Metabolic Reprogramming in SARS-CoV-2 Infection Impacts the Outcome of COVID-19 Patients.

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection triggers inflammatory clinical stages that affect the outcome of patients with coronavirus disease 2019 (COVID-19). Disease severity may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. The aim of this study was to characterize the profile of amino acids and acylcarnitines in COVID-19 patients. A multicenter, cross-sectional study was carried out. A total of 453 individuals were classified by disease severity. Levels of 11 amino acids, 31 acylcarnitines, and succinylacetone in serum samples were analyzed by electrospray ionization-triple quadrupole tandem mass spectrometry. Different clusters were observed in partial least squares discriminant analysis, with phenylalanine, alanine, citrulline, proline, and succinylacetone providing the major contribution to the variability in each cluster (variable importance in the projection >1.5). In logistic models adjusted by age, sex, type 2 diabetes mellitus, hypertension, and nutritional status, phenylalanine was associated with critical outcomes (odds ratio=5.3 (95% CI 3.16-9.2) in the severe vs. critical model, with an area under the curve of 0.84 (95% CI 0.77-0.90). In conclusion the metabolic imbalance in COVID-19 patients might affect disease progression. This work shows an association of phenylalanine with critical outcomes in COVID-19 patients, highlighting phenylalanine as a potential metabolic biomarker of disease severity.

Association of the Transmembrane Serine Protease-2 (TMPRSS2) Polymorphisms with COVID-19.

SARS-CoV-2 uses the ACE2 receptor and the cellular protease TMPRSS2 for entry into target cells. The present study aimed to establish if the TMPRSS2 polymorphisms are associated with COVID-19 disease. The study included 609 patients with COVID-19 confirmed by RT-PCR test and 291 individuals negative for the SARS-CoV-2 infection confirmed by RT-PCR test and without antibodies anti-SARS-CoV-2. Four TMPRSS2 polymorphisms (rs12329760, rs2298659, rs456298, and rs462574) were determined using the 5'exonuclease TaqMan assays. Under different inheritance models, the rs2298659 (pcodominant2 = 0.018, precessive = 0.006, padditive = 0.019), rs456298 (pcodominant1 = 0.014, pcodominant2 = 0.004; pdominant = 0.009, precessive = 0.004, padditive = 0.0009), and rs462574 (pcodominant1 = 0.017, pcodominant2 = 0.004, pdominant = 0.041, precessive = 0.002, padditive = 0.003) polymorphisms were associated with high risk of developing COVID-19. Two risks (ATGC and GAAC) and two protectives (GAGC and GAGT) haplotypes were detected. High levels of lactic acid dehydrogenase (LDH) were observed in patients with the rs462574AA and rs456298TT genotypes (p = 0.005 and p = 0.020, respectively), whereas, high heart rate was present in patients with the rs462574AA genotype (p = 0.028). Our data suggest that the rs2298659, rs456298, and rs462574 polymorphisms independently and as haplotypes are associated with the risk of COVID-19. The rs456298 and rs462574 genotypes are related to high levels of LDH and heart rate.

The rs8176740 T/A and rs512770 T/C Genetic Variants of the ABO Gene Increased the Risk of COVID-19, as well as the Plasma Concentration Platelets.

We conducted a case-control study in order to evaluate whether ABO gene polymorphisms were associated with a high risk of developing COVID-19 in a cohort of patients. Six ABO gene polymorphisms (rs651007 T/C, rs579459 T/C, rs495828 T/G, rs8176746 A/C, rs8176740 T/A, and rs512770 T/C) were determined using TaqMan genotyping assays in a group of 415 COVID-19 patients and 288 healthy controls. The distribution of rs651007 T/C, rs579459 T/C, rs495828 T/G, and rs8176746 A/C polymorphisms was similar in patients and healthy controls. Nonetheless, under co-dominant (OR = 1.89, pCCo-dominant = 6 × 10-6), recessive (OR = 1.98, pCRecessive = 1 × 10-4), and additive (OR = 1.36, pCAdditive = 3 × 10-3) models, the TT genotype of the rs8176740 T/A polymorphism increased the risk of developing COVID-19. In the same way, under co-dominant, recessive, and additive models, the TT genotype of the rs512770 T/C polymorphism was associated with a high risk of developing COVID-19 (OR = 1.87, pCCo-dominant = 2 × 10-3; OR = 1.87, pCRecessive = 5 × 10-4; and OR = 1.35, pCAdditive = 4 × 10-3, respectively). On the other hand, the GTC and GAT haplotypes were associated with a high risk of COVID-19 (OR = 5.45, pC = 1 × 10-6 and OR = 6.33, pC = 1 × 10-6, respectively). In addition, the rs8176740 TT genotype was associated with high-platelet plasma concentrations in patients with COVID-19. Our data suggested that the ABO rs512770 T/C and rs8176740 T/A polymorphisms increased the risk of developing COVID-19 and the plasma concentration of platelets.

