Genome Medicine最新文献

{"title":"Genome sequencing as a generic diagnostic strategy for rare disease.","authors":"Gaby Schobers, Ronny Derks, Amber den Ouden, Hilde Swinkels, Jeroen van Reeuwijk, Ermanno Bosgoed, Dorien Lugtenberg, Su Ming Sun, Jordi Corominas Galbany, Marjan Weiss, Marinus J Blok, Richelle A C M Olde Keizer, Tom Hofste, Debby Hellebrekers, Nicole de Leeuw, Alexander Stegmann, Erik-Jan Kamsteeg, Aimee D C Paulussen, Marjolijn J L Ligtenberg, Xiangqun Zheng Bradley, John Peden, Alejandra Gutierrez, Adam Pullen, Tom Payne, Christian Gilissen, Arthur van den Wijngaard, Han G Brunner, Marcel Nelen, Helger G Yntema, Lisenka E L M Vissers","doi":"10.1186/s13073-024-01301-y","DOIUrl":"10.1186/s13073-024-01301-y","url":null,"abstract":"<p><strong>Background: </strong>To diagnose the full spectrum of hereditary and congenital diseases, genetic laboratories use many different workflows, ranging from karyotyping to exome sequencing. A single generic high-throughput workflow would greatly increase efficiency. We assessed whether genome sequencing (GS) can replace these existing workflows aimed at germline genetic diagnosis for rare disease.</p><p><strong>Methods: </strong>We performed short-read GS (NovaSeq™6000; 150 bp paired-end reads, 37 × mean coverage) on 1000 cases with 1271 known clinically relevant variants, identified across different workflows, representative of our tertiary diagnostic centers. Variants were categorized into small variants (single nucleotide variants and indels < 50 bp), large variants (copy number variants and short tandem repeats) and other variants (structural variants and aneuploidies). Variant calling format files were queried per variant, from which workflow-specific true positive rates (TPRs) for detection were determined. A TPR of ≥ 98% was considered the threshold for transition to GS. A GS-first scenario was generated for our laboratory, using diagnostic efficacy and predicted false negative as primary outcome measures. As input, we modeled the diagnostic path for all 24,570 individuals referred in 2022, combining the clinical referral, the transition of the underlying workflow(s) to GS, and the variant type(s) to be detected.</p><p><strong>Results: </strong>Overall, 95% (1206/1271) of variants were detected. Detection rates differed per variant category: small variants in 96% (826/860), large variants in 93% (341/366), and other variants in 87% (39/45). TPRs varied between workflows (79-100%), with 7/10 being replaceable by GS. Models for our laboratory indicate that a GS-first strategy would be feasible for 84.9% of clinical referrals (750/883), translating to 71% of all individuals (17,444/24,570) receiving GS as their primary test. An estimated false negative rate of 0.3% could be expected.</p><p><strong>Conclusions: </strong>GS can capture clinically relevant germline variants in a 'GS-first strategy' for the majority of clinical indications in a genetics diagnostic lab.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10868087/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139734908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of type 1 diabetes genetic risk screening in children in diverse communities: the Virginia PrIMeD project.","authors":"Kristin A Guertin, David R Repaske, Julia F Taylor, Eli S Williams, Suna Onengut-Gumuscu, Wei-Min Chen, Sarah R Boggs, Liping Yu, Luke Allen, Lacey Botteon, Louis Daniel, Katherine G Keating, Mika K Labergerie, Tyler S Lienhart, Jorge A Gonzalez-Mejia, Matt J Starnowski, Stephen S Rich","doi":"10.1186/s13073-024-01305-8","DOIUrl":"10.1186/s13073-024-01305-8","url":null,"abstract":"<p><strong>Background: </strong>Population screening for risk of type 1 diabetes (T1D) has been proposed to identify those with islet autoimmunity (presence of islet autoantibodies). As islet autoantibodies can be transient, screening with a genetic risk score has been proposed as an entry into autoantibody testing.</p><p><strong>Methods: </strong>Children were recruited from eight general pediatric and specialty clinics across Virginia with diverse community settings. Recruiters in each clinic obtained informed consent/assent, a medical history, and a saliva sample for DNA extraction in children with and without a history of T1D. A custom genotyping panel was used to define T1D genetic risk based upon associated SNPs in European- and African-genetic ancestry. Subjects at \"high genetic risk\" were offered a separate blood collection for screening four islet autoantibodies. A follow-up contact (email, mail, and telephone) in one half of the participants determined interest and occurrence of subsequent T1D.