Pharmacogenomics: current status and future perspectives.

Inter-individual variability in drug response, be it efficacy or safety, is common and likely to become an increasing problem globally given the growing elderly population requiring treatment. Reasons for this inter-individual variability include genomic factors, an area of study called pharmacogenomics. With genotyping technologies now widely available and decreasing in cost, implementing pharmacogenomics into clinical practice - widely regarded as one of the initial steps in mainstreaming genomic medicine - is currently a focus in many countries worldwide. However, major challenges of implementation lie at the point of delivery into health-care systems, including the modification of current clinical pathways coupled with a massive knowledge gap in pharmacogenomics in the health-care workforce. Pharmacogenomics can also be used in a broader sense for drug discovery and development, with increasing evidence suggesting that genomically defined targets have an increased success rate during clinical development.

HLA Allele-Restricted Immune-Mediated Adverse Drug Reactions: Framework for Genetic Prediction.

Human leukocyte antigen (HLA) is a hallmark genetic marker for the prediction of certain immune-mediated adverse drug reactions (ADRs). Numerous basic and clinical research studies have provided the evidence base to push forward the clinical implementation of HLA testing for the prevention of such ADRs in susceptible patients. This review explores current translational progress in using HLA as a key susceptibility factor for immune ADRs and highlights gaps in our knowledge. Furthermore, relevant findings of HLA-mediated drug-specific T cell activation are covered, focusing on cellular approaches to link genetic associations to drug-HLA binding as a complementary approach to understand disease pathogenesis.

Activation of Human CD8+ T Cells with Nitroso Dapsone-Modified HLA-B*13:01-Binding Peptides.

Previous studies have shown that cysteine-reactive drug metabolites bind covalently with protein to activate patient T cells. However, the nature of the antigenic determinants that interact with HLA and whether T cell stimulatory peptides contain the bound drug metabolite has not been defined. Because susceptibility to dapsone hypersensitivity is associated with the expression of HLA-B*13:01, we have designed and synthesized nitroso dapsone-modified, HLA-B*13:01 binding peptides and explored their immunogenicity using T cells from hypersensitive human patients. Cysteine-containing 9-mer peptides with high binding affinity to HLA-B*13:01 were designed (AQDCEAAAL [Pep1], AQDACEAAL [Pep2], and AQDAEACAL [Pep3]), and the cysteine residue was modified with nitroso dapsone. CD8+ T cell clones were generated and characterized in terms of phenotype, function, and cross-reactivity. Autologous APCs and C1R cells expressing HLA-B*13:01 were used to determine HLA restriction. Mass spectrometry confirmed that nitroso dapsone-peptides were modified at the appropriate site and were free of soluble dapsone and nitroso dapsone. APC HLA-B*13:01-restricted nitroso dapsone-modified Pep1- (n = 124) and Pep3-responsive (n = 48) CD8+ clones were generated. Clones proliferated and secreted effector molecules with graded concentrations of nitroso dapsone-modified Pep1 or Pep3. They also displayed reactivity against soluble nitroso dapsone, which forms adducts in situ, but not with the unmodified peptide or dapsone. Cross-reactivity was observed between nitroso dapsone-modified peptides with cysteine residues in different positions in the peptide sequence. These data characterize a drug metabolite hapten CD8+ T cell response in an HLA risk allele-restricted form of drug hypersensitivity and provide a framework for structural analysis of hapten HLA binding interactions.

DPYD genetic polymorphisms in non-European patients with severe fluoropyrimidine-related toxicity: a systematic review.

