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PubMed2026

Rare variant analysis of whole genome sequenced juvenile idiopathic arthritis multiplex pedigrees identifies rare variants in NOD2 and ACVR1.

Juvenile idiopathic arthritis is a complex rheumatic disease that is influenced by environmental and genetic factors. Linkage and genome-wide association studies have identified genes that contribute to the risk of developing juvenile idiopathic arthritis but are limited in their ability to identify disease-risk variants of large effect. Penetrant, heritable risk variants can be detected in high-risk families, but such cases are uncommon due to the low prevalence of juvenile idiopathic arthritis. This study utilizes whole-genome sequencing of 23 multiplex families, the largest such cohort to date, to discover variants and genes relevant to JIA pathogenesis. Pathogenic variants in NOD2 associated with Blau syndrome, an ultra-rare Mendelian inflammatory disorder, are the most recurrent variants in the cohort, consistent with previous reports that milder presentations of Blau syndrome are oftentimes misdiagnosed as juvenile idiopathic arthritis. For the first time, however, rare variants in ACVR1 and SMAD6, integral components of the Bone Morphogenic Protein pathway, are found to be associated with juvenile idiopathic arthritis. Identified ACVR1 variants map to critical protein domains. AlphaFold modeling predicts that the ACVR1 interaction with its inhibitor OGT is disrupted by these variants, indicating that the patient-mutated protein has a gain-of-function phenotype. Drosophila melanogaster expressing either a wild-type or patient-mutated version of ACVR1 exhibit embryonic lethality, with the mutant exhibiting 1.4-fold greater lethality than wild-type. The combination of family-based cohorts for gene discovery, AI-based computational tools, and animal model studies for tests of variant function underscores shared disease pathogenesis between JIA and monogenic disorders of immunity and connective tissue.

Arthritis, Juvenile↗

PubMed2026

The Biobank Rare Variant consortium powers the discovery of rare genetic associations through global collaboration.

Rare coding variants can have large effects on disease risk and provide direct routes from human genetics to disease mechanisms and therapeutic targets, but their discovery is constrained by sample size, particularly for low-prevalence diseases. Here we establish the Biobank Rare Variant Analysis (BRaVa) consortium, a global rare variant association resource that integrates sequencing and linked health-record data from ten biobanks and cohorts comprising over 1.2 million individuals across diverse ancestries. We performed gene-based meta-analyses of rare coding variation across 33 clinical endpoints and 11 quantitative traits. Aggregating evidence across biobanks and ancestries identified 514 gene-trait associations, including 31 not previously reported in prior studies or curated association resources following systematic literature review. Notably, 36.1% of gene-level associations were undetectable in any individual biobank, and 91 emerged only through cross-ancestry meta-analysis, demonstrating that federated integration enables discovery beyond the reach of single cohorts. Similar gains were observed at the variant level, where 25.0% of phenotype-locus associations were detectable only through meta-analysis. Effect size estimates were correlated across ancestries with concordant directions of effect, supporting the generalizability of rare variant associations. The identified signals implicate pathways involved in transcriptional and epigenetic regulation, metabolism, vascular and epithelial biology, and immune function, highlighting rare coding variation as an engine for biological discovery across medical record phenotypes. For example, damaging variation in ANKRD12 implicates inflammatory transcriptional dysregulation in asthma and chronic obstructive pulmonary disease, and ultra-rare predicted loss-of-function variants in NAA15 link protein acetylation processes to type 2 diabetes risk. BRaVa establishes a scalable framework and freely available community resource for rare variant meta-analysis across global biobanks. Public release of gene- and variant-level association summary statistics provides a reference map of rare coding variant associations to support disease gene discovery, biological interpretation, and therapeutic target prioritization as sequencing-linked health-record resources continue to expand.

Journal Article↗

PubMed2022

Mortality Among Patients With Early-Onset Atrial Fibrillation and Rare Variants in Cardiomyopathy and Arrhythmia Genes.

