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Lee SM, Loo CE, Prasasya RD, Bartolomei MS, Kohli RM, Zhou W. Low-input and single-cell methods for Infinium DNA methylation BeadChips. Nucleic Acids Res 2024; 52:e38. [PMID: 38407446 DOI: 10.1093/nar/gkae127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 01/29/2024] [Accepted: 02/10/2024] [Indexed: 02/27/2024] Open
Abstract
The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and ∼25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signal's influence on the DNA methylation level readings. The modified detection P-value calculation achieved higher sensitivities for low-input datasets and was validated in over 100 000 public diverse methylome profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.
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Affiliation(s)
- Sol Moe Lee
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA 19104, USA
| | - Christian E Loo
- Graduate Group in Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rexxi D Prasasya
- Department of Cell and Developmental Biology, Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Marisa S Bartolomei
- Department of Cell and Developmental Biology, Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Rahul M Kohli
- Department of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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Zhou W, Johnson BK, Morrison J, Beddows I, Eapen J, Katsman E, Semwal A, Habib W, Heo L, Laird P, Berman B, Triche T, Shen H. BISCUIT: an efficient, standards-compliant tool suite for simultaneous genetic and epigenetic inference in bulk and single-cell studies. Nucleic Acids Res 2024; 52:e32. [PMID: 38412294 PMCID: PMC11014253 DOI: 10.1093/nar/gkae097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 01/23/2024] [Accepted: 02/08/2024] [Indexed: 02/29/2024] Open
Abstract
Data from both bulk and single-cell whole-genome DNA methylation experiments are under-utilized in many ways. This is attributable to inefficient mapping of methylation sequencing reads, routinely discarded genetic information, and neglected read-level epigenetic and genetic linkage information. We introduce the BISulfite-seq Command line User Interface Toolkit (BISCUIT) and its companion R/Bioconductor package, biscuiteer, for simultaneous extraction of genetic and epigenetic information from bulk and single-cell DNA methylation sequencing. BISCUIT's performance, flexibility and standards-compliant output allow large, complex experimental designs to be characterized on clinical timescales. BISCUIT is particularly suited for processing data from single-cell DNA methylation assays, with its excellent scalability, efficiency, and ability to greatly enhance mappability, a key challenge for single-cell studies. We also introduce the epiBED format for single-molecule analysis of coupled epigenetic and genetic information, facilitating the study of cellular and tissue heterogeneity from DNA methylation sequencing.
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Affiliation(s)
- Wanding Zhou
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Benjamin K Johnson
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Jacob Morrison
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Ian Beddows
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - James Eapen
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Efrat Katsman
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 9112102, Israel
| | - Ayush Semwal
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Walid Abi Habib
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Lyong Heo
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Peter W Laird
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Benjamin P Berman
- Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 9112102, Israel
| | - Timothy J Triche
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Hui Shen
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
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Yehya N, Booth TJ, Ardhanari GD, Thompson JM, Lam LKM, Till JE, Mai MV, Keim G, McKeone DJ, Halstead ES, Lahni P, Varisco BM, Zhou W, Carpenter EL, Christie JD, Mangalmurti NS. Inflammatory and tissue injury marker dynamics in pediatric acute respiratory distress syndrome. J Clin Invest 2024:e177896. [PMID: 38573766 DOI: 10.1172/jci177896] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND The molecular signature of pediatric acute respiratory distress syndrome (ARDS) is poorly described, and the degree to which hyperinflammation or specific tissue injury contributes to outcomes is unknown. Therefore, we profiled inflammation and tissue injury dynamics over the first 7 days of ARDS, and associated specific biomarkers with mortality, persistent ARDS, and persistent multiple organ dysfunction syndrome (MODS). METHODS In a single-center prospective cohort of intubated pediatric ARDS, we collected plasma on days 0, 3, and 7. Nineteen biomarkers reflecting inflammation, tissue injury, and damage associated molecular patterns were measured. We assessed the relationship between biomarkers and trajectories with mortality, persistent ARDS, or persistent MODS using multivariable mixed effect models. RESULTS In 279 subjects (64 [23%] non-survivors), hyperinflammatory cytokines, tissue injury markers, and DAMPs were higher in non-survivors. Survivors and non-survivors showed different biomarker trajectories. IL-1α, sTNFR1, ANG2, and SPD increased in non-survivors, while DAMPs remained persistently elevated. ANG2 and P3NP were associated with persistent ARDS, whereas multiple cytokines, tissue injury markers, and DAMPs were associated with persistent MODS. Corticosteroid use did not impact the association of biomarker levels or trajectory with mortality. CONCLUSIONS Pediatric ARDS survivors and non-survivors had distinct biomarker trajectories, with cytokines, endothelial and alveolar epithelial injury, and DAMPs elevated in non-survivors. Mortality markers overlapped with markers associated with persistent MODS, rather than persistent ARDS.
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Affiliation(s)
- Nadir Yehya
- Division of Pediatric Critical Care, Department of Anesthesiology and Criti, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, United States of America
| | - Thomas J Booth
- Division of Pediatric Critical Care, Department of Anesthesiology and Criti, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, United States of America
| | - Gnana D Ardhanari
- Division of Pediatric Cardiac Critical Care Medicine, Children's Heart Inst, Memorial Hermann Hospital, University of Texas Health McGovern Medical School, Houston, United States of America
| | - Jill M Thompson
- Division of Pediatric Critical Care, Department of Anesthesiology and Criti, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, United States of America
| | - L K Metthew Lam
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States of America
| | - Jacob E Till
- Division of Hematology-Oncology, Department of Medicine, Abramson Cancer Ce, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States of America
| | - Mark V Mai
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, Children's Healthcare of Atlanta and Emory University, Atlanta, United States of America
| | - Garrett Keim
- Division of Pediatric Critical Care, Department of Anesthesiology and Criti, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, United States of America
| | - Daniel J McKeone
- Division of Pediatric Hematology and Oncology, Department of Pediatrics, Pennsylvania State University College of Medicine, Hershey, United States of America
| | - E Scott Halstead
- Division of Pediatric Critical Care Medicine, Department of Pediatrics, Pennsylvania State University College of Medicine, Hershey, United States of America
| | - Patrick Lahni
- Division of Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, United States of America
| | - Brian M Varisco
- Section of Critical Care, Department of Pediatrics, University of Arkansas for Medical Sciences and Arkansas Children's Research Institute, Little Rock, United States of America
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, United States of America
| | - Erica L Carpenter
- Division of Hematology-Oncology, Department of Medicine, Abramson Cancer Ce, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States of America
| | - Jason D Christie
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States of America
| | - Nilam S Mangalmurti
- Division of Pulmonary, Allergy, and Critical Care, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States of America
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Liu W, Zhou W, Zhang Y, Ge X, Qi W, Lin T, Cao Q, Cao L. Strictureplasty may lead to increased preference in the surgical management of Crohn's disease: a case-matched study. Tech Coloproctol 2024; 28:40. [PMID: 38507096 DOI: 10.1007/s10151-024-02915-5] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 03/05/2024] [Indexed: 03/22/2024]
Abstract
BACKGROUND Resection and strictureplasty are the two surgical modalities used in the management of Crohn's disease (CD). The objective of this study was to compare morbidity and clinical recurrence between patients who underwent strictureplasty and patients who underwent resection. METHODS Patients with CD who underwent strictureplasty between January 2012 and December 2022 were enrolled. The patients were well matched with patients who underwent resection without strictureplasty. Patient- and disease-specific characteristics, postoperative morbidity, and clinical recurrence were also analyzed. RESULTS A total of 118 patients who underwent a total of 192 strictureplasties were well matched to 118 patients who underwent resection. The strictureplasty group exhibited significantly less blood loss (30 ml versus 50 ml, p < 0.001) and stoma creation (2.5% versus 16.9%, p < 0.001). No significant difference was found regarding postoperative complications or length of postoperative stay. At the end of the follow-up, the overall rate of clinical recurrence was 39.4%, and no difference was observed between the two groups. Postoperative prophylactic use of biologics (odds ratio = 0.2, p < 0.001) was the only protective factor against recurrence. CONCLUSION Strictureplasty does not increase the risk of complications or recurrence compared with resection. It represents a viable alternative to resection in selected patients, and as such, it should have a broader scope of indications and greater acceptance among surgeons.
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Affiliation(s)
- W Liu
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - W Zhou
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China.
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China.
| | - Y Zhang
- School of Medicine, Shantou University, Shantou, 515063, Guangdong Province, China
| | - X Ge
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - W Qi
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - T Lin
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China
| | - Q Cao
- Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, People's Republic of China
| | - L Cao
- Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, People's Republic of China.
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Zhao X, Zhang Q, Tao S, Zhou W, Jia PY. Corrigendum to "Association of edentulism and all-cause mortality in Chinese older adults: do sex differences exist?" [Public Health 221 (2023) 184-189]. Public Health 2024; 228:206. [PMID: 38402114 DOI: 10.1016/j.puhe.2023.11.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/26/2024]
Affiliation(s)
- X Zhao
- School of Health Humanities, Peking University, Beijing, China
| | - Q Zhang
- National School of Development, Peking University, Beijing, China
| | - S Tao
- School of Health Humanities, Peking University, Beijing, China
| | - W Zhou
- Research Center for Public Health and Social Security, School of Public Administration, Hunan University, Hunan, China
| | - P-Y Jia
- Department of the Fourth Clinical Division, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical, Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry, Ministry of Health & NMPA Key Laboratory for Dental Materials, Beijing, China.
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6
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Ahsan MU, Gouru A, Chan J, Zhou W, Wang K. A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing. Nat Commun 2024; 15:1448. [PMID: 38365920 PMCID: PMC10873387 DOI: 10.1038/s41467-024-45778-y] [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: 05/25/2023] [Accepted: 02/04/2024] [Indexed: 02/18/2024] Open
Abstract
Oxford Nanopore sequencing can detect DNA methylations from ionic current signal of single molecules, offering a unique advantage over conventional methods. Additionally, adaptive sampling, a software-controlled enrichment method for targeted sequencing, allows reduced representation methylation sequencing that can be applied to CpG islands or imprinted regions. Here we present DeepMod2, a comprehensive deep-learning framework for methylation detection using ionic current signal from Nanopore sequencing. DeepMod2 implements both a bidirectional long short-term memory (BiLSTM) model and a Transformer model and can analyze POD5 and FAST5 signal files generated on R9 and R10 flowcells. Additionally, DeepMod2 can run efficiently on central processing unit (CPU) through model pruning and can infer epihaplotypes or haplotype-specific methylation calls from phased reads. We use multiple publicly available and newly generated datasets to evaluate the performance of DeepMod2 under varying scenarios. DeepMod2 has comparable performance to Guppy and Dorado, which are the current state-of-the-art methods from Oxford Nanopore Technologies that remain closed-source. Moreover, we show a high correlation (r = 0.96) between reduced representation and whole-genome Nanopore sequencing. In summary, DeepMod2 is an open-source tool that enables fast and accurate DNA methylation detection from whole-genome or adaptive sequencing data on a diverse range of flowcell types.
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Affiliation(s)
- Mian Umair Ahsan
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Anagha Gouru
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Joe Chan
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Kai Wang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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Tiedemann RL, Hrit J, Du Q, Wiseman AK, Eden HE, Dickson BM, Kong X, Chomiak AA, Vaughan RM, Hebert JM, David Y, Zhou W, Baylin SB, Jones PA, Clark SJ, Rothbart SB. UHRF1 ubiquitin ligase activity supports the maintenance of low-density CpG methylation. bioRxiv 2024:2024.02.13.580169. [PMID: 38405904 PMCID: PMC10888769 DOI: 10.1101/2024.02.13.580169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
The RING E3 ubiquitin ligase UHRF1 is an established cofactor for DNA methylation inheritance. Nucleosomal engagement through histone and DNA interactions directs UHRF1 ubiquitin ligase activity toward lysines on histone H3 tails, creating binding sites for DNMT1 through ubiquitin interacting motifs (UIM1 and UIM2). Here, we profile contributions of UHRF1 and DNMT1 to genome-wide DNA methylation inheritance and dissect specific roles for ubiquitin signaling in this process. We reveal DNA methylation maintenance at low-density CpGs is vulnerable to disruption of UHRF1 ubiquitin ligase activity and DNMT1 ubiquitin reading activity through UIM1. Hypomethylation of low-density CpGs in this manner induces formation of partially methylated domains (PMD), a methylation signature observed across human cancers. Furthermore, disrupting DNMT1 UIM2 function abolishes DNA methylation maintenance. Collectively, we show DNMT1-dependent DNA methylation inheritance is a ubiquitin-regulated process and suggest a disrupted UHRF1-DNMT1 ubiquitin signaling axis contributes to the development of PMDs in human cancers.
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Al-Aroomi MA, Mashrah MA, Al-Worafi NA, Zhou W, Sun C, Pan C. Biomechanical and aesthetic outcomes following radial forearm free flap transfer: comparison of ipsilateral full-thickness skin graft and traditional split-thickness skin graft. Int J Oral Maxillofac Surg 2024; 53:109-116. [PMID: 37244863 DOI: 10.1016/j.ijom.2023.04.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 04/21/2023] [Accepted: 04/26/2023] [Indexed: 05/29/2023]
Abstract
The radial forearm free flap (RFFF) is associated with donor site morbidity. This study aimed to quantify the functional and aesthetic outcomes after closure of the RFFF donor site using triangular full-thickness skin grafts (FTSGs) harvested adjacent to the flap or traditional split-thickness skin grafts (STSGs). The study included patients who underwent oral cavity reconstruction with an RFFF between March 2017 and August 2021. The patients were divided into two groups based on the donor site closure method: FTSG or STSG. The primary outcomes were biomechanical grip strength, pinch strength, and range of wrist movements. Subjective donor site morbidity, aesthetic and functional results were also analysed. The study included 75 patients (FTSG n = 35; STSG n = 40). Postoperatively, there was a statistically significant difference in grip strength (P = 0.049) and wrist extension (P = 0.047) between the FTSG and STSG groups, in favour of the STSG. Differences between the groups in pinch strength and other wrist motions were not statistically significant. The harvesting time was significantly shorter for the FTSG (P = 0.041) and the appearance of the donor site was better (P = 0.026) when compared to the STSG. Cold intolerance was more frequent in the STSG group (32.5% STSG vs 6.7% FTSG; P = 0.017). Subjective function, numbness, pain, hypertrophic scar, itching, and social stigma did not differ significantly between the groups. Compared with the STSG, the FTSG showed better cosmesis and avoided additional donor sites, with clinically negligible differences in hand biomechanics.
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Affiliation(s)
- M A Al-Aroomi
- Department of Oral and Maxillofacial-Head and Neck Surgery, School of Stomatology, Oral Diseases Laboratory of Liaoning, China Medical University, Shenyang, Liaoning, China.
| | - M A Mashrah
- Department of Implantology, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangdong Engineering Research Center of Oral Restoration and Reconstruction, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, Guangdong, China
| | - N A Al-Worafi
- Department of Orthodontics, School of Stomatology, China Medical University, Shenyang, Liaoning, China
| | - W Zhou
- Department of Oral and Maxillofacial-Head and Neck Surgery, School of Stomatology, Oral Diseases Laboratory of Liaoning, China Medical University, Shenyang, Liaoning, China
| | - C Sun
- Department of Oral and Maxillofacial-Head and Neck Surgery, School of Stomatology, Oral Diseases Laboratory of Liaoning, China Medical University, Shenyang, Liaoning, China.
| | - C Pan
- Department of Oral and Maxillofacial Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou City, China
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Zhou W, Li X. Fish diversity and selection of taxa for conservation in the Salween and Irrawaddy Rivers, Southeast Asia. Sci Rep 2024; 14:2393. [PMID: 38287045 PMCID: PMC10825156 DOI: 10.1038/s41598-024-51205-5] [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: 08/19/2023] [Accepted: 01/02/2024] [Indexed: 01/31/2024] Open
Abstract
Species diversity indices provide quantitative data for understanding the variations and trends in fish species diversity, as well as information on species richness and evenness. However, these diversity indices do not reflect differences in specific taxa, which can be of importance as key conservation targets, especially during the planning and construction of protected areas. In this study, simultaneously combining our improved traditional fish fauna analysis (TFFA) with the value of fish fauna presence (VFFP) methods, we studied fish diversity in the Salween and Irrawaddy basins. The results of the TFFA reflected the families (subfamilies) and genera that constitute the main body of fish diversity in the river basins. The results of the VFFP assessment showed which families (subfamilies) and genera were representative of certain characteristics in the basins. The VFFP scores of genera could be used as indicator indices and as priority taxa in the planning and construction of fish resource reserves. In this paper, we propose for the first time that the role and status of monotypic genera (genera comprising only a single species) in the conservation of fish diversity should not be ignored, and they should rather be a priority for protection.
