Personalized medicine: Genetic risk prediction of drug response

Elucidation of novel SNPs affecting immune response to classical swine fever vaccination in pigs using immunogenomics approach

The host genetic makeup plays a significant role in causing the within-breed variation among individuals after vaccination. The present study was undertaken to elucidate the genetic basis of differential immune response between high and low responder Landlly (Landrace X Ghurrah) piglets vis-à-vis CSF vaccination. For the purpose, E2 antibody response against CSF vaccination was estimated in sampled animals on the day of vaccination and 21-day post-vaccination as a measure of humoral immune response. Double-digestion restriction associated DNA (ddRAD) sequencing was undertaken on 96 randomly chosen Landlly piglets using Illumina HiSeq platform. SNP markers were called using standard methodology. Genome-wide association study (GWAS) was undertaken in PLINK program to identify the informative SNP markers significantly associated with differential immune response. The results revealed significant SNPs associated with E2 antibody response against CSF vaccination. The genome-wide informative SNPs for the humoral immune response against CSF vaccination were located on SSC10, SSC17, SSC9, SSC2, SSC3 and SSC6. The overlapping and flanking genes (500Kb upstream and downstream) of significant SNPs were CYB5R1, PCMTD2, WT1, IL9R, CD101, TMEM64, TLR6, PIGG, ADIPOR1, PRSS37, EIF3M, and DNAJC24. Functional enrichment and annotation analysis were undertaken for these genes in order to gain maximum insights into the association of these genes with immune system functionality in pigs. The genetic makeup was associated with differential immune response against CSF vaccination in Landlly piglets while the identified informative SNPs may be used as suitable markers for determining variation in host immune response against CSF vaccination in pigs.

Pharmacogenomics of Preeclampsia therapies: Current evidence and future challenges for clinical implementation

Preeclampsia is a pregnancy-specific disorder, and it is a leading cause of maternal and perinatal morbidity and mortality. The application of pharmacogenetics to antihypertensive agents and dose selection in women with preeclampsia is still in its infancy. No current prescribing guidelines from the clinical pharmacogenetics implementation consortium (CPIC) exist for preeclampsia. Although more studies on pharmacogenomics are underway, there is some evidence for the pharmacogenomics of preeclampsia therapies, considering both the pharmacokinetic (PK) and pharmacodynamic (PD) properties of drugs used in preeclampsia. It has been revealed that the CYP2D6*10 variant is significantly higher in women with preeclampsia who are non-responsive to labetalol compared to those who are in the responsive group. Various genetic variants of PD targets, i.e., NOS3, MMP9, MMP2, TIMP1, TIMP3, VEGF, and NAMPT, have been investigated to assess the responsiveness of antihypertensive therapies in preeclampsia management, and they indicated that certain genetic variants of MMP9, TIMP1, and NAMPT are more frequently observed in those who are non-responsive to anti-hypertensive therapies compared to those who are responsive. Further, gene-gene interactions have revealed that NAMPT, TIMP1, and MMP2 genotypes are associated with an increased risk of preeclampsia, and they are more frequently observed in the non-responsive subgroup of women with preeclampsia. The current evidence is not rigorous enough for clinical implementation; however, an institutional or regional-based retrospective analysis of audited data may help close the knowledge gap during the transitional period from a traditional approach (a "one-size-fits-all" strategy) to the pharmacogenomics of preeclampsia therapies.

Gene-Environment Interactions: My Unique Journey

I am deeply honored to be invited to write this scientific autobiography. As a physician-scientist, pediatrician, molecular biologist, and geneticist, I have authored/coauthored more than 600 publications in the fields of clinical medicine, biochemistry, biophysics, pharmacology, drug metabolism, toxicology, molecular biology, cancer, standardized gene nomenclature, developmental toxicology and teratogenesis, mouse genetics, human genetics, and evolutionary genomics. Looking back, I think my career can be divided into four distinct research areas, which I summarize mostly chronologically in this article: (a) discovery and characterization of the AHR/CYP1 axis, (b) pharmacogenomics and genetic prediction of response to drugs and other environmental toxicants, (c) standardized drug-metabolizing gene nomenclature based on evolutionary divergence, and (d) discovery and characterization of the SLC39A8 gene encoding the ZIP8 metal cation influx transporter. Collectively, all four topics embrace gene-environment interactions, hence the title of my autobiography.

