Pharmacogenomics: unlocking the human genome for better drug therapy

Pharmacogenomics of Old and New Immunosuppressive Drugs for Precision Medicine in Kidney Transplantation

Kidney transplantation is the preferred therapeutic option for end-stage kidney disease, but, despite major therapeutic advancements, allograft rejection continues to endanger graft survival. Every patient is unique due to his or her clinical history, drug metabolism, genetic background, and epigenetics. For this reason, examples of "personalized medicine" and "precision medicine" have steadily increased in recent decades. The final target of precision medicine is to maximize drug efficacy and minimize toxicity for each individual patient. Immunosuppressive drugs, in the setting of kidney transplantation, require a precise dosage to avoid either adverse events (overdosage) or a lack of efficacy (underdosage). In this review, we will explore the knowledge regarding the pharmacogenomics of the main immunosuppressive medications currently utilized in kidney transplantation. We will focus on clinically relevant pharmacogenomic data, that is, the polymorphisms of the genes that metabolize immunosuppressive drugs.

Pharmacogenetics of Praziquantel Metabolism: Evaluating the Cytochrome P450 Genes of Zimbabwean Patients During a Schistosomiasis Treatment

Schistosomiasis is a parasitic disease infecting over 236 million people annually, with the majority affected residing on the African continent. Control of this disease is reliant on the drug praziquantel (PZQ), with treatment success dependent on an individual reaching PZQ concentrations lethal to schistosomes. Despite the complete reliance on PZQ to treat schistosomiasis in Africa, the characterization of the pharmacogenetics associated with PZQ metabolism in African populations has been sparse. We aimed to characterize genetic variation in the drug-metabolising cytochrome P450 enzymes (CYPs) and determine the association between each variant and the efficacy of PZQ treatment in Zimbabwean patients exposed to Schistosoma haematobium infection. Genomic DNA from blood samples of 114 case-control Zimbabweans infected with schistosomes were sequenced using the CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 genes as targets. Bioinformatic tools were used to identify and predict functional effects of detected single nucleotide polymorphisms (SNPs). A random forest (RF) model was then used to assess SNPs most predictive of PZQ efficacy, with a misclassification rate of 29%. SNPs were detected across all six genes, with 70 SNPs identified and multiple functional changes to the CYP enzymes predicted. Only four SNPs were significantly associated with PZQ efficacy using χ² tests, with rs951840747 (OR: 3.61, p = 0.01) in the CYP1A2 gene having the highest odds of an individual possessing this SNP clearing infection, and rs6976017 (OR: 2.19, p = 0.045) of CYP3A5 determined to be the most predictive of PZQ efficacy via the RF. Only the rs28371702 (CC) genotype (OR: 2.36, p = 0.024) of CYP2D6 was significantly associated with an unsuccessful PZQ treatment. This study adds to the genomic characterization of the diverse populations in Africa and identifies variants relevant to other pharmacogenetic studies crucial for the development and usage of drugs in these populations.

Polygenic risk, population structure and ongoing difficulties with race in human genetics

‘The Apportionment of Human Diversity’ stands as a noteworthy intervention, both for the field of human population genetics as well as in the annals of public communication of science. Despite the widespread uptake of Lewontin's conclusion that racial classification is of ‘virtually no genetic or taxonomic significance’, the biomedical research community continues to grapple with whether and how best to account for race in its work. Nowhere is this struggle more apparent than in the latest attempts to translate genetic associations with complex disease risk to clinical use in the form of polygenic risk scores, or PRS. In this perspective piece, we trace current challenges surrounding the appropriate development and clinical application of PRS in diverse patient cohorts to ongoing difficulties deciding which facets of population structure matter, and for what reasons, to human health. Despite numerous analytical innovations, there are reasons that emerge from Lewontin's work to remain sceptical that accounting for population structure in the context of polygenic risk estimation will allow us to more effectively identify and intervene on the significant health disparities which plague marginalized populations around the world.

This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

Pharmacogenomics: A Step forward Precision Medicine in Childhood Asthma

Personalized medicine, an approach to care in which individual characteristics are used for targeting interventions and maximizing health outcomes, is rapidly becoming a reality for many diseases. Childhood asthma is a heterogeneous disease and many children have uncontrolled symptoms. Therefore, an individualized approach is needed for improving asthma outcomes in children. The rapidly evolving fields of genomics and pharmacogenomics may provide a way to achieve asthma control and reduce future risks in children with asthma. In particular, pharmacogenomics can provide tools for identifying novel molecular mechanisms and biomarkers to guide treatment. Emergent high-throughput technologies, along with patient pheno-endotypization, will increase our knowledge of several molecular mechanisms involved in asthma pathophysiology and contribute to selecting and stratifying appropriate treatment for each patient.

Phase I Study of Zotiraciclib in Combination with Temozolomide for Patients with Recurrent High-grade Astrocytomas

PURPOSE

To investigate the toxicity profile and establish an optimal dosing schedule of zotiraciclib with temozolomide in patients with recurrent high-grade astrocytoma.

PATIENTS AND METHODS

This two-stage phase I trial determined the MTD of zotiraciclib combined with either dose-dense (Arm1) or metronomic (Arm2) temozolomide using a Bayesian Optimal Interval design; then a randomized cohort expansion compared the progression-free survival rate at 4 months (PFS4) of the two arms for an efficient determination of a temozolomide schedule to combine with zotiraciclib at MTD. Pharmacokinetic and pharmacogenomic profiling were included. Patient-reported outcome was evaluated by longitudinal symptom burden.

RESULTS

Fifty-three patients were enrolled. Dose-limiting toxicities were neutropenia, diarrhea, elevated liver enzymes, and fatigue. MTD of zotiraciclib was 250 mg in both arms and thus selected for the cohort expansion. Dose-dense temozolomide plus zotiraciclib (PSF4 40%) compared favorably with metronomic temozolomide (PFS4 25%). Symptom burden worsened at cycle 2 but stabilized by cycle 4 in both arms. A significant decrease in absolute neutrophil count and neutrophil reactive oxygen species production occurred 12-24 hours after an oral dose of zotiraciclib but both recovered by 72 hours. Pharmacokinetic/pharmacogenomic analyses revealed that the CYP1A2_5347T>C (rs2470890) polymorphism was associated with higher AUCinf value.

CONCLUSIONS

Zotiraciclib combined with temozolomide is safe in patients with recurrent high-grade astrocytomas. Zotiraciclib-induced neutropenia can be profound but mostly transient, warranting close monitoring rather than treatment discontinuation. Once validated, polymorphisms predicting drug metabolism may allow personalized dosing of zotiraciclib.

