Low levels of soluble DPP4 among Saudis may have constituted a risk factor for MERS endemicity.

Most of the cases of Middle East respiratory syndrome coronavirus (MERS-CoV) were reported in Saudi Arabia. Dipeptidyl peptidase-4 (DPP4) was identified as the receptor for the virus. The level of soluble DPP4 (sDPP4) was found to be reduced in MERS-CoV infected patients while high levels of sDPP4 were suggested to be protective against MERS-CoV in animal models. We investigated whether the Saudi population has lower levels of sDPP4 which makes them more susceptible to MERS-CoV infection and, therefore, could explain the larger number of cases from the country. Blood samples were collected from 219 Saudi blood donors and 200 blood donors from other ethnic groups. The plasma level of sDPP4 was measured by ELISA and the following SNPs in the DPP4 gene; rs35128070, rs1861978, rs79700168, and rs17574, were genotyped by TaqMan SNP genotyping assay. The average level of plasma sDDP4 was significantly lower in Saudis than other Arabs and non-Arabs (P value 0.0003 and 0.012, respectively). The genotypes AG of rs35128070 and GT of rs1861978 were significantly associated with lower sDPP4 among Saudis (P value 0.002 for each). While both genotypes AA and AG of rs79700168 and rs17574 were associated with significantly lower average sDPP4 level in Saudis compared to other ethnic groups (P value 0.031 and 0.032, and 0.027 and 0.014, respectively). Herein, we report that the Saudi population has lower levels of plasma sDPP4 than other ethnic groups, which is associated with genetic variants in the DPP4 gene. This may have contributed to increase the susceptibility of the Saudi population to MERS-CoV infection and could be a factor in the long-lasting persistence of the virus in the country.

Bacterial and Fungal Coinfection in Critically Ill COVID-19 Cases and Predictive Role of Procalcitonin During the First Wave at an Academic Health Center.

BACKGROUND: Coinfection at various sites can complicate the clinical course of coronavirus disease of 2019 (COVID-19) patients leading to worse prognosis and increased mortality. We aimed to investigate the occurrence of coinfection in critically ill COVID-19 cases, and the predictive role of routinely tested biomarkers on admission for mortality. METHODS: This is a retrospective study of all SARS-CoV-2-infected cases, who were admitted to King Fahad Hospital of the University between March 2020 and December 2020. We reviewed the data in the electronic charts in the healthcare information management system including initial presentation, clinical course, radiological and laboratory findings and reported all significant microbiological cultures that indicated antimicrobial therapy. The mortality data were reviewed for severely ill patients who were admitted to critical care units. RESULTS: Of 1091 admitted patients, there were 70 fatalities (6.4%). 182 COVID-19 persons were admitted to the critical care service, of whom 114 patients (62.6%) survived. The in-hospital mortality was 13.4%. Coinfection was noted in 67/68 non-survivors, and Gram-negative pathogens (Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumanni) represented more than 50% of the etiological agents. We noted that the serum procalcitonin on admission was higher for non-survivors (Median = 1.6 ng/mL ± 4.7) than in survivors (Median = 0.2 ng/mL ± 4.2) (p ≤ 0.05). CONCLUSION: Coinfection is a serious complication for COVID-19 especially in the presence of co-morbidities. High levels of procalcitonin on admission may predict non-survival in critically ill cases in whom bacterial or fungal co-infection is likely.

Dormancy models for Mycobacterium tuberculosis: A minireview

Dormancy models for Mycobacterium tuberculosis play important roles in understanding various aspects of tuberculosis pathogenesis and in the testing of novel therapeutic regimens. By simulating the latent tuberculosis infection, in which the bacteria exist in a non-replicative state, the models demonstrate reduced susceptibility to antimycobacterial agents. This minireview outlines the models available for simulating latent tuberculosis both in vitro and in several animal species. Additionally, this minireview discusses the advantages and disadvantages of these models for investigating the bacterial subpopulations and susceptibilities to sterilization by various antituberculosis drugs.