Clinical Pharmacology & Therapeutics

Topiramate (TPM) is approved for seizures and migraine prophylaxis and is used off-label for several neuropsychiatric conditions. The available dosage forms, including tablets and sprinkle capsules, are unsuitable for patients who may be unable to take medicine orally. The resulting potential treatment interruptions could have untoward consequences and underscores the importance of developing a parenteral formulation. In this study, we developed a population pharmacokinetic model of a novel, intravenous TPM formulation using data from a study in patients with epilepsy or migraine receiving a single intravenous dose of stable-labeled TPM. In total, 246 TPM concentrations from 20 adult patients were included for model development. A three-compartment pharmacokinetic model with linear elimination fit the concentration-time data best. Simulations for various loading and maintenance regimens for patients with and without enzyme-inducing comedications were performed. The final estimates(95% confidence interval (CI)) for CL (L/h), V1 (L), and the peripheral volumes, V2 and V3 for a 70 kg person were 1.31(1.01 - 1.53), 9.84 (8.49 - 11.0), 39.1 (36.5 - 41.8)L, and 9.01 (6.41 - 44.3) respectively. The use of enzyme-inducing co-medication was the only significant covariate, associated with a 63% increase in clearance .Goodness-of-fit plots and visual predictive checks indicate satisfactory model performance and prediction. The simulation results indicate that adjusting doses for patients receiving IV TPM can mitigate the changes in plasma TPM concentrations resulting from enzyme induction. This population pharmacokinetic model for intravenous topiramate can inform dosing decisions for patients with epilepsy when used as either initiation or bridging therapy.

GLP-1 receptor agonists (GLP-1 RAs) are effective in delaying progression of chronic kidney disease in individuals with type 2 diabetes mellitus (T2DM). We evaluated whether GLP-1 RA prescription is associated with reduced nephrotoxicity in adults receiving long-term lithium therapy. We conducted a retrospective, propensity score-matched cohort study using electronic health records from the TriNetX global network, which includes de-identified data from over 127 million patients across 109 healthcare organizations. The study population consisted of adults aged [≥]18 years with T2DM, with lithium exposure within the 2 years preceding the index date and at least one prescription for a GLP-1 RA. The primary efficacy outcome was the rate of renal nephrotoxicity in persons with T2DM prescribed lithium and a GLP-1 RA versus those with T2DM prescribed lithium but no GLP-1 RA or other antidiabetic agents. Nephrotoxicity was a composite of ICD-10 and CPT-coded renal disease. Incidence and time-to-event outcomes were assessed using Kaplan-Meier curves and Cox proportional hazards models. In our 24-month analysis, 462 matched patient pairs were included. Initiation of a GLP-1 RA during lithium therapy was associated with a lower incidence of renal events versus lithium alone (6{middle dot}1% vs 10{middle dot}4%), corresponding to a risk difference of -4.3% (95% CI -7{middle dot}86 to -0{middle dot}80), a risk ratio of 0{middle dot}58 (95% CI 0{middle dot}37-0{middle dot}91; p=0{middle dot}017), and higher event-free survival (89{middle dot}0% vs 83{middle dot}2%; log-rank p=0{middle dot}037). GLP-1 receptor agonist therapy was associated with a reduction in reports of lithium-associated nephrotoxicity. Our findings provide impetus to conduct mechanistic renal histopathologic studies combining GLP-1 RAs with lithium.

Human genetics has become a cornerstone of drug target discovery, yet the value of Mendelian randomization (MR) for predicting clinical success remains uncertain. Here, we systematically evaluated MR across 11,482 target-indication pairs with documented Phase II clinical outcomes to assess its utility for drug development. We find that MR statistical significance alone does not enrich for Phase II success, in contrast to genome-wide association study (GWAS) support, which confers an increase in success probability. However, this apparent limitation reflects the heterogeneous nature of clinical failure and the fact that MR encodes information beyond P values. When MR-derived features, including instrument strength and explained variance, are integrated into machine learning models, predictive performance improves substantially. An MR-informed XGBoost classifier identifies target-indication pairs with a 55% overall approval rate, corresponding to a 6.4-fold enrichment over unstratified programs and a 2.8-fold improvement over GWAS- supported targets in Phase II. Notably, this enrichment is achieved without reliance on statistically significant MR results. Our findings demonstrate that MR is most informative when treated as a graded, context-dependent source of causal evidence rather than a binary hypothesis test, and that its integration with machine learning enables scalable, genetics-informed prioritization of drug targets across the clinical pipeline.

