Features of clinical symptom and inflammatory marker regression in the use of thermal oxygen-helium mixture in SARS-CoV-2 pneumonia treatment

New coronavirus infection is accompanied by high mortality and socio-economic losses in the world community. Despite the continuous process of including new medication with antiviral and anti-inflammatory effects in the disease treatment, the development of complications, primarily of hypoxic origin, and mortality remain high.The aim of the study is to evaluate the effect of the use of thermal oxygen-helium mixture in the therapy on the rate of regression of clinical and laboratory signs of inflammation, as well as the length of patient hospital stay.Material and methods. 59 patient medical records with moderate and severe disease were analyzed. The article summarizes experience of patient management with COVID-19-associated pneumonia who are treated with or without the use of thermal oxygen-helium mixture in one of intensive care units in multi-filed hospital.Results and discussion. It has been proven that the use of a thermal oxygen-helium mixture in the SARS-CoV-2 pneumonia treatment is effective.

Biomarker Association with Hypertension in Mild Versus Severe Sickle Cell Disease Genotypes of a Single Center Cohort, in Comparison with African Americans from the Nhanes Study

Introduction: Previous studies have reported that patients with sickle cell disease (SCD) have lower systemic blood pressures when compared with age-, sex-, and race-matched controls. We compared systolic and diastolic blood pressure (SBP and DBP) measurements in an SCD patient cohort followed at our clinical center with values obtained from background population using African Americans from the National Health and Nutrition Examination Survey (NHANES) study. Furthermore, we evaluated the association of SBP and DBP with clinical and laboratory variables in our patient cohort in comparison to NHANES. Methods: We cross-sectionally analyzed 442 adult SCD patients receiving medical care at the University of Illinois at Chicago (UIC) between 2009-2018, categorized as severe (HbSS/Sβ 0-thalassemia; n=342) or mild (HbSC/Sβ +-thalassemia; n=100) genotypes. 884 African American from the NHANES were age-, sex-, and race- matched as control in a 2:1 ratio. We evaluated associations between systolic and diastolic BP and 32 clinical and laboratory variables. Evaluation of medians, interquartile range (IQR), Wilcoxon rank sum and the χ2 test, were performed on covariates. Clinical associations between biomarkers and primary outcomes of SBP, DBP, were determined by first applying single marker regression with covariates. Significant biomarkers were then analyzed by multi-marker regression and model selection to predict the relative strength of outcome association for these biomarkers. All variables included were normally distributed or transformed to normal distribution. Results: The median age of participants ranged from 31-38 years for both SCD cohorts and NHANES control. 16%, 21% and 8% of the mild genotype patients, severe genotype patients and NHANES controls, respectively were on at least one antihypertensive medication for either hypertension or proteinuria. The median (IQR) for systolic and diastolic BP for the patients with mild genotype were 122 mm Hg (112-130) and 78mmHg (70-84); severe genotype 119 mmHg (110-128) and 70 mmHg (64-75); NHANES 118(110-128) and 70 mmHg (62-78). Systolic blood pressures did not differ among the SCD groups versus NHANES, but diastolic blood pressures were higher in the mild SCD genotype patients than severe SCD patients (P<0.0001) or NHANES (P<0.0001), regardless of antihypertensive therapy. After controlling for covariates, in the severe genotype patients SBP associated significantly with gender and prior diagnosis of hypertension, but SBP associated only with hemoglobin level in the mild genotype patients. In contrast diastolic BP associated with gender and hemoglobin in the mild genotype but had no significant association in the severe genotype patients. In the NHANES controls, we observed that SBP was significantly associated with age, gender, BMI, prior hypertension, LDH, total bilirubin, urine albumin-creatinine ratio; and DBP associated with age, BMI, WBC count (Table 1). Discussion: Our SCD patient cohorts demonstrate a much higher median SBP, and for the mild genotype patients, higher DBP than was described for their age group in the cooperative study of sickle cell disease (Pegelow et al 1997). When compared with a contemporary NHANES cohort, we failed to observe a lower SBP or DBP as was expected. Higher systolic blood pressure has been reported as risk factor for the development of silent cerebral infarct in HbSS children (DeBaun et al 2014). Our study also shows that BP changes in SCD may be less influenced by traditional anthropometric measures and clinical markers. Figure 1 Figure 1. Disclosures Saraf: Global Blood Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding. Gordeuk: Modus Therapeutics: Consultancy; Novartis: Research Funding; Incyte: Research Funding; Emmaus: Consultancy, Research Funding; Global Blood Therapeutics: Consultancy, Research Funding; CSL Behring: Consultancy.

Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle

We performed a genome-wide association study and fine mapping using two methods (single marker regression: frequentist approach and Bayesian C (BayesC): fitting selected single nucleotide polymorphisms (SNPs) in a Bayesian framework) through three high-density SNP chip platforms to analyze milk production phenotypes in Korean Holstein cattle (n = 2780). We identified four significant SNPs for each phenotype in the single marker regression model: AX-311625843 and AX-115099068 on Bos taurus autosome (BTA) 14 for milk yield (MY) and adjusted 305-d fat yield (FY), respectively, AX-428357234 on BTA 18 for adjusted 305-d protein yield (PY), and AX-185120896 on BTA 5 for somatic cell score (SCS). Using the BayesC model, we discovered significant 1-Mb window regions that harbored over 0.5% of the additive genetic variance effects for four milk production phenotypes. The concordant significant SNPs and 1-Mb window regions were characterized into quantitative trait loci (QTL). Among the QTL regions, we focused on a well-known gene (diacylglycerol O-acyltransferase 1 (DGAT1)) and newly identified genes (phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) for MY and FY, and observed that DGAT1 is involved in glycerolipid metabolism, fat digestion and absorption, metabolic pathways, and retinol metabolism, and PDE4B is involved in cAMP signaling. Our findings suggest that the candidate genes in QTL are strongly related to physiological mechanisms related to the fat production and consequent total MY in Korean Holstein cattle.

Biomarkers of Cardiopulmonary, Renal, and Liver Dysfunction in an Adult Sickle Cell Disease Cohort

