Identification of characteristic molecular signature for volatile organic compounds in peripheral blood of rat

Association of volatile organic compounds exposure with the risk of depression in U.S. adults: a cross‑sectional study from NHANES 2013-2016

BACKGROUND

Volatile organic compounds (VOCs) are a broad class of chemicals, and previous studies showed that VOCs could increase the risk of central nervous system disorders. However, few studies have comprehensively explored their association with depression among general adults.

OBJECTIVE

We aimed to explore the association between blood VOCs and depression risk based on a large cross-sectional study of the National Health and Nutrition Examination Survey (NHANES).

METHODS

We analyzed data from 3449 American adults in the NHANES 2013-2016. Survey-weighted logistic regression model was used to explore the association of ten blood VOCs with depression. Subsequently, the relative importance of the selected VOCs was determined using the XGBoost model. The weighted quantile sum (WQS) regression model was used to explore the overall association of 10 blood VOCs with depression. Subgroup analyses were performed to identify high-risk populations. Finally, restricted cubic spline (RCS) analysis was utilized to explore the dose-response relationship between blood VOCs and the risk of depression.

RESULTS

XGBoost Algorithm model identified blood 2,5-dimethylfuran was the most critical variable in depression. The logistic regression model showed that blood benzene, blood 2,5-dimethylfuran, and blood furan showed a positive correlation with depression. In subgroup analysis, we found that the effects of the above VOCs on depression existed among the female, young middle-aged, and overweight-obese population. Mixture VOCs exposure was positively associated with depression risk (OR = 2.089, 95% CI: 1.299-3.361), and 2,5-dimethylfuran had the largest weights in WQS regression. RCS displayed that blood benzene, blood 2,5-dimethylfuran, and blood furan were positively associated with depression.

CONCLUSION

The results of this study indicated that VOCs exposure was associated with an increased prevalence of depression in U.S. adults. Women, young and middle-aged, and overweight-obese populations are more vulnerable to VOCs.

Depletion of Hemoglobin Transcripts and Long-Read Sequencing Improves the Transcriptome Annotation of the Polar Bear (Ursus maritimus)

Transcriptome studies evaluating whole blood and tissues are often confounded by overrepresentation of highly abundant transcripts. These abundant transcripts are problematic, as they compete with and prevent the detection of rare RNA transcripts, obscuring their biological importance. This issue is more pronounced when using long-read sequencing technologies for isoform-level transcriptome analysis, as they have relatively lower throughput compared to short-read sequencers. As a result, long-read based transcriptome analysis is prohibitively expensive for non-model organisms. While there are off-the-shelf kits available for select model organisms capable of depleting highly abundant transcripts for alpha (HBA) and beta (HBB) hemoglobin, they are unsuitable for non-model organisms. To address this, we have adapted the recent CRISPR/Cas9-based depletion method (depletion of abundant sequences by hybridization) for long-read full-length cDNA sequencing approaches that we call Long-DASH. Using a recombinant Cas9 protein with appropriate guide RNAs, full-length hemoglobin transcripts can be depleted in vitro prior to performing any short- and long-read sequencing library preparations. Using this method, we sequenced depleted full-length cDNA in parallel using both our Oxford Nanopore Technology (ONT) based R2C2 long-read approach, as well as the Illumina short-read based Smart-seq2 approach. To showcase this, we have applied our methods to create an isoform-level transcriptome from whole blood samples derived from three polar bears (Ursus maritimus). Using Long-DASH, we succeeded in depleting hemoglobin transcripts and generated deep Smart-seq2 Illumina datasets and 3.8 million R2C2 full-length cDNA consensus reads. Applying Long-DASH with our isoform identification pipeline, Mandalorion, we discovered ∼6,000 high-confidence isoforms and a number of novel genes. This indicates that there is a high diversity of gene isoforms within U. maritimus not yet reported. This reproducible and straightforward approach has not only improved the polar bear transcriptome annotations but will serve as the foundation for future efforts to investigate transcriptional dynamics within the 19 polar bear subpopulations around the Arctic.

Identification of time-dependent biomarkers and effects of exposure to volatile organic compounds using high-throughput analysis

Volatile organic compounds (VOCs) can be easily taken up by humans, leading to various diseases, such as respiratory system and central nervous system disorders. Environmental risk assessment is generally conducted using traditional tests, which may be time-consuming and technically challenging. Therefore, analysis of the effects of VOCs, such as toluene, ethylbenzene, and xylene, may be improved by use of novel, high-throughput methods, such as microarray analysis. In this study, we examined the effects of VOCs exposure in humans on gene expression and methylation using microarray analysis. We recruited participants who had short-term exposure, long-term exposure, or no exposure. We then analyzed changes in gene expression in blood samples from these participants. A total of 866 genes were upregulated, while 366 genes were downregulated in the short-term exposure group. Similarly, in the long-term exposure group, a total of 852 and 480 genes were up- or downregulated, respectively. Hierarchical clustering analysis was used to divide the clustered genes into nine clusters to investigate the expression of variations in accordance with the exposure period. And the methylation microarray was performed at the same time to see whether this expression variation is related to the epigenetic study. Finally, we have 5 genes that were upregulated and 12 genes that were downregulated, gradually and respectively, so these genes are expected to function as biomarkers of the duration of exposure to VOCs. Further research is required to determine the time-dependent effects of VOCs on epigenetic regulation of gene expression. © 2015 Wiley Periodicals, Inc. Environ Toxicol 31: 1563-1570, 2016.

