Performance in omics analyses of blood samples in long-term storage: opportunities for the exploitation of existing biobanks in environmental health research

Characteristics of RNA Stabilizer RNApro for Peripheral Blood Collection

Peripheral blood is the most practical tissue for human immune system gene expression profiling because it is easily accessible, whereas the site of primary infection in certain diseases may not be easily accessible. Due to the ex vivo instability of RNA transcripts, a key challenge in the gene expression analysis of blood samples is the rapid sample handling and stabilization of the mRNA by adding an RNA preservative (PAXgeneTM Blood RNA Tubes, TempusTM Blood RNA tubes, RNAlater Stabilization Reagent, RNAgard® Blood Tubes). BioMole (Turin, Italy) has developed a novel blood stabilizer, called RNApro, in which RNA is stabilized during phlebotomy and sample storage. In this study, RNApro performance intended as RNA yield, integrity, and stability was evaluated. Our results show that blood samples stored at -80 °C and re-extracted after 7 years show no differences in terms of quantity, quality, and amplificability. The samples in the RNAlater stabilization solution can be stored at room temperature for up to one week or at 4 °C for up to one month. Similar results can also be observed for PAXgene tubes, Tempus tubes, and RNAgard tubes. In agreement with these data, the RNApro stabilization solution preserves the RNA from degradation for up to 1 month at 4 °C and 1 week at room temperature. RNApro can be stored indifferently at -80, -20, 4 °C, or room temperature for up to 2 months after, and then could be stored at -80 °C for up to seven years. In summary, our study is the first to analyze the performance of an RNA stabilizer called RNApro. We can conclude that several studies have shown significant differences in gene expression analysis when the sample was preserved in different RNA stabilizers. Therefore, it is desirable to standardize the method of nucleic acid conservation when comparing data from transcriptomic analyses.

Molecular insights into PCB neurotoxicity: Comparing transcriptomic responses across dopaminergic neurons, population blood cells, and Parkinson's disease pathology

Parkinson's disease (PD) is a complex neurodegenerative disorder influenced by genetic factors and environmental exposures. Polychlorinated biphenyls (PCBs), a group of synthetic organic compounds, have been identified as potential environmental risk factors for neurodegenerative diseases, including PD. We explored PCB-induced neurotoxicity mechanisms using iPSC-derived dopaminergic neurons and assessed their transcriptomic responses to varying PCB concentrations (0.01 μM, 0.5 μM, and 10 μM). Specifically, we focused on PCB-180, a congener known for its accumulation in human brains. The exposure durations were 24 h and 74 h, allowing us to capture both short-term and more prolonged effects on gene expression patterns. We observed that PCB exposure led to the suppression of oxidative phosphorylation, synaptic function, and neurotransmitter release, implicating these pathways in PCB-induced neurotoxicity. In our comparative analysis, we noted similarities in PCB-induced changes with other PD-related compounds like MPP+ and rotenone. Our findings also aligned with gene expression changes in human blood derived from a population exposed to PCBs, highlighting broader inflammatory responses. Additionally, molecular patterns seen in iPSC-derived neurons were confirmed in postmortem PD brain tissues, validating our in vitro results. In conclusion, our study offers novel insights into the multifaceted impacts of PCB-induced perturbations on various cellular contexts relevant to PD. The use of iPSC-derived dopaminergic neurons allowed us to decipher intricate transcriptomic alterations, bridging the gap between in vitro and in vivo findings. This work underscores the potential role of PCB exposure in neurodegenerative diseases like PD, emphasizing the need to consider both systemic and cell specific effects.

Development and analytical validation of a novel nasopharynx swab-based Epstein-Barr virus C promoter methylation quantitative assay for nasopharyngeal carcinoma detection

OBJECTIVES

Epstein-Barr virus (EBV) C promoter (Cp) hypermethylation, a crucial factor for EBV latent infection of nasopharyngeal epithelial cells, has been recognized as a promising biomarker for nasopharyngeal carcinoma (NPC) detection. In this study, we develop a novel EBV Cp methylation quantification (E-CpMQ) assay and evaluate its diagnostic performance for NPC detection.

METHODS

A novel qPCR assay for simultaneous quantification of methylated- and unmethylated EBV Cp was developed by the combinational modification of MethyLight and QASM, with an innovative calibrator to improve the detection accuracy and consistency. The NP swab samples and synthetic standards were used for the analytical validation of the E-CpMQ. The diagnostic efficacy of the developed E-CpMQ assay was validated in 137 NPC patients and 137 non-NPC controls.

RESULTS

The E-CpMQ assay can detect the EBV Cp methylation ratio in one reaction system under 10 copies with 100 % recognition specificity, which is highly correlated to pyrosequencing with a correlation coefficient over 0.99. The calibrated E-CpMQ assay reduces the coefficient of variation by an average of 55.5 % with a total variance of less than 0.06 units standard deviation (SD). Linear methylation ratio detection range from 4.76 to 99.01 %. The sensitivity and specificity of the E-CpMQ respectively are 96.4 % (95 % CI: 91.7-98.8 %), 89.8 % (95 % CI: 83.5-94.3 %).

CONCLUSIONS

The developed E-CpMQ assay with a calibrator enables accurate and reproducible EBV Cp methylation ratio quantification and offers a sensitive, specific, cost-effective method for NPC early detection.

Uveal Melanoma Patients Have a Distinct Metabolic Phenotype in Peripheral Blood

Uveal melanomas (UM) are detected earlier. Consequently, tumors are smaller, allowing for novel eye-preserving treatments. This reduces tumor tissue available for genomic profiling. Additionally, these small tumors can be hard to differentiate from nevi, creating the need for minimally invasive detection and prognostication. Metabolites show promise as minimally invasive detection by resembling the biological phenotype. In this pilot study, we determined metabolite patterns in the peripheral blood of UM patients (n = 113) and controls (n = 46) using untargeted metabolomics. Using a random forest classifier (RFC) and leave-one-out cross-validation, we confirmed discriminatory metabolite patterns in UM patients compared to controls with an area under the curve of the receiver operating characteristic of 0.99 in both positive and negative ion modes. The RFC and leave-one-out cross-validation did not reveal discriminatory metabolite patterns in high-risk versus low-risk of metastasizing in UM patients. Ten-time repeated analyses of the RFC and LOOCV using 50% randomly distributed samples showed similar results for UM patients versus controls and prognostic groups. Pathway analysis using annotated metabolites indicated dysregulation of several processes associated with malignancies. Consequently, minimally invasive metabolomics could potentially allow for screening as it distinguishes metabolite patterns that are putatively associated with oncogenic processes in the peripheral blood plasma of UM patients from controls at the time of diagnosis.

Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS

BACKGROUND

Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions.

METHODS AND FINDINGS

In this study, we compared COVID-19 ARDS (n = 43) and bacterial sepsis-induced (non-COVID-19) ARDS (n = 24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within- ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation.

CONCLUSION

We present a first comprehensive molecular characterization of differences between two ARDS etiologies-COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions.

Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS

Background

Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions.

Methods and Findings

In this study, we compared COVID-19 ARDS (n=43) and bacterial sepsis-induced (non-COVID-19) ARDS (n=24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within-ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation.

Conclusion

We present a first comprehensive molecular characterization of differences between two ARDS etiologies - COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions.

