The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies

Network-based identification and mechanism exploration of active ingredients against Alzheimer's disease via targeting endoplasmic reticulum stress from traditional chinese medicine

Alzheimer's disease is a neurodegenerative disease that leads to dementia and poses a serious threat to the health of the elderly. Traditional Chinese medicine (TCM) presents as a promising novel therapeutic therapy for preventing and treating dementia. Studies have shown that natural products derived from kidney-tonifying herbs can effectively inhibit AD. Furthermore, endoplasmic reticulum (ER) stress is a critical factor in the pathology of AD. Regulation of ER stress is a crucial approach to prevent and treat AD. Thus, in this study, we first collected kidney-tonifying herbs, integrated chemical ingredients from multiple TCM databases, and constructed a comprehensive drug-target network. Subsequently, we employed the endophenotype network (network proximity) method to identify potential active ingredients in kidney-tonifying herbs that prevented AD via regulating ER stress. By combining the predicted outcomes, we discovered that 32 natural products could ameliorate AD pathology via regulating ER stress. After a comprehensive evaluation of the multi-network model and systematic pharmacological analyses, we further selected several promising compounds for in vitro testing in the APP-SH-SY5Y cell model. Experimental results showed that echinacoside and danthron were able to effectively reduce ER stress-mediated neuronal apoptosis by inhibiting the expression levels of BIP, p-PERK, ATF6, and CHOP in APP-SH-SY5Y cells. Overall, this study utilized the endophenotype network to preliminarily decipher the effective material basis and potential molecular mechanism of kidney-tonifying Chinese medicine for prevention and treatment of AD.

Deep-GenMut: Automated genetic mutation classification in oncology: A deep learning comparative study

Early cancer detection and treatment depend on the discovery of specific genes that cause cancer. The classification of genetic mutations was initially done manually. However, this process relies on pathologists and can be a time-consuming task. Therefore, to improve the precision of clinical interpretation, researchers have developed computational algorithms that leverage next-generation sequencing technologies for automated mutation analysis. This paper utilized four deep learning classification models with training collections of biomedical texts. These models comprise bidirectional encoder representations from transformers for Biomedical text mining (BioBERT), a specialized language model implemented for biological contexts. Impressive results in multiple tasks, including text classification, language inference, and question answering, can be obtained by simply adding an extra layer to the BioBERT model. Moreover, bidirectional encoder representations from transformers (BERT), long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) have been leveraged to produce very good results in categorizing genetic mutations based on textual evidence. The dataset used in the work was created by Memorial Sloan Kettering Cancer Center (MSKCC), which contains several mutations. Furthermore, this dataset poses a major classification challenge in the Kaggle research prediction competitions. In carrying out the work, three challenges were identified: enormous text length, biased representation of the data, and repeated data instances. Based on the commonly used evaluation metrics, the experimental results show that the BioBERT model outperforms other models with an F1 score of 0.87 and 0.850 MCC, which can be considered as improved performance compared to similar results in the literature that have an F1 score of 0.70 achieved with the BERT model.

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.

Aortic disease and cardiomyopathy in patients with a novel DNMT3A gene variant causing Tatton-Brown-Rahman syndrome

Tatton-Brown-Rahman syndrome (TBRS) is a rare congenital genetic disorder caused by autosomal dominant pathogenic variants in the DNA methyltransferase DNMT3A gene. Typical TBRS clinical features are overgrowth, intellectual disability, and minor facial anomalies. However, since the syndrome was first described in 2014, a widening spectrum of abnormalities is being described. Cardiovascular abnormalities are less commonly reported but can be a major complication of the syndrome. This article describes a family of three individuals diagnosed with TBRS in adulthood and highlights the variable expression of cardiovascular features. A 34-year-old proband presented with progressive aortic dilatation, mitral valve (MV) regurgitation, left ventricular (LV) dilatation, and ventricular arrhythmias. The affected family members (mother and brother) were diagnosed with MV regurgitation, LV dilatation, and arrhythmias. Exome sequencing and computational protein analysis suggested that the novel familial DNMT3A mutation Ser775Tyr is located in the methyltransferase domain, however, distant from the active site or DNA-binding loops. Nevertheless, this bulky substitution may have a significant effect on DNMT3A protein structure, dynamics, and function. Analysis of peripheral blood cfDNA and transcriptome showed shortened mononucleosome fragments and altered gene expression in a number of genes related to cardiovascular health and of yet undescribed function, including several lncRNAs. This highlights the importance of epigenetic regulation by DNMT3A on cardiovascular system development and function. From the clinical perspective, we suggest that new patients diagnosed with congenital DNMT3A variants and TBRS require close examination and follow-up for aortic dilatation and valvular disease because these conditions can progress rapidly. Moreover, personalized treatments, based on the specific DNMT3A variants and the different pathways of their function loss, can be envisioned in the future.

An integrative framework to prioritize genes in more than 500 loci associated with body mass index

Obesity is a major risk factor for a myriad of diseases, affecting >600 million people worldwide. Genome-wide association studies (GWASs) have identified hundreds of genetic variants that influence body mass index (BMI), a commonly used metric to assess obesity risk. Most variants are non-coding and likely act through regulating genes nearby. Here, we apply multiple computational methods to prioritize the likely causal gene(s) within each of the 536 previously reported GWAS-identified BMI-associated loci. We performed summary-data-based Mendelian randomization (SMR), FINEMAP, DEPICT, MAGMA, transcriptome-wide association studies (TWASs), mutation significance cutoff (MSC), polygenic priority score (PoPS), and the nearest gene strategy. Results of each method were weighted based on their success in identifying genes known to be implicated in obesity, ranking all prioritized genes according to a confidence score (minimum: 0; max: 28). We identified 292 high-scoring genes (≥11) in 264 loci, including genes known to play a role in body weight regulation (e.g., DGKI, ANKRD26, MC4R, LEPR, BDNF, GIPR, AKT3, KAT8, MTOR) and genes related to comorbidities (e.g., FGFR1, ISL1, TFAP2B, PARK2, TCF7L2, GSK3B). For most of the high-scoring genes, however, we found limited or no evidence for a role in obesity, including the top-scoring gene BPTF. Many of the top-scoring genes seem to act through a neuronal regulation of body weight, whereas others affect peripheral pathways, including circadian rhythm, insulin secretion, and glucose and carbohydrate homeostasis. The characterization of these likely causal genes can increase our understanding of the underlying biology and offer avenues to develop therapeutics for weight loss.

Are Next-Generation Pathogenicity Predictors Applicable to Cancer?

Next-generation pathogenicity predictors are designed to identify pathogenic mutations in genetic disorders but are increasingly used to detect driver mutations in cancer. Despite this, their suitability for cancer is not fully established. Here we have assessed the effectiveness of next-generation pathogenicity predictors when applied to cancer by using a comprehensive experimental benchmark of cancer driver and neutral mutations. Our findings indicate that state-of-the-art methods AlphaMissense and VARITY demonstrate commendable performance despite generally underperforming compared to cancer-specific methods. This is notable considering that these methods do not explicitly incorporate cancer-related data in their training and have made concerted efforts to prevent data leakage from the human-curated training and test sets. Nevertheless, it should be mentioned that a significant limitation of using pathogenicity predictors for cancer arises from their inability to detect cancer potential driver mutations specific for a particular cancer type.

Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT)

Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.

Lagophthalmos-induced corneal perforation in a patient with congenital erythropoietic porphyria

Congenital erythropoietic porphyria (CEP) is a rare autosomal recessive disorder in which the activity of uroporphyrinogen III synthase (UROS) is decreased. This results in the accumulation of photoreactive porphyrinogens, primarily in the skin and bone marrow. We describe a case of a patient with CEP who initially presented with scarring and shortening of the anterior and posterior lid lamella, which led to the development of lagophthalmos. Vascularized hyperkeratotic plaques in both corneas were also present. Despite treatment with topical ocular surface lubricants, corneal perforation with iris and uvea prolapse developed and evisceration of the right eye under local anesthesia was performed. The presented case suggests that despite topical therapy, ocular complications may exacerbate requiring surgical intervention, especially in the presence of lagophthalmos.

