Using Genome Sequence Data to Predict SARS-CoV-2 Detection Cycle Threshold Values (preprint)

The continuing emergence of SARS-CoV-2 variants of concern (VOCs) presents a serious public health threat, exacerbating the effects of the COVID19 pandemic. Although millions of genomes have been deposited in public archives since the start of the pandemic, predicting SARS-CoV-2 clinical characteristics from the genome sequence remains challenging. In this study, we used a collection of over 29,000 high quality SARS-CoV-2 genomes to build machine learning models for predicting clinical detection cycle threshold (Ct) values, which correspond with viral load. After evaluating several machine learning methods and parameters, our best model was a random forest regressor that used 10-mer oligonucleotides as features and achieved an R2 score of 0.521 +/- 0.010 (95% confidence interval over 5 folds) and an RMSE of 5.7 +/- 0.034, demonstrating the ability of the models to detect the presence of a signal in the genomic data. In an attempt to predict Ct values for newly emerging variants, we predicted Ct values for Omicron variants using models trained on previous variants. We found that approximately 5% of the data in the model needed to be from the new variant in order to learn its Ct values. Finally, to understand how the model is working, we evaluated the top features and found that the model is using a multitude of k-mers from across the genome to make the predictions. However, when we looked at the top k-mers that occurred most frequently across the set of genomes, we observed a clustering of k-mers that span spike protein regions corresponding with key variations that are hallmarks of the VOCs including G339, K417, L452, N501, and P681, indicating that these sites are informative in the model and may impact the Ct values that are observed in clinical samples.

How can we promote co-creation in communities? The perspective of health promoting professionals in four European countries

Purpose>The aim was to identify the competencies professionals need to promote co-creation engagement within communities.Design/methodology/approach>Co-creation could contribute to building community capacity to promote health. Professional development is key to support co-creative practices. Participants were professionals in a position to promote co-creation processes in health-promoting welfare settings across Denmark, Portugal, France and United Kingdom. An overarching unstructured topic guide was used within interviews, focus groups, questionnaires and creative activities.Findings>The need to develop competencies to promote co-creation was high across all countries. Creating a common understanding of co-creation and the processes involved to increase inclusivity, engagement and shared understanding was also necessary. Competencies included: How to run co-creation from the beginning of the process right through to evaluation, using feedback and communication throughout using an open action-oriented approach;initiating a perspective change and committing to the transformation of co-creation into a real-life process.Practical implications>Overall, learning about underlying principles, process initiation, implementation and facilitation of co-creation were areas identified to be included within a co-creation training programme. This can be applied through the framework of enabling change, advocating for co-creative processes, mediating through partnership, communication, leadership, assessment, planning, implementation, evaluation and research, ethical values and knowledge of co-creative processes.Originality/value>This study provides novel findings on the competencies needed for health promoting professionals to embed co-creative processes within their practice, and the key concerns that professionals with a position to mediate co-creation have in transferring the term of co-creation into a real-world practice.

Signals of significantly increased vaccine breakthrough, decreased hospitalization rates, and less severe disease in patients with COVID-19 caused by the Omicron variant of SARS-CoV-2 in Houston, Texas (preprint)

Genetic variants of SARS-CoV-2 continue to dramatically alter the landscape of the COVID-19 pandemic. The recently described variant of concern designated Omicron (B.1.1.529) has rapidly spread worldwide and is now responsible for the majority of COVID-19 cases in many countries. Because Omicron was recognized very recently, many knowledge gaps exist about its epidemiology, clinical severity, and disease course. A genome sequencing study of SARS-CoV-2 in the Houston Methodist healthcare system identified 4,468 symptomatic patients with infections caused by Omicron from late November 2021 through January 5, 2022. Omicron very rapidly increased in only three weeks to cause 90% of all new COVID-19 cases, and at the end of the study period caused 98% of new cases. Compared to patients infected with either Alpha or Delta variants in our healthcare system, Omicron patients were significantly younger, had significantly increased vaccine breakthrough rates, and were significantly less likely to be hospitalized. Omicron patients required less intense respiratory support and had a shorter length of hospital stay, consistent with on average decreased disease severity. Two patients with Omicron “stealth” sublineage BA.2 also were identified. The data document the unusually rapid spread and increased occurrence of COVID-19 caused by the Omicron variant in metropolitan Houston, and address the lack of information about disease character among US patients.