Peripheral blood DNA methylation profiles predict future development of B-cell Non-Hodgkin Lymphoma

Lack of accurate methods for early lymphoma detection limits the ability to cure patients. Since patients with Non-Hodgkin lymphomas (NHL) who present with advanced disease have worse outcomes, accurate and sensitive methods for early detection are needed to improve patient care. We developed a DNA methylation-based prediction tool for NHL, based on blood samples collected prospectively from 278 apparently healthy patients who were followed for up to 16 years to monitor for NHL development. A predictive score was developed using machine learning methods in a robust training/validation framework. Our predictive score incorporates CpG DNA methylation at 135 genomic positions, with higher scores predicting higher risk. It was 85% and 78% accurate for identifying patients at risk of developing future NHL, in patients with high or low epigenetic mitotic clock respectively, in a validation cohort. It was also sensitive at detecting active NHL (96.3% accuracy) and healthy status (95.6% accuracy) in additional independent cohorts. Scores optimized for specific NHL subtypes showed significant but lower accuracy for predicting other subtypes. Our score incorporates hyper-methylation of Polycomb and HOX genes, which have roles in NHL development, as well as PAX5 - a master transcriptional regulator of B-cell fate. Subjects with higher risk scores showed higher regulatory T-cells, memory B-cells, but lower naïve T helper lymphocytes fractions in the blood. Future prospective studies will be required to confirm the utility of our signature for managing patients who are at high risk for developing future NHL.

The influence of blood sample processing on blood-based DNA methylation signatures

Stability is crucial for the clinical applicable biomarker such as DNA methylation profiles. However, the influence of various blood processing on the DNA methylation signatures have been barely studied. Here, we systematically evaluated the impact of temporary storage and frozen and thaw on the levels of DNA methylation. The methylation intensities of 13 CpG loci from 53 individuals (42 healthy participants and 11 lung cancer patients) whose blood samples were processed by up to 14 various protocols were quantitatively determined by the mass spectrometry, obtaining more than 8,000 quantitative data. We disclosed a trend of accumulatively increased DNA methylation along with time when the blood from healthy people were stored for up to 96 hours at room temperature (RT), whereas the storage at 4℃ had much weaker effects or no impact. On the contrary, the methylation patterns in the blood of lung cancer patients were more stable at both RT and 4℃ even for 96 hours. Multiple cycles of frozen and thaw could result in demethylation, but was more significant to the blood than to the extracted DNA. Our study indicated that the blood processing in vitro could influence the DNA methylation signatures and introduce unexpected biases.

Metabolomic signatures of low- and high-adiposity neonates differ based on maternal BMI

Maternal obesity [body mass index (BMI) > 30 kg/m²] is associated with greater neonatal adiposity, cord blood (CB) insulin levels, and a proinflammatory phenotype at birth, contributing to risk of future cardiometabolic disease in the offspring. Variation in neonatal adiposity within maternal BMI groups is underappreciated, and it remains unclear whether the metabolic impairments at birth are an outcome of maternal obesity or excess fetal fat accrual. We examined the hypothesis that CB metabolites associated with fetal fat accrual differ between offspring of normal-weight and obese women. Umbilical venous blood was collected at the time of scheduled cesarean delivery from 50 normal-weight women (LE; pregravid BMI = 22.3 ± 1.7 kg/m²) and 50 obese women (OB; BMI = 34.5 ± 3.0 kg/m²). Neonatal adiposity was estimated from flank skinfold thickness. The first (low adiposity, LA) and third (high adiposity, HA) tertiles of neonatal %body fat were used to create four groups: OBLA, OBHA, LELA, and LEHA. CB metabolites were measured via untargeted metabolomics. Broadly, the LA offspring of OB women (OBLA) metabolite signature differed from other groups. Lauric acid (C12:0) was 82-118% higher in OBLA vs. all other groups [false discovery rate (FDR) < 0.01]. Several other fatty acids, including palmitate, stearate, and linoleate, were higher in OBLA vs. OBHA groups. CB metabolites, such as lauric acid, a medium-chain fatty acid that may improve insulin sensitivity, were associated with neonatal adiposity differently between offspring of women with and without obesity. Changes in metabolically active lipids at birth may have long-term consequences for offspring metabolism.NEW & NOTEWORTHY Using untargeted metabolomics in 100 newborns, we found that cord blood metabolite signatures associated with neonatal adiposity differed between offspring of women with and without obesity.

The impact of pre-freezing storage time and temperature on gene expression of blood collected in EDTA tubes

Background

Blood is a common source of RNA for gene expression studies. However, it is known to be vulnerable to pre-analytical variables. Although RNA stabilization systems have been shown to reduce such influence, traditional EDTA tubes are still widely used since they are less expensive and enable to study specific leukocyte populations. This study aimed to assess the influence of storage time and temperature between blood sampling and handling on RNA from peripheral blood mononuclear cells (PBMCs).

Methods and results

Nine blood samples were collected in EDTA tubes from 10 healthy donors. One tube from each donor was immediately processed for PBMC isolation, while the others were first incubated at either 4 degrees Celsius (°C) or room temperature for 2, 4, 6 and 24 h. RNA yield and quality and the expression level of fourt housekeeping (B2M, CASC3, GAPDH, HPRT1) and 8 target genes (CD14, CD19, CD20, IL10, MxA, TNF, TNFAIP3, NR4A2) were compared between samples.

RNA yield, quality and integrity did not vary significantly with time and temperature. B2M was the most stable housekeeping gene, while the others were increasingly influenced by storing time, especially at 4 °C. Even when normalized to B2M, the expression level of some target genes, particularly TNFAIP3 and NR4A2, was highly affected by delays in blood processing at either temperature, already from 2 h.

Conclusion

Pre-analytical processing has a great impact on transcript expression from blood collected in EDTA tubes, especially on genes related to inflammation. Standardized procedure of blood handling are needed to obtain reliable results.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11033-022-07320-5.

Sample management: a primary critical starting point for successful omics studies

Biological samples collected from cohort studies are widely utilized in molecular genetic studies and are typically stored long term for future applications, such as omics analyses. The extent of sample availability is determined by proper sample handling, and it is of primary importance for successful omics studies. However, questions on whether samples in long-term storage are properly available for omics experiments has been raised, because the quality and availability of such samples remain unknown until their actual utilization. In that perspective, several guidelines for proper sample management have been suggested. In addition, several researchers assessed how improper management damages sample using mock sample and suggested a set of requirements for sample handling. In this review, we present several considerations for sample handling eligible for omics studies. Focusing on birth cohorts, we describe the types of samples collected from which omics data were generated. This review ultimately aims to provide proper guidelines for sample handling for successful human omics studies.

Prenatal Exposure to Heavy Metals Affects Gestational Age by Altering DNA Methylation Patterns

Environmental exposure is known to have toxic effects. Maternal environmental exposure not only affects mothers but also their fetuses in utero, which may interrupt their early development. Preterm birth, one of the outcomes of prenatal exposure, is a significant factor in lifelong health risks. To understand the effects of prenatal exposome on preterm birth, we studied the association between maternal and prenatal heavy metal exposure and gestational age, using resources from the MOthers' and Children's Environmental Health (MOCEH) study in South Korea. Additionally, a methylation assay was performed to analyze epigenetic mediation using genomic DNA derived from the cord blood of 384 participants in the MOCEH study. The results suggest that maternal cadmium exposure is associated with a decrease in gestational age through an alteration in DNA methylation at a specific CpG site, cg21010642. The CpG site was annotated to a gene involved in early embryonic development. Therefore, irregular methylation patterns at this site may contribute to premature birth by mediating irregular biological mechanisms.