Phenotypic and genetic analysis of children with unexplained neurodevelopmental delay and neurodevelopmental comorbidities in a Chinese cohort using trio-based whole-exome sequencing

BACKGROUND

Trio-based whole-exome sequencing (trio-WES) enables identification of pathogenic variants, including copy-number variants (CNVs), in children with unexplained neurodevelopmental delay (NDD) and neurodevelopmental comorbidities (NDCs), including autism spectrum disorder (ASD), epilepsy, and attention deficit hyperactivity disorder. Further phenotypic and genetic analysis on trio-WES-tested NDD-NDCs cases may help to identify key phenotypic factors related to higher diagnostic yield of using trio-WES and novel risk genes associated with NDCs in clinical settings.

METHODS

In this study, we retrospectively performed phenotypic analysis on 163 trio-WES-tested NDD-NDCs children to determine the phenotypic differences between genetically diagnosed and non-genetically diagnosed groups. Additionally, we conducted genetic analysis of ASD genes with the help of Simons Foundation for Autism Research Institute (SFARI) Gene database to identify novel possible ASD-risk genes underlying genetic NDD conditions.

RESULTS

Among these 163 patients, pathogenic variants were identified in 82 cases (82/163, 50.3%), including 20 cases with CNVs. By comparing phenotypic variables between genetically diagnosed group (82 cases) and non-genetically diagnosed group (81 cases) with multivariate binary logistic regression analysis, we revealed that NDD-NDCs cases presenting with severe-profound NDD [53/82 vs 17/81, adjusted-OR (95%CI): 4.865 (2.213 - 10.694), adjusted-P < 0.001] or having multiple NDCs [26/82 vs 8/81, adjusted-OR (95%CI): 3.731 (1.399 - 9.950), adjusted-P = 0.009] or accompanying ASD [64/82 vs 35/81, adjusted-OR (95%CI): 3.256 (1.479 - 7.168), adjusted-P = 0.003] and head circumference abnormality [33/82 vs 11/81, adjusted-OR (95%CI): 2.788 (1.148 - 6.774), adjusted-P = 0.024] were more likely to have a genetic diagnosis using trio-WES. Moreover, 37 genes with monogenetic variants were identified in 48 patients genetically diagnosed with NDD-ASD, and 15 dosage-sensitive genes were identified in 16 individuals with NDD-ASD carrying CNVs. Most of those genes had been proven to be ASD-related genes. However, some of them (9 genes) were not proven sufficiently to correlate with ASD. By literature review and constructing protein-protein interaction networks among these 9 candidate ASD-risk genes and 102 established ASD genes obtained from the SFARI Gene database, we identified CUL4B, KCNH1, and PLA2G6 as novel possible ASD-risk genes underlying genetic NDD conditions.

CONCLUSIONS

Trio-WES testing is recommended for patients with unexplained NDD-NDCs that have severe-profound NDD or multiple NDCs, particularly those with accompanying ASD and head circumference abnormality, as these independent factors may increase the likelihood of genetic diagnosis using trio-WES. Moreover, NDD patients with pathogenic variants in CUL4B, KCNH1 and PLA2G6 should be aware of potential risks of developing ASD during their disease courses.

A novel variant in the FLNB gene associated with spondylocarpotarsal synostosis syndrome

OBJECTIVES

Genetic disorders involved in skeleton system arise due to the disturbance in skeletal development, growth and homeostasis. Filamin B is an actin binding protein which is large dimeric protein which cross link actin cytoskeleton filaments into dynamic structure. A single nucleotide changes in the FLNB gene causes spondylocarpotarsal synostosis syndrome, a rare bone disorder due to which the fusion of carpels and tarsals synostosis occurred along with fused vertebrae. In the current study we investigated a family residing in north-western areas of Pakistan.

METHODS

The whole exome sequencing of proband was performed followed by Sanger sequencing of all family members of the subject to validate the variant segregation within the family. Bioinformatics tools were utilized to assess the pathogenicity of the variant.

RESULTS

Whole Exome Sequencing revealed a novel variant (NM_001457: c.209C>T and p.Pro70Leu) in the FLNB gene which was homozygous missense mutation in the FLNB gene. The variant was further validated and visualized by Sanger sequencing and protein structure studies respectively as mentioned before.

CONCLUSIONS

The findings have highlighted the importance of the molecular diagnosis in SCT (spondylocarpotarsal synostosis syndrome) for genetic risk counselling in consanguineous families.

The clinical utility and diagnostic implementation of human subject cell transdifferentiation followed by RNA sequencing

RNA sequencing (RNA-seq) has recently been used in translational research settings to facilitate diagnoses of Mendelian disorders. A significant obstacle for clinical laboratories in adopting RNA-seq is the low or absent expression of a significant number of disease-associated genes/transcripts in clinically accessible samples. As this is especially problematic in neurological diseases, we developed a clinical diagnostic approach that enhanced the detection and evaluation of tissue-specific genes/transcripts through fibroblast-to-neuron cell transdifferentiation. The approach is designed specifically to suit clinical implementation, emphasizing simplicity, cost effectiveness, turnaround time, and reproducibility. For clinical validation, we generated induced neurons (iNeurons) from 71 individuals with primary neurological phenotypes recruited to the Undiagnosed Diseases Network. The overall diagnostic yield was 25.4%. Over a quarter of the diagnostic findings benefited from transdifferentiation and could not be achieved by fibroblast RNA-seq alone. This iNeuron transcriptomic approach can be effectively integrated into diagnostic whole-transcriptome evaluation of individuals with genetic disorders.

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.

Lysosomal genes contribute to Parkinson's disease near agriculture with high intensity pesticide use

Parkinson's disease (PD), the second most common neurodegenerative disorder, develops sporadically, likely through a combination of polygenic and environmental factors. Previous studies associate pesticide exposure and genes involved in lysosomal function with PD risk. We evaluated the frequency of variants in lysosomal function genes among patients from the Parkinson's, Environment, and Genes (PEG) study with ambient pesticide exposure from agricultural sources. 757 PD patients, primarily of White European/non-Hispanic ancestry (75%), were screened for variants in 85 genes using a custom amplicon panel. Variant enrichment was calculated against the Genome Aggregation Database (gnomAD). Enriched exonic variants were prioritized by exposure to a cluster of pesticides used on cotton and severity of disease progression in a subset of 386 patients subdivided by race/ethnicity. Gene enrichment analysis identified 36 variants in 26 genes in PEG PD patients. Twelve of the identified genes (12/26, 46%) had multiple enriched variants and/or a single enriched variant present in multiple individuals, representing 61% (22/36) of the observed variation in the cohort. The majority of enriched variants (26/36, 72%) were found in genes contributing to lysosomal function, particularly autophagy, and were bioinformatically deemed functionally deleterious (31/36, 86%). We conclude that, in this study, variants in genes associated with lysosomal function, notably autophagy, were enriched in PD patients exposed to agricultural pesticides suggesting that altered lysosomal function may generate an underlying susceptibility for developing PD with pesticide exposure. Further study of gene-environment interactions targeting lysosomal function may improve understanding of PD risk in individuals exposed to pesticides.

Mutational spectrum of CFTR in cystic fibrosis patients with gastrointestinal and hepatobiliary manifestations

BACKGROUND

Cystic fibrosis (CF) is a rare and debilitating autosomal recessive disorder. It hampers the normal function of various organs and causes severe damage to the lungs, and digestive system leading to recurring pneumonia. Cf also affects reproductive health eventually may cause infertility. The disease manifests due to genetic aberrations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. This study aimed to screen for CFTR gene variants in Pakistani CF patients representing variable phenotypes.

METHODS

Clinical exome and Sanger sequencing were performed after clinical characterization of 25 suspected cases of CF (CF1-CF25). ACMG guidelines were followed to interpret the clinical significance of the identified variants.

RESULTS

Clinical investigations revealed common phenotypes such as pancreatic insufficiency, chest infections, chronic liver and lung diseases. Some patients also displayed symptoms like gastroesophageal reflux disease (GERD), neonatal cholestasis, acrodermatitis, diabetes mellitus, and abnormal malabsorptive stools. Genetic analysis of the 25 CF patients identified deleterious variants in the CFTR gene. Notably, 12% of patients showed compound heterozygous variants, while 88% had homozygous variants. The most prevalent variant was p. (Met1Thr or Met1?) at 24%, previously not reported in the Pakistani population. The second most common variant was p. (Phe508del) at 16%. Other variants, including p. (Leu218*), p. (Tyr569Asp), p. (Glu585Ter), and p. (Arg1162*) were also identified in the present study. Genetic analysis of one of the present patients showed a pathogenic variant in G6PD in addition to CFTR.

