Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

CNVs and Human Well-being: Integrating Psychiatric, Physical, and Socioeconomic Perspectives

Copy number variations (CNVs) have emerged as crucial genetic factors influencing a wide spectrum of human health outcomes, with particularly strong associations to psychiatric disorders. This review presents a synthesis of diverse impacts of psychiatric disorder-associated CNVs on neurodevelopment, brain function, and physical health across the lifespan. Large-scale studies have revealed that CNV carriers exhibit an increased risk for psychiatric disorders, cognitive deficits, sleep disturbances, neurological disorders, and other physical conditions, including cardiovascular diseases, diabetes, and renal disease, highlighting the wide-ranging impact of CNVs beyond the brain. Neuroimaging studies reveal substantial CNV effects on brain structure, from cortical and subcortical alterations to white matter microstructure, with effect sizes often exceeding those observed in idiopathic psychiatric disorders. Cellular and animal models have begun to elucidate dynamic CNV effects on neurodevelopment, neuronal function, and cellular energy metabolism, while revealing complex CNV-environment interactions and cell type-specific responses, particularly in studies of 22q11.2 deletion syndrome. This review also explores the complex interplay between psychiatric and physical health conditions in CNV carriers, and how these interactions contribute to adverse socioeconomic outcomes, including reduced educational attainment and income levels, creating a feedback loop that further impacts health outcomes. Finally, this review also highlights research limitations and proposes key priorities for clinical implementation, including the need for longitudinal studies, standardized guidelines for CNV result reporting and genetic counseling, and integrated care networks, providing a foundation for advancing the field of precision psychiatry.

Genetic heterogeneity in familial forms of genetic generalized epilepsy: from mono- to oligogenism

Genetic generalized epilepsy (GGE) including childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy (JME), and GGE with tonic-clonic seizures (TCS) (GGE-TCS), is genetically influenced with a two- to four- fold increased risk in the first-degree relatives of patients. Since large families with GGE are very rare, international studies have focused on sporadic GGE patients using whole exome sequencing, suggesting that GGE are highly genetically heterogeneous and rather involve rare or ultra-rare variants. Moreover, a polygenic mode of inheritance is suspected in most cases. We performed SNP microarrays and whole exome sequencing in 20 families from Sudan, focusing on those with at least four affected members. Standard genetic filters and Endeavour algorithm for functional prioritization of genes selected likely susceptibility variants in FAT1, DCHS1 or ASTN2 genes. FAT1 and DCHS1 are adhesion transmembrane proteins interacting during brain development, while ASTN2 is involved in dendrite development. Our approach on familial forms of GGE is complementary to large-scale collaborative consortia studies of sporadic cases. Our study reinforces the hypothesis that GGE is genetically heterogeneous, even in a relatively limited geographic area, and mainly oligogenic, as supported by the low familial penetrance of GGE and by the Bayesian algorithm that we developed in a large pedigree with JME. Since populations with founder effect and endogamy are appropriate to study autosomal recessive pathologies, they would be also adapted to decipher genetic components of complex diseases, using the reported bayesian model.

Rare copy number variant analysis in case-control studies using snp array data: a scalable and automated data analysis pipeline

BACKGROUND

Rare copy number variants (CNVs) significantly influence the human genome and may contribute to disease susceptibility. High-throughput SNP genotyping platforms provide data that can be used for CNV detection, but it requires the complex pipelining of bioinformatic tools. Here, we propose a flexible bioinformatic pipeline for rare CNV analysis from human SNP array data.

RESULTS

The pipeline consists of two major sub-pipelines: (1) Calling and quality control (QC) analysis, and (2) Rare CNV analysis. It is implemented in Snakemake following a rule-based structure that enables automation and scalability while maintaining flexibility.

CONCLUSIONS

Our pipeline automates the detection and analysis of rare CNVs. It implements a rigorous CNV quality control, assesses the frequencies of these rare CNVs in patients versus controls, and evaluates the impact of CNVs on specific genes or pathways. We hence aim to provide an efficient yet flexible bioinformatic framework to investigate rare CNVs in biomedical research.