IMPORTANCE: Patients with early-onset atrial fibrillation (AF) are enriched for rare variants in cardiomyopathy and arrhythmia genes. The clinical significance of these rare variants in patients with early-onset AF is unknown. OBJECTIVE: To assess the association between rare variants in cardiomyopathy and arrhythmia genes detected in patients with early-onset AF and time to death. DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study included participants with AF diagnosed before 66 years of age who underwent whole-genome sequencing through the National Heart, Lung and Blood Institute's Trans-Omics for Precision Medicine program. Participants were enrolled from November 23, 1999, to June 2, 2015. Data were analyzed from February 26 to September 19, 2021. EXPOSURES: Rare variants identified in a panel of 145 genes that are included in cardiomyopathy and arrhythmia panels used by commercial clinical genetic testing laboratories. MAIN OUTCOMES AND MEASURES: The primary study outcome was time to death and was adjudicated from medical records and the National Death Index. Multivariable Cox proportional hazards regression was used to evaluate the association of disease-associated variants with risk of death after adjustment for age at AF diagnosis, sex, race, body mass index, left ventricular ejection fraction, and an interaction term of age at AF diagnosis and disease-associated variant status. RESULTS: Among 1293 participants (934 [72%] male; median age at enrollment, 56.0 years; IQR, 48.0-61.0 years), disease-associated (pathogenic or likely pathogenic) rare variants were found in 131 (10%). During a median follow-up of 9.9 years (IQR, 6.9-13.2 years), 219 participants (17%) died. In univariable analysis, disease-associated variants were associated with an increased risk of mortality (hazard ratio, [HR], 1.5; 95% CI, 1.0-2.1; P = .05); the association remained significant in multivariable modeling when adjusted for age at AF diagnosis, sex, race, body mass index, left ventricular ejection fraction, and an interaction term between disease-associated variant status and age at AF diagnosis. The interaction demonstrated that disease-associated variants were associated with a significantly higher risk of mortality compared with no disease-associated variant when AF was diagnosed at a younger age (P = .008 for interaction). Higher body mass index (per IQR: HR, 1.4; 95% CI, 1.2-1.6; P < .001) and lower left ventricular ejection fraction (per IQR: HR, 0.8; 95% CI, 0.7-0.8; P < .001) were associated with higher mortality risk. There were 73 cardiomyopathy-related deaths, 40 sudden deaths, and 10 stroke-related deaths. Mortality among patients with the most prevalent genes with disease-associated variants was 26% (10 of 38 patients) for TTN, 33% (6 of 18) for MYH7, 22% (2 of 9) for LMNA, 0% (0 of 10) for MYH6, and 0% (0 of 8) for KCNQ1. CONCLUSIONS AND RELEVANCE: The findings suggest that rare variants in cardiomyopathy and arrhythmia genes may be associated with increased risk of mortality among patients with early-onset AF, especially those diagnosed at a younger age. Genetic testing may provide important prognostic information for patients with early-onset AF.

Atrial Fibrillation↗

PubMed2026

Rare variant effect estimation and polygenic risk prediction.

Due to their low frequency, estimating the effects of rare variants is challenging. Here we propose RareEffect, a method that first estimates gene-based or region-based heritability and then each variant effect size using an empirical Bayes approach. Our method uses a variance component model, which is popular in rare variant tests, and is designed to provide two levels of effect sizes-gene/region level and variant level-that can provide better interpretation. To adjust for the case-control imbalance in phenotypes, our approach uses a fast implementation of the Firth bias correction. We demonstrate the accuracy and computational efficiency of our method through extensive simulations and analysis of UK Biobank whole-exome sequencing data for 100 traits. Additionally, we show that the effect sizes obtained from our model can be leveraged to improve polygenic score performance, thereby outperforming recently developed methods for rare variant polygenic scoring.

Humans↗

PubMed2024

Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes.

Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5 × 10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.

Diabetes Mellitus, Type 2↗

PubMed2026

RAREsim2: flexible simulation of rare variant genetic data using real haplotypes.

