1
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Weng C, Yu F, Yang D, Poeschla M, Liggett LA, Jones MG, Qiu X, Wahlster L, Caulier A, Hussmann JA, Schnell A, Yost KE, Koblan LW, Martin-Rufino JD, Min J, Hammond A, Ssozi D, Bueno R, Mallidi H, Kreso A, Escabi J, Rideout WM, Jacks T, Hormoz S, van Galen P, Weissman JS, Sankaran VG. Deciphering cell states and genealogies of human haematopoiesis. Nature 2024; 627:389-398. [PMID: 38253266 PMCID: PMC10937407 DOI: 10.1038/s41586-024-07066-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 01/12/2024] [Indexed: 01/24/2024]
Abstract
The human blood system is maintained through the differentiation and massive amplification of a limited number of long-lived haematopoietic stem cells (HSCs)1. Perturbations to this process underlie diverse diseases, but the clonal contributions to human haematopoiesis and how this changes with age remain incompletely understood. Although recent insights have emerged from barcoding studies in model systems2-5, simultaneous detection of cell states and phylogenies from natural barcodes in humans remains challenging. Here we introduce an improved, single-cell lineage-tracing system based on deep detection of naturally occurring mitochondrial DNA mutations with simultaneous readout of transcriptional states and chromatin accessibility. We use this system to define the clonal architecture of HSCs and map the physiological state and output of clones. We uncover functional heterogeneity in HSC clones, which is stable over months and manifests as both differences in total HSC output and biases towards the production of different mature cell types. We also find that the diversity of HSC clones decreases markedly with age, leading to an oligoclonal structure with multiple distinct clonal expansions. Our study thus provides a clonally resolved and cell-state-aware atlas of human haematopoiesis at single-cell resolution, showing an unappreciated functional diversity of human HSC clones and, more broadly, paving the way for refined studies of clonal dynamics across a range of tissues in human health and disease.
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Affiliation(s)
- Chen Weng
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Fulong Yu
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, P.R. China
| | - Dian Yang
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Molecular Pharmacology and Therapeutics, Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Michael Poeschla
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - L Alexander Liggett
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matthew G Jones
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Dermatology, Stanford University, Stanford, CA, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Xiaojie Qiu
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Genetics and Computer Science, BASE Research Initiative, Betty Irene Moore Children's Heart Center, Stanford University, Stanford, CA, USA
| | - Lara Wahlster
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alexis Caulier
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jeffrey A Hussmann
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alexandra Schnell
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kathryn E Yost
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Luke W Koblan
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jorge D Martin-Rufino
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joseph Min
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alessandro Hammond
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Daniel Ssozi
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Hematology, Brigham and Women's Hospital, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Raphael Bueno
- Division of Thoracic and Cardiac Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Hari Mallidi
- Division of Thoracic and Cardiac Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Antonia Kreso
- Division of Cardiac Surgery, Massachusetts General Hospital, Boston, MA, USA
| | - Javier Escabi
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - William M Rideout
- Koch Institute For Integrative Cancer Research at MIT, MIT, Cambridge, MA, USA
| | - Tyler Jacks
- Koch Institute For Integrative Cancer Research at MIT, MIT, Cambridge, MA, USA
| | - Sahand Hormoz
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Peter van Galen
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Hematology, Brigham and Women's Hospital, Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Ludwig Center at Harvard, Harvard Medical School, Boston, MA, USA
| | - Jonathan S Weissman
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA.
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Koch Institute For Integrative Cancer Research at MIT, MIT, Cambridge, MA, USA.
| | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Harvard Stem Cell Institute, Cambridge, MA, USA.
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2
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Zhang H, Yu X, Ye J, Li H, Hu J, Tan Y, Fang Y, Akbay E, Yu F, Weng C, Sankaran VG, Bachoo RM, Maher E, Minna J, Zhang A, Li B. Systematic investigation of mitochondrial transfer between cancer cells and T cells at single-cell resolution. Cancer Cell 2023; 41:1788-1802.e10. [PMID: 37816332 PMCID: PMC10568073 DOI: 10.1016/j.ccell.2023.09.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 06/27/2023] [Accepted: 09/05/2023] [Indexed: 10/12/2023]
Abstract
Mitochondria (MT) participate in most metabolic activities of mammalian cells. A near-unidirectional mitochondrial transfer from T cells to cancer cells was recently observed to "metabolically empower" cancer cells while "depleting immune cells," providing new insights into tumor-T cell interaction and immune evasion. Here, we leverage single-cell RNA-seq technology and introduce MERCI, a statistical deconvolution method for tracing and quantifying mitochondrial trafficking between cancer and T cells. Through rigorous benchmarking and validation, MERCI accurately predicts the recipient cells and their relative mitochondrial compositions. Application of MERCI to human cancer samples identifies a reproducible MT transfer phenotype, with its signature genes involved in cytoskeleton remodeling, energy production, and TNF-α signaling pathways. Moreover, MT transfer is associated with increased cell cycle activity and poor clinical outcome across different cancer types. In summary, MERCI enables systematic investigation of an understudied aspect of tumor-T cell interactions that may lead to the development of therapeutic opportunities.
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Affiliation(s)
- Hongyi Zhang
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA; Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Xuexin Yu
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA; Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jianfeng Ye
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Huiyu Li
- Hamon Center for Therapeutic Oncology Research, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Jing Hu
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA; Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yuhao Tan
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yan Fang
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Esra Akbay
- Department of Pathology, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Fulong Yu
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Chen Weng
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Vijay G Sankaran
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Robert M Bachoo
- Department of Neurology and Neurotherapeutics, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Elizabeth Maher
- Department of Neurology and Neurotherapeutics, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - John Minna
- Hamon Center for Therapeutic Oncology Research, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Anli Zhang
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA.
| | - Bo Li
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA; Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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3
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Weng C, Gu A, Zhang S, Lu L, Ke L, Gao P, Liu X, Wang Y, Hu P, Plummer D, MacDonald E, Zhang S, Xi J, Lai S, Leskov K, Yuan K, Jin F, Li Y. Single cell multiomic analysis reveals diabetes-associated β-cell heterogeneity driven by HNF1A. Nat Commun 2023; 14:5400. [PMID: 37669939 PMCID: PMC10480445 DOI: 10.1038/s41467-023-41228-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 08/29/2023] [Indexed: 09/07/2023] Open
Abstract
Broad heterogeneity in pancreatic β-cell function and morphology has been widely reported. However, determining which components of this cellular heterogeneity serve a diabetes-relevant function remains challenging. Here, we integrate single-cell transcriptome, single-nuclei chromatin accessibility, and cell-type specific 3D genome profiles from human islets and identify Type II Diabetes (T2D)-associated β-cell heterogeneity at both transcriptomic and epigenomic levels. We develop a computational method to explicitly dissect the intra-donor and inter-donor heterogeneity between single β-cells, which reflect distinct mechanisms of T2D pathogenesis. Integrative transcriptomic and epigenomic analysis identifies HNF1A as a principal driver of intra-donor heterogeneity between β-cells from the same donors; HNF1A expression is also reduced in β-cells from T2D donors. Interestingly, HNF1A activity in single β-cells is significantly associated with lower Na+ currents and we nominate a HNF1A target, FXYD2, as the primary mitigator. Our study demonstrates the value of investigating disease-associated single-cell heterogeneity and provides new insights into the pathogenesis of T2D.
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Affiliation(s)
- Chen Weng
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Anniya Gu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- Medical Scientist Training Program (MSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Shanshan Zhang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Leina Lu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Luxin Ke
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Peidong Gao
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Xiaoxiao Liu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Yuntong Wang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Peinan Hu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Dylan Plummer
- Department of Computer and Data Sciences, School of Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Elise MacDonald
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Saixian Zhang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Jiajia Xi
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Sisi Lai
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Konstantin Leskov
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Kyle Yuan
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- Department of Biochemistry, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Fulai Jin
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA.
- Department of Computer and Data Sciences, School of Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA.
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, 44106, USA.
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA.
| | - Yan Li
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA.
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4
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Martin-Rufino JD, Castano N, Pang M, Grody EI, Joubran S, Caulier A, Wahlster L, Li T, Qiu X, Riera-Escandell AM, Newby GA, Al'Khafaji A, Chaudhary S, Black S, Weng C, Munson G, Liu DR, Wlodarski MW, Sims K, Oakley JH, Fasano RM, Xavier RJ, Lander ES, Klein DE, Sankaran VG. Massively parallel base editing to map variant effects in human hematopoiesis. Cell 2023; 186:2456-2474.e24. [PMID: 37137305 PMCID: PMC10225359 DOI: 10.1016/j.cell.2023.03.035] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/26/2023] [Accepted: 03/30/2023] [Indexed: 05/05/2023]
Abstract
Systematic evaluation of the impact of genetic variants is critical for the study and treatment of human physiology and disease. While specific mutations can be introduced by genome engineering, we still lack scalable approaches that are applicable to the important setting of primary cells, such as blood and immune cells. Here, we describe the development of massively parallel base-editing screens in human hematopoietic stem and progenitor cells. Such approaches enable functional screens for variant effects across any hematopoietic differentiation state. Moreover, they allow for rich phenotyping through single-cell RNA sequencing readouts and separately for characterization of editing outcomes through pooled single-cell genotyping. We efficiently design improved leukemia immunotherapy approaches, comprehensively identify non-coding variants modulating fetal hemoglobin expression, define mechanisms regulating hematopoietic differentiation, and probe the pathogenicity of uncharacterized disease-associated variants. These strategies will advance effective and high-throughput variant-to-function mapping in human hematopoiesis to identify the causes of diverse diseases.
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Affiliation(s)
- Jorge D Martin-Rufino
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; PhD Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115, USA
| | - Nicole Castano
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Michael Pang
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard-MIT Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA
| | | | - Samantha Joubran
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Chemical Biology PhD Program, Harvard Medical School, Boston, MA 02115, USA
| | - Alexis Caulier
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Lara Wahlster
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Tongqing Li
- Department of Pharmacology and Yale Cancer Biology Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Xiaojie Qiu
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | | | - Gregory A Newby
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Aziz Al'Khafaji
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Susan Black
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Chen Weng
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Glen Munson
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - David R Liu
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Marcin W Wlodarski
- Department of Hematology, St Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Kacie Sims
- St. Jude Affiliate Clinic at Our Lady of the Lake Children's Health, Baton Rouge, LA 70809, USA
| | - Jamie H Oakley
- Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta and Emory University, Atlanta, GA 30322, USA
| | - Ross M Fasano
- Aflac Cancer and Blood Disorders Center, Children's Healthcare of Atlanta and Emory University, Atlanta, GA 30322, USA
| | - Ramnik J Xavier
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Center for Computational and Integrative Biology, Department of Molecular Biology, and Center for the Study of Inflammatory Bowel Disease, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Daryl E Klein
- Department of Pharmacology and Yale Cancer Biology Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Stem Cell Institute, Cambridge, MA 02138, USA.
