Human Genomics最新文献

{"title":"Increasing pathogenic germline variant diagnosis rates in precision medicine: current best practices and future opportunities.","authors":"Sonam Dukda, Manoharan Kumar, Andrew Calcino, Ulf Schmitz, Matt A Field","doi":"10.1186/s40246-025-00811-z","DOIUrl":"https://doi.org/10.1186/s40246-025-00811-z","url":null,"abstract":"<p><p>The accurate diagnosis of pathogenic variants is essential for effective clinical decision making within precision medicine programs. Despite significant advances in both the quality and quantity of molecular patient data, diagnostic rates remain suboptimal for many inherited diseases. As such, prioritisation and identification of pathogenic disease-causing variants remains a complex and rapidly evolving field. This review explores the latest technological and computational options being used to increase genetic diagnosis rates in precision medicine programs.While interpreting genetic variation via standards such as ACMG guidelines is increasingly being recognized as a gold standard approach, the underlying datasets and algorithms recommended are often slow to incorporate additional data types and methodologies. For example, new technological developments, particularly in single-cell and long-read sequencing, offer great opportunity to improve genetic diagnosis rates, however, how to best interpret and integrate increasingly complex multi-omics patient data remains unclear. Further, advances in artificial intelligence and machine learning applications in biomedical research offer enormous potential, however they require careful consideration and benchmarking given the clinical nature of the data. This review covers the current state of the art in available sequencing technologies, software methodologies for variant annotation/prioritisation, pedigree-based strategies and the potential role of machine learning applications. We describe a key set of design principles required for a modern multi-omic precision medicine framework that is robust, modular, secure, flexible, and scalable. Creating a next generation framework will ensure we realise the full potential of precision medicine into the future.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"97"},"PeriodicalIF":4.3,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12374290/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952091","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":"Flu-CNN: identifying host specificity of Influenza A virus using convolutional networks.","authors":"Mingda Hu, Nan Luo, Boqian Wang, Renjie Meng, Yunxiang Zhao, Zili Chai, Yuan Jin, Junjie Yue, Xin Wang, Wei Chen, Hongguang Ren","doi":"10.1186/s40246-025-00812-y","DOIUrl":"https://doi.org/10.1186/s40246-025-00812-y","url":null,"abstract":"<p><p>Influenza A viruses (IAVs) have historically posed significant public health threats, causing severe pandemics. Viral host specificity is typically constrained by host barriers, limiting the range of species that can be infected. However, these barriers are not absolute, and occasionally, cross-species transmission occurs, leading to human outbreaks. Early identification of changes in IAV host specificity is, therefore, critical. Despite advancements, identifying host susceptibility from genomic sequences during outbreaks remains challenging. Timely predictions are critical for effective real-time outbreak management and risk mitigation during the early stages of an epidemic. To address this, we proposed Flu-level Convolutional Neural Networks (Flu-CNN), a model designed to analyze genomic segments and identify IAV host specificity, with a particular focus on avian influenza viruses that could potentially infect humans. Extensive evaluations on large-scale genomic datasets containing 911,098 sequences show that Flu-CNN achieves an impressive 99% accuracy in determining host specificity from a single genomic segment, even for high-risk subtypes like H5N1, H7N9, and H9N2, which have a limited number of viral strains. Given its high level of accuracy, the model was applied to identify key mutations and assess the zoonotic potential of these strains. Furthermore, our study presents a pioneering approach for predicting IAV host specificity, offering novel insights into the evolutionary trajectory of these viruses. The model's significance extends beyond evolutionary analysis, playing a pivotal role in outbreak surveillance and contributing to efforts aimed at preventing the viral spread on a global scale.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"96"},"PeriodicalIF":4.3,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12374346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952158","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":"Clinical and prognostic significance of m6A hypomethylation and IGF2BP3 overexpression in gastric cancer: an integrated epigenomic-transcriptomic analysis.","authors":"Xiangchen Hu, Zhe Wang, Youwei Kou, Yujing Huang","doi":"10.1186/s40246-025-00802-0","DOIUrl":"https://doi.org/10.1186/s40246-025-00802-0","url":null,"abstract":"<p><strong>Background: </strong>Gastric cancer (GC) ranks as the fifth most prevalent malignancy and the third leading cause of cancer-related mortality worldwide, with complex pathogenesis driven by genetic and epigenetic alterations. While genetic contributors to GC have been extensively studied, the functional role of N6-methyladenosine (m6A) RNA methylation-the most abundant eukaryotic RNA modification-in gastric carcinogenesis remains insufficiently characterized. This study aimed to investigate transcriptome-wide m6A methylation dysregulation and its mechanistic implications in GC progression.