Rapid antigen detection tests (Ag-RDT) for SARS-CoV-2 with emergency use authorization generally include a condition of authorization to evaluate the test's performance in asymptomatic individuals ...when used serially. We aim to describe a novel study design that was used to generate regulatory-quality data to evaluate the serial use of Ag-RDT in detecting SARS-CoV-2 virus among asymptomatic individuals.
This prospective cohort study used a siteless, digital approach to assess longitudinal performance of Ag-RDT. Individuals over 2 years old from across the USA with no reported COVID-19 symptoms in the 14 days prior to study enrollment were eligible to enroll in this study. Participants throughout the mainland USA were enrolled through a digital platform between October 18, 2021 and February 15, 2022. Participants were asked to test using Ag-RDT and molecular comparators every 48 hours for 15 days. Enrollment demographics, geographic distribution, and SARS-CoV-2 infection rates are reported.
A total of 7361 participants enrolled in the study, and 492 participants tested positive for SARS-CoV-2, including 154 who were asymptomatic and tested negative to start the study. This exceeded the initial enrollment goals of 60 positive participants. We enrolled participants from 44 US states, and geographic distribution of participants shifted in accordance with the changing COVID-19 prevalence nationwide.
The digital site-less approach employed in the "Test Us At Home" study enabled rapid, efficient, and rigorous evaluation of rapid diagnostics for COVID-19 and can be adapted across research disciplines to optimize study enrollment and accessibility.
Adenosine-to-inosine (A-to-I) RNA editing is a conserved post-transcriptional mechanism mediated by ADAR enzymes that diversifies the transcriptome by altering selected nucleotides in RNA molecules. ...Although many editing sites have recently been discovered, the extent to which most sites are edited and how the editing is regulated in different biological contexts are not fully understood. Here we report dynamic spatiotemporal patterns and new regulators of RNA editing, discovered through an extensive profiling of A-to-I RNA editing in 8,551 human samples (representing 53 body sites from 552 individuals) from the Genotype-Tissue Expression (GTEx) project and in hundreds of other primate and mouse samples. We show that editing levels in non-repetitive coding regions vary more between tissues than editing levels in repetitive regions. Globally, ADAR1 is the primary editor of repetitive sites and ADAR2 is the primary editor of non-repetitive coding sites, whereas the catalytically inactive ADAR3 predominantly acts as an inhibitor of editing. Cross-species analysis of RNA editing in several tissues revealed that species, rather than tissue type, is the primary determinant of editing levels, suggesting stronger cis-directed regulation of RNA editing for most sites, although the small set of conserved coding sites is under stronger trans-regulation. In addition, we curated an extensive set of ADAR1 and ADAR2 targets and showed that many editing sites display distinct tissue-specific regulation by the ADAR enzymes in vivo. Further analysis of the GTEx data revealed several potential regulators of editing, such as AIMP2, which reduces editing in muscles by enhancing the degradation of the ADAR proteins. Collectively, our work provides insights into the complex cis- and trans-regulation of A-to-I editing.
The impact of sex on gene expression across human tissues Oliva, Meritxell; Muñoz-Aguirre, Manuel; Kim-Hellmuth, Sarah ...
Science (American Association for the Advancement of Science),
09/2020, Letnik:
369, Številka:
6509
Journal Article
Recenzirano
Odprti dostop
Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex ...differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.
Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying ...functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.
Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. ...Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.
The National Institutes of Health (NIH) Genotype-Tissue Expression (GTEx) project was designed to evaluate how genetic variation and epigenetic effects influence gene expression in normal tissue.
To ...ensure that the grossly normal-appearing tissues collected were free from disease, each specimen underwent histologic evaluation.
In total, nearly 30 000 tissue aliquots collected from almost 1000 postmortem donors underwent histologic review by project pathologists, and detailed observations of any abnormalities or lesions present were recorded.
