BMC Medical Genomics最新文献

{"title":"Identification of a novel intronic variant in COL4A2 gene associated with fetal severe cerebral encephalomalacia and subdural hemorrhage.","authors":"Rong-Yue Sun, Yue Xu, Qing-Qing Huang, Si-Si Hu, Hua-Zhi Xu, Yan-Zhao Luo, Ting Zhu, Jun-Hui Sun, Yu-Jing Gong, Mian-Mian Zhu, Hong-Wei Wang, Jing-Ye Pan, Chao-Sheng Lu, Dan Wang","doi":"10.1186/s12920-024-02012-4","DOIUrl":"10.1186/s12920-024-02012-4","url":null,"abstract":"<p><strong>Background: </strong>Genetic variants in COL4A2 are less common than those of COL4A1 and their fetal clinical phenotype has not been well described to date. We present a fetus from China with an intronic variant in COL4A2 associated with a prenatal diagnosis of severe cerebral encephalomalacia and subdural hemorrhage.</p><p><strong>Methods: </strong>Whole exome sequencing (WES) was applied to screen potential genetic causes. Bioinformatic analysis was performed to predict the pathogenicity of the variant. In in vitro experiment, the minigene assays were performed to assess the variant's effect.</p><p><strong>Results: </strong>In this proband, we observed ventriculomegaly, subdural hemorrhage, and extensive encephalomalacia that initially suggested cerebral hypoxic-ischemic and/or hemorrhagic lesions. WES identified a de novo heterozygous variant c.549 + 5G > A in COL4A2 gene. This novel variant leads to the skipping of exon 8, which induces the loss of 24 native amino acids, resulting in a shortened COL4A2 protein (p.Pro161_Gly184del).</p><p><strong>Conclusion: </strong>Our study demonstrated that c.549 + 5G > A in COL4A2 gene is a disease-causing variant by aberrant splicing. This finding enriches the variant spectrum of COL4A2 gene, which not only improves the understanding of the fetal neurological disorders associated with hypoxic-ischemic and hemorrhagic lesions from a clinical perspective but also provides guidance on genetic diagnosis and counseling.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"17 1","pages":"238"},"PeriodicalIF":2.1,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11441077/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142340651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic yield of exome sequencing-based copy number variation analysis in Mendelian disorders: a clinical application.","authors":"Tahir Atik, Enise Avci Durmusalioglu, Esra Isik, Melis Kose, Seda Kanmaz, Ayca Aykut, Asude Durmaz, Ferda Ozkinay, Ozgur Cogulu","doi":"10.1186/s12920-024-02015-1","DOIUrl":"10.1186/s12920-024-02015-1","url":null,"abstract":"<p><p>Next-generation sequencing (NGS) coupled with bioinformatic tools has revolutionized the detection of copy number variations (CNVs), which are implicated in the emergence of Mendelian disorders. In this study, we evaluated the diagnostic yield of exome sequencing-based CNV analysis in 449 patients with suspected Mendelian disorders. We aimed to assess the diagnostic yield of this recently utilized method and expand the clinical spectrum of intragenic CNVs. The cohort underwent whole exome sequencing (WES) and clinical exome sequencing (CES). Using GATK-gCNV, we identified 12 pathogenic CNVs that correlated with their clinical findings and resulting in a diagnostic yield of 2.67%. Importantly, the study emphasizes the role of CNVs in the etiology of Mendelian disorders and highlights the value of exome sequencing-based CNV analysis in routine diagnostic processes.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"17 1","pages":"239"},"PeriodicalIF":2.1,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11441242/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142340649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional analysis of a novel nonsense PPP1R12A variant in a Chinese family with infantile epilepsy.","authors":"Ling Tong, Xinxin Wang, Huiqin Wang, Rong Yang, Xiaoyan Li, Xiaoguang Yin","doi":"10.1186/s12920-024-02009-z","DOIUrl":"10.1186/s12920-024-02009-z","url":null,"abstract":"<p><strong>Background: </strong>Defects in PPP1R12A can lead to genitourinary and/or brain malformation syndrome (GUBS). GUBS is primarily characterized by neurological or genitourinary system abnormalities, but a few reported cases are associated with neonatal seizures. Here, we report a case of a female newborn with neonatal seizures caused by a novel variant in PPP1R12A, aiming to enhance the clinical and variant data of genetic factors related to epilepsy in early life.</p><p><strong>Methods: </strong>Whole-exome and Sanger sequencing were used for familial variant assessment, and bioinformatics was employed to annotate the variant. A structural model of the mutant protein was simulated using molecular dynamics (MD), and the free binding energy between PPP1R12A and PPP1CB was analyzed. A mutant plasmid was constructed, and mutant protein expression was analyzed using western blotting (WB), and the interaction between the mutant and PPP1CB proteins using co-immunoprecipitation (Co-IP) experiments.