BackgroundBiomedical Large Language Models (LLMs) combined with prompt engineering offer domain-specific reasoning, yet their application to individual-level causality assessment remains unexplored. This study evaluated five combinations of biomedical LLMs, prompting strategies, and causality algorithms by comparing their agreement with two human expert evaluators. Research design and methodsA total of 150 Individual Case Safety Reports (ICSRs) were analyzed: 140 reports from Food and Drug Administration Adverse Event Reporting System (FAERS), and 10 myocarditis/pericarditis ICSRs from Vaccine AERS (VAERS). Assessments were conducted using the Naranjo and WHO-UMC algorithms. Biomedical LLMs tested included TinyLlama 1.1B, Medicine LLaMA-3 8B, and MedLLaMA v20, combined with Chain-of-Thought (CoT) or Decomposition prompting. Agreement was measured using Gwets Agreement Coefficient 1 (AC1) and percentage agreement, alongside performance metrics and qualitative error analysis. ResultsThe Medicine LLaMA-3 8B-Naranjo-CoT combination achieved the highest agreement with human assessors for the final classification of causality (64%). Biomedical LLMs demonstrated low inter-rater agreement on critical items of causality assessment such as identification of listed AE, temporal plausibility, alternative causes, and objective evidence of AEs. Frequent model failures included irrelevant responses. ConclusionsBiomedical LLMs showed improved performance over general purpose models previously tested but remain suboptimal for reliable causality assessment of ICSRs.

Background Antibiotic pricing is a key determinant of access and stewardship in low- and middle-income countries (LMICs), yet empirical evidence on how prices are formed within pharmaceutical markets remains limited. However, there is little longitudinal evidence on how antibiotic prices behave within national pharmaceutical supply systems. This study evaluated the patterns and determinants of systemic antibiotic pricing in Tanzania using national regulatory import permit data. Methods We conducted a retrospective analysis of antibiotic importation records from the Tanzania Medicines and Medical Devices Authority for 2010-2016. Systemic antibiotics for human use imported via oral or parenteral routes were included. Unit prices (USD per smallest unit of measure) were summarized using the median and interquartile range (IQR). Prices were compared by route of administration, supplier country, and product naming practice (INN-named versus brand-named) using Mann-Whitney U and Kruskal-Wallis tests with false discovery rate adjustment. Results Of the 14,301 records, 10,894 (76.2%) met the inclusion criteria. Oral antibiotics predominated (89.6%). Although the median oral antibiotic prices declined over time, substantial price dispersion persisted across all study years. Parenteral antibiotics were consistently more expensive (USD 0.755-3.370) and more variable than oral antibiotics. Importation was concentrated in a few medicines, with amoxicillin-clavulanate (16.7%) and amoxicillin (11.4%) accounting for over one-quarter of records, and in a few supplier countries, with India representing 44.9% of the records. Significant price differences between INN-named and branded products were observed for amoxicillin (adjusted p<0.001) and ciprofloxacin (adjusted p=0.018), whereas prices differed significantly by supplier country across major medicines (adjusted p<0.05). Across medicines and years, wide within-product price distributions indicate persistent market segmentation rather than price convergence. Conclusions Antibiotic import prices in Tanzania exhibit systematic and reproducible variations associated with formulation type, supplier origin, and product naming practices. The findings indicate that procurement structure and supplier participation strongly influence pricing in the import-dependent pharmaceutical market. Monitoring import-level prices can serve as an upstream indicator of market conditions and support evidence-informed procurement, pricing regulations, and antimicrobial stewardship policies in LMIC settings.

Artificial intelligence (AI), particularly large language models (LLMs), is increasingly explored in healthcare, yet its real-world usability and safety in high-risk clinical pharmacy tasks remain uncertain. Vancomycin therapeutic drug monitoring (TDM), which requires precise pharmacokinetic calculations and context-sensitive interpretation within a narrow therapeutic window, provides a stringent test case for AI-assisted decision support. This proof-of-concept study developed and evaluated a hybrid clinical decision support system (TDM-AID) integrating a validated deterministic pharmacokinetic calculation engine, GPT-4o-based structured clinical interpretation, and retrieval-augmented guideline support. Thirty retrospective adult vancomycin TDM cases were assessed using a weighted six-domain rubric covering pharmacokinetic accuracy, AUC estimation, prospective prediction, timing recommendations, clinical judgment, and documentation quality. Two independent expert pharmacists evaluated system outputs against benchmark consultations. The overall median performance was 78% (IQR 12%), classified as Acceptable, and 73% (IQR 14%) when deterministic calculations were excluded. Foundational pharmacokinetic calculations achieved 100% accuracy. Clinical judgment demonstrated Good performance (83%), whereas prospective prediction was limited (58%), and timing recommendations were absent in all cases. Safety violations occurred in 17% of cases, including dose recommendations exceeding 4 g/day. Inter-rater reliability was good (ICC 0.87). These findings suggest that hybrid AI-driven decision support is technically feasible and usable as a pharmacist-augmenting draft generator; however, limitations in predictive reasoning, timing logistics, and safety enforcement necessitate deterministic safeguards and mandatory expert oversight before clinical implementation.

