Causal Variants Research Articles

Prognostic role of gene variants in sudden cardiac death risk associated to paediatric hypertrophic cardiomyopathy

Abstract Introduction Genetic testing plays an important role in diagnosis of hypertrophic cardiomyopathy (HCM), being sarcomeric genes commonly involved, particularly MYBPC3. However, arrhythmic risk related to genotype remains unclear in adults and almost unexplored in children. Hence, current sudden cardiac death (SCD) risk calculators do not include genetic information. Purpose To analyse risk of arrhythmic events associated with causal variants in MYBPC3 respecting to other genes in a paediatric cohort with non-syndromic HCM from a cardiomyopathy referral centre. Methods This retrospective study included patients with non-syndromic HCM 0-18 years old between 2009-2022. Demographic, clinical, and genetic data were collected. Genetic variants pathogenicity followed American College of Medical Genetics criteria. A positive genetic test was considered if a likely pathogenic or pathogenic variant in HCM related genes was found. Considered outcomes were SCD or a major arrhythmic cardiac event (MACE) within 5 years follow-up: recovered SCD, appropriate ICD therapy, or sustained ventricular tachycardia. Some SCD-risk estimation models (in 5 years) as HCM Risk-SCD model for patients >=15 y.o and/or 55 kg, ESC Guidelines paediatric algorithm, and HCM Risk-Kids model were applied. Results 77 patients were diagnosed with non-syndromic HCM. A causal variant was found in 45/73 (62%). No significant differences in cardiac phenotype were found related to genes. 10/77 patients (13%) presented a MACE in 5 years follow-up. A positive genetic study was significantly associated with having an event (p=0.011). Most patients with a positive genetic test harboured MYBPC3 variants (21/45, 47%), however only 2 patients who suffered a MACE had a causal variant in MYBPC3. Those with causal variants in genes other than MYBPC3 presented more and earlier events (p=0.022). Risk of having a MACE during follow-up was higher when presenting causal variants in genes other than MYBPC3: Hazard Ratio 18.5 (95% CI 2.31, 148), p=0.006. Applying HCM Risk-SCD calculator, model had better predictive discrimination when variable "causal variant in gene other than MYBPC3" was added in multivariate analysis, with high-risk category >=6% (C-statistic =0.931 vs 0.844) and intermediate-risk category 4-6% (C-statistic =0.845 vs 0.514). Same occurred with ESC Guidelines algorithm, adding that variable to 2 risk factors category (C-statistic =0.881 vs 0.742) or 1 risk factor (C-statistic =0.844 vs 0.635). HCM Risk-Kids also improved its predictive discrimination adding the genetic value to high-risk category >=6% (C-statistic =0.896 vs 0.796) and intermediate-risk (C-statistic =0.821 vs 0.506). Conclusions Genotype may have prognostic value in SCD risk in HCM in children. Our results suggests that causal genetic variants in genes other than MYBPC3 can lead to higher risk of SCD. Genetic information might be considered for future models of arrhythmic risk in children with HCM.

Multivariate Bayesian variable selection for multi-trait genetic fine mapping

Abstract Genome-wide association studies (GWAS) have identified thousands of single-nucleotide polymorphisms (SNPs) associated with complex traits, but determining the underlying causal variants remains challenging. Fine mapping aims to pinpoint the potentially causal variants from a large number of correlated SNPs possibly with group structure in GWAS-enriched genomic regions using variable selection approaches. In multi-trait fine mapping, we are interested in identifying the causal variants for multiple related traits. Existing multivariate variable selection methods for fine mapping select variables for all responses without considering the possible heterogeneity across different responses. Here, we develop a novel multivariate Bayesian variable selection method for multi-trait fine mapping to select causal variants from a large number of grouped SNPs that target at multiple correlated and possibly heterogeneous traits. Our new method is featured by its selection at multiple levels, incorporation of prior biological knowledge to guide selection and identification of best subset of traits the variants target at. We showed the advantage of our method over existing methods via comprehensive simulations that mimic typical fine-mapping settings and a real-world fine-mapping example in UK Biobank, where we identified critical causal variants potentially targeting at different subsets of addictive behaviours and risk factors.

