RESUMO
BACKGROUND: High self-renewal capacity and most permissive nature of umbilical cord blood (CB) results with successful transplant outcomes but low hematopoietic stem and progenitor cell (HSPC) counts limits wider use. In order to overcome this problem ex vivo expansion with small molecules such as Valproic acid (VPA) or Nicotinamide (NAM) have been shown to be effective. To the best of our knowledge, the combinatory effects of VPA and NAM on HSPC expansion has not been studied earlier. The aim of this study was to analyze ex vivo and in vivo efficacy of VPA and NAM either alone or in combination in terms of expansion and engraftment. METHODS: A total of 44 CB units were included in this study. To determine the ex vivo and in vivo efficacy, human CB CD34+ cells were expanded with VPA and/or NAM and colony forming unit (CFU) assay was performed on expanded HSPC. Xenotransplantation was performed simultaneously by intravenous injection of expanded HSPC to NOD-SCID gamma (NSG) mice (n = 22). Significance of the difference between the expansion groups or xenotransplantation models was analyzed using t-test, Mann-Whitney, ANOVA or Kruskal-Wallis tests as appropriate considering the normality of distributions and the number of groups analyzed. RESULTS: In vitro CD34+ HSPC expansion fold relative to cytokines-only was significantly higher with VPA compared to NAM [2.23 (1.07-5.59) vs 1.48 (1.00-4.40); p < 0.05]. Synergistic effect of VPA+NAM has achieved a maximum relative expansion fold at 21 days (D21) of incubation [2.95 (1.00-11.94)]. There was no significant difference between VPA and VPA+NAM D21 (p = 0.44). Fold number of colony-forming unit granulocyte-macrophage (CFU-GM) colonies relative to the cytokine-only group was in favor of NAM compared to VPA [1.87 (1.00-3.59) vs 1.00 (1.00-1.81); p < 0.01]. VPA+NAM D21 [1.62 (1.00-2.77)] was also superior against VPA (p < 0.05). There was no significant difference between NAM and VPA+NAM D21. Following human CB34+ CB transplantation (CBT) in the mouse model, fastest in vivo leukocyte recovery was observed with VPA+NAM expanded cells (6 ± 2 days) and the highest levels of human CD45 chimerism was detectable with VPA-expanded CBT (VPA: 5.42 % at day 28; NAM: 2.45 % at day 31; VPA+NAM 1.8 % at day 31). CONCLUSION: Our study results suggest using VPA alone, rather than in combination with NAM or NAM alone, to achieve better and faster expansion and engraftment of CB HSPC.
RESUMO
Associations between inherited Killer Immunoglobulin-like Receptor (KIR) genotypes and the severity of multiple RNA virus infections have been reported. This prospective study was initiated to investigate if such an association exists for COVID-19. In this cohort study performed at Ankara University, 132 COVID-19 patients (56 asymptomatic, 51 mild-intermediate, and 25 patients with severe disease) were genotyped for KIR and ligands. Ankara University Donor Registry (n:449) KIR data was used for comparison. Clinical parameters (age, gender, comorbidities, blood group antigens, inflammation biomarkers) and KIR genotypes across cohorts of asymptomatic, mild-intermediate, or severe disease were compared to construct a risk prediction model based on multivariate binary logistic regression analysis with backward elimination method. Age, blood group, number of comorbidities, CRP, D-dimer, and telomeric and centromeric KIR genotypes (tAA, tAB1, and cAB1) along with their cognate ligands were found to differ between cohorts. Two prediction models were constructed; both included age, number of comorbidities, and blood group. Inclusion of the KIR genotypes in the second prediction model exp (-3.52 + 1.56 age group - 2.74 blood group (type A vs others) + 1.26 number of comorbidities - 2.46 tAB1 with ligand + 3.17 tAA with ligand) increased the predictive performance with a 92.9% correct classification for asymptomatic and 76% for severe cases (AUC: 0.93; P < 0.0001, 95% CI 0.88, 0.99). This novel risk model, consisting of KIR genotypes with their cognate ligands, and clinical parameters but excluding earlier published inflammation-related biomarkers allow for the prediction of the severity of COVID-19 infection prior to the onset of infection. This study is listed in the National COVID-19 clinical research studies database.