BackgroundPersonalized pharmacotherapy requires systematic consideration of genetic factors influencing drug efficacy and safety. The accumulation of large-scale whole-exome sequencing (WES) data provides an opportunity to assess population frequencies of clinically significant pharmacogenetic variants; however, the diagnostic applicability of exome data for pharmacogenomics remains insufficiently studied. Materials and MethodsA retrospective analysis of 6,102 anonymized sequencing datasets obtained between 2020 and 2025 was performed using the DNBSEQ-G400 (MGI) platform and Agilent SureSelect Human All Exon v6/v7/v8 enrichment kits. SNV and indel detection, CNV analysis, high-resolution HLA typing, and diplotype assignment for key pharmacogenes were conducted. Pharmacogenomic annotations were derived from PharmGKB (levels of evidence 1A-2B), CPIC, and PharmVar. Additionally, WES limitations and the feasibility of imputing non-coding pharmacogenetic variants were evaluated. ResultsPopulation frequencies of alleles and metabolic phenotypes were determined for 13 Very Important Pharmacogenes (VIPs), along with the distribution of HLA class I and II alleles. The highest allelic and phenotypic variability was observed in CYP family genes, particularly CYP2D6, CYP2C19, and CYP2B6. A total of 663 pharmacogenomic annotations were identified, predominantly related to drug metabolism (50.38%) and toxicity (29.56%), including psychotropic agents, anticoagulants, statins, opioid analgesics, antineoplastic agents, and immunosuppressants. At least 32 drugs require pharmacogenetic testing based on variants located in non-coding regions, as well as accurate CYP2D6 copy number determination. Linkage disequilibrium analysis demonstrated the inability to reliably impute most non-coding pharmacogenetic variants from WES data. ConclusionThese findings represent one of the largest reference assessments to date of pharmacogenetically significant variant and HLA allele frequencies in the Russian population. The results confirm the utility of WES for population pharmacogenomic screening while simultaneously highlighting its fundamental limitations and the need for alternative genetic diagnostic methods in selected cases.

BackgroundPersistent Spinal Pain Syndrome (PSPS) type II represents a challenging clinical entity with limited therapeutic options. Various spinal cord stimulation (SCS) modalities have emerged as potential treatments, but their comparative effectiveness remains unclear. ObjectiveOur goal in this paper is to systematically evaluate and compare the efficacy of different SCS modalities in patients with PSPS type II through meta-analysis of available randomized controlled trials. Evidence ReviewWe conducted a systematic review following PRISMA guidelines, searching major databases for randomized controlled trials evaluating SCS modalities in PSPS type II patients until the end of May 2025(search updated on October 3rd). Primary outcomes included pain intensity (VAS) and functional disability (ODI) at 6 and 12 months. Subgroup analyses compared tonic versus burst stimulation and high-frequency versus low-frequency SCS. FindingsNine randomized controlled trials were included, encompassing 565 patients across different SCS modalities. For the primary outcome of clinically meaningful pain relief ([&ge;]50% reduction), pooled analysis demonstrated that 45% (95% CI: 18-75%, I{superscript 2} = 92.2%) of patients achieved this threshold for back pain and 55% (95% CI: 45-65%, I{superscript 2} = 0%) for leg pain. Subgroup analysis revealed significant differences in back pain responder rates by stimulation modality: High-frequency SCS demonstrated responder rates of 92% (95% CI: 79-98%) versus 28% (95% CI: 13-49%) for conventional frequencies (p < 0.001). For leg pain, no significant difference was observed between tonic (51%, 95% CI: 37-65%) and burst stimulation (60%, 95% CI: 45-74%, p = 0.36) and mean VAS scores demonstrated significantly lower pain with high-frequency SCS (13.30, 95% CI: 8.82-17.78) compared to conventional frequency (28.42, 95% CI: 24.02-32.88, p<0.0001). For back pain, mean VAS scores decreased from a baseline of 73.03 to 41.67 (95% CI: 36.12-47.22, I{superscript 2}=22.8%) at 6 months and remained stable at 35.66 (95% CI: 25.39-45.93, I{superscript 2}=75.0%) at 12 months. Leg pain showed more pronounced improvement, with VAS scores declining from a baseline of 61.81 to 23.75 (95% CI: 17.69-29.81, I{superscript 2}=78.8%) at 6 months and 29.16 (95% CI: 24.81-33.52, I{superscript 2}=0%) at 12 months). Meta-regression identified longer pain duration and older age as positive predictors of response, while higher baseline leg pain predicted lower responder rates. Serious adverse events occurred in 10%, with a 16% revision surgery rate. Only two studies demonstrated a low risk of bias across all domains. ConclusionsCurrent evidence demonstrates that various SCS modalities provide clinically meaningful pain relief in PSPS type II patients, with approximately half achieving [&ge;]50% pain reduction. High-frequency SCS shows significantly superior responder rates for back pain compared to conventional tonic stimulation, while burst stimulation yields significantly superior reductions in continuous pain intensity metrics. However, the limited number of studies, substantial heterogeneity, and lack of head-to-head comparisons prevent definitive recommendations regarding optimal stimulation parameters. Future large-scale randomized trials with standardized protocols and responder-based outcomes are needed to establish evidence-based treatment algorithms for PSPS type II patients.

