Genome Medicine最新文献

{"title":"MorphoITH: a framework for deconvolving intra-tumor heterogeneity using tissue morphology.","authors":"Aleksandra Weronika Nielsen, Hafez Eslami Manoochehri, Hua Zhong, Vandana Panwar, Vipul Jarmale, Jay Jasti, Mehrdad Nourani, Dinesh Rakheja, James Brugarolas, Payal Kapur, Satwik Rajaram","doi":"10.1186/s13073-025-01504-x","DOIUrl":"10.1186/s13073-025-01504-x","url":null,"abstract":"<p><strong>Background: </strong>Tumor evolution, driven by the emergence of genetically and epigenetically distinct subclones, enables cancers to adapt to selective pressures and become more aggressive, posing a major challenge in oncology. Multi-regional sequencing has been the primary means of studying tumor evolution and the resultant intra-tumor heterogeneity (ITH), but its high cost, resource-intensiveness, and limited scalability have hindered clinical utility.</p><p><strong>Methods: </strong>Here, we present MorphoITH, a novel framework that aims to infer molecular ITH from routinely collected histopathology slides by quantifying phenotypic diversity. MorphoITH integrates a task-agnostic, self-supervised deep learning similarity measure to capture phenotypic variation across multiple dimensions (cytology, architecture, and microenvironment) along with rigorous methods to eliminate spurious sources of variation.</p><p><strong>Results: </strong>Applying MorphoITH to clear cell renal cell carcinoma (ccRCC), a disease notably shaped by ITH, we show that it captures clinically significant biological features such as vascular architecture and nuclear grade. MorphoITH also recognizes morphological changes associated with subclonal alterations in key driver genes (BAP1, PBRM1, SETD2). Finally, in a multi-regional sequencing dataset, we find that the morphological trajectories revealed by MorphoITH largely mirror underlying patterns of genetic evolution.</p><p><strong>Conclusions: </strong>MorphoITH provides a scalable and rigorous approach to quantify morphological ITH, serving as a potential proxy for underlying genetic ITH and tumor evolution. By linking histopathology with genomic insights, it lays the foundation for more refined phenotypic profiling in support of precision oncology.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"101"},"PeriodicalIF":10.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12447597/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145085932","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":"Evaluating genome sequencing strategies: trio, singleton, and standard testing in rare disease diagnosis.","authors":"Daniel Kaschta, Christina Post, Franziska Gaass, Milad Al-Tawil, Vincent Arriens, Saranya Balachandran, Tobias Bäumer, Valerie Berge, Friederike Birgel, Andreas Dalski, Maike Dittmar, Andre Franke, Sören Franzenburg, Janina Fuß, Bettina Gehring, Rebecca Gembicki, Bianca Greiten, Kristin Grohte, Britta Hanker, Kristian Händler, Lana Harder, Yorck Hellenbroich, Theresia Herget, Gloria Herrmann, Olaf Hiort, Kirstin Hoff, Birga Hoffmann, Nadine Hornig, Irina Hüning, Monika Kautza-Lucht, Juliane Köhler, Anna-Sophie Liegmann, Jasmin Lisfeld, Britt-Sabina Löscher, Nils G Margraf, Michelle Meyenborg, Anna Möllring, Hiltrud Muhle, Eva Maria Murga Penas, Henning Nommels, Dzhoy Papingi, Imke Poggenburg, Jelena Pozojevic, Philip Rosenstiel, Andreas Recke, Kimberly Roberts, Laelia Rösler, Franka Rust, Maj-Britt Salewski, Katharina Schau-Römer, Christian Schlein, Varun K A Sreenivasan, Louiza Toutouna, Caroline Utermann-Thüsing, Amelie T van der Ven, Alexander E Volk, Janne Wehnert, Sandra Wilson, Rixa Woitschach, Veronica Yumiceba, Christine Zühlke, Alexander Münchau, Norbert Brüggemann, Inga Vater, Almuth Caliebe, Inga Nagel, Malte Spielmann","doi":"10.1186/s13073-025-01516-7","DOIUrl":"10.1186/s13073-025-01516-7","url":null,"abstract":"<p><strong>Background: </strong>Short-read genome sequencing (GS) is among the most comprehensive genetic testing methods available, capable of detecting single-nucleotide variants, copy-number variants, mitochondrial variants, repeat expansions, and structural variants in a single assay. Despite its technical advantages, the full clinical utility of GS in real-world diagnostic settings remains to be fully established.