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Due to their pivotal role in orchestrating the immune response, HLA loci were recognized as candidates for genetic association studies related to the severity of COVID‐19. Since the findings on the effects of HLA alleles on the outcome of SARS‐CoV‐2 infection remain inconclusive, we aimed to elucidate the potential involvement of genetic variability within HLA loci in the molecular genetics of COVID‐19 by classifying the articles according to different disease severity/outcomes and by conducting a systematic review with meta‐analysis. Potentially eligible studies were identified by searching PubMed, Scopus and Web of Science literature databases. A total of 28 studies with 13,073 participants were included in qualitative synthesis, while the results of 19 studies with 10,551 SARS‐CoV‐2‐positive participants were pooled in the meta‐analysis. According to the results of quantitative data synthesis, association with COVID‐19 severity or with the lethal outcome was determined for the following alleles and allele families: HLA‐A*01, HLA‐A*03, HLA‐A*11, HLA‐A*23, HLA‐A*31, HLA‐A*68, HLA‐A*68:02, HLA‐B*07:02, HLA‐B*14, HLA‐B*15, HLA‐B*40:02, HLA‐B*51:01, HLA‐B*53, HLA‐B*54, HLA‐B*54:01, HLA‐C*04, HLA‐C*04:01, HLA‐C*06, HLA‐C*07:02, HLA‐DRB1*11, HLA‐DRB1*15, HLA‐DQB1*03 and HLA‐DQB1*06 (assuming either allelic or dominant genetic model). We conclude that alleles of HLA‐A, ‐B, ‐C, ‐DRB1 and ‐DQB1 loci may represent potential biomarkers of COVID‐19 severity and/or mortality, which needs to be confirmed in a larger set of studies.

Genes involved in the regulation of viral recognition and its entry into a host cell have been identified as candidates for genetic association studies on COVID-19 severity. Published findings on the effects of polymorphisms within ACE1 , ACE2 , TMPRSS2 , IFITM3 and VDR genes remained inconclusive, so we conducted a systematic review and meta-analysis in order to elucidate their potential involvement in the genetic basis underlying the severity of COVID-19 and/or an outcome of SARS-CoV-2 infection. Identification of potentially eligible studies was based on PubMed, Scopus and Web of Science database search. Relevant studies (n=29) with a total number of 8247 SARS-CoV-2-positive participants were included in qualitative synthesis, while results of 21 studies involving 5939 were pooled in meta-analysis. Minor allele I of rs1799752 located within ACE1 was identified as a protective variant against severe COVID-19, while its effect on mortality rate was opposite. Similarly, minor allele A of ACE2 polymorphism, rs2285666, was found to associate with a decreased risk of severe COVID-19 ( P = 0.003, OR = 0.512, 95 % CI = 0.331-0.793). Statistical significance was also seen for the association between COVID-19 severity and rs12329760 located within TMPRSS2 . Our results did not support the supposed association of rs12252 in IFITM3 and polymorphisms within VDR with disease severity. We conclude that genetic variants within ACE1 , ACE2 and TMPRSS2 may be potential biomarkers of COVID-19 severity, which needs to be further confirmed in a larger set of studies.

Purpose Disease or a specific condition may cause alteration of human transferrin (hTf) glycosylation pattern. A specific analytical platform, lectin‐based protein microarray, is designed and optimized for the investigation of hTf glycans, attached to the protein core in their native form. Experimental design hTf molecules isolated from healthy persons of different age, diabetes mellitus type 2 (T2DM) or colorectal carcinoma (CRC) patients are used for method validation. Reliability of the results is ensured by three criteria for the evaluation of hTf–lectin interactions: i) signal‐to‐noise ratio above 3, ii) signal intensity above 250 arbitrary units, and iii) hTf concentration ensuring high sensitivity of the assay. Results Six lectins, out of fourteen tested, satisfy the criteria. hTf is spotted at concentration of 50 µg mL−L. When physiological samples (isolated hTf) are analyzed, the highest potential to differentiate between population groups expresses Aleuria aurantia (AAL), Triticum vulgaris (WGA) and Phaseolus vulgaris (PHA‐E) lectins. The initial amount of hTf which can be analyzed is very low (75 pg). Conclusion and clinical relevance Results confirm that a very sensitive, high‐throughput lectin‐based protein microarray platform can be formulated to detect changes in hTf glycan structures which can be considered as biomarkers of ageing or a disease.