Pharmacometabolomics-aided Pharmacogenomics in Autoimmune Disease

Κάτσιλα, Θεοδώρα; Konstantinou, Evangelia; Lavda, Ioanna; Malakis, Harilaos; Papantoni, Ioanna; Skondra, Lamprini; Patrinos, George P.

doi:10.1016/j.ebiom.2016.02.001

Cited by 25 publications

(21 citation statements)

References 72 publications

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“…Fourth, handling the massive data comprising the interplay of genomic and environmental influences (diet, lifestyle, polypharmacy, toxins, gut microbiome) forms a data‐intensive and complex context that offers intervention opportunities, but also presents challenges that must be addressed in the near future. In the current era of big data, a major challenge is that of data exchange in merging high‐throughput data sets coming to and from diverse architectural platforms and the integration of health information technology (IT) interoperable tools to generate and/or test hypotheses with regard to disease heterogeneity or mechanisms for variation in drug response …”

Section: Discussionmentioning

confidence: 99%

“…Pharmacogenomics by itself does not study the environmental influences on drug metabolism nor the role of the microbiome on pharmacokinetics (absorption, distribution, metabolism, excretion) and/or pharmacodynamics. Despite the successes, clinical pharmacogenomics still needs more validated actionable genomic data that will inform diagnosis, prognosis, or treatment . In the era of precision medicine, more rigorously designed clinical research considering these physiologic and environmental factors is needed to demonstrate pharmacodynamic causal associations within standardized architectures for genomic variants …”

Section: Gut‐liver Microbiome Role In Drug Metabolism and Toxicitymentioning

confidence: 99%

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Omics for Understanding the Gut‐Liver‐Microbiome Axis and Precision Medicine

Khalsa

Duffy

Riscuta

et al. 2017

Clinical Pharm in Drug Dev

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Human metabolic disease opens a new view to understanding the contribution of the intestinal microbiome to drug metabolism and drug-induced toxicity in gut-liver function. The gut microbiome, a key determinant of intestinal inflammation, also plays a direct role in chronic inflammation and liver disease. Gut bacterial communities directly metabolize certain drugs, reducing their bioavailability and influencing individual variation in drug response. In addition, some microbiome-produced compounds may affect drug pharmacokinetics and pharmacodynamics via altered expression of metabolizing enzymes and drug transporters or genes coding for drug target proteins, drug response phenotypes, and disease states. Molecular-based high-throughput technologies are providing novel insight about host-gut microbiome interactions, homeostasis, and xenobiotic effects associated with wide variation in efficacy or toxicity in humans. It is envisioned that future approaches to treating and preventing liver disease will benefit from in-depth studies of the liver-microbiome axis. Thus, the microbiome shares a fundamental role in human physiology with various organ systems, and its importance must be considered in the rapid evolution of precision medicine. A new emerging perspective of understanding the effect of the gut microbiome on human response to drugs would be indispensable for developing efficacious, safe, and cost-effective precision therapies.

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Section: Discussionmentioning

confidence: 99%

Section: Gut‐liver Microbiome Role In Drug Metabolism and Toxicitymentioning

confidence: 99%

Omics for Understanding the Gut‐Liver‐Microbiome Axis and Precision Medicine

Khalsa

Duffy

Riscuta

et al. 2017

Clinical Pharm in Drug Dev

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“…Recently, we have outlined the paradigm of pharmacometabolomics-aided pharmacogenomics in autoimmune diseases to address the interplay of genomic and environmental influences with information technologies to facilitate data analysis as well as sense- and decision-making on the basis of synergy between artificial and human intelligence. We propose that better-informed, rapid, and cost-effective “omics” studies need the implementation of holistic and multidisciplinary approaches [31]. …”