Unraveling the genetic basis of epilepsy: Recent advances and implications for diagnosis and treatment

Epilepsy, affecting approximately 1% of the global population, manifests as recurring seizures and is heavily influenced by genetic factors. Recent advancements in genetic technologies have revolutionized our understanding of epilepsy's genetic landscape. Key studies, such as the discovery of mutations in ion channels (e.g., SCN1A and SCN2A), neurotransmitter receptors (e.g., GABRA1), and synaptic proteins (e.g., SYNGAP1, KCNQ2), have illuminated critical pathways underlying epilepsy susceptibility and pathogenesis. Genome-wide association studies (GWAS) have identified specific genetic variations linked to epilepsy risk, such as variants near SCN1A and PCDH7, enhancing diagnostic accuracy and enabling personalized treatment strategies. Moreover, epigenetic mechanisms, including DNA methylation (e.g., MBD5), histone modifications (e.g., HDACs), and non-coding RNAs (e.g., miR-134), play pivotal roles in altering gene expression and synaptic plasticity, contributing to epileptogenesis. These discoveries offer promising avenues for therapeutic interventions aimed at improving outcomes for epilepsy patients. Genetic testing has become essential in clinical practice, facilitating precise diagnosis and tailored management approaches based on individual genetic profiles. Furthermore, insights into epigenetic regulation suggest novel therapeutic targets for developing more effective epilepsy treatments. In summary, this review highlights significant progress in understanding the genetic and epigenetic foundations of epilepsy. By integrating findings from key studies and specifying genes involved in epigenetic modifications, we underscore the potential for advanced therapeutic strategies in this complex neurological disorder, emphasizing the importance of personalized medicine approaches in epilepsy management.

The pleiotropic spectrum of proximal 16p11.2 CNVs

Recurrent genomic rearrangements at 16p11.2 BP4-5 represent one of the most common causes of genomic disorders. Originally associated with increased risk for autism spectrum disorder, schizophrenia, and intellectual disability, as well as adiposity and head circumference, these CNVs have since been associated with a plethora of phenotypic alterations, albeit with high variability in expressivity and incomplete penetrance. Here, we comprehensively review the pleiotropy associated with 16p11.2 BP4-5 rearrangements to shine light on its full phenotypic spectrum. Illustrating this phenotypic heterogeneity, we expose many parallels between findings gathered from clinical versus population-based cohorts, which often point to the same physiological systems, and emphasize the role of the CNV beyond neuropsychiatric and anthropometric traits. Revealing the complex and variable clinical manifestations of this CNV is crucial for accurate diagnosis and personalized treatment strategies for carrier individuals. Furthermore, we discuss areas of research that will be key to identifying factors contributing to phenotypic heterogeneity and gaining mechanistic insights into the molecular pathways underlying observed associations, while demonstrating how diversity in affected individuals, cohorts, experimental models, and analytical approaches can catalyze discoveries.

The role of candidate pharmacogenetic variants in determining valproic acid efficacy, toxicity and concentrations in patients with epilepsy

Background

Antiseizure medications (ASM) exhibit considerable interindividual variability in terms of efficacy and adverse events. Genetic variation is thought to contribute to these differences in clinical outcomes. Specifically, the response to valproic acid (VPA), a widely used ASM, is influenced by multiple pharmacogenetic factors. However, and in contrast to other ASMs such as phenytoin and carbamazepine, there is a paucity of data on the association between VPA and various gene variants. The aim of this study was hence to evaluate the influence of candidate pharmacogenetic variants on VPA efficacy, toxicity and serum concentrations in a homogeneous cohort of patients newly diagnosed with genetic generalized epilepsies (GGE).

Methods

In this prospective cohort study, demographic, clinical and treatment outcomes of GGE patients were retrieved from their medical records. Whole exome sequencing was performed in collaboration with Epi25. Gene variants associated with VPA efficacy, metabolism and toxicities were retrieved from PharmGKB. An analysis was then conducted to explore potential associations between these gene variants and VPA clinical outcomes.

Results

Of the 166 patients included, 60 (36.1%) experienced treatment failure while 106 (63.9%) achieved treatment success. After adjusting for VPA maintenance dose, carriers of the rs3892097 (CYP2D6) variant were 2.5 times more likely to experience treatment failure compared to wildtype (p = 0.026). The rs1057910 variant (CYP2C9*3) was associated with increased serum VPA concentrations (p = 0.034). Moreover, the rs1137101 variant (LEPR gene, a metabolism regulator) was significantly associated with a higher risk of weight gain (regression coefficient of 3.430 [0.674; 6.186], p = 0.015) and a higher frequency of hair loss (OR = 3.394 [1.157; 9.956], p = 0.026), while the rs4480 variant (SOD2 gene, encoding for a mitochondrial scavenging enzyme) was correlated with a lower frequency of hair loss (OR = 0.276 [0.089; 0.858], p = 0.026).