Associations between CYP3A4, CYP3A5 and SCN1A polymorphisms and carbamazepine metabolism in epilepsy: A meta-analysis

BACKGROUND AND OBJECTIVE

CYP3A4 (rs2242480), CYP3A5 (rs776746) and SCN1A (rs3812718 and rs2298771) gene polymorphisms were previously indicated to be associated with carbamazepine (CBZ) metabolism and resistance in epilepsy. However, previous studies regarding the effects of these polymorphisms still remain controversial. Therefore, we performed a meta-analysis to evaluate whether the four polymorphisms are associated with CBZ metabolism and resistance.

METHODS

The PubMed, EMBASE, Cochrane library, Chinese National Knowledge Infrastructure, Chinese Science and Technique Journals Database, China Biology Medicine disc and Wan Fang Database were searched up to January 2021 for appropriate studies regarding the association of rs2242480, rs776746, rs3812718 and rs2234922 polymorphisms with CBZ metabolism and resistance. The meta-analysis was conducted by Review Manager 5.3 software.

RESULTS

Eighteen studies involving 2546 related epilepsy patients were included. We found that the G allele of CYP3A4 rs2242480 markedly decreased the plasma CBZ concentration in epilepsy. For CYP3A5 rs776746 polymorphism, the GG genotype (homozygote codominant model: GG vs. AA) and GG + GA genotype (dominant model: GG + GA vs. AA and recessive model: GG vs. GA + AA) were respectively found to be significantly associated with increased CBZ plasma concentration. Additionally, it was also found that the SCN1A rs3812718 A allele was significantly associated with decreased CBZ plasma concentration and increased CBZ resistance. However, no association was observed between SCN1A rs2298771 polymorphism and CBZ metabolism and resistance.

CONCLUSION

The CYP3A4 rs2242480, CYP3A5 rs776746 and SCN1A rs3812718 polymorphisms may play important roles in CBZ metabolism and resistance, while SCN1A rs2298771 polymorphism is not associated with CBZ in epilepsy. These findings would improve the individualized therapy of epileptic patients in clinics.

Pharmacogenomic potential in advanced cancer patients

PURPOSE

The prevalence of pharmacogenetically actionable medications in advanced cancer patients whose therapy may be optimized with genotype data was determined.

METHODS

Patients enrolled in our institutional molecular tumor board observational cohort were included in this study. Collected data included demographics, type(s) of cancer, and outpatient medications. Medications were classified as "pharmacogenetically actionable" if there are Clinical Pharmacogenetics Implementation Consortium (CPIC) therapeutic recommendations for that medication based on the presence of germline variations. The prevalence of pharmacogenetically actionable medications in the study population was determined, and the frequency of opportunities for pharmacogenetic prescribing and adverse event (AE) mitigation were estimated.

RESULTS

In a cohort of 193 patients with advanced cancer, 65% of patients were taking a pharmacogenetically actionable medication. Approximately 10% of the outpatient medications taken by the study population had a pharmacogenetic association. The most common pharmacogenetically actionable medications being used were ondansetron (47%), capecitabine (10%), and sertraline (7%). Using published genetic variation frequencies and AE risk, we conservatively estimated that 7.1% of cancer patients would be eligible for genetic-based medication adjustment, and 101 AEs would be prevented in 10,000 patients genotyped.

CONCLUSION

Medications with pharmacogenetic associations are used commonly in the advanced cancer patient population. This widespread exposure supports the implementation of prospective genotyping in the treatment of these high-risk patients.

Clinical Pharmacogenetics for Precision Medicine: Successes and Setbacks

BACKGROUND

Pharmacogenetics is a key component in the delivery of therapeutics to maximize pharmacologic efficacy and minimize toxicity. There are numerous identified gene-drug pairs that demonstrate the utility of pharmacogenetics testing for drug or dose selection. Although some of these pairs have translated into clinical use, pharmacogenetic testing has not yet made its way into routine clinical practice at many institutions.

CONTENT

This review provides an overview of clinically actionable pharmacogenetics in precision medicine. Examples of successfully implemented gene-drug pairs, along with common testing methodologies and guidelines for application, are discussed. Remaining barriers to widespread clinical implementation are also examined.

SUMMARY

There is a recognized role for genotyping in the guidance of therapeutic drug regimens and the prevention of adverse drug reactions. Evidence-based guidelines are available to aid in the selection of treatment upon pharmacogenetics testing for established gene-drug pairs. Multidisciplinary clinical collaboration and clinical decision support tools will be critical for widespread adoption, and financial reimbursement barriers remain.

A 17-molecule set as a predictor of complete response to neoadjuvant chemotherapy with docetaxel, cisplatin, and 5-fluorouracil in esophageal cancer

Background

Recently, neoadjuvant chemotherapy with docetaxel/cisplatin/5-fluorouracil (NAC-DCF) was identified as a novel strong regimen with a high rate of pathological complete response (pCR) in advanced esophageal cancer in Japan. Predicting pCR will contribute to the therapeutic strategy and the prevention of surgical invasion. However, a predictor of pCR after NAC-DCF has not yet been developed. The aim of this study was to identify a novel predictor of pCR in locally advanced esophageal cancer treated with NAC-DCF.

Patients and methods

A total of 32 patients who received NAC-DCF followed by esophagectomy between June 2013 and March 2016 were enrolled in this study. We divided the patients into the following 2 groups: pCR group (9 cases) and non-pCR group (23 cases), and compared gene expressions between these groups using DNA microarray data and KeyMolnet. Subsequently, a validation study of candidate molecular expression was performed in 7 additional cases.

Results

Seventeen molecules, including transcription factor E2F, T-cell-specific transcription factor, Src (known as “proto-oncogene tyrosine-protein kinase of sarcoma”), interferon regulatory factor 1, thymidylate synthase, cyclin B, cyclin-dependent kinase (CDK) 4, CDK, caspase-1, vitamin D receptor, histone deacetylase, MAPK/ERK kinase, bcl-2-associated X protein, runt-related transcription factor 1, PR domain zinc finger protein 1, platelet-derived growth factor receptor, and interleukin 1, were identified as candidate molecules. The molecules were mainly associated with pathways, such as transcriptional regulation by SMAD, RB/E2F, and STAT. The validation study indicated that 12 of the 17 molecules (71%) matched the trends of molecular expression.

Conclusions

A 17-molecule set that predicts pCR after NAC-DCF for locally advanced esophageal cancer was identified.

