Log2 Transformation Research Articles

Red blood cell folate level is associated with periodontitis in American adults: results from the NHANES 2009–2014

BackgroundRed blood cell (RBC) folate is an indicator of long-term folate nutrition. Whether there is an association between RBC folate and periodontitis is unclear. This study aimed to use the NHANES database to determine whether RBC folate is associated with moderate/severe periodontitis.MethodsA cross-sectional analysis of 10,151 participants in the NHANES database from 2009 to 2014 was performed. Multivariate logistic regression was used to analyze the independent relationship between RBC folate and moderate/severe periodontitis. The generalized additive model (GAM), restricted cubic splines (RCS), smooth curve fitting, and threshold effect analysis were used to explore the dose–response relationship and the potential nonlinear relationship between RBC folate and periodontitis. Finally, subgroup analysis and interaction tests were performed to determine the effect of covariates on the relationship between RBC folate and moderate/severe periodontitis.ResultsAfter adjusting for all confounders, there was a negative association between RBC folate concentration and moderate/severe periodontitis. The lowest fraction Q1 (< 360 ng/mL) of RBC folate concentration was used as the reference group, multivariable-adjusted ORs and 95% CIs of the second (360-463 ng/mL), third (464-569 ng/mL), fourth (570-732 ng/mL), and the highest quintile (> 733 ng/mL) categories were 0.88 (0.77, 1.01), 0.83 (0.72, 0.96), 0.77 (0.67, 0.90), 0.65 (0.56, 0.77) respectively. Additionally, a threshold nonlinear association was found between RBC folate (ng/mL) log2 transformation and moderate/severe periodontitis.ConclusionThis cross-sectional study revealed a negative relationship between RBC folate and moderate/severe periodontitis within a certain threshold range. Dentists and policymakers should pay closer attention to oral hygiene and health care for people with low or high RBC folate levels. Further causal and longitudinal research mechanisms are needed to validate our findings.

Association between secondhand smoke exposure and rheumatoid arthritis in US never-smoking adults: a cross-sectional study from NHANES

While smoking is widely acknowledged as a risk factor for rheumatoid arthritis (RA), the connection between secondhand smoke (SHS) exposure and RA in never-smoking adults remains limited and inconsistent. This study aims to explore and quantify this association using serum cotinine levels. We conducted a cross-sectional study with 14,940 adults who self-report as never smokers, using National Health and Nutrition Examination Survey data from 1999 to 2018. Based on previous literature, SHS exposure was categorized into four groups according to serum cotinine levels. Compared to individuals in the unexposed group (serum cotinine < 0.05 ng/mL), the adjusted odds ratio (OR) for RA was 1.37 (95% CI 1.14–1.64, p = 0.001) in the low exposure group (serum cotinine at 0.05 to 0.99 ng/mL) after adjusting for covariates. However, no significant association was found in the moderate exposure group (serum cotinine at 1 to 10 ng/mL) or the heavy exposure group (serum cotinine ≥ 10 ng/mL). Furthermore, we detected a non-linear, positively saturated correlation between the cotinine levels after log2 transformation and RA, with a turning point at approximately − 2.756 ng/mL (OR = 1.163, 95% CI 1.073–1.261, p = 0.0002). The stability of the results was confirmed by subgroup analysis.

Discovering Promising Biomarkers and Therapeutic Targets for Duchenne Muscular Dystrophy: a Multiomics Meta-Analysis Approach.

Duchenne muscular dystrophy (DMD) is a genetic disorder that causes muscle weakness and degeneration. In this study, we identified potential biomarkers and drug targets for DMD through a comprehensive meta-analysis of mRNA profiles. We conducted an in-depth analysis of three microarray datasets from the GEO database, utilizing the Affymetrix platform. A rigorous data pre-processing pipeline encompassed background correction, normalization, log2 transformation and probe-to-gene symbol mapping. Robust multi-array average method followed by Limma package in R was employed to ensure differential expression analysis within individual datasets, yielding gene-specific p-values. We identified 63 genes exhibiting statistically significant differential expression across the three datasets (p < 0.05) and an absolute log fold change > 1.5. Functional enrichment analyses of these differentially expressed genes were done, followed by pathway analyses. Our results suggested pertinent biological processes, molecular functions and cellular components associated with DMD. Finally, eight hub genes-COL6A3, COL1A1, COL3A1, COL1A2, POSTN, TIMP1, THBS2 and SPP1-were pinpointed as central players in the network. Two differentially expressed genes with substantial absolute log-fold changes, namely, DMD, downregulated and MYH3, upregulated, were identified as potential therapeutic candidates. In light of these findings, our work contributes not only to understanding DMD at the molecular level but also presents potential targets for therapeutic strategies. Finally,our study facilitates the development of therapeuticinterventions that can effectively control and mitigate the impact of DMD.

