No abstract

The coding-complete genome sequence of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain isolated from an Iraqi patient was sequenced for the first-time using Illumina MiSeq technology. There was a D614G mutation in the spike protein-coding sequence. This report is valuable for better understanding the spread of the virus in Iraq.

Since the first reported case of coronavirus disease 2019 (COVID-19) in China, SARS-CoV-2 has been spreading worldwide. Genomic surveillance of SARS-CoV-2 has had a critical role in tracking the emergence, introduction, and spread of new variants, which may affect transmissibility, pathogenicity, and escape from infection or vaccine-induced immunity. As anticipated, the rapid increase in COVID-19 infections in Iraq in February 2021 is due to the introduction of variants of concern during the second wave of the COVID-19 pandemic. To understand the molecular epidemiology of SARS-CoV-2 during the second wave in Iraq (2021), we sequenced 76 complete SARS-CoV-2 genomes using NGS technology and identified genomic mutations and proportions of circulating variants among these. Also, we performed an in silico study to predict the effect of the truncation of NS7a protein (ORF7a) on its function. We detected nine different lineages of SARS-CoV-2. The B.1.1.7 lineage was predominant (80.20%) from February to May 2021, while only one B.1.351 strain was detected. Interestingly, the phylogenetic analysis showed that multiple strains of the B.1.1.7 lineage clustered closely with those from European countries. A notable frequency (43.33%) of stop codon mutation (NS7a Q62stop) was detected among the B.1.1.7 lineage sequences. In silico analysis of NS7a with Q62stop found that this stop codon had no considerable effect on the function of NS7a. This work provides molecular epidemiological insights into the spread variants of SARS-CoV-2 in Iraq, which are most likely imported from Europe.

Background: COVID-19 has emerged recently and become of global concern. Computed tomography (CT) plays a vital role in the diagnosis. Objectives: To characterize the pulmonary CT changes and distributions of COVID-19 infection in regard to different age groups. Methods: Chest CT scan of 104 symptomatic patients with COVID-19 infection, from 7 Iraqi isolation centers were retrospectively analyzed between March 10th and April 5th, 2020. Patients were sub-classified according to their ages to three groups (young adult:20-39years, middle age:40-59years and old age:60- 90years). Results: The most common findings were ground-glass opacities (GGO) (92.3%, followed by consolidation (27.9%), bronchovascular thickening (15.4%), and crazy-paving (12.5%). Less commonly, there were tree-inbud (6.7%), pulmonary nodules (5.8%), bronchiectasis (3.8%), pleural effusion (1.9%), and cavitation (1%). There were no hallo sign, reversed hallo sign, nor mediastinal lymphadenopathy. Pulmonary changes were unilateral in 16.7% and bilateral in 83.3%, central in 14.6%, peripheral in 57.3%, and diffuse (central and peripheral) in 28.1%. Most cases showed multi-lobar changes (70.8%), while the lower lobe was more commonly involved (17.7%) than middle lobe/lingula (8.3%) and upper lobe (3.1%). In unilateral involvement, changes were more on the right (68.8%) than left (31.2%) side. Compared with middle and old age groups, young adult patients showed significantly lesser frequency of consolidation (17% vs. 13.3% and 37%), diffuse changes 28.1% (14.2% vs. 35.3% and 40.5%), bilateral disease (71.4% vs. 94.1% and 85.2%), and multi-lobar involvement (51.4% vs. 82.4% and 81.4%) respectively. Conclusion: Bilateral and peripheral GGO were the most frequent findings with the right side and lower lobar predilection. Extent and pattern seem to be age-related.

Background Forensic DNA phenotyping has gained momentum in the recent past due to the prediction of externally visible characters (EVCs) from the biological sample. The most common phenotypes like eye, hair, and skin color are predicted from the biological samples using a web-based system called IrisPlex. Based on six genetic SNPs, the IrisPlex system is developed and validated for its prediction accuracy in diverse ethnic groups worldwide. In previous studies, this system proved to have significant prediction accuracy. The EVCs vary substantially based on different geographical locations. Hence, the objective of this study was to validate the accuracy of the IrisPlex system in predicting the eye colors in the Iraqi population. Methods Six genetic single-nucleotide polymorphisms SNPs (HERC2-rs12913832, OCA2- rs1800407, SLC24A4-rs12896399, SLC45A2- rs16891982, TYR-rs1393350, and IRF4- rs12203592) in 58 Iraqi subjects were performed using Sequenom MassARRAY Genotyping. According to Liu et al., a predicted probability of 0.7 was considered as the threshold. Results Participants in this study of brown color were observed in 44.83%, intermediate in 43.1%, and blue in 12.07%. Completely predictive accuracy is obtained in 1; we observed the AUC at threshold 0.7 was 0.91 for brown, 0.79 for blue, and 0.60 for intermediate eye color. The sensitivity was 42.85% for blue, 0% for intermediate eye color, and 100% for brown-colored eye. Specificity was 100% for blue, 100% for intermediate, and 78.13% for brown eye color. Conclusion Hence, it was concluded that the prediction accuracy of the IrisPlex system for blue and brown color eye in the Iraqi population is significant in the studied population size. However, a pivotal study with larger sample size is required to represent the prediction accuracy of the IrisPlex system in the whole Iraqi population.