Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure

AAVrh.10 delivery of novel APOE2-Christchurch variant suppresses amyloid and Tau pathology in Alzheimer's disease mice

Gene therapy to treat hereditary disorders conventionally delivers the normal allele to compensate for loss-of-function mutations. More effective gene therapy may be achieved using a gain-of-function variant. We tested the hypothesis that AAVrh.10-mediated CNS delivery of the human APOE2 allele with the Christchurch mutation (R136S) (E2Ch) will provide superior protection against APOE4-associated Alzheimer's disease (AD) in mice compared to the unmodified APOE2 allele (E2). The vectors were assessed in two mouse strains with humanized APOE4: APP.PSEN1/TRE4 "amyloid mice" and P301S/TRE4, "tau mice." Both the E2Ch and E2 vectors prevented Aβ42 and Aβ40 accumulation and decreased β-amyloid aggregates in amyloid mice, but only the E2Ch vector suppressed tau tangles in tau mice. Microglial activation and reactive astrocytes were significantly suppressed by both vectors in amyloid mice but only the E2Ch vector mediated significant suppression of Iba1 and glial fibrillary acidic protein (GFAP) in tau mice. In four behavioral assays, the E2 and E2Ch vectors had similar benefits in amyloid mice, but E2Ch outperformed E2 in tau mice. In summary, while E2 is effective in suppressing amyloid pathology, the novel E2 variant E2Ch more effectively treats both the amyloid and tau pathology of murine AD in APOE4 background, supporting the development of AAVrh.10APOE2Ch as a therapy for APOE4-associated AD.

Biochemistry and genetics are coming together to improve our understanding of genotype to phenotype relationships

Since genome sequencing became accessible, determining how specific differences in genotypes lead to complex phenotypes such as disease has become one of the key goals in biomedicine. Predicting effects of sequence variants on cellular or organismal phenotype faces several challenges. First, variants simultaneously affect multiple protein properties and predicting their combined effect is complex. Second, effects of changes in a single protein propagate through the cellular network, which we only partially understand. In this review, we emphasize the importance of both biochemistry and genetics in addressing these challenges. Moreover, we highlight work that blurs the distinction between biochemistry and genetics fields to provide new insights into the genotype-to-phenotype relationships.

Clinical Characterization of a National Cohort of Patients With Germline WT1 Variants Including Late-Onset Phenotypes

Introduction

WT1 disorder is a recently introduced term for phenotypes associated with germline Wilms Tumor 1 (WT1) variants, including glomerulopathy, urogenital anomalies, and Wilms tumor. Previous studies showed a bias toward missense variants in the DNA-binding/Zinc-finger domain of WT1 (exon 8 and 9) and patients with early-onset glomerulopathy. Thorough genotype-phenotype correlations including follow-up data on late-onset glomerulopathy risk are lacking. To characterize the genotypic and phenotypic spectrum of WT1 disorder, we describe a national cohort of individuals with WT1 variants.

Methods

We requested clinical and genetic data of all patients with germline WT1 variants at all Dutch genetic laboratories.

Results

We identified 43 patients with pathogenic WT1 variants (truncating, n = 19; missense, n = 13; splice-site, n = 7; and deletions, n = 4). Wilms tumor was the only clinical manifestation in 10 patients, of whom 9 were female. Wilms tumor occurred in 18 of 19 patients with truncating variants, in 4 of 4 patients with deletions, and was rarer in patients with missense or splice-site variants. All patients with missense and 6 of 7 with splice-site variants developed chronic kidney disease (CKD) versus 5 of 19 patients with truncating variants (3 in adulthood, with kidney failure at the age of 24, 26, and 41 years) and 1 of 4 with a deletion. Urogenital malformations occurred predominantly in 46,XY individuals.

Conclusion

Among patients with WT1 variants, a genotype-phenotype correlation was observed for Wilms tumor risk and age of CKD onset. Although childhood-onset CKD was more common in patients with missense variants in the DNA-binding/Zinc-finger domain, other patients may develop CKD and kidney failure later in life. Therefore, life-long surveillance of kidney function is recommended. Being alert about WT1 variants is especially important for girls with Wilms tumor who often miss additional phenotypes.

Detection of Genetic Variations in Children with Tetralogy of Fallot Using Whole Exome Sequencing Technology Integrated Bioinformatics Analysis

Background: Tetralogy of Fallot (TOF) is the most common cyanotic heart defect in newborns, with a complex etiology and genetic variation considered to be one of the main pathogenic factors. Identifying genetic variations associated with TOF has important clinical value for understanding its pathogenesis, patient susceptibility, and prognosis of patients with TOF. Therefore, this study aimed to identify potential pathogenic genes of TOF through comprehensive genetic analysis. Materials and Methods: In this study, we employed whole exome sequencing (WES) of the DNA of 47 Chinese children who received surgical TOF treatment at the Children's Hospital of Zhejiang University of Medicine and processed for DNA extraction and quantification of the DNA following WES using the Illumina NovaSeq platform. WES data undergo strict quality control and analysis processes including alignment, postprocessing, variant calling, annotation, and prioritization. Key tools, such as GATK's haplotype calling module and Annotate Variation, were used for variant annotation. In addition, by combining bioinformatics tools such as SIFT, Polyphen2, and Clin Pred, we evaluated the potential impact of nonsynonymous mutations on protein function and referred to relevant literature to support our prediction. Results: Comprehensive data analysis and quality assessment analysis corroborated the data generated from the WES dataset of 47 patients with TOF. Interpreting variants from the perspective of clinical pathogenicity results revealed a novel polymorphism and variant associated with TOF. The identified genetic results revealed evidence for a major contribution of MUTYH, RARB, GFM1, PDZD2, CEP57, DCPS, POMT2, BUB1B, CYP19A1, MAZ, USP10, and TCF3 and provided novel findings for functionally interacting proteins associated with the pathomechanism of TOF. Seven pathogenic variants related to TOF were detected, most of which were previously unreported in this cohort. Conclusions: The genetic variations discovered in this study emphasize the importance of genetic factors in the pathogenesis of TOF, revealing its complex molecular pathways and protein-protein interactions. The study of genetic diversity provides a new perspective for understanding the etiology of TOF and promotes an in-depth exploration of its pathological mechanisms. These findings lay the foundation for subsequent clinical research and the development of treatment strategies.

Protein structural context of cancer mutations reveals molecular mechanisms and candidate driver genes

Advances in protein structure determination and modeling allow us to study the structural context of human genetic variants on an unprecedented scale. Here, we analyze millions of cancer-associated missense mutations based on their structural locations and predicted perturbative effects. By considering the collective properties of mutations at the level of individual proteins, we identify distinct patterns associated with tumor suppressors and oncogenes. Tumor suppressors are enriched in structurally damaging mutations, consistent with loss-of-function mechanisms, while oncogene mutations tend to be structurally mild, reflecting selection for gain-of-function driver mutations and against loss-of-function mutations. Although oncogenes are difficult to distinguish from genes with no role in cancer using only structural damage, we find that the three-dimensional clustering of mutations is highly predictive. These observations allow us to identify candidate driver genes and speculate about their molecular roles, which we expect will have general utility in the analysis of cancer sequencing data.

GoFCards: an integrated database and analytic platform for gain of function variants in humans

Gain-of-function (GOF) variants, which introduce new or amplify protein functions, are essential for understanding disease mechanisms. Despite advances in genomics and functional research, identifying and analyzing pathogenic GOF variants remains challenging owing to fragmented data and database limitations, underscoring the difficulty in accessing critical genetic information. To address this challenge, we manually reviewed the literature, pinpointing 3089 single-nucleotide variants and 72 insertions and deletions in 579 genes associated with 1299 diseases from 2069 studies, and integrated these with the 3.5 million predicted GOF variants. Our approach is complemented by a proprietary scoring system that prioritizes GOF variants on the basis of the evidence supporting their GOF effects and provides predictive scores for variants that lack existing documentation. We then developed a database named GoFCards for general geneticists and clinicians to easily obtain GOF variants in humans (http://www.genemed.tech/gofcards). This database also contains data from >150 sources and offers comprehensive variant-level and gene-level annotations, with the aim of providing users with convenient access to detailed and relevant genetic information. Furthermore, GoFCards empowers users with limited bioinformatic skills to analyze and annotate genetic data, and prioritize GOF variants. GoFCards offers an efficient platform for interpreting GOF variants and thereby advancing genetic research.