CONCLUSION

The study reports novel and reported variants in the CFTR gene in CF patients in Pakistani population having distinct phenotypes. It also emphasizes screening suspected Pakistani CF patients for the p. (Met1Thr) variant because of its increased observance and prevalence in the study. Moreover, the findings also signify searching for additional pathogenic variants in the genome of CF patients, which may modify the phenotypes. The findings contribute valuable information for the diagnosis, genetic counseling, and potential therapeutic strategies for CF patients in Pakistan.

Computational Analysis of Deleterious nsSNPs in INS Gene Associated with Permanent Neonatal Diabetes Mellitus

Insulin gene mutations affect the structure of insulin and are considered a leading cause of neonatal diabetes and permanent neonatal diabetes mellitus PNDM. These mutations can affect the production and secretion of insulin, resulting in inadequate insulin levels and subsequent hyperglycemia. Early discovery or prediction of PNDM can aid in better management and treatment. The current study identified potential deleterious non-synonymous single nucleotide polymorphisms nsSNPs in the INS gene. The analysis of the nsSNPs in the INS gene was conducted using bioinformatics tools by implementing computational algorithms including SIFT, PolyPhen2, SNAP2, SNPs & GO, PhD-SNP, MutPred2, I-Mutant, MuPro, and HOPE tools to investigate the prediction of the potential association between nsSNPs in the INS gene and PNDM. Three mutations, C96Y, P52R, and C96R, were shown to potentially reduce the stability and function of the INS protein. These mutants were subjected to MDSs for structural analysis. Results suggested that these three potential pathogenic mutations may affect the stability and functionality of the insulin protein encoded by the INS gene. Therefore, these changes may influence the development of PNDM. Further researches are required to fully understand the various effects of mutations in the INS gene on insulin synthesis and function. These data can aid in genetic testing for PNDM to evaluate its risk and create treatment and prevention strategies in personalized medicine.

Detection and characterization of copy number variation in three differentially-selected Nellore cattle populations

Introduction: Nellore cattle (Bos taurus indicus) is the main beef cattle breed raised in Brazil. This breed is well adapted to tropical conditions and, more recently, has experienced intensive genetic selection for multiple performance traits. Over the past 43 years, an experimental breeding program has been developed in the Institute of Animal Science (IZ, Sertaozinho, SP, Brazil), which resulted in three differentially-selected lines known as Nellore Control (NeC), Nellore Selection (NeS), and Nellore Traditional (NeT). The primary goal of this selection experiment was to determine the response to selection for yearling weight (YW) and residual feed intake (RFI) on Nellore cattle. The main objectives of this study were to: 1) identify copy number variation (CNVs) in Nellore cattle from three selection lines; 2) identify and characterize CNV regions (CNVR) on these three lines; and 3) perform functional enrichment analyses of the CNVR identified. Results: A total of 14,914 unique CNVs and 1,884 CNVRs were identified when considering all lines as a single population. The CNVRs were non-uniformly distributed across the chromosomes of the three selection lines included in the study. The NeT line had the highest number of CNVRs (n = 1,493), followed by the NeS (n = 823) and NeC (n = 482) lines. The CNVRs covered 23,449,890 bp (0.94%), 40,175,556 bp (1.61%), and 63,212,273 bp (2.54%) of the genome of the NeC, NeS, and NeT lines, respectively. Two CNVRs were commonly identified between the three lines, and six, two, and four exclusive regions were identified for NeC, NeS, and NeT, respectively. All the exclusive regions overlap with important genes, such as SMARCD3, SLC15A1, and MAPK1. Key biological processes associated with the candidate genes were identified, including pathways related to growth and metabolism. Conclusion: This study revealed large variability in CNVs and CNVRs across three Nellore lines differentially selected for YW and RFI. Gene annotation and gene ontology analyses of the exclusive CNVRs to each line revealed specific genes and biological processes involved in the expression of growth and feed efficiency traits. These findings contribute to the understanding of the genetic mechanisms underlying the phenotypic differences among the three Nellore selection lines.

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.

Burden of Mendelian disorders in a large Middle Eastern biobank

BACKGROUND

Genome sequencing of large biobanks from under-represented ancestries provides a valuable resource for the interrogation of Mendelian disease burden at world population level, complementing small-scale familial studies.

METHODS

Here, we interrogate 6045 whole genomes from Qatar-a Middle Eastern population with high consanguinity and understudied mutational burden-enrolled at the national Biobank and phenotyped for 58 clinically-relevant quantitative traits. We examine a curated set of 2648 Mendelian genes from 20 panels, annotating known and novel pathogenic variants and assessing their penetrance and impact on the measured traits.

RESULTS

We find that 62.5% of participants are carriers of at least 1 known pathogenic variant relating to recessive conditions, with homozygosity observed in 1 in 150 subjects (0.6%) for which Peninsular Arabs are particularly enriched versus other ancestries (5.8-fold). On average, 52.3 loss-of-function variants were found per genome, 6.5 of which affect a known Mendelian gene. Several variants annotated in ClinVar/HGMD as pathogenic appeared at intermediate frequencies in this cohort (1-3%), highlighting Arab founder effect, while others have exceedingly high frequencies (> 5%) prompting reconsideration as benign. Furthermore, cumulative gene burden analysis revealed 56 genes having gene carrier frequency > 1/50, including 5 ACMG Tier 3 panel genes which would be candidates for adding to newborn screening in the country. Additionally, leveraging 58 biobank traits, we systematically assess the impact of novel/rare variants on phenotypes and discover 39 candidate large-effect variants associating with extreme quantitative traits. Furthermore, through rare variant burden testing, we discover 13 genes with high mutational load, including 5 with impact on traits relevant to disease conditions, including metabolic disorder and type 2 diabetes, consistent with the high prevalence of these conditions in the region.

CONCLUSIONS

This study on the first phase of the growing Qatar Genome Program cohort provides a comprehensive resource from a Middle Eastern population to understand the global mutational burden in Mendelian genes and their impact on traits in seemingly healthy individuals in high consanguinity settings.

Truncating variants of the sterol recognition region of SHH cause hypertelorism phenotype rather than hypotelorism-holoprosencephaly

Sonic hedgehog signaling molecule (SHH) is a key molecule in the cilia-mediated signaling pathway and a critical morphogen in embryogenesis. The association between loss-of-function variants of SHH and holoprosencephaly is well established. In mice experiments, reduced or increased signaling of SHH have been shown to be associated with narrowing or excessive expansion of the facial midline, respectively. Herein, we report two unrelated patients with de novo truncating variants of SHH presenting with hypertelorism rather than hypotelorism. The first patient was a 13-year-old girl. Her facial features included hypertelorism, strabismus, telecanthus, malocclusion, frontal bossing, and wide widow's peak. She had borderline developmental delay and agenesis of the corpus callosum. She had a nonsense variant of SHH: Chr7(GRCh38):g.155802987C > T, NM_000193.4:c.1302G > A, p.(Trp434*). The second patient was a 25-year-old girl. Her facial features included hypertelorism and wide widow's peak. She had developmental delay and agenesis of the corpus callosum. She had a frameshift variant of SHH: Chr7(GRCh38):g.155803072_155803074delCGGinsT, NM_000193.4:c.1215_1217delCCGinsA, p.(Asp405Glufs*92). The hypertelorism phenotype contrasts sharply with the prototypical hypotelorism-holoprosencephaly phenotype associated with loss-of-function of SHH. We concluded that a subset of truncating variants of SHH could be associated with hypertelorism rather than hypotelorism.

Functional categorization of gene regulatory variants that cause Mendelian conditions

Much of our current understanding of rare human diseases is driven by coding genetic variants. However, non-coding genetic variants play a pivotal role in numerous rare human diseases, resulting in diverse functional impacts ranging from altered gene regulation, splicing, and/or transcript stability. With the increasing use of genome sequencing in clinical practice, it is paramount to have a clear framework for understanding how non-coding genetic variants cause disease. To this end, we have synthesized the literature on hundreds of non-coding genetic variants that cause rare Mendelian conditions via the disruption of gene regulatory patterns and propose a functional classification system. Specifically, we have adapted the functional classification framework used for coding variants (i.e., loss-of-function, gain-of-function, and dominant-negative) to account for features unique to non-coding gene regulatory variants. We identify that non-coding gene regulatory variants can be split into three distinct categories by functional impact: (1) non-modular loss-of-expression (LOE) variants; (2) modular loss-of-expression (mLOE) variants; and (3) gain-of-ectopic-expression (GOE) variants. Whereas LOE variants have a direct corollary with coding loss-of-function variants, mLOE and GOE variants represent disease mechanisms that are largely unique to non-coding variants. These functional classifications aim to provide a unified terminology for categorizing the functional impact of non-coding variants that disrupt gene regulatory patterns in Mendelian conditions.