Despite sampling of normal-appearing tissue, in-depth review revealed incidental findings among GTEx samples that included neoplastic, autoimmune, and genetic conditions; the incidence of some of these conditions among GTEx donors differed from those previously reported for other populations. A number of age-related abnormalities observed during histologic review of tissue specimens are also described.
Histologic findings from the GTEx project may serve to improve populational awareness of several conditions and present a unique opportunity for others to explore age- and gender-influenced conditions. Resources from the study, including histologic image and sequencing data, are publicly available for research.
The National Institutes of Health Genotype-Tissue Expression (GTEx) project was developed to elucidate how genetic variation influences gene expression in multiple normal tissues procured from ...postmortem donors.
To provide critical insight into a biospecimen's suitability for subsequent analysis, each biospecimen underwent quality assessment measures that included evaluation for underlying disease and potential effects introduced by preanalytic factors.
Electronic images of each tissue collected from nearly 1000 postmortem donors were evaluated by board-certified pathologists for the extent of autolysis, tissue purity, and the type and abundance of any extraneous tissue. Tissue-specific differences in the severity of autolysis and RNA integrity were evaluated, as were potential relationships between these markers and the duration of postmortem interval and rapidity of death.
Tissue-specific challenges in the procurement and preservation of the nearly 30 000 tissue specimens collected during the GTEx project are summarized. Differences in the degree of autolysis and RNA integrity number were observed among the 40 tissue types evaluated, and tissue-specific susceptibilities to the duration of postmortem interval and rapidity of death were observed.
Ninety-five percent of tissues were of sufficient quality to support RNA sequencing analysis. Biospecimens, annotated whole slide images, de-identified clinical data, and genomic data generated for GTEx represent a high-quality and comprehensive resource for the scientific community that has contributed to its use in approximately 1695 articles. Biospecimens and data collected under the GTEx project are available via the GTEx portal and authorized access to the Database of Genotypes and Phenotypes; procedures and whole slide images are available from the National Cancer Institute.
The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes (
...-eQTLs). More research is needed to identify effects of genetic variation on distant genes (
-eQTLs) and understand their biological mechanisms. One common
-eQTLs mechanism is "mediation" by a local (
) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are "
-mediators" of
-eQTLs, including those "
-hubs" involved in regulation of many
-genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying
-eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study
-mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of
-hubs and
-eQTL regulation across tissue types.
Despite widespread use of formalin-fixed, paraffin-embedded (FFPE) tissue in clinical and research settings, potential effects of variable tissue processing remain largely unknown.
To elucidate ...molecular effects associated with clinically relevant preanalytical variability, the National Cancer Institute initiated the Biospecimen Preanalytical Variables (BPV) program.
The BPV program, a well-controlled series of systematic, blind and randomized studies, investigated whether a delay to fixation (DTF) or time in fixative (TIF) affects the quantity and quality of DNA and RNA isolated from FFPE colon, kidney, and ovarian tumors in comparison to case-matched snap-frozen controls.
DNA and RNA yields were comparable among FFPE biospecimens subjected to different DTF and TIF time points. DNA and RNA quality metrics revealed assay- and time point-specific effects of DTF and TIF. A quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay was superior when assessing RNA quality, consistently detecting differences between FFPE and snap-frozen biospecimens and among DTF and TIF time points. RNA Integrity Number and DV
(representing the percentage of RNA fragments longer than 200 nucleotides) displayed more limited sensitivity. Differences in DNA quality (Q-ratio) between FFPE and snap-frozen biospecimens and among DTF and TIF time points were detected with a qPCR-based assay.
DNA and RNA quality may be adversely affected in some tumor types by a 12-hour DTF or a TIF of 72 hours. Results presented here as well as those of additional BPV molecular analyses underway will aid in the identification of acceptable delays and optimal fixation times, and quality assays that are suitable predictors of an FFPE biospecimen's fit-for-purpose.
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