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5
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Dong R, Lv C, Weng C, Lian A, Zhang L, Chen J, Ye M. Environmental damage compensation for illegal solid waste dumping in China. Ecotoxicol Environ Saf 2023; 253:114657. [PMID: 36807058 DOI: 10.1016/j.ecoenv.2023.114657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 01/28/2023] [Accepted: 02/13/2023] [Indexed: 06/18/2023]
Abstract
China aims to improve its system for pursuing environmental damage compensation environmental violation cases. To hold violators accountable, China has an effective system for the identification and assessment (I&A) of environmental damage. This study selected a typical case of the illegal dumping of solid waste (IDSW) in China to analyze the causes, the degree, and characteristics of environmental damage, focusing on components such as the physical quantification and valuation of damage. The findings were as follows: (1) Compensation claimants and obligors consider baseline damage confirmation and causality analysis key components of I&A. (2) The I&A process for a specific case needs to focus on key nodes such as the type, location, and duration of IDSW. (3) Restraining IDSW requires accurately quantifying the physical and value-related losses caused by solid waste dumping. (4) In the selected case study, the damage from environmental contamination caused by the IDSW incident amounted to 3938,990 yuan, including an environmental damage value of 3651,990 yuan and a transaction cost of 287,000 yuan. Both parties accepted the I&A calculation process in this case, and the desired punishment effect was achieved. Hence, the case study demonstrated that accurate I&A is the technical basis for environmental damage compensation. Thus, in the future, more attention should be paid to the role of scientific and technological means and knowledge reserves in the I&A of environmental damage.
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Affiliation(s)
- Rencai Dong
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Chencan Lv
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Chen Weng
- Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Anxin Lian
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Lulu Zhang
- Guangdong Provincial Academy of Environmental Sciences, Guangzhou 510045, China.
| | - Jialiang Chen
- Guangdong Provincial Academy of Environmental Sciences, Guangzhou 510045, China.
| | - Mai Ye
- Guangdong Provincial Academy of Environmental Sciences, Guangzhou 510045, China.
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6
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Wei T, Huang Y, Weng C, Chen F, Tan C, Liu W, Deng Z, Li J. Lipid rafts may affect the coalescence of milk fat globules through phase transition after thermal treatment. Food Chem 2023; 399:133867. [DOI: 10.1016/j.foodchem.2022.133867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 07/25/2022] [Accepted: 08/04/2022] [Indexed: 11/16/2022]
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7
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Wang J, Weng C, Wang Z, Li C, Wang T. What Constitutes the High-Quality Soundscape in Human Habitats? Utilizing a Random Forest Model to Explore Soundscape and Its Geospatial Factors Behind. Int J Environ Res Public Health 2022; 19:13913. [PMID: 36360793 PMCID: PMC9654861 DOI: 10.3390/ijerph192113913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 10/22/2022] [Accepted: 10/22/2022] [Indexed: 06/16/2023]
Abstract
Soundscape is the production of sounds and the acoustic environment, and it emphasizes peoples' perceiving and experiencing process in the context. To this end, this paper focuses on the Pearl River Delta in China, and implements an empirical study based on the soundscape evaluation data from the Participatory Soundscape Sensing (PSS) system, and the geospatial data from multiple sources. The optimal variable set with 24 features are successfully used to establish a random forest model to predict the soundscape comfort of a new site (F1 = 0.61). Results show that the acoustic factors are most important to successfully classify soundscape comfort (averaged relative importance of 17.45), subsequently ranking by built environment elements (11.28), temporal factors (9.59), and demographic factors (9.14), while landscape index (8.60) and land cover type (7.71) seem to have unclear importance. Furthermore, the partial dependence analysis provides the answers about the appropriate threshold or category of various variables to quantitatively or qualitatively specify the necessary management and control metrics for maintaining soundscape quality. These findings suggest that mainstreaming the soundscape in the coupled natural-human systems and clarifying the mechanisms between soundscape perception and geospatial factors can be beneficial to create a high-quality soundscape in human habitats.
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Affiliation(s)
- Jingyi Wang
- Fujian Key Laboratory of Watershed Ecology, Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chen Weng
- Fujian Key Laboratory of Watershed Ecology, Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhen Wang
- School of Statistics, Huaqiao University, Xiamen 361021, China
| | - Chunming Li
- Fujian Key Laboratory of Watershed Ecology, Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Tingting Wang
- School of Statistics, Huaqiao University, Xiamen 361021, China
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8
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Wang R, Zhang G, Zhu Q, Ma T, Weng C, Zhang D, Zeng H, Wang T, Gao F. 1234P Neoadjuvant camrelizumab plus docetaxel and carboplatin in locally advanced esophageal squamous cell carcinoma (ESCC): A prospective study. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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9
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Gupta A, Martin-Rufino JD, Jones TR, Subramanian V, Qiu X, Grody EI, Bloemendal A, Weng C, Niu SY, Min KH, Mehta A, Zhang K, Siraj L, Al' Khafaji A, Sankaran VG, Raychaudhuri S, Cleary B, Grossman S, Lander ES. Inferring gene regulation from stochastic transcriptional variation across single cells at steady state. Proc Natl Acad Sci U S A 2022; 119:e2207392119. [PMID: 35969771 PMCID: PMC9407670 DOI: 10.1073/pnas.2207392119] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 07/20/2022] [Indexed: 12/24/2022] Open
Abstract
Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.
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Affiliation(s)
- Anika Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115
| | - Jorge D. Martin-Rufino
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115
- Dana-Farber Cancer Institute, Boston, MA 02215
| | | | | | - Xiaojie Qiu
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142
- HHMI, Massachusetts Institute of Technology, Cambridge, MA 02139
| | | | | | - Chen Weng
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115
- Dana-Farber Cancer Institute, Boston, MA 02215
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142
| | | | - Kyung Hoi Min
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Arnav Mehta
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Massachusetts General Hospital, Boston, MA 02114
| | - Kaite Zhang
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Layla Siraj
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | | | - Vijay G. Sankaran
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115
- Dana-Farber Cancer Institute, Boston, MA 02215
| | - Soumya Raychaudhuri
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA 02115
| | - Brian Cleary
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | | | - Eric S. Lander
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115
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10
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Qiu X, Zhang Y, Martin-Rufino JD, Weng C, Hosseinzadeh S, Yang D, Pogson AN, Hein MY, Hoi Joseph Min K, Wang L, Grody EI, Shurtleff MJ, Yuan R, Xu S, Ma Y, Replogle JM, Lander ES, Darmanis S, Bahar I, Sankaran VG, Xing J, Weissman JS. Mapping transcriptomic vector fields of single cells. Cell 2022; 185:690-711.e45. [PMID: 35108499 PMCID: PMC9332140 DOI: 10.1016/j.cell.2021.12.045] [Citation(s) in RCA: 100] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 10/08/2021] [Accepted: 12/28/2021] [Indexed: 01/03/2023]
Abstract
Single-cell (sc)-RNA-seq, together with RNA-velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo, that infers absolute RNA velocity, reconstructs continuous vector-field functions that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo’s power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically-labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1–GATA1 circuit. Leveraging the Least-Action-Path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo thus represents an important step in advancing quantitative and predictive theories of cell-state transitions.
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Affiliation(s)
- Xiaojie Qiu
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Yan Zhang
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA; Joint CMU-Pitt Ph.D. Program in Computational Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jorge D Martin-Rufino
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Chen Weng
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA; Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Shayan Hosseinzadeh
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Dian Yang
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Angela N Pogson
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Marco Y Hein
- Chan Zuckerberg Biohub, 499 Illinois St, San Francisco, CA 94158, USA
| | - Kyung Hoi Joseph Min
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Li Wang
- Department of Mathematics, University of Texas at Arlington, Arlington, TX, USA
| | | | | | - Ruoshi Yuan
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA, USA
| | | | - Yian Ma
- Halıcıoğlu Data Science Institute, University of California San Diego, San Diego, CA, USA
| | - Joseph M Replogle
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA; Medical Scientist Training Program, University of California, San Francisco, CA, USA
| | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Systems Biology Harvard Medical School, Boston, MA 02125, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Ivet Bahar
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA; Joint CMU-Pitt Ph.D. Program in Computational Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vijay G Sankaran
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA; Joint CMU-Pitt Ph.D. Program in Computational Biology, University of Pittsburgh, Pittsburgh, PA, USA; UPMC-Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA; Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Jonathan S Weissman
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA; Koch Institute For Integrative Cancer Research at MIT, MIT, Cambridge, MA, USA.
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11
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Yu F, Cato LD, Weng C, Liggett LA, Jeon S, Xu K, Chiang CW, Wiemels JL, Weissman JS, de Smith AJ, Sankaran VG. Variant to function mapping at single-cell resolution through network propagation.. [PMID: 35118467 PMCID: PMC8811900 DOI: 10.1101/2022.01.23.477426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
With burgeoning human disease genetic associations and single-cell genomic atlases covering a range of tissues, there are unprecedented opportunities to systematically gain insights into the mechanisms of disease-causal variation. However, sparsity and noise, particularly in the context of single-cell epigenomic data, hamper the identification of disease- or trait-relevant cell types, states, and trajectories. To overcome these challenges, we have developed the SCAVENGE method, which maps causal variants to their relevant cellular context at single-cell resolution by employing the strategy of network propagation. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation including enrichment of blood traits at distinct stages of human hematopoiesis, defining monocyte subsets that increase the risk for severe coronavirus disease 2019 (COVID-19), and identifying intermediate lymphocyte developmental states that are critical for predisposition to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution, but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.