Interethnic variability of pharmacogenetic biomarkers in Mexican healthy volunteers: a report from the RIBEF (Ibero-American Network of Pharmacogenetics and Pharmacogenomics)

Mexico presents a complex population diversity integrated by Mexican indigenous (MI) (7% of Mexico's population) and Mexican mestizos (MMs). This composition highlights the importance of pharmacogenetic studies in Mexican populations. The aims of this study were to analyze the reported frequencies of the most relevant pharmacogenetic biomarkers and metabolic phenotypes in healthy volunteers from Mexican populations and to assess its interethnic variability across MI and MM populations. After a literature search in PubMed, and according to previously defined inclusion criteria, 63 pharmacogenetic studies performed in Mexican healthy volunteers up to date were selected. These reports comprised 56,292 healthy volunteers (71.58% MM). Allele frequencies in 31 pharmacogenetic biomarkers, from 121 searched, are described. Nine of these biomarkers presented variation within MM and MI groups. The frequencies of CYP2D6*3, *4, *5, *10, *17, *35 and *41 alleles in the MM group were different from those reported in the MI group. CYP2C9*2 and *3 alleles were more frequent in MM than in MI populations (χ2 test, p<0.05). CYP2C19*3 allele was not found in the MM or MI populations reported. For UGT1A1*28, only one study was found. HLA-A*31:01 and HLA-B*15:02 were present in some MM and MI populations. Poor metabolizers for CYP2D6 and CYP2C9 were more frequent in MM than in MI groups (χ2 test, p<0.05). Only 26% of the relevant pharmacogenetic biomarkers searched have been studied in Mexican healthy volunteers; therefore, further studies are warranted. The frequency variation of biomarkers in MM and MI populations could be important for the clinical implementation of pharmacogenetics in Mexico.

Metabolomics Applications in Precision Medicine: An Oncological Perspective

Nowadays, cancer therapy remains limited by the conventional one-size-fits-all approach. In this context, treatment decisions are based on the clinical stage of disease but fail to ascertain the individual´s underlying biology and its role in driving malignancy. The identification of better therapies for cancer treatment is thus limited by the lack of sufficient data regarding the characterization of specific biochemical signatures associated with each particular cancer patient or group of patients. Metabolomics approaches promise a better understanding of cancer, a disease characterized by significant alterations in bioenergetic metabolism, by identifying changes in the pattern of metabolite expression in addition to changes in the concentration of individual metabolites as well as alterations in biochemical pathways. These approaches hold the potential of identifying novel biomarkers with different clinical applications, including the development of more specific diagnostic methods based on the characterization of metabolic subtypes, the monitoring of currently used cancer therapeutics to evaluate the response and the prognostic outcome with a given therapy, and the evaluation of the mechanisms involved in disease relapse and drug resistance. This review discusses metabolomics applications in different oncological processes underlining the potential of this omics approach to further advance the implementation of precision medicine in the oncology area.

Development of HLA-B*57:01 Genotyping Real-Time PCR with Optimized Hydrolysis Probe Design

HLA-B*57:01 genotyping before abacavir (ABC) administration is a standard of care to avoid ABC-driven hypersensitivity reactions. Several HLA-B*57:01 tests have been developed, each with advantages and disadvantages. Some have limited accuracy, require special instrumentation, and/or are labor intensive and expensive. We developed a novel hydrolysis probe-based real-time PCR method of HLA-B*57:01 genotyping. Primer and probes were designed based on published sequence variations in exon 3 of HLA-B that distinguish HLA-B*57:01 from ABC-insensitive alleles such as HLA-B*57:03 and HLA-B*58:01. We designed PCR primers to amplify HLA-B*57:01 along with closely related alleles, such as HLA-B*57:03, directly from genomic DNA. Most ABC-insensitive alleles, including HLA-B*58:01, would not produce any products in the PCR reaction. Our hydrolysis probes enable differentiation of HLA-B*57:01 from the other amplified, but ABC-insensitive, alleles. In addition to using real-time PCR, we used restriction enzymes to generate differential digestion patterns that led to the development of an HLA-B*57:01 PCR-restriction fragment length polymorphism marker. When used to genotype a set of 75 selected clinical samples, our real-time PCR assay demonstrated 100% accuracy in distinguishing between the HLA-B*57:01-positive and -negative alleles when results were compared to those of sequence-specific oligonucleotide probe typing and reference laboratory testing. Our newly developed test will allow clinical laboratories with real-time PCR capabilities to perform HLA-B*57:01 genotyping in a timely and economical manner.

Pharmacogenomics Genome Wise Association Clinical Studies

Pharmacogenomics deals with drug responses in individual based on genetic variation in genome. Based on genetic variations, drugs may produce more or less therapeutic effect, and same way in side effects also. Physicians can use information about your genetic makeup to choose those drugs and drug doses to get better therapy. Optimizing drug therapy and rational dose adjustment with respect to genetic makeup will maximize drug efficacy and minimal adverse effects. This broken traditional ‘trial and error' method of ‘one drug fits all', and ‘one dose fits all' which contributing to 25–50% of drug toxicity or treatment failures. This will contribute to improve the ways in which existing drugs are used, genomic research will lead to drug development to produce new drugs that are highly effective without serious side effects. This approach to bring personalized medicine more practice and drug combinations are optimized for each individual' genetic makeup.

Phenotyping and genotyping of CYP2C19 using comparative metabolism of proguanil in sickle-cell disease patients and healthy controls in Nigeria

Polymorphic expression of metabolic enzymes have been identified as one of the key factors responsible for the interindividual/ethnic/racial variability in drug metabolism and effect. In Nigeria, there is a disproportionately high incidence of sickle-cell disease (SCD), a condition characterized by painful crisis frequently triggered by malaria. Proguanil, a substrate of the polymorphic CYP2C19, is a chemoprophylactic antimalarial drug widely used among SCD patients in Nigeria. This study aimed to conduct a comparative CYP2C19 phenotyping among SCD patients and healthy controls and to compare the results with those previously reported. One hundred seventy-seven unrelated subjects comprising 131 SCD patients and 46 non-SCD volunteers were phenotyped. This was carried out by collecting pooled urine samples over 8 h following PG administration. Proguanil and its major CYP2C19-dependent metabolites were measured by high-performance liquid chromatography. Metabolic ratios (MRs) were computed and employed in classifying subjects into poor or extensive metabolizers. Among SCD group, 130 (99.2%) were extensive metabolizers (EMs) and 1 (0.8%) was poor metabolizer (PM) of PG, while 95.7 and 4.3% non-SCDs were EMs and PMs, respectively. MRs ranged from 0.02 to 8.70 for SCD EMs and from 0.22 to 8.33 for non-SCD EMs . Two non-SCDs with MRs of 18.18 and 25.76 and the SCD with MR of 16.77 regarded as PMs had earlier been genotyped as CYP2C19*2/*2. Poor metabolizers of proguanil in SCD patients are reported for the first time. Regardless of clinical significance, a difference in metabolic disposition of proguanil and CYP2C19 by SCDs and non-SCDs was established.