Utility of polygenic risk score for prediction of dilated cardiomyopathy and modulation of severity of LV dysfunction among cases

Abstract Background Dilated cardiomyopathy (DCM) is a predominant cause of heart failure and a leading indication for cardiac transplantation. While rare genetic variants are established as causative factors in familial forms of the disease, recent genome-wide association studies (GWAS) have also underscored the significant contribution of common genetic variation to DCM. Polygenic scores (PGS) constructed from GWAS have demonstrated promise in risk stratification for a range of common diseases and may similarly have value for risk prediction in DCM. However, data regarding the clinical utility of PGS in DCM remains sparse. Purpose We aimed to evaluate the utility of PGS for prediction of DCM and its association with left ventricular ejection fraction (LVEF) and family history. We further aimed to assess the contribution of PGS in DCM patients with established causative rare variants (genotype-positive) and those without (genotype-negative). Methods We used a previously-constructed PGS, which was developed from a GWAS meta-analysis (8387 DCM cases and 939161 controls) and multi-trait analysis (MTAG) with cardiac MRI traits. In the present analysis, we calculated PGS for a newly assembled cohort of 978 DCM cases from a major university medical centre and 7207 controls from a national register. To evaluate the clinical utility of PGS, we built logistic regression models and assessed the association between PGS and DCM status. Subsequently, we performed subgroup analyses, including: i) individuals of European ancestry, ii) non-European ancestry, iii) males, iv) females, v) genotype-positive participants(n=193), and vi) genotype-negative participants (n=294). We then used linear and logistic regression models, respectively, to assess the associations of PGS with LVEF and documented family history of DCM. Results PGS demonstrated a significant enrichment among DCM cases compared to controls (OR per SD 1.93, P = 9.47E-68). This association persisted with consistent effect estimates - ranging from OR 1.5 to 2.2 - across all examined subgroups and demonstrated sufficient statistical significance (all P<1.58E-06) (Figure 1). Genotype-negative cases had a significantly higher PGS compared to genotype-positive individuals (P = 0.0015), although PGS was significantly enriched in both groups as compared to controls. Furthermore, among DCM cases, higher PGS was significantly associated with lower LVEF at first presentation (P=0.03, beta=-0.5% per SD) (Figure 2). There was no significant association found between PGS and family history. Conclusions PGS is strongly associated with risk of DCM, and may modulate the severity of LV dysfunction among DCM cases. Polygenic burden contributes to DCM risk in both genotype-positive and negative cases, although the contribution is stronger in patients without known causative rare variants. Overall, our results suggest a potential clinical applicability for PGS in DCM risk stratification.Figure 1.Association of PGS with DCMFigure 2.Association of PGS with LVEF

Whole-exome sequencing to identify causative variants in cases of sudden cardiac death below 50 years

Abstract Background Sudden cardiac death (SCD) in individuals under 50 frequently remains unexplained, especially when no structural cardiac abnormalities are present, a condition known as sudden arrhythmic death (SAD). This study assesses the utility of whole exome sequencing (WES) with a comprehensive gene panel in elucidating the genetic foundations of SCD. Methods SCD autopsy cases from a university hospital (1995-2023) were analysed both retrospectively and prospectively. WES was conducted on 32 cases, employing a virtual panel of 1,304 genes. Variant prioritization was based on pathogenicity according to American College of Medical Genetics and Genomics guidelines. Results WES unveiled causative variants in 22 out of 32 cases (68% diagnostic yield). Of these, 12 cases (38%) possessed pathogenic or likely pathogenic variants, and 17 highly suspicious variants of uncertain significance (VUS/LP) were identified in 10 patients (31%). The diagnostic yield of our comprehensive panel (69%) surpassed that of major susceptibility gene panels, with 22% for primary susceptibility genes and 56% for the TruSight Cardio Panel. Half of the cases had multiple variants, underscoring the genetic complexity of SCD. Of the genes analysed, 18 were associated with cardiac disease on OMIM or ClinGen, while 9, unique to our panel, were linked to cardiac function but had disputed or limited disease associations. Conclusions WES with a specific gene panel, a scheme for variant prioritization, and a comprehensive, multidisciplinary approach to variant interpretation is an effective approach to genetic testing in SCD cases ≤50 years.Added value of WES

Proteogenomic analysis in population biobanks identifies new therapeutic targets across heart failure subtypes

