UNASSIGNED: GNE myopathy is a rare slowly progressive adult-onset distal myopathy with autosomal recessive inheritance. It has distinctive features of quadriceps sparing with preferential anterior tibial involvement. Most patients eventually become wheelchair bound by 10-20 years after onset. This study analyzes the phenotype-genotype characteristics and disease progression in a large cohort of GNEM patients from India.
UNASSIGNED: Retrospective observational study on GNEM from a quaternary neurology referral hospital in southern India. Data was collected from clinical phenotyping, serum creatine kinase levels, muscle biopsy histopathology, genetic analysis and functional assessment scales - IBMFRS and MDFRS.
UNASSIGNED: 157 patients were included with mean age at onset and diagnosis: 26.5±6.2 years and 32.8±7.8 years, respectively. M:F ratio was 25 : 13. Most common presenting symptom: foot drop (46.5%) and limb girdle weakness (19.1%). Wasting and weakness of small muscles of hand and finger flexors seen in 66.2% and as an initial symptoms in 5.2%. Though tibialis anterior involvement was most common (89.2%), early quadriceps weakness was noted in 3.2% and Beevor\'s sign in 59.2%. Rimmed vacuoles were present in 75% of patients with muscle biopsy. Most common variant was the Indian Founder variant identified in 129 patients (c.2179 G>A, p.Val727Met - 82.2%) and most common zygosity being compound heterozygous state (n = 115, 87.5%). Biallelic kinase domain variations predisposed to a more severe phenotype. Wheelchair bound state noted in 8.9% with a mean age and duration of 32.0±7.1 and 6.3±4.9 years respectively, earlier than previous studies on other ethnic groups.
UNASSIGNED: This is the largest GNEM cohort reported from South Asia. The p.Val727Met variant in compound heterozygous state is noted in majority (82.2%) of the cases. Observed relationships between genotype and clinical parameters shows that severity of the disease might be attributable to specific GNE genotype and thus could aid in predicting the disease progression.

BACKGROUND: Decoding human genomic sequences requires comprehensive analysis of DNA sequence functionality. Through computational and experimental approaches, researchers have studied the genotype-phenotype relationship and generate important datasets that help unravel complicated genetic blueprints. Thus, the recently developed artificial intelligence methods can be used to interpret the functions of those DNA sequences.
METHODS: This study explores the use of deep learning, particularly pre-trained genomic models like DNA_bert_6 and human_gpt2-v1, in interpreting and representing human genome sequences. Initially, we meticulously constructed multiple datasets linking genotypes and phenotypes to fine-tune those models for precise DNA sequence classification. Additionally, we evaluate the influence of sequence length on classification results and analyze the impact of feature extraction in the hidden layers of our model using the HERV dataset. To enhance our understanding of phenotype-specific patterns recognized by the model, we perform enrichment, pathogenicity and conservation analyzes of specific motifs in the human endogenous retrovirus (HERV) sequence with high average local representation weight (ALRW) scores.
RESULTS: We have constructed multiple genotype-phenotype datasets displaying commendable classification performance in comparison with random genomic sequences, particularly in the HERV dataset, which achieved binary and multi-classification accuracies and F1 values exceeding 0.935 and 0.888, respectively. Notably, the fine-tuning of the HERV dataset not only improved our ability to identify and distinguish diverse information types within DNA sequences but also successfully identified specific motifs associated with neurological disorders and cancers in regions with high ALRW scores. Subsequent analysis of these motifs shed light on the adaptive responses of species to environmental pressures and their co-evolution with pathogens.
CONCLUSIONS: These findings highlight the potential of pre-trained genomic models in learning DNA sequence representations, particularly when utilizing the HERV dataset, and provide valuable insights for future research endeavors. This study represents an innovative strategy that combines pre-trained genomic model representations with classical methods for analyzing the functionality of genome sequences, thereby promoting cross-fertilization between genomics and artificial intelligence.