</p><p><strong>Results: </strong>The patient experienced tonic-clonic seizures on the second day after birth. Genetic testing revealed a heterozygous variant in PPP1R12A, NM_002480.3:c.2533 C > T (p.Arg845Ter). Both parents had the wild-type gene. MD suggested that loss of the C-terminal structure in the mutant protein altered its structural stability and increased the binding energy with PPP1CB, indicating unstable protein-protein interactions. On WB, a low-molecular-weight band was observed, indicating that the protein was truncated. Co-IP indicated that the mutant protein no longer interacted with PPP1CB, indicating an effect on the structural stability of the myosin phase complex.</p><p><strong>Conclusion: </strong>The PPP1R12A c.2533 C > T variant may explain the neonatal seizures in the present case. The findings of this study expand the spectrum of PPP1R12A variants and highlight the potential significance of truncated proteins in the pathogenesis of GUBS.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"17 1","pages":"236"},"PeriodicalIF":2.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11429181/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142340650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validating the splicing effect of rare variants in the SLC26A4 gene using minigene assay.","authors":"Yixin Zhao, Yan Long, Tao Shi, Xin Ma, Chengyu Lian, Hanjun Wang, Hongen Xu, Lisheng Yu, Xiaotao Zhao","doi":"10.1186/s12920-024-02007-1","DOIUrl":"10.1186/s12920-024-02007-1","url":null,"abstract":"<p><strong>Background: </strong>The SLC26A4 gene is the second most common cause of hereditary hearing loss in human. The aim of this study was to utilize the minigene assay in order to identify pathogenic variants of SLC26A4 associated with enlarged vestibular aqueduct (EVA) and hearing loss (HL) in two patients.</p><p><strong>Methods: </strong>The patients were subjected to multiplex PCR amplification and next-generation sequencing of common deafness genes (including GJB2, SLC26A4, and MT-RNR1), then bioinformatics analysis was performed on the sequencing data to identify candidate pathogenic variants. Minigene experiments were conducted to determine the potential impact of the variants on splicing.</p><p><strong>Results: </strong>Genetic testing revealed that the first patient carried compound heterozygous variants c.[1149 + 1G > A]; [919-2 A > G] in the SLC26A4 gene, while the second patient carried compound heterozygous variants c.[2089 + 3 A > T]; [919-2 A > G] in the same gene. Minigene experiments demonstrated that both c.1149 + 1G > A and c.2089 + 3 A > T affected mRNA splicing. According to the ACMG guidelines and the recommendations of the ClinGen Hearing Loss Expert Panel for ACMG variant interpretation, these variants were classified as \"likely pathogenic\".</p><p><strong>Conclusions: </strong>This study identified the molecular etiology of hearing loss in two patients with EVA and elucidated the impact of rare variants on splicing, thus contributing to the mutational spectrum of pathogenic variants in the SLC26A4 gene.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"17 1","pages":"233"},"PeriodicalIF":2.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11430457/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142340653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.","authors":"Agaz H Wani, Seyma Katrinli, Xiang Zhao, Nikolaos P Daskalakis, Anthony S Zannas, Allison E Aiello, Dewleen G Baker, Marco P Boks, Leslie A Brick, Chia-Yen Chen, Shareefa Dalvie, Catherine Fortier, Elbert Geuze, Jasmeet P Hayes, Ronald C Kessler, Anthony P King, Nastassja Koen, Israel Liberzon, Adriana Lori, Jurjen J Luykx, Adam X Maihofer, William Milberg, Mark W Miller, Mary S Mufford, Nicole R Nugent, Sheila Rauch, Kerry J Ressler, Victoria B Risbrough, Bart P F Rutten, Dan J Stein, Murray B Stein, Robert J Ursano, Mieke H Verfaellie, Eric Vermetten, Christiaan H Vinkers, Erin B Ware, Derek E Wildman, Erika J Wolf, Caroline M Nievergelt, Mark W Logue, Alicia K Smith, Monica Uddin","doi":"10.1186/s12920-024-02002-6","DOIUrl":"10.1186/s12920-024-02002-6","url":null,"abstract":"<p><strong>Background: </strong>Incorporating genomic data into risk prediction has become an increasingly popular approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not.</p><p><strong>Methods: </strong>Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts.</p><p><strong>Results: </strong>The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p=0.006), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD.</p><p><strong>Conclusion: </strong>The inclusion of exposure variables adds to the predictive power of MRS. Classification-based MRS may be useful in predicting risk of future PTSD in populations with anticipated trauma exposure. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting PTSD and, relatedly, improve their performance in independent cohorts.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"17 1","pages":"235"},"PeriodicalIF":2.