Human Genetics

Primary open-angle glaucoma (POAG) disproportionately affects individuals of African ancestry, yet rare coding variation in this population remains understudied. To address this gap, we performed a multi-cohort exome-wide meta-analysis across POAAGG, PMBB, All of Us, and UK Biobank, including 4,815 POAG cases and 22,922 controls of genetically inferred African ancestry. Although no gene reached exome-wide significance, we identified several suggestive gene-level associations driven by rare variants (minor allele frequency [≤]0.1% or singletons),including signals in SRF, BLTP3A, METTL2A, and KRT10. Among these, SRF demonstrated the strongest association and was driven by rare missense variants with moderate effect sizes. Given its role in cytoskeletal organization and actin dynamics; processes central to trabecular meshwork function and intraocular pressure regulation SRF represents a biologically plausible candidate gene. Notably, these genes have not been previously highlighted in predominantly European ancestry POAG association studies, suggesting potential ancestry-specific rare variant contributions. Overall, our findings highlight the critical importance of investigating rare coding variation in POAG, in disproportionately affected populations to deepen understanding of POAG etiology and genetic risk.

ImportanceGenome-wide association studies have identified hundreds of common single nucleotide polymorphisms (SNPs) and small insertions/deletions (indels) associated with primary open-angle glaucoma (POAG) risk, though these variants have modest effect sizes and individually may have minor contributions to disease development. As whole-genome sequencing data is becoming more readily available, structural variants and other complex genomic features can be interrogated for contribution to disease risk. ObjectiveTest the association of structural variants in known glaucoma loci with disease risk. DesignCross-sectional study. SettingA multicenter cohort of individuals from the United States who contributed genomic and electronic health record data to the All of Us Research Program. ParticipantsPOAG case/control cohorts were generated in the All of Us Researcher Workbench using age (>40 for cases, >65 for controls) and ICD 9/10 diagnosis codes. Main Outcomes and MeasuresLogistic regression analyses adjusted for age, sex, and the top 10 principal components of ancestry were used to test association of structural variants within 500 kilobases of 309 known open-angle glaucoma risk loci. The significance threshold after Bonferroni correction was set at p<1.6x10-4. Results516 POAG cases and 18,716 controls of European ancestry from the All of Us v8 data release were included in the analysis. Mean age was 77.0 years among cases and 74.7 years among controls. Females comprised 45.7% of cases and 56.5% of controls. An 8,732 base pair deletion upstream of PITX2 (chr4:110680827-110689558) was associated with 7.3-fold higher odds of POAG (95% confidence interval: 2.9-18.5, p= 2.4x10-5, variant carrier frequency= 1.6% in cases and 0.25% in controls). Functional annotation identified multiple enhancers overlapping the deletion, suggesting that this structural variant likely impacts gene regulation and expression. Conclusion and RelevanceWhole genome sequencing data captures rare structural variants with large effect sizes that are missed by conventional SNP and indel genotyping approaches, enabling improved POAG risk stratification. These data also expand the phenotypic spectrum of structural variation in the PITX2 locus from childhood glaucoma to adult-onset disease, where age at diagnosis and clinical severity may be influenced by the extent of disrupted regulatory elements.

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=3.30x10-9), 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.

Menieres disease (MD) is a chronic inner ear disorder characterized by recurrent vertigo, fluctuating sensorineural hearing loss, and tinnitus. Despite these distinctive symptoms, its etiology remains poorly understood. We performed a genome-wide meta-analysis of 8,969 cases and 1,962,542 controls across five large biobanks, identifying five independent genome-wide significant loci and estimating an observed-scale SNP heritability of 7% (SE 0.8%), consistent with a modest but significant genetic contribution to MD risk. Fine-mapping and integrative functional analyses implicate two convergent biological processes - developmental regulation of the inner ear, involving EYA4, EYA1, and LMO4 - and retinoic acid metabolism, with loci near CYP26A1/C1 and ALDH1A2 suggesting disrupted RA signaling in sensory and fluid-pressure homeostasis. These developmental regulator genes are robustly expressed in fetal and adult human inner ear cell types, supporting a model in which altered developmental programs predispose to adult vestibular and auditory dysfunction. Phenome-wide and genetic correlation analyses further reveal shared genetic architecture between MD and related traits, including vertigo, tinnitus, hearing loss, migraine, and sleep apnea, situating MD within a broader spectrum of sensory and neurological disorders. Collectively, these findings establish a genetic framework for Menieres disease risk and implicate developmental regulators and retinoic acid signaling as key contributing pathways.