</p><p><strong>Methods: </strong>This study systematically compared singleton GS (sGS), trio GS (tGS), and exome sequencing-based standard-of-care (SoC) genetic testing in 416 patients with rare diseases in a blinded, prospective study. Three independent teams with divergent baseline expertise evaluated the diagnostic yield of GS as a unifying first-tier test and directly compared its variant detection capabilities, learning curve, and clinical feasibility. The SoC team had extensive prior experience in exome-based diagnostics, while the sGS and tGS teams were newly trained in GS interpretation. Diagnostic yield was assessed through both prospective and retrospective analyses.</p><p><strong>Results: </strong>In our prospective analysis, tGS achieved the highest diagnostic yield for likely pathogenic/pathogenic variants at 36.1% in the newly trained team, surpassing the experienced SoC team at 35.1% and the newly trained sGS team at 28.8%. To evaluate which variants could technically be identified and account for differences in team experience, we conducted a retrospective analysis, achieving diagnostic yields of 36.7% for SoC, 39.1% for sGS, and 40.0% for tGS. The superior yield of GS was attributed to its ability to detect deep intronic, non-coding, and small copy-number variants missed by SoC. Notably, tGS identified three de novo variants classified as likely pathogenic based on recent GeneMatcher collaborations and newly published gene-disease association studies.</p><p><strong>Conclusions: </strong>Our findings demonstrate that GS, particularly tGS, outperforms SoC in diagnosing rare diseases, with sGS providing a more cost-effective alternative. These results suggest that GS should be considered a first-tier genetic test, offering an efficient, single-step approach to reduce the diagnostic odyssey for patients with rare diseases. The trio approach proved especially valuable for less experienced teams, as inheritance data facilitated variant interpretation and maintained high diagnostic yield, while experienced teams achieved comparable results with singleton analysis alone.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"100"},"PeriodicalIF":10.4,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12445032/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145080347","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":"Publisher Correction: Evaluation of familial phenotype deviation to measure the impact of de novo mutations in autism.","authors":"Soo-Whee Kim, Hyeji Lee, Da Yea Song, Gang-Hee Lee, Jae Hyun Han, Jee Won Lee, Hee Jung Byun, Ji Hyun Son, Ye Rim Kim, Yoojeong Lee, Eunjoon Kim, Donna M Werling, So Hyun Kim, Stephan J Sanders, Hee Jeong Yoo, Joon-Yong An","doi":"10.1186/s13073-025-01540-7","DOIUrl":"10.1186/s13073-025-01540-7","url":null,"abstract":"","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"99"},"PeriodicalIF":10.4,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12409946/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145000411","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":"Deep learning-based histomorphological subtyping and risk stratification of small cell lung cancer from hematoxylin and eosin-stained whole slide images.","authors":"Yibo Zhang, Shilong Liu, Jun Chen, Ruanqi Chen, Zijian Yang, Ruyu Sheng, Xin Li, Taolue Wang, Hongyu Liu, Fan Yang, Jianming Ying, Lin Yang, Jie Sun, Meng Zhou","doi":"10.1186/s13073-025-01526-5","DOIUrl":"10.1186/s13073-025-01526-5","url":null,"abstract":"<p><strong>Background: </strong>Accurate subtyping and risk stratification are imperative for prognostication and clinical decision-making in small cell lung cancer (SCLC). However, traditional molecular subtyping is resource-intensive and challenging to translate into clinical practice.</p><p><strong>Methods: </strong>A total of 517 SCLC patients and their corresponding hematoxylin and eosin (H&E)-stained whole slide images (WSIs) from three independent medical institutions were analyzed. A hybrid clustering-based unsupervised deep representation learning model was developed to identify histomorphological phenotypes (HIPO) and characterize tumor ecosystem diversity. Consensus clustering and a deep learning-based stratification system were used to define histomorphological subtypes (HIPOS) based on patient-level HIPO features. Survival analysis and Cox proportional hazards regression models were used to assess the clinical significance of HIPOS. An integrated analysis of pathomics, proteomics, and immunohistochemistry was conducted to explore the biological and microenvironmental correlates of HIPOS.