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Affiliation(s)
- W Zhou
- Key Laboratory for Conserving Wildlife with Small Populations in Yunnan, Southwest Forestry University, 300 Bailongsi Road, Kunming, 650224, Yunnan, China.
| | - X Li
- Key Laboratory for Conserving Wildlife with Small Populations in Yunnan, Southwest Forestry University, 300 Bailongsi Road, Kunming, 650224, Yunnan, China
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Carreras-Gallo N, Dwaraka VB, Jima DD, Skaar DA, Mendez TL, Planchart A, Zhou W, Jirtle RL, Smith R, Hoyo C. Creation and Validation of the First Infinium DNA Methylation Array for the Human Imprintome. bioRxiv 2024:2024.01.15.575646. [PMID: 38293193 PMCID: PMC10827131 DOI: 10.1101/2024.01.15.575646] [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] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Background Differentially methylated imprint control regions (ICRs) regulate the monoallelic expression of imprinted genes. Their epigenetic dysregulation by environmental exposures throughout life results in the formation of common chronic diseases. Unfortunately, existing Infinium methylation arrays lack the ability to profile these regions adequately. Whole genome bisulfite sequencing (WGBS) is the unique method able to profile these regions, but it is very expensive and it requires not only a high coverage but it is also computationally intensive to assess those regions. Findings To address this deficiency, we developed a custom methylation array containing 22,819 probes. Among them, 9,757 probes map to 1,088 out of the 1,488 candidate ICRs recently described. To assess the performance of the array, we created matched samples processed with the Human Imprintome array and WGBS, which is the current standard method for assessing the methylation of the Human Imprintome. We compared the methylation levels from the shared CpG sites and obtained a mean R 2 = 0.569. We also created matched samples processed with the Human Imprintome array and the Infinium Methylation EPIC v2 array and obtained a mean R 2 = 0.796. Furthermore, replication experiments demonstrated high reliability (ICC: 0.799-0.945). Conclusions Our custom array will be useful for replicable and accurate assessment, mechanistic insight, and targeted investigation of ICRs. This tool should accelerate the discovery of ICRs associated with a wide range of diseases and exposures, and advance our understanding of genomic imprinting and its relevance in development and disease formation throughout the life course.
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Du J, Chen X, Wang Y, Yang Z, Wu D, Zhang Q, Liu Y, Zhu X, Jiang S, Cao Y, Chen C, Du L, Zhou W, Lee SK, Xia H, Hei M. Regional variations in retinopathy of prematurity incidence for preterm infants <32 weeks' gestation in China. Public Health 2024; 226:91-98. [PMID: 38029699 DOI: 10.1016/j.puhe.2023.10.033] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 09/30/2023] [Accepted: 10/13/2023] [Indexed: 12/01/2023]
Abstract
OBJECTIVES National-level data on the incidence of retinopathy of prematurity (ROP) in different regions of China is insufficient. This study aimed to compare ROP incidences and care practices in different regions of China and their relationship with regional gross domestic product (GDP) per capita. STUDY DESIGN Retrospective cohort study. METHODS All infants born at <32 weeks gestational age (GA) and admitted to 70 neonatal intensive care units (NICUs) from January 1, 2019, to December 31, 2020, were enrolled. Hospitals were categorised into three regional groups according to geographical locations and GDP per capita from high to low: Eastern, Central, and Western China. The incidence of death or ROP, and care practices were compared among the groups. RESULTS A total of 18,579 infants were enrolled. Median GA was 29.9 (interquartile range 28.4-31.0) weeks and birth weight was 1318.1 (317.2) g. The percentage of GA <28 weeks, complete administration of antenatal steroids, and weight gain velocity during NICU stay were highest in Eastern China and lowest in Western China (all P < 0.01). In Eastern, Central, and Western China, the rates of death or any stage of ROP were 33.3%, 38.5%, and 39.2%, respectively (P < 0.01). CONCLUSIONS There were considerable regional disparities in ROP incidence in preterm infants with GA <32 weeks in China. The incidence of death or ROP ranged from high to low in Western, Central, and Eastern China.
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Affiliation(s)
- J Du
- Neonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, China; National Center of Children's Health, Beijing, China
| | - X Chen
- Department of Neonatology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Y Wang
- NHC Key Laboratory of Neonatal Diseases, Fudan University, Children's Hospital of Fudan University, Shanghai, China; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Z Yang
- Neonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, China; National Center of Children's Health, Beijing, China
| | - D Wu
- Neonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, China; National Center of Children's Health, Beijing, China
| | - Q Zhang
- Neonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, China; National Center of Children's Health, Beijing, China
| | - Y Liu
- Neonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, China; National Center of Children's Health, Beijing, China
| | - X Zhu
- Neonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, China; National Center of Children's Health, Beijing, China
| | - S Jiang
- NHC Key Laboratory of Neonatal Diseases, Fudan University, Children's Hospital of Fudan University, Shanghai, China; Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Y Cao
- NHC Key Laboratory of Neonatal Diseases, Fudan University, Children's Hospital of Fudan University, Shanghai, China; Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - C Chen
- NHC Key Laboratory of Neonatal Diseases, Fudan University, Children's Hospital of Fudan University, Shanghai, China; Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - L Du
- Neonatal Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China; National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou, China
| | - W Zhou
- NHC Key Laboratory of Neonatal Diseases, Fudan University, Children's Hospital of Fudan University, Shanghai, China; Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - S K Lee
- Maternal-Infant Care Research Centre and Department of Pediatrics, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - H Xia
- Department of Neonatology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - M Hei
- Neonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, China; National Center of Children's Health, Beijing, China.
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12
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Gong L, Chen K, Zhang H, Zhang S, Luo W, Zhou W, Zhang B, Xu R, Xi C. Higher Cognitive Reserve Is Beneficial for Cognitive Performance Via Various Locus Coeruleus Functional Pathways in the Pre-Dementia Stage of Alzheimer's Disease. J Prev Alzheimers Dis 2024; 11:484-494. [PMID: 38374755 DOI: 10.14283/jpad.2023.127] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
BACKGROUND Cognitive reserve (CR) shows protective effects on cognitive function in older adult and in Alzheimer's disease (AD). However, the brain mechanisms underlying the CR effect on the non-dementia AD spectrum (subjective cognitive decline (SCD) and mild cognitive impairment (MCI)) are unknown. The aim of this study was to investigate the potential moderate effect of CR on brain functional networks associated with cognitive performance. METHODS We selected 200 participants, including 48 cognitively normal (CN) and 56 SCD, and 96 patients with MCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Seed-based locus coeruleus functional connectivity (LC FC) was conducted to detect early brain functional changes in the non-dementia AD spectrum. CR was assessed via years of education and intelligence (IQ). The ANDI composite executive function scores (ADNI-EF) and ADNI composite memory scores (ANDI-MEM) at baseline and 24-month follow-up were used to assess cognitive performance. RESULTS Compared to the CN group, the SCD group showed abnormal LC FC with the executive control network (dorsolateral prefrontal cortex, DLPFC), salience network, sensorimotor network, reward network, and hippocampus, while these alterations were inverted at the MCI stage. The LC-hippocampus FC was correlated with ADNI-MEM at baseline and follow-up, and these relationships were moderated by education. The LC-DLPFC FC was correlated with ADNI-EF at baseline, and this association was moderated by IQ. CONCLUSION Our results manifested that higher levels of CR would confer protective effects on SCD and MCI. Furthermore, IQ and education could moderate the relationship between LC FC and cognition through different pathways.
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Affiliation(s)
- L Gong
- Liang Gong and Chunhua XI: Gong, Department of Neurology, Chengdu Second People's Hospital, Qingyunnan Road 10, Chengdu, Sichuan 610017, China; ; Tel: +86 17360251891; Fax: +86 28 67830800; Xi, Department of Neurology, The Third Affiliated Hospital of Anhui Medical University, Huaihe Road 390, Heifei, Anhui 230061, China,
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13
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Jiang W, Zhao Y, Wu X, Du Y, Zhou W. Health inequalities of global protein-energy malnutrition from 1990 to 2019 and forecast prevalence for 2044: data from the Global Burden of Disease Study 2019. Public Health 2023; 225:102-109. [PMID: 37924634 DOI: 10.1016/j.puhe.2023.10.003] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 09/12/2023] [Accepted: 10/02/2023] [Indexed: 11/06/2023]
Abstract
OBJECTIVES Protein-energy malnutrition poses a serious medical problem worldwide. This study aims to describe the global burden, trends, and health inequalities of protein-energy malnutrition and forecasts for future prevalence. STUDY DESIGN This was a comprehensive analysis based on data provided by the Global Burden of Disease Study 2019. METHODS Data were obtained from the Global Health Data Exchange query tool, including prevalence, deaths, disability-adjusted life years (DALYs) and sociodemographic index (SDI). The estimated annual percentage changes were calculated to evaluate temporal trends. We quantified cross-country inequalities in protein-energy malnutrition burden and predicted the prevalence number and rate to 2044. RESULTS Globally, there were 147,672,757 (130,405,923 to 167,471,359) cases of protein-energy malnutrition in 2019, with 212,242 (185,403 to 246,217) deaths. Eastern Sub-Saharan Africa had the highest age-standardised death and DALY rates in 2019. From 1990 to 2019, the global age-standardised prevalence rate of protein-energy malnutrition showed an upward trend, while the age-standardised death rate showed a downward trend. A significant decline occurred in SDI-related health inequality, from 2126.1 DALYs per 100,000 persons between the poorest and richest countries in 1990 to 357.9 DALYs per 100,000 persons in 2019. There was a trend of decreasing age-standardised death and DALY rates along with increases in the SDI. Frontier analyses showed that there is much room for improving the current situation of protein-energy malnutrition in some countries. In the next 35 years, the prevalence of protein-energy malnutrition will continue to increase. CONCLUSION Although the disease burden of protein-energy malnutrition has greatly decreased since 1990 and health inequalities between countries are shrinking, the prevalence in Asian and African countries may continue to increase. Focussing on regional differences and strengthening the nutritional intake of people in underdeveloped areas are necessary to reduce future burdens.
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Affiliation(s)
- W Jiang
- The Second Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Y Zhao
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - X Wu
- The First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Y Du
- The Second Clinical Medical College, Lanzhou University, Lanzhou, China
| | - W Zhou
- The Second Clinical Medical College, Lanzhou University, Lanzhou, China.
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14
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Tang K, Wang F, Dai SQ, Yang ZY, Duan LY, Luo ML, Tay FR, Niu LN, Zhou W, Chen JH. Enhanced Bonding to Caries-Affected Dentin Using an Isocyanate-Based Primer. J Dent Res 2023; 102:1444-1451. [PMID: 37950512 DOI: 10.1177/00220345231199416] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023] Open
Abstract
Dental caries is the most common oral disease and the most common cause of resin restorations. In minimally invasive dentistry, the principle behind cavity preparation is to remove external caries-infected dentin (CID) and preserve internal caries-affected dentin (CAD) and sound dentin (SD). The cavity floor is mainly composed of CAD, but the poor bonding performance of CAD has become a widespread concern. This study evaluated the performance of a new collagen-reactive monomer (ITCM) used as a primer to improve the bonding performance of CAD. The experimental specimens were grouped as follows: SD, CAD, and ITCM-pretreated CAD (CAD-ITCM). Dentin slices were obtained for attenuated total reflectance-Fourier transform infrared (ATR-FTIR) analysis. The bonded samples were subjected to microtensile bond strength analysis after 24 h of water storage or aging by thermocycling, and the bonding interface quality was evaluated by nanoleakage assessment, interfacial nanoindentation testing, and in situ zymography. Cytotoxicity experiments with ITCM were performed. ATR-FTIR showed that the isocyanate groups in ITCM can covalently bind and form hydrogen bonds with the collagen in CAD to mediate chemical bonding. ITCM pretreatment significantly improved the bond strength of CAD (P < 0.05), reduced interfacial nanoleakage, improved the sealing of the bonding interface, enhanced the homogeneity of the hybrid layer, and inhibited matrix metalloproteinase activity. In addition, ITCM presented acceptable biocompatibility for dental restorative application. Taken together, this study reported the application of ITCM to induce collagen-based chemical bonding in the CAD bonding system, which fills the gap in strategies to improve the bonding performance of CAD immediately and after aging and has important clinical application prospects.
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Affiliation(s)
- K Tang
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - F Wang
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - S Q Dai
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Z Y Yang
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - L Y Duan
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - M L Luo
- Institute of Stomatology & Oral Maxilla Facial Key Laboratory, The First Medical Center, Chinese PLA General Hospital & Department of Stomatology, The First Medical Center, Chinese PLA General Hospital, Xi'an, Beijing, China
| | - F R Tay
- The Dental College of Georgia, Augusta University, Augusta, GA, USA
| | - L N Niu
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - W Zhou
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - J H Chen
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, China
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15
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Ning N, Zhang Y, Liu Q, Zhou W, He Y, Liu Y, Jin L, Ma Y. American Heart Association's new 'Life's Essential 8' score in association with cardiovascular disease: a national cross-sectional analysis. Public Health 2023; 225:336-342. [PMID: 37976656 DOI: 10.1016/j.puhe.2023.10.027] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 09/19/2023] [Accepted: 10/12/2023] [Indexed: 11/19/2023]
Abstract
OBJECTIVE The American Heart Association (AHA) has recently updated and enhanced the quantification of cardiovascular health by using the Life's Essential 8 (LE8) score. We intended to examine the correlation between cardiovascular health status, as measured by the new LE8 score, and cardiovascular disease (CVD) in US adults. STUDY DESIGN National cross-sectional study. METHODS A total of 24,730 individuals without pregnancy and with complete data from 2007 to 2018 enrolled in the study. The overall LE8 score was divided into low, moderate, and high groups. Multivariate logistic regressions were used to assess the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between the LE8 score and the presence of CVD. RESULTS Overall, the high LE8 group had a younger age (20-59 years, 82.95%) and more females (60.09%) compared to the low LE8 group. Moderate and high LE8 correlated negatively with the presence of CVD (moderate, OR: 0.46, 95% CI: 0.39-0.54; high, OR: 0.26, 95% CI: 0.21-0.33). One standard deviation increment in the LE8 score correlated significantly with lower odds of CVD (OR: 0.64; 95% CI: 0.60-0.69). Further stratification analysis also detected a significant relationship between the new LE8 score and CVD, and the result was enhanced among the young and women (P-interaction<0.001). CONCLUSIONS Higher LE8 score correlated with lower odds of CVD, especially among the young and women.
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Affiliation(s)
- N Ning
- Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning Province, PR China.
| | - Y Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, No.1163 Xinmin Street, Changchun, Jilin, 130021, China.
| | - Q Liu
- Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning Province, PR China.
| | - W Zhou
- Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning Province, PR China.
| | - Y He
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, No.1163 Xinmin Street, Changchun, Jilin, 130021, China.
| | - Y Liu
- Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning Province, PR China.
| | - L Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, No.1163 Xinmin Street, Changchun, Jilin, 130021, China.
| | - Y Ma
- Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning Province, PR China.
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Morrison J, Zhou W, Johnson BK, Shen H. Dupsifter: a lightweight duplicate marking tool for whole genome bisulfite sequencing. Bioinformatics 2023; 39:btad729. [PMID: 38092060 PMCID: PMC10724848 DOI: 10.1093/bioinformatics/btad729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 11/08/2023] [Accepted: 12/12/2023] [Indexed: 12/18/2023] Open
Abstract
SUMMARY In whole genome sequencing data, polymerase chain reaction amplification results in duplicate DNA fragments coming from the same location in the genome. The process of preparing a whole genome bisulfite sequencing (WGBS) library, on the other hand, can create two DNA fragments from the same location that should not be considered duplicates. Currently, only one WGBS-aware duplicate marking tool exists. However, it only works with the output from a single tool, does not accept streaming input or output, and requires a substantial amount of memory relative to the input size. Dupsifter provides an aligner-agnostic duplicate marking tool that is lightweight, has streaming capabilities, and is memory efficient. AVAILABILITY AND IMPLEMENTATION Source code and binaries are freely available at https://github.com/huishenlab/dupsifter under the MIT license. Dupsifter is implemented in C and is supported on macOS and Linux.