BACKGROUND: Pre-treatment DPYD screening is mandated in the UK and EU to reduce the risk of severe and potentially fatal fluoropyrimidine-related toxicity. Four DPYD gene variants which are more prominently found in Europeans are tested. METHODS: Our systematic review in patients of non-European ancestry followed PRISMA guidelines to identify relevant articles up to April 2023. Published in silico functional predictions and in vitro functional data were also extracted. We also undertook in silico prediction for all DPYD variants identified. RESULTS: In 32 studies, published between 1998 and 2022, 53 DPYD variants were evaluated in patients from 12 countries encompassing 5 ethnic groups: African American, East Asian, Latin American, Middle Eastern, and South Asian. One of the 4 common European DPYD variants, c.1905+1G>A, is also present in South Asian, East Asian and Middle Eastern patients with severe fluoropyrimidine-related toxicity. There seems to be relatively strong evidence for the c.557A>G variant, which is found in individuals of African ancestry, but is not currently included in the UK genotyping panel. CONCLUSION: Extending UK pre-treatment DPYD screening to include variants that are present in some non-European ancestry groups will improve patient safety and reduce race and health inequalities in ethnically diverse societies.

A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study.

BACKGROUND: The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed. METHODS: We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants. FINDINGS: Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51·4 % female, 48·6% male; 97·7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1·6%] of the study group and 47 [1·3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11·0%] in the study group and 285 [7·9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21·0%) of 725 patients in the study group and 231 (27·7%) of 833 patients in the control group (odds ratio [OR] 0·70 [95% CI 0·54-0·91]; p=0·0075), whereas for all patients, the incidence was 628 (21·5%) of 2923 patients in the study group and 934 (28·6%) of 3270 patients in the control group (OR 0·70 [95% CI 0·61-0·79]; p <0·0001). INTERPRETATION: Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe. FUNDING: European Union Horizon 2020.

Precision medicine in cardiovascular therapeutics: Evaluating the role of pharmacogenetic analysis prior to drug treatment.

Pharmacogenomics is the examination of how genetic variation influences drug metabolism and response, in terms of both efficacy and safety. In cardiovascular disease, patient-specific diplotypes determine phenotypes, thereby influencing the efficacy and safety of drug treatments, including statins, antiarrhythmics, anticoagulants and antiplatelets. Notably, polymorphisms in key genes, such as CYP2C9, CYP2C19, VKORC1 and SLCO1B1, significantly impact the outcomes of treatment with clopidogrel, warfarin and simvastatin. Furthermore, the CYP2C19 polymorphism influences the pharmacokinetics and safety of the novel hypertrophic cardiomyopathy inhibitor, mavacamten. In this review, we critically assess the clinical application of pharmacogenomics in cardiovascular disease and delineate present and future utilization of pharmacogenomics. This includes insights into identifying missing heritability, the integration of whole genome sequencing and the application of polygenic risk scores to enhance the precision of personalized drug therapy. Our discussion encompasses health economic analyses that underscore the cost benefits associated with pre-emptive genotyping for warfarin and clopidogrel treatments, albeit acknowledging the need for further research in this area. In summary, we contend that cardiovascular pharmacogenomic analyses are underpinned by a wealth of evidence, and implementation is already occurring for some of these gene-drug pairs, but as with any area of medicine, we need to continually gather more information to optimize the use of pharmacogenomics in clinical practice.

Being precise with anticoagulation to reduce adverse drug reactions: are we there yet?

Anticoagulants are potent therapeutics widely used in medical and surgical settings, and the amount spent on anticoagulation is rising. Although warfarin remains a widely prescribed oral anticoagulant, prescriptions of direct oral anticoagulants (DOACs) have increased rapidly. Heparin-based parenteral anticoagulants include both unfractionated and low molecular weight heparins (LMWHs). In clinical practice, anticoagulants are generally well tolerated, although interindividual variability in response is apparent. This variability in anticoagulant response can lead to serious incident thrombosis, haemorrhage and off-target adverse reactions such as heparin-induced thrombocytopaenia (HIT). This review seeks to highlight the genetic, environmental and clinical factors associated with variability in anticoagulant response, and review the current evidence base for tailoring the drug, dose, and/or monitoring decisions to identified patient subgroups to improve anticoagulant safety. Areas that would benefit from further research are also identified. Validated variants in VKORC1, CYP2C9 and CYP4F2 constitute biomarkers for differential warfarin response and genotype-informed warfarin dosing has been shown to reduce adverse clinical events. Polymorphisms in CES1 appear relevant to dabigatran exposure but the genetic studies focusing on clinical outcomes such as bleeding are sparse. The influence of body weight on LMWH response merits further attention, as does the relationship between anti-Xa levels and clinical outcomes. Ultimately, safe and effective anticoagulation requires both a deeper parsing of factors contributing to variable response, and further prospective studies to determine optimal therapeutic strategies in identified higher risk subgroups.