MOTIVATION: Realistic simulated data is critical for advancing methodological development and optimizing study design in genetics research. However, many genetic simulation tools are unable to replicate the distribution of rare variants or incorporate key genetic information, such as functional annotations and linkage disequilibrium. RAREsim, an accurate rare variant simulation algorithm that uses real genetic haplotypes, was developed to address these limitations. Here, we introduce RAREsim2, an update that provides both streamlined software and new functionalities for simulating individual-level differences (e.g., case-control status, technological or batch effects) and variant-level differences to represent a variety of causal models. RESULTS: We demonstrate RAREsim2's utility with three rare variant association methods (Burden, SKAT, and SKAT-O) across several simulation scenarios, including various genetic ancestries, gene sizes, strengths of association, and proportions of risk variants. Type I Error was maintained and the test with the highest power matched previously known patterns. Importantly, real genetic regions can be simulated to include known variant functions and disease associations. Ultimately, RAREsim2 offers additional flexibility and ease in simulating a multitude of realistic genetic scenarios. AVAILABILITY AND IMPLEMENTATION: The RAREsim2 Python package is publicly available on Github (https://github.com/Hendricks-Research-Team/RAREsim2), PyPI (https://pypi.org/project/raresim/), and Zenodo (https://doi.org/10.5281/zenodo.19442523). Code for the example demonstration can be found at https://github.com/JessMurphy/RAREsim2-demo.

Software↗

PubMed2025

Leveraging functional annotations to map rare variants associated with Alzheimer disease with gruyere.

Increased availability of whole-genome sequencing (WGS) has facilitated the study of rare variants (RVs) in complex diseases. Multiple RV association tests are available to study the relationship between genotype and phenotype, but most do not fully leverage the availability of variant-level functional annotations. We propose genome-wide rare variant enrichment evaluation (gruyere), an empirical Bayesian framework that complements existing methods by learning global, trait-specific weights for functional annotations to improve variant prioritization. We apply gruyere to WGS data from the Alzheimer's Disease Sequencing Project to identify Alzheimer disease (AD)-associated genes and annotations. Growing evidence suggests that the disruption of microglial regulation is a key contributor to AD risk, yet existing methods have not examined rare non-coding effects that incorporate such cell-type-specific information. To address this gap, we (1) define per-gene non-coding RV test sets using predicted enhancer and promoter regions in microglia and other brain cell types (oligodendrocytes, astrocytes, and neurons) and (2) include cell-type-specific variant effect predictions (VEPs) as functional annotations. gruyere identifies 13 significant genetic associations not detected by other RV methods, four of which remain significant in omnibus tests. We find that deep-learning-based VEPs for splicing, transcription factor binding, and chromatin state are highly predictive of functional non-coding RVs. Our study establishes a robust framework incorporating functional annotations, coding RVs, and cell-type-associated non-coding RVs to perform genome-wide association tests, uncovering AD-relevant genes and annotations.

Alzheimer Disease↗

PubMed2026

Integrating multi-ancestry common and rare variant mapping accelerates therapeutic target discovery.

Integrating human genetics into therapeutic discovery accelerates drug development. However, ancestral biases in historical cohorts have left critical functional variation largely uncharted. Here, we leverage the diverse NIH All of Us Research Program to conduct comprehensive common- and rare-variant association analyses for 624 quantitative traits across 369,655 ancestrally diverse individuals. We identified 6,181 genome-wide significant locus-trait associations (526 novel) and 416 gene-trait associations (105 novel) via rare-variant burden testing. By integrating fine-mapping with computational variant-effect predictors, we systematically prioritized rare, likely causal variants driving these signals. Jointly modeling common and rare variation with protein-class annotations significantly improved the identification of known drug targets compared to common-variant analysis alone. Notably, we identified NRG4 as a high-confidence candidate therapeutic target for preserving kidney function. Our findings demonstrate that characterization of rare and common variation across diverse populations enhances causal gene discovery and identifies novel, actionable therapeutic targets.

Journal Article↗

PubMed2025

Rare variants in MIR184 are a novel genetic cause of Fuchs endothelial corneal dystrophy.

PURPOSE: To identify novel genetic causes of Fuchs endothelial corneal dystrophy (FECD) within a genetically unsolved patient cohort lacking repeat expansions in the TCF4 gene (Exp-). METHODS: A rare variant analysis framework (CoCoRV) was applied to exome data, in combination with in silico modeling, luciferase reporter, and RNA-seq analysis to characterize transcriptome-wide consequences of identified variants. RESULTS: A gene burden analysis identified MIR184, a microRNA encoding gene, to be enriched for rare pathogenic variants within the studied Exp- FECD cohort. In total, 2 noncoding rare variants were identified in 4 unrelated FECD probands: NR_029705.1:n.58G>A and n.73G>T. Both variants altered highly conserved mature sequence residues, were predicted to induce hairpin structural changes, and were experimentally determined to disrupt microRNA-mRNA interactions. RNA-seq of transfected human corneal endothelial cells revealed that the mutants elicited distinct transcriptomic profiles. Enriched KEGG pathways included PI3K-Akt signaling, focal adhesion, and immune response, revealing shared pathogenic mechanisms between MIR184-associated FECD and the more common TCF4 repeat expansion-mediated form of disease. CONCLUSION: MIR184 variants are a novel rare genetic cause of FECD, and common pathways of transcriptomic dysregulation are shared across genetically distinct subtypes of the disease. These pathways may serve as future gene agnostic targets for therapeutic interventions.