Biochemical, biophysical, and structural investigations of two mutants (C154Y and R312H) of the human Kir2.1 channel involved in the Andersen-Tawil syndrome

Inwardly rectifying potassium (Kir) channels play a pivotal role in physiology by establishing, maintaining, and regulating the resting membrane potential of the cells, particularly contributing to the cellular repolarization of many excitable cells. Dysfunction in Kir2.1 channels is implicated in several chronic and debilitating human diseases for which there are currently no effective treatments. Specifically, Kir2.1-R312H and Kir2.1-C154Y mutations are associated with Andersen-Tawil syndrome (ATS) in humans. We have investigated the impact of these two mutants in the trafficking of the channel to the cell membrane and function in Xenopus laevis oocytes. Despite both mutations being trafficked to the cell membrane at different extents and capable of binding PIP2 (phosphatidylinositol-4,5-bisphosphate), the main modulator for channel activity, they resulted in defective channels that do not display K+ current, albeit through different molecular mechanisms. Coexpression studies showed that R312H and C154Y are expressed and associated with the WT subunits. While WT subunits could rescue R312H dysfunction, the presence of a unique C154Y subunit disrupts the function of the entire complex, which is a typical feature of mutations with a dominant-negative effect. Molecular dynamics simulations showed that Kir2.1-C154Y mutation induces a loss in the structural plasticity of the selectivity filter, impairing the K+ flow. In addition, the cryo-EM structure of the Kir2.1-R312H mutant has been reconstructed. This study identified the molecular mechanisms by which two ATS-causing mutations impact Kir2.1 channel function and provide valuable insights that can guide potential strategies for the development of future therapeutic interventions for ATS.

Recent Applications of In Silico Approaches for Studying Receptor Mutations Associated with Human Pathologies

In recent years, the advent of computational techniques to predict the potential activity of a drug interacting with a receptor or to predict the structure of unidentified proteins with aberrant characteristics has significantly impacted the field of drug design. We provide a comprehensive review of the current state of in silico approaches and software for investigating the effects of receptor mutations associated with human diseases, focusing on both frequent and rare mutations. The reported techniques include virtual screening, homology modeling, threading, docking, and molecular dynamics. This review clearly shows that it is common for successful studies to integrate different techniques in drug design, with docking and molecular dynamics being the most frequently used techniques. This trend reflects the current emphasis on developing novel therapies for diseases resulting from receptor mutations with the recently discovered AlphaFold algorithm as the driving force.

Structural and functional consequences of non-synonymous SNPs within the LAMA2 protein: a molecular dynamics perspective

Clinical phenotypic presentations associated with LAMA2 deficiency have shown a variety of manifestations. LAMA2 mutations are mainly linked to congenital muscular dystrophy, but there is also mounting evidence suggesting their presence in inflammatory breast cancer, laryngopharyngeal squamous cell carcinoma, and ventricular tachycardia related to coronary artery disease and cardiomyopathy. This study examined the structural and functional impacts of 144 non-synonymous single nucleotide polymorphisms (nsSNPs) within the LAMA2 gene. Through multi-tiered sequence and structure-based methods, 11 deleterious and destabilizing mutations were identified (A1362T, E1308Q, E1360G, I1276S, L1195P, M1359T, P1232H, P1238A, P1272L, Y1234H, Y1338C). Further, four mutations (L1195P, Y1234H, P1238A, A1362T), which aligned with conserved positions, were subjected to 500 ns molecular dynamics (MD) simulations. RMSD calculated from MD trajectories highlighted structural disparities between wild-type and mutant forms, with the latter showing greater flexibility. Radius of gyration analysis indicated reduced compactness, solvent accessibility changes suggested unfolding, and hydrogen bond (HB) analysis demonstrated disrupted integrity. The HB analysis revealed disruptions in structural integrity due to diminished hydrogen bonds in mutants. Secondary structure analysis revealed significant alterations in secondary structural content. Principal Component Analysis unveiled increased dynamic behavior in mutants. Gibbs free energy landscape analysis reflected distinct energy minima regions in mutants, indicating structural destabilization. Overall, this study revealed the functional and structural ramifications of nsSNPs in the LAMA2 gene, providing valuable insights into potential disease-causing mutations and warranting future research on understanding LAMA2 associated diseases and disorders.

Clinical exome sequencing data from patients with inborn errors of immunity: Cohort level diagnostic yield and the benefit of systematic reanalysis

While next generation sequencing has expanded the scientific understanding of Inborn Errors of Immunity (IEI), the clinical use and re-use of exome sequencing is still emerging. We revisited clinical exome data from 1300 IEI patients using an updated in silico IEI gene panel. Variants were classified and curated through expert review. The molecular diagnostic yield after standard exome analysis was 11.8 %. Through systematic reanalysis, we identified variants of interest in 5.2 % of undiagnosed patients, with 76.7 % being (candidate) disease-causing, providing a (candidate) diagnosis in 15.2 % of our cohort. We find a 1.7 percentage point increase in conclusive molecular diagnoses. We find a high degree of actionability in patients with a genetic diagnosis (76.4 %). Despite the modest absolute diagnostic gain, these data support the benefit of iterative exome reanalysis in IEI patients, conveying the notion that our current understanding of genes and variants involved in IEI is by far not saturated.

Genetics and Genomics 101

Genetic mutations, both favorable and unfavorable, are the raw material for improvement in livestock populations. The random inheritance of these mutations is essential for generating progenies with genetic potential greater than their parents. These mutations can act either in a simple manner, such that a single alteration disrupts phenotype, or in a complex manner where hundreds or thousands of mutations of small effect create a continuous distribution of phenotypes. Selection tools leverage phenotypic records, pedigrees, and genomics to estimate the genetic potential of individual animals. This more accurate accounting of genetic potential has generated enormous gains in livestock populations.

Dual inheritance patterns: A spectrum of non-syndromic inherited retinal disease phenotypes with varying molecular mechanisms

Inherited retinal diseases (IRDs) encompass a variety of disease phenotypes and are known to display both clinical and genetic heterogeneity. A further complexity is that for several IRD-associated genes, pathogenic variants have been reported to cause either autosomal dominant (AD) or autosomal recessive (AR) diseases. The possibility of dual inheritance can create a challenge for variant interpretation as well as the genetic counselling of patients. This review aims to determine whether the molecular mechanisms behind the dual inheritance of each IRD-associated gene is well established, not yet properly understood, or if the association is questionable. Each gene is discussed individually in detail due to different protein structures and functions, but there are overlapping characteristics. For example, eight genes only have a limited number of reported pathogenic variants or a hotspot region implicated in the second inheritance pattern. Whereas CRX and RP1 display distinct spatial patterns for AR and AD pathogenic variants based on the variant type and/or location. The genes with a questionable dual inheritance, namely AIPL1, CRB1, and RCBTB1 highlight the importance of carefully considering allele frequency data. Finally, the crucial role relevant functional studies in animal and cell models play in validating a variant's biochemical or molecular effect is emphasised.

