Abstract Introduction Neuromuscular disorders (NMDs) encompass a broad group of conditions that primarily affect the peripheral nervous system. They are often caused by genetic alterations that impair skeletal muscle function and result in debilitating symptoms. Obtaining an accurate molecular diagnosis remains a challenge, potentially because variants in genes that have yet to be identified as causal. We therefore used advanced computational methods to study the genetic architecture of NMDs and to identify key features that distinguish NMD genes from other genes in the broader genome. Methods Curated genes implicated in NMDs ( n = 639; GeneTable of NMDs) were obtained and merged with a comprehensive set of genomic features for human autosomal protein-coding genes. Machine-learning-based feature selection and ranking were performed using Boruta, along with complementary analytical approaches. These analyses were used to identify the most important genic features ( n = 134, subcategories: gene complexity, genetic variation, expression patterns, and other general gene traits) for discriminating NMD genes from other genes in the genome Results NMD genes exhibit enriched expression in disease-relevant tissues, including skeletal muscle and heart. Additionally, compared with other protein-coding genes, these genes exhibit increased transcriptomic complexity (e.g., longer transcripts and more unique isoforms), contain more short tandem repeats, and show greater variation in conservation across model organisms. Conclusions This study identified several key genomic features that may distinguish NMD genes from the rest of the genome. This may enhance the identification of novel causal genes and could ultimately facilitate earlier diagnosis and medical management for affected individuals.

Age-related hearing loss (ARHL) is a progressive, bilateral decline in hearing ability that affects one in four individuals over 60 years of age worldwide. While previous genome-wide association studies (GWAS) have identified distinct single-nucleotide variants (SNVs) associated with metabolic and sensory ARHL phenotypes, the contribution of short tandem repeats (STRs) - a neglected yet important class of genetic variants - remains poorly understood. To address this gap, TRTools was used to impute STRs from a high quality, sequencing-derived SNV-STR reference panel to investigate the association between STRs and metabolic and sensory estimates. Heritability analyses revealed that while STRs contribute to estimates of both ARHL components, this class of variation plays a more important role in metabolic hearing loss (6%), which typically increases with age, compared to sensory hearing loss (4%). Further, the inclusion of this class of variant into GWAS analyses uncovered an association between a haplotype consisting of two missense variants (rs7714670 and rs6453022) and an intronic STR (chr5:73778077:A16) in ARHGEF28 (P=3.30×10-9), proving further insight into the variants driving this previously identified signal. Notably, burden analyses revealed that rare and longer repeats were associated with an increased risk of the metabolic phenotype and a reduced risk of the sensory phenotype. Functional annotation of significant and nominally significant STRs revealed potential effects on gene expression and splicing of nearby genes. Our findings provide the first evidence that STRs explain some of the missing heritability of ARHL phenotypes and create an STR resource for researchers to use in future analyses.

PURPOSE:One in 20 people using dimethyl fumarate (DMF), a commonly used disease-modifying therapy for multiple sclerosis (MS), develops severe lymphopenia. We aimed to identify genetic variation associated with DMF-related lymphopenia. METHODS:Using a case-control design, we included cases that had either grade 2 (absolute lymphocyte count <0.8 × 109/L) or 3 (<0.5 × 109/L) lymphopenia during DMF. Controls had normal lymphocyte counts and ⩾1 year of DMF exposure. We generated a polygenic score for lymphocyte counts and evaluated its ability to predict DMF-associated lymphopenia in two cohorts, with adjustment for covariates. We also conducted a genome-wide association study (GWAS) and gene-based analyses. FINDINGS:The discovery cohort comprised 238 PwMS of European genetic ancestry from Canada/Australia (n = 72 grade 2 cases, 34 grade 3 cases), and the replication cohort comprised 156 PwMS from Sweden (n = 34 grade 2, 14 grade 3). A higher polygenic score for lymphocyte counts predicted reduced risk of grade 2 lymphopenia (hazard ratio = 0.43, 95% confidence interval: 0.25-0.73). The GWAS identified one locus associated with the minimum lymphocyte count during DMF (rs17087205, beta = -0.63, SE = 0.11, p = 3.89e-8) but did not replicate (beta = -0.04, p = 0.47). CONCLUSION:Common polygenic variation of lymphocyte counts was significantly associated with moderate lymphopenia during DMF treatment.