Pharmacogenetic studies update in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a silent progressive polygenic metabolic disorder resulting from ineffective insulin cascading in the body. World-wide, about 415 million people are suffering from T2DM with a projected rise to 642 million in 2040. T2DM is treated with several classes of oral antidiabetic drugs (OADs) viz. biguanides, sulfonylureas, thiazolidinediones, meglitinides, etc. Treatment strategies for T2DM are to minimize long-term micro and macro vascular complications by achieving an optimized glycemic control. Genetic variations in the human genome not only disclose the risk of T2DM development but also predict the personalized response to drug therapy. Inter-individual variability in response to OADs is due to polymorphisms in genes encoding drug receptors, transporters, and metabolizing enzymes for example, genetic variants in solute carrier transporters (SLC22A1, SLC22A2, SLC22A3, SLC47A1 and SLC47A2) are actively involved in glycemic/HbA1c management of metformin. In addition, CYP gene encoding Cytochrome P450 enzymes also play a crucial role with respect to metabolism of drugs. Pharmacogenetic studies provide insights on the relationship between individual genetic variants and variable therapeutic outcomes of various OADs. Clinical utility of pharmacogenetic study is to predict the therapeutic dose of various OADs on individual basis. Pharmacogenetics therefore, is a step towards personalized medicine which will greatly improve the efficacy of diabetes treatment.

Pharmacogenomics in Pediatric Patients: Towards Personalized Medicine

It is well known that drug responses differ among patients with regard to dose requirements, efficacy, and adverse drug reactions (ADRs). The differences in drug responses are partially explained by genetic variation. This paper highlights some examples of areas in which the different responses (dose, efficacy, and ADRs) are studied in children, including cancer (cisplatin), thrombosis (vitamin K antagonists), and asthma (long-acting β2 agonists). For childhood cancer, the replication of data is challenging due to a high heterogeneity in study populations, which is mostly due to all the different treatment protocols. For example, the replication cohorts of the association of variants in TPMT and COMT with cisplatin-induced ototoxicity gave conflicting results, possibly as a result of this heterogeneity. For the vitamin K antagonists, the evidence of the association between variants in VKORC1 and CYP2C9 and the dose is clear. Genetic dosing models have been developed, but the implementation is held back by the impossibility of conducting a randomized controlled trial with such a small and diverse population. For the long-acting β2 agonists, there is enough evidence for the association between variant ADRB2 Arg16 and treatment response to start clinical trials to assess clinical value and cost effectiveness of genotyping. However, further research is still needed to define the different asthma phenotypes to study associations in comparable cohorts. These examples show the challenges which are encountered in pediatric pharmacogenomic studies. They also display the importance of collaborations to obtain good quality evidence for the implementation of genetic testing in clinical practice to optimize and personalize treatment.

Evaluation of cytochrome P450 2C9 activity in normal, healthy, adult Western Indian population by both phenotyping and genotyping

Objectives:

Cytochrome P450 2C9 (CYP2C9) is a member of cytochrome P450 (CYP) family that accounts for nearly 18% of the total CYP protein content in the human liver microsomes and catalyzes almost 15–20% of the drugs. Considering the paucity of data on the polymorphisms of CYP2C9 in Western Indian population, the present study was conducted to evaluate the prevalence of CYP2C9 polymorphisms (*1, *2 and *3) and correlate it with the activity using flurbiprofen (FLB) as a probe drug.

Materials and Methods:

A 100 mg FLB capsule was administered to 298 healthy adult participants. Venous blood samples were analyzed at 2 h postdose for the estimation of FLB and 4-hydroxy FLB. Metabolic ratio (MR) was calculated to determine the extent of poor metabolizer (PM) and rapid metabolizer status using probit plot. Genotyping of CYP2C9 polymorphism was performed using polymerase chain reaction-restriction fragment length polymorphism technique.

Results:

Of the total 298 participants, phenotype was assessable in 288 and genotype was performed in 289 participants. The median (range) MR of the study population was 6.6 (1.65–66.05). Five participants were found to be PMs by phenotype. Of the total 289 participants, 209 (72.3%) (66.7, 77.2) had CYP2C9*1/*1, 25 (8.7%) (5.8, 12.7) with CYP2C9*1/*2, 55 (19%) (14.8, 24.1) had CYP2C9*1/*3, 3 (1%) (0.3, 3.3) had CYP2C9*2/*3 genotype. A significant association between phenotype and genotype was observed.

Conclusion:

To conclude, the present study found significant association of CYP2C9 activity by both phenotype and genotype and these findings have to be corroborated in different kinds of patients.

Placental transfer of antidepressant medications: implications for postnatal adaptation syndrome

Seven to thirteen percent of women are either prescribed or taking (depending on the study) an antidepressant during pregnancy. Because antidepressants freely cross into the intrauterine environment, we aim to summarize the current findings on placental transfer of antidepressants. Although generally low risk, antidepressants have been associated with postnatal adaptation syndrome (PNAS). Specifically, we explore whether the antidepressants most closely associated with PNAS (paroxetine, fluoxetine, venlafaxine) cross the placenta to a greater extent than other antidepressants. We review research on antidepressants in the context of placental anatomy, placental transport mechanisms, placental metabolism, pharmacokinetics, as well as non-placental maternal and fetal factors. This provides insight into the complexity involved in understanding how placental transfer of antidepressants may relate to adverse perinatal outcomes. Ultimately, from this data there is no pattern in which PNAS is related to placental transfer of antidepressant medications. In general, there is large interindividual variability for each type of antidepressant. To make the most clinically informed decisions about the use of antidepressants in pregnancy, studies that link maternal, placental and fetal genetic polymorphisms, placental transfer rates and infant outcomes are needed.