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Affiliation(s)
- Jacob Morrison
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, United States
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, United States
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Benjamin K Johnson
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, United States
| | - Hui Shen
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, United States
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Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Author Correction: Universal DNA methylation age across mammalian tissues. Nat Aging 2023; 3:1462. [PMID: 37674040 PMCID: PMC10645586 DOI: 10.1038/s43587-023-00499-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Affiliation(s)
- A T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - Z Fei
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, Riverside, CA, USA
| | - A Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - T R Robeck
- Zoological SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - J A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - R Lowe
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - Q Yan
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - J Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - H Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - V A Acosta-Rodriguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - D M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - J Almunia
- Loro Parque Fundacion, Puerto de la Cruz, Spain
| | - A Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - R Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C S Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - G Banks
- School of Science and Technology, Clifton Campus, Nottingham Trent University, Nottingham, UK
| | - K Belov
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - N C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - P Black
- Busch Gardens Tampa, Tampa, FL, USA
| | - D T Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
- Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - E K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - C E Breeze
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - R T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - G G Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - A Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - J M Cavin
- Gulf World, Dolphin Company, Panama City Beach, FL, USA
| | - L Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - I Chatzistamou
- Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - H Chen
- Department of Pharmacology, Addiction Science and Toxicology, the University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - P Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - O W Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S M Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - L N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - M L Cossette
- Department of Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - J Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - J DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S DiRocco
- SeaWorld of Florida, Orlando, FL, USA
| | - C Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | | | - C K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - S Emmrich
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E Erbay
- Altos Labs, San Francisco, CA, USA
| | - C Erlacher-Reid
- SeaWorld of Florida, Orlando, FL, USA
- SeaWorld Orlando, Orlando, FL, USA
| | - C G Faulkes
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - S H Ferguson
- Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - C J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - J M Gaillard
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - E Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - L Gerber
- Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - V N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - R G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - M J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - C B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - E N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - M B Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - D W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - M Haulena
- Vancouver Aquarium, Vancouver, British Columbia, Canada
| | - K Herrick
- SeaWorld of California, San Diego, CA, USA
| | - A N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - C J Hogg
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - T A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - T Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
- Division of Genetics and Metabolism, Oishei Children's Hospital, Buffalo, NY, USA
| | | | - A J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - G Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - O Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | - H Katcher
- Yuvan Research, Mountain View, CA, USA
| | | | - V Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - H Kiaris
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M S Kobor
- Edwin S.H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - P Kordowitzki
- Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences, Olsztyn, Poland
- Institute for Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | - W R Koski
- LGL Limited, King City, Ontario, Canada
| | - M Krützen
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
| | - S B Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Larison
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Center for Tropical Research, Institute for the Environment and Sustainability, UCLA, Los Angeles, CA, USA
| | - S G Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - J F Lemaitre
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - A J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - X Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - D T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - T J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - N Macoretta
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - D Maddox
- White Oak Conservation, Yulee, FL, USA
| | - C O Matkin
- North Gulf Oceanic Society, Homer, AK, USA
| | - J A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - J Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - J J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - G A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - K Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - J Munshi-South
- Louis Calder Center-Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - A Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M Nagy
- Museum fur Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - P Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - P W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - N B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Niehrs
- Institute of Molecular Biology, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - J K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - P O'Tierney Ginn
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - D T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Division of Regulatory Genomics and Cancer Evolution, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - A G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - S Osborn
- SeaWorld of Texas, San Antonio, TX, USA
| | - E A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - K M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - K C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - M Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - K J Peters
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
| | - A B Pedersen
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - J L Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - D W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - G M Pinho
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - J R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
| | - P Reddy
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - B Rey
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - B R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - J Robbins
- Center for Coastal Studies, Provincetown, MA, USA
| | | | - J Russell
- SeaWorld of California, San Diego, CA, USA
| | - E Rydkina
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - L L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - A B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - K M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - D Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | - T Schmitt
- SeaWorld of California, San Diego, CA, USA
| | | | - L B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - K E Sears
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - A W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - A Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - A B A Shafer
- Department of Forensic Science, Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - D Shanmuganayagam
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - K Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - I Sinha
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - R G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - E Soltanmaohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | | | - L Staggs
- SeaWorld of Florida, Orlando, FL, USA
| | | | - K J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - D T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | - V J Sugrue
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - B Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - J S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Takasugi
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E C Teeling
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - M J Thompson
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Van Bonn
- John G. Shedd Aquarium, Chicago, IL, USA
| | - S C Vernes
- School of Biology, the University of St Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - D Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - H V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M C Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - N Wang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R K Wayne
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - G S Wilkinson
- Department of Biology, University of Maryland, College Park, MD, USA
| | - C K Williams
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - X W Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M Yao
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - B G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - B Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Zhang
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - P Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, USA
| | - Y Zhao
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - W Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Zimmermann
- Department of Mathematics and Technology, University of Applied Sciences Koblenz, Koblenz, Germany
| | - J Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - K Raj
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - S Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
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Bai L, Zhou W, Xie XX, Chen SM, Yan YX, Zhang XT. [Pelvic coronal inclination change in adolescent flexible flatfoot surgically treated with arthroereisis]. Zhonghua Yi Xue Za Zhi 2023; 103:2921-2925. [PMID: 37752050 DOI: 10.3760/cma.j.cn112137-20230116-00094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/28/2023]
Abstract
Objective: To evaluate adolescent pelvic coronal inclination angle change after flatfoot treated with arthroereisis. Method: A case-series study. From June 2018 to September 2020, 25 children with flexible flat foot and pelvic obliquity were included in this retrospective study in Peking University Shenzhen Hospital. There were 17 males and 8 females with a mean age of (11.2±2.2) years (9-15 years). There were 5 cases of unilateral flatfoot and 20 cases of bilateral flatfoot. All of the patients were surgically treated with arthroereisis. Regular follow-up was done in 3 months, 1 and 2 years postoperatively. Weightbearing fluoroscopy of entire lower limb and foot were investigated to measure Meary's angle, calcaneal pitch angle, height difference at ankle and pelvic plane, pelvic inclination and sacrum-iliac distance (F value) on coronal plane. Results: The mean Mearys' angle at 3 month postoperatively was improved when compared with that before the operation (3.1°±1.5° vs 25.9°±4.3°, P<0.001), and it remained at the same level 2 years after the operation (compared with that at 1 year after the operation, P=0.748). The calcaneal pitch angle improved significantly at 3-month follow-up when compared with that before the operation (16.6°±2.4° vs 9.9°±1.5°, P<0.001), and there was no significant change between 1 year and 2 years after operation (P=0.542). The height difference at mortise plane were also reduced at the 3-month follow-up(P<0.001), and it remained at the same level at 1 year and 2 years after the operation (P=0.159). Pelvic height difference decreased dramatically from (12.4±1.7) mm (before operation) to (7.1±1.2) mm(3 month after the operation) (P<0.001), it decreased to (3.6±1.8) mm 1 year after the operation (compared with that at 3 months after the operation, P<0.001), and no further reduction was observed 2 years after the surgery (P=0.483). The pelvic inclination angle and sacrum-iliac distance were also improved at 3-month follow-up when compared with those before the operation (both P<0.001), and they declined further 1 year after the operation(both P<0.05), but the decreasing trend disappeared at the 2-year follow-up (both P>0.05). Conclusion: For adolescent flexible flat foot patients with pelvic obliquity, the coronal inclination and pelvic height discrepancy would partially recovered with correction of flatfoot deformity, but it could not be completely corrected in the mean follow-up period of 2 years after the operation.
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Affiliation(s)
- L Bai
- Department of Sports Medicine, Peking University Shenzhen Hospital, Shenzhen 518036, China
| | - W Zhou
- Department of Radiology, Peking University Shenzhen Hospital, Shenzhen 518036, China
| | - X X Xie
- Department of Sports Medicine, Peking University Shenzhen Hospital, Shenzhen 518036, China
| | - S M Chen
- Department of Sports Medicine, Peking University Shenzhen Hospital, Shenzhen 518036, China
| | - Y X Yan
- Department of Sports Medicine, Peking University Shenzhen Hospital, Shenzhen 518036, China
| | - X T Zhang
- Department of Sports Medicine, Peking University Shenzhen Hospital, Shenzhen 518036, China
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Zhou W, Yin Y, Shi M, Zhao L. A Retrospective Analysis of Immediate Postoperative Electron Radiotherapy for Keloids. Int J Radiat Oncol Biol Phys 2023; 117:e217. [PMID: 37784890 DOI: 10.1016/j.ijrobp.2023.06.1113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The increasing incidence of keloid has seriously affected people's physical and mental health, and the postoperative recurrence rate is as high as 50-80%. Postoperative radiotherapy has been shown to significantly reduce the recurrence of keloid. Given the different treatment patterns in different institutions, we tried to analyze the data of patients in our center. MATERIALS/METHODS We retrospectively analyzed the clinical data of 455 patients with 498 keloids treated in our institution from 2010 to 2017. All patients received a four-fraction electron radiotherapy with single dose of 4 Gy within 24 hours of surgery. The recurrence and adverse reaction of immediate adjuvant radiotherapy in these patients was evaluated. RESULTS At the last follow-up date, 130 (26.5%) keloids had recurred after a middle follow-up of 68.1 months (42.6-129.9 months). The recurrence rates of 1 year, 3 years and 5 years were respectively14.5%, 18.7% and 21%. Recurrence rates vary depending on the keloid location. Among them, the recurrence rate of ear was low with 14% (43/298). Face, head neck and limbs was moderate with 38.8% (17/44) and 33.3% (8/24). Chest and Suprapubic region had a high recurrence rate of 50.8% (32/64) and 47.8% (33/69). Among the patients with recurrence, 16.9% (22/130) felt that their symptoms were better than before treatment, and 37.7% (49/130) were not worsen, which was acceptable. Multivariate analysis showed that age and duration of postoperative pruritus pain were correlated with recurrence (P = 0.036; P = 0.02). Radiotherapy combined with steroid and silicone reduced the recurrence rate compared with radiotherapy alone (P = 0.015). During treatment and follow-up, Infection occurred in 2 patients and cutaneous fibroblastoma in 1 patient. CONCLUSION Our radiotherapy regimen can effectively reduce the recurrence rate and improve the symptoms of patients with keloids, especially ear keloids. High recurrence sites need further improvement of radiotherapy dose and fraction. Combination of multiple treatments is better than single treatment.
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Affiliation(s)
- W Zhou
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - Y Yin
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - M Shi
- Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - L Zhao
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China, Xi'an, China
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Tao D, Sun L, Wang LL, Yang D, Jiang Y, Zhou W, Wang Y, Wu YZ. Early Stereotactic Body Radiotherapy to the Primary Lung Lesion for Patients with Advanced NSCLC Treated with First-Line Systemic Therapy. Int J Radiat Oncol Biol Phys 2023; 117:S128. [PMID: 37784330 DOI: 10.1016/j.ijrobp.2023.06.474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Although adding consolidative stereotactic body radiotherapy (SBRT) to systemic therapy improves survival in advanced non-small cell lung cancer (NSCLC), the optimal timing of SBRT remains unclear. This study aimed to explore the clinical outcome of early and delayed SBRT to primary lung lesions of advanced NSCLC patients treated with first-line systemic therapy. MATERIALS/METHODS We identified patients with advanced NSCLC who were suitable to receiveSBRT for the primary lung tumors after first-line systemic therapy. All eligible patients were treated with first-line systemic therapy and SBRT for their primary lung lesions. Early SBRT group was defined as patients who received SBRT for their primary lung tumor at the maximal response of systemic therapy. Delayed SBRT group was defined as patients who received SBRT after the occurrence of oligoprogression in primary lung tumor. The primary endpoints were progression-free survival 1 (PFS1, time from start of first-line systemic therapy to disease progression) and PFS2 (time from start of first-line systemic therapy to disease progression after SBRT). Overall survival (OS) and adverse effects (AEs) were secondary endpoints. A two-sided P value of 0.05 was considered statistically significant. All of the statistical analyses were performed with statistical software. RESULTS A total of184 patients with advanced NSCLC treated with SBRT for primary tumors were screened, and 49 patients were eligible for enrollment in this study. The median age of the entire cohort was 66 years (range, 37-80 years), and 34 (69.4%) patients were male. Thirty-four patients (69.4%) were treated by target therapy and 15 (30.6%) were treated by chemotherapy and immunotherapy. Of the 49 eligible patients, 28(57.1%) received early SBRT to lung primary tumor and 21(42.9%) received delayed SBRT to lung primary tumor. The early SBRT group showed a significantly prolonged PFS1 as compared with the delayed SBRT group (mPFS1: 30 months vs. 8 months, P<0.001). The median PFS2 of the early SBRT group was longer than that of the delayed SBRT group, but the difference between the two groups did not achieve a statistical significance (mPFS2: 42 months vs. 23 months, P = 0.303). Median OS of both groups has not reached. No severe toxicities (≥grade 3) were observed in early SBRT group and only one patient in the delayed SBRT group experienced grade 3 radiation pneumonitis. CONCLUSION Early SBRT to the primary lung lesion significantly improved PFS and is a new potentially effective and tolerable treatment option for patients with advanced NSCLC who had stable disease during first-line systemic therapy.
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Affiliation(s)
- D Tao
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - L Sun
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - L L Wang
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - D Yang
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Y Jiang
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - W Zhou
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Y Wang
- Radiation Oncology Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Y Z Wu
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
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Kaur D, Lee SM, Goldberg D, Spix NJ, Hinoue T, Li HT, Dwaraka VB, Smith R, Shen H, Liang G, Renke N, Laird PW, Zhou W. Comprehensive Evaluation of The Infinium Human MethylationEPIC v2 BeadChip. Epigenetics Commun 2023; 3:6. [PMID: 38455390 PMCID: PMC10919401 DOI: 10.1186/s43682-023-00021-5] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 09/18/2023] [Indexed: 03/09/2024]
Abstract
Infinium Methylation BeadChips are widely used to profile DNA cytosine modifications in large cohort studies for reasons of cost-effectiveness, accurate quantification, and user-friendly data analysis in characterizing these canonical epigenetic marks. In this work, we conducted a comprehensive evaluation of the updated Infinium MethylationEPIC v2 BeadChip (EPICv2). Our evaluation revealed that EPICv2 offers significant improvements over its predecessors, including expanded enhancer coverage, applicability to diverse ancestry groups, support for low-input DNA down to one nanogram, coverage of existing epigenetic clocks, cell type deconvolution panels, and human trait associations, while maintaining accuracy and reproducibility. Using EPICv2, we were able to identify epigenome and sequence signatures in cell line models of DNMT and SETD2 loss and/or hypomorphism. Furthermore, we provided probe-wise evaluation and annotation to facilitate the use of new features on this array for studying the interplay between somatic mutations and epigenetic landscape in cancer genomics. In conclusion, EPICv2 provides researchers with a valuable tool for studying epigenetic modifications and their role in development and disease.
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Affiliation(s)
- Diljeet Kaur
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
- These authors contribute equally
| | - Sol Moe Lee
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
- These authors contribute equally
| | - David Goldberg
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
| | - Nathan J Spix
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Toshinori Hinoue
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Hong-Tao Li
- Department of Urology, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
| | | | - Ryan Smith
- TruDiagnostic Inc, Lexington, KY 40503, USA
| | - Hui Shen
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Gangning Liang
- Department of Urology, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Nicole Renke
- Illumina, Inc., Product Management Department, San Diego, CA 92122, USA
| | - Peter W Laird
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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22
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Lee SM, Loo CE, Prasasya RD, Bartolomei MS, Kohli RM, Zhou W. Low-input and single-cell methods for Infinium DNA methylation BeadChips. bioRxiv 2023:2023.09.18.558252. [PMID: 37786695 PMCID: PMC10541608 DOI: 10.1101/2023.09.18.558252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
The Infinium BeadChip is the most widely used DNA methylome assay technology for population-scale epigenome profiling. However, the standard workflow requires over 200 ng of input DNA, hindering its application to small cell-number samples, such as primordial germ cells. We developed experimental and analysis workflows to extend this technology to suboptimal input DNA conditions, including ultra-low input down to single cells. DNA preamplification significantly enhanced detection rates to over 50% in five-cell samples and ∼25% in single cells. Enzymatic conversion also substantially improved data quality. Computationally, we developed a method to model the background signal's influence on the DNA methylation level readings. The modified detection p -values calculation achieved higher sensitivities for low-input datasets and was validated in over 100,000 public datasets with diverse methylation profiles. We employed the optimized workflow to query the demethylation dynamics in mouse primordial germ cells available at low cell numbers. Our data revealed nuanced chromatin states, sex disparities, and the role of DNA methylation in transposable element regulation during germ cell development. Collectively, we present comprehensive experimental and computational solutions to extend this widely used methylation assay technology to applications with limited DNA.
