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Using ensemble learning and hierarchical strategy to predict the outcomes of ESWL for upper ureteral stone treatment

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Computers in Biology and medicine 2024年 179卷 108904-108904页

作者： Chen, Chi-Wei Liu, Wayne-Young Huang, Lan-Ying Chu, Yen-Wei Graduate Degree Program of Smart Healthcare & Bioinformatics I-Shou University Kaohsiung City Taiwan Department of Biomedical Engineering I-Shou University Kaohsiung City Taiwan Doctoral Program in Medical Biotechnology National Chung Hsing University Taichung City Taiwan Department of Urology Jen-Ai Hospital Taichung City Taiwan Graduate Institute of Genomics and Bioinformatics National Chung Hsing University Taichung City Taiwan Institute of Molecular Biology National Chung Hsing University Taichung City Taiwan Agricultural Biotechnology Center National Chung Hsing University Taichung City Taiwan Rong Hsing Research Center for Translational Medicine Taichung City Taiwan Ph. D Program in Medical Biotechnology National Chung Hsing University Taichung City Taiwan Taichung402 Taiwan

Urinary tract stones are a common and frequently recurring medical issue. Accurately predicting the success rate after surgery can help avoid ineffective medical procedures and reduce unnecessary healthcare costs. This study collected data from patients with upper ureter stones who underwent extracorporeal shock wave lithotripsy, including cases of successful as well as unsuccessful stone removal after the first and second lithotripsy procedures, and constructed prediction systems for the outcomes of the first and second lithotripsy procedures. Features were extracted from three categories of information: patient characteristics, stone characteristics, and extracorporeal shock wave lithotripsy machine data, and additional features were created using Feature Creation. Finally, the impact of features on the models was analyzed using six methods to calculate feature importance. Our prediction model for the first lithotripsy, selected from among 43 methods and seven ensemble learning techniques, achieves an AUC of 0.91. For the second lithotripsy, the AUC reaches 0.76. The results indicate that the detailed and binary information provided by patients regarding their history of stone experiences contributes differently to the predictive accuracy of the first and second lithotripsy procedures. The prediction tool is available at https://***/ks. © 2024

关键词： Machine learning

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Differential regulation of JAK1 expression by ETS1 associated with predisposition to primary biliary cholangitis

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Journal of Genetics and genomics 2023年第10期50卷 807-812页

作者： Peng Jiang Chan Wang Mingming Zhang Ye Tian Weifeng Zhao Junyi Xin Yexi Huang Zhibin Zhao Wenjuan Sun Jie Long Ruqi Tang Fang Qiu Xingjuan Shi Yi Zhao Li Zhu Na Dai Lei Liu Xudong Wu Jinshan Nie Bo Jiang Youlin Shao Yueqiu Gao Jianjiang Yu Zhigang Hu Zhidong Zang Yuhua Gong Yaping Dai Lan Wang Ningling Ding Ping Xu Sufang Chen Lu Wang Jing Xu Luyao Zhang Junyan Hong Ruonan Qian Hu Li Xuan Jiang Congwei Chen Wenyan Tian Jian Wu Yuzhang Jiang Chongxu Han Kui Zhang Hong Qiu Li Li Hong Fan Liming Chen Jianqiong Zhang Zhongsheng Sun Xiao Han Zhenhua Dai Erguang Li M.Eric Gershwin Zhexiong Lian Xiong Ma Michael F.Seldin Weichang Chen Meilin Wang Xiangdong Liu Key Laboratory of Developmental Genes and Human Diseases School of Life Science and TechnologySoutheast UniversityNanjingJiangsu 210096China Institute of Translational Medicine Yangzhou University Medical CollegeYangzhouJiangsu 225009China Department of Radiology&Oncology The Second Affiliated Hospital of Soochow UniversitySuzhouJiangsu 215004China The First Affiliated Hospital of Soochow University SuzhouJiangsu 215006China Department of Bioinformatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjingJiangsu 210029China Author links open overlay panelYexi Huang Guangdong Provincial People's Hospital Guangdong Academy of Medical SciencesGuangzhouGuangdong 510080China Department of Gastroenterology and Hepatology Shanghai Institute of Digestive DiseasesShanghai Jiao Tong University School of Medicine Affiliated Renji HospitalShanghai 200001China Department of Laboratory Medicine The Fourth Affiliated Hospital of Nanjing Medical UniversityNanjingJiangsu 210031China Department of Gastrointestinal Endoscopy Eastern Hepatobiliary Surgery HospitalShanghai 201800China The Fifth People's Hospital Soochow UniversitySuzhouJiangsu 215007China Department of Gastroenterology Jiangsu University Affiliated Kunshan HospitalKunshanJiangsu 215300China Department of Gastroenterology Yixing People's HospitalYixinJiangsu 214200China Department of Gastroenterology Yancheng First People's HospitalYanchengJiangsu 224005China Department of Gastroenterology Taicang First People's HospitalSoochow UniversityTaicangJiangsu 215400China Department of Hepatology Jingjiang Second People's HospitalJingjiangJiangsu 214500China Department of Hepatology The Third People's Hospital of ChangzhouChangzhouJiangsu 213001China Department of Liver Diseases Shuguang HospitalShanghai University of Traditional Chinese MedicineShanghai 201203China Department of Laboratory Medicine Jiangyin People's HospitalSoutheast UniversityJiangyinJiangsu 214400China Department of Labora

