Antihistamines and azithromycin as a treatment for COVID-19 on primary health care - A retrospective observational study in elderly patients.

BACKGROUND: Between March and April 2020, 84 elderly patients with suspected COVID-19 living in two nursing homes of Yepes, Toledo (Spain) were treated early with antihistamines (dexchlorpheniramine, cetirizine or loratadine), adding azithromycin in the 25 symptomatic cases. The outcomes are retrospectively reported. The primary endpoint is the fatality rate of COVID-19. The secondary endpoints are the hospital and ICU admission rates. Endpoints were compared with the official Spanish rates for the elderly. The mean age of our population was 85 and 48% were over 80 years old. No hospital admissions, deaths, nor adverse drug effects were reported in our patient population. By the end of June, 100% of the residents had positive serology for COVID-19. Although clinical trials are needed to determine the efficacy of both drugs in the treatment of COVID-19, this analysis suggests that primary care diagnosis and treatment with antihistamines, plus azithromycin in selected cases, may treat COVID-19 and prevent progression to severe disease in elderly patients.

Omics Analysis and Quality Control Pipelines in a High-Performance Computing Environment.

Data quality is often an overlooked feature in the analysis of omics data. This is particularly relevant in studies of chemical and pathogen exposures that can modify an individual's epigenome and transcriptome with persistence over time. Portable, quality control (QC) pipelines for multiple different omics datasets are therefore needed. To meet these goals, portable quality assurance (QA) metrics, metric acceptability criterion, and pipelines to compute these metrics were developed and consolidated into one framework for 12 different omics assays. Performance of these QA metrics and pipelines were evaluated on human data generated by the Defense Advanced Research Projects Agency (DARPA) Epigenetic CHaracterization and Observation (ECHO) program. Twelve analytical pipelines were developed leveraging standard tools when possible. These QC pipelines were containerized using Singularity to ensure portability and scalability. Datasets for these 12 omics assays were analyzed and results were summarized. The quality thresholds and metrics used were described. We found that these pipelines enabled early identification of lower quality datasets, datasets with insufficient reads for additional sequencing, and experimental protocols needing refinements. These omics data analysis and QC pipelines are available as open-source resources as reported and discussed in this article for the omics and life sciences communities.

Antihistamines as an early treatment for Covid-19.

Infection with SARs-COV-2 results in COVID-19 disease. Between March 2020 and August 2021, 468 COVID-19 patients confirmed by PCR or antigen test, in Yepes, Spain, received early treatment with antihistamines, adding azithromycin in selected cases. The primary endpoint is the hospitalization rate of COVID-19 patients, and the secondary endpoints are ICU admission and mortality rates. All endpoints are compared with the official Spanish rates during the time period of the study. There were 20 hospital admissions (hospitalization rate 4,3%), 5 ICU admissions (ICU admission rate 1,1%) and 3 deaths (fatality rate of 0,6%). No patients in the study required follow up treatment, which suggest they did not develop long COVID. Results from this retrospective trail indicate that early treatment of SARS-COV-2 positive patients with antihistamines may reduce the odds of hospitalization (OR: 0.490, CI: 0.313-0.767, p-value: 0.001). Randomized controlled clinical trials are needed to further evaluate the effects of early antihistamine treatment of SARS-CoV-2 patients to prevent hospitalization, ICU admission, mortality and long-covid.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. SARS-CoV-2 infection is necessary but not sufficient for development of clinical COVID-19 disease. Currently, there are no approved pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We have investigated several plausible hypotheses for famotidine activity including antiviral and host-mediated mechanisms of action. We propose that the principal mechanism of action of famotidine for relieving COVID-19 symptoms involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release. Based on these findings and associated hypothesis, new COVID-19 multi-drug treatment strategies based on repurposing well-characterized drugs are being developed and clinically tested, and many of these drugs are available worldwide in inexpensive generic oral forms suitable for both outpatient and inpatient treatment of COVID-19 disease.

Analysis of complex DNA mixtures using massively parallel sequencing of SNPs with low minor allele frequencies.

DNA mixtures from 3 or more contributors have proven difficult to analyze using the current state-of-the-art method of short-tandem repeat (STR) amplification followed by capillary electrophoresis (CE). Here we analyze samples from both laboratory-defined mixtures and complex multi-contributor touch samples using a single nucleotide polymorphism (SNP) panel comprised of 2311 low-minor-allele-frequency loci, combined with massively parallel sequencing (MPS). This approach demonstrates that as many as 10 people can be identified in touch samples using a threshold of -Log P(RMNE) of 6, and a detection rate of 18-94 % across 10 different materials using a threshold of -Log P(RMNE) of 2. Thirty-two false positives were observed in 100 touch samples.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. Currently, there are no pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We explore several plausible avenues of activity including antiviral and host-mediated actions. We propose that the principal famotidine mechanism of action for COVID-19 involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release.

Estimating Individual Contributions to Complex DNA SNP Mixtures.

High-throughput sequencing (HTS) of large panels of single nucleotide polymorphisms (SNPs) provides an alternative or complimentary approach to short tandem repeats (STRs) panels for the analysis of complex DNA mixture forensic samples. For STRs, methods to estimate individual contribution concentrations compare capillary electrophoresis peak heights, peak areas, or HTS allele read counts within a mixture. This article introduces three approaches (mean, median, and slope methods) for estimating individual DNA contributions to forensic mixtures for HTS/massively parallel sequencing (MPS) SNP panels. For SNPs, the major:minor allele ratios or counts, unique to each contributor, were compared to estimate contributor proportion within the mixture using the mean, median, and slope intercept for these alleles. The estimates for these three methods were typically within 5% of planned experimental contributions for defined mixtures.

GrigoraSNPs: Optimized Analysis of SNPs for DNA Forensics.

High-throughput sequencing (HTS) of single nucleotide polymorphisms (SNPs) enables additional DNA forensic capabilities not attainable using traditional STR panels. However, the inclusion of sets of loci selected for mixture analysis, extended kinship, phenotype, biogeographic ancestry prediction, etc., can result in large panel sizes that are difficult to analyze in a rapid fashion. GrigoraSNP was developed to address the allele-calling bottleneck that was encountered when analyzing SNP panels with more than 5000 loci using HTS. GrigoraSNPs uses a MapReduce parallel data processing on multiple computational threads plus a novel locus-identification hashing strategy leveraging target sequence tags. This tool optimizes the SNP calling module of the DNA analysis pipeline with runtimes that scale linearly with the number of HTS reads. Results are compared with SNP analysis pipelines implemented with SAMtools and GATK. GrigoraSNPs removes a computational bottleneck for processing forensic samples with large HTS SNP panels.