Discovery‐based proteomics identifies plasma proteins that predict longitudinal cognitive decline in older adults over a 7‐year follow‐up period

AbstractBackgroundRecent technological advances have enabled large‐scale proteomic profiling of plasma and especially in studies of Alzheimer’s disease. However, studies that have comprehensively examined longitudinal cognitive decline as an outcome from plasma protein levels prior to the onset of clinical dementia are limited. This project aimed to identify plasma proteins predictive of cognitive decline across a robust neuropsychological protocol over a 7‐year follow‐up period.MethodsVanderbilt Memory and Aging Project participants (n = 333, 73±7 years, 41% female) free of clinical dementia at study entry underwent fasting blood draw and comprehensive serial neuropsychological assessment over a 7‐year period (mean follow‐up = 5.8 years). Plasma samples were subjected to multiplex liquid chromatography tandem mass spectrometry analysis to quantify cross‐sectional protein abundances for each participant at study entry. Normalization of proteomic data adjusted for batch effects, high levels of missingness, and log2 transformation. Linear mixed‐effects regressions related protein levels to longitudinal neuropsychological outcomes, adjusting for age, sex, race/ethnicity, education, baseline cognitive status, apolipoprotein E ε4 status, and follow‐up time. False discovery rate correction was applied to the a priori significance threshold.ResultsInitial proteomics analyses yielded 3,784 proteins, of which 686 were used as analytical predictors following quality control, post‐acquisition filtering, and data normalization. Regression analyses resulted in 86 proteins which predicted longitudinal decline in global cognition, as assessed by the Montreal Cognitive Assessment. In analyses with individual neuropsychological domains as outcomes, 144 proteins predicted longitudinal decline in at least one neuropsychological domain [episodic memory (40 proteins), language (72 proteins), information processing speed (99 proteins), executive function (22 proteins), visuospatial skills (55 proteins)]. There was a smaller number of proteins (i.e., five) that were predictive of longitudinal cognitive decline across all domains.ConclusionWe conducted large‐scale proteomics analyses and identified 144 plasma proteins at study entry among a cohort of older adults free of clinical dementia that predict subsequent decline in cognition over a 7‐year follow‐up period. Five of these proteins were predictive of decline across all domains suggesting these proteins may represent biological pathways that adversely affect brain health with increasing age. Replication is needed to validate identified proteins as potential biomarkers of cognitive decline.

Acute Kidney Injury (AKI) in COVID-19: In silico Identification of LncRNA-MiRNA-Gene Networks and Key Transcription Factors.

Acute kidney injury (AKI) accounts for up to 29% of severe COVID-19 cases and increases mortality among these patients. Viral infections participate in the pathogenesis of diseases by changing the expression profile of normal transcriptome. This study attempts to identify LncRNA-miRNA-gene and TF-gene networks as gene expression regulating networks in the kidney tissues of COVID-19 patients. In this analysis, four kidney libraries from the GEO repository were considered. To conduct the preprocessing, Deseq2 software in R was used for the purpose of data normalization and log2 transformation. In addition, pre- and post-normalization, PCA and box plots were developed using ggplot2 software in R for quality control. The expression profiles of the kidney samples of COVID-19 patients and control individuals were compared using DEseq2 software in R. The considered significance thresholds for DEGs were Adj P value < 0.05 and |logFC| >2. Then, to predict molecular interactions in lncRNA-miRNA-gene networks, different databases, including DeepBase v3.0, miRNATissueAtlas2, DIANA-LncBase v3, and miRWalk, were used. Furthermore, by employing ChEA databases, interactions at the TF-Gene level were obtained. Finally, the obtained networks were plotted using Stringdb and Cytoscape v8. Results obtained from the comparison of the post-mortem kidney tissue samples of the COVID-19 patients with the healthy kidney tissue samples showed significant changes in the expression of more than 2000 genes. In addition, predictions regarding the miRNA-gene interaction network based on DEGs obtained from this meta-analysis showed that 11 miRNAs targeted the obtained DEGs. Interestingly, in the kidney tissue, these 11 miRNAs interacted with LINC01874, LINC01788, and LINC01320, which have high specificity for this tissue. Moreover, four transcription factors of EGR1, SMAD4, STAT3, and CHD1 were identified as key transcription factors regulating DEGs. Taken together, the current study showed several dysregulated genes in the kidney of patients affected with COVID-19. This study suggests lncRNA-miRNA-gene networks and key TFs as new diagnostic and therapeutic targets for experimental and preclinical studies.

Associations between smoke exposure and kidney stones: results from the NHANES (2007-2018) and Mendelian randomization analysis.