Guidelines for pre-analytical conditions for assessing the methylation of circulating cell-free DNA

Methylation analysis of circulating cell-free DNA (cirDNA), as a liquid biopsy, has a significant potential to advance the detection, prognosis, and treatment of cancer, as well as many genetic disorders. The role of epigenetics in disease development has been reported in several hereditary disorders, and epigenetic modifications are regarded as one of the earliest and most significant genomic aberrations that arise during carcinogenesis. Liquid biopsy can be employed for the detection of these epigenetic biomarkers. It consists of isolation (pre-analytical) and detection (analytical) phases. The choice of pre-analytical variables comprising cirDNA extraction and bisulfite conversion methods can affect the identification of cirDNA methylation. Indeed, different techniques give a different return of cirDNA, which confirms the importance of pre-analytical procedures in clinical diagnostics. Although novel techniques have been developed for the simplification of methylation analysis, the process remains complex, as the steps of DNA extraction, bisulfite treatment, and methylation detection are each carried out separately. Recent studies have noted the absence of any standard method for the pre-analytical processing of methylated cirDNA. We have therefore conducted a comprehensive and systematic review of the important pre-analytical and analytical variables and the patient-related factors which form the basis of our guidelines for analyzing methylated cirDNA in liquid biopsy.

Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients

BACKGROUND

AKI requiring dialysis (AKI-D) is associated with prolonged hospitalization, mortality, and progressive CKD among survivors. Previous studies have examined only select urine or serum biomarkers for predicting kidney recovery from AKI.

METHODS

Serum samples collected on day 8 of randomized RRT from 72 patients enrolled in the Veteran's Affairs/National Institutes of Health Acute Renal Failure Trial Network study were analyzed by the SOMAscan proteomic platform to profile 1305 proteins in each sample. Of these patients, 38 recovered kidney function and dialysis was discontinued, whereas another 34 patients remained on dialysis by day 28.

RESULTS

Differential serum levels of 119 proteins, with 53 higher and 66 lower, were detected in samples from patients who discontinued dialysis, compared with patients who remained on dialysis by day 28. Patients were classified into tertiles on the basis of SOMAscan protein measurements for the 25 proteins most differentially expressed. The association of serum levels of each protein with kidney recovery was further evaluated using logistic regression analysis. Higher serum levels of CXCL11, CXCL2/CXCL3, CD86, Wnt-7a, BTK, c-Myc, TIMP-3, CCL5, ghrelin, PDGF-C, survivin, CA2, IL-9, EGF, and neuregulin-1, and lower levels of soluble CXCL16, IL1RL1, stanniocalcin-1, IL-6, and FGF23 when classified in tertiles were significantly associated with better kidney recovery. This significant association persisted for each of these proteins after adjusting for potential confounding risk factors including age, sex, cardiovascular SOFA score, congestive heart failure, diabetes, modality of intensive dialysis treatment, cause of AKI, baseline serum creatinine, day 8 urine volume, and estimated 60-day mortality risk.

CONCLUSIONS

These results suggest concerted changes between survival-related proteins and immune-regulatory chemokines in regulating angiogenesis, endothelial and epithelial remodeling, and kidney cell regeneration, illustrating potential mechanisms of kidney recovery. Thus, this study identifies potential novel predictive biomarkers of kidney recovery in patients with AKI-D.

Novel Serum and Urinary Metabolites Associated with Diabetic Retinopathy in Three Asian Cohorts

Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus, a metabolic disorder, but understanding of its pathophysiology remains incomplete. Meta-analysis of three population-based cross-sectional studies (2004–11) representing three major Asian ethnic groups (aged 40–80 years: Chinese, 592; Malays, 1052; Indians, 1320) was performed. A panel of 228 serum/plasma metabolites and 54 urinary metabolites were quantified using nuclear magnetic resonance (NMR) spectroscopy. Main outcomes were defined as any DR, moderate/above DR, and vision-threatening DR assessed from retinal photographs. The relationship between metabolites and DR outcomes was assessed using multivariate logistic regression models, and metabolites significant after Bonferroni correction were meta-analyzed. Among serum/plasma metabolites, lower levels of tyrosine and cholesterol esters to total lipids ratio in IDL and higher levels of creatinine were positively associated with all three outcomes of DR (all p < 0.005). Among urinary metabolites, lower levels of citrate, ethanolamine, formate, and hypoxanthine were positively associated with all three DR outcomes (all p < 0.005). Higher levels of serum/plasma 3-hydroxybutyrate and lower levels of urinary 3-hydroxyisobutyrate were associated with VTDR. Comprehensive metabolic profiling in three large Asian cohorts with DR demonstrated alterations in serum/plasma and urinary metabolites mostly related to amino acids, lipoprotein subclasses, kidney function, and glycolysis.

Prospective Identification of Elevated Circulating CDCP1 in Patients Years before Onset of Lung Cancer

Increasing evidence points to a role for inflammation in lung carcinogenesis. A small number of circulating inflammatory proteins have been identified as showing elevated levels prior to lung cancer diagnosis, indicating the potential for prospective circulating protein concentration as a marker of early carcinogenesis. To identify novel markers of lung cancer risk, we measured a panel of 92 circulating inflammatory proteins in 648 prediagnostic blood samples from two prospective cohorts in Italy and Norway (women only). To preserve the comparability of results and protect against confounding factors, the main statistical analyses were conducted in women from both studies, with replication sought in men (Italian participants). Univariate and penalized regression models revealed for the first time higher blood levels of CDCP1 protein in cases that went on to develop lung cancer compared with controls, irrespective of time to diagnosis, smoking habits, and gender. This association was validated in an additional 450 samples. Associations were stronger for future cases of adenocarcinoma where CDCP1 showed better explanatory performance. Integrative analyses combining gene expression and protein levels of CDCP1 measured in the same individuals suggested a link between CDCP1 and the expression of transcripts of LRRN3 and SEM1. Enrichment analyses indicated a potential role for CDCP1 in pathways related to cell adhesion and mobility, such as the WNT/β-catenin pathway. Overall, this study identifies lung cancer-related dysregulation of CDCP1 expression years before diagnosis. SIGNIFICANCE: Prospective proteomics analyses reveal an association between increased levels of circulating CDCP1 and lung carcinogenesis irrespective of smoking and years before diagnosis, and integrating gene expression indicates potential underlying mechanisms.See related commentary by Itzstein et al., p. 3441.

Impact of storage conditions on peripheral leukocytes transcriptome

Leukocytes reflect the physiological and pathological states of each individual, and transcriptomic data of leukocytes have been used to reflect health conditions. Since the overall impact of ex vivo conditions on the leukocyte transcriptome before RNA stabilization remains unclear, we evaluated the influence of temporary storage conditions on the leukocyte transcriptome through RNA sequencing. We collected peripheral blood with EDTA tubes, which were processed immediately or stored either at 4 °C or room temperature (RT, 18-22 °C) for 2 h, 6 h and 24 h. Total cellular RNA was extracted from 42 leukocyte samples after red blood cells lysis for subsequent RNA sequencing. We applied weighted gene co-expression network analysis to construct co-expression networks of mRNA and lncRNA among the samples, and then performed gene ontology (GO) term enrichment to explore possible biological processes affected by storage conditions. Storage conditions change the gene expression of peripheral leukocytes. Comparing with fresh leukocytes, storage for 24 h at 4 °C and RT affected 1515 (1.51%) and 10,823 (10.82%) genes, respectively. Pathway enrichment analysis identified nucleosome assembly enriched in up-regulated genes at both conditions. When blood was stored at RT for 24 h, genes involved in apoptotic signaling pathway, negative regulation of cell cycle and lymphocyte activation were upregulated, while the relative proportion of neutrophils was significantly decreased. Temporary storage conditions profoundly affect the gene expression profiles of leukocytes and might further change cell viability and state. Storage of blood samples at 4 °C within 6 h largely maintains their original transcriptome.