BACKGROUND: Using the Clinical Audit Research and Evaluation of Motor Neuron Disease (CARE-MND) database and the Scottish Regenerative Neurology Tissue Bank, we aimed to outline the genetic epidemiology and phenotypes of an incident cohort of people with MND (pwMND) to gain a realistic impression of the genetic landscape and genotype-phenotype associations.
METHODS: Phenotypic markers were identified from the CARE-MND platform. Sequence analysis of 48 genes was undertaken. Variants were classified using a structured evidence-based approach. Samples were also tested for C9orf72 hexanucleotide expansions using repeat-prime PCR methodology.
RESULTS: 339 pwMND donated a DNA sample: 44 (13.0%) fulfilled criteria for having a pathogenic variant/repeat expansion, 53.5% of those with a family history of MND and 9.3% of those without. The majority (30 (8.8%)) had a pathogenic C9orf72 repeat expansion, including two with intermediate expansions. Having a C9orf72 expansion was associated with a significantly lower Edinburgh Cognitive and Behavioural ALS Screen ALS-Specific score (p = 0.0005). The known pathogenic SOD1 variant p.(Ile114Thr), frequently observed in the Scottish population, was detected in 9 (2.7%) of total cases but in 17.9% of familial cases. Rare variants were detected in FUS and NEK1. One individual carried both a C9orf72 expansion and SOD1 variant.
CONCLUSIONS: Our results provide an accurate summary of MND demographics and genetic epidemiology. We recommend early genetic testing of people with cognitive impairment to ensure that C9orf72 carriers are given the best opportunity for informed treatment planning. Scotland is enriched for the SOD1 p.(Ile114Thr) variant and this has significant implications with regards to future genetically-targeted treatments.

UNASSIGNED: Given the unique natural history of GBA-related Parkinson\'s disease (GBA-PD) and the potential for novel treatments in this population, genetic testing prioritization for the identification of GBA-PD patients is crucial for prognostication, individualizing treatment, and stratification for clinical trials. Assessing the predictive value of certain clinical traits for the GBA-variant carrier status will help target genetic testing in clinical settings where cost and access limit its availability.
UNASSIGNED: In-depth clinical characterization through standardized rating scales for motor and non-motor symptoms and self-reported binomial information of a cohort of subjects with PD (n = 100) from our center and from the larger cohort of the Parkinson\'s Progression Marker Initiative (PPMI) was utilized to evaluate the predictive values of clinical traits for GBA variant carrier status. The model was cross-validated across the two cohorts.
UNASSIGNED: Leveraging non-motor symptoms of PD, we established successful discrimination of GBA variants in the PPMI cohort and study cohort (AUC 0.897 and 0.738, respectively). The PPMI cohort model successfully generalized to the study cohort data using both MDS-UPDRS scores and binomial data (AUC 0.740 and 0.734, respectively) while the study cohort model did not.
UNASSIGNED: We assessed the predictive value of non-motor symptoms of PD for identifying GBA carrier status in the general PD population. These data can be used to determine a simple, clinically oriented model using either the MDS-UPDRS or subjective symptom reporting from patients. Our results can inform patient counseling about the expected carrier risk and test prioritization for the expected identification of GBA variants.