It is currently controversial whether smoke exposure is associated with the risk of kidney stones. Herein, publicly available databases were combined to explore relationships with the risk of nephrolithiasis in terms of smoking status and serum cotinine concentrations. First, we conducted an observational study using data from 2007 to 2018, based on the National Health and Nutrition Examination Survey (NHANES) database. Univariate analysis, multivariate logistic regression, trend testing, restricted cubic spline (RCS), and multiple imputation (MI) were the main analytical methods of our study. Then, A Mendelian randomization (MR) analysis was performed to explore the causal relationship between serum cotinine and nephrolithiasis. Genetic instruments for serum cotinine and pooled data for kidney stones were derived from publicly available large-scale genome-wide association studies (GWAS). Inverse-variance weighting (IVW) was the primary method for our MR analysis. A total of 34,657 and 31,352 participants were included in the observational study based on smoking status and serum cotinine concentrations, respectively. Under full adjustment of covariates, current smokers had an increased risk of kidney stones compared to non-smokers [OR = 1.17 (1.04-1.31), P = 0.009, P for trend = 0.010]. Compared with serum cotinine of <0.05 ng/ml, serum cotinine levels of 0.05-2.99 ng/ml [OR = 1.15 (1.03-1.29), P = 0.013] and ≥3.00 ng/ml [OR = 1.22 (1.10-1.37), P < 0.001] were observed to have a higher risk of nephrolithiasis (P for trend < 0.001). In addition, a non-linear relationship between log2-transformed serum cotinine and the risk of nephrolithiasis was found (P for non-linearity = 0.028). Similar results were found when serum cotinine (log2 transformation) was used as a continuous variable [OR = 1.02 (1.01-1.03), P < 0.001] or complete data was used to analyze after MI. In the MR analysis, genetically predicted high serum cotinine was causally related to the high risk of nephrolithiasis [IVW: OR = 1.09 (1.00-1.19), P = 0.044]. Current smoking and high serum cotinine concentrations may be associated with an increased risk of kidney stones. Further research is needed to validate this relationship and explore its underlying mechanisms.

The relationship between serum albumin and prostate-specific antigen: A analysis of the National Health and Nutrition Examination Survey, 2003-2010.

Previous studies have shown that serum albumin is associated with prostate cancer (PCa), but not with prostate-specific antigen (PSA) levels in populations without PCa history. Therefore, we analyzed secondary data provided by the National Health and Nutrition Examination Survey (NHANES) (2003-2010). In total, 5,469 participants were selected from the NHANES database (2003-2010). Serum albumin and PSA levels were serially considered independent and dependent variables, serially. A number of covariates were included in this study, including demographic, dietary, physical examination, and comorbidity data. Using weighted linear regression model and smooth curve fitting, the linear and non-linear relationship between serum albumin and PSA was investigated. After modulating underlying interference factors, the weighted multivariate linear regression analysis revealed that serum albumin did not independently predict PSA levels (β = -0.009 95%CI: -0.020, 0.002). Nevertheless, a non-linear relationship was found between serum albumin and PSA, with a point of 41 g/L. Left of the inflection point, the effect size, 95%CI, and P-value were 0.019 (log2 transformation) (-0.006, 0.043) and 0.1335, respectively. We found a negative association between serum albumin and PSA on the right side of the inflection point, with effect size, 95%CI, and a P-value of -0.022 (log2 transformation) (-0.037, -0.007), 0.0036. In summary, serum albumin and PSA levels are not linearly related. When serum albumin levels exceed 41 g, serum albumin levels are negatively associated with PSA levels.

Construction of a pyroptosis-related lncRNAs signature for predicting prognosis and immunotherapy response in glioma.

Recent studies have proved that pyroptosis-related long non-coding RNAs (PRlncRNAs) are closely linked to tumor progression, prognosis, and immunity. Here, we systematically evaluated the correlation of PRlncRNAs with glioma prognosis. This study included 3 glioma cohorts (The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and Gravendeel). Through Pearson correlation analysis, PRlncRNAs were screened from these 3 cohorts. Univariate Cox regression analysis was then carried out to determine the prognostic PRlncRNAs. A pyroptosis-related lncRNAs signature (PRLS) was then built by least absolute shrinkage and selection operator and multivariate Cox analyses. We systematically evaluated the correlation of the PRLS with the prognosis, immune features, and tumor mutation burden in glioma. A total of 14 prognostic PRlncRNAs overlapped in all cohorts and were selected as candidate lncRNAs. Based on The Cancer Genome Atlas cohort, a PRLS containing 7 PRlncRNAs was built. In all cohorts, the PRLS was proved to be a good predictor of glioma prognosis, with a higher risk score related to a poorer prognosis. We observed obvious differences in the immune microenvironment, immune cell infiltration level, and immune checkpoint expression in low- and high-risk subgroups. Compared with low-risk cases, high-risk cases had lower Tumor Immune Dysfunction and Exclusion scores and greater tumor mutation burden, indicating that high-risk cases can be more sensitive to immunotherapy. A nomogram combining PRLS and clinical parameters was constructed, which showed more robust and accurate predictive power. In conclusion, the PRLS is a potentially useful indicator for predicting prognosis and response to immunotherapy in glioma. Our findings may provide a useful insight into clinically individualized treatment strategies for patients.

Digital Spatial Profiling of Glomerular Gene Expression in Pauci-Immune Focal Necrotizing Glomerulonephritis.