Humans↗

PubMed2024

Rare variant contribution to the heritability of coronary artery disease.

Whole genome sequences (WGS) enable discovery of rare variants which may contribute to missing heritability of coronary artery disease (CAD). To measure their contribution, we apply the GREML-LDMS-I approach to WGS of 4949 cases and 17,494 controls of European ancestry from the NHLBI TOPMed program. We estimate CAD heritability at 34.3% assuming a prevalence of 8.2%. Ultra-rare (minor allele frequency ≤ 0.1%) variants with low linkage disequilibrium (LD) score contribute ~50% of the heritability. We also investigate CAD heritability enrichment using a diverse set of functional annotations: i) constraint; ii) predicted protein-altering impact; iii) cis-regulatory elements from a cell-specific chromatin atlas of the human coronary; and iv) annotation principal components representing a wide range of functional processes. We observe marked enrichment of CAD heritability for most functional annotations. These results reveal the predominant role of ultra-rare variants in low LD on the heritability of CAD. Moreover, they highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

Humans↗

PubMed2026

Systematic common and rare variant association testing in 392,030 whole genomes in All of Us.

Large-scale genome-wide association studies (GWAS) and rare variant association studies (RVAS) from population biobanks provide valuable resources for gene discovery in complex human traits. We present an analysis of the All of Us Research Program v8 release, which includes whole genome sequencing data and harmonized phenotypic information of 392,030 participants after quality control, enabling a unified investigation of rare and common variants across a spectrum of human traits and diseases. We build an extensive phenome- and genome-wide ("All by All") computational framework to perform GWAS and RVAS on 3,602 phenotypes and identify 49,863 approximately independent, high-quality single-variant and gene-level associations. Meta-analyses of All of Us and UK Biobank, with sample sizes as large as 786,871 participants, further enhance statistical power and find 193 pLoF gene-phenotype associations that are not significant in either cohort alone, including 22 associations not highlighted by previous studies. We also present a public interactive browser that integrates association results for common and rare variants to facilitate interpretation and rapid querying of summary statistics, along with supporting documentation, and a Featured Workspace in the All of Us Researcher Workbench. Our framework will apply to iterative data releases as All of Us grows, empowering researchers worldwide to uncover insights into the functional effects of genetic components on complex traits and diseases.

Journal Article↗

PubMed2026

Genome-Wide and Rare Variant Association Studies of Amblyopia in Admixed American and African Ancestry Groups.