Analysis of the ARTIC version 3 and version 4 SARS-CoV-2 primers and their impact on the detection of the G142D amino acid substitution in the spike protein (preprint)

The ARTIC Network provides a common resource of PCR primer sequences and recommendations for amplifying SARS-CoV-2 genomes. The initial tiling strategy was developed with the reference genome Wuhan-01, and subsequent iterations have addressed areas of low amplification and sequence drop out. Recently, a new version (V4) was released, based on new variant genome sequences, in response to the realization that some V3 primers were located in regions with key mutations. Herein, we compare the performance of the ARTIC V3 and V4 primer sets with a matched set of 663 SARS-CoV-2 clinical samples sequenced with an Illumina NovaSeq 6000 instrument. We observe general improvements in sequencing depth and quality, and improved resolution of the SNP causing the D950N variation in the spike protein. Importantly, we also find nearly universal presence of spike protein substitution G142D in Delta-lineage samples. Due to the prior release and widespread use of the ARTIC V3 primers during the initial surge of the Delta variant, it is likely that the G142D amino acid substitution is substantially underrepresented among early Delta variant genomes deposited in public repositories. In addition to the improved performance of the ARTIC V4 primer set, this study also illustrates the importance of the primer scheme in downstream analyses. ImportanceARTIC Network primers are commonly used by laboratories worldwide to amplify and sequence SARS-CoV-2 present in clinical samples. As new variants have evolved and spread, it was found that the V3 primer set poorly amplified several key mutations. In this report, we compare the results of sequencing a matched set of samples with the V3 and V4 primer sets. We find that adoption of the ARTIC V4 primer set is critical for accurate sequencing of the SARS-CoV-2 spike region. The absence of metadata describing the primer scheme used will negatively impact the downstream use of publicly available SARS-Cov-2 sequencing reads and assembled genomes.

The rapid reemergence of seasonal respiratory viruses in Houston, Texas, after relaxing COVID-19 restrictions (preprint)

Brief abstract Implementation of measures to limit the spread of the SARS-CoV-2 virus at the start of the COVID-19 pandemic resulted in a rapid decrease in all other respiratory pathogens. As COVID-19 containment measures were relaxed, the first non-COVID respiratory viruses to return to prepandemic levels were members of the rhinovirus/enterovirus, followed by the rapid return of seasonal coronaviruses, parainfluenza, and respiratory syncytial virus after the complete removal of COVID-19 precautions at the state level, including an end to mask mandates. Inasmuch as COVID-19 has dominated the landscape of respiratory infections since early 2020, it is important for clinicians to recognize the return of non-COVID respiratory pathogens may be rapid and significant when COVID-19 containment measures are removed.

Identification and trajectory of growth of concerning SARS-CoV-2 variants in Houston, Texas, January through April 2021 based on 11,568 genome sequences (preprint)

Genetic variants of the SARS-CoV-2 virus are of substantial concern because they can detrimentally alter the pandemic course and disease features in individual patients. Here we report SARS-CoV-2 genome sequences from 12,476 patients in the Houston Methodist healthcare system diagnosed from January 1, 2021 through May 31, 2021. The SARS-CoV-2 variant designated U.K. B.1.1.7 increased rapidly and caused 63%-90% of all new cases in the Houston area in the latter half of May. Eleven of the 3,276 B.1.1.7 genomes had an E484K change in spike protein. Compared with non-B.1.1.7 patients, individuals with B.1.1.7 had a significantly lower cycle threshold value (a proxy for higher virus load) and significantly higher rate of hospitalization. Other variants (e.g., B.1.429, B.1.427, P.1, P.2, and R.1) also increased rapidly, although the magnitude was less than for B.1.1.7. We identified 22 patients infected with B.1.617 "India" variants; these patients had a high rate of hospitalization. Vaccine breakthrough cases (n=207) were caused by a heterogeneous array of virus genotypes, including many that are not variants of interest or concern. In the aggregate, our study delineates the trajectory of concerning SARS-CoV-2 variants circulating in a major metropolitan area, documents B.1.1.7 as the major cause of new cases in Houston, and heralds the arrival and spread of B.1.617 variants in the metroplex.

Rapid, widespread, and preferential increase of SARS-CoV-2 B.1.1.7 variant in Houston, TX, revealed by 8,857 genome sequences (preprint)

Genetic variants of the SARS-CoV-2 virus have become of great interest worldwide because they have the potential to detrimentally alter the course of the SARS-CoV-2 pandemic, and disease in individual patients. We recently sequenced 20,453 SARS- CoV-2 genomes from patients with COVID-19 disease in metropolitan Houston (population 7 million), dating from March 2020 to early February 2021. We discovered that all major variants of concern or interest are circulating in the region. To follow up on this discovery, we analyzed 8,857 genome sequences from patients in eight Houston Methodist hospitals dispersed throughout the metroplex diagnosed from January 1, 2021 to March 7, 2021. This sample represents 94% of Houston Methodist cases and 4.8% of all reported cases in metropolitan Houston during this period. We discovered rapid, widespread, and preferential increase of the SARS-CoV-2 UK B.1.1.7 throughout the region. The estimated case doubling time in the Houston area is 6.9 days. None of the 648 UK B.1.1.7 samples identified had the E484K change in spike protein that can cause decreased recognition by antibodies.