</p><p><strong>Results: </strong>A total of 3818 children aged 2-16 years were recruited, with 14.2% (n = 542) having a \"high genetic risk.\" Of children with \"high genetic risk\" and without pre-existing T1D (n = 494), 7.0% (34/494) consented for autoantibody screening; 82.4% (28/34) who consented also completed the blood collection, and 7.1% (2/28) of them tested positive for multiple autoantibodies. Among children with pre-existing T1D (n = 91), 52% (n = 48) had a \"high genetic risk.\" In the sample of children with existing T1D, there was no relationship between genetic risk and age at T1D onset. A major factor in obtaining islet autoantibody testing was concern over SARS-CoV-2 exposure.</p><p><strong>Conclusions: </strong>Minimally invasive saliva sampling implemented using a genetic risk score can identify children at genetic risk of T1D. Consent for autoantibody screening, however, was limited largely due to the SARS-CoV-2 pandemic and need for blood collection.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10865687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139734909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An atlas of cell-type-specific interactome networks across 44 human tumor types.","authors":"Zekun Li, Gerui Liu, Xiaoxiao Yang, Meng Shu, Wen Jin, Yang Tong, Xiaochuan Liu, Yuting Wang, Jiapei Yuan, Yang Yang","doi":"10.1186/s13073-024-01303-w","DOIUrl":"10.1186/s13073-024-01303-w","url":null,"abstract":"<p><strong>Background: </strong>Biological processes are controlled by groups of genes acting in concert. Investigating gene-gene interactions within different cell types can help researchers understand the regulatory mechanisms behind human complex diseases, such as tumors.</p><p><strong>Methods: </strong>We collected extensive single-cell RNA-seq data from tumors, involving 563 patients with 44 different tumor types. Through our analysis, we identified various cell types in tumors and created an atlas of different immune cell subsets across different tumor types. Using the SCINET method, we reconstructed interactome networks specific to different cell types. Diverse functional data was then integrated to gain biological insights into the networks, including somatic mutation patterns and gene functional annotation. Additionally, genes with prognostic relevance within the networks were also identified. We also examined cell-cell communications to investigate how gene interactions modulate cell-cell interactions.</p><p><strong>Results: </strong>We developed a data portal called CellNetdb for researchers to study cell-type-specific interactome networks. Our findings indicate that these networks can be used to identify genes with topological specificity in different cell types. We also found that prognostic genes can deconvolved into cell types through analyzing network connectivity. Additionally, we identified commonalities and differences in cell-type-specific networks across different tumor types. Our results suggest that these networks can be used to prioritize risk genes.</p><p><strong>Conclusions: </strong>This study presented CellNetdb, a comprehensive repository featuring an atlas of cell-type-specific interactome networks across 44 human tumor types. The findings underscore the utility of these networks in delineating the intricacies of tumor microenvironments and advancing the understanding of molecular mechanisms underpinning human tumors.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10860273/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139722259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular-guided therapy for the treatment of patients with relapsed and refractory childhood cancers: a Beat Childhood Cancer Research Consortium trial.","authors":"Giselle L Saulnier Sholler, Genevieve Bergendahl, Elizabeth C Lewis, Jacqueline Kraveka, William Ferguson, Abhinav B Nagulapally, Karl Dykema, Valerie I Brown, Michael S Isakoff, Joseph Junewick, Deanna Mitchell, Jawhar Rawwas, William Roberts, Don Eslin, Javier Oesterheld, Randal K Wada, Devang Pastakia, Virginia Harrod, Kevin Ginn, Raya Saab, Kevin Bielamowicz, Jason Glover, Eugenia Chang, Gina K Hanna, Daniel Enriquez, Tyler Izatt, Rebecca F Halperin, Abigail Moore, Sara A Byron, William P D Hendricks, Jeffrey M Trent","doi":"10.1186/s13073-024-01297-5","DOIUrl":"10.1186/s13073-024-01297-5","url":null,"abstract":"<p><strong>Background: </strong>Children with relapsed central nervous system (CNS tumors), neuroblastoma, sarcomas, and other rare solid tumors face poor outcomes. This prospective clinical trial examined the feasibility of combining genomic and transcriptomic profiling of tumor samples with a molecular tumor board (MTB) approach to make real‑time treatment decisions for children with relapsed/refractory solid tumors.