The genetic relationship between asthma and lung function may be dependent on age-at-onset (AAO) of asthma. We investigated whether the shared genetics between asthma AAO and lung function is dependent on AAO. Asthma cases from UK Biobank were subset according to their AAO and genetic correlation was used to obtain genetically homogeneous groups, i.e., [&le;]20 (LT20), 20-40, and >40 (GT40) years. Association analysis and fine-mapping were performed to identify shared genetics between AAO groups and lung function. Mediation and quantitative trait locus (QTL) analyses were performed to identify mechanisms underlying shared genetic associations. Chr5, chr6, chr12, and chr17 each had one region that displayed a cross-phenotype replicated association with at least one AAO group and lung function. Overlapping credible sets obtained from fine-mapping were observed on chr5 and chr6. Mediation analyses demonstrated that for each region the proportion mediated through asthma on lung function was larger for asthma LT20 compared to 20-40 and GT40 suggesting that their effects on lung function were more strongly driven by this association. Tissue-specific QTL analysis revealed shared etiology on chr5 may be acting through SLC22A5 and C5orf56 which might play an important role in decreased lung function among individuals with earlier-onset asthma.

Rhabdomyolysis is the acute breakdown of skeletal muscle resulting from failure of cellular homeostasis in response to metabolic stress. Recurrent forms are frequently linked to inherited defects affecting energy metabolism or calcium handling. Ryanodine receptor type 3 (RyR3) is an intracellular calcium release channel, expressed in skeletal muscle, that contributes to the fine-tuning of calcium signaling. Although variants in other calcium-handling proteins have been implicated in rhabdomyolysis, the role of RyR3 has not been established. In this study, we report rare compound heterozygous missense variants in RYR3 identified in two unrelated individuals with severe, fever-triggered recurrent rhabdomyolysis. Muscle biopsies revealed mild structural changes with triadic disorganization, mitochondrial alterations, lipid accumulation, and autophagic material, while overall muscle architecture was largely preserved. Structural modeling supports the pathogenicity of the variants, and calcium flux analysis demonstrated significantly reduced ryanodine receptor-mediated calcium release in patient-derived myoblasts. Functional analyses showed that RyR3 deficiency impaired starvation-induced autophagy, characterized by defective autophagosome formation and reduced autophagic flux, and increased susceptibility to metabolic stress. Mitochondrial bioenergetic profiling revealed reduced oxidative phosphorylation capacity and decreased membrane potential under stress conditions, consistent with compromised mitochondrial adaptation. In zebrafish, ryr3 knockdown resulted in structural and functional muscle abnormalities, including reduced myotome area and decreased locomotor activity, associated with impaired autophagic flux. This study establishes a novel association between recessive RYR3 variants and recurrent rhabdomyolysis and identifies RyR3 as a critical regulator of skeletal muscle stress adaptation through calcium-dependent control of autophagy and mitochondrial homeostasis. More broadly, our findings further highlight autophagy as a central determinant of muscle resilience in the context of rhabdomyolysis.

Low-frequency variants (LFVs), defined by minor allele frequencies (MAF) of 1-5%, occupy the gap between common and rare variants in both frequency and effect size. The conventional genome-wide association study (GWAS) significance threshold (5x10-) is overly conservative for LFVs, which account for more than 25% of variants in GWAS. This limitation may obscure meaningful associations in highly heritable yet genetically complex disorders such as autism spectrum disorder (ASD). We hypothesize that the scarcity of significant LFVs in ASD GWAS reflects statistical constraints rather than a true lack of association. To address this, we derived a MAF-specific genome-wide significance threshold using linkage disequilibrium-informed simulations applied to ASD GWAS summary statistics, identifying 2.03x10- as optimal. Applying this threshold revealed three novel LFVs mapping to zinc finger proteins (ZNF420, ZNF781) and known ASD-related genes (KMT2E, PRKDC, MCM4). Enrichment analyses suggested their function in nervous system development and gene regulation. Our findings highlight the contribution of LFVs to ASD risk and underscore the importance of frequency-aware association strategies.