Abstract Background Heart failure (HF) represents a multifactorial clinical syndrome with differential response to existing therapies across its subtypes. Proteogenomic analysis of genetic variants associated with changes in circulating protein level and risk of heart failure subtypes provides an opportunity for a systematic identification of proteins with subtype-specific causal effects as novel therapeutic targets. Purpose To identify proteins as potential therapeutic targets for specific heart failure subtypes by leveraging proteomics and genomics data in population biobanks. Methods We evaluated the causal effects of 2,773 proteins on 5 HF-related outcomes, including overall HF, non-ischaemic HF (ni-HF), ni-HF with reduced / preserved ejection fraction (ni-HFrEF / ni-HFpEF), and dilated cardiomyopathy (DCM). For each protein-phenotype pair, we performed a two-sample Mendelian randomisation (MR) analysis using protein-specific genetic association estimates derived from protein quantitative trait locus (pQTL) studies in 114,145 individuals from deCODE, UK Biobank, Fenland study, and SCALLOP consortium and genome-wide association studies (GWAS) of HF outcomes in 145,795 individuals by HERMES Consortium. We further prioritised candidate protein targets based on replication of results across datasets, model parameters, assays, and colocalization of causal genetic variants. Finally, we profiled the causal effects of identified proteins on 32 related cardiac traits and risk factors to explore potential mechanisms of actions and on-target side effects. Results We identified 493 proteins associated with at least one HF outcome at a false discovery rate (FDR) < 1% in the primary MR analysis. We further prioritised 44 proteins with concordant effect direction across datasets, model parameters, and assays or colocalization in at least one dataset. All 44 identified proteins showed cross association with at least one of 35 tested traits other than HF or cardiomyopathies at FDR <1%, including coronary artery disease (18 proteins), body mass index (11 proteins), type 2 diabetes (6 proteins), systolic / diastolic blood pressure (13 proteins), and chronic kidney disease (9 proteins). Conclusion We characterised the causal associations of 2,773 circulating proteins across HF-related outcomes and prioritised 44 proteins by integrating proteomics and genomics data in population biobanks. These findings extend our understanding of the molecular mechanism underlying different forms of HF and may inform the development of new therapeutic strategies.Study design

Micro-capture-C in vessel wall cell types identifies mechanisms underlying coronary artery disease susceptibility loci

Abstract Genetics is estimated to account for 50% of Coronary Artery Disease (CAD) risk. Genome-Wide Association Studies (GWAS) have revealed 100s of genomic loci which are associated with CAD (1). However, moving from GWAS signals to causal genes has proved challenging, slowing progress in developing interventions for CAD and other diseases. The greatest challenge in interpreting GWAS data is that only 10% of variants are in protein-coding regions and 90% are in "non-coding" genomic regions. Many of these non-coding variants are found in regulatory elements such as enhancers. Enhancers are distal regulatory elements that bind transcription factors and regulate genes up to 1 million base pairs away. This is achieved by DNA looping bringing enhancers into physical proximity with target genes. However, it is not possible to predict which gene(s) a given enhancer will regulate based on genomic location alone. We aimed to develop a generalisable workflow to solve CAD GWAS signals accurately and sensitively, by identifying causal enhancer SNPs and linking them mechanistically to output genes in a cell-type specific manner. We combined cell-specific epigenomic mapping with machine learning to prioritise 21,959 SNPs from 861 candidate CAD loci, in endothelial cells (HUVECs) and smooth muscle cells (HCASMCs). Micro-Capture-C (MCC) was used to resolve enhancer-promoter interactions at base-pair resolution (2). MNase footprinting determined differential transcription factor binding at specific enhancer SNPs. In HCASMCs, 20 putative enhancers containing CAD SNPs were found to interact with 32 genes, and in HUVECs 25 enhancers interacted with 48 genes. These genes were enriched for pathways including TGFb signalling, RUNX3 activity, and MAPK6/MAPK4 signalling. To prove causality at specific loci, heterozygous SNPs were identified in the individual primary cell lines. The interaction frequency at these elements was statistically compared between risk and non-risk alleles. For example, at the 9p21.3 locus, an enhancer containing a non-risk T allele was found to interact more strongly with the CDKN2B gene, compared to the risk G allele. Interestingly, this imbalance between allele interaction was potentiated by stimulation with TGFb, a key mediator in atherosclerosis. Furthermore, the transcription factor footprint at the SNP location was altered by the risk allele, indicating the mechanistic cause of the CAD-associated change in CDKN2B expression. We demonstrate a combined computational and experimental approach to identify causal non-coding variants in CAD risk loci, at scale. Among the key outputs of this study is the identification of the risk variant (rs1537373), output gene (CDKN2B), and specific cell type (HCASMC) underlying the 9p21.3 locus association with CAD risk. Using this approach to translate GWAS signals into cell-type specific outputs genes, will lead to a better understanding of the pathogenesis of CAD, and new therapeutic opportunities.

