Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction of CYP2C9, HLA-A and HLA-B with anti-epileptic drugs.

By developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy, the Dutch Pharmacogenetics Working Group (DPWG) aims to advance the implementation of pharmacogenetics (PGx). This guideline outlines the gene-drug interaction of CYP2C9 and HLA-B with phenytoin, HLA-A and HLA-B with carbamazepine and HLA-B with oxcarbazepine and lamotrigine. A systematic review was performed and pharmacotherapeutic recommendations were developed. For CYP2C9 intermediate and poor metabolisers, the DPWG recommends lowering the daily dose of phenytoin and adjust based on effect and serum concentration after 7-10 days. For HLA-B*15:02 carriers, the risk of severe cutaneous adverse events associated with phenytoin, carbamazepine, oxcarbazepine, and lamotrigine is strongly increased. For carbamazepine, this risk is also increased in HLA-B*15:11 and HLA-A*31:01 carriers. For HLA-B*15:02, HLA-B*15:11 and HLA-A*31:01 positive patients, the DPWG recommends choosing an alternative anti-epileptic drug. If not possible, it is recommended to advise the patient to report any rash while using carbamazepine, lamotrigine, oxcarbazepine or phenytoin immediately. Carbamazepine should not be used in an HLA-B*15:02 positive patient. DPWG considers CYP2C9 genotyping before the start of phenytoin "essential" for toxicity prevention. For patients with an ancestry in which the abovementioned HLA-alleles are prevalent, the DPWG considers HLA-B*15:02 genotyping before the start of carbamazepine, phenytoin, oxcarbazepine, and lamotrigine "beneficial", as well as genotyping for HLA-B*15:11 and HLA-A*31:01 before initiating carbamazepine.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2D6, CYP3A4 and CYP1A2 and antipsychotics.

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to optimize pharmacotherapy. A guideline describing the gene-drug interaction between the genes CYP2D6, CYP3A4 and CYP1A2 and antipsychotics is presented here. The DPWG identified gene-drug interactions that require therapy adjustments when respective genotype is known for CYP2D6 with aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol, and for CYP3A4 with quetiapine. Evidence-based dose recommendations were obtained based on a systematic review of published literature. Reduction of the normal dose is recommended for aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol for CYP2D6-predicted PMs, and for pimozide and zuclopenthixol also for CYP2D6 IMs. For CYP2D6 UMs, a dose increase or an alternative drug is recommended for haloperidol and an alternative drug or titration of the dose for risperidone. In addition, in case of no or limited clinical effect, a dose increase is recommended for zuclopenthixol for CYP2D6 UMs. Even though evidence is limited, the DPWG recommends choosing an alternative drug to treat symptoms of depression or a dose reduction for other indications for quetiapine and CYP3A4 PMs. No therapy adjustments are recommended for the other CYP2D6 and CYP3A4 predicted phenotypes. In addition, no action is required for the gene-drug combinations CYP2D6 and clozapine, flupentixol, olanzapine or quetiapine and also not for CYP1A2 and clozapine or olanzapine. For identified gene-drug interactions requiring therapy adjustments, genotyping of CYP2D6 or CYP3A4 prior to treatment should not be considered for all patients, but on an individual patient basis only.

Personal Genomes in Practice: Exploring Citizen and Healthcare Professionals' Perspectives on Personalized Genomic Medicine and Personal Health Data Spaces Using a Mixed-Methods Design.

Ongoing health challenges, such as the increased global burden of chronic disease, are increasingly answered by calls for personalized approaches to healthcare. Genomic medicine, a vital component of these personalization strategies, is applied in risk assessment, prevention, prognostication, and therapeutic targeting. However, several practical, ethical, and technological challenges remain. Across Europe, Personal Health Data Space (PHDS) projects are under development aiming to establish patient-centered, interoperable data ecosystems balancing data access, control, and use for individual citizens to complement the research and commercial focus of the European Health Data Space provisions. The current study explores healthcare users' and health care professionals' perspectives on personalized genomic medicine and PHDS solutions, in casu the Personal Genetic Locker (PGL). A mixed-methods design was used, including surveys, interviews, and focus groups. Several meta-themes were generated from the data: (i) participants were interested in genomic information; (ii) participants valued data control, robust infrastructure, and sharing data with non-commercial stakeholders; (iii) autonomy was a central concern for all participants; (iv) institutional and interpersonal trust were highly significant for genomic medicine; and (v) participants encouraged the implementation of PHDSs since PHDSs were thought to promote the use of genomic data and enhance patients' control over their data. To conclude, we formulated several facilitators to implement genomic medicine in healthcare based on the perspectives of a diverse set of stakeholders.