A model for the return and referral of all clinically significant secondary findings of genomic sequencing

Secondary findings (SFs) identified through genomic sequencing (GS) can offer a wide range of health benefits to patients. Resource and capacity constraints pose a challenge to their clinical management; therefore, clinical workflows are needed to optimise the health benefits of SFs. In this paper, we describe a model we created for the return and referral of all clinically significant SFs, beyond medically actionable results, from GS. As part of a randomised controlled trial evaluating the outcomes and costs of disclosing all clinically significant SFs from GS, we consulted genetics and primary care experts to determine a feasible workflow to manage SFs. Consensus was sought to determine appropriate clinical recommendations for each category of SF and which clinician specialist would provide follow-up care. We developed a communication and referral plan for each category of SFs. This involved referrals to specialised clinics, such as an Adult Genetics clinic, for highly penetrant medically actionable findings. Common and non-urgent SFs, such as pharmacogenomics and carrier status results for non-family planning participants, were directed back to the family physician (FP). SF results and recommendations were communicated directly to participants to respect autonomy and to their FPs to support follow-up of SFs. We describe a model for the return and referral of all clinically significant SFs to facilitate the utility of GS and promote the health benefits of SFs. This may serve as a model for others returning GS results transitioning participants from research to clinical settings.

A personalized pharmaco-epistatic network model of precision medicine

Precision medicine, the utilization of targeted treatments to address an individual's disease, relies on knowledge about the genetic cause of that individual's drug response. Here, we present a functional graph (FunGraph) theory to chart comprehensive pharmacogenetic architecture for each and every patient. FunGraph is the combination of functional mapping - a dynamic model for genetic mapping and evolutionary game theory guiding interactive strategies. It coalesces all pharmacogenetic factors into multilayer and multiplex networks that fully capture bidirectional, signed and weighted epistasis. It can visualize and interrogate how epistasis moves in the cell and how this movement leads to patient- and context-specific genetic architecture in response to organismic physiology. We discuss the future implementation of FunGraph to achieve precision medicine. Teaser: We present a functional graph (FunGraph) theory to draw a complete picture of pharmacogenetic architecture underlying interindividual variability in drug response. FunGraph can characterize how each gene acts and interacts with every other gene to mediate therapeutic response.

Unlocking Genetic Profiles with a Programmable DNA-Powered Decoding Circuit

Human genetic architecture provides remarkable insights into disease risk prediction and personalized medication. Advances in genomics have boosted the fine-mapping of disease-associated genetic variants across human genome. In healthcare practice, interpreting intricate genetic profiles into actionable medical decisions can improve health outcomes but remains challenging. Here an intelligent genetic decoder is engineered with programmable DNA computation to automate clinical analyses and interpretations. The DNA-based decoder recognizes multiplex genetic information by one-pot ligase-dependent reactions and interprets implicit genetic profiles into explicit decision reports. It is shown that the DNA decoder implements intended computation on genetic profiles and outputs a corresponding answer within hours. Effectiveness in 30 human genomic samples is validated and it is shown that it achieves desirable performance on the interpretation of CYP2C19 genetic profiles into drug responses, with accuracy equivalent to that of Sanger sequencing. Circuit modules of the DNA decoder can also be readily reprogrammed to interpret another pharmacogenetics genes, provide drug dosing recommendations, and implement reliable molecular calculation of polygenic risk score (PRS) and PRS-informed cancer risk assessment. The DNA-powered intelligent decoder provides a general solution to the translation of complex genetic profiles into actionable healthcare decisions and will facilitate personalized healthcare in primary care.

Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology

More information about a person's genetic makeup, drug response, multi-omics response, and genomic response is now available leading to a gradual shift towards personalized treatment. Additionally, the promotion of non-animal testing has fueled the computational toxicogenomics as a pivotal part of the next-gen risk assessment paradigm. Artificial Intelligence (AI) has the potential to provid new ways analyzing the patient data and making predictions about treatment outcomes or toxicity. As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. AI can process and integrate a multitude of data including genome data, patient records, clinical data and identify patterns to derive predictive models anticipating clinical outcomes and assessing the risk of any personalized medicine approaches. In this article, we have studied the current trends and future perspectives in personalized medicine & toxicology, the role of toxicogenomics in connecting the two fields, and the impact of AI on personalized medicine & toxicology. In this work, we also study the key challenges and limitations in personalized medicine, toxicogenomics, and AI in order to fully realize their potential.