Conclusion

These findings highlight the role of genetic factors in VPA treatment and underscore the potential for developing therapeutic strategies to enhance patient outcomes and minimize adverse effects.

Relationship between inflammation/immunity and epilepsy: A multi-omics mendelian randomization study integrating GWAS, eQTL, and mQTL data

OBJECTIVES

Increasing evidence suggests that activated innate/adaptive immunity induces an inflammatory response, thereby participating in epileptogenesis. However, the biological explanation of inflammation/immunity as a potential cause for epilepsy remains largely unknown. This research aimed to determine the causal effects of inflammation/immune-related genes in epilepsy based on multi-omics mendelian randomization (MR).

METHODS

We employed summary-data-based MR (SMR) approach to combine GWAS for epilepsy (12,891 cases and 312,803 control) with gene expression quantitative trait loci (cis-eQTL, 31,684 participants) and DNA methylation QTL (cis-mQTL, 1,980 participants) data. Five additional MR methods were then used for sensitivity analyses to confirm the reliability of causal associations. In addition, enrichment analysis of key genes was conducted to provide insight into the biological functions of epilepsy risk variants.

RESULTS

A total of 386 inflammation/immune-related genes were selected for further analyses. Primary SMR analysis indicated that 37 DNA methylation sites and six genes regulated by them had potential causal relationship with epilepsy. MR analysis further refined the results, identifying three genes that had a causal effect on epilepsy. Notably, VEGFA (OR: 0.925; 95 % CI: 0.862-0.994) expression was negatively correlated with epilepsy risk, whereas IL16 (OR: 1.076; 95 % CI: 1.028-1.126) and HLA-DPA1 (OR: 1.041; 95 % CI: 1.009-1.074) expressions were positively associated with epilepsy risk. Functional enrichment analysis revealed that the identified genes were involved in GO-BP terms related to VEGF activation signaling and chemotaxis regulation.

CONCLUSION

This analysis confirms the causal role of inflammation/immunity in epilepsy, and the identified candidate genes provide clues for drug development in clinical practice.

Genome-wide association testing beyond SNPs

Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale.

Copy Number Variation and Epilepsy: State of the Art in the Era of High-Throughput Sequencing-A Multicenter Cohort Study

BACKGROUND

Genetic epilepsy diagnosis is increasing due to technological advancements. Although the use of molecular diagnosis is increasing, chromosomal microarray analysis (CMA) remains an important diagnostic tool for many patients. We aim to explore the role and indications of CMA in epilepsy, given the current genomic advances.

METHODS

We obtained data from 378 epileptic described patients, who underwent CMA between 2015 and 2021. Different types of syndromic or nonsyndromic epilepsy were represented.

RESULTS

After excluding patients who were undertreated or had missing data, we included 250 patients with treated epilepsy and relevant clinical information. These patients mostly had focal epilepsy or developmental and epileptic encephalopathy, with a median start age of 2 years. Ninety percent of the patients had intellectual disability, more than two thirds had normal head size, and 60% had an abnormal magnetic resonance imaging. We also included 10 patients with epilepsy without comorbidities. In our cohort, we identified 35 pathogenic copy number variations (CNVs) explaining epilepsy with nine recurrent CNVs enriched in patients with epilepsy, 12 CNVs related to neurodevelopmental disorder phenotype with possible epilepsy, five CNVs including a gene already known in epilepsy, and nine CNVs based on size combined with de novo occurrence. The diagnosis rate in our study reached 14% (35 of 250) with first-line CMA, as previously reported. Although targeted gene panel sequencing could potentially diagnose some of the reported epilepsy CNVs (34% [12 of 35]).

CONCLUSIONS

CMA remains a viable option as the first-line genetic test in cases where other genetic tests are not available and as a second-line diagnostic technique if gene panel or exome sequencing yields negative results.