Understanding the heterogeneous performance of variant effect predictors across human protein-coding genes

Variant effect predictors (VEPs) are computational tools developed to assess the impacts of genetic mutations, often in terms of likely pathogenicity, employing diverse algorithms and training data. Here, we investigate the performance of 35 VEPs in the discrimination between pathogenic and putatively benign missense variants across 963 human protein-coding genes. We observe considerable gene-level heterogeneity as measured by the widely used area under the receiver operating characteristic curve (AUROC) metric. To investigate the origins of this heterogeneity and the extent to which gene-level VEP performance is predictable, for each VEP, we train random forest models to predict the gene-level AUROC. We find that performance as measured by AUROC is related to factors such as gene function, protein structure, and evolutionary conservation. Notably, intrinsic disorder in proteins emerged as a significant factor influencing apparent VEP performance, often leading to inflated AUROC values due to their enrichment in weakly conserved putatively benign variants. Our results suggest that gene-level features may be useful for identifying genes where VEP predictions are likely to be more or less reliable. However, our work also shows that AUROC, despite being independent of class balance, still has crucial limitations when used for comparing VEP performance across different genes.

Gain- and loss-of-function alleles within signaling pathways lead to phenotypic diversity among individuals

Understanding how phenotypic diversity is generated is an important question in biology. We explored phenotypic diversity among wild yeast isolates (Saccharomyces cerevisiae) and found variation in the activity of MAPK signaling pathways as a contributing mechanism. To uncover the genetic basis of this mechanism, we identified 1957 SNPs in 62 candidate genes encoding signaling proteins from a MAPK signaling module within a large collection of yeast (>1500 individuals). Follow-up testing identified functionally relevant variants in key signaling proteins. Loss-of-function (LOF) alleles in a PAK kinase impacted protein stability and pathway specificity decreasing filamentous growth and mating phenotypes. In contrast, gain-of-function (GOF) alleles in G-proteins that were hyperactivating induced filamentous growth. Similar amino acid substitutions in G-proteins were identified in metazoans that in some cases were fixed in multicellular lineages including humans, suggesting hyperactivating GOF alleles may play roles in generating phenotypic diversity across eukaryotes. A mucin signaler that regulates MAPK activity was also found to contain a prevalance of presumed GOF alleles amoung individuals based on changes in mucin repeat numbers. Thus, genetic variation in signaling pathways may act as a reservoir for generating phenotypic diversity across eukaryotes.

Current and Future Directions in Developing Effective Treatments for PRPH2-Associated Retinal Diseases: A Workshop Report

Purpose and Methods

A workshop of affected individuals and their families, clinicians, researchers, and industry representatives was convened in March 2023 to define the knowledge landscape of peripherin 2 (PRPH2) biology and identify challenges and opportunities towards developing PRPH2-associated inherited retinal disease (IRD) treatments.

Results

The results of an online survey and presentations from affected individuals and their family members revealed disease characteristics and impacts on daily living. Scientific sessions highlighted the significant heterogeneity in clinical presentation of PRPH2-related retinopathy; PRPH2's crucial function in rod and cone outer segment formation and maintenance; the usefulness of existing animal and cellular models for understanding disease pathophysiology; and possible therapeutic approaches for autosomal dominant PRPH2-associated IRDs, including gene-specific therapies and gene-agnostic approaches. Priority gaps identified by the workshop included having a more complete understanding of PRPH2's fundamental biology and factors contributing to PRPH2-related disease phenotypic diversity, establishing genotype-phenotype correlations, and creating additional models to probe the functional consequences of PRPH2 variants and to test therapies. Additionally, a natural history study involving a large number of participants is required to more fully characterize PRPH2-related disease progression, aiding in interventional clinical trial design.

Conclusions

Because PRPH2-associated IRDs are rare, maximizing opportunities for communication and collaboration among stakeholders, such as that provided by the workshop, is crucial to overcome the challenges to developing effective treatments and improve the lives of affected individuals.

Translational Relevance

Fostering communication among stakeholders to identify knowledge gaps, therapeutic challenges, and potential opportunities toward developing effective treatments for PRPH2-related IRDs.

Considerations for reporting variants in novel candidate genes identified during clinical genomic testing

Since the first novel gene discovery for a Mendelian condition was made via exome sequencing, the rapid increase in the number of genes known to underlie Mendelian conditions coupled with the adoption of exome (and more recently, genome) sequencing by diagnostic testing labs has changed the landscape of genomic testing for rare diseases. Specifically, many individuals suspected to have a Mendelian condition are now routinely offered clinical ES. This commonly results in a precise genetic diagnosis but frequently overlooks the identification of novel candidate genes. Such candidates are also less likely to be identified in the absence of large-scale gene discovery research programs. Accordingly, clinical laboratories have both the opportunity, and some might argue a responsibility, to contribute to novel gene discovery, which should, in turn, increase the diagnostic yield for many conditions. However, clinical diagnostic laboratories must necessarily balance priorities for throughput, turnaround time, cost efficiency, clinician preferences, and regulatory constraints and often do not have the infrastructure or resources to effectively participate in either clinical translational or basic genome science research efforts. For these and other reasons, many laboratories have historically refrained from broadly sharing potentially pathogenic variants in novel genes via networks such as Matchmaker Exchange, much less reporting such results to ordering providers. Efforts to report such results are further complicated by a lack of guidelines for clinical reporting and interpretation of variants in novel candidate genes. Nevertheless, there are myriad benefits for many stakeholders, including patients/families, clinicians, and researchers, if clinical laboratories systematically and routinely identify, share, and report novel candidate genes. To facilitate this change in practice, we developed criteria for triaging, sharing, and reporting novel candidate genes that are most likely to be promptly validated as underlying a Mendelian condition and translated to use in clinical settings.

Understanding large scale sequencing datasets through changes to protein folding

The expansion of high-quality, low-cost sequencing has created an enormous opportunity to understand how genetic variants alter cellular behaviour in disease. The high diversity of mutations observed has however drawn a spotlight onto the need for predictive modelling of mutational effects on phenotype from variants of uncertain significance. This is particularly important in the clinic due to the potential value in guiding clinical diagnosis and patient treatment. Recent computational modelling has highlighted the importance of mutation induced protein misfolding as a common mechanism for loss of protein or domain function, aided by developments in methods that make large computational screens tractable. Here we review recent applications of this approach to different genes, and how they have enabled and supported subsequent studies. We further discuss developments in the approach and the role for the approach in light of increasingly high throughput experimental approaches.

Interpretation of molecular autopsy findings in 45 sudden unexplained death cases: from coding region to untranslated region

Sudden unexplained death (SUD) can affect apparently healthy adolescents and young adults with no prior clinical symptoms and no clear diagnostic findings at autopsy. Although primary cardiac arrhythmias have been shown to be the direct cause of death in the majority of SUD cases, the genetic predisposition contributing to SUD remains incompletely understood. Currently, molecular autopsy is considered to be an effective diagnostic tool in the multidisciplinary management of SUD, but the analysis focuses mainly on the coding region and the significance of many identified variants remains unclear. Recent studies have demonstrated the strong association between human disease and genetic variants in untranslated regions (UTRs), highlighting the potential role of UTR variants in the genetic predisposition to SUD. In this study, we searched for UTR variants with likely functional effects in the exome data of 45 SUD cases. Among 244 genes associated with cardiac diseases, three candidate variants with high confidence of pathogenicity were identified in the UTRs of SCO2, CALM2 and TBX3 based on a rigorous filtering strategy. A functional assay further validated the effect of these candidate variants on gene transcriptional activity. In addition, the constraint metrics, intolerance indexes, and dosage sensitivity scores of genes affected by the candidate variants were considered when estimating the consequence of aberrant gene expression. In conclusion, our study presents a practical strategy for UTR variant prioritization and functional annotation, which could improve the interpretation of molecular autopsy findings in SUD cohorts.

Prevalence of the cancer-associated germline variants in Russian adults and long-living individuals: using the ACMG recommendations and computational interpreters for pathogenicity assessment

Background

Population studies are essential for gathering critical disease prevalence data. Automated pathogenicity assessment tools enhance the capacity to interpret and annotate large amounts of genetic data. In this study, we assessed the prevalence of cancer-associated germline variants in Russia using a semiautomated variant interpretation algorithm.