Primary biliary cholangitis(PBC)is an autoimmune liver disease characterized by the destruction of intrahepatic small bile ducts and progressive cholestasis,eventually leading to liver cirrhosis and hepatic failure wi... 详细信息

关键词： cholangitis biliary

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ITIH4 alleviates OVA-induced asthma by regulating lung-gut microbiota

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Molecular medicine (Cambridge, Mass.) 2025年第1期31卷 204页

作者： Yi-Hsuan Liu Yueh-Lun Lee Chia-Li Han Yu-Chun Lo Zih-An Liao Yu-Syuan Shih Yi-Wen Lin Syue-Wei Peng Kang-Yun Lee Shu-Chuan Ho Sheng-Ming Wu Cheng-Wei Lin Kian Fan Chung Jer-Hwa Chang Hsiao-Chi Chuang School of Respiratory Therapy College of Medicine Taipei Medical University 250 Wuxing Street Taipei 11031 Taiwan. Department of Microbiology and Immunology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan. Master Program in Clinical Genomics and Proteomics College of Pharmacy Taipei Medical University Taipei Taiwan. The Ph.D. Program for Neural Regenerative Medicine College of Medical Science and Technology Taipei Medical University Taipei Taiwan. Division of Pulmonary Medicine Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei Taiwan. Division of Pulmonary Medicine Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan. Graduate Institute of Medical Sciences College of Medicine Taipei Medical University Taipei Taiwan. Department of Biochemistry and Molecular Cell Biology Taipei Medical University Taipei Taiwan. National Heart and Lung Institute Imperial College London London UK. School of Respiratory Therapy College of Medicine Taipei Medical University 250 Wuxing Street Taipei 11031 Taiwan. m102094030@tmu.edu.tw. Division of Pulmonary Medicine Department of Internal Medicine Wan Fang Hospital Taipei Medical University Taipei Taiwan. m102094030@tmu.edu.tw. School of Respiratory Therapy College of Medicine Taipei Medical University 250 Wuxing Street Taipei 11031 Taiwan. chuanghc@tmu.edu.tw. Division of Pulmonary Medicine Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan. chuanghc@tmu.edu.tw. National Heart and Lung Institute Imperial College London London UK. chuanghc@tmu.edu.tw. Cell Physiology and Molecular Image Research Center Wan Fang Hospital Taipei Medical University Taipei Taiwan. chuanghc@tmu.edu.tw.