PurposeFuchs endothelial corneal dystrophy (FECD) is a common corneal disease and a leading indication for endothelial keratoplasty (EK). Although CTG18.1 repeat expansion is a major genetic risk factor, the contribution of polygenic background to disease progression remains unclear. We evaluated whether combining CTG18.1 expansion status with a FECD-specific polygenic risk score (PRS) enables genomic prediction of progression to EK. MethodsWe retrospectively analysed 589 individuals with FECD from two European centers, with replication in an independent cohort of 185 individuals. Association of CTG18.1 expansion ([&ge;]50 repeats) and PRS with time to EK were evaluated using Cox models adjusted for sex and ancestry. ResultsExpansion-positive status was associated with earlier EK (HR 2.30; 95% CI 1.62- 3.26; P<.001). Addition of PRS improved prediction (C-index 0.614 vs 0.602; P=.014). Each 1-SD increase in PRS was associated with earlier EK (HR 1.16; 95% CI 1.03-1.30; P=.015), with replication in the validation cohort (HR 1.42; 95% CI 1.15-1.75; P=.001). ConclusionIntegration of monogenic and polygenic risk enables genomic prediction of FECD progression, supporting clinical genomic risk stratification to inform individualized monitoring and timing of intervention.

Autism spectrum disorder (ASD; MIM 209850) is reported to vary globally from 0.01% in East Asian populations to 4.36% in certain Australian cohorts. Despite high heritability estimates (61-94%), the genetic architecture underlying ASD susceptibility remains poorly characterized across diverse populations, as most genomic studies have initially focused on individuals of European ancestry. To investigate ancestry-specific genetic contributions to ASD, we analyzed whole-genome sequencing data from three independent ASD cohorts. We identified admixed ASD probands (n = 1 033) and ancestry-matched controls (n = 1 033) and performed admixture mapping (AM). AM using five continental reference populations (European, African, East Asian, South Asian, and Native American) identified five ancestry-specific ASD-susceptibility loci, including one African-related locus at 1p21.2 near S1PR1 and four Native American-associated loci at chromosome 11q13.4. Three of these latter loci were contiguous and encompassed genes previously implicated in ASD, notably SHANK2 and DHCR7, with fine-mapping identifying a significantly associated variant between the two genes (rs77695321; P = 1.52 x 10-). The fourth Native American-associated signal at 11q13.4 overlapped the folate receptor genes FOLR1 and FOLR3, with fine-mapping identifying a genome-wide significant variant (rs7950807; P = 5.21 x 10-). A secondary admixture mapping analysis restricted to Latin American individuals, incorporating 6 487 Brazilian controls, identified 16 additional ancestry-specific loci across seven genomic regions.

LDB1 encodes transcriptional regulator protein LIM-domain-binding protein 1, which plays an important role in neurogenesis. Few C-terminal likely gene disrupting (LGD) variants have been reported in the literature in individuals with congenital ventriculomegaly. Through international collaboration, we now assembled a cohort of 16 individuals with de novo variants affecting various regions of LDB1. Eleven variants affect either the whole gene or the N-terminal dimerization domain (including gene deletions, NMD-sensitive LGD-, and missense variants) and five variants (missense or NMD-escaping LGD variants) affect only the C-terminus of LDB1 containing the LIM interaction domain. All individuals showed variable neurodevelopmental phenotypes, including developmental delay and behavioral anomalies. In line with literature reports, individuals harboring C-terminal variants additionally presented with ventriculomegaly, establishing a genotype-phenotype correlation. In accordance, we found diverging pathomechanisms in vitro: N-terminal missense variants disrupt homodimerization of LDB1, likely leading to a loss of function, while C-terminal variants impair interaction with the essential partner LHX2 in a dominant-negative manner. These findings were confirmed in vivo in Drosophila melanogaster. Toxicity of overexpressed human LDB1 in Drosophila was not observed with N-terminal missense variants but was exacerbated by C-terminal variants. Similarly, phenotypes associated with LDB1/chi loss were rescued by overexpression of wild-type LDB1, but neither by LDB1 harboring N-terminal missense variants nor by C-terminal variants that even worsened phenotypes. In summary, our findings link de novo variants in LDB1 to two overlapping, but distinct neurodevelopmental phenotypes based on variant location, and highlight two separate pathomechanisms underlying LDB1-related neurodevelopmental disorders.