Dutch pharmacogenetics working group (DPWG) guideline for the gene-drug interaction of CYP2D6 and COMT with atomoxetine and methylphenidate.

Pharmacogenetics (PGx) studies the effect of heritable genetic variation on drug response. Clinical adoption of PGx has remained limited, despite progress in the field. To promote implementation, the Dutch Pharmacogenetics Working Group (DPWG) develops evidence-based guidelines on how to optimize pharmacotherapy based on PGx test results. This guideline describes optimization of atomoxetine therapy based on genetic variation in the CYP2D6 gene. The CYP2D6 enzyme is involved in conversion of atomoxetine into the metabolite 4-hydroxyatomoxetine. With decreasing CYP2D6 enzyme activity, the exposure to atomoxetine and the risk of atomoxetine induced side effects increases. So, for patients with genetically absent CYP2D6 enzyme activity (CYP2D6 poor metabolisers), the DPWG recommends to start with the normal initial dose, bearing in mind that increasing this dose probably will not be required. In case of side effects and/or a late response, the DPWG recommends to reduce the dose and check for sustained effectiveness for both poor metabolisers and patients with genetically reduced CYP2D6 enzyme activity (CYP2D6 intermediate metabolisers). Extra vigilance for ineffectiveness is required in patients with genetically increased CYP2D6 enzyme activity (CYP2D6 ultra-rapid metabolisers). No interaction was found between the CYP2D6 and COMT genes and methylphenidate. In addition, no interaction was found between CYP2D6 and clonidine, confirming the suitability of clonidine as a possible alternative for atomoxetine in variant CYP2D6 metabolisers. The DPWG classifies CYP2D6 genotyping as being "potentially beneficial" for atomoxetine. CYP2D6 testing prior to treatment can be considered on an individual patient basis.

Dutch pharmacogenetics working group (DPWG) guideline for the gene-drug interaction between UGT1A1 and irinotecan.

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate PGx implementation by developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy. This guideline describes the starting dose optimization of the anti-cancer drug irinotecan to decrease the risk of severe toxicity, such as (febrile) neutropenia or diarrhoea. Uridine diphosphate glucuronosyl transferase 1A1 (UGT1A1 encoded by the UGT1A1 gene) enzyme deficiency increases risk of irinotecan-induced toxicity. Gene variants leading to UGT1A1 enzyme deficiency (e.g. UGT1A1*6, *28 and *37) can be used to optimize an individual's starting dose thereby preventing carriers from toxicity. Homozygous or compound heterozygous carriers of these allele variants are defined as UGT1A1 poor metabolisers (PM). DPWG recommends a 70% starting dose in PM patients and no dose reduction in IM patients who start treatment with irinotecan. Based on the DPWG clinical implication score, UGT1A1 genotyping is considered "essential", indicating that UGT1A1 testing must be performed prior to initiating irinotecan treatment.

Hemoglobinopathy screening in primary care in the Netherlands: exploring the problems and needs of patients and general practitioners.

The prevalence of hemoglobinopathies in The Netherlands is increasing due to migration. Hemoglobinopathies are severe hereditary diseases. An informed reproductive choice by at-risk couples, such as pre-implantation diagnosis or termination of affected pregnancies, can be made if carriers are detected prior to conception. Using a qualitative design, the needs and wishes of patients, carriers and general practitioners were evaluated regarding carrier detection of hemoglobinopathies in primary care practice. 30 semi-structured interviews were established with 10 general practitioners, 10 patients and 10 carriers. The interviews were audio-recorded, transcribed verbatim and analysed using content analysis to identify recurring themes. Three themes were generated regarding carrier detection of hemoglobinopathies: (1) a need for more information about hemoglobinopathy, (2) a need for indications when to refer for analysis (carrier diagnostics) and (3) insight concerning organization and roles in care for hemoglobinopathy carriers and patients. These themes reflected a need to increase awareness of hemoglobinopathy, improve competences among general practitioners through better education and improvement of communication with patients and their unidentified family members. This study shows the scope of the problem and the critical need for action to improve informed reproductive decision making for the at-risk population.

