Frontiers in Genetics最新文献

Background: Previous observational studies have shown that Hypothyroidism is associated with Von Willebrand Disease (VWD), but the causal relationship has not been confirmed because of conflicting findings and confounding by mixing factors. There are also some studies suggesting that polyunsaturated fatty acids (PUFA) may be one of the potential mediators. In this study, we used a Mendelian randomization study to analyze the causal relationship between Hypothyroidism and VWD and to investigate whether polyunsaturated fatty acids mediate the effects of Hypothyroidism on VWD.

Methods: Using a large publicly available genome-wide association study of predominantly European ancestry to obtain data on Hypothyroidism, VWD, and PUFA, we conducted a two-sample Mendelian randomization study to assess the causal relationship between Hypothyroidism and VWD and assess the potential role of Polyunsaturated fatty acids in mediating the causal pathway between Hypothyroidism and VWD. Finally, we also inferred reverse causality between VWD and Hypothyroidism. Inverse variance weighting (IVW) was the primary analytical method.

Results: We found that Hypothyroidism may be negatively causally associated with the development of VWD and that PUFA have a role in mediating role in this process (the ratio of the mediating effect: 24.33%). The causal effects of Hypothyroidism and PUFA on VWD remained significant (p < 0.05) after correction of each other by MVMR.

Conclusion: Our study unveils a novel negative correlation between hypothyroidism and VWD, further enriched by the discovery of partial mediation by PUFA. This groundbreaking finding not only advances our comprehension of VWD etiology but also opens promising avenues for its control and treatment. By elucidating the intricate interplay between hypothyroidism, PUFA, and VWD, our research pioneers a paradigm shift in therapeutic approaches, offering fresh perspectives for the management of this complex disorder.

Introduction: Mucopolysaccharidosis type VI (MPSVI), an autosomal recessive lysosomal storage disorder caused by pathogenic variants in ARSB gene. Usually, whole exome sequencing (WES) can identify these variants, and if WES failed to detect causative variants, whole-genome sequencing (WGS) may be considered to investigate deep intronic variations and structural alterations in patients.

Methods: Whole-exome sequencing (WES) and whole genome sequencing (WGS) were performed in a Chinese family having a boy with suspected diagnosis of MPS with macrocephaly, coarse facial features, broad forehead, thick lips, frontal bossing, craniosynostosis, blue spots, frequent upper respiratory infections, inguinal hernia, and dysostosis multiplex. Lysosomal enzymatic assays for leucocytes were used to assess the activity of arylsulfatase B of the boy's leucocytes. Sanger sequencing and karyotyping analysis were used to validate the variants identified in the boy and his parents.

Results: This boy diagnosed with MPSVI based on clinical phenotypes and laboratory biochemical assays, and WES identified only a maternally inherited missense variant, c.908G>T (p.Gly303Val), in the ARSB gene. By performing WGS, we found a paracentric inversion involving chromosome 5q14.1q13.2 (78180730-138771424 inv), disrupting the ARSB gene on the proband and his father. The inversion was confirmed through karyotyping analysis, and the breakpoints were validated by agarose gel electrophoresis and Sanger sequencing.

Disscussion: This study reminds us that WGS should be done when WES failed to achieve a molecular diagonosis, and it also underscores the importance of WGS especially in cases of high clinical suspicion.

Peanut is a vital source of protein, particularly in the tropical regions of Asian and African countries. About three-quarters of peanut production occurs worldwide in arid and semi-arid regions, making drought an important concern in peanut production. In the US about two-thirds of peanuts are grown in non-irrigated lands, where drought accounts for 50 million USD loss each year. The looming threat of climate change exacerbates this situation by increasing erratic rainfall. Drought not only reduces yield but also degrades product quality. Peanuts under drought stress exhibit higher levels of pre-harvest aflatoxin contamination, a toxic fungal metabolite detrimental to both humans and animals. One way to sustain peanut production in drought-prone regions and address pre-harvest aflatoxin contamination is by developing drought-tolerant peanut cultivars, a process that can be accelerated by understanding the underlying physiological and genetic mechanisms for tolerance to drought stress. Different physiological attributes and genetic regions have been identified in drought-tolerant cultivars that help them cope with drought stress. The advent of precise genetic studies, artificial intelligence, high-throughput phenotyping, bioinformatics, and data science have significantly improved drought studies in peanuts. Yet, breeding peanuts for drought tolerance is often a challenge as it is a complex trait significantly affected by environmental conditions. Besides technological advancements, the success of drought-tolerant cultivar development also relies on the identification of suitable germplasm and the conservation of peanut genetic variation.

