Pharmacometabolomics Informs Viromics toward Precision Medicine

Drug-microbiota interactions: an emerging priority for precision medicine

Individual variability in drug response (IVDR) can be a major cause of adverse drug reactions (ADRs) and prolonged therapy, resulting in a substantial health and economic burden. Despite extensive research in pharmacogenomics regarding the impact of individual genetic background on pharmacokinetics (PK) and pharmacodynamics (PD), genetic diversity explains only a limited proportion of IVDR. The role of gut microbiota, also known as the second genome, and its metabolites in modulating therapeutic outcomes in human diseases have been highlighted by recent studies. Consequently, the burgeoning field of pharmacomicrobiomics aims to explore the correlation between microbiota variation and IVDR or ADRs. This review presents an up-to-date overview of the intricate interactions between gut microbiota and classical therapeutic agents for human systemic diseases, including cancer, cardiovascular diseases (CVDs), endocrine diseases, and others. We summarise how microbiota, directly and indirectly, modify the absorption, distribution, metabolism, and excretion (ADME) of drugs. Conversely, drugs can also modulate the composition and function of gut microbiota, leading to changes in microbial metabolism and immune response. We also discuss the practical challenges, strategies, and opportunities in this field, emphasizing the critical need to develop an innovative approach to multi-omics, integrate various data types, including human and microbiota genomic data, as well as translate lab data into clinical practice. To sum up, pharmacomicrobiomics represents a promising avenue to address IVDR and improve patient outcomes, and further research in this field is imperative to unlock its full potential for precision medicine.

The Potential Use of Antibiotics Against Helicobacter pylori Infection: Biopharmaceutical Implications

Helicobacter pylori (H. pylori) is a notorious, recalcitrant and silent germ, which can cause a variety of debilitating stomach diseases, including gastric and duodenal ulcers and gastric cancer. This microbe predominantly colonizes the mucosal layer of the human stomach and survives in the inhospitable gastric microenvironment, by adapting to this hostile milieu. In this review, we first discuss H. pylori colonization and invasion. Thereafter, we provide a survey of current curative options based on polypharmacy, looking at pharmacokinetics, pharmacodynamics and pharmaceutical microbiology concepts, in the battle against H. pylori infection.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Pharmacomicrobiomics informs clinical pharmacogenomics

Aim: Microbiota-host-xenobiotics interactions in humans become of prime interest when clinical pharmacogenomics is to be implemented. Despite the advent of technology, information still needs to be translated into knowledge for optimum patient stratification and disease management. Material & methods: Herein, we mined metagenomic, pharmacometagenomic and pharmacomicrobiomic datasets to map microbiota-host-drugs networks. Results: Datasets were multifaceted and voluminous. Interoperability, data sparsity and scarcity remain a challenge. Mapping microbiota-host-drugs networks allowed the prediction of drug response/toxicity and modulation of the microbiota-host-drugs interplay. Conclusion: Our approach triangulated microbiota, host and drug networks revealing the need for contextual data and open science via microattribution to accelerate knowledge growth. Our findings may serve as a data storehouse for a user-friendly query system, coupled with databanks and databases.

Copy number variation profiling in pharmacogenetics CYP-450 and GST genes in Colombian population

BACKGROUND

Copy Number variation (CNVs) in genes related to drug absorption, distribution, metabolism and excretion (ADME) are relevant in the interindividual variability of drug response. Studies of the CNVs in ADME genes in Latin America population are lacking. The objective of the study was to identify the genetic variability of CNVs in CYP-450 and GST genes in a subgroup of individuals of Colombian origin.

METHODS

Genomic DNA was isolated from 123 healthy individuals from a Colombian population. Multiplex Ligation-Dependent Probe Amplification (MLPA) was performed for the identification of CNVs in 40 genomic regions of 11 CYP-450 and 3 GST genes. The genetic variability, allelic and genotypic frequencies were analyzed.

RESULTS

We found that 13 out of 14 genes had CNVs: 5 (35.7%) exhibited deletions and duplications, while 8 (57.1%) presented either deletions or duplications.. 33.3% of individuals carried deletions and duplications while 49.6% had a unique type of CNV (deletion or duplication). The allelic frequencies of the CYP and GST genes were 0 to 47.6% (allele null), 0 to 17.5% (duplicated alleles) and 37 to 100% (normal alleles).

CONCLUSIONS

Our results describe, for the first time, the genomic profile of CNVs in a subgroup of Colombian population in GST and CYP-450 genes. GST genes indicated greater genetic variability than CYP-450 genes. The data obtained contributes to the knowledge of genetic profiles in Latin American subgroups. Although the clinical relevance of CNVs has not been fully established, it is a valuable source of pharmacogenetic variability data with potential involvement in the response to medications.