BACKGROUND:Inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4), a Type 2 acute phase protein, is critical for resolving inflammation and promoting tissue repair. While its role in chronic respiratory diseases is recognized, its effects on asthma remain unclear. This study investigated the effects of ITIH4 on the modulation of lung and gut microbiota, the attenuation of allergic inflammation, and the improvement of respiratory outcomes in an asthma mouse model. METHODS:Six-week-old male Balb/c mice were divided into five groups: control, ITIH4, ovalbumin (OVA), and two OVA + ITIH4 treatment groups at different doses. Lung function and oxygen saturation were measured, and bronchoalveolar lavage fluid (BALF) was analyzed for white blood cell counts and cytokines. Lung and gut microbiota were profiled using 16 S rRNA gene sequencing, and short-chain fatty acids (SCFAs) were measured using gas chromatography-mass spectrometry (GC-MS). Proteomic profiling of intestinal tissues was conducted to identify ITIH4-associated signaling pathways. RESULTS:ITIH4 administration significantly mitigated OVA-induced asthma symptoms by reducing weight loss, airway resistance, and tissue damping (p < 0.05). Histological analysis showed decreased airway wall thickening and lung injury scores (p < 0.05). ITIH4 also lowered BALF eosinophils and lymphocytes, IgE, and Th2 cytokines (IL-4, IL-5, and IL-13) (p < 0.05). ITIH4 treatment modulated microbiome composition, enriching Gram-positive taxa (Nocardioidaceae and Acholeplasmataceae) and depleting Gram-negative Helicobacteraceae (p < 0.05). SCFAs correlated with microbiome alterations, notably reduced 4-methylpentanoic acid levels (p < 0.05). Proteomic analysis revealed a dose-dependent activation of granzyme A signaling and suppression of metabolic and solute transport pathways. CONCLUSIONS:ITIH4 ameliorates asthma symptoms by modulating lung and gut microbiota, dampening Th2-driven inflammation, and restoring mucosal immune balance. These

关键词： Airway hyperresponsiveness Inflammation Microbiome Short-chain fatty acid Th2

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Development of Machine Learning Models for Predicting Radiation Dermatitis in Breast Cancer Patients Using Clinical Risk Factors, Patient-Reported Outcomes, and Serum Cytokine Biomarkers

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Clinical Breast Cancer 2025年

作者： Lin, Neil Abbas-Aghababazadeh, Farnoosh Su, Jie Wu, Alison J. Lin, Cherie Shi, Wei Xu, Wei Haibe-Kains, Benjamin Liu, Fei-Fei Kwan, Jennifer Y.Y. Institute of Medical Science Temerty Faculty of Medicine University of Toronto Toronto Canada Temerty Faculty of Medicine University of Toronto Toronto Canada Princess Margaret Bioinformatics and Computational Genomics Laboratory University Health Network Toronto Canada Biostatistics Division Princess Margaret Cancer Centre Toronto Canada Research Institute Princess Margaret Cancer Centre Toronto Canada Department of Computer Science University of Toronto Toronto Canada Ontario Institute for Cancer Research Toronto Canada Vector Institute for Artificial Intelligence Toronto Canada Department of Radiation Oncology Temerty Faculty of Medicine University of Toronto Toronto Canada Department of Medical Biophysics Temerty Faculty of Medicine University of Toronto Toronto Canada Radiation Medicine Program Princess Margaret Cancer Centre Toronto Canada

