The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine

Clinical Features of Seven COL2A1 Variations in Chinese Children With Type II Collagen Disorders

AIM

Type II collagen, encoded by the collagen type II alpha 1 (COL2A1) gene, is crucial for the structure of cartilage. This study aims to improve our understanding of Spondyloepiphyseal Dysplasia Congenita (SEDC) caused by mutations in COL2A1. We also aim to evaluate the safety and efficacy of growth hormone (GH) therapy in two SEDC patients.

METHODS

We performed genetic analyses of seven paediatric patients from unrelated Chinese families. Two patients received GH therapy, and their growth trajectories were monitored over 3.5 and 3 years.

RESULTS

Genetic screening identified six missense mutations (Gly1110Ser, Gly1107Glu, Gly873Arg, Gly456Ala, Gly1062Ser and Gly1182Arg) and one intron variant in COL2A1. All patients (five girls and two boys, ranging from 2 years and 7 months to 12 years) were diagnosed with SEDC, exhibiting disproportionate short stature and skeletal abnormalities. GH therapy resulted in height increases of 0.76 and 0.27 standard deviation scores over 3.5 and 3 years, respectively, with no significant side effects.

CONCLUSION

This study expands the mutation spectrum of COL2A1 and supports the efficacy and safety of GH therapy in SEDC patients, highlighting the need for multi-center studies to further investigate GH's therapeutic potential.

Developing a disease-specific accessible transcriptional signature as a biomarker for ataxia with oculomotor apraxia type 2

BACKGROUND

Genetic ataxias are clinically heterogenous neurodegenerative conditions often involving rare or private mutations and it is often difficult to assign pathogenicity to rare gene variants solely based on DNA sequencing. An effective functional assay from an easy-to-obtain biospecimen would aid this assessment and be of high clinical value. SETX encodes a ubiquitous DNA/RNA helicase crucial for resolving R-loops and maintaining genome stability. Loss-of-function mutations cause a recessive disorder, Ataxia with Oculomotor Apraxia Type 2 (AOA2).

METHODS

Here we utilize Weighted Gene Co-expression Network Analysis (WGCNA) from patient blood to construct an AOA2-specific transcriptomic signature as a biomarker to evaluate SETX variants in patients clinically suspected of having AOA2.

RESULTS

WGCNA from peripheral blood RNA of 11 AOA2 patients from 7 families initially identified a single gene module that was modestly effective in distinguishing individuals with AOA2 from controls (sensitivity 73%, specificity 97%) and was able to robustly differentiate AOA2 patients from those with genetically distinct, yet phenotypically similar, neurological disorders (sensitivity 100%, specificity 100%). An independent derivation of the transcriptional biomarker identified a dual module model that was able to better distinguish individuals with AOA2 from controls (sensitivity 100%, specificity 97%). As validation, we examined a second cohort of 21 patients from 13 families and demonstrate that this dual module transcriptional biomarker could discriminate patients clinically suspected of AOA2 from controls (57%, 95%CI: 34%-78%). Overall, the transcriptional biomarker was able to separate AOA2 subjects (n = 32) from controls (n = 35) with 72% sensitivity and 97% specificity. Notably, this transcriptomic biomarker enabled verification of the first pathogenic SETX mutation found in a non-canonical transcript, expanding the spectrum of mutations that contribute to AOA2.

CONCLUSIONS

Our study identified a transcriptional biomarker that was able to differentiate AOA2 from controls and from other related neurological disorders, consequently expanding the spectrum of known pathogenic mutations. This proof-of-concept study illustrates that transcriptional biomarkers may be used to validate variants of uncertain significance in known genetic diseases.

A probabilistic graphical model for estimating selection coefficients of nonsynonymous variants from human population sequence data

Accurately predicting the effect of missense variants is important in discovering disease risk genes and clinical genetic diagnostics. Commonly used computational methods predict pathogenicity, which does not capture the quantitative impact on fitness in humans. We develop a method, MisFit, to estimate missense fitness effect using a graphical model. MisFit jointly models the effect at a molecular level ( d ) and a population level (selection coefficient, s ), assuming that in the same gene, missense variants with similar d have similar s . We train it by maximizing probability of observed allele counts in 236,017 individuals of European ancestry. We show that s is informative in predicting allele frequency across ancestries and consistent with the fraction of de novo mutations in sites under strong selection. Further, s outperforms previous methods in prioritizing de novo missense variants in individuals with neurodevelopmental disorders. In conclusion, MisFit accurately predicts s and yields new insights from genomic data.

Contribution of families using the GenIDA database to the description of MED13L syndrome and literature review

The GenIDA project aims to improve the understanding and management of rare genetic forms of intellectual disability by fostering collaboration among patients, caregivers, healthcare professionals, and research professionals. Clinical data is provided by patients' families via a structured questionnaire to identify medically relevant insights and better understand the natural history of rare diseases. This study focused on MED13L syndrome, analyzing data from 41 patients in the GenIDA database and comparing it with 102 cases from the scientific literature and 6 new descriptions of patients from our medical center.The GenIDA series confirmed the key features of MED13L syndrome, including global developmental delay, poor speech, intellectual disability, and cardiac defects (OMIM #616789), at frequencies similar to those reported in the literature. The GenIDA series identified a higher prevalence of visual impairment (76%) and highlighted under-recognized musculoskeletal issues, such as foot deformities, which had previously received little attention. This study highlights the value of family-reported data in describing the full phenotype of rare syndromes. A comprehensive review of published cases showed that patients with missense variants have more severe impairments, including increased cardiac defects, global developmental delay, and a higher incidence of epilepsy, than patients with premature truncated variants.These findings highlight the importance of family involvement in rare disease research and the need for further studies to explore genotype-phenotype correlations to improve patient care and outcomes.

Role of Next-Generation Sequencing in Diagnosis of Familial Hypercholesterolemia in Serbia

Objectives: Familial hypercholesterolemia (FH) is an autosomal dominant disorder of lipid metabolism characterized by high levels of low-density lipoprotein (LDL). This study aimed to identify variants in the LDLR, APOB, PCSK9 and LDLRAP1 genes and to identify the genotype-phenotype correlation in Serbian FH patients. Method: This study included a total of 101 patients suspected of having FH based on clinical criteria. Genetic analysis was performed by the next-generation sequencing (NGS) method. Results: An overall mutation detection rate of 43.6% was achieved. Thirteen distinct variants were detected in the LDLR gene (93.2%). The most frequently observed variant was c.858C>A p.(Ser286Arg), which was present in 26% of the LDLR-positive patients. Additional variants were detected in the APOB gene. No pathogenic variants were detected in the PCSK9 or LDLRAP1 genes. Comparing genetically FH-positive and FH-negative patients, statistical significance was observed in terms of age (p < 0.001), total cholesterol (TC) (p < 0.001), low-density-lipoprotein cholesterol (LDL-C) (p < 0.001) and triglyceridemia (p < 0.001). Conclusions: This study represents the first insight into the genetic basis of FH in Serbia. Taking into consideration that variants were detected in more than one gene and that the variants in the LDLR gene were distributed across nearly all exons, the FH diagnostics in Serbia ought to be based on NGS methodology.

Algorithmic assessment reveals functional implications of GABRD gene variants linked to idiopathic generalized epilepsy

OBJECTIVE

The primary objective of this study is to address the challenge posed by the increasing number of variants of unknown clinical significance (VUS) within the GABRD gene, which encodes the δ subunit of γ-Aminobutyric acid type A receptors. The focus is on predicting the most pathogenic GABRD VUS to enhance precision medicine and improve our understanding of relevant pathophysiology.

METHODS

The study employs a combination of in silico algorithms to analyze 82 variants of unknown clinical significance of GABRD gene sourced from the ClinVar database. Initially, separate algorithms based on sequence homology are utilized to assess this variant set. Subsequently, consensus variants predicted as pathogenic undergo further evaluation through a web server employing an algorithm based on structural homology. The resulting 11 variants are then validated using in silico tools that assess variant effects based on genetic and molecular data. The evaluation includes consideration of disease association and protein stability due to amino acid substitutions.

RESULTS

The study identifies specific variants (L111R, R114C, D123N, G150S, and L243P) in the coding region of the GABRD gene, which are predicted as deleterious by multiple algorithms. These variants are evolutionarily conserved, mapped onto the extracellular domain of the δ subunit, and associated with idiopathic generalized epilepsy.