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12
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Yu F, Cato LD, Weng C, Liggett LA, Jeon S, Xu K, Chiang CWK, Wiemels JL, Weissman JS, de Smith AJ, Sankaran VG. Variant to function mapping at single-cell resolution through network propagation. Nat Biotechnol 2022; 40:1644-1653. [PMID: 35668323 PMCID: PMC9646486 DOI: 10.1038/s41587-022-01341-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 04/29/2022] [Indexed: 12/30/2022]
Abstract
Genome-wide association studies in combination with single-cell genomic atlases can provide insights into the mechanisms of disease-causal genetic variation. However, identification of disease-relevant or trait-relevant cell types, states and trajectories is often hampered by sparsity and noise, particularly in the analysis of single-cell epigenomic data. To overcome these challenges, we present SCAVENGE, a computational algorithm that uses network propagation to map causal variants to their relevant cellular context at single-cell resolution. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation, applying the method to blood traits at distinct stages of human hematopoiesis, to monocyte subsets that increase the risk for severe Coronavirus Disease 2019 (COVID-19) and to intermediate lymphocyte developmental states that predispose to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.
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Affiliation(s)
- Fulong Yu
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Liam D. Cato
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Chen Weng
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.270301.70000 0001 2292 6283Whitehead Institute for Biomedical Research, Cambridge, MA USA
| | - L. Alexander Liggett
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Soyoung Jeon
- grid.42505.360000 0001 2156 6853Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Keren Xu
- grid.42505.360000 0001 2156 6853Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Charleston W. K. Chiang
- grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA USA
| | - Joseph L. Wiemels
- grid.42505.360000 0001 2156 6853Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Jonathan S. Weissman
- grid.270301.70000 0001 2292 6283Whitehead Institute for Biomedical Research, Cambridge, MA USA ,grid.116068.80000 0001 2341 2786Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Adam J. de Smith
- grid.42505.360000 0001 2156 6853Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA USA ,grid.42505.360000 0001 2156 6853Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Vijay G. Sankaran
- grid.38142.3c000000041936754XDivision of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XDepartment of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.511171.2Harvard Stem Cell Institute, Cambridge, MA USA
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13
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Qiu L, Deng Z, Zhao C, Xiao T, Weng C, Li J, Zheng L. Nutritional composition and proteomic analysis of soft-shelled turtle (Pelodiscus sinensis) egg and identification of oligopeptides with alpha-glucosidase inhibitory activity. Food Res Int 2021; 145:110414. [PMID: 34112417 DOI: 10.1016/j.foodres.2021.110414] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 04/19/2021] [Accepted: 05/10/2021] [Indexed: 12/23/2022]
Abstract
This study aimed to explore nutritional compositions and proteomics of soft-shelled turtle (SST) egg, as well as identify potential antidiabetic oligopeptides with α-glucosidase inhibitory property. Results revealed that SST egg is a promising source of highly nutritious proteins and minerals (54.64% and 5.81% of dry matter, respectively). Further proteomic analysis showed SST egg proteins contained at least 9 protein families, such as transferrin/iron binding protein and immunoregulation-related protein. Hydrolysis by different enzymes, especially papain, remarkably increased α-glucosidase inhibitory activity and scavenging activity for ABTS, DPPH, hydroxyl and oxygen radicals of SST egg proteins. Peptides from papain hydrolysate were fractionated using ultrafiltration followed by reverse phase chromatography, and 16 peptides were identified in the most active fraction by LC-QTOF-MS/MS. Molecular docking revealed that 14 of these peptides could easily dock into the substrate-binding pocket and/or inhibitor binding sites of α-glucosidase with the docking score below -150 kcal/mol, indicating their potential α-glucosidase inhibitory properties. The five most abundant oligopeptides with potent interaction with α-glucosidase were further synthesized, and oligopeptides HNKPEVEVR, ARDASVLK and SGTLLHK strongly inhibited the activity of α-glucosidase (IC50 of 56, 195 and 289 µmol/L, respectively). Therefore, oligopeptides from enzymatic hydrolysate of SST egg protein exhibit potential antidiabetic activity, making it a promising functional food ingredient.
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Affiliation(s)
- Leyun Qiu
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, Jiangxi, PR China
| | - Zeyuan Deng
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, Jiangxi, PR China; Institute for Advanced Study, University of Nanchang, Nanchang 330031, Jiangxi, PR China
| | - Caidong Zhao
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, Jiangxi, PR China
| | - Ting Xiao
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, Jiangxi, PR China
| | - Chen Weng
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, Jiangxi, PR China
| | - Jing Li
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, Jiangxi, PR China
| | - Liufeng Zheng
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, Jiangxi, PR China.
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Khan A, Lu C, Hayes M, Connolly J, Mentch F, Sleiman P, Hakonarson H, Mukherjee E, Weng C, Hripcsak G, Kiryluk K, Wheless L, Petukhova L. 171 Hidradenitis suppurativa genome-wide association study. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.02.191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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15
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Bell A, Babbush K, Khan A, Hayes M, Connolly J, Mentch F, Sleiman P, Hakonarson H, Mukherjee E, Hripcsak G, Kiryluk K, Weng C, Cohen S, Wheless L, Petukhova L. 328 Data driven approach identifies hidradenitis suppurativa subtypes in electronic health records. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.02.350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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16
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Colvin A, Dabela E, Khan A, Hayes M, Connolly J, Mentch F, Almoguera B, Hakonarson H, Mukherjee E, Hripcsak G, Weng C, Kiryluk K, Wheless L, Petukhova L. 366 Adverse reproductive outcomes among women with hidradenitis suppurativa. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.02.388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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17
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Khan A, McGovern J, Yang Z, Wang C, Hughes T, Dabela E, Garzon M, Lauren C, Levin L, Dai Z, Hayes M, Connolly J, Mentch F, Almoguera B, Sleiman P, Hakonarson H, Denny J, Love J, Shalek A, Hripcsak G, Weng C, Ionita-Laza I, Kiryluk K, Petukhova L. 570 A genome-wide association study in an African American cohort implicates IL-12A in acne. J Invest Dermatol 2021. [DOI: 10.1016/j.jid.2021.02.597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Zou Q, Wei M, Zhang N, Niu X, Weng C, Deng ZY, Li J. Different Influences of trans Fatty Acids on the Phospholipase A2 and Arachidonic Acid Metabolic Pathway in Hepatocytes. J Agric Food Chem 2021; 69:4120-4133. [PMID: 33819034 DOI: 10.1021/acs.jafc.1c01097] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
This study investigated the effects of 9t18:1 (representing I-TFAs), 9t16:1, and 11t18:1 (representing R-TFAs) and their mixtures on the normal human hepatocyte LO2 cell function, the possible mechanism of lipid metabolism by lipidomics, and the relationship between phospholipase A2 (PLA2) and the arachidonic acid (AA) metabolic pathway. Here, we found that the damaging effect of 9t18:1 on the LO2 cell function was significantly greater than those of 11t18:1 and 9t16:1 (p < 0.05), and the damaging effects of CHB and HSO were significantly greater than those of HHB and CM (p < 0.05). The lipidomic results showed that TFAs and TFA mixtures caused a significant change in the lipid profiles of LO2 cells, in which the TAG, PL, and OL contents increased significantly. Moreover, 9t18:1 regulated only the protein expression of cPLA2 but did not participate in the AA metabolic pathway, while 11t18:1 and 9t16:1 participated in the COX-2 and CYP450 pathways, respectively.
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Affiliation(s)
- Qian Zou
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China
| | - Meng Wei
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China
| | - Niu Zhang
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China
| | - Xian Niu
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China
| | - Chen Weng
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China
| | - Ze-Yuan Deng
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China
| | - Jing Li
- State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China
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Povysil G, Butler-Laporte G, Shang N, Weng C, Khan A, Alaamery M, Nakanishi T, Zhou S, Forgetta V, Eveleigh R, Bourgey M, Aziz N, Jones S, Knoppers B, Scherer S, Strug L, Lepage P, Ragoussis J, Bourque G, Alghamdi J, Aljawini N, Albes N, Al-Afghani HM, Alghamdi B, Almutair M, Mahmoud ES, Safie LA, Bardisy HE, Al Harthi FS, Alshareef A, Suliman BA, Alqahtani S, AlMalik A, Alrashed MM, Massadeh S, Mooser V, Lathrop M, Arabi Y, Mbarek H, Saad C, Al-Muftah W, Badji R, Al Thani A, Ismail SI, Gharavi AG, Abedalthagafi MS, Richards JB, Goldstein DB, Kiryluk K. Failure to replicate the association of rare loss-of-function variants in type I IFN immunity genes with severe COVID-19. medRxiv 2020:2020.12.18.20248226. [PMID: 33398295 PMCID: PMC7781338 DOI: 10.1101/2020.12.18.20248226] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,934 COVID-19 cases (713 with severe and 1,221 with mild disease) and 15,251 ancestry-matched population controls across four independent COVID-19 biobanks. We then tested if rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only one rare pLOF mutation across these genes amongst 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We find no evidence of association of rare loss-of-function variants in the proposed 13 candidate genes with severe COVID-19 outcomes.
