Biology subjects

Grosser, T.

Publications and source records attributed to Grosser, T..

5 recordsLinked to original sources

bioRxiv2024

Metabolomic Response to Non-Steroidal Anti-Inflammatory Drugs

Non-steroidal anti-inflammatory drugs (NSAIDs) are popular choices for the mitigation of pain and inflammation; however, they are accompanied by side effects in the gastrointestinal and cardiovascular systems. We compared the effects of naproxen, a traditional NSAID, and celecoxib, a cyclooxygenase -2 (Cox-2) inhibitor, in humans. Our findings showed a decrease in tryptophan and kynurenine levels in plasma of volunteers treated with naproxen. We further validated this result in mice. Additionally, we find that the depression of tryptophan was independent of both Cox-1 and Cox-2 inhibition, but rather was due to the displacement of bound tryptophan by naproxen. Supplementation of tryptophan in naproxen-treated mice rescued fecal blood loss and inflammatory gene expression driven by IL-1{beta} in the heart.

systems biology↗

bioRxiv2020

Myeloid cell mPGES-1 mediates inflammatory pain hypersensitivity in mice.

Nonsteroidal anti-inflammatory drugs (NSAIDs) relieve inflammatory pain by predominant suppression of cyclooxygenase-2 derived prostaglandin (PG) E2. Innate immune cells contribute to inflammatory pain hypersensitivity and may be an attractive target for novel non-addictive approaches to pain management. We studied the contribution of PGE2 produced by myeloid cell microsomal prostaglandin E synthase -1 (mPGES-1) to peripheral inflammation and hyperalgesia in mice. Selective deletion of mPGES-1 in myeloid cells by crossing LysM-Cre mice with mPGES-1flox/flox mice (Mac-mPGES-1-KO) resulted in significantly reduced mechanical and thermal hyperalgesia in complete Freunds adjuvant (CFA)-evoked hind paw inflammation, zymosan-induced peri-articular inflammation and collagen II antibody-induced arthritis models. Systemic COX-2 inhibition or myeloid cell specific COX-2 deletion (by crossing LysM-Cre with COX-2 flox/flox mice) recapitulated reduction of CFA-induced inflammation and hyperalgesia. In contrast, deletion of mPGES-1 in neurons and glial cells by crossing mPGES-1flox/flox mice with Nestin-Cre mice had no detectable effect on inflammatory pain hypersensitivity. While macrophage recruitment was unaltered, tissue concentrations of PGE2, IL-1{beta} and TNF were significantly reduced in Mac-mPGES-1-KO paw tissues following CFA induction. Our results demonstrate that myeloid cell mPGES-1 is the dominant source of PGE2 in inflammatory pain hypersensitivity. Targeting myeloid cell mPGES-1 may afford a novel approach to inflammatory pain therapy.

pharmacology and toxicology↗

bioRxiv2018

Variability in the Analgesic Response to Ibuprofen Following Third-Molar Extraction is Associated with Differences in Activation of the Cyclooxygenase Pathway

