Finger stick blood collection for gene expression profiling and storage of tempus blood RNA tubes

Design of a targeted blood transcriptional panel for monitoring immunological changes accompanying pregnancy

Background

Immunomodulatory processes exert steering functions throughout pregnancy. Detecting diversions from this physiologic immune clock may help identify pregnant women at risk for pregnancy-associated complications. We present results from a data-driven selection process to develop a targeted panel of mRNAs that may prove effective in detecting pregnancies diverting from the norm.

Methods

Based on a de novo dataset from a resource-constrained setting and a dataset from a resource-rich area readily available in the public domain, whole blood gene expression profiles of uneventful pregnancies were captured at multiple time points during pregnancy. BloodGen3, a fixed blood transcriptional module repertoire, was employed to analyze and visualize gene expression patterns in the two datasets. Differentially expressed genes were identified by comparing their abundance to non-pregnant postpartum controls. The selection process for a targeted gene panel considered (i) transcript abundance in whole blood; (ii) degree of correlation with the BloodGen3 module; and (iii) pregnancy biology.

Results

We identified 176 transcripts that were complemented with eight housekeeping genes. Changes in transcript abundance were seen in the early stages of pregnancy and similar patterns were observed in both datasets. Functional gene annotation suggested significant changes in the lymphoid, prostaglandin and inflammation-associated compartments, when compared to the postpartum controls.

Conclusion

The gene panel presented here holds promise for the development of predictive, targeted, transcriptional profiling assays. Such assays might become useful for monitoring of pregnant women, specifically to detect potential adverse events early. Prospective validation of this targeted assay, in-depth investigation of functional annotations of differentially expressed genes, and assessment of common pregnancy-associated complications with the aim to identify these early in pregnancy to improve pregnancy outcomes are the next steps.

Characterization of the internal working-life exposome using minimally and non-invasive sampling methods - a narrative review

During recent years, we are moving away from the 'one exposure, one disease'-approach in occupational settings and towards a more comprehensive approach, taking into account the totality of exposures during a life course by using an exposome approach. Taking an exposome approach however is accompanied by many challenges, one of which, for example, relates to the collection of biological samples. Methods used for sample collection in occupational exposome studies should ideally be minimally invasive, while at the same time sensitive, and enable meaningful repeated sampling in a large population and over a longer time period. This might be hampered in specific situations e.g., people working in remote areas, during pandemics or with flexible work hours. In these situations, using self-sampling techniques might offer a solution. Therefore, our aim was to identify existing self-sampling techniques and to evaluate the applicability of these techniques in an occupational exposome context by conducting a literature review. We here present an overview of current self-sampling methodologies used to characterize the internal exposome. In addition, the use of different biological matrices was evaluated and subdivided based on their level of invasiveness and applicability in an occupational exposome context. In conclusion, this review and the overview of self-sampling techniques presented herein can serve as a guide in the design of future (occupational) exposome studies while circumventing sample collection challenges associated with exposome studies.

Technical assessment of different extraction methods and transcriptome profiling of RNA isolated from small volumes of blood

Transcriptome profiling of human whole blood is used to discover biomarkers of diseases and to assess phenotypic traits. Recently, finger-stick blood collection systems have allowed a less invasive and quicker collection of peripheral blood. Such non-invasive sampling of small volumes of blood offers practical advantages. The quality of gene expression data is strictly dependent on the steps used for the sample collection, extraction, preparation and sequencing. Here we have: (i) compared the manual and automated RNA extraction of small volumes of blood using the Tempus Spin RNA isolation kit and the MagMAX for Stabilized Blood RNA Isolation kit , respectively; and (ii) assessed the effect of TURBO DNA Free treatment on the transcriptomic data of RNA isolated from small volumes of blood. We have used the QuantSeq 3' FWD mRNA-Seq Library Prep kit to prepare RNA-seq libraries, which were sequenced on the Illumina NextSeq 500 system. The samples isolated manually displayed a higher variability in the transcriptomic data as compared to the other samples. The TURBO DNA Free treatment affected the RNA samples negatively, decreasing the RNA yield and reducing the quality and reproducibility of the transcriptomic data. We conclude that automated extraction systems should be preferred over manual extraction systems for data consistency, and that the TURBO DNA Free treatment should be avoided when working on RNA samples isolated manually from small volumes of blood.

Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model

Aims

Current non-invasive screening methods for cardiac allograft rejection have shown limited discrimination and are yet to be broadly integrated into heart transplant care. Given electrocardiogram (ECG) changes have been reported with severe cardiac allograft rejection, this study aimed to develop a deep-learning model, a form of artificial intelligence, to detect allograft rejection using the 12-lead ECG (AI-ECG).

Methods and results

Heart transplant recipients were identified across three Mayo Clinic sites between 1998 and 2021. Twelve-lead digital ECG data and endomyocardial biopsy results were extracted from medical records. Allograft rejection was defined as moderate or severe acute cellular rejection (ACR) based on International Society for Heart and Lung Transplantation guidelines. The extracted data (7590 unique ECG-biopsy pairs, belonging to 1427 patients) was partitioned into training (80%), validation (10%), and test sets (10%) such that each patient was included in only one partition. Model performance metrics were based on the test set (n = 140 patients; 758 ECG-biopsy pairs). The AI-ECG detected ACR with an area under the receiver operating curve (AUC) of 0.84 [95% confidence interval (CI): 0.78-0.90] and 95% (19/20; 95% CI: 75-100%) sensitivity. A prospective proof-of-concept screening study (n = 56; 97 ECG-biopsy pairs) showed the AI-ECG detected ACR with AUC = 0.78 (95% CI: 0.61-0.96) and 100% (2/2; 95% CI: 16-100%) sensitivity.

Conclusion

An AI-ECG model is effective for detection of moderate-to-severe ACR in heart transplant recipients. Our findings could improve transplant care by providing a rapid, non-invasive, and potentially remote screening option for cardiac allograft function.

High-temporal resolution profiling reveals distinct immune trajectories following the first and second doses of COVID-19 mRNA vaccines

Knowledge of the mechanisms underpinning the development of protective immunity conferred by mRNA vaccines is fragmentary. Here, we investigated responses to coronavirus disease 2019 (COVID-19) mRNA vaccination via high-temporal resolution blood transcriptome profiling. The first vaccine dose elicited modest interferon and adaptive immune responses, which peaked on days 2 and 5, respectively. The second vaccine dose, in contrast, elicited sharp day 1 interferon, inflammation, and erythroid cell responses, followed by a day 5 plasmablast response. Both post-first and post-second dose interferon signatures were associated with the subsequent development of antibody responses. Yet, we observed distinct interferon response patterns after each of the doses that may reflect quantitative or qualitative differences in interferon induction. Distinct interferon response phenotypes were also observed in patients with COVID-19 and were associated with severity and differences in duration of intensive care. Together, this study also highlights the benefits of adopting high-frequency sampling protocols in profiling vaccine-elicited immune responses.

Transcriptomic Profiles in Children With Septic Shock With or Without Immunoparalysis

Background

Severe innate immune suppression, termed immunoparalysis, is associated with increased risks of nosocomial infection and mortality in children with septic shock. Currently, immunoparalysis cannot be clinically diagnosed in children, and mechanisms remain unclear. Transcriptomic studies identify subsets of septic children with downregulation of genes within adaptive immune pathways, but assays of immune function have not been performed as part of these studies, and little is known about transcriptomic profiles of children with immunoparalysis.

