Human Genomics最新文献

{"title":"The associations of candidate gene polymorphisms with aspirin resistance in patients with ischemic disease: a meta-analysis.","authors":"Chun-Xing Li, Li-Chaoyue Sun, Yu-Qiao Wang, Tian-Tian Liu, Jin-Rui Cai, Hua Liu, Zhao Ren, Zhanmiao Yi","doi":"10.1186/s40246-024-00699-1","DOIUrl":"10.1186/s40246-024-00699-1","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"135"},"PeriodicalIF":3.8,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11610159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142768504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-read sequencing enables comprehensive molecular genetic diagnosis of Fabry disease.","authors":"Fengxia Yao, Na Hao, Danhua Li, Weimin Zhang, Jingwen Zhou, Zhengqing Qiu, Aiping Mao, Wanli Meng, Juntao Liu","doi":"10.1186/s40246-024-00697-3","DOIUrl":"10.1186/s40246-024-00697-3","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"133"},"PeriodicalIF":3.8,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11603755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142750440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of single-cell sequencing and drug sensitivity profiling reveals an 11-gene prognostic model for liver cancer.","authors":"Qunfang Zhou, Jingqiang Wu, Jiaxin Bei, Zixuan Zhai, Xiuzhen Chen, Wei Liang, Jing Meng, Mingyu Liu","doi":"10.1186/s40246-024-00698-2","DOIUrl":"10.1186/s40246-024-00698-2","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"132"},"PeriodicalIF":3.8,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11590408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142716225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SCAN: a nanopore-based, cost effective decision-supporting tool for mass screening of aneuploidies.","authors":"Anne Kristine Schack, M Carmen Garrido-Navas, David Galevski, Gjorgji Madjarov, Lukasz Krych","doi":"10.1186/s40246-024-00690-w","DOIUrl":"10.1186/s40246-024-00690-w","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"131"},"PeriodicalIF":3.8,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11583562/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142692878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing understanding of human variability through toxicokinetic modeling, in vitro-in vivo extrapolation, and new approach methodologies.","authors":"Anna Kreutz, Xiaoqing Chang, Helena T Hogberg, Barbara A Wetmore","doi":"10.1186/s40246-024-00691-9","DOIUrl":"10.1186/s40246-024-00691-9","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"129"},"PeriodicalIF":3.8,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11580331/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142686900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic heterogeneity in familial forms of genetic generalized epilepsy: from mono- to oligogenism.","authors":"Maha Dahawi, Jean-Madeleine de Sainte Agathe, Mohamed S Elmagzoub, Elhami A Ahmed, Julien Buratti, Thomas Courtin, Eric Noé, Julie Bogoin, Bruno Copin, Fatima A Elmugadam, Wasma A Abdelgadir, Ahmed K M A Ahmed, Mohamed A Daldoum, Rayan Mamoon Ibrahim Altayeb, Mohamed Bashir, Leena Mohamed Khalid, Sahar Gamil, Sara Baldassari, Liena Elsayed, Boris Keren, Gregory Nuel, Ammar E Ahmed, Eric Leguern","doi":"10.1186/s40246-024-00659-9","DOIUrl":"10.1186/s40246-024-00659-9","url":null,"abstract":"<p><p>Genetic generalized epilepsy (GGE) including childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy (JME), and GGE with tonic-clonic seizures (TCS) (GGE-TCS), is genetically influenced with a two- to four- fold increased risk in the first-degree relatives of patients. Since large families with GGE are very rare, international studies have focused on sporadic GGE patients using whole exome sequencing, suggesting that GGE are highly genetically heterogeneous and rather involve rare or ultra-rare variants. Moreover, a polygenic mode of inheritance is suspected in most cases. We performed SNP microarrays and whole exome sequencing in 20 families from Sudan, focusing on those with at least four affected members. Standard genetic filters and Endeavour algorithm for functional prioritization of genes selected likely susceptibility variants in FAT1, DCHS1 or ASTN2 genes. FAT1 and DCHS1 are adhesion transmembrane proteins interacting during brain development, while ASTN2 is involved in dendrite development. Our approach on familial forms of GGE is complementary to large-scale collaborative consortia studies of sporadic cases. Our study reinforces the hypothesis that GGE is genetically heterogeneous, even in a relatively limited geographic area, and mainly oligogenic, as supported by the low familial penetrance of GGE and by the Bayesian algorithm that we developed in a large pedigree with JME. Since populations with founder effect and endogamy are appropriate to study autosomal recessive pathologies, they would be also adapted to decipher genetic components of complex diseases, using the reported bayesian model.