Background: Lung adenocarcinoma (LUAD) is a highly aggressive tumor with one of the highest morbidity and mortality rates in the world. Nucleotide metabolic processes are critical for cancer development, progression, and alteration of the tumor microenvironment. However, the effect of nucleotide metabolism on LUAD remains to be thoroughly investigated.

Methods: Transcriptomic and clinical data of LUAD were downloaded and organized from TCGA and GEO databases. Genes related to nucleotide metabolism were downloaded from the Msigdb database. Genes associated with LUAD prognosis were identified using univariate COX analysis, and a prognostic risk model was constructed using the machine learning combination of Lasso + Stepcox. The model's predictive validity was evaluated using KM survival and timeROC curves. Based on the prognostic model, LUAD patients were classified into different nucleotide metabolism subtypes, and the differences between patients of different subtypes were explored in terms of genomic mutations, functional enrichment, tumor immune characteristics, and immunotherapy responses. Finally, the key gene SNRPA was screened, and a series of in vitro experiments were performed on LUAD cell lines to explore the role of SNRPA in LUAD.

Result: LUAD patients could be accurately categorized into subtypes based on the nucleotide metabolism-related prognostic risk score (NMBRS). There were significant differences in prognosis between patients of different subtypes, and the NMBRS showed high accuracy in predicting the prognosis of LUAD patients. In addition, patients of different subtypes showed significant differences in genomic mutation and functional enrichment and exhibited different anti-tumor immune profiles. Importantly, NMBRS can be used to predict the responsiveness of LUAD patients to immunotherapy. The results of in vitro cellular experiments indicate that SNRPA plays an important role in the development and progression of lung adenocarcinoma.

Conclusion: This study comprehensively reveals the prognostic value and clinical application of nucleotide metabolism in LUAD. A prognostic signature constructed based on genes related to nucleotide metabolism accurately predicted the prognosis of LUAD patients, and this signature can be used as a guide for LUAD immunotherapy.

Introduction: Typical adolescent neurodevelopment is marked by decreases in grey matter (GM) volume, increases in myelination, measured by fractional anisotropy (FA), and improvement in cognitive performance.

Methods: To understand how epigenetic changes, methylation (DNAm) in particular, may be involved during this phase of development, we studied cognitive assessments, DNAm from saliva, and neuroimaging data from a longitudinal cohort of normally developing adolescents, aged nine to fourteen. We extracted networks of methylation with patterns of correlated change using a weighted gene correlation network analysis (WCGNA). Modules from these analyses, consisting of co-methylation networks, were then used in multivariate analyses with GM, FA, and cognitive measures to assess the nature of their relationships with cognitive improvement and brain development in adolescence.

Results: This longitudinal exploration of co-methylated networks revealed an increase in correlated epigenetic changes as subjects progressed into adolescence. Co-methylation networks enriched for pathways involved in neuronal systems, potassium channels, neurexins and neuroligins were both conserved across time as well as associated with maturation patterns in GM, FA, and cognition.

Discussion: Our research shows that correlated changes in the DNAm of genes in neuronal processes involved in adolescent brain development that were both conserved across time and related to typical cognitive and brain maturation, revealing possible epigenetic mechanisms driving this stage of development.

Objectives: Unlike other diseases, cancer is not just a genome disease but should broadly be viewed as a disease of the cellular machinery. Therefore, integrative multifaceted approaches are crucial to understanding the complex nature of cancer biology. Bcl-2 (B-cell lymphoma 2), encoded by the human BCL-2 gene, is an anti-apoptotic molecule that plays a key role in apoptosis and genetic variation of Bcl-2 proteins and is vital in disrupting the apoptotic machinery. Single nucleotide polymorphisms (SNPs) are considered viable diagnostic and therapeutic biomarkers for various cancers. Therefore, this study explores the association between SNPs in Bcl-2 and the structural, functional, protein-protein interactions (PPIs), drug binding and dynamic characteristics.

Methods: Comprehensive cross-validated bioinformatics tools and molecular dynamics (MD) simulations. Multiple sequence, genetic, structural and disease phenotype analyses were applied in this study.

Results: Analysis revealed that out of 130 mutations, approximately 8.5% of these mutations were classified as pathogenic. Furthermore, two particular variants, namely, Bcl-2^G101V and Bcl-2^F104L, were found to be the most deleterious across all analyses. Following 500 ns, MD simulations showed that these mutations caused a significant distortion in the protein conformational, protein-protein interactions (PPIs), and drug binding landscape compared to Bcl-2^WT.

