflammatory and anti-viral immunity in pregnancy and provide a potential target for intervention.

Expression of socially sensitive genes: The multi-ethnic study of atherosclerosis

BACKGROUND

Gene expression may be an important biological mediator in associations between social factors and health. However, previous studies were limited by small sample sizes and use of differing cell types with heterogeneous expression patterns. We use a large population-based cohort with gene expression measured solely in monocytes to investigate associations between seven social factors and expression of genes previously found to be sensitive to social factors.

METHODS

We employ three methodological approaches: 1) omnibus test for the entire gene set (Global ANCOVA), 2) assessment of each association individually (linear regression), and 3) machine learning method that performs variable selection with correlated predictors (elastic net).

RESULTS

In global analyses, significant associations with the a priori defined socially sensitive gene set were detected for major or lifetime discrimination and chronic burden (p = 0.019 and p = 0.047, respectively). Marginally significant associations were detected for loneliness and adult socioeconomic status (p = 0.066, p = 0.093, respectively). No associations were significant in linear regression analyses after accounting for multiple testing. However, a small percentage of gene expressions (up to 11%) were associated with at least one social factor using elastic net.

CONCLUSION

The Global ANCOVA and elastic net findings suggest that a small percentage of genes may be "socially sensitive," (i.e. demonstrate differential expression by social factor), yet single gene approaches such as linear regression may be ill powered to capture this relationship. Future research should further investigate the biological mechanisms through which social factors act to influence gene expression and how systemic changes in gene expression affect overall health.

HEROD: a human ethnic and regional specific omics database

Motivation

Genetic and gene expression variations within and between populations and across geographical regions have substantial effects on the biological phenotypes, diseases, and therapeutic response. The development of precision medicines can be facilitated by the OMICS studies of the patients of specific ethnicity and geographic region. However, there is an inadequate facility for broadly and conveniently accessing the ethnic and regional specific OMICS data.

Results

Here, we introduced a new free database, HEROD, a human ethnic and regional specific OMICS database. Its first version contains the gene expression data of 53 070 patients of 169 diseases in seven ethnic populations from 193 cities/regions in 49 nations curated from the Gene Expression Omnibus (GEO), the ArrayExpress Archive of Functional Genomics Data (ArrayExpress), the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Geographic region information of curated patients was mainly manually extracted from referenced publications of each original study. These data can be accessed and downloaded via keyword search, World map search, and menu-bar search of disease name, the international classification of disease code, geographical region, location of sample collection, ethnic population, gender, age, sample source organ, patient type (patient or healthy), sample type (disease or normal tissue) and assay type on the web interface.

Availability and implementation

The HEROD database is freely accessible at http://bidd2.nus.edu.sg/herod/index.php. The database and web interface are implemented in MySQL, PHP and HTML with all major browsers supported.

Contact

phacyz@nus.edu.sg.

Genetic Architecture of Sexual Dimorphism in Humans

Males and females differ across a broad spectrum of morphological, physiological, and behavioral characters. In fact, sexually dimorphic traits typically contribute the largest component of phenotypic variance in most taxa that use sex to reproduce. However, we know very little about the mechanisms that maintain these dimorphic states and how these sexually dimorphic traits evolve. Here, we review our current knowledge of the underlying genetic basis of sexual dimorphism in humans. First, we briefly review the etiology of sex differences starting from sex determination's initial switch early in embryogenesis. We then survey recent sex-biased transcriptomic expression literature in order to provide additional insight into the landscape of sex-biased gene expression in both gonadal and non-gonadal tissues: from overall prevalence to tissue specificity to conservation across species. Finally, we discuss implications of sex-biased genetic architecture to human health and disease in light of the National Institute of Health's recently proposed initiative to promote study samples from both sexes.