</p><p><strong>Methods: </strong>Subjects were divided into three strata: stratum 1-relapsed/refractory neuroblastoma; stratum 2-relapsed/refractory CNS tumors; and stratum 3-relapsed/refractory rare solid tumors. Tumor samples were sent for tumor/normal whole-exome (WES) and tumor whole-transcriptome (WTS) sequencing, and the genomic data were used in a multi-institutional MTB to make real‑time treatment decisions. The MTB recommended plan allowed for a combination of up to 4 agents. Feasibility was measured by time to completion of genomic sequencing, MTB review and initiation of treatment. Response was assessed after every two cycles using Response Evaluation Criteria in Solid Tumors (RECIST). Patient clinical benefit was calculated by the sum of the CR, PR, SD, and NED subjects divided by the sum of complete response (CR), partial response (PR), stable disease (SD), no evidence of disease (NED), and progressive disease (PD) subjects. Grade 3 and higher related and unexpected adverse events (AEs) were tabulated for safety evaluation.</p><p><strong>Results: </strong>A total of 186 eligible patients were enrolled with 144 evaluable for safety and 124 evaluable for response. The average number of days from biopsy to initiation of the MTB-recommended combination therapy was 38 days. Patient benefit was exhibited in 65% of all subjects, 67% of neuroblastoma subjects, 73% of CNS tumor subjects, and 60% of rare tumor subjects. There was little associated toxicity above that expected for the MGT drugs used during this trial, suggestive of the safety of utilizing this method of selecting combination targeted therapy.</p><p><strong>Conclusions: </strong>This trial demonstrated the feasibility, safety, and efficacy of a comprehensive sequencing model to guide personalized therapy for patients with any relapsed/refractory solid malignancy. Personalized therapy was well tolerated, and the clinical benefit rate of 65% in these heavily pretreated populations suggests that this treatment strategy could be an effective option for relapsed and refractory pediatric cancers.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov, NCT02162732. Prospectively registered on June 11, 2014.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10860258/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139722277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel genetic markers for chronic kidney disease in a geographically isolated population of Indigenous Australians: Individual and multiple phenotype genome-wide association study.","authors":"Vignesh Arunachalam, Rodney Lea, Wendy Hoy, Simon Lee, Susan Mott, Judith Savige, John D Mathews, Brendan J McMorran, Shivashankar H Nagaraj","doi":"10.1186/s13073-024-01299-3","DOIUrl":"10.1186/s13073-024-01299-3","url":null,"abstract":"<p><strong>Background: </strong>Chronic kidney disease (CKD) is highly prevalent among Indigenous Australians, especially those in remote regions. The Tiwi population has been isolated from mainland Australia for millennia and exhibits unique genetic characteristics that distinguish them from other Indigenous and non-Indigenous populations. Notably, the rate of end-stage renal disease is up to 20 times greater in this population compared to non-Indigenous populations. Despite the identification of numerous genetic loci associated with kidney disease through GWAS, the Indigenous population such as Tiwi remains severely underrepresented and the increased prevalence of CKD in this population may be due to unique disease-causing alleles/genes.</p><p><strong>Methods: </strong>We used albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) to estimate the prevalence of kidney disease in the Tiwi population (N = 492) in comparison to the UK Biobank (UKBB) (N = 134,724) database. We then performed an exploratory factor analysis to identify correlations among 10 CKD-related phenotypes and identify new multi-phenotype factors. We subsequently conducted a genome-wide association study (GWAS) on all single and multiple phenotype factors using mixed linear regression models, adjusted for age, sex, population stratification, and genetic relatedness between individuals.