OBJECTIVE: To identify genetic variants associated with amblyopia in African (AFR) and Admixed American (AMR) ancestry groups, expanding on previous studies conducted in European ancestry. DESIGN: Retrospective ancestry-stratified genome-wide association study (GWAS) and gene-level rare variant association study (RVAS). PARTICIPANTS: Participants in the All of Us Research Program from AFR and AMR ancestry groups who had whole-genome sequencing available. Cases and controls were distinguished based on the presence of International Classification of Diseases 9/10/SNOMED diagnosis codes for amblyopia in electronic health records. This yielded ancestry-stratified subsets of 269 cases and 71 585 controls of AMR ancestry and 366 cases and 79 460 controls of AFR ancestry. METHODS: Stratified logistic regression models were adjusted for age, biological sex, and the top 10 principal components of genomic ancestry. GWAS was limited to common variants (minor allele frequency ≥1%), and RVAS was limited to rare variants with coding sequence-altering effects (minor allele frequency >1%, exonic only, excluding synonymous variants) aggregated at the gene level using the SKAT algorithm. Downstream analyses of the significant variants were performed using KEGG and GO pathway analysis and STRING database queries for protein-protein interactions and gene-gene interactions. MAIN OUTCOME MEASURES: Single-nucleotide polymorphisms were determined to have genome-wide significance if P < 5e-8 in the GWAS, and genes were determined to have significant association with amblyopia in the RVAS if P < 8.0 × 10-4. RESULTS: In the AMR GWAS, 245 unique single-nucleotide polymorphisms mapping to 97 distinct loci were identified, notably within neurodevelopmental and axonal guidance genes, including ROBO1, SEMA4B, PTPRD, NRXN1, and CAMK2D. The AFR GWAS identified 11 significant variants corresponding to 6 loci mapping primarily to long noncoding RNAs and pseudogenes. The AMR RVAS identified 15 genes, including axonal transport genes (KIF1B and KIF7) and growth factor signaling genes (EGF, ERBIN, and AKAP17A). The AFR RVAS identified a single gene, DLG2, which encodes the postsynaptic protein PSD-93, which promotes the closure of the sensitive period of neuroplasticity for vision in early childhood. CONCLUSIONS: Genetic risk architectures for amblyopia differ across ancestries but fundamentally converge on neurodevelopmental signaling, cortical synapse assembly, and sensitive period plasticity rather than ocular structural dynamics. FINANCIAL DISCLOSURE(S): The authors have no proprietary or commercial interest in any materials discussed in this article.

Amblyopia↗

PubMed1978

Rare variants, private polymorphisms, and locus heterozygosity in Amerindian populations.

The results of 21,103 electrophoretic typings distributed across 28 polypeptides in members of 12 Amerindian tribes are reported, and the accumulated results of electrophoretic studies on these same polypeptides in 21 Amerindian tribes are then analyzed. Thus far 11 'private' polymorphisms have been identified in these tribes. When the tribal samples are combined and traits achieving polymorphic proportions in the total sample excluded from consideration, the average frequency of rare variants is 2.8 per 1,000 determinations. For a subset of 23 of these polypeptides also studied in Caucasians and Japanese, variant frequencies per 1,000 determinations are: Indians, 2.2; Caucasians (British), 1.6; and Japanese, 1.5. Average locus heterogeneity for these polypeptides (based on rare variants plus polymorphisms) is: Indians, .049; Caucasians, .078; and Japanese, .077. A higher proportion of loci are monomorphic within tribes than within civilized urban populations. It is argued that for inferences concerning the forces maintaining genetic variability within populations, studies on samples from tribespeople are much more appropriate than studies on samples from civilized urban populations.

Blood Proteins↗

PubMed2021

Early-Onset Atrial Fibrillation and the Prevalence of Rare Variants in Cardiomyopathy and Arrhythmia Genes.

IMPORTANCE: Early-onset atrial fibrillation (AF) can be the initial manifestation of a more serious underlying inherited cardiomyopathy or arrhythmia syndrome. OBJECTIVE: To examine the results of genetic testing for early-onset AF. DESIGN, SETTING, AND PARTICIPANTS: This prospective, observational cohort study enrolled participants from an academic medical center who had AF diagnosed before 66 years of age and underwent whole genome sequencing through the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine program. Participants were enrolled from November 23, 1999, to June 2, 2015. Data analysis was performed from October 24, 2020, to March 11, 2021. EXPOSURES: Rare variants identified in a panel of 145 genes that are included on cardiomyopathy and arrhythmia panels used by commercial clinical genetic testing laboratories. MAIN OUTCOMES AND MEASURES: Sequencing data were analyzed using an automated process followed by manual review by a panel of independent, blinded reviewers. The primary outcome was classification of rare variants using American College of Medical Genetics and Genomics criteria: benign, likely benign, variant of undetermined significance, likely pathogenic, or pathogenic. Disease-associated variants were defined as pathogenic/likely pathogenic variants in genes associated with autosomal dominant or X-linked dominant disorders. RESULTS: Among 1293 participants (934 [72.2%] male; median [interquartile range] age at enrollment, 56 [48-61] years; median [interquartile range] age at AF diagnosis, 50 [41-56] years), genetic testing identified 131 participants (10.1%) with a disease-associated variant, 812 (62.8%) with a variant of undetermined significance, 92 (7.1%) as heterozygous carriers for an autosomal recessive disorder, and 258 (20.0%) with no suspicious variant. The likelihood of a disease-associated variant was highest in participants with AF diagnosed before the age of 30 years (20 of 119 [16.8%; 95% CI, 10.0%-23.6%]) and lowest after the age of 60 years (8 of 112 [7.1%; 95% CI, 2.4%-11.9%]). Disease-associated variants were more often associated with inherited cardiomyopathy syndromes compared with inherited arrhythmias. The most common genes were TTN (n = 38), MYH7 (n = 18), MYH6 (n = 10), LMNA (n = 9), and KCNQ1 (n = 8). CONCLUSIONS AND RELEVANCE: In this cohort study, genetic testing identified a disease-associated variant in 10% of patients with early-onset AF (the percentage was higher if diagnosed before the age of 30 years and lower if diagnosed after the age of 60 years). Most pathogenic/likely pathogenic variants are in genes associated with cardiomyopathy. These results support the use of genetic testing in early-onset AF.