CSF1R-related disorder: State of the art, challenges, and proposition of a new terminology

Recent developments in adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP) and other disorders due to CSF1R variants led to the emergence of symptomatic and prophylactic treatment options. The growing body of knowledge on genetics, pathomechanisms, clinical, and radiological features in patients harboring CSF1R variants challenges the current concepts and terminology to define the disorders, in addition to bringing up new questions on genotype-phenotype relationships. Therefore, this paper discusses the present complexities and challenges in the research on ALSP due to CSF1R variants. We illustrate our new concepts with two cases that are compound heterozygotes for CSF1R variants. Although their clinical phenotype resembles ALSP, the diagnosis of brain abnormalities, neurodegeneration, and dysosteosclerosis (BANDDOS) seems more appropriate based on their genotype. As the diagnostic classification dilemma cannot be resolved with currently used concepts and terminology on these disorders, we propose a new nomenclature of "CSF1R-related disorder" with subcategories of "early-onset (<18 years old) and late-onset (≥18 years old) forms". We highlight the heterogeneity of CSF1R variant carriers in age at onset, spectrum and severity of clinical presentation, and progression rate, even within the same family. We argue that multiple factors, including genetic architecture and environment, converge to result in an individual's disease phenotype.

Therapeutic strategies for aberrant splicing in cancer and genetic disorders

Accurate pre-mRNA splicing is essential for proper protein translation; however, aberrant splicing is commonly observed in the context of cancer and genetic disorders. Notably, in genetic diseases, these splicing abnormalities often play a pivotal role. Substantial challenges persist in accurately identifying and classifying disease-induced aberrant splicing, as well as in development of targeted therapeutic strategies. In this review, we examine prevalent forms of aberrant splicing and explore potential therapeutic approaches aimed at addressing these splicing-related diseases. This summary contributes to a deeper understanding of the complexities about aberrant splicing and provide a foundation for the development of effective therapeutic interventions in the field of genetic disorders and cancer.

Expanding the genetics and phenotypes of ocular congenital cranial dysinnervation disorders

Purpose

To identify genetic etiologies and genotype/phenotype associations for unsolved ocular congenital cranial dysinnervation disorders (oCCDDs).

Methods

We coupled phenotyping with exome or genome sequencing of 467 pedigrees with genetically unsolved oCCDDs, integrating analyses of pedigrees, human and animal model phenotypes, and de novo variants to identify rare candidate single nucleotide variants, insertion/deletions, and structural variants disrupting protein-coding regions. Prioritized variants were classified for pathogenicity and evaluated for genotype/phenotype correlations.

Results

Analyses elucidated phenotypic subgroups, identified pathogenic/likely pathogenic variant(s) in 43/467 probands (9.2%), and prioritized variants of uncertain significance in 70/467 additional probands (15.0%). These included known and novel variants in established oCCDD genes, genes associated with syndromes that sometimes include oCCDDs (e.g., MYH10, KIF21B, TGFBR2, TUBB6), genes that fit the syndromic component of the phenotype but had no prior oCCDD association (e.g., CDK13, TGFB2), genes with no reported association with oCCDDs or the syndromic phenotypes (e.g., TUBA4A, KIF5C, CTNNA1, KLB, FGF21), and genes associated with oCCDD phenocopies that had resulted in misdiagnoses.

Conclusion

This study suggests that unsolved oCCDDs are clinically and genetically heterogeneous disorders often overlapping other Mendelian conditions and nominates many candidates for future replication and functional studies.

When rare meets common: Treatable genetic diseases are enriched in the general psychiatric population

Mental illnesses are one of the biggest contributors to the global disease burden. Despite the increased recognition, diagnosis and ongoing research of mental health disorders, the etiology and underlying molecular mechanisms of these disorders are yet to be fully elucidated. Moreover, despite many treatment options available, a large subset of the psychiatric patient population is nonresponsive to standard medications and therapies. There has not been a comprehensive study to date examining the burden and impact of treatable genetic disorders (TGDs) that can present with neuropsychiatric features in psychiatric patient populations. In this study, we test the hypothesis that TGDs that present with psychiatric symptoms are more prevalent within psychiatric patient populations compared to the general population by performing targeted next-generation sequencing of 129 genes associated with 108 TGDs in a cohort of 2301 psychiatric patients. In total, 48 putative affected and 180 putative carriers for TGDs were identified, with known or likely pathogenic variants in 79 genes. Despite screening for only 108 genetic disorders, this study showed a two-fold (2.09%) enrichment for genetic disorders within the psychiatric population relative to the estimated 1% cumulative prevalence of all single gene disorders globally. This strongly suggests that the prevalence of these, and most likely all, genetic diseases is greatly underestimated in psychiatric populations. Increasing awareness and ensuring accurate diagnosis of TGDs will open new avenues to targeted treatment for a subset of psychiatric patients.

Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey

BACKGROUND

National and international amalgamation of genomic data offers opportunity for research and audit, including analyses enabling improved classification of variants of uncertain significance. Review of individual-level data from National Health Service (NHS) testing of cancer susceptibility genes (2002-2023) submitted to the National Disease Registration Service revealed heterogeneity across participating laboratories regarding (1) the structure, quality and completeness of submitted data, and (2) the ease with which that data could be assembled locally for submission.

METHODS

In May 2023, we undertook a closed online survey of 51 clinical scientists who provided consensus responses representing all 17 of 17 NHS molecular genetic laboratories in England and Wales which undertake NHS diagnostic analyses of cancer susceptibility genes. The survey included 18 questions relating to 'next-generation sequencing workflow' (11), 'variant classification' (3) and 'phenotypical context' (4).

RESULTS

Widely differing processes were reported for transfer of variant data into their local LIMS (Laboratory Information Management System), for the formatting in which the variants are stored in the LIMS and which classes of variants are retained in the local LIMS. Differing local provisions and workflow for variant classifications were also reported, including the resources provided and the mechanisms by which classifications are stored.

CONCLUSION

The survey responses illustrate heterogeneous laboratory workflow for preparation of genomic variant data from local LIMS for centralised submission. Workflow is often labour-intensive and inefficient, involving multiple manual steps which introduce opportunities for error. These survey findings and adoption of the concomitant recommendations may support improvement in laboratory dataflows, better facilitating submission of data for central amalgamation.

Heterozygous COL17A1 variants are a frequent cause of amelogenesis imperfecta

BACKGROUND

Collagen XVII is most typically associated with human disease when biallelic COL17A1 variants (>230) cause junctional epidermolysis bullosa (JEB), a rare, genetically heterogeneous, mucocutaneous blistering disease with amelogenesis imperfecta (AI), a developmental enamel defect. Despite recognition that heterozygous carriers in JEB families can have AI, and that heterozygous COL17A1 variants also cause dominant corneal epithelial recurrent erosion dystrophy (ERED), the importance of heterozygous COL17A1 variants causing dominant non-syndromic AI is not widely recognised.

METHODS

Probands from an AI cohort were screened by single molecule molecular inversion probes or targeted hybridisation capture (both a custom panel and whole exome sequencing) for COL17A1 variants. Patient phenotypes were assessed by clinical examination and analyses of affected teeth.

RESULTS

Nineteen unrelated probands with isolated AI (no co-segregating features) had 17 heterozygous, potentially pathogenic COL17A1 variants, including missense, premature termination codons, frameshift and splice site variants in both the endo-domains and the ecto-domains of the protein. The AI phenotype was consistent with enamel of near normal thickness and variable focal hypoplasia with surface irregularities including pitting.