</p><p><strong>Results: </strong>Based on ACR, 20.3% of the population was at severely increased risk of CKD progression and showed elevated levels of ACR compared to the UKBB population independent of HbA1c. A GWAS of ACR revealed novel association loci in the genes MEG3 (chr14:100812018:T:A), RAB36 (rs11704318), and TIAM2 (rs9689640). Additionally, multiple phenotypes GWAS of ACR, eGFR, urine albumin, and serum creatinine identified a novel variant that mapped to the gene MEIS2 (chr15:37218869:A:G). Most of the identified variants were found to be either absent or rare in the UKBB population.</p><p><strong>Conclusions: </strong>Our study highlights the Tiwi population's predisposition towards elevated ACR, and the collection of novel genetic variants associated with kidney function. These associations may prove valuable in the early diagnosis and treatment of renal disease in this underrepresented population. Additionally, further research is needed to comprehensively validate the functions of the identified variants/genes.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10860247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139722278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microbial-derived imidazole propionate links the heart failure-associated microbiome alterations to disease severity.","authors":"Sajan C Raju, Antonio Molinaro, Ayodeji Awoyemi, Silje F Jørgensen, Peder R Braadland, Andraz Nendl, Ingebjørg Seljeflot, Per M Ueland, Adrian McCann, Pål Aukrust, Beate Vestad, Cristiane Mayerhofer, Kaspar Broch, Lars Gullestad, Knut T Lappegård, Bente Halvorsen, Karsten Kristiansen, Johannes R Hov, Marius Trøseid","doi":"10.1186/s13073-024-01296-6","DOIUrl":"10.1186/s13073-024-01296-6","url":null,"abstract":"<p><strong>Background: </strong>Interactions between the gut microbiota, diet, and host metabolism contribute to the development of cardiovascular disease, but a firm link between disease-specific gut microbiota alterations and circulating metabolites is lacking.</p><p><strong>Methods: </strong>We performed shot-gun sequencing on 235 samples from 166 HF patients and 69 healthy control samples. Separate plasma samples from healthy controls (n = 53) were used for the comparison of imidazole propionate (ImP) levels. Taxonomy and functional pathways for shotgun sequencing data was assigned using MetaPhlAn3 and HUMAnN3 pipelines.</p><p><strong>Results: </strong>Here, we show that heart failure (HF) is associated with a specific compositional and functional shift of the gut microbiota that is linked to circulating levels of the microbial histidine-derived metabolite ImP. Circulating ImP levels are elevated in chronic HF patients compared to controls and associated with HF-related gut microbiota alterations. Contrary to the microbiota composition, ImP levels provide insight into etiology and severity of HF and also associate with markers of intestinal permeability and systemic inflammation.</p><p><strong>Conclusions: </strong>Our findings establish a connection between changes in the gut microbiota, the presence, etiology, and severity of HF, and the gut-microbially produced metabolite ImP. While ImP appears promising as a circulating biomarker reflecting gut dysbiosis related to HF, further studies are essential to demonstrate its causal or contributing role in HF pathogenesis.</p><p><strong>Trial registration: </strong>NCT02637167, registered December 22, 2015.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10854170/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139706545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rare subclonal sequencing of breast cancers indicates putative metastatic driver mutations are predominately acquired after dissemination.","authors":"Matthew R Lawrence-Paul, Tien-Chi Pan, Dhruv K Pant, Natalie N C Shih, Yan Chen, George K Belka, Michael Feldman, Angela DeMichele, Lewis A Chodosh","doi":"10.1186/s13073-024-01293-9","DOIUrl":"10.1186/s13073-024-01293-9","url":null,"abstract":"<p><strong>Background: </strong>Evolutionary models of breast cancer progression differ on the extent to which metastatic potential is pre-encoded within primary tumors. Although metastatic recurrences often harbor putative driver mutations that are not detected in their antecedent primary tumor using standard sequencing technologies, whether these mutations were acquired before or after dissemination remains unclear.