Human Genomics最新文献

Background: TP53 variant classification benefits from the availability of large-scale functional data for missense variants generated using cDNA-based assays. However, absence of comprehensive splicing assay data for TP53 confounds the classification of the subset of predicted missense and synonymous variants that are also predicted to alter splicing. Our study aimed to generate and apply splicing assay data for a prioritised group of 59 TP53 predicted missense or synonymous variants that are also predicted to affect splicing by either SpliceAI or MaxEntScan.

Methods: We conducted splicing analyses using a minigene construct containing TP53 exons 2 to 9 transfected into human breast cancer SKBR3 cells, and compared results against different splice prediction methods, including correlation with the SpliceAI-10k calculator. We additionally applied the splicing results for TP53 variant classification using an approach consistent with the ClinGen Sequence Variant Interpretation Splicing Subgroup recommendations.

Results: Aberrant transcript profile consistent with loss of function, and for which a PVS1 (RNA) code would be assigned, was observed for 42 (71%) of prioritised variants, of which aberrant transcript expression was over 50% for 26 variants, and over 80% for 15 variants. Data supported the use of SpliceAI ≥ 0.2 cutoff for predicted splicing impact of TP53 variants. Prediction of aberration types using SpliceAI-10k calculator generally aligned with the corresponding assay results, though maximum SpliceAI score did not accurately predict level of aberrant expression. Application of the observed splicing results was used to reclassify 27/59 (46%) test variants as (likely) pathogenic or (likely) benign.

Conclusions: In conclusion, this study enhances the integration of splicing predictions and provides splicing assay data for exonic variants to support TP53 germline classification.

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.

Background: Oral squamous cell carcinoma (OSCC) is an aggressive malignancy with poor prognosis. Neutrophil infiltration has been associated with unfavorable outcomes in OSCC, but the underlying molecular mechanisms remain unclear.

Methods: This study integrated single-cell transcriptomics (scRNA-seq) with bulk RNA-seq data to analyze neutrophil infiltration patterns in OSCC and identify key gene modules using weighted gene co-expression network analysis (hdWGCNA). A prognostic model was developed based on univariate and Lasso-Cox regression analyses, stratifying patients into high- and low-risk groups. Immune landscape and drug sensitivity analyses were conducted to explore group-specific differences. Additionally, Mendelian randomization analysis was employed to identify genes causally related to OSCC progression.

Results: Several key pathways associated with neutrophil interactions in OSCC progression were identified, leading to the construction of a prognostic model based on significant module genes. The model demonstrated strong predictive performance in distinguishing survival rates between high- and low-risk groups. Immune landscape analysis revealed significant differences in cell infiltration patterns and TIDE scores between the groups. Drug sensitivity analysis highlighted differences in drug responsiveness between high- and low-risk groups.

Conclusion: This study elucidates the critical role of neutrophils and their associated gene modules in OSCC progression. The prognostic model provides a novel reference for patient stratification and targeted therapy. These findings offer potential new targets for OSCC diagnosis, prognosis, and immunotherapy.

Background: Atherosclerosis (AS) is a major cause of cardiovascular diseases and neutrophil extracellular traps (NETs) may be actively involved in the development of atherosclerosis. Identifying key biomarkers in this process is essential for developing targeted treatments for AS.

Methods: We performed bioinformatics analysis using a NETosis-related gene (NRGs) set and three AS datasets (GSE100927, GSE21545, and GSE159677). Differential expression analysis and machine learning techniques (random forest and SVM-RFE) were used to screen for key NRGs. Functional enrichment analysis was conducted using GO and KEGG pathways. The expression and role of PTAFR and NETs in the mouse AS model were validated through histology, immunofluorescence, flow cytometry, and Western blot analysis. The regulatory relationship between PTAFR and NETs was confirmed by siRNA and antagonist intervention targeting PTAFR.

Results: We identified 24 differentially expressed NRGs in AS. Random Forest and SVM-RFE analyses highlighted PTAFR as a key gene. Prognostic analysis revealed PTAFR significantly impacts ischemic events in AS patients. WB and immunofluorescence confirmed increased levels of NETs and PTAFR in the mouse AS model. Single-cell analysis, flow cytometry, and immunofluorescence revealed that PTAFR is primarily distributed in macrophages and neutrophils. Cellular experiments further confirmed that PTAFR regulates NETs formation.

Conclusion: PTAFR is an important regulatory factor for NET formation in AS, influencing the progression and prognosis of atherosclerosis. Targeting PTAFR may provide new therapeutic strategies for AS.