Methods

We examined 74,996 Russian adults (Group 1) and 2,872 long-living individuals aged ≥ 90 years (Group 2) for variants in 28 ACMG-recommended cancer-associated genes in three steps: InterVar annotation; ClinVar interpretation; and a manual review of the prioritized variants based on the available data. Using the data on the place of birth and the region of residence, we determined the geographical distribution of the detected variants and tracked the migration dynamics of their carriers.

Results

We report 175 novel del-VUSs. We detected 232 pathogenic variants, 46 likely pathogenic variants, and 216 del-VUSs in Group 1 and 19 pathogenic variants, 2 likely pathogenic variants, and 16 del-VUSs in Group 2. For each detected variant, we provide a description of its functional significance and geographical distribution.

Conclusion

The present study offers extensive genetic data on the Russian population, critical for future genetic research and improved primary cancer prevention and genetic screening strategies. The proposed hybrid assessment algorithm streamlines variant prioritization and pathogenicity assessment and offers a reliable and verifiable way of identifying variants of uncertain significance that need to be manually reviewed.

De Novo Missense Variations of ATP8B2 Impair Its Phosphatidylcholine Flippase Activity

P4-ATPases comprise a family of lipid flippases that translocate lipids from the exoplasmic (or luminal) to the cytoplasmic leaflet of biological membranes. Of the 14 known human P4-ATPases, ATP8B2 is a phosphatidylcholine flippase at the plasma membrane, but its physiological function is not well understood. Although ATP8B2 could interact with both CDC50A and CDC50B, it required only the CDC50A interaction for its exit from the endoplasmic reticulum and subsequent transport to the plasma membrane. Three de novo monoallelic missense variations of ATP8B2 were found in patients with intellectual disability. None of these variations affected the interaction of ATP8B2 with CDC50A or its localization to the plasma membrane. However, variations of either of two amino acid residues, which are conserved in all P4-ATPases, significantly reduced the phosphatidylcholine flippase activity of ATP8B2. Furthermore, mutations in the corresponding residues of ATP8B1 and ATP11C were found to decrease their flippase activities toward phosphatidylcholine and phosphatidylserine, respectively. These results indicate that the conserved amino acid residues are crucial for the enzymatic activities of the P4-ATPases.

Genetic therapies and potential therapeutic applications of CRISPR activators in the eye

Conventional gene therapy involving supplementation only treats loss-of-function diseases and is limited by viral packaging sizes, precluding therapy of large genes. The discovery of CRISPR/Cas has led to a paradigm shift in the field of genetic therapy, with the promise of precise gene editing, thus broadening the range of diseases that can be treated. The initial uses of CRISPR/Cas have focused mainly on gene editing or silencing of abnormal variants via utilising Cas endonuclease to trigger the target cell endogenous non-homologous end joining. Subsequently, the technology has evolved to modify the Cas enzyme and even its guide RNA, leading to more efficient editing tools in the form of base and prime editing. Further advancements of this CRISPR/Cas technology itself have expanded its functional repertoire from targeted editing to programmable transactivation, shifting the therapeutic focus to precise endogenous gene activation or upregulation with the potential for epigenetic modifications. In vivo experiments using this platform have demonstrated the potential of CRISPR-activators (CRISPRa) to treat various loss-of-function diseases, as well as in regenerative medicine, highlighting their versatility to overcome limitations associated with conventional strategies. This review summarises the molecular mechanisms of CRISPRa platforms, the current applications of this technology in vivo, and discusses potential solutions to translational hurdles for this therapy, with a focus on ophthalmic diseases.

Guidance for estimating penetrance of monogenic disease-causing variants in population cohorts

Penetrance is the probability that an individual with a pathogenic genetic variant develops a specific disease. Knowing the penetrance of variants for monogenic disorders is important for counseling of individuals. Until recently, estimates of penetrance have largely relied on affected individuals and their at-risk family members being clinically referred for genetic testing, a 'phenotype-first' approach. This approach substantially overestimates the penetrance of variants because of ascertainment bias. The recent availability of whole-genome sequencing data in individuals from very-large-scale population-based cohorts now allows 'genotype-first' estimates of penetrance for many conditions. Although this type of population-based study can underestimate penetrance owing to recruitment biases, it provides more accurate estimates of penetrance for secondary or incidental findings. Here, we provide guidance for the conduct of penetrance studies to ensure that robust genotypes and phenotypes are used to accurately estimate penetrance of variants and groups of similarly annotated variants from population-based studies.

Proteome-scale prediction of molecular mechanisms underlying dominant genetic diseases

Many dominant genetic disorders result from protein-altering mutations, acting primarily through dominant-negative (DN), gain-of-function (GOF), and loss-of-function (LOF) mechanisms. Deciphering the mechanisms by which dominant diseases exert their effects is often experimentally challenging and resource intensive, but is essential for developing appropriate therapeutic approaches. Diseases that arise via a LOF mechanism are more amenable to be treated by conventional gene therapy, whereas DN and GOF mechanisms may require gene editing or targeting by small molecules. Moreover, pathogenic missense mutations that act via DN and GOF mechanisms are more difficult to identify than those that act via LOF using nearly all currently available variant effect predictors. Here, we introduce a tripartite statistical model made up of support vector machine binary classifiers trained to predict whether human protein coding genes are likely to be associated with DN, GOF, or LOF molecular disease mechanisms. We test the utility of the predictions by examining biologically and clinically meaningful properties known to be associated with the mechanisms. Our results strongly support that the models are able to generalise on unseen data and offer insight into the functional attributes of proteins associated with different mechanisms. We hope that our predictions will serve as a springboard for researchers studying novel variants and those of uncertain clinical significance, guiding variant interpretation strategies and experimental characterisation. Predictions for the human UniProt reference proteome are available at https://osf.io/z4dcp/.

De novo missense variants in HDAC3 leading to epigenetic machinery dysfunction are associated with a variable neurodevelopmental disorder

Histone deacetylase 3 (HDAC3) is a crucial epigenetic modulator essential for various developmental and physiological functions. Although its dysfunction is increasingly recognized in abnormal phenotypes, to our knowledge, there have been no established reports of human diseases directly linked to HDAC3 dysfunction. Using trio exome sequencing and extensive phenotypic analysis, we correlated heterozygous de novo variants in HDAC3 with a neurodevelopmental disorder having variable clinical presentations, frequently associated with intellectual disability, developmental delay, epilepsy, and musculoskeletal abnormalities. In a cohort of six individuals, we identified missense variants in HDAC3 (c.277G>A [p.Asp93Asn], c.328G>A [p.Ala110Thr], c.601C>T [p.Pro201Ser], c. 797T>C [p.Leu266Ser], c.799G>A [p.Gly267Ser], and c.1075C>T [p.Arg359Cys]), all located in evolutionarily conserved sites and confirmed as de novo. Experimental studies identified defective deacetylation activity in the p.Asp93Asn, p.Pro201Ser, p.Leu266Ser, and p.Gly267Ser variants, positioned near the enzymatic pocket. In addition, proteomic analysis employing co-immunoprecipitation revealed that the disrupted interactions with molecules involved in the CoREST and NCoR complexes, particularly in the p.Ala110Thr variant, consist of a central pathogenic mechanism. Moreover, immunofluorescence analysis showed diminished nuclear to cytoplasmic fluorescence ratio in the p.Ala110Thr, p.Gly267Ser, and p.Arg359Cys variants, indicating impaired nuclear localization. Taken together, our study highlights that de novo missense variants in HDAC3 are associated with a broad spectrum of neurodevelopmental disorders, which emphasizes the complex role of HDAC3 in histone deacetylase activity, multi-protein complex interactions, and nuclear localization for proper physiological functions. These insights open new avenues for understanding the molecular mechanisms of HDAC3-related disorders and may inform future therapeutic strategies.

