Novel Insights into the Effects of Genetic Variants on Serum Urate Response to an Acute Fructose Challenge: A Pilot Study

Studies have shown that genetic variations can influence metabolic response to nutrient intake, and that diets rich in fructose contribute to hyperuricemia. In this pilot study, our aim was to determine the variability of serum urate in response to an acute fructose challenge and to investigate if genetic variants would affect this response in young to middle-aged adults who self-reported as Black or White. Fifty-seven participants consumed a fructose-rich beverage after an overnight fast. Blood was drawn at five time points (baseline, 30, 60, 120, and 180 min after consumption). Thirty urate-related single nucleotide polymorphisms (SNPs) were analyzed for their associations with baseline serum urate and its percent changes, using a two-step modeling approach followed by meta-analysis. At baseline, serum urate (mg/dL, mean ± SD) was higher in Whites (5.60 ± 1.01 vs. 5.37 ± 0.96), men (6.17 ± 1.14 vs. 5.24 ± 0.79), and those with obesity (5.69 ± 1.08 vs. 5.42 ± 1.06 vs. 5.34 ± 0.80). Three SNPs were significantly associated with baseline serum urate or its percent changes, and six SNPs were nominally associated with percent changes in serum urate. In summary, our results showed that genetic variants could play a role in short-term urate metabolism.

Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

BACKGROUND

The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system.

METHODS

In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings.

RESULTS

Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host.

CONCLUSIONS

Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.

Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

BACKGROUND

The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system.

METHODS

In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings.

RESULTS

Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host.

CONCLUSIONS

Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.

Variation of Serum Lycopene in Response to 100% Watermelon Juice: An Exploratory Analysis of Genetic Variants in a Randomized Controlled Crossover Study

BACKGROUND

Watermelon, a rich source of lycopene, has garnered attention for cardioprotective effects including cholesterol reduction and promotion of redox balance. It is unknown whether 100% watermelon juice may represent a food-first approach to confer cardioprotective benefits of lycopene.

OBJECTIVES

This study examined influences of 100% watermelon juice on serum lycopene, lipids, and antioxidant capacity. Secondly, the study explored genetic influences on lycopene metabolism and bioavailability.

METHODS

A placebo-controlled, randomized, double-blind, crossover trial with postmenopausal women (n = 16, mean ± SD age: 60 ± 4.1 y) assessed effects of 100% watermelon juice on mechanistic and clinical outcomes influencing vascular function. Participants maintained low-lycopene diets for a 1-wk run-in period and throughout the study. Morning and evening consumption of 100% watermelon juice provided a daily dose of 14.4 ± 0.34 mg lycopene. Study arms of 4 wk were separated by a 2-wk washout period. Saliva was collected for genetic analysis of single nucleotide polymorphisms, and fasting blood samples were taken pre- and post-study arms. Statistical analyses included mixed models, linear regression, and nonparametric tests.

RESULTS

Serum lycopene exhibited a significant treatment effect (P = 0.002) along with notable interindividual responses; however, significant improvements in serum lipids or antioxidant capacity were not observed. Genetic variant rs6564851 in the β-carotene 15,15'-oxygenase-1 (BCO1) gene was associated with changes in lycopene such that TT homozygotes exhibited a significantly greater increase (β ± SE: 13.4 ± 1.6, P = 1.4 × 10-06).

CONCLUSIONS

Watermelon juice supplementation did not result in improvements in serum lipids or antioxidant capacity; however, results support findings in which watermelon juice significantly, yet differentially, increased circulating lycopene. Genetics appears to explain some of the variability. Given that dose has been shown to overcome individual responsiveness to lycopene interventions, future investigations with varying doses of lycopene-rich foods would be strengthened by genotyping so as to establish personalized nutrition recommendations.This trial was registered at clinicaltrials.gov as NCT03626168.

Identification of single nucleotide pleomorphisms associated with periodontal disease in head and neck cancer irradiation patients by exome sequencing

OBJECTIVE

Periodontal disease (PD) is a common oral complication in patients with head and neck cancer (HNC) undergoing radiation therapy (RT). Our objective was to identify candidate single nucleotide polymorphisms (SNPs) associated with PD in radiation-treated patients with HNC.

STUDY DESIGN

DNA was extracted from the saliva of patients with HNC (n = 69) before RT. Clinical attachment loss (CAL) increment greater than 0.2 mm over 24 months after RT was used to define PD progression. After exome sequencing, SNPs associated with post-RT PD progression were identified by using logistic regression and homozygosity analyses. The web tools STRING, the Database for Annotation, Visualization and Integrated Discovery (DAVID), GeneCodis, and Ensembl Variant Effect Predictor were used for functional analysis.

RESULTS

Of the 48 patients with HNC with post-RT PD progression, 24 had no tooth with 5 mm or greater pocket depth before RT, whereas of the 21 patients with HNC without progression, 11 had PD initially. A total of 330 SNPs (249 genes) with over-represented homozygous genotype (98.5% variant allele) were found to be associated with post-RT PD. Sixty of these corresponded to PD-related pathways, including previously identified genes. In patients with HNC with post-RT PD progression, SNPs were found in genes (n = 10) in contrast to those without progression (n = 7).

CONCLUSIONS

The SNPs of collagen genes were identified, potentially defining susceptibility to PD in patients with HNC, and this could be further investigated to characterize PD drug targets.