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Fulltext Diversity and Evolutionary Histories of Human Coronaviruses NL63 and 229E Associated with Acute Upper Respiratory Tract Symptoms in Kuala Lumpur, Malaysia

Al-Khannaq MN, Ng KT, Oong XY, Pang YK, Takebe Y, Chook JB, et al.

Am J Trop Med Hyg, 2016 05 04;94(5):1058-64.
PMID: 26928836 DOI: 10.4269/ajtmh.15-0810

The human alphacoronaviruses HCoV-NL63 and HCoV-229E are commonly associated with upper respiratory tract infections (URTI). Information on their molecular epidemiology and evolutionary dynamics in the tropical region of southeast Asia however is limited. Here, we analyzed the phylogenetic, temporal distribution, population history, and clinical manifestations among patients infected with HCoV-NL63 and HCoV-229E. Nasopharyngeal swabs were collected from 2,060 consenting adults presented with acute URTI symptoms in Kuala Lumpur, Malaysia, between 2012 and 2013. The presence of HCoV-NL63 and HCoV-229E was detected using multiplex polymerase chain reaction (PCR). The spike glycoprotein, nucleocapsid, and 1a genes were sequenced for phylogenetic reconstruction and Bayesian coalescent inference. A total of 68/2,060 (3.3%) subjects were positive for human alphacoronavirus; HCoV-NL63 and HCoV-229E were detected in 45 (2.2%) and 23 (1.1%) patients, respectively. A peak in the number of HCoV-NL63 infections was recorded between June and October 2012. Phylogenetic inference revealed that 62.8% of HCoV-NL63 infections belonged to genotype B, 37.2% was genotype C, while all HCoV-229E sequences were clustered within group 4. Molecular dating analysis indicated that the origin of HCoV-NL63 was dated to 1921, before it diverged into genotype A (1975), genotype B (1996), and genotype C (2003). The root of the HCoV-229E tree was dated to 1955, before it diverged into groups 1-4 between the 1970s and 1990s. The study described the seasonality, molecular diversity, and evolutionary dynamics of human alphacoronavirus infections in a tropical region.
Fulltext Molecular epidemiology and evolutionary histories of human coronavirus OC43 and HKU1 among patients with upper respiratory tract infections in Kuala Lumpur, Malaysia

Al-Khannaq MN, Ng KT, Oong XY, Pang YK, Takebe Y, Chook JB, et al.

Virol J, 2016 Feb 25;13:33.
PMID: 26916286 DOI: 10.1186/s12985-016-0488-4

BACKGROUND: Despite the worldwide circulation of human coronavirus OC43 (HCoV-OC43) and HKU1 (HCoV-HKU1), data on their molecular epidemiology and evolutionary dynamics in the tropical Southeast Asia region is lacking.
METHODS: The study aimed to investigate the genetic diversity, temporal distribution, population history and clinical symptoms of betacoronavirus infections in Kuala Lumpur, Malaysia between 2012 and 2013. A total of 2,060 adults presented with acute respiratory symptoms were screened for the presence of betacoronaviruses using multiplex PCR. The spike glycoprotein, nucleocapsid and 1a genes were sequenced for phylogenetic reconstruction and Bayesian coalescent inference.
RESULTS: A total of 48/2060 (2.4 %) specimens were tested positive for HCoV-OC43 (1.3 %) and HCoV-HKU1 (1.1 %). Both HCoV-OC43 and HCoV-HKU1 were co-circulating throughout the year, with the lowest detection rates reported in the October-January period. Phylogenetic analysis of the spike gene showed that the majority of HCoV-OC43 isolates were grouped into two previously undefined genotypes, provisionally assigned as novel lineage 1 and novel lineage 2. Sign of natural recombination was observed in these potentially novel lineages. Location mapping showed that the novel lineage 1 is currently circulating in Malaysia, Thailand, Japan and China, while novel lineage 2 can be found in Malaysia and China. Molecular dating showed the origin of HCoV-OC43 around late 1950s, before it diverged into genotypes A (1960s), B (1990s), and other genotypes (2000s). Phylogenetic analysis revealed that 27.3 % of the HCoV-HKU1 strains belong to genotype A while 72.7 % belongs to genotype B. The tree root of HCoV-HKU1 was similar to that of HCoV-OC43, with the tMRCA of genotypes A and B estimated around the 1990s and 2000s, respectively. Correlation of HCoV-OC43 and HCoV-HKU1 with the severity of respiratory symptoms was not observed.
CONCLUSIONS: The present study reported the molecular complexity and evolutionary dynamics of human betacoronaviruses among adults with acute respiratory symptoms in a tropical country. Two novel HCoV-OC43 genetic lineages were identified, warranting further investigation on their genotypic and phenotypic characteristics.
Study site: Primary Care Clinic, University Malaya Medical Centre (UMMC), Kuala Lumpur, Malaysia
Fulltext Predictors for detecting chronic respiratory diseases in community surveys: A pilot cross-sectional survey in four South and South East Asian low- and middle-income countries

Agarwal D, Hanafi NS, Khoo EM, Parker RA, Ghorpade D, Salvi S, et al.

J Glob Health, 2021;11:04065.
PMID: 34737865 DOI: 10.7189/jogh.11.04065

Background: Our previous scoping review revealed limitations and inconsistencies in population surveys of chronic respiratory disease. Informed by this review, we piloted a cross-sectional survey of adults in four South/South-East Asian low-and middle-income countries (LMICs) to assess survey feasibility and identify variables that predicted asthma or chronic obstructive pulmonary disease (COPD).
Methods: We administered relevant translations of the BOLD-1 questionnaire with additional questions from ECRHS-II, performed spirometry and arranged specialist clinical review for a sub-group to confirm the diagnosis. Using random sampling, we piloted a community-based survey at five sites in four LMICs and noted any practical barriers to conducting the survey. Three clinicians independently used information from questionnaires, spirometry and specialist reviews, and reached consensus on a clinical diagnosis. We used lasso regression to identify variables that predicted the clinical diagnoses and attempted to develop an algorithm for detecting asthma and COPD.
Results: Of 508 participants, 55.9% reported one or more chronic respiratory symptoms. The prevalence of asthma was 16.3%; COPD 4.5%; and 'other chronic respiratory disease' 3.0%. Based on consensus categorisation (n = 483 complete records), "Wheezing in last 12 months" and "Waking up with a feeling of tightness" were the strongest predictors for asthma. For COPD, age and spirometry results were the strongest predictors. Practical challenges included logistics (participant recruitment; researcher safety); misinterpretation of questions due to local dialects; and assuring quality spirometry in the field.
Conclusion: Detecting asthma in population surveys relies on symptoms and history. In contrast, spirometry and age were the best predictors of COPD. Logistical, language and spirometry-related challenges need to be addressed.

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