CONCLUSION

These results indicate that COL17A1 variants are a frequent cause of dominantly inherited non-syndromic AI. Comparison of variants implicated in AI and JEB identifies similarities in type and distribution, with five identified in both conditions, one of which may also cause ERED. Increased availability of genetic testing means that more individuals will receive reports of heterozygous COL17A1 variants. We propose that patients with isolated AI or ERED, due to COL17A1 variants, should be considered as potential carriers for JEB and counselled accordingly, reflecting the importance of multidisciplinary care.

Pre-clinical evaluation of the efficacy and safety of human induced pluripotent stem cell-derived cardiomyocyte patch

BACKGROUND

Cell- or tissue-based regenerative therapy is an attractive approach to treat heart failure. A tissue patch that can safely and effectively repair damaged heart muscle would greatly improve outcomes for patients with heart failure. In this study, we conducted a preclinical proof-of-concept analysis of the efficacy and safety of clinical-grade human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) patches.

METHODS

A clinical-grade hiPSC line was established using peripheral blood mononuclear cells from a healthy volunteer that was homozygous for human leukocyte antigens. The hiPSCs were differentiated into cardiomyocytes. The obtained hiPSC-CMs were cultured on temperature-responsive culture dishes for patch fabrication. The cellular characteristics, safety, and efficacy of hiPSCs, hiPSC-CMs, and hiPSC-CM patches were analyzed.

RESULTS

The hiPSC-CMs expressed cardiomyocyte-specific genes and proteins, and electrophysiological analyses revealed that hiPSC-CMs exhibit similar properties to human primary myocardial cells. In vitro and in vivo safety studies indicated that tumorigenic cells were absent. Moreover, whole-genome and exome sequencing revealed no genomic mutations. General toxicity tests also showed no adverse events posttransplantation. A porcine model of myocardial infarction demonstrated significantly improved cardiac function and angiogenesis in response to cytokine secretion from hiPSC-CM patches. No lethal arrhythmias were observed.

CONCLUSIONS

hiPSC-CM patches are promising for future translational research and may have clinical application potential for the treatment of heart failure.

PdmIRD: missense variants pathogenicity prediction for inherited retinal diseases in a disease-specific manner

Accurate discrimination of pathogenic and nonpathogenic variation remains an enormous challenge in clinical genetic testing of inherited retinal diseases (IRDs) patients. Computational methods for predicting variant pathogenicity are the main solutions for this dilemma. The majority of the state-of-the-art variant pathogenicity prediction tools disregard the differences in characteristics among different genes and treat all types of mutations equally. Since missense variants are the most common type of variation in the coding region of the human genome, we developed a novel missense mutation pathogenicity prediction tool, named Prediction of Deleterious Missense Mutation for IRDs (PdmIRD) in this study. PdmIRD was tailored for IRDs-related genes and constructed with the conditional random forest model. Population frequencies and a newly available prediction tool were incorporated into PdmIRD to improve the performance of the model. The evaluation of PdmIRD demonstrated its superior performance over nonspecific tools (areas under the curves, 0.984 and 0.910) and an existing eye abnormalities-specific tool (areas under the curves, 0.975 and 0.891). We also demonstrated the submodel that used a smaller gene panel further slightly improved performance. Our study provides evidence that a disease-specific model can enhance the prediction of missense mutation pathogenicity, especially when new and important features are considered. Additionally, this study provides guidance for exploring the characteristics and functions of the mutated proteins in a greater number of Mendelian disorders.

Meta-analysis of 46,000 germline de novo mutations linked to human inherited disease

BACKGROUND

De novo mutations (DNMs) are variants that occur anew in the offspring of noncarrier parents. They are not inherited from either parent but rather result from endogenous mutational processes involving errors of DNA repair/replication. These spontaneous errors play a significant role in the causation of genetic disorders, and their importance in the context of molecular diagnostic medicine has become steadily more apparent as more DNMs have been reported in the literature. In this study, we examined 46,489 disease-associated DNMs annotated by the Human Gene Mutation Database (HGMD) to ascertain their distribution across gene and disease categories.

RESULTS

Most disease-associated DNMs reported to date are found to be associated with developmental and psychiatric disorders, a reflection of the focus of sequencing efforts over the last decade. Of the 13,277 human genes in which DNMs have so far been found, the top-10 genes with the highest proportions of DNM relative to gene size were H3-3 A, DDX3X, CSNK2B, PURA, ZC4H2, STXBP1, SCN1A, SATB2, H3-3B and TUBA1A. The distribution of CADD and REVEL scores for both disease-associated DNMs and those mutations not reported to be de novo revealed a trend towards higher deleteriousness for DNMs, consistent with the likely lower selection pressure impacting them. This contrasts with the non-DNMs, which are presumed to have been subject to continuous negative selection over multiple generations.

CONCLUSION

This meta-analysis provides important information on the occurrence and distribution of disease-associated DNMs in association with heritable disease and should make a significant contribution to our understanding of this major type of mutation.

Novel ancestry-specific primary open-angle glaucoma loci and shared biology with vascular mechanisms and cell proliferation

Primary open-angle glaucoma (POAG), a leading cause of irreversible blindness globally, shows disparity in prevalence and manifestations across ancestries. We perform meta-analysis across 15 biobanks (of the Global Biobank Meta-analysis Initiative) (n = 1,487,441: cases = 26,848) and merge with previous multi-ancestry studies, with the combined dataset representing the largest and most diverse POAG study to date (n = 1,478,037: cases = 46,325) and identify 17 novel significant loci, 5 of which were ancestry specific. Gene-enrichment and transcriptome-wide association analyses implicate vascular and cancer genes, a fifth of which are primary ciliary related. We perform an extensive statistical analysis of SIX6 and CDKN2B-AS1 loci in human GTEx data and across large electronic health records showing interaction between SIX6 gene and causal variants in the chr9p21.3 locus, with expression effect on CDKN2A/B. Our results suggest that some POAG risk variants may be ancestry specific, sex specific, or both, and support the contribution of genes involved in programmed cell death in POAG pathogenesis.

Novel variants ensued genomic imprinting in familial central precocious puberty

INTRODUCTION

Central precocious puberty (CPP) is characterized by the early onset of puberty and is associated with the critical processes involved in the pubertal switch. The puberty-related gene pool in the human genome is considerably large though few have been described in CPP. Within those genes, the genomic imprinting features of the MKRN3 and DLK1 genes add additional complexity to the understanding of the pathologic pathways. This study aimed to investigate the molecular etiology in the CPP cohort.

METHODS

Eighteen familial CPP cases were investigated by Sanger sequencing for five CPP-related genes; DLK1, KISS1, KISS1R, MKRN3, and PROKR2. Segregation analysis was performed in all patients with pathogenic variants. Using an ELISA test, the functional pathogenicity of novel variants was also investigated in conjunction with serum delta-like 1 homolog (DLK1) concentrations.

RESULTS

In three probands, a known variant in the MKRN3 gene (c.982C>T/p.(Arg328Cys)) and two novel variants in the DLK1 gene (c.357C>G/p.(Tyr119Ter) and c.67+78C>T) were identified. All three were inherited from the paternal allele. The individuals carrying the DLK1 variants had low detectable DLK1 levels in their serum.

CONCLUSIONS

The frequencies were 5.5% (1/18) for MKRN3 11% (2/18) for DLK1, and none for either KISS1, KISS1R, and PROKR2. Low serum DLK1 levels in affected individuals supported the relationship between here described novel DLK1 gene variants with CPP. Nonsense nature of c.357C>G/p.(Tyr119Ter) and an alteration in the evolutionarily conserved nucleotide c.67+78C>T suggested the disruptive nature of the variant's compatibility with CPP.

PICOTEES: a privacy-preserving online service of phenotype exploration for genetic-diagnostic variants from Chinese children cohorts

The growth in biomedical data resources has raised potential privacy concerns and risks of genetic information leakage. For instance, exome sequencing aids clinical decisions by comparing data through web services, but it requires significant trust between users and providers. To alleviate privacy concerns, the most commonly used strategy is to anonymize sensitive data. Unfortunately, studies have shown that anonymization is insufficient to protect against reidentification attacks. Recently, privacy-preserving technologies have been applied to preserve application utility while protecting the privacy of biomedical data. We present the PICOTEES framework, a privacy-preserving online service of phenotype exploration for genetic-diagnostic variants (https://birthdefectlab.cn:3000/). PICOTEES enables privacy-preserving queries of the phenotype spectrum for a single variant by utilizing trusted execution environment technology, which can protect the privacy of the user's query information, backend models, and data, as well as the final results. We demonstrate the utility and performance of PICOTEES by exploring a bioinformatics dataset. The dataset is from a cohort containing 20,909 genetic testing patients with 3,152,508 variants from the Children's Hospital of Fudan University in China, dominated by the Chinese Han population (>99.9%). Our query results yield a large number of unreported diagnostic variants and previously reported pathogenicity.