Glycolysis: An early marker for vancomycin-specific T-cell activation.

BACKGROUND: Vancomycin, a glycopeptide antibiotic used for Gram-positive bacterial infections, has been linked with drug reaction with eosinophilia and systemic symptoms (DRESS) in HLA-A*32:01-expressing individuals. This is associated with activation of T lymphocytes, for which glycolysis has been isolated as a fuel pathway following antigenic stimulation. However, the metabolic processes that underpin drug-reactive T-cell activation are currently undefined and may shed light on the energetic conditions needed for the elicitation of drug hypersensitivity or tolerogenic pathways. Here, we sought to characterise the immunological and metabolic pathways involved in drug-specific T-cell activation within the context of DRESS pathogenesis using vancomycin as model compound and drug-reactive T-cell clones (TCCs) generated from healthy donors and vancomycin-hypersensitive patients. METHODS: CD4+ and CD8+ vancomycin-responsive TCCs were generated by serial dilution. The Seahorse XFe96 Analyzer was used to measure the extracellular acidification rate (ECAR) as an indicator of glycolytic function. Additionally, T-cell proliferation and cytokine release (IFN-γ) assay were utilised to correlate the bioenergetic characteristics of T-cell activation with in vitro assays. RESULTS: Model T-cell stimulants induced non-specific T-cell activation, characterised by immediate augmentation of ECAR and rate of ATP production (JATPglyc). There was a dose-dependent and drug-specific glycolytic shift when vancomycin-reactive TCCs were exposed to the drug. Vancomycin-reactive TCCs did not exhibit T-cell cross-reactivity with structurally similar compounds within proliferative and cytokine readouts. However, cross-reactivity was observed when analysing energetic responses; TCCs with prior specificity for vancomycin were also found to exhibit glycolytic switching after exposure to teicoplanin. Glycolytic activation of TCC was HLA restricted, as exposure to HLA blockade attenuated the glycolytic induction. CONCLUSION: These studies describe the glycolytic shift of CD4+ and CD8+ T cells following vancomycin exposure. Since similar glycolytic switching is observed with teicoplanin, which did not activate T cells, it is possible the master switch for T-cell activation is located upstream of metabolic signalling.

Patients with naproxen-induced liver injury display T-cell memory responses toward an oxidative (S)-O-desmethyl naproxen metabolite but not the acyl glucuronide.

BACKGROUND: Exposure to nonsteroidal anti-inflammatory drugs (NSAIDs) such as ibuprofen (IBU) and naproxen (NAP) is associated with idiosyncratic drug-induced liver injury (DILI). Carboxylate bioactivation into reactive metabolites (e.g., acyl glucuronides, AG) and resulting T-cell activation is hypothesized as causal for this adverse event. However, conclusive evidence supporting this is lacking. METHODS: In this work, we identify CD4+ and CD8+ T-cell hepatic infiltration in a biopsy from an IBU DILI patient. Lymphocyte transformation test and IFN-γ ELIspot, conducted on peripheral blood mononuclear cells (PBMCs) of patients with NAP-DILI, were used to explore drug-specific T-cell activation. T-cell clones (TCC) were generated and tested for drug specificity, phenotype/function, and pathways of T-cell activation. Cells were exposed to NAP, its oxidative metabolite 6-O-desmethyl NAP (DM-NAP), its AG or synthesized NAP-AG human-serum albumin adducts (NAP-AG adduct). RESULTS: CD4+ and CD8+ T-cells from patients expressing a range of different Vß receptors were stimulated to proliferate and secrete IFN-γ and IL-22 when exposed to DM-NAP, but not NAP, NAP-AG or the NAP-AG adduct. Activation of the CD4+ TCC was HLA-DQ-restricted and dependent on antigen presenting cells (APC); most TCC were activated with DM-NAP-pulsed APC, while fixation of APC blocked the T-cell response. Cross-reactivity was not observed with structurally-related drugs. CONCLUSION: Our results confirm hepatic T-cell infiltrations in NSAID-induced DILI, and show a T-cell memory response toward DM-NAP indicating an immune-mediated basis for the adverse event. Whilst bioactivation at the carboxylate group is widely hypothesized to be pathogenic for NSAID associated DILI, we found no evidence of this with NAP.