Integrating Next-Generation Sequencing in the Clinical Pharmacogenomics Workflow

Pharmacogenomics has been recognized as a fundamental tool in the era of personalized medicine with up to 266 drug labels, approved by major regulatory bodies, currently containing pharmacogenomics information. Next-generation sequencing analysis assumes a critical role in personalized medicine, providing a comprehensive profile of an individual's variome, particularly that of clinical relevance, comprising of pathogenic variants and pharmacogenomic biomarkers. Here, we propose a strategy to integrate next-generation sequencing into the current clinical pharmacogenomics workflow from deep resequencing to pharmacogenomics consultation, according to the existing guidelines and recommendations.

Retracted Article: A high-throughput metabolomics strategy for discovering the influence of differential metabolites and metabolic pathways of huaxian capsules on sepsis-associated Qi deficiency and blood stasis syndrome

High-throughput metabolomics can be used to investigate the therapeutic targets and metabolic mechanisms of traditional Chinese medicine formulae.

Pharmacometabolomics Informs Quantitative Radiomics for Glioblastoma Diagnostic Innovation

Applications of omics systems biology technologies have enormous promise for radiology and diagnostics in surgical fields. In this context, the emerging fields of radiomics (a systems scale approach to radiology using a host of technologies, including omics) and pharmacometabolomics (use of metabolomics for patient and disease stratification and guiding precision medicine) offer much synergy for diagnostic innovation in surgery, particularly in neurosurgery. This synthesis of omics fields and applications is timely because diagnostic accuracy in central nervous system tumors still challenges decision-making. Considering the vast heterogeneity in brain tumors, disease phenotypes, and interindividual variability in surgical and chemotherapy outcomes, we believe that diagnostic accuracy can be markedly improved by quantitative radiomics coupled to pharmacometabolomics and related health information technologies while optimizing economic costs of traditional diagnostics. In this expert review, we present an innovation analysis on a systems-level multi-omics approach toward diagnostic accuracy in central nervous system tumors. For this, we suggest that glioblastomas serve as a useful application paradigm. We performed a literature search on PubMed for articles published in English between 2006 and 2016. We used the search terms "radiomics," "glioblastoma," "biomarkers," "pharmacogenomics," "pharmacometabolomics," "pharmacometabonomics/pharmacometabolomics," "collaborative informatics," and "precision medicine." A list of the top 4 insights we derived from this literature analysis is presented in this study. For example, we found that (i) tumor grading needs to be better refined, (ii) diagnostic precision should be improved, (iii) standardization in radiomics is lacking, and (iv) quantitative radiomics needs to prove clinical implementation. We conclude with an interdisciplinary call to the metabolomics, pharmacy/pharmacology, radiology, and surgery communities that pharmacometabolomics coupled to information technologies (chemoinformatics tools, databases, collaborative systems) can inform quantitative radiomics, thus translating Big Data and information growth to knowledge growth, rational drug development and diagnostics innovation for glioblastomas, and possibly in other brain tumors.

Key Pharmacogenomic Considerations for Sickle Cell Disease Patients

Sickle cell disease (SCD), although a monogenic disease, exhibits a complex clinical phenotype that hampers optimum patient stratification and disease management, especially on hydroxyurea treatment. Moreover, theranostics, the combination of diagnostics to individualize and optimize therapeutic interventions, has not been firmly on the forefront of SCD research and clinical management to date. We suggest that if tailor-made theranostics in SCD is envisaged, pharmacogenomics is anticipated to be the way forward. Herein, we present the current key pharmacogenomic opportunities and challenges in SCD, considering population variation, ethics, and socioeconomic aspects. We focus on pharmacogenomics and pain management, genethics, and cost-effectiveness in SCD. We searched for and synthesized data from PubMed and Google Scholar, and the references from relevant articles, using the keywords "pharmacogenomics," "sickle cell disease," "hydroxyurea," "ethics," "pain management," "morphine metabolism," "opioids," "pharmacogenomics and chronic pain," "cost-effectiveness," and "economic evaluation." Only articles published in English were included. So far, when pharmacogenomics in SCD has been considered, interindividual variability in hydroxyurea response/toxicity has been of primary interest. We underscore the need to extend pharmacogenomic considerations on other therapeutic interventions currently present using a holistic patient-centric approach, and taking disease complications into account as well. Furthermore, we raise awareness toward socioeconomic, ethical, and population differences in the way sickle cell pharmacogenomics might unfold in the future. If pharmacogenomics in SCD is to be used in the clinic in an evidence-based manner, cost-effectiveness and population-specific empirical ethics data are urgently needed.