</p><p><strong>Methods: </strong>Methylated RNA immunoprecipitation sequencing (MeRIP-seq) was performed to map m6A epitranscriptomes in paired GC and adjacent normal tissues. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted on 253 hypomethylated mRNAs to delineate the biological pathways associated with m6A dysregulation. The transcriptomic profiles were analyzed using RNA-seq, while a retrospective cohort analysis (n = 58) evaluated the correlations between IGF2BP3 expression and the clinicopathological characteristics of patients with GC.</p><p><strong>Results: </strong>MeRIP-seq analysis demonstrated transcriptome-wide m6A hypomethylation in GC tissues, identifying 271 significantly reduced peaks (p < 0.01). Functional annotation revealed enrichment of hypomethylated transcripts in metabolic pathways and transcriptional dysregulation. Notably, m6A-related genes exhibited widespread activation in GC, with IGF2BP3 showing the most pronounced upregulation (106-fold increase, p < 0.0001). Clinically, elevated IGF2BP3 expression significantly correlated with lymph node involvement (p = 0.016) and advanced TNM staging (p = 0.028).</p><p><strong>Conclusion: </strong>This study establishes m6A methylation dysregulation as a critical mechanism in GC pathogenesis and identifies IGF2BP3 as both a potential therapeutic target and a prognostic biomarker in GC.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"95"},"PeriodicalIF":4.3,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12374356/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144952145","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":"Variants of NLRP genes encoding subcortical maternal complex components are linked to biparental placental mesenchymal dysplasia.","authors":"Ayaka Murase, Hiroyuki Mishima, Saori Aoki, Satoshi Hara, Musashi Kubiura-Ichimaru, Takashi Ohba, Koh-Ichiro Yoshiura, Hidenobu Soejima","doi":"10.1186/s40246-025-00814-w","DOIUrl":"10.1186/s40246-025-00814-w","url":null,"abstract":"<p><strong>Background: </strong>Placental mesenchymal dysplasia (PMD) is a placental abnormality resembling partial hydatidiform moles without trophoblastic proliferation. Although many PMD cases involve androgenetic/biparental mosaicism or chimerism, we recently reported that approximately 30% of cases retain biparental genomes (BiPMD) and exhibit aberrant methylation at multiple imprinted differentially methylated regions (DMRs). This resembles multilocus imprinting disturbances (MLIDs) and biparental hydatidiform moles (BiHMs), which are associated with pathogenic variants in subcortical maternal complex (SCMC) genes. However, the involvement of SCMC variants in BiPMD pathogenesis remains unclear.</p><p><strong>Results: </strong>We performed whole-exome sequencing on seven mothers with BiPMD during pregnancy, focusing on SCMC-related and DNA methylation maintenance genes. We identified compound heterozygous frameshift and missense variants in NLRP5 in one mother, and a heterozygous missense variant in NLRP2 in another. In silico predictions suggested that the NLRP5 frameshift variant was pathogenic, whereas the missense variants were deemed likely benign. Methylation specific-multiplex ligation-dependent probe amplification (MS-MLPA) of placental tissues revealed aberrant methylation patterns in multiple imprinted DMRs. The affected DMRs varied between cases and within the same case, with abnormalities also observed in macroscopically normal placental regions.</p><p><strong>Conclusions: </strong>These findings suggest that maternal variants in NLRP genes, which encode components of the SCMC, may contribute to the development of BiPMD with MLIDs. SCMC dysfunction due to SCMC gene mutations may cause aberrant methylation at imprinted DMRs in early embryos with cell-to-cell variation in the affected DMRs among cells, leading to a mosaic pattern of abnormal cells and normal cells. Through differentiation into placental tissues in this mosaic condition, BiPMD with aberrant methylation of multiple DMRs can occur. Taken together, our findings support the hypothesis that MLID in live-born individuals, BiPMD, and BiHMs may collectively represent a continuum within the MLID spectrum. Further studies are needed to elucidate how SCMC dysfunction leads to imprinting errors and to improve the diagnosis and understanding of PMD and related imprinting disorders.