The analgesic efficacy of non-steroidal anti-inflammatory drugs (NSAIDs) has long been recognized to be limited by substantial interindividual variability in pain relief, but the underlying mechanisms are not well understood. We performed pain phenotyping, functional neuroimaging, pharmacokinetic/pharmacodynamic assessments, inflammation biomarkers, and gene expression profiling in healthy subjects who underwent surgical extraction of bony impacted third molars, in order to characterize factors associated with heterogeneity in response to ibuprofen.\n\nSubjects were treated with rapid-acting ibuprofen (400 mg; N=19) or placebo (N=10) in a randomized, double-blind design. Compared to placebo, ibuprofen-treated subjects exhibited greater reduction in pain scores, alterations in regional cerebral blood flow in brain regions associated with pain processing, and inhibition of ex vivo cyclooxygenase activity and urinary prostaglandin metabolite excretion as indices of biochemical drug action (p<0.05). As expected, ibuprofen-treated subjects could be stratified into partial responders (N=9, required rescue medication within the dosing interval) and complete responders (N=10, no rescue medication). This was also reflected by differences in pain scores (p<0.01) as early as 30 minutes following drug administration (p<0.05). Variability in analgesic efficacy was not associated with demographic or clinical characteristics, ibuprofen pharmacokinetics, metabolizing enzyme genotype, or the degree of cyclooxygenase inhibition by ibuprofen. However, complete responders had higher concentrations of inflammatory biomarkers in urine and serum, than partial responders. Specifically, a stable urinary prostaglandin E2 metabolite, serum TNF and IL-8 were higher in patients who did not require rescue medication compared those who did (p < 0.05). RNAseq gene expression analysis in PBMCs collected after surgery and ibuprofen administration showed enrichment of inflammation related pathways among genes differentially expressed (q < 0.2) between complete and partial responders\n\nThese findings suggest that patients who receive substantial pain relief from ibuprofen have a more pronounced activation of the prostanoid biosynthetic pathway and regulation of the inflammatory pain phenotype differs from those patients who are insufficiently treated with ibuprofen alone and may require an opioid or other therapeutic intervention.

genomics↗

bioRxiv2018

Distinct vascular genomic response of proton and gamma radiation.

Purpose. The cardiovascular biology of proton radiotherapy is not well understood. We aimed to compare the genomic dose-response to proton and gamma radiation of the mouse aorta to assess whether their vascular effects may diverge.\n\nMaterials and methods. We performed comparative RNA sequencing of the aorta following (4 hrs) total-body proton and gamma irradiation (0.5 - 200 cGy whole body dose, 10 dose levels) of conscious mice. A trend analysis identified genes that showed a dose response.\n\nResults. While fewer genes were dose-responsive to proton than gamma radiation (29 vs. 194 genes; q-value [≤] 0.1), the magnitude of the effect was greater. Highly responsive genes were enriched for radiation response pathways (DNA damage, apoptosis, cellular stress and inflammation; p-value [≤] 0.01). Gamma, but not proton radiation induced additionally genes in vasculature specific pathways. Genes responsive to both radiation types showed almost perfectly superimposable dose-response relationships.\n\nConclusions. Despite the activation of canonical radiation response pathways by both radiation types, we detected marked differences in the genomic response of the murine aorta. Models of cardiovascular risk based on photon radiation may not accurately predict the risk associated with proton radiation.

systems biology↗

bioRxiv2018

Iso-relevance Functions - A Systematic Approach to Ranking Genomic Features by Differential Effect Size

It is common to measure large numbers of features to identify those differing between experimental conditions; for example using RNA-Seq to search for differentially expressed genes. Ranking by p-value allows for statistical control, but has well known issues: unreliability without many replicates; and significance of biologically irrelevant effect sizes. As a result prioritization is typically performed in conjunction with effect size; the canonical one being "fold-change" [Formula]. However fold-change has several issues: division by zero, sensitivity to small values in the denominator, insensitivity to magnitude (1 over 2 equals 100 over 200). To mitigate these problems adding 1 to all values is a widely used heuristic; which we show using real and simulated data is typically highly sub-optimal, while the value 20 is nearly optimal in all cases. From another point of view, adding a fixed "pseudocount" to all values is essentially re-defining effect size from fold-change to something else. To explore this further, we axiomatize the concept of effect size and use this mathematical framework to study the problem in general. We also present the remarkable finding that pseudocounts strike a balance between sorting by fold-change and sorting by difference. Therefore, optimization is equivalent to finding the most harmonious balance between these two extremes. Lastly, the framework is illustrated on a fundamentally different type of problem, that of ranking di-codons by their differential abundance in the ORFeome of different species, where p-values are unavailable and one must solve the problem directly with effect sizes.

bioinformatics↗