Genotype-driven therapeutics in DEE and metabolic epilepsy: navigating treatment efficacy and drug resistance

Neonatal intensive care unit (NICU), particularly in treating developmental and epileptic encephalopathy (DEE) and metabolic epilepsy (ME), requires a deep understanding of their complex etiologies and treatment responses. After excluding treatable cases such as infectious or autoimmune encephalitis, our focus shifted to a more challenging subgroup of 59 patients for in-depth genetic analysis using exome sequencing (ES). The ES analysis identified 40 genetic abnormalities, significantly including de novo variants. Notably, we found structural variation as duplications in regions 2q24.3, including SCN1A and SCN2A were observed in 7 cases. These genetic variants, impacting ion channels, glucose transport, transcription regulation, and kinases, play a crucial role in determining medication efficacy. More than one-third (34.2%) of patients with DEE had an unfavorable response to anti-seizure medications (ASMs) in the chronic phase. However, since the ketogenic supplementary diet showed a positive effect, more than three-quarters (80%) of these drug-resistant patients improved during a 3-month follow-up. In contrast, the ME had a lower adverse reaction rate of 9.1% (2/22) to specialized medications, yet there were 5 fatalities and 10 cases with unidentified genetic etiologies. This study suggests the potential of categorizing drug-resistant variants and that a ketogenic diet could be beneficial in managing DEE and ME. It also opens new perspectives on the mechanisms of the ketogenic diet on the discovered genetic variants.

Genome-wide association study of copy number variations in Parkinson's disease

Objective

Our study investigates the impact of copy number variations (CNVs) on Parkinson's disease (PD) pathogenesis using genome-wide data, aiming to uncover novel genetic mechanisms and improve the understanding of the role of CNVs in sporadic PD.

Methods

We applied a sliding window approach to perform CNV-GWAS and conducted genome-wide burden analyses on CNV data from 11,035 PD patients (including 2,731 early-onset PD (EOPD)) and 8,901 controls from the COURAGE-PD consortium.

Results

We identified 14 genome-wide significant CNV loci associated with PD, including one deletion and 13 duplications. Among these, duplications in 7q22.1, 11q12.3 and 7q33 displayed the highest effect. Two significant duplications overlapped with PD-related genes SNCA and VPS13C, but none overlapped with recent significant SNP-based GWAS findings. Five duplications included genes associated with neurological disease, and four overlapping genes were dosage-sensitive and intolerant to loss-of-function variants. Enriched pathways included neurodegeneration, steroid hormone biosynthesis, and lipid metabolism. In early-onset cases, four loci were significantly associated with EOPD, including three known duplications and one novel deletion in PRKN. CNV burden analysis showed a higher prevalence of CNVs in PD-related genes in patients compared to controls (OR=1.56 [1.18-2.09], p=0.0013), with PRKN showing the highest burden (OR=1.47 [1.10-1.98], p=0.026). Patients with CNVs in PRKN had an earlier disease onset. Burden analysis with controls and EOPD patients showed similar results.

Interpretation

This is the largest CNV-based GWAS in PD identifying novel CNV regions and confirming the significant CNV burden in EOPD, primarily driven by the PRKN gene, warranting further investigation.

Surgical outcomes of patients with genetically refractory epilepsy: A systematic review and meta-analysis

OBJECTIVE

To summarize the surgical outcomes of genetically refractory epilepsy and identify prognostic factors for these outcomes.

METHODS

A literature search of the PubMed, Web of Science, and Embase databases for relevant studies, published between January 1, 2002 and December 31, 2023, was performed using specific search terms. All studies addressing surgical outcomes and follow-up of genetically refractory epilepsy were included. All statistical analyses were performed using STATA software (StataCorp LLC, College Station, TX, USA). This review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, 2020 (i.e., "PRISMA") reporting guidelines.

RESULTS

Of the 3833 studies retrieved, 55 fulfilled the inclusion criteria. Eight studies were eligible for meta-analysis at the study level. Pooled outcomes revealed that 74 % of patients who underwent resective surgery (95 % confidence interval [CI] 0.55-0.89; z = 9.47, p < 0.05) achieved Engel I status at the last follow-up. In the study level analysis, pooled outcomes revealed that 9 % of patients who underwent vagus nerve stimulation achieved seizure-free status (95 % CI 0.00-0.31; z = 1.74, p < 0.05), and 61 % (95 % CI 0.55-0.89; z = 11.96, p < 0.05) achieved a 50 % reduction in seizure frequency at the last follow-up. Fifty-three studies comprising 249 patients were included in an individual-level analysis. Among patients who underwent lesion resection or lobectomy/multilobar resection, 65 % (100/153) achieved Engel I status at the last follow-up. Univariate analysis indicated that female sex, somatic mutations, and presenting with focal seizure symptoms were associated with better prognosis (p < 0.05). Additionally, 75 % (21/28) of patients who underwent hemispherectomy/hemispherotomy achieved Engel I status at the last follow-up. In the individual-level analysis, among patients treated with vagus nerve stimulation, 21 % (10/47) were seizure-free and 64 % (30/47) experienced >50 % reduction in seizure frequency compared with baseline.