CONCLUSIONS

The findings suggest structural or functional consequences that lead to pathogenicity, offering valuable insights for wet-lab experimentation. Besides, the findings contribute to the validation of clinically significant genetic variants in the GABRD gene, which is critical for epilepsy precision medicine.

Key genes altered in glioblastoma based on bioinformatics (Review)

Glioblastoma multiforme (GBM) is an aggressive brain tumor with poor prognosis. Recent advancements in bioinformatics have contributed to uncovering the genetic alterations that underlie the development and progression of GBM. Analysis of extensive genomic data led to the identification of significant pathways involved in GBM, such as the PI3K/AKT/mTOR and Ras/Raf/MEK/ERK signaling pathways, alongside key genes such as EGFR, TP53 and TERT. These findings have enhanced our understanding of GBM biology and led to the identification of new therapeutic targets. Bioinformatics has become an indispensable tool in pinpointing the genetic modifications that drive GBM, paving the way for innovative treatment strategies. This approach not only aids in comprehending the complexities of GBM but also holds promise for improving outcomes in patients suffering from this devastating disease. The ongoing integration of bioinformatics in GBM research continues to be vital for advancing therapeutic options.

Defects in mRNA splicing and implications for infertility: a comprehensive review and in silico analysis

BACKGROUND

mRNA splicing is a fundamental process in the reproductive system, playing a pivotal role in reproductive development and endocrine function, and ensuring the proper execution of meiosis, mitosis, and gamete function. Trans-acting factors and cis-acting elements are key players in mRNA splicing whose dysfunction can potentially lead to male and female infertility. Although hundreds of trans-acting factors have been implicated in mRNA splicing, the mechanisms by which these factors influence reproductive processes are fully understood for only a subset. Furthermore, the clinical impact of variations in cis-acting elements on human infertility has not been comprehensively characterized, leading to probable omissions of pathogenic variants in standard genetic analyses.

OBJECTIVE AND RATIONALE

This review aimed to summarize our current understanding of the factors involved in mRNA splicing regulation and their association with infertility disorders. We introduced methods for prioritizing and functionally validating splicing variants associated with human infertility. Additionally, we explored corresponding abnormal splicing therapies that could potentially provide insight into treating human infertility.

SEARCH METHODS

Systematic literature searches of human and model organisms were performed in the PubMed database between May 1977 and July 2024. To identify mRNA splicing-related genes and pathogenic variants in infertility, the search terms 'splice', 'splicing', 'variant', and 'mutation' were combined with azoospermia, oligozoospermia, asthenozoospermia, multiple morphological abnormalities of the sperm flagella, acephalic spermatozoa, disorders of sex development, early embryonic arrest, reproductive endocrine disorders, oocyte maturation arrest, premature ovarian failure, primary ovarian insufficiency, zona pellucida, fertilization defects, infertile, fertile, infertility, fertility, reproduction, and reproductive.

OUTCOMES

Our search identified 5014 publications, of which 291 were included in the final analysis. This review provided a comprehensive overview of the biological mechanisms of mRNA splicing, with a focus on the roles of trans-acting factors and cis-acting elements. We highlighted the disruption of 52 trans-acting proteins involved in spliceosome assembly and catalytic activity and recognized splicing regulatory regions and epigenetic regulation associated with infertility. The 73 functionally validated splicing variants in the cis-acting elements of 54 genes have been reported in 20 types of human infertility; 27 of them were located outside the canonical splice sites and potentially overlooked in standard genetic analysis due to likely benign or of uncertain significance. The in silico prediction of splicing can prioritize potential splicing abnormalities that may be true pathogenic mechanisms. We also summarize the methods for prioritizing splicing variants and strategies for functional validation and review splicing therapy approaches for other diseases, providing a reference for abnormal reproduction treatment.

WIDER IMPLICATIONS

Our comprehensive review of trans-acting factors and cis-acting elements in mRNA splicing will further promote a more thorough understanding of reproductive regulatory processes, leading to improved pathogenic variant identification and potential treatments for human infertility.

REGISTRATION NUMBER

N/A.

The genomic and epigenomic landscape of iridocorneal endothelial syndrome

Iridocorneal endothelial (ICE) syndrome is a rare, irreversibly blinding eye disease with an unknown etiology. Understanding its genomic and epigenomic landscape could aid in developing etiology-based therapies. In this study, we recruited 99 ICE patients and performed whole-genome sequencing (WGS) on 51 and genome-wide DNA methylation profiling on 48 of them. We conducted mutational burden testing on genes and noncoding regulatory regions, comparing the ICE cohort with control groups (9197 East Asians from the gnomAD database and 350 normal Chinese from our in-house cohort). Copy number variation (CNV) analysis and differential methylation of regions were also explored. We identified RP1L1 (27/51, 53%) with a significantly higher coding-altering mutational burden in the ICE cohort (p < 8.3×10-7), with mutations predominantly at chr8:10467637 (hg19). Additionally, 41 regions with significant CNVs were identified, including two regions at chr19:15783859-15791329 (hg19) and chr3:75786061-75790887 (hg19), showing copy number loss in 39 and 19 patients, respectively. We also identified 2,717 differentially methylated regions (DMRs), with hypomethylation prevalent in ICE syndrome (91.9% of DMRs). Among these, 45 recurrent hypomethylated regions (HMRs) in more than 10% of ICE patients showed differential methylation compared to normal controls. This study presents the first comprehensive genomic and epigenomic characterization of ICE syndrome, offering insights into its underlying etiology.

A probabilistic graphical model for estimating selection coefficient of nonsynonymous variants from human population sequence data

Accurately predicting the effect of missense variants is important in discovering disease risk genes and clinical genetic diagnostics. Commonly used computational methods predict pathogenicity, which does not capture the quantitative impact on fitness in humans. We developed a method, MisFit, to estimate missense fitness effect using a graphical model. MisFit jointly models the effect at a molecular level (𝑑) and a population level (selection coefficient, 𝑠), assuming that in the same gene, missense variants with similar 𝑑 have similar 𝑠. We trained it by maximizing probability of observed allele counts in 236,017 European individuals. We show that 𝑠 is informative in predicting allele frequency across ancestries and consistent with the fraction of de novo mutations in sites under strong selection. Further, 𝑠 outperforms previous methods in prioritizing de novo missense variants in individuals with neurodevelopmental disorders. In conclusion, MisFit accurately predicts 𝑠 and yields new insights from genomic data.

Intelligent design of mechanical metamaterials: a GCNN-based structural genome database approach

The reciprocal mapping between the geometry and properties of a unit cell is crucial for the intelligent and inverse design of advanced materials and structural systems. Beyond classical homogenization-based numerical methods, this paper presents an efficient and accurate mapping between the geometry and properties of a class of unit cells described by moving morphable components, achieved via a graph convolutional neural network. This leads to a structural genome database (SGD) approach for the intelligent design of mechanical metamaterials. Using the SGD approach, metamaterials exhibiting the Hashin-Shtrikman upper bound of bulk modulus, auxetic behavior and the unimodal property have been created, with design efficiency improved by 3-4 orders of magnitude. Additionally, transfer learning and a small amount of training data allow the SGD to predict non-local behaviors beyond a unit cell, such as optimized unit cells with critical buckling strength enhanced by nearly 200% and a bandgap metamaterial with a relative bandgap width of 51%. Experimentally validated optimized metamaterials demonstrate auxetic behavior and superior buckling resistance. The proposed SGD approach holds promise for the advanced design of multi-scale and multi-physics systems.

Understanding a point mutation signature D54K in the caspase activation recruitment domain of NOD1 capitulating concerted immunity via atomistic simulation

Point mutation D54K in the human N-terminal caspase recruitment domain (CARD) of nucleotide-binding oligomerization domain -1 (NOD1) abrogates an imperative downstream interaction with receptor-interacting protein kinase (RIPK2) that entails combating bacterial infections and inflammatory dysfunction. Here, we addressed the molecular details concerning conformational changes and interaction patterns (monomeric-dimeric states) of D54K by signature-based molecular dynamics simulation. Initially, the sequence analysis prioritized D54K as a pathogenic mutation, among other variants, based on a sequence signature. Since the mutation is highly conserved, we derived the distant ortholog to predict the sequence and structural similarity between native and mutant. This analysis showed the utility of 33 communal core residues associated with structural-functional preservation and variations, concurrently served to infer the cryptic hotspots Cys39, Glu53, Asp54, Glu56, Ile57, Leu74, and Lys78 determining the inter helical fold forming homodimers for putative receptor interaction. Subsequently, the atomistic simulations with free energy (MM/PB(GB)SA) calculations predicted structural alteration that takes place in the N-terminal mutant CARD where coils changed to helices (45 α3- L4-α4-L6- α683) in contrast to native (45T2-L4-α4-L6-T483). Likewise, the C-terminal helices 93T1-α7105 connected to the loops distorted compared to native 93α6-L7105 may result in conformational misfolding that promotes functional regulation and activation. These structural perturbations of D54K possibly destabilize the flexible adaptation of critical homotypic NOD1CARD-CARDRIPK2 interactions (α4Asp42-Arg488α5 and α6Phe86-Lys471α4) is consistent with earlier experimental reports. Altogether, our findings unveil the conformational plasticity of mutation-dependent immunomodulatory response and may aid in functional validation exploring clinical investigation on CARD-regulated immunotherapies to prevent systemic infection and inflammation.