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"130"},"PeriodicalIF":3.8,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11583555/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142686903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global transcriptome modulation by xenobiotics: the role of alternative splicing in adaptive responses to chemical exposures.","authors":"Andrew J Annalora, Jacki L Coburn, Antony Jozic, Patrick L Iversen, Craig B Marcus","doi":"10.1186/s40246-024-00694-6","DOIUrl":"10.1186/s40246-024-00694-6","url":null,"abstract":"<p><strong>Background: </strong>Xenobiotic exposures can extensively influence the expression and alternative splicing of drug-metabolizing enzymes, including cytochromes P450 (CYPs), though their transcriptome-wide impact on splicing remains underexplored. This study used a well-characterized splicing event in the Cyp2b2 gene to validate a sandwich-cultured primary rat hepatocyte model for studying global splicing in vitro. Using endpoint PCR, RNA sequencing, and bioinformatics tools (rSeqDiff, rMATs, IGV), we analyzed differential gene expression and splicing in CYP and nuclear receptor genes, as well as the entire transcriptome, to understand how xenobiotic exposures shape alternative splicing and activate xenosensors.</p><p><strong>Methods: </strong>Primary rat hepatocytes in sandwich culture were exposed to two methylenedioxybenzene (MDB) congeners and carbamazepine, with gene expression and splicing assessed. A 3D-clustergram integrating KEGG pathway analysis with differential gene expression provided distinct splicing landscapes for each xenobiotic, showing that splicing diversity does not always align with gene expression changes.</p><p><strong>Results: </strong>Endpoint PCR revealed a Cyp2b2v to wild-type Cyp2b2 splicing ratio near 1:1 (100%) under most conditions, while RNA-seq showed a stable baseline closer to 40%. C6-MDB reduced this ratio to ~ 50% by PCR and ~ 39% by RNA-seq, showing slight method-dependent variations yet consistent trends. In contrast, exon 6 skipping in Cyp1a1 occurred only with MDB exposure, implicating AHR activation. Xenobiotic treatments also induced alternative splicing in defensome and stress-responsive genes, including the phase II enzyme Gstm3, Albumin, Orm1, and Fxyd1, highlighting their roles in xenobiotic response modulation. Significant splicing changes in factors such as SRSF1, SRSF7, and METTL3 suggest a coordinated feedback loop involving epitranscriptomic modulation and cross-talk within SR protein networks, refining splice site selection, transcript stability, and cellular fate.</p><p><strong>Conclusions: </strong>This study demonstrates how xenobiotic structural features influence gene expression and splicing, revealing splicing patterns that expand our understanding of transcriptome diversity and function. By identifying regulatory mechanisms, including AHR activation, epitranscriptomic modulation, and crosstalk within SR protein networks, that shape adaptive responses to xenobiotic stress, this work offers insights into the splicing and transcriptional networks that maintain cellular homeostasis. These findings provide predictive biomarkers for toxic exposures and highlight the potential of splicing profiles as diagnostic tools for assessing the health impacts of chemical exposure.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"127"},"PeriodicalIF":3.8,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11572221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142667598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of public perceptions on the use of artificial intelligence in genomic medicine.","authors":"Jack E Harrison, Fiona Lynch, Zornitza Stark, Danya F Vears","doi":"10.1186/s40246-024-00686-6","DOIUrl":"10.1186/s40246-024-00686-6","url":null,"abstract":"<p><strong>Purpose: </strong>Next generation sequencing has led to the creation of large pools of genomic data with analysis rather than data generation now the limiting factor. Artificial intelligence (AI) may be required to optimize the benefits of these data, but little is known about how the public feels about the use of AI in genomics.</p><p><strong>Methods: </strong>We conducted focus groups with members of the Australian public. Participants were recruited via social media advertisements. We explored potential uses of AI in genomic medicine, the benefits, risks, and the possible social implications of its use.</p><p><strong>Results: </strong>Participants (n = 34) largely felt comfortable with AI analysing their own genomic data and generally agreed about its benefits. Concerns were raised over data security, the potential for misdiagnosis, and bias AI may perpetuate. Many participants wanted checking mechanisms for when results were generated using AI.</p><p><strong>Conclusions: </strong>The insights gained from these discussions help to understand public concerns around the use of AI in genomic medicine. Our findings can help to inform both policies around genomic AI and how to educate the public on its use.