Computational Predictors of the Predominant Protein Function: SARS-CoV-2 Case Older adult’s longitudinal experiences of household isolation and social distancing during the COVID-19 pandemic

Summary In this chapter, we describe the main molecular features of SARS-CoV-2 that cause COVID-19 disease, as well as a high-efficiency computational prediction called Polarity Index Method?. We also introduce a molecular classification of the RNA virus and DNA virus families and two main classifications: supervised and non-supervised algorithms of the predictions of the predominant function of proteins. Finally, some results obtained by the proposed non-supervised method are given, as well as some particularities found about the linear representation of proteins. Background Due to the global pandemic, governments have enforced household isolation and social distancing to reduce infection and mortality rate. However, the impact of prolonged enforced isolation for older people who are prone to social isolation and loneliness has yet to be understood. Objectives A longitudinal study to understand the lived experience of people aged 70 and older, living in England during COVID-19 restrictions. Methods All participants completed five qualitative telephone interviews from 20 April to 7 July 2020. The majority completed individual interviews (n = 13), whilst two participants completed these interviews as a couple. Interviews were audio-recorded, transcribed verbatim and thematic analysis completed from the perspective of hermeneutic phenomenology. Results Three themes included (1) engagement and confusion with government restrictions;(2) socialisation through virtual platforms and opportunistic physical social contact;and (3) accessing health care during COVID-19 restrictions. Conclusion Older people are committed to following government restrictions, and government campaigns need to consider the potential impact of placing an emphasis on avoiding healthcare services. Virtual platforms are supportive but not sufficient to reduce social isolation and loneliness of older people. Thus, nurses supporting older people living in the community need to understand these concepts to provide holistic care and support older people's mental and physical health. Implications for practice Nurses are ideally placed to support older people to understand the current government restrictions, when to attend acute healthcare services or to engage virtually with healthcare appointments, and to discuss the risks of physically socialising with others.

The rs8176740 T/A and rs512770 T/C Genetic Variants of the ABO Gene Increased the Risk of COVID-19, as well as the Plasma Concentration Platelets

We conducted a case-control study in order to evaluate whether ABO gene polymorphisms were associated with a high risk of developing COVID-19 in a cohort of patients. Six ABO gene polymorphisms (rs651007 T/C, rs579459 T/C, rs495828 T/G, rs8176746 A/C, rs8176740 T/A, and rs512770 T/C) were determined using TaqMan genotyping assays in a group of 415 COVID-19 patients and 288 healthy controls. The distribution of rs651007 T/C, rs579459 T/C, rs495828 T/G, and rs8176746 A/C polymorphisms was similar in patients and healthy controls. Nonetheless, under co-dominant (OR = 1.89, pCCo-dominant = 6 ×10−6), recessive (OR = 1.98, pCRecessive = 1 ×10−4), and additive (OR = 1.36, pCAdditive = 3 ×10−3) models, the TT genotype of the rs8176740 T/A polymorphism increased the risk of developing COVID-19. In the same way, under co-dominant, recessive, and additive models, the TT genotype of the rs512770 T/C polymorphism was associated with a high risk of developing COVID-19 (OR = 1.87, pCCo-dominant = 2 ×10−3;OR = 1.87, pCRecessive = 5 ×10−4;and OR = 1.35, pCAdditive = 4 ×10−3, respectively). On the other hand, the GTC and GAT haplotypes were associated with a high risk of COVID-19 (OR = 5.45, pC = 1 ×10−6 and OR = 6.33, pC = 1 ×10−6, respectively). In addition, the rs8176740 TT genotype was associated with high-platelet plasma concentrations in patients with COVID-19. Our data suggested that the ABO rs512770 T/C and rs8176740 T/A polymorphisms increased the risk of developing COVID-19 and the plasma concentration of platelets.