Sphingolipidomics in Translational Sepsis Research-Biomedical Considerations and Perspectives

Scientific Background: Sphingolipids are a highly diverse group of lipids with respect to physicochemical properties controlling either structure, distribution, or function, all of them regulating cellular response in health and disease. Mass spectrometry, on the other hand, is an analytical technique characterizing ionized molecules or fragments thereof by mass-to-charge ratios, which has been prosperingly developed for rapid and reliable qualitative and quantitative identification of lipid species. Parallel to best performance of in-depth chromatographical separation of lipid classes, preconditions of precise quantitation of unique molecular species by preprocessing of biological samples have to be fulfilled. As a consequence, “lipid profiles” across model systems and human individuals, esp. complex (clinical) samples, have become eminent over the last couple of years due to sensitivity, specificity, and discriminatory capability. Therefore, it is significance to consider the entire experimental strategy from sample collection and preparation, data acquisition, analysis, and interpretation.

Areas Covered: In this review, we outline considerations with clinical (i.e., human) samples with special emphasis on sample handling, specific physicochemical properties, target measurements, and resulting profiling of sphingolipids in biomedicine and translational research to maximize sensitivity and specificity as well as to provide robust and reproducible results. A brief commentary is also provided regarding new insights of “clinical sphingolipidomics” in translational sepsis research.

Expert Opinion: The role of mass spectrometry of sphingolipids and related species (“sphingolipidomics”) to investigate cellular and compartment-specific response to stress, e.g., in generalized infection and sepsis, is on the rise and the ability to integrate multiple datasets from diverse classes of biomolecules by mass spectrometry measurements and metabolomics will be crucial to fostering our understanding of human health as well as response to disease and treatment.

Blood Transcriptome Response to Environmental Metal Exposure Reveals Potential Biological Processes Related to Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disease which is manifested by a progressive and irreversible decline of cognition, memory loss, a shortened attention span, and changes in personality. Aging and genetic pre-dispositions, particularly the presence of a specific form of apolipoprotein E (APOE), are main risk factors of sporadic AD; however, a large body of evidence has shown that multiple environmental factors, including exposure to toxic metals, increase the risk for late onset AD. Lead (Pb) and cadmium (Cd) are ubiquitous toxic metals with a wide range of applications resulting in global distribution in the environment and exposure of all living organisms on earth. In addition to being classified as carcinogenic (Cd) and possibly carcinogenic (Pb) to humans by the International Agency for Research on Cancer, both compounds disrupt metal homeostasis and can cause toxic responses at the cellular and organismal levels. Pb toxicity targets the central nervous system and evidence for that has emerged also for Cd. Recent epidemiological studies show that both metals possibly are etiological factors of multiple neurodegenerative diseases, including Alzheimer's disease (AD). To further explore the association between metal exposure and AD risk we applied whole transcriptome gene expression analysis in peripheral blood leukocytes (PBLs) from 632 subjects of the general population, taken from the EnviroGenomarkers project. We used linear mixed effect models to associate metal exposure to gene expression after adjustment for gender, age, BMI, smoking, and alcohol consumption. For Pb exposure only few associations were identified, including a downregulation of the human eukaryotic translation initiation factor 5 (eIF5). In contrast, Cd exposure, particularly in males, revealed a much stronger transcriptomic response, featuring multiple pathways related to pathomolecular mechanisms of AD, such as endocytosis, neutrophil degranulation, and Interleukin−7 signaling. A gender stratified analysis revealed that the Cd responses were male-specific and included a downregulation of the APOE gene in men. This exploratory study revealed novel hypothetical findings which might contribute to the understanding of the neurotoxic effects of chronic Pb and Cd exposure and possibly improve our knowledge on the molecular mechanisms linking metal exposure to AD risk.

Advances in Comprehensive Exposure Assessment: Opportunities for the US Military

OBJECTIVE

Review advances in exposure assessment offered by the exposome concept and new -omics and sensor technologies.

METHODS

Narrative review of advances, including current efforts and potential future applications by the US military.

RESULTS

Exposure assessment methods from both bottom-up and top-down exposomics approaches are advancing at a rapid pace, and the US military is engaged in developing both approaches. Top-down approaches employ various -omics technologies to identify biomarkers of internal exposure and biological effect. Bottom-up approaches use new sensor technology to better measure external dose. Key challenges of both approaches are largely centered around how to integrate, analyze, and interpret large datasets that are multidimensional and disparate.

CONCLUSIONS

Advances in -omics and sensor technologies may dramatically enhance exposure assessment and improve our ability to characterize health risks related to occupational and environmental exposures, including for the US military.

A multi-omics approach to investigate the inflammatory response to life course socioeconomic position

Aim: Inflammation represents a potential pathway through which socioeconomic position (SEP) is biologically embedded. Materials & methods: We analyzed inflammatory biomarkers in response to life course SEP by integrating multi-omics DNA-methylation, gene expression and protein level in 178 European Prospective Investigation into Cancer and Nutrition-Italy participants. Results & conclusion: We identified 61 potential cis acting CpG loci whose methylation levels were associated with gene expression at a Bonferroni correction. We examined the relationships between life course SEP and these 61 cis-acting regulatory methylation sites individually and jointly using several scores. Less-advantaged SEP participants exhibit, later in life, a lower inflammatory methylome score, suggesting an overall increased expression of the corresponding inflammatory genes or proteins, supporting the hypothesis that SEP impacts adult physiology through inflammation.

Recommendations and Best Practices for Standardizing the Pre-Analytical Processing of Blood and Urine Samples in Metabolomics

Metabolomics can be significantly influenced by a range of pre-analytical factors, such as sample collection, pre-processing, aliquoting, transport, storage and thawing. This therefore shows the crucial need for standardizing the pre-analytical phase with the aim of minimizing the inter-sample variability driven by these technical issues, as well as for maintaining the metabolic integrity of biological samples to ensure that metabolomic profiles are a direct expression of the in vivo biochemical status. This review article provides an updated literature revision of the most important factors related to sample handling and pre-processing that may affect metabolomics results, particularly focusing on the most commonly investigated biofluids in metabolomics, namely blood plasma/serum and urine. Finally, we also provide some general recommendations and best practices aimed to standardize and accurately report all these pre-analytical aspects in metabolomics research.

The key points in the pre-analytical procedures of blood and urine samples in metabolomics studies

BACKGROUND

Metabolomics provides measurement of numerous metabolites in human samples, which can be a useful tool in clinical research. Blood and urine are regarded as preferred subjects of study because of their minimally invasive collection and simple preprocessing methods. Adhering to standard operating procedures is an essential factor in ensuring excellent sample quality and reliable results.

AIM OF REVIEW

In this review, we summarize the studies about the impacts of various preprocessing factors on metabolomics studies involving clinical blood and urine samples in order to provide guidance for sample collection and preprocessing.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical information is important for sample grouping and data analysis which deserves attention before sample collection. Plasma and serum as well as urine samples are appropriate for metabolomics analysis. Collection tubes, hemolysis, delay at room temperature, and freeze-thaw cycles may affect metabolic profiles of blood samples. Collection time, time between sampling and examination, contamination, normalization strategies, and storage conditions may alter analysis results of urine samples. Taking these collection and preprocessing factors into account, this review provides suggestions of standard sample preprocessing.