Development of the pharmacogenomics and genomics literacy framework for pharmacists

BACKGROUND

Pharmacists play a unique role in integrating genomic medicine and pharmacogenomics into the clinical practice and to translate pharmacogenomics from bench to bedside. However, the literature suggests that the knowledge gap in pharmacogenomics is a major challenge; therefore, developing pharmacists' skills and literacy to achieve this anticipated role is highly important. We aim to conceptualize a personalized literacy framework for the adoption of genomic medicine and pharmacogenomics by pharmacists in the United Arab Emirates with possible regional and global relevance.

RESULTS

A qualitative approach using focus groups was used to design and to guide the development of a pharmacogenomics literacy framework. The Health Literacy Skills framework was used as a guide to conceptualize the pharmacogenomics literacy for pharmacists. The framework included six major components with specific suggested factors to improve pharmacists' pharmacogenomics literacy. Major components include individual inputs, demand, skills, knowledge, attitude and sociocultural factors.

CONCLUSION

This framework confirms a holistic bottom-up approach toward the implementation of pharmacogenomics. Personalized medicine entails personalized efforts and frameworks. Similar framework can be created for other healthcare providers, patients and stakeholders.

Characterization of Pharmacogenetic Information in Food and Drug Administration Drug Labeling and the Table of Pharmacogenetic Associations

BACKGROUND

The US Food and Drug Administration (FDA) recommends using only FDA-reviewed pharmacogenetic information to make prescribing decisions based on genetic test results. Such information is available in drug labeling and in the Table of Pharmacogenetic Associations ("Associations table").

OBJECTIVE

To compile a list of drug-gene pairs from drug labeling and the Associations table and categorize the pharmacogenetic information and clinical outcome associated with each drug-gene pair.

METHODS

This was a cross-sectional analysis of pharmacogenetic information in the Associations table and individual drug labeling in March 2020. We used the Table of Pharmacogenomic Biomarkers in Drug Labeling to identify drug labels to review. We categorized the pharmacogenetic information for each drug-gene pair according to whether the purpose was to describe (1) polymorphisms affecting drug disposition (metabolism or transport), (2) polymorphisms affecting a direct drug target, (3) variants associated with adverse drug reaction (ADR) susceptibility, (4) variants associated with therapeutic failure, (5) a biomarker-defined indication, or (6) a biomarker-defined ADR. We also categorized the clinical outcome-efficacy, safety, or unknown-associated with each drug-gene pair. We reported counts and proportions of drug-gene pairs in each pharmacogenetic information and clinical outcome category.

RESULTS

We identified 308 drug-gene pairs, of which 36% were associated with a biomarker-defined drug indication, 33% with polymorphic drug metabolism, and 28% with ADR susceptibility. Most drug-gene pairs (n = 267, 87%) were associated with an efficacy or safety-related outcome.

CONCLUSION AND RELEVANCE

FDA-reviewed pharmacogenetic information is available for more than 300 drug-gene pairs and can help guide prescribing decisions.

How is safety of dermatology drugs assessed: trials, registries, and spontaneous reporting

Introduction: Skin conditions are common and highly varied in their etiology; therefore, a diverse array of therapeutics are utilized. Drug safety studies in dermatology can be challenging as there are over 3000 diagnoses to consider. As a result, dermatologists rely on data from multiple sources including clinical trials and real-world evidence.Areas covered: In this review, we cover the main sources of safety data available, their strengths and weaknesses and how dermatologists should utilize such data. We use real-world examples of the different types of adverse events reported and how they are best captured by either randomized controlled trials or post-marketing pharmacovigilance methods. With multiple new therapies in dermatology, such as dupilumab for atopic dermatitis and janus-kinase inhibitors for alopecia areata the specialty is awash with evolving high-level evidence for their use. It is important to understand the optimal way to assess safety from trials but also appreciate the need for ongoing capture of safety data in clinical practice.Expert opinion: In dermatology, there is a plethora of conditions to treat and clinical trials, post-marketing surveillance, such as drug registries and spontaneous reporting, all enable dermatologists to gain a more comprehensive understanding of the safety profiles of drugs being used.

Direct-to-Consumer Nutrigenetics Testing: An Overview

At present, specialized companies offering genetic testing services without the involvement of clinicians are growing; this development is a direct consequence of the significant decrease in genotyping and sequencing costs. Online companies offer predictions about the risk of developing complex diseases during one's life course, and they offer suggestions for personal lifestyle. Several companies have been created that provide nutrigenetics services; these companies suggest dietary indications-a central issue in the prevention and etiopathogenesis of specific diseases-based on one's personal genetic background. Dietary patterns are defined on the basis of a limited set of genetic markers. In this article, we analyze the online nutrigenetics services offered by 45 companies worldwide, to obtain an overall picture of the costs, the types of nutritional traits considered and the level of scientific precision of the services proposed. Our analysis clearly highlights the need for specific guidelines, in order to ensure a set of minimum quality standards for the nutrigenetics services offered to the customer.

