Human Genomics最新文献

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.

Background: Liver cancer has a high global incidence, particularly in East Asia. Early detection difficulties lead to poor prognosis. Single-cell sequencing precisely identifies gene expression differences in specific cell types, making it valuable in tumor microenvironment research and immune drug development. However, the characteristics of tumor cells themselves are equally important for patient prognosis and treatment.

Methods: We downloaded single-cell sequencing data from GSE189903, grouped cells by cluster markers, and classified epithelial cells into adjacent non-tumor, normal, and tumor cells. Differential gene and survival analyses identified significant differential genes. Using TCGA-LIHC data, we divided 370 patients into test and training sets. We constructed and validated a LASSO model based on these genes in both sets and two external datasets. Functional, immune infiltration, and mutation analyses were performed on high and low-risk groups. We also used RNA-seq and IC50 data of 15 liver cancer cell lines from GDSC, scoring them with our prognostic model to identify potential drugs for high-risk patients.

Results: Dimensionality reduction and clustering of 34 single-cell samples identified five subgroups, with epithelial cells further classified. Differential gene analysis identified 124 significant genes. An 11-gene prognostic model was constructed, effectively stratifying patient prognosis (p < 0.05) and achieving an AUC above 0.6 for 5 year survival prediction in multiple cohorts. Functional analysis revealed that upregulated genes in high-risk groups were enriched in cell adhesion pathways, while downregulated genes were enriched in metabolic pathways. Mutation analysis showed more TP53 mutations in the high-risk group and more CTNNB1 mutations in the low-risk group. Immune infiltration analysis indicated higher immune scores and less CD8 + naive T cell infiltration in the high-risk group. Drug sensitivity analysis identified 14 drugs with lower IC50 in the high-risk group, including clinically approved Sorafenib and Axitinib for treating unresectable HCC.

Conclusion: We established an 11-gene prognostic model that effectively stratifies liver cancer patients based on differentially expressed genes between tumor and adjacent non-tumor cells clustered by scRNA-seq data. The two risk groups had significantly different molecular characteristics. We identified 14 drugs that might be effective for high-risk HCC patients. Our study provides novel insights into tumor cell characteristics, aiding in research on tumor development and treatment.

In developed countries, Newborn Screening (NBS) programs aim to detect treatable yet clinically silent disorders. The selection of disorders to be included in NBS considers severity, treatment availability, prevalence, and analysis cost. However, numerous genetic disorders remain excluded from routine testing due to high expenses and specialized equipment requirements. Here we present SCAN, a novel, non-invasive, and cost-effective decision-support tool utilizing nanopore sequencing for estimating proportions of chromosomes responsible for the most common aneuploidies. SCAN combines DNA enrichment (amplification), barcoding, nanopore sequencing, and machine learning predictive modeling. In a proof-of-concept study for Klinefelter Syndrome, SCAN achieved 100% sensitivity, specificity, and accuracy, becoming the world's first IVD-certified genetic test utilising nanopore sequencing. Further model training shows promise in expanding this assay to detect other chromosomal aneuploidies included in the protocol.

The merging of physiology and toxicokinetics, or pharmacokinetics, with computational modeling to characterize dosimetry has led to major advances for both the chemical and pharmaceutical research arenas. Driven by the mutual need to estimate internal exposures where in vivo data generation was simply not possible, the application of toxicokinetic modeling has grown exponentially in the past 30 years. In toxicology the need has been the derivation of quantitative estimates of toxicokinetic and toxicodynamic variability to evaluate the suitability of the tenfold uncertainty factor employed in risk assessment decision-making. Consideration of a host of physiologic, ontogenetic, genetic, and exposure factors are all required for comprehensive characterization. Fortunately, the underlying framework of physiologically based toxicokinetic models can accommodate these inputs, in addition to being amenable to capturing time-varying dynamics. Meanwhile, international interest in advancing new approach methodologies has fueled the generation of in vitro toxicity and toxicokinetic data that can be applied in in vitro-in vivo extrapolation approaches to provide human-specific risk-based information for historically data-poor chemicals. This review will provide a brief introduction to the structure and evolution of toxicokinetic and physiologically based toxicokinetic models as they advanced to incorporate variability and a wide range of complex exposure scenarios. This will be followed by a state of the science update describing current and emerging experimental and modeling strategies for population and life-stage variability, including the increasing application of in vitro-in vivo extrapolation with physiologically based toxicokinetic models in pharmaceutical and chemical safety research. The review will conclude with case study examples demonstrating novel applications of physiologically based toxicokinetic modeling and an update on its applications for regulatory decision-making. Physiologically based toxicokinetic modeling provides a sound framework for variability evaluation in chemical risk assessment.