OBJECTIVE: The goal of the study was to search for novel bi-allelic CRB1 mutations, and then to analyze the CRB1 literature at the genotypic and phenotypic levels.
METHODS: We screened various variables such as the CRB1 mutation types, domains, exons, and genotypes and their relation with specific ocular phenotypes. An emphasis was given to the bi-allelic missense and nonsense mutations because of their high prevalence compared to other mutation types. Finally, we quantified the effect of various non-modifiable factors over the best-corrected visual acuity oculus uterque (BCVA OU) using multivariate linear regression models and identified genetic interactions.
RESULTS: A novel bi-allelic missense in the exon 9 of CRB1; c.2936G > A; p.(Gly979Asp) was found to be associated with rod-cone dystrophy (RCD). CRB1 mutation type, exons, domains, and genotype distribution varied significantly according to fundus characteristics, such as peripheral pigmentation and condition, optic disc, vessels, macular condition, and pigmentation (P < 0.05). Of the 154 articles retrieved from PubMed, 96 studies with 439 bi-allelic CRB1 patients were included. Missense mutations were significantly associated with an absence of macular pigments, pale optic disc, and periphery pigmentation, resulting in a higher risk of RCD (P < 0.05). In contrast, homozygous nonsense mutations were associated with macular pigments, periphery pigments, and a high risk of LCA (P < 0.05) and increased BCVA OU levels. We found that age, mutation types, and inherited retinal diseases were critical determinants of BCVA OU as they significantly increased it by 33% 26%, and 38%, respectively (P < 0.05). Loss of function alleles additively increased the risk of LCA, with nonsense having a more profound effect than indels. Finally, our analysis showed that p.(Cys948Tyr) and p.(Lys801Ter) and p.(Lys801Ter); p.(Cys896Ter) might interact to modify BCVA OU levels.
CONCLUSIONS: This meta-analysis updated the literature and identified genotype-phenotype associations in bi-allelic CRB1 patients.

Viruses persist in nature owing to their extreme genetic heterogeneity and large population sizes, which enable them to evade host immune defenses, escape antiviral drugs, and adapt to new hosts. The persistence of viruses is challenging to study because mutations affect multiple virus genes, interactions among genes in their impacts on virus growth are seldom known, and measures of viral fitness are yet to be standardized. To address these challenges, we employed a data-driven computational model of cell infection by a virus. The infection model accounted for the kinetics of viral gene expression, functional gene-gene interactions, genome replication, and allocation of host cellular resources to produce progeny of vesicular stomatitis virus, a prototype RNA virus. We used this model to computationally probe how interactions among genes carrying up to eleven deleterious mutations affect different measures of virus fitness: single-cycle growth yields and multicycle rates of infection spread. Individual mutations were implemented by perturbing biophysical parameters associated with individual gene functions of the wild-type model. Our analysis revealed synergistic epistasis among deleterious mutations in their effects on virus yield; so adverse effects of single deleterious mutations were amplified by interaction. For the same mutations, multicycle infection spread indicated weak or negligible epistasis, where single mutations act alone in their effects on infection spread. These results were robust to simulation in high- and low-host resource environments. Our work highlights how different types and magnitudes of epistasis can arise for genetically identical virus variants, depending on the fitness measure. More broadly, gene-gene interactions can differently affect how viruses grow and spread.

The HXB/BXH family of recombinant inbred rat strains is a unique genetic resource that has been extensively phenotyped over 25 years, resulting in a vast dataset of quantitative molecular and physiological phenotypes. We built a pangenome graph from 10x Genomics Linked-Read data for 31 recombinant inbred rats to study genetic variation and association mapping. The pangenome includes 0.2Gb of sequence that is not present the reference mRatBN7.2, confirming the capture of substantial additional variation. We validated variants in challenging regions, including complex structural variants resolving into multiple haplotypes. Phenome-wide association analysis of validated SNPs uncovered variants associated with glucose/insulin levels and hippocampal gene expression. We propose an interaction between Pirl1l1, chromogranin expression, TNF-α levels, and insulin regulation. This study demonstrates the utility of linked-read pangenomes for comprehensive variant detection and mapping phenotypic diversity in a widely used rat genetic reference panel.