Gain-of-function human UNC93B1 variants cause systemic lupus erythematosus and chilblain lupus

UNC93B1 is a transmembrane domain protein mediating the signaling of endosomal Toll-like receptors (TLRs). We report five families harboring rare missense substitutions (I317M, G325C, L330R, R466S, and R525P) in UNC93B1 causing systemic lupus erythematosus (SLE) or chilblain lupus (CBL) as either autosomal dominant or autosomal recessive traits. As for a D34A mutation causing murine lupus, we recorded a gain of TLR7 and, to a lesser extent, TLR8 activity with the I317M (in vitro) and G325C (in vitro and ex vivo) variants in the context of SLE. Contrastingly, in three families segregating CBL, the L330R, R466S, and R525P variants were isomorphic with respect to TLR7 activity in vitro and, for R525P, ex vivo. Rather, these variants demonstrated a gain of TLR8 activity. We observed enhanced interaction of the G325C, L330R, and R466S variants with TLR8, but not the R525P substitution, indicating different disease mechanisms. Overall, these observations suggest that UNC93B1 mutations cause monogenic SLE or CBL due to differentially enhanced TLR7 and TLR8 signaling.

Integrating Large-Scale Protein Structure Prediction into Human Genetics Research

The last five years have seen impressive progress in deep learning models applied to protein research. Most notably, sequence-based structure predictions have seen transformative gains in the form of AlphaFold2 and related approaches. Millions of missense protein variants in the human population lack annotations, and these computational methods are a valuable means to prioritize variants for further analysis. Here, we review the recent progress in deep learning models applied to the prediction of protein structure and protein variants, with particular emphasis on their implications for human genetics and health. Improved prediction of protein structures facilitates annotations of the impact of variants on protein stability, protein-protein interaction interfaces, and small-molecule binding pockets. Moreover, it contributes to the study of host-pathogen interactions and the characterization of protein function. As genome sequencing in large cohorts becomes increasingly prevalent, we believe that better integration of state-of-the-art protein informatics technologies into human genetics research is of paramount importance.

QAFI: a novel method for quantitative estimation of missense variant impact using protein-specific predictors and ensemble learning

Next-generation sequencing (NGS) has revolutionized genetic diagnostics, yet its application in precision medicine remains incomplete, despite significant advances in computational tools for variant annotation. Many variants remain unannotated, and existing tools often fail to accurately predict the range of impacts that variants have on protein function. This limitation restricts their utility in relevant applications such as predicting disease severity and onset age. In response to these challenges, a new generation of computational models is emerging, aimed at producing quantitative predictions of genetic variant impacts. However, the field is still in its early stages, and several issues need to be addressed, including improved performance and better interpretability. This study introduces QAFI, a novel methodology that integrates protein-specific regression models within an ensemble learning framework, utilizing conservation-based and structure-related features derived from AlphaFold models. Our findings indicate that QAFI significantly enhances the accuracy of quantitative predictions across various proteins. The approach has been rigorously validated through its application in the CAGI6 contest, focusing on ARSA protein variants, and further tested on a comprehensive set of clinically labeled variants, demonstrating its generalizability and robust predictive power. The straightforward nature of our models may also contribute to better interpretability of the results.

The double whammy of ER-retention and dominant-negative effects in numerous autosomal dominant diseases: significance in disease mechanisms and therapy

The endoplasmic reticulum (ER) employs stringent quality control mechanisms to ensure the integrity of protein folding, allowing only properly folded, processed and assembled proteins to exit the ER and reach their functional destinations. Mutant proteins unable to attain their correct tertiary conformation or form complexes with their partners are retained in the ER and subsequently degraded through ER-associated protein degradation (ERAD) and associated mechanisms. ER retention contributes to a spectrum of monogenic diseases with diverse modes of inheritance and molecular mechanisms. In autosomal dominant diseases, when mutant proteins get retained in the ER, they can interact with their wild-type counterparts. This interaction may lead to the formation of mixed dimers or aberrant complexes, disrupting their normal trafficking and function in a dominant-negative manner. The combination of ER retention and dominant-negative effects has been frequently documented to cause a significant loss of functional proteins, thereby exacerbating disease severity. This review aims to examine existing literature and provide insights into the impact of dominant-negative effects exerted by mutant proteins retained in the ER in a range of autosomal dominant diseases including skeletal and connective tissue disorders, vascular disorders, neurological disorders, eye disorders and serpinopathies. Most crucially, we aim to emphasize the importance of this area of research, offering substantial potential for understanding the factors influencing phenotypic variability associated with genetic variants. Furthermore, we highlight current and prospective therapeutic approaches targeted at ameliorating the effects of mutations exhibiting dominant-negative effects. These approaches encompass experimental studies exploring treatments and their translation into clinical practice.

Considerations for reporting variants in novel candidate genes identified during clinical genomic testing

Since the first novel gene discovery for a Mendelian condition was made via exome sequencing (ES), the rapid increase in the number of genes known to underlie Mendelian conditions coupled with the adoption of exome (and more recently, genome) sequencing by diagnostic testing labs has changed the landscape of genomic testing for rare disease. Specifically, many individuals suspected to have a Mendelian condition are now routinely offered clinical ES. This commonly results in a precise genetic diagnosis but frequently overlooks the identification of novel candidate genes. Such candidates are also less likely to be identified in the absence of large-scale gene discovery research programs. Accordingly, clinical laboratories have both the opportunity, and some might argue a responsibility, to contribute to novel gene discovery which should in turn increase the diagnostic yield for many conditions. However, clinical diagnostic laboratories must necessarily balance priorities for throughput, turnaround time, cost efficiency, clinician preferences, and regulatory constraints, and often do not have the infrastructure or resources to effectively participate in either clinical translational or basic genome science research efforts. For these and other reasons, many laboratories have historically refrained from broadly sharing potentially pathogenic variants in novel genes via networks like Matchmaker Exchange, much less reporting such results to ordering providers. Efforts to report such results are further complicated by a lack of guidelines for clinical reporting and interpretation of variants in novel candidate genes. Nevertheless, there are myriad benefits for many stakeholders, including patients/families, clinicians, researchers, if clinical laboratories systematically and routinely identify, share, and report novel candidate genes. To facilitate this change in practice, we developed criteria for triaging, sharing, and reporting novel candidate genes that are most likely to be promptly validated as underlying a Mendelian condition and translated to use in clinical settings.

Altered chromatin topologies caused by balanced chromosomal translocation lead to central iris hypoplasia

Despite the advent of genomic sequencing, molecular diagnosis remains unsolved in approximately half of patients with Mendelian disorders, largely due to unclarified functions of noncoding regions and the difficulty in identifying complex structural variations. In this study, we map a unique form of central iris hypoplasia in a large family to 6q15-q23.3 and 18p11.31-q12.1 using a genome-wide linkage scan. Long-read sequencing reveals a balanced translocation t(6;18)(q22.31;p11.22) with intergenic breakpoints. By performing Hi-C on induced pluripotent stem cells from a patient, we identify two chromatin topologically associating domains spanning across the breakpoints. These alterations lead the ectopic chromatin interactions between APCDD1 on chromosome 18 and enhancers on chromosome 6, resulting in upregulation of APCDD1. Notably, APCDD1 is specifically localized in the iris of human eyes. Our findings demonstrate that noncoding structural variations can lead to Mendelian diseases by disrupting the 3D genome structure and resulting in altered gene expression.

A monoallelic UXS1 variant associated with short-limbed short stature

BACKGROUND

Serine residues in the protein backbone of heavily glycosylated proteoglycans are bound to glycosaminoglycans through a tetrasaccharide linker. UXS1 encodes UDP-glucuronate decarboxylase 1, which catalyzes synthesis of UDP-xylose, the donor of the first building block in the linker. Defects in other enzymes involved in formation of the tetrasaccharide linker cause so-called linkeropathies, characterized by short stature, radio-ulnar synostosis, decreased bone density, congenital contractures, dislocations, and more.

METHODS

Whole exome sequencing was performed in a father and son who presented with a mild skeletal dysplasia, as well as the father's unaffected parents. Wild-type and mutant UXS1 were recombinantly expressed in Escherichia coli and purified. Enzyme activity was evaluated by LC-MS/MS. In vivo effects were studied using HeparinRed assay and metabolomics.

