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1.
J Med Virol ; 94(4): 1696-1700, 2022 04.
Article in English | MEDLINE | ID: covidwho-1718390

ABSTRACT

Emerging reports of SARS-CoV-2 breakthrough infections entail methodical genomic surveillance for determining the efficacy of vaccines. This study elaborates genomic analysis of isolates from breakthrough infections following vaccination with AZD1222/Covishield and BBV152/Covaxin. Variants of concern B.1.617.2 and B.1.1.7 responsible for cases surge in April-May 2021 in Delhi, were the predominant lineages among breakthrough infections.


Subject(s)
COVID-19/virology , SARS-CoV-2/genetics , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , ChAdOx1 nCoV-19/administration & dosage , Female , Genome, Viral/genetics , Genomics , Humans , India/epidemiology , Male , Middle Aged , Phylogeny , SARS-CoV-2/immunology , SARS-CoV-2/isolation & purification , Vaccination , Vaccines, Inactivated/administration & dosage , Young Adult
2.
Science ; 374(6570): 995-999, 2021 Nov 19.
Article in English | MEDLINE | ID: covidwho-1526449

ABSTRACT

Delhi, the national capital of India, experienced multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks in 2020 and reached population seropositivity of >50% by 2021. During April 2021, the city became overwhelmed by COVID-19 cases and fatalities, as a new variant, B.1.617.2 (Delta), replaced B.1.1.7 (Alpha). A Bayesian model explains the growth advantage of Delta through a combination of increased transmissibility and reduced sensitivity to immune responses generated against earlier variants (median estimates: 1.5-fold greater transmissibility and 20% reduction in sensitivity). Seropositivity of an employee and family cohort increased from 42% to 87.5% between March and July 2021, with 27% reinfections, as judged by increased antibody concentration after a previous decline. The likely high transmissibility and partial evasion of immunity by the Delta variant contributed to an overwhelming surge in Delhi.


Subject(s)
COVID-19/epidemiology , COVID-19/virology , Genome, Viral , Adolescent , Adult , COVID-19/immunology , COVID-19/transmission , Child , Humans , Immune Evasion , India/epidemiology , Molecular Epidemiology , Phylogeny , Reinfection , Seroepidemiologic Studies , Young Adult
5.
STAR Protoc ; 2(3): 100755, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1337008

ABSTRACT

Sequencing of SARS-CoV-2 genomes is crucial for understanding the genetic epidemiology of the COVID-19 pandemic. It is also critical for understanding the evolution of the virus and also for the rapid development of diagnostic tools. The present protocol is a modification of the Illumina COVIDSeq test. We describe an amplicon-based next-generation sequencing approach with short turnaround time, adapted for bench-top sequencers like MiSeq, iSeq, and MiniSeq. For complete details on the use and execution of this protocol, please refer to Bhoyar et al. (2021).


Subject(s)
COVID-19 Nucleic Acid Testing/methods , COVID-19 Nucleic Acid Testing/statistics & numerical data , COVID-19/diagnosis , Genome, Viral , High-Throughput Nucleotide Sequencing/methods , RNA, Viral/genetics , SARS-CoV-2/genetics , COVID-19/genetics , COVID-19/virology , High-Throughput Nucleotide Sequencing/standards , Humans , RNA, Viral/analysis , SARS-CoV-2/isolation & purification
6.
Pharmacogenomics ; 22(10): 603-618, 2021 07.
Article in English | MEDLINE | ID: covidwho-1278319

ABSTRACT

Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.


Subject(s)
COVID-19 Drug Treatment , COVID-19/genetics , Antiviral Agents/therapeutic use , Asian People , Drug Interactions/genetics , Genome/genetics , Genotype , Humans , India , Pharmacogenetics/methods , Pharmacogenomic Testing/methods , Pharmacogenomic Variants/genetics , SARS-CoV-2/drug effects
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