Effects of preservation duration at 4 °C on the quality of RNA in rabbit blood specimens

A prolonged preservation duration of blood specimens at 4 °C may occur due to the distance from collection points to storage facilities in many biobanks, especially for multicenter studies. This could lead to RNA degradation, affecting downstream analyses. However, effects of preservation durations at 4 °C on RNA quality in blood specimens need to be studied. We collected rabbit blood using EDTA tubes and stored them at 4 °C for different preservation durations. Then, we examined the quality of RNA from whole blood and leukocytes isolated from rabbit blood. Our results show that the purity of whole blood RNA and leukocyte RNA does not indicate significant change after rabbit blood is stored at 4 °C for different preservation durations (from 1 h to 7 days). The integrity of leukocyte RNA indicates the same result as above, but the integrity of whole blood RNA is significantly decreased after rabbit blood is stored at 4 °C for over 3 days. Moreover, expression of SMAD7, MKI67, FOS, TGFβ1 and HIF1α of whole blood RNA and leukocyte RNA remains basically stable, but PCNA expression of whole blood RNA or leukocyte RNA is significantly decreased after rabbit blood is stored at 4 °C for over 24 h or 7 days. Therefore, these results suggest that high-quality RNA is obtained from the fresher blood specimens and if blood specimens are stored for over 3 days at 4 °C, the quality of leukocyte RNA is more stable and of better quality than that of whole blood RNA.

Standard guidelines for the publication of telomere qPCR results in evolutionary ecology

Telomere length has been used as a proxy of fitness, aging and lifespan in vertebrates. In the last decade, dozens of articles reporting on telomere dynamics in the fields of ecology and evolution have been published for a wide range of taxa. With this growing interest, it is necessary to ensure the accuracy and reproducibility of telomere length measurement techniques. Real-time quantitative PCR (qPCR) is routinely applied to measure relative telomere length. However, this technique is highly sensitive to several methodological variables and the optimization of qPCR telomere assays remains highly variable between studies. Therefore, standardized guidelines are required to enable the optimization of robust protocols, and to help in judging the validity of the presented results. This review provides an overview of preanalytical and analytical factors that can lead to qPCR inconsistencies and biases, including: (a) sample type, collection and storage; (b) DNA extraction, storage and quality; (c) qPCR primers, laboratory reagents, and assay conditions; and (d) data analysis. We propose a minimum level of information for publication of qPCR telomere assays in evolutionary ecology considering the methodological pitfalls and sources of error. This review highlights the complexity of the optimization and validation of qPCR for telomere measurement per se, demonstrating the importance of transparency and clarity of reporting methodological details required for reliable, reproducible and comparable qPCR telomere assays. We encourage efforts to implement standardized protocols that ensure the rigour and quality of telomere dynamics studies.

A vision for exposome epidemiology: The pregnancy exposome in relation to breast cancer in the Child Health and Development Studies

Etiology of complex diseases, such as breast cancer, involves multiple genetic, behavioral and environmental factors. Gene sequencing enabled detection of genetic risks with relatively small effect size, and high-resolution metabolomics (HRM) to provide omics level data for exposures is poised to do the same for environmental epidemiology. Coupling HRM to the Child Health and Development Studies (CHDS) cohort combines two unique resources to create a prototype for exposome epidemiology, in which omics scale measures of exposure are used for study of distribution and determinants of health and disease. Using this approach, exposures and biologic responses during pregnancy have been linked to breast cancer in the CHDS. With improved chemical coverage and extension to larger populations and other disease processes, development of exposome epidemiology portends discovery of new disease-associated environment factors with small effect size as well as new capabilities to disentangle these from behavioral and other risk factors.

How to Make a Cost Model for the Birth Cohort Biobank in China

Biobanks and cohort studies are a popular topic in China these days and even in the global scientific research field. Cohorts with biological material are necessary to investigate potential biological mechanisms behind a disease and its early detection. Establishing a biobank is expensive and the long-term sustainability of biorepositories is a key issue globally. There is some published information on tools to calculate the biospecimen user fee; however, they may not be suitable for China's biobanks (as most of the biobanks in China are not for profit and are funded by government or research grants, and as such, funding is a major constraint). The limited published data also tend to be highly variable and specific to the type of biobank. The authors of this article aim to present the basis of a cost analysis model for a biobank of human biological samples of a birth cohort in Shanghai, China. The results show that it is very practical for us to consider how to build a cost model for the birth cohort biobank from the direct funds, such as storage equipment, temperature monitoring system, information management system, and so on. We conclude that by comparing the similarities and differences between China's cost model and that of other countries, this paper provides valuable information for biobankers to identify new perspectives on potential collaborators and mutual learning opportunities.

Evaluation of RNA purification methods by using different blood stabilization tubes: identification of key features for epidemiological studies

Objective

Peripheral blood is the most promising source of RNA biomarkers for diagnostic and epidemiological studies, because the presence of disease and prognostic information is reflected in the gene expression pattern. Quality RNA is used by a number of different downstream applications, so the selection of the most appropriate RNA stabilization and purification method is important. We have analyzed the RNA purified from 300 blood samples from 25 donors processed by two technicians using three methodologies with Tempus and PaxGene tubes.

Results

The best quality sample results were obtained with the Tempus Spin RNA Isolation Kit and the PaxGene Blood miRNA Kit, although larger amounts of RNA were obtained with the Tempus Spin RNA Isolation Kit. Lower Cq values were observed for RNA and miRNA genes in samples that were tested with PaxGene Blood miRNA Kit and Tempus Spin RNA Isolation Kit respectively. We identify the Tempus Spin RNA Isolation Kit as the most robust methodology, whilst the MagMax for Stabilized Blood Tubes RNA Isolation Kit showed the most instability. For biobanks, which process a large cohort and conduct epidemiological studies, the Tempus Spin RNA Isolation Kit is the most appropriate methodology. The study demonstrates the robustness of real-life procedures.

Considerations for mass spectrometry-based multi-omic analysis of clinical samples

Introduction: The role of mass spectrometry in biomolecule analysis has become paramount over the last several decades ranging in the analysis across model systems and human specimens. Accordingly, the presence of mass spectrometers in clinical laboratories has also expanded alongside the number of researchers investigating the protein, lipid, and metabolite composition of an array of biospecimens. With this increase in the number of omic investigations, it is important to consider the entire experimental strategy from sample collection and storage, data collection and analysis.Areas covered: In this short review, we outline considerations for working with clinical (e.g. human) specimens including blood, urine, and cerebrospinal fluid, with emphasis on sample handling, profiling composition, targeted measurements and relevance to disease. Discussions of integrated genomic or transcriptomic datasets are not included. A brief commentary is also provided regarding new technologies with clinical relevance.Expert opinion: The role of mass spectrometry to investigate clinically related specimens is on the rise and the ability to integrate multiple omics datasets from mass spectrometry measurements will be crucial to further understanding human health and disease.

Transcriptome analysis of fibroblasts from schizophrenia patients reveals differential expression of schizophrenia-related genes

Schizophrenia is a complex neurodevelopmental disorder with high rate of morbidity and mortality. While the heritability rate is high, the precise etiology is still unknown. Although schizophrenia is a central nervous system disorder, studies using peripheral tissues have also been established to search for patient specific biomarkers and to increase understanding of schizophrenia etiology. Among all peripheral tissues, fibroblasts stand out as they are easy to obtain and culture. Furthermore, they keep genetic stability for long period and exhibit molecular similarities to cells from nervous system. Using a unique set of fibroblast samples from a genetically isolated population in northern Sweden, we performed whole transcriptome sequencing to compare differentially expressed genes in seven controls and nine patients. We found differential fibroblast expression between cases and controls for 48 genes, including eight genes previously implicated in schizophrenia or schizophrenia related pathways; HGF, PRRT2, EGR1, EGR3, C11orf87, TLR3, PLEKHH2 and PIK3CD. Weighted gene correlation network analysis identified three differentially co-expressed networks of genes significantly-associated with schizophrenia. All three modules were significantly suppressed in patients compared to control, with one module highly enriched in genes involved in synaptic plasticity, behavior and synaptic transmission. In conclusion, our results support the use of fibroblasts for identification of differentially expressed genes in schizophrenia and highlight dysregulation of synaptic networks as an important mechanism in schizophrenia.