RESULTS

The son had short long bones, normal epiphysis, and subtle metaphyseal changes especially in his legs. The likely pathogenic heterozygous variant NM_001253875.1(UXS1):c.557T>A p.(Ile186Asn) detected in the son was de novo in the father. Purified Ile186Asn-UXS1, in contrast to the wild-type, was not able to convert UDP-glucuronic acid to UDP-xylose. Plasma glycosaminoglycan levels were decreased in both son and father.

CONCLUSION

This is the first report linking UXS1 to short-limbed short stature in humans.

The full spectrum of SLC22 OCT1 mutations illuminates the bridge between drug transporter biophysics and pharmacogenomics

Mutations in transporters can impact an individual's response to drugs and cause many diseases. Few variants in transporters have been evaluated for their functional impact. Here, we combine saturation mutagenesis and multi-phenotypic screening to dissect the impact of 11,213 missense single-amino-acid deletions, and synonymous variants across the 554 residues of OCT1, a key liver xenobiotic transporter. By quantifying in parallel expression and substrate uptake, we find that most variants exert their primary effect on protein abundance, a phenotype not commonly measured alongside function. Using our mutagenesis results combined with structure prediction and molecular dynamic simulations, we develop accurate structure-function models of the entire transport cycle, providing biophysical characterization of all known and possible human OCT1 polymorphisms. This work provides a complete functional map of OCT1 variants along with a framework for integrating functional genomics, biophysical modeling, and human genetics to predict variant effects on disease and drug efficacy.

PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context

Accurate prediction of the functional impact of missense variants is important for disease gene discovery, clinical genetic diagnostics, therapeutic strategies, and protein engineering. Previous efforts have focused on predicting a binary pathogenicity classification, but the functional impact of missense variants is multi-dimensional. Pathogenic missense variants in the same gene may act through different modes of action (i.e., gain/loss-of-function) by affecting different aspects of protein function. They may result in distinct clinical conditions that require different treatments. We developed a new method, PreMode, to perform gene-specific mode-of-action predictions. PreMode models effects of coding sequence variants using SE(3)-equivariant graph neural networks on protein sequences and structures. Using the largest-to-date set of missense variants with known modes of action, we showed that PreMode reached state-of-the-art performance in multiple types of mode-of-action predictions by efficient transfer-learning. Additionally, PreMode's prediction of G/LoF variants in a kinase is consistent with inactive-active conformation transition energy changes. Finally, we show that PreMode enables efficient study design of deep mutational scans and optimization in protein engineering.

Heterozygous CAPZA2 mutations cause global developmental delay, hypotonia with epilepsy: a case report and the literature review

CAPZA2 encodes the α2 subunit of CAPZA, which is vital for actin polymerization and depolymerization in humans. However, understanding of diseases associated with CAPZA2 remains limited. To date, only three cases have been documented with neurodevelopmental abnormalities such as delayed motor development, speech delay, intellectual disability, hypotonia, and a history of seizures. In this study, we document a patient who exhibited seizures, mild intellectual disability, and impaired motor development yet did not demonstrate speech delay or hypotonia. The patient also suffered from recurrent instances of respiratory infections, gastrointestinal and allergic diseases. A novel de novo splicing variant c.219+1 G > A was detected in the CAPZA2 gene through whole-exome sequencing. This variant led to exon 4 skipping in mRNA splicing, confirmed by RT-PCR and Sanger sequencing. To our knowledge, this is the third study on human CAPZA2 defects, documenting the fourth unambiguously diagnosed case. Furthermore, this splicing mutation type is reported here for the first time. Our research offers additional support for the existence of a CAPZA2-related non-syndromic neurodevelopmental disorder. Our findings augment our understanding of the phenotypic range associated with CAPZA2 deficiency and enrich the knowledge of the mutational spectrum of the CAPZA2 gene.

An update on clinical presentation and responses to therapy of patients with hereditary hypophosphatemic rickets with hypercalciuria (HHRH)

Pathogenic variants in solute carrier family 34, member 3 (SLC34A3), the gene encoding the sodium-dependent phosphate cotransporter 2c (NPT2c), cause hereditary hypophosphatemic rickets with hypercalciuria (HHRH). Here, we report a pooled analysis of clinical and laboratory records of 304 individuals from 145 kindreds, including 20 previously unreported HHRH kindreds, in which two novel SLC34A3 pathogenic variants were identified. Compound heterozygous/homozygous carriers show above 90% penetrance for kidney and bone phenotypes. The biochemical phenotype for heterozygous carriers is intermediate with decreased serum phosphate, tubular reabsorption of phosphate (TRP (%)), fibroblast growth factor 23, and intact parathyroid hormone, but increased serum 1,25-dihydroxy vitamin D, and urine calcium excretion causing idiopathic hypercalciuria in 38%, with bone phenotypes still observed in 23% of patients. Oral phosphate supplementation is the current standard of care, which typically normalizes serum phosphate. However, although in more than half of individuals this therapy achieves correction of hypophosphatemia it fails to resolve the other outcomes. The American College of Medical Genetics and Genomics score correlated with functional analysis of frequent SLC34A3 pathogenic variants in vitro and baseline disease severity. The number of mutant alleles and baseline TRP (%) were identified as predictors for kidney and bone phenotypes, baseline TRP (%) furthermore predicted response to therapy. Certain SLC34A3/NPT2c pathogenic variants can be identified with partial responses to therapy, whereas with some overlap, others present only with kidney phenotypes and a third group present only with bone phenotypes. Thus, our report highlights important novel clinical aspects of HHRH and heterozygous carriers, raises awareness to this rare group of disorders and can be a foundation for future studies urgently needed to guide therapy of HHRH.

Molecular Dynamics Simulation of Kir6.2 Variants Reveals Potential Association with Diabetes Mellitus

Diabetes mellitus (DM) represents a problem for the healthcare system worldwide. DM has very serious complications such as blindness, kidney failure, and cardiovascular disease. In addition to the very bad socioeconomic impacts, it influences patients and their families and communities. The global costs of DM and its complications are huge and expected to rise by the year 2030. DM is caused by genetic and environmental risk factors. Genetic testing will aid in early diagnosis and identification of susceptible individuals or populations using ATP-sensitive potassium (KATP) channels present in different tissues such as the pancreas, myocardium, myocytes, and nervous tissues. The channels respond to different concentrations of blood sugar, stimulation by hormones, or ischemic conditions. In pancreatic cells, they regulate the secretion of insulin and glucagon. Mutations in the KCNJ11 gene that encodes the Kir6.2 protein (a major constituent of KATP channels) were reported to be associated with Type 2 DM, neonatal diabetes mellitus (NDM), and maturity-onset diabetes of the young (MODY). Kir6.2 harbors binding sites for ATP and phosphatidylinositol 4,5-diphosphate (PIP2). The ATP inhibits the KATP channel, while the (PIP2) activates it. A Kir6.2 mutation at tyrosine330 (Y330) was demonstrated to reduce ATP inhibition and predisposes to NDM. In this study, we examined the effect of mutations on the Kir6.2 structure using bioinformatics tools and molecular dynamic simulations (SIFT, PolyPhen, SNAP2, PANTHER, PhD&SNP, SNP&Go, I-Mutant, MuPro, MutPred, ConSurf, HOPE, and GROMACS). Our results indicated that M199R, R201H, R206H, and Y330H mutations influence Kir6.2 structure and function and therefore may cause DM. We conclude that MD simulations are useful techniques to predict the effects of mutations on protein structure. In addition, the M199R, R201H, R206H, and Y330H variant in the Kir6.2 protein may be associated with DM. These results require further verification in protein-protein interactions, Kir6.2 function, and case-control studies.