Background: Polyglutamine (polyQ) disorders, such as Huntington disease (HD) and several spinocerebellar ataxias, are severe neurological disorders caused by repeat expansions of the glutamine codon. These conditions lack effective treatments, with therapeutic research focused on pathogenic gene knockdown. We aimed to profile these genes using diverse human genomic data to guide therapeutic strategies by identifying new biology and assessing off-target effects of knocking these genes down. Methods: We conducted an unbiased phenome-wide study to identify human traits and diseases linked to polyQ disorder genes (Open Targets L2G>0.5). Network analyses explored shared trait associations and overlapping biological processes among these genes. Lastly, we assessed the theoretical druggability of polyQ disorder genes using recently identified features predictive of clinical trial success and compared them to repeat expansion (HD) modifier genes. Results: We identified 215 human phenotype/polyQ disorder gene associations from 3,095 studies, indicating potential adverse effects from gene knockdown. Shared trait associations among polyQ disorder genes suggested overlapping biological processes despite distinct functions. Drug target profile analysis revealed an unfavorable risk profile for polyQ disorder genes, particularly ATN1 , ATXN1 , ATXN7 , and HTT , due to genomic features such as constraint, molecular interactions, and tissue specificity. PolyQ disorder genes also showed significantly more safety-related risks than HD modifier genes ( P =7.03x10-3). Conclusion: Our analyses emphasize the pleiotropic nature of polyQ disorder genes, highlighting their potential risks as drug targets due to safety concerns. These findings reinforce the importance of exploring alternate therapeutic strategies, such as targeting genetic modifier genes, to mitigate these challenges. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement We thank the Natural Sciences and Engineering Research Council of Canada through the Canada Research Chairs Initiative and Discovery Grant Program, as well as the Health Sciences Centre Foundation Winnipeg, for the financial support provided to GEBW. BID was also supported through the Canadian Institutes of Health Research Canada Research Chairs Initiative. The Research Manitoba Graduate Studentship and Rady Faculty of Health Sciences Student Top-Up supported NKL. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Bannatyne Research Ethics Board of the University of Manitoba gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data used in the analyses described in this study are publicly accessible to researchers through the consortia that generated them. Analysis scripts for data accession, analysis and visualization are accessible at https://github.com/Wright-Lab-Neurogenomics-Research/polyQ\_genes\_characterization_analyses

Polyglutamine (polyQ) disorders, such as Huntington disease (HD) and several spinocerebellar ataxias, are severe neurological disorders caused by glutamine codon repeat expansions. These conditions lack effective treatments, with therapeutic research focused on pathogenic gene knockdown. This investigation aimed to profile these genes using diverse human genomic data to inform therapeutic strategies by identifying new biology and assessing the potential on-target effects of knocking down these genes. We conducted an unbiased phenome-wide study to identify human traits and diseases linked to polyQ disorder genes (Open Targets L2G > 0.5). Network analyses explored shared trait associations and overlapping biological processes among these genes. Lastly, we assessed the theoretical druggability of polyQ disorder genes using recently identified features predictive of clinical trial success and compared them with repeat expansion (HD) modifier genes. Our analyses identified 215 human phenotype/polyQ disorder gene associations from 3,095 studies, indicating potential adverse effects from gene knockdown. Shared trait associations among genes suggested overlapping biological processes despite distinct functions. Drug target profile analysis revealed increased safety concerns due to genomic features (i.e., constraint, molecular interactions, and tissue specificity) for polyQ disorder genes, particularly ATN1, ATXN1, ATXN7, and HTT. PolyQ disorder genes also showed significantly more safety-related risks than HD genetic modifier genes (p = 7.03 × 10-3). In conclusion, our analyses emphasize the pleiotropic nature of polyQ disorder genes, highlighting their potential risks as drug targets. These findings reinforce the importance of exploring alternative therapeutic strategies, such as targeting genetic modifier genes, as well as allele-selective approaches, to mitigate these challenges.