Background: Consanguineous marriage is a major contributing factor for many genetic diseases and a burden to the healthcare system and national economy due to costly long-term care. Earlier studies highlighted the significantly limited awareness of the higher prevalence of genetic disease due to consanguinity even among the educated Arabs. In Saudi Arabia, more than 50% of marriages are between first cousins. This national study aims to gauge the level of the public awareness regarding the consanguinity and its impact on prevalence of genetic diseases across the Saudi Arabia.

Methods: A cross-sectional bilingual online survey was conducted across Saudi Arabia, distributed through a variety of social media platforms for all residents. Pooled summary data was used from the participants.

Results: Majority of the 9191 participants are < 30 years of age (72.85%), single (61.35%), women (74.12%) and college educated (77.16%). Consanguineous marriages are common in the extended family of 61.24% of participants. Though majority of them (85.45%) recognise the higher genetic disease risk associated with consanguinity, low awareness among men was observed (76.61 vs 88.53%). Sickle cell anaemia and thalassemia were not considered as genetic diseases by 60.68% of males and 48.39% of females, though they are the most common genetic diseases in Saudi Arabia. More women are aware of the carrier screening tests than men (42.62 vs 34.56%). Only 6.87% know the rationale behind the national mandatory premarital screening tests and the diseases screened. Although almost all (99.18%) are active users of the social media, 47.77% of men and 57.17% of women use them to search for health-related information.

Conclusion: The present study, one of the largest national surveys in highly consanguineous society, highlights that even the young and college-educated participants have low awareness of the genetic disease burden, which is strikingly high in all corners of the country. Social media platforms can be used by genetic professionals and national organizations to disseminate the reliable educational material to the public to reduce the national healthcare and economic burden in the future.

Background: A significant proportion of cardiomyopathy patients remain genetically unsolved. Our aim was to use the large genomes cohort of the 100,000 genomes project (100KGP) to explore the proportion of potentially causal mitochondrial (mtDNA) variants in cardiomyopathy patients, particularly in genotype-elusive participants. The homoplasmic MT-TI 4300A>G is unusual in that it typically presents with a cardiac-only phenotype, but MT-TI is currently not part of the genes analysed for non-syndromic cardiomyopathies.

Results: We analysed 1363 cardiomyopathy genomes from the 100KGP project (of which only 172 had been previously solved) to detect disease causing mtDNA variants. MitoHPC was used to call variants. For controls, 1329 random subjects not recruited for a cardiomyopathy diagnosis and not related to any participant in the cardiomyopathy cohort were selected. We have additionally compared the frequency of detected variants with published UK Biobank data. Pathogenicity annotations were assigned based on MitoMap. Four patients, all with a diagnosis of hypertrophic cardiomyopathy (HCM) and without a previously identified genetic cause from the 100KGP clinical-standard analysis, were found to harbour the pathogenic MT-TI m.4300A>G variant (0.6% of HCM cases without a diagnosis).

Conclusion: These data support the inclusion of MT-TI in the initial genetic testing panel for (non-syndromic) HCM.

Purpose: Mucopolysaccharidosis type II (MPS II) is a rare X-linked lysosomal storage disorder caused by genetic alterations in the iduronate 2-sulfatase (IDS) gene. A wide range of variants has been reported for different countries and ethnic groups. We collected, analyzed and uniformly summarized all published IDS gene variants reported in literature up to June 2023, here providing the first worldwide review and classification.

Methods: Data was obtained from a literature search, conducted in PubMed and Google. All data was analyzed to define the most common alleles, geographic distribution and genotype-phenotype correlation. Moreover, point variants were classified according to their pathogenicity, based on the ACMG guidelines.

Results: Several types of variants have been described in the IDS gene, including intrachromosomal homologous recombination occurring between the homologous regions of IDS gene and its pseudogene IDSP1. Overall, we collected 2852 individuals from 2798 families, including 24 female patients. Most families carried missense variants, followed by large deletions-insertions and complex rearrangements, small frameshift deletions/insertions and nonsense variants. Based on ACMG guidelines, 62.9% of the 779 point variants were classified as "pathogenic", 35.4% as "likely pathogenic", and the remaining 13 variants as having "uncertain significance".

Conclusion: Data from this study confirmed that MPS II is a genetically very heterogeneous disorder, making genotype-phenotype correlation very challenging and in most cases merely unfeasible. Mutation updates are essential for the correct molecular diagnosis, genetic counseling, prenatal and preimplantation diagnosis, and disease management.

Background: Recently, extensive research has been conducted on the relationship between aspirin gene polymorphisms and aspirin resistance (AR) in patients with ischemic diseases. Among the numerous candidate genes, it remains unclear which ones are significantly associated with AR and could potentially serve as potential biomarkers for genetic testing before aspirin use.