A Structural Proteome Screen Identifies Protein Mimicry in Host-Microbe Systems

Host-microbe systems are evolutionary niches that produce coevolved biological interactions and are a key component of global health. However, these systems have historically been a difficult field of biological research due to their experimental intractability. Impactful advances in global health will be obtained by leveraging in silico screens to identify genes involved in mediating interspecific interactions. These predictions will progress our understanding of these systems and lay the groundwork for future in vitro and in vivo experiments and bioengineering projects. A driver of host-manipulation and intracellular survival utilized by host-associated microbes is molecular mimicry, a critical mechanism that can occur at any level from DNA to protein structures. We applied protein structure prediction and alignment tools to explore host-associated bacterial structural proteomes for examples of protein structure mimicry. By leveraging the Legionella pneumophila proteome and its many known structural mimics, we developed and validated a screen that can be applied to virtually any host-microbe system to uncover signals of protein mimicry. These mimics represent candidate proteins that mediate host interactions in microbial proteomes. We successfully applied this screen to other microbes with demonstrated effects on global health, Helicobacter pylori and Wolbachia , identifying protein mimic candidates in each proteome. We discuss the roles these candidates may play in important Wolbachia -induced phenotypes and show that Wobachia infection can partially rescue the loss of one of these factors. This work demonstrates how a genome-wide screen for candidates of host-manipulation and intracellular survival offers an opportunity to identify functionally important genes in host-microbe systems.

DNA binding analysis of rare variants in homeodomains reveals homeodomain specificity-determining residues

Homeodomains (HDs) are the second largest class of DNA binding domains (DBDs) among eukaryotic sequence-specific transcription factors (TFs) and are the TF structural class with the largest number of disease-associated mutations in the Human Gene Mutation Database (HGMD). Despite numerous structural studies and large-scale analyses of HD DNA binding specificity, HD-DNA recognition is still not fully understood. Here, we analyze 92 human HD mutants, including disease-associated variants and variants of uncertain significance (VUS), for their effects on DNA binding activity. Many of the variants alter DNA binding affinity and/or specificity. Detailed biochemical analysis and structural modeling identifies 14 previously unknown specificity-determining positions, 5 of which do not contact DNA. The same missense substitution at analogous positions within different HDs often exhibits different effects on DNA binding activity. Variant effect prediction tools perform moderately well in distinguishing variants with altered DNA binding affinity, but poorly in identifying those with altered binding specificity. Our results highlight the need for biochemical assays of TF coding variants and prioritize dozens of variants for further investigations into their pathogenicity and the development of clinical diagnostics and precision therapies.

Prioritizing genomic variants pathogenicity via DNA, RNA, and protein-level features based on extreme gradient boosting

Genetic diseases are mostly implicated with genetic variants, including missense, synonymous, non-sense, and copy number variants. These different kinds of variants are indicated to affect phenotypes in various ways from previous studies. It remains essential but challenging to understand the functional consequences of these genetic variants, especially the noncoding ones, due to the lack of corresponding annotations. While many computational methods have been proposed to identify the risk variants. Most of them have only curated DNA-level and protein-level annotations to predict the pathogenicity of the variants, and others have been restricted to missense variants exclusively. In this study, we have curated DNA-, RNA-, and protein-level features to discriminate disease-causing variants in both coding and noncoding regions, where the features of protein sequences and protein structures have been shown essential for analyzing missense variants in coding regions while the features related to RNA-splicing and RBP binding are significant for variants in noncoding regions and synonymous variants in coding regions. Through the integration of these features, we have formulated the Multi-level feature Genomic Variants Predictor (ML-GVP) using the gradient boosting tree. The method has been trained on more than 400,000 variants in the Sherloc-training set from the 6th critical assessment of genome interpretation with superior performance. The method is one of the two best-performing predictors on the blind test in the Sherloc assessment, and is further confirmed by another independent test dataset of de novo variants.

In-Silico Method for Predicting Pathogenic Missense Variants Using Online Tools: AURKA Gene as a Model

Background

In-silico analysis provides a fast, simple, and cost-free method for identifying potentially pathogenic single nucleotide variants.

Objective

To propose a simple and relatively fast method for the prediction of variant pathogenicity using free online in-silico (IS) tools with AURKA gene as a model.

Materials and Methods

We aim to propose a methodology to predict variants with high pathogenic potential using computational analysis, using AURKA gene as model. We predicted a protein model and analyzed 209 out of 64,369 AURKA variants obtained from Ensembl database. We used bioinformatic tools to predict pathogenicity. The results were compared through the VarSome website, which includes its own pathogenicity score and the American College of Medical Genetics (ACMG) classification.

Results

Out of the 209 analyzed variants, 16 were considered pathogenic, and 13 were located in the catalytic domain. The most frequent protein changes were size and hydrophobicity modifications of amino acids. Proline and Glycine amino acid substitutions were the most frequent changes predicted as pathogenic. These bioinformatic tools predicted functional changes, such as protein up or down-regulation, gain or loss of molecule interactions, and structural protein modifications. When compared to the ACMG classification, 10 out of 16 variants were considered likely pathogenic, with 7 out of 10 changes at Proline/Glycine substitutions.

Conclusion

This method allows quick and cost-free bulk variant screening to identify variants with pathogenic potential for further association and/or functional studies.

Spectral Fluorescence Pathology of Protein Misfolding Disorders

Protein misfolding has been extensively studied in the context of neurodegenerative disorders and systemic amyloidoses. Due to misfolding and aggregation of proteins being highly heterogeneous and generating a variety of structures, a growing body of evidence illustrates numerous ways how the aggregates contribute to progression of diseases such as Alzheimer's disease, Parkinson's disease, and prion disorders. Different misfolded species of the same protein, commonly referred to as strains, appear to play a significant role in shaping the disease clinical phenotype and clinical progression. The distinct toxicity profiles of various misfolded proteins underscore their importance. Current diagnostics struggle to differentiate among these strains early in the disease course. This review explores the potential of spectral fluorescence approaches to illuminate the complexities of protein misfolding pathology and discusses the applications of advanced spectral methods in the detection and characterization of protein misfolding disorders. By examining spectrally variable probes, current data analysis approaches, and important considerations for the use of these techniques, this review aims to provide an overview of the progress made in this field and highlights directions for future research.

Epigenetic editing for autosomal dominant neurological disorders

Epigenetics refers to the molecules and mechanisms that modify gene expression states without changing the nucleotide context. These modifications are what encode the cell state during differentiation or epigenetic memory in mitosis. Epigenetic modifications can alter gene expression by changing the chromatin architecture by altering the affinity for DNA to wrap around histone octamers, forming nucleosomes. The higher affinity the DNA has for the histones, the tighter it will wrap and therefore induce a heterochromatin state, silencing gene expression. Several groups have shown the ability to harness the cell's natural epigenetic modification pathways to engineer proteins that can induce changes in epigenetics and consequently regulate gene expression. Therefore, epigenetic modification can be used to target and treat disorders through the modification of endogenous gene expression. The use of epigenetic modifications may prove an effective path towards regulating gene expression to potentially correct or cure genetic disorders.

Walking with giants: The challenges of variant impact assessment in the giant sarcomeric protein titin

Titin, the so-called "third filament" of the sarcomere, represents a difficult challenge for the determination of damaging genetic variants. A single titin molecule extends across half the length of a sarcomere in striated muscle, fulfilling a variety of vital structural and signaling roles, and has been linked to an equally varied range of myopathies, resulting in a significant burden on individuals and healthcare systems alike. While the consequences of truncating variants of titin are well-documented, the ramifications of the missense variants prevalent in the general population are less so. We here present a compendium of titin missense variants-those that result in a single amino-acid substitution in coding regions-reported to be pathogenic and discuss these in light of the nature of titin and the variant position within the sarcomere and their domain, the structural, pathological, and biophysical characteristics that define them, and the methods used for characterization. Finally, we discuss the current knowledge and integration of the multiple fields that have contributed to our understanding of titin-related pathology and offer suggestions as to how these concurrent methodologies may aid the further development in our understanding of titin and hopefully extend to other, less well-studied giant proteins. This article is categorized under: Cardiovascular Diseases > Genetics/Genomics/Epigenetics Congenital Diseases > Genetics/Genomics/Epigenetics Congenital Diseases > Molecular and Cellular Physiology.