Prediction of family inheritance in non-sarcomeric hypertrophic cardiomyopathy using clinical variables and 12-lead electrocardiogram artificial intelligence models

Abstract Background Hypertrophic cardiomyopathy (HCM) can be familial even in the absence of a causative sarcomeric variant, justifying periodical screening of first-degree relatives. However, indiscriminate screening may burden low-risk individuals unnecessarily. The prevalence and predictors of familial disease in non-sarcomeric HCM remain inadequately characterized. Purpose Our study aims to develop a tailored approach to family screening based on index cases’ clinical profiles. By leveraging artificial intelligence (AI) models, we aim to predict the likelihood of family disease using pertinent clinical variables and electrocardiograms (ECGs) from the proband. Methods From January 2008 to June 2022, all probands diagnosed with HCM at our Heart Institute genetics clinic were included if they had i) negative genetic testing for a (likely) pathogenic variant in a sarcomeric gene and ii) ≥1 first- or second-degree relative screened for HCM. The outcome was the presence of family disease defined as left ventricular wall thickness ≥13mm or verified autopsy report confirming HCM. Predictors of family disease were assessed at the first genetic clinic visit and considered age, sex, hypertension, and echocardiography metrics (maximal wall thickness, septal morphology, outflow tract obstruction at rest or Valsava). Using 12-lead ECGs and clinical variables, we used machine learning to train two distinct AI models. Model A utilized ECG signals only to train a ResNet model, while Model B used both ECGs and selected clinical variables (below 0.2 alpha level in logistic regressions) to train a random forest model to predict family disease. We performed evaluations at both ECG-level (one ECG used per patient) and patient-level (all available ECGs used in a patient) and we present individual and ensemble model performance. Results Among 356 families with sarcomere-negative HCM, 106 (30%) were familial. Probands were aged 53 ± 16 years, 30% female, 36% with a diagnosis of hypertension and 43% with peak outflow tract obstruction ≥30mmHg. In univariable logistic regressions, family disease was associated with age at diagnosis (OR 0.89 per 5-year, P=0.003), hypertension (OR 0.60, P=0.046) and obstruction (OR 0.52, P=0.013). The ensemble AI model, which integrated clinical and ECG data, achieved an AUC of 0.82 (95% CI: [0.795, 0.848]). It demonstrated a specificity of 0.891 (95% CI: [0.867, 0.913]) and a negative predictive value of 0.798 (95% CI: [0.772, 0.823]). When comparing ECG-level and patient-level data (1 to 10 ECGs per patient), the models consistently achieved AUC values between 0.78 and 0.81, indicating stable performance across various data subsets. Conclusion The prevalence of family inheritance in sarcomere-negative HCM can be accurately predicted using AI models that integrate clinical variables and 12-lead ECG data. This approach could enable tailored screening strategies based on the likelihood of family disease.

Amplicon-based long-read sequencing is useful for confirming zygosity of DSG2 variants associated with Japanese ARVC

Abstract Background Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy mainly caused by desmosomal gene variants. Previously, we reported that DSG2 variants were the most common in 153 Japanese ARVC probands (DSG2 multiple, n=62 and single, n=4; PKP2, n=28; others, n=7). Among the multiple DSG2 variant carriers, 22 probands were compound heterozygous carriers, and 25 were homozygous, which were confirmed by genetic testing for family members (Figure A). On the other hand, 88% of their family members with single DSG2 variant carriers were not diagnosed with ARVC, which meant that recessive DSG2 variants were the major cause of ARVC in Japan. However, zygosities in remaining 15 probands with multiple DSG2 variants were unknown due to the lack of genome data from their parents. Purpose This study aimed to clarify the zygosities of multiple DSG2 variants using amplicon-based long-read sequencing. Methods Genomic DNA was extracted from whole blood using standard protocols. The range containing multiple variants was amplified by long-range PCR. Sequencing libraries were prepared using ONT Ligation Sequencing Kit. Each library was loaded onto a flow cell for sequencing on ONT GridION Mk1 running MinKNOW control software. FASTQ files were aligned to hg38 using minimap2. Variants were called using Clair3 and phased using WhatsHap. Integrative Genomics Viewer (IGV) was used for visualization of the phased variants. Results We successfully phased all the multiple DSG2 variants found in the 15 proband. A typical result of amplicon-based LRS was shown in Figure B. It was IGV screen shot of reads at DSG2 containing c.874C>T (p.R292C) and c.1481A>C (p.D494A). The reads colored in red belonged to one haplotype, while the ones in blue belonged to the other. Each of the two variants was on different color reads, indicating they were compound heterozygous variants. Using LRS, we confirmed all the 15 probands had compound heterozygous variants in DSG2. Overall, the 62 probands (40.5%) with DSG2 variants were recessive variant carriers (Figure A). Conclusions Japanese ARVC was mainly caused by autosomal recessive variants in DSG2. Clarifying the zygosity of causative variants is crucial for the diagnosis in recessive diseases including Japanese ARVC. Amplicon-based LRS was helpful for phasing the multiple DSG2 variants directly without genetic testing of the parents.Figure AFigure B