Conclusion: Despite being a predictive study, the findings presented in this report would offer a perspective insight for further experimental investigation, rational drug design, and cancer gene therapy.

Background: Delays in diagnosing rare genetic disorders often arise due to limited awareness and systemic challenges in primary care. This case highlights the importance of a holistic approach to patient care, encompassing timely detection and comprehensive evaluation of clinical features.

Methods: We report the case of a 21-year-old Ecuadorian male with facial and hand dysmorphias, cardiomegaly, pulmonary hypertension, and patent ductus arteriosus (PDA). Whole-exome sequencing, performed using the Illumina NextSeq platform. We extensively analyzed over 100 genes linked to congenital structural heart diseases.

Results: The genetic findings provided a definitive diagnosis of Craniofacial-Deafness-Hand Syndrome, an extremely rare autosomal dominant condition, but found no variants that explain the patient's cardiac phenotype. We identified a novel pathogenic missense variant in the PAX3 gene (c.A91C, p. T31P).

Discussion and conclusions: This case underscores the necessity of integrating genetic testing into routine clinical practice to enhance diagnostic precision for rare diseases. It also highlights the need for multidisciplinary collaboration and a holistic care model to improve patient outcomes. The unique association of Craniofacial-Deafness-Hand Syndrome with cardiovascular anomalies due to a PAX3 variation provides valuable insights into the genetic underpinnings of this rare condition.

Recent advancements in deep learning, particularly large language models (LLMs), made a significant impact on how researchers study microbiome and metagenomics data. Microbial protein and genomic sequences, like natural languages, form a language of life, enabling the adoption of LLMs to extract useful insights from complex microbial ecologies. In this paper, we review applications of deep learning and language models in analyzing microbiome and metagenomics data. We focus on problem formulations, necessary datasets, and the integration of language modeling techniques. We provide an extensive overview of protein/genomic language modeling and their contributions to microbiome studies. We also discuss applications such as novel viromics language modeling, biosynthetic gene cluster prediction, and knowledge integration for metagenomics studies.

Facioscapulohumeral muscular dystrophy type 1 (FSHD1) and Becker muscular dystrophy (BMD) are distinct disorders caused by different genetic variations and exhibiting different inheritance patterns. The co-occurrence of both conditions within the same family is rare. In this case report, the proband was a 10 year-old boy who presented with eye and mouth orbicular muscles, shoulder and proximal upper and lower limbs weakness. Genetic testing showed that the number of D4Z4 repeat units in the sub-terminal region 4qA of chromosome 4q35 in the proband was only 4 (normal value ≥ 11) and, at the same time, a heterozygous deletion was found in exons 13-29 of DMD gene in the proband, thus the diagnosis was clinically and genetically compatible with both FSHD1 and BMD. Pedigree investigation revealed that his maternal grandmother, mother, aunt and cousin also had muscle weakness in the face, shoulders and limbs. Genetic testing confirmed that each of the four relatives had four D4Z4 repeats in the 4qA region, and all of them carried a heterozygous deletion in exons 13-29 of DMD. Based on the X-linked features of DMD/BMD, the maternal grandmother, mother, and aunt were diagnosed with FSHD1 combined with DMD deletion carriers, and the male cousin was diagnosed with FSHD1 combined with BMD. This study identifies a family with a co-occurrence of clinically overt FSHD1 and BMD, which has important reference value for the diagnosis and treatment of hereditary myopathies.

High-altitude adaptation is a remarkable example of natural selection, yet the genomic and physiological adaptation mechanisms of Ethiopian highlanders remain poorly understood compared to their Andean and Tibetan counterparts. Ethiopian populations, such as the Amhara and Oromo, exhibit unique adaptive strategies characterized by moderate hemoglobin levels and enhanced arterial oxygen saturation, indicating distinct mechanisms of coping with chronic hypoxia. This review synthesizes current genomic insights into Ethiopian high-altitude adaptation, identifying key candidate genes involved in hypoxia tolerance and examining the influence of genetic diversity and historical admixture on adaptive responses. Furthermore, the review highlights significant research gaps, particularly the underrepresentation of Ethiopian populations in global genomic studies, the lack of comprehensive genotype-phenotype analyses, and inconsistencies in research methodologies. Addressing these gaps is crucial for advancing our understanding of the genetic basis of human adaptation to extreme environments and for developing a more complete picture of human physiological resilience. This review offers a comparative perspective with Tibetan and Andean highlanders, emphasizing the need for expanding genomic representation and refining methodologies to uncover the genetic mechanisms underlying high-altitude adaptation in Ethiopian populations.