Genetic variant interpretation for the neurologist - A pragmatic approach in the next-generation sequencing era in childhood epilepsy

Genetic advances over the past decade have enhanced our understanding of the genetic landscape of childhood epilepsy. However a major challenge for clinicians ha been understanding the rationale and systematic approach towards interpretation of the clinical significance of variant(s) detected in their patients. As the clinical paradigm evolves from gene panels to whole exome or whole genome testing including rapid genome sequencing, the number of patients tested and variants identified per patient will only increase. Each step in the process of variant interpretation has limitations and there is no single criterion which enables the clinician to draw reliable conclusions on a causal relationship between the variant and disease without robust clinical phenotyping. Although many automated online analysis software tools are available, these carry a risk of misinterpretation. This guideline provides a pragmatic, real-world approach to variant interpretation for the child neurologist. The focus will be on ascertaining aspects such as variant frequency, subtype, inheritance pattern, structural and functional consequence with regard to genotype-phenotype correlations, while refraining from mere interpretation of the classification provided in a genetic test report. It will not replace the expert advice of colleagues in clinical genetics, however as genomic investigations become a first-line test for epilepsy, it is vital that neurologists and epileptologists are equipped to navigate this landscape.

Differential functional consequences of GRIN2A mutations associated with schizophrenia and neurodevelopmental disorders

Human genetic studies have revealed rare missense and protein-truncating variants in GRIN2A, encoding for the GluN2A subunit of the NMDA receptors, that confer significant risk for schizophrenia (SCZ). Mutations in GRIN2A are also associated with epilepsy and developmental delay/intellectual disability (DD/ID). However, it remains enigmatic how alterations to the same protein can result in diverse clinical phenotypes. Here, we performed functional characterization of human GluN1/GluN2A heteromeric NMDA receptors that contain SCZ-linked GluN2A variants, and compared them to NMDA receptors with GluN2A variants associated with epilepsy or DD/ID. Our findings demonstrate that SCZ-associated GRIN2A variants were predominantly loss-of-function (LoF), whereas epilepsy and DD/ID-associated variants resulted in both gain- and loss-of-function phenotypes. We additionally show that M653I and S809R, LoF GRIN2A variants associated with DD/ID, exert a dominant-negative effect when co-expressed with a wild-type GluN2A, whereas E58Ter and Y698C, SCZ-linked LoF variants, and A727T, an epilepsy-linked LoF variant, do not. These data offer a potential mechanism by which SCZ/epilepsy and DD/ID-linked variants can cause different effects on receptor function and therefore result in divergent pathological outcomes.

Interpreting the effect of mutations to protein binding sites from large-scale genomic screens

Predicting the functionality of missense mutations is extremely difficult. Large-scale genomic screens are commonly performed to identify mutational correlates or drivers of disease and treatment resistance, but interpretation of how these mutations impact protein function is limited. One such consequence of mutations to a protein is to impact its ability to bind and interact with partners or small molecules such as ATP, thereby modulating its function. Multiple methods exist for predicting the impact of a single mutation on protein-protein binding energy, but it is difficult in the context of a genomic screen to understand if these mutations with large impacts on binding are more common than statistically expected. We present a methodology for taking mutational data from large-scale genomic screens and generating functional and statistical insights into their role in the binding of proteins both with each other and their small molecule ligands. This allows a quantitative and statistical analysis to determine whether mutations impacting protein binding or ligand interactions are occurring more or less frequently than expected by chance. We achieve this by calculating the potential impact of any possible mutation and comparing an expected distribution to the observed mutations. This method is applied to examples demonstrating its ability to interpret mutations involved in protein-protein binding, protein-DNA interactions, and the evolution of therapeutic resistance.

Applications of Gene Therapy in Cardiomyopathies

Gene therapy is defined by the introduction of new genes or the genetic modification of existing genes and/or their regulatory portions via gene replacement and gene editing strategies, respectively. The genetic material is usually delivered though cardiotropic vectors such as adeno-associated virus 9 or engineered capsids. The enthusiasm for gene therapy has been hampered somewhat by adverse events observed in clinical trials, including dose-dependent immunologic reactions such as hepatotoxicity, acquired hemolytic uremic syndrome and myocarditis. Notably, gene therapy for Duchenne muscular dystrophy has recently been approved and pivotal clinical trials are testing gene therapy approaches in rare myocardial conditions such as Danon disease and Fabry disease. Furthermore, promising results have been shown in animal models of gene therapy in hypertrophic cardiomyopathy and arrhythmogenic cardiomyopathy. This review summarizes the gene therapy techniques, the toxicity risk associated with adeno-associated virus delivery, the ongoing clinical trials, and future targets.

Ensemble-based design of tau to inhibit aggregation while preserving biological activity

The microtubule-associated protein tau is implicated in neurodegenerative diseases characterized by amyloid formation. Mutations associated with frontotemporal dementia increase tau aggregation propensity and disrupt its endogenous microtubule-binding activity. The structural relationship between aggregation propensity and biological activity remains unclear. We employed a multi-disciplinary approach, including computational modeling, NMR, cross-linking mass spectrometry, and cell models to design tau sequences that stabilize its structural ensemble. Our findings reveal that substitutions near the conserved 'PGGG' beta-turn motif can modulate local conformation, more stably engaging in interactions with the 306VQIVYK311 amyloid motif to decrease aggregation in vitro and in cells. Designed tau sequences maintain microtubule binding and explain why 3R isoforms of tau exhibit reduced pathogenesis over 4R isoforms. We propose a simple mechanism to reduce the formation of pathogenic species while preserving biological function, offering insights for therapeutic strategies aimed at reducing protein misfolding in neurodegenerative diseases.

Transcriptome analysis in a humanized mouse model of familial dysautonomia reveals tissue-specific gene expression disruption in the peripheral nervous system

Familial dysautonomia (FD) is a rare recessive neurodevelopmental disease caused by a splice mutation in the Elongator acetyltransferase complex subunit 1 (ELP1) gene. This mutation results in a tissue-specific reduction of ELP1 protein, with the lowest levels in the central and peripheral nervous systems (CNS and PNS, respectively). FD patients exhibit complex neurological phenotypes due to the loss of sensory and autonomic neurons. Disease symptoms include decreased pain and temperature perception, impaired or absent myotatic reflexes, proprioceptive ataxia, and progressive retinal degeneration. While the involvement of the PNS in FD pathogenesis has been clearly recognized, the underlying mechanisms responsible for the preferential neuronal loss remain unknown. In this study, we aimed to elucidate the molecular mechanisms underlying FD by conducting a comprehensive transcriptome analysis of neuronal tissues from the phenotypic mouse model TgFD9; Elp1Δ20/flox. This mouse recapitulates the same tissue-specific ELP1 mis-splicing observed in patients while modeling many of the disease manifestations. Comparison of FD and control transcriptomes from dorsal root ganglion (DRG), trigeminal ganglion (TG), medulla (MED), cortex, and spinal cord (SC) showed significantly more differentially expressed genes (DEGs) in the PNS than the CNS. We then identified genes that were tightly co-expressed and functionally dependent on the level of full-length ELP1 transcript. These genes, defined as ELP1 dose-responsive genes, were combined with the DEGs to generate tissue-specific dysregulated FD signature genes and networks. Within the PNS networks, we observed direct connections between Elp1 and genes involved in tRNA synthesis and genes related to amine metabolism and synaptic signaling. Importantly, transcriptomic dysregulation in PNS tissues exhibited enrichment for neuronal subtype markers associated with peptidergic nociceptors and myelinated sensory neurons, which are known to be affected in FD. In summary, this study has identified critical tissue-specific gene networks underlying the etiology of FD and provides new insights into the molecular basis of the disease.