A cellular assay to determine the fusion capacity of MFN2 variants linked to Charcot-Marie-Tooth disease of type 2 A

Charcot-Marie-Tooth Disease (CMT) is an inherited peripheral neuropathy with two main forms: demyelinating CMT1 and axonal CMT2. The most frequent subtype of CMT2 (CMT2A) is linked to mutations of MFN2, encoding a ubiquitously expressed GTP-binding protein anchored to the mitochondrial outer membrane and essential for mitochondrial fusion. The use of Next-Generation Sequencing has led to the identification of increasing numbers of MFN2 variants, yet many of them remain of unknown significance, depriving patients of a clear diagnosis. In this work, we establish a cellular assay allowing to assess the impact of 12 known MFN2 variants linked to CMT2A on mitochondrial fusion. The functional analysis revealed that out of the 12 selected MFN2 mutations, only six exhibited reduced fusion activity. The classification of MFN2 variants according to the results of the functional assay revealed a correlation between the fusion capacity, the age at onset of CMT2A and computational variant effect predictions relying on the analysis of the protein sequence. The functional assay and the results obtained will assist and improve the classification of novel MFN2 variants identified in patients.

Rare and common genetic variants underlying the risk of Hirschsprung's disease

Hirschsprung's disease (HSCR) is a congenital enteric neuropathic disorder characterized by high heritability (>80%) and polygenic inheritance (>20 genes). The previous genome-wide association studies (GWAS) identified several common variants associated with HSCR and demonstrated increased predictive performance for HSCR risk in Europeans using a genetic risk score, there remains a notable gap in knowledge regarding Chinese populations. We conducted whole exome sequencing in a HSCR case cohort in Chinese. By using the common controls (505 controls from 1KG EAS and 10 588 controls from ChinaMAP), we conducted GWAS for the common variants in the exome and gene-based association for rare variants. We further validated the associated variants and genes in replicated samples and in vitro and vivo experiments. We identified one novel gene PLK5 by GWAS and suggested 45 novel putative genes based the gene-based test. By using genetic variant at RET and PLK5, we constructed a genetic risk score that could identify the individuals with very high genetic risk for HSCR. Compared with patients with zero or one risk allele from the three variants, the risk for HSCR was 36.61 times higher with six alleles. In addition, we delineated a HSCR risk gene landscape that encompasses 57 genes, which explains 88.5% and 54.5% of HSCR in Chinese and European, respectively. In summary, this study improved the understanding of genetic architecture of HSCR and provided a risk prediction approach for HSCR in the Chinese.

Gastric gastrointestinal stromal tumor in a patient with neurofibromatosis type I presenting with anemia: A case report

BACKGROUND

Gastrointestinal stromal tumors (GISTs) are caused by mutations in the KIT and platelet derived growth factor receptor alpha genes in approximately 90% of cases. A minority of wild-type GISTs are associated with neurofibromatosis type 1 (NF1), an autosomal dominant genetic disease resulting from pathogenic mutations in the NF1 gene, which encodes the neurofibromin protein. NF1 patients often exhibit multi-system involvement, with café-au-lait macules and neurofibromas being characteristic symptoms. GISTs are a rare complication of NF1, with the tumors most frequently occurring in the small intestine (90% of cases), while occurrences in the stomach are rare.

CASE SUMMARY

A 51-year-old woman presented to the emergency department with complaints of dizziness, fatigue, chest tightness, and dark stools. Initial examination revealed a red blood cell count of 1.99 × 1012/L and a hemoglobin level of 43 g/L. She underwent blood transfusions and fluid replacement to stabilize her condition. Further investigations identified typical café-au-lait macules on her trunk, limbs, and face, along with neurofibromas. Endoscopy showed coffee-colored fluid in the gastric cavity, a large submucosal elevation with an exudative covering, and ulcer formation on the gastric fundus. Exploratory laparoscopy confirmed the tumor's origin in the gastric fundus, and resection of the giant GIST was performed. Pathological analysis revealed a necrotic GIST measuring 18 cm × 14 cm, classified as high-risk, with approximately 5 mitotic figures per 10 high-power fields and no tumor at the margins. Immunohistochemistry results were CD117 (+), delay of germination 1 (+), CD34 (+), and succinate dehydrogenase complex iron sulfur subunit B intact expression. Genetic testing using next-generation sequencing confirmed an NF1 gene mutation. The patient underwent successful tumor resection and was discharged home with postoperative regorafenib therapy. A follow-up at one year showed no recurrence.

CONCLUSION

Given the diversity of clinical symptoms associated with NF1 and the complexity of NF1-related GISTs, surgical resection with complete tumor removal remains the preferred treatment option. However, the absence of a standardized treatment protocol for adjuvant therapy presents numerous challenges for clinicians.

AI-Driven Drug Discovery for Rare Diseases

Rare diseases (RDs), affecting 300 million people globally, present a daunting public health challenge characterized by complexity, limited treatment options, and diagnostic hurdles. Despite legislative efforts, such as the 1983 US Orphan Drug Act, more than 90% of RDs lack effective therapies. Traditional drug discovery models, marked by lengthy development cycles and high failure rates, struggle to meet the unique demands of RDs, often yielding poor returns on investment. However, the advent of artificial intelligence (AI), encompassing machine learning (ML) and deep learning (DL), offers groundbreaking solutions. This review explores AI's potential to revolutionize drug discovery for RDs by overcoming these challenges. It discusses AI-driven advancements, such as drug repurposing, biomarker discovery, personalized medicine, genetics, clinical trial optimization, corporate innovations, and novel drug target identification. By synthesizing current knowledge and recent breakthroughs, this review provides crucial insights into how AI can accelerate therapeutic development for RDs, ultimately improving patient outcomes. This comprehensive analysis fills a critical gap in the literature, enhancing understanding of AI's pivotal role in transforming RD research and guiding future research and development efforts in this vital area of medicine.

Experiences from dual genome next-generation sequencing panel testing for mitochondrial disorders: a comprehensive molecular diagnosis

Introduction

The molecular diagnosis of mitochondrial disorders is complicated by phenotypic variability, genetic heterogeneity, and the complexity of mitochondrial heteroplasmy. Next-generation sequencing (NGS) of the mitochondrial genome in combination with a targeted panel of nuclear genes associated with mitochondrial disease provides the highest likelihood of obtaining a comprehensive molecular diagnosis. To assess the clinical utility of this approach, we describe the results from a retrospective review of patients having dual genome panel testing for mitochondrial disease.

Methods

Dual genome panel testing by NGS was performed on a cohort of 1,509 unrelated affected individuals with suspected mitochondrial disorders. This test included 163 nuclear genes associated with mitochondrial diseases and the entire mitochondrial genome. A retrospective review was performed to evaluate diagnostic yield, disease-gene contributions, and heteroplasmy levels of pathogenic/likely pathogenic (P/LP) mitochondrial DNA (mtDNA) variants.

Results

The overall diagnostic yield was 14.6%, with 7.7% from the nuclear genome and 6.9% from the mtDNA genome. P/LP variants in nuclear genes were enriched in both well-established genes (e.g., POLG) and more recently described genes (e.g., FBXL4), highlighting the importance of keeping the panel design updated.

Conclusion

Variants in nuclear and mitochondrial genomes equally contributed to a 14.6% diagnostic yield in this patient cohort. Dual genome NGS testing provides a comprehensive framework for diagnosing mitochondrial disorders, offering clinical utility that can be considered as first-tier approach compared to single genome testing. Characterizing disease-causing genes, variants, and mtDNA heteroplasmy enhances understanding of mitochondrial disorders. Testing alternative tissues can further increase diagnostic yield.