Methods

We performed a nested case-control study to identify differences in RNA expression patterns between children with septic shock with immunoparalysis (defined as lipopolysaccharide (LPS)-induced tumor necrosis factor (TNF)α response < 200 pg/ml) vs those with normal LPS-induced TNFα response. Children were enrolled within 48 hours of the onset of septic shock and divided into two groups based on LPS-induced TNFα response. RNA was extracted from whole blood for RNAseq, differential expression analyses using DESeq2 software, and pathway analyses using Ingenuity Pathway Analysis.

Results

32 children were included in analyses. Comparing those with immunoparalysis (n =19) to those with normal TNFα response (n = 13), 2,303 transcripts were differentially expressed with absolute value fold change ≥ 1.5 and false discovery rate ≤ 0.05. The majority of downregulated pathways in children with immunoparalysis were pathways that involved interactions between innate and adaptive immune cells necessary for cell-mediated immunity, crosstalk between dendritic cells and natural killer cells, and natural killer cell signaling pathways. Upregulated pathways included those involved in humoral immunity (T helper cell type 2), corticotropin signaling, platelet activation (GP6 signaling), and leukocyte migration and extravasation.

Conclusions

Our study suggests that gene expression data might be useful to identify children with immunoparalysis and identifies several key differentially regulated pathways involved in both innate and adaptive immunity. Our ongoing work in this area aims to dissect interactions between innate and adaptive immunity in septic children and to more fully elucidate patient-specific immunologic pathophysiology to guide individualized immunotherapeutic targets.

Innate immune signatures to a partially-efficacious HIV vaccine predict correlates of HIV-1 infection risk

The pox-protein regimen tested in the RV144 trial is the only vaccine strategy demonstrated to prevent HIV-1 infection. Subsequent analyses identified antibody and cellular immune responses as correlates of risk (CoRs) for HIV infection. Early predictors of these CoRs could provide insight into vaccine-induced protection and guide efforts to enhance vaccine efficacy. Using specimens from a phase 1b trial of the RV144 regimen in HIV-1-uninfected South Africans (HVTN 097), we profiled innate responses to the first ALVAC-HIV immunization. PBMC transcriptional responses peaked 1 day post-vaccination. Type I and II interferon signaling pathways were activated, as were innate pathways critical for adaptive immune priming. We then identified two innate immune transcriptional signatures strongly associated with adaptive immune CoR after completion of the 4-dose regimen. Day 1 signatures were positively associated with antibody-dependent cellular cytotoxicity and phagocytosis activity at Month 6.5. Conversely, a signature present on Days 3 and 7 was inversely associated with Env-specific CD4+ T cell responses at Months 6.5 and 12; rapid resolution of this signature was associated with higher Env-specific CD4+ T-cell responses. These are the first-reported early immune biomarkers of vaccine-induced responses associated with HIV-1 acquisition risk in humans and suggest hypotheses to improve HIV-1 vaccine regimens.

The innate immune response is the body’s initial defense against pathogens and is linked to and shapes the subsequent adaptive immune response, which can confer long-lasting protection. For a vaccine with partial efficacy, such as the RV144 HIV vaccine regimen, identifying early innate responses that are linked with adaptive responses—particularly those for which evidence has accumulated that they might be important for protection—could help a more efficacious version be developed. In the HVTN 097 study, the RV144 prime-boost (ALVAC-HIV and AIDSVAX B/E) vaccine regimen was given to South African participants. We characterized the innate response to the first dose of ALVAC-HIV in these participants and identified gene expression signatures present within the first few days that were associated with antibody and T-cell responses to the full vaccine regimen measured up to 1 year later. As these antibody and T-cell responses have previously been implicated in protection, our findings suggest ways of refining the RV144 regimen and also have broader applications to vaccine development.

