SARS-CoV-2 genomic surveillance in Malaysia: displacement of B.1.617.2 with AY lineages as the dominant Delta variants and the introduction of Omicron during the fourth epidemic wave

Azami, Nor Azila Muhammad; Perera, David; Thayan, Ravindran; Bakar, Sazaly Abu; Sam, I‐Ching; Salleh, Mohd Zaki; Mat-Isa, Mohd-Noor; Mutalib, Nurul Syakima Ab; Aik, Wong Kiing; Suppiah, Jeyanthi; Tan, Kian Lam; Chan, Yoke Fun; Teh, Lay Kek; Azzam, Ghows; Rasheed, Zahirrah Begam Mohamed; Chan, Jonathan Chia Jui; Kamel, Khayri Azizi; Tan, Jia-Yi; Rahman, Omar Khalilur; Lim, Wai Feng; Johari, Nor Azfa; Ishak, Muhiddin; Yunos, Ryia Illani Mohd; Anasir, Mohd Ishtiaq; Wong, Jo-Ern; Fu, Jolene Yin Ling; Noorizhab, Mohd Nur Fakhruzzaman; Sapian, Irni Suhayu; Mokhtar, Mira Farzana Mohamad; Shahri, Nur Alyaa Afifah Md; Ghafar, Khairun Nur Abdul; Yusuf, Siti Nur Hasanah Mohd; Noor, Yusuf Muhammad; Jamal, Rahman

doi:10.1016/j.ijid.2022.10.044

Cited by 14 publications

(7 citation statements)

References 23 publications

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“…Our study has revealed a significant link between higher comorbidity counts and enhanced mutations within the SARS-CoV-2 virus. Previous studies showed that comorbidities that are associated with higher ACE2 expression may enhance the virus entry and the severity of COVID-19 infection [ 23 ]. It is possible that comorbidities contribute to the enhanced systemic inflammation releases reactive oxygen species and drives mutations.…”

Section: Discussionmentioning

confidence: 99%

Unravelling the link between SARS-CoV-2 mutation frequencies, patient comorbidities, and structural dynamics

Azzeri,

Mohamed,

Wan Rosli

et al. 2024

PLoS ONE

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Genomic surveillance is crucial for tracking emergence and spread of novel variants of pathogens, such as SARS-CoV-2, to inform public health interventions and to enforce control measures. However, in some settings especially in low- and middle- income counties, where sequencing platforms are limited, only certain patients get to be selected for sequencing surveillance. Here, we show that patients with multiple comorbidities potentially harbour SARS-CoV-2 with higher mutation rates and thus deserve more attention for genomic surveillance. The relationship between the patient comorbidities, and type of amino acid mutations was assessed. Correlation analysis showed that there was a significant tendency for mutations to occur within the ORF1a region for patients with higher number of comorbidities. Frequency analysis of the amino acid substitution within ORF1a showed that nsp3 P822L of the PLpro protease was one of the highest occurring mutations. Using molecular dynamics, we simulated that the P822L mutation in PLpro represents a system with lower Root Mean Square Deviation (RMSD) fluctuations, and consistent Radius of gyration (Rg), Solvent Accessible Surface Area (SASA) values—indicate a much stabler protein than the wildtype. The outcome of this study will help determine the relationship between the clinical status of a patient and the mutations of the infecting SARS-CoV-2 virus.

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Section: Discussionmentioning

confidence: 99%

Unravelling the link between SARS-CoV-2 mutation frequencies, patient comorbidities, and structural dynamics

Azzeri,

Mohamed,

Wan Rosli

et al. 2024

PLoS ONE

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show abstract

“…The first Omicron variant, B.1.1, was detected in Sabah in February 2022, a few months after the detection from West Malaysia. Travellers visiting Middle Eastern countries introduced the first imported Omicron cases in Malaysia [ 49 ]. After replacing the Delta variant, Omicron caused a sharp increase in the number of COVID-19 cases, but the severity of the disease was reduced compared to the previous variant [ 24 ].…”

Section: Discussionmentioning

confidence: 99%

“…Since most of the samples from Sabah were sequenced during the fourth and fifth waves of the pandemic, the mutational analysis in this study was mainly focused on Delta and Omicron variants. The most common mutations found in both West Malaysia and Sabah were a nonsynonymous mutation in the S protein, Spike_D614G, and a missense mutation of a segment of ORF1ab encoding the RNA-dependent RNA polymerase, NSP12_P323L, with a frequency of 99% in both regions [ 49 ]. Interestingly, about 99.5% of a synonymous mutation in the predicted phosphodiesterase papain-like proteinase (NSP3) mutation, F106F, was detected in West Malaysia and Sarawak but was absent in the Sabah samples.…”