Role of Transporters and Enzymes in Metabolism and Distribution of 4-Chlorokynurenine (AV-101).

4-Chlorokynurenine (4-Cl-KYN, AV-101) is a prodrug of a NMDA receptor antagonist and is in clinical development for potential CNS indications. We sought to further understand the distribution and metabolism of 4-Cl-KYN, as this information might provide a strategy to enhance the clinical development of this drug. We used excretion studies in rats, in vitro transporter assays, and pharmacogenetic analysis of clinical trial data to determine how 4-Cl-KYN and metabolites are distributed. Our data indicated that a novel acetylated metabolite (N-acetyl-4-Cl-KYN) did not affect the uptake of 4-Cl-KYN across the blood-brain barrier via LAT1. 4-Cl-KYN and its metabolites were found to be renally excreted in rodents. In addition, we found that N-acetyl-4-Cl-KYN inhibited renal and hepatic transporters involved in excretion. Thus, this metabolite has the potential to limit the excretion of a range of compounds. Our pharmacogenetic analysis found that a SNP in N-acetyltransferase 8 (NAT8, rs13538) was linked to levels of N-acetyl-4-Cl-KYN relative to 4-Cl-KYN found in the plasma and that a SNP in SLC7A5 (rs28582913) was associated with the plasma levels of the active metabolite, 7-Cl-KYNA. Thus, we have a pharmacogenetics-based association for plasma drug level that could aid in the drug development of 4-Cl-KYN and have investigated the interaction of a novel metabolite with drug transporters.

Adverse drug reactions and hospital admissions: Large case-control study of patients aged 65-100 years using linked English primary care and hospital data.

BACKGROUND: Adverse drug reactions (ADRs) are common and a leading cause of injury. However, information on ADR risks of individual medicines is often limited. The aim of this hypothesis-generating study was to assess the relative importance of ADR-related and emergency hospital admission for large group of medication classes. METHODS: This study was a propensity-matched case-control study in English primary care. Data sources were Clinical Practice Research Databank and Aurum with longitudinal, anonymized, patient level electronic health records (EHRs) from English general practices linked to hospital records. Cases aged 65-100 with ADR-related or emergency hospital admission were matched to up to six controls by age, sex, morbidity and propensity scores for hospital admission risk. Medication groups with systemic administration as listed in the British National Formulary (used by prescribers for medication advice). Prescribing in the 84 days before the index date was assessed. Only medication groups with 50+ cases exposed were analysed. The outcomes of interest were ADR-related and emergency hospital admissions. Conditional logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CI). RESULTS: The overall population included 121 546 cases with an ADR-related and 849 769 cases with emergency hospital admission. The percentage of hospitalizations with an ADR-related code for admission diagnosis was 1.83% and 6.58% with an ADR-related code at any time during hospitalization. A total of 137 medication groups was included in the main ADR analyses. Of these, 13 (9.5%) had statistically non-significant adjusted ORs, 58 (42.3%) statistically significant ORs between 1.0 and 1.5, 37 (27.0%) between 1.5-2.0, 18 (13.1%) between 2.0-3.0 and 11 (8.0%) 3.0 or higher. Several classes of antibiotics (including penicillins) were among medicines with largest ORs. Evaluating the 14 medications most often associated with ADRs, a strong association was found between the number of these medicines and the risk of ADR-related hospital admission (adjusted OR of 7.53 (95% CI 7.15-7.93) for those exposed to 6+ of these medicines). CONCLUSIONS AND RELEVANCE: There is a need for a regular systematic assessment of the harm-benefit ratio of medicines, harvesting the information in large healthcare databases and combining it with causality assessment of individual case histories.