PurposeThere is a need for novel therapies for diabetic retinopathy (DR) because existing therapies treat only certain features of DR and do not work optimally for all patients. While proteomic studies provide insight into disease pathobiology, they are often limited to small sample sizes due to high costs, limiting their generalizability and reproducibility. Moreover, they often yield lists of tens to hundreds of proteins with differential expression, making it difficult to prioritize the most biologically relevant biomarkers beyond using arbitrary fold-change and false-detection rate cutoffs. Here, we applied a two-stage multimodal AI approach: first, we integrated EHR and proteomics data to rationally prioritize candidate protein biomarkers and, next, validated these biomarkers in an independent cohort. These protein biomarkers of DR are rooted in the EHR data and thereby more likely to be biological drivers of disease. MethodsWe obtained EHR data from a large number of patients with and without DR (N=319,997) from the STARR-OMOP database and obtained aqueous humor liquid biopsies from a subset of these patients (N=101) for high-resolution proteomic profiling. We developed Clinical and Omics Multi-Modal Analysis Enhanced with Transfer Learning (COMET) to perform integrated analysis of proteomics and all available EHR data to identify protein biomarkers of DR. The model was trained in two phases: first, it was pretrained using patients with EHR data alone (N=319,896), and then, it was fine tuned using patients with both EHR and proteomics data (N=101), allowing it to learn both clinical and molecular features associated with DR. Findings from COMET were then validated with liquid biopsies from an independent, validation cohort (N=164). Resultst-distributed stochastic neighbor embedding (t-SNE) analysis of EHR and proteomics data identified proteins clustering with related EHR features. Levels of STX3 and NOTCH2, proteins involved in retinal function, were correlated with a diagnosis of macular edema, a record of a visual field exam, and a prescription for latanoprost, highlighting protein-EHR alignment. The pretrained, multimodal COMET model was superior (AUROC=0.98, AUPRC=0.91) compared to models generated using either EHR or proteomics data alone or without pretraining (AUROC: 0.76 to 0.92; AUPRC: 0.47 to 0.74). The proteins SERPINE1, QPCT, AKR1C2, IL2RB, and SRSF6 were prioritized by the COMET model compared to the models without pretraining, supporting their potential role in DR pathobiology, and were subsequently validated in an independent cohort. ConclusionWe used multimodal AI to prioritize protein biomarkers of DR that are most strongly linked to EHR elements, as well as identifying other protein biomarkers associated with disease features like diabetic macular edema. These findings serve as a foundation for future mechanistic studies and highlight the synergistic value of using multimodal AI to fuse EHR and proteomics data for enhanced proteomics analysis.

RationaleIdiopathic pulmonary fibrosis (IPF) is a rare, chronic, progressive lung disease with high mortality and few treatment options. Using an additive genetic model, genome-wide association studies (GWAS) have identified multiple risk loci highlighting new genes and pathways of interest. Since IPF risk could also be influenced by non-additive effects, we hypothesised that association analyses using alternative genetic models may provide additional mechanistic insight. ObjectivesTo perform GWAS of IPF susceptibility to detect associations where the underlying effects are consistent with recessive or dominant genetic models. MethodsWe performed GWAS of IPF susceptibility, with logistic regression assuming dominant or recessive genetic models, including 5,159 IPF cases, from clinically-curated sources, and 27,459 controls. We functionally annotated independent signals and performed variant-to-gene mapping, applying fine-mapping to define potentially causal variants and genes. We assessed differential expression levels of genes of interest in publicly available single cell RNAseq data and in primary cells derived from IPF donors and controls. Main ResultsWe identified five genome-wide significant signals, under a recessive model, that had not been reported previously. These included exonic variants in the cell-cycle gene Polyamine-Modulated Factor 1 (PMF1) and in Epsin 3 (EPN3) genes. We also observed evidence of increased PMF1 expression in airway basal cells of IPF patients compared to controls. ConclusionsUsing alternative genetic models in IPF susceptibility GWAS identified new signals and genes, providing new insights into IPF pathogenesis and potential future therapies.