Adverse Drug Reactions Across the Age Continuum: Epidemiology, Diagnostic Challenges, Prevention, and Treatments

Adverse drug reactions (ADRs) are common and important complications of drug therapy for children. The risk for ADRs changes over childhood, as do the nature and types of ADRs. Importantly, the risk and nature of ADRs in children are markedly different from those of adults, and adult data cannot be relied on to guide safe drug therapy in children. There are groups of children, notably those with complex and chronic diseases, who are at substantial risk for ADRs. The evaluation of an undesired effect during therapy is ideally accomplished by an organized approach that is a skill that clinicians who care for children-especially those children at high risk for ADRs must have. Additionally, clinicians as well as drug regulatory agencies and industry need to be both vigilant and astute as well as aware that ADRs in children are often different in nature and frequency from those in adults. The increasing use of pharmacogenomics to guide drug dosing and the increasing number of biological agents will provide new sets of challenges to clinicians over the next decade.

Cytochrome P450: genotype to phenotype

The cytochromes P450 comprise a family of enzymes that are responsible for around three-quarters of all drug metabolism reactions that occur in human populations. Many isoforms of cytochrome P450 exist but most reactions are undertaken by CYP2C9, CYP2C19, CYP2D6 and CYP3A4. This brief review focusses on the first three isozymes which exhibit polymorphism of phenotype.If there is a wide variation in drug metabolising capacity within the population, this may precipitate clinical consequences and influence the drug treatment of patients. Such problems range from a lack of efficacy to unanticipated toxicity. In order to minimise untoward events and "personalise" a patient's treatment, efforts have been made to discover an individual's drug metabolism status. This requires knowledge of the subject's phenotype at the time of clinical treatment. Since such testing is difficult, time-consuming and costly, the simpler approach of genotyping has been advocated.However, the correlation between genotype and phenotype is not good, with values of up to 50% misprediction being reported. Genotype-assisted forecasts cannot therefore be used with confidence to replace actual phenotype measurements. Obfuscating factors discussed include gene splicing, single nucleotide polymorphisms, epigenetics and microRNA, transcription regulation and multiple gene copies.

Impact of Polypharmacy on Candidate Biomarker miRNomes for the Diagnosis of Fibromyalgia and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Striking Back on Treatments

Fibromyalgia (FM) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) are diseases of unknown etiology presenting complex and often overlapping symptomatology. Despite promising advances on the study of miRNomes of these diseases, no validated molecular diagnostic biomarker yet exists. Since FM and ME/CFS patient treatments commonly include polypharmacy, it is of concern that biomarker miRNAs are masked by drug interactions. Aiming at discriminating between drug-effects and true disease-associated differential miRNA expression, we evaluated the potential impact of commonly prescribed drugs on disease miRNomes, as reported by the literature. By using the web search tools SM2miR, Pharmaco-miR, and repoDB, we found a list of commonly prescribed drugs that impact FM and ME/CFS miRNomes and therefore could be interfering in the process of biomarker discovery. On another end, disease-associated miRNomes may incline a patient’s response to treatment and toxicity. Here, we explored treatments for diseases in general that could be affected by FM and ME/CFS miRNomes, finding a long list of them, including treatments for lymphoma, a type of cancer affecting ME/CFS patients at a higher rate than healthy population. We conclude that FM and ME/CFS miRNomes could help refine pharmacogenomic/pharmacoepigenomic analysis to elevate future personalized medicine and precision medicine programs in the clinic.

Epigenetics and MicroRNAs in Pharmacogenetics

Germline pharmacogenetics has so far mainly studied common variants in "pharmacogenes," i.e., genes encoding drug metabolizing enzymes and transporters (DMET genes), certain auxiliary and regulatory genes, and drug target genes. Despite remarkable progress in understanding genetically determined differences in pharmacokinetics and pharmacodynamics of drugs, currently known common variants even in important pharmacogenes explain genetic variability only partially. This suggests "missing heritability" that may in part be due to rare variants in the classical pharmacogenes, but current evidence suggests that largely unexplored resources with potential for pharmacogenetics exist, both within already known pharmacogenes and in entirely new areas. In particular, recent studies suggest that epigenetic processes and noncoding RNAs, including mostly microRNAs (miRNAs), represent important and largely unexplored layers of DMET gene regulation that may fill some of the gaps in understanding interindividual variability and lead to new biomarkers. In this chapter we summarize recent advances in the understanding of genetic variability in epigenetic and miRNA-mediated processes with focus on their significance for DMET regulation and pharmacokinetic or pharmacological endpoints.