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23
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Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Universal DNA methylation age across mammalian tissues. Nat Aging 2023; 3:1144-1166. [PMID: 37563227 PMCID: PMC10501909 DOI: 10.1038/s43587-023-00462-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.
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Affiliation(s)
- A T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - Z Fei
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, Riverside, CA, USA
| | - A Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - T R Robeck
- Zoological SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - J A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - R Lowe
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - Q Yan
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - J Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - H Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - V A Acosta-Rodriguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - D M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - J Almunia
- Loro Parque Fundacion, Puerto de la Cruz, Spain
| | - A Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - R Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C S Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - G Banks
- School of Science and Technology, Clifton Campus, Nottingham Trent University, Nottingham, UK
| | - K Belov
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - N C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - P Black
- Busch Gardens Tampa, Tampa, FL, USA
| | - D T Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
- Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - E K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - C E Breeze
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - R T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - G G Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - A Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - J M Cavin
- Gulf World, Dolphin Company, Panama City Beach, FL, USA
| | - L Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - I Chatzistamou
- Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - H Chen
- Department of Pharmacology, Addiction Science and Toxicology, the University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - P Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - O W Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S M Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - L N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - M L Cossette
- Department of Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - J Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - J DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S DiRocco
- SeaWorld of Florida, Orlando, FL, USA
| | - C Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | | | - C K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - S Emmrich
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E Erbay
- Altos Labs, San Francisco, CA, USA
| | - C Erlacher-Reid
- SeaWorld of Florida, Orlando, FL, USA
- SeaWorld Orlando, Orlando, FL, USA
| | - C G Faulkes
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - S H Ferguson
- Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - C J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - J M Gaillard
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - E Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - L Gerber
- Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - V N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - R G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - M J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - C B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - E N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - M B Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - D W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - M Haulena
- Vancouver Aquarium, Vancouver, British Columbia, Canada
| | - K Herrick
- SeaWorld of California, San Diego, CA, USA
| | - A N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - C J Hogg
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - T A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - T Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
- Division of Genetics and Metabolism, Oishei Children's Hospital, Buffalo, NY, USA
| | | | - A J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - G Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - O Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | - H Katcher
- Yuvan Research, Mountain View, CA, USA
| | | | - V Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - H Kiaris
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M S Kobor
- Edwin S.H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - P Kordowitzki
- Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences, Olsztyn, Poland
- Institute for Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | - W R Koski
- LGL Limited, King City, Ontario, Canada
| | - M Krützen
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
| | - S B Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Larison
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Center for Tropical Research, Institute for the Environment and Sustainability, UCLA, Los Angeles, CA, USA
| | - S G Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - J F Lemaitre
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - A J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - X Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - D T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - T J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - N Macoretta
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - D Maddox
- White Oak Conservation, Yulee, FL, USA
| | - C O Matkin
- North Gulf Oceanic Society, Homer, AK, USA
| | - J A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - J Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - J J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - G A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - K Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - J Munshi-South
- Louis Calder Center-Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - A Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M Nagy
- Museum fur Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - P Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - P W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - N B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Niehrs
- Institute of Molecular Biology, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - J K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - P O'Tierney Ginn
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - D T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Division of Regulatory Genomics and Cancer Evolution, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - A G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - S Osborn
- SeaWorld of Texas, San Antonio, TX, USA
| | - E A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - K M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - K C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - M Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - K J Peters
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
| | - A B Pedersen
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - J L Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - D W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - G M Pinho
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - J R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
| | - P Reddy
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - B Rey
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - B R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - J Robbins
- Center for Coastal Studies, Provincetown, MA, USA
| | | | - J Russell
- SeaWorld of California, San Diego, CA, USA
| | - E Rydkina
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - L L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - A B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - K M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - D Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | - T Schmitt
- SeaWorld of California, San Diego, CA, USA
| | | | - L B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - K E Sears
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - A W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - A Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - A B A Shafer
- Department of Forensic Science, Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - D Shanmuganayagam
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - K Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - I Sinha
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - R G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - E Soltanmaohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | | | - L Staggs
- SeaWorld of Florida, Orlando, FL, USA
| | | | - K J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - D T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | - V J Sugrue
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - B Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - J S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Takasugi
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E C Teeling
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - M J Thompson
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Van Bonn
- John G. Shedd Aquarium, Chicago, IL, USA
| | - S C Vernes
- School of Biology, the University of St Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - D Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - H V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M C Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - N Wang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R K Wayne
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - G S Wilkinson
- Department of Biology, University of Maryland, College Park, MD, USA
| | - C K Williams
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - X W Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M Yao
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - B G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - B Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Zhang
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - P Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, USA
| | - Y Zhao
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - W Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Zimmermann
- Department of Mathematics and Technology, University of Applied Sciences Koblenz, Koblenz, Germany
| | - J Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - K Raj
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - S Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
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24
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Haghani A, Li CZ, Robeck TR, Zhang J, Lu AT, Ablaeva J, Acosta-Rodríguez VA, Adams DM, Alagaili AN, Almunia J, Aloysius A, Amor NMS, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter G, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chavez AS, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke S, Cook JA, Cooper LN, Cossette ML, Day J, DeYoung J, Dirocco S, Dold C, Dunnum JL, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Fei Z, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Goya RG, Grant MJ, Green CB, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaître JF, Levine AJ, Li X, Li C, Lim AR, Lin DTS, Lindemann DM, Liphardt SW, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Murphy WJ, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, Nyamsuren B, O'Brien JK, Ginn PO, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pedersen AB, Pellegrini M, Peters KJ, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Shafer ABA, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmohammadi E, Spangler ML, Spriggs M, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Vu H, Wallingford MC, Wang N, Wilkinson GS, Williams RW, Yan Q, Yao M, Young BG, Zhang B, Zhang Z, Zhao Y, Zhao P, Zhou W, Zoller JA, Ernst J, Seluanov A, Gorbunova V, Yang XW, Raj K, Horvath S. DNA methylation networks underlying mammalian traits. Science 2023; 381:eabq5693. [PMID: 37561875 DOI: 10.1126/science.abq5693] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
Using DNA methylation profiles (n = 15,456) from 348 mammalian species, we constructed phyloepigenetic trees that bear marked similarities to traditional phylogenetic ones. Using unsupervised clustering across all samples, we identified 55 distinct cytosine modules, of which 30 are related to traits such as maximum life span, adult weight, age, sex, and human mortality risk. Maximum life span is associated with methylation levels in HOXL subclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species.
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Affiliation(s)
- Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Caesar Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Janssen Research & Development, Spring House, PA, USA
| | - Todd R Robeck
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - Joshua Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ake T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
| | - Julia Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Victoria A Acosta-Rodríguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Danielle M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - Abdulaziz N Alagaili
- Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Javier Almunia
- Loro Parque Fundacion, Avenida Loro Parque, Puerto de la Cruz, Tenerife, Spain
| | - Ajoy Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - Nabil M S Amor
- Laboratory of Biodiversity, Parasitology, and Ecology, University of Tunis El Manar, Tunis, Tunisia
| | - Reza Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Adriana Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Scott Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - Gareth Banks
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Science and Innovation Campus, Oxfordshire, UK
| | - Katherine Belov
- School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - Nigel C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | | | - Daniel T Blumstein
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
- The Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - Eleanor K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | | | - Robert T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - Janine L Brown
- Center for Species Survival, Smithsonian National Zoo and Conservation Biology, Front Royal, VA, USA
| | - Gerald Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - Alex Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, Otago, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, Otago, New Zealand
| | - Julie M Cavin
- Gulf World Marine Park - Dolphin Company, Panama City Beach, FL, USA
| | - Lisa Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - Ioulia Chatzistamou
- Department of Pathology, Microbiology & Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - Andreas S Chavez
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
- Translational Data Analytics Institute, The Ohio State University, Columbus, OH, USA
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, USA
| | - Kaiyang Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Priscila Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - Oi-Wa Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Shannon Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, Otago, New Zealand
| | - Joseph A Cook
- University of New Mexico, Department of Biology and Museum of Southwestern Biology, Albuquerque, NM, USA
| | - Lisa N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - Marie-Laurence Cossette
- Department of Environmental & Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - Joanna Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - Joseph DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Christopher Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - Jonathan L Dunnum
- University of New Mexico, Department of Biology and Museum of Southwestern Biology, Albuquerque, NM, USA
| | | | - Candice K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - Stephan Emmrich
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Ebru Erbay
- Altos Labs, Bay Area Institute of Science, Redwood City, CA, USA
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | | | - Chris G Faulkes
- School of Biological and Chemical Sciences, Queen Mary University of London, London, UK
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Zhe Fei
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, CA, USA
| | - Steven H Ferguson
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - Carrie J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - Jean-Michel Gaillard
- University of Lyon, CNRS, Laboratoire de Biométrie et Biologie Evolutive, Villeurbanne, France
| | - Eva Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - Livia Gerber
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia
- Australian National Wildlife Collection, CSIRO, Canberra, Australia
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rodolfo G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - Matthew J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Carla B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Bradley Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - Daniel W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | | | | | - Andrew N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Carolyn J Hogg
- School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - Timothy A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - Taosheng Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | | | - Anna J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Division of Infectious Diseases, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Molecular Genetics, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Gareth Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - Olga Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | | | | | - Vimala Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - Hippokratis Kiaris
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - Michael S Kobor
- Edwin S. H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Pawel Kordowitzki
- Institute of Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | | | - Michael Krützen
- Evolutionary Genetics Group, Department of Anthropology, University of Zurich, Zurich, Switzerland
| | - Soo Bin Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Brenda Larison
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
- Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sang-Goo Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marianne Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - Jean-François Lemaître
- University of Lyon, CNRS, Laboratoire de Biométrie et Biologie Evolutive, Villeurbanne, France
| | - Andrew J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Xinmin Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Cun Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - Andrea R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - David T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | | | - Thomas J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | | | | | | | - Julie A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - June Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - Jennifer J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin Madison, Madison, WI, USA
| | - Gisele A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - Khyobeni Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - Jason Munshi-South
- Louis Calder Center - Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, TX, USA
| | - Asieh Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - Martina Nagy
- Museum fur Naturkunde, Leibniz-Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - Pritika Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Peter W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - Ngoc B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Christof Niehrs
- Institute of Molecular Biology (IMB), Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | | | - Justine K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | | | - Duncan T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Deutsches Krebsforschungszentrum, Division of Regulatory Genomics and Cancer Evolution, Heidelberg, Germany
| | | | | | - Elaine A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Kim M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - Kimberly C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Amy B Pedersen
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - Matteo Pellegrini
- Department Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Katharina J Peters
- Evolutionary Genetics Group, Department of Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, New South Wales, Australia
| | | | - Darren W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - Gabriela M Pinho
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Jocelyn Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jesse R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Natalia A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - Pradeep Reddy
- Altos Labs, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Benjamin Rey
- University of Lyon, CNRS, Laboratoire de Biométrie et Biologie Evolutive, Villeurbanne, France
| | - Beate R Ritz
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
| | | | | | | | - Elena Rydkina
- Department of Biology, University of Rochester, Rochester, NY, USA
| | | | - Adam B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio, and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - Kyle M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Dennis Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | | | | | - Lawrence B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Karen E Sears
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Ashley W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - Aaron B A Shafer
- Department of Forensic Science, Environmental & Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - Anastasia V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Kavita Singh
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - Ishani Sinha
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Jesse Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - Russel G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Elham Soltanmohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | | | | | | | | | - Karen J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - Donald T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | | | - Balazs Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - Joseph S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Masaki Takasugi
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Emma C Teeling
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin, Ireland
| | - Michael J Thompson
- Department Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Bill Van Bonn
- Animal Care and Science Division, John G. Shedd Aquarium, Chicago, IL, USA
| | - Sonja C Vernes
- School of Biology, The University of St. Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
| | - Diego Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Harry V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ha Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Nan Wang
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - Qi Yan
- Altos Labs, San Diego, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Mingjia Yao
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Brent G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - Bohan Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Zhihui Zhang
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Yang Zhao
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - Peng Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Joseph A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Jason Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrei Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - Vera Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - X William Yang
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego, CA, USA
- Altos Labs, Cambridge, UK
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Ding W, Goldberg D, Zhou W. PyComplexHeatmap: a Python package to visualize multimodal genomics data. Imeta 2023; 2:e115. [PMID: 38454967 PMCID: PMC10919210 DOI: 10.1002/imt2.115] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 05/03/2023] [Indexed: 03/09/2024]
Abstract
Python has emerged as a robust programming language increasingly employed in genomics data analysis, largely due to its comprehensive deep learning libraries and proficiency in handling large-scale data, such as single-cell multi-omics datasets. Although Python has become a prominent data science ecosystem for bioinformatics, there remains a growing demand for advanced heatmap visualization and assembly tools, which are not sufficiently addressed by existing Python-based data visualization libraries. We present PyComplexHeatmap, an all-inclusive Python library for heatmap visualization, inspired by the ComplexHeatmap package currently available in R. PyComplexHeatmap is built upon the matplotlib library and features a versatile, modular interface that seamlessly integrates with other Python-based data science tools, such as Pandas, NumPy, and genomics tools, such as Scanpy, in a standard-compliant manner. This library caters to the requirements of exquisite rendering of multimodal matrix data, incorporating both textual and graphical annotations, thereby enabling efficient integrative analysis of multimodal data and associated metadata.
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Affiliation(s)
- Wubin Ding
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | - David Goldberg
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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26
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Zhao X, Zhang Q, Tao S, Zhou W, Jia PY. Association of edentulism and all-cause mortality in Chinese older adults: do sex differences exist? Public Health 2023; 221:184-189. [PMID: 37473651 DOI: 10.1016/j.puhe.2023.05.018] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 03/31/2023] [Accepted: 05/23/2023] [Indexed: 07/22/2023]
Abstract
OBJECTIVES Previous studies revealed that tooth loss or edentulism was related to mortality. However, research in developing countries with large numbers of elderly populations is rare, and whether sex differences exist in this relationship is unknown. This study aimed to investigate the association between edentulism and 7-year all-cause mortality among older adults in China and whether sex differences existed. STUDY DESIGN This was a prospective cohort study. METHODS Data were from 2011 to 2018 waves of the China Health and Retirement Longitudinal Study. A total of 6538 participants aged ≥60 years were included. Logistic models were adopted to estimate the risks of mortality according to edentulism. RESULTS The participants with edentulism at baseline were 20% more likely to die over 7 years after controlling for a set of covariates (odds ratio [OR] = 1.20, 95% confidence interval [CI]: 1.02-1.42). Moreover, edentulism was associated with a 35% higher odds of death among male participants (OR = 1.35, 95% CI: 1.08-1.70), whereas a significant association was not found in female participants. CONCLUSIONS The findings demonstrated that baseline edentulism predicted all-cause mortality in Chinese older adults, and sex differences existed in this association. This study implied the importance of developing oral health education programs, incorporating dietary recommendations into dental care for edentulous patients, and expanding the coverage of dental services in the health insurance system to prevent edentulism and alleviate its negative outcomes for older adults.
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Affiliation(s)
- X Zhao
- School of Health Humanities, Peking University, Beijing, China.
| | - Q Zhang
- National School of Development, Peking University, Beijing, China.
| | - S Tao
- School of Health Humanities, Peking University, Beijing, China.
| | - W Zhou
- Research Center for Public Health and Social Security, School of Public Administration, Hunan University, Hunan, China.
| | - P-Y Jia
- Department of the Fourth Clinical Division, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, Beijing, China.