Section: Discussionmentioning

confidence: 99%

Timeline of SARS-CoV-2 Transmission in Sabah, Malaysia: Tracking the Molecular Evolution

et al. 2023

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Background: The COVID-19 pandemic poses an unprecedented public health challenge in Malaysia. The impact of COVID-19 varies between countries, including geographically divided states within a country. The deadly transmission of COVID-19 has taken a heavy toll in Sabah, Malaysia’s third most populous state, contributing nearly 10% to the recorded national death toll as of 31 December 2022. Although several SARS-CoV-2 genome sequences have been analysed in Malaysia, molecular epidemiology data from Sabah focusing on the diversity and evolution of SARS-CoV-2 variants are still lacking. This study examines the major SARS-CoV-2 variants and emerging mutations from Sabah, the Malaysian Borneo, which is geographically divided from West Malaysia by the South China Sea. Methods: A total of 583 COVID-19 samples were subjected to whole genome sequencing and analysed with an additional 1123 Sabah COVID-19 sequences retrieved from the GISAID EpiCoV consortium. Nextclade and Pangolin were used to classify these sequences according to the clades and lineages. To determine the molecular evolutionary characteristics, Bayesian time-scaled phylogenetic analysis employing the maximum likelihood algorithm was performed on selected SARS-CoV-2 genome sequences, using the Wuhan-Hu-1 sequence as a reference. Results: Sabah was affected starting from the second COVID-19 wave in Malaysia, and the early sequences were classified under the O clade. The clade was gradually replaced during subsequent waves by G, GH, GK and GRA, with the latter being dominant as of December 2022. Phylogenetically, the Delta isolates in this study belong to the three main subclades 21A, 21J and 21I, while Omicron isolates belong to 21M, 21L and 22B. The time-scaled phylogeny suggested that SARS-CoV-2 introduced into Sabah originated from Peninsular Malaysia in early March 2020, and phylodynamic analysis indicated that increased viral spread was observed in early March and declined in late April, followed by an evolutionary stationary phase in June 2020. Conclusion: Continuous molecular epidemiology of SARS-CoV-2 in Sabah will provide a deeper understanding of the emergence and dominance of each variant in the locality, thus facilitating public health intervention measures.

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“…The predominance of the strain in Sarawak coincides with and is similar to the circulating predominant strain in Indonesia from March to May 2021 [ 54 ]. It was suggested that the variant that predominates the Pasai cluster could have originated locally [ 55 ], further facilitating the rapidity of the virus transmission in a population where immunity is none [ 56 ].…”

Section: Discussionmentioning

confidence: 99%

Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia

et al. 2023

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Background In Sarawak, 252 300 coronavirus disease 2019 (COVID-19) cases have been recorded with 1 619 fatalities in 2021, compared to only 1 117 cases in 2020. Since Sarawak is geographically separated from Peninsular Malaysia and half of its population resides in rural districts where medical resources are limited, the analysis of spatiotemporal heterogeneity of disease incidence rates and their relationship with socio-demographic factors are crucial in understanding the spread of the disease in Sarawak. Methods The spatial dependence of district-wise incidence rates is investigated using spatial autocorrelation analysis with two orders of contiguity weights for various pandemic waves. Nine determinants are chosen from 14 covariates of socio-demographic factors via elastic net regression and recursive partitioning. The relationships between incidence rates and socio-demographic factors are examined using ordinary least squares, spatial lag and spatial error models, and geographically weighted regression. Results In the first 8 months of 2021, COVID-19 severely affected Sarawak’s central region, which was followed by the southern region in the next 2 months. In the third wave, based on second-order spatial weights, the incidence rate in a district is most strongly influenced by its neighboring districts’ rate, although the variance of incidence rates is best explained by local regression coefficient estimates of socio-demographic factors in the first wave. It is discovered that the percentage of households with garbage collection facilities, population density and the proportion of male in the population are positively associated with the increase in COVID-19 incidence rates. Conclusion This research provides useful insights for the State Government and public health authorities to critically incorporate socio-demographic characteristics of local communities into evidence-based decision-making for altering disease monitoring and response plans. Policymakers can make well-informed judgments and implement targeted interventions by having an in-depth understanding of the spatial patterns and relationships between COVID-19 incidence rates and socio-demographic characteristics. This will effectively help in mitigating the spread of the disease.

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SARS-CoV-2 genomic surveillance in Malaysia: displacement of B.1.617.2 with AY lineages as the dominant Delta variants and the introduction of Omicron during the fourth epidemic wave

Cited by 14 publications

References 23 publications

Unravelling the link between SARS-CoV-2 mutation frequencies, patient comorbidities, and structural dynamics

Unravelling the link between SARS-CoV-2 mutation frequencies, patient comorbidities, and structural dynamics

Timeline of SARS-CoV-2 Transmission in Sabah, Malaysia: Tracking the Molecular Evolution

Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia

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