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSINTRODUCTIONC_ST_ABSTreatment response in Alzheimers disease (AD) varies substantially across patients, yet no validated frameworks exist to estimate heterogeneous treatment effects (HTE) from observational data while controlling for confounding bias. METHODSWe developed a causal machine learning framework integrating expert-guided causal graphs, complementary HTE estimators, sensitivity analyses, and policy learning. We applied it to cholinesterase inhibitors (ChEIs) in MCI due to AD to patients from the NACC and ADNI cohorts. RESULTSAnalysing 4,049 patients with 12-month and 2,223 with 36-month follow-up, all estimators indicated null or negative long-term ChEI effects on cognitive and functional outcomes, notably on functional measures. ChEIs showed slightly more deleterious effects among men than women. DISCUSSIONThis framework provides a methodology for estimating HTE from observational data. It revealed no beneficial responder subgroups, highlighting the challenge of detecting treatment heterogeneity in moderately sized cohorts. This approach can inform treatment selection for other AD therapies including memantine, anti-amyloid agents, and emerging treatments.

IntroductionPatients undergoing anterior cruciate ligament (ACL) reconstruction experience substantial postoperative pain, which delays recovery and leads to both immediate and long-term opioid use. In other knee procedures, infiltration between the popliteal artery and the capsule of the posterior knee (IPACK) has demonstrated analgesic and opioid reducing effects. However, the effect in patients undergoing ACL reconstruction has not been investigated. We aimed to investigate the real-world effect of IPACK in patients undergoing ACL reconstruction on immediate postoperative opioid consumption. ParticipantsIn this single-centre difference-in-differences cohort study, all patients who underwent ACL reconstruction surgery at Bispebjerg Hospital, Denmark, from 1 February 2024 to 30 June 2025 are included. The study further includes a similar reference cohort, comprising all patients who underwent trochleaplasty, Elmslie-Trillat, or medial patellofemoral ligament reconstruction during the same period, and at the same hospital. InterventionThe primary exposure is the implementation of IPACK as part of perioperative management for ACL reconstruction on 1 January 2025. The IPACK was performed under ultrasound guidance, immediately before surgery, administering 20 mL of ropivacaine 0.5% between the popliteal artery and the posterior knee capsule. OutcomesThe primary outcome is the cumulative opioid consumption from surgical incision to 2 hours postoperatively. Secondary outcomes include the cumulative opioid consumption from incision to 24 hours postoperatively, the worst reported pain score at 0-24h postoperatively, occurrence of postoperative nausea or vomiting (PONV) 0-24h postoperatively, length of PACU stay, length of hospital stay, and nerve injuries. As an exploratory outcome, carbon dioxide emissions will be investigated. Statistical analysisThe main analysis will be a standard two-way fixed effects DiD regression assessing the changes occurring at the time of implementation of IPACK in the ACL cohort, with adjustment for the underlying time trend. Continuous outcomes are reported as mean difference (95% confidence interval [CI]), and binary outcomes as absolute and relative risks (95% CI).

AimsLow-dose aspirin is no longer routinely recommended for primary prevention in older adults because bleeding risks outweigh cardiovascular benefits. We aimed to investigate whether polygenic scores (PGSs) could modify the effects of aspirin on major bleeding and major adverse cardiovascular events (MACE) in a trial of older individuals. MethodsWe conducted post-hoc genetic analysis of the Aspirin in Reducing Events in the Elderly (ASPREE) randomized, placebo-controlled trial in Australia and the United States. Participants aged [&ge;]70 years ([&ge;]65 years for U.S. minorities) without cardiovascular disease, dementia, or physical disability were randomized to 100 mg daily aspirin or placebo. Among those with high-quality genotyping data (n=13,571; median follow-up 4.6 years), we tested 572 cardiovascular- and hematologic-related PGSs for interaction with aspirin using Cox proportional hazards models, applying Bonferroni correction. ResultsA triglyceride-related PGS (PGS003144) modified aspirins effect on major bleeding (interaction P=5.9x10-5; Bonferroni-adjusted P=0.034). In the lowest PGS quintile, aspirin increased major bleeding compared with placebo (hazard ratio [HR] 2.28; 95% CI 1.45-3.58) without reducing MACE (HR 1.04; 95% CI 0.67-1.62). In contrast, in the highest quintile, aspirin was associated with lower risks of major bleeding (HR 0.62; 95% CI 0.38-0.97) and MACE (HR 0.66; 95% CI 0.44-0.99). Baseline measured triglyceride levels demonstrated a similar pattern of effect modification. ConclusionA triglyceride-related PGS identifies older adults with divergent bleeding and cardiovascular responses to aspirin, supporting the potential role of genetically-informed strategies for primary cardiovascular prevention. Lay summaryThis study shows that genetic differences related to triglyceride levels may help identify older adults who are more likely to be harmed or to benefit from taking aspirin to prevent heart disease. O_LIIn older adults with certain genetic profiles linked to triglycerides, aspirin increased the risk of serious bleeding without reducing heart attacks or strokes, while in others it was associated with lower risks of both bleeding and cardiovascular events. C_LIO_LIUsing genetic information alongside traditional risk factors could help tailor aspirin use for primary prevention, avoiding unnecessary harm while identifying those most likely to benefit. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/26346656v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@7ac690org.highwire.dtl.DTLVardef@8256c2org.highwire.dtl.DTLVardef@10de40corg.highwire.dtl.DTLVardef@f6e5e9_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure, Graphical Abstract:C_FLOATNO Genetic stratification of aspirin benefit and harm using a triglyceride polygenic score. Screening of 572 polygenic scores in the ASPREE trial identified a triglyceride-related PGS that modified aspirin-associated bleeding and cardiovascular risk. Aspirin increased bleeding risk in the lowest PGS quintile but reduced major bleeding and MACE in the highest quintile. Abbreviations: PGS, polygenic score; GI, gastrointestinal; IC, intracranial; MACE, major adverse cardiovascular events. C_FIG