Differential Gene Expression across Breed and Sex in Commercial Pigs Administered Fenbendazole and Flunixin Meglumine

Characterizing the variability in transcript levels across breeds and sex in swine for genes that play a role in drug metabolism may shed light on breed and sex differences in drug metabolism. The objective of the study is to determine if there is heterogeneity between swine breeds and sex in transcript levels for genes previously shown to play a role in drug metabolism for animals administered flunixin meglumine or fenbendazole. Crossbred nursery female and castrated male pigs (n = 169) spread across 5 groups were utilized. Sires (n = 15) of the pigs were purebred Duroc, Landrace, Yorkshire or Hampshire boars mated to a common sow population. Animals were randomly placed into the following treatments: no drug (control), flunixin meglumine, or fenbendazole. One hour after the second dosing, animals were sacrificed and liver samples collected. Quantitative Real-Time PCR was used to measure liver gene expression of the following genes: SULT1A1, ABCB1, CYP1A2, CYP2E1, CYP3A22 and CYP3A29. The control animals were used to investigate baseline transcript level differences across breed and sex. Post drug administration transcript differences across breed and sex were investigated by comparing animals administered the drug to the controls. Contrasts to determine fold change were constructed from a model that included fixed and random effects within each drug. Significant (P-value <0.007) basal transcript differences were found across breeds for SULT1A1, CYP3A29 and CYP3A22. Across drugs, significant (P-value <0.0038) transcript differences existed between animals given a drug and controls across breeds and sex for ABCB1, PS and CYP1A2. Significant (P <0.0038) transcript differences across breeds were found for CYP2E1 and SULT1A1 for flunixin meglumine and fenbendazole, respectively. The current analysis found transcript level differences across swine breeds and sex for multiple genes, which provides greater insight into the relationship between flunixin meglumine and fenbendazole and known drug metabolizing genes.

Are pharmacogenomic biomarkers an effective tool to predict taxane toxicity and outcome in breast cancer patients? Literature review

PURPOSE

Breast cancer is a heterogeneous disease, characterized by various molecular phenotypes that correlate with different prognosis and response to treatments. Taxanes are some of the most active chemotherapeutic agents for breast cancer; however, their utilization is limited, due to hematologic and cumulative neurotoxicity on treated patients. To understand why only some patients experience severe adverse effects and why patients respond and develop resistance with different rates to taxane therapy, the metabolic pathways of these drugs should be completely unraveled. The variant forms of several genes, related to taxane pharmacokinetics, can be indicative markers of clinical parameters, such as toxicity or outcome.

METHODS

The search of the data has been conducted through PubMed database, presenting clinical data, clinical trials and basic research restricted to English language until June 2015.

RESULTS

We studied the literature in order to find any possible association between the major pharmacogenomic variants and specific taxane-related toxicity and patient outcome. We found that the data of these studies are sometimes discordant, due to both the small number of enrolled patients and the heterogeneity of the examined population.

CONCLUSIONS

Among all analyzed genes, only CYP1B1 and ABCB1 resulted the strongest candidates to become biomarkers of clinical response to taxane therapy in breast cancer, although their utilization still remains an experimental procedure. In the future, greater studies on genetic polymorphisms should be performed in order to identify differentiating signatures for patients with higher toxicity and with resistant or responsive outcome, before the administration of taxanes.

Pharmacogenetics of cancer drugs

The variability in treatment outcomes among patients receiving the same therapy for seemingly similar tumors can be attributed in part to genetics. The tumor's (somatic) genome largely dictates the effectiveness of the therapy, and the patient's (germline) genome influences drug exposure and the patient's sensitivity to toxicity. Many potentially clinically useful associations have been discovered between common germline genetic polymorphisms and outcomes of cancer treatment. This review highlights the germline pharmacogenetic associations that are currently being used to guide cancer treatment decisions, those that are most likely to someday be clinically useful, and associations that are well known but their roles in clinical management are not yet certain. In the future, germline genetic information will likely be available from tumor genetic analyses, creating an efficient opportunity to integrate the two genomes to optimize treatment outcomes for each individual cancer patient.

Screening for 392 polymorphisms in 141 pharmacogenes

Pharmacogenomics is the study of the association between inter-individual genetic differences and drug responses. Researches in pharmacogenomics have been performed in compliance with the use of several genotyping technologies. In this study, a total of 392 single-nucleotide polymorphisms (SNPs) located in 141 pharmacogenes, including 21 phase I, 13 phase II, 18 transporter and 5 modifier genes, were selected and genotyped in 150 subjects using the GoldenGate assay or the SNaPshot technique. These variants were in Hardy-Weinberg equilibrium (HWE) (P>0.05), except for 22 SNPs. Genotyping of the 392 SNPs revealed that the minor allele frequencies of 47 SNPs were <0.05, 105 SNPs were monomorphic and 22 variants were not in HWE. Also, based on previous studies, we predicted the association between the polymorphisms of certain pharmacogenes, such as cytochrome P450 2D6, cytochrome P450 2C9, vitamin K epoxide reductase complex, subunit 1, cytochrome P450 2C19, human leukocyte antigen, class I, B and thiopurine S-methyltransferase, and drug efficacy. In conclusion, our study demonstrated the allele distribution of SNPs in 141 pharmacogenes as determined by high-throughput screening. Our results may be helpful in developing personalized medicines by using pharmacogene polymorphisms.

Revitalizing personalized medicine: respecting biomolecular complexities beyond gene expression

Despite recent advancements in "omic" technologies, personalized medicine has not realized its fullest potential due to isolated and incomplete application of gene expression tools. In many instances, pharmacogenomics is being interchangeably used for personalized medicine, when actually it is one of the many facets of personalized medicine. Herein, we highlight key issues that are hampering the advancement of personalized medicine and highlight emerging predictive tools that can serve as a decision support mechanism for physicians to personalize treatments.

The effect of breed and sex on sulfamethazine, enrofloxacin, fenbendazole and flunixin meglumine pharmacokinetic parameters in swine

Drug use in livestock has received increased attention due to welfare concerns and food safety. Characterizing heterogeneity in the way swine populations respond to drugs could allow for group-specific dose or drug recommendations. Our objective was to determine whether drug clearance differs across genetic backgrounds and sex for sulfamethazine, enrofloxacin, fenbendazole and flunixin meglumine. Two sires from each of four breeds were mated to a common sow population. The nursery pigs generated (n = 114) were utilized in a random crossover design. Drugs were administered intravenously and blood collected a minimum of 10 times over 48 h. A non-compartmental analysis of drug and metabolite plasma concentration vs. time profiles was performed. Within-drug and metabolite analysis of pharmacokinetic parameters included fixed effects of drug administration date, sex and breed of sire. Breed differences existed for flunixin meglumine (P-value<0.05; Cl, Vdss ) and oxfendazole (P-value<0.05, AUC0→∞ ). Sex differences existed for oxfendazole (P-value < 0.05; Tmax ) and sulfamethazine (P-value < 0.05, Cl). Differences in drug clearance were seen, and future work will determine the degree of additive genetic variation utilizing a larger population.

Next revolution in the molecular theranostics of infectious diseases: microfabricated systems for personalized medicine

The molecular diagnosis of infectious diseases is currently going through a revolution sustained by the regulatory approval of amplification tests that have been shown to be equivalent or superior to existing gold standard methods. The recent approval of a microarray system for the pharmacogenomic profiling of cytochrome P450-mediated drug metabolism is paving the way to novel, rapid, sensitive, robust and economical microfabricated systems for point-of-care diagnostics, which are utilized closer and closer to the patient's bedside. These systems will enable the multiparametric genetic evaluation of several medical conditions, including infectious diseases. This forecoming revolution will position molecular theranostics in a broader integrated view of personalized medicine, which exploits genetic information from microbes and human hosts to optimize patient management and disease treatment.