Next-generation sequencing and bioinformatics in rare movement disorders

The ability to sequence entire exomes and genomes has revolutionized molecular testing in rare movement disorders, and genomic sequencing is becoming an integral part of routine diagnostic workflows for these heterogeneous conditions. However, interpretation of the extensive genomic variant information that is being generated presents substantial challenges. In this Perspective, we outline multidimensional strategies for genetic diagnosis in patients with rare movement disorders. We examine bioinformatics tools and computational metrics that have been developed to facilitate accurate prioritization of disease-causing variants. Additionally, we highlight community-driven data-sharing and case-matchmaking platforms, which are designed to foster the discovery of new genotype-phenotype relationships. Finally, we consider how multiomic data integration might optimize diagnostic success by combining genomic, epigenetic, transcriptomic and/or proteomic profiling to enable a more holistic evaluation of variant effects. Together, the approaches that we discuss offer pathways to the improved understanding of the genetic basis of rare movement disorders.

Structurally-informed human interactome reveals proteome-wide perturbations by disease mutations

Human genome sequencing studies have identified numerous loci associated with complex diseases. However, translating human genetic and genomic findings to disease pathobiology and therapeutic discovery remains a major challenge at multiscale interactome network levels. Here, we present a deep-learning-based ensemble framework, termed PIONEER (Protein-protein InteractiOn iNtErfacE pRediction), that accurately predicts protein binding partner-specific interfaces for all known protein interactions in humans and seven other common model organisms, generating comprehensive structurally-informed protein interactomes. We demonstrate that PIONEER outperforms existing state-of-the-art methods. We further systematically validated PIONEER predictions experimentally through generating 2,395 mutations and testing their impact on 6,754 mutation-interaction pairs, confirming the high quality and validity of PIONEER predictions. We show that disease-associated mutations are enriched in PIONEER-predicted protein-protein interfaces after mapping mutations from ~60,000 germline exomes and ~36,000 somatic genomes. We identify 586 significant protein-protein interactions (PPIs) enriched with PIONEER-predicted interface somatic mutations (termed oncoPPIs) from pan-cancer analysis of ~11,000 tumor whole-exomes across 33 cancer types. We show that PIONEER-predicted oncoPPIs are significantly associated with patient survival and drug responses from both cancer cell lines and patient-derived xenograft mouse models. We identify a landscape of PPI-perturbing tumor alleles upon ubiquitination by E3 ligases, and we experimentally validate the tumorigenic KEAP1-NRF2 interface mutation p.Thr80Lys in non-small cell lung cancer. We show that PIONEER-predicted PPI-perturbing alleles alter protein abundance and correlates with drug responses and patient survival in colon and uterine cancers as demonstrated by proteogenomic data from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium. PIONEER, implemented as both a web server platform and a software package, identifies functional consequences of disease-associated alleles and offers a deep learning tool for precision medicine at multiscale interactome network levels.

Special electromyographic features in a child with paramyotonia congenita: A case report and review of literature

BACKGROUND

Paramyotonia congenita (PMC) stands as a rare sodium channelopaty of skeletal muscle, initially identified by Eulenburg. The identification of PMC often relies on electromyography (EMG), a diagnostic technique. The child's needle EMG unveiled trains of myotonic discharges with notably giant amplitudes, alongside irregular wave trains of myotonic discharges. This distinctive observation had not surfaced in earlier studies.

CASE SUMMARY

We report the case of a 3-year-old female child with PMC, who exhibited laryngeal stridor, muffled speech, myotonia from birth. Cold, exposure to cool water, crying, and physical activity exacerbated the myotonia, which was relieved in warmth, yet never normalized. Percussion myotonia was observable in bilateral biceps. Myotonia symptoms remained unchanged after potassium-rich food consumption like bananas. Hyperkalemic periodic paralysis was excluded. Cranial magnetic resonance imaging yielded normal results. Blood potassium remained within normal range, while creatine kinase showed slight elevation. Exome-wide genetic testing pinpointed a heterozygous mutation on chromosome SCN4A: c.3917G>A (p.G1306E). After a six-month mexiletine regimen, symptoms alleviated.

CONCLUSION

In this case revealed the two types of myotonic discharges, and had not been documented in other studies. We underscore two distinctive features: Giant-amplitude potentials and irregular waves.

Review of Computational Methods and Database Sources for Predicting the Effects of Coding Frameshift Small Insertion and Deletion Variations

Genetic variations (including substitutions, insertions, and deletions) exert a profound influence on DNA sequences. These variations are systematically classified as synonymous, nonsynonymous, and nonsense, each manifesting distinct effects on proteins. The implementation of high-throughput sequencing has significantly augmented our comprehension of the intricate interplay between gene variations and protein structure and function, as well as their ramifications in the context of diseases. Frameshift variations, particularly small insertions and deletions (indels), disrupt protein coding and are instrumental in disease pathogenesis. This review presents a succinct review of computational methods, databases, current challenges, and future directions in predicting the consequences of coding frameshift small indels variations. We analyzed the predictive efficacy, reliability, and utilization of computational methods and variant account, reliability, and utilization of database. Besides, we also compared the prediction methodologies on GOF/LOF pathogenic variation data. Addressing the challenges pertaining to prediction accuracy and cross-species generalizability, nascent technologies such as AI and deep learning harbor immense potential to enhance predictive capabilities. The importance of interdisciplinary research and collaboration cannot be overstated for devising effective diagnosis, treatment, and prevention strategies concerning diseases associated with coding frameshift indels variations.

Neurofibromatosis type 1: Clinical characteristics and mutation spectrum in a North Indian cohort

Background

Neurofibromatosis type 1 (NF1) is a unique, highly penetrant neuro-cutaneous disorder with a wide range of manifestations. Though the clinical diagnosis of NF1 is straight forward, there can be other disorders which mimic NF1, especially its cutaneous features. Here we describe the clinical and mutation spectrum of a series of individuals whose primary diagnosis was NF1 or NF1 related disorders.

Methods

We have screened 29 unrelated individuals who fulfilled the clinical criteria of NF1. Whole exome sequencing (WES) was done in all individuals except one with suspected microdeletion syndrome with NF1 in whom Cytogenetic microarray (CMA) was done.

Results

Out of 29 suspected patients, 25 had germline pathogenic/likely pathogenic variants involving NF1 gene. Five novel and 20 known variants in coding and non-coding regions were identified, among them 7 variants were deletions (28%), 7 nonsense (28%), 3 splice-site (12%), 4 missense (16%), 2 duplications (8%) and 2 (8%) were contiguous deletions. In those where NF1 variants were not detected, 3 had neurofibromatosis type 2 (NF2) and 1 rare autosomal recessive form of Elher Danlos syndrome.

Conclusion

We hereby present the wide range of manifestations in different age groups and the mutation spectrum ranging from small scale variants to contiguous gene deletion syndromes involving NF1 gene. We highlight the usefulness of molecular testing and its importance in tumor surveillance and genetic counseling in this disorder.

MAGPIE: accurate pathogenic prediction for multiple variant types using machine learning approach

Identifying pathogenic variants from the vast majority of nucleotide variation remains a challenge. We present a method named Multimodal Annotation Generated Pathogenic Impact Evaluator (MAGPIE) that predicts the pathogenicity of multi-type variants. MAGPIE uses the ClinVar dataset for training and demonstrates superior performance in both the independent test set and multiple orthogonal validation datasets, accurately predicting variant pathogenicity. Notably, MAGPIE performs best in predicting the pathogenicity of rare variants and highly imbalanced datasets. Overall, results underline the robustness of MAGPIE as a valuable tool for predicting pathogenicity in various types of human genome variations. MAGPIE is available at https://github.com/shenlab-genomics/magpie .