</p><p><strong>Methods: </strong>To ascertain whether putative metastatic driver mutations initially deemed specific to the metastasis by whole exome sequencing were, in actuality, present within rare ancestral subclones of the primary tumors from which they arose, we employed error-controlled ultra-deep sequencing (UDS-UMI) coupled with FFPE artifact mitigation by uracil-DNA glycosylase (UDG) to assess the presence of 132 \"metastasis-specific\" mutations within antecedent primary tumors from 21 patients. Maximum mutation detection sensitivity was ~1% of primary tumor cells. A conceptual framework was developed to estimate relative likelihoods of alternative models of mutation acquisition.</p><p><strong>Results: </strong>The ancestral primary tumor subclone responsible for seeding the metastasis was identified in 29% of patients, implicating several putative drivers in metastatic seeding including LRP5 A65V and PEAK1 K140Q. Despite this, 93% of metastasis-specific mutations in putative metastatic driver genes remained undetected within primary tumors, as did 96% of metastasis-specific mutations in known breast cancer drivers, including ERRB2 V777L, ESR1 D538G, and AKT1 D323H. Strikingly, even in those cases in which the rare ancestral subclone was identified, 87% of metastasis-specific putative driver mutations remained undetected. Modeling indicated that the sequential acquisition of multiple metastasis-specific driver or passenger mutations within the same rare subclonal lineage of the primary tumor was highly improbable.</p><p><strong>Conclusions: </strong>Our results strongly suggest that metastatic driver mutations are sequentially acquired and selected within the same clonal lineage both before, but more commonly after, dissemination from the primary tumor, and that these mutations are biologically consequential. Despite inherent limitations in sampling archival primary tumors, our findings indicate that tumor cells in most patients continue to undergo clinically relevant genomic evolution after their dissemination from the primary tumor. This provides further evidence that metastatic recurrence is a multi-step, mutation-driven process that extends beyond primary tumor dissemination and underscores the importance of longitudinal tumor assessment to help guide clinical decisions.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10848417/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139697254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pro-inflammatory feedback loops define immune responses to pathogenic Lentivirus infection.","authors":"Aaron J Wilk, Joshua O Marceau, Samuel W Kazer, Ira Fleming, Vincent N Miao, Jennyfer Galvez-Reyes, Jason T Kimata, Alex K Shalek, Susan Holmes, Julie Overbaugh, Catherine A Blish","doi":"10.1186/s13073-024-01290-y","DOIUrl":"10.1186/s13073-024-01290-y","url":null,"abstract":"<p><strong>Background: </strong>The Lentivirus human immunodeficiency virus (HIV) causes chronic inflammation and AIDS in humans, with variable rates of disease progression between individuals driven by both host and viral factors. Similarly, simian lentiviruses vary in their pathogenicity based on characteristics of both the host species and the virus strain, yet the immune underpinnings that drive differential Lentivirus pathogenicity remain incompletely understood.</p><p><strong>Methods: </strong>We profile immune responses in a unique model of differential lentiviral pathogenicity where pig-tailed macaques are infected with highly genetically similar variants of SIV that differ in virulence. We apply longitudinal single-cell transcriptomics to this cohort, along with single-cell resolution cell-cell communication techniques, to understand the immune mechanisms underlying lentiviral pathogenicity.</p><p><strong>Results: </strong>Compared to a minimally pathogenic lentiviral variant, infection with a highly pathogenic variant results in a more delayed, broad, and sustained activation of inflammatory pathways, including an extensive global interferon signature. Conversely, individual cells infected with highly pathogenic Lentivirus upregulated fewer interferon-stimulated genes at a lower magnitude, indicating that highly pathogenic Lentivirus has evolved to partially escape from interferon responses. Further, we identify CXCL10 and CXCL16 as important molecular drivers of inflammatory pathways specifically in response to highly pathogenic Lentivirus infection. Immune responses to highly pathogenic Lentivirus infection are characterized by amplifying regulatory circuits of pro-inflammatory cytokines with dense longitudinal connectivity.</p><p><strong>Conclusions: </strong>Our work presents a model of lentiviral pathogenicity where failures in early viral control mechanisms lead to delayed, sustained, and amplifying pro-inflammatory circuits, which in turn drives disease progression.