Impact of long-term storage and freeze-thawing on eight circulating microRNAs in plasma samples

Sample collection, processing, storage and isolation methods constitute pre-analytic factors that can influence the quality of samples used in research and clinical practice. With regard to biobanking practices, a critical point in the sample's life chain is storage, particularly long-term storage. Since most studies examine the influence of different temperatures (4°C, room temperature) or delays in sample processing on sample quality, there is only little information on the effects of long-term storage at ultra-low (vapor phase of liquid nitrogen) temperatures on biomarker levels. Among these biomarkers, circulating miRNAs hold great potential for diagnosis or prognosis for a variety of diseases, like cancer, infections and chronic diseases, and are thus of high interest in several scientific questions. We therefore investigated the influence of long-term storage on levels of eight circulating miRNAs (miR-103a-3p, miR-191-5p, miR-124-3p, miR-30c-5p, miR-451a, miR-23a-3p, miR-93-5p, miR-24-3p, and miR-33b-5p) from 10 participants from the population-based cohort study KORA. Sample collection took place during the baseline survey S4 and the follow-up surveys F4 and FF4, over a time period spanning from 1999 to 2014. The influence of freeze-thaw (f/t) cycles on miRNA stability was also investigated using samples from volunteers (n = 6). Obtained plasma samples were profiled using Exiqon's miRCURYTM real-time PCR profiling system, and repeated measures ANOVA was used to check for storage or f/t effects. Our results show that detected levels of most of the studied miRNAs showed no statistically significant changes due to storage at ultra-low temperatures for up to 17 years; miR-451a levels were altered due to contamination during sampling. Freeze-thawing of one to four cycles showed an effect only on miR-30c-5p. Our results highlight the robustness of this set of circulating miRNAs for decades of storage at ultra-low temperatures and several freeze-thaw cycles, which makes our findings increasingly relevant for research conducted with biobanked samples.

Stability of the Human Plasma Proteome to Pre-analytical Variability as Assessed by an Aptamer-Based Approach

Variable processing and storage of whole blood and/or plasma are potential confounders in biomarker development and clinical assays. The goal of the study was to investigate how pre-analytical variables impact the human plasma proteome. Whole blood obtained from 16 apparently healthy individuals was collected in six EDTA tubes and processed randomly under six pre-analytical variable conditions including blood storage at 0 °C or RT for 6 h (B6h0C or B6hRT) before processing to plasma, plasma storage at 4 °C or RT for 24 h (P24h4C or P24hRT), low centrifugal force at 1300 × g, (Low×g), and immediate processing to plasma under 2500 × g (control) followed by plasma storage at -80 °C. An aptamer-based proteomic assay was performed to identify significantly changed proteins (fold change ≥1.2, P < 0.05, and false discovery rate < 0.05) relative to the control from a total of 1305 proteins assayed. Pre-analytical conditions Low×g and B6h0C resulted in the most plasma proteome changes with 200 and 148 proteins significantly changed, respectively. Only 36 proteins were changed under B6hRT. Conditions P24h4C and P24hRT yielded changes of 28 and 75 proteins, respectively. The complement system was activated in vitro under the conditions B6hRT, P24h4C, and P24hRT. The results suggest that particular pre-analytical variables should be controlled for clinical measurement of specific biomarkers.

Pre-Analytical Factors that Affect Metabolite Stability in Human Urine, Plasma, and Serum: A Review

Metabolomics provides a comprehensive assessment of numerous small molecules in biological samples. As it integrates the effects of exogenous exposures, endogenous metabolism, and genetic variation, metabolomics is well-suited for studies examining metabolic profiles associated with a variety of chronic diseases. In this review, we summarize the studies that have characterized the effects of various pre-analytical factors on both targeted and untargeted metabolomic studies involving human plasma, serum, and urine and were published through 14 January 2019. A standardized protocol was used for extracting data from full-text articles identified by searching PubMed and EMBASE. For plasma and serum samples, metabolomic profiles were affected by fasting status, hemolysis, collection time, processing delays, particularly at room temperature, and repeated freeze/thaw cycles. For urine samples, collection time and fasting, centrifugation conditions, filtration and the use of additives, normalization procedures and multiple freeze/thaw cycles were found to alter metabolomic findings. Consideration of the effects of pre-analytical factors is a particularly important issue for epidemiological studies where samples are often collected in nonclinical settings and various locations and are subjected to time and temperature delays prior being to processed and frozen for storage.

Genes associated with Parkinson's disease respond to increasing polychlorinated biphenyl levels in the blood of healthy females

Polychlorinated biphenyls (PCBs) are a class of widespread environmental pollutants, commonly found in human blood, that have been suggested to be linked to the occurrence of sporadic Parkinson's disease (PD). It has been reported that some non-coplanar PCBs accumulate in the brains of female PD patients. To improve our understanding of the association between PCB exposure and PD risk we have applied whole transcriptome gene expression analysis in blood cells from 594 PCB-exposed subjects (369 female, 225 male). Interestingly, we observe that in females, blood levels of non-coplanar PCBs appear to be associated with expression levels of PD-specific genes. However, no such association was detected in males. Among the 131 PD-specific genes affected, 39 have been shown to display similar changes in expression levels in the substantia nigra of deceased PD patients. Especially among the down-regulated genes, transcripts of genes involved in neurotransmitter vesicle-related functions were predominant.

The Effect of Anticoagulants, Temperature, and Time on the Human Plasma Metabolome and Lipidome from Healthy Donors as Determined by Liquid Chromatography-Mass Spectrometry

Liquid-chromatography mass spectrometry is commonly used to identify and quantify metabolites from biological samples to gain insight into human physiology and pathology. Metabolites and their abundance in biological samples are labile and sensitive to variations in collection conditions, handling and processing. Variations in sample handling could influence metabolite levels in ways not related to biology, ultimately leading to the misinterpretation of results. For example, anticoagulants and preservatives modulate enzyme activity and metabolite oxidization. Temperature may alter both enzymatic and non-enzymatic chemistry. The potential for variation induced by collection conditions is particularly important when samples are collected in remote locations without immediate access to specimen processing. Data are needed regarding the variation introduced by clinical sample collection processes to avoid introducing artifact biases. In this study, we used metabolomics and lipidomics approaches paired with univariate and multivariate statistical analyses to assess the effects of anticoagulant, temperature, and time on healthy human plasma samples collected to provide guidelines on sample collection, handling, and processing for vaccinology. Principal component analyses demonstrated clustering by sample collection procedure and that anticoagulant type had the greatest effect on sample metabolite variation. Lipids such as glycerophospholipids, acylcarnitines, sphingolipids, diacylglycerols, triacylglycerols, and cholesteryl esters are significantly affected by anticoagulant type as are amino acids such as aspartate, histidine, and glutamine. Most plasma metabolites and lipids were unaffected by storage time and temperature. Based on this study, we recommend samples be collected using a single anticoagulant (preferably EDTA) with sample processing at <24 h at 4 °C.

An Integrated Analysis of Metabolites, Peptides, and Inflammation Biomarkers for Assessment of Preanalytical Variability of Human Plasma

Discrepancies in blood sample collection and processing could have a significant impact on levels of metabolites, peptides, and protein biomarkers of inflammation in the blood; thus, sample quality control is critical for successful biomarker identification and validation. In this study, we analyzed the effects of several preanalytical processing conditions, including different storage times and temperatures for blood or plasma samples and different centrifugation forces on the levels of metabolites, peptides, and inflammation biomarkers in human plasma samples using ethylenediaminetetraacetic acid (EDTA) as an anticoagulant. Temperature was found to be the major factor for metabolite variation, and both time and temperature were identified as major factors for peptide variation. For inflammation biomarkers, temperature played different roles depending on the sample type (blood or plasma). Low temperature affected inflammation biomarkers in blood, while room temperature impacted inflammation biomarkers in plasma.

