Although advanced age, male sex, and some comorbidities impact the clinical course of COVID-19, these factors only partially explain the inter-individual variability in disease severity. Some studies have shown that genetic polymorphisms contribute to COVID-19 severity; however, the results are inconclusive. Thus, we investigated the association between polymorphisms in ACE1, ACE2, DPP9, IFIH1, IFNAR2, IFNL4, TLR3, TMPRSS2, and TYK2 and the clinical course of COVID-19. A total of 694 patients with COVID-19 were categorized as: (1) ward inpatients (moderate symptoms) or patients admitted at the intensive care unit (ICU; severe symptoms); and (2) survivors or non-survivors. In females, the rs1990760/IFIH1 T/T genotype was associated with risk of ICU admission and death. Moreover, the rs1799752/ACE1 Ins and rs12329760/TMPRSS2 T alleles were associated with risk of ICU admission. In non-white patients, the rs2236757/IFNAR2 A/A genotype was associated with risk of ICU admission, while the rs1799752/ACE1 Ins/Ins genotype, rs2236757/IFNAR2 A/A genotype, and rs12329760/TMPRSS2 T allele were associated with risk of death. Moreover, some of the analyzed polymorphisms interact in the risk of worse COVID-19 outcomes. In conclusion, this study shows an association of rs1799752/ACE1, rs1990760/IFIH1, rs2236757/IFNAR2, rs12329760/TMPRSS2, and rs2304256/TYK2 polymorphisms with worse COVID-19 outcomes, especially among female and non-white patients.

Long non-coding RNAs (lncRNAs) are RNAs with >200 nucleotides that are unable to encode proteins and are involved in gene expression regulation. LncRNAs have a key role in many physiological and pathological processes and, consequently, they have been associated with several human diseases, including diabetes chronic complications, such as diabetes kidney disease (DKD). In this context, some studies have identified the dysregulation of the lncRNAs MALAT1 and TUG1 in patients with DKD; nevertheless, available data are still contradictory. Thus, the objective of this study was to compare MALAT1 and TUG1 expressions in urine of patients with type 1 diabetes mellitus (T1DM) categorized according to DKD presence. This study comprised 18 T1DM patients with DKD (cases) and 9 long-duration T1DM patients without DKD (controls). MALAT1 and TUG1 were analyzed using qPCR. Bioinformatics analyses were done to identify both lncRNA target genes and the signaling pathways under their regulation. The lncRNA MALAT1 was upregulated in urine of T1DM patients with DKD vs . T1DM controls (P = 0.007). The expression of lncRNA TUG1 did not differ between groups (P = 0.815). Bioinformatics analysis showed these two lncRNAs take part in metabolism-related pathways. The present study shows that the lncRNA MALAT1 is upregulated in T1DM patients presenting DKD.

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