Exposure to Metals, Pesticides, and Air Pollutants: Focus on Resulting DNA Methylation Changes in Neurodegenerative Diseases

Individuals affected by neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS), are dramatically increasing worldwide. Thus, several efforts are being made to develop strategies for stopping or slowing the spread of these illnesses. Although causative genetic variants linked to the onset of these diseases are known, they can explain only a small portion of cases. The etiopathology underlying the neurodegenerative process in most of the patients is likely due to the interplay between predisposing genetic variants and environmental factors. Epigenetic mechanisms, including DNA methylation, are central candidates in translating the effects of environmental factors in genome modulation, and they play a critical role in the etiology of AD, PD, and ALS. Among the main environmental exposures that have been linked to an increased risk for these diseases, accumulating evidence points to the role of heavy metals, pesticides, and air pollutants. These compounds could trigger neurodegeneration through different mechanisms, mainly neuroinflammation and the induction of oxidative stress. However, increasing evidence suggests that they are also capable of inducing epigenetic alterations in neurons. In this article, we review the available literature linking exposure to metals, pesticides, and air pollutants to DNA methylation changes relevant to neurodegeneration.

Genetic Variants Supporting the Diagnosis of Primary Ciliary Dyskinesia in Japan.

Primary ciliary dyskinesia (PCD; OMIM 244400) is a rare genetic disorder affecting motile cilia and is characterized by impaired mucociliary clearance in the airway epithelium that leads to chronic oto-sinopulmonary manifestations. To date, over 50 PCD-causing genes have been identified, with these genes and their variants varying globally across populations. We performed targeted resequencing of 42 PCD-causative genes in 150 Japanese patients suspected of having PCD and identified pathogenic or likely pathogenic variants in 51 patients. Among these, 24 patients exhibited a homozygous deletion of DRC1 exons 1-4, the most common cause of PCD in Japan. The allele frequency of this deletion was estimated at 0.0034 (95% CI: 0.0025-0.0044), based on bioinformatic analysis of 7906 whole-genome sequences from the general Japanese population. Additionally, RNA sequencing of nasal samples supplemented in silico variant predictions, aiding in the identification of causative variants. Considering potential ethnic differences, it is essential to accumulate global data on these variants and their functional impacts.

Variants of the PTPN11 Gene in Mexican Patients with Noonan Syndrome

Background/Objectives: Noonan syndrome (NS) is a genetic multisystem disease characterized by distinctive facial features, short stature, chest deformity, and congenital heart defects. NS is caused by gene variants of the RAS/MAPK pathway, with PTPN11 accounting for about 50% of cases. This study aimed to identify PTPN11 pathogenic variants in Mexican patients with NS to enhance our understanding of the disease in this population. Methods: This study included 91 probands and 60 relatives, all of which were clinically evaluated by a geneticist. Sanger sequencing was used to screen the entire PTPN11 gene. Results: Twenty-one previously reported pathogenic variants were identified in 47.3% of the probands. The most frequently occurring were p.Asn308Asp (16.3%) and p.Met504Val (16.3%). Variants p.Tyr279Cys and p.Thr468Met were found exclusively in patients with lentiginosis. Eighty-three percent of patients carried a variant in one of the three exons (3, 8, or 13) where the greatest genetic diversity was observed. Common clinical findings identified in probands included short stature (82%), cardiac anomalies (70.7%), short neck (68.4%), and pectus excavatum (63.2%), although features represented by only one patient each were also detected. Conclusions: This study confirmed the clinical diagnosis of NS in 43 probands and 11 relatives, and further genetic analysis of the remaining 48 probands is required to identify the causal variant. The genetic and clinical variability observed in our cohort was consistent with reports from other populations, underscoring the importance of comprehensive care for all patients. This research provides the most extensive clinical and molecular characterization of NS in Mexican patients, identifying pathogenic variants of PTPN11.