Background: Radiation dermatitis (RD) is a significant side effect of radiotherapy experienced by breast cancer patients. Severe symptoms include desquamation or ulceration of irradiated skin, which impacts quality of life and increases healthcare costs. Early identification of patients at risk for severe RD can facilitate preventive management and reduce severe symptoms. This study evaluated the utility of subjective and objective factors, such as patient-reported outcomes (PROs) and serum cytokines, for predicting RD in breast cancer patients. The performance of machine learning (ML) and logistic regression-based models were compared. Patients and Methods: Data from 147 breast cancer patients who underwent radiotherapy was analyzed to develop prognostic models. ML algorithms, including neural networks, random forest, XGBoost, and logistic regression, were employed to predict clinically significant Grade 2+ RD. Clinical factors, PROs, and cytokine biomarkers were incorporated into the risk models. Model performance was evaluated using nested cross-validation with separate loops for hyperparameter tuning and calculating performance metrics. Results: Feature selection identified 18 predictors of Grade 2+ RD including smoking, radiotherapy boost, reduced motivation, and the cytokines interleukin-4, interleukin-17, interleukin-1RA, interferon-gamma, and stromal cell-derived factor-1a. Incorporating these predictors, the XGBoost model achieved the highest performance with an area under the curve (AUC) of 0.780 (95% CI: 0.701-0.854). This was not significantly improved over the logistic regression model, which demonstrated an AUC of 0.714 (95% CI: 0.629-0.798). Conclusion: Clinical risk factors, PROs, and serum cytokine levels provide complementary prognostic information for predicting severe RD in breast cancer patients undergoing radiotherapy. ML and logistic regression models demonstrated comparable performance for predicting clinically significant RD with AUC>0.70. ©

关键词： Cancer survivorship Oncology Predictive modeling Radiotherapy Skin toxicity

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Unsupervised clustering identified clinically relevant metabolic syndrome endotypes in UK and Taiwan Biobanks

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iScience 2024年第7期27卷 109815页

作者： Lim, Aylwin Ming Wee Lim, Evan Unit Chen, Pei-Lung Fann, Cathy Shen Jang Taiwan International Graduate Program in Molecular Medicine National Yang Ming Chiao Tung University and Academia Sinica Taipei 112304 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei 115 Taiwan ASUS Intelligent Cloud Services (AICS) Taipei 112 Taiwan College of Computing Georgia Institute of Technology Atlanta 30332 GA United States Graduate Institute of Medical Genomics and Proteomics College of Medicine National Taiwan University Taipei 10617 Taiwan Department of Medical Genetics National Taiwan University Hospital Taipei 100 Taiwan

Metabolic syndrome (MetS) is a collection of cardiovascular risk factors;however, the high prevalence and heterogeneity impede effective clinical management. We conducted unsupervised clustering on individuals from UK Biobank to reveal endotypes. Five MetS subgroups were identified: Cluster 1 (C1): non-descriptive, Cluster 2 (C2): hypertensive, Cluster 3 (C3): obese, Cluster 4 (C4): lipodystrophy-like, and Cluster 5 (C5): hyperglycemic. For all of the endotypes, we identified the corresponding cardiometabolic traits and their associations with clinical outcomes. Genome-wide association studies (GWASs) were conducted to identify associated genotypic traits. We then determined endotype-specific genotypic traits and constructed polygenic risk score (PRS) models specific to each endotype. GWAS of each MetS clusters revealed different genotypic traits. C1 GWAS revealed novel findings of TRIM63, MYBPC3, MYLPF, and RAPSN. Intriguingly, C1, C3, and C4 were associated with genes highly expressed in brain tissues. MetS clusters with comparable phenotypic and genotypic traits were identified in Taiwan Biobank. © 2024 Institute of Biomedical Sciences, Academia Sinica, Taiwan

关键词： Association analysis Classification of bioinformatical subject Human metabolism Risk stratification Syndrome

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Chemoresistance in acute myeloid leukemia: An alternative single-cell RNA sequencing approach

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Hematological oncology 2023年第3期41卷 499-509页