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Affiliation(s)
- Gundula Povysil
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Guillaume Butler-Laporte
- Lady Davis Institute for Medical Research, Montréal, Québec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Québec, Canada
| | - Ning Shang
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University
| | - Chen Weng
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University
| | - Manal Alaamery
- Developmental Medicine Department, King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
- KACST-BWH Center of Excellence for Biomedicine, Joint Centers of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- King Abdulaziz City for Science and Technology (KACST)-Saudi Human Genome Satellite Lab at Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
| | - Tomoko Nakanishi
- Lady Davis Institute for Medical Research, Montréal, Québec, Canada
- Department of Human Genetics, McGill University, Montréal, Canada
- Kyoto-McGill International Collaborative School in Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Research Fellow, Japan Society for the Promotion of Science, Japan
| | - Sirui Zhou
- Lady Davis Institute for Medical Research, Montréal, Québec, Canada
| | | | - Robert Eveleigh
- Canadian Centre for Computational Genomics, McGill University, Montreal, Canada
- McGill Genome Center, McGill University, Montréal, Québec, Canada
| | - Mathieu Bourgey
- Canadian Centre for Computational Genomics, McGill University, Montreal, Canada
- McGill Genome Center, McGill University, Montréal, Québec, Canada
| | - Naveed Aziz
- Canadian COVID Genomics Network, HostSeq Project, Canada
| | - Steven Jones
- Canadian COVID Genomics Network, HostSeq Project, Canada
| | | | | | - Lisa Strug
- Canadian COVID Genomics Network, HostSeq Project, Canada
| | - Pierre Lepage
- Canadian Centre for Computational Genomics, McGill University, Montreal, Canada
| | - Jiannis Ragoussis
- Department of Human Genetics, McGill University, Montréal, Canada
- Canadian Centre for Computational Genomics, McGill University, Montreal, Canada
| | - Guillaume Bourque
- Department of Human Genetics, McGill University, Montréal, Canada
- McGill Genome Center, McGill University, Montréal, Québec, Canada
- Canadian Centre for Computational Genomics, McGill University, Montreal, Canada
| | - Jahad Alghamdi
- Saudi Biobank, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Nora Aljawini
- Developmental Medicine Department, King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
- KACST-BWH Center of Excellence for Biomedicine, Joint Centers of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- King Abdulaziz City for Science and Technology (KACST)-Saudi Human Genome Satellite Lab at Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
| | - Nour Albes
- Developmental Medicine Department, King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
- KACST-BWH Center of Excellence for Biomedicine, Joint Centers of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- Intensive Care Department, Ministry of National Guard Health Affairs, King Saud Bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia
| | - Hani M. Al-Afghani
- Laboratory Department, Security Forces Hospital, General Directorate of Medical Services, Ministry of Interior, Clinical Laboratory Sciences, Taibah University, Madina, Saudi Arabia
| | - Bader Alghamdi
- Developmental Medicine Department, King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
| | - Mansour Almutair
- Developmental Medicine Department, King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
| | - Ebrahim Sabri Mahmoud
- King Abdulaziz City for Science and Technology (KACST)-Saudi Human Genome Satellite Lab at Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
| | - Leen Abu Safie
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Hadeel El Bardisy
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Fawz S. Al Harthi
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Abdulraheem Alshareef
- Laboratory Department, Security Forces Hospital, General Directorate of Medical Services, Ministry of Interior, Clinical Laboratory Sciences, Taibah University, Madina, Saudi Arabia
| | - Bandar Ali Suliman
- The Liver Transplant Unit, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Saleh Alqahtani
- The Liver Transplant Unit, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
- The Division of Gastroenterology and Hepatology, Johns Hopkins University, Baltimore, USA
| | - Abdulaziz AlMalik
- Life Science and Environmental Institute, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - May M. Alrashed
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Salam Massadeh
- Developmental Medicine Department, King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences, King Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
- KACST-BWH Center of Excellence for Biomedicine, Joint Centers of Excellence Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
- King Abdulaziz City for Science and Technology (KACST)-Saudi Human Genome Satellite Lab at Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
| | - Vincent Mooser
- Department of Human Genetics, McGill University, Montréal, Canada
| | - Mark Lathrop
- Department of Human Genetics, McGill University, Montréal, Canada
- Canadian COVID Genomics Network, HostSeq Project, Canada
- Canadian Centre for Computational Genomics, McGill University, Montreal, Canada
| | - Yaseen Arabi
- King Abdulaziz City for Science and Technology (KACST)-Saudi Human Genome Satellite Lab at Abdulaziz Medical City, Ministry of National Guard Health Affairs (MNGHA), Riyadh, Saudi Arabia
- Intensive Care Department, Ministry of National Guard Health Affairs, King Saud Bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia
| | - Hamdi Mbarek
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Chadi Saad
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Wadha Al-Muftah
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Radja Badji
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Asma Al Thani
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Said I. Ismail
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Ali G. Gharavi
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University
- Center for Precision Medicine and Genomics. Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University, New York, New York, USA
| | - Malak S. Abedalthagafi
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
- Life Science and Environmental Institute, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - J Brent Richards
- Lady Davis Institute for Medical Research, Montréal, Québec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Québec, Canada
- Department of Human Genetics, McGill University, Montréal, Canada
- Department of Twin Research, King’s College London, London, UK
| | - David B. Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Genetics & Development, Columbia University, New York, New York, USA
| | - Krzysztof Kiryluk
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University
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20
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Weng C, Deng ZY, Zhang N, Zou Q, Fan YW, Liu R, Zhen LF, Li J. Lipid profiles of Chinese soft-shell turtle eggs (Pelodiscus sinensis). J Food Compost Anal 2020. [DOI: 10.1016/j.jfca.2020.103627] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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21
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Weng C, Xi J, Li H, Cui J, Gu A, Lai S, Leskov K, Ke L, Jin F, Li Y. Single-cell lineage analysis reveals extensive multimodal transcriptional control during directed beta-cell differentiation. Nat Metab 2020; 2:1443-1458. [PMID: 33257854 PMCID: PMC7744443 DOI: 10.1038/s42255-020-00314-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 10/22/2020] [Indexed: 11/08/2022]
Abstract
The in vitro differentiation of insulin-producing beta-like cells can model aspects of human pancreatic development. Here, we generate 95,308 single-cell transcriptomes and reconstruct a lineage tree of the entire differentiation process from human embryonic stem cells to beta-like cells to study temporally regulated genes during differentiation. We identify so-called 'switch genes' at the branch point of endocrine/non-endocrine cell fate choice, revealing insights into the mechanisms of differentiation-promoting reagents, such as NOTCH and ROCKII inhibitors, and providing improved differentiation protocols. Over 20% of all detectable genes are activated multiple times during differentiation, even though their enhancer activation is usually unimodal, indicating extensive gene reuse driven by different enhancers. We also identify a stage-specific enhancer at the TCF7L2 locus for diabetes, uncovered by genome-wide association studies, that drives a transient wave of gene expression in pancreatic progenitors. Finally, we develop a web app to visualize gene expression on the lineage tree, providing a comprehensive single-cell data resource for researchers studying islet biology and diabetes.
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Affiliation(s)
- Chen Weng
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Jiajia Xi
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Haiyan Li
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Jian Cui
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Anniya Gu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- Medical Scientist Training Program (MSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Sisi Lai
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Konstantin Leskov
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Luxin Ke
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- Master of Science in Biology Program, Department of Biology, College of Arts and Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Fulai Jin
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
- Department of Population and Quantitative Health Sciences, Department of Electrical Engineering and Computer Science, Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA.
| | - Yan Li
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
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22
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Hu SB, Zou Q, Lv X, Zhou RL, Niu X, Weng C, Chen F, Fan YW, Deng ZY, Li J. 9t18:1 and 11t18:1 activate the MAPK pathway to regulate the expression of PLA2 and cause inflammation in HUVECs. Food Funct 2020; 11:649-661. [PMID: 31895396 DOI: 10.1039/c9fo01982k] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
trans fatty acids (TFAs) have been reported to promote vascular diseases mainly by promoting apoptosis and inflammation of vascular endothelial cells. However, it has been reported in recent years that elaidic acid (9t18:1) and vaccenic acid (11t18:1) may have different effects on vascular health. This study investigated the effects of 9t18:1 and 11t18:1 on human umbilical vein endothelial cell (HUVEC) function and the possible mechanism of inflammation by analyzing the changes in the phospholipid composition and the relationship between phospholipase A2 (PLA2) and MAPK pathway. Here we found that the effect of 11t18:1 on cell viability, membrane damage and cellular inflammation was significantly lower than that of 9t18:1 (p < 0.05). And 9t18:1 and 11t18:1 had different effects on phospholipid composition. Both 9t18:1 and 11t18:1 significantly increased the protein expression of PLA2. Moreover, the MAPK pathway regulated the expression of PLA2, inflammatory cytokines and cyclooxygenase-2 (COX-2) and the secretion of prostaglandin E2 (PGE2) in HUVECs induced by 9t18:1 and 11t18:1. In conclusion, 9t18:1 and 11t18:1 activated the MAPK pathway which regulated the expression of PLA2 to cause inflammation in HUVECs.
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Affiliation(s)
- Sheng-Ben Hu
- State Key Lab of Food Science and Technology, Institute for Advanced Study, Nanchang University, Nanchang, Jiangxi 330047, China
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23
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Van Buren E, Hu M, Weng C, Jin F, Li Y, Wu D, Li Y. TWO-SIGMA: A novel two-component single cell model-based association method for single-cell RNA-seq data. Genet Epidemiol 2020; 45:142-153. [PMID: 32989764 DOI: 10.1002/gepi.22361] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Revised: 08/31/2020] [Accepted: 09/03/2020] [Indexed: 01/06/2023]
Abstract
In this paper, we develop TWO-SIGMA, a TWO-component SInGle cell Model-based Association method for differential expression (DE) analyses in single-cell RNA-seq (scRNA-seq) data. The first component models the probability of "drop-out" with a mixed-effects logistic regression model and the second component models the (conditional) mean expression with a mixed-effects negative binomial regression model. TWO-SIGMA is extremely flexible in that it: (i) does not require a log-transformation of the outcome, (ii) allows for overdispersed and zero-inflated counts, (iii) accommodates a correlation structure between cells from the same individual via random effect terms, (iv) can analyze unbalanced designs (in which the number of cells does not need to be identical for all samples), (v) can control for additional sample-level and cell-level covariates including batch effects, (vi) provides interpretable effect size estimates, and (vii) enables general tests of DE beyond two-group comparisons. To our knowledge, TWO-SIGMA is the only method for analyzing scRNA-seq data that can simultaneously accomplish each of these features. Simulations studies show that TWO-SIGMA outperforms alternative regression-based approaches in both type-I error control and power enhancement when the data contains even moderate within-sample correlation. A real data analysis using pancreas islet single-cells exhibits the flexibility of TWO-SIGMA and demonstrates that incorrectly failing to include random effect terms can have dramatic impacts on scientific conclusions. TWO-SIGMA is implemented in the R package twosigma available at https://github.com/edvanburen/twosigma.
