Metabolomics Approach for Validation of Self-Reported Ibuprofen and Acetaminophen Use

Cocktails of NSAIDs and 17α Ethinylestradiol at Environmentally Relevant Doses in Drinking Water Alter Puberty Onset in Mice Intergenerationally

Non-steroidal anti-inflammatory drugs (NSAIDs) and 17α-ethinyl-estradiol (EE2) are among the most relevant endocrine-disrupting pharmaceuticals found in the environment, particularly in surface and drinking water due to their incomplete removal via wastewater treatment plants. Exposure of pregnant mice to NSAID therapeutic doses during the sex determination period has a negative impact on gonadal development and fertility in adults; however, the effects of their chronic exposure at lower doses are unknown. In this study, we investigated the impact of chronic exposure to a mixture containing ibuprofen, 2hydroxy-ibuprofen, diclofenac, and EE2 at two environmentally relevant doses (added to the drinking water from fetal life until puberty) on the reproductive tract in F1 exposed mice and their F2 offspring. In F1 animals, exposure delayed male puberty and accelerated female puberty. In post-pubertal F1 testes and ovaries, differentiation/maturation of the different gonad cell types was altered, and some of these modifications were observed also in the non-exposed F2 generation. Transcriptomic analysis of post-pubertal testes and ovaries of F1 (exposed) and F2 animals revealed significant changes in gene expression profiles and enriched pathways, particularly the inflammasome, metabolism and extracellular matrix pathways, compared with controls (non-exposed). This suggested that exposure to these drug cocktails has an intergenerational impact. The identified Adverse Outcome Pathway (AOP) networks for NSAIDs and EE2, at doses that are relevant to everyday human exposure, will improve the AOP network of the human reproductive system development concerning endocrine disruptor chemicals. It may serve to identify other putative endocrine disruptors for mammalian species based on the expression of biomarkers.

Validation of self-reported medication use applying untargeted mass spectrometry-based metabolomics techniques in the Rhineland study

AIMS

To assess the validity of self-reported continuous medication use with drug metabolites measured in plasma by using untargeted mass spectrometric techniques.

METHODS

In a population-based cohort in Bonn, Germany, we compared interview-based, self-reported medication intake with drug-specific metabolites measured in plasma (based on participants who completed their study visits between March 2016 and February 2020). Analyses were done stratified by sex and age (<65 years vs ≥65 years). Cohen's kappa (κ) statistics with 95% confidence intervals (CI) were calculated.

RESULTS

A total of 13 drugs used to treat hypertension, gout, diabetes, epilepsy and depression were analysed in a sample of 4386 individuals (mean age 55 years, 56.1% women). Eleven drugs showed almost perfect agreement (κ > 0.8), whereas sitagliptin and hydrochlorothiazide showed substantial (κ = 0.8, 95% CI 0.71-0.90) and moderate agreement (κ = 0.61, 95% CI 0.56-0.66), respectively. Frequency of use allowed sex- and age-stratified analyses for eight and nine drugs, respectively. For five drugs, concordance tended to be higher for women than for men. For most drugs, concordance was higher among individuals aged ≥65 years than among individuals aged <65 years, but these age-related differences were not statistically significant.

CONCLUSION

High concordance rates between self-reported drug use and metabolites measured in plasma suggest that self-reported drug use is reliable and accurate for assessing drug use.

Self-Reported Medication Use and Urinary Drug Metabolites in the German Chronic Kidney Disease (GCKD) Study

BACKGROUND

Polypharmacy is common among patients with CKD, but little is known about the urinary excretion of many drugs and their metabolites among patients with CKD.

METHODS

To evaluate self-reported medication use in relation to urine drug metabolite levels in a large cohort of patients with CKD, the German Chronic Kidney Disease study, we ascertained self-reported use of 158 substances and 41 medication groups, and coded active ingredients according to the Anatomical Therapeutic Chemical Classification System. We used a nontargeted mass spectrometry-based approach to quantify metabolites in urine; calculated specificity, sensitivity, and accuracy of medication use and corresponding metabolite measurements; and used multivariable regression models to evaluate associations and prescription patterns.

RESULTS

Among 4885 participants, there were 108 medication-drug metabolite pairs on the basis of reported medication use and 78 drug metabolites. Accuracy was excellent for measurements of 36 individual substances in which the unchanged drug was measured in urine (median, 98.5%; range, 61.1%-100%). For 66 pairs of substances and their related drug metabolites, median measurement-based specificity and sensitivity were 99.2% (range, 84.0%-100%) and 71.7% (range, 1.2%-100%), respectively. Commonly prescribed medications for hypertension and cardiovascular risk reduction-including angiotensin II receptor blockers, calcium channel blockers, and metoprolol-showed high sensitivity and specificity. Although self-reported use of prescribed analgesics (acetaminophen, ibuprofen) was <3% each, drug metabolite levels indicated higher usage (acetaminophen, 10%-26%; ibuprofen, 10%-18%).

CONCLUSIONS

This comprehensive screen of associations between urine drug metabolite levels and self-reported medication use supports the use of pharmacometabolomics to assess medication adherence and prescription patterns in persons with CKD, and indicates under-reported use of medications available over the counter, such as analgesics.

Bioactive antiinflammatory antibacterial hemostatic citrate-based dressing with macrophage polarization regulation for accelerating wound healing and hair follicle neogenesis

The efficient cutaneous wound healing accompanied with the enhanced skin appendage regeneration is still a challenge. The bacterial infection and excessive/prolonged inflammation inhibit wound healing process and result in the scar formation. Herein, we reported an anti-inflammatory polycitrate-polyethyleneimine-Ibuprofen (PCEI) and multifunctional PCEI-based F127-ε-polypeptide-alginic (FEA) dressing (FEA-PCEI) for accelerating wound healing and hair follicle neogenesis. PCEI showed the excellent anti-inflammation function through stimulating macrophage towards anti-inflammatory M2 subtype polarization. The FEA-PCEI dressing showed the temperature-response gelation, injectability, robust antibacterial activity, light-damage-resistant, homeostasis ability, and good cytocompatibility. The optimized dosage of FEA-PCEI dressing could significantly accelerate wound healing with anti-infection ability, reduce the scar formation, and promote the hair follicle neogenesis. This study provided a wound-repairing strategy through regulating the phenotype of immune cells by the designing bioactive multifunctional biomaterials.