Genetic profiling of Wilson disease reveals a potential recurrent pathogenic variant of ATP7B in the Jordanian population

OBJECTIVES

Wilson disease (WD) is an autosomal-recessive disorder that disrupts copper homeostasis. ATPase copper transporting beta (ATP7B) gene is implicated as the disease-causing gene in WD. The common symptoms associated with WD include hepatic, neurological, psychiatric, and ophthalmic manifestations. The genetic landscape of WD is under-investigated in the Middle East and has never been studied in Jordan. We aimed to investigate the genetic profile of several unrelated Jordanian families with one or more patients affected by WD.

METHODS

Twenty-four Jordanian families with WD underwent clinical evaluation and genetic profiling by whole-exome and Sanger sequencing.

RESULTS

Surprisingly, the same variant (ATP7B:c.3551C>T;p.Ile1184Thr) was identified, for the first time, exclusively in the homozygous state, in eight consanguineous unrelated families. Before our study, the previous classification of this variant was either of uncertain significance (VUS) or likely pathogenic (LP). Interestingly, the patients harboring this variant displayed variable clinical manifestations on both the intra- and interfamilial levels, as previously described in cases with WD. The age of diagnosis, hepatic manifestations, neuropsychiatric involvements, and Kayser-Fleischer ring occurrence varied significantly in terms of existence and severity among the recruited individuals. Following our investigation, based on clinical data and co-segregation analysis, we re-classified the variant ATP7B:c.3551C>T;p.Ile1184Thr from VUS/LP to pathogenic, for the first time. Besides, our genetic analysis helped in resolving diagnostic ambiguity by either establishing or ruling out the diagnosis of WD.

CONCLUSION

Since the identified variant (ATP7B:p.Ile1184Thr) was discovered in multiple unrelated families, we create an avenue for the potential consideration of this variant as a recurrent, or possibly a founder variant, in the Jordanian population. Our work sheds light, for the first time, on the molecular underpinnings of WD in Jordan and compiles the WD-causing variants in the Middle East. Ultimately, the findings of our work can guide designing region-specific targeted genetic testing of WD in Jordan and provide valuable insights to direct clinical decisions for atypical WD presentations.

New Insights Into the Spectrum of RASopathies: Clinical and Genetic Data in a Cohort of 121 Spanish Patients

Noonan syndrome and related disorders are a group of well-known genetic conditions caused by dysregulation of the Ras/mitogen-activated protein kinase (RAS/MAPK) pathway. Because of the overlap of clinical and molecular features, they are now called RASopathies. In this study, we retrospectively analyzed the clinical data of 121 patients with a molecularly confirmed diagnosis of RASopathy, describing frequencies for clinical features in all organ systems as well as molecular data. The most common clinical diagnosis was Noonan Syndrome and the most frequently affected gene was PTPN11 followed by SOS1, RAF1, LZTR1, and RIT1. All patients had distinctive craniofacial features indicative of the RASopathy spectrum but we report some atypical features regarding craniofacial shape, such as craniosynostosis and microcephaly. We also describe uncommon clinical characteristics such as aortic dilation, multivalvular heart disease, abnormalities of the posterior fossa, and uterine congenital anomalies in female patients. Furthermore, the presence of multiple giant cell granulomas was observed specifically in patients with SOS1 variants. This comprehensive evaluation allows broadening the phenotypic spectrum of our population and their correlation with the genotype, which are essential to improve the recognition and the follow up of RASopathies as a multisystemic disease.

Integrative analysis of KCNQ1 variants reveals molecular mechanisms of type 1 long QT syndrome pathogenesis

Loss-of-function (LOF) pathogenic variants in KCNQ1 encoding a cardiac potassium channel predispose to sudden cardiac death in type 1 congenital long QT syndrome (LQT1). To determine the spectrum of molecular mechanisms responsible for this life-threatening condition, we used an integrative approach to determine the biophysical, functional, and trafficking properties of 61 KCNQ1 variants distributed throughout all domains of the channel. Impaired trafficking to the plasma membrane was the most common cause of LOF across all channel domains, often but not always coinciding with protein instability. However, many LOF variants, particularly in transmembrane domains, trafficked normally, but when coexpressed with KCNE1 exhibited impaired conductance, altered voltage dependence, or abnormal gating kinetics, highlighting diverse pathogenic mechanisms. This indicates a need for personalized treatment approaches for LQT1. Use of our data to benchmark variant pathogenicity prediction methods demonstrated that prediction accuracy depends on the exact mechanism of pathogenicity associated with a given variant.

Genetic variants in PIKFYVE: A review of ocular phenotypes

Many studies have identified disease-causing variants of PIKFYVE in ocular tissues; however, a comprehensive review of these variants and their ocular phenotypes is lacking. The phosphoinositide kinase PIKFYVE plays crucial roles in the endolysosomal pathway in autophagy and phagocytosis, both essential for cellular homeostasis. In this review, we evaluate the reported disease-causing PIKFYVE variants and their associated phenotypes in humans to identify potential genotype-phenotype correlations. Variants in PIKFYVE have been associated with corneal fleck dystrophy, congenital cataracts and possibly keratoconus. There are unvalidated associations of variants in PIKFYVE with autism spectrum disorder and congenital heart disease. We show that variants causing corneal fleck dystrophy exist in the chaperonin-like domain of PIKFYVE as well as the region between the chaperonin-like and the kinase domains. Similarly, congenital cataract variants appear to be specific to the kinase domain of the protein. This review consolidates existing knowledge on PIKFYVE variants in ocular disease and bridges fundamental science and clinical manifestations, potentially informing future diagnostic and treatment strategies for PIKFYVE-associated ocular disorders.

Identifying somatic driver mutations in cancer with a language model of the human genome

Somatic driver mutations play important roles in cancer and must be precisely identified to advance our understanding of tumorigenesis and its promotion and progression. However, identifying somatic driver mutations remains challenging in Homo sapiens genomics due to the random nature of mutations and the high cost of qualitative experiments. Building on the powerful sequence interpretation capabilities of language models, we propose a self-attention-based contextualized pretrained language model for somatic driver mutation identification. We pretrained the model with the Homo sapiens reference genome to equip it with the ability to understand genome sequences and then fine-tuned it for oncogene and tumor suppressor gene prediction tasks, enabling it to extract features related to driver genes from the original genome sequence. The fine-tuned model was used to obtain the mutations' carcinogenic effect characteristics to further identify whether the mutation is a driver or a passenger. Compared with other computational algorithms, our method achieved excellent somatic driver mutation identification performance on the test set, with an absolute improvement of 4.31% in AUROC over the best comparison method. The strong performance of our method indicates that it can provide new insights into the discovery of cancer drivers.

PharmFreq: a comprehensive atlas of ethnogeographic allelic variation in clinically important pharmacogenes

Genetic polymorphisms in drug metabolizing enzymes, drug transporters as well as in genes encoding the human major histocompatibility complex contribute to inter-individual differences in drug efficacy and safety. The extent, pattern and complexity of such pharmacogenetic variation differ drastically across human populations. Here, we present PharmFreq, a global repository of pharmacogenetic frequency information that aggregates frequency data of 658 allelic variants from over 10 million individuals collected from >1200 studies across 144 countries. Most investigations were conducted in East Asian and European populations, accounting for 29.4 and 26.6% of all studies, respectively. We find that the number of studies per country and aggregated cohort size correlated significantly with population size (R = 0.55, P= 3*10-9) and country gross domestic product (R = 0.43, P= 2*10-6) with overall population coverage varying between 5% in Estonia to < 0.001% in many countries in Sub-Saharan Africa and Asia. All frequency data are openly accessible via a web-based interactive dashboard at pharmfreq.com that facilitates the exploration, visualization and analysis of country- and population-specific data and their inferred phenotypic consequences. PharmFreq thus presents a comprehensive, freely available resource for pharmacogenetic variant frequencies that can inform about ethnogeographic pharmacogenomic diversity and reveal important inequities that help to focus future research efforts into underrepresented populations.