Pauci-immune focal necrotizing glomerulonephritis (piFNGN) involves asynchronous onset and progression of injurious lesions in biopsies. Pathologists can describe this heterogeneity within a biopsy, but translating the information into prognostic or expression analyses is challenging. Understanding the underlying molecular processes could improve treatment; however, bulk or single-cell transcriptomic analyses of dissociated tissue disregard the heterogeneity of glomerular injury. We characterize protein and mRNA expression of individual glomeruli in 20 biopsies from 18 patients with antineutrophil cytoplasmic antibody-associated piFNGN using the NanoString digital spatial profiling (DSP) platform. For this purpose, circular annotations of glomeruli were analyzed using protein, immuno-oncology RNA, and Cancer Transcriptome Atlas panels (n=120, 72, and 48 glomeruli, respectively). Histologic evaluation of glomerular patterns of injury was performed in adjacent serial sections. Expression data were processed by log2 transformation, quantile normalization, and batch adjustment. DSP revealed distinct but overlapping gene expression profiles relating to the morphological evolution of injurious lesions, including dynamic expression of various immune checkpoint regulators. Enrichment analysis indicated deregulated pathways that underline known and highlight novel potential mechanisms of disease. Moreover, by capturing individual glomeruli, DSP describes heterogeneity between and within biopsies. We demonstrate the benefit of spatial profiling for characterization of heterogeneous glomerular injury, indicating novel molecular correlates of glomerular injury in piFNGN.

Digital spatial profiling of glomerular gene expression in pauci-immune focal necrotizing glomerulonephritis

Introduction: Pauci-immune focal necrotizing glomerulonephritis (piFNGN) involves asynchronous onset and progression of injurious lesions in biopsies. Pathologists describe this heterogeneity within a biopsy, but translating the information into prognostic or expression analyses is challenging. Understanding the underlying molecular processes could improve treatment; however, bulk or single cell transcriptomic analyses of dissociated tissue disregard the heterogeneity of glomerular injury. Methods: We characterize protein and mRNA expression of individual glomeruli in 20 biopsies from 18 patients with anti-neutrophil cytoplasmic antibody-associated piFNGN using the Nanostring digital spatial profiling (DSP) platform. For this purpose, circular annotations of glomeruli were analyzed using protein, immuno-oncology RNA, and cancer transcriptome atlas panels (n=120, 72, and 48 glomeruli, respectively). Histological evaluation of glomerular patterns of injury was performed in adjacent serial sections. Expression data was processed by log2 transformation, quantile normalization and batch adjustment. Results: DSP revealed distinct but overlapping gene expression profiles relating to the morphological evolution of injurious lesions, including dynamic expression of various immune checkpoint regulators. Enrichment analysis indicated deregulated pathways that underline known and highlight novel potential mechanisms of disease. Moreover, by capturing individual glomeruli, DSP describes heterogeneity between and within biopsies. Conclusions: We demonstrate the benefit of spatial profiling for characterization of heterogeneous glomerular injury, indicating novel molecular correlates of glomerular injury in piFNGN.

Abstract 160: Associations Between Markers Of Inflammation And Myocardial Injury In Out-of-hospital Cardiac Arrest Patients After Treatment With Tocilizumab - A Sub Study Of The IMICA Trial

Background: Systemic inflammation is a major component of the post-cardiac arrest syndrome. Treatment with tocilizumab, an interleukin 6 receptor antagonist, was shown in the IMICA trial to reduces systemic inflammation and markers of myocardial injury in comatose resuscitated out-of-hospital cardiac arrest (OHCA) patients. This was demonstrated by lower levels of the markers of inflammation, CRP, and leukocytes, as well as the marker of myocardial injury, Troponin T (TnT), in patients treated with tocilizumab compared to placebo. OBJECTIVE: To investigate associations between markers of inflammation and myocardial injury in the IMICA trial. Methods: At admission, 80 OHCA patients were randomized to either tocilizumab or placebo (NCT03863015). Area under the curve (AUC) between 0-72 hours was calculated for leukocyte count, CRP, and TnT. Spearman’s correlation analyses were performed after log2 transformation. Results: AUC of leukocytes correlated positively with TnT in both treatment arms (tocilizumab: r=0.4, p=0.03; placebo: r=0.4, p=0.02; see figure). Also, a positive correlation between AUC of CRP and TnT was found in patients treated with tocilizumab but not in patients receiving placebo (tocilizumab: r=0.3, p=0.03; placebo: r&lt;0.1 p=0.86). Conclusions: These findings illustrate that in general, patients with lower levels of leukocytes also had lower levels of myocardial injury. The correlation between CRP and TnT in the tocilizumab group could possibly reflect response to treatment, or baseline activity prior to treatment. Modulation of inflammation could have cardioprotective as well as systemic effects, both of which could be possible mechanisms for the reductions in biomarkers of myocardial injury as previously reported in this trial. However, correlation does not necessarily imply causality and it is possible that other, yet uninvestigated mechanisms are responsible for the observed effects of tocilizumab.

Development of the gut microbiota in healthy twins during the first 2 years of life and associations with body mass index z-score: Results from the Wuhan twin birth cohort study.