作者： Po-Liang Cheng Tzu-Hung Hsiao Chung-Hsing Chen Miao-Neng Hung Pei-Pei Jhan Li-Wen Lee Ting-Shuan Wu Jia-Rung Tsai Chieh-Lin Jerry Teng Department of Medical Research Taichung Veterans General Hospital Taichung Taiwan. Research Center for Biomedical Science and Engineering National Tsing Hua University Hsinchu Taiwan. Department of Public Health Fu Jen Catholic University New Taipei City Taiwan. Institute of Genomics and Bioinformatics National Chung Hsing University Taichung Taiwan. National Institute of Cancer Research National Health Research Institutes Zhunan Taiwan. Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan. Division of Hematology/Medical Oncology Department of Medicine Taichung Veterans General Hospital Taichung Taiwan. Department of Life Science Tunghai University Taichung Taiwan. School of Medicine Chung Shan Medical University Taichung Taiwan. Ph.D. Program in Translational Medicine National Chung Hsing University Taichung Taiwan. Rong Hsing Research Center for Translational Medicine National Chung Hsing University Taichung Taiwan.

Our previous study demonstrated that myc, mitochondrial oxidative phosphorylation, mTOR, and stemness are independently responsible for chemoresistance in acute myeloid leukemia (AML) cells. This study aimed to identify potential mechanisms of chemoresistance of the "7 + 3" induction in AML by using a single-cell RNA sequencing (scRNA-seq) approach. In the present study, 13 untreated patients with de novo AML were enrolled and stratified into two groups: complete remission (CR; n = 8) and non-CR (n = 5). Single-cell RNA sequencing was used to analyze genetic profiles of 28,950 AML cells from these patients; results were validated using a previously published bulk RNA-seq dataset. Our study results showed chemoresistant AML cells had premature accumulation during early hematopoiesis. Hematopoietic stem cell-like cells from the non-CR group expressed more leukemic stem cell markers (CD9, CD82, IL3RA, and IL1RAP) than those from the CR group. Chemoresistant progenitor cells had impaired myeloid differentiation owing to early arrest of hematopoiesis. Notably, AML cells analyzed by scRNA-seq and bulk RNA-seq harbored a comparable myeloid lineage cell fraction, which internally validated our results. Using the TCGA database, our analysis demonstrated that patients with AML with higher expression of chemoresistant genetic markers (IL3RA and IL1RAP) had a worse overall survival (p < 0.01 for IL3RA; p < 0.05 for IL1RAP). In conclusion, AML cells responsive and resistant to the "7 + 3" induction were derived from a diverse cancerous hematopoietic stem cell population, as indicated by the specific genetic biomarkers obtained using scRNA-seq approach. Furthermore, arrest of hematopoiesis was shown to occur earlier in chemoresistant AML cells, furthering the current understanding of chemoresistance in AML.

关键词： acute myeloid leukemia chemoresistance leukemia stem cells single-cell RNA-seq

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Integrative modeling of transmitted and de novo variants identifies novel risk genes for congenital heart disease

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Quantitative Biology 2021年第2期9卷 216-227页

作者： Mo Li Xue Zeng Chentian Jin Sheng Chih Jin Weilai Dong Martina Brueckner Richard Lifton Qiongshi Lu Hongyu Zhao Department of Biostatistics Yale School of Public HealthNew HavenCT 06510USA Department of Genetics Yale UniversityNew HavenCT 06510USA Department of Molecular Cellular&Developmental BiologyYale UniversityCT 06510USA Department of Genetics Washington University School of MedicineSt LouisMO 63110USA Department of Pediatrics Yale UniversityNew HavenCT 06510USA Laboratory of Human Genetics and Genomics Rockefeller UniversityNew YorkNY 10065USA Department of Biostatistics and Medical Informatics University of Wisconsin-MadisonMadisonWl 53792USA Program of Computational Biology and Bioinformatics Yale UniversityNew HavenCT 06510USA

Background:Whole-exome sequencing(WES)studies have identified multiple genes enriched for de novo mutations(DNMs)in congenital heart disease(CHD)***,risk gene identification based on DNMs alone remains statistically challenging due to heterogenous etiology of CHD and low mutation rate in each ***:In this manuscript,we introduce a hierarchical Bayesian framework for gene-level association test which jointly analyzes de novo and rare transmitted *** integrative modeling of multiple types of genetic variants,gene-level annotations,and reference data from large population cohorts,our method accurately characterizes the expected frequencies of both de novo and transmitted variants and shows improved statistical power compared to analyses based on DNMs ***:Applied to WES data of 2,645 CHD proband-parent trios,our method identified 15 significant genes,half of which are novel,leading to new insights into the genetic bases of ***:These results showcase the power of integrative analysis of transmitted and de novo variants for disease gene discovery.