The UCSC Genome Browser database: 2025 update

The UCSC Genome Browser (https://genome.ucsc.edu) is a widely utilized web-based tool for visualization and analysis of genomic data, encompassing over 4000 assemblies from diverse organisms. Since its release in 2001, it has become an essential resource for genomics and bioinformatics research. Annotation data available on Genome Browser includes both internally created and maintained tracks as well as custom tracks and track hubs provided by the research community. This last year's updates include over 25 new annotation tracks such as the gnomAD 4.1 track on the human GRCh38/hg38 assembly, the addition of three new public hubs, and significant expansions to the Genome Archive[GenArk) system for interacting with the enormous variety of assemblies. We have also made improvements to our interface, including updates to the browser graphic page, such as a new popup dialog feature that now displays item details without requiring navigation away from the main Genome Browser page. GenePred tracks have been upgraded with right-click options for zooming and precise navigation, along with enhanced mouseOver functions. Additional improvements include a new grouping feature for track hubs and hub description info links. A new tutorial focusing on Clinical Genetics has also been added to the UCSC Genome Browser.

Multiparametric MRI along with machine learning predicts prognosis and treatment response in pediatric low-grade glioma

Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatment, leading to tumor progression and adverse outcomes in cases where complete resection is unachievable. Early prediction of treatment responsiveness and suitability for immunotherapy has the potential to improve clinical management and outcomes. Here, we present a radiogenomic analysis of pLGGs, integrating MRI and RNA sequencing data. We identify three immunologically distinct clusters, with one group characterized by increased immune activity and poorer prognosis, indicating potential benefit from immunotherapies. We develop a radiomic signature that predicts these immune profiles with over 80% accuracy. Furthermore, our clinicoradiomic model predicts progression-free survival and correlates with treatment response. We also identify genetic variants and transcriptomic pathways associated with progression risk, highlighting links to tumor growth and immune response. This radiogenomic study in pLGGs provides a framework for the identification of high-risk patients who may benefit from targeted therapies.

Human disease-causing missense genetic variants are enriched in the evolutionarily ancient domains of the cytosolic aminoacyl-tRNA synthetase proteins

All life depends on accurate and efficient protein synthesis. The aminoacyl-tRNA synthetases (aaRSs) are a family of proteins that play an essential role in protein translation, as they catalyze the esterification reaction that charges a transfer RNA (tRNA) with its cognate amino acid. However, new domains added to the aaRSs over the course of evolution in eukaryotes confer novel functions unrelated to protein translation. To date, damaging variants that affect aaRS-encoding genes have been linked to over 50 human diseases. In this study, we leverage the evolutionary history of the aaRS proteins to better understand the distribution of disease-causing missense variants in human cytosolic aaRSs. We hypothesized that disease-causing missense variants in human aaRSs were more likely to be located in the ancient domains of the aaRS, essential for the aminoacylation reaction, rather than in the evolutionarily more recent domains found in eukaryotes. We determined the locations of the modern and ancient domains in each aaRS protein found in humans. We then statistically assessed the positional conservation across each domain and examined the distribution of pathogenic and benign/unknown missense human genetic variants across these domains. We establish that pathogenic missense variants in the human aaRS proteins are enriched in the evolutionarily ancient domains while benign/unknown missense variants are enriched in the modern domains. In addition to defining the evolutionary history of human aaRS proteins through domain identification, we anticipate that this work will improve the ability to diagnose patients affected by damaging genetic variants in the aaRS protein family.

Modulation of Haemostatic Balance in Combined von Willebrand Disease and Antithrombin Deficiency: A Comprehensive Family Study

INTRODUCTION

Maintaining the balance between procoagulant and anticoagulant factors is essential for effective haemostasis. Emerging evidence suggests a modulation of bleeding tendency by factors in the anticoagulant and fibrinolytic systems.

AIM

This study investigates the clinical and laboratory characteristics of a family with combined von Willebrand disease (VWD) and antithrombin (AT) deficiency.

METHODS

The study focused on a 38-year-old female index patient (IP) with severe type 3 VWD and a history of bleeding disorders. Coagulation assays included VWF antigen, platelet-dependent VWF activity, factor VIII activity, thrombin generation assay (TGA) and AT activity. Molecular genetic analyses were conducted by a targeted DNA custom next generation sequencing (NGS) panel.

RESULTS

The IP and one of her sisters suffered type 3 VWD. While the IP presents with a classical severe bleeding phenotype, the sister (II-2) exhibited less severe bleeding symptoms. Extended family members showed type 1 VWD with mild presentations. NGS revealed a homozygous deletion of exon 6 in the VWF gene in the IP and her sister (II-2). All other family members carry this genetic variant in a heterozygous state. Additionally, II-2 has a heterozygous variant in the SERPINC1 gene (c.133C>T, p.Arg45Trp). Both IP and II-2 carry a homozygous prothrombin G20210A variant. TGA results indicated reduced thrombin generation in severe VWD patients, with a pronounced thrombin burst in those with the AT and prothrombin G20210A variant.

CONCLUSIONS

AT deficiency appears to modulate bleeding symptoms in severe VWD. This study emphasizes the importance of comprehensive genetic and phenotypic evaluation in managing complex coagulation disorders.

Novel Splice-Altering Variants in the CHM and CACNA1F Genes Causative of X-Linked Choroideremia and Cone Dystrophy

BACKGROUND

An estimated 10-15% of all genetic diseases are attributable to variants in noncanonical splice sites, auxiliary splice sites and deep-intronic variants. Most of these unstudied variants are classified as variants of uncertain significance (VUS), which are not clinically actionable. This study investigated two novel splice-altering variants, CHM NM_000390.4:c.941-11T>G and CACNA1F NM_005183.4:c.2576+4_2576+5del implicated in choroideremia and cone dystrophy (COD), respectively, resulting in significant visual loss.

METHODS

Next-generation sequencing was employed to identify the candidate variants in CHM and CACNA1F, which were confirmed using Sanger sequencing. Cascade analysis was undertaken when additional family members were available. Functional analysis was conducted by cloning genomic regions of interest into gateway expression vectors, creating variant and wildtype midigenes, which were subsequently transfected into HEK293 cells. RNA was harvested and amplified by RT-PCR to investigate the splicing profile for each variant compared to the wildtype. Novel variants were reclassified according to ACMG/AMP and ClinGen SVI guidelines.

RESULTS

Midigene functional analysis confirmed that both variants disrupted splicing. The CHM NM_000390.4:c.941-11T>G variant caused exon 8 skipping, leading to a frameshift and the CACNA1F NM_005183.4:c.2576+4_2576+5del variant caused a multimodal splice defect leading to an in-frame insertion of seven amino acids and a frameshift. With this evidence, the former was upgraded to likely pathogenic and the latter to a hot VUS.

CONCLUSIONS

This study adds to the mutational spectrum of splicing defects implicated in retinal degenerations by identifying and characterising two novel variants in CHM and CACNA1F. Our results highlight the importance of conducting functional analysis to investigate the consequences of intronic splice-altering variants and the significance of reclassifying VUS to confirm a genetic diagnosis.

A comprehensive benchmark for multiple highly efficient base editors with broad targeting scope

As the toolbox of base editors (BEs) expands, selecting appropriate BE and guide RNA (gRNA) to achieve optimal editing efficiency and outcome for a given target becomes challenging. Here, we construct a set of 10 adenine and cytosine BEs with high activity and broad targeting scope, and comprehensively evaluate their editing profiles and properties head-to-head with 34,040 BE-gRNA-target combinations using genomically integrated long targets and tiling gRNA strategies. Interestingly, we observe widespread non-canonical protospacer adjacent motifs (PAMs) for these BEs. Using this large-scale benchmark data, we build a deep learning model, named BEEP (Base Editing Efficiency Predictor), for predicting the editing efficiency and outcome of these BEs. Guided by BEEP, we experimentally test and validate the installment of 3,558 disease-associated single nucleotide variants (SNVs) via BEs, including 20.1% of target sites that would be generally considered as "uneditable", due to the lack of canonical PAMs. We further predict candidate BE-gRNA-target combinations for modeling 1,752,651 ClinVar SNVs. We also identify several cancer-associated SNVs that drive the resistance to BRAF inhibitors in melanoma. These efforts benchmark the performance and illuminate the capabilities of multiple highly useful BEs for interrogating functional SNVs. A practical webserver (http://beep.weililab.org/) is freely accessible to guide the selection of optimal BEs and gRNAs for a given target.