</p><p><strong>Results: </strong>We performed histomorphological phenotyping of SCLC using unsupervised deep representation learning from WSIs and identified 15 HIPOs. Unsupervised clustering of HIPO profiles stratified SCLCs into two reproducible image-based subtypes: HIPOS-I and HIPOS-II. Patients in the HIPOS-I group had better overall survival and disease-free survival compared to those in HIPOS-II, independent of clinical features and molecular subtypes. Multimodal analyses revealed that HIPOS-I tumors were characterized by enriched immune infiltration and immune activation, whereas HIPOS-II tumors displayed increased fibrosis, cellular pleomorphism, and dysregulated oxidative metabolism. Additionally, we developed a simplified deep-learning model to predict HIPOS subtypes to enhance clinical applications and validated the prognostic value of these subtypes in independent cohorts.</p><p><strong>Conclusions: </strong>This study demonstrates the potential of a deep learning-based histomorphological subtyping system to improve patient stratification and prognosis prediction in SCLC. The HIPOS offers a promising and clinically applicable tool for personalized management using routine H&E-stained WSIs.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"98"},"PeriodicalIF":10.4,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12406473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144951163","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":"Integrating breast cancer polygenic risk scores at scale in the WISDOM Study: a national randomized personalized screening trial.","authors":"Kirkpatrick B Fergus, Rachel S Heise, Lisa Madlensky, Allison Fiscalini, Leah Sabacan, Sarah Theiner, Shreya Kapoor, Irene A Soto, Amie Blanco, Katherine Ross, Deborah Goodman-Gruen, Maren Scheuner, Donglei Hu, Diane Heditsian, Susie Brain, Vignesh A Arasu, Andrea Kaster, Lisa Chapa, Olufunmilayo I Olopade, Martin Eklund, Jeffrey A Tice, Elad Ziv, Laura van 't Veer, Laura J Esserman, Yiwey Shieh","doi":"10.1186/s13073-025-01524-7","DOIUrl":"https://doi.org/10.1186/s13073-025-01524-7","url":null,"abstract":"<p><strong>Background: </strong>The Women Informed to Screen Depending On Measures of risk (WISDOM) Study is the first prospective, population-wide application of personalized breast cancer screening. We aim to demonstrate the feasibility of the study's novel use of polygenic risk scores (PRSs) to tailor screening, evaluate our strategy for adapting PRSs to diverse populations, and quantify the impact of incorporating PRS on the study's screening recommendations.</p><p><strong>Methods: </strong>WISDOM is a randomized, preference-tolerant screening trial in the USA testing the safety and morbidity of risk-based versus annual screening in women aged 40-74 without a prior history of breast cancer. This early report includes participants in the risk-based arm only and compares screening recommendations generated by the Breast Cancer Surveillance Consortium (BCSC) clinical risk model alone versus the BCSC model modified by a PRS (BCSC-PRS). The main outcome of interest is the proportion of participants with a change in screening recommendation after integrating PRS for risk stratification.</p><p><strong>Results: </strong>In the risk-based arm, 21,631 participants received a PRS. Small but statistically significant differences in the PRS were seen between major racial and ethnic groups (p < 0.001), and higher PRS was associated with greater extent of family history (p < 0.001) and denser breasts (p < 0.001). BCSC-PRS risk estimates changed the screening recommendations for 14% of women aged 40-49 compared to BCSC alone and for 10% of women aged 50-74. Projected net screening encounters at the population level were similar for both age groups.</p><p><strong>Conclusions: </strong>In a first-in-kind application of PRS to inform breast cancer screening approaches, we demonstrate feasibility for scaled implementation, moderate changes to individual screening recommendations, and minimal projected downstream burden on the healthcare system.</p><p><strong>Trial registration: </strong>Prospectively registered on ClinicalTrials.gov as NCT02620852 on 12/2/2015.