Defining the transcriptome of PIK3CA-altered cells in a human capillary malformation using single cell long-read sequencing

PIK3CA-related overgrowth spectrum (PROS) disorders are caused by somatic mosaic variants that result in constitutive activation of the phosphatidylinositol-3-kinase/AKT/mTOR pathway. Promising responses to molecularly targeted therapy have been reported, although identification of an appropriate agent can be hampered by the mosaic nature and corresponding low variant allele frequency of the causal variant. Moreover, our understanding of the molecular consequences of these variants—for example how they affect gene expression profiles—remains limited. Here we describe in vitro expansion of a human capillary malformation followed by molecular characterization using exome sequencing, single cell gene expression, and targeted long-read single cell RNA-sequencing in a patient with clinical features consistent with Megalencephaly-Capillary Malformation Syndrome (MCAP, a PROS condition). These approaches identified a targetable PIK3CA variant with expression restricted to PAX3+ fibroblast and undifferentiated keratinocyte populations. This study highlights the innovative combination of next-generation single cell sequencing methods to better understand unique transcriptomic profiles and cell types associated with MCAP, revealing molecular intricacies of this genetic syndrome.

Clinical relevance of protein-truncating variants of germline DNA repair genes in prostate cancer

BackgroundInterpreting genetic variants remains a challenge in prostate cancer (PCa). Although many annotation tools are available for prioritizing causal variants, the clinical relevance of these variants is rarely studied.MethodsWe collected a cohort study that included 274 PCa patients from June 2017 to December 2020 and sequenced 19 DNA damage repair (DDR) genes in these patients and explored the clinical consequence of these different approaches. We also examined all-cause and PCa-specific survival in DDR gene mutation carriers compared to non-carriers after androgen receptor (AR)-directed therapy.ResultsWe identified 13 variants from 19 DDR genes in a total of 14 (5.1%) patients who had at least one presumed pathogenic mutation using different annotation methods. Four variants were annotated as pathogenic, 11 variants were predicted as protein-truncating variants (PTVs), four variants received proxy-deleterious (Combined Annotation-Dependent Depletion scores of > 30), and only one variant was identified as a pathogenic variant or as having a functional effect by all three methods. PCa patients with PTVs were significantly associated with early onset, high cancer stage, and a worse response to AR-directed treatment. However, patients carrying a proxy-deleterious variant were only associated with a higher T (tumor) stage and N (node) stage than those without such a variant, but not associated with other clinical characteristics. In patients treated with AR-directed therapy, patients with a PTV showed an increased risk of all-cause death (adjusted hazard ratio (aHR) = 3.51, 95% confidence interval (CI): 1.06 ~ 11.56) and PCa-specific death (aHR = 4.49, 95% CI: 1.87 ~ 10.77) compared to non-PTV carriers after adjustment. We were unable to examine gene-specific risks due to the small number of patients.ConclusionsPTVs may assist in guiding treatment and early screening in PCa, while population-specific data for pathogenic variants are still being amassed.

HEARRING group genetic marker study: genetic background of CI patients.

While cochlear implantation (CI) and electric acoustic stimulation (EAS) have a positive outcome in most cases, their effectiveness varies depending on the etiology of the hearing loss. Among the various etiologies, genetic factors are the leading cause of hearing loss and may impact CI and EAS outcomes. To reveal the genetic background of the hearing loss in CI/EAS patients in each ethnic population, we undertook a multi-center study involving the genetic testing of hearing loss in CI/EAS patients from 10 centers. Saliva samples and clinical information for the patients and their family members were obtained and next-generation sequencing analysis using a panel carrying 63 deafness genes was then performed. Genetic testing successfully identified the causative gene variants in 54.5% (48/88) of patients with pre-lingual onset hearing loss (onset under 6 years) and in 12% (12/95) of those with late-onset hearing loss (onset at 6 years or more). We clearly indicated that genetic factors are the most common cause of hearing loss regardless of ethnic background. Saliva-based genetic testing is a useful tool for multi-center studies seeking to clarify the genetic causes of hearing loss in CI or EAS patients between countries separated by distance.