IntroductionChronic pain in fibromyalgia may be driven by abnormal ongoing activity in a subclass of C-fibre nociceptors known as Type1B or CMi nociceptors. As is common in C-nociceptor microneurography studies, the modest patient numbers in these prior studies generate large confidence intervals around the point estimate of the prevalence of this abnormal activity. This complicates the interpretation of the relative importance of this ongoing nociceptor activity as a pain generating mechanism in fibromyalgia. The study aims to improve precision via an adaptive Bayesian protocol that maximises the yield and quality of data collection whilst minimising patient burden. MethodsThe study employs an optimised microneurography protocol with an adaptive study design. The microneurography protocol incorporates early identification of CMi nociceptors via an abbreviated activity dependent slowing protocol to increase yields enabling efficient collection of the primary outcome data. The adaptive study design will use Bayesian principles to iteratively assess the predictive probability of futility, and terminate early if there is high confidence that the hypothesis is false. Furthermore, the study will employ questionnaires to explore links with pain in the area under study to the electrophysiology data. Finally, quantitative sensory testing will be used to investigate whether the irritable nociceptor phenotype is associated with abnormalities in CMi nociceptor physiology. Ethics & DisseminationThis study has received HRA REC approval in the UK. Participants will provide written informed consent, and may withdraw at any time without consequence. At the end of the study, the results will be disseminated through peer-reviewed publication, and the data made available via a data repository. Strengths & limitations of this studyBayesian predictive probability of futility to minimise patient burden in microneurography Microneurography for objective interrogation of the peripheral nervous system Optimised microneurography protocol to efficiently answer primary hypotheses Subjective elements of early termination criteria of the study assessed and co-developed with Patient and Public Inclusion and Engagement Group

BackgroundAmiodarone is a widely used antiarrhythmic which frequently induces thyroid dysfunction, including both amiodarone-induced hypothyroidism (AIH) and thyrotoxicosis (AIT). Whether genetic factors contribute to these adverse drug reactions is unknown. In this study, we aimed to identify genetic variants that influence the risk of amiodarone-induced thyroid dysfunction and to evaluate their potential to support genotype-guided risk screening. MethodsThis pharmacogenetic study comprised two genome-wide meta-analyses of AIH and AIT using five datasets (Copenhagen Hospital Biobank, The Danish Blood Donor Study, Estonian Biobank, deCODE genetics, and Mass General Brigham Biobank). Key measures included the odds ratio (OR) per risk allele, the variants effects on spontaneous thyroid disease and biomarkers, and their clinical predictive ability, assessed by the area under the receiver operating curve (AUC), positive and negative predictive values (PPV and NPV). FindingsThe AIH meta-analysis (880 cases, 4,031 controls) identified three genome-wide significant loci in: FOXE1 (rs36052460; OR 2.58, allele frequency [AF] = 64.3%, P = 2.55 x 10-44), FOXA2 (rs2424459; OR 1.67, AF = 71.3%, P = 2.59 x 10-14), and ADAM32 (rs12681571; OR 1.49, AF = 61.8%, P = 3.05 x 10-9). The AIT meta-analysis (385 cases, 4,936 controls) identified one locus in CAPZB (rs867355; OR 1.63, AF = 66.1%, P = 3.49 x 10-8). In risk prediction models, a polygenic risk score (PRS) of the AIH variants increased the AUC by 9.2% (95% CI 6.6 - 11.9%), which outperformed a genome-wide hypothyroidism PRS (1.5% AUC increase, 95%CI 0.0 - 2.9%). Similarly, the CAPZB variant improved AIT prediction (AUC increase of 4.0%, 95% CI 0.4 - 7.5%) beyond a hyperthyroidism PRS (0.2% AUC increase, 95%CI -0.8 - 1.2%). Genotype-guided screening would identify individuals at low risk (NPVs ranging from 90-95% and PPVs 2-20%). InterpretationWe identified genetic variants that influence the risk of developing amiodarone-induced thyroid dysfunction. Genotype-guided screening offers a potential complement to current strategies and personalize pre-treatment risk assessment for patients initiating amiodarone therapy.