Introduction In sickle cell disease (SCD), chronic anemia, hypoxia, and NO scavenging related to intravascular hemolysis contribute to diastolic dysfunction and pulmonary hypertension. Free hemoglobin and heme released during hemolysis cause oxidative stress and exacerbate vascular inflammation. Iron overload from frequent blood transfusions provokes reactive oxygen species and consequently cellular damage. We examined correlation of biomarkers reflecting major aspects of SCD patho-physiology (hemolysis, anemia, hypoxia, inflammation, and iron overload) with cardiopulmonary, renal, and liver dysfunction in an adult SCD cohort. The study provides observational evidence for etiologies of sickle cell organ damage by assessing the relative strength of outcome association for these biomarkers. Methods The study included 442 SCD patients with median age of 31 years, 77% with severe β hemoglobin mutation genotypes (HbSS, HbSβ0-thalassemia, HbSOarab) and 58% female. Biomarkers were identified for the SCD etiological conditions listed in Table 1. Primary cardiopulmonary outcomes were left heart enlargement (left atrial and ventricular diameter) and elevated systolic pulmonary artery pressure measured by tricuspid regurgitation peak velocity (TRV). The primary renal outcome was elevated urine albumin to creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. Primary hepatic outcomes were hepatocyte integrity estimated as the first principal component (PC) of alanine transaminase (ALT) and aspartate aminotransferase (AST), cholestasis estimated as the first PC of alkaline phosphatase (ALP) and direct bilirubin, and functioning liver mass measured by serum albumin1. Clinical associations between biomarkers and primary outcomes first applied single marker regression with covariates of age, gender, and severity of β hemoglobin genotype. Significant biomarkers representative of the major SCD etiological conditions were then analyzed by multi-marker regression and model selection. Results Left atrial diameter showed significant associations with biomarkers of hemolysis (LDH, percent reticulocytes, AST, total bilirubin), anemia (HCT, HGB), hypoxia (HCT, HGB, O2 saturation), and inflammation (WBC) (Table 1). Left ventricular diameter had a profile of biomarker associations similar to left atrial diameter. TRV showed significant associations with biomarkers of hemolysis (LDH, percent reticulocytes, AST), anemia (HCT, HGB), hypoxia (HCT, HGB, O2 saturation), inflammation (WBC), and iron overload (ferritin) (Table 1). In multi-marker analysis, anemia and hypoxia (low HCT, low O2 saturation) associated with greater left atrial diameter and with high TRV (Figure 1). Urine ACR significantly associated with biomarkers of hemolysis (LDH, AST, percent reticulocytes), anemia (HCT, HGB), hypoxia (HCT, HGB, O2 saturation), inflammation (WBC, serum albumin), and iron overload (ferritin) (Table 1). Impaired kidney function based on eGFR <60 mL/min/1.73m2 had a profile of biomarker associations similar to ACR. In multi-marker analysis, hemolysis (high LDH), anemia (low HCT), and iron overload (high ferritin) associated with increased ACR that indicates renal damage (Figure 2). Hepatocyte integrity significantly associated with biomarkers of hemolysis (percent reticulocytes), anemia (HCT, HGB), hypoxia (HCT, HGB, O2 saturation), inflammation (WBC, serum albumin), and iron overload (ferritin) (Table 2). Cholestasis had a profile of biomarker associations similar to decreased hepatocyte integrity (Table 2). Functioning liver mass showed significant association with hemolysis (percent reticulocyte), anemia (HGB, HCT), and iron overload (ferritin) (Table 2). In multi-marker analysis, hemolysis (high percent reticulocyte) and iron overload (high ferritin) associated with decreased hepatocyte integrity (Figure 3A, 3B), whereas anemia (low HCT) and iron overload (high ferritin) associated with cholestasis (Figure 3C, 3D) and with low functioning liver mass (Figure 3E, 3F). Conclusion Our study indicated significant correlations of anemia and hypoxia with both left heart enlargement and elevated pulmonary arterial systolic pressure. Our study also underscores a significant impact of iron overload on renal and liver damages. Acknowledgement We thank CSL Behring Biotherapies for Life™ for their support of this study. Disclosures Saraf: Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Research Funding. Gordeuk:Pfizer: Research Funding; Inctye: Research Funding; Imara: Research Funding; CSL Behring: Consultancy, Honoraria, Research Funding; Ironwood: Research Funding; Global Blood Therapeutics: Consultancy, Honoraria, Research Funding; Emmaus: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Modus Therapeutics: Consultancy, Honoraria.

EigenGWAS: finding loci under selection through genome-wide association studies of eigenvectors in structured populations

We apply the statistical framework for genome-wide association studies (GWAS) to eigenvector decomposition (EigenGWAS), which is commonly used in population genetics to characterise the structure of genetic data. We show that loci under selection can be detected in a structured population by using eigenvectors as phenotypes in a single-marker GWAS. We find LCT to be under selection between HapMap CEU-TSI cohorts, a finding that was replicated across European countries in the POPRES samples. HERC2 was also found to be differentiated between both the CEU-TSI cohort and among POPRES samples, reflecting the likely anthropological differences in skin and hair colour between northern and southern European populations. We show that when determining the effect of a SNP on an eigenvector, three methods of single-marker regression of eigenvectors, best linear unbiased prediction of eigenvectors, and singular value decomposition of SNP data are equivalent to each other. We also demonstrate that estimated SNP effects on eigenvectors from a reference panel can be used to predict eigenvectors (the projected eigenvectors) in a target sample with high accuracy, particularly for the primary eigenvectors. Under this GWAS framework, ancestry informative markers and loci under selection can be identified, and population structure can be captured and easily interpreted. We have developed freely available software to facilitate the application of the methods (https://github.com/gc5k/GEAR/wiki/EigenGWAS).