Adult↗

PubMed2024

Association of common and rare variants with Alzheimer's disease in more than 13,000 diverse individuals with whole-genome sequencing from the Alzheimer's Disease Sequencing Project.

INTRODUCTION: Alzheimer's disease (AD) is a common disorder of the elderly that is both highly heritable and genetically heterogeneous. METHODS: We investigated the association of AD with both common variants and aggregates of rare coding and non-coding variants in 13,371 individuals of diverse ancestry with whole genome sequencing (WGS) data. RESULTS: Pooled-population analyses of all individuals identified genetic variants at apolipoprotein E (APOE) and BIN1 associated with AD (p < 5 × 10-8). Subgroup-specific analyses identified a haplotype on chromosome 14 including PSEN1 associated with AD in Hispanics, further supported by aggregate testing of rare coding and non-coding variants in the region. Common variants in LINC00320 were observed associated with AD in Black individuals (p = 1.9 × 10-9). Finally, we observed rare non-coding variants in the promoter of TOMM40 distinct of APOE in pooled-population analyses (p = 7.2 × 10-8). DISCUSSION: We observed that complementary pooled-population and subgroup-specific analyses offered unique insights into the genetic architecture of AD. HIGHLIGHTS: We determine the association of genetic variants with Alzheimer's disease (AD) using 13,371 individuals of diverse ancestry with whole genome sequencing (WGS) data. We identified genetic variants at apolipoprotein E (APOE), BIN1, PSEN1, and LINC00320 associated with AD. We observed rare non-coding variants in the promoter of TOMM40 distinct of APOE.

Humans↗

PubMed2026

Investigating genetic susceptibility to concussion through rare variants in ion channel and neurotransmission genes.

Some individuals appear more susceptible to concussion or mild traumatic brain injury (mTBI) and the severity, range, and the persistence of post-concussion symptoms vary considerably between affected individuals. Genetic factors are likely to contribute to this variability. Symptomatic overlap of post-concussion syndrome with neurological conditions such as familial hemiplegic migraine (FHM) caused by rare pathogenic variants in ion channel and synapse protein genes, with high sensitivity to head trauma for some patients, suggests that variation in similar pathways may influence concussion susceptibility and recovery. To investigate this hypothesis, we performed whole exome sequencing in 93 unrelated individuals who had sustained a single or multiple concussions and examined rare protein-altering variants in FHM genes, other neuronal ion channel and transporter genes, and genes involved in neurotransmission. We identified 62 different rare missense variants across 24 genes in 59 participants (63%), with 26 individuals carrying 2 or more variants. The prevalence of specific likely damaging rare variants in the 16 ion channel-related genes that were identified was approximately fivefold higher than that observed from gnomAD population controls (Odds Ratio = 5.44, 95% CI [4.13,7.18], P < 0.0001). Notably, voltage-gated calcium and sodium channel genes, including SCN9A, together with neurotransmission-related genes such as SNCAIP, harboured multiple potentially deleterious variants. These findings suggest that rare deleterious variants in genes involved in ion homeostasis and neurotransmission may contribute to an individual's susceptibility to concussion or more severe post-concussion symptoms. This study provides a foundation for future genetic and functional investigations aimed at improving our understanding of concussion susceptibility and outcomes. Further validation in larger cohorts and mechanistic studies is warranted to determine their utility as biomarkers of concussion risk and prognosis.