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Gao ZX, Zhao YJ, Zhu YJ, Xiao N, Wen AN, Zhou W, Mao BC, Zhang Y, Qi W, Wang Y. [The design method of the digital sequential tooth-sectioning guide for the extraction of mandibular impacted third molars]. Zhonghua Kou Qiang Yi Xue Za Zhi 2023; 58:435-441. [PMID: 37082847 DOI: 10.3760/cma.j.cn112144-20220721-00398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/22/2023]
Abstract
Objective: To explore a method for digitally designing and fabricating a sequential tooth-sectioning guide that can assist in the extraction of mandibular horizontal impacted third molars, preliminarily evaluate its feasibility and provide a reference for clinical application. Methods: Twenty patients with mandibular low level impacted third molars who visited the Department of General Dentistry, Peking University School and Hospital of Stomatology from March 2021 to January 2022 were selected. Cone-beam CT showed direct contact between the roots and mandibular canal, and full range impressions of the patients' intraoral teeth were taken and optical scans of the dental model were performed. The patients' cone-beam CT data and optical scan data were reconstructed in three dimensions, anatomical structure extraction, registration fusion, and the design of the structure of the guide (including crown-sectioning guide and root-sectioning guide) by Mimics 24.0, Geomagic Wrap 2021, and Magics 21.0 software, and then the titanium guide was three dimension printed, and the guide was tried on the dental model. After confirmation, the guide was used to assist the dentist in the operation. We observed whether the guide was in place, the number of tooth splitting, the matching of tooth splitting with the preoperative design, the operation time, and whether there were any complications. Results: In this study, 20 sectioning guides were successfully printed, all of them were well fitted in the patients' mouth, the average number of section was 3.4 times, the tooth parts was better matched with the preoperative design, and the average operative time of the guides was (29.2±9.8) minutes without complications such as perforation of the bone cortex. Conclusions: The use of sequential sectioning guides to assist in the extraction of mandibular impacted third molars was initially validated to accurately replicate the preoperative sectioning design, and is expected to provide a digital solution to improve surgical precision and ensure safety. Further studies with larger sample sizes are needed to evaluate its accuracy and safety.
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Affiliation(s)
- Z X Gao
- Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China
| | - Y J Zhao
- Center of Digital Dentistry, Faculty of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
| | - Y J Zhu
- Center of Digital Dentistry, Faculty of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
| | - N Xiao
- Center of Digital Dentistry, Faculty of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
| | - A N Wen
- Center of Digital Dentistry, Faculty of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
| | - W Zhou
- Department of General Dentistry, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
| | - B C Mao
- Department of Orthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
| | - Y Zhang
- Department of VIP Dental Service, Lanzhou Stomatological Hospital, Lanzhou 730031, China
| | - W Qi
- Department of General Dentistry, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
| | - Y Wang
- Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China
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Liu L, Deng R, Zhou W, Lin M, Xia L, Gao H. [Mechanisms mediating the inhibitory effects of quercetin against phthalates-induced testicular oxidative damage in rats]. Nan Fang Yi Ke Da Xue Xue Bao 2023; 43:577-584. [PMID: 37202193 DOI: 10.12122/j.issn.1673-4254.2023.04.10] [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] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
OBJECTIVE To explore the mechanism underlying the inhibitory effect of quercetin against testicular oxidative damage induced by a mixture of 3 commonly used phthalates (MPEs) in rats. METHODS Forty male Sprague-Dawley rats were randomly divided into control group, MPEs exposure group, and MPEs with low-, median- and high-dose quercetin treatment groups. For MPEs exposure, the rats were subjected to intragastric administration of MPEs at the daily dose of 900 mg/kg for 30 consecutive days; Quercetin treatments were administered in the same manner at the daily dose of 10, 30, and 90 mg/kg. After the treatments, serum levels of testosterone, luteinizing hormone (LH), follicle stimulating hormone (FSH), and testicular malondialdeyhde (MDA), catalase (CAT) and superoxide dismutase (SOD) were detected, and testicular pathologies of the rats were observed with HE staining. The expressions of nuclear factor-E2-related factor 2 (Nrf2), Kelch-like ECH2 associated protein 1 (Keap1) and heme oxygenase 1 (HO-1) in the testis were detected using immunofluorescence assay and Western blotting. RESULTS Compared with the control group, the rats with MPEs exposure showed significant reductions of the anogenital distance, weight of the testis and epididymis, and the coefficients of the testis and epididymis with lowered serum testosterone, LH and FSH levels (P < 0.05). Testicular histological examination revealed atrophy of the seminiferous tubules, spermatogenic arrest, and hyperplasia of the Leydig cells in MPEs-exposed rats. MPEs exposure also caused significant increments of testicular Nrf2, MDA, SOD, CAT and HO-1 expressions and lowered testicular Keap1 expression (P < 0.05). Treatment with quercetin at the median and high doses significantly ameliorated the pathological changes induced by MPEs exposure (P < 0.05). CONCLUSION Quercetin treatment inhibits MPEs-induced oxidative testicular damage in rats possibly by direct scavenging of free radicals to lower testicular oxidative stress and restore the regulation of the Nrf2 signaling pathway.
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Affiliation(s)
- L Liu
- Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou 325035, China
- Zhejiang Provincial Key Laboratory of Watershed Science and Health, Wenzhou Medical University, Wenzhou 325035, China
| | - R Deng
- Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou 325035, China
| | - W Zhou
- Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou 325035, China
| | - M Lin
- Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou 325035, China
| | - L Xia
- Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou 325035, China
- Zhejiang Provincial Key Laboratory of Watershed Science and Health, Wenzhou Medical University, Wenzhou 325035, China
| | - H Gao
- Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou 325035, China
- Zhejiang Provincial Key Laboratory of Watershed Science and Health, Wenzhou Medical University, Wenzhou 325035, China
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Tang H, Yuan K, Zheng P, Xiao T, Zhang H, Zhao X, Zhou W, Wang S, Liu W. Synthesis, crystal structure and optical properties of the quasi-0D lead-free organic-inorganic hybrid crystal (C6H14N)3Bi2I9·H2O. J SOLID STATE CHEM 2023. [DOI: 10.1016/j.jssc.2023.124011] [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: 03/31/2023]
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Ding W, Kaur D, Horvath S, Zhou W. Comparative epigenome analysis using Infinium DNA methylation BeadChips. Brief Bioinform 2023; 24:6974838. [PMID: 36617464 PMCID: PMC10147478 DOI: 10.1093/bib/bbac617] [Citation(s) in RCA: 2] [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: 10/12/2022] [Revised: 12/05/2022] [Accepted: 12/15/2022] [Indexed: 01/10/2023] Open
Abstract
The arrival of the Infinium DNA methylation BeadChips for mice and other nonhuman mammalian species has outpaced the development of the informatics that supports their use for epigenetics study in model organisms. Here, we present informatics infrastructure and methods to allow easy DNA methylation analysis on multiple species, including domesticated animals and inbred laboratory mice (in SeSAMe version 1.16.0+). First, we developed a data-driven analysis pipeline covering species inference, genome-specific data preprocessing and regression modeling. We targeted genomes of 310 species and 37 inbred mouse strains and showed that genome-specific preprocessing prevents artifacts and yields more accurate measurements than generic pipelines. Second, we uncovered the dynamics of the epigenome evolution in different genomic territories and tissue types through comparative analysis. We identified a catalog of inbred mouse strain-specific methylation differences, some of which are linked to the strains' immune, metabolic and neurological phenotypes. By streamlining DNA methylation array analysis for undesigned genomes, our methods extend epigenome research to broad species contexts.
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Affiliation(s)
- Wubin Ding
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
| | - Diljeet Kaur
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA
| | - Steve Horvath
- Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA.,Altos Labs, San Diego, CA, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA.,Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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Shi Y, Zhou W. Interactive Effects of Dietary Inflammatory Index with BMI for the Risk of Stroke among Adults in the United States: Insight from NHANES 2011-2018. J Nutr Health Aging 2023; 27:277-284. [PMID: 37170435 DOI: 10.1007/s12603-023-1904-1] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
BACKGROUND AND AIM Research on the correlation between Dietary Inflammation Index (DII) and stroke is limited. Patients with high body mass index (BMI), as a high-risk group for stroke, require attention. Therefore, we aimed to examine the interactive effects of dietary inflammation and BMI on the risk of stroke among adults in the United States. METHODS AND RESULTS Overall, 9,384 participants were included in this study. The exposure variable was the DII, which was calculated based on the overall inflammatory effect score, and the outcome was stroke. Overall, there was a positive relationship between DII (as a continuous variable) and stroke. Increased level of DII was significantly associated with increased risk of stroke (odds ratio [OR]: 1.21, 95% CI: 1.06-1.38), which was enhanced by higher BMI (OR: 1.35, 95% CI: 1.15-1.58) with significant additive interactions. There was a significant secondary interaction of copresence of BMI ≥25 kg/m2, systolic blood pressure (SBP) ≥140 mmHg, and high DII for increased stroke, with a further increase in OR to 1.41 (1.19-1.67). CONCLUSIONS This cross-sectional study shows that the relationship between higher DII levels and the significant increase in stroke prevalence was further amplified in patients with SBP ≥140 mmHg and higher BMI.
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Affiliation(s)
- Y Shi
- Wei Zhou, MPH, Department of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, Nanchang of Jiangxi, China.No. 1 Minde Road, Nanchang of Jiangxi, 330006, China,
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Gerstung M, Jolly C, Leshchiner I, Dentro SC, Gonzalez S, Rosebrock D, Mitchell TJ, Rubanova Y, Anur P, Yu K, Tarabichi M, Deshwar A, Wintersinger J, Kleinheinz K, Vázquez-García I, Haase K, Jerman L, Sengupta S, Macintyre G, Malikic S, Donmez N, Livitz DG, Cmero M, Demeulemeester J, Schumacher S, Fan Y, Yao X, Lee J, Schlesner M, Boutros PC, Bowtell DD, Zhu H, Getz G, Imielinski M, Beroukhim R, Sahinalp SC, Ji Y, Peifer M, Markowetz F, Mustonen V, Yuan K, Wang W, Morris QD, Spellman PT, Wedge DC, Van Loo P, Tarabichi M, Wintersinger J, Deshwar AG, Yu K, Gonzalez S, Rubanova Y, Macintyre G, Adams DJ, Anur P, Beroukhim R, Boutros PC, Bowtell DD, Campbell PJ, Cao S, Christie EL, Cmero M, Cun Y, Dawson KJ, Demeulemeester J, Donmez N, Drews RM, Eils R, Fan Y, Fittall M, Garsed DW, Getz G, Ha G, Imielinski M, Jerman L, Ji Y, Kleinheinz K, Lee J, Lee-Six H, Livitz DG, Malikic S, Markowetz F, Martincorena I, Mitchell TJ, Mustonen V, Oesper L, Peifer M, Peto M, Raphael BJ, Rosebrock D, Sahinalp SC, Salcedo A, Schlesner M, Schumacher S, Sengupta S, Shi R, Shin SJ, Spiro O, Pitkänen E, Pivot X, Piñeiro-Yáñez E, Planko L, Plass C, Polak P, Pons T, Popescu I, Potapova O, Prasad A, Stein LD, Preston SR, Prinz M, Pritchard AL, Prokopec SD, Provenzano E, Puente XS, Puig S, Puiggròs M, Pulido-Tamayo S, Pupo GM, Vázquez-García I, Purdie CA, Quinn MC, Rabionet R, Rader JS, Radlwimmer B, Radovic P, Raeder B, Raine KM, Ramakrishna M, Ramakrishnan K, Vembu S, Ramalingam S, Raphael BJ, Rathmell WK, Rausch T, Reifenberger G, Reimand J, Reis-Filho J, Reuter V, Reyes-Salazar I, Reyna MA, Wheeler DA, Reynolds SM, Rheinbay E, Riazalhosseini Y, Richardson AL, Richter J, Ringel M, Ringnér M, Rino Y, Rippe K, Roach J, Yang TP, Roberts LR, Roberts ND, Roberts SA, Robertson AG, Robertson AJ, Rodriguez JB, Rodriguez-Martin B, Rodríguez-González FG, Roehrl MHA, Rohde M, Yao X, Rokutan H, Romieu G, Rooman I, Roques T, Rosebrock D, Rosenberg M, Rosenstiel PC, Rosenwald A, Rowe EW, Royo R, Yuan K, Rozen SG, Rubanova Y, Rubin MA, Rubio-Perez C, Rudneva VA, Rusev BC, Ruzzenente A, Rätsch G, Sabarinathan R, Sabelnykova VY, Zhu H, Sadeghi S, Sahinalp SC, Saini N, Saito-Adachi M, Saksena G, Salcedo A, Salgado R, Salichos L, Sallari R, Saller C, Wang W, Salvia R, Sam M, Samra JS, Sanchez-Vega F, Sander C, Sanders G, Sarin R, Sarrafi I, Sasaki-Oku A, Sauer T, Morris QD, Sauter G, Saw RPM, Scardoni M, Scarlett CJ, Scarpa A, Scelo G, Schadendorf D, Schein JE, Schilhabel MB, Schlesner M, Spellman PT, Schlomm T, Schmidt HK, Schramm SJ, Schreiber S, Schultz N, Schumacher SE, Schwarz RF, Scolyer RA, Scott D, Scully R, Wedge DC, Seethala R, Segre AV, Selander I, Semple CA, Senbabaoglu Y, Sengupta S, Sereni E, Serra S, Sgroi DC, Shackleton M, Van Loo P, Shah NC, Shahabi S, Shang CA, Shang P, Shapira O, Shelton T, Shen C, Shen H, Shepherd R, Shi R, Spellman PT, Shi Y, Shiah YJ, Shibata T, Shih J, Shimizu E, Shimizu K, Shin SJ, Shiraishi Y, Shmaya T, Shmulevich I, Wedge DC, Shorser SI, Short C, Shrestha R, Shringarpure SS, Shriver C, Shuai S, Sidiropoulos N, Siebert R, Sieuwerts AM, Sieverling L, Van Loo P, Signoretti S, Sikora KO, Simbolo M, Simon R, Simons JV, Simpson JT, Simpson PT, Singer S, Sinnott-Armstrong N, Sipahimalani P, Aaltonen LA, Skelly TJ, Smid M, Smith J, Smith-McCune K, Socci ND, Sofia HJ, Soloway MG, Song L, Sood AK, Sothi S, Abascal F, Sotiriou C, Soulette CM, Span PN, Spellman PT, Sperandio N, Spillane AJ, Spiro O, Spring J, Staaf J, Stadler PF, Abeshouse A, Staib P, Stark SG, Stebbings L, Stefánsson ÓA, Stegle O, Stein LD, Stenhouse A, Stewart C, Stilgenbauer S, Stobbe MD, Aburatani H, Stratton MR, Stretch JR, Struck AJ, Stuart JM, Stunnenberg HG, Su H, Su X, Sun RX, Sungalee