Genome-Wide Association Study of Insertions and Deletions Identified Novel Loci Associated with Milk Production Traits in Dairy Cattle

Genome-wide association study (GWAS) have identified a large number of SNPs associated with milk production traits in dairy cattle. Behind SNPs, INDELs are the second most abundant genetic polymorphisms in the genome, which may exhibit an independent association with complex traits in humans and other species. However, there are no reports on GWASs of INDELs for milk production traits in dairy cattle. In this study, using imputed sequence data, we performed INDEL-based and SNP-based GWASs for milk production traits in a Holstein cattle population. We identified 58 unique significant INDELs for one or multiple traits. The majority of these INDELs are in considerable LD with nearby significant SNPs. However, through conditional association analysis, we identified nine INDELs which showed independent associations. Genomic annotations of these INDELs indicated some novel associated genes, i.e., TRNAG-CCC, EPPK1, PPM1K, PTDSS1, and mir-10163, which were not reported in previous SNP-based GWASs. Our findings suggest that INDEL-based GWASs could be valuable complement to SNP-based GWASs for milk production traits.

Association study of GBA1 variants with MSA based on comprehensive sequence analysis -Pitfalls in short-read sequence analysis depending on the human reference genome

Multiple system atrophy (MSA) is a neurodegenerative disorder characterized by various combinations of autonomic failure, parkinsonism, and cerebellar ataxia. To elucidate variants associated with MSA, we have been conducting short-read-based whole-genome sequence analysis. In the process of the association studies, we initially focused on GBA1, a previously proposed susceptibility gene for MSA, to evaluate whether GBA1 variants can be efficiently identified despite its extraordinarily high homology with its pseudogene, GBA1LP. To accomplish this, we conducted a short-read whole-genome sequence analysis with alignment to GRCh38 as well as Sanger sequence analysis and compared the results. We identified five variants with inconsistencies between the two pipelines, of which three variants (p.L483P, p.A495P-p.V499V, p.L483_M489delinsW) were the results of misalignment due to minor alleles in GBA1P1 registered in GRCh38. The miscalling events in these variants were resolved by alignment to GRCh37 as the reference genome, where the major alleles are registered. In addition, a structural variant was not properly identified either by short-read or by Sanger sequence analyses. Having accomplished correct variant calling, we identified three variants pathogenic for Gaucher disease (p.S310G, p.L483P, and p.L483_M489delinsW). Of these variants, the allele frequency of p.L483P (0.003) in the MSA cases was higher than that (0.0011) in controls. The meta-analysis incorporating a previous report demonstrated a significant association of p.L483P with MSA with an odds ratio of 2.85 (95% CI; 1.05 - 7.76, p = 0.0400).

Structural and functional prediction, evaluation, and validation in the post-sequencing era

The surge of genome sequencing data has underlined substantial genetic variants of uncertain significance (VUS). The decryption of VUS discovered by sequencing poses a major challenge in the post-sequencing era. Although experimental assays have progressed in classifying VUS, only a tiny fraction of the human genes have been explored experimentally. Thus, it is urgently needed to generate state-of-the-art functional predictors of VUS in silico. Artificial intelligence (AI) is an invaluable tool to assist in the identification of VUS with high efficiency and accuracy. An increasing number of studies indicate that AI has brought an exciting acceleration in the interpretation of VUS, and our group has already used AI to develop protein structure-based prediction models. In this review, we provide an overview of the previous research on AI-based prediction of missense variants, and elucidate the challenges and opportunities for protein structure-based variant prediction in the post-sequencing era.

Real-World Performance of Integrative Clinical Genomics in Pediatric Precision Oncology

Despite significant improvement in the survival of pediatric patients with cancer, treatment outcomes for high-risk, relapsed, and refractory cancers remain unsatisfactory. Moreover, prolonged survival is frequently associated with long-term adverse effects due to intensive multimodal treatments. Accelerating the progress of pediatric oncology requires both therapeutic advances and strategies to mitigate the long-term cytotoxic side effects, potentially through targeting specific molecular drivers of pediatric malignancies. In this report, we present the results of integrative genomic and transcriptomic profiling of 230 patients with malignant solid tumors (the "primary cohort") and 18 patients with recurrent or otherwise difficult-to-treat nonmalignant conditions (the "secondary cohort"). The integrative workflow for the primary cohort enabled the identification of clinically significant single nucleotide variants, small insertions/deletions, and fusion genes, which were found in 55% and 28% of patients, respectively. For 38% of patients, molecularly informed treatment recommendations were made. In the secondary cohort, known or potentially driving alteration was detected in 89% of cases, including a suspected novel causal gene for patients with inclusion body infantile digital fibromatosis. Furthermore, 47% of findings also brought therapeutic implications for subsequent management. Across both cohorts, changes or refinements to the original histopathological diagnoses were achieved in 4% of cases. Our study demonstrates the efficacy of integrating advanced genomic and transcriptomic analyses to identify therapeutic targets, refine diagnoses, and optimize treatment strategies for challenging pediatric and young adult malignancies and underscores the need for broad implementation of precision oncology in clinical settings.

Disease Progression of GNE Myopathy and Its Relationship With Genotype: A Retrospective, Observational Study in Chinese Patients

Background and Objectives

Studies on the natural disease progression of detailed motor dysfunction in patients with GNE myopathy are rare. This study aimed to investigate motor function involvement during disease progression and its relationship with the genotype among Chinese patients with GNE myopathy.

Methods

This retrospective observational cohort study included all patients with genetically confirmed GNE myopathy enrolled at Peking University First Hospital between 2000 and 2023. Patients with GNE myopathy were stratified into 2 subgroups based on with or without p.D207V mutation. Data on clinically significant muscular problems were collected from patients' medical history and follow-up assessments to evaluate motor function using the GNE Myopathy Functional Activity Scale and the modified Rankin Scale.

Results

Eighty-three patients with GNE myopathy were included, with a median age at examination of 36 years (range 25-57) and a median age at onset (AAO) of 26 years (range 16-46). The Kaplan-Meier curves revealed that patients with the p.D207V mutation experienced a significantly later AAO (27 years [95% CI 25-29]) and onset age of wheelchair dependency (50 years [95% CI 46-54]) compared with those without the mutation, who had an AAO of 24 years (95% CI 22-26) and an onset age of wheelchair dependency of 45 years (95% CI 36-54). Multivariate Cox regression analysis, adjusted for sex and disease duration, revealed that patients without the p.D207V mutation had a higher risk of wheelchair dependency, with an adjusted hazard ratio of 2.361 (95% CI 1.030-5.411). Barthel indexes (BIs) were negatively correlated with the disease duration and positively correlated with AAOs. Patients with GNE with earlier AAO exhibited a shorter disease duration of developing functional dependency (BIs <60) than did those with later AAOs.

Discussion

Our results provide insights into the motor function involvement observed during disease progression in Chinese patients with GNE myopathy, and relatively mild disease severity was observed in those with the p.D207V mutation.

RNA Splicing Aberrations in Hereditary Cancer: Insights from Turkish Patients

The process of RNA splicing is fundamental in contributing to proteomic diversity and regulating gene expression. Dysregulation of splicing is associated with various human disorders, including cancer. Through functional studies, this study sought to examine the potential impact of seven variants within six inherited cancer-related genes on RNA splicing patterns in Turkish cancer patients. Upon detecting variants using Next-Generation Sequencing (NGS), we used Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) and Sanger sequencing to elucidate the effects of these variants on splicing. Three of the seven variants demonstrated no discernible effect on RNA, while four exhibited pathogenic characteristics. Specifically, the variants APC c.532-1G>A rs1554072547, BRCA1c.4358-3A>G rs1567779966, BRCA2c.7436-1G>C rs81002830 and MSH3c.1897-1G>A rs1744149615 were identified as pathogenic, while the variants BLMc.4076+4T>G rs183176301, RB1c.2489+2T>C rs1555294636 and RB1c.1050-2A>G rs? were found to be benign from a splicing perspective. These findings highlight the importance of verifying the precise consequences of splice-site variants through experimental analysis, given their potential implications for genetic disorders and cancer predisposition. This research contributes to the understanding of splice-site variants in inherited cancer predisposition, particularly among Turkish cancer patients. It emphasizes the necessity for further exploration into the mechanisms and functional consequences of alternative splicing for potential therapeutic interventions in cancer.

