Predicting vaccine effectiveness against severe COVID-19 over time and against variants: a meta-analysis

Vaccine protection from symptomatic SARS-CoV-2 infection has been shown to be strongly correlated with neutralising antibody titres; however, this has not yet been demonstrated for severe COVID-19. To explore whether this relationship also holds for severe COVID-19, we performed a systematic search for studies reporting on protection against different SARS-CoV-2 clinical endpoints and extracted data from 15 studies. Since matched neutralising antibody titres were not available, we used the vaccine regimen, time since vaccination and variant of concern to predict corresponding neutralising antibody titres. We then compared the observed vaccine effectiveness reported in these studies to the protection predicted by a previously published model of the relationship between neutralising antibody titre and vaccine effectiveness against severe COVID-19. We find that predicted neutralising antibody titres are strongly correlated with observed vaccine effectiveness against symptomatic (Spearman ρ = 0.95, p < 0.001) and severe (Spearman ρ = 0.72, p < 0.001 for both) COVID-19 and that the loss of neutralising antibodies over time and to new variants are strongly predictive of observed vaccine protection against severe COVID-19

The magnitude and timing of recalled immunity after breakthrough infection is shaped by SARS-CoV-2 variants

Vaccination against SARS-CoV-2 protects from infection and improves clinical outcomes in breakthrough infections, likely reflecting residual vaccine-elicited immunity and recall of immunological memory. Here, we define the early kinetics of spike-specific humoral and cellular immunity after vaccination of seropositive individuals and after Delta or Omicron breakthrough infection in vaccinated individuals. Early longitudinal sampling revealed the timing and magnitude of recall, with the phenotypic activation of B cells preceding an increase in neutralizing antibody titers. While vaccination of seropositive individuals resulted in robust recall of humoral and T cell immunity, recall of vaccine-elicited responses was delayed and variable in magnitude during breakthrough infections and depended on the infecting variant of concern. While the delayed kinetics of immune recall provides a potential mechanism for the lack of early control of viral replication, the recall of antibodies coincided with viral clearance and likely underpins the protective effects of vaccination against severe COVID-19

Monoclonal antibody levels and protection from COVID-19

Multiple monoclonal antibodies have been shown to be effective for both prophylaxis and therapy for SARS-CoV-2 infection. Here we aggregate data from randomized controlled trials assessing the use of monoclonal antibodies (mAb) in preventing symptomatic SARS-CoV-2 infection. We use data on the in vivo concentration of mAb and the associated protection from COVID-19 over time to model the dose-response relationship of mAb for prophylaxis. We estimate that 50% protection from COVID-19 is achieved with a mAb concentration of 96-fold of the in vitro IC50 (95% CI: 32—285). This relationship provides a tool for predicting the prophylactic efficacy of new mAb and against SARS-CoV-2 variants. Finally, we compare the relationship between neutralization titer and protection from COVID-19 after either mAb treatment or vaccination. We find no significant difference between the 50% protective titer for mAb and vaccination, although sample sizes limited the power to detect a difference

Determinants of passive antibody efficacy in SARS-CoV-2 infection: a systematic review and meta-analysis

Background: Randomised controlled trials of passive antibodies as treatment and prophylaxis for COVID-19 have reported variable efficacy. However, the determinants of efficacy have not been identified. We aimed to assess how the dose and timing of administration affect treatment outcome. Methods: In this systematic review and meta-analysis, we extracted data from published studies of passive antibody treatment from Jan 1, 2019, to Jan 31, 2023, that were identified by searching multiple databases, including MEDLINE, PubMed, and ClinicalTrials.gov. We included only randomised controlled trials of passive antibody administration for the prevention or treatment of COVID-19. To compare administered antibody dose between different treatments, we used data on in-vitro neutralisation titres to normalise dose by antibody potency. We used mixed-effects regression and model fitting to analyse the relationship between timing, dose and efficacy. Findings: We found 58 randomised controlled trials that investigated passive antibody therapies for the treatment or prevention of COVID-19. Earlier clinical stage at treatment initiation was highly predictive of the efficacy of both monoclonal antibodies (p<0·0001) and convalescent plasma therapy (p=0·030) in preventing progression to subsequent stages, with either prophylaxis or treatment in outpatients showing the greatest effects. For the treatment of outpatients with COVID-19, we found a significant association between the dose administered and efficacy in preventing hospitalisation (relative risk 0·77; p<0·0001). Using this relationship, we predicted that no approved monoclonal antibody was expected to provide more than 30% efficacy against some omicron (B.1.1.529) subvariants, such as BQ.1.1. Interpretation: Early administration before hospitalisation and sufficient doses of passive antibody therapy are crucial to achieving high efficacy in preventing clinical progression. The relationship between dose and efficacy provides a framework for the rational assessment of future passive antibody prophylaxis and treatment strategies for COVID-19. Funding: The Australian Government Department of Health, Medical Research Future Fund, National Health and Medical Research Council, the University of New South Wales, Monash University, Haematology Society of Australia and New Zealand, Leukaemia Foundation, and the Victorian Government

Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data

Background: MicroRNAs (miRNAs) are short, non-coding RNA regulators of protein coding genes. miRNAs play a very important role in diverse biological processes and various diseases. Many algorithms are able to predict miRNA genes and their targets, but their transcription regulation is still under investigation. It is generally believed that intragenic miRNAs (located in introns or exons of protein coding genes) are co-transcribed with their host genes and most intergenic miRNAs transcribed from their own RNA polymerase II (Pol II) promoter. However, the length of the primary transcripts and promoter organization is currently unknown. Methodology: We performed Pol II chromatin immunoprecipitation (ChIP)-chip using a custom array surrounding regions of known miRNA genes. To identify the true core transcription start sites of the miRNA genes we developed a new tool (CPPP). We showed that miRNA genes can be transcribed from promoters located several kilobases away and that their promoters share the same general features as those of protein coding genes. Finally, we found evidence that as many as 26% of the intragenic miRNAs may be transcribed from their own unique promoters. Conclusion: miRNA promoters have similar features to those of protein coding genes, but miRNA transcript organization is more complex. © 2009 Corcoran et al

Logopenic and nonfluent variants of primary progressive aphasia are differentiated by acoustic measures of speech production

Differentiation of logopenic (lvPPA) and nonfluent/agrammatic (nfvPPA) variants of Primary Progressive Aphasia is important yet remains challenging since it hinges on expert based evaluation of speech and language production. In this study acoustic measures of speech in conjunction with voxel-based morphometry were used to determine the success of the measures as an adjunct to diagnosis and to explore the neural basis of apraxia of speech in nfvPPA. Forty-one patients (21 lvPPA, 20 nfvPPA) were recruited from a consecutive sample with suspected frontotemporal dementia. Patients were diagnosed using the current gold-standard of expert perceptual judgment, based on presence/absence of particular speech features during speaking tasks. Seventeen healthy age-matched adults served as controls. MRI scans were available for 11 control and 37 PPA cases; 23 of the PPA cases underwent amyloid ligand PET imaging. Measures, corresponding to perceptual features of apraxia of speech, were periods of silence during reading and relative vowel duration and intensity in polysyllable word repetition. Discriminant function analyses revealed that a measure of relative vowel duration differentiated nfvPPA cases from both control and lvPPA cases (r2 = 0.47) with 88% agreement with expert judgment of presence of apraxia of speech in nfvPPA cases. VBM analysis showed that relative vowel duration covaried with grey matter intensity in areas critical for speech motor planning and programming: precentral gyrus, supplementary motor area and inferior frontal gyrus bilaterally, only affected in the nfvPPA group. This bilateral involvement of frontal speech networks in nfvPPA potentially affects access to compensatory mechanisms involving right hemisphere homologues. Measures of silences during reading also discriminated the PPA and control groups, but did not increase predictive accuracy. Findings suggest that a measure of relative vowel duration from of a polysyllable word repetition task may be sufficient for detecting most cases of apraxia of speech and distinguishing between nfvPPA and lvPPA

Evaluation of qPCR-Based Assays for Leprosy Diagnosis Directly in Clinical Specimens