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Affiliation(s)
- Eric Van Buren
- Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Chen Weng
- Department of Genetics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Fulai Jin
- Department of Genetics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yan Li
- Department of Genetics, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Di Wu
- Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Division of Oral and Craniofacial Health Sciences, Adams School of Dentistry, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yun Li
- Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Department of Genetics, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.,Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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24
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Liao Z, Weng C, Long S, Xiao Z. Do social ties foster firms’ environmental innovation? The moderating effect of resource bricolage. Technology Analysis & Strategic Management 2020. [DOI: 10.1080/09537325.2020.1821876] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Zhongju Liao
- School of Economics and Management, Zhejiang Sci-Tech University, Hangzhou, People’s Republic of China
| | - Chen Weng
- School of Economics and Management, Zhejiang Sci-Tech University, Hangzhou, People’s Republic of China
| | - Siying Long
- School of Economics and Management, South China Agricultural University, Guangzhou, People’s Republic of China
| | - Zengrui Xiao
- School of International Education, Zhejiang Sci-Tech University, Hangzhou 310018, People’s Republic of China
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25
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Hu R, Walker E, Huang C, Xu Y, Weng C, Erickson GE, Coldren A, Yang X, Brissova M, Kaverina I, Balamurugan AN, Wright CVE, Li Y, Stein R, Gu G. Myt Transcription Factors Prevent Stress-Response Gene Overactivation to Enable Postnatal Pancreatic β Cell Proliferation, Function, and Survival. Dev Cell 2020; 53:754. [PMID: 32574594 PMCID: PMC8143432 DOI: 10.1016/j.devcel.2020.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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26
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Weng C, Xu J, Wang Q, Lu W, Liu Z. Efficacy and safety of duloxetine in osteoarthritis or chronic low back pain: a Systematic review and meta-analysis. Osteoarthritis Cartilage 2020; 28:721-734. [PMID: 32169731 DOI: 10.1016/j.joca.2020.03.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 02/06/2020] [Accepted: 03/02/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To evaluate the efficacy and safety of duloxetine in the treatment of patients with osteoarthritis (OA) or chronic low back pain (CLBP). METHODS Relevant randomized controlled trials (RCTs) were searched in PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov. Included RCTs compared the efficacy and safety of duloxetine vs placebo in the treatment of OA or CLBP. Weighted mean difference (WMD) were calculated for continuous outcomes while risk ratio (RR) were calculated for dichotomous outcomes. RESULTS Nine RCTs were included in our meta-analysis. Duloxetine had significant improvement over placebo in Brief Pain Inventory 24-h average pain [WMD: -0.67; 95% confidence interval (CI):-0.80, -0.53], weekly mean of the 24-h average pain (WMD: -0.65; 95% CI: -0.79, -0.52), Patient's Global Impression of Improvement (WMD: -0.41; 95% CI: -0.49, -0.32), Clinical Global Impression of Severity (WMD: -0.32; 95% CI: -0.38, -0.25), European Quality of Life Questionnaire-5 Dimension (WMD: 0.04; 95% CI: 0.02, 0.07). In addition, duloxetine is associated with more treatment-emergent adverse events (TEAEs) (RR: 1.25; 95% CI: 1.17, 1.33) and discontinuations for adverse events (AEs) (RR: 2.31; 95% CI: 1.81, 2.94). However, there was no statistically significant difference in serious AEs between duloxetine and placebo. CONCLUSION Duloxetine had modest to moderate effects on pain relief, function improvement, mood regulation and improvement in quality of life with mild AEs in the treatment of OA or CLBP. Future RCTs should focus on comparing duloxetine with other oral drugs and assessing the long-term safety of duloxetine.
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Affiliation(s)
- C Weng
- Department of Rheumatology and Immunology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
| | - J Xu
- Department of Rheumatology and Immunology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
| | - Q Wang
- Department of Rheumatology and Immunology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
| | - W Lu
- Department of Rheumatology and Immunology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
| | - Z Liu
- Department of Rheumatology and Immunology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
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27
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Sun J, Zhou Z, Weng C, Wang C, Chen J, Feng X, Yu P, Qi M. Identification and functional characterization of a hemizygous novel intronic variant in OCRL gene causes Lowe syndrome. Clin Exp Nephrol 2020; 24:657-665. [PMID: 32394213 DOI: 10.1007/s10157-020-01897-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Accepted: 04/23/2020] [Indexed: 10/24/2022]
Abstract
BACKGROUND Lowe syndrome is an X-linked multisystem disorder affecting eyes, nervous system, and kidney. The main causes are mutations in the OCRL gene that encodes a member of the inositol polyphosphate-5-phosphatase protein family. In this study, we aimed to gain new insights into the consequences of a novel OCRL intronic variant on pre-mRNA splicing as a main cause of Lowe syndrome in a boy. METHODS After clinical diagnosis of the patient with Lowe syndrome, genetic testing was used to detect the presence of the OCRL variants. In silico analysis, human splicing finder and PyMol were used to predict this variant effect. Then, we analyzed the variant transcript by using a minigene construct in addition to in silico analysis. RESULTS A hemizygous novel splicing variant in the intron 10 splice donor site of OCRL (c.939 + 3A > C) was identified in a boy with Lowe syndrome. We detected that the splice junction variant leads to aberrant OCRL mRNA splicing which results in the formation of an alternative transcript in which 29 nucleotides of exon 10 were skipped. The findings obtained from the exon-trapping assay were identical to those of in silico analysis. Hence, the truncated OCRL protein may lacked the last 597 native amino acids. CONCLUSIONS The minigene assays detected the same transcript abnormality to in silico assay and were reliable in revealing the pathogenicity of the intronic variant we have used previously. Overall, this study provides new insights about Lowe syndrome and further reveals the molecular pathogenicity mechanism of the intronic variant disease.
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Affiliation(s)
- Junhui Sun
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Research Building A713, Yuhangtang Road 866, Hangzhou, China.,Zhejiang California International Nanosystems Institute, Zhjiang University, Hangzhou, China
| | - Zhongwei Zhou
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Research Building A713, Yuhangtang Road 866, Hangzhou, China
| | - Chen Weng
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Research Building A713, Yuhangtang Road 866, Hangzhou, China
| | - Chaojun Wang
- Department of Urology, The First Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Jiao Chen
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Research Building A713, Yuhangtang Road 866, Hangzhou, China
| | - Xue Feng
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Research Building A713, Yuhangtang Road 866, Hangzhou, China
| | - Ping Yu
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Research Building A713, Yuhangtang Road 866, Hangzhou, China
| | - Ming Qi
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Research Building A713, Yuhangtang Road 866, Hangzhou, China. .,Zhejiang California International Nanosystems Institute, Zhjiang University, Hangzhou, China. .,Center for Genetic and Genomic Medicine First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China. .,Department of Pathology and Laboratory of Medicine, University of Rochester Medical Centre, Rochester, NY, USA. .,DIAN Diagnostics, Hangzhou, China.
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Hu R, Walker E, Huang C, Xu Y, Weng C, Erickson GE, Coldren A, Yang X, Brissova M, Kaverina I, Balamurugan AN, Wright CVE, Li Y, Stein R, Gu G. Myt Transcription Factors Prevent Stress-Response Gene Overactivation to Enable Postnatal Pancreatic β Cell Proliferation, Function, and Survival. Dev Cell 2020; 53:390-405.e10. [PMID: 32359405 PMCID: PMC7278035 DOI: 10.1016/j.devcel.2020.04.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2019] [Revised: 03/06/2020] [Accepted: 04/03/2020] [Indexed: 02/06/2023]
Abstract
Although cellular stress response is important for maintaining function and survival, overactivation of late-stage stress effectors cause dysfunction and death. We show that the myelin transcription factors (TFs) Myt1 (Nzf2), Myt2 (Myt1l, Nztf1, and Png-1), and Myt3 (St18 and Nzf3) prevent such overactivation in islet β cells. Thus, we found that co-inactivating the Myt TFs in mouse pancreatic progenitors compromised postnatal β cell function, proliferation, and survival, preceded by upregulation of late-stage stress-response genes activating transcription factors (e.g., Atf4) and heat-shock proteins (Hsps). Myt1 binds putative enhancers of Atf4 and Hsps, whose overexpression largely recapitulated the Myt-mutant phenotypes. Moreover, Myt(MYT)-TF levels were upregulated in mouse and human β cells during metabolic stress-induced compensation but downregulated in dysfunctional type 2 diabetic (T2D) human β cells. Lastly, MYT knockdown caused stress-gene overactivation and death in human EndoC-βH1 cells. These findings suggest that Myt TFs are essential restrictors of stress-response overactivity.
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Affiliation(s)
- Ruiying Hu
- Vanderbilt Program in Developmental Biology, Department of Cell and Developmental Biology, and Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Emily Walker
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Chen Huang
- Vanderbilt Program in Developmental Biology, Department of Cell and Developmental Biology, and Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Yanwen Xu
- Vanderbilt Program in Developmental Biology, Department of Cell and Developmental Biology, and Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Chen Weng
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Gillian E Erickson
- Vanderbilt Program in Developmental Biology, Department of Cell and Developmental Biology, and Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Anastasia Coldren
- Department of Medicine, Vanderbilt Medical Center, Nashville, TN 27232, USA
| | - Xiaodun Yang
- Vanderbilt Program in Developmental Biology, Department of Cell and Developmental Biology, and Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Marcela Brissova
- Department of Medicine, Vanderbilt Medical Center, Nashville, TN 27232, USA
| | - Irina Kaverina
- Vanderbilt Program in Developmental Biology, Department of Cell and Developmental Biology, and Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Appakalai N Balamurugan
- Department of Surgery, Clinical Islet Transplantation Laboratory, Cardiovascular Innovation Institute, University of Louisville, Louisville, KY 40202, USA
| | - Christopher V E Wright
- Vanderbilt Program in Developmental Biology, Department of Cell and Developmental Biology, and Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Yan Li
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Roland Stein
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Guoqiang Gu
- Vanderbilt Program in Developmental Biology, Department of Cell and Developmental Biology, and Center for Stem Cell Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
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Weng C, Chen LH, Chao AS, Wang CJ. 2363 Laparoscopic Management of Heterotopic Cornual Pregnancy - Tips & Tricks. J Minim Invasive Gynecol 2019. [DOI: 10.1016/j.jmig.2019.09.090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Fang Z, Weng C, Li H, Tao R, Mai W, Liu X, Lu L, Lai S, Duan Q, Alvarez C, Arvan P, Wynshaw-Boris A, Li Y, Pei Y, Jin F, Li Y. Single-Cell Heterogeneity Analysis and CRISPR Screen Identify Key β-Cell-Specific Disease Genes. Cell Rep 2019; 26:3132-3144.e7. [PMID: 30865899 PMCID: PMC6573026 DOI: 10.1016/j.celrep.2019.02.043] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 05/03/2018] [Accepted: 02/12/2019] [Indexed: 01/13/2023] Open
Abstract
Identification of human disease signature genes typically requires samples from many donors to achieve statistical significance. Here, we show that single-cell heterogeneity analysis may overcome this hurdle by significantly improving the test sensitivity. We analyzed the transcriptome of 39,905 single islets cells from 9 donors and observed distinct β cell heterogeneity trajectories associated with obesity or type 2 diabetes (T2D). We therefore developed RePACT, a sensitive single-cell analysis algorithm to identify both common and specific signature genes for obesity and T2D. We mapped both β-cell-specific genes and disease signature genes to the insulin regulatory network identified from a genome-wide CRISPR screen. Our integrative analysis discovered the previously unrecognized roles of the cohesin loading complex and the NuA4/Tip60 histone acetyltransferase complex in regulating insulin transcription and release. Our study demonstrated the power of combining single-cell heterogeneity analysis and functional genomics to dissect the etiology of complex diseases.