Pharmacogenetics and Pharmacogenomics as New Tools to Optimise Cancer Chemotherapy

Pharmacogenetics takes into account the individual variability of the genome and its relationships with drug activity. Numerous gene polymorphisms occurring at the level of drug metabolising enzymes, drug transporters or drug targets have been identified; they may be responsible for an alteration of the phenotype, and of individual changes in drug efficacy and/or toxicity. Pharmacogenomics takes into account the genetic alterations present in tumours and their role in drug activity. It may be possible to establish correlations between the activity of a drug and the level of expression of tumour genes, and thus select the most appropriate drugs to prescribe for the treatment of individual tumours. Pharmacogenetics and pharmacogenomics are acting synergistically for the personalisation of treatments, on the basis of the constitutive singularity of patients and of the molecular characteristics of tumours.

Pharmacometabonomics and personalized medicine

BACKGROUND

Pharmacometabonomics is a new branch of science, first described in 2006 and defined as 'the prediction of the effects of a drug on the basis of a mathematical model of pre-dose metabolite profiles'. Pharmacometabonomics has been used to predict drug metabolism, pharmacokinetics (PK), drug safety and drug efficacy in both animals and humans and is complementary to both pharmacogenomics (PGx) and pharmacoproteomics.

METHODS

A literature review using the search terms pharmacometabonomics, pharmacometabolomics, pharmaco-metabonomics, pharmaco-metabolomics and the singular form of all those terms was conducted in October 2012 using PubMed and Web of Science. The review was updated until mid April 2013.

RESULTS

Since the original description of pharmacometabonomics in 2006, 21 original publications and eight reviews have emerged, covering a broad range of applications from the prediction of PK to the prediction of drug metabolism, efficacy and safety in humans and animals.

CONCLUSIONS

Pharmacometabonomics promises to be an important new approach to the delivery of personalized medicine to improve both drug efficacy and safety for patients in the future. Pharmacometabonomics is particularly powerful as it is sensitive to both genetic and environmental factors such as diet, drug intake and most importantly, a person's microbiome. PGx is now over 50 years old and although it has not achieved as much as some hoped, it is starting to have important applications in personalized medicine. We predict that pharmacometabonomics will be equally important in the next few decades and will be both valuable in its own right and complementary to pharmacoproteomics and PGx.

Use of pharmacogenetics for predicting cancer prognosis and treatment exposure, response and toxicity

Cancer treatment is complicated because of a multitude of treatment options and little patient-specific information to help clinicians choose appropriate therapy. There are two genomes relevant in cancer treatment: the tumor (somatic) and the patient (germline). Together, these two genomes dictate treatment outcome through four processes: the somatic genome primarily determines tumor prognosis and response while the germline genome modulates treatment exposure and toxicity. In this review, we describe the influence of these genomes on treatment outcomes by highlighting examples of genetic variation that are predictors of each of these four factors, prognosis, response, toxicity and exposure, and discuss the translation and clinical implementation of each. Use of pre-treatment pharmacogenetic testing will someday enable clinicians to make individualized therapy decisions about aggressiveness, drug selection and dose, improving treatment outcomes for cancer patients.

TMEM158 and FBLP1 as novel marker genes of cisplatin sensitivity in non-small cell lung cancer cells

Even after development of molecular targeting therapies, platinum-based chemotherapy is still a standard care for treatment of locally advanced non-small cell lung cancer (NSCLC). So far, critical molecular markers capable to predict the therapeutic response in NSCLC patients remain undetermined. We here attempted to identify novel biomarker genes for cisplatin (CDDP) for a tailored therapy. Initial screening to explorer association of IC(50) values of CDDP obtained by MTT assay and gene expression levels measured with oligonucleotide microarray and real-time RT-PCR provided 6 candidate genes, namely, NUBPL, C9orf30, ZNF12, TMEM158, GSK3B, and FBLP1 using 9 lung cancer cells consisting of 3 small and 6 NSCLC cells. These 6 genes together with 5 reported biomarkers, i.e., GSTP1, ERCC1, BRCA1, FRAP1, and RRM1, were subjected to a linear regression analysis using 12 NSCLC cell lines including 6 additional NSCLC cells: only FBLP1 and TMEM158 genes showed positive associations with statistical significances (P = .016 and .026, respectively). The biological significance of these genes was explored by in vitro experiments: Knockdown experiments in PC-9/CDDP cells revealed that the reduced expression of TMEM158 significantly decreased the chemo-resistance against CDDP (P <.0001), while 2 transformants of PC-6 cells stably over-expressing FBLP1 resulted in an enhanced resistance to CDDP (P = .004 and P = .001). Furthermore, a stepwise multiple regression analysis demonstrated the best prediction formula could be fixed when we used expression data of TMEM158 and FBLP1 (R(2) = 0.755, P = .0018). TMEM158 and FBLP1 may be powerful predictive biomarkers for CDDP therapy in NSCLC.

Concept-based learning of personalized prescribing

The variability of drug response in different patients can be caused by various factors including age, change in renal function, co-medication and genotype. Traditionally, these personal variables are considered by clinicians prior to issuing a prescription. This paper provides an overview of a process to individualize prescribing for a patient with an emphasis on how to train (learning) clinicians in skillful rational prescribing. For this purpose the 6STEP methodology, a concept-based learning strategy to achieve a structured therapeutic plan, has been introduced. In contrast to older educational approaches which focused primarily on the drugs or the process of prescribing, the 6STEP is a patient-centred method resulting in individualized therapy. The six interlinked steps provide the (training) prescriber with a structured framework that facilitates a rationalized therapeutic decision by focusing on the individual patient parameters that influence drug response. Educational tools for rational prescribing involve understanding of basic and clinical pharmacological principles, practicing to write 6STEP therapeutic plans, learning from feedback sessions on these plans and actively obtaining up to date information on drugs and therapeutic standards from online resources.