BackgroundPersons with epilepsy are at increased risk of depression/anxiety. Older antiseizure medications (ASMs) had drug-drug interactions that complicated pharmacotherapy of depression/anxiety; newer ASMs lack this drawback but can have psychiatric side effects. Anxiety/depression are increasingly recognized and treated pharmacologically. We hypothesized that the likelihood of treatment with selective serotonin uptake inhibitors (SSRI) would have increased in adult-onset epilepsy when prescription habits shifted towards newer ASMs. MethodsWe linked national health registers and included 28569 persons with epilepsy incident in 2006-2020 and 68509 age- and sex matched controls. We assessed the risk of starting SSRI treatment compared to age- and sex-matched controls across three incidence periods: 2006-2010, 2011-2015, and 2016-2020. Cox regression was used to estimate adjusted hazard ratios (HRs), and subgroup analyses explored age, sex, and comorbidities. Specialist psychiatric care was also assessed as a measure of more severe depression. Analysis including persons with SSRI-use before the epilepsy diagnosis were used for sensitivity analyses. FindingsPersons with epilepsy had higher risks of starting SSRIs compared to controls; 1986/9561 (20.8%) received SSRI during follow-up after epilepsy in 2006-2010 and 2020/9165 (22.0%) in 2016-2020; adjusted HRs were 1.92 (95%CI:1.79 - 2.06) in 2006-2010, 1.84 (95%CI:1.72-1.97) in 2011-2015, and 1.81 (95%CI:1.69 - 1.94) in 2016-2020. Among individuals aged 18-30 years at their epilepsy diagnosis, the proportion receiving SSRIs remained the same between the first and last calendar periods (18.2%). Because of increased treatment of controls, the adjusted HRs of SSRI-treatment decreased from 2.33, (95% CI:1.96 - 2.78) to 1.63, (95% CI 1.39 to 1.91). The HR of specialist psychiatric care was not significantly different between the time periods. Most comorbidities were consistently associated with increased likelihood of SSRI treatment, whereas intellectual disability decreased the likelihood in some periods. InterpretationWe found no evidence of overall increased SSRI initiation or psychiatric care after the shift to newer ASMs. Person with epilepsy remain more likely to receive SSRI treatment, but probably not to a level matching the higher prevalence of depression. Increased SSRI treatment of younger age adults has not been matched by increased treatment of young adults with epilepsy. This suggests a potentially widening treatment gap and a need for increased recognition of depression in young adults with epilepsy. FundingSwedish Research Council (2023-02816), Swedish state through the ALF-agreement (ALFGBG-1006343), Knut och Ragnvi Jacobsson foundation, Swedish Society for Medical Research (S18-0040), Swedish Society of medicine (SLS-881501), Epilepsifonden, Rune och Ulla Amlovs stiftelse.

IntroductionAdverse drug reactions (ADRs) remain a major public health issue, and genetic factors contribute importantly to interindividual variability in drug response. Pharmacogenetic testing helps reduce ADR risk by optimizing drug selection and dosage, particularly in monogenic disorders. Material and MethodsWhole-exome sequencing of 6,739 samples from the Russian population was performed using the MGIEasy Universal DNA Library Prep Set on the DNBSEQ-G400 platform (MGI). Variants in 48 genes were examined, focusing on inherited arrhythmias (Long QT syndrome, Short QT syndrome, Timothy syndrome, Andersen-Tawil syndrome, Brugada syndrome, Atrial fibrillation, Catecholaminergic polymorphic ventricular tachycardia), enzyme deficiencies (Glucose-6-Phosphate Dehydrogenase Deficiency [G6PDD], Porphyrias), Dravet Syndrome (DS) and Malignant Hyperthermia (MH). All identified variants had been reported at least once as pathogenic (P) or likely pathogenic (LP) in ClinVar, along with those occasionally classified as variants of uncertain significance (VUS). Each variant was manually re-evaluated according to ACMG criteria. ResultsA total of 75 unique variants in 18 genes were observed in 119 individuals (1.77%), including 21 carriers and 13 women with a G6PD mutation. Of these, 46 variants were classified as P, 21 as LP, and 8 as VUS. Missense variants accounted for the largest proportion (73.33%). The most affected genes were KCNQ1 (24/119), which exhibited the highest number of unique variants (18), G6PD (20/119), SCN1A (15/119), and RYR1 (14/119). Regarding associated conditions, mutations linked to arrhythmias were found in 51 individuals, MH in 27, G6PDD in 20, DS in 15, and Porphyrias in 6. ConclusionsIncorporating genetic information on both common and rare clinically actionable variants into therapeutic decision-making has the potential to improve medication safety, reduce preventable ADRs, and enhance the effectiveness of personalized pharmacotherapy.