Dutch pharmacogenetics working group guideline for the gene-drug interaction of ABCG2, HLA-B and Allopurinol, and MTHFR, folic acid and methotrexate.

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate PGx implementation by developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy. This guideline describes the gene-drug interaction of ABCG2 with allopurinol, HLA-B with allopurinol, MTHFR with folic acid, and MTHFR with methotrexate, relevant for the treatment of gout, cancer, and rheumatoid arthritis. A systematic review was performed based on which pharmacotherapeutic recommendations were developed. Allopurinol is less effective in patients with the ABCG2 p.(Gln141Lys) variant. In HLA-B*58:01 carriers, the risk of severe cutaneous adverse events associated with allopurinol is strongly increased. The DPWG recommends using a higher allopurinol dose in patients with the ABCG2 p.(Gln141Lys) variant. For HLA-B*58:01 positive patients the DPWG recommends choosing an alternative (for instance febuxostat). The DPWG indicates that another option would be to precede treatment with allopurinol tolerance induction. Genotyping of ABCG2 in patients starting on allopurinol was judged to be 'potentially beneficial' for drug effectiveness, meaning genotyping can be considered on an individual patient basis. Genotyping for HLA-B*58:01 in patients starting on allopurinol was judged to be 'beneficial' for drug safety, meaning it is advised to consider genotyping the patient before (or directly after) drug therapy has been initiated. For MTHFR-folic acid there is evidence for a gene-drug interaction, but there is insufficient evidence for a clinical effect that makes therapy adjustment useful. Finally, for MTHFR-methotrexate there is insufficient evidence for a gene-drug interaction.

FHH Quick App Review: How Can a Quality Review Process Assist Primary Care Providers in Choosing a Family Health History App for Patient Care?

Family health history (FHH) is a data type serving risk assessment, diagnosis, research, and preventive health. Despite technological leaps in genomic variant detection, FHH remains the most accessible, least expensive, and most practical assessment tool for assessing risks attributable to genetic inheritance. The purpose of this manuscript is to outline a process to assist primary care professionals in choosing FHH digital tools for patient care based on the new ISO/TS 82304-2 Technical Specification (TS), which is a recently developed method to determine eHealth app quality. With a focus on eHealth in primary care, we applied the quality label concept to FHH, and how a primary care physician can quickly review the quality and reliability of an FHH app. Based on our review of the ISO TS's 81 questions, we compiled a list of 25 questions that are recommended to be more succinct as an initial review. We call this process the FHH Quick App Review. Our 'informative-only' 25 questions do not produce a quality score, but a guide to complete an initial review of FHH apps. Most of the questions are straight from the ISO TS, some are modified or de novo. We believe the 25 questions are not only relevant to FHH app reviews but could also serve to aid app development and clinical implementation.

Hemoglobinopathy prevention in primary care: a reflection of underdetection and difficulties with accessibility of medical care, a quantitative study.

As in most Northern European countries, the prevalence of hemoglobinopathies in The Netherlands is increasing due to migration. Although hemoglobinopathies are severe chronic diseases with few treatment options, timely detection of carriers allows at-risk couples to make informed reproductive choices such as pre-implantation diagnosis, prenatal diagnosis or termination of affected pregnancies. Using a quantitative design, we evaluated the prevalence of hemoglobinopathies in The Hague region, The Netherlands. Patient and carrier registries from hospital, laboratory and general practitioners allowed this quantitative analysis. The highest prevalence of hemoglobinopathies was seen in immigrant neighborhoods, and a large gap was noted between estimated carrier prevalence and the actual registration of carriers in electronic patient records. Carrier prevalence was estimated to be 13,704; however, the ELAN database contains only 1542 cases with ICPC codes for sickle cell disease or thalassemia. Although more research is needed to define the requirements of the healthcare system to address this challenge, this study clearly shows the gap between estimated carrier prevalence and registration and thereby the pressing need for action.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2D6 and opioids (codeine, tramadol and oxycodone).