关键词： rare variants gene-level association test congenital heart disease de novo mutation

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Dissecting the epigenomic dynamics of human fetal germ cell development at single-cell resolution

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细胞研究（英文版） 2021年第4期31卷 463-477页

作者： Li Li Lin Li Qingqing Li Xixi Liu Xinyi Ma Jun Yong Shuai Gao Xinglong Wu Yuan Wei Xiaoye Wang Wei Wang Rong Li Jie Yan Xiaohui Zhu Lu Wen Jie Qiao Liying Yan Fuchou Tang Beijing Advanced Innovation Center for Genomics Department of Obstetrics and GynecologyThird HospitalSchool of Life SciencesPeking UniversityBeijing 100871China Biomedical Pioneering Innovation Center Center for Reproductive MedicineMinistry of EducationKey Laboratory of Cell Proliferation and DifferentiationBeijing 100871China Stem Cell Program Boston Children's HospitalBostonMA 02115USA Department of Stem Cell and Regenerative Biology Harvard UniversityCambridgeMA 02138USA Department of Pathophysiology Guangdong Provincial Key Laboratory of ProteomicsSchool of Basic Medical SciencesSouthern Medical UniversityGuangzhouGuangdong 510515China Beijing Advanced Innovation Center for Genomics Department of Obstetrics and GynecologyThird HospitalSchool of Life SciencesPeking UniversityBeijing 100871China Biomedical Pioneering Innovation Center Center for Reproductive MedicineMinistry of EducationKey Laboratory of Cell Proliferation and DifferentiationBeijing 100871China Beijing Advanced Innovation Center for Genomics Department of Obstetrics and GynecologyThird HospitalSchool of Life SciencesPeking UniversityBeijing 100871China Beijing Advanced Innovation Center for Genomics Department of Obstetrics and GynecologyThird HospitalSchool of Life SciencesPeking UniversityBeijing 100871China Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology Beijing 100191China Beijing Advanced Innovation Center for Genomics Department of Obstetrics and GynecologyThird HospitalSchool of Life SciencesPeking UniversityBeijing 100871China Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology Beijing 100191China Key Laboratory of Assisted Reproduction Ministry of EducationBeijing 100191China Peking-Tsinghua Center for Life Sciences Peking UniversityBeijing 100871China Beijing Advanced Innovation Center for Genomics Department of Obstetrics and GynecologyThird HospitalSchool of Life SciencesPeking UniversityBeijing 1008

Proper development of fetal germ cells(FGCs)is vital for the precise transmission of genetic and epigenetic information through *** transcriptional landscapes of human FGC development have been revealed;however,the epigenetic reprogramming process of FGCs remains ***,we profiled the genome-wide DNA methylation and chromatin accessibility of human FGCs at different phases as well as gonadal niche cells at single-cell ***,we found that DNA methylation levels of FGCs changed in a temporal manner,whereas FGCs at different phases in the same embryo exhibited comparable DNA methylation levels and ***,we revealed the phase-specific chromatin accessibility signatures at the promoter regions of a large set of critical transcription factors and signaling pathway *** also identified potential distal regulatory elements including enhancers in ***,compared with other hominid-specific retrotransposons,SVA_D might have a broad spectrum of binding capacity for transcription factors,including SOX15 and ***,using an in vitro culture system of human FGCs,we showed that the BMP signaling pathway promoted the cell proliferation of FGCs,and regulated the WNT signaling pathway by orchestrating the chromatin accessibility of its ligand *** single-cell epigenomic atlas and functional assays provide valuable insights for understanding the strongly heterogeneous,unsynchronized,yet highly robust nature of human germ cell development.