Effects of Long-Term Storage at -80 °C on the Human Plasma Metabolome

High-quality biological samples are required for the favorable outcome of research studies, and valid data sets are crucial for successful biomarker identification. Prolonged storage of biospecimens may have an artificial effect on compound levels. In order to investigate the potential effects of long-term storage on the metabolome, human ethylenediaminetetraacetic acid (EDTA) plasma samples stored for up to 16 years were analyzed by gas and liquid chromatography-tandem mass spectrometry-based metabolomics. Only 2% of 231 tested plasma metabolites were altered in the first seven years of storage. However, upon longer storage periods of up to 16 years and more time differences of few years significantly affected up to 26% of the investigated metabolites when analyzed within subject age groups. Ontology classes that were most affected included complex lipids, fatty acids, energy metabolism molecules, and amino acids. In conclusion, the human plasma metabolome is adequately stable to long-term storage at −80 °C for up to seven years but significant changes occur upon longer storage. However, other biospecimens may display different sensitivities to long-term storage. Therefore, in retrospective studies on EDTA plasma samples, analysis is best performed within the first seven years of storage.

DNA Methylation in Inflammatory Pathways Modifies the Association between BMI and Adult-Onset Non-Atopic Asthma

A high body mass (BMI) index has repeatedly been associated with non-atopic asthma, but the biological mechanism linking obesity to asthma is still poorly understood. We aimed to test the hypothesis that inflammation and/or innate immunity plays a role in the obesity-asthma link. DNA methylome was measured in blood samples of 61 non-atopic participants with asthma and 146 non-atopic participants without asthma (non-smokers for at least 10 years) taking part in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) study. Modification by DNA methylation of the association of BMI or BMI change over 10 years with adult-onset asthma was examined at each CpG site and differentially methylated region. Pathway enrichment tests were conducted for genes in a priori curated inflammatory pathways and the NLRP3-IL1B-IL17 axis. The latter was chosen on the basis of previous work in mice. Inflammatory pathways including glucocorticoid/PPAR signaling (p = 0.0023), MAPK signaling (p = 0.013), NF-κB signaling (p = 0.031), and PI3K/AKT signaling (p = 0.031) were enriched for the effect modification of BMI, while NLRP3-IL1B-IL17 axis was enriched for the effect modification of BMI change over 10 years (p = 0.046). DNA methylation measured in peripheral blood is consistent with inflammation as a link between BMI and adult-onset asthma and with the NLRP3-IL1B-IL17 axis as a link between BMI change over 10 years and adult-onset asthma in non-atopic participants.

RNA and DNA Integrity Remain Stable in Frozen Tissue After Long-Term Storage at Cryogenic Temperatures: A Report from the Ontario Tumour Bank

Background: It is widely assumed that the integrity of tissue specimens remains stable indefinitely if preserved at cryogenic temperatures. With biobanking reaching a level of maturity where samples are increasingly stored for 10 years and beyond, this assumption of prolonged stability should be tested. Data from such an assessment are critical to verify if samples stored for extended durations remain "fit for purpose" or if there is need to reconsider the utility of samples stored beyond a certain timeframe. The Ontario Tumour Bank has been collecting samples since 2004, and assesses a random selection of frozen samples each year for RNA and DNA integrity as a part of ongoing quality control (QC) practices. This historical quality assessment data provide a unique opportunity to assess the impact of extended storage on nucleic acid integrity using replicate samples that remain in the bank in the present day as comparators. Methods: To examine the stability of fresh-frozen tumor tissue stored at cryogenic temperatures, RNA was extracted and analyzed from 87 cases over 14 disease sites stored long term in vapor-phase liquid nitrogen (LN2) (approximately -180°C). Historical QC data were compared against new data after re-extraction of replicate samples to determine the effect of extended storage on RNA quality. In addition, DNA was extracted from a subselection of samples (n = 20) to determine the effect of prolonged storage on DNA integrity. Results: No time-dependent decrease in tissue RNA or DNA quality, as measured by RNA integrity number (RIN) and DNA integrity number, was observed over an 11-year period. As a secondary observation, RNA integrity was not predictive of DNA integrity: DNA quality may still be very good, and as such RIN scores should not be used as a substitute indicator for evaluating DNA. Conclusions: Extended cryogenic storage beyond 2-11 years remains a viable option for maintaining the high quality of specimens in biobanks.

The comet assay for human biomonitoring: Effect of cryopreservation on DNA damage in different blood cell preparations

This study was designed within the frame of the COST Action hCOMET 15132 (Working Group 6), with the aim of comparing different peripheral blood cell preparations for their feasibility in human biomonitoring studies, using the comet assay for the evaluation of DNA damage. Basal levels of strand breaks/ALS and formamidopyrimidine DNA glycosylase (Fpg) - sites, and H₂O₂ (500 μM)-induced strand breaks, were measured in whole blood, peripheral blood mononuclear cells - lymphocytes and monocytes - and buffy coat; in fresh and 1, 4 and 12 weeks-frozen samples. The comparison among the fresh preparations showed that the basal levels of DNA damage were all very low and similar in the three samples. Frozen whole blood samples stored in cryostraws without cryoprotection showed similar basal levels of DNA damage as fresh samples, indicating that this preparation, often chosen for biobanks, resists efficiently freezing/thawing artifacts. However, long-term storage of frozen buffy coat samples in cryostraws and with no cryopreservative did not appear feasible. Storage up to 3 months of frozen cryoprotected peripheral blood mononuclear cells induced small increases in basal strand breaks and no other statistically significant modification. Altogether, this study suggests that whole blood could be the most suitable sample to be used to perform comet assay in human epidemiological biomonitoring for genotoxicity assessment in frozen samples, such as those stored in biobanks.

Age-Related Differences in miRNA Expression in Mexican-American Newborns and Children

Epigenetic mechanisms have emerged as an important pathway through which environmental exposures can affect health through the regulation of gene expression without changes in DNA sequence: microRNAs (miRNAs) are short non-coding RNAs that target protein-coding mRNAs, leading to post-transcriptional repression. They are involved in important physiologic processes, but little is known about how miRNA expression may change with age in children. We used an nCounter miRNA assay to assess the expression of 43 miRNAs in buffy coat samples collected from newborns (n = 121) and 7-year-old (n = 142) children. We identified 36 miRNAs that were differentially expressed between newborns and 7-year-olds after controlling for blood cell composition. Using pathway analysis, we found that differentially expressed miRNAs targeted genes enriched for processes related to post-translational modifications, metabolism, and immune response. Our study found that unlike adults, where miRNA expression levels in peripheral blood may decrease with age, expression levels of most miRNAs increased from birth to mid-childhood. This may be reflective of the role miRNAs may play in the highly coordinated mechanisms regulating genes involved in children's development. Furthermore, it will be important to adjust for both age and blood cell composition in future pediatric studies of miRNA expression in blood.