The gut microbiota undergoes rapid and vital changes to microbial community structure and the microbial-immune crosstalk during the first 3 years of life, which is thought to be involved in the pathobiology of later-life disease. Compared to single-born children, little is known about the gut microbiota of twins in early childhood. Based on the Wuhan Twin Birth Cohort study, 344 stool samples from 204 twin families were analyzed to investigate the difference in gut microbiota composition at 6, 12, and 24 months of age. Furthermore, this study evaluated the association between gut microbiota development curves and body mass index z-score (BMI_Z) curves at 6, 12, and 24 months of age. The predominant microbiota phyla identified in twins were Proteobacteria, Actinobacteriota, Firmicutes, Bacteroidota, and Verrucomicrobiota. The richness and diversity of gut microbiota increased from 6 to 24 months old (alpha diversity with p < 0.05). Beta diversity revealed 61 gut microbiota genera that were significantly different in relative abundance among the three age groups. Among the 61 gut microbiota genera, 30 distinct trajectory curves (DTCs) were generated by group-based trajectory models after log2 transformation of their relative abundance. Subsequently, Spearman correlation analysis revealed that only five gut microbiota DTC were correlated with the BMI_Z DTC. Therefore, we further examined the association between the five gut microbiota genera DTC and BMI_Z DTC using generalized estimation equation models. The results revealed a significant association between the DTC groups of Parabacteroides and that of BMI_Z (coefficient = 0.75, p = 0.04). The results of this study validated the hypothesis that the richness and diversity of gut microbiota developed with age in twins. Moreover, participants with a higher DTC of log2-transformed Parabacteroides had a higher BMI_Z DTC during the first 2 years of life. Further studies are needed to confirm the association between Parabacteroides and BMI_Z in other populations.

Abstract 3417: Effects of plasma exosome isolation methods on detectable multiomic profiles in cancer patients and healthy controls

Abstract Introduction: Circulating exosomes in blood have been considered as a treasure chest for biomarker discovery in cancer. Due to their heterogeneity, different isolation methods may enrich distinct exosome cargos generating different omic profiles. In this study, we evaluated the effects of plasma exosome isolation methods on detectable multiomic profiles in cancer patients and healthy controls. Methods: Plasma exosomes were isolated from prostate cancer patients (PC; N = 11), lung cancer patients (LC; N = 13), and matched healthy controls (HC; N = 10) using three methods [SBI (size exclusion), Takara (lectin binding), and Wako (Tim4 binding)]. Mass spectrometry was performed to determine exosome lipidome and metabolome profiles. To evaluate group-specific exosome enrichment, we developed an exosome enrichment index (EEI) by summing 50 smallest p-values after log2 transformation. Higher EEI indicates prefrential capture of significant exosome cargos from patients over controls. Results: Our data showed that the SBI method generated the most identified lipids from exosome across all groups (LC = 935, PC = 939, and HC = 943), followed by Takara (245, 245 and 245) and Wako (205, 208 and 213). Compared to controls, LC patients had 31 higher and 5 lower lipid levels (FDR &amp;lt; 0.1) using the SBI and 3 higher and 1 lower level (FDR &amp;lt; 0.1) using Takara. We did not observe any differences between cancer and normal samples using Wako. The most detectable known metabolites were found in exosomes from SBI (LC = 188, PC = 191, and HC = 100), followed by Wako (LC = 107, PC = 107, and HC = 107) and Takara (LC = 99, PC = 100, and HC = 100). Of the metabolites from SBI, 5 were significantly higher (FDR&amp;lt;0.1) in PC patients than in controls. The most significant metabolite in PC was L-Cystathionine, which has been shown to be upregulated in bone-metastatic PC3 cells. Neither Takara nor Wako exosome fractions showed differently expressed metabolites between any groups. Our EEI analysis showed the highest lipid EEI from SBI in PC (474.4) and LC (906.74), while a lower lipid EEI from Takara in PC (359.9), LC (495.58), and Wako in PC (307.5) and LC (148.1). Metabolite EEI showed an EEI range from 590.3 in SBI PC to 185.6 in Takara LC. SBI, again, achieved the highest EEI for both PC and LC (357.3). Conclusion: These results support that the SBI method can capture more heterogeneous exosome populations, possibly because this size exclusion-based method does not discriminate exosomes with different protein components. In contrast, Takara and Wako methods target exosome surface proteins, enriching specific exosome subpopulations resulting in less diversity of detectable lipids and metabolites. Overall, these findings suggest that exosome isolation methods can select subpopulations and determine the exosome content, which will significantly impact exosome-based biomarker discovery. Citation Format: Alex C. Soupir, Paul A. Stewart, Yury Nunez Lopez, Brandon J. Manley, Bruna Pellini, Jingsong Zhang, Qianxing Mo, Douglas C. Marchion, Min Lui, John M. Koomen, Erin M. Siegel, Liang Wang. Effects of plasma exosome isolation methods on detectable multiomic profiles in cancer patients and healthy controls [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3417.