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Affiliation(s)
- Zhou Fang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Chen Weng
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Haiyan Li
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Ran Tao
- Center for Cancer and Immunology Research, Brain Tumor Institute, Children's National Medical Center, Washington, D.C. 20010, USA
| | - Weihua Mai
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA; Department of Neurology, the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province 519000, China
| | - Xiaoxiao Liu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Leina Lu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Sisi Lai
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Qing Duan
- Department of Biostatistics, Department of Genetics, Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Carlos Alvarez
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA; The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Peter Arvan
- Division of Metabolism, Endocrinology, and Diabetes, University of Michigan Medical Center, Ann Arbor, MI 48109, USA
| | - Anthony Wynshaw-Boris
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Yun Li
- Department of Biostatistics, Department of Genetics, Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Yanxin Pei
- Center for Cancer and Immunology Research, Brain Tumor Institute, Children's National Medical Center, Washington, D.C. 20010, USA
| | - Fulai Jin
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA; Department of Population and Quantitative Health Sciences, Department of Electrical Engineering and Computer Science, Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA.
| | - Yan Li
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA.
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Affiliation(s)
- Yang Sun
- School of Economics and Management, Zhejiang Sci-Tech University, Hangzhou, People’s Republic of China
| | - Chen Weng
- School of Economics and Management, Zhejiang Sci-Tech University, Hangzhou, People’s Republic of China
| | - Zhongju Liao
- School of Economics and Management, Zhejiang Sci-Tech University, Hangzhou, People’s Republic of China
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Chen Y, Tseng S, Koh C, Chung C, Weng C, Tsai Y. Zinc Deficiency and Long-Term Outcome in Cases After Isolated Intestinal Transplantation in Taiwan. Transplant Proc 2018; 50:2771-2774. [PMID: 30401395 DOI: 10.1016/j.transproceed.2018.03.094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2018] [Accepted: 03/02/2018] [Indexed: 12/11/2022]
Abstract
OBJECTIVES The small intestine is the primary site for absorption of dietary zinc. Intestinal transplant recipients are at high risk for zinc deficiency because of the long process of posttransplant adaptation. We initiated an intestinal transplant program in Taiwan in 2007. In this study, we aimed to retrospectively investigate the incidence of zinc deficiency in recipients after intestinal transplantation. METHODS Twenty-one isolated intestinal transplants were performed in 20 patients with 1 retransplantation. The level of serum zinc was monitored periodically, and zinc supplements were administered when zinc level was below 700 ng/mL. Twelve patients with graft above 1-year survival and with available related data were enrolled for the analysis of zinc deficiency. The levels of serum zinc were tracked, and the protocol of zinc supplementation is discussed herein. RESULTS The survival rates of 20 transplant recipients for 1 year, 3 years, and 5 years were 85%, 75%, and 65%, respectively. In the 12 grafts that survived longer than 1 year, we found that zinc deficiency was highest during the third (41.7%) to sixth (50%) month after transplantation. Sustained supplementation of zinc was required for over 70% of patients throughout the 3-year period to maintain their zinc level around the lower normal limit. CONCLUSION The outcome of isolated small bowel transplantation is promising. Periodical monitoring and sufficient dosing of zinc supplements should be considered into the posttransplant protocol to prevent zinc deficiency after intestinal transplantation.
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Affiliation(s)
- Y Chen
- Department of Surgery, Far Eastern Memorial Hospital, Pan-Chiao, New Taipei, Taiwan, Republic of China; Department of Chemical Engineering and Materials Science, Yuan Ze University, Chung-Li, Taoyuan, Taiwan, Republic of China
| | - S Tseng
- Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan, Republic of China
| | - C Koh
- Department of Surgery, Far Eastern Memorial Hospital, Pan-Chiao, New Taipei, Taiwan, Republic of China
| | - C Chung
- Department of Internal Medicine, Far Eastern Memorial Hospital, Pan-Chiao, New Taipei, Taiwan, Republic of China; College of Medicine, Fu Jen Catholic University, Xin-Zhuang, New Taipei, Taiwan
| | - C Weng
- Department of Surgery, Far Eastern Memorial Hospital, Pan-Chiao, New Taipei, Taiwan, Republic of China
| | - Y Tsai
- Department of Surgery, Far Eastern Memorial Hospital, Pan-Chiao, New Taipei, Taiwan, Republic of China; Department of Chemical Engineering and Materials Science, Yuan Ze University, Chung-Li, Taoyuan, Taiwan, Republic of China; Department of Materials and Textiles, Oriental Institute of Technology, Pan-Chiao, New Taipei, Taiwan, Republic of China.
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Elitt MS, Shick HE, Madhavan M, Allan KC, Clayton BLL, Weng C, Miller TE, Factor DC, Barbar L, Nawash BS, Nevin ZS, Lager AM, Li Y, Jin F, Adams DJ, Tesar PJ. Chemical Screening Identifies Enhancers of Mutant Oligodendrocyte Survival and Unmasks a Distinct Pathological Phase in Pelizaeus-Merzbacher Disease. Stem Cell Reports 2018; 11:711-726. [PMID: 30146490 PMCID: PMC6135742 DOI: 10.1016/j.stemcr.2018.07.015] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 07/30/2018] [Accepted: 07/30/2018] [Indexed: 01/15/2023] Open
Abstract
Pelizaeus-Merzbacher disease (PMD) is a fatal X-linked disorder caused by loss of myelinating oligodendrocytes and consequent hypomyelination. The underlying cellular and molecular dysfunctions are not fully defined, but therapeutic enhancement of oligodendrocyte survival could restore functional myelination in patients. Here we generated pure, scalable quantities of induced pluripotent stem cell-derived oligodendrocyte progenitor cells (OPCs) from a severe mouse model of PMD, Plp1jimpy. Temporal phenotypic and transcriptomic studies defined an early pathological window characterized by endoplasmic reticulum (ER) stress and cell death as OPCs exit their progenitor state. High-throughput phenotypic screening identified a compound, Ro 25-6981, which modulates the ER stress response and rescues mutant oligodendrocyte survival in jimpy, in vitro and in vivo, and in human PMD oligocortical spheroids. Surprisingly, increasing oligodendrocyte survival did not restore subsequent myelination, revealing a second pathological phase. Collectively, our work shows that PMD oligodendrocyte loss can be rescued pharmacologically and defines a need for multifactorial intervention to restore myelination.
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Affiliation(s)
- Matthew S Elitt
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - H Elizabeth Shick
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Mayur Madhavan
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Kevin C Allan
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Benjamin L L Clayton
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Chen Weng
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Tyler E Miller
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Daniel C Factor
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Lilianne Barbar
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Baraa S Nawash
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Zachary S Nevin
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Angela M Lager
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Yan Li
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Fulai Jin
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA; Department of Engineering and Computer Science, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA; Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Drew J Adams
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA; Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Paul J Tesar
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA; Department of Neurosciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA; Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA.
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Tong M, Shang N, Wang R, Lebwohl B, Mehl K, Hripcsak G, Weng C, Kiryluk K, Petukhova L. 316 Development of a phenotyping algorithm to identify patients with autoimmune disease in electronic health records for future large scale studies. J Invest Dermatol 2018. [DOI: 10.1016/j.jid.2018.03.322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Feng X, Weng C, Wei T, Sun J, Huang F, Yu P, Qi M. Two EDA gene mutations in chinese patients with hypohidrotic ectodermal dysplasia. J Eur Acad Dermatol Venereol 2018; 32:e324-e326. [PMID: 29444360 DOI: 10.1111/jdv.14874] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- X Feng
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - C Weng
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - T Wei
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - J Sun
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - F Huang
- Department of Dermatology of Suxi Health-center, Yiwu, 322009, China
| | - P Yu
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - M Qi
- Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Hangzhou, 310058, China.,Department of Pathology and Laboratory Medicine, University of Rochester, New York, NY, 14604, USA.,Assisted Reproduction Unit, Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China.,Key Laboratory of Reproductive Dysfunction Management of Zhejiang Province, Hangzhou, 310016, China.,DIAN Diagnostics, Hangzhou, 310024, China
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Zhang Q, Wei Y, Han H, Weng C. Enhancing bioethanol production from water hyacinth by new combined pretreatment methods. Bioresour Technol 2018; 251:358-363. [PMID: 29291533 DOI: 10.1016/j.biortech.2017.12.085] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2017] [Revised: 12/23/2017] [Accepted: 12/26/2017] [Indexed: 05/06/2023]
Abstract
This study investigated the possibility of enhancing bioethanol production by combined pretreatment methods for water hyacinth. Three different kinds of pretreatment methods, including microbial pretreatment, microbial combined dilute acid pretreatment, and microbial combined dilute alkaline pretreatment, were investigated for water hyacinth degradation. The results showed that microbial combined dilute acid pretreatment is the most effective method, resulting in the highest cellulose content (39.4 ± 2.8%) and reducing sugars production (430.66 mg·g-1). Scanning Electron Microscopy and Fourier Transform Infrared Spectrometer analysis indicated that the basic tissue of water hyacinth was significantly destroyed. Compared to the other previously reported pretreatment methods for water hyacinth, which did not append additional cellulase and microbes for hydrolysis process, the microbial combined dilute acid pretreatment of our research could achieve the highest reducing sugars. Moreover, the production of bioethanol could achieve 1.40 g·L-1 after fermentation, which could provide an extremely promising way for utilization of water hyacinth.