Computational Predictors of the Predominant Protein Function: SARS-CoV-2 Case Noise as a risk factor for COVID-19 transmission: Comment on Zhang: “Estimation of differential occupational risk of COVID-19 by comparing risk factors with case data by occupational group”

Summary In this chapter, we describe the main molecular features of SARS-CoV-2 that cause COVID-19 disease, as well as a high-efficiency computational prediction called Polarity Index Method?. We also introduce a molecular classification of the RNA virus and DNA virus families and two main classifications: supervised and non-supervised algorithms of the predictions of the predominant function of proteins. Finally, some results obtained by the proposed non-supervised method are given, as well as some particularities found about the linear representation of proteins.

Bioinformatics-Based Characterization of Proteins Related to SARS-CoV- 2 Using the Polarity Index Method® (PIM®) and Intrinsic Disorder Predisposition

Background: : The global outbreak of the 2019 novel Coronavirus disease (COVID-19) caused by infection with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which appeared in China at the end of 2019, signifies a major public health issue at the current time. Objective: The objective of the present study is to characterize the physicochemical properties of the SARS-CoV-2 proteins at a residues level, and to generate a “bioinformatics fingerprint” in the form of a “PIM profile” created for each sequence utilizing the Polarity Index Method (PIM), suitable for the identification of these proteins. Methods: Two different bioinformatics approaches were used to analyze sequence characteristics of these proteins at the residues level, an in-house bioinformatics system PIM, and a set of the commonly used algorithms for the prediction of protein intrinsic disorder predisposition, such as PONDR VLXT, PONDR VL3, PONDR VSL2, PONDR FIT, IUPred_short and IUPred_long. The PIM profile was generated for four SARS-CoV-2 structural proteins and compared with the corresponding profiles of the SARS-CoV-2 non-structural proteins, SARS-CoV-2 putative proteins, SARS-- CoV proteins, MERS-CoV proteins, sets of bacterial, fungal, and viral proteins, cell-penetrating peptides, and a set of intrinsically disordered proteins. We also searched for the UniProt proteins with PIM profiles similar to those of SARS-CoV-2 structural, non-structural, and putative proteins. Results: We show that SARS-CoV-2 structural, non-structural, and putative proteins are characterized by a unique PIM profile. A total of 1736 proteins were identified from the 562,253 “reviewed” proteins from the UniProt database, whose PIM profile was similar to that of the SARS-CoV-2 structural, non-structural, and putative proteins. Conclusion: The PIM profile represents an important characteristic that might be useful for the identification of proteins similar to SARS-CoV-2 proteins.

ACE and ACE2 Gene Variants Are Associated With Severe Outcomes of COVID-19 in Men.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the current coronavirus disease 2019 (COVID-19) pandemic, affecting more than 219 countries and causing the death of more than 5 million people worldwide. The genetic background represents a factor that predisposes the way the host responds to SARS-CoV-2 infection. In this sense, genetic variants of ACE and ACE2 could explain the observed interindividual variability to COVID-19 outcomes. In order to improve the understanding of how genetic variants of ACE and ACE2 are involved in the severity of COVID-19, we included a total of 481 individuals who showed clinical manifestations of COVID-19 and were diagnosed by reverse transcription PCR (RT-PCR). Genomic DNA was extracted from peripheral blood and saliva samples. ACE insertion/deletion polymorphism was evaluated by the high-resolution melting method; ACE single-nucleotide polymorphism (SNP) (rs4344) and ACE2 SNPs (rs2285666 and rs2074192) were genotyped using TaqMan probes. We assessed the association of ACE and ACE2 polymorphisms with disease severity using logistic regression analysis adjusted by age, sex, hypertension, type 2 diabetes, and obesity. The severity of the illness in our study population was divided as 31% mild, 26% severe, and 43% critical illness; additionally, 18% of individuals died, of whom 54% were male. Our results showed in the codominant model a contribution of ACE2 gene rs2285666 T/T genotype to critical outcome [odds ratio (OR) = 1.83; 95%CI = 1.01-3.29; p = 0.04] and to require oxygen supplementation (OR = 1.76; 95%CI = 1.01-3.04; p = 0.04), in addition to a strong association of the T allele of this variant to develop critical illness in male individuals (OR = 1.81; 95%CI = 1.10-2.98; p = 0.02). We suggest that the T allele of rs2285666 represents a risk factor for severe and critical outcomes of COVID-19, especially for men, regardless of age, hypertension, obesity, and type 2 diabetes.