DDRE-40. BIOINFORMATICS ANALYSIS OF GRADE I AND III MENINGIOMA GENE EXPRESSION SUGGESTS MMP28 AS A POSSIBLE POSITIVE PROGNOSTIC INDICATOR

Abstract Meningiomas are the most common primary brain tumor. Grade I meningiomas are slow growing with a good prognosis following surgical resection. High grade meningiomas (II and III) are more aggressive with greater rates of recurrence and poor prognosis despite surgical resection and radiotherapy. This study sought to identify key pathways and genes that contribute to the molecular mechanisms that separate these distinct meningioma phenotypes. FFPE specimens were evaluated and graded by a pathologist. Total RNA was extracted from tissue curls and RNA samples were measured with the Illumina DASL whole genome gene expression assay (n = 29,374 probes). A log2 transformation was applied to all of the data and quantile normalization using 21 samples. A t-test of the log2 expression of the 10 grade III samples and 11 grade I samples resulted in 1505 differentially expressed genes. The GeneCard Suite’s GeneAnalytics tool was used to perform pathway enrichment analysis. Similar to other comparable data sets, DNA Damage, Cell Cycle, EGF/EGFR Signaling, TGF-Beta Signaling, and PI3K-AKT Signaling pathways were among the 20 enriched pathways. Notably, matrix metalloprotease 28 (MMP28, also known as epilysin) was down regulated in grade III meningiomas compared to grade I (III/I expression ratio 0.315; P=0.015). MMP28 is expressed in numerous tissues including the nervous system during development and regeneration. In cancer, MMP28 is thought to enhance epithelial to mesenchymal transition by altering the TGF-B signaling pathways. MMP28 is an indicator of poor prognosis for pancreatic, lung, gastric and hepatic cancers as well as glioblastoma. However, MMP28 has also been reported as down regulated during malignant transformation in colon cancer. Our data suggest that MMP28 may have an alternative role in meningioma and serve as a positive prognostic indicator.

Relationship of daily total somatic cell output with somatic cell concentration and clinical mastitis

Somatic cell count (SCC) measures the concentration of somatic cells in milk and is used as a mastitis diagnostic tool. It is plausible that variation in milk yield could alter the relationship between SCC and mastitis status. Our objective was to evaluate total daily SCC output as a predictor of clinical mastitis. Data included 37,035 test-day records from 4,179 lactations of 1,679 cows and 1,286 mastitis events from an experimental herd. Daily total SCC was derived by multiplying SCC by daily milk yield in milliliters and transformed to daily total somatic cell score (DTSCS) via a log2 transformation. Milk yield, SCS, and DTSCS were evaluated with mixed models that included the proximity of a mastitis event to the test date and days in milk as the main fixed effects. A second series of logistic regression was conducted that considered mastitis (1 = mastitis occurred during a test interval; 0 = no mastitis) as the dependent variable with milk yield, SCS, and DTSCS the main independent effects. Least squares means for test dates associated with mastitis-free lactations were 2.43 and 2.25 for SCS and DTSCS, respectively. The corresponding values were 5.96 for SCS and 5.66 for DTSCS for the week of a mastitis event. Whereas SCS declined rapidly in early lactation and then increased steadily thereafter, DTSCS was lowest in early lactation and increased by a proportionally smaller amount throughout lactation. Including both SCS and DTSCS in the same model improved the logistic regression model fit over a model with SCS only. Dilution effects from milk yield influence SCS, and consideration of DTSCS in management and genetic selection schemes could improve mastitis detection and resistance.

Association of homologous recombination deficiency in ovarian cancer with neoantigen load and expression of immune checkpoints.

5536 Background: Immune checkpoint blockade (ICB) is being explored as a treatment option in ovarian cancer, but objective response rates for single agent ICB are modest at around 10-15%. Validated biomarkers are needed to predict which patients will respond to ICB. BRCA mutations and homologous recombination deficiency (HRD) status are the only validated integral biomarkers in ovarian cancer. HRD tumors exhibit defective DNA repair mechanisms that promote increased mutational burden, which we postulate may correlate with higher neoantigen load and increased expression of targetable immune checkpoints. Methods: The Cancer Genome Atlas (TCGA) ovarian cancer dataset was evaluated and previously published, well annotated samples were obtained for HRD status. HLA type was determined with OptiType. Nonsynonymous mutations were annotated with Ensembl VEP. pVAC-Seq using NetMHCpan algorithm predicted neoepitopes 9 amino acids in length for MHC class I, reporting only those with a predicted IC50 less than 500 nM. Immune checkpoint gene expression counts were normalized with TCGAbiolinks. Correlation between HRD status and neoantigen load was assessed by Wilcoxon test. After log2 transformation, Wilcoxon tests evaluated for association between HRD status and expression of immune checkpoints. The relationship between HRD status and PD-L1 protein abundance with reverse phase protein array was measured. Results: Data from 154 HRD positive and 198 HRD negative tumors were analyzed. HRD positive status correlated with higher neoantigen load (p = 0.038) and increased expression of the immune checkpoints CTLA4 (p = 0.024), TIGIT (p = 0.027), and PVR (p = 0.002), but not PD-L1 (p = 0.238), LAG3 (p = 0.583), HVEM (p = 0.805), GAL9 (p = 0.750), NECTIN2 (p = 0.874), VSIG3 (p = 0.438), PSGL1 (p = 0.205) or VISTA (p = 0.531). TIM3 (p = 0.064) and B7H3 (p = 0.052) both demonstrated a trend towards increased expression in HRD tumors. Interestingly, HRD status showed a negative association with PVRIG (p = 0.028). There was no association between PD-L1 protein abundance and HRD status. Conclusions: HRD positive ovarian tumors demonstrate higher neoantigen load than HRD negative tumors, as well as increased expression of certain immune checkpoints. This supports the hypothesis that increased neoantigen load leads to compensatory induction of immune checkpoints, and suggests that HRD status may predict response to ICB, particularly to drugs that target CTLA4, TIGIT, PVR, TIM3 and B7H4.