Mechanochemical consequences of myopathy-linked mutations in Tpm2.2 on striated muscle contractility

Tropomyosin (Tpm) is an actin-binding protein central to muscle contraction regulation. The Tpm sequence consists of periodic repeats corresponding to seven actin-binding sites, further divided in two functionally distinct halves. To clarify the importance of the first and second halves of the actin-binding periods in regulating the interaction of myosin with actin, we introduced hypercontractile mutations D20H, E181K located in the N-terminal halves of periods 1 and 5 and hypocontractile mutations E41K, N202K located in the C-terminal halves of periods 1 and 5 of the skeletal muscle Tpm isoform Tpm2.2. Wild-type and mutant Tpms displayed similar actin-binding properties, however, as revealed by FRET experiments, the hypercontractile mutations affected the binding geometry and orientation of Tpm2.2 on actin, causing a stimulation of myosin motor performance. Contrary, the hypocontractile mutations led to an inhibition of both, actin activation of the myosin ATPase and motor activity, that was more pronounced than with wild-type Tpm2.2. Single ATP turnover kinetic experiments indicate that the introduced mutations have opposite effects on product release kinetics. While the hypercontractile Tpm2.2 mutants accelerated product release, the hypocontractile mutants decelerated product release from myosin, thus having either an activating or inhibitory influence on myosin motor performance, which agrees with the muscle disease phenotypes caused by these mutations.

Computational analysis and molecular dynamics simulation of high-risk single nucleotide polymorphisms of the ADAM10 gene

Polymorphisms of the disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) are linked to pathophysiological changes in lung inflammation, cancer, Alzheimer's disease (AD), encephalopathy, liver fibrosis, and cardiovascular diseases. In this study, we predicted the pathogenicity of ADAM10 non-synonymous single nucleotide polymorphisms (nsSNPs) in a wide array of mutation analyzing bioinformatics tools. We retrieved 423 nsSNPs from dbSNP-NCBI for the analysis, and 13 were predicted deleterious by each of the ten tools: SIFT, PROVEAN, CONDEL, PANTHER-PSEP, SNAP2, SuSPect, PolyPhen-2, Meta-SNP, Mutation Assessor and Predict-SNP. Further assessment of amino acid sequences, homology models, conservation profiles, and inter-atomic interactions identified C222G, G361E and C639Y as the most pathogenic mutations. We validated this prediction through structural stability analysis using DUET, I-Mutant Suite, SNPeffect and Dynamut. Molecular dynamics simulations and principal component analysis also indicated considerable instability of the C222G, G361E and C639Y variants. Therefore, these ADAM10 nsSNPs could be candidates for diagnostic genetic screening and therapeutic molecular targeting.Communicated by Ramaswamy H. Sarma.

Missed diagnosis of Fabry disease: should we screen patients with multiple sclerosis?

INTRODUCTION

Fabry disease (FD) can be undiagnosed in the context of multiple sclerosis (MS) due to similar clinical and paraclinical features. Our study aimed to determine the prevalence (and the necessity of screening) of FD among patients with possible or definite MS.

METHODS

In this prospective monocentric observational study, we included consecutive patients enrolled between May 2017 and May 2019 after the first clinical event suggestive of MS. All patients underwent FD screening using dried blood spots in a stepwise manner combining genetic and enzyme testing. Patients were followed until May 2022.

RESULTS

We included 160 patients (73.1% female, mean age 33.9 years). The 2017 revised McDonald's criteria for definite MS were fulfilled by 74 (46.3%) patients at the time of study recruitment and 89 (55.6%) patients after 3-5 years of follow-up. None of the patients had a pathogenic GLA variant, and four (2.5%) had a variant of unknown significance (p.A143T, p.S126G, 2 × p.D313Y). In two of these patients, the intrathecal synthesis of oligoclonal bands was absent, and none had hyperproteinorachia or pleocytosis in cerebrospinal fluid. Detailed examination of FD organ manifestations revealed only discrete ocular and kidney involvement in two patients.

CONCLUSION

The prevalence of FD in the population of suspected or definite MS patients does not appear to be high. Our results do not support routine FD screening in all patients with a possible diagnosis of MS, but there is an urgent need to search for red flags and include FD in the differential diagnosis of MS.

Plasma-derived human factor X concentrate for the treatment of patients with hereditary factor X deficiency

INTRODUCTION

Hereditary factor X (FX) deficiency (HFXD) is an autosomal recessive rare bleeding disorder that leads to defects in the FX protein. Depending on the degree of deficiency, patients may be at risk of life-threatening bleeding episodes. Historical treatments for FX deficiency include prothrombin complex concentrates, which can increase the risk of thrombosis, and fresh frozen plasma, which can cause volume overload and transfusion reactions. Plasma-derived FX (pdFX), a single-factor, high-purity, high-potency human FX treatment, was approved in 2015 in the United States and in 2016 in Europe for on-demand treatment and prophylaxis of bleeding episodes and perioperative management of patients with HFXD.

METHODS

Five studies that examined the use of pdFX in patients with mild (plasma FX activity [FX:C] ≥5 IU/dL), moderate (FX:C ≥1 and <5 IU/dL), or severe (FX:C < 1 IU/dL) HFXD were reviewed: TEN01, TEN02 and TEN03 were prospective, open-label, multicentre, nonrandomised studies, and TEN05 and TEN06 were multicentre retrospective studies.

RESULTS

When used as an on-demand treatment, pdFX was judged by investigators to be successful in treating 41/42 (97.6%), 2/3 (66.6%) and 79/79 (100%) bleeds in TEN01, TEN02 and TEN05, respectively. When used prophylactically, pdFX was judged 'excellent' for the prevention of bleeds in nine (100%) and eight (100%) patients in TEN02 and TEN05, respectively. Perioperative treatment and pharmacokinetics were also assessed. pdFX was safe and well tolerated.

CONCLUSIONS

Together, these studies support the use of pdFX for on-demand treatment of bleeding, routine prophylaxis, and perioperative management of bleeding in patients with HFXD.

Cellular development and evolution of the mammalian cerebellum

The expansion of the neocortex, a hallmark of mammalian evolution1,2, was accompanied by an increase in cerebellar neuron numbers3. However, little is known about the evolution of the cellular programmes underlying the development of the cerebellum in mammals. In this study we generated single-nucleus RNA-sequencing data for around 400,000 cells to trace the development of the cerebellum from early neurogenesis to adulthood in human, mouse and the marsupial opossum. We established a consensus classification of the cellular diversity in the developing mammalian cerebellum and validated it by spatial mapping in the fetal human cerebellum. Our cross-species analyses revealed largely conserved developmental dynamics of cell-type generation, except for Purkinje cells, for which we observed an expansion of early-born subtypes in the human lineage. Global transcriptome profiles, conserved cell-state markers and gene-expression trajectories across neuronal differentiation show that cerebellar cell-type-defining programmes have been overall preserved for at least 160 million years. However, we also identified many orthologous genes that gained or lost expression in cerebellar neural cell types in one of the species or evolved new expression trajectories during neuronal differentiation, indicating widespread gene repurposing at the cell-type level. In sum, our study unveils shared and lineage-specific gene-expression programmes governing the development of cerebellar cells and expands our understanding of mammalian brain evolution.

A c.1775C > T Point Mutation of Sodium Channel Alfa Subunit Gene (SCN4A) in a Three-Generation Sardinian Family with Sodium Channel Myotonia

Background

The nondystrophic myotonias are rare muscle hyperexcitability disorders caused by gain-of-function mutations in the SCN4A gene or loss-of-function mutations in the CLCN1 gene. Clinically, they are characterized by myotonia, defined as delayed muscle relaxation after voluntary contraction, which leads to symptoms of muscle stiffness, pain, fatigue, and weakness. Diagnosis is based on history and examination findings, the presence of electrical myotonia on electromyography, and genetic confirmation.

Methods

Next-generation sequencing including the CLCN1 and SCN4A genes was performed in patients with clinical neuromuscular disorders. Electromyography, Short Exercise Test, in vivo and in vitro electrophysiology, site-directed mutagenesis and heterologous expression were collected.

Results

A heterozygous point mutation (c.1775C > T, p.Thr592Ile) of muscle voltage-gated sodium channel α subunit gene (SCN4A) has been identified in five female patients over three generations, in a family with non-dystrophic myotonia. The muscle stiffness and myotonia involve mainly the face and hands, but also affect walking and running, appearing early after birth and presenting a clear cold sensitivity. Very hot temperatures, menstruation and pregnancy also exacerbate the symptoms; muscle pain and a warm-up phenomenon are variable features. Neither paralytic attacks nor post-exercise weakness has been reported. Muscle hypertrophy with cramp-like pain and increased stiffness developed during pregnancy. The symptoms were controlled with both mexiletine and acetazolamide. The Short Exercise Test after muscle cooling revealed two different patterns, with moderate absolute changes of compound muscle action potential amplitude.