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"94"},"PeriodicalIF":4.3,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12366317/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144882725","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":"Bringing our genomes to medicine - the 2026 human genome meeting.","authors":"George P Patrinos, Juergen K V Reichardt, Piero Carninci, Ada Hamosh, Christina Mitropoulou, Vasilis Vasiliou","doi":"10.1186/s40246-025-00804-y","DOIUrl":"10.1186/s40246-025-00804-y","url":null,"abstract":"","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"93"},"PeriodicalIF":4.3,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12355788/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144855071","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":"MicroRNAs in long COVID: roles, diagnostic biomarker potential and detection.","authors":"Naomi-Eunicia Paval, Olga Adriana Căliman-Sturdza, Andrei Lobiuc, Mihai Dimian, Ioan-Ovidiu Sirbu, Mihai Covasa","doi":"10.1186/s40246-025-00810-0","DOIUrl":"10.1186/s40246-025-00810-0","url":null,"abstract":"<p><p>Long COVID or Post-Acute Sequelae of SARS-CoV-2 Infection (PASC), marked by persistent symptoms lasting weeks to months after acute SARS-CoV-2 infection, affects multiple organ systems including the respiratory, cardiovascular, neurological, gastrointestinal, and renal systems. These prolonged effects stem from chronic inflammation, immune dysregulation, and direct viral injury. MicroRNAs (miRNAs)-small non-coding RNAs involved in gene regulation-play a pivotal role in this process by modulating immune responses, inflammation, and cellular stress. Altered miRNA expression patterns during and after infection contribute to the pathogenesis of Long COVID. While conventional miRNA detection techniques have been valuable, they face limitations in sensitivity, throughput, and detecting RNA modifications. This review highlights Oxford Nanopore Sequencing (ONS) as a promising alternative, offering real-time, long-read, amplification-free RNA sequencing that preserves native modifications. ONS enables direct sequencing of full-length miRNAs and their precursors, providing novel insights into miRNA processing and regulatory roles. Despite current challenges with short-read accuracy, ongoing technical advances are improving ONS performance. Its integration in miRNA profiling holds significant potential for uncovering novel regulatory interactions and advancing clinical biomarker discovery in Long COVID and other conditions.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"90"},"PeriodicalIF":4.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352008/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144845834","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":"Spatial transcriptomics and scRNA-seq: decoding tumor complexity and constructing prognostic models in colorectal cancer.","authors":"Wei Song, Yatao Wang, Min Zhou, Fengqin Guo, Yanliang Liu","doi":"10.1186/s40246-025-00805-x","DOIUrl":"10.1186/s40246-025-00805-x","url":null,"abstract":"<p><strong>Introduction: </strong>Recent advancements in transcriptomic analysis, combined with single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics, have deepened our understanding of the tumor microenvironment and cellular heterogeneity, laying the groundwork for personalized therapies. The aim of this research is to explore the heterogeneity of tumor cells in colorectal cancer (CRC) and evaluate their prognostic value in different therapeutic contexts, emphasizing the impact of tumor cell heterogeneity on disease progression.</p><p><strong>Methods: </strong>scRNA-seq alongside spatial transcriptomics was employed to analyze the heterogeneity of tumor cells in CRC, the spatial distribution of tumor cells, and their interactions with the microenvironment.</p><p><strong>Results: </strong>We identified nine distinct tumor cell subtypes, with MLXIPL + neoplasm prevalent in advanced CRC, while ADH1C + and MUC2 + neoplasms were more common in early-stage CRC. MLXIPL + neoplasm was significantly associated with chemotherapy and targeted therapy efficacy. Analysis of spatial transcriptomics indicated that MLXIPL + neoplasm is located in the core area of the tumor cells. We developed a 13-gene prognostic signature (PS) using machine learning algorithm (StepCox backward), which predicts the prognosis of CRC patients. Furthermore, the patients with low PS score demonstrated higher immune cell infiltration and immune regulatory factors, suggesting enhanced immune surveillance and treatment response.</p><p><strong>Conclusions: </strong>The findings highlight the critical role of tumor cell heterogeneity in CRC progression and treatment response, suggesting the need for personalized therapeutic strategies targeting different subpopulations. The constructed PS demonstrates significant clinical application value in predicting patient prognosis.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"92"},"PeriodicalIF":4.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12351954/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144845835","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":"Whole-exome sequencing identifies TRIM72 as a candidate gene for autosomal recessive limb-girdle muscular dystrophy.","authors":"Abdelaziz Tlili, Abdullah Al Mutery","doi":"10.1186/s40246-025-00809-7","DOIUrl":"10.1186/s40246-025-00809-7","url":null,"abstract":"<p><strong>Background: </strong>Limb-girdle muscular dystrophies (LGMDs) constitute a genetically diverse group of disorders characterized by progressive proximal muscle weakness and atrophy. Despite advances in genetic diagnostics, numerous cases remain unresolved due to extensive genetic heterogeneity, emphasizing the necessity for continued identification of novel pathogenic variants.