The increased reliability and efficiency of the quantitative polymerase chain reaction (qPCR) makes it a promising tool for performing large-scale screening for infectious disease among high-risk individuals. To date, no study has evaluated the specificity and sensitivity of different qPCR assays for leprosy diagnosis using a range of clinical samples that could bias molecular results such as difficult-to-diagnose cases. In this study, qPCR assays amplifying different M. leprae gene targets, sodA, 16S rRNA, RLEP and Ag 85B were compared for leprosy differential diagnosis. qPCR assays were performed on frozen skin biopsy samples from a total of 62 patients: 21 untreated multibacillary (MB), 26 untreated paucibacillary (PB) leprosy patients, as well as 10 patients suffering from other dermatological diseases and 5 healthy donors. To develop standardized protocols and to overcome the bias resulted from using chromosome count cutoffs arbitrarily defined for different assays, decision tree classifiers were used to estimate optimum cutoffs and to evaluate the assays. As a result, we found a decreasing sensitivity for Ag 85B (66.1%), 16S rRNA (62.9%), and sodA (59.7%) optimized assay classifiers, but with similar maximum specificity for leprosy diagnosis. Conversely, the RLEP assay showed to be the most sensitive (87.1%). Moreover, RLEP assay was positive for 3 samples of patients originally not diagnosed as having leprosy, but these patients developed leprosy 5–10 years after the collection of the biopsy. In addition, 4 other samples of patients clinically classified as non-leprosy presented detectable chromosome counts in their samples by the RLEP assay suggesting that those patients either had leprosy that was misdiagnosed or a subclinical state of leprosy. Overall, these results are encouraging and suggest that RLEP assay could be useful as a sensitive diagnostic test to detect M. leprae infection before major clinical manifestations

Assessment of clusters of transcription factor binding sites in relationship to human promoter, CpG islands and gene expression

BACKGROUND: Gene expression is regulated mainly by transcription factors (TFs) that interact with regulatory cis-elements on DNA sequences. To identify functional regulatory elements, computer searching can predict TF binding sites (TFBS) using position weight matrices (PWMs) that represent positional base frequencies of collected experimentally determined TFBS. A disadvantage of this approach is the large output of results for genomic DNA. One strategy to identify genuine TFBS is to utilize local concentrations of predicted TFBS. It is unclear whether there is a general tendency for TFBS to cluster at promoter regions, although this is the case for certain TFBS. Also unclear is the identification of TFs that have TFBS concentrated in promoters and to what level this occurs. This study hopes to answer some of these questions. RESULTS: We developed the cluster score measure to evaluate the correlation between predicted TFBS clusters and promoter sequences for each PWM. Non-promoter sequences were used as a control. Using the cluster score, we identified a PWM group called PWM-PCP, in which TFBS clusters positively correlate with promoters, and another PWM group called PWM-NCP, in which TFBS clusters negatively correlate with promoters. The PWM-PCP group comprises 47% of the 199 vertebrate PWMs, while the PWM-NCP group occupied 11 percent. After reducing the effect of CpG islands (CGI) against the clusters using partial correlation coefficients among three properties (promoter, CGI and predicted TFBS cluster), we identified two PWM groups including those strongly correlated with CGI and those not correlated with CGI. CONCLUSION: Not all PWMs predict TFBS correlated with human promoter sequences. Two main PWM groups were identified: (1) those that show TFBS clustered in promoters associated with CGI, and (2) those that show TFBS clustered in promoters independent of CGI. Assessment of PWM matches will allow more positive interpretation of TFBS in regulatory regions

RBF-TSS: Identification of Transcription Start Site in Human Using Radial Basis Functions Network and Oligonucleotide Positional Frequencies

Accurate identification of promoter regions and transcription start sites (TSS) in genomic DNA allows for a more complete understanding of the structure of genes and gene regulation within a given genome. Many recently published methods have achieved high identification accuracy of TSS. However, models providing more accurate modeling of promoters and TSS are needed. A novel identification method for identifying transcription start sites that improves the accuracy of TSS recognition for recently published methods is proposed. This method incorporates a metric feature based on oligonucleotide positional frequencies, taking into account the nature of promoters. A radial basis function neural network for identifying transcription start sites (RBF-TSS) is proposed and employed as a classification algorithm. Using non-overlapping chunks (windows) of size 50 and 500 on the human genome, the proposed method achieves an area under the Receiver Operator Characteristic curve (auROC) of 94.75% and 95.08% respectively, providing increased performance over existing TSS prediction methods

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response