STUDY QUESTION[Do structural genomic variants, that can be identified by using optical genome mapping, contribute to male infertility?] SUMMARY ANSWER[By using optical genome mapping we can identify several types of structural variants, both known and new, that may contribute to male infertility.] WHAT IS KNOWN ALREADY[Traditional approaches such as karyotyping, CFTR and chromosome Y microdeletion testing are successful in explaining clinical findings in [~]30% of MI patients, leaving the rest without a genetic diagnosis. Recent research suggests at least 265 genes may play a role in male fertility. While the assessment of the roles of copy number variants and single nucleotide variants in monogenic forms of disease in these genes is underway, much less is known about structural variants.] STUDY DESIGN, SIZE, DURATION[We performed a longitudinal case/control study on a total of 220 individuals; 88 patients with male infertility, negative for cytogenetic abnormalities using karyotyping, and molecular testing for chrY microdeletions, and CFTR gene variants, and 132 healthy male individuals that underwent optical genomic mapping for other reasons. Exclusion criteria for the control cohort were low-sperm quality and/or inclusion in IVF procedures. The study was approved by the National Medical Ethics Committee of the Republic of Slovenia (reference number: 0120-213/2022/6). Optical genome mapping was performed from an aliquot of whole blood collected for routine testing purposes at the Clinical Institute of Genomic Medicine (CIGM), UMC Ljubljana from January 2023 to November 2024.] PARTICIPANTS/MATERIALS, SETTING, METHODS[We examined structural variants in 220 participants by using optical genome mapping, which was performed with DLE-1 SP-G2 chemistry and the Saphyr instrument. The de novo assembly and Variant Annotation Pipeline were executed on Bionano Solve3.7_20221013_25 while reporting and direct visualization of structural variants was done on Bionano Access 1.7.2. All obtained variants were filtered using the Bionano Access software and in-house generated gene/regions of interest panel bed files. The first filter was applied to include variants below a population frequency of 10%, and overlapping the regions of interest. Subsequently, all variants occurring with frequency 0% in the internal manufacturer variant dataset were manually evaluated for possible involvement of the overlapping genes or regions in biological processes involved in MI. The male infertility cohort also underwent research whole exome analyses as previously reported. All results of optical genomic mapping were confirmed by an appropriate alternative method where available.] MAIN RESULTS AND THE ROLE OF CHANCE[We show that the overall number of structural variants in MI patients does not differ from that of healthy individuals. By looking in detail at genes and regions associated with MI, we identified 21 rare variants absent from controls in 25.0 % of MI patients, of which five were likely causative, and two would be missed by using traditional approaches. These variants include inversions, duplications, amplifications, deletions (e.g. SPAG1), and insertions/expansions (e.g. DMPK), that were validated using additional methods. While the remaining SV cannot be currently classified as pathogenic according to existing criteria, they open a new avenue in genetic research of MI. LARGE SCALE DATA[Variants reported in this study were deposited into ClinVar under accession numbers SUB15650956 (https://www.ncbi.nlm.nih.gov/clinvar/)] LIMITATIONS, REASONS FOR CAUTION[Technical limitations of optical genome mapping include the lack of DLE-1 labelling of centromeric and telomeric regions, the inability to detect Robertsonian translocations, the unclear exact location of smaller structural variants located between the DLE-1 labels, and unclear boundaries in case of their location in segmentally duplicated regions (this limitation is shared with other methods). The ACGM criteria of rarity are also hard to apply, as the fertility status of the individuals in healthy population databases such as GnomAD and DGV is unknown. Similarly, gene-associated phenotype and the proposed inheritance model both need to be considered as parts of the ACMG criteria, but for many candidate genes associated with MI, no model of inheritance has yet been proposed.] WIDER IMPLICATIONS OF THE FINDINGS[Currently, with the established diagnostic approaches we are able to resolve [~]30% of male infertility cases, with [~]70% of patients remaining undiagnosed. The significance of our work is in showing that rare structural variants can be identified in MI, by using optical genome mapping, opening new avenues of research of the genetics of this important contributor to human fertility.] STUDY FUNDING/COMPETING INTEREST(S)[All authors declare having no conflict of interest in regard to this research. This work was funded by the Slovenian Research and Innovation Agency (ARIS) Programme grant P3-0326: Gynecology and Reproduction: Genomics for personalized medicine] Lay summaryMale infertility affects about 5% of adult males and has complex causes, including genetic ones, such as mutations in the CFTR gene, small deletions on chromosome Y, and balanced translocations, but currently we can only find a genetic cause in [~]30% of patients. This means [~]70% of cases remain undiagnosed but potentially, they too may have a yet unknown genetic cause. Indeed, so far research has shown at least 265 genes have been proposed to play a role in male fertility. In these genes, there has so far been limited research of single nucleotide variants and of copy number variants, but many structural variants are not visible using commonly used methods in clinical genetic testing. Therefore, apart from chromosome Y microdeletions and chromosomal numerical and structural anomalies, such as balanced translocations, the role of smaller structural variants in male infertility is unknown, but based from what we know from other diseases, they also may play a role in male infertility. Optical genome mapping is a novel method for the detection of structural variants, such as balanced and unbalanced translocations, insertions, duplications, deletions, and complex structural rearrangements in a wide range of sizes. By using optical genome mapping to test a cohort of 88 infertile men and 132 healthy controls, we aimed to provide the first insights into the range of SV that may be associated with MI. We found, by using optical genome mapping, the overall number of structural variants in MI patients not to be significantly different to the control group. However, by looking at genes and regions associated with MI, we can find rare structural variants that are absent from controls in 25.0% of MI patients. These variants include inversions, duplications, amplifications, deletions (e.g. deletion in SPAG1), and insertions/expansions (e.g. in DMPK), that were validated using additional methods. Five of these variants (5.6%) were likely causative, and two would be missed by traditional approaches. While the remaining SV cannot be currently classified as pathogenic according to existing criteria, they open a new avenue in genetic research of MI.