Updates on the immunopathology and genomics of severe cutaneous adverse drug reactions.

Severe cutaneous adverse reactions (SCARs) such as Stevens-Johnson syndrome, toxic epidermal necrolysis (SJS/TEN), and drug reaction with eosinophilia and systemic symptoms (DRESS)/drug-induced hypersensitivity syndrome (DIHS) cause significant morbidity and mortality and impede new drug development. HLA class I associations with SJS/TEN and drug reaction with eosinophilia and systemic symptoms/drug-induced hypersensitivity syndrome have aided preventive efforts and provided insights into immunopathogenesis. In SJS/TEN, HLA class I-restricted oligoclonal CD8+ T-cell responses occur at the tissue level. However, specific HLA risk allele(s) and antigens driving this response have not been identified for most drugs. HLA risk alleles also have incomplete positive and negative predictive values, making truly comprehensive screening currently challenging. Although, there have been key paradigm shifts in knowledge regarding drug hypersensitivity, there are still many open and unanswered questions about SCAR immunopathogenesis, as well as genetic and environmental risk. In addition to understanding the cellular and molecular basis of SCAR at the single-cell level, identification of the MHC-restricted drug-reactive self- or viral peptides driving the hypersensitivity reaction will also be critical to advancing premarketing strategies to predict risk at an individual and drug level. This will also enable identification of biologic markers for earlier diagnosis and accurate prognosis, as well as drug causality and targeted therapeutics.

Assessing the impact of alcohol consumption on the genetic contribution to mean corpuscular volume.

The relationship between the genetic loci that influence mean corpuscular volume (MCV) and those associated with excess alcohol drinking is unknown. We used white British participants from the UK Biobank (n = 362 595) to assess the association between alcohol consumption and MCV, and whether this was modulated by genetic factors. Multivariable regression was applied to identify predictors of MCV. GWAS, with and without stratification for alcohol consumption, determined how genetic variants influence MCV. SNPs in ADH1B, ADH1C and ALDH1B were used to construct a genetic score to test the assumption that acetaldehyde formation is an important determinant of MCV. Additional investigations using Mendelian randomization and phenome-wide association analysis were conducted. Increasing alcohol consumption by 40 g/week resulted in a 0.30% [95% confidence interval CI: 0.30-0.31%] increase in MCV (P < 1.0 × 10-320). Unstratified (irrespective of alcohol intake) GWAS identified 212 loci associated with MCV, of which 108 were novel. There was no heterogeneity of allelic effects by drinking status. No association was found between MCV and the genetic score generated from alcohol metabolizing genes. Mendelian randomization demonstrated a causal effect for alcohol on MCV. Seventy-one SNP-outcome pairs reached statistical significance in phenome-wide association analysis, with evidence of shared genetic architecture for MCV and thyroid dysfunction, and mineral metabolism disorders. MCV increases linearly with alcohol intake in a causal manner. Many genetic loci influence MCV, with new loci identified in this analysis that provide novel biological insights. However, there was no interaction between alcohol consumption and the allelic variants associated with MCV.

Characterization of Drug-Specific CD4+ T-Cells Reveals Possible Roles of HLA Class II in the Pathogenesis of Carbamazepine Hypersensitivity Reactions.