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"128"},"PeriodicalIF":3.8,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11575060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142667581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ralationship between polymorphisms and diplotypes of HLA-G 3'UTR and fetuses with abnormal chromosomes or unexplained pregnancy loss (UPL).","authors":"Danping Xu, Yiyang Zhu, Jun Wang, Heqin Guan, Xiuzhen Shen","doi":"10.1186/s40246-024-00695-5","DOIUrl":"10.1186/s40246-024-00695-5","url":null,"abstract":"<p><strong>Objectives: </strong>Human leukocyte antigen G (HLA-G) plays a crucial role in pregnancy. Pregnancy loss (PL) is caused by a variety of causes, such as fetal chromosomal abnormalities, maternal hypertension and diabetes, immune causes, spontaneous immune diseases, infections, unknown causes, etc. This study reports on the association of fetal HLA-G 3'UTR polymorphisms and diplotypes with chromosomally abnormal fetuses (CAF) or unexplained pregnancy loss (UPL).</p><p><strong>Methods: </strong>A total of 552 specimens were collected and grouped by next-generation sequencing technology (NGS) and fetal survival: UPL (112 cases), CAF (170 cases) and control (258 cases). The polymorphisms of HLA-G 3'UTR in all samples were detected by Sanger sequencing. The genotypes, haplotypes and diplotypes of HLA-G 3'UTR were analyzed. The classification and regression tree (CART) analysis was used to evaluate the role of HLA-G diplotypes in predicting fetal outcomes. The correlations between CAF or UPL and maternal age, paternal age, times of miscarrage, times of delivery were analyzed by logistic regression.</p><p><strong>Results: </strong>The frequencies of HLA-G + 2960del/del and + 3035CC genotypes were remarkablly increased in CAF than those in control group. The frequencies of HLA-G + 2960ins/del, + 3010CC, + 3035TC, + 3142GG, + 3187AA in CAF were significantly lower than those in normal fetuses. Through genetic models and logistic regression analysis, the dominant model of HLA-G 3'UTR genotypes [such as + 2960 (OR = 1.27, 95% CI = 1.05-1.54, p = 0.016), + 3010 (OR = 0.78, 95% CI = 0.63-0.97, p = 0.026), + 3035 (OR = 1.22, 95% CI = 1.00-1.49, p = 0.047), + 3142 (OR = 0.76, 95% CI = 0.62-0.95, p = 0.014) and + 3187 (OR = 0.80, 95% CI = 0.65-0.99, p = 0.041)] were dramatically associated with CAF. However, the frequencies of HLA-G + 3010GC, + 3142GC and + 3187AG in fetuses with UPL were memorably decreased than those in normal fetuses. No significant difference was found in the frequencies of HLA-G haplotypes in all groups. However, the frequency of UTR-1 positive specimens in CAF was significantly higher than that in UPL and control group. At the same time, the frequency of UTR-1/UTR-3 diplotypes in CAF was observably higher than that in UPL and control group, while the UTR-1/UTR-7 frequency in UPL was signally lower than that in control group. Multivariate logistic regression analysis indicated that positive HLA-G UTR-1 (OR = 1.8, 95% CI = 1.16-2.81, p = 0.009), times of abortion (OR = 1.23, 95% CI = 1.02-1.50, p = 0.035), and times of delivery (OR = 0.31, 95% CI = 0.20-0.48, p < 0.001) were correlated with CAF.</p><p><strong>Conclusions: </strong>This study suggests that HLA-G 3'UTR polymorphisms and diplotypes play an important role in the process of successful pregnancy of the embryos with abnormal chromosomes after fertilization. At the same time, Different alleles or diplotypes also affect the development of embryos with UPL.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"126"},"PeriodicalIF":3.8,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11572094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142647624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Methyltransferase-like 3 represents a prospective target for the diagnosis and treatment of kidney diseases.","authors":"Bin Song, Xiaolong Wu, Yan Zeng","doi":"10.1186/s40246-024-00692-8","DOIUrl":"10.1186/s40246-024-00692-8","url":null,"abstract":"<p><p>Kidney disease is marked by complex pathological mechanisms and significant therapeutic hurdles, resulting in high morbidity and mortality rates globally. A deeper understanding of the fundamental processes involved can aid in identifying novel therapeutic targets and improving treatment efficacy. Current comprehensive data analyses indicate the involvement of methyltransferase-like 3 (METTL3) and its role in RNA N⁶-methyladenosine methylation in various renal pathologies, including acute kidney injury, renal fibrosis, and chronic kidney disease. However, there is a paucity of thorough reviews that clarify the functional mechanisms of METTL3 and evaluate its importance in enhancing therapeutic outcomes. This review seeks to systematically examine the roles, mechanisms, and potential clinical applications of METTL3 in renal diseases. The findings presented suggest that METTL3 is implicated in the etiology and exacerbation of kidney disorders, affecting their onset, progression, malignancy, and responsiveness to chemotherapeutic agents through the regulation of specific genetic pathways. In conclusion, this review underscores a detrimental correlation between METTL3 and kidney diseases, highlighting the therapeutic promise of targeting METTL3. Additionally, it offers critical insights for researchers concerning the diagnosis, prognosis, and treatment strategies for renal conditions.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"18 1","pages":"125"},"PeriodicalIF":3.8,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11562609/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142619322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}