IntroductionFibrosis can affect organs throughout the body and is present in a wide range of diseases. Recent research has suggested that there could be shared biological mechanisms that lead to fibrosis in different organs. MethodsWe performed genome-wide association studies using UK Biobank for fibrosis in 12 different organ-systems and meta-analysed results with previously published studies of fibrotic diseases. We considered genetic associations that colocalised across [&ge;]3 organs as those likely to be involved in general fibrotic mechanisms and also identified novel genetic variants not previously reported as associated with fibrosis. Genetic correlation of fibrosis between organs was calculated using linkage disequilibrium score regression (LDSC). Discovery analyses were performed using European ancestry individuals and results were tested further in African, South Asian and East Asian ancestry groups. ResultsWe identified eight genetic loci that colocalised across three or more organs. One of these signals, located near the SH2B3 and ATXN2 genes, showed evidence of a shared causal variant for fibrosis across five organs. We also identified two novel fibrotic associations, one implicating alternative splicing of TFCP2L1 for urinary fibrosis and another implicating a missense variant in FAM180A for intestinal-pancreatic fibrosis. We observed significant genetic correlations for all organs, particularly for liver and skeletal fibrosis. ConclusionWe found evidence of shared genetic associations for fibrosis across organs, both at individual genetic loci and genome-wide. This highlights specific genes that may contribute to fibrosis across organs and diseases, which may facilitate the development of new therapies.

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.

ObjectiveTo identify risk loci for Fuchs endothelial corneal dystrophy (FECD) and improve a genetic risk prediction model. DesignGenome-wide association study (GWAS), polygenic risk score (PRS) construction, and TCF4 CTG18.1 short tandem repeat (STR) length inference. ParticipantsThe study included 7,316 Europeans (EUR) with FECD or related corneal dystrophy phenotypes and 1,588,467 controls from the UK Biobank, All of Us, FinnGen, and the Million Veteran Program. Two independent EUR FECD cohorts were used for PRS validation (1,851/2,679 cases/controls and 124/257 cases/controls). African (AFR) ancestry analyses included 455 cases and 121,154 controls to build PRS. A subset of All of Us participants was used for joint PRS and STR modelling. MethodsGWAS meta-analyses were performed using FECD diagnoses or corneal dystrophy proxies where necessary, with validity assessed via genetic correlation. Risk loci were identified, and ancestry-specific PRSs were constructed using SBayesRC. PRS performance was evaluated across ancestries with and without TCF4 STR data. Main OutcomeWe identified novel loci for corneal dystrophy and constructed PRS-based and STR-based prediction models. ResultsThe GWAS meta-analysis identified 24 risk loci associated with corneal dystrophy, including 12 novel loci, doubling previous FECD studies. The optimised PRS outperformed existing models in two independent FECD validation cohorts (AUC = 0.83, 95% CI: 0.82-0.84; DeLongs P = 7.04 x 10-19), with individuals in the top PRS decile showing 14-fold and 19-fold increased risk in the two validation sets, respectively In All of Us, STR expansion (>40 repeats) was the key predictor of FECD risk, yielding excellent discrimination (AUC = 0.89; OR = 54) with minimal improvement from PRS. Consistent with this, STR expansion remained the primary driver of risk across ancestries, while PRS provided modest independent value for broader corneal dystrophy phenotypes in EUR and admixed American populations. Among participants without large STR expansion, overall predictive performance was modest; PRS was the only significant genetic contributor (OR = 1.37) for broader corneal dystrophy in Europeans, whereas analyses in FECD non-expansion carriers were underpowered. ConclusionsThese findings refine the genetic architecture of FECD, enhance risk prediction, and support a tiered strategy integrating STR expansion testing with PRS. Key PointsO_ST_ABSQuestionC_ST_ABSCan polygenic risk scores (PRS), alone or combined with TCF4 CTG18.1 short tandem repeat (STR) length, improve genetic risk prediction for Fuchs endothelial corneal dystrophy (FECD)? FindingsIn this GWAS meta-analysis of 7,316 cases and 1,588,467 controls, PRS showed strong predictive performance in validation cohorts lacking STR data. When STR length was available, it was the main predictor of FECD risk with limited additional contribution from PRS. Among non-expansion STR carriers, PRS helped stratify risk for broader corneal dystrophy in Europeans. MeaningPRS provide a practical, complementary approach for FECD risk prediction, particularly when STR data are unavailable.