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11429352/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142340648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics analysis of ferroptosis in frozen shoulder.","authors":"Hongcui Zhang, Jiahua Zhou, Zhihua Liu, Kaile Wang, Hexun Jiang","doi":"10.1186/s12920-024-02011-5","DOIUrl":"https://doi.org/10.1186/s12920-024-02011-5","url":null,"abstract":"<p><strong>Objectives: </strong>Frozen shoulder is a common shoulder disease that significantly affects the patient's life and work. Ferroptosis is a new type of programmed cell death, which is involved in many diseases. However, there have been no studies reporting the relationship between frozen shoulders and ferroptosis. This study identified potential molecular markers of ferroptosis in frozen shoulders to provide more effective strategies for the treatment of frozen shoulders.</p><p><strong>Methods: </strong>GSE238053 was downloaded from the Gene Expression Omnibus (GEO) dataset and intersected with ferroptosis genes to obtain differentially expressed genes (DEGs). The signaling pathways and biological functions of DEGs were performed by WebGestalt and Metascape. The interactions related to these DEGs and the key genes between frozen shoulders and ferroptosis was performed by STRING and Cytoscape. A frozen shoulders rat model was used to validate our predicted genes, Western Blot and qRT-PCR was used to assess the expression levels of our genes of interest.</p><p><strong>Results: </strong>A total of 34 DEGs between GSE238053 and Ferroptosis Database were obtained, most of which were involved in the HIF-1 signaling pathway and inflammatory response. A protein-protein interaction network was obtained by Cytoscape and the key genes (IL-6, HMOX1 and TLR4) were screened by MCODE. Our results of Western Blot showed that the protein expression level of TLR4 and HMOX1 were elevated, and the protein level of IL-6 decreased in frozen shoulders rat model. The mRNA level after frozen shoulders showed that IL-6 was upregulated, whereas TLR4 and HMOX1were downregulated.</p><p><strong>Conclusions: </strong>The results demonstrated that ferroptosis may affect the pathological process of frozen shoulders through these signaling pathways and genes. The identification of IL-6, HMOX1 and TLR4 genes can provide new therapeutic targets for frozen shoulders.</p>","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"17 1","pages":"234"},"PeriodicalIF":2.1,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11428309/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142340636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of a molecular diagnostic system for neurogenic rosacea by combining transcriptome sequencing and machine learning","authors":"Rui Mao, Ji Li","doi":"10.1186/s12920-024-02008-0","DOIUrl":"https://doi.org/10.1186/s12920-024-02008-0","url":null,"abstract":"Patients with neurogenic rosacea (NR) frequently demonstrate pronounced neurological manifestations, often unresponsive to conventional therapeutic approaches. A molecular-level understanding and diagnosis of this patient cohort could significantly guide clinical interventions. In this study, we amalgamated our sequencing data (n = 46) with a publicly accessible database (n = 38) to perform an unsupervised cluster analysis of the integrated dataset. The eighty-four rosacea patients were partitioned into two distinct clusters. Neurovascular biomarkers were found to be elevated in cluster 1 compared to cluster 2. Pathways in cluster 1 were predominantly involved in neurotransmitter synthesis, transmission, and functionality, whereas cluster 2 pathways were centered on inflammation-related processes. Differential gene expression analysis and WGCNA were employed to delineate the characteristic gene sets of the two clusters. Subsequently, a diagnostic model was constructed from the identified gene sets using linear regression methodologies. The model's C index, comprising genes PNPLA3, CUX2, PLIN2, and HMGCR, achieved a remarkable value of 0.9683, with an area under the curve (AUC) for the training cohort's nomogram of 0.9376. Clinical characteristics from our dataset (n = 46) were assessed by three seasoned dermatologists, forming the NR validation cohort (NR, n = 18; non-neurogenic rosacea, n = 28). Upon application of our model to NR diagnosis, the model's AUC value reached 0.9023. Finally, potential therapeutic candidates for both patient groups were predicted via the Connectivity Map. In summation, this study unveiled two clusters with unique molecular phenotypes within rosacea, leading to the development of a precise diagnostic model instrumental in NR diagnosis.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"65 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of autophagy-related genes as potential biomarkers correlated with immune infiltration in bipolar disorder: a bioinformatics analysis","authors":"Dong Cao, Yafang Liu, Jinghong Mei, Shuailong Yu, Cong Zeng, Jing Zhang, Yujuan Li","doi":"10.1186/s12920-024-02003-5","DOIUrl":"https://doi.org/10.1186/s12920-024-02003-5","url":null,"abstract":"Bipolar disorder (BPD) is a kind of manic and depressive phase alternate episodes of serious mental illness, and it is correlated with well-documented cortical brain abnormalities. Emerging evidence supports that autophagy dysfunction in neuronal system contributes to pathophysiological changes in neurological disease. However, the role of autophagy in bipolar disorder has rarely been elucidated. This study aimed to identify the autophagy-related gene as a potential biomarker Correlated to immune infiltration in BPD. The