关键词： Developmental biology Epigenetics

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Repurposed Nrf2 activator dimethyl fumarate rescues muscle inflammation and fibrosis in an aggravated mdx mouse model of Duchenne muscular dystrophy

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Redox Biology 2025年 84卷 103676页

作者： Kourakis, Stephanie Timpani, Cara A. Bagaric, Ryan M. Qi, Bo Ali, Benazir A. Boyer, Rebecca Spiesberger, Guinevere Kandhari, Nitika Yan, Xu Kuang, Jujiao Tulangekar, Ankita de Haan, Judy B. Deveson-Lucas, Deanna Stupka, Nicole Fischer, Dirk Rybalka, Emma Institute for Health and Sport (IHeS) Victoria University Melbourne VIC Australia Inherited and Acquired Myopathies Program Australian Institute for Musculoskeletal Science (AIMSS) St Albans VIC Australia Department of Medicine – Western Health Melbourne Medical School The University of Melbourne St Albans VIC Australia Monash Genomics and Bioinformatics Platform Biomedical Discovery Institute Monash University Clayton VIC Australia Sarcopenia Research Program Australian Institute for Musculoskeletal Science (AIMSS) St Albans VIC Australia Basic Science Domain Oxidative Stress Laboratory Baker Heart and Diabetes Institute Melbourne VIC Australia Baker Department of Cardiometabolic Health University of Melbourne Parkville VIC Australia Division of Neuropediatric and Developmental Medicine University Children's Hospital of Basel (UKBB) Basel Switzerland

In inherited neuromuscular disease, Duchenne muscular dystrophy (DMD), glucocorticoids significantly slow disease progression yet impart side effects severe enough to preclude use in a significant proportion of patients. Extending our findings that acute treatment with FDA approved multiple sclerosis drug, dimethyl fumarate (DMF), rescues muscle pathology in juvenile mdx mice, we aimed to conduct tiered pre-clinical testing toward translation. To aggravate disease phenotype in adult mdx muscles that usually lack human equivalent muscle pathology, we used bi-weekly treadmill running for 4 weeks which increased plasma DMD biomarker, creatine kinase, by 2-fold and quadriceps fibrosis by ∼30 %. Using this model, we screened DMF for 5 weeks in a head-to-head comparison, and in combination, with standard-of-care prednisone (PRED), to model the most likely clinical trial scenario. We show comparable efficacy between DMF and PRED at reducing inflammation via NF-κB suppression and CD68⁺ macrophage infiltration. Moderate term DMF monotherapy had additional anti-fibrotic and anti-lipogenic effects on skeletal and cardiac muscle beyond those seen with PRED treatment, although combination therapy exacerbated fibrosis in quadriceps. Our study supports DMF as a repurposing candidate for DMD, especially for patients who cannot tolerate chronic glucocorticoid treatment. We also highlight the importance of evaluating combination therapy to identify potential off-target effects between emerging therapeutics and glucocorticoids towards better designed clinical trials. © 2025

关键词： Dimethyl fumarate Duchenne muscular dystrophy Muscle pathology Therapeutics

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Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries (vol 55, pg 89, 2023)

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NATURE GENETICS 2023年第3期55卷 519-520页