We report a previously undescribed genotypic configuration identified in twins with HNRNPU-related neurodevelopmental disorder. Both twins have two closely spaced mosaic variants on the same allele that never co-occur on any single DNA molecule, resulting in three distinct cell lineages within each individual. We define this genotypic configuration as clustered monoallelic mosaicism (cMoMa). Recognizing the extreme improbability of such a configuration, we systematically explore two potential mechanisms for its origin. We propose that this genotype arises from an asymmetric repair of a single mutational event in an early embryonic cell, yielding divergent outcomes on sister chromatids. Screening of datasets (COSMIC and MosaicBase) uncovered additional cMoMa-like cases, suggesting that the mechanism is not unique to our case, but rather represents a broader, previously unrecognized path of mutagenesis that extends our current definition of mosaicism.

BackgroundMitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA-based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis. RNA sequencing (RNA-seq) provides a complementary layer of evidence by revealing functional consequences of genetic variation, thereby improving diagnostic yield. MethodsWe performed RNA-seq on skin fibroblasts from 140 pediatric patients with suspected mitochondrial disease who remained genetically undiagnosed after whole exome sequencing (WES). Aberrant RNA expression and splicing were identified using the detection of RNA outliers pipeline (DROP). Based on WES findings, patients were stratified into a candidate group (n=28), in which RNA-seq evaluated the pathogenicity of WES-identified variants of uncertain significance and an unsolved group (n=112), in which RNA-seq was used to pinpoint candidate genes. In six cases where RNA-seq identified the aberrant RNA-event but WES did not detect the causative variants, whole genome sequencing (WGS) was performed. ResultsIntegrative RNA-seq, WES, and WGS analysis resulted in a genetic diagnosis in 25% of patients overall (20/28 [71%] in the candidate group; 15/112 [13%] in the unsolved group). Aberrant splicing explained most candidate-group diagnoses, including variants misclassified by in silico predictors such as SpliceAI. Fourteen percent of protein-truncating variants predicted to undergo nonsense-mediated decay (NMD) escaped degradation, highlighting the functional limits of current predictions. The variants identified in the unsolved cohort included synonymous, missense, deep intronic, near-splice-site variants, and large deletions. The most frequent amongst them was a recurrent synonymous East Asian founder mutation in ECHS1, accounting for seven cases. Interestingly, across 231 pathogenic variants associated with aberrant RNA phenotypes compiled from this study and prior reports, half were non-coding and half were coding variants. ConclusionRNA-seq substantially enhances molecular diagnosis in mitochondrial disease by exposing cryptic splicing, regulatory, and NMD-escape events invisible to DNA sequencing alone. These data advocate transcriptome analysis as an essential component of comprehensive genomic diagnostics in neuro-metabolic disease. Significance StatementMitochondrial diseases remain among the most challenging inherited metabolic disorders to diagnose, with nearly half of patients unresolved despite advanced DNA sequencing. By integrating transcriptome profiling into the diagnostic workflow, this study demonstrates that RNA sequencing can reveal pathogenic mechanisms invisible to exome or genome analysis, including cryptic splicing, regulatory variants, and transcripts that escape nonsense-mediated decay. The findings establish RNA-seq as a decisive bridge between genotype and phenotype, uncovering functional consequences of genetic variation and redefining molecular diagnostics for mitochondrial and other neuro-metabolic diseases.