S, Susak H, Adams DJ, Suzuki A, Sweep F, Szczepanowski M, Sültmann H, Yugawa T, Tam A, Tamborero D, Tan BKT, Tan D, Tan P, Agrawal N, Tanaka H, Taniguchi H, Tanskanen TJ, Tarabichi M, Tarnuzzer R, Tarpey P, Taschuk ML, Tatsuno K, Tavaré S, Taylor DF, Ahn KS, Taylor-Weiner A, Teague JW, Teh BT, Tembe V, Temes J, Thai K, Thayer SP, Thiessen N, Thomas G, Thomas S, Ahn SM, Thompson A, Thompson AM, Thompson JFF, Thompson RH, Thorne H, Thorne LB, Thorogood A, Tiao G, Tijanic N, Timms LE, Aikata H, Tirabosco R, Tojo M, Tommasi S, Toon CW, Toprak UH, Torrents D, Tortora G, Tost J, Totoki Y, Townend D, Akbani R, Traficante N, Treilleux I, Trotta JR, Trümper LHP, Tsao M, Tsunoda T, Tubio JMC, Tucker O, Turkington R, Turner DJ, Akdemir KC, Tutt A, Ueno M, Ueno NT, Umbricht C, Umer HM, Underwood TJ, Urban L, Urushidate T, Ushiku T, Uusküla-Reimand L, Al-Ahmadie H, Valencia A, Van Den Berg DJ, Van Laere S, Van Loo P, Van Meir EG, Van den Eynden GG, Van der Kwast T, Vasudev N, Vazquez M, Vedururu R, Al-Sedairy ST, Veluvolu U, Vembu S, Verbeke LPC, Vermeulen P, Verrill C, Viari A, Vicente D, Vicentini C, VijayRaghavan K, Viksna J, Al-Shahrour F, Vilain RE, Villasante I, Vincent-Salomon A, Visakorpi T, Voet D, Vyas P, Vázquez-García I, Waddell NM, Waddell N, Wadelius C, Alawi M, Wadi L, Wagener R, Wala JA, Wang J, Wang J, Wang L, Wang Q, Wang W, Wang Y, Wang Z, Albert M, Waring PM, Warnatz HJ, Warrell J, Warren AY, Waszak SM, Wedge DC, Weichenhan D, Weinberger P, Weinstein JN, Weischenfeldt J, Aldape K, Weisenberger DJ, Welch I, Wendl MC, Werner J, Whalley JP, Wheeler DA, Whitaker HC, Wigle D, Wilkerson MD, Williams A, Alexandrov LB, Wilmott JS, Wilson GW, Wilson JM, Wilson RK, Winterhoff B, Wintersinger JA, Wiznerowicz M, Wolf S, Wong BH, Wong T, Ally A, Wong W, Woo Y, Wood S, Wouters BG, Wright AJ, Wright DW, Wright MH, Wu CL, Wu DY, Wu G, Alsop K, Wu J, Wu K, Wu Y, Wu Z, Xi L, Xia T, Xiang Q, Xiao X, Xing R, Xiong H, Alvarez EG, Xu Q, Xu Y, Xue H, Yachida S, Yakneen S, Yamaguchi R, Yamaguchi TN, Yamamoto M, Yamamoto S, Yamaue H, Amary F, Yang F, Yang H, Yang JY, Yang L, Yang L, Yang S, Yang TP, Yang Y, Yao X, Yaspo ML, Amin SB, Yates L, Yau C, Ye C, Ye K, Yellapantula VD, Yoon CJ, Yoon SS, Yousif F, Yu J, Yu K, Aminou B, Yu W, Yu Y, Yuan K, Yuan Y, Yuen D, Yung CK, Zaikova O, Zamora J, Zapatka M, Zenklusen JC, Ammerpohl O, Zenz T, Zeps N, Zhang CZ, Zhang F, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Anderson MJ, Zhang X, Zhang X, Zhang Y, Zhang Z, Zhao Z, Zheng L, Zheng X, Zhou W, Zhou Y, Zhu B, Ang Y, Zhu H, Zhu J, Zhu S, Zou L, Zou X, deFazio A, van As N, van Deurzen CHM, van de Vijver MJ, van’t Veer L, Antonello D, von Mering C, Anur P, Aparicio S, Appelbaum EL, Arai Y, Aretz A, Arihiro K, Ariizumi SI, Armenia J, Arnould L, Asa S, Assenov Y, Atwal G, Aukema S, Auman JT, Aure MRR, Awadalla P, Aymerich M, Bader GD, Baez-Ortega A, Bailey MH, Bailey PJ, Balasundaram M, Balu S, Bandopadhayay P, Banks RE, Barbi S, Barbour AP, Barenboim J, Barnholtz-Sloan J, Barr H, Barrera E, Bartlett J, Bartolome J, Bassi C, Bathe OF, Baumhoer D, Bavi P, Baylin SB, Bazant W, Beardsmore D, Beck TA, Behjati S, Behren A, Niu B, Bell C, Beltran S, Benz C, Berchuck A, Bergmann AK, Bergstrom EN, Berman BP, Berney DM, Bernhart SH, Beroukhim R, Berrios M, Bersani S, Bertl J, Betancourt M, Bhandari V, Bhosle SG, Biankin AV, Bieg M, Bigner D, Binder H, Birney E, Birrer M, Biswas NK, Bjerkehagen B, Bodenheimer T, Boice L, Bonizzato G, De Bono JS, Boot A, Bootwalla MS, Borg A, Borkhardt A, Boroevich KA, Borozan I, Borst C, Bosenberg M, Bosio M, Boultwood J, Bourque G, Boutros PC, Bova GS, Bowen DT, Bowlby R, Bowtell DDL, Boyault S, Boyce R, Boyd J, Brazma A, Brennan P, Brewer DS, Brinkman AB, Bristow RG, Broaddus RR, Brock JE, Brock M, Broeks A, Brooks AN, Brooks D, Brors B, Brunak S, Bruxner TJC, Bruzos AL, Buchanan A, Buchhalter I, Buchholz C, Bullman S, Burke H, Burkhardt B, Burns KH, Busanovich J, Bustamante CD, Butler AP, Butte AJ, Byrne NJ, Børresen-Dale AL, Caesar-Johnson SJ, Cafferkey A, Cahill D, Calabrese C, Caldas C, Calvo F, Camacho N, Campbell PJ, Campo E, Cantù C, Cao S, Carey TE, Carlevaro-Fita J, Carlsen R, Cataldo I, Cazzola M, Cebon J, Cerfolio R, Chadwick DE, Chakravarty D, Chalmers D, Chan CWY, Chan K, Chan-Seng-Yue M, Chandan VS, Chang DK, Chanock SJ, Chantrill LA, Chateigner A, Chatterjee N, Chayama K, Chen HW, Chen J, Chen K, Chen Y, Chen Z, Cherniack AD, Chien J, Chiew YE, Chin SF, Cho J, Cho S, Choi JK, Choi W, Chomienne C, Chong Z, Choo SP, Chou A, Christ AN, Christie EL, Chuah E, Cibulskis C, Cibulskis K, Cingarlini S, Clapham P, Claviez A, Cleary S, Cloonan N, Cmero M, Collins CC, Connor AA, Cooke SL, Cooper CS, Cope L, Corbo V, Cordes MG, Cordner SM, Cortés-Ciriano I, Covington K, Cowin PA, Craft B, Craft D, Creighton CJ, Cun Y, Curley E, Cutcutache I, Czajka K, Czerniak B, Dagg RA, Danilova L, Davi MV, Davidson NR, Davies H, Davis IJ, Davis-Dusenbery BN, Dawson KJ, De La Vega FM, De Paoli-Iseppi R, Defreitas T, Tos APD, Delaneau O, Demchok JA, Demeulemeester J, Demidov GM, Demircioğlu D, Dennis NM, Denroche RE, Dentro SC, Desai N, Deshpande V, Deshwar AG, Desmedt C, Deu-Pons J, Dhalla N, Dhani NC, Dhingra P, Dhir R, DiBiase A, Diamanti K, Ding L, Ding S, Dinh HQ, Dirix L, 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D, Lee D, Lee EA, Lee HJ, Lee JJK, Lee JY, Lee J, Lee MTM, Lee-Six H, Lehmann KV, Lehrach H, Lenze D, Leonard CR, Leongamornlert DA, Leshchiner I, Letourneau L, Letunic I, Levine DA, Lewis L, Ley T, Li C, Li CH, Li HI, Li J, Li L, Li S, Li S, Li X, Li X, Li X, Li Y, Liang H, Liang SB, Lichter P, Lin P, Lin Z, Linehan WM, Lingjærde OC, Liu D, Liu EM, Liu FFF, Liu F, Liu J, Liu X, Livingstone J, Livitz D, Livni N, Lochovsky L, Loeffler M, Long GV, Lopez-Guillermo A, Lou S, Louis DN, Lovat LB, Lu Y, Lu YJ, Lu Y, Luchini C, Lungu I, Luo X, Luxton HJ, Lynch AG, Lype L, López C, López-Otín C, Ma EZ, Ma Y, MacGrogan G, MacRae S, Macintyre G, Madsen T, Maejima K, Mafficini A, Maglinte DT, Maitra A, Majumder PP, Malcovati L, Malikic S, Malleo G, Mann GJ, Mantovani-Löffler L, Marchal K, Marchegiani G, Mardis ER, Margolin AA, Marin MG, Markowetz F, Markowski J, Marks J, Marques-Bonet T, Marra MA, Marsden L, Martens JWM, Martin S, Martin-Subero JI, Martincorena I, Martinez-Fundichely A, Maruvka YE, Mashl RJ, Massie CE, Matthew TJ, Matthews L, Mayer E, Mayes S, Mayo M, Mbabaali F, McCune K, McDermott U, McGillivray PD, McLellan MD, McPherson JD, McPherson JR, McPherson TA, Meier SR, Meng A, Meng S, Menzies A, Merrett ND, Merson S, Meyerson M, Meyerson W, Mieczkowski PA, Mihaiescu GL, Mijalkovic S, Mikkelsen T, Milella M, Mileshkin L, Miller CA, Miller DK, Miller JK, Mills GB, Milovanovic A, Minner S, Miotto M, Arnau GM, Mirabello L, Mitchell C, Mitchell TJ, Miyano S, Miyoshi N, Mizuno S, Molnár-Gábor F, Moore MJ, Moore RA, Morganella S, Morris QD, Morrison C, Mose LE, Moser CD, Muiños F, Mularoni L, Mungall AJ, Mungall K, Musgrove EA, Mustonen V, Mutch D, Muyas F, Muzny DM, Muñoz A, Myers J, Myklebost O, Möller P, Nagae G, Nagrial AM, Nahal-Bose HK, Nakagama H, Nakagawa H, Nakamura H, Nakamura T, Nakano K, Nandi T, Nangalia J, Nastic M, Navarro A, Navarro FCP, Neal DE, Nettekoven G, Newell F, Newhouse SJ, Newton Y, Ng AWT, Ng A, Nicholson J, Nicol D, Nie Y, Nielsen GP, Nielsen 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Author Correction: The evolutionary history of 2,658 cancers. Nature 2023; 614:E42. [PMID: 36697833 PMCID: PMC9931577 DOI: 10.1038/s41586-022-05601-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Moritz Gerstung
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK. .,European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany. .,Wellcome Sanger Institute, Cambridge, UK.
| | - Clemency Jolly
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Ignaty Leshchiner
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Stefan C. Dentro
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK
| | - Santiago Gonzalez
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Daniel Rosebrock
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Thomas J. Mitchell
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Yulia Rubanova
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Pavana Anur
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - Kaixian Yu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Maxime Tarabichi
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Amit Deshwar
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Jeff Wintersinger
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | - Kortine Kleinheinz
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.7700.00000 0001 2190 4373Heidelberg University, Heidelberg, Germany
| | - Ignacio Vázquez-García
- grid.10306.340000 0004 0606 5382Wellcome Sanger Institute, Cambridge, UK ,grid.5335.00000000121885934University of Cambridge, Cambridge, UK
| | - Kerstin Haase
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK
| | - Lara Jerman
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK ,grid.8954.00000 0001 0721 6013University of Ljubljana, Ljubljana, Slovenia
| | - Subhajit Sengupta
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA
| | - Geoff Macintyre
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Salem Malikic
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Nilgun Donmez
- grid.61971.380000 0004 1936 7494Simon Fraser University, Burnaby, British Columbia Canada ,grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada
| | - Dimitri G. Livitz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Marek Cmero
- grid.1008.90000 0001 2179 088XUniversity of Melbourne, Melbourne, Victoria Australia ,grid.1042.70000 0004 0432 4889Walter and Eliza Hall Institute, Melbourne, Victoria Australia
| | - Jonas Demeulemeester
- grid.451388.30000 0004 1795 1830The Francis Crick Institute, London, UK ,grid.5596.f0000 0001 0668 7884University of Leuven, Leuven, Belgium
| | - Steven Schumacher
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Yu Fan
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Xiaotong Yao
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Juhee Lee
- grid.205975.c0000 0001 0740 6917University of California Santa Cruz, Santa Cruz, CA USA
| | - Matthias Schlesner
- grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Paul C. Boutros
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.419890.d0000 0004 0626 690XOntario Institute for Cancer Research, Toronto, Ontario Canada ,grid.19006.3e0000 0000 9632 6718University of California, Los Angeles, CA USA
| | - David D. Bowtell
- grid.1055.10000000403978434Peter MacCallum Cancer Centre, Melbourne, Victoria Australia
| | - Hongtu Zhu
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Gad Getz
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA USA ,grid.32224.350000 0004 0386 9924Department of Pathology, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Marcin Imielinski
- grid.5386.8000000041936877XWeill Cornell Medicine, New York, NY USA ,grid.429884.b0000 0004 1791 0895New York Genome Center, New York, NY USA
| | - Rameen Beroukhim
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - S. Cenk Sahinalp
- grid.412541.70000 0001 0684 7796Vancouver Prostate Centre, Vancouver, British Columbia Canada ,grid.411377.70000 0001 0790 959XIndiana University, Bloomington, IN USA
| | - Yuan Ji
- grid.240372.00000 0004 0400 4439NorthShore University HealthSystem, Evanston, IL USA ,grid.170205.10000 0004 1936 7822The University of Chicago, Chicago, IL USA
| | - Martin Peifer
- grid.6190.e0000 0000 8580 3777University of Cologne, Cologne, Germany
| | - Florian Markowetz
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Ville Mustonen
- grid.7737.40000 0004 0410 2071University of Helsinki, Helsinki, Finland
| | - Ke Yuan
- grid.5335.00000000121885934Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK ,grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Wenyi Wang
- grid.240145.60000 0001 2291 4776The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Quaid D. Morris
- grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada ,grid.494618.6Vector Institute, Toronto, Ontario Canada
| | | | - Paul T. Spellman
- grid.5288.70000 0000 9758 5690Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR USA
| | - David C. Wedge
- grid.4991.50000 0004 1936 8948Big Data Institute, University of Oxford, Oxford, UK ,grid.454382.c0000 0004 7871 7212Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Peter Van Loo
- The Francis Crick Institute, London, UK. .,University of Leuven, Leuven, Belgium.
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Liu H, Zhou W, Liu Q, Yu J, Wang C. Global Prevalence and Factors Associated with Frailty among Community-Dwelling Older Adults with Hypertension: A Systematic Review and Meta-Analysis. J Nutr Health Aging 2023; 27:1238-1247. [PMID: 38151875 DOI: 10.1007/s12603-023-2035-5] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 11/06/2023] [Indexed: 12/29/2023]
Abstract
BACKGROUND Frailty may increase the risk of adverse outcomes and the presence of comorbidities in hypertension. Understanding the prevalence of frailty in older adults with hypertension is of great importance, whereas estimates of the prevalence of frailty in this population vary greatly. OBJECTIVES A systematic review and meta-analysis was conducted to estimate the pooled prevalence of frailty and prefrailty among community-dwelling older adults with hypertension, and to examine the risk factors associated with (pre)frailty in this population. METHODS PubMed, Web of Science, The Cochrane Library, EMBASE, and CINAHL were searched from the inception to May 10, 2023. Investigators assessed eligibility, extracted data, and evaluated methodological quality. The pooled prevalence of frailty and prefrailty was calculated using the random-effects model. Meta-regression analysis and subgroup analysis were conducted to explore sources of heterogeneity. Sensitivity analysis was undertaken by the leave-one-out method and by removing studies with moderate/high risk of bias. The Mantel-Haenszel or inverse variance method was used to estimate risk factors of frailty. RESULTS A total of 14 studies met the inclusion criteria, involving 185,249 participants. The pooled prevalence in older adults with hypertension was 23% (95% CI 0.09-0.36) for frailty and 46% (95% CI 0.38-0.54) for prefrailty. The pooled prevalence of frailty was greater in studies with a higher proportion of females (24%, 95% CI 0.05-0.50), using multidimensional tools to define frailty (30%, 95% CI 0.10-0.51) and conducted in Western Pacific (27%, 95% CI 0.17-0.39). Age, female sex, depression, and previous hospitalizations were risk factors of frailty among older adults with hypertension. CONCLUSION Frailty and prefrailty are prevalent in community-dwelling older adults with hypertension, and limited risk factors are identified. This implicates the importance of frailty assessment integrated into the routine primary care for older adults with hypertension in community settings as well as the understanding of potential factors.