While loss-of-function (LoF) variants in KCNQ2 are associated with a spectrum of neonatal-onset epilepsies, gain-of-function (GoF) variants cause a more complex phenotype that precludes neonatal-onset epilepsy. In the present work, the clinical features of three patients carrying a de novo KCNQ2 Y141N (n ​= ​1) or G239S variant (n ​= ​2) respectively, are described. All three patients had a mild global developmental delay, with prominent language deficits, and strong activation of interictal epileptic activity during sleep. Epileptic seizures were not reported. The absence of neonatal seizures suggested a GoF effect and prompted functional testing of the variants. In vitro whole-cell patch-clamp electrophysiological experiments in Chinese Hamster Ovary cells transiently-transfected with the cDNAs encoding Kv7.2 subunits carrying the Y141N or G239S variants in homomeric or heteromeric configurations with Kv7.2 subunits, revealed that currents from channels incorporating mutant subunits displayed increased current densities and hyperpolarizing shifts of about 10 ​mV in activation gating; both these functional features are consistent with an in vitro GoF phenotype. The antidepressant drug amitriptyline induced a reversible and concentration-dependent inhibition of current carried by Kv7.2 Y141N and G239S mutant channels. Based on in vitro results, amitriptyline was prescribed in one patient (G239S), prompting a significant improvement in motor, verbal, social, sensory and adaptive behavior skillsduring the two-year-treatment period. Thus, our results suggest that KCNQ2 GoF variants Y141N and G239S cause a mild DD with prominent language deficits in the absence of neonatal seizures and that treatment with the Kv7 channel blocker amitriptyline might represent a potential targeted treatment for patients with KCNQ2 GoF variants.

A Chinese family was identified to have two patients with rickets, an adult female and a male child (proband), both exhibiting signs related to X-linked hypophosphatemic rickets (XLH). Gene sequencing analysis revealed a deletion of adenine at position 1985 (c.1985delA) in the PHEX-encoding gene. To investigate the relationship between this mutation and the pathogenicity of XLH, as well as analyze the effects of different dosages of PHEX gene mutations on clinical phenotypes, we developed a rat model carrying the PHEX deletion mutation. The CRISPR/Cas9 gene editing technology was employed to construct the rat model with the PHEX gene mutation (c.1985delA). Through reproductive procedures, five genotypes of rats were obtained: female wild type (X/X), female heterozygous (-/X), female homozygous wild type (-/-), male wild type (X/Y), and male hemizygous (-/Y). The rats with different genotypes underwent analysis of growth, serum biochemical parameters, and bone microstructure. The results demonstrated the successful generation of a stable rat model inheriting the PHEX gene mutation. Compared to the wild-type rats, the mutant rats displayed delayed growth, shorter femurs, and significantly reduced bone mass. Among the female rats, the homozygous individuals exhibited the smallest body size, decreased bone mass, shortest femur length, and severe deformities. Moreover, the mutant rats showed significantly lower blood phosphorus concentration, elevated levels of FGF23 and alkaline phosphatase, and increased expression of phosphorus regulators. In conclusion, the XLH rat model with the PHEX gene mutation dosage demonstrated its impact on growth and development, serum biochemical parameters, and femoral morphology.

Seasonal shedding of winter hair at the start of summer is well studied in wild and domesticated populations. However, the genetic influences on this trait and their interactions are poorly understood. We use data from 13,364 cattle with 36,899 repeated phenotypes to investigate the relationship between hair shedding and environmental variables, single nucleotide polymorphisms, and their interactions to understand quantitative differences in seasonal shedding. Using deregressed estimated breeding values from a repeated records model in a genome-wide association analysis (GWAA) and meta-analysis of year-specific GWAA gave remarkably similar results. These GWAA identified hundreds of variants associated with seasonal hair shedding. There were especially strong associations between chromosomes 5 and 23. Genotype-by-environment interaction GWAA identified 1,040 day length-by-genotype interaction associations and 17 apparent temperature-by-genotype interaction associations with hair shedding, highlighting the importance of day length on hair shedding. Accurate genomic predictions of hair shedding were created for the entire dataset, Angus, Hereford, Brangus, and multibreed datasets. Loci related to metabolism and light-sensing have a large influence on seasonal hair shedding. This is one of the largest genetic analyses of a phenological trait and provides insight into both agriculture production and basic science.