The current Dutch Pharmacogenetics Working Group (DPWG) guideline, describes the gene-drug interaction between CYP2D6 and the opioids codeine, tramadol and oxycodone. CYP2D6 genotype is translated into normal metaboliser (NM), intermediate metaboliser (IM), poor metaboliser (PM) or ultra-rapid metaboliser (UM). Codeine is contraindicated in UM adults if doses >20 mg every 6 h (q6h), in children ≥12 years if doses >10 mg q6h, or with additional risk factors. In PMs, an alternative analgesic should be given which is not or to a lesser extent metabolised by CYP2D6 (not tramadol). In IMs with insufficient analgesia, a higher dose or alternative analgesic should be given. For tramadol, the recommendations for IMs and PMs are the same as the recommendation for codeine and IMs. UMs should receive an alternative drug not or to a lesser extent metabolised by CYP2D6 or the dose should be decreased to 40% of the commonly prescribed dose. Due to the absence of effect on clinical outcomes of oxycodone in PMs, IMs and UMs no action is required. DPWG classifies CYP2D6 genotyping for codeine "beneficial" and recommends testing prior to, or shortly after initiation of treatment in case of higher doses or additional risk factors. CYP2D6 genotyping is classified as "potentially beneficial" for tramadol and can be considered on an individual patient basis.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2C19 and CYP2D6 and SSRIs.

The Dutch Pharmacogenetics Working Group (DPWG) guideline presented here, presents the gene-drug interaction between the genes CYP2C19 and CYP2D6 and antidepressants of the selective serotonin reuptake inhibitor type (SSRIs). Both genes' genotypes are translated into predicted normal metabolizer (NM), intermediate metabolizer (IM), poor metabolizer (PM), or ultra-rapid metabolizer (UM). Evidence-based dose recommendations were obtained, based on a structured analysis of published literature. In CYP2C19 PM patients, escitalopram dose should not exceed 50% of the normal maximum dose. In CYP2C19 IM patients, this is 75% of the normal maximum dose. Escitalopram should be avoided in UM patients. In CYP2C19 PM patients, citalopram dose should not exceed 50% of the normal maximum dose. In CYP2C19 IM patients, this is 70% (65-75%) of the normal maximum dose. In contrast to escitalopram, no action is needed for CYP2C19 UM patients. In CYP2C19 PM patients, sertraline dose should not exceed 37.5% of the normal maximum dose. No action is needed for CYP2C19 IM and UM patients. In CYP2D6 UM patients, paroxetine should be avoided. No action is needed for CYP2D6 PM and IM patients. In addition, no action is needed for the other gene-drug combinations. Clinical effects (increase in adverse events or decrease in efficacy) were lacking for these other gene-drug combinations. DPWG classifies CYP2C19 genotyping before the start of escitalopram, citalopram, and sertraline, and CYP2D6 genotyping before the start of paroxetine as "potentially beneficial" for toxicity/effectivity predictions. This indicates that genotyping prior to treatment can be considered on an individual patient basis.

[Oncogenetics]. / Oncogenetica.

Determining whether a hereditary cancer predisposition is present, is important for both the cancer patient and his family. It is relevant for surveillance and prevention or early detection of new tumours, treatment options and issues surrounding the desire to have children. For this reason, it must be ensured that for every patient with cancer (now or in the past) referral for genetic testing is considered. In this article we indicate how to take a family history and where to find and how to apply referral criteria if such a question arises in clinical practice. The consequences of a genetic diagnosis are illustrated by a breast cancer case.

Modernizing family health history: achievable strategies to reduce implementation gaps.

Family health history (FHH) is a valuable yet underused healthcare tool for assessing health risks for both prevalent disorders like diabetes, cancer, and cardiovascular diseases, and for rare, monogenic disorders. Full implementation of FHH collection and analysis in healthcare could improve both primary and secondary disease prevention for individuals and, through cascade testing, make at risk family members eligible for pre-symptomatic testing and preventative interventions. In addition to risk assessment in the clinic, FHH is increasingly important for interpreting clinical genetic testing results and for research connecting health risks to genomic variation. Despite this value, diverse implementation gaps in clinical settings undermine its potential clinical value and limit the quality of connected health and genomic data. The NHGRI Family Health History Group, an open-membership, US-based group with international members, believes that integrating FHH in healthcare and research is more important than ever, and that achievable implementation advances, including education, are urgently needed to boost the pace of translational utility in genomic medicine. An inventory of implementation gaps and proposed achievable strategies to address them, representing a consensus developed in meetings from 2019-2020, is presented here. The proposed measures are diverse, interdisciplinary, and are guided by experience and ongoing implementation and research efforts.