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Affiliation(s)
- H Liu
- Cuili Wang, PhD, is a senior research scientist, School of Nursing, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China; (C. Wang)
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Krishnamurthy S, Kube D, Kumar K, Kumar P, Kumar S, Kumar Y, Kundra R, Kübler K, Küppers R, Lagergren J, Lai PH, Laird PW, Lakhani SR, Lalansingh CM, Lalonde E, Lamaze FC, Lambert A, Lander E, Landgraf P, Landoni L, Langerød A, Lanzós A, Larsimont D, Larsson E, Lathrop M, Lau LMS, Lawerenz C, Lawlor RT, Lawrence MS, Lazar AJ, Lazic AM, Le X, Lee D, Lee D, Lee EA, Lee HJ, Lee JJK, Lee JY, Lee J, Lee MTM, Lee-Six H, Lehmann KV, Lehrach H, Lenze D, Leonard CR, Leongamornlert DA, Leshchiner I, Letourneau L, Letunic I, Levine DA, Lewis L, Ley T, Li C, Li CH, Li HI, Li J, Li L, Li S, Li S, Li X, Li X, Li X, Li Y, Liang H, Liang SB, Lichter P, Lin P, Lin Z, Linehan WM, Lingjærde OC, Liu D, Liu EM, Liu FFF, Liu F, Liu J, Liu X, Livingstone J, Livitz D, Livni N, Lochovsky L, Loeffler M, Long GV, Lopez-Guillermo A, Lou S, Louis DN, Lovat LB, Lu Y, Lu YJ, Lu Y, Luchini C, Lungu I, Luo X, Luxton HJ, Lynch AG, Lype L, López C, López-Otín C, Ma EZ, Ma Y, MacGrogan G, MacRae S, Macintyre G, Madsen T, Maejima K, Mafficini A, Maglinte DT, Maitra A, Majumder PP, Malcovati L, Malikic S, Malleo G, Mann GJ, Mantovani-Löffler L, Marchal K, Marchegiani G, Mardis ER, Margolin AA, Marin MG, Markowetz F, Markowski J, Marks J, Marques-Bonet T, Marra MA, Marsden L, Martens JWM, Martin S, Martin-Subero JI, Martincorena I, Martinez-Fundichely A, Maruvka YE, Mashl RJ, Massie CE, Matthew TJ, Matthews L, Mayer E, Mayes S, Mayo M, Mbabaali F, McCune K, McDermott U, McGillivray PD, McLellan MD, McPherson JD, McPherson JR, McPherson TA, Meier SR, Meng A, Meng S, Menzies A, Merrett ND, Merson S, Meyerson M, Meyerson W, Mieczkowski PA, Mihaiescu GL, Mijalkovic S, Mikkelsen T, Milella M, Mileshkin L, Miller CA, Miller DK, Miller JK, Mills GB, Milovanovic A, Minner S, Miotto M, Arnau GM, Mirabello L, Mitchell C, Mitchell TJ, Miyano S, Miyoshi N, Mizuno S, Molnár-Gábor F, Moore MJ, Moore RA, Morganella S, Morris QD, Morrison C, Mose LE, Moser CD, Muiños F, Mularoni L, Mungall AJ, Mungall K, Musgrove EA, Mustonen V, Mutch D, Muyas F, Muzny DM, Muñoz A, Myers J, Myklebost O, Möller P, Nagae G, Nagrial AM, Nahal-Bose HK, Nakagama H, Nakagawa H, Nakamura H, Nakamura T, Nakano K, Nandi T, Nangalia J, Nastic M, Navarro A, Navarro FCP, Neal DE, Nettekoven G, Newell F, Newhouse SJ, Newton Y, Ng AWT, Ng A, Nicholson J, Nicol D, Nie Y, Nielsen GP, Nielsen MM, Nik-Zainal S, Noble MS, Nones K, Northcott PA, Notta F, O’Connor BD, O’Donnell P, O’Donovan M, O’Meara S, O’Neill BP, O’Neill JR, Ocana D, Ochoa A, Oesper L, Ogden C, Ohdan H, Ohi K, Ohno-Machado L, Oien KA, Ojesina AI, Ojima H, Okusaka T, Omberg L, Ong CK, Ossowski S, Ott G, Ouellette BFF, P’ng C, Paczkowska M, Paiella S, Pairojkul C, Pajic M, Pan-Hammarström Q, Papaemmanuil E, Papatheodorou I, Paramasivam N, Park JW, Park JW, Park K, Park K, Park PJ, Parker JS, Parsons SL, Pass H, Pasternack D, Pastore A, Patch AM, Pauporté I, Pea A, Pearson JV. Author Correction: Genomic basis for RNA alterations in cancer. Nature 2023; 614:E37. [PMID: 36697831 PMCID: PMC9931574 DOI: 10.1038/s41586-022-05596-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
| | - Claudia Calabrese
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Natalie R. Davidson
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.5386.8000000041936877XWeill Cornell Medical College, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Deniz Demircioğlu
- grid.4280.e0000 0001 2180 6431National University of Singapore, Singapore, Singapore ,grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Nuno A. Fonseca
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Yao He
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - André Kahles
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Kjong-Van Lehmann
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Fenglin Liu
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Yuichi Shiraishi
- grid.26999.3d0000 0001 2151 536XThe University of Tokyo, Minato-ku, Japan
| | - Cameron M. Soulette
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Lara Urban
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Liliana Greger
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Siliang Li
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Dongbing Liu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Marc D. Perry
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.266102.10000 0001 2297 6811University of California, San Francisco, San Francisco, CA USA
| | - Qian Xiang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Fan Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
| | - Junjun Zhang
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Peter Bailey
- grid.8756.c0000 0001 2193 314XUniversity of Glasgow, Glasgow, UK
| | - Serap Erkek
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Katherine A. Hoadley
- grid.10698.360000000122483208The University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Yong Hou
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Matthew R. Huska
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Helena Kilpinen
- grid.83440.3b0000000121901201University College London, London, UK
| | - Jan O. Korbel
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Maximillian G. Marin
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA
| | - Julia Markowski
- grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany
| | - Tannistha Nandi
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore
| | - Qiang Pan-Hammarström
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.4714.60000 0004 1937 0626Karolinska Institutet, Stockholm, Sweden
| | - Chandra Sekhar Pedamallu
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Reiner Siebert
- grid.410712.10000 0004 0473 882XUlm University and Ulm University Medical Center, Ulm, Germany
| | - Stefan G. Stark
- grid.5801.c0000 0001 2156 2780ETH Zurich, Zurich, Switzerland ,grid.51462.340000 0001 2171 9952Memorial Sloan Kettering Cancer Center, New York, NY USA ,grid.419765.80000 0001 2223 3006SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland ,grid.412004.30000 0004 0478 9977University Hospital Zurich, Zurich, Switzerland
| | - Hong Su
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Patrick Tan
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.428397.30000 0004 0385 0924Duke-NUS Medical School, Singapore, Singapore
| | - Sebastian M. Waszak
- grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Christina Yung
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Shida Zhu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Philip Awadalla
- grid.17063.330000 0001 2157 2938Ontario Institute for Cancer Research, Toronto, Ontario, Canada ,grid.17063.330000 0001 2157 2938University of Toronto, Toronto, Ontario Canada
| | - Chad J. Creighton
- grid.39382.330000 0001 2160 926XBaylor College of Medicine, Houston, TX USA
| | - Matthew Meyerson
- grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | | | - Kui Wu
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China ,grid.507779.b0000 0004 4910 5858China National GeneBank-Shenzhen, Shenzhen, China
| | - Huanming Yang
- grid.21155.320000 0001 2034 1839BGI-Shenzhen, Shenzhen, China
| | | | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.
| | - Angela N. Brooks
- grid.205975.c0000 0001 0740 6917University of California, Santa Cruz, Santa Cruz, CA USA ,grid.66859.340000 0004 0546 1623Broad Institute, Cambridge, MA USA ,grid.65499.370000 0001 2106 9910Dana-Farber Cancer Institute, Boston, MA USA
| | - Jonathan Göke
- grid.418377.e0000 0004 0620 715XGenome Institute of Singapore, Singapore, Singapore ,grid.410724.40000 0004 0620 9745National Cancer Centre Singapore, Singapore, Singapore
| | - Gunnar Rätsch
- ETH Zurich, Zurich, Switzerland. .,Memorial Sloan Kettering Cancer Center, New York, NY, USA. .,Weill Cornell Medical College, New York, NY, USA. .,SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,University Hospital Zurich, Zurich, Switzerland.
| | - Roland F. Schwarz
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.419491.00000 0001 1014 0849Berlin Institute for Medical Systems Biology, Max Delbruck Center for Molecular Medicine, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), partner site Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oliver Stegle
- grid.225360.00000 0000 9709 7726European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK ,grid.4709.a0000 0004 0495 846XEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Zemin Zhang
- grid.11135.370000 0001 2256 9319Peking University, Beijing, China
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Heyne HO, Karjalainen J, Karczewski KJ, Lemmelä SM, Zhou W, Havulinna AS, Kurki M, Rehm HL, Palotie A, Daly MJ. Mono- and biallelic variant effects on disease at biobank scale. Nature 2023; 613:519-525. [PMID: 36653560 PMCID: PMC9849130 DOI: 10.1038/s41586-022-05420-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [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: 04/28/2021] [Accepted: 10/06/2022] [Indexed: 01/20/2023]
Abstract
Identifying causal factors for Mendelian and common diseases is an ongoing challenge in medical genetics1. Population bottleneck events, such as those that occurred in the history of the Finnish population, enrich some homozygous variants to higher frequencies, which facilitates the identification of variants that cause diseases with recessive inheritance2,3. Here we examine the homozygous and heterozygous effects of 44,370 coding variants on 2,444 disease phenotypes using data from the nationwide electronic health records of 176,899 Finnish individuals. We find associations for homozygous genotypes across a broad spectrum of phenotypes, including known associations with retinal dystrophy and novel associations with adult-onset cataract and female infertility. Of the recessive disease associations that we identify, 13 out of 20 would have been missed by the additive model that is typically used in genome-wide association studies. We use these results to find many known Mendelian variants whose inheritance cannot be adequately described by a conventional definition of dominant or recessive. In particular, we find variants that are known to cause diseases with recessive inheritance with significant heterozygous phenotypic effects. Similarly, we find presumed benign variants with disease effects. Our results show how biobanks, particularly in founder populations, can broaden our understanding of complex dosage effects of Mendelian variants on disease.
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Affiliation(s)
- H O Heyne
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland. .,Digital Health Center, Hasso Plattner Institute for Digital Engineering, University of Potsdam, Potsdam, Germany. .,Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - J Karjalainen
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.,Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - K J Karczewski
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.,Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - S M Lemmelä
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.,Finnish Institute for Health and Welfare, Helsinki, Finland
| | - W Zhou
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.,Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | - A S Havulinna
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.,Finnish Institute for Health and Welfare, Helsinki, Finland
| | - M Kurki
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.,Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - H L Rehm
- Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - A Palotie
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland.,Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - M J Daly
- Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland. .,Program for Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. .,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
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Yu Y, Zhou W, Li Y, Wan W, Yao D, Wei X. Nuclear and Mitochondrial DNA Suggest That Nature Reserve Maintains Novel Haplotypes and Genetic Diversity of Honeybees (Apis cerana). RUSS J GENET+ 2022. [DOI: 10.1134/s1022795422120146] [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: 12/29/2022]
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37
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DiNatale A, Worrede A, Iqbal W, Marchioli M, Toth A, Sjöström M, Zhu X, Corey E, Feng FY, Zhou W, Fatatis A. IL-1β expression driven by androgen receptor absence or inactivation promotes prostate cancer bone metastasis. Cancer Res Commun 2022; 2:1545-1557. [PMID: 36561929 PMCID: PMC9770512 DOI: 10.1158/2767-9764.crc-22-0262] [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] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
We report the inverse association between the expression of androgen receptor (AR) and interleukin-1beta (IL-1β) in a cohort of patients with metastatic castration resistant prostate cancer (mCRPC). We also discovered that AR represses the IL-1β gene by binding an androgen response element (ARE) half-site located within the promoter, which explains the IL-1β expression in AR-negative (ARNEG) cancer cells. Consistently, androgen-depletion or AR-pathway inhibitors (ARIs) de-repressed IL-1β in ARPOS cancer cells, both in vitro and in vivo. The AR transcriptional repression is sustained by histone de-acetylation at the H3K27 mark in the IL-1β promoter. Notably, patients' data suggest that DNA methylation prevents IL-1β expression, even if the AR-signaling axis is inactive. Our previous studies show that secreted IL-1β supports metastatic progression in mice by altering the transcriptome of tumor-associated bone stroma. Thus, in prostate cancer patients harboring ARNEG tumor cells or treated with ADT/ARIs, and with the IL-1β gene unmethylated, IL-1β could condition the metastatic microenvironment to sustain disease progression.
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Affiliation(s)
- Anthony DiNatale
- Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA;,Present address: Janssen Oncology, Spring House, PA
| | - Asurayya Worrede
- Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA;,Present address: AstraZeneca, Baltimore, MD
| | - Waleed Iqbal
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Michael Marchioli
- Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA
| | - Allison Toth
- Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA
| | | | - Xiaolin Zhu
- Department of Radiation Oncology, UCSF, San Francisco, CA
| | - Eva Corey
- Department of Urology, University of Washington, WA
| | - Felix Y. Feng
- Department of Radiation Oncology, UCSF, San Francisco, CA
| | - Wanding Zhou
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Alessandro Fatatis
- Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA;,Program in Translational and Cellular Oncology, Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA
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38
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Zhou W, Kong Y, LiYuan Z. PD-1 Inhibitor Combined with Radiotherapy and GM-CSF with or not IL-2 (PRaG Regimen) for Advanced Metastatic Non-Small Cell Lung Cancer. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1570] [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: 10/31/2022]
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39
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Chipps B, Soong W, Panettieri R, Carr W, Gandhi H, Zhou W, Llanos-Ackert J, Ambrose C. PATIENT-REPORTED TRIGGER NUMBER IS A STRONG PREDICTOR OF UNCONTROLLED DISEASE AMONG PATIENTS WITH SEVERE ASTHMA. Ann Allergy Asthma Immunol 2022. [DOI: 10.1016/j.anai.2022.08.632] [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: 11/11/2022]
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40
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Hong C, Li H, Parel PM, Berg AR, Rodante J, Keel A, Teague HL, Playford MP, Chen MY, Zhou W, Sorokin AV, Bluemke DA, Mehta NN. Application of machine learning to identify top determinants of fibrofatty plaque burden by CCTA in humans with psoriasis. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Introduction
Fibrofatty plaque burden (FFB) is a high-risk, vulnerable plaque feature comprised of an atheromatous core and fibrous cap with increased risk of coronary artery disease (CAD) [1]. Psoriasis (PSO) is a chronic inflammatory disease linked with atherosclerotic risk and premature cardiovascular disease, driven in part by vulnerable plaque rupture [2,3]. Machine learning (ML) previously showed the prognostic value of FFB in predicting 5-year risk of cardiac-related mortality in patients with CAD [4]. Whether ML can predict FFB in psoriasis is understudied.
Purpose
To use ML to identify top determinants of FFB by CCTA in PSO.
Methods
320 consecutive participants with psoriasis were recruited as part of an ongoing cohort study, of whom 307 had FFB analyzed with coronary computed tomography angiography (CCTA) and quantified by QAngio CT (Medis, The Netherlands). 140 out of 182 potential determinants were subjected to ML algorithms analyzed by random forest and validated by 5-fold cross validation to select the top determinants based on R-square criteria. Lipid concentration and size were measured by nuclear magnetic resonance (NMR) and sdLDL-C was calculated by Sampson's formula.
Results
The top 21 determinants of FFB at baseline were grouped into 3 categories: cardiometabolic risk factors (BMI, sex, DBP, mean arterial pressure, exercise, heart rate, glucose, anxiety, psoriasis disease duration), clinical measurements (basophils, platelets, hemoglobin, RBC, alkaline phosphatase, ALT, creatinine, neutrophil-to-lymphocyte ratio), and lipoproteins (LDL particle size, apolipoprotein A1, apolipoprotein B-to-A1 ratio, calculated sdLDL-C).
Conclusion
ML confirmed that FFB strongly correlates with cardiometabolic risk factors, clinical measurements, and lipoproteins. Further investigations into these top determinants of FFB over time may provide insight into potential therapeutic interventions that decrease cardiovascular risk in patients with chronic inflammatory diseases and should be validated in larger studies.
Funding Acknowledgement
Type of funding sources: Public Institution(s). Main funding source(s): This study was supported by the National Heart, Lung and Blood Institute (NHLBI) IntramuralResearch Program (ZIA-HL-06193). This research was made possible through the NIH MedicalResearch Scholars Program, a public-private partnership supported jointly by the NIH andcontributions to the Foundation for the NIH from the Doris Duke Charitable Foundation,Genentech, the American Association for Dental Research, the Colgate-Palmolive Company, andother private donors.