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Affiliation(s)
- Qiuzhuo Zhang
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, 200241 Shanghai, China.
| | - Yan Wei
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, 200241 Shanghai, China; School of Environmental Science and Engineering, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Hui Han
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, 200241 Shanghai, China
| | - Chen Weng
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, 200241 Shanghai, China
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Abstract
Abstract
In recent years, porous materials are gaining in popularity for engineering applications, due to their special characteristics, such as low density, large specific surface area, and excellent permeability. In this study, powder processing technique was used to prepare ultra-high molecular weight polyethylene UHMWPE porous materials. Sintering temperature was obtained by combining differential scanning calorimetry (DSC) analysis and tensile tests. The surface morphology of sintering necks and tensile fracture were observed by scanning electron microscopy (SEM). Finally, single factor tests and orthogonal experiments were conducted to optimize three main processing parameters for a better permeability. It is found that the proper sintering temperature range would be from 143 to 153.1°C. According to the significance of influence, processing factors come in the sequence of the particle size, the compaction strength and the sintering temperature. Porous materials were successfully prepared, under the optimized parameters as the particle size >250 μm, the compaction strength of 2.5 MPa and the sintering temperature of 152°C.
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Affiliation(s)
- B.-Y. Jiang
- State Key Laboratory of High Performance Complex Manufacturing , Central South University, Changsha, Hunan , PRC
- College of Mechanical and Electrical Engineering , Central South University, Changsha, Hunan , PRC
| | - M.-Y. Zhou
- State Key Laboratory of High Performance Complex Manufacturing , Central South University, Changsha, Hunan , PRC
- College of Mechanical and Electrical Engineering , Central South University, Changsha, Hunan , PRC
| | - C. Weng
- State Key Laboratory of High Performance Complex Manufacturing , Central South University, Changsha, Hunan , PRC
- College of Mechanical and Electrical Engineering , Central South University, Changsha, Hunan , PRC
| | - C.-F. Li
- State Key Laboratory of High Performance Complex Manufacturing , Central South University, Changsha, Hunan , PRC
- College of Mechanical and Electrical Engineering , Central South University, Changsha, Hunan , PRC
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Wang H, Weng C, Chen H. Positive association between KCNJ5 rs2604204 (A/C) polymorphism and plasma aldosterone levels, but also plasma renin and angiotensin I and II levels, in newly diagnosed hypertensive Chinese: a case–control study. J Hum Hypertens 2017; 31:457-461. [DOI: 10.1038/jhh.2016.97] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Revised: 11/20/2016] [Accepted: 12/02/2016] [Indexed: 12/28/2022]
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Abstract
OBJECTIVES To reflect on the notable events and significant developments in Clinical Research Informatics (CRI) in the year of 2015 and discuss near-term trends impacting CRI. METHODS We selected key publications that highlight not only important recent advances in CRI but also notable events likely to have significant impact on CRI activities over the next few years or longer, and consulted the discussions in relevant scientific communities and an online living textbook for modern clinical trials. We also related the new concepts with old problems to improve the continuity of CRI research. RESULTS The highlights in CRI in 2015 include the growing adoption of electronic health records (EHR), the rapid development of regional, national, and global clinical data research networks for using EHR data to integrate scalable clinical research with clinical care and generate robust medical evidence. Data quality, integration, and fusion, data access by researchers, study transparency, results reproducibility, and infrastructure sustainability are persistent challenges. CONCLUSION The advances in Big Data Analytics and Internet technologies together with the engagement of citizens in sciences are shaping the global clinical research enterprise, which is getting more open and increasingly stakeholder-centered, where stakeholders include patients, clinicians, researchers, and sponsors.
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Affiliation(s)
- C Weng
- Chunhua Weng, PhD, FACMI, Department of Biomedical Informatics, Columbia University, 622 W 168 Street, PH-20, New York, NY 10032, USA, E-mail:
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Hu L, Li X, Liu Q, Xu J, Ge H, Wang Z, Wang H, Wang Z, Shi C, Xu X, Huang J, Lin Z, Pieper RO, Weng C. UBE2S, a novel substrate of Akt1, associates with Ku70 and regulates DNA repair and glioblastoma multiforme resistance to chemotherapy. Oncogene 2016; 36:1145-1156. [PMID: 27593939 DOI: 10.1038/onc.2016.281] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Revised: 06/17/2016] [Accepted: 06/28/2016] [Indexed: 12/31/2022]
Abstract
Glioblastoma multiforme (GBM) is the most common primary malignant brain cancer in adults. However, the molecular events underlying carcinogenesis and their interplay remain elusive. Here, we report that the stability of Ubiquitin-conjugating enzyme E2S (UBE2S) is regulated by the PTEN/Akt pathway and that its degradation depends on the ubiquitin-proteasome system. Mechanistically, Akt1 physically interacted with and phosphorylated UBE2S at Thr 152, enhancing its stability by inhibiting proteasomal degradation. Additionally, accumulated UBE2S was found to be associated with the components of the non-homologous end-joining (NHEJ) complex and participated in the NHEJ-mediated DNA repair process. The association of Ku70 with UBE2S was enhanced, and the complex was recruited to double-stranded break (DSB) sites in response to etoposide treatment. Furthermore, knockdown of UBE2S expression inhibited NHEJ-mediated DSB repair and rendered glioblastoma cells more sensitive to chemotherapy. Overall, our findings provide a novel drug target that may serve as the rationale for the development of a new therapeutic approach.
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Affiliation(s)
- L Hu
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.,State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute of Chinese Academy of Agricultural Sciences, Harbin, China
| | - X Li
- Department of Neurosurgery, Liaocheng People's Hospital of Shandong University, Liaocheng, China
| | - Q Liu
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute of Chinese Academy of Agricultural Sciences, Harbin, China
| | - J Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - H Ge
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Z Wang
- Department of Epidemiology and Biostatistics, Harbin Medical University, Harbin, China
| | - H Wang
- Department of Pathology, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Z Wang
- Saint-Antoine Research Centre, University Pierre and Marie CURIE, Paris, France
| | - C Shi
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - X Xu
- Beijing Key Laboratory of DNA Damage Response and College of Life Sciences, Capital Normal University, Beijing, China
| | - J Huang
- Department of Neurosurgery, University of Florida, Gainesville, USA
| | - Z Lin
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - R O Pieper
- Department of Neurological Surgery, University of California, San Francisco, USA
| | - C Weng
- State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute of Chinese Academy of Agricultural Sciences, Harbin, China
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Zhang Q, Weng C, Huang H, Achal V, Wang D. Optimization of Bioethanol Production Using Whole Plant of Water Hyacinth as Substrate in Simultaneous Saccharification and Fermentation Process. Front Microbiol 2016; 6:1411. [PMID: 26779125 PMCID: PMC4703791 DOI: 10.3389/fmicb.2015.01411] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2015] [Accepted: 11/27/2015] [Indexed: 11/13/2022] Open
Abstract
Water hyacinth was used as substrate for bioethanol production in the present study. Combination of acid pretreatment and enzymatic hydrolysis was the most effective process for sugar production that resulted in the production of 402.93 mg reducing sugar at optimal condition. A regression model was built to optimize the fermentation factors according to response surface method in saccharification and fermentation (SSF) process. The optimized condition for ethanol production by SSF process was fermented at 38.87°C in 81.87 h when inoculated with 6.11 ml yeast, where 1.291 g/L bioethanol was produced. Meanwhile, 1.289 g/L ethanol was produced during experimentation, which showed reliability of presented regression model in this research. The optimization method discussed in the present study leading to relatively high bioethanol production could provide a promising way for Alien Invasive Species with high cellulose content.
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Affiliation(s)
- Qiuzhuo Zhang
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University Shanghai, China
| | - Chen Weng
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University Shanghai, China
| | - Huiqin Huang
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University Shanghai, China
| | - Varenyam Achal
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University Shanghai, China
| | - Duanchao Wang
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University Shanghai, China
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Abstract
Excessive renal sympathetic nerve activation may be one of the mechanisms underlying obesity-related hypertension. Impaired baroreflex sensitivity, adipokine disorders-such as leptin, adiponectin, and resistin-activation of the renin-angiotensin system, hyperinsulinemia, insulin resistance, and renal sodium retention present in obesity increase renal sympathetic nerve activity, thus contributing to the development of hypertension. Renal sympathetic denervation reduces both renal sympathetic activity and blood pressure in patients with obesity-related hypertension.
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Affiliation(s)
- W Chen
- Department of Cardiology, The Third Xiangya Hospital, Central South University, 410013, Changsha, China
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Weng C, Chen J, Sun L, Zhou ZW, Feng X, Sun JH, Lu LP, Yu P, Qi M. A de novo mosaic mutation of PHEX in a boy with hypophosphatemic rickets. J Hum Genet 2015; 61:223-7. [PMID: 26559751 DOI: 10.1038/jhg.2015.133] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2015] [Revised: 09/13/2015] [Accepted: 10/09/2015] [Indexed: 01/11/2023]
Abstract
X-linked dominant hypophosphatemic rickets (XLHR), is characterized mainly by renal phosphate wasting with hypophosphatemia, short stature and abnormal bone mineralization. PHEX, located at Xp22.1-p22.2, is the gene causing XLHR. We aim to characterize the pathogenesis of a Chinese boy who is apparently 'heterozygous' in PHEX gene. Direct sequencing showed two peaks: one was a wild-type 'G' and the other was one base substitution to 'A', though the patient was a male. TA clone assay clearly showed each sequences and the ratios. The mutation effect was predicted via bioinformatics and validated by exon-trapping assay. Real-time PCR was applied to determine the copy number of PHEX. TA clone assay showed the frequency of normal (G) to mutant allele (A) as 19:13. Normal karyotype and real-time PCR results indicate the normal copy number of PHEX. This splice site mutation leads to 4 bp of exon 18 skipping out causing frame shift p.Gly590Glufs*28 that ends up with a loss of active site and Zn(2+)-binding site of PHEX, which probably interfere with renal phosphate reabsorption and bone mineralization. In conclusion, mutation at conserved splice acceptor site resulted in aberrant splicing, ending up with a damaged protein product. This novel mutation is de novo in mosaic pattern that may be induced during early postzygotic period. Taking mosaic somatic mutation of PHEX into consideration is strongly suggested in genetic counseling and etiology research for XLHR.