Conclusions

The p.Thr592Ile mutation in the SCN4A gene identified in this Sardinian family was responsible of clinical phenotype of myotonia.

Beyond the kidney biopsy: genomic approach to undetermined kidney diseases

Background

According to data from large national registries, almost 20%-25% of patients with end-stage kidney disease have an undetermined kidney disease (UKD). Recent data have shown that monogenic disease-causing variants are under-diagnosed. We performed exome sequencing (ES) on UKD patients in our center to improve the diagnosis rate.

Methods

ES was proposed in routine practice for patients with UKD including kidney biopsy from January 2019 to December 2021. Mutations were detected using a targeted bioinformatic customized kidney gene panel (675 genes). The pathogenicity was assessed using American College of Medical Genetics guidelines.

Results

We included 230 adult patients, median age 47.5 years. Consanguinity was reported by 25 patients. A family history of kidney disease was documented in 115 patients (50%). Kidney biopsies were either inconclusive in 69 patients (30.1%) or impossible in 71 (30.9%). We detected 28 monogenic renal disorders in 75 (32.6%) patients. Collagenopathies was the most common genetic kidney diagnosis (46.7%), with COL4A3 and COL4A4 accounting for 80% of these diagnoses. Tubulopathies (16%) and ciliopathies (14.7%) yielded, respectively, the second and third genetic kidney diagnosis category and UMOD-associated nephropathy as the main genetic findings for tubulopathies (7/11). Ten of the 22 patients having ES "first" eventually received a positive diagnosis, thereby avoiding 11 biopsies. Among the 44 patients with glomerular, tubulo-interstitial or vascular nephropathy, 13 (29.5%) were phenocopies. The diagnostic yield of ES was higher in female patients (P = .02) and in patients with a family history of kidney disease (P < .0001), reaching 56.8% when the patient had both first- and second-degree family history of renal disease.

Conclusion

Genetic diagnosis has provided new clinical insights by clarifying or reclassifying kidney disease etiology in over a third of UKD patients. Exome "first" may have a significant positive diagnostic yield, thus avoiding invasive kidney biopsy; moreover, the diagnostic yield remains elevated even when biopsy is impossible or inconclusive. ES provides a clinical benefit for routine nephrological healthcare in patients with UKD.

Induction of Translational Readthrough on Protein Tyrosine Phosphatases Targeted by Premature Termination Codon Mutations in Human Disease

Nonsense mutations generating premature termination codons (PTCs) in various genes are frequently associated with somatic cancer and hereditary human diseases since PTCs commonly generate truncated proteins with defective or altered function. Induced translational readthrough during protein biosynthesis facilitates the incorporation of an amino acid at the position of a PTC, allowing the synthesis of a complete protein. This may evade the pathological effect of the PTC mutation and provide new therapeutic opportunities. Several protein tyrosine phosphatases (PTPs) genes are targeted by PTC in human disease, the tumor suppressor PTEN being the more prominent paradigm. Here, using PTEN and laforin as examples, two PTPs from the dual-specificity phosphatase subfamily, we describe methodologies to analyze in silico the distribution and frequency of pathogenic PTC in PTP genes. We also summarize laboratory protocols and technical notes to study the induced translational readthrough reconstitution of the synthesis of PTP targeted by PTC in association with disease in cellular models.

INF2 and ROBO2 gene mutation in an Indian family with end stage renal failure and follow-up of renal transplantation

BACKGROUND

Accurate genetic diagnosis of end-stage renal disease patients with a family history of renal dysfunction is very essential. It not only helps in proper prognosis, but becomes crucial in designating donor for live related renal transplant. We here present a case of family with deleterious mutations in INF2 and ROBO2 and its importance of genetic testing before preparing for kidney transplantation.

CASE PRESENTATION

We report the case of a 29-year-female with end-stage renal disease and rapidly progressive renal failure. Mutational analysis revealed an Autosomal Dominant inheritance pattern and mutation in exon 4 of the INF2 gene (p. Thr215Ser) and exon 26 of the ROBO2 gene (p. Arg1371Cys). Her mother was diagnosed for CKD stage 4 with creatinine level of 4.3 mg/dL. Genetic variants (INF2 and ROBO2) identified in proband were tested in her sisters and mother. Her elder sister was positive for both heterozygous variants (INF2 and ROBO2). Her mother was positive for mutation in INF2 gene, and her donor elder sister did not showed mutation in INF2 gene and had mutation in ROBO2 gene without any clinical symptoms.

CONCLUSION

This case report emphasize that familial genetic screening has allowed us in allocating the donor selection in family where family member had history of genetic defect of Chronic Kidney Disease. Information of the causative renal disorder is extremely valuable for risk-assessment and planning of kidney transplantation.

Benchmarking splice variant prediction algorithms using massively parallel splicing assays

BACKGROUND

Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucleotides remains difficult. Computational predictors are often discordant, compounding the challenge of variant interpretation. Because they are primarily validated using clinical variant sets heavily biased to known canonical splice site mutations, it remains unclear how well their performance generalizes.

RESULTS

We benchmark eight widely used splicing effect prediction algorithms, leveraging massively parallel splicing assays (MPSAs) as a source of experimentally determined ground-truth. MPSAs simultaneously assay many variants to nominate candidate SDVs. We compare experimentally measured splicing outcomes with bioinformatic predictions for 3,616 variants in five genes. Algorithms' concordance with MPSA measurements, and with each other, is lower for exonic than intronic variants, underscoring the difficulty of identifying missense or synonymous SDVs. Deep learning-based predictors trained on gene model annotations achieve the best overall performance at distinguishing disruptive and neutral variants, and controlling for overall call rate genome-wide, SpliceAI and Pangolin have superior sensitivity. Finally, our results highlight two practical considerations when scoring variants genome-wide: finding an optimal score cutoff, and the substantial variability introduced by differences in gene model annotation, and we suggest strategies for optimal splice effect prediction in the face of these issues.

CONCLUSION

SpliceAI and Pangolin show the best overall performance among predictors tested, however, improvements in splice effect prediction are still needed especially within exons.

Computational approaches for identifying disease-causing mutations in proteins

Advancements in genome sequencing have expanded the scope of investigating mutations in proteins across different diseases. Amino acid mutations in a protein alter its structure, stability and function and some of them lead to diseases. Identification of disease-causing mutations is a challenging task and it will be helpful for designing therapeutic strategies. Hence, mutation data available in the literature have been curated and stored in several databases, which have been effectively utilized for developing computational methods to identify deleterious mutations (drivers), using sequence and structure-based properties of proteins. In this chapter, we describe the contents of specific databases that have information on disease-causing and neutral mutations followed by sequence and structure-based properties. Further, characteristic features of disease-causing mutations will be discussed along with computational methods for identifying cancer hotspot residues and disease-causing mutations in proteins.

Classic Galactosemia: Clinical and Computational Characterization of a Novel GALT Missense Variant (p.A303D) and a Literature Review

Classic galactosemia is an autosomal recessive inherited liver disorder of carbohydrate metabolism caused by deficient activity of galactose-1-phosphate uridylyltransferase (GALT). While a galactose-restricted diet is lifesaving, most patients still develop long-term complications. In this study, we report on a two-week-old female patient who is a compound heterozygote for a known pathogenic variant (p.K285N) and a novel missense variant (p.A303D) in the GALT gene. Segregation analysis showed that the patient inherited the p.K285N pathogenic variant from her father and the p.A303D variant from her mother. A bioinformatics analysis to predict the impact of the p.A303D missense variant on the structure and stability of the GALT protein revealed that it may be pathogenic. Based on this finding, we performed a literature review of all GALT missense variants identified in homozygous and compound heterozygous galactosemia patients carrying the p.K285N pathogenic variant to explore their molecular effects on the clinical phenotype of the disease. Our analysis revealed that these missense variants are responsible for a wide range of molecular defects. This study expands the clinical and mutational spectrum in classic galactosemia and reinforces the importance of understanding the molecular consequences of genetic variants to incorporate genetic analysis into clinical care.