作者： Fernandez-Rozadilla, Ceres Timofeeva, Maria Chen, Zhishan Law, Philip Thomas, Minta Schmit, Stephanie Diez-Obrero, Virginia Hsu, Li Fernandez-Tajes, Juan Palles, Claire Sherwood, Kitty Briggs, Sarah Svinti, Victoria Donnelly, Kevin Farrington, Susan Blackmur, James Vaughan-Shaw, Peter Shu, Xiao-ou Long, Jirong Cai, Qiuyin Guo, Xingyi Lu, Yingchang Broderick, Peter Studd, James Huyghe, Jeroen Harrison, Tabitha Conti, David Dampier, Christopher Devall, Mathew Schumacher, Fredrick Melas, Marilena Rennert, Gad Obon-Santacana, Mireia Martin-Sanchez, Vicente Moratalla-Navarro, Ferran Oh, Jae Hwan Kim, Jeongseon Jee, Sun Ha Jung, Keum Ji Kweon, Sun-Seog Shin, Min-Ho Shin, Aesun Ahn, Yoon-Ok Kim, Dong-Hyun Oze, Isao Wen, Wanqing Matsuo, Keitaro Matsuda, Koichi Tanikawa, Chizu Ren, Zefang Gao, Yu-Tang Jia, Wei-Hua Hopper, John Jenkins, Mark Win, Aung Ko Pai, Rish Figueiredo, Jane Haile, Robert Gallinger, Steven Woods, Michael Newcomb, Polly Duggan, David Cheadle, Jeremy Kaplan, Richard Maughan, Timothy Kerr, Rachel Kerr, David Kirac, Iva Bohm, Jan Mecklin, Lukka-Pekka Jousilahti, Pekka Knekt, Paul Aaltonen, Lauri Rissanen, Harri Pukkala, Eero Eriksson, Johan Cajuso, Tatiana Hanninen, Ulrika Kondelin, Johanna Palin, Kimmo Tanskanen, Tomas Renkonen-Sinisalo, Laura Zanke, Brent Mannisto, Satu Albanes, Demetrius Weinstein, Stephanie Ruiz-Narvaez, Edward Palmer, Julie Buchanan, Daniel Platz, Elizabeth Visvanathan, Kala Ulrich, Cornelia Siegel, Erin Brezina, Stefanie Gsur, Andrea Campbell, Peter Chang-Claude, Jenny Hoffmeister, Michael Brenner, Hermann Slattery, Martha Potter, John Tsilidis, Konstantinos Schulze, Matthias Gunter, Marc Murphy, Neil Castells, Antoni Castellvi-Bel, Sergi Moreira, Leticia Arndt, Volker Shcherbina, Anna Stern, Mariana Pardamean, Bens Bishop, Timothy Giles, Graham Southey, Melissa Idos, Gregory McDonnell, Kevin Abu-Ful, Zomoroda Greenson, Joel Shulman, Katerina Lejbkowicz, Flavio Offit, Kenneth Su, Yu-Ru Steinfelder, Robert Keku, Temitope van Guelpen, Bethany Hudson, Thomas Hampel, Heather Pearlman, Edinburgh Cancer Research Centre Institute of Genomics and Cancer University of Edinburgh Edinburgh UK Genomic Medicine Group Instituto de Investigacion Sanitaria de Santiago Santiago de Compostela Spain Colon Cancer Genetics Group Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK Danish Institute for Advanced Study Department of Public Health University of Southern Denmark Odense Denmark Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University Medical Center Nashville TN USA Division of Genetics and Epidemiology Institute of Cancer Research London UK Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle WA USA Genomic Medicine Institute Cleveland Clinic Cleveland OH USA Population and Cancer Prevention Program Case Comprehensive Cancer Center Cleveland OH USA Colorectal Cancer Group ONCOBELL Program Bellvitge Biomedical Research Institute Barcelona Spain Oncology Data Analytics Program Catalan Institute of Oncology Barcelona Spain Consortium for Biomedical Research in Epidemiology and Public Health Madrid Madrid Spain Department of Clinical Sciences Faculty of Medicine University of Barcelona Barcelona Spain Department of Biostatistics School of Public Health University of Washington Seattle WA USA Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham UK Department of Public Health Richard Doll Building University of Oxford Oxford UK Department of Biomedical Informatics Vanderbilt University School of Medicine Nashville TN USA Department of Preventive Medicine USC Norris Comprehensive Cancer Center Keck School of Medicine University of Southern California Los Angeles CA USA Center for Public Health Genomics Department of Public Health Sciences University of Virginia Charlottesville VA USA Department of Populat

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.

关键词： Colorectal cancer Epigenomics Genome-wide association studies Transcriptomics

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