Humans↗

PubMed2024

Validating the splicing effect of rare variants in the SLC26A4 gene using minigene assay.

BACKGROUND: The SLC26A4 gene is the second most common cause of hereditary hearing loss in human. The aim of this study was to utilize the minigene assay in order to identify pathogenic variants of SLC26A4 associated with enlarged vestibular aqueduct (EVA) and hearing loss (HL) in two patients. METHODS: The patients were subjected to multiplex PCR amplification and next-generation sequencing of common deafness genes (including GJB2, SLC26A4, and MT-RNR1), then bioinformatics analysis was performed on the sequencing data to identify candidate pathogenic variants. Minigene experiments were conducted to determine the potential impact of the variants on splicing. RESULTS: Genetic testing revealed that the first patient carried compound heterozygous variants c.[1149 + 1G > A]; [919-2 A > G] in the SLC26A4 gene, while the second patient carried compound heterozygous variants c.[2089 + 3 A > T]; [919-2 A > G] in the same gene. Minigene experiments demonstrated that both c.1149 + 1G > A and c.2089 + 3 A > T affected mRNA splicing. According to the ACMG guidelines and the recommendations of the ClinGen Hearing Loss Expert Panel for ACMG variant interpretation, these variants were classified as "likely pathogenic". CONCLUSIONS: This study identified the molecular etiology of hearing loss in two patients with EVA and elucidated the impact of rare variants on splicing, thus contributing to the mutational spectrum of pathogenic variants in the SLC26A4 gene.

Humans↗

PubMed2025

Rare variants and survival of patients with idiopathic pulmonary fibrosis: analysis of a multicentre, observational cohort study with independent validation.

BACKGROUND: Rare pathogenic variants in telomere-related genes are associated with poorer clinical outcomes in idiopathic pulmonary fibrosis (IPF). We aimed to assess whether rare qualifying variants in monogenic adult-onset pulmonary fibrosis genes are associated with IPF survival. Using polygenic risk scores (PRS), we also evaluated the influence of common IPF risk variants in patients carrying the qualifying variants. METHODS: We identified qualifying variants in telomere and non-telomere genes using whole-genome sequences from individuals clinically diagnosed with IPF and enrolled in the Pulmonary Fibrosis Foundation Patient Registry (PFFPR), a large multicentre, observational cohort study (March 29, 2016 to June 15, 2018, n=888). We also derived a PRS for IPF (PRS-IPF) from known common sentinel IPF variants. The primary outcome was the association between qualifying variants and survival. The secondary outcome was the association between qualifying variants and PRS-IPF. We used logistic regression models adjusted for sex, age at diagnosis, and principal components of genetic heterogeneity to examine the mutual relationship of qualifying variants and PRS-IPF. The association between qualifying variants and PRS-IPF with survival was tested using Cox proportional hazard models adjusted for baseline confounders. Validation of the results was sought in data from an independent multicentre, prospective, observational cohort study of IPF in the UK (PROFILE, May 17, 2010 to Sept 5, 2017, n=472), and results were meta-analysed under a fixed-effects model. FINDINGS: We included 888 patients from PFFPR and 472 from PROFILE, totalling 1360 participants. In the PFFPR, carriers of qualifying variants in monogenic adult-onset pulmonary fibrosis genes were associated with lower PRS-IPF (odds ratio 1·79 [95% CI 1·15-2·81]; p=0·010) and shorter survival (hazard ratio 1·53 [1·12-2·10]; p=7·33 × 10-3). Individuals with the lowest PRS-IPF also had worse survival (1·61 [1·25-2·07]; p=1·87 × 10-4). These findings were validated in PROFILE and the meta-analysis of the results showed a consistent direction of effect across both cohorts. INTERPRETATION: We found non-additive effects between qualifying variants and common risk variants in IPF survival, suggesting distinct disease subtypes and raising the possibility of using PRS to guide sequencing prioritisation. Assessing the carrier status for qualifying variants and modelling PRS-IPF promises to further contribute to predicting disease progression among patients with IPF. FUNDING: Instituto de Salud Carlos III; Instituto Tecnológico y de Eenergías Renovables; Cabildo Insular de Tenerife; Fundación DISA; National Heart, Lung, and Blood Institute of the US National Institutes of Health; and UK Medical Research Council.

Humans↗