Pharmacogenomics: historical perspective and current status

Pharmacogenomics and its predecessor pharmacogenetics study the contribution of genetic factors to the interindividual variability in drug efficacy and safety. One of the major goals of pharmacogenomics is to tailor drugs to individuals based on their genetic makeup and molecular profile. From early findings in the 1950s uncovering inherited deficiencies in drug metabolism that explained drug-related adverse events, to nowadays genome-wide approaches assessing genetic variation in multiple genes, pharmacogenomics has come a long way. The evolution of pharmacogenomics has paralleled the evolution of genotyping technologies, the completion of the human genome sequencing and the HapMap project. Despite these advances, the implementation of pharmacogenomics in clinical practice has yet been limited. Here we present an overview of the history and current applications of pharmacogenomics in patient selection, dosing, and drug development with illustrative examples of these categories. Some of the challenges in the field and future perspectives are also presented.

Prakriti-based medicine: A step towards personalized medicine

The concept of personalized medicine has been around for as long as people have been practicing medicine. From Charaka to Hippocrates, all have practiced the personalized approach for treating a disease. In the 21^st century, personalized medicine is all about DNA. Whereas the single nucleotide polymorphism (SNP) and epigenetic factors influence drug response and form the basis of personalized medicine, the tridosha theory forms the basis of Prakriti-based medicine. It is well established by now that western allopathic medicine is excellent in handling acute medical crises, whereas Ayurveda has successfully demonstrated an ability to manage chronic disorders that Western medicine has been unable to cure. With effective integration of ‘omics’ Prakriti-based medicine can play a vital role in this changing scenario of global health wisdom as Ayurveda offers its modalities by way of ahara (diet), vihara (lifestyle), and aushadhi (medication), which are the three pillars of prakriti-based medicine making it a holistic science. Prakriti-based medicine and other traditional medicine systems have the potential to offer remedies to the challenging health issues like adverse drug reactions, drug withdrawals, and economic disparities among few. An integrative global approach could do wonders to health sciences benefiting a broad spectrum of patients.

Nanotheranostics for personalized medicine

The application of nanotechnology in the biomedical field, known as nanomedicine, has gained much interest in the recent past, as versatile strategy for selective drug delivery and diagnostic purposes. The already encouraging results obtained with monofunctional nanomedicines have directed the efforts of the scientists towards the creation of "nanotheranostics" (i.e. theranostic nanomedicines) which integrate imaging and therapeutic functions in a single platform. Nanotheranostics hold great promises because they combine the simultaneous non-invasive diagnosis and treatment of diseases with the exciting possibility to monitor in real time drug release and distribution, thus predicting and validating the effectiveness of the therapy. Due to these features nanotheranostics are extremely attractive for optimizing treatment outcomes in cancer and other severe diseases. The following step is the attempt to use nanotheranostics for performing a real personalized medicine which will tailor optimized treatment to each patient, taking into account the individual variability. Clinical application of nanotheranostics would enable earlier detection and treatment of diseases and earlier assessment of the response, thus allowing screening for patients which would potentially respond to therapy and have higher possibilities of a favorable outcome. This concept makes nanotheranostics extremely appealing to elaborate personalized therapeutic protocols for achieving the maximal benefit along with a high safety profile. Among the several systems developed up to now, this review focuses on the nanotheranostics which, due to the promising results, show the highest potential of translation to clinical applications and may transform into concrete practice the concept of personalized nanomedicine.

Obesity genetics: a monopoly game of genes

Obesity is a complex disease that affects all ethnic populations worldwide. The etiology of this disease is based on the interaction of genetic factors, environment and lifestyles indicators. Genetic contribution to the epidemic has gained attention from 2 sources: monogenic syndromes that display severe obesity, and the polygenic model of common obesity. Single mutations can render a syndrome with severe obesity resulting from alteration in central o peripheral appetite control mechanisms. The interaction of several polymorphisms and epigenetic modifications constitute the basic plot for common obesity, molecular ingredients that should not confuse the investigator-they make this riddle even harder to decipher.

Role of pharmacogenomics in the treatment of tuberculosis: a review

BACKGROUND

Tuberculosis is one of the major public health problems worldwide. Modern antituberculous treatment can cure most patients; cure rates > 95% are achieved with standard short-course chemotherapy regimens containing isoniazid, rifampicin, pyrazinamide, and ethambutol among patients with drug-susceptible strains of tuberculosis; however, a small proportion do not respond to treatment or develop serious adverse events. Pharmacogenomic studies of drugs used in the treatment of tuberculosis could help us understand intersubject variations in treatment response. In this review, we compiled pharmacogenomic data on antituberculous drugs that were available from different settings that would give a better insight into the role of pharmacogenomics in the treatment of tuberculosis, thereby enhancing the efficacy and limiting the toxicity of existing antituberculosis medications.

METHODS

The PubMed database was searched from 1960 to the present using the keywords "tuberculosis", "antituberculosis treatment", "isoniazid", "rifampicin", "pyrazinamide", "ethambutol", "pharmacogenomics", and "polymorphism". Abstracts from meetings and review articles were included.

CONCLUSION

Studies conducted in different settings suggest that pharmacogenomics plays a significant role in isoniazid metabolism, and impacts both treatment efficacy and frequency of adverse reactions. Single nucleotide polymorphisms influencing plasma rifampicin concentrations are also reported. No data are available regarding other first-line drugs, ie, ethambutol and pyrazinamide. There is a need to incorporate pharmacogenomics into clinical trials of tuberculosis in order to understand the factors impacting therapeutic success and occurrence of adverse drug effects.

CYP2C8*3 predicts benefit/risk profile in breast cancer patients receiving neoadjuvant paclitaxel

Paclitaxel is one of the most frequently used chemotherapeutic agents for the treatment of breast cancer patients. Using a candidate gene approach, we hypothesized that polymorphisms in genes relevant to the metabolism and transport of paclitaxel are associated with treatment efficacy and toxicity. Patient and tumor characteristics and treatment outcomes were collected prospectively for breast cancer patients treated with paclitaxel-containing regimens in the neoadjuvant setting. Treatment response was measured before and after each phase of treatment by clinical tumor measurement and categorized according to RECIST criteria, while toxicity data were collected from physician notes. The primary endpoint was achievement of clinical complete response (cCR) and secondary endpoints included clinical response rate (complete response+partial response) and grade 3+ peripheral neuropathy. The genotypes and haplotypes assessed were CYP1B1*3, CYP2C8*3, CYP3A4*1B/CYP3A5*3C, and ABCB1*2. A total of 111 patients were included in this study. Overall, cCR was 30.1% to the paclitaxel component. CYP2C8*3 carriers (23/111, 20.7%) had higher rates of cCR (55% vs. 23%; OR=3.92 [95% CI: 1.46-10.48], corrected p=0.046). In the secondary toxicity analysis, we observed a trend toward greater risk of severe neuropathy (22% vs. 8%; OR=3.13 [95% CI: 0.89-11.01], uncorrected p=0.075) in subjects carrying the CYP2C8*3 variant. Other polymorphisms interrogated were not significantly associated with response or toxicity. Patients carrying CYP2C8*3 are more likely to achieve clinical complete response from neoadjuvant paclitaxel treatment, but may also be at increased risk of experiencing severe peripheral neurotoxicity.