Genetic heterogeneity in autosomal recessive hearing loss: a survey of Brazilian families

IntroductionHearing loss is a frequent sensory impairment type in humans, with about 50% of prelingual cases being attributed to genetic factors. Autosomal recessive hearing loss (ARHL) exhibits great locus heterogeneity and is responsible for 70%–80% of hereditary nonsyndromic cases.MethodsA total of 90 unrelated Brazilian individuals were selected for having hearing loss of presumably autosomal recessive inheritance, either born from consanguineous marriages or belonging to families with two or more affected individuals in the sibship and most cases were of normal hearing parents. In all cases, common pathogenic variants in GJB2 (c.35delG), GJB6 [del(GJB6-D13S1830) and del(GJB6-D13S1854)] and MT-RNR1 (m.1555A>G) were discarded and most were previously assessed by complete Sanger sequencing of GJB2. Their genetic material was analyzed through next-generation sequencing, targeting 99 hearing loss-related genes and/or whole exome sequencing.ResultsIn 32 of the 90 probands (36,7%) causative variants were identified, with autosomal recessive inheritance confirmed in all, except for two cases due to dominant variants (SIX1 and P2RX2). Thirty-nine different causative variants were found in 24 different known hearing loss-associated genes, among which 10 variants are novel, indicating wide genetic heterogeneity in the sample, after exclusion of common pathogenic variants. Despite the genetic heterogeneity, some genes showed greater contribution: GJB2, CDH23, MYO15A, OTOF, and USH2A.ConclusionThe present results confirmed that next-generation sequencing is an effective tool for identifying causative variants in autosomal recessive hearing loss. To our knowledge, this is the first report of next-generation sequencing being applied to a large cohort of pedigrees with presumable autosomal recessive hearing loss in Brazil and South America.

A Frameshift Variant in ANKRD24 Implicates Its Role in Human Non-Syndromic Hearing Loss.

Hearing loss (HL) is the most prevalent sensorineural disorders, affecting about one in 1000 newborns. Over half of the cases are attributed to genetic factors; however, due to the extensive clinical and genetic heterogeneity, many cases remain without a conclusive genetic diagnosis. The advent of next-generation sequencing methodologies in recent years has greatly helped unravel the genetic etiology of HL by identifying numerous genes and causative variants. Despite this, much remains to be uncovered about the genetic basis of sensorineural hearing loss (SNHL). Here, we report an Iranian consanguineous family with postlingual, moderate-to-severe autosomal recessive SNHL. After first excluding plausible variants in known deafness-causing genes using whole exome sequencing, we reanalyzed the data, using a gene/variant prioritization pipeline established for novel gene discovery for HL. This approach identified a novel homozygous frameshift variant c.1934_1937del; (p.Thr645Lysfs*52) in ANKRD24, which segregated with the HL phenotype in the family. Recently, ANKRD24 has been shown to be a pivotal constituent of the stereocilia rootlet in cochlea hair cells and interacts with TRIOBP, a protein already implicated in human deafness. Our data implicate for the first time, ANKRD24 in human nonsyndromic HL (NSHL) and expands the genetic spectrum of HL.

Clinical and genetic characterisation of childhood-onset sensorineural hearing loss reveal associated phenotypes and enrichment of pathogenic founder mutations in the Finnish population

Objective To examine the clinical and genetic characteristics of childhood-onset bilateral sensorineural hearing loss (SNHL) in Finland. Design Retrospective analysis. Study sample A total of 249 children younger than 18 years were diagnosed with bilateral SNHL in Oulu University Hospital, Finland, from 2017 to 2022. Results Pathogenic or likely pathogenic gene variants or chromosome abnormalities explaining SNHL were identified in 41% (N = 101/249) of children. Likely causative variants were more commonly identified in patients with severe SNHL than in those with moderate or mild SNHL. Our study identified likely causative gene variants in 24 different genes and six different likely causative chromosome abnormalities, demonstrating the genetic heterogeneity of SNHL. Population-enriched founder mutations were identified in the CABP2, CLRN1, MYO7A, SUCLA2, TMC1, and TWNK genes. A significant number of patients had associated phenotypes, including global developmental delay or intellectual disability (16%), language disorder (20%), ophthalmological abnormalities (16%), or malformations other than those involving the ear (10%). Conclusions SNHL is genetically and clinically heterogeneous. Pathogenic variants in GJB2 were the most common. Several population-enriched variants were identified as causing SNHL in the northern Finnish population. Associated medical phenotypes are common and should be taken into account in patients’ follow-up and treatment.