microarray dataset GSE23848 and autophagy-related genes (ARGs) were downloaded. Differentially expressed genes (DEGs) between normal and BPD samples were screened using the R software. Machine learning algorithms were performed to screen the significant candidate biomarker from autophagy-related differentially expressed genes (ARDEGs). The correlation between the screened ARDEGs and infiltrating immune cells was explored through correlation analysis. In this study, the autophagy pathway was abundantly enriched and activated in BPD, as indicated by Pathway enrichment analysis. We identified 16 ARDEGs in BPD compared to the normal group. A signature of 4 ARDEGs (ERN1, ATG3, CTSB, and EIF2AK3) was screened. ROC analysis showed that the above genes have good diagnostic performance. In addition, immune correlation analysis considered that the above four genes significantly correlated with immune cells in BPD. Autophagy - immune cell axis mediates pathophysiological changes in BPD. Four important ARDEGs are prospective to be potential biomarkers associated with immune infiltration in BPD and helpful for the prediction or diagnosis of BPD.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"17 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Whole exome sequencing analysis of 167 men with primary infertility","authors":"Haiyan Zhou, Zhaochu Yin, Bin Ni, Jiwu Lin, Shuwei Luo, Wanqin Xie","doi":"10.1186/s12920-024-02005-3","DOIUrl":"https://doi.org/10.1186/s12920-024-02005-3","url":null,"abstract":"Spermatogenic failure is one of the leading causes of male infertility and its genetic etiology has not yet been fully understood. The study screened a cohort of patients (n = 167) with primary male infertility in contrast to 210 normally fertile men using whole exome sequencing (WES). The expression analysis of the candidate genes based on public single cell sequencing data was performed using the R language Seurat package. No pathogenic copy number variations (CNVs) related to male infertility were identified using the the GATK-gCNV tool. Accordingly, variants of 17 known causative (five X-linked and twelve autosomal) genes, including ACTRT1, ADAD2, AR, BCORL1, CFAP47, CFAP54, DNAH17, DNAH6, DNAH7, DNAH8, DNAH9, FSIP2, MSH4, SLC9C1, TDRD9, TTC21A, and WNK3, were identified in 23 patients. Variants of 12 candidate (seven X-linked and five autosomal) genes were identified, among which CHTF18, DDB1, DNAH12, FANCB, GALNT3, OPHN1, SCML2, UPF3A, and ZMYM3 had altered fertility and semen characteristics in previously described knockout mouse models, whereas MAGEC1,RBMXL3, and ZNF185 were recurrently detected in patients with male factor infertility. The human testis single cell-sequencing database reveals that CHTF18, DDB1 and MAGEC1 are preferentially expressed in spermatogonial stem cells. DNAH12 and GALNT3 are found primarily in spermatocytes and early spermatids. UPF3A is present at a high level throughout spermatogenesis except in elongating spermatids. The testicular expression profiles of these candidate genes underlie their potential roles in spermatogenesis and the pathogenesis of male infertility. WES is an effective tool in the genetic diagnosis of primary male infertility. Our findings provide useful information on precise treatment, genetic counseling, and birth defect prevention for male factor infertility.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"147 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transcriptomic analysis reveals key molecular signatures across recovery phases of hemorrhagic fever with renal syndrome","authors":"Yuanyuan Hu, Chao Wu, Tuohang Li, Yang Wu, Kun Yao, Mengtian Zhang, Pan Li, Xuzhao Bian","doi":"10.1186/s12920-024-02004-4","DOIUrl":"https://doi.org/10.1186/s12920-024-02004-4","url":null,"abstract":"Hemorrhagic fever with renal syndrome (HFRS), a life-threatening zoonosis caused by hantavirus, poses significant mortality risks and lacks specific treatments. This study aimed to delineate the transcriptomic alterations during the recovery phases of HFRS. RNA sequencing was employed to analyze the transcriptomic alterations in peripheral blood mononuclear cells from HFRS patients across the oliguric phase (OP), diuretic phase (DP), and convalescent phase (CP). Twelve differentially expressed genes (DEGs) were validated using quantitative real-time PCR in larger sample sets. Our analysis revealed pronounced transcriptomic differences between DP and OP, with 38 DEGs showing consistent expression changes across all three phases. Notably, immune checkpoint genes like CD83 and NR4A1 demonstrated a monotonic increase, in contrast to a monotonic decrease observed in antiviral and immunomodulatory genes, including IFI27 and RNASE2. Furthermore, this research elucidates a sustained attenuation of immune responses across three phases, alongside an upregulation of pathways related to tissue repair and regeneration. Our research reveals the transcriptomic shifts during the recovery phases of HFRS, illuminating key genes and pathways that may serve as biomarkers for disease progression and recovery.","PeriodicalId":8915,"journal":{"name":"BMC Medical Genomics","volume":"32 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}