A Neutrophil-Driven Inflammatory Signature Characterizes the Blood Transcriptome Fingerprint of Psoriasis

Transcriptome profiling approaches have been widely used to investigate the mechanisms underlying psoriasis pathogenesis. Most researchers have measured changes in transcript abundance in skin biopsies; relatively few have examined transcriptome changes in the blood. Although less relevant to the study of psoriasis pathogenesis, blood transcriptome profiles can be readily compared across various diseases. Here, we used a pre-established set of 382 transcriptional modules as a common framework to compare changes in blood transcript abundance in two independent public psoriasis datasets. We then compared the resulting "transcriptional fingerprints" to those obtained for a reference set of 16 pathological or physiological states. The perturbations in blood transcript abundance in psoriasis were relatively subtle compared to the changes we observed in other autoimmune and auto-inflammatory diseases. However, we did observe a consistent pattern of changes for a set of modules associated with neutrophil activation and inflammation; interestingly, this pattern resembled that observed in patients with Kawasaki disease. This similarity between the blood-transcriptome signatures in psoriasis and Kawasaki disease suggests that the immune mechanisms driving their pathogenesis might be partially shared.

A modular framework for the development of targeted Covid-19 blood transcript profiling panels

BACKGROUND

Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of targeted blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection.

METHODS

We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates.

RESULTS

As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: immunological relevance, therapeutic development relevance and SARS biology relevance.

CONCLUSION

Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.

Influence of storage conditions of small volumes of blood on immune transcriptomic profiles

OBJECTIVE

Transcriptome analysis of human whole blood is used to discover biomarkers of diseases and to assess phenotypic traits. Here we have collected small volumes of blood in Tempus solution and tested whether different storage conditions have an impact on transcriptomic profiling. Fifty µl of blood were collected in 100µl of Tempus solutions, freezed at - 20 °C for 1 day and eventually thawed, stored and processed under five different conditions: (i) - 20 °C for 1 week; (ii) +4 °C for 1 week; (iii) room temperature for 1 week; (iv) room temperature for 1 day, - 20 °C for 1 day, room temperature until testing at day 7, (v) - 20 °C for 1 week, RNA was isolated and stored in GenTegra solution. We used 272 immune transcript specific assays to test the expression profiling using qPCR based Fluidigm BioMark HD dynamic array.

RESULTS

RNA yield ranged between 0.17 and 1.39µg. Except for one sample, RIN values were > 7. Using Principal Component Analysis, we saw that the storage conditions did not drive sample distribution. The condition that showed larger variability was the RT-FR-RT (room temperature-freezing-room temperature), suggesting that freezing-thawing cycles may have a worse effect on data reproducibility than keeping the samples at room temperature.

Investigating gene expression profiles of whole blood and peripheral blood mononuclear cells using multiple collection and processing methods

Gene expression profiling using blood samples is a valuable tool for biomarker discovery in clinical studies. Different whole blood RNA collection and processing methods are highly variable and might confound comparisons of results across studies. The main aim of the current study is to compare how blood storage, extraction methodologies, and the blood components themselves may influence gene expression profiling. Whole blood and peripheral blood mononuclear cell (PBMC) samples were collected in triplicate from five healthy donors. Whole blood was collected in RNAgard® and PAXgene® Blood RNA Tubes, as well as in collection tubes with anticoagulants such as dipotassium ethylenediaminetetraacetic acid (K2EDTA) and Acid Citrate Dextrose Solution A (ACD-A). PBMCs were separated using sodium citrate Cell Preparation Tubes (CPT™), FICOLL™, magnetic separation, and the LeukoLOCK™ methods. After blood collection, the LeukoLOCK™, K2EDTA and ACD-A blood tubes were shipped overnight using cold conditions and samples from the rest of the collection were immediately frozen with or without pre-processing. The RNA was isolated from whole blood and PBMCs using a total of 10 different experimental conditions employing several widely utilized RNA isolation methods. The RNA quality was assessed by RNA Integrity Number (RIN), which showed that all PBMC procedures had the highest RIN values when blood was stabilized in TRIzol® Reagent before RNA extraction. Initial data analysis showed that human blood stored and shipped at 4°C overnight performed equally well when checked for quality using RNA integrity number when compared to frozen stabilized blood. Comparisons within and across donor/method replicates showed signal-to-noise patterns which were not captured by RIN value alone. Pathway analysis using the top 1000 false discovery rate (FDR) corrected differentially expressed genes (DEGs) showed frozen vs. cold shipping conditions greatly impacted gene expression patterns in whole blood. However, the top 1000 FDR corrected DEGs from PBMCs preserved after frozen vs. cold shipping conditions (LeukoLOCK™ preserved in RNAlater®) revealed no significantly affected pathways. Our results provide novel insight into how RNA isolation, various storage, handling, and processing methodologies can influence RNA quality and apparent gene expression using blood samples. Careful consideration is necessary to avoid bias resulting from downstream processing. Better characterization of the effects of collection method idiosyncrasies will facilitate further research in understanding the effect of gene expression variability in human sample types.