Both short and long sleep duration have been associated with poor glycemic control and an increased risk of developing type 2 diabetes mellitus. Although sleep duration may differentially modify the effects of genetic risk factors for type 2 diabetes, this has not been systematically investigated. In the present study, we conducted genome-wide gene by sleep duration meta-analyses, separately assessing interactions of short and long sleep, for fasting glucose, fasting insulin, and hemoglobin A1c in up to 489,309 individuals without diabetes from seven different population groups. In total, 16 loci were identified to interact with sleep duration -- six with short sleep and ten with long sleep. Of these, four loci were identified through cross-population meta-analysis. Mapped genes exhibit pathway connections to pericyte apoptosis, NMDA receptor activity, the GLUT1 receptor, neurological health, and sleep architecture. Eleven loci (VRK2, PCDH7, TFAP2A, CAP2, PAPPA, ZCCHC2, MYH9, SGIP1, JAKMIP3, RRAS2, MAPT) have not been reported in previous glycemic trait genome-wide association studies. Interaction loci identify divergent biological mechanisms for short and long sleep duration influencing glycemic control, suggesting specific pathways of intervention for precision medicine approaches to diabetes prevention and management. Article HighlightsO_LIThe biological mechanisms of how sleep duration impacts type 2 diabetes pathogenesis and glycemic control are unclear. C_LIO_LIThis study reveals 16 loci (11 novel) that interact with either short or long sleep duration to influence hemoglobin A1c, fasting glucose, or fasting insulin. Short and long sleep duration loci were non-overlapping. C_LIO_LIRegulation of copper and diacylglycerol levels appear as distinct cellular mechanisms implicated by long and short sleep duration loci respectively. C_LIO_LIIdentified gene targets present insight for potential type 2 diabetes therapeutic design approaches related to JIP1-JNK interaction disruption, pericyte health, NMDA receptor activity, anti-inflammatory and leptin-enhancing dietary supplements, and serpins. C_LI

ObjectivesTo screen the entire genome for genes associated with risk for lateral epicondylopathy and improve understanding of underlying biological mechanisms and inform future research aimed at risk stratification and personalized prevention and treatment strategies. MethodsA genome-wide association study was conducted using UK Biobank data. Lateral epicondylopathy cases were identified based on electronic health records from individuals of European ancestry. Logistic regression tested associations between single-nucleotide polymorphisms and disease status, adjusting for sex, age, height, weight and ancestry principal components. Previously-identified candidate genes from the literature were also tested for association with lateral epicondylopathy. ResultsAmong 20,390 cases of lateral epicondylopathy, two loci reached genome-wide significance: one comprising 144 linked SNPs and one single SNP. The first locus, led by rs13127477 (p=7.7x10-12; OR 0.93, 95% CI 0.91 to 0.95), is located near three SIBLING genes (IBSP, MEPE and SPP1) involved in extracellular matrix remodelling at fibrocartilaginous entheses. The risk allele was associated with increased SIBLING gene expression, suggesting that excessive entheseal matrix remodelling contributes to disease susceptibility. The second locus was defined by rs138254824 (p=3.69x10-8; OR 3.42, 95% CI 2.23 to 5.25) near NEDD9 and TMEM170B. Previously reported collagen gene associations were not replicated. ConclusionIn the first genome-wide screen for lateral epicondylopathy, two loci were identified. These loci provide insight regarding the pathophysiology of lateral epicondylopathy and a roadmap for preventing and treating this injury with personalized medicine. Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSLateral epicondylopathy is a common and disabling overuse tendon condition, yet its genetic basis has remained poorly characterised, with prior studies limited to small candidate gene analyses. What this study addsThis study provides the first genome-wide association analysis of lateral epicondylopathy, identifying two risk loci on chromosomes 4 and 6 and implicating SIBLING genes (IBSP, MEPE, and SPP1) involved in entheseal extracellular matrix remodelling. How this study might affect research, practice or policyThese findings offer new biological insight into disease susceptibility and challenge previously reported collagen gene associations.