Characteristic molecular signatures of early exposure to volatile organic compounds in rat liver

OBJECTIVE

Investigation on whether the characteristic molecular signatures can discriminate individual volatile organic compounds (VOCs) and provide predictive markers for the detection of VOC exposure.

METHODS

Transcriptomic analysis of liver tissues was performed 48 h after the single oral administration of three VOCs doses at LD25 or LD5 values, to Sprague-Dawley.

RESULTS

Combination analysis of different multi-classifications suggested that 145 genes predicted VOC exposure. Additionally, Gene Set Enrichment Analysis of genes deregulated by VOCs revealed that T cell prolymphatic leukemia signaling was inactivated in all VOCs.

CONCLUSIONS

These molecular markers could be widely implemented to assess and predict environmental exposure to VOCs.

Monitoring states of altered carbohydrate metabolism via breath analysis: are times ripe for transition from potential to reality?

PURPOSE OF REVIEW

To introduce the potential of breath analysis as a diagnostic or monitoring tool in diabetes.

RECENT FINDINGS

Blood testing for plasma glucose and other metabolic variables is the base for the diagnosis and management of diabetes, whose two main types (type 1 and type 2, T1DM, T2DM) are projected to affect 450 million by 2030. As blood testing is often uncomfortable, painful, costly, and in some situations unreliable, the quest for alternative, noninvasive methods has been ongoing for decades. Breath analysis has emerged as an ideal alternative as sample collection is easy, painless, flexible, noninvasive, practical, and inexpensive. No single exhaled gas can reflect systemic glucose concentrations. Multiple gases, however, have been linked to various aspects of glucose metabolism, and integrated analysis of their simultaneous profiles during prolonged glycemic fluctuations has yielded accurate predictions of plasma values, building expectation that a clinically usable breath-based glucometer may be developed within a few years.

SUMMARY

While prototypes of hand-held breath testing glucometers may still be several years away, current research shows the imminent promise of this methodology and the widening support for its development.

Blood transcriptomics: applications in toxicology

The number of new chemicals that are being synthesized each year has been steadily increasing. While chemicals are of immense benefit to mankind, many of them have a significant negative impact, primarily owing to their inherent chemistry and toxicity, on the environment as well as human health. In addition to chemical exposures, human exposures to numerous non-chemical toxic agents take place in the environment and workplace. Given that human exposure to toxic agents is often unavoidable and many of these agents are found to have detrimental human health effects, it is important to develop strategies to prevent the adverse health effects associated with toxic exposures. Early detection of adverse health effects as well as a clear understanding of the mechanisms, especially at the molecular level, underlying these effects are key elements in preventing the adverse health effects associated with human exposure to toxic agents. Recent developments in genomics, especially transcriptomics, have prompted investigations into this important area of toxicology. Previous studies conducted in our laboratory and elsewhere have demonstrated the potential application of blood gene expression profiling as a sensitive, mechanistically relevant and practical surrogate approach for the early detection of adverse health effects associated with exposure to toxic agents. The advantages of blood gene expression profiling as a surrogate approach to detect early target organ toxicity and the molecular mechanisms underlying the toxicity are illustrated and discussed using recent studies on hepatotoxicity and pulmonary toxicity. Furthermore, the important challenges this emerging field in toxicology faces are presented in this review article.

Monitoring of deiodinase deficiency based on transcriptomic responses in SH-SY5Y cells

Iodothyronine deiodinase types I, II, and III (D1, D2, and D3, respectively), which constitute a family of selenoenzymes, activate and inactivate thyroid hormones through the removal of specific iodine moieties from thyroxine and its derivatives. These enzymes are important in the biological effects mediated by thyroid hormones. The expression of activating and inactivating deiodinases plays a critical role in a number of cell systems, including the neuronal system, during development as well as in adult vertebrates. To investigate deiodinase-disrupting chemicals based on transcriptomic responses, we examined differences in gene expression profiles between T3-treated and deiodinase-knockdown SH-SY5Y cells using microarray analysis and quantitative real-time RT-PCR. A total of 1,558 genes, consisting of 755 upregulated and 803 downregulated genes, were differentially expressed between the T3-treated and deiodinase-knockdown cells. The expression levels of 10 of these genes (ID2, ID3, CCL2, TBX3, TGOLN2, C1orf71, ZNF676, GULP1, KLF9, and ITGB5) were altered by deiodinase-disrupting chemicals (2,3,7,8-tetrachlorodibenzo-p-dioxin, polychlorinated biphenyls, propylthiouracil, iodoacetic acid, methylmercury, β-estradiol, methimazole, 3-methylcholanthrene, aminotriazole, amiodarone, cadmium chloride, dimethoate, fenvalerate, octylmethoxycinnamate, iopanoic acid, methoxychlor, and 4-methylbenzylidene-camphor). These genes are potential biomarkers for detecting deiodinase deficiency and predicting their effects on thyroid hormone production.