Differential Expression Analysis for the Identification of Survival Associated Genes in Primary Bladder Cancer using Microarray Data

Bladder cancer (BC) is a highly malignant and malevolent tumor whose incidence and mortality worldwide remains high. This paper aimed to identify the differentially expressed genes (DEGs) between normal and primary bladder cancer samples, which might be of prognostic value, and evaluate their association to clinical outcomes (survival) in patients with primary bladder cancer. A sample of 256 gene expression profiles of which 10 were normal bladder mucosae whereas 165 were primary bladder cancer tissues were downloaded from the gene expression omnibus (GEO). The limma package in R was used to perform screening for DEGs after variance reduction through quantile normalization and log2 transformation. Gene Ontology (GO), KEGG enrichment analysis, and Network analysis were performed to determine the functions of these DEGs. Cox proportional hazard regression model was then used to determine the association between the top selected DEGs and overall primary bladder cancer survival. Selected genes were then encoded as either low, middle or high expression and Kaplan-Meier plots then used to visualize the effect of these expression levels for the selected five genes on bladder cancer survival probability. This study identified a total of 5, 979 DEGs where 2, 878 were upregulated, 3, 101 were downregulated and 37, 169 were not significantly expressed differently. Cox proportional hazard stepwise regression models revealed a number of DEGs that have a statistically significant association to bladder cancer. The selected five DEGs associated with survival were EDNRB (HR=1.9858, 95%CI 1.4965–2.6350), COL14A1 (HR=1.5335, 95%C1 1.1670–2.0151), MOXD1 (HR=1.4878, 95%CI 1.1070–1.9996), FAM107A (HR=1.4970, 95%CI 1.1162–2.0077), and REM1 (HR=1.5999, 95%CI 1.2422–2.0605). After encoding these genes as either low, middle, or high expression, high expression of both EDNRB, COL14A1, FAM107A, and REM1 were found to result into statistically significant reductions in survival probabilities of patients (p0.05). The genes found in this study could provide useful insight in the understanding of the association between the identified DEGs and primary bladder cancer survival, which can further inform future studies and clinical therapies.

A meta-analysis of comorbidities in COVID-19: Which diseases increase the susceptibility of SARS-CoV-2 infection?

Comorbidities in COVID-19 patients often lead to more severe outcomes. The disease-specific molecular events, which may induce susceptibility to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, are being investigated. To assess this, we retrieved array-based gene expression datasets from patients of 30 frequently occurring acute, chronic, or infectious diseases. Comparative analyses of the datasets were performed after quantile normalization and log2 transformation. Among the 78 host genes prominently implicated in COVID-19 infection, ACE2 (receptor for SARS-CoV-2) was positively regulated in several cases, namely, leukemia, psoriasis, lung cancer, non-alcoholic fatty liver disease (NAFLD), breast cancer, and pulmonary arterial hypertension (PAH). FURIN was positively regulated in some cases, such as leukemia, psoriasis, NAFLD, lung cancer, and type II diabetes (T2D), while TMPRSS2 was positively regulated in only 3 cases, namely, leukemia, lung cancer, and T2D. Genes encoding various interferons, cytokines, chemokines, and mediators of JAK-STAT pathway were positively regulated in leukemia, NAFLD, and T2D cases. Among the 161 genes that are positively regulated in the lungs of COVID-19 patients, 99–111 genes in leukemia (including various studied subtypes), 77 genes in NAFLD, and 48 genes in psoriasis were also positively regulated. Because of the high similarity in gene expression patterns, the patients of leukemia, NAFLD, T2D, psoriasis, and PAH may need additional preventive care against acquiring SARS-CoV-2 infections. Further, two genes CARBONIC ANHYDRASE 11 (CA11) and CLUSTERIN (CLU) were positively regulated in the lungs of patients infected with either SARS-CoV-2, or SARS-CoV or Middle East Respiratory Syndrome Coronavirus (MERS-CoV).