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"97"},"PeriodicalIF":10.4,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12395744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144951145","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":"Correction: Single-nucleus transcriptomics reveals a distinct microglial state and increased MSR1-mediated phagocytosis as common features across dementia subtypes.","authors":"Sook-Yoong Chia, Mengwei Li, Zhihong Li, Haitao Tu, Jolene Wei Ling Lee, Lifeng Qiu, Jingjing Ling, Richard Reynolds, Salvatore Albani, Eng-King Tan, Adeline Su Lyn Ng, Jinmiao Chen, Li Zeng","doi":"10.1186/s13073-025-01537-2","DOIUrl":"https://doi.org/10.1186/s13073-025-01537-2","url":null,"abstract":"","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"96"},"PeriodicalIF":10.4,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12392659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144951147","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":"Effect of clonal hematopoiesis on plaque morphology and prognosis in patients with acute myocardial infarction.","authors":"Jiannan Li, Runzhen Chen, Jinying Zhou, Nan Li, Peng Zhou, Chen Liu, Li Song, Xiaoxiao Zhao, Yi Chen, Shaodi Yan, Hongbing Yan, Yu Tan, Hanjun Zhao","doi":"10.1186/s13073-025-01531-8","DOIUrl":"10.1186/s13073-025-01531-8","url":null,"abstract":"<p><strong>Background: </strong>Clonal hematopoiesis of indeterminate potential (CHIP) is related to cardiovascular disorders and poor prognosis. However, the relationship between CHIP and clinical outcome as well as pathological phenotype of patients with acute myocardial infarction was unknown. Herein, we aimed to investigate the associations between CHIP mutation stratified by variant allele frequency (VAF) from 0.5% to 2% and the incidence of major adverse cardiovascular events (MACE) as well as the characteristics of culprit lesions in patients with ST-segment elevation myocardial infarction (STEMI).</p><p><strong>Methods: </strong>Targeted deep sequencing with a unique molecular identifier (UMI) was used to examine CHIP with VAFs greater than 0.5%, 1%, and 2% in prospective cohort including a total of 1403 patients with STEMI, and MACE including all-cause death, myocardial infarction, stroke, and unplanned revascularization during follow-up was recorded. In addition, the morphology of culprit plaques detected by optical coherence tomography (OCT) in 355 patients with de novo lesions were evaluated via image analysis.</p><p><strong>Results: </strong>The CHIP mutation frequency in each VAF stratification increased with increasing age. Patients with either TET2 or ASXL1 CHIP mutations presented significantly greater mortality than those without for VAF > 2%, 1%, and 0.5% (17.1% vs. 10.1%, p = 0.0001; 17.0% vs. 10.3%, p = 0.0464; and 17.8% vs. 9.8%, p = 0.0025 for VAF > 2%, 1%, and 0.5%, respectively). For other MACE including myocardial infarction, stroke and unplanned revascularization, no significant difference was observed. Simultaneous assessment of CHIP and systemic inflammation revealed combined effects on all-cause mortality, depicted by significant higher risk for patients with high-sensitivity C-reactive protein level > 5.8 mg/L and concomitant CHIP. Moreover, subgroup analysis revealed that patients with CHIP mutations got greater clinical benefit of ticagrelor and statin than those without CHIP. Additionally, patients with TET2/ASXL1 VAFs of > 0.5% and 1% were significantly prone to exhibit a greater prevalence of ruptured fibrous cap in culprit lesions than those without (33 [70.2%] vs. 145 [47.1%], p = 0.0031; 16 [72.7%] vs. 162 [48.6%], p = 0.0287).</p><p><strong>Conclusions: </strong>TET2/ASXL1 CHIP mutations with VAF > 2% combined with high inflammatory status were indicative of high mortality in patients with STEMI. Additionally, TET2/ASXL1 mutation with a VAF > 0.5% favored the recognition of vulnerable plaque features in patients with STEMI.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"94"},"PeriodicalIF":10.4,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12376346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144951137","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":"Replication-associated mechanisms contribute to an increased CpG > TpG mutation burden in mismatch repair-deficient cancers.","authors":"Joseph C Ward, Ignacio Soriano, Steve Thorn, Juan Fernández-Tajes, Kitty Sherwood, Güler Gül, Joost Scheffers, Anna Frangou, Ben Kinnersley, Ioannis Kafetzopoulos, Duncan Sproul, Sara Galavotti, Claire Palles, Andreas J Gruber, David N Church, Ian Tomlinson","doi":"10.1186/s13073-025-01525-6","DOIUrl":"https://doi.org/10.1186/s13073-025-01525-6","url":null,"abstract":"<p><strong>Background: </strong>Single base substitution (SBS) mutations, particularly C > T and