CONCLUSION

Meticulous presurgical evaluation and selection of appropriate surgical procedures can, to a certain extent, effectively control seizures. Therefore, various surgical procedures should be considered when treating patients with genetically refractory epilepsy.

Advances in big data and omics: Paving the way for discovery in childhood epilepsies

The insights gained from big data and omics approaches have transformed the field of childhood genetic epilepsy. With an increasing number of individuals receiving genetic testing for seizures, we are provided with an opportunity to identify clinically relevant subgroups and extract meaningful observations from this large-scale clinical data. However, the volume of data from electronic medical records and omics (e.g., genomics, transcriptomics) is so vast that standardized methods, such as the Human Phenotype Ontology, are necessary for reliable and comprehensive characterization. Here, we explore the integration of clinical and omics data, highlighting how these approaches pave the way for discovery in childhood epilepsies.

High positive predictive value of CNVs detected by clinical exome sequencing in suspected genetic diseases

BACKGROUND

Genetic disorders often manifest as abnormal fetal or childhood development. Copy number variations (CNVs) represent a significant genetic mechanism underlying such disorders. Despite their importance, the effectiveness of clinical exome sequencing (CES) in detecting CNVs, particularly small ones, remains incompletely understood. We aimed to evaluate the detection of both large and small CNVs using CES in a substantial clinical cohort, including parent-offspring trios and proband only analysis.

METHODS

We conducted a retrospective analysis of CES data from 2428 families, collected from 2018 to 2021. Detected CNV were categorized as large or small, and various validation techniques including chromosome microarray (CMA), Multiplex ligation-dependent probe amplification assay (MLPA), and/or PCR-based methods, were employed for cross-validation.

RESULTS

Our CNV discovery pipeline identified 171 CNV events in 154 cases, resulting in an overall detection rate of 6.3%. Validation was performed on 113 CNVs from 103 cases to assess CES reliability. The overall concordance rate between CES and other validation methods was 88.49% (100/113). Specifically, CES demonstrated complete consistency in detecting large CNV. However, for small CNVs, consistency rates were 81.08% (30/37) for deletions and 73.91% (17/23) for duplications.

CONCLUSION

CES demonstrated high sensitivity and reliability in CNV detection. It emerges as an economical and dependable option for the clinical CNV detection in cases of developmental abnormalities, especially fetal structural abnormalities.

Exploring epileptic phenotypes in PRRT2-related disorders: A report of two cases and literature appraisal

BACKGROUND

The proline-rich transmembrane protein 2 (PRRT2) is a synaptic protein involved in neurotransmitter vesicle release. PRRT2 protein is highly expressed in the cerebellum, cerebral cortex, basal ganglia, and hippocampus. Variants in PRRT2 have been identified as a cause of several neurological disorders, including epilepsy, movement disorders, and headache.

METHODS

We report two families carrying two distinct PRRT2 mutations showing childhood onset of movement disorders, headache, and epilepsy. Demographics, clinical, EEG, neuroimaging, and genetic sequencing study data were collected. A systematic review of the literature was also performed to dissect the most frequently reported PRRT2-associated epileptic phenotypes.

RESULTS

two variants in PRRT2 gene (NM_145239.3:c718C>T, p.Arg240Ter; c.649dupC, p.Arg217Profs*8) were identified. The two variants altered the same extracellular domain of PRRT2. The de novo PRRT2 mutation (c718C>T, p.Arg240Ter) was related to multi-drug-resistant epilepsy. According to the literature, homozygous, biallelic variants and 16p11.2 deletions lead to PRRT2 haploinsufficiency and a more severe phenotype.

CONCLUSIONS

PRRT2 mutations can be associated with several epileptic phenotypes ranging from benign ASM-responsive form to more severe epileptic encephalopathies. Identifying PRRT2 variants in epilepsy patients may help achieve more personalized treatment approaches. However, phenotype-genotype correlations remain a challenge.

ATP1A2-related epileptic encephalopathy and movement disorder: Clinical features of three novel patients

OBJECTIVE

Variants in the ATP1A2 gene exhibit a wide clinical spectrum, ranging from familial hemiplegic migraine to childhood epilepsies and early infantile developmental epileptic encephalopathy (EIDEE) with movement disorders. This study aims to describe the epileptology of three unpublished cases and summarize epilepsy features of the other 17 published cases with ATP1A2 variants and EIDEE.