Huntington's disease is caused by a CAG repeat in the HTT gene. Repeat length correlates inversely with the age of onset but only explains part of the observed clinical variability. Genome-wide association studies highlight DNA repair genes in modifying disease onset, but further research is required to identify causal genes and evaluate their tractability as drug targets. To address these gaps and learn important preclinical information, we analysed genome-wide association study data from a large Huntington's disease age-of-onset study (n = 9064), prioritizing robust candidate Huntington's disease modifier genes using bioinformatic approaches and analysing related information for these genes from large-scale human genetic repositories. We supplemented this information with other Huntington's disease-related screens, including exome studies of Huntington's disease onset and high-throughput assessments of mHTT toxicity. To confirm whether Huntington's disease modifiers are shared across repeat expansion disorders, we also analysed age-of-onset genome-wide association study data from X-linked dystonia-parkinsonism caused by a (CCCTCT)n expansion. We also studied modifier-related associations with rare diseases to inform potential off-target therapeutic effects and conducted comprehensive phenome-wide studies to identify other traits linked to these genes. Finally, we evaluated the aggregated human genetic evidence and theoretical druggability of the prioritized Huntington's disease modifier genes, including characteristics recently associated with clinical trial stoppage due to safety concerns (i.e. human genetic constraint, number of interacting partners and RNA tissue expression specificity). In total, we annotated and assessed nine robust candidate Huntington's disease modifier genes. Notably, we detected a high correlation (R 2 = 0.78) in top age-of-onset genome-wide association study hits across repeat expansion disorders, emphasizing cross-disorder relevance. Clinical genetic repositories analysis showed DNA repair genes, such as MLH1, PMS2 and MSH3, are associated with cancer phenotypes, suggesting potential limitations as drug targets. LIG1 and RRM2B were both associated with neurofibrillary tangles, which may provide a link to a potential role in mHTT aggregates, while MSH3 was associated with several cortical morphology-related traits relevant to Huntington's disease. Finally, human genetic evidence and theoretical druggability analyses prioritized and ranked modifier genes, with PMS1 exhibiting the most favourable profile. Notably, HTT itself ranked poorly as a theoretical drug target, emphasizing the importance of exploring modifier-based alternative targets. In conclusion, our study highlights the importance of human genomic information to prioritize Huntington's disease modifier genes as drug targets, providing a basis for future therapeutic development in Huntington's disease and other repeat expansion disorders.

INTRODUCTION:Cannabis products have been used in the management of headaches in adults and may play a role in pediatric chronic pain. Canadian pediatricians report increasing use of cannabis for the management of chronic headaches, despite no well-controlled studies to inform its dosing, safety, and effectiveness. The aim of our clinical trial is to determine the dosing and safety of a Cannabidiol (CBD)-enriched Cannabis Herbal Extract (CHE) for the treatment of chronic headaches in adolescents. METHODS AND ANALYSIS:Youth, parents, and an expert steering committee co-designed this tolerability study. Twenty adolescents (aged 14 to 17 years), with a chronic migraine diagnosis for more than 6 months that has not responded to other therapies will be enrolled into an open label, dose escalation study across three Canadian sites. Study participants will receive escalating doses of a CBD-enriched CHE (MPL-001 with a THC:CBD of 1:25), starting at 0.2-0.4 mg/kg of CBD per day and escalating monthly up to 0.8-1.0 mg/kg of CBD per day. The primary objective of this study is to determine the safety and tolerability of CBD-enriched CHE in adolescents with chronic migraine. Secondary objectives of this study will inform the development of subsequent randomized controlled trials and include investigating the relationship between the dose escalation and change in the frequency of headache, impact and intensity of pain, changes in sleep, mood, function, and quality of life. Exploratory outcomes include investigating steady-state trough plasma levels of bioactive cannabinoids and investigating how pharmacogenetic profiles affect cannabinoid metabolism among adolescents receiving CBD-enriched CHE. DISCUSSION:This protocol was co-designed with youth and describes a tolerability clinical trial of CBD-enriched CHE in adolescents with chronic headaches that have not responded to conventional therapies. This study is the first clinical trial on cannabis products in adolescents with chronic headaches and will inform the development of future comparative effectiveness clinical trials. TRIAL REGISTRATION:CAN-CHA trial is registered with ClinicalTrials.gov with a number of register NCT05337033.