</p><p><strong>Results: </strong>Using whole-exome sequencing (WES) in a Saudi family affected by autosomal recessive LGMD, we identified a novel homozygous frameshift mutation (c.891delT; p.Ala298ArgfsTer64) in the TRIM72 (MG53) gene, which we propose as a strong candidate gene for LGMD. Segregation analysis via Sanger sequencing confirmed that the variant co-segregated precisely with the disease phenotype and was absent in ethnically matched control cohorts. TRIM72 encodes a muscle-specific E3 ubiquitin ligase involved in sarcolemmal membrane repair, critical for maintaining muscle cell integrity. Functional parallels between TRIM72 and the LGMD-associated TRIM32, alongside corroborating evidence from animal models and cellular studies, support the candidacy of TRIM72 in LGMD pathogenesis.</p><p><strong>Conclusion: </strong>Our findings identify TRIM72 as a novel candidate gene implicated in autosomal recessive LGMD, expanding the genetic spectrum of this heterogeneous disease. This discovery underscores the critical roles of TRIM family proteins in muscle pathology and reinforces the value of advanced genetic sequencing methodologies in diagnosing unresolved muscular dystrophy cases.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"91"},"PeriodicalIF":4.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12351760/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144845836","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":"Insights into the tripartite relationship between cervical cancer, human papillomavirus, and the vaginal microbiome: a mega-analysis.","authors":"Hannah H Rashwan, Mohammed H Ali, Mazen M Mostafa, Raghda Ramadan, Mohamed Mysara","doi":"10.1186/s40246-025-00795-w","DOIUrl":"10.1186/s40246-025-00795-w","url":null,"abstract":"<p><strong>Background: </strong>Cervical cancer (CC) is the fourth most prevalent malignancy among women worldwide, where 99.7% of the cases are linked to persistent human papillomavirus (HPV) infections. While emerging evidence suggests a role for vaginal microbiome dysbiosis in HPV-driven CC, the specific microbial alterations and their functional implications remain unclear. However, inconsistencies in identifying specific microbial signatures-largely due to heterogeneous study designs, targeted 16S rRNA regions, and data processing methods-have limited the generalizability of existing findings. To address these challenges, we conducted a standardized mega-analysis using a compositionality-aware approach to ensure consistency and minimize technical bias across studies.</p><p><strong>Results: </strong>Our mega-analysis consolidates findings from five case-control 16S rRNA ampilicon sequencing studies, encompassing 215 samples. Compared to healthy controls, CC patients exhibited significantly higher alpha diversity (Shannon index, p <0.005) and a shift from a Lactobacillus-dominant to a polymicrobial vaginal microbiome. This microbial dysbiosis was characterized by an increased abundance of Porphyromonadaceae, particularly Porphyromonas asaccharolytica, and other anaerobic bacterial species such as Campylobacter ureolyticus, Peptococcus niger, and Anaerococcus obesiensis (FDR <0.05). Functional profiling of the altered microbiome revealed enrichment in pathways associated with chronic inflammation, fatty acid biosynthesis, amino acid metabolism, cellular proliferation, invasion, and metastasis.</p><p><strong>Conclusions: </strong>This mega-analysis presents the most methodologically homogeneous study to date of CC-associated vaginal microbiome using publicly available 16S datasets. Our findings not only deepen our understanding of microbial influences on CC but also pave the way for novel diagnostic and therapeutic approaches potentially enhancing patient outcomes in CC care. These insights open new avenues for clinical interventions that extend beyond conventional HPV-centric strategies.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"89"},"PeriodicalIF":4.3,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12341356/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144834982","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":"Correction: Identification and experimental validation of ulcerative colitis-associated hub genes through integrated WGCNA and lysosomal autophagy analysis.","authors":"Yuanpei Zhao, Yijun Li, Qingwen Xu, Lili Ding, Weiming Li, Qinghua Zou, Yichen Hu, Kaiwen Shi, Hongyuan Liu","doi":"10.1186/s40246-025-00799-6","DOIUrl":"10.1186/s40246-025-00799-6","url":null,"abstract":"","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"88"},"PeriodicalIF":4.3,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335045/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144811998","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}