Adhatoda vasica and Tinospora cordifolia extracts ameliorate clinical and molecular markers in mild COVID-19 patients: a randomized open-label three-armed study.

BACKGROUND: SARS-CoV-2 infections caused mild-to-moderate illness. However, a sizable portion of infected people experience a rapid progression of hyper-inflammatory and hypoxic respiratory illness that necessitates an effective and safer remedy to combat COVID-19. METHODS: A total of 150 COVID-19-positive patients with no to mild symptoms, between the age groups 19-65 years were enrolled in this randomized, open-labeled three-armed clinical trial. Among them, 136 patients completed the study with RT-PCR negative reports. The patients received herbal drugs orally (Group A (Adhatoda vasica; AV; 500 mg; n = 50); Group B (Tinospora cordifolia; TC; 500 mg; n = 43), and Group C (AV + TC; 250 mg each; n = 43)) for 14 days. Clinical symptoms, vital parameters, and viral clearance were taken as primary outcomes, and biochemical, hematological parameters, cytokines, and biomarkers were evaluated at three time points as secondary outcomes. RESULTS: We found that the mean viral clearance time was 13.92 days (95% confidence interval [CI] 12.85-14.99) in Group A, 13.44 days (95% confidence interval [CI] 12.14-14.74) in Group B, and 11.86 days (95% confidence interval [CI] 10.62-13.11) days in Group C. Over a period of 14 days, the mean temperature in Groups A, and B significantly decreased linearly. In Group A, during the trial period, eosinophils, and PT/INR increased significantly, while monocytes, SGOT, globulin, serum ferritin, and HIF-1α, a marker of hypoxia reduced significantly. On the other hand, in Group B hsCRP decreased at mid-treatment. Eosinophil levels increased in Group C during the treatment, while MCP-3 levels were significantly reduced. CONCLUSIONS: All the patients of the three-armed interventions recovered from COVID-19 and none of them reported any adverse effects from the drugs. Group C patients (AV + TC) resulted in a quicker viral clearance as compared to the other two groups. We provide the first clinical report of AV herbal extract acting as a modifier of HIF-1α in COVID-19 patients along with a reduction in levels of ferritin, VEGF, and PT/INR as the markers of hypoxia, inflammation, and thrombosis highlighting the potential use in progression stages, whereas the TC group showed immunomodulatory effects. Trial registration Clinical Trials Database -India (ICMR-NIMS), CTRI/2020/09/028043. Registered 24th September 2020, https://www.ctri.nic.in/Clinicaltrials/pdf_generate.php?trialid=47443&EncHid=&modid=&compid=%27,%2747443det%27.

HLA-SPREAD: a natural language processing based resource for curating HLA association from PubMed abstracts.

Extreme complexity in the Human Leukocyte Antigens (HLA) system and its nomenclature makes it difficult to interpret and integrate relevant information for HLA associations with diseases, Adverse Drug Reactions (ADR) and Transplantation. PubMed search displays ~ 146,000 studies on HLA reported from diverse locations. Currently, IPD-IMGT/HLA (Robinson et al., Nucleic Acids Research 48:D948-D955, 2019) database houses data on 28,320 HLA alleles. We developed an automated pipeline with a unified graphical user interface HLA-SPREAD that provides a structured information on SNPs, Populations, REsources, ADRs and Diseases information. Information on HLA was extracted from ~ 28 million PubMed abstracts extracted using Natural Language Processing (NLP). Python scripts were used to mine and curate information on diseases, filter false positives and categorize to 24 tree hierarchical groups and named Entity Recognition (NER) algorithms followed by semantic analysis to infer HLA association(s). This resource from 109 countries and 40 ethnic groups provides interesting insights on: markers associated with allelic/haplotypic association in autoimmune, cancer, viral and skin diseases, transplantation outcome and ADRs for hypersensitivity. Summary information on clinically relevant biomarkers related to HLA disease associations with mapped susceptible/risk alleles are readily retrievable from HLASPREAD. The resource is available at URL http://hla-spread.igib.res.in/ . This resource is first of its kind that can help uncover novel patterns in HLA gene-disease associations.