A prospective cohort for the investigation of alteration in temporal transcriptional and microbiome trajectories preceding preterm birth: a study protocol

INTRODUCTION

Preterm birth (PTB) results from heterogeneous influences and is a major contributor to neonatal mortality and morbidity that continues to have adverse effects on infants beyond the neonatal period. This protocol describes the procedures to determine molecular signatures predictive of PTB through high-frequency sampling during pregnancy, at delivery and the postpartum period.

METHODS AND ANALYSIS

Four hundred first trimester pregnant women from either Myanmar or Thailand of either Karen or Burman ethnicity, with a viable, singleton pregnancy will be enrolled in this non-interventional, prospective pregnancy birth cohort study and will be followed through to the postpartum period. Fortnightly finger prick capillary blood sampling will allow the monitoring of genome-wide transcript abundance in whole blood. Collection of stool samples and vaginal swabs each trimester, at delivery and postpartum will allow monitoring of intestinal and vaginal microbial composition. In a nested case-control analysis, perturbations of transcript abundance in capillary blood as well as longitudinal changes of the gut, vaginal and oral microbiome will be compared between mothers giving birth to preterm and matched cases giving birth to term neonates. Placenta tissue of preterm and term neonates will be used to determine bacterial colonisation as well as for the establishment of coding and non-coding RNA profiles. In addition, RNA profiles of circulating, non-coding RNA in cord blood serum will be compared with those of maternal peripheral blood serum at time of delivery.

ETHICS AND DISSEMINATION

This research protocol that aims to detect perturbations in molecular trajectories preceding adverse pregnancy outcomes was approved by the ethics committee of the Faculty of Tropical Medicine, Mahidol University in Bangkok, Thailand (Ethics Reference: TMEC 15-062), the Oxford Tropical Research Ethics Committee (Ethics Reference: OxTREC: 33-15) and the local Tak Province Community Ethics Advisory Board. The results of this cooperative project will be disseminated in multiple publications staggered over time in international peer-reviewed scientific journals.

TRIAL REGISTRATION NUMBER

NCT02797327; Pre-results.

Finger stick blood collection for gene expression profiling and storage of tempus blood RNA tubes

With this report we aim to make available a standard operating procedure (SOP) developed for RNA stabilization of small blood volumes collected via a finger stick. The anticipation that this procedure may be improved through peer-review and/or readers public comments is another element motivating the publication of this SOP. Procuring blood samples from human subjects can, among other uses, enable assessment of the immune status of an individual subject via the profiling of RNA abundance using technologies such as real time PCR, NanoString, microarrays or RNA-sequencing. It is often desirable to minimize blood volumes and employ methods that are the least invasive and can be practically implemented outside of clinical settings. Finger stick blood samples are increasingly used for measurement of levels of pharmacological drugs and biological analytes. It is a simple and convenient procedure amenable for instance to field use or self-collection at home using a blood sample collection kit. Such methodologies should also enable the procurement of blood samples at high frequency for health or disease monitoring applications.