Genetic polymorphisms of ACE1, ACE2, IFTM3, TMPRSS2 and TNFα genes associated with susceptibility and severity of SARS-CoV-2 infection: a systematic review and meta-analysis.

BACKGROUND: Some human polymorphisms of ACE1, ACE2, IFITM3, TMPRSS2 and TNFα genes may have an effect on the susceptibility to SARS-CoV-2 infection and increase the risk to develop severe COVID-19. We conducted a systematic review of current evidence to investigate the association of genetic variants of these genes with the susceptibility to virus infection and patient prognosis. METHODS: We systematically searched Medline, Embase and The Cochrane Library for articles published until May 2022, and included observational studies covering genetic association of ACE1, ACE2, IFITM3, TMPRSS2 and TNFα genes with COVID-19 susceptibility or prognosis. We evaluated the methodological quality of included studies, and pooled data as convenient in meta-analysis (MA). Odds ratio (OR) values and 95% confidence intervals were calculated. RESULTS: We included 35 studies (20 on ACE, 5 each on IFITM3, TMPRSS2, TNFα), enrolling 21,452 participants, of them 9401 were COVID-19 confirmed cases. ACE1 rs4646994 and rs1799752, ACE2 rs2285666, TMPRSS2 rs12329760, IFITM3 rs12252 and TNFα rs1800629 were identifies as common polymorphisms. Our MA showed an association between genetic polymorphisms and susceptibility to SARS-CoV-2 infection for IFITM3 rs12252 CC (OR 5.67) and CT (OR 1.64) genotypes. Furthermore, MA uncovered that both ACE DD (OR 1.27) and IFITM3 CC (OR 2.26) genotypes carriers had a significantly increased risk of developing severe COVID-19. DISCUSSION: These results provide a critical evaluation of genetic polymorphisms as predictors in SARS-CoV-2 infection. ACE1 DD and IFITM3 CC polymorphisms would lead to a genetic predisposition for severe lung injury in patients with COVID-19.

Evidence of SARS-CoV-2 reinfection: analysis of 35,000 subjects and overview of systematic reviews.

BACKGROUND: Reinfection by SARS-CoV-2 is a rare but possible event. We evaluated the prevalence of reinfections in the Province of Modena and performed an overview of systematic reviews to summarize the current knowledge. METHODS: We applied big data analysis and retrospectively analysed the results of oro- or naso-pharyngeal swab results tested for molecular research of viral RNA of SARS-CoV-2 between 1 January 2021 and 30 June 2021 at a single center. We selected individuals with samples sequence of positive, negative and then positive results. Between first and second positive result we considered a time interval of 90 days to be sure of a reinfection. We also performed a search for and evaluation of systematic reviews reporting SARS-CoV-2 reinfection rates. Main information was collected and the methodological quality of each review was assessed, according to A Measurement Tool to Assess systematic Reviews (AMSTAR). RESULTS: Initial positive results were revealed in more than 35,000 (20%) subjects; most (28%) were aged 30-49 years old. Reinfection was reported in 1,258 (3.5%); most (33%) were aged 30-49 years old. Reinfection rates according to vaccinated or non-vaccinated subjects were 0.6% vs 1.1% (p < 0.0001). Nine systematic reviews were identified and confirmed that SARS-CoV-2 reinfection rate is a rare event. AMSTAR revealed very low-moderate levels of quality among selected systematic reviews. CONCLUSIONS: There is a real, albeit rare risk of SARS-CoV-2 reinfection. Big data analysis enabled accurate estimates of the reinfection rates. Nevertheless, a standardized approach to identify and report reinfection cases should be developed.

Estimate false-negative RT-PCR rates for SARS-CoV-2. A systematic review and meta-analysis.

BACKGROUND: Molecular-based tests used to identify symptomatic or asymptomatic patients infected by SARS-CoV-2 are characterized by high specificity but scarce sensitivity, generating false-negative results. We aimed to estimate, through a systematic review of the literature, the rate of RT-PCR false negatives at initial testing for COVID-19. METHODS: We systematically searched Pubmed, Embase and CENTRAL as well as a list of reference literature. We included observational studies that collected samples from respiratory tract to detect SARS-CoV-2 RNA using RT-PCR, reporting the number of false-negative subjects and the number of final patients with a COVID-19 diagnosis. Reported rates of false negatives were pooled in a meta-analysis as appropriate. We assessed the risk of bias of included studies and graded the quality of evidence according to the GRADE method. All information in this article is current up to February 2021. RESULTS: We included 32 studies, enrolling more than 18,000 patients infected by SARS-CoV-2. The overall false-negative rate was 0.12 (95%CI from 0.10 to 0.14) with very low certainty of evidence. The impact of misdiagnoses was estimated according to disease prevalence; a range between 2 and 58/1,000 subjects could be misdiagnosed with a disease prevalence of 10%, increasing to 290/1,000 misdiagnosed subjects with a disease prevalence of 50%. CONCLUSIONS: This systematic review showed that up to 58% of COVID-19 patients may have initial false-negative RT-PCR results, suggesting the need to implement a correct diagnostic strategy to correctly identify suspected cases, thereby reducing false-negative results and decreasing the disease burden among the population.

Accuracy of the serological detection of IgG and IgM to SARS-Cov-2: a prospective, cross-sectional study.

In response to the rapidly evolving of SARS-CoV-2 infection, numerous serological tests have been developed but their sensitivity and specificity are unclear. We collected serum samples of patients and health-care professionals to assess the accuracy of chemiluminescent (CLIA) and two lateral flow immunochromatographic assays (LFIA) to determine IgG and IgM antibodies to SARS-CoV-2 virus. We calculated the φ correlation for qualitative results and test accuracy, adopting the following case definition: either real-time-PCR positivity or serological positivity with at least two different tests. We analyzed 259 samples, obtaining strong correlation between CLIA and both LFIA for IgG (φ=0.9), and moderate correlation for IgM (φ=0.6). For patients, the sensitivity was suboptimal for all methods (CLIA 81%, LFIA A 85%, LFIA B 78%), while it was poor in asymptomatic health-care workers (CLIA 50%, LFIA A 50%, LFIA B 33%). Overall, CLIA is more sensitive and specific for the determination of both IgG and IgM, whilst both LFIA methods reported good sensitivity and specificity for IgG, but scarce sensitivity for the IgM determination. The determination of SARS-CoV-2-specific IgG is useful to detect infection 6 days from symptom onset.