Individualized medicine, health medicine, and constitutional theory in Chinese medicine

The patterns of modern science and changes in the medical model can result in the transformation of the current state of individualized and health medicines into being the primary trend in medical development. Chinese and Western medical systems are dissimilar in terms of value orientations, thinking style, and research directions because of their different historical and cultural backgrounds. Individualized treatment in modern medicine is mainly established based on individual genome information and the differences in mononucleotide polymorphisms. However, such treatment method is expensive, creates an uncertain genetic marker, and leads to different result interpretations, among other problems. The Chinese constitutional theory developed in the 1970s expresses the principle behind Chinese health medicine and individual treatment and provides the corresponding methods. The Chinese constitutional theory divides the constitution of the Chinese population into nine categories based on established classification criteria. It promotes the study of the relationship of each constitution to diseases and Chinese medicine preparation toward adjusting the constitution and preventing diseases. The theory also provides methods and tools for individualized treatment. Constitution identification shows the direction and provides the core technology for the evaluation of the health status. By combining the developments in modern biotechnology, new diagnostic techniques and treatment models of constitution-differentiation, disease-differentiation, and syndrome-differentiation can be established for the development of individualized Chinese medicine treatment and health medicine for the international medical community.

The interactions of age, sex, body mass index, genetics, and steroid weight-based doses on tacrolimus dosing requirement after adult kidney transplantation

PURPOSE

The aim of this study was to evaluate the effect of different clinical covariates on tacrolimus dose requirements in adult kidney transplant patients with a specific focus on drug interactions.

PATIENTS

Tacrolimus dosing requirement, normalized by drug levels and expressed as the concentration/dose (C/D) ratio as a surrogate index of tacrolimus bioavailability, was employed to identify four categories of tacrolimus dosing requirement, namely, very high, high, small, and very-small, in very fast, fast, slow, and very slow metabolizers, respectively. Steroid weight-based doses were analyzed instead of fixed doses, and genetic analysis of cytochrome P450 (CYP) 3A5*1/*3 and multi-drug resistance 1 (MDR1) C3435T and C1236T polymorphisms were performed

RESULTS

Multivariate analysis on 450 adult transplant patients identified six risk factors for being slow metabolizers and therefore requiring small tacrolimus doses: male sex (OR 1.615, p = 0.020); age >60 years (OR 2.456, p = 0.0005); body mass index ≥ 25 (OR 1.546, p = 0.046), hepatitis C virus positivity (OR 2.800, p = 0.0004); low steroid dose <0.06 mg/kg (OR 3.101, p < 0.0001). Patients with a small tacrolimus requirement were at increased risk for multiple infections (OR 1.533, p = 0.0008) and higher systolic blood pressure (OR 1.385, p = 0.022) and showed a significant association with the CYP3A5*3/*3 genotype adjusted by MDR1 polymorphisms C3435T and C1236T (OR 8.104, p = 0.0001).

CONCLUSIONS

Our results demonstrate the importance of the interaction among genetic and clinical factors in conditioning tacrolimus disposition, with corticosteroid weight-based dose being the only modifiable risk factor for tacrolimus requirement. As the tacrolimus dosing requirement increases with increasing tacrolimus clearance through concomitant steroid use, undesirable changes in tacrolimus levels may occur when steroid doses are tapered, predominantly in slow metabolizers. This often neglected drug interaction has to be monitored to optimize tacrolimus exposure in kidney transplant patients.

Pharmacogenetics: implications for therapy in rheumatic diseases

DMARDs not only improve the joint pain and swelling associated with rheumatoid arthritis (RA), but also slow down the joint damage associated with the disease. The efficacy of biologic therapies, introduced in the past decade for the treatment of RA, has been unequivocally established. Similarly, in addition to traditional drugs such as hydroxychloroquine, new biologic agents such as rituximab have been introduced for systemic lupus erythematosus in recent years. However, considerable variability occurs in the responses of patients to these therapies. Pharmacogenetics, the study of variations in genes encoding drug transporters, drug-metabolizing enzymes and drug targets, and their translation to differential responses to drugs, is a rapidly progressing field in rheumatology. Pharmacogenetic applications, particularly to the old vanguard DMARD, methotrexate, and the newer, more expensive biologic agents, might make personalized therapy in rheumatic diseases possible. The pharmacogenetics of commonly used DMARDs and of biologic therapies are described in this Review.

Pharmacogenomic contribution to drug response

There has been significant progress made in individualizing cancer therapy, especially for colorectal and breast cancer. This has included objective determination of aggressiveness of therapy using molecular predictors of disease recurrence (i.e., Mammaprint, OncotypeDX), identifying altered drug activation for dose modifications (i.e., DPYD, CYP2D6, UGT1A1), or variation in drug targets or components of a pharmacodynamic pathway (TYMS, EGFR, KRAS). With patient-specific molecular characteristics increasingly guiding therapy, this review provides important and timely insights on targeted therapy. Ultimately, integration of both pharmacogenomic and clinical characteristics can provide powerful predictive tools for stratifying responders from nonresponders and identifying patients at increased risk for toxicity.

Pharmacogenetics, pharmacogenomics, and individualized medicine

Individual variability in drug efficacy and drug safety is a major challenge in current clinical practice, drug development, and drug regulation. For more than 5 decades, studies of pharmacogenetics have provided ample examples of causal relations between genotypes and drug response to account for phenotypic variations of clinical importance in drug therapy. The convergence of pharmacogenetics and human genomics in recent years has dramatically accelerated the discovery of new genetic variations that potentially underlie variability in drug response, giving birth to pharmacogenomics. In addition to the rapid accumulation of knowledge on genome-disease and genome-drug interactions, there arises the hope of individualized medicine. Here we review recent progress in the understanding of genetic contributions to major individual variability in drug therapy with focus on genetic variations of drug target, drug metabolism, drug transport, disease susceptibility, and drug safety. Challenges to future pharmacogenomics and its translation into individualized medicine, drug development, and regulation are discussed. For example, knowledge on genetic determinants of disease pathogenesis and drug action, especially those of complex disease and drug response, is not always available. Relating the many gene variations from genomic sequencing to clinical phenotypes may not be straightforward. It is often very challenging to conduct large scale, prospective studies to establish causal associations between genetic variations and drug response or to evaluate the utility and cost-effectiveness of genomic medicine. Overcoming the obstacles holds promise for achieving the ultimate goal of effective and safe medication to targeted patients with appropriate genotypes.