Dipeptidylpeptidase-4 levels and DPP4 gene polymorphisms in patients with COVID-19. Association with disease and with severity.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes de COVID-19 disease use as a principal receptor the angiotensin-converting enzyme-2 (ACE2). It has been suggested that dipeptidyl peptidase-4 (DPP4) can be another possible receptor for this virus. The present study aimed to establish if the DPP4 levels and DPP4 polymorphisms are associated with COVID-19 disease and its severity. METHODS: The study included 107 COVID-19 patients and 263 matched-healthy controls. Fifty patients required invasive mechanical ventilation. The DPP4 was quantified in serum using the Bioplex system. Based on the previous results and the functional prediction analysis, we select for the study 5 DPP4 polymorphisms (rs12617336, rs12617656, rs1558957, rs3788979, and rs17574) and these were determined using the 5´exonuclease TaqMan assays. RESULTS: Low levels of DPP4 were observed in COVID-19 patients (46.5 [33.1-57.7] ng/mL) when compared to healthy controls (125.3 [100.3-157.3] ng/mL) (P < 0.0001). Also, patients that required mechanical ventilation showed lower DPP4 levels (42.8 [29.8-56.9] ng/mL) than those that did not need this procedure (49.2 [39.9-65.6] ng/mL) (P = 0.012). DPP4 levels correlated negatively with age, fibrinogen, and platelet levels, and positively with albumin, alanine aminotransferase, and percentage of neutrophils. The DPP4 rs3788979 polymorphism was associated with a high risk of COVID-19 disease and, the TT genotype carriers had the lowest DPP4 levels. CONCLUSIONS: In summary, in the present study, an association of low levels of DPP4 with COVID-19 disease and severity was found. The association of the DPP4 rs3788979 polymorphism with COVID-19 is also reported.

A high-throughput multiplexed microfluidic device for COVID-19 serology assays.

The applications of serology tests to the virus SARS-CoV-2 are diverse, ranging from diagnosing COVID-19, understanding the humoral response to this disease, and estimating its prevalence in a population, to modeling the course of the pandemic. COVID-19 serology assays will significantly benefit from sensitive and reliable technologies that can process dozens of samples in parallel, thus reducing costs and time; however, they will also benefit from biosensors that can assess antibody reactivities to multiple SARS-CoV-2 antigens. Here, we report a high-throughput microfluidic device that can assess antibody reactivities against four SARS-CoV-2 antigens from up to 50 serum samples in parallel. This semi-automatic platform measures IgG and IgM levels against four SARS-CoV-2 proteins: the spike protein (S), the S1 subunit (S1), the receptor-binding domain (RBD), and the nucleocapsid (N). After assay optimization, we evaluated sera from infected individuals with COVID-19 and a cohort of archival samples from 2018. The assay achieved a sensitivity of 95% and a specificity of 91%. Nonetheless, both parameters increased to 100% when evaluating sera from individuals in the third week after symptom onset. To further assess our platform's utility, we monitored the antibody titers from 5 COVID-19 patients over a time course of several weeks. Our platform can aid in global efforts to control and understand COVID-19.

Variability in genes related to SARS-CoV-2 entry into host cells (ACE2, TMPRSS2, TMPRSS11A, ELANE, and CTSL) and its potential use in association studies.

BACKGROUND: The prevalence and mortality of the outbreak of the COVID-19 pandemic show marked geographic variation. The presence of several subtypes of the coronavirus and the genetic differences in the populations could condition that variation. Thus, the objective of this study was to propose variants in genes that encode proteins related to the SARS-CoV-2 entry into the host cells as possible targets for genetic associations studies. METHODS: The allelic frequencies of the polymorphisms in the ACE2, TMPRSS2, TMPRSS11A, cathepsin L (CTSL), and elastase (ELANE) genes were obtained in four populations from the American, African, European, and Asian continents reported in the 1000 Genome Project. Moreover, we evaluated the potential biological effect of these variants using different web-based tools. RESULTS: In the coding sequences of these genes, we detected one probably-damaging polymorphism located in the TMPRSS2 gene (rs12329760) that produces a change of amino acid. Furthermore, forty-eight polymorphisms with possible functional consequences were detected in the non-coding sequences of the following genes: three in ACE2, seventeen in TMPRSS2, ten in TMPRSS11A, twelve in ELANE, and six in CTSL. These polymorphisms produce binding sites for transcription factors and microRNAs. The minor allele frequencies of these polymorphisms vary in each community; indeed, some of them are high in specific populations. CONCLUSION: In summary, using data of the 1000 Genome Project and web-based tools, we propose some polymorphisms, which, depending on the population, could be used for genetic association studies.