Table S1 provides a summary of the genetic association results in the European only cohort

Figure S2 provides a visualization of the hearing thresholds of patients grouped by ACYP2 and WFS1 genotype

Figure S1 provides a visualization of the genetic ancestry of the cohort

Figure S4 provides examples of audiogram configurations

Genetic variation in CYP2B6 and CYP2A6 is known to impact interindividual response to antiretrovirals, nicotine, and bupropion, among other drugs. However, the full catalogue of clinically relevant pharmacogenetic variants in these genes is yet to be established, especially across African populations. This study therefore aimed to characterize the star allele (haplotype) distribution in CYP2B6 and CYP2A6 across diverse and understudied sub‐Saharan African (SSA) populations. We called star alleles from 961 high‐depth full genomes using StellarPGx, Aldy, and PyPGx. In addition, we performed CYP2B6 and CYP2A6 star allele frequency comparisons between SSA and other global biogeographical groups represented in the new 1000 Genomes Project high‐coverage dataset (n = 2,000). This study presents frequency information for star alleles in CYP2B6 (e.g., *6 and *18; frequency of 21–47% and 2–19%, respectively) and CYP2A6 (e.g., *4, *9, and *17; frequency of 0–6%, 3–10%, and 6–20%, respectively), and predicted phenotypes (for CYP2B6), across various African populations. In addition, 50 potentially novel African‐ancestry star alleles were computationally predicted by StellarPGx in CYP2B6 and CYP2A6 combined. For each of these genes, over 4% of the study participants had predicted novel star alleles. Three novel star alleles in CYP2A6 (*54, *55, and *56) and CYP2B6 apiece, and several suballeles were further validated via targeted Single‐Molecule Real‐Time resequencing. Our findings are important for informing the design of comprehensive pharmacogenetic testing platforms, and are highly relevant for personalized medicine strategies, especially relating to antiretroviral medication and smoking cessation treatment in Africa and the African diaspora. More broadly, this study highlights the importance of sampling diverse African ethnolinguistic groups for accurate characterization of the pharmacogene variation landscape across the continent.

Background: Ondansetron is a highly effective antiemetic for the treatment of nausea and vomiting. However, this medication has also been associated with QT prolongation. Pharmacogenomic information on therapeutic response to ondansetron exists, but no investigation has been performed on genetic factors that influence the cardiac safety of this medication. Methods: Three patient groups receiving ondansetron were recruited and followed prospectively (pediatric postsurgical patients n = 101; pediatric oncology patients n = 98; pregnant women n = 62). Electrocardiograms were conducted at baseline, and 5- and 30-min post-ondansetron administration, to determine the effect of ondansetron treatment on QT interval. Pharmacogenomic associations were assessed via analyses of comprehensive CYP2D6 genotyping and genome-wide association study data. Results: In the entire cohort, 62 patients (24.1%) met the criteria for prolonged QT, with 1.2% of the cohort exhibiting unsafe QT prolongation. The most significant shift from baseline occurred at five minutes postondansetron administration (P = 9.8 x 10(-4)). CYP2D6 activity score was not associated with prolonged QT. Genome-wide analyses identified novel associations with a missense variant in TLR3 (rs3775291; P = 2.00 x 10(-7)) and a variant linked to the expression of SLC36A1 (rs34124313; P = 1.97 x 10(-7)). Conclusions: This study has provided insight into the genomic basis of ondansetron-induced cardiac changes and has emphasized the importance of genes that have been implicated in serotonin-related traits. These biologically-relevant findings represent the first step towards understanding this adverse event with the overall goal to improve the safety of this commonly used antiemetic medication.