Carbamazepine (CBZ) is an aromatic anticonvulsant known to cause drug hypersensitivity reactions, which range in severity from relatively mild maculopapular exanthema to potentially fatal Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS-TEN). These reactions are known to be associated with human leukocyte antigen (HLA) class I alleles, and CBZ interacts preferentially with the related HLA proteins to activate CD8+ T-cells. This study aimed to evaluate the contribution of HLA class II in the effector mechanism(s) of CBZ hypersensitivity. CBZ-specific T-cells clones were generated from two healthy donors and two hypersensitive patients with high-risk HLA class I markers. Phenotype, function, HLA allele restriction, response pathways, and cross-reactivity of CBZ-specific T-cells were assessed using flow cytometry, proliferation analysis, enzyme-linked immunosorbent spot, and enzyme-linked immunosorbent assay. The association between HLA class II allele restriction and CBZ hypersensitivity was reviewed using Allele Frequency Net Database. Forty-four polyclonal CD4+ CBZ-specific T-cell clones were generated and found to be restricted to HLA-DR, particularly HLA-DRB1*07:01. This CD4+-mediated response proceeded through a direct pharmacological interaction between CBZ and HLA-DR molecules. Similar to the CD8+ response, CBZ-stimulated CD4+ clones secreted granulysin, a key mediator of SJS-TEN. Our database review revealed an association between HLA-DRB1*07:01 and CBZ-induced SJS-TEN. These findings implicate HLA class II antigen presentation as an additional pathogenic factor for CBZ hypersensitivity reactions. Both HLA class II molecules and drug-responsive CD4+ T-cells should be evaluated further to gain better insights into the pathogenesis of drug hypersensitivity reactions.

Analysis of serum microRNA-122 in a randomized controlled trial of N-acetylcysteine for treatment of antituberculosis drug-induced liver injury.

AIM: Serum microRNA-122 (miR-122) is a novel biomarker for drug-induced liver injury, with good sensitivity in the early diagnosis of paracetamol-induced liver injury. We describe miR-122 concentrations in participants with antituberculosis drug-induced liver injury (AT-DILI). We explored the relationship between miR-122 and alanine aminotransferase (ALT) concentrations and the effect of N-acetylcysteine (NAC) on miR-122 concentrations. METHODS: We included participants from a randomized placebo-controlled trial of intravenous NAC in AT-DILI. ALT and miR-122 concentrations were quantified before and after infusion of NAC/placebo. We assessed correlations between ALT and miR-122 concentrations and described changes in ALT and miR-122 concentrations between sampling occasions. RESULTS: We included 45 participants; mean age (± standard deviation) 38 (±10) years, 58% female and 91% HIV positive. The median (interquartile range) time between pre- and post-infusion biomarker specimens was 68 h (47-77 h). The median pre-infusion ALT and miR-122 concentrations were 420 U/L (238-580) and 0.58 pM (0.18-1.47), respectively. Pre-infusion ALT and miR-122 concentrations were correlated (Spearman's ρ = .54, P = .0001). Median fold-changes in ALT and miR-122 concentrations between sampling were 0.56 (0.43-0.69) and 0.75 (0.23-1.53), respectively, and were similar in the NAC and placebo groups (P = .40 and P = .68 respectively). CONCLUSIONS: miR-122 concentrations in our participants with AT-DILI were considerably higher than previously reported in healthy volunteers and in patients on antituberculosis therapy without liver injury. We did not detect an effect of NAC on miR-122 concentrations. Further research is needed to determine the utility of miR-122 in the diagnosis and management of AT-DILI.

Exploring the impact of design criteria for reference sets on performance evaluation of signal detection algorithms: The case of drug-drug interactions.