METHODS

Medical records of three novel patients with pathogenic ATP1A2 variants were retrospectively reviewed. Additionally, the PUBMED, EMBASE, and Cochrane databases were searched until December 2023 for articles on EIDEE with ATP1A2 variants, without language or publication year restrictions.

RESULTS

Three female patients, aged 6 months-10 years, were investigated. Epilepsy onset occurred between 5 days and 2 years, accompanied by severe developmental delay, intellectual disability, drug-resistant epilepsy, severe movement disorder, and recurrent status epilepticus. All individuals had pathogenic variants of the ATP1A2 gene (ATP1A2 c.720_721del (p.Ile240MetfsTer9), ATP1A2c.3022C > T (p.Arg1008Trp), ATP1A2 c.1096G > T (p.Gly366Cys), according to ACMG criteria. Memantine was p) rescribed to three patients, one with a reduction in ictal frequency, one with improvement in gait pattern, coordination, and attention span, and another one in alertness without significant side effects.

SIGNIFICANCE

This study reinforces the association between ATP1A2 variants and a severe phenotype. All patients had de novo variants, focal motor seizures with impaired awareness as the primary type of seizure; of the 11 EEGs recorded, 10 presented a slow background rhythm, 7 multifocal interictal epileptiform discharges (IED), predominantly temporal IEDs, followed by frontal IED, as well as ten ictal recordings, which showed ictal onset from the same regions mentioned above. Treatment with antiseizure medication was generally ineffective, but memantine showed moderate improvement. Prospective studies are needed to enlarge the phenotype and assess the efficacy of NMDA receptor antagonist therapies in reducing seizure frequency and improving quality of life.

Rare copy-number variants as modulators of common disease susceptibility

BACKGROUND

Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described.

METHODS

Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank.

RESULTS

We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS.

CONCLUSIONS

Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.

The Human Phenotype Ontology in 2024: phenotypes around the world

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

Genetic Association Analysis of Copy Number Variations for Meat Quality in Beef Cattle

Meat quality is an economically important trait for global food production. Copy number variations (CNVs) have been previously implicated in elucidating the genetic basis of complex traits. In this article, we detected a total of 112,198 CNVs and 10,102 CNV regions (CNVRs) based on the Bovine HD SNP array. Next, we performed a CNV-based genome-wide association analysis (GWAS) of six meat quality traits and identified 12 significant CNV segments corresponding to eight candidate genes, including PCDH15, CSMD3, etc. Using region-based association analysis, we further identified six CNV segments relevant to meat quality in beef cattle. Among these, TRIM77 and TRIM64 within CNVR4 on BTA29 were detected as candidate genes for backfat thickness (BFT). Notably, we identified a 34 kb duplication for meat color (MC) which was supported by read-depth signals, and this duplication was embedded within the keratin gene family including KRT4, KRT78, and KRT79. Our findings will help to dissect the genetic architecture of meat quality traits from the aspects of CNVs, and subsequently improve the selection process in breeding programs.

Toward the use of novel alternative methods in epilepsy modeling and drug discovery

Epilepsy is a chronic brain disease and, considering the amount of people affected of all ages worldwide, one of the most common neurological disorders. Over 20 novel antiseizure medications (ASMs) have been released since 1993, yet despite substantial advancements in our understanding of the molecular mechanisms behind epileptogenesis, over one-third of patients continue to be resistant to available therapies. This is partially explained by the fact that the majority of existing medicines only address seizure suppression rather than underlying processes. Understanding the origin of this neurological illness requires conducting human neurological and genetic studies. However, the limitation of sample sizes, ethical concerns, and the requirement for appropriate controls (many patients have already had anti-epileptic medication exposure) in human clinical trials underscore the requirement for supplemental models. So far, mammalian models of epilepsy have helped to shed light on the underlying causes of the condition, but the high costs related to breeding of the animals, low throughput, and regulatory restrictions on their research limit their usefulness in drug screening. Here, we present an overview of the state of art in epilepsy modeling describing gold standard animal models used up to date and review the possible alternatives for this research field. Our focus will be mainly on ex vivo, in vitro, and in vivo larval zebrafish models contributing to the 3R in epilepsy modeling and drug screening. We provide a description of pharmacological and genetic methods currently available but also on the possibilities offered by the continued development in gene editing methodologies, especially CRISPR/Cas9-based, for high-throughput disease modeling and anti-epileptic drugs testing.