Section: Discussionmentioning

confidence: 99%

Novel genetic risk variants for pediatric celiac disease

et al. 2016

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BackgroundCeliac disease is a complex chronic immune-mediated disorder of the small intestine. Today, the pathobiology of the disease is unclear, perplexing differential diagnosis, patient stratification, and decision-making in the clinic.MethodsHerein, we adopted a next-generation sequencing approach in a celiac disease trio of Greek descent to identify all genomic variants with the potential of celiac disease predisposition.ResultsAnalysis revealed six genomic variants of prime interest: SLC9A4 c.1919G>A, KIAA1109 c.2933T>C and c.4268_4269delCCinsTA, HoxB6 c.668C>A, HoxD12 c.418G>A, and NCK2 c.745_746delAAinsG, from which NCK2 c.745_746delAAinsG is novel. Data validation in pediatric celiac disease patients of Greek (n = 109) and Serbian (n = 73) descent and their healthy counterparts (n = 111 and n = 32, respectively) indicated that HoxD12 c.418G>A is more prevalent in celiac disease patients in the Serbian population (P < 0.01), while NCK2 c.745_746delAAinsG is less prevalent in celiac disease patients rather than healthy individuals of Greek descent (P = 0.03). SLC9A4 c.1919G>A and KIAA1109 c.2933T>C and c.4268_4269delCCinsTA were more abundant in patients; nevertheless, they failed to show statistical significance.ConclusionsThe next-generation sequencing-based family genomics approach described herein may serve as a paradigm towards the identification of novel functional variants with the aim of understanding complex disease pathobiology.Electronic supplementary materialThe online version of this article (doi:10.1186/s40246-016-0091-1) contains supplementary material, which is available to authorized users.

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“…Recently, a new concept has arisen, namely “pharmacometabolomics-aided pharmacogenomics,” to reinforce the identification and validation of clinically relevant associations (Ji et al, 2011; Suhre et al, 2011; Abo et al, 2012). We have recently proposed that pharmacometabolomics-aided pharmacogenomics may have an even greater impact if coupled to information technologies to facilitate data analysis and sense- and decision-making on the basis of a synergy between artificial and human intelligence (Katsila et al, 2016). …”

Section: “Which Entities Are Predictive Of Response To/toxicity Of Xementioning

confidence: 99%

Pharmacometabolomics Informs Viromics toward Precision Medicine

Balasopoulou¹,

Patrinos²,

Κάτσιλα³

2016

Front. Pharmacol.

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Nowadays, we are experiencing the big data era with the emerging challenge of single data interpretation. Although the advent of high-throughput technologies as well as chemo- and bio-informatics tools presents pan-omics data as the way forward to precision medicine, personalized health care and tailored-made therapeutics can be only envisaged when interindividual variability in response to/toxicity of xenobiotics can be interpreted and thus, predicted. We know that such variability is the net outcome of genetics (host and microbiota) and environmental factors (diet, lifestyle, polypharmacy, and microbiota) and for this, tremendous efforts have been made to clarify key-molecules from correlation to causality to clinical significance. Herein, we focus on the host–microbiome interplay and its direct and indirect impact on efficacy and toxicity of xenobiotics and we inevitably wonder about the role of viruses, as the least acknowledged ones. We present the emerging discipline of pharmacometabolomics-informed viromics, in which pre-dose metabotypes can assist modeling and prediction of interindividual response to/toxicity of xenobiotics. Such features, either alone or in combination with host genetics, can power biomarker discovery so long as the features are variable among patients, stable enough to be of predictive value, and better than pre-existing tools for predicting therapeutic efficacy/toxicity.

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Pharmacometabolomics-aided Pharmacogenomics in Autoimmune Disease

Cited by 25 publications

References 72 publications

Omics for Understanding the Gut‐Liver‐Microbiome Axis and Precision Medicine

Omics for Understanding the Gut‐Liver‐Microbiome Axis and Precision Medicine

Novel genetic risk variants for pediatric celiac disease

Pharmacometabolomics Informs Viromics toward Precision Medicine

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