High-risk gene expression profiles for colorectal liver metastases

Presenter: Michael Turgeon MD | Emory University Background: Over half of patients with colorectal cancer develop liver metastases with a minority of patients considered resectable at presentation. While there has been significant progress in the development of new biologics for the treatment of colorectal liver metastases (CRLM), only a small proportion of patients harbor actionable mutations. Furthermore, gene expression patterns of liver-specific metastases remain unclear. Our aim was to identify high-risk gene expression profiles for patients with CRLM to better inform prognosis and the development of novel targeted therapies. Methods: We examined 53 formalin-fixed paraffin-embedded (FFPE) colorectal liver metastasis samples from patients who underwent complete metastasectomy from 2009-2017 at a single institution. Immune cell infiltration was confirmed with CD45 antibody staining via immunohistochemistry (IHC). Targeted mRNA expression profiling was performed with extracted RNA using the NanoString Immune Oncology (IO360) 750-gene panel. Expression counts were normalized by the geometric mean of the positive-control and the most stable housekeeping genes were selected using the geNorm algorithm followed by log2 transformation. The differential expression analysis with fold changes and p-values were calculated using the NanoString methodology. Groups of interest were dichotomized based on synchronous versus metachronous disease and risk profiles. Risk profiles were based on median and quartile overall survival (OS) cut-points. “High-risk” was considered OS below the median or 25th percentile, while “low-risk” was OS above the median, above the 75th percentile, or no death due to disease. Results: Of 53 patients, median overall survival was 58 months. Median follow-up was 36 months. Using the NanoString IO360 panel, we detected no differentially expressed genes between synchronous (n=28) and metachronous (n=25) CRLM. Considering risk profiles, four differentially expressed genes were identified comparing tumors from high-risk (n=4) versus low-risk (n=18) patients based on a median OS cut-point of 45 months. Pathway analysis indicated these gene expression signatures were associated with antigen presentation, DNA repair, and collagen synthesis. When comparing the 25th percentile (high-risk n=2) to the 75th percentile (low-risk n=16), a total of 68 down-regulated genes were detected that were primarily involved in the antigen presentation pathways. Conclusion: Patients with colorectal liver metastases with poor overall survival may have a distinct, “high-risk” gene expression profile that manifests in alterations in antigen presentation, DNA repair, and collagen synthesis pathways. The identified genes serve as promising molecular markers for prognostication and for the development of novel targeted therapies. Next steps include NanoString analysis with an expanded cohort, immunohistochemistry to validate protein expression, and modulation of gene expression in cell lines.

N-Terminal Pro-B-Type Natriuretic Peptide and Clinical Outcomes: Vericiguat Heart Failure With Reduced Ejection Fraction Study

ObjectivesThe purpose of this study was to examine the treatment effect of vericiguat in relation to N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels at randomization. BackgroundVericiguat compared with placebo reduced the primary outcome of cardiovascular death (CVD) or heart failure hospitalization (HFH) in patients with HF with reduced ejection fraction (HFrEF) in the VICTORIA (A Study of Vericiguat in Participants With Heart Failure With Reduced Ejection Fraction) trial. Because an interaction existed between treatment and the primary outcome according to pre-specified quartiles of NT-proBNP at randomization, we examined this further. MethodsThis study evaluated the NT-proBNP relationship with the primary outcome in 4,805 of 5,050 patients as a risk-adjusted, log-transformed continuous variable. Hazard ratios (HRs) and 95% confidence intervals (CIs) are presented. ResultsMedian NT-proBNP was 2,816 pg/ml (25th to 75th percentile: 1,556 to 5,314 pg/ml). The study treatment effect varied across the spectrum of NT-proBNP at randomization (with log2 transformation, p for interaction = 0.002). A significant association between treatment effects existed in patients with levels <4,000 pg/ml and remained evident up to 8,000 pg/ml. A 23% relative risk reduction occurred in the primary endpoint with NT-proBNP ≤4,000 pg/ml (HR: 0.77; 95% CI: 0.68 to 0.88). For NT-proBNP values ≤4,000 pg/ml (n = 3,100), the HR was 0.78 (95% CI: 0.67 to 0.90) for HFH and 0.75 (95% CI: 0.60 to 0.94) for CVD. For NT-proBNP ≤8,000 pg/ml (n = 4,133), the HR was 0.85 (95% CI: 0.76 to 0.95) for the primary outcome, 0.84 (95% CI: 0.75 to 0.95) for HFH, and 0.84 (95% CI: 0.71 to 0.99) for CVD. For NT-proBNP >8,000 pg/ml (n = 672), the HR was 1.16 (95% CI: 0.94 to 1.41) for the primary outcome. ConclusionsA reduction in the primary composite endpoint and its CVD and HFH components was observed in patients on vericiguat compared with subjects on placebo with NT-proBNP levels up to 8,000 pg/ml. This provided new insight into the benefit observed in high-risk patients with worsening HFrEF. (A Study of Vericiguat in Participants With Heart Failure With Reduced Ejection Fraction [HFrEF] [MK-1242-001] [VICTORIA]; NCT02861534)