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Affiliation(s)
- Chen Weng
- Department of Cell Biology and Medical Genetics, School of Medicine Zhejiang University, Hangzhou, China
| | - Jiao Chen
- Department of Cell Biology and Medical Genetics, School of Medicine Zhejiang University, Hangzhou, China
| | - Li Sun
- Department of Nephrology and Rheumatology, Children's Hospital of Fudan University, Shanghai, China
| | - Zhong-Wei Zhou
- Department of Cell Biology and Medical Genetics, School of Medicine Zhejiang University, Hangzhou, China
| | - Xue Feng
- Department of Cell Biology and Medical Genetics, School of Medicine Zhejiang University, Hangzhou, China
| | - Jun-Hui Sun
- Department of Cell Biology and Medical Genetics, School of Medicine Zhejiang University, Hangzhou, China
| | - Ling-Ping Lu
- Department of Cell Biology and Medical Genetics, School of Medicine Zhejiang University, Hangzhou, China
| | - Ping Yu
- Department of Cell Biology and Medical Genetics, School of Medicine Zhejiang University, Hangzhou, China
| | - Ming Qi
- Department of Cell Biology and Medical Genetics, School of Medicine Zhejiang University, Hangzhou, China.,Center for Genetic and Genomic Medicine, Zhejiang University Medical School First Affiliated Hospital, Hangzhou, China.,Department of Pathology and Laboratory Medicine, University of Rochester, Rochester, NY, USA
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Weng C, Fu Y, Jiang H, Zhuang S, Li H. Binding interaction between a queen pheromone component HOB and pheromone binding protein ASP1 of Apis cerana. Int J Biol Macromol 2015; 72:430-6. [DOI: 10.1016/j.ijbiomac.2014.08.046] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2014] [Revised: 08/22/2014] [Accepted: 08/25/2014] [Indexed: 11/30/2022]
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45
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Yang L, Yang J, Zhang T, Weng C, Hong F, Tong F, Yang R, Yin X, Yu P, Huang X, Qi M. Identification of eight novel mutations and transcript analysis of two splicing mutations in Chinese newborns with MCC deficiency. Clin Genet 2014; 88:484-8. [PMID: 25382614 DOI: 10.1111/cge.12535] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2014] [Revised: 11/04/2014] [Accepted: 11/04/2014] [Indexed: 11/26/2022]
Affiliation(s)
- L. Yang
- Department of Genetics and Metabolism; Children's Hospital; School of Medicine Zhejiang University; Hangzhou China
- Department of Cell Biology and Medical Genetics; School of Medicine Zhejiang University; Hangzhou China
| | - J. Yang
- Department of Genetics and Metabolism; Children's Hospital; School of Medicine Zhejiang University; Hangzhou China
| | - T. Zhang
- Department of Genetics and Metabolism; Children's Hospital; School of Medicine Zhejiang University; Hangzhou China
| | - C. Weng
- Department of Cell Biology and Medical Genetics; School of Medicine Zhejiang University; Hangzhou China
| | - F. Hong
- Department of Genetics and Metabolism; Children's Hospital; School of Medicine Zhejiang University; Hangzhou China
| | - F. Tong
- Department of Genetics and Metabolism; Children's Hospital; School of Medicine Zhejiang University; Hangzhou China
| | - R. Yang
- Department of Genetics and Metabolism; Children's Hospital; School of Medicine Zhejiang University; Hangzhou China
| | - X. Yin
- Department of Medicine; School of Medicine Hangzhou Normal University; Hangzhou China
| | - P. Yu
- Department of Cell Biology and Medical Genetics; School of Medicine Zhejiang University; Hangzhou China
| | - X. Huang
- Department of Genetics and Metabolism; Children's Hospital; School of Medicine Zhejiang University; Hangzhou China
| | - M. Qi
- Department of Cell Biology and Medical Genetics; School of Medicine Zhejiang University; Hangzhou China
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Abstract
OBJECTIVES To develop an adaptive approach to mine frequent semantic tags (FSTs) from heterogeneous clinical research texts. METHODS We develop a "plug-n-play" framework that integrates replaceable unsupervised kernel algorithms with formatting, functional, and utility wrappers for FST mining. Temporal information identification and semantic equivalence detection were two example functional wrappers. We first compared this approach's recall and efficiency for mining FSTs from ClinicalTrials.gov to that of a recently published tag-mining algorithm. Then we assessed this approach's adaptability to two other types of clinical research texts: clinical data requests and clinical trial protocols, by comparing the prevalence trends of FSTs across three texts. RESULTS Our approach increased the average recall and speed by 12.8% and 47.02% respectively upon the baseline when mining FSTs from ClinicalTrials.gov, and maintained an overlap in relevant FSTs with the base- line ranging between 76.9% and 100% for varying FST frequency thresholds. The FSTs saturated when the data size reached 200 documents. Consistent trends in the prevalence of FST were observed across the three texts as the data size or frequency threshold changed. CONCLUSIONS This paper contributes an adaptive tag-mining framework that is scalable and adaptable without sacrificing its recall. This component-based architectural design can be potentially generalizable to improve the adaptability of other clinical text mining methods.
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Affiliation(s)
| | - C Weng
- Chunhua Weng, Ph.D., Associate Professor, Department of Biomedical Informatics, Columbia University, 622 W 168 Street, PH-20, New York, NY, 10032, USA, E-mail:
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Weng C, Li Y, Ryan P, Zhang Y, Liu F, Gao J, Bigger JT, Hripcsak G. A distribution-based method for assessing the differences between clinical trial target populations and patient populations in electronic health records. Appl Clin Inform 2014; 5:463-79. [PMID: 25024761 DOI: 10.4338/aci-2013-12-ra-0105] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Accepted: 04/09/2014] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVE To improve the transparency of clinical trial generalizability and to illustrate the method using Type 2 diabetes as an example. METHODS Our data included 1,761 diabetes clinical trials and the electronic health records (EHR) of 26,120 patients with Type 2 diabetes who visited Columbia University Medical Center of New-York Presbyterian Hospital. The two populations were compared using the Generalizability Index for Study Traits (GIST) on the earliest diagnosis age and the mean hemoglobin A1c (HbA1c) values. RESULTS Greater than 70% of Type 2 diabetes studies allow patients with HbA1c measures between 7 and 10.5, but less than 40% of studies allow HbA1c<7 and fewer than 45% of studies allow HbA1c>10.5. In the real-world population, only 38% of patients had HbA1c between 7 and 10.5, with 12% having values above the range and 52% having HbA1c<7. The GIST for HbA1c was 0.51. Most studies adopted broad age value ranges, with the most common restrictions excluding patients >80 or <18 years. Most of the real-world population fell within this range, but 2% of patients were <18 at time of first diagnosis and 8% were >80. The GIST for age was 0.75. CONCLUSIONS We contribute a scalable method to profile and compare aggregated clinical trial target populations with EHR patient populations. We demonstrate that Type 2 diabetes studies are more generalizable with regard to age than they are with regard to HbA1c. We found that the generalizability of age increased from Phase 1 to Phase 3 while the generalizability of HbA1c decreased during those same phases. This method can generalize to other medical conditions and other continuous or binary variables. We envision the potential use of EHR data for examining the generalizability of clinical trials and for defining population-representative clinical trial eligibility criteria.
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Affiliation(s)
- C Weng
- Department of Biomedical Informatics, Columbia University , New York, NY 10032
| | - Y Li
- Department of Computer Science, City College of New York , New York, NY 10031
| | - P Ryan
- Janssen Research and Development , Titusville, New Jersey, 08560 ; Observational Health Data Sciences and Informatics , New York, NY, 10032
| | - Y Zhang
- Department of Biostatistics, Columbia University , New York, NY 10032
| | - F Liu
- Department of Biomedical Informatics, Columbia University , New York, NY 10032
| | - J Gao
- Business School, Columbia University , New York, NY 10025
| | - J T Bigger
- Department of Medicine, Columbia University , New York, NY 10032
| | - G Hripcsak
- Department of Biomedical Informatics, Columbia University , New York, NY 10032
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48
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Abstract
Abstract
Microchannel deformation is a problem which often occurs in the thermal bonding of polymer microfluidic chip, and which is significantly determined by bonding parameters. In this paper, numerical analysis of the microchannel deformation in the process of in-mold bonding polymer chip was conducted, using Young's modulus and shear relaxation modulus of polymethylmethacrylate (PMMA) obtained in creep tests. Adhesion between the top and two lateral walls of microchannel was observed in the results, which can be attributed mainly to the viscoelastic deformation of PMMA. It was also revealed that the maximum percent deformation of microchannel is in height, and that bonding temperature had greater effect on the deformation of microchannel than bonding pressure and bonding time. The deformation of microchannel in simulation were consistent with those of experiment under the optimized parameters of 105 °C, 2 MPa and 240 s.
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Affiliation(s)
- C.-P. Chu
- State Key Laboratory of High Performance Complex Manufacturing , College of Mechanical and Electrical Engineering, Central South University, Changsha , PRC
| | - B.-Y. Jiang
- State Key Laboratory of High Performance Complex Manufacturing , College of Mechanical and Electrical Engineering, Central South University, Changsha , PRC
| | - C. Weng
- State Key Laboratory of High Performance Complex Manufacturing , College of Mechanical and Electrical Engineering, Central South University, Changsha , PRC
| | - F.-Z. Jiang
- State Key Laboratory of High Performance Complex Manufacturing , College of Mechanical and Electrical Engineering, Central South University, Changsha , PRC
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49
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Molina K, Weng C, Everitt M. Predictors of Late Renal Dysfunction after Pediatric Heart Transplantation: A UNOS Database Analysis. J Heart Lung Transplant 2014. [DOI: 10.1016/j.healun.2014.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022] Open
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50
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Boland MR, Miotto R, Gao J, Weng C. Feasibility of feature-based indexing, clustering, and search of clinical trials. A case study of breast cancer trials from ClinicalTrials.gov. Methods Inf Med 2013; 52:382-94. [PMID: 23666475 PMCID: PMC3796134 DOI: 10.3414/me12-01-0092] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2012] [Accepted: 02/21/2013] [Indexed: 11/09/2022]
Abstract
BACKGROUND When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space. OBJECTIVES This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes. METHODS We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively. RESULTS We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction. CONCLUSIONS It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency.
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Affiliation(s)
- M R Boland
- Chunhua Weng, PhD, Florence Irving Assistant Professor, Department of Biomedical Informatics, Columbia University, 622 W 168th Street, VC-5 New York, NY 10032 USA, E-mail:
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