Characteristic molecular signature for early detection and prediction of persistent organic pollutants in rat liver

Persistent organic pollutants (POPs) are degradation-resistant anthropogenic chemicals that accumulate in the food chain and in adipose tissue, and are among the most hazardous compounds ever synthesized. However, their toxic mechanisms are still undefined. To investigate whether characteristic molecular signatures can discriminate individual POP and provide prediction markers for the early detection of POPs exposure in an animal model, we performed transcriptomic analysis of rat liver tissues after exposure to POPs. The six different POPs (toxaphene, hexachlorobenzene, chlordane, mirex, dieldrin, and heptachlor) were administered to 11-week-old male Sprague-Dawley rats, and after 48 h of exposure, RNAs were extracted from liver tissues and subjected to rat whole genome expression microarrays. Early during exposure, conventional toxicological analysis including changes in the body and organ weight, histopathological examination, and blood biochemical analysis did not reflect any toxicant stresses. However, unsupervised gene expression analysis of rat liver tissues revealed in a characteristic molecular signature for each toxicant, and supervised analysis identified 2708 outlier genes that discerned the POPs exposure group from the vehicle-treated control. Combination analysis of two different multiclassifications suggested 384 genes as early detection markers for predicting each POP exposure with 100% accuracy. The data from large-scale gene expression analysis of a different POP exposure in rat model suggest that characteristic expression profiles exist in liver hepatic cells and multiclassification of POP-specific molecular signatures can discriminate each toxicant at an early exposure time. The use of these molecular markers may be more widely implemented in combination with more traditional techniques for assessment and prediction of toxicity exposure to POPs from an environmental aspect.

Characteristic molecular signature for the early detection and prediction of polycyclic aromatic hydrocarbons in rat liver

Predictions of toxicity are central for the assessment of chemical toxicity, and the effects of environmental toxic compounds are still a major issue for predicting potential human health risks. Among the various environmental toxicants, polycyclic aromatic hydrocarbons (PAHs) are an important class of environmental pollutant, and many PAHs are known or suspected carcinogens. In the present study, to investigate whether characteristic expression profiles of PAHs exist in rat liver and whether a characteristic molecular signature can discriminate and predict among different PAHs at an early exposure time, we analyzed the genome-wide expression profiles of rat livers exposed to PAHs [benzo[a]anthracene (BA), benzo[a]pyrene (BP), phenanthrene (PA) and naphthalene (NT)]. At early time-point PAH exposure, large-scale gene expression analysis resulted in characteristic molecular signatures for each PAH, and supervised analysis identified 1183 outlier genes as a distinct molecular signature discerning PAHs from the normal control group. We identified 158 outlier genes as early predictive and surrogate markers for predicting each tested PAH by combination of two different multi-classification algorithms with 100% accuracy through a leave-one out cross-validation method. In conclusion, the characteristic gene expression signatures from a rat model system could be used as predictable and discernible gene-based biomarkers for the detection and prediction of PAHs, and these molecular markers may provide insights into the underlying mechanisms for genotoxicity of exposure to PAHs from environmental aspect.

The clinical potential of exhaled breath analysis for diabetes mellitus

Various compounds in present human breath have long been loosely associated with pathological states (including acetone smell in uncontrolled diabetes). Only recently, however, the precise measurement of exhaled volatile organic compounds (VOCs) and aerosolized particles was made possible at extremely low concentrations by advances in several analytical methodologies, described in detail in the international literature and each suitable for specific subsets of exhaled compounds. Exhaled gases may be generated endogenously (in the pulmonary tract, blood, or peripheral tissues), as metabolic by-products of human cells or colonizing micro-organisms, or may be inhaled as atmospheric pollutants; growing evidence indicates that several of these molecules have distinct cell-to-cell signaling functions. Independent of origin and physiological role, exhaled VOCs are attractive candidates as biomarkers of cellular activity/metabolism, and could be incorporated in future non-invasive clinical testing devices. Indeed, several recent studies reported altered exhaled gas profiles in dysmetabolic conditions and relatively accurate predictions of glucose concentrations, at least in controlled experimental conditions, for healthy and diabetic subjects over a broad range of glycemic values. Optimization of this methodology and validation in large-scale trials under a wider range of conditions is needed to determine its true potential to transition into practical clinical use.