The Role Of The Human Microbiome In Stratified Medicine And Pharmacogenetics

Pharmacogenetics has the capability of having a key role in the delivery of personalised medicine based on the genotypic and/or phenotypic data of a patient. However, there are substantial differences in the pharmacokinetics of therapeutics that, in some cases, may be due to the microbiome instead of solely on the human genome. Pharmacomicrobiomics has the potential to deliver patient-tailored therapeutics that will maximise the efficacy of a drug and minimise its toxicity by identifying bacterial communities and metabolites. It has become quite evident that drug inactivation is linked to microbiome constituents. Therefore, understanding the interaction between drugs and commensal bacteria will allow strains to become biomarkers to predict response or even manipulated to ameliorate therapeutic outcomes.

The gut microbiome is known to influence the metabolism of xenobiotics, therefore, having a significant impact on both the side effects and efficacy of these pharmaceuticals. Drug bioavailability is influenced by the totality of first-pass metabolism from dietary enzymes. Preceding host tissue interaction, it is theorised that xenobiotics potentially interact with the gut microbiota. This would facilitate the gut flora to have a key role in first pass metabolism as seen (Figure 1). Various research elucidates that two pathways are utilised during gut microbial metabolism of drugs: hydrolysis and reduction (Selma, Espín & Tomás-Barberán, 2009)(Bowey, Adlercreutz & Rowland, 2003). [image: ]Figure 1: Different drug metabolism modalities between xenobiotics and gut microbiota. The gut microbiome can involve dietary complexes alongside liver and intestinal enzymes in this process (Saad, Rizkallah & Aziz, 2012). Reductive metabolism can promote anaerobic respiration while hydrolysis sustains the provision of substrates available for microbial growth (Haiser and Turnbaugh, 2013). Based on this ideology, it is implied that a vast array of small molecules are impacted by particular microbial species along the gut (Figure 1). The identification of these species could be fundamental to predicting the modifications of xenobiotics by the gut microbiome.

Gut bacteria can produce β-glucuronidases that are known to be capable of re-activating drugs resulting in higher toxicity. Irinotecan is commonly used in the treatment of colorectal cancer (CRC) (Mani, Boelsterli & Redinbo, 2014). Post-intricate metabolic transformation into its bioactive form SN-38, it is glucuronidated by hepatic enzymes into an inactive form SN-38G. β-glucuronidases produced by microbes in the biliary tree can cleave the sugar moiety form SN-38G producing SN-38. Consequentially, the increased toxicity directed at intestinal epithelial cells is proposed to intensify diarrhea for CRC patients. Similarly, non-steroidal anti-inflammatory drugs are affected by β-glucuronidases with metabolites converted into an active form resulting in inflammation and loss of integrity of mucosal surfaces (Stein, Voigt & Jordan, 2009). These examples give evidence towards the potentiality for a microbial role in drug metabolism. Microbiome-based diagnostic biomarkers could be developed to be predictive of optimal drug dosage in relation to individual microbiomes. Although clinical, genetic and phenotypic traits are major factors for pharmacokinetics, it does not fully justify the dosage variability between patients (Boughton et al. , 2013). Tacrolimus is a calcineurin inhibitor utilised as an immunosuppressant with a proportion of its recipients requiring an increased dosage (Lee et al. , 2015). Research has suggested that the bacterium Faecalibacterium prausnitzii is a positive indicator for tacrolimus dosage.

Lee et al. demonstrated that kidney transplant recipients with abundant F. prausnitzii required higher doses of tacrolimus. A recent study has elucidated that F. prausnitzii could hypothetically convert tacrolimus into a less potent form in the gut, resulting in low tacrolimus bioavailability (Guo et al. , 2018). Similar to tacrolimus metabolism, digoxin can be reduced at different rates depending on the strain of Eggerthella lenta present. Research has shown that strains with the cgr operon could encode proteins that inactivate the drug (Haiser et al. , 2014). Theoretically, drugs could be designed to block cgr operon binding sites, sustaining the bioavailability of digoxin (Kumar et al. , 2018). Hence, microbiome screening could have a role in personalised medicine by predicting a response due to gut flora. Potentially, microbiomes could be targeted or altered in a manner that would be clinically beneficial to the patient. The relationship between pharmacology and the microbiome has gained increasing appreciation and is facilitating the move towards a more microbiome-based medicine. Growth in this area of study may lead to the ability to alter human gut microbiomes and predict individual drug response by screening genetic or metabolite profiles of gut flora. While in its infancy, it could be possible to establish inhibitors of microbial enzymes that would circumvent undesirable biotransformations of xenobiotics. Studies have shown that a highly conserved ‘bacterial loop’ exists amongst gut microbiota enzymes (Wallace et al. , 2010).

However, one limitation towards this approach is that the loop is not universal to every bacterial glucuronidase (Wallace et al. , 2015). One approach to fully understand microbiome mechanisms is a biobank. Initiatives such as LifeLines DAG3 and LifeLines NEXT cohort are currently studying population groups through their gut microbiota, genotypes, phenotypes and medications (Doestzada et al. , 2018). These information databases will offer the potential to systematically research distinct drug metabolism variability alongside microbial factors. It is hoped that studying these microbiomes will highlight causation instead of association with drug metabolism variations. The microbiome is emerging as a significant component of inevitable personalised medicine. Further research will facilitate clinicians to hybridise personal microbiomes and genotypes to predict therapeutic response and modify microbiomes to improve drug efficacy for each patient. However, due to the enormous diversity of the microbiome, individualised testing protocols and biobanks need to be established. Overcoming these current limitations will bring a new level to stratified medicine.