T > C, are increased owing to unrepaired DNA replication errors in mismatch repair-deficient (MMRd) cancers. Excess CpG > TpG mutations have been reported in MMRd cancers defective in mismatch detection (dMutSα), but not in mismatch correction (dMutLα). Somatic CpG > TpG mutations conventionally result from unrepaired spontaneous deamination of 5'-methylcytosine throughout the cell cycle, causing T:G mismatches and signature SBS1. It has been proposed that MutSα detects those mismatches, prior to error correction by base excision repair (BER). However, other evidence appears inconsistent with that hypothesis: for example, MutSα is specifically expressed in S/G₂ phases of the cell cycle, and defects in replicative DNA polymerase proofreading specifically cause excess CpG > TpG mutations in signature SBS10b.</p><p><strong>Methods: </strong>We analysed mutation spectra and COSMIC mutation signatures in whole-genome sequencing data from 1803 colorectal cancers (164 dMutLα, 20 dMutSα) and 596 endometrial cancers (103 dMutLα, 9 dMutSα) from the UK 100,000 Genomes Project. We mapped each C > T mutation to its genomic features, including normal DNA methylation state, replication timing, transcription strand, and replication strand, to investigate the mechanism(s) by which these mutations arise.</p><p><strong>Results: </strong>We confirmed that dMutSα tumours specifically had higher CpG > TpG burdens than dMutLα tumours. We could fully reconstitute the observed dMutSα CpG > TpG mutation spectrum by adding CpG > TpG mutations in proportion to their SBS1 activity to the dMutLα spectrum. However, other evidence indicated that the SBS1 excess in dMutSα cancers did not come from 5'-methylcytosine deamination alone: non-CpG C > T mutations were also increased in dMutSα cancers; and, in contrast to tumours deficient in BER, CpG > TpG mutations were biased to the leading DNA replication strand, at similar levels in dMutSα and dMutLα cancers, suggesting an origin in DNA replication. Other substitution mutations usually corrected by BER were not increased in dMutSα tumours.</p><p><strong>Conclusions: </strong>There is a CpG > TpG and SBS1 excess specific to dMutSα MMRd tumours, consistent with previous reports, and we find a general increase in somatic C > T mutations. Contrary to some other studies, the similar leading replication strand bias in both dMutSα and dMutLα tumours indicates that at least some of the excess CpG > TpG mutations arise via DNA replication errors, and not primarily via the replication-independent deamination of 5'-methylcytosine.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"95"},"PeriodicalIF":10.4,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12376743/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144951101","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":"Evaluation of familial phenotype deviation to measure the impact of de novo mutations in autism.","authors":"Soo-Whee Kim, Hyeji Lee, Da Yea Song, Gang-Hee Lee, Jae Hyun Han, Jee Won Lee, Hee Jung Byun, Ji Hyun Son, Ye Rim Kim, Yoojeong Lee, Eunjoon Kim, Donna M Werling, So Hyun Kim, Stephan J Sanders, Hee Jeong Yoo, Joon-Yong An","doi":"10.1186/s13073-025-01532-7","DOIUrl":"10.1186/s13073-025-01532-7","url":null,"abstract":"<p><strong>Background: </strong>The phenotypic outcomes of de novo variants (DNVs) in autism spectrum disorder (ASD) exhibit wide variability. To date, no study has comprehensively estimated DNV effects accounting for familial phenotypic background.</p><p><strong>Methods: </strong>To evaluate DNV effects in a family-relative context, we defined within-family standardized deviations (WFSD) by subtracting phenotype scores of unaffected family members and standardizing the result. We applied this approach to 78,685 individuals from 21,735 families from ASD cohorts of diverse ancestries. We compared the distribution, associations with disruptive DNVs, and gene discovery results between WFSD and raw phenotype scores. We further performed outlier analysis based on WFSDs per gene to detect genes with high variability between families.</p><p><strong>Results: </strong>We observed that ASD probands with disruptive DNVs exhibited greater behavioral symptoms and lower adaptive functioning relative to their within-family unaffected members. Compared to raw phenotype scores, WFSD provided clearer associations with DNVs and enabled greater yield in DNV-enriched gene discovery, including 18 novel ASD-associated genes. Outlier analysis identified 11 genes with high intrafamilial variability in phenotypic effects, influenced by mutation sites within functional domains or exons.