In this randomized, double-blind, controlled trial of 8 weeks of repetitive transcranial magnetic stimulation (rTMS) for chronic pain, we compared the classic primary motor cortex (M1) rTMS with a novel target-selection strategy based on pre-therapy cortical connectivity. Guided by principles of homeostatic plasticity, we tested whether stimulating the cortical site with the lowest pre-therapy global connectivity would be more effective than two active comparators: stimulating the site with the highest pre-therapy global connectivity or stimulating M1 independent of connectivity. Before starting rTMS treatment, TMS-evoked EEG potentials were recorded from four cortical targets: M1, the dorsolateral prefrontal cortex, the anterior cingulate cortex, and the posterosuperior insular cortex. For each target, global connectivity was quantified using a distance-weighted, phase-based index (debiased weighted phase lag index, wPLI) derived from pre- and post-TMS-evoked EEG activity, capturing both the magnitude and spatial extent of TMS-induced oscillatory phase locking across cortical regions. Target allocation in the Low- and High-Connectivity groups was based on this global connectivity measure. Ninety patients with chronic pain were randomized to Low-Connectivity, High-Connectivity, or Classic-M1 groups. Treatment consisted of 12 rTMS sessions delivered over 8 weeks to the assigned target. The primary outcome was the proportion of patients achieving [&ge;] 30% reduction in pain intensity. Secondary outcomes included continuous change in pain intensity, pain interference, sleep, fatigue, mood, quality of life, and patient global impression of change. No between-group differences were observed for primary or secondary outcomes (p > 0.05). In prespecified exploratory analyses, we examined whether pre-therapy local connectivity (within-target wPLI) predicted treatment response. In the Classic-M1 group, lower pre-therapy local M1 connectivity was associated with a greater reduction in pain intensity (r = 0.50, p = 0.005). This association was not observed in the Low- or High-Connectivity groups. A regression model including group-by-connectivity interaction indicated that the relationship between local connectivity and pain reduction differed between the Classic-M1 and High-Connectivity groups (p = 0.038). The results of this clinical trial showed that connectivity-based target allocation using global connectivity did not improve clinical outcomes. However, lower local M1 connectivity was associated with greater pain reduction following Classic-M1 stimulation, suggesting that local M1 connectivity may serve as a potential biomarker of response.

BackgroundUnderstanding the associations among biopsychosocial factors is essential for improving research and treatment of chronic low back pain (CLBP). Here we characterized interrelations among biopsychosocial domains using network analysis and identified the most influential features in CLBP. MethodsData came from Quebec Low Back Pain Study, comprising 4,489 CLBP participants. We modeled relationships among baseline biopsychosocial features as networks, where nodes represent features and edges encode statistical or causal dependencies among them. Undirected network was inferred using distance correlation. Directed network was constructed using the Linear Non-Gaussian Acyclic Model, which estimates plausible causal directions. Influence maximization was performed using the Independent Cascade (IC) model to identify the most influential features in each network. ResultsIn the undirected network, physical function and pain interference were the most central nodes, followed by depression. In the directed network, fear of movement, catastrophizing, and widespread pain emerged as key downstream hubs receiving multiple causal inputs, whereas pain interference, physical function, and depression acted as major upstream drivers exerting broad causal influence. IC diffusion simulations further identified pain interference and physical function as the most influential features in the undirected and directed networks, respectively. ConclusionsPain interference, physical function, and depression consistently emerged as key components of the CLBP biopsychosocial network. These features exert causal effects on fear of movement, catastrophizing, and widespread pain, with diffusion analyses confirming their roles as system-wide drivers. Interventions targeting functionality and pain interference, rather than pain intensity alone, may yield broader benefits across psychological and functional domains.

BackgroundA coronary artery calcium (CAC) score of 0 is widely considered to indicate low short- to intermediate-term risk for coronary artery disease (CAD) and is frequently used to defer lipid-lowering therapy. However, a subset of individuals with CAC=0 still experience events, highlighting residual risk not captured by imaging alone. Polygenic risk scores (PRS) quantify lifelong inherited susceptibility, but conventional approaches rely on predefined ancestry labels despite human genetic diversity existing along a continuum. To address this limitation, we developed 8 Billion, a novel, label-free framework that models genetic similarity without pre-labeling individuals by ancestry. We evaluated whether a CAD PRS derived using this approach identifies clinically meaningful residual risk among individuals with baseline CAC=0. MethodsWe analyzed participants from the Multi-Ethnic Study of Atherosclerosis (MESA) with baseline CAC=0. The 8 Billion framework estimates individualized PRS by anchoring each participant to a genetically similar reference neighborhood rather than discrete ancestry groups. Multivariable Cox proportional hazards models assessed associations between PRS-defined risk groups and incident CAD, adjusting for principal components of genetic variation (PC1-PC4), age, sex, smoking status, systolic blood pressure, total and high-density lipoprotein cholesterol, diabetes, and antihypertensive medication use. Two classifications were evaluated: (1) a Top 5% group defined by the highest 5% of PRS-derived odds ratios in the cohort; and (2) an individualized high-risk group defined using a personalized threshold derived from the 8 Billion framework. Ten-year absolute risk estimates were derived from adjusted models. ResultsDespite CAC=0 at baseline, polygenic burden was independently associated with incident CAD. Individuals in the Top 5% PRS group had higher risk of CAD events compared with the remainder (hazard ratio [HR], 3.12; 95% CI, 1.05-9.31; P=0.041). The individualized high-risk group defined through 8 Billion was similarly associated with increased CAD risk (HR, 2.52; 95% CI, 1.12-5.66; P=0.025). Estimated 10-year ASCVD risk among high-PRS individuals exceeded the 7.5% threshold commonly used to guide initiation of lipid-lowering therapy, despite CAC=0. In fully adjusted models, conventional risk factors were not statistically significant within this subset. ConclusionsAmong individuals with CAC=0 in a multi-ethnic cohort, a label-free, ancestry-continuum PRS approach identified subgroups at significantly increased risk of incident CAD and at guideline-relevant 10-year treatment thresholds. Integration of polygenic risk with CAC imaging refines preventive decision-making beyond imaging alone. Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABSO_LIAmong individuals with baseline CAC=0, the Allelica Multi-ancestry CAD PRS calculated with the 8 Billion framework identified subgroups at significantly increased risk of incident CAD. C_LIO_LIIn this CAC=0 population, high polygenic risk was associated with 10-year risk estimates above the 7.5% treatment threshold, whereas conventional risk factors were not statistically significant in adjusted models. C_LI What are the clinical implications?O_LIA CAC score of 0 should not be interpreted as uniformly protective, because genetically high-risk individuals may still experience clinically meaningful coronary events. C_LIO_LIIntegrating PRS with CAC assessment may improve preventive decision-making by identifying patients with residual risk despite reassuring baseline imaging. C_LIO_LIIn selected patients with CAC=0, high polygenic risk may support closer follow-up and earlier consideration of lipid-lowering therapy or other preventive strategies and imaging modalities. C_LI