Using Personal Genomic Data within Primary Care: A Bioinformatics Approach to Pharmacogenomics.

One application of personalized medicine is the tailoring of medication to the individual, so that the medication will have the highest chance of success. In order to individualize medication, one must have a complete inventory of all current pharmaceutical compounds (a detailed formulary) combined with pharmacogenetic datasets, the genetic makeup of the patient, their (medical) family history and other health-related data. For healthcare professionals to make the best use of this information, it must be visualized in a way that makes the most medically relevant data accessible for their decision-making. Similarly, to enable bioinformatics analysis of these data, it must be prepared and provided through an interface for controlled computational analysis. Due to the high degree of personal information gathered for such initiatives, privacy-sensitive implementation choices and ethical standards are paramount. The Personal Genetic Locker project provides an approach to enable the use of personal genomic data in primary care. In this paper, we provide a description of the Personal Genetic Locker project and show its utility through a use case based on open standards, which is illustrated by the 4MedBox system.

SERIES: eHealth in primary care. Part 3: eHealth education in primary care.

BACKGROUND: Education is essential to the integration of eHealth into primary care, but eHealth is not yet embedded in medical education. OBJECTIVES: In this opinion article, we aim to support organisers of Continuing Professional Development (CPD) and teachers delivering medical vocational training by providing recommendations for eHealth education. First, we describe what is required to help primary care professionals and trainees learn about eHealth. Second, we elaborate on how eHealth education might be provided. DISCUSSION: We consider four essential topics. First, an understanding of existing evidence-based eHealth applications and conditions for successful development and implementation. Second, required digital competencies of providers and patients. Third, how eHealth changes patient-provider and provider-provider relationships and finally, understanding the handling of digital data. Educational activities to address these topics include eLearning, blended learning, courses, simulation exercises, real-life practice, supervision and reflection, role modelling and community of practice learning. More specifically, a CanMEDS framework aimed at defining curriculum learning goals can support eHealth education by describing roles and required competencies. Alternatively, Kern's conceptual model can be used to design eHealth training programmes that match the educational needs of the stakeholders using eHealth. CONCLUSION: Vocational and CPD training in General Practice needs to build on eHealth capabilities now. We strongly advise the incorporation of eHealth education into vocational training and CPD activities, rather than providing it as a separate single module. How learning goals and activities take shape and how competencies are evaluated clearly requires further practice, evaluation and study.

SERIES: eHealth in primary care. Part 2: Exploring the ethical implications of its application in primary care practice.

Background: eHealth promises to increase self-management and personalised medicine and improve cost-effectiveness in primary care. Paired with these promises are ethical implications, as eHealth will affect patients' and primary care professionals' (PCPs) experiences, values, norms, and relationships.Objectives: We argue what ethical implications related to the impact of eHealth on four vital aspects of primary care could (and should) be anticipated.Discussion: (1) EHealth influences dealing with predictive and diagnostic uncertainty. Machine-learning based clinical decision support systems offer (seemingly) objective, quantified, and personalised outcomes. However, they also introduce new loci of uncertainty and subjectivity. The decision-making process becomes opaque, and algorithms can be invalid, biased, or even discriminatory. This has implications for professional responsibilities and judgments, justice, autonomy, and trust. (2) EHealth affects the roles and responsibilities of patients because it can stimulate self-management and autonomy. However, autonomy can also be compromised, e.g. in cases of persuasive technologies and eHealth can increase existing health disparities. (3) The delegation of tasks to a network of technologies and stakeholders requires attention for responsibility gaps and new responsibilities. (4) The triangulate relationship: patient-eHealth-PCP requires a reconsideration of the role of human interaction and 'humanness' in primary care as well as of shaping Shared Decision Making.Conclusion: Our analysis is an essential first step towards setting up a dedicated ethics research agenda that should be examined in parallel to the development and implementation of eHealth. The ultimate goal is to inspire the development of practice-specific ethical recommendations.