</p><p><strong>Conclusions: </strong>Familial DNV analysis provides accurate effect estimates, a reliable basis for predicting clinical outcomes, and precise support while minimizing confounding from family background. This approach improves the identification of ASD-associated genes with true phenotypic effects by reducing variability, as well as genes with genuine phenotypic heterogeneity across families driven by mutation site. These findings enhance our understanding of ASD phenotype variability and inform potential targets for intervention.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"93"},"PeriodicalIF":10.4,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12366145/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144951106","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":"Single-nucleus transcriptomics reveals a distinct microglial state and increased MSR1-mediated phagocytosis as common features across dementia subtypes.","authors":"Sook-Yoong Chia, Mengwei Li, Zhihong Li, Haitao Tu, Jolene Wei Ling Lee, Lifeng Qiu, Jingjing Ling, Richard Reynolds, Salvatore Albani, Eng-King Tan, Adeline Su Lyn Ng, Jinmiao Chen, Li Zeng","doi":"10.1186/s13073-025-01519-4","DOIUrl":"10.1186/s13073-025-01519-4","url":null,"abstract":"<p><strong>Background: </strong>Alzheimer's disease (AD), dementia with Lewy bodies (DLB), and Parkinson's disease dementia (PDD) collectively represent the majority of dementia cases worldwide. While these subtypes share clinical, genetic, and pathological features, their transcriptomic similarities and differences remain poorly understood.</p><p><strong>Methods: </strong>We applied single-nucleus RNA-sequencing (snRNA-seq) to prefrontal cortex samples from individuals with non-cognitive impairment control (NCI), and dementia subtypes (AD, DLB, and PDD) to investigate cell type-specific gene expression patterns and pathways underlying pathological similarities and differences across dementia subtypes. SnRNA-seq findings were validated through RNAscope, immunohistochemistry, and additional biochemical analyses in human tissues and cellular models.</p><p><strong>Results: </strong>SnRNA-seq analysis revealed elevated microglial proportions across all dementia subtypes compared to NCI. Further analysis of cell type-specific transcriptomes identified overlapping differentially expressed genes (DEGs) between microglia and oligodendrocytes across all dementia subtypes. While AD showed molecular similarities to NCI, PDD and DLB were clustered more closely together, sharing a greater number of DEGs and related pathways, predominantly associated with microglia. Investigation of interactions between microglia and oligodendrocytes revealed a distinct microglial state in all dementia subtypes. MSR1, a gene encoding a scavenger receptor, was upregulated in microglia across all dementia subtypes, along with its associated gene HSPA1A in oligodendrocytes. RNAscope supported the potential interaction between microglia and oligodendrocytes, where these cells were in closer proximity to each other in human cortical tissues of PDD compared to NCI. MSR1 expression was significantly increased in cortical primary microglia from PD mice compared with non-transgenic (NTg) mice. Additionally, the expression of myelin-associated genes (MBP, MOBP, and PLP1) was significantly upregulated in PD microglia compared to NTg, supporting the presence of the distinct microglia. Furthermore, MSR1-positive microglia colocalised with MBP in cortical tissue of PDD patients, suggesting a functional role of MSR1 in myelin debris clearance. Overexpression of MSR1 in microglial cells enhanced their phagocytic activity toward myelin, and reciprocally, myelin treatment upregulated MSR1 protein levels, indicating enhanced MSR1-mediated myelin phagocytosis.</p><p><strong>Conclusions: </strong>Our findings provide novel insights into the cell type-specific role of microglial MSR1 in AD, DLB, and PDD, linking its increased phagocytic capacity to myelin defects as a common feature of neurodegenerative dementias.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"92"},"PeriodicalIF":10.4,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12359983/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144872870","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}