An Atypical Mechanism of SUMOylation of Neurofibromin SecPH Domain Provides New Insights into SUMOylation Site Selection

Neurofibromin (Nf1) is a giant multidomain protein encoded by the tumour-suppressor gene NF1. NF1 is mutated in a common genetic disease, neurofibromatosis type I (NF1), and in various cancers. The protein has a Ras-GAP (GTPase activating protein) activity but is also connected to diverse signalling pathways through its SecPH domain, which interacts with lipids and different protein partners. We previously showed that Nf1 partially colocalized with the ProMyelocytic Leukemia (PML) protein in PML nuclear bodies, hotspots of SUMOylation, thereby suggesting the potential SUMOylation of Nf1. Here, we demonstrate that the full-length isoform 2 and a SecPH fragment of Nf1 are substrates of the SUMO pathway and identify a well-defined SUMOylation profile of SecPH with two main modified lysines. One of these sites, K1731, is highly conserved and surface-exposed. Despite the presence of an inverted SUMO consensus motif surrounding K1731, and a potential SUMO-interacting motif (SIM) within SecPH, we show that neither of these elements is necessary for K1731 SUMOylation, which is also independent of Ubc9 SUMOylation on K14. A 3D model of an interaction between SecPH and Ubc9 centred on K1731, combined with site-directed mutagenesis, identifies specific structural elements of SecPH required for K1731 SUMOylation, some of which are affected in reported NF1 pathogenic variants. This work provides a new example of SUMOylation dependent on the tertiary rather than primary protein structure surrounding the modified site, expanding our knowledge of mechanisms governing SUMOylation site selection.

Newborn screening for acid sphingomyelinase deficiency in Illinois: A single center's experience

Acid sphingomyelinase deficiency (ASMD) is a rare lysosomal storage disorder (LSD) caused by reduced activity of the acid sphingomyelinase (ASM) enzyme, which leads to progressive storage of sphingomyelin and related lipids in the body. ASMD is caused by biallelic variants in the SMPD1 gene, which encodes for the ASM enzyme. Current estimates of disease incidence range from 0.4 to 0.6 in 100 000 livebirths, although this is likely an underestimation of the true frequency of the disorder. While there is no cure for ASMD, comprehensive care guidelines and enzyme replacement therapy are available, making an early diagnosis crucial. Newborn screening (NBS) for ASMD is possible through measurement of ASM activity in dried blood spots and offers the opportunity for early diagnosis. In 2015, Illinois (IL) became the first to initiate statewide implementation of NBS for ASMD. This study describes the outcomes of screen-positive patients referred to Ann & Robert H. Lurie Children's Hospital (Lurie). Ten infants were referred for diagnostic evaluation at Lurie, and all 10 infants were classified as confirmed ASMD or at risk for ASMD through a combination of molecular and biochemical testing. Disease incidence was calculated using data from this statewide implementation program and was ~0.79 in 100 000 livebirths. This study demonstrates successful implementation of NBS for ASMD in IL, with high screen specificity and a notable absence of false positive screens.

Unravelling the spectrum of von Willebrand factor variants in quantitative von Willebrand disease: results from a German cohort study

BACKGROUND

Von Willebrand disease (VWD), the most prevalent hereditary bleeding disorder, results from deficiency of von Willebrand factor (VWF).

OBJECTIVES

This large cohort study aims to offer a comprehensive exploration of mutation spectra and laboratory features in quantitative VWF deficiencies, shedding light on genetic underpinnings and genotype-phenotype associations.

METHODS

Our cohort consisted of 221 Caucasian index patients with quantitative VWD, along with 47 individuals whose plasma VWF levels fell within the lower normal boundaries (50-70 IU/dL). We conducted comprehensive VWF assays and genetic analyses, encompassing VWF gene sequencing, copy number variation investigations, and bioinformatic assessments.

RESULTS

Following International Society on Thrombosis and Haemostasis-Scientific and Standardization Committee VWF guidelines, 77 index patients were characterized as having type 1 VWD (VWF antigen [VWF:Ag] < 30 IU/dL), 111 as having type 1 VWD (VWF:Ag, 30-50 IU/dL), and 33 as having type 3 VWD. Mutation detection rates were 88%, 65%, and 92%, respectively. Notably, blood group O overrepresentation was evident in type 1 with VWF:Ag of 30 to 50 IU/dL, particularly among mutation-negative patients, suggesting a potential causal role of blood group O. A total of 223 VWF variants, comprising 147 distinct variations, were identified in quantitative VWD patients, of which 57 were novel variants (39%). Additionally, approximately 70% of individuals with VWF levels within the lower normal boundaries (50-70 IU/dL) displayed VWF variants.

CONCLUSION

Our data advance our understanding of the molecular mechanisms underlying quantitative VWD, offering valuable insights for future research and clinical management. Distinct mutation patterns were observed among subgroups, particularly the contrast between type 1 VWD (VWF:Ag < 30 IU/dL) and type 1 VWD (VWF:Ag, 30-50 IU/dL), an area with limited prior investigation.

Investigating the role of keratin proteins and microbial associations in hereditary and pathogenic alopecia

The purpose of this research was to identify the role of keratin proteins in causing inherited as well as pathogenic alopecia, pinpoint deleterious SNPs, and predict structural changes affecting protein-protein interactions in hair disorders. To elucidate the role of keratin proteins and genetic mutations in alopecia by analyzing protein structures through bioinformatics and identifying a mutation in the LPAR6 gene. It sought to identify the microorganisms linked to alopecia and conducted a comprehensive bioinformatics analysis of proteins with unknown experimental structures and molecular simulation analysis. The study identified a genetic mutation (c.188 A > T, p.Asp63Val) in the LPAR6 gene associated with hereditary hair loss. Pathogenic alopecia was identified to be associated with S. aureus and two ic keratinophilic fungi namely M. canis, and T. violaceum. Additionally, among 14 proteins lacking prior structural information, four proteins namely Keratin, type II cuticular Hb3 (KR1), Keratin, type II cuticular Hb6 (KR2), Keratin, type II cytoskeletal 74 (KR3) and Keratin, type II cuticular Hb1 (KR4) exhibited common 'K-head' and 'F' domains. Docking analysis revealed five distinct binding sites (C1-C5) for each protein. The 'K-head' displayed the highest predicted binding affinities with Vina scores of -5.6 for KR2 and - 4.7 for KR4 whereas the 'F' domain showed Vina scores of -6.0 for KR3 and - 5.7 for KR2. This research underscores the crucial role of keratin proteins in both hereditary and pathogenic alopecia, emphasizing their significance for future investigations.

Evaluation of whole genome sequencing utility in identifying driver alterations in cancer genome

In cancer genome analysis, identifying pathogenic alterations and assessing their effects on oncogenic processes is important. Although whole exome sequencing (WES) can effectively detect such changes, driver alterations could not be identified in 27.8% of the cases, according to a previous study. The objectives of the present study were to evaluate the utility of whole genome sequencing (WGS) and clarify its differences with WES in terms of driver alteration detection. For this purpose, WGS analysis was conducted on 177 driverless WES samples, selected from 5,480 fresh frozen samples derived from 5,140 Japanese patients with cancer. These samples were selected as primary tumor, both WES and transcriptome profiling were performed, estimated tumor content of ≥ 30%, and no driver alterations were identified by WES. WGS identified driver and likely driver alterations in 68.4 and 22.6% of the samples, respectively. The most frequent alteration type was oncogene amplification, followed by tumor suppressor gene deletion and small variants located outside the coding region. In the remaining 9.0% of samples, no such signals were identified; therefore, further investigations are required. The current study clearly demonstrated the role and utility of WGS in identifying genomic alterations that contribute to tumorigenesis.

The power of hybridization capture - Illustrated using an expanded gene panel on 100 post mortem samples, focusing on sudden unexplained death

Sudden unexpected death (SUD) is an unexpected event that in many cases are caused by diseases with an underlying genetic background. Forensic molecular autopsy is an approach that has gained wide-spread attention, in part explained by the rapid progress of DNA sequencing techniques. The approach leverages genetic data in combination with medical autopsy findings in post-mortem samples to explore a potential underlying genetic cause of death. Traditional forensic approaches to molecular autopsy focus on a small panel of genes, say <200 genes, with strong association to heart conditions whereas clinical genetics tend to capture entire exomes while subsequently selecting targeted panels bioinformatically. The drop in price and the increased throughput has promoted wider exome sequencing as a viable method to discover genetic variants. We explore a targeted gene panel consisting of 2422 genes, selected based on their broad association to sudden unexplained death. A hybridization capture approach from Twist Bioscience based on double stranded DNA probes was used to target exons of the included genes. We selected and sequenced a total of 98 post-mortem samples from historical forensic autopsy cases where the cause of death could not be unambiguously determined based on medical findings and that had a previous negative molecular autopsy. In the current study, we focus on the performance of the hybridization capture technology on a 2422 gene panel and explore metrics related to sequencing success using a mid-end NextSeq 550 as well as a MiSeq FGx platform. With the latter we demonstrate that our sequence data benefits from 2×300 bp sequencing increasing coverage, in particular, for difficult regions where shadow coverage, i.e. regions outside the probes, are utilized. The results further illustrate a highly uniform capture across the panel of genes (mean fold80=1.5), in turn minimizing excessive sequencing costs to reach sufficient coverage, i.e. 20X. We outline a stepwise procedure to select genes associated with SUD through virtual bioinformatical panels extracting tier of genes with increasing strength of association to SUD. We propose some prioritization strategies to filter variants with highest potential and show that the number of high priority genetic variant requiring manual inspections is few (0-3 for all tiers of genes) when all filters are applied.