PURPOSE: To evaluate the impact of multiple design criteria for reference sets that are used to quantitatively assess the performance of pharmacovigilance signal detection algorithms (SDAs) for drug-drug interactions (DDIs). METHODS: Starting from a large and diversified reference set for two-way DDIs, we generated custom-made reference sets of various sizes considering multiple design criteria (e.g., adverse event background prevalence). We assessed differences observed in the performance metrics of three SDAs when applied to FDA Adverse Event Reporting System (FAERS) data. RESULTS: For some design criteria, the impact on the performance metrics was neglectable for the different SDAs (e.g., theoretical evidence associated with positive controls), while others (e.g., restriction to designated medical events, event background prevalence) seemed to have opposing and effects of different sizes on the Area Under the Curve (AUC) and positive predictive value (PPV) estimates. CONCLUSIONS: The relative composition of reference sets can significantly impact the evaluation metrics, potentially altering the conclusions regarding which methodologies are perceived to perform best. We therefore need to carefully consider the selection of controls to avoid misinterpretation of signals triggered by confounding factors rather than true associations as well as adding biases to our evaluation by "favoring" some algorithms while penalizing others.

Interventions for reducing anticholinergic medication burden in older adults-a systematic review and meta-analysis.

INTRODUCTION: Anticholinergic medications block the neurotransmitter acetylcholine in the brain and peripheral nervous system. Many medications have anticholinergic properties, and the cumulative effect of these medications is termed anticholinergic burden. Increased anticholinergic burden can have short-term side effects such as dry mouth, blurred vision and urinary retention as well as long-term effects including dementia, worsening physical function and falls. METHODS: We carried out a systematic review (SR) with meta-analysis (MA) looking at randomised controlled trials addressing interventions to reduce anticholinergic burden in older adults. RESULTS: We identified seven papers suitable for inclusion in our SR and MA. Interventions included multi-disciplinary involvement in medication reviews and deprescribing of AC medications. Pooled data revealed no significant difference in outcomes between control and intervention group for falls (OR = 0.76, 95% CI: 0.52-1.11, n = 647), cognition (mean difference = 1.54, 95% CI: -0.04 to 3.13, n = 405), anticholinergic burden (mean difference = 0.04, 95% CI: -0.11 to 0.18, n = 710) or quality of life (mean difference = 0.04, 95% CI: -0.04 to 0.12, n = 461). DISCUSSION: Overall, there was no significant difference with interventions to reduce anticholinergic burden. As we did not see a significant change in anticholinergic burden scores following interventions, it is likely other outcomes would not change. Short follow-up time and lack of training and support surrounding successful deprescribing may have contributed.

The Implementation of Pharmacogenetics in the United Kingdom.

There is considerable inter-individual variability in the effectiveness and safety of pharmaceutical interventions. This phenomenon can be attributed to a multitude of factors; however, it is widely acknowledged that common genetic variation affecting drug absorption or metabolism play a substantial contributory role. This is a concept known as pharmacogenetics. Understanding how common genetic variants influence responses to medications, and using this knowledge to inform prescribing practice, could yield significant advantages for both patients and healthcare systems. Some health services around the world have introduced pharmacogenetics into routine practice, whereas others are less advanced along the implementation pathway. This chapter introduces the field of pharmacogenetics, the existing body of evidence, and discusses barriers to implementation. The chapter will specifically focus on efforts to introduce pharmacogenetics in the NHS, highlighting key challenges related to scale, informatics, and education.

A genetic risk score and diabetes predict development of alcohol-related cirrhosis in drinkers.

