Multi-variate statistical and machine learning reveals the interplay between sex and age in antibody responses to de novo SARS-CoV-2 infection and vaccination (preprint)

Prevention of negative COVID19 infection outcomes and infection/vaccine-acquired immunity is associated with the quality of antibody responses, whose variance by age and sex are poorly understood. Integrated, network approaches, identified sex and age effects in antibody responses and neutralization potential of de novo infection and vaccination throughout the Covid-19 pandemic. Cluster analysis found neutralization values followed SARS-CoV-2 specific receptor binding RIgG, spike SIgG and S and RIgA levels based on COVID19 status. Stochastic behavior tests and other analytical methods revealed sex differences only in persons <40y.o. Serum IgA antibody titers correlated with neutralization only in females 40-60y.o. Network analysis found males could improve IgA responses after vaccination dose 2, unlike >60 y.o. females. Complex correlation analyses found vaccination induced less antibody isotype switching and neutralization in older persons, especially in females. Sex dependent antibody & neutralization behavior decayed fastest in older males and with vaccination. Such sex and age characterization by machine learning can direct studies integrating cell mediated responses to define yet elusive correlates of protection and inform age and sex precision-focused vaccine design.

DAPTEV: Deep aptamer evolutionary modelling for COVID-19 drug design (preprint)

Typical drug discovery and development processes are costly, time consuming and often biased by expert opinion. Aptamers are short, single-stranded oligonucleotides (RNA/DNA) that bind to target proteins and other types of biomolecules. Compared with small-molecule drugs, aptamers can bind to their targets with high affinity (binding strength) and specificity (uniquely interacting with the target only). The conventional development process for aptamers utilizes a manual process known as Systematic Evolution of Ligands by Exponential Enrichment (SELEX), which is costly, slow, dependent on library choice and often produces aptamers that are not optimized. To address these challenges, in this research, we create an intelligent approach, named DAPTEV, for generating and evolving aptamer sequences to support aptamer-based drug discovery and development. Using the COVID-19 spike protein as a target, our computational results suggest that DAPTEV is able to produce structurally complex aptamers with strong binding affinities.

Relative Ratios of Human Seasonal Coronavirus Antibodies Predict the Efficiency of Cross-Neutralization of SARS-CoV-2 Spike Binding to ACE2 (preprint)

Antibodies raised against highly prevalent human seasonal coronaviruses (sCoVs), which are responsible for the common cold, are known to cross-react with SARS-CoV-2 antigens. This cross-reactivity prompts questions about their protective role against SARS-CoV-2 infections and COVID-19 disease severity. However, the relationship between sCoV exposure and SARS-CoV-2 correlates of protection have not been clearly identified. Here we performed a cross-sectional analysis of cross-reactivity and cross-neutralization to three SARS-CoV-2 antigens using pre-pandemic serum from four different groups: pediatrics and adolescents (<21 yrs of age), persons 21 to 70 yrs of age, persons older than 70 yrs of age, and persons living with HCV or HIV. We find that antibody cross-reactivity to SARS-CoV-2 antigens varied between 1.6% and 15.3% depending on the cohort and the isotype-antigen pair analyzed. We also demonstrate a broad range of neutralizing activity (0-45%) in pre-pandemic serum that interferes with SARS-CoV-2 spike attachment to ACE2. While the abundance of sCoV antibodies did not directly correlate with neutralization efficiency, by using machine learning methodologies, we show that neutralizing activity is rather dependent on the latent variables related to the pattern ratios of sCoVs antibodies presented by each person. These were independent of age or sex, and could be accurately predicted by comparing the relative ratios of IgGs in sera directed to NL63, 229E, HKU-1, and OC43 spike proteins. More specifically, we identified antibodies to NL63 and OC43 as being the two most important predictors of latent variables responsible for protection, and 229E as being the least weighted. Our data support that exposure to sCoVs triggers various cellular and immune responses that influence the efficiency of SARS-CoV-2 spike binding to ACE2, and may impact COVID-19 disease severity through various other latent variables.

Metabolomics and Computational Analysis of the Role of Monoamine Oxidase Activity in Delirium and SARS-COV-2 Infection (preprint)

Delirium is an acute change in attention and cognition occurring in ~65% of severe SARS-CoV-2 cases. It is also common following surgery and an indicator of brain vulnerability and risk for the development of dementia. In this work we analyzed the underlying role of metabolism in delirium-susceptibility in the postoperative setting using metabolomic profiling of cerebrospinal fluid and blood taken from the same patients prior to planned orthopaedic surgery. Distance correlation analysis and Random Forest (RF) feature selection were used to determine changes in metabolic networks. We found significant concentration 2 differences in several amino acids, acylcarnitines and polyamines linking delirium-prone patients to known factors in Alzheimer’s disease such as monoamine oxidase B (MAOB) protein. Subsequent computational structural comparison between MAOB and angiotensin converting enzyme 2 as well as protein-protein docking analysis showed that there potentially is strong binding of SARS-CoV-2 spike protein to MAOB. The possibility that SARS-CoV-2 influences MAOB activity leading to the observed neurological and platelet-based complications of SARS-CoV-2 infection requires further investigation.

Potential involvement of monoamine oxidase activity in SARS-COV2 infection and delirium onset (preprint)

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a range of extra-respiratory signs and symptoms. One such manifestation is delirium, an acute confusional state occurring in 60-70% of severe SARS-CoV-2 cases. Delirium is also a common clinical syndrome following planned orthopedic surgery. This investigation initially explored the underlying role of metabolism in delirium-susceptibility in this setting. Metabolomics profiles of cerebrospinal fluid (CSF) and blood taken prior to surgery found significant concentration differences of several amino acids, acylcarnitines and polyamines were observed in delirium-prone patients. Phenethylamine (PEA) concentrations in delirium-prone patients was significantly lower in CSF than in blood, whilst in age- and gender-matched controls the opposite was observed (adjusted p values: 1.8x10-6 (control) and 1.788x10-10 (delirium)). PEA is metabolised by monoamine oxidase B (MAOB), a putative enzyme target for the treatment of Alzheimers disease, Parkinsons disease and depression. Our computational structural comparisons of MAOB and angiotensin converting enzyme (ACE) 2 found high similarity, specifically within the SARS-CoV-2 spike protein. MAOB structural alignment to ACE2 was 51% overall, but this was over 95% in the ACE2-spike protein binding region. Thus, it is possible that the spike protein interacts with MAOB on a molecular level. A previously published metabolomic dataset of control subjects and patients with either mild or severe COVID-19 was then analysed. Major concentration differences in some metabolites attributed to altered MAO activity were detected. Therefore, our hypothesis is that the SARS-CoV-2 influences MAOB activity, which is one potential cause for the many observed neurological and platelet based complications of SARS-CoV-2 infection. Further research is required to establish what effect MAOB inhibitors might have on these pathways. There is no evidence at present to support the withholding of MAOB inhibitors.