Clinical and Molecular Profiles of a Cohort of Egyptian Patients with Collagen VI-Related Dystrophy

Collagen VI-related dystrophies (COL6-RD) display a wide spectrum of disease severity and genetic variability ranging from mild Bethlem myopathy (BM) to severe Ullrich congenital muscular dystrophy (UCMD) and the intermediate severities in between with dual modes of inheritance, dominant and recessive. In the current study, next-generation sequencing demonstrated potential variants in the genes coding for the three alpha chains of collagen VI (COL6A1, COL6A2, or COL6A3) in a cohort of Egyptian patients with progressive muscle weakness (n = 23). Based on the age of disease onset and the patient clinical course, subjects were diagnosed as follows: 12 with UCMD, 8 with BM, and 3 with intermediate disease form. Fourteen pathogenic variants, including 5 novel alterations, were reported in the enrolled subjects. They included 3 missense, 3 frameshift, and 6 splicing variants in 4, 3, and 6 families, respectively. In addition, a nonsense variant in a single family and an inframe variant in 3 different families were also detected. Recessive and dominant modes of inheritance were recorded in 9 and 8 families, respectively. According to ACMG guidelines, variants were classified as pathogenic (n = 7), likely pathogenic (n = 4), or VUS (n = 3) with significant pathogenic potential. To our knowledge, the study provided the first report of the clinical and genetic findings of a cohort of Egyptian patients with collagen VI deficiency. Inter- and intra-familial clinical variability was evident among the study cohort.

Genetically inferred birthweight, height, and puberty timing and risk of osteosarcoma

INTRODUCTION

Several studies have linked increased risk of osteosarcoma with tall stature, high birthweight, and early puberty, although evidence is inconsistent. We used genetic risk scores (GRS) based on established genetic loci for these traits and evaluated associations between genetically inferred birthweight, height, and puberty timing with osteosarcoma.

METHODS

Using genotype data from two genome-wide association studies, totaling 1039 cases and 2923 controls of European ancestry, association analyses were conducted using logistic regression for each study and meta-analyzed to estimate pooled odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses were conducted by case diagnosis age, metastasis status, tumor location, tumor histology, and presence of a known pathogenic variant in a cancer susceptibility gene.

RESULTS

Genetically inferred higher birthweight was associated with an increased risk of osteosarcoma (OR =1.59, 95% CI 1.07-2.38, P = 0.02). This association was strongest in cases without metastatic disease (OR =2.46, 95% CI 1.44-4.19, P = 9.5 ×10-04). Although there was no overall association between osteosarcoma and genetically inferred taller stature (OR=1.06, 95% CI 0.96-1.17, P = 0.28), the GRS for taller stature was associated with an increased risk of osteosarcoma in 154 cases with a known pathogenic cancer susceptibility gene variant (OR=1.29, 95% CI 1.03-1.63, P = 0.03). There were no significant associations between the GRS for puberty timing and osteosarcoma.

CONCLUSION

A genetic propensity to higher birthweight was associated with increased osteosarcoma risk, suggesting that shared genetic factors or biological pathways that affect birthweight may contribute to osteosarcoma pathogenesis.

Generative language models on nucleotide sequences of human genes

Language models, especially transformer-based ones, have achieved colossal success in natural language processing. To be precise, studies like BERT for natural language understanding and works like GPT-3 for natural language generation are very important. If we consider DNA sequences as a text written with an alphabet of four letters representing the nucleotides, they are similar in structure to natural languages. This similarity has led to the development of discriminative language models such as DNABERT in the field of DNA-related bioinformatics. To our knowledge, however, the generative side of the coin is still largely unexplored. Therefore, we have focused on the development of an autoregressive generative language model such as GPT-3 for DNA sequences. Since working with whole DNA sequences is challenging without extensive computational resources, we decided to conduct our study on a smaller scale and focus on nucleotide sequences of human genes, i.e. unique parts of DNA with specific functions, rather than the whole DNA. This decision has not significantly changed the structure of the problem, as both DNA and genes can be considered as 1D sequences consisting of four different nucleotides without losing much information and without oversimplification. First of all, we systematically studied an almost entirely unexplored problem and observed that recurrent neural networks (RNNs) perform best, while simple techniques such as N-grams are also promising. Another beneficial point was learning how to work with generative models on languages we do not understand, unlike natural languages. The importance of using real-world tasks beyond classical metrics such as perplexity was noted. In addition, we examined whether the data-hungry nature of these models can be altered by selecting a language with minimal vocabulary size, four due to four different types of nucleotides. The reason for reviewing this was that choosing such a language might make the problem easier. However, in this study, we found that this did not change the amount of data required very much.

Whole genome sequencing in adults with clinical hallmarks of hypophosphatasia negative for ALPL variants

BACKGROUND

Hypophosphatasia (HPP) is a rare disease caused by deficient activity of tissue-nonspecific alkaline phosphatase (ALP), encoded by the ALPL gene. The primary objective was to explore novel ALPL variants by whole genome sequencing (WGS) in patients with HPP who previously tested negative by standard methods for ALPL variants. The secondary objective was to search for genes beyond ALPL that may reduce ALP activity or contribute to HPP symptoms.

METHODS AND RESULTS

WGS was performed in 16 patients clinically diagnosed with HPP who had ALP activity below the normal range and tested negative for ALPL variants. Genetic variants in ALPL and genes possibly associated with low ALP activity or phenotypic overlap with HPP were assessed. All 16 patients had ALP activity below the normal range. WGS did not identify any novel disease-causing ALPL variants. Positive findings for other gene variants were identified in 4 patients: 1 patient presented with variants in COL1A1, NLRP12, and SCN9A, coding for collagen, type, I alpha-1 chain, nod-like receptor pyrin domain containing 12, and sodium voltage-gated channel alpha subunit 9, respectively; 1 presented with a heterozygous, likely pathogenic variant in P3H1 coding for prolyl 3 hydroxylase 1; 1 presented with a heterozygous pathogenic variant in SGCE, coding for sarcoglycan epsilon; and 1 presented with a heterozygous variant of uncertain significance in VDR, encoding vitamin D receptor.

CONCLUSION

Genomic analysis did not identify novel ALPL variants or a pattern of disease-causing variants in genes other than ALPL to explain the HPP phenotype in these patients.

REGISTRATION

Clinicaltrials.gov identifier: NCT04925804.

Nanopore Deep Sequencing as a Tool to Characterize and Quantify Aberrant Splicing Caused by Variants in Inherited Retinal Dystrophy Genes

The contribution of splicing variants to molecular diagnostics of inherited diseases is reported to be less than 10%. This figure is likely an underestimation due to several factors including difficulty in predicting the effect of such variants, the need for functional assays, and the inability to detect them (depending on their locations and the sequencing technology used). The aim of this study was to assess the utility of Nanopore sequencing in characterizing and quantifying aberrant splicing events. For this purpose, we selected 19 candidate splicing variants that were identified in patients affected by inherited retinal dystrophies. Several in silico tools were deployed to predict the nature and estimate the magnitude of variant-induced aberrant splicing events. Minigene assay or whole blood-derived cDNA was used to functionally characterize the variants. PCR amplification of minigene-specific cDNA or the target gene in blood cDNA, combined with Nanopore sequencing, was used to identify the resulting transcripts. Thirteen out of nineteen variants caused aberrant splicing events, including cryptic splice site activation, exon skipping, pseudoexon inclusion, or a combination of these. Nanopore sequencing allowed for the identification of full-length transcripts and their precise quantification, which were often in accord with in silico predictions. The method detected reliably low-abundant transcripts, which would not be detected by conventional strategies, such as RT-PCR followed by Sanger sequencing.