Background-Blockers (ABs) are the most commonly prescribed medications for benign prostatic hyperplasia (BPH), a highly prevalent condition. Although the ALLHAT raised concerns about cardiovascular (CV) safety of nonselective ABs for the treatment of hypertension, the comparative CV risk profile of selective 1A-adrenergic receptor (1A-AR) antagonists for BPH remains unclear. MethodsWe conducted a retrospective cohort study using the TriNetX federated research network (158 million patients across 113 healthcare organizations). Males aged 55 to 90 years with BPH who initiated ABs or 5-ARIs between October 1, 2015, and database lock were included. Three propensity score-matched analyses were conducted: (1) selective 1A-AR antagonists versus 5-ARIs (n=48,096 per group); (2) nonselective ABs versus 5-ARIs (n=33,232 per group); and (3) 1A-selective versus nonselective ABs (n=54,872 per group). Exposures were new use of selective 1A-AR antagonists, nonselective ABs, or 5-ARIs with evidence of adherence. Main outcomes and measures were heart failure (HF) hospitalization, acute MI, stroke, any hospitalization, major adverse CV events (MACE), and composite MACE plus HF at 1, 3, and 5 years. ResultsIn the 1A-selective AB versus 5-ARI analysis, 1A-selective ABs were associated with increased risk at 1 year of HF (hazard ratio [HR], 1.48 [95% CI, 1.39-1.57]), MI (HR, 1.41 [95% CI, 1.28-1.54]), and stroke (HR, 1.36 [95% CI, 1.22-1.50]). Similar patterns were observed for nonselective ABs versus 5-ARIs: HF (HR, 1.46), MI (HR, 1.29), stroke (HR, 1.32). At 5 years, CV risks remained elevated: HF (HR, 1.50 for selective ABs; HR, 1.52 for nonselective ABs), MI (HR, 1.41; HR, 1.30), and stroke (HR, 1.37; HR, 1.29). Head-to-head comparison of selective versus nonselective ABs showed similar CV outcomes (HF HR, 1.10 at 1 year). ConclusionsBoth 1A-selective and nonselective ABs were associated with increased CV event risk compared with 5-ARIs that persisted through 5 years of follow-up. These findings, which were robust across sensitivity analyses and specific to clinically important CV endpoints, may inform shared decision-making for BPH pharmacotherapy.

BackgroundAnthracyclines are central to childhood cancer therapy but predispose patients to cardiotoxicity leading to long-term cardiovascular risk. Endothelial injury and impaired repair contribute to this, yet pediatric data remain limited. ObjectiveTo longitudinally assess endothelial injury and repair in childhood cancer patients treated with anthracyclines by quantifying circulating endothelial cells (CECs) and endothelial progenitor cells (EPCs). MethodsIn a single-centre retrospective cohort, children (<18 years) diagnosed with leukemia (n=35) or lymphoma (n=13) were studied at four timepoints: pre-treatment ("Pre"), [~]1-month- ("End"), 3 months- (3M), and 1 year- (1Y) post-treatment. Peripheral blood mononuclear cells were analyzed by flow cytometry to quantify CECs and EPCs, and EPC fate was assessed by p16 (senescence) and Annexin V (apoptosis). Cardiac injury biomarkers and left ventricular function were assessed at each timepoint. ResultsLongitudinal trends of CEC and EPC counts were similar between leukemia and lymphoma participants. CECs were highest at pre-treatment and declined significantly thereafter, though they remained marginally elevated during remission compared with healthy controls, indicating that endothelial damage had largely subsided following treatment. EPCs were also highest at pre-treatment and decreased to levels below healthy controls during remission, suggesting impaired baseline endothelial maintenance and repair. Furthermore, EPCs were predominantly senescent up to 1-year post-treatment. ConclusionsEndothelial injury resolves by treatment completion, but repair remains impaired during remission with EPC pools dominated by senescent cells. This suggests defective endothelial regeneration, rather than persistent injury, drives long-term cardiovascular complications and underscores the need to restore EPC viability and function in childhood cancer survivors.