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Affiliation(s)
- C Hong
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - H Li
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - P M Parel
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - A R Berg
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - J Rodante
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - A Keel
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - H L Teague
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - M P Playford
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - M Y Chen
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - W Zhou
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - A V Sorokin
- National Heart Lung and Blood Institute , Bethesda , United States of America
| | - D A Bluemke
- University of Wisconsin-Madison, Department of Radiology , Madison , United States of America
| | - N N Mehta
- National Heart Lung and Blood Institute , Bethesda , United States of America
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El Zein A, Colby S, Zhou W, Shelnutt K, Greene G, Mathews A. Association between Food Insecurity and Perceived Stress in College Students: A Prospective Study. J Acad Nutr Diet 2022. [DOI: 10.1016/j.jand.2022.08.087] [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: 11/17/2022]
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42
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Zhang F, Wang Z, Su H, Zhao H, Lu W, Zhou W, Zhang H. Effect of a home-based resistance exercise program in elderly participants with osteoporosis: a randomized controlled trial. Osteoporos Int 2022; 33:1937-1947. [PMID: 35704055 DOI: 10.1007/s00198-022-06456-1] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 05/31/2022] [Indexed: 11/30/2022]
Abstract
UNLABELLED The effectiveness of home-based resistance exercise in elder participants with osteoporosis remains unclear. This study demonstrates the beneficial effects of this mode of exercise on improving physical function, increasing confidence in exercise, and reducing fear of falling. INTRODUCTION This study aims to evaluate the effect of a home-based resistance exercise (HBRE) program versus control on physical function, exercise self-efficacy, falling efficacy, and health-related quality of life (HRQOL). METHODS This randomized controlled trial included 72 elderly participants with osteoporosis. Participants in the intervention group received a 12-week HBRE program, and the control group received usual care. The primary outcome was physical function, including muscle strength and balance ability; secondary outcomes were exercise self-efficacy, falling efficacy, and HRQOL. Within-group and between-group changes in outcome were evaluated by t-test and rank-sum test. RESULTS A total of 68 subjects were included in the final analysis. Improvement in physical function was significantly greater in the HBRE group compared with controls. On a psychological level, exercise self-efficacy and falling efficacy improved significantly in the HBRE group; no significant change was observed in the control group. Most of the dimensions of HRQOL demonstrated improvements as well. The adherence was 85.29%, with no adverse events related to the exercise. CONCLUSION A 12-week HBRE program was safe non-pharmacological therapy for elderly participants with osteoporosis, improving physical function, exercise self-efficacy, reduced fear of falling, and improved HRQOL. TRIAL REGISTRATION Chinese Clinical Trial Register: ChiCTR2100051455. Registered 23.09.21. Retrospectively registered.
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Affiliation(s)
- F Zhang
- Department of Nursing, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - Z Wang
- Department of Orthopedic Surgery, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - H Su
- Department of Oncology, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - H Zhao
- Department of Orthopedic Surgery, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - W Lu
- Department of Orthopedic Surgery, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - W Zhou
- Department of Nursing, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - H Zhang
- Department of Nursing, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
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Chambwe N, Sayaman RW, Hu D, Huntsman S, Kemal A, Caesar-Johnson S, Zenklusen JC, Ziv E, Beroukhim R, Cherniack AD, Carrot-Zhang J, Berger AC, Han S, Meyerson M, Damrauer JS, Hoadley KA, Felau I, Demchok JA, Mensah MK, Tarnuzzer R, Wang Z, Yang L, Knijnenburg TA, Robertson AG, Yau C, Benz C, Huang KL, Newberg JY, Frampton GM, Mashl RJ, Ding L, Romanel A, Demichelis F, Zhou W, Laird PW, Shen H, Wong CK, Stuart JM, Lazar AJ, Le X, Oak N. Analysis of germline-driven ancestry-associated gene expression in cancers. STAR Protoc 2022; 3:101586. [PMID: 35942349 PMCID: PMC9356164 DOI: 10.1016/j.xpro.2022.101586] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Differential mRNA expression between ancestry groups can be explained by both genetic and environmental factors. We outline a computational workflow to determine the extent to which germline genetic variation explains cancer-specific molecular differences across ancestry groups. Using multi-omics datasets from The Cancer Genome Atlas (TCGA), we enumerate ancestry-informative markers colocalized with cancer-type-specific expression quantitative trait loci (e-QTLs) at ancestry-associated genes. This approach is generalizable to other settings with paired germline genotyping and mRNA expression data for a multi-ethnic cohort. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020), Robertson et al. (2021), and Sayaman et al. (2021). Protocol for obtaining controlled access TCGA datasets Protocols for quality control analysis and genotype imputation of TCGA germline data Statistical analysis for determining ancestry-associated SNPs Determination of ancestry-associated germline genetic variation driving mRNA expression
Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
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Kim J, Moreno A, Lee J, Lee H, Li X, Zhou W, Cao J, Krueger J. 807 Hidradenitis suppurativa type 17 T-cell transcriptome is different from psoriasis. J Invest Dermatol 2022. [DOI: 10.1016/j.jid.2022.05.821] [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: 10/17/2022]
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45
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Zhou W, Hinoue T, Barnes B, Mitchell O, Iqbal W, Lee SM, Foy KK, Lee KH, Moyer EJ, VanderArk A, Koeman JM, Ding W, Kalkat M, Spix NJ, Eagleson B, Pospisilik JA, Szabó PE, Bartolomei MS, Vander Schaaf NA, Kang L, Wiseman AK, Jones PA, Krawczyk CM, Adams M, Porecha R, Chen BH, Shen H, Laird PW. DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse. Cell Genom 2022; 2:100144. [PMID: 35873672 PMCID: PMC9306256 DOI: 10.1016/j.xgen.2022.100144] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 03/20/2022] [Accepted: 05/20/2022] [Indexed: 05/21/2023]
Abstract
We have developed a mouse DNA methylation array that contains 296,070 probes representing the diversity of mouse DNA methylation biology. We present a mouse methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, ages, sexes, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, patient-derived xenograft assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging, and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. Apc Min/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This Infinium Mouse Methylation BeadChip (version MM285) is widely accessible to the research community and will accelerate high-sample-throughput studies in this important model organism.
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Affiliation(s)
- Wanding Zhou
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Corresponding author
| | - Toshinori Hinoue
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Bret Barnes
- Illumina, Inc., Bioinformatics and Instrument Software Department, San Diego, CA 92122, USA
| | - Owen Mitchell
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Waleed Iqbal
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Sol Moe Lee
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kelly K. Foy
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Kwang-Ho Lee
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Ethan J. Moyer
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Alexandra VanderArk
- Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Julie M. Koeman
- Genomics Core, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Wubin Ding
- Center for Computational and Genomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Manpreet Kalkat
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Nathan J. Spix
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Bryn Eagleson
- Vivarium and Transgenics Core, Van Andel Institute, Grand Rapids, MI 49503, USA
| | | | - Piroska E. Szabó
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Marisa S. Bartolomei
- Department of Cell and Developmental Biology, Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | | | - Liang Kang
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Ashley K. Wiseman
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Peter A. Jones
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Connie M. Krawczyk
- Department of Metabolism and Nutritional Programming, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Marie Adams
- Genomics Core, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Rishi Porecha
- Illumina, Inc., Bioinformatics and Instrument Software Department, San Diego, CA 92122, USA
| | | | - Hui Shen
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
- Corresponding author
| | - Peter W. Laird
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
- Corresponding author
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Chen Q, Zhou WZ, Zhou NY, Yang H, Wang YM, Zhang HY, Li QH, Wang NR, Chen HY, Ao L, Liu JY, Zhou ZY, Zhang H, Zhou W, Qi HB, Cao J. [Preconception reproductive health and birth outcome cohort in Chongqing: the cohort profile]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:1134-1139. [PMID: 35856211 DOI: 10.3760/cma.j.cn112338-20220219-00134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Birth cohort is an important platform to study the effect of early-life exposure on health outcome, but large cohorts to investigate the effect of preconception exposure, especially paternal exposure, on reproductive health and birth outcome are limited. The Preconception Reproductive Health and Birth Outcome Cohort (PREBIC) is a prospective birth cohort study which pays equal attention to the contribution of environmental, psychological, behavioral as well as other factors to reproductive health and adverse birth outcomes in both men and women in Chongqing, China. PREBIC started in 2019 and plans to recruit 20 800 reproductive-age couples with child-bearing willingness. Followed up was conducted to understand the conception status of the women within two years. Women in pregnancy would be visited at first, second, third trimesters and after delivery. The offspring would be monitored until 2 years old to understand the incidences of preterm birth, low birth weight, birth defects, neurodevelopmental disorders and other outcomes. Related information and biospecimen collections (including semen, peripheral blood, urine, placenta, umbilical cord, cord blood and oral swab) were scheduled in each period. By January 2022, PREBIC had recruited 8 698 participants from all 38 districts in Chongqing. The goal of PREBIC is to establish one of the largest prospective preconception birth cohorts covering both men and women, which might provide a unique insight to understand the effects of the full reproductive cycle on reproductive health and adverse outcomes, with especial emphasis on preconception exposures.
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Affiliation(s)
- Q Chen
- Institute of Toxicology,College of Military Preventive Medicine,Third Military Medical University/Army Medical University,Chongqing 400038,China
| | - W Z Zhou
- Quality Management Department,Women and Children's Hospital of Chongqing Medical University, Chongqing 401120,China
| | - N Y Zhou
- Institute of Toxicology,College of Military Preventive Medicine,Third Military Medical University/Army Medical University,Chongqing 400038,China
| | - H Yang
- Institute of Toxicology,College of Military Preventive Medicine,Third Military Medical University/Army Medical University,Chongqing 400038,China
| | - Y M Wang
- Institute of Toxicology,College of Military Preventive Medicine,Third Military Medical University/Army Medical University,Chongqing 400038,China
| | - H Y Zhang
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing 401120,China
| | - Q H Li
- Clinical Laboratory Department,Women and Children's Hospital of Chongqing Medical University, Chongqing 401120,China
| | - N R Wang
- Department of Pediatrics, Women and Children Hospital of Chongqing Medical University, Chongqing 401120,China
| | - H Y Chen
- Quality Management Department,Women and Children's Hospital of Chongqing Medical University, Chongqing 401120,China
| | - L Ao
- Institute of Toxicology,College of Military Preventive Medicine,Third Military Medical University/Army Medical University,Chongqing 400038,China
| | - J Y Liu
- Institute of Toxicology,College of Military Preventive Medicine,Third Military Medical University/Army Medical University,Chongqing 400038,China
| | - Z Y Zhou
- Department of Environmental Health,College of Military Preventive Medicine,Third Military Medical University/Army Medical University,Chongqing 400038,China
| | - H Zhang
- Administration Office,Chongqing Health Center for Women and Children,Chongqing 401120,China
| | - W Zhou
- Administration Office,Chongqing Health Center for Women and Children,Chongqing 401120,China
| | - H B Qi
- Administration Office,Chongqing Health Center for Women and Children,Chongqing 401120,China
| | - Jia Cao
- Institute of Toxicology,College of Military Preventive Medicine,Third Military Medical University/Army Medical University,Chongqing 400038,China
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Hsu L, Bui V, O'Hagan R, Sorokin A, Zhou W, Jones E, Mehta N, Chen M. 404 Fully Automated Quantification Of Epicardial And Thoracic Adipose Tissue From Cardiovascular Computed Tomography. J Cardiovasc Comput Tomogr 2022. [DOI: 10.1016/j.jcct.2022.06.009] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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Bui V, Hsu L, Sun A, Tran L, Shanbhag S, Chang L, Zhou W, Mehta N, Chen M. 401 Deepheartct: A Fully Automatic Hybrid Structure Segmentation Framework Based On Atlas, Reverse Ranking, And Convolutional Neural Network For Computed Tomography Angiography. J Cardiovasc Comput Tomogr 2022. [DOI: 10.1016/j.jcct.2022.06.006] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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Zhou W, Wang L, Wang L, Wang YH, Zhao CY. [Cone-beam CT analysis of external root resorption of maxillary incisors before and after traction of impacted canines]. Zhonghua Kou Qiang Yi Xue Za Zhi 2022; 57:611-617. [PMID: 35692005 DOI: 10.3760/cma.j.cn112144-20210716-00332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To analyze the external root resorption of incisors caused by maxillary canine impaction, and to explore the changes of incisor external root resorption after orthodontic treatment. Methods: Twenty-four patients with impacted maxillary canines leading to external root resorption of incisors treated in Department of Orthodontics, Affiliated Hospital of Stomatology, Nanjing Medical University from July 2011 to January 2019 were selected. The age ranged from 10 to 14 years [(12.3±1.6) years], including 11 males and 14 females. The maxillary incisors with external root resorption before treatment were included in the resorption group (21 central incisors and 22 lateral incisors), and the maxillary incisors without external root resorption were used as the control group (26 central incisors and 21 lateral incisors). Cone-beam CT was taken before treatment, immediately after treatment and one year after treatment. At the one year follow-up 15 patients were collected (10 central incisors and 12 lateral incisors in the resorption group, while 16 central incisors and 12 lateral incisors in the control group). The root length and tooth volume of maxillary incisors were measured and analyzed before canine traction, after canine traction finished and at the one year follow-up. Results: After the treatment of maxillary impacted canines, the root length and volume of the central and lateral incisors in both resorption group and control group were significantly less than that before treatment (P<0.05). At the one year follow-up, the root length and volume of the incisors (central incisors in the resorption group and the central and lateral incisors in control group) were significantly less than those immediately after impacted canine traction (P<0.05). During the canine traction, the difference of the volume change in lateral incisors between the resorption group [(17±6) mm3] and the control group [(12±5) mm3] was statistically significant (t=2.51, P<0.05). During the one year follow-up period, the difference between the changes of the root length in maxillary central incisors in the resorption group [(0.5±0.4) mm] and in the control group [(0.2±0.1) mm] was statistically significant (t=2.35, P<0.05). Conclusions: For maxillary incisors with external root resorption caused by impacted maxillary canines, the external root resorption could not stop immediately after the treatment of impacted canines. The root resorption in maxillary lateral incisors mainly occured during the traction process, while the root resorption in maxillary central incisors existed during the orthodontic treatment and in the follow-up period.
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Affiliation(s)
- W Zhou
- Department of Orthodontics, Affiliated Hospital of Stomatology, Nanjing Medical University & Institute of Stomatology, Nanjing Medical University, Nanjing 210029, China
| | - L Wang
- Department of Orthodontics, Affiliated Hospital of Stomatology, Nanjing Medical University & Institute of Stomatology, Nanjing Medical University, Nanjing 210029, China
| | - L Wang
- Department of Orthodontics, Affiliated Hospital of Stomatology, Nanjing Medical University & Institute of Stomatology, Nanjing Medical University, Nanjing 210029, China
| | - Y H Wang
- Department of Orthodontics, Affiliated Hospital of Stomatology, Nanjing Medical University & Institute of Stomatology, Nanjing Medical University, Nanjing 210029, China
| | - C Y Zhao
- Department of Orthodontics, Affiliated Hospital of Stomatology, Nanjing Medical University & Institute of Stomatology, Nanjing Medical University, Nanjing 210029, China
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Iqbal W, Zhou W. Computational methods for single-cell DNA methylomes. Genomics, Proteomics & Bioinformatics 2022:S1672-0229(22)00074-2. [PMID: 35718270 PMCID: PMC10372927 DOI: 10.1016/j.gpb.2022.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 04/28/2022] [Accepted: 05/10/2022] [Indexed: 11/19/2022]
Abstract
Dissecting intercellular epigenetic differences is key to understanding tissue heterogeneity. Recent advances in single-cell DNA methylome profiling have presented opportunities to resolve this heterogeneity at the maximum resolution. While these advances enable us to explore frontiers of chromatin biology and better understand cell lineage relationships, they pose new challenges in data processing and interpretation. This review surveys the current state of computational tools developed for single-cell DNA methylome data analysis. We discuss critical components of single-cell DNA methylome data analysis, including data preprocessing, quality control, imputation, dimensionality reduction, cell clustering, supervised cell annotation, cell lineage reconstruction, gene activity scoring, and integration with transcriptome data. We also highlight unique aspects of single-cell DNA methylome data analysis and discuss how techniques common to other single-cell omics data analyses can be adapted to analyzing DNA methylomes. Finally, we discuss existing challenges and opportunities for future development.
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Affiliation(s)
- Waleed Iqbal
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Wanding Zhou
- Center for Computational and Genomic Medicine, 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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