Patient perspectives following pharmacogenomics results disclosure in an integrated health system

Aim: To assess patient perceptions and utilization of pharmacogenomics (PGx) testing in an integrated community health system. Methods: Fifty-seven patients completed an online survey assessing their experiences with PGx testing offered through two methods: a designated PGx clinic or direct access in-home testing. Results: The majority of participants perceived PGx testing as helpful in their healthcare and reported understanding their results. Some had concerns about privacy and discrimination; most lacked familiarity with the Genetic Information Nondiscrimination Act. There were no significant differences in views between participants tested through either model. Conclusion: Participants reported value in both methods of PGx testing. Patient experiences, understanding and result utilization will play an important role in informing future development and implementation of PGx programs.

The aryl hydrocarbon receptor in the crossroad of signalling networks with therapeutic value

The aryl hydrocarbon receptor (AhR) is well-known for its major contributions to the cellular responses against environmental toxins and carcinogens. Notably, AhR has also emerged as a key transcription factor controlling many physiological processes including cell proliferation and apoptosis, differentiation, adhesion and migration, pluripotency and stemness. These novel functions have broadened our understanding of the signalling pathways and molecular intermediates interacting with AhR under both homeostatic and pathological conditions. Recent discoveries link AhR with the function of essential organs such as liver, skin and gonads, and with complex organismal structures including the immune and cardiovascular systems. The identification of potential endogenous ligands able to regulate AhR activity, opens the possibility of designing ad hoc molecules with pharmacological and/or therapeutic value to treat human diseases in which AhR may have a causal role. Integration of experimental data from in vitro and in vivo studies with "omic" analyses of human patients affected with cancer, immune diseases, inflammation or neurological disorders will likely contribute to validate the clinical relevance of AhR and the possible benefits of modulating its activity by pharmacologically-driven strategies. In this review, we will highlight signalling pathways involved in human diseases that could be targetable by AhR modulators and discuss the feasibility of using such molecules in therapy. The pros and cons of AhR-aimed approaches will be also mentioned.

Primary care physician experiences with integrated pharmacogenomic testing in a community health system

Aim: To explore primary care physicians’ views of the utility and delivery of direct access to pharmacogenomics (PGx) testing in a community health system. Methods: This descriptive study assessed the perspectives of 15 healthcare providers utilizing qualitative individual interviews. Results: Three main themes emerged: perceived value and utility of PGx testing; challenges to implementation in practice; and provider as well as patient needs. Conclusion: While providers in this study viewed benefits of PGx testing as avoiding side effects, titrating doses more quickly, improving shared decision-making and providing psychological reassurance, challenges will need to be addressed such as privacy concerns, cost, insurance coverage and understanding the complexity of PGx test results.

Perspective on the Genetic Response to Antiparasitics: A Review Article

BACKGROUND

Drugs' pharmacokinetics and pharmacodynamics can be affected by diverse genetic variations, within which simple nucleotide polymorphisms (SNPs) are the most common. Genetic variability is one of the factors that could explain questions like why a given drug does not have the desired effect or why do adverse drug reactions arise.

METHODS

In this retrospective observational study, literature search limits were set within PubMed database as well as the epidemiological bulletins published by the Mexican Ministry of Health, from Jan 1st 2001 to Mar 31st 2017 (16 years).

RESULTS

Metabolism of antiparasitic drugs and their interindividual responses are mainly modified by variations in cytochrome P450 enzymes. These enzymes show high frequencies of polymorphic variability thus affecting the expression of CYP2C, CYP2A, CYP2A6, CYP2D6, CYP2E6 and CYP2A6 isoforms. Research in this field opens the door to new personalized treatment approaches in medicine.

CONCLUSION

Clinical and pharmacological utility yield by applying pharmacogenetics to antiparasitic treatments is not intended as a mean to improve the prescription process, but to select or exclude patients that could present adverse drug reactions as well as to evaluate genetic alterations which result in a diversity of responses, ultimately seeking to provide a more effective and safe treatment; therefore choosing a proper dose for the appropriate patient and the optimal treatment duration. Furthermore, pharmacogenetics assists in the development of vaccines. In other words, the aim of this discipline is to find therapeutic targets allowing personalized treatments.