BACKGROUND & AIMS: Only a minority of excess alcohol drinkers develop cirrhosis. We developed and evaluated risk stratification scores to identify those at highest risk. METHODS: Three cohorts (GenomALC-1: n = 1,690, GenomALC-2: n = 3,037, UK Biobank: relevant n = 6,898) with a history of heavy alcohol consumption (≥80 g/day (men), ≥50 g/day (women), for ≥10 years) were included. Cases were participants with alcohol-related cirrhosis. Controls had a history of similar alcohol consumption but no evidence of liver disease. Risk scores were computed from up to 8 genetic loci identified previously as associated with alcohol-related cirrhosis and 3 clinical risk factors. Score performance for the stratification of alcohol-related cirrhosis risk was assessed and compared across the alcohol-related liver disease spectrum, including hepatocellular carcinoma (HCC). RESULTS: A combination of 3 single nucleotide polymorphisms (SNPs) (PNPLA3:rs738409, SUGP1-TM6SF2:rs10401969, HSD17B13:rs6834314) and diabetes status best discriminated cirrhosis risk. The odds ratios (ORs) and (95% CIs) between the lowest (Q1) and highest (Q5) score quintiles of the 3-SNP score, based on independent allelic effect size estimates, were 5.99 (4.18-8.60) (GenomALC-1), 2.81 (2.03-3.89) (GenomALC-2), and 3.10 (2.32-4.14) (UK Biobank). Patients with diabetes and high risk scores had ORs of 14.7 (7.69-28.1) (GenomALC-1) and 17.1 (11.3-25.7) (UK Biobank) compared to those without diabetes and with low risk scores. Patients with cirrhosis and HCC had significantly higher mean risk scores than patients with cirrhosis alone (0.76 ± 0.06 vs. 0.61 ± 0.02, p = 0.007). Score performance was not significantly enhanced by information on additional genetic risk variants, body mass index or coffee consumption. CONCLUSIONS: A risk score based on 3 genetic risk variants and diabetes status enables the stratification of heavy drinkers based on their risk of cirrhosis, allowing for the provision of earlier preventative interventions. LAY SUMMARY: Excessive chronic drinking leads to cirrhosis in some people, but so far there is no way to identify those at high risk of developing this debilitating disease. We developed a genetic risk score that can identify patients at high risk. The risk of cirrhosis is increased >10-fold with just two risk factors - diabetes and a high genetic risk score. Risk assessment using this test could enable the early and personalised management of this disease in high-risk patients.

Genome-wide Association Study and Meta-analysis on Alcohol-Associated Liver Cirrhosis Identifies Genetic Risk Factors.

BACKGROUND AND AIMS: Only a minority of heavy drinkers progress to alcohol-associated cirrhosis (ALC). The aim of this study was to identify common genetic variants that underlie risk for ALC. APPROACH AND RESULTS: We analyzed data from 1,128 subjects of European ancestry with ALC and 614 heavy-drinking subjects without known liver disease from Australia, the United States, the United Kingdom, and three countries in Europe. A genome-wide association study (GWAS) was performed, adjusting for principal components and clinical covariates (alcohol use, age, sex, body mass index, and diabetes). We validated our GWAS findings using UK Biobank. We then performed a meta-analysis combining data from our study, the UK Biobank, and a previously published GWAS. Our GWAS found genome-wide significant risk association of rs738409 in patatin-like phospholipase domain containing 3 (PNPLA3) (odds ratio [OR] = 2.19 [G allele], P = 4.93 × 10-17 ) and rs4607179 near HSD17B13 (OR = 0.57 [C allele], P = 1.09 × 10-10 ) with ALC. Conditional analysis accounting for the PNPLA3 and HSD17B13 loci identified a protective association at rs374702773 in Fas-associated factor family member 2 (FAF2) (OR = 0.61 [del(T) allele], P = 2.56 × 10-8 ) for ALC. This association was replicated in the UK Biobank using conditional analysis (OR = 0.79, P = 0.001). Meta-analysis (without conditioning) confirmed genome-wide significance for the identified FAF2 locus as well as PNPLA3 and HSD17B13. Two other previously known loci (SERPINA1 and SUGP1/TM6SF2) were also genome-wide significant in the meta-analysis. GeneOntology pathway analysis identified lipid droplets as the target for several identified genes. In conclusion, our GWAS identified a locus at FAF2 associated with reduced risk of ALC among heavy drinkers. Like the PNPLA3 and HSD17B13 gene products, the FAF2 product has been localized to fat droplets in hepatocytes. CONCLUSIONS: Our genetic findings implicate lipid droplets in the biological pathway(s) underlying ALC.