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10840164/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139691605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Historic methicillin-resistant Staphylococcus aureus: expanding current knowledge using molecular epidemiological characterization of a Swiss legacy collection.","authors":"Vanni Benvenga, Aline Cuénod, Srinithi Purushothaman, Gottfried Dasen, Maja Weisser, Stefano Bassetti, Tim Roloff, Martin Siegemund, Ulrich Heininger, Julia Bielicki, Marianne Wehrli, Paul Friderich, Reno Frei, Andreas Widmer, Kathrin Herzog, Hans Fankhauser, Oliver Nolte, Thomas Bodmer, Martin Risch, Olivier Dubuis, Sigrid Pranghofer, Romana Calligaris-Maibach, Susanne Graf, Vincent Perreten, Helena M B Seth-Smith, Adrian Egli","doi":"10.1186/s13073-024-01292-w","DOIUrl":"10.1186/s13073-024-01292-w","url":null,"abstract":"<p><strong>Background: </strong>Few methicillin-resistant Staphylococcus aureus (MRSA) from the early years of its global emergence have been sequenced. Knowledge about evolutionary factors promoting the success of specific MRSA multi-locus sequence types (MLSTs) remains scarce. We aimed to characterize a legacy MRSA collection isolated from 1965 to 1987 and compare it against publicly available international and local genomes.</p><p><strong>Methods: </strong>We accessed 451 historic (1965-1987) MRSA isolates stored in the Culture Collection of Switzerland, mostly collected from the Zurich region. We determined phenotypic antimicrobial resistance (AMR) and performed whole genome sequencing (WGS) using Illumina short-read sequencing on all isolates and long-read sequencing on a selection with Oxford Nanopore Technology. For context, we included 103 publicly available international assemblies from 1960 to 1992 and sequenced 1207 modern Swiss MRSA isolates from 2007 to 2022. We analyzed the core genome (cg)MLST and predicted SCCmec cassette types, AMR, and virulence genes.</p><p><strong>Results: </strong>Among the 451 historic Swiss MRSA isolates, we found 17 sequence types (STs) of which 11 have been previously described. Two STs were novel combinations of known loci and six isolates carried previously unsubmitted MLST alleles, representing five new STs (ST7843, ST7844, ST7837, ST7839, and ST7842). Most isolates (83% 376/451) represented ST247-MRSA-I isolated in the 1960s, followed by ST7844 (6% 25/451), a novel single locus variant (SLV) of ST239. Analysis by cgMLST indicated that isolates belonging to ST7844-MRSA-III cluster within the diversity of ST239-MRSA-III. Early MRSA were predominantly from clonal complex (CC)8. From 1980 to the end of the twentieth century, we observed that CC22 and CC5 as well as CC8 were present, both locally and internationally.</p><p><strong>Conclusions: </strong>The combined analysis of 1761 historic and contemporary MRSA isolates across more than 50 years uncovered novel STs and allowed us a glimpse into the lineage flux between Swiss-German and international MRSA across time.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10840241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139691639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification.","authors":"Xinan Wang, Ziwei Zhang, Yi Ding, Tony Chen, Lorelei Mucci, Demetrios Albanes, Maria Teresa Landi, Neil E Caporaso, Stephen Lam, Adonina Tardon, Chu Chen, Stig E Bojesen, Mattias Johansson, Angela Risch, Heike Bickeböller, H-Erich Wichmann, Gadi Rennert, Susanne Arnold, Paul Brennan, James D McKay, John K Field, Sanjay S Shete, Loic Le Marchand, Geoffrey Liu, Angeline S Andrew, Lambertus A Kiemeney, Shan Zienolddiny-Narui, Annelie Behndig, Mikael Johansson, Angie Cox, Philip Lazarus, Matthew B Schabath, Melinda C Aldrich, Rayjean J Hung, Christopher I Amos, Xihong Lin, David C Christiani","doi":"10.1186/s13073-024-01298-4","DOIUrl":"10.1186/s13073-024-01298-4","url":null,"abstract":"<p><strong>Background: </strong>Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored.</p><p><strong>Methods: </strong>Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold.</p><p><strong>Results: </strong>Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12-3.50, P-value = 4.13 × 10^-15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99-2.49, P-value = 5.70 × 10^-46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72-0.74).</p><p><strong>Conclusions: </strong>Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10840262/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139691640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}