SELP Asp603Asn and severe thrombosis in COVID-19 males

Fallerini, Chiara; Daga, Sergio; Benetti, Elisa; Picchiotti, Nicola; Zguro, Kristina; Catapano, Francesca; Baroni, Virginia; Lanini, Simone; Bucalossi, Alessandro; Marotta, Giuseppe; Colombo, Francesca; Baldassarri, Margherita; Fava, Francesca; Beligni, Giada; Sarno, Laura; Alaverdian, Diana; Palmieri, Maria; Croci, Susanna; Isidori, Andrea M.; Furini, Simone; Frullanti, Elisa; Renieri, Alessandra; Mari, Francesca

doi:10.1186/s13045-021-01136-9

Cited by 14 publications

(7 citation statements)

References 14 publications

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“…This is also observed in isolated vessels of patients with this disease. Thus, sickle cell anemia is a pathological condition in which there is an increased proinflammatory and procoagulant state in the microcirculation, and P-selectin is a key factor, as in COVID-19 (Matsu et al, 2001;Fallerini et al, 2021).…”

Section: P-selectin and Its Role In Hemostasismentioning

confidence: 99%

Role of P-Selectin in the Development of Hemostasis Disorders in COVID-19

Golubeva

2022

Biol Bull Rev

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This is a review of data on the impact of COVID-19 on blood clotting. An important feature of the pathogenesis of severe acute respiratory syndrome caused by the SARS-Co-2 coronavirus is the risk of thrombotic complications including microvascular thrombosis, venous thromboembolism, and stroke. These thrombotic complications, like thrombocytopenia, are markers of the severe form of COVID-19 and are associated with multiple organ failure and increased mortality. One of the central mechanisms of this pathology is dysregulation of the adhesive protein P-selectin. The study of the mechanisms of changes in hemostasis and vascular pathology, and the role in these processes of biomarkers of thrombogenesis, and primarily of P-selectin of various origins (platelets, endothelial cells, and plasma), can bring some clarity to the understanding of the pathogenesis and therapy of COVID-19.

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Section: P-selectin and Its Role In Hemostasismentioning

confidence: 99%

Role of P-Selectin in the Development of Hemostasis Disorders in COVID-19

Golubeva

2022

Biol Bull Rev

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“…a LASSO logistic regression, has been applied to extract some thousands of coding genetic features contributing to COVID-19 severity [35, 16]. Subsequent functional validation of extracted features demonstrated that, in each tested case, the association with severity has a biological basis and suggested hints for adjuvant treatment [5, 15, 14, 11, 3, 2, 27, 31]. Using the extracted features it has been built a severity score named Integrated PolyGenic Score (IPGS), whose performances reached about 75% for both sensitivity and specificity [16].…”

Section: Introductionmentioning

confidence: 99%

Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

Martelloni

Turchi

Fallerini

et al. 2023

Preprint

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The impact of common and rare variants in COVID-19 host genetics is widely studied in [16]. Here, common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. Firstly, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score, the so called IPGS, which offers a very simple description of the contribution of host genetics in COVID-19 severity. IPGS leads to an accuracy of 55-60% on different cohorts and, after a logistic regression with in input both IPGS and the age, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using the information on the host organs involved in the disease. We generalized the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into "Boolean quantum features", inspired by the Quantum Mechanics. The organs' coefficients were set via the application of the genetic algorithm Pygad and, after that, we defined two new Integrated PolyGenic Score (IPGS1 and IPGS2). By applying a logistic regression with both IPGS2 (or indifferently IPGS1) and age as input, we reach an accuracy of 84-86%, thus improving the results previously shown in [16] by a factor of 10%.

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“…It has already been clearly demonstrated that age, sex, and the presence of other pre-existing disorders, such as diabetes or cardiovascular disease, influence the different prognoses of some patients [ 1 , 2 , 3 ]. It is now well recognized that host genetic factors also play a crucial role in determining COVID-19 clinical outcomes and so far, various common [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ] and rare [ 12 , 13 , 14 , 15 , 16 , 17 ] genetic variants are already described in association with susceptibility and severity. In particular, our GEN-COVID consortium has previously shown that the individuals carrying single pathogenic variants of the CFTR gene, i.e., CF-carriers, were more likely to undergo severe COVID-19, with a higher risk of 14-day mortality [ 17 ] and their geographical distribution correlated with COVID-19 spread and fatalities in 37 countries [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

Gain- and Loss-of-Function CFTR Alleles Are Associated with COVID-19 Clinical Outcomes

Baldassarri

Zguro

Tomati

et al. 2022

Cells

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Carriers of single pathogenic variants of the CFTR (cystic fibrosis transmembrane conductance regulator) gene have a higher risk of severe COVID-19 and 14-day death. The machine learning post-Mendelian model pinpointed CFTR as a bidirectional modulator of COVID-19 outcomes. Here, we demonstrate that the rare complex allele [G576V;R668C] is associated with a milder disease via a gain-of-function mechanism. Conversely, CFTR ultra-rare alleles with reduced function are associated with disease severity either alone (dominant disorder) or with another hypomorphic allele in the second chromosome (recessive disorder) with a global residual CFTR activity between 50 to 91%. Furthermore, we characterized novel CFTR complex alleles, including [A238V;F508del], [R74W;D1270N;V201M], [I1027T;F508del], [I506V;D1168G], and simple alleles, including R347C, F1052V, Y625N, I328V, K68E, A309D, A252T, G542*, V562I, R1066H, I506V, I807M, which lead to a reduced CFTR function and thus, to more severe COVID-19. In conclusion, CFTR genetic analysis is an important tool in identifying patients at risk of severe COVID-19.

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SELP Asp603Asn and severe thrombosis in COVID-19 males

Cited by 14 publications

References 14 publications

Role of P-Selectin in the Development of Hemostasis Disorders in COVID-19

Role of P-Selectin in the Development of Hemostasis Disorders in COVID-19

Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

Gain- and Loss-of-Function CFTR Alleles Are Associated with COVID-19 Clinical Outcomes

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