Neurologists’ understanding of reproductive medicine options for genetic forms of motor neuron disease

Objectives To examine the knowledge, confidence and practice of motor neuron disease (MND) clinicians toward discussing reproductive options with people who carry a causal variant in an MND gene (both clinically affected and asymptomatic). Methods An online cross-sectional survey was distributed nationwide to UK MND clinicians and clinical geneticists and genetic counselors. The survey assessed respondents’ understanding on reproductive medicine techniques; their confidence in discussing reproductive medicine options and their access to information resources. Results Seventy six clinicians responded to the online survey (45 neurology clinicians and 31 clinical geneticists). MND clinicians had limited knowledge and low confidence in discussing reproductive medicine options. Geneticists were more likely to carry out reproductive genetic counseling with very few MND clinicians reporting undertaking these discussions. Further, 57% of the 45 MND clinicians surveyed reported to have never made a referral for reproductive genetic counseling. Multiple barriers to offering reproductive counseling or referral were identified including a lack of knowledge, lack of awareness of the different options, lack of clinic time and uncertainty around issues such as funding for PGT and whose responsibility it comes under. Conclusions There is a need for training and education on reproductive options and referral for these options needs to be integrated within the health system. Developing more resources for both clinicians and patients is required as MND clinicians reported a lack of resources.

Base editing screens define the genetic landscape of cancer drug resistance mechanisms.

Drug resistance is a principal limitation to the long-term efficacy of cancer therapies. Cancer genome sequencing can retrospectively delineate the genetic basis of drug resistance, but this requires large numbers of post-treatment samples to nominate causal variants. Here we prospectively identify genetic mechanisms of resistance to ten oncology drugs from CRISPR base editing mutagenesis screens in four cancer cell lines using a guide RNA library predicted to install 32,476 variants in 11 cancer genes. We identify four functional classes of protein variants modulating drug sensitivity and use single-cell transcriptomics to reveal how these variants operate through distinct mechanisms, including eliciting a drug-addicted cell state. We identify variants that can be targeted with alternative inhibitors to overcome resistance and functionally validate an epidermal growth factor receptor (EGFR) variant that sensitizes lung cancer cells to EGFR inhibitors. Our variant-to-function map has implications for patient stratification, therapy combinations and drug scheduling in cancer treatment.

ABCA3 c.838C>T (p.Arg280Cys, R280C) and c.697C>T (p.Gln233Ter, Q233X, Q233*) as Causative Variants for RDS: A Family Case Study and Literature Review.

Background: Respiratory distress syndrome (RDS) is the primary cause of respiratory failure in preterm infants, but it also affects 5-7% of term infants. Dysfunctions in pulmonary surfactant metabolism, resulting from mutations of the lung surfactant genes, are rare diseases, ranging from fatal neonatal RDS to interstitial lung disease, associated with increased morbidity and mortality. This study aims to clarify the clinical significance of ABCA3 variants found in a specific family case, as existing data in the literature are inconsistent. Material and Methods: A family case report was conducted; targeted panel genetic testing identified a variant of the SFTPB gene and two variants of ABCA3 genes. Comprehensive research involving a systematic review of PubMed, Google Scholar databases, and genome browsers was used to clarify the pathogenicity of the two ABCA3 variants found in the index patient. Advanced prediction tools were employed to assess the pathogenicity of the two ABCA3 variants, ensuring the validity and reliability of our findings. Results: The index case exhibited fatal neonatal RDS. Genetic testing revealed the presence of the SFTPB p.Val267Ile variant, which was not previously reported but is a benign variant based on family genetic testing and history. Additionally, two ABCA3 gene variants were identified: c.697C>T, not yet reported, and c.838C>T. These variants were found to affect ABCA3 protein function and were likely associated with neonatal RDS. Prediction tools and data from nine other cases in the literature supported this conclusion. Conclusions: Based on in silico predictors, an analysis of the presented family, and cases described in the literature, it is reasonable to consider reclassifying the two ABCA3 variants identified in the index case as pathogenic/pathogenic. Reclassification will improve genetic counseling accuracy and facilitate correct diagnosis.