Methods: Eligible articles were searched in PubMed, Embase, Cochrane Library, WanFang, CNKI and Sinomed. A cohort study examining the efficacy of aspirin in secondary prevention for patients with ischemic diseases, along with a discussion on genetic polymorphisms and their association with AR, has been included. The Newcastle-Ottawa Scale for assessing the quality of included studies. Odds ratios (OR) with 95% confidence intervals (CI) were used as measures of effect. Subgroup analyses were conducted based on different genotypes with the same genetic polymorphisms, different research regions and types of ischemic diseases.

Results: From 75 eligible articles, 94 candidate gene polymorphisms were analyzed. In the overall analysis, 25 genes were subjected to meta-analysis and 69 genes were systematically described. 23 gene polymorphisms were observed to be significantly associated with AR, including PTGS2(rs20417) (OR = 0.57, 95% CI: 0.44-0.73), ITGA2(rs1126643) (OR = 0.52, 95% CI: 0.29-0.93), and TbXA2R(rs1131882) (OR = 1.54, 95% CI: 1.09-2.18) were obtained from the combined analysis of this study, and 20 genes were systematically described in this study. Further subgroup analyses demonstrated that AA genotype for PTGS1(rs1330344) (OR = 0.56, 95%CI:0.43-0.74), C allele for PTGS1(rs5788) (OR = 0.51, 95%CI: 0.30-0.87) polymorphisms were significantly associated with AR. The polymorphisms of 13 genes, including PTGS1(rs1236913), have been studied only in Asia, GP6(rs1613662) has been studied only in Europe, and the polymorphisms of 5 genes, including ABCB1(rs1045642), showed different correlations with AR in various regions. The individuals with the PTGS1 (rs5788) variant who experienced an ischemic stroke (OR = 0.98, 95%CI: 0.54-1.67) may exhibit an elevated risk of AR compared to those with coronary artery disease (OR = 0.51, 95%CI: 0.3-0.87).

Conclusions: Our meta-analysis indicates that PTGS2(rs20417), ITGA2(rs1126643), and TbXA2R(rs1131882) could be potential genetic biomarkers for AR. Among these, PTGS2 (rs20417) is particularly suggested for individuals in Asia with ischemic diseases before aspirin use, as the GC/CC genotype raises AR risk by 42% compared to GG. ITGA2 (rs1126643) increases AR risk by 48% in Asia with the TC/TC genotype versus CC. However, results for ABCB1(rs1045642) and GP1BA(rs2243093) vary by regions, requiring further research.

Background: The clinical diagnosis of Fabry Disease (FD) can be challenging due to the clinical heterogeneity, especially in females. Patients with FD often experience a prolonged interval between the onset of symptoms and receiving a diagnosis. Genetic testing is the gold standard for precise diagnosis of FD, however conventional genetic testing could miss deep intronic variants and large deletions or duplications. Although next-generation sequencing, which analyzes numerous genes, has been successfully used for FD diagnosis and can detect complex variants, an effective and rapid tool for identifying a wide range of variants is imminent, contributing to decrease the diagnostic delay.

Methods: The comprehensive Analysis of FD (CAFD) assay was developed for FD genetic diagnosis, employing long-range PCR coupled with long-read sequencing to target the full-length GLA gene and its flanking regions. Its clinical performance was assessed through a comparative analysis with Sanger sequencing.

Results: Genetic testing was performed on 82 individuals, including 48 probands and 34 relatives. The CAFD assay additionally identified variants in two probands: one had a novel and de novo pathogenic variant with a 1715 bp insertion in intron 4, and the other carried two deep intronic VUS variants in cis-configuration also in intron 4. In total, CAFD identified 47 different variants among 48 probands. Of these, 42 (89.36%, 42/47) were pathogenic, while 5 (10.64%, 5/47) were VUS. Sixteen (34.04%, 16/47) of the variants were novel, including 15 SNV/Indels and one large intronic insertion. Pedigree analysis of 21 probands identified four de novo disease-causing variants. Hence, FD exhibits not only variable clinical presentations but also a wide spectrum of variants. Utilizing a comprehensive testing algorithm for diagnosing FD, which includes enzyme activity, clinical features, and genetic testing, the diagnostic yield of CAFD is 97.92% (47/48), which is higher than that of conventional Sanger sequencing, at 95.83% (46/48).

Conclusion: The duration between initial clinical presentation and diagnosis remains long and winding. CAFD provides precise diagnosis for a wide spectrum of GLA variants, promoting timely diagnosis and appropriate treatment for FD patients.