Depression during pregnancy affects 10–15% of women, and 5% of women take antidepressants during pregnancy. Clinical guidelines provide recommendations for selective serotonin reuptake inhibitor (SSRI) drug choice and dose based on CYP2D6 and CYP2C19 genotype; however, they are based on evidence from non-pregnant cohorts. This study aimed to test the hypothesis that women with function-altering variants (increased, decreased, or no function) in these pharmacogenes, taking SSRIs prenatally, would have more depression symptoms than women whose pharmacogenetic variants are associated with normal SSRI metabolism. Comprehensive CYP2D6 and CYP2C19 genotyping using a range of methods, including gene copy number analysis, was performed as secondary analyses on two longitudinal cohorts of pregnant women (N = 83) taking the SSRIs paroxetine, citalopram, escitalopram, or sertraline. The Kruskal–Wallis test compared mean depression scores across four predicted metabolizer groups: poor (n = 5), intermediate (n = 10), normal (n = 53), and ultrarapid (n = 15). There were no significant differences between mean depression scores across the four metabolizer groups (H(3) = .73, p = .87, eta-squared = .029, epsilon-squared = .0089). This is the first study of the relationship in pregnancy between CYP2C19 pharmacogenetic variations and depression symptoms in the context of SSRI use. Findings from this initial study do not support the clinical use of pharmacogenetic testing for SSRI use during the second or third trimesters of pregnancy, but these findings should be confirmed in larger cohorts. There is an urgent need for further research to clarify the utility of pharmacogenetic testing for pregnant women, especially as companies offering direct-to-consumer genetic testing expand their marketing efforts.

Polygenic scores (PGSs) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGSs for drug‐related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n = 30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGSs were derived from large‐scale genome‐wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g., schizophrenia‐derived PGSs for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGSs, with between 3 and 6.6 million variants included in the PGSs. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGSs deposited on the Polygenic Score Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

BACKGROUND & AIMS:According to pivotal clinical trials, cure rates for sofosbuvir-based antiviral therapy exceed 96%. Treatment failure is usually assumed to be because of virological resistance-associated substitutions or clinical risk factors, yet the role of patient-specific genetic factors has not been well explored. We determined if patient-specific genetic factors help predict patients likely to fail sofosbuvir treatment in real-world treatment situations.METHODS:We recruited sofosbuvir-treated patients with chronic hepatitis C from five Canadian treatment sites, and performed a case-control pharmacogenomics study assessing both previously published and novel genetic polymorphisms. Specifically studied were variants predicted to impair CES1-dependent production of sofosbuvir's active metabolite, interferon-λ signalling variants expected to impact a patient's immune response to the virus and an HLA variant associated with increased spontaneous and treatment-induced viral clearance.RESULTS:Three hundred and fifty-nine sofosbuvir-treated patients were available for analyses after exclusions, with 34 (9.5%) failing treatment. We identified CES1 variants as novel predictors for treatment failure in European patients (rs115629050 or rs4513095; odds ratio (OR): 5.43; 95% confidence interval (CI): 1.64-18.01; P = .0057), replicated associations with IFNL4 variants predicted to increase interferon-λ signalling (eg rs12979860; OR: 2.25; 95% CI: 1.25-4.06; P = .0071) and discovered a novel association with a coding variant predicted to enhance the activity of IFNL4's receptor (rs2834167 in IL10RB; OR: 1.81; 95% CI: 1.01-3.24; P = .047).CONCLUSIONS:Ultimately, this work demonstrates that patient-specific genetic factors could be used as a tool to identify patients at higher risk of treatment failure and allow for these patients to receive effective therapy sooner.

Cytochrome P450 2D6 (CYP2D6) is a key enzyme in drug response owing to its involvement in the metabolism of ~ 25% of clinically prescribed medications. The encoding CYP2D6 gene is highly polymorphic, and many pharmacogenetics studies have been performed worldwide to investigate the distribution of CYP2D6 star alleles (haplotypes); however, African populations have been relatively understudied to date. In this study, the distributions of CYP2D6 star alleles and predicted drug metabolizer phenotypes-derived from activity scores-were examined across multiple sub-Saharan African populations based on bioinformatics analysis of 961 high-depth whole genome sequences. This was followed by characterization of novel star alleles and suballeles in a subset of the participants via targeted high-fidelity Single-Molecule Real-Time resequencing (Pacific Biosciences). This study revealed varying frequencies of known CYP2D6 alleles and predicted phenotypes across different African ethnolinguistic groups. Twenty-seven novel CYP2D6 star alleles were predicted computationally and two of them were further validated. This study highlights the importance of studying variation in key pharmacogenes such as CYP2D6 in the African context to better understand population-specific allele frequencies. This will aid in the development of better genotyping panels and star allele detection approaches with a view toward supporting effective implementation of precision medicine strategies in Africa and across the African diaspora.

European superpopulation effect allele frequency.d Odds ratio (all other effects are beta estimates).