Identification of Sex-Specific Transcriptome Responses to Polychlorinated Biphenyls (PCBs)

PCBs are classified as xenoestrogens and carcinogens and their health risks may be sex-specific. To identify potential sex-specific responses to PCB-exposure we established gene expression profiles in a population study subdivided into females and males. Gene expression profiles were determined in a study population consisting of 512 subjects from the EnviroGenomarkers project, 217 subjects who developed lymphoma and 295 controls were selected in later life. We ran linear mixed models in order to find associations between gene expression and exposure to PCBs, while correcting for confounders, in particular distribution of white blood cells (WBC), as well as random effects. The analysis was subdivided according to sex and development of lymphoma in later life. The changes in gene expression as a result of exposure to the six studied PCB congeners were sex- and WBC type specific. The relatively large number of genes that are significantly associated with PCB-exposure in the female subpopulation already indicates different biological response mechanisms to PCBs between the two sexes. The interaction analysis between different PCBs and WBCs provides only a small overlap between sexes. In males, cancer-related pathways and in females immune system-related pathways are identified in association with PCBs and WBCs. Future lymphoma cases and controls for both sexes show different responses to the interaction of PCBs with WBCs, suggesting a role of the immune system in PCB-related cancer development.

Rapid, Reproducible, Quantifiable NMR Metabolomics: Methanol and Methanol: Chloroform Precipitation for Removal of Macromolecules in Serum and Whole Blood

Background: Though blood is an excellent biofluid for metabolomics, proteins and lipids present in blood can interfere with 1d-¹H NMR spectra and disrupt quantification of metabolites. Here, we present effective macromolecule removal strategies for serum and whole blood (WB) samples. Methods: A variety of macromolecule removal strategies were compared in both WB and serum, along with tests of ultrafiltration alone and in combination with precipitation methods. Results: In healthy human serum, methanol:chloroform:water extraction with ultrafiltration was compared to methanol precipitation with and without ultrafiltration. Methods were tested in healthy pooled human serum, and in serum from patients with sepsis. Effects of long-term storage at −80 °C were tested to explore the impact of macromolecule removal strategy on serum from different conditions. In WB a variety of extraction strategies were tested in two types of WB (from pigs and baboons) to examine the impact of macromolecule removal strategies on different samples. Conclusions: In healthy human serum methanol precipitation of serum with ultrafiltration was superior, but was similar in recovery and variance to methanol:chloroform:water extraction with ultrafiltration in pooled serum from patients with sepsis. In WB, high quality, quantifiable spectra were obtained with the use of a methanol: chloroform precipitation.

Epigenome-wide association study of adiposity and future risk of obesity-related diseases

BACKGROUND

Obesity is an established risk factor for several common chronic diseases such as breast and colorectal cancer, metabolic and cardiovascular diseases; however, the biological basis for these relationships is not fully understood. To explore the association of obesity with these conditions, we investigated peripheral blood leucocyte (PBL) DNA methylation markers for adiposity and their contribution to risk of incident breast and colorectal cancer and myocardial infarction.

METHODS

DNA methylation profiles (Illumina Infinium® HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waist-height ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population.

RESULTS

We identified 40 CpG loci with methylation levels associated with at least one adiposity measure. Of these, one CpG locus (cg06500161) in ABCG1 was associated with all four adiposity measures (P = 9.07×10-8 to 3.27×10-18) and lower transcriptional activity of the full-length isoform of ABCG1 (P = 6.00×10-7), higher triglyceride levels (P = 5.37×10-9) and higher triglycerides-to-HDL cholesterol ratio (P = 1.03×10-10). Of the 40 informative and obesity-related CpG loci, two (in IL2RB and FGF18) were significantly associated with colorectal cancer (inversely, P < 1.6×10-3) and one intergenic locus on chromosome 1 was inversely associated with myocardial infarction (P < 1.25×10-3), independently of obesity and established risk factors.

CONCLUSION

Our results suggest that epigenetic changes, in particular altered DNA methylation patterns, may be an intermediate biomarker at the intersection of obesity and obesity-related diseases, and could offer clues as to underlying biological mechanisms.

Impact of post-collection freezing delay on the reliability of serum metabolomics in samples reflecting the California mid-term pregnancy biobank

BACKGROUND

Population-based biorepositories are important resources, but sample handling can affect data quality.

OBJECTIVE

Identify metabolites of value for clinical investigations despite extended postcollection freezing delays, using protocols representing a California mid-term pregnancy biobank.

METHODS

Blood collected from non-pregnant healthy female volunteers (n = 20) underwent three handling protocols after 30 min clotting at room temperature: (1) ideal-samples frozen (- 80 °C) within 2 h of collection; (2) delayed freezing-samples held at room temperature for 3 days, then 4 °C for 9 days, the median times for biobank samples, and then frozen; (3) delayed freezing with freeze-thaw-the delayed freezing protocol with a freeze-thaw cycle simulating retrieved sample sub-aliquoting. Mass spectrometry-based untargeted metabolomic analyses of primary metabolism and complex lipids and targeted profiling of oxylipins, endocannabinoids, ceramides/sphingoid-bases, and bile acids were performed. Metabolite concentrations and intraclass correlation coefficients (ICC) were compared, with the ideal protocol as the reference.

RESULTS

Sixty-two percent of 428 identified compounds had good to excellent ICCs, a metric of concordance between measurements of samples handled with the different protocols. Sphingomyelins, phosphatidylcholines, cholesteryl esters, triacylglycerols, bile acids and fatty acid diols were the least affected by non-ideal handling, while sugars, organic acids, amino acids, monoacylglycerols, lysophospholipids, N-acylethanolamides, polyunsaturated fatty acids, and numerous oxylipins were altered by delayed freezing. Freeze-thaw effects were assay-specific with lipids being most stable.

CONCLUSIONS

Despite extended post-collection freezing delays characteristic of some biobanks of opportunistically collected clinical samples, numerous metabolomic compounds had both stable levels and good concordance.

Metabolomics in the study of retinal health and disease

Metabolomics is the qualitative and quantitative assessment of the metabolites (small molecules < 1.5 kDa) in body fluids. The metabolites are the downstream of the genetic transcription and translation processes and also downstream of the interactions with environmental exposures; thus, they are thought to closely relate to the phenotype, especially for multifactorial diseases. In the last decade, metabolomics has been increasingly used to identify biomarkers in disease, and it is currently recognized as a very powerful tool with great potential for clinical translation. The metabolome and the associated pathways also help improve our understanding of the pathophysiology and mechanisms of disease. While there has been increasing interest and research in metabolomics of the eye, the application of metabolomics to retinal diseases has been limited, even though these are leading causes of blindness. In this manuscript, we perform a comprehensive summary of the tools and knowledge required to perform a metabolomics study, and we highlight essential statistical methods for rigorous study design and data analysis. We review available protocols, summarize the best approaches, and address the current unmet need for information on collection and processing of tissues and biofluids that can be used for metabolomics of retinal diseases. Additionally, we critically analyze recent work in this field, both in animal models and in human clinical disease, including diabetic retinopathy and age-related macular degeneration. Finally, we identify opportunities for future research applying metabolomics to improve our current assessment and understanding of mechanisms of vitreoretinal diseases, and to hence improve patient assessment and care.

Obtaining High-Quality Blood Specimens for Downstream Applications: A Review of Current Knowledge and Best Practices

Blood is a biological fluid that contains multiple blood fraction and cellular components. High-quality blood specimens are essential prerequisites for various downstream applications such as molecular epidemiology studies, genomics, and proteomics studies. Currently, protocols and research publications concerning the collection, handling, preservation, and stability of blood or blood fractions are constantly emerging. Moreover, standardized guidelines are a requirement for biorepositories to tightly control preanalytical variables originating from these procedures and obtain high-quality blood specimen for downstream analyses. In this review article, we summarize the best practices and fit-for-purpose protocols regarding blood collection, processing, storage, and stability. In addition, we present some typical quality biomarkers, which could be used to evaluate the integrity of blood specimens.

Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow.