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Jakubek YA, Ma X, Stilp AM, Yu F, Bacon J, Wong JW, Aguet F, Ardlie K, Arnett D, Barnes K, Bis JC, Blackwell T, Becker LC, Boerwinkle E, Bowler RP, Budoff MJ, Carson AP, Chen J, Cho MH, Coresh J, Cox N, de Vries PS, DeMeo DL, Fardo DW, Fornage M, Guo X, Hall ME, Heard-Costa N, Hidalgo B, Irvin MR, Johnson AD, Kenny EE, Levy D, Li Y, Lima JA, Liu Y, Loos RJF, Machiela MJ, Mathias RA, Mitchell BD, Murabito J, Mychaleckyj JC, North K, Orchard P, Parker SC, Pershad Y, Peyser PA, Pratte KA, Psaty BM, Raffield LM, Redline S, Rich SS, Rotter JI, Shah SJ, Smith JA, Smith AP, Smith A, Taub M, Tiwari HK, Tracy R, Tuftin B, Bick AG, Sankaran VG, Reiner AP, Scheet P, Auer PL. Genomic and phenotypic correlates of mosaic loss of chromosome Y in blood. medRxiv 2024:2024.04.16.24305851. [PMID: 38699360 PMCID: PMC11065036 DOI: 10.1101/2024.04.16.24305851] [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: 05/05/2024]
Abstract
Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer's disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program. This approach enabled us to identify differences in mLOY frequencies across populations defined by genetic similarity, revealing a higher frequency of mLOY in the European American (EA) ancestry group compared to those of Hispanic American (HA), African American (AA), and East Asian (EAS) ancestry. Further, we identified two genes ( CFHR1 and LRP6 ) that harbor multiple rare, putatively deleterious variants associated with mLOY susceptibility, show that subsets of human hematopoietic stem cells are enriched for activity of mLOY susceptibility variants, and that certain alleles on chromosome Y are more likely to be lost than others.
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Varshney A, Manickam N, Orchard P, Tovar A, Zhang Z, Feng F, Erdos MR, Narisu N, Ventresca C, Nishino K, Rai V, Stringham HM, Jackson AU, Tamsen T, Gao C, Yang M, Koues OI, Welch JD, Burant CF, Williams LK, Jenkinson C, DeFronzo RA, Norton L, Saramies J, Lakka TA, Laakso M, Tuomilehto J, Mohlke KL, Kitzman JO, Koistinen HA, Liu J, Boehnke M, Collins FS, Scott LJ, Parker SCJ. Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulation. bioRxiv 2023:2023.12.15.571696. [PMID: 38168419 PMCID: PMC10760134 DOI: 10.1101/2023.12.15.571696] [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] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Skeletal muscle, the largest human organ by weight, is relevant to several polygenic metabolic traits and diseases including type 2 diabetes (T2D). Identifying genetic mechanisms underlying these traits requires pinpointing the relevant cell types, regulatory elements, target genes, and causal variants. Here, we used genetic multiplexing to generate population-scale single nucleus (sn) chromatin accessibility (snATAC-seq) and transcriptome (snRNA-seq) maps across 287 frozen human skeletal muscle biopsies representing 456,880 nuclei. We identified 13 cell types that collectively represented 983,155 ATAC summits. We integrated genetic variation to discover 6,866 expression quantitative trait loci (eQTL) and 100,928 chromatin accessibility QTL (caQTL) (5% FDR) across the five most abundant cell types, cataloging caQTL peaks that atlas-level snATAC maps often miss. We identified 1,973 eGenes colocalized with caQTL and used mediation analyses to construct causal directional maps for chromatin accessibility and gene expression. 3,378 genome-wide association study (GWAS) signals across 43 relevant traits colocalized with sn-e/caQTL, 52% in a cell-specific manner. 77% of GWAS signals colocalized with caQTL and not eQTL, highlighting the critical importance of population-scale chromatin profiling for GWAS functional studies. GWAS-caQTL colocalization showed distinct cell-specific regulatory paradigms. For example, a C2CD4A/B T2D GWAS signal colocalized with caQTL in muscle fibers and multiple chromatin loop models nominated VPS13C, a glucose uptake gene. Sequence of the caQTL peak overlapping caSNP rs7163757 showed allelic regulatory activity differences in a human myocyte cell line massively parallel reporter assay. These results illuminate the genetic regulatory architecture of human skeletal muscle at high-resolution epigenomic, transcriptomic, and cell state scales and serve as a template for population-scale multi-omic mapping in complex tissues and traits.
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Affiliation(s)
- Arushi Varshney
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Nandini Manickam
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Peter Orchard
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Adelaide Tovar
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Zhenhao Zhang
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fan Feng
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Michael R Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Christa Ventresca
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Dept. of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kirsten Nishino
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Vivek Rai
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Heather M Stringham
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Anne U Jackson
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Tricia Tamsen
- Biomedical Research Core Facilities Advanced Genomics Core, University of Michigan, Ann Arbor, MI, USA
| | - Chao Gao
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Mao Yang
- Department of Internal Medicine, Center for Individualized and Genomic Medicine Research, Henry Ford Hospital, Detroit, MI, USA
| | - Olivia I Koues
- Biomedical Research Core Facilities Advanced Genomics Core, University of Michigan, Ann Arbor, MI, USA
| | - Joshua D Welch
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Charles F Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - L Keoki Williams
- Department of Internal Medicine, Center for Individualized and Genomic Medicine Research, Henry Ford Hospital, Detroit, MI, USA
| | - Chris Jenkinson
- South Texas Diabetes and Obesity Research Institute, School of Medicine, University of Texas, Rio Grande Valley, TX, USA
| | - Ralph A DeFronzo
- Department of Medicine/Diabetes Division, University of Texas Health, San Antonio, TX, USA
| | - Luke Norton
- Department of Medicine/Diabetes Division, University of Texas Health, San Antonio, TX, USA
| | - Jouko Saramies
- Savitaipale Health Center, South Karelia Central Hospital, Lappeenranta, Finland
| | - Timo A Lakka
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Jaakko Tuomilehto
- Dept. of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Dept. of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Karen L Mohlke
- Dept. of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Jacob O Kitzman
- Dept. of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Heikki A Koistinen
- Dept. of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Jie Liu
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Francis S Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Laura J Scott
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Stephen C J Parker
- Dept. of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Dept. of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
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Walker JT, Saunders DC, Rai V, Chen HH, Orchard P, Dai C, Pettway YD, Hopkirk AL, Reihsmann CV, Tao Y, Fan S, Shrestha S, Varshney A, Petty LE, Wright JJ, Ventresca C, Agarwala S, Aramandla R, Poffenberger G, Jenkins R, Mei S, Hart NJ, Phillips S, Kang H, Greiner DL, Shultz LD, Bottino R, Liu J, Below JE, Parker SCJ, Powers AC, Brissova M. Genetic risk converges on regulatory networks mediating early type 2 diabetes. Nature 2023; 624:621-629. [PMID: 38049589 DOI: 10.1038/s41586-023-06693-2] [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: 12/02/2021] [Accepted: 09/28/2023] [Indexed: 12/06/2023]
Abstract
Type 2 diabetes mellitus (T2D), a major cause of worldwide morbidity and mortality, is characterized by dysfunction of insulin-producing pancreatic islet β cells1,2. T2D genome-wide association studies (GWAS) have identified hundreds of signals in non-coding and β cell regulatory genomic regions, but deciphering their biological mechanisms remains challenging3-5. Here, to identify early disease-driving events, we performed traditional and multiplexed pancreatic tissue imaging, sorted-islet cell transcriptomics and islet functional analysis of early-stage T2D and control donors. By integrating diverse modalities, we show that early-stage T2D is characterized by β cell-intrinsic defects that can be proportioned into gene regulatory modules with enrichment in signals of genetic risk. After identifying the β cell hub gene and transcription factor RFX6 within one such module, we demonstrated multiple layers of genetic risk that converge on an RFX6-mediated network to reduce insulin secretion by β cells. RFX6 perturbation in primary human islet cells alters β cell chromatin architecture at regions enriched for T2D GWAS signals, and population-scale genetic analyses causally link genetically predicted reduced RFX6 expression with increased T2D risk. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs and individuals, and thus we anticipate that this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits using GWAS data.
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Affiliation(s)
- John T Walker
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Diane C Saunders
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Vivek Rai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chunhua Dai
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yasminye D Pettway
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Alexander L Hopkirk
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Conrad V Reihsmann
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yicheng Tao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Simin Fan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Shristi Shrestha
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jordan J Wright
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christa Ventresca
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Samir Agarwala
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Radhika Aramandla
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Greg Poffenberger
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Regina Jenkins
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shaojun Mei
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nathaniel J Hart
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sharon Phillips
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dale L Greiner
- Department of Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, MA, USA
| | | | - Rita Bottino
- Imagine Pharma, Devon, PA, USA
- Institute of Cellular Therapeutics, Allegheny-Singer Research Institute, Allegheny Health Network, Pittsburgh, PA, USA
| | - Jie Liu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
| | - Alvin C Powers
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA.
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- VA Tennessee Valley Healthcare System, Nashville, TN, USA.
| | - Marcela Brissova
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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Zhao Z, D’Oliveira Albanus R, Taylor H, Tang X, Han Y, Orchard P, Varshney A, Zhang T, Manickam N, Erdos M, Narisu N, Taylor L, Saavedra X, Zhong A, Li B, Zhou T, Naji A, Liu C, Collins F, Parker SCJ, Chen S. An integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D associated genes and regulatory signals. Res Sq 2023:rs.3.rs-3343318. [PMID: 37886586 PMCID: PMC10602166 DOI: 10.21203/rs.3.rs-3343318/v1] [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] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Genome wide association studies (GWAS) have identified over 100 signals associated with type 1 diabetes (T1D). However, translating any given T1D GWAS signal into mechanistic insights, including putative causal variants and the context (cell type and cell state) in which they function, has been limited. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in healthy and autoantibody+ (AAB+) human islets, as well as islets under multiple T1D stimulatory conditions. We broadly nominate effector cell types for all T1D GWAS signals. We further nominated higher-resolution contexts, including effector cell types, regulatory elements, and genes for three independent T1D risk variants acting through islet cells within the pancreas at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we created isogenic gene knockouts DLK1-/-, RASGRP1-/-, and TOX-/-, and the corresponding regulatory region knockout, RASGRP1Δ, and DLK1Δ hESCs. Loss of RASGRP1 or DLK1, as well as knockout of the regulatory region of RASGRP1 or DLK1, increased β cell apoptosis. Additionally, pancreatic β cells derived from isogenic hESCs carrying the risk allele of rs3783355A/A exhibited increased β cell death. Finally, RNA-seq and ATAC-seq identified five genes upregulated in both RASGRP1-/- and DLK1-/- β-like cells, four of which are associated with T1D. Together, this work reports an integrative approach for combining single cell multi-omics, GWAS, and isogenic hESC-derived β-like cells to prioritize the T1D associated signals and their underlying context-specific cell types, genes, SNPs, and regulatory elements, to illuminate biological functions and molecular mechanisms.
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Affiliation(s)
- Zeping Zhao
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | | | - Henry Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xuming Tang
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Yuling Han
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Tuo Zhang
- Stem Cell Research Facility, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Nandini Manickam
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Mike Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Leland Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaxia Saavedra
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Aaron Zhong
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Bo Li
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Ting Zhou
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Ali Naji
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Chengyang Liu
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Francis Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Stephen CJ Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
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5
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Behera S, LeFaive J, Orchard P, Mahmoud M, Paulin LF, Farek J, Soto DC, Parker SCJ, Smith AV, Dennis MY, Zook JM, Sedlazeck FJ. FixItFelix: improving genomic analysis by fixing reference errors. Genome Biol 2023; 24:31. [PMID: 36810122 PMCID: PMC9942314 DOI: 10.1186/s13059-023-02863-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 01/20/2023] [Indexed: 02/23/2023] Open
Abstract
The current version of the human reference genome, GRCh38, contains a number of errors including 1.2 Mbp of falsely duplicated and 8.04 Mbp of collapsed regions. These errors impact the variant calling of 33 protein-coding genes, including 12 with medical relevance. Here, we present FixItFelix, an efficient remapping approach, together with a modified version of the GRCh38 reference genome that improves the subsequent analysis across these genes within minutes for an existing alignment file while maintaining the same coordinates. We showcase these improvements over multi-ethnic control samples, demonstrating improvements for population variant calling as well as eQTL studies.
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Affiliation(s)
- Sairam Behera
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jonathon LeFaive
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Luis F Paulin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jesse Farek
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Daniela C Soto
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, CA, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Albert V Smith
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Megan Y Dennis
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, CA, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
- Department of Computer Science, Rice University, Houston, TX, USA.
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6
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Huang S, Lund T, Orchard P, Gupta A, Nascene D. Dilated Optic Nerve Sheath in Mucopolysaccharidosis I: Common and Not Necessarily High Intracranial Pressure. AJNR Am J Neuroradiol 2023; 44:91-94. [PMID: 36581456 PMCID: PMC9835902 DOI: 10.3174/ajnr.a7755] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 12/05/2022] [Indexed: 12/31/2022]
Abstract
Hydrocephalus is one of the earliest manifestations of mucopolysaccharidosis I-Hurler syndrome, and delayed treatment of hydrocephalus can lead to neurocognitive delay or even death. Optic nerve sheath diameter has been established as a noninvasive measurement to detect elevated intracranial pressure. This study aimed to establish correlations between optic nerve sheath diameter and opening pressure. Forty-nine MR images and opening pressures in patients with mucopolysaccharidosis I-Hurler syndrome were retrospectively reviewed from 2008 to 2020. The optic nerve sheath diameter was measured 3 mm posterior to the posterior margin of the globe (retrobulbar) and 10 mm anterior to the optic foramen (midpoint segment), and the average was taken between the 2 eyes. Opening pressure was measured with the patient in the lateral decubitus position with controlled end-tidal CO2 on the same day as the MR imaging. The average retrobulbar optic nerve sheath diameter was 5.33 mm, higher than the previously reported measurement in healthy controls, in patients with idiopathic intracranial hypertension, and there was a positive correlation between age and the optic nerve sheath diameter measured at the retrobulbar or midpoint segment (retrobulbar segment, R 2 = 0.27, P < .01; midpoint segment, R 2 = 0.20, P < .01). However, there was no correlation between retrobulbar or midpoint segment optic nerve sheath diameter and opening pressure (retrobulbar segment, R 2 = 0.02, P = .17; midpoint segment, R 2 = 0.03, P < .12). This study shows a higher average optic nerve sheath diameter in patients with mucopolysaccharidosis I-Hurler syndrome than in healthy controls regardless of the location of the measurement. However, the degree of optic nerve sheath dilation does not correlate with opening pressure, suggesting that increased optic nerve sheath diameter is an ocular manifestation of mucopolysaccharidosis I-Hurler syndrome itself rather than a marker of elevated intracranial pressure.
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Affiliation(s)
- S Huang
- From the Department of Neurosurgery (S.H.)
| | - T Lund
- Division of Pediatric Blood and Marrow Transplant (T.L., P.O., A.G.)
| | - P Orchard
- Division of Pediatric Blood and Marrow Transplant (T.L., P.O., A.G.)
| | - A Gupta
- Division of Pediatric Blood and Marrow Transplant (T.L., P.O., A.G.)
| | - D Nascene
- Department of Radiology (D.N.), University of Minnesota, Minneapolis, Minnesota
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7
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Qin T, Lee C, Li S, Cavalcante RG, Orchard P, Yao H, Zhang H, Wang S, Patil S, Boyle AP, Sartor MA. Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data. Genome Biol 2022; 23:105. [PMID: 35473573 PMCID: PMC9044877 DOI: 10.1186/s13059-022-02668-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 04/06/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Revealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1860 human genome-wide distal enhancer-to-target gene definitions (EnTDefs). To evaluate performance, we used gene set enrichment (GSE) testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology annotations, and other benchmarks. RESULTS The top ranked 741 (40%) EnTDefs significantly outperform the common, naïve approach of linking distal regions to the nearest genes, and the top 10 EnTDefs perform well when applied to ChIP-seq data of other cell types. The GSE-based ranking of EnTDefs is highly concordant with ranking based on overlap with curated benchmarks of enhancer-gene interactions. Both our top general EnTDef and cell-type-specific EnTDefs significantly outperform seven independent computational and experiment-based enhancer-gene pair datasets. We show that using our top EnTDefs for GSE with either genome-wide DNA methylation or ATAC-seq data is able to better recapitulate the biological processes changed in gene expression data performed in parallel for the same experiment than our lower-ranked EnTDefs. CONCLUSIONS Our findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.
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Affiliation(s)
- Tingting Qin
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
| | - Christopher Lee
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Biostatistics, School of Public Health, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Shiting Li
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Raymond G Cavalcante
- Biomedical Research Core Facilities, Epigenomics Core, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Heming Yao
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Hanrui Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Shuze Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Snehal Patil
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Alan P Boyle
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Maureen A Sartor
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
- Department of Biostatistics, School of Public Health, University of Michigan Medical School, Ann Arbor, MI, USA.
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8
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Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res 2021; 31:2258-2275. [PMID: 34815310 PMCID: PMC8647829 DOI: 10.1101/gr.268482.120] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 09/16/2021] [Indexed: 12/12/2022]
Abstract
Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 33,862 nuclei and identify seven cell types ranging in abundance from 59.6% to 1.0% of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site-distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome-wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells (∼3.5% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, transcription factor motifs, and target genes for type 2 diabetes signals. These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for nominating causal GWAS SNPs and cell types.
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Affiliation(s)
- Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Nandini Manickam
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Christa Ventresca
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Swarooparani Vadlamudi
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Vivek Rai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Jeremy Kaplan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Claudia Lalancette
- Epigenomics Core, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Katherine Gallagher
- Department of Surgery, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Charles F Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
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9
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Varshney A, Kyono Y, Elangovan VR, Wang C, Erdos MR, Narisu N, Albanus RD, Orchard P, Stitzel ML, Collins FS, Kitzman JO, Parker SCJ. A Transcription Start Site Map in Human Pancreatic Islets Reveals Functional Regulatory Signatures. Diabetes 2021; 70:1581-1591. [PMID: 33849996 PMCID: PMC8336006 DOI: 10.2337/db20-1087] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 04/09/2021] [Indexed: 12/21/2022]
Abstract
Identifying the tissue-specific molecular signatures of active regulatory elements is critical to understand gene regulatory mechanisms. Here, we identify transcription start sites (TSS) using cap analysis of gene expression (CAGE) across 57 human pancreatic islet samples. We identify 9,954 reproducible CAGE tag clusters (TCs), ∼20% of which are islet specific and occur mostly distal to known gene TSS. We integrated islet CAGE data with histone modification and chromatin accessibility profiles to identify epigenomic signatures of transcription initiation. Using a massively parallel reporter assay, we validated the transcriptional enhancer activity for 2,279 of 3,378 (∼68%) tested islet CAGE elements (5% false discovery rate). TCs within accessible enhancers show higher enrichment to overlap type 2 diabetes genome-wide association study (GWAS) signals than existing islet annotations, which emphasizes the utility of mapping CAGE profiles in disease-relevant tissue. This work provides a high-resolution map of transcriptional initiation in human pancreatic islets with utility for dissecting active enhancers at GWAS loci.
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Affiliation(s)
- Arushi Varshney
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI
- Department of Human Genetics, University of Michigan, Ann Arbor, MI
| | - Yasuhiro Kyono
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI
| | | | - Collin Wang
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI
| | - Michael R Erdos
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Narisu Narisu
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | | | - Peter Orchard
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI
| | | | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Jacob O Kitzman
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI
- Department of Human Genetics, University of Michigan, Ann Arbor, MI
| | - Stephen C J Parker
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI
- Department of Human Genetics, University of Michigan, Ann Arbor, MI
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10
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Currin KW, Erdos MR, Narisu N, Rai V, Vadlamudi S, Perrin HJ, Idol JR, Yan T, Albanus RD, Broadaway KA, Etheridge AS, Bonnycastle LL, Orchard P, Didion JP, Chaudhry AS, Innocenti F, Schuetz EG, Scott LJ, Parker SCJ, Collins FS, Mohlke KL. Genetic effects on liver chromatin accessibility identify disease regulatory variants. Am J Hum Genet 2021; 108:1169-1189. [PMID: 34038741 PMCID: PMC8323023 DOI: 10.1016/j.ajhg.2021.05.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 05/04/2021] [Indexed: 02/02/2023] Open
Abstract
Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTLs) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTLs have been identified in a limited set of human tissues. Here we mapped caQTLs in human liver tissue in 20 liver samples and identified 3,123 caQTLs. The caQTL variants are enriched in liver tissue promoter and enhancer states and frequently disrupt binding motifs of transcription factors expressed in liver. We predicted target genes for 861 caQTL peaks using proximity, chromatin interactions, correlation with promoter accessibility or gene expression, and colocalization with expression QTLs. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTLs and GWAS signals, 56 of which contained a predicted caPeak target gene. At the LITAF LDL-cholesterol GWAS locus, we validated that a caQTL variant showed allelic differences in protein binding and transcriptional activity. These caQTLs contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci.
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Affiliation(s)
- Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Michael R Erdos
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Vivek Rai
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Hannah J Perrin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Jacqueline R Idol
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Tingfen Yan
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - K Alaine Broadaway
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Amy S Etheridge
- Eshelman School of Pharmacy and Center for Pharmacogenomics and Individualized Therapy, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Lori L Bonnycastle
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Peter Orchard
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - John P Didion
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Amarjit S Chaudhry
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Federico Innocenti
- Eshelman School of Pharmacy and Center for Pharmacogenomics and Individualized Therapy, University of North Carolina, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Erin G Schuetz
- Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Stephen C J Parker
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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11
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D'Oliveira Albanus R, Kyono Y, Hensley J, Varshney A, Orchard P, Kitzman JO, Parker SCJ. Chromatin information content landscapes inform transcription factor and DNA interactions. Nat Commun 2021; 12:1307. [PMID: 33637709 PMCID: PMC7910283 DOI: 10.1038/s41467-021-21534-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 01/29/2021] [Indexed: 01/31/2023] Open
Abstract
Interactions between transcription factors and chromatin are fundamental to genome organization and regulation and, ultimately, cell state. Here, we use information theory to measure signatures of organized chromatin resulting from transcription factor-chromatin interactions encoded in the patterns of the accessible genome, which we term chromatin information enrichment (CIE). We calculate CIE for hundreds of transcription factor motifs across human samples and identify two classes: low and high CIE. The 10-20% of common and tissue-specific high CIE transcription factor motifs, associate with higher protein-DNA residence time, including different binding site subclasses of the same transcription factor, increased nucleosome phasing, specific protein domains, and the genetic control of both chromatin accessibility and gene expression. These results show that variations in the information encoded in chromatin architecture reflect functional biological variation, with implications for cell state dynamics and memory.
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Affiliation(s)
| | - Yasuhiro Kyono
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, USA
- Tempus Labs, Inc. Chicago, IL, Chicago, USA
| | - John Hensley
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA
| | - Arushi Varshney
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA
| | - Peter Orchard
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA
| | - Jacob O Kitzman
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, USA
| | - Stephen C J Parker
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, USA.
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12
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Viñuela A, Varshney A, van de Bunt M, Prasad RB, Asplund O, Bennett A, Boehnke M, Brown AA, Erdos MR, Fadista J, Hansson O, Hatem G, Howald C, Iyengar AK, Johnson P, Krus U, MacDonald PE, Mahajan A, Manning Fox JE, Narisu N, Nylander V, Orchard P, Oskolkov N, Panousis NI, Payne A, Stitzel ML, Vadlamudi S, Welch R, Collins FS, Mohlke KL, Gloyn AL, Scott LJ, Dermitzakis ET, Groop L, Parker SCJ, McCarthy MI. Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D. Nat Commun 2020; 11:4912. [PMID: 32999275 PMCID: PMC7528108 DOI: 10.1038/s41467-020-18581-8] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 08/12/2020] [Indexed: 02/08/2023] Open
Abstract
Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.
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Affiliation(s)
- Ana Viñuela
- grid.8591.50000 0001 2322 4988Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland ,grid.8591.50000 0001 2322 4988Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland ,grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland ,grid.1006.70000 0001 0462 7212Biosciences Institute, Faculty of Medical Sciences, Newcastle University, NE1 4EP Newcastle, UK
| | - Arushi Varshney
- grid.214458.e0000000086837370Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Martijn van de Bunt
- grid.4991.50000 0004 1936 8948Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN UK ,grid.4991.50000 0004 1936 8948Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7LE UK ,grid.410556.30000 0001 0440 1440Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, OX3 7LE UK
| | - Rashmi B. Prasad
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Olof Asplund
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Amanda Bennett
- grid.4991.50000 0004 1936 8948Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN UK
| | - Michael Boehnke
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Andrew A. Brown
- grid.8591.50000 0001 2322 4988Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland ,grid.8591.50000 0001 2322 4988Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland ,grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland ,grid.8241.f0000 0004 0397 2876Population Health and Genomics, University of Dundee, Dundee, Scotland, DD1 9SY UK
| | - Michael R. Erdos
- grid.280128.10000 0001 2233 9230Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892 USA
| | - João Fadista
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden ,grid.6203.70000 0004 0417 4147Department of Epidemiology Research, Statens Serum Institut, Copenhagen, DK 2300 Denmark ,grid.7737.40000 0004 0410 2071Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
| | - Ola Hansson
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden ,grid.7737.40000 0004 0410 2071Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
| | - Gad Hatem
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Cédric Howald
- grid.8591.50000 0001 2322 4988Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland ,grid.8591.50000 0001 2322 4988Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland ,grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Apoorva K. Iyengar
- grid.410711.20000 0001 1034 1720Department of Genetics, University of North Carolina, Chapel Hill, NC 27599 USA
| | - Paul Johnson
- grid.4991.50000 0004 1936 8948Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN UK
| | - Ulrika Krus
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Patrick E. MacDonald
- grid.17089.37Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta Canada
| | - Anubha Mahajan
- grid.4991.50000 0004 1936 8948Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN UK ,grid.418158.10000 0004 0534 4718Present Address: Human Genetics, Genentech, 1 DNA Way, South San Francisco, CA 94080 USA
| | - Jocelyn E. Manning Fox
- grid.17089.37Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta Canada
| | - Narisu Narisu
- grid.280128.10000 0001 2233 9230Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892 USA
| | - Vibe Nylander
- grid.4991.50000 0004 1936 8948Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7LE UK
| | - Peter Orchard
- grid.214458.e0000000086837370Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Nikolay Oskolkov
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Nikolaos I. Panousis
- grid.8591.50000 0001 2322 4988Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland ,grid.8591.50000 0001 2322 4988Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland ,grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Anthony Payne
- grid.4991.50000 0004 1936 8948Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN UK
| | - Michael L. Stitzel
- grid.249880.f0000 0004 0374 0039The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032 USA ,grid.63054.340000 0001 0860 4915Department of Genetics and Genome Sciences, Institute for Systems Genomics, University of Connecticut, Farmington, CT 06032 USA
| | - Swarooparani Vadlamudi
- grid.410711.20000 0001 1034 1720Department of Genetics, University of North Carolina, Chapel Hill, NC 27599 USA
| | - Ryan Welch
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Francis S. Collins
- grid.280128.10000 0001 2233 9230Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892 USA
| | - Karen L. Mohlke
- grid.410711.20000 0001 1034 1720Department of Genetics, University of North Carolina, Chapel Hill, NC 27599 USA
| | - Anna L. Gloyn
- grid.4991.50000 0004 1936 8948Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN UK ,grid.4991.50000 0004 1936 8948Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7LE UK ,grid.410556.30000 0001 0440 1440Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, OX3 7LE UK ,grid.168010.e0000000419368956Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford University, Stanford, CA USA
| | - Laura J. Scott
- grid.214458.e0000000086837370Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Emmanouil T. Dermitzakis
- grid.8591.50000 0001 2322 4988Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland ,grid.8591.50000 0001 2322 4988Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland ,grid.419765.80000 0001 2223 3006Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Leif Groop
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden ,grid.7737.40000 0004 0410 2071Finnish Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
| | - Stephen C. J. Parker
- grid.214458.e0000000086837370Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109 USA ,grid.214458.e0000000086837370Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109 USA
| | - Mark I. McCarthy
- grid.4991.50000 0004 1936 8948Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN UK ,grid.4991.50000 0004 1936 8948Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7LE UK ,grid.410556.30000 0001 0440 1440Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, OX3 7LE UK ,grid.418158.10000 0004 0534 4718Present Address: Human Genetics, Genentech, 1 DNA Way, South San Francisco, CA 94080 USA
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13
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Liu T, Mi L, Xiong J, Orchard P, Yu Q, Yu L, Zhao XY, Meng ZX, Parker SCJ, Lin JD, Li S. BAF60a deficiency uncouples chromatin accessibility and cold sensitivity from white fat browning. Nat Commun 2020; 11:2379. [PMID: 32404872 PMCID: PMC7221096 DOI: 10.1038/s41467-020-16148-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 03/19/2020] [Indexed: 02/08/2023] Open
Abstract
Brown and beige fat share a remarkably similar transcriptional program that supports fuel oxidation and thermogenesis. The chromatin-remodeling machinery that governs genome accessibility and renders adipocytes poised for thermogenic activation remains elusive. Here we show that BAF60a, a subunit of the SWI/SNF chromatin-remodeling complexes, serves an indispensable role in cold-induced thermogenesis in brown fat. BAF60a maintains chromatin accessibility at PPARγ and EBF2 binding sites for key thermogenic genes. Surprisingly, fat-specific BAF60a inactivation triggers more pronounced cold-induced browning of inguinal white adipose tissue that is linked to induction of MC2R, a receptor for the pituitary hormone ACTH. Elevated MC2R expression sensitizes adipocytes and BAF60a-deficient adipose tissue to thermogenic activation in response to ACTH stimulation. These observations reveal an unexpected dichotomous role of BAF60a-mediated chromatin remodeling in transcriptional control of brown and beige gene programs and illustrate a pituitary-adipose signaling axis in the control of thermogenesis.
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MESH Headings
- Adipocytes, Brown/drug effects
- Adipocytes, Brown/metabolism
- Adipocytes, Brown/ultrastructure
- Adipose Tissue, Beige/metabolism
- Adipose Tissue, Brown/drug effects
- Adipose Tissue, Brown/metabolism
- Adipose Tissue, White/drug effects
- Adipose Tissue, White/metabolism
- Adrenocorticotropic Hormone/pharmacology
- Animals
- Basic Helix-Loop-Helix Transcription Factors/metabolism
- Binding Sites/genetics
- Cells, Cultured
- Chromatin/genetics
- Chromatin/metabolism
- Chromosomal Proteins, Non-Histone/deficiency
- Chromosomal Proteins, Non-Histone/genetics
- Cold Temperature
- Gene Expression/drug effects
- Membrane Proteins/genetics
- Membrane Proteins/metabolism
- Mice, Inbred C57BL
- Mice, Knockout
- Mice, Transgenic
- Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha/metabolism
- Thermogenesis/drug effects
- Thermogenesis/genetics
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Affiliation(s)
- Tongyu Liu
- Life Sciences Institute and Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Lin Mi
- Life Sciences Institute and Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jing Xiong
- Life Sciences Institute and Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Qi Yu
- Life Sciences Institute and Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Lei Yu
- Life Sciences Institute and Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Xu-Yun Zhao
- Life Sciences Institute and Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Zhuo-Xian Meng
- Department of Pathology and Pathophysiology, Key Laboratory of Disease Proteomics of Zhejiang Province, Hangzhou, Zhejiang, 310058, China
- Chronic Disease Research Institute of School of Public Health, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310058, China
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jiandie D Lin
- Life Sciences Institute and Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA.
| | - Siming Li
- Life Sciences Institute and Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, 48109, USA.
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14
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Lawlor N, Márquez EJ, Orchard P, Narisu N, Shamim MS, Thibodeau A, Varshney A, Kursawe R, Erdos MR, Kanke M, Gu H, Pak E, Dutra A, Russell S, Li X, Piecuch E, Luo O, Chines PS, Fuchbserger C, Sethupathy P, Aiden AP, Ruan Y, Aiden EL, Collins FS, Ucar D, Parker SCJ, Stitzel ML. Multiomic Profiling Identifies cis-Regulatory Networks Underlying Human Pancreatic β Cell Identity and Function. Cell Rep 2020; 26:788-801.e6. [PMID: 30650367 PMCID: PMC6389269 DOI: 10.1016/j.celrep.2018.12.083] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 10/26/2018] [Accepted: 12/18/2018] [Indexed: 12/22/2022] Open
Abstract
EndoC-βH1 is emerging as a critical human β cell model to study the genetic and environmental etiologies of β cell (dys)function and diabetes. Comprehensive knowledge of its molecular landscape is lacking, yet required, for effective use of this model. Here, we report chromosomal (spectral karyotyping), genetic (genotyping), epigenomic (ChIP-seq and ATAC-seq), chromatin interaction (Hi-C and Pol2 ChIA-PET), and transcriptomic (RNA-seq and miRNA-seq) maps of EndoC-βH1. Analyses of these maps define known (e.g., PDX1 and ISL1) and putative (e.g., PCSK1 and mir-375) β cell-specific transcriptional cis-regulatory networks and identify allelic effects on cis-regulatory element use. Importantly, comparison with maps generated in primary human islets and/or β cells indicates preservation of chromatin looping but also highlights chromosomal aberrations and fetal genomic signatures in EndoC-βH1. Together, these maps, and a web application we created for their exploration, provide important tools for the design of experiments to probe and manipulate the genetic programs governing β cell identity and (dys)function in diabetes. EndoC-βH1 is becoming an important cellular model to study genes and pathways governing human β cell identity and function, but its (epi)genomic similarity to primary human islets is unknown. Lawlor et al. complete and compare extensive EndoC and primary human islet multiomic maps to identify shared and distinct genomic circuitry.
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Affiliation(s)
- Nathan Lawlor
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Eladio J Márquez
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Narisu Narisu
- National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Muhammad Saad Shamim
- Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Medical Scientist Training Program, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Department of Computational and Applied Mathematics, Rice University, Houston, TX 77030, USA; Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Asa Thibodeau
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Arushi Varshney
- Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Romy Kursawe
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Michael R Erdos
- National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Matt Kanke
- Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Huiya Gu
- Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Evgenia Pak
- National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Amalia Dutra
- National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Sheikh Russell
- Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Department of Computational and Applied Mathematics, Rice University, Houston, TX 77030, USA
| | - Xingwang Li
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Emaly Piecuch
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT 06032, USA
| | - Oscar Luo
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Peter S Chines
- National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Christian Fuchbserger
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Praveen Sethupathy
- Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Aviva Presser Aiden
- Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Bioengineering, Rice University, Houston, TX 77030, USA; Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yijun Ruan
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA
| | - Erez Lieberman Aiden
- Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Department of Computational and Applied Mathematics, Rice University, Houston, TX 77030, USA; Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA; Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Francis S Collins
- National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Duygu Ucar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT 06032, USA; Institute for Systems Genomics, University of Connecticut, Farmington, CT 06032, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Michael L Stitzel
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA; Department of Genetics and Genome Sciences, University of Connecticut, Farmington, CT 06032, USA; Institute for Systems Genomics, University of Connecticut, Farmington, CT 06032, USA.
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15
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Orchard P, White JS, Thomas PE, Mychalowych A, Kiseleva A, Hensley J, Allen B, Parker SCJ, Keegan CE. Genome-wide chromatin accessibility and transcriptome profiling show minimal epigenome changes and coordinated transcriptional dysregulation of hedgehog signaling in Danforth's short tail mice. Hum Mol Genet 2020; 28:736-750. [PMID: 30380057 DOI: 10.1093/hmg/ddy378] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 10/23/2018] [Accepted: 10/26/2018] [Indexed: 12/20/2022] Open
Abstract
Danforth's short tail (Sd) mice provide an excellent model for investigating the underlying etiology of human caudal birth defects, which affect 1 in 10 000 live births. Sd animals exhibit aberrant axial skeleton, urogenital and gastrointestinal development similar to human caudal malformation syndromes including urorectal septum malformation, caudal regression, vertebral-anal-cardiac-tracheo-esophageal fistula-renal-limb (VACTERL) association and persistent cloaca. Previous studies have shown that the Sd mutation results from an endogenous retroviral (ERV) insertion upstream of the Ptf1a gene resulting in its ectopic expression at E9.5. Though the genetic lesion has been determined, the resulting epigenomic and transcriptomic changes driving the phenotype have not been investigated. Here, we performed ATAC-seq experiments on isolated E9.5 tailbud tissue, which revealed minimal changes in chromatin accessibility in Sd/Sd mutant embryos. Interestingly, chromatin changes were localized to a small interval adjacent to the Sd ERV insertion overlapping a known Ptf1a enhancer region, which is conserved in mice and humans. Furthermore, mRNA-seq experiments revealed increased transcription of Ptf1a target genes and, importantly, downregulation of hedgehog pathway genes. Reduced sonic hedgehog (SHH) signaling was confirmed by in situ hybridization and immunofluorescence suggesting that the Sd phenotype results, in part, from downregulated SHH signaling. Taken together, these data demonstrate substantial transcriptome changes in the Sd mouse, and indicate that the effect of the ERV insertion on Ptf1a expression may be mediated by increased chromatin accessibility at a conserved Ptf1a enhancer. We propose that human caudal dysgenesis disorders may result from dysregulation of hedgehog signaling pathways.
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Affiliation(s)
- Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - James S White
- Department of Pediatrics, Division of Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Peedikayil E Thomas
- Department of Pediatrics, Division of Genetics, University of Michigan, Ann Arbor, MI, USA.,Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Anna Mychalowych
- Department of Pediatrics, Division of Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Anya Kiseleva
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - John Hensley
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Benjamin Allen
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.,Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Catherine E Keegan
- Department of Pediatrics, Division of Genetics, University of Michigan, Ann Arbor, MI, USA.,Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
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16
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Patterson P, Orchard P, Friedsam J, Schiena E, Ellis S. Supporting Cancer Patients Who Are Also Parents: Establishment of a Cross-Sector Service for Families With Adolescent and Young Adult Children. J Glob Oncol 2018. [DOI: 10.1200/jgo.18.96800] [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: 11/20/2022] Open
Abstract
Background and context: Traditionally adult hospitals focus on the patient and less on their family. Adolescent and young adult children of cancer patients (AYA offspring) have significant psychosocial burdens associated with their parent's cancer however they are often invisible within hospitals with no clear referral pathways to community-based support. AYA offspring are 3-6 times more likely than peers to have clinically elevated levels of distress which increases with age. Research shows that 1 of the greatest concerns for parents is how to communicate about cancer with their children, and 1 of the greatest needs for AYA offspring is information about their parent's cancer and talking with their parents about it. Aim: CanTeen, a national AYA cancer community support organization, sought to address these needs by embedding a Parent Support Worker within the social work teams of tertiary hospitals for patients who are parents of AYA children. This service aims to assist with specific parenting challenges that arise due to a cancer diagnosis and establish a referral pathway for AYA offspring to CanTeen for support. Strategy/Tactics: Cofunding with philanthropic organizations was sought and CanTeen executives engaged in advocacy work with senior hospital management, demonstrating the need for the service and a plan to embed it within the existing hospital social work team and services. Program/Policy process: A new Parent Support Worker role was established to provide social work care to parents of AYA children following a parent's cancer diagnosis. The service provides support with parenting issues that arise due to the diagnosis as well as staff education, secondary consultations, and referrals of AYA offspring to CanTeen. A service improvement approach has been established with the collection of monitoring data measuring volume of referrals/sessions, capacity building of other staff, information given to young people and referrals to CanTeen. A service evaluation seeking feedback from patients and relevant hospital staff is also underway. Outcomes: To date, philanthropic funding and hospital support was gained to establish a pilot program placing a Parent Support Worker in 3 hospitals. Early indications are that this novel service is integrating well into established hospital teams and processes, and adding considerable value with the provision of this focused family support. What was learned: This advocacy initiative is highlighting the benefits of a model of care in adult hospitals that centrally considers family and the strength of a well-planned cross-sector service initiative.
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Affiliation(s)
- P. Patterson
- CanTeen Australia, Newtown, Australia
- The University of Sydney, Sydney, Australia
| | | | | | - E. Schiena
- Peter MacCallum Cancer Centre, Melbourne, Australia
| | - S. Ellis
- Peter MacCallum Cancer Centre, Melbourne, Australia
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17
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Orchard P, Agakova A, Pinnock H, Burton CD, Sarran C, Agakov F, McKinstry B. Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data. J Med Internet Res 2018; 20:e263. [PMID: 30249589 PMCID: PMC6231768 DOI: 10.2196/jmir.9227] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Revised: 04/19/2018] [Accepted: 06/18/2018] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Telemonitoring of symptoms and physiological signs has been suggested as a means of early detection of chronic obstructive pulmonary disease (COPD) exacerbations, with a view to instituting timely treatment. However, algorithms to identify exacerbations result in frequent false-positive results and increased workload. Machine learning, when applied to predictive modelling, can determine patterns of risk factors useful for improving prediction quality. OBJECTIVE Our objectives were to (1) establish whether machine learning techniques applied to telemonitoring datasets improve prediction of hospital admissions and decisions to start corticosteroids, and (2) determine whether the addition of weather data further improves such predictions. METHODS We used daily symptoms, physiological measures, and medication data, with baseline demography, COPD severity, quality of life, and hospital admissions from a pilot and large randomized controlled trial of telemonitoring in COPD. We linked weather data from the United Kingdom meteorological service. We used feature selection and extraction techniques for time series to construct up to 153 predictive patterns (features) from symptom, medication, and physiological measurements. We used the resulting variables to construct predictive models fitted to training sets of patients and compared them with common symptom-counting algorithms. RESULTS We had a mean 363 days of telemonitoring data from 135 patients. The two most practical traditional score-counting algorithms, restricted to cases with complete data, resulted in area under the receiver operating characteristic curve (AUC) estimates of 0.60 (95% CI 0.51-0.69) and 0.58 (95% CI 0.50-0.67) for predicting admissions based on a single day's readings. However, in a real-world scenario allowing for missing data, with greater numbers of patient daily data and hospitalizations (N=57,150, N+=55, respectively), the performance of all the traditional algorithms fell, including those based on 2 days' data. One of the most frequently used algorithms performed no better than chance. All considered machine learning models demonstrated significant improvements; the best machine learning algorithm based on 57,150 episodes resulted in an aggregated AUC of 0.74 (95% CI 0.67-0.80). Adding weather data measurements did not improve the predictive performance of the best model (AUC 0.74, 95% CI 0.69-0.79). To achieve an 80% true-positive rate (sensitivity), the traditional algorithms were associated with an 80% false-positive rate: our algorithm halved this rate to approximately 40% (specificity approximately 60%). The machine learning algorithm was moderately superior to the best symptom-counting algorithm (AUC 0.77, 95% CI 0.74-0.79 vs AUC 0.66, 95% CI 0.63-0.68) at predicting the need for corticosteroids. CONCLUSIONS Early detection and management of COPD remains an important goal given its huge personal and economic costs. Machine learning approaches, which can be tailored to an individual's baseline profile and can learn from experience of the individual patient, are superior to existing predictive algorithms and show promise in achieving this goal. TRIAL REGISTRATION International Standard Randomized Controlled Trial Number ISRCTN96634935; http://www.isrctn.com/ISRCTN96634935 (Archived by WebCite at http://www.webcitation.org/722YkuhAz).
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Affiliation(s)
| | | | - Hilary Pinnock
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | | | | | | | - Brian McKinstry
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom
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18
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Taylor JC, Bongartz T, Massey J, Mifsud B, Spiliopoulou A, Scott IC, Wang J, Morgan M, Plant D, Colombo M, Orchard P, Twigg S, McInnes IB, Porter D, Freeston JE, Nam JL, Cordell HJ, Isaacs JD, Strathdee JL, Arnett D, de Hair MJH, Tak PP, Aslibekyan S, van Vollenhoven RF, Padyukov L, Bridges SL, Pitzalis C, Cope AP, Verstappen SMM, Emery P, Barnes MR, Agakov F, McKeigue P, Mushiroda T, Kubo M, Weinshilboum R, Barton A, Morgan AW, Barrett JH. Genome-wide association study of response to methotrexate in early rheumatoid arthritis patients. Pharmacogenomics J 2018; 18:528-538. [PMID: 29795407 DOI: 10.1038/s41397-018-0025-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Revised: 10/10/2017] [Accepted: 02/09/2018] [Indexed: 11/09/2022]
Abstract
Methotrexate (MTX) monotherapy is a common first treatment for rheumatoid arthritis (RA), but many patients do not respond adequately. In order to identify genetic predictors of response, we have combined data from two consortia to carry out a genome-wide study of response to MTX in 1424 early RA patients of European ancestry. Clinical endpoints were change from baseline to 6 months after starting treatment in swollen 28-joint count, tender 28-joint count, C-reactive protein and the overall 3-component disease activity score (DAS28). No single nucleotide polymorphism (SNP) reached genome-wide statistical significance for any outcome measure. The strongest evidence for association was with rs168201 in NRG3 (p = 10-7 for change in DAS28). Some support was also seen for association with ZMIZ1, previously highlighted in a study of response to MTX in juvenile idiopathic arthritis. Follow-up in two smaller cohorts of 429 and 177 RA patients did not support these findings, although these cohorts were more heterogeneous.
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Affiliation(s)
- John C Taylor
- Leeds Institute of Cancer and Pathology, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | | | - Jonathan Massey
- Arthritis Research UK Centre for Genetics and Genomics, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.,NIHR Manchester BRC, Central Manchester Foundation Trust, Manchester, UK
| | - Borbala Mifsud
- Clinical Pharmacology, William Harvey Research Institute, Queen Mary University, London, UK
| | - Athina Spiliopoulou
- Centre for Population Health Sciences, Usher Institute, University of Edinburgh Old Medical School, Teviot Place, Edinburgh, UK.,Pharmatics Ltd., 9, Little France Road, Edinburgh, UK
| | - Ian C Scott
- Research Institute for Primary Care and Health Sciences, Primary Care Sciences, Keele University and Department of Rheumatology, Haywood Hospital, High Lane, Burslem, Staffordshire, UK.,Department of Medical and Molecular Genetics, King's College London, London, UK
| | | | - Michael Morgan
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK.,Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge, UK
| | - Darren Plant
- Arthritis Research UK Centre for Genetics and Genomics, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.,NIHR Manchester BRC, Central Manchester Foundation Trust, Manchester, UK
| | - Marco Colombo
- Centre for Population Health Sciences, Usher Institute, University of Edinburgh Old Medical School, Teviot Place, Edinburgh, UK
| | - Peter Orchard
- Pharmatics Ltd., 9, Little France Road, Edinburgh, UK
| | - Sarah Twigg
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Iain B McInnes
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK
| | - Duncan Porter
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK
| | - Jane E Freeston
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Jackie L Nam
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | | | - John D Isaacs
- Musculoskeletal Research Group, Institute of Cellular Medicine, Newcastle University and NIHR Newcastle Biomedical Research Centre in Ageing and Long Term Conditions, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Jenna L Strathdee
- Leeds Institute of Cancer and Pathology, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Donna Arnett
- University of Kentucky College of Public Health, Lexington, KY, 40536, USA
| | | | - Paul P Tak
- Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.,GlaxoSmithKline, Stevenage, UK.,Cambridge University, Cambridge, UK.,Ghent University, Ghent, Belgium
| | - Stella Aslibekyan
- Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ronald F van Vollenhoven
- Rheumatology Unit, Department of Medicine Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Leonid Padyukov
- Rheumatology Unit, Department of Medicine Solna, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - S Louis Bridges
- Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Costantino Pitzalis
- Barts and The London School of Medicine & Dentistry, William Harvey Research Institute, Queen Mary University, London, UK
| | - Andrew P Cope
- Academic Department of Rheumatology, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Suzanne M M Verstappen
- Arthritis Research UK Centre for Genetics and Genomics, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.,NIHR Manchester BRC, Central Manchester Foundation Trust, Manchester, UK
| | - Paul Emery
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Michael R Barnes
- Barts and The London School of Medicine & Dentistry, William Harvey Research Institute, Queen Mary University, London, UK
| | - Felix Agakov
- Pharmatics Ltd., 9, Little France Road, Edinburgh, UK
| | - Paul McKeigue
- Centre for Population Health Sciences, Usher Institute, University of Edinburgh Old Medical School, Teviot Place, Edinburgh, UK
| | | | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Tokyo, Japan
| | | | - Anne Barton
- Arthritis Research UK Centre for Genetics and Genomics, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.,NIHR Manchester BRC, Central Manchester Foundation Trust, Manchester, UK
| | - Ann W Morgan
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
| | - Jennifer H Barrett
- Leeds Institute of Cancer and Pathology, University of Leeds, and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
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Bamford R, Rowlands C, Williams S, Orchard P, Pickering G, Dacombe P, Longman R, Boorman P, Rodd C, Langdon I, Eastaugh-Waring S, Coulston J. Boot camps – The future for surgical training? Int J Surg 2016. [DOI: 10.1016/j.ijsu.2016.08.362] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Vohra RS, Pasquali S, Kirkham AJ, Marriott P, Johnstone M, Spreadborough P, Alderson D, Griffiths EA, Fenwick S, Elmasry M, Nunes Q, Kennedy D, Basit Khan R, Khan MAS, Magee CJ, Jones SM, Mason D, Parappally CP, Mathur P, Saunders M, Jamel S, Ul Haque S, Zafar S, Shiwani MH, Samuel N, Dar F, Jackson A, Lovett B, Dindyal S, Winter H, Fletcher T, Rahman S, Wheatley K, Nieto T, Ayaani S, Youssef H, Nijjar RS, Watkin H, Naumann D, Emeshi S, Sarmah PB, Lee K, Joji N, Heath J, Teasdale RL, Weerasinghe C, Needham PJ, Welbourn H, Forster L, Finch D, Blazeby JM, Robb W, McNair AGK, Hrycaiczuk A, Charalabopoulos A, Kadirkamanathan S, Tang CB, Jayanthi NVG, Noor N, Dobbins B, Cockbain AJ, Nilsen-Nunn A, Siqueira J, Pellen M, Cowley JB, Ho WM, Miu V, White TJ, Hodgkins KA, Kinghorn A, Tutton MG, Al-Abed YA, Menzies D, Ahmad A, Reed J, Khan S, Monk D, Vitone LJ, Murtaza G, Joel A, Brennan S, Shier D, Zhang C, Yoganathan T, Robinson SJ, McCallum IJD, Jones MJ, Elsayed M, Tuck L, Wayman J, Carney K, Aroori S, Hosie KB, Kimble A, Bunting DM, Fawole AS, Basheer M, Dave RV, Sarveswaran J, Jones E, Kendal C, Tilston MP, Gough M, Wallace T, Singh S, Downing J, Mockford KA, Issa E, Shah N, Chauhan N, Wilson TR, Forouzanfar A, Wild JRL, Nofal E, Bunnell C, Madbak K, Rao STV, Devoto L, Siddiqi N, Khawaja Z, Hewes JC, Gould L, Chambers A, Urriza Rodriguez D, Sen G, Robinson S, Carney K, Bartlett F, Rae DM, Stevenson TEJ, Sarvananthan K, Dwerryhouse SJ, Higgs SM, Old OJ, Hardy TJ, Shah R, Hornby ST, Keogh K, Frank L, Al-Akash M, Upchurch EA, Frame RJ, Hughes M, Jelley C, Weaver S, Roy S, Sillo TO, Galanopoulos G, Cuming T, Cunha P, Tayeh S, Kaptanis S, Heshaishi M, Eisawi A, Abayomi M, Ngu WS, Fleming K, Singh Bajwa D, Chitre V, Aryal K, Ferris P, Silva M, Lammy S, Mohamed S, Khawaja A, Hussain A, Ghazanfar MA, Bellini MI, Ebdewi H, Elshaer M, Gravante G, Drake B, Ogedegbe A, Mukherjee D, Arhi C, Giwa Nusrat Iqbal L, Watson NF, Kumar Aggarwal S, Orchard P, Villatoro E, Willson PD, Wa K, Mok J, Woodman T, Deguara J, Garcea G, Babu BI, Dennison AR, Malde D, Lloyd D, Satheesan S, Al-Taan O, Boddy A, Slavin JP, Jones RP, Ballance L, Gerakopoulos S, Jambulingam P, Mansour S, Sakai N, Acharya V, Sadat MM, Karim L, Larkin D, Amin K, Khan A, Law J, Jamdar S, Smith SR, Sampat K, M O'shea K, Manu M, Asprou FM, Malik NS, Chang J, Johnstone M, Lewis M, Roberts GP, Karavadra B, Photi E, Hewes J, Gould L, Chambers A, Rodriguez D, O'Reilly DA, Rate AJ, Sekhar H, Henderson LT, Starmer BZ, Coe PO, Tolofari S, Barrie J, Bashir G, Sloane J, Madanipour S, Halkias C, Trevatt AEJ, Borowski DW, Hornsby J, Courtney MJ, Virupaksha S, Seymour K, Robinson S, Hawkins H, Bawa S, Gallagher PV, Reid A, Wood P, Finch JG, Parmar J, Stirland E, Gardner-Thorpe J, Al-Muhktar A, Peterson M, Majeed A, Bajwa FM, Martin J, Choy A, Tsang A, Pore N, Andrew DR, Al-Khyatt W, Taylor C, Bhandari S, Chambers A, Subramanium D, Toh SKC, Carter NC, Mercer SJ, Knight B, Tate S, Pearce B, Wainwright D, Vijay V, Alagaratnam S, Sinha S, Khan S, El-Hasani SS, Hussain AA, Bhattacharya V, Kansal N, Fasih T, Jackson C, Siddiqui MN, Chishti IA, Fordham IJ, Siddiqui Z, Bausbacher H, Geogloma I, Gurung K, Tsavellas G, Basynat P, Kiran Shrestha A, Basu S, Chhabra Mohan Harilingam A, Rabie M, Akhtar M, Kumar P, Jafferbhoy SF, Hussain N, Raza S, Haque M, Alam I, Aseem R, Patel S, Asad M, Booth MI, Ball WR, Wood CPJ, Pinho-Gomes AC, Kausar A, Rami Obeidallah M, Varghase J, Lodhia J, Bradley D, Rengifo C, Lindsay D, Gopalswamy S, Finlay I, Wardle S, Bullen N, Iftikhar SY, Awan A, Ahmed J, Leeder P, Fusai G, Bond-Smith G, Psica A, Puri Y, Hou D, Noble F, Szentpali K, Broadhurst J, Date R, Hossack MR, Li Goh Y, Turner P, Shetty V, Riera M, Macano CAW, Sukha A, Preston SR, Hoban JR, Puntis DJ, Williams SV, Krysztopik R, Kynaston J, Batt J, Doe M, Goscimski A, Jones GH, Smith SR, Hall C, Carty N, Ahmed J, Panteleimonitis S, Gunasekera RT, Sheel ARG, Lennon H, Hindley C, Reddy M, Kenny R, Elkheir N, McGlone ER, Rajaganeshan R, Hancorn K, Hargreaves A, Prasad R, Longbotham DA, Vijayanand D, Wijetunga I, Ziprin P, Nicolay CR, Yeldham G, Read E, Gossage JA, Rolph RC, Ebied H, Phull M, Khan MA, Popplewell M, Kyriakidis D, Hussain A, Henley N, Packer JR, Derbyshire L, Porter J, Appleton S, Farouk M, Basra M, Jennings NA, Ali S, Kanakala V, Ali H, Lane R, Dickson-Lowe R, Zarsadias P, Mirza D, Puig S, Al Amari K, Vijayan D, Sutcliffe R, Marudanayagam R, Hamady Z, Prasad AR, Patel A, Durkin D, Kaur P, Bowen L, Byrne JP, Pearson KL, Delisle TG, Davies J, Tomlinson MA, Johnpulle MA, Slawinski C, Macdonald A, Nicholson J, Newton K, Mbuvi J, Farooq A, Sidhartha Mothe B, Zafrani Z, Brett D, Francombe J, Spreadborough P, Barnes J, Cheung M, Al-Bahrani AZ, Preziosi G, Urbonas T, Alberts J, Mallik M, Patel K, Segaran A, Doulias T, Sufi PA, Yao C, Pollock S, Manzelli A, Wajed S, Kourkulos M, Pezzuto R, Wadley M, Hamilton E, Jaunoo S, Padwick R, Sayegh M, Newton RC, Hebbar M, Farag SF, Spearman J, Hamdan MF, D'Costa C, Blane C, Giles M, Peter MB, Hirst NA, Hossain T, Pannu A, El-Dhuwaib Y, Morrison TEM, Taylor GW, Thompson RLE, McCune K, Loughlin P, Lawther R, Byrnes CK, Simpson DJ, Mawhinney A, Warren C, McKay D, McIlmunn C, Martin S, MacArtney M, Diamond T, Davey P, Jones C, Clements JM, Digney R, Chan WM, McCain S, Gull S, Janeczko A, Dorrian E, Harris A, Dawson S, Johnston D, McAree B, Ghareeb E, Thomas G, Connelly M, McKenzie S, Cieplucha K, Spence G, Campbell W, Hooks G, Bradley N, Hill ADK, Cassidy JT, Boland M, Burke P, Nally DM, Hill ADK, Khogali E, Shabo W, Iskandar E, McEntee GP, O'Neill MA, Peirce C, Lyons EM, O'Sullivan AW, Thakkar R, Carroll P, Ivanovski I, Balfe P, Lee M, Winter DC, Kelly ME, Hoti E, Maguire D, Karunakaran P, Geoghegan JG, Martin ST, McDermott F, Cross KS, Cooke F, Zeeshan S, Murphy JO, Mealy K, Mohan HM, Nedujchelyn Y, Fahad Ullah M, Ahmed I, Giovinazzo F, Milburn J, Prince S, Brooke E, Buchan J, Khalil AM, Vaughan EM, Ramage MI, Aldridge RC, Gibson S, Nicholson GA, Vass DG, Grant AJ, Holroyd DJ, Jones MA, Sutton CMLR, O'Dwyer P, Nilsson F, Weber B, Williamson TK, Lalla K, Bryant A, Carter CR, Forrest CR, Hunter DI, Nassar AH, Orizu MN, Knight K, Qandeel H, Suttie S, Belding R, McClarey A, Boyd AT, Guthrie GJK, Lim PJ, Luhmann A, Watson AJM, Richards CH, Nicol L, Madurska M, Harrison E, Boyce KM, Roebuck A, Ferguson G, Pati P, Wilson MSJ, Dalgaty F, Fothergill L, Driscoll PJ, Mozolowski KL, Banwell V, Bennett SP, Rogers PN, Skelly BL, Rutherford CL, Mirza AK, Lazim T, Lim HCC, Duke D, Ahmed T, Beasley WD, Wilkinson MD, Maharaj G, Malcolm C, Brown TH, Shingler GM, Mowbray N, Radwan R, Morcous P, Wood S, Kadhim A, Stewart DJ, Baker AL, Tanner N, Shenoy H, Hafiz S, Marchi JA, Singh-Ranger D, Hisham E, Ainley P, O'Neill S, Terrace J, Napetti S, Hopwood B, Rhys T, Downing J, Kanavati O, Coats M, Aleksandrov D, Kallaway C, Yahya S, Weber B, Templeton A, Trotter M, Lo C, Dhillon A, Heywood N, Aawsaj Y, Hamdan A, Reece-Bolton O, McGuigan A, Shahin Y, Ali A, Luther A, Nicholson JA, Rajendran I, Boal M, Ritchie J. Population-based cohort study of variation in the use of emergency cholecystectomy for benign gallbladder diseases. Br J Surg 2016; 103:1716-1726. [PMID: 27748962 DOI: 10.1002/bjs.10288] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 06/21/2016] [Accepted: 07/06/2016] [Indexed: 01/05/2023]
Abstract
Abstract
Background
The aims of this prospective population-based cohort study were to identify the patient and hospital characteristics associated with emergency cholecystectomy, and the influences of these in determining variations between hospitals.
Methods
Data were collected for consecutive patients undergoing cholecystectomy in acute UK and Irish hospitals between 1 March and 1 May 2014. Potential explanatory variables influencing the performance of emergency cholecystectomy were analysed by means of multilevel, multivariable logistic regression modelling using a two-level hierarchical structure with patients (level 1) nested within hospitals (level 2).
Results
Data were collected on 4744 cholecystectomies from 165 hospitals. Increasing age, lower ASA fitness grade, biliary colic, the need for further imaging (magnetic retrograde cholangiopancreatography), endoscopic interventions (endoscopic retrograde cholangiopancreatography) and admission to a non-biliary centre significantly reduced the likelihood of an emergency cholecystectomy being performed. The multilevel model was used to calculate the probability of receiving an emergency cholecystectomy for a woman aged 40 years or over with an ASA grade of I or II and a BMI of at least 25·0 kg/m2, who presented with acute cholecystitis with an ultrasound scan showing a thick-walled gallbladder and a normal common bile duct. The mean predicted probability of receiving an emergency cholecystectomy was 0·52 (95 per cent c.i. 0·45 to 0·57). The predicted probabilities ranged from 0·02 to 0·95 across the 165 hospitals, demonstrating significant variation between hospitals.
Conclusion
Patients with similar characteristics presenting to different hospitals with acute gallbladder pathology do not receive comparable care.
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Affiliation(s)
| | - R S Vohra
- Trent Oesophago-Gastric Unit, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - S Pasquali
- Surgical Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - A J Kirkham
- Cancer Research UK Clinical Trials Unit, University of Birmingham, Birmingham, UK
| | - P Marriott
- West Midlands Research Collaborative, Academic Department of Surgery, University of Birmingham, Birmingham, UK
| | - M Johnstone
- West Midlands Research Collaborative, Academic Department of Surgery, University of Birmingham, Birmingham, UK
| | - P Spreadborough
- West Midlands Research Collaborative, Academic Department of Surgery, University of Birmingham, Birmingham, UK
| | - D Alderson
- Academic Department of Surgery, University of Birmingham, Birmingham, UK
| | - E A Griffiths
- Department of Upper Gastrointestinal Surgery, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - S Fenwick
- Aintree University Hospital NHS Foundation Trust
| | - M Elmasry
- Aintree University Hospital NHS Foundation Trust
| | - Q Nunes
- Aintree University Hospital NHS Foundation Trust
| | - D Kennedy
- Aintree University Hospital NHS Foundation Trust
| | | | | | | | | | - D Mason
- Wirral University Teaching Hospital
| | | | | | | | - S Jamel
- Barnet and Chase Farm Hospital
| | | | - S Zafar
- Barnet and Chase Farm Hospital
| | | | - N Samuel
- Barnsley District General Hospital
| | - F Dar
- Barnsley District General Hospital
| | | | | | | | | | | | | | - K Wheatley
- Sandwell and West Birmingham Hospitals NHS Trust
| | - T Nieto
- Sandwell and West Birmingham Hospitals NHS Trust
| | - S Ayaani
- Sandwell and West Birmingham Hospitals NHS Trust
| | - H Youssef
- Heart of England Foundation NHS Trust
| | | | - H Watkin
- Heart of England Foundation NHS Trust
| | - D Naumann
- Heart of England Foundation NHS Trust
| | - S Emeshi
- Heart of England Foundation NHS Trust
| | | | - K Lee
- Heart of England Foundation NHS Trust
| | - N Joji
- Heart of England Foundation NHS Trust
| | - J Heath
- Blackpool Teaching Hospitals NHS Foundation Trust
| | - R L Teasdale
- Blackpool Teaching Hospitals NHS Foundation Trust
| | | | - P J Needham
- Bradford Teaching Hospitals NHS Foundation Trust
| | - H Welbourn
- Bradford Teaching Hospitals NHS Foundation Trust
| | - L Forster
- Bradford Teaching Hospitals NHS Foundation Trust
| | - D Finch
- Bradford Teaching Hospitals NHS Foundation Trust
| | | | - W Robb
- University Hospitals Bristol NHS Trust
| | | | | | | | | | | | | | | | - B Dobbins
- Calderdale and Huddersfield NHS Trust
| | | | | | | | - M Pellen
- Hull and East Yorkshire NHS Trust
| | | | - W-M Ho
- Hull and East Yorkshire NHS Trust
| | - V Miu
- Hull and East Yorkshire NHS Trust
| | - T J White
- Chesterfield Royal Hospital NHS Foundation Trust
| | - K A Hodgkins
- Chesterfield Royal Hospital NHS Foundation Trust
| | - A Kinghorn
- Chesterfield Royal Hospital NHS Foundation Trust
| | - M G Tutton
- Colchester Hospital University NHS Foundation Trust
| | - Y A Al-Abed
- Colchester Hospital University NHS Foundation Trust
| | - D Menzies
- Colchester Hospital University NHS Foundation Trust
| | - A Ahmad
- Colchester Hospital University NHS Foundation Trust
| | - J Reed
- Colchester Hospital University NHS Foundation Trust
| | - S Khan
- Colchester Hospital University NHS Foundation Trust
| | - D Monk
- Countess of Chester NHS Foundation Trust
| | - L J Vitone
- Countess of Chester NHS Foundation Trust
| | - G Murtaza
- Countess of Chester NHS Foundation Trust
| | - A Joel
- Countess of Chester NHS Foundation Trust
| | | | - D Shier
- Croydon Health Services NHS Trust
| | - C Zhang
- Croydon Health Services NHS Trust
| | | | | | | | - M J Jones
- North Cumbria University Hospitals Trust
| | - M Elsayed
- North Cumbria University Hospitals Trust
| | - L Tuck
- North Cumbria University Hospitals Trust
| | - J Wayman
- North Cumbria University Hospitals Trust
| | - K Carney
- North Cumbria University Hospitals Trust
| | | | | | | | | | | | | | | | | | | | | | - M P Tilston
- Northern Lincolnshire and Goole NHS Foundation Trust
| | - M Gough
- Northern Lincolnshire and Goole NHS Foundation Trust
| | - T Wallace
- Northern Lincolnshire and Goole NHS Foundation Trust
| | - S Singh
- Northern Lincolnshire and Goole NHS Foundation Trust
| | - J Downing
- Northern Lincolnshire and Goole NHS Foundation Trust
| | - K A Mockford
- Northern Lincolnshire and Goole NHS Foundation Trust
| | - E Issa
- Northern Lincolnshire and Goole NHS Foundation Trust
| | - N Shah
- Northern Lincolnshire and Goole NHS Foundation Trust
| | - N Chauhan
- Northern Lincolnshire and Goole NHS Foundation Trust
| | - T R Wilson
- Doncaster and Bassetlaw Hospitals NHS Foundation Trust
| | - A Forouzanfar
- Doncaster and Bassetlaw Hospitals NHS Foundation Trust
| | - J R L Wild
- Doncaster and Bassetlaw Hospitals NHS Foundation Trust
| | - E Nofal
- Doncaster and Bassetlaw Hospitals NHS Foundation Trust
| | - C Bunnell
- Doncaster and Bassetlaw Hospitals NHS Foundation Trust
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- Doncaster and Bassetlaw Hospitals NHS Foundation Trust
| | - S T V Rao
- Dorset County Hospital NHS Foundation Trust
| | - L Devoto
- Dorset County Hospital NHS Foundation Trust
| | - N Siddiqi
- Dorset County Hospital NHS Foundation Trust
| | - Z Khawaja
- Dorset County Hospital NHS Foundation Trust
| | | | | | | | | | | | | | | | | | - D M Rae
- Frimley Park Hospital NHS Trust
| | | | | | | | | | - O J Old
- Gloucestershire Hospitals NHS Trust
| | | | - R Shah
- Gloucestershire Hospitals NHS Trust
| | | | - K Keogh
- Gloucestershire Hospitals NHS Trust
| | - L Frank
- Gloucestershire Hospitals NHS Trust
| | - M Al-Akash
- Great Western Hospitals NHS Foundation Trust
| | | | - R J Frame
- Harrogate and District NHS Foundation Trust
| | - M Hughes
- Harrogate and District NHS Foundation Trust
| | - C Jelley
- Harrogate and District NHS Foundation Trust
| | | | | | | | | | - T Cuming
- Homerton University Hospital NHS Trust
| | - P Cunha
- Homerton University Hospital NHS Trust
| | - S Tayeh
- Homerton University Hospital NHS Trust
| | | | | | - A Eisawi
- Tees Hospitals NHS Foundation Trust
| | | | - W S Ngu
- Tees Hospitals NHS Foundation Trust
| | | | | | - V Chitre
- Paget University Hospitals NHS Foundation Trust
| | - K Aryal
- Paget University Hospitals NHS Foundation Trust
| | - P Ferris
- Paget University Hospitals NHS Foundation Trust
| | | | | | | | | | | | | | | | - H Ebdewi
- Kettering General Hospital NHS Foundation Trust
| | - M Elshaer
- Kettering General Hospital NHS Foundation Trust
| | - G Gravante
- Kettering General Hospital NHS Foundation Trust
| | - B Drake
- Kettering General Hospital NHS Foundation Trust
| | - A Ogedegbe
- Barking, Havering and Redbridge University Hospitals NHS Trust
| | - D Mukherjee
- Barking, Havering and Redbridge University Hospitals NHS Trust
| | - C Arhi
- Barking, Havering and Redbridge University Hospitals NHS Trust
| | | | | | | | | | | | | | - K Wa
- Kingston Hospital NHS Foundation Trust
| | - J Mok
- Kingston Hospital NHS Foundation Trust
| | - T Woodman
- Kingston Hospital NHS Foundation Trust
| | - J Deguara
- Kingston Hospital NHS Foundation Trust
| | - G Garcea
- University Hospitals of Leicester NHS Trust
| | - B I Babu
- University Hospitals of Leicester NHS Trust
| | | | - D Malde
- University Hospitals of Leicester NHS Trust
| | - D Lloyd
- University Hospitals of Leicester NHS Trust
| | | | - O Al-Taan
- University Hospitals of Leicester NHS Trust
| | - A Boddy
- University Hospitals of Leicester NHS Trust
| | - J P Slavin
- Leighton Hospital, Mid Cheshire Hospitals NHS Foundation Trust
| | - R P Jones
- Leighton Hospital, Mid Cheshire Hospitals NHS Foundation Trust
| | - L Ballance
- Leighton Hospital, Mid Cheshire Hospitals NHS Foundation Trust
| | - S Gerakopoulos
- Leighton Hospital, Mid Cheshire Hospitals NHS Foundation Trust
| | - P Jambulingam
- Luton and Dunstable University Hospital NHS Foundation Trust
| | - S Mansour
- Luton and Dunstable University Hospital NHS Foundation Trust
| | - N Sakai
- Luton and Dunstable University Hospital NHS Foundation Trust
| | - V Acharya
- Luton and Dunstable University Hospital NHS Foundation Trust
| | - M M Sadat
- Macclesfield District General Hospital
| | - L Karim
- Macclesfield District General Hospital
| | - D Larkin
- Macclesfield District General Hospital
| | - K Amin
- Macclesfield District General Hospital
| | - A Khan
- Central Manchester NHS Foundation Trust
| | - J Law
- Central Manchester NHS Foundation Trust
| | - S Jamdar
- Central Manchester NHS Foundation Trust
| | - S R Smith
- Central Manchester NHS Foundation Trust
| | - K Sampat
- Central Manchester NHS Foundation Trust
| | | | - M Manu
- Royal Wolverhampton Hospitals NHS Trust
| | | | - N S Malik
- Royal Wolverhampton Hospitals NHS Trust
| | - J Chang
- Royal Wolverhampton Hospitals NHS Trust
| | | | - M Lewis
- Norfolk and Norwich University Hospitals NHS Foundation Trust
| | - G P Roberts
- Norfolk and Norwich University Hospitals NHS Foundation Trust
| | - B Karavadra
- Norfolk and Norwich University Hospitals NHS Foundation Trust
| | - E Photi
- Norfolk and Norwich University Hospitals NHS Foundation Trust
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - J Hornsby
- North Tees and Hartlepool NHS Foundation Trust
| | | | | | - K Seymour
- Northumbria Healthcare NHS Foundation Trust
| | - S Robinson
- Northumbria Healthcare NHS Foundation Trust
| | - H Hawkins
- Northumbria Healthcare NHS Foundation Trust
| | - S Bawa
- Northumbria Healthcare NHS Foundation Trust
| | | | - A Reid
- Northumbria Healthcare NHS Foundation Trust
| | - P Wood
- Northumbria Healthcare NHS Foundation Trust
| | - J G Finch
- Northampton General Hospital NHS Trust
| | - J Parmar
- Northampton General Hospital NHS Trust
| | | | | | - A Al-Muhktar
- Sheffield Teaching Hospitals NHS Foundation Trust
| | - M Peterson
- Sheffield Teaching Hospitals NHS Foundation Trust
| | - A Majeed
- Sheffield Teaching Hospitals NHS Foundation Trust
| | | | | | - A Choy
- Peterborough City Hospital
| | | | - N Pore
- United Lincolnshire Hospitals NHS Trust
| | | | | | - C Taylor
- United Lincolnshire Hospitals NHS Trust
| | | | | | | | | | | | | | | | - S Tate
- Portsmouth Hospitals NHS Trust
| | | | | | - V Vijay
- The Princess Alexandra Hospital NHS Trust
| | | | - S Sinha
- The Princess Alexandra Hospital NHS Trust
| | - S Khan
- The Princess Alexandra Hospital NHS Trust
| | | | - A A Hussain
- King's College Hospital NHS Foundation Trust
| | | | - N Kansal
- Gateshead Health NHS Foundation Trust
| | - T Fasih
- Gateshead Health NHS Foundation Trust
| | - C Jackson
- Gateshead Health NHS Foundation Trust
| | | | | | | | | | | | | | - K Gurung
- Queen Elizabeth Hospital NHS Trust
| | - G Tsavellas
- East Kent Hospitals University NHS Foundation Trust
| | - P Basynat
- East Kent Hospitals University NHS Foundation Trust
| | | | - S Basu
- East Kent Hospitals University NHS Foundation Trust
| | | | - M Rabie
- East Kent Hospitals University NHS Foundation Trust
| | - M Akhtar
- East Kent Hospitals University NHS Foundation Trust
| | - P Kumar
- Burton Hospitals NHS Foundation Trust
| | | | - N Hussain
- Burton Hospitals NHS Foundation Trust
| | - S Raza
- Burton Hospitals NHS Foundation Trust
| | - M Haque
- Royal Albert Edward Infirmary, Wigan Wrightington and Leigh NHS Trust
| | - I Alam
- Royal Albert Edward Infirmary, Wigan Wrightington and Leigh NHS Trust
| | - R Aseem
- Royal Albert Edward Infirmary, Wigan Wrightington and Leigh NHS Trust
| | - S Patel
- Royal Albert Edward Infirmary, Wigan Wrightington and Leigh NHS Trust
| | - M Asad
- Royal Albert Edward Infirmary, Wigan Wrightington and Leigh NHS Trust
| | - M I Booth
- Royal Berkshire NHS Foundation Trust
| | - W R Ball
- Royal Berkshire NHS Foundation Trust
| | | | | | | | | | - J Varghase
- Royal Bolton Hospital NHS Foundation Trust
| | - J Lodhia
- Royal Bolton Hospital NHS Foundation Trust
| | - D Bradley
- Royal Bolton Hospital NHS Foundation Trust
| | - C Rengifo
- Royal Bolton Hospital NHS Foundation Trust
| | - D Lindsay
- Royal Bolton Hospital NHS Foundation Trust
| | | | | | | | | | | | - A Awan
- Royal Derby NHS Foundation Trust
| | - J Ahmed
- Royal Derby NHS Foundation Trust
| | - P Leeder
- Royal Derby NHS Foundation Trust
| | | | | | | | | | - D Hou
- Hampshire Hospital NHS Foundation Trust
| | - F Noble
- Hampshire Hospital NHS Foundation Trust
| | | | | | - R Date
- Lancashire Teaching Hospitals NHS Foundation Trust
| | - M R Hossack
- Lancashire Teaching Hospitals NHS Foundation Trust
| | - Y Li Goh
- Lancashire Teaching Hospitals NHS Foundation Trust
| | - P Turner
- Lancashire Teaching Hospitals NHS Foundation Trust
| | - V Shetty
- Lancashire Teaching Hospitals NHS Foundation Trust
| | | | | | | | - S R Preston
- Royal Surrey County Hospital NHS Foundation Trust
| | - J R Hoban
- Royal Surrey County Hospital NHS Foundation Trust
| | - D J Puntis
- Royal Surrey County Hospital NHS Foundation Trust
| | - S V Williams
- Royal Surrey County Hospital NHS Foundation Trust
| | | | | | - J Batt
- Royal United Hospital Bath NHS Trust
| | - M Doe
- Royal United Hospital Bath NHS Trust
| | | | | | | | - C Hall
- Salford Royal NHS Foundation Trust
| | - N Carty
- Salisbury Hospital Foundation Trust
| | - J Ahmed
- Salisbury Hospital Foundation Trust
| | | | | | | | - H Lennon
- Southport and Ormskirk Hospital NHS Trust
| | - C Hindley
- Southport and Ormskirk Hospital NHS Trust
| | - M Reddy
- St George's Healthcare NHS Trust
| | - R Kenny
- St George's Healthcare NHS Trust
| | | | | | | | - K Hancorn
- St Helens and Knowsley Teaching Hospitals NHS Trust
| | - A Hargreaves
- St Helens and Knowsley Teaching Hospitals NHS Trust
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- Imperial College Healthcare NHS Trust
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- Imperial College Healthcare NHS Trust
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- Imperial College Healthcare NHS Trust
| | | | | | | | | | - M A Khan
- Mid Staffordshire NHS Foundation Trust
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- Mid Staffordshire NHS Foundation Trust
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- City Hospitals Sunderland NHS Foundation Trust
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- City Hospitals Sunderland NHS Foundation Trust
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- Tunbridge Wells and Maidstone NHS Trust
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- Tunbridge Wells and Maidstone NHS Trust
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- University Hospital Birmingham NHS Foundation Trust
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- University Hospital Birmingham NHS Foundation Trust
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- University Hospital Birmingham NHS Foundation Trust
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- University Hospital Birmingham NHS Foundation Trust
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- University Hospital Birmingham NHS Foundation Trust
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- University Hospital Coventry and Warwickshire NHS Trust
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- University Hospital Coventry and Warwickshire NHS Trust
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- University Hospital Coventry and Warwickshire NHS Trust
| | - D Durkin
- University Hospital of North Staffordshire NHS Trust
| | - P Kaur
- University Hospital of North Staffordshire NHS Trust
| | - L Bowen
- University Hospital of North Staffordshire NHS Trust
| | - J P Byrne
- University Hospital Southampton NHS Foundation Trust
| | - K L Pearson
- University Hospital Southampton NHS Foundation Trust
| | - T G Delisle
- University Hospital Southampton NHS Foundation Trust
| | - J Davies
- University Hospital Southampton NHS Foundation Trust
| | | | | | | | - A Macdonald
- University Hospital South Manchester NHS Foundation Trust
| | - J Nicholson
- University Hospital South Manchester NHS Foundation Trust
| | - K Newton
- University Hospital South Manchester NHS Foundation Trust
| | - J Mbuvi
- University Hospital South Manchester NHS Foundation Trust
| | - A Farooq
- Warrington and Halton Hospitals NHS Trust
| | | | - Z Zafrani
- Warrington and Halton Hospitals NHS Trust
| | - D Brett
- Warrington and Halton Hospitals NHS Trust
| | | | | | - J Barnes
- South Warwickshire NHS Foundation Trust
| | - M Cheung
- South Warwickshire NHS Foundation Trust
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - M Wadley
- Worcestershire Acute Hospitals NHS Trust
| | - E Hamilton
- Worcestershire Acute Hospitals NHS Trust
| | - S Jaunoo
- Worcestershire Acute Hospitals NHS Trust
| | - R Padwick
- Worcestershire Acute Hospitals NHS Trust
| | - M Sayegh
- Western Sussex Hospitals NHS Foundation Trust
| | - R C Newton
- Western Sussex Hospitals NHS Foundation Trust
| | - M Hebbar
- Western Sussex Hospitals NHS Foundation Trust
| | - S F Farag
- Western Sussex Hospitals NHS Foundation Trust
| | | | | | | | - C Blane
- Yeovil District Hospital NHS Trust
| | - M Giles
- York Teaching Hospital NHS Foundation Trust
| | - M B Peter
- York Teaching Hospital NHS Foundation Trust
| | - N A Hirst
- York Teaching Hospital NHS Foundation Trust
| | - T Hossain
- York Teaching Hospital NHS Foundation Trust
| | - A Pannu
- York Teaching Hospital NHS Foundation Trust
| | | | | | - G W Taylor
- York Teaching Hospital NHS Foundation Trust
| | | | | | | | | | | | | | | | | | | | | | | | | | - T Diamond
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - P Davey
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - C Jones
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - J M Clements
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - R Digney
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - W M Chan
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - S McCain
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - S Gull
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - A Janeczko
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - E Dorrian
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - A Harris
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - S Dawson
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - D Johnston
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
| | - B McAree
- Belfast City Hospital, Mater Infirmorum Hospital Belfast and Royal Victoria Hospital
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- University Hospital Limerick
| | | | - A D K Hill
- Louth County Hospital and Our Lady of Lourdes Hospital
| | - E Khogali
- Louth County Hospital and Our Lady of Lourdes Hospital
| | - W Shabo
- Louth County Hospital and Our Lady of Lourdes Hospital
| | - E Iskandar
- Louth County Hospital and Our Lady of Lourdes Hospital
| | | | | | | | | | | | | | | | | | - P Balfe
- St Luke's General Hospital Kilkenny
| | - M Lee
- St Luke's General Hospital Kilkenny
| | - D C Winter
- St Vincent's University and Private Hospitals, Dublin
| | - M E Kelly
- St Vincent's University and Private Hospitals, Dublin
| | - E Hoti
- St Vincent's University and Private Hospitals, Dublin
| | - D Maguire
- St Vincent's University and Private Hospitals, Dublin
| | - P Karunakaran
- St Vincent's University and Private Hospitals, Dublin
| | - J G Geoghegan
- St Vincent's University and Private Hospitals, Dublin
| | - S T Martin
- St Vincent's University and Private Hospitals, Dublin
| | - F McDermott
- St Vincent's University and Private Hospitals, Dublin
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - S Gibson
- Crosshouse Hospital, Ayrshire and Arran
| | | | - D G Vass
- Crosshouse Hospital, Ayrshire and Arran
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - H C C Lim
- Glangwili General and Prince Philip Hospital
| | - D Duke
- Glangwili General and Prince Philip Hospital
| | - T Ahmed
- Glangwili General and Prince Philip Hospital
| | - W D Beasley
- Glangwili General and Prince Philip Hospital
| | | | - G Maharaj
- Glangwili General and Prince Philip Hospital
| | - C Malcolm
- Glangwili General and Prince Philip Hospital
| | | | | | | | - R Radwan
- Morriston and Singleton Hospitals
| | | | - S Wood
- Princess of Wales Hospital
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Theodoratou E, Thaçi K, Agakov F, Timofeeva MN, Štambuk J, Pučić-Baković M, Vučković F, Orchard P, Agakova A, Din FVN, Brown E, Rudd PM, Farrington SM, Dunlop MG, Campbell H, Lauc G. Glycosylation of plasma IgG in colorectal cancer prognosis. Sci Rep 2016; 6:28098. [PMID: 27302279 PMCID: PMC4908421 DOI: 10.1038/srep28098] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2016] [Accepted: 05/27/2016] [Indexed: 01/17/2023] Open
Abstract
In this study we demonstrate the potential value of Immunoglobulin G (IgG) glycosylation as a novel prognostic biomarker of colorectal cancer (CRC). We analysed plasma IgG glycans in 1229 CRC patients and correlated with survival outcomes. We assessed the predictive value of clinical algorithms and compared this to algorithms that also included glycan predictors. Decreased galactosylation, decreased sialylation (of fucosylated IgG glycan structures) and increased bisecting GlcNAc in IgG glycan structures were strongly associated with all-cause (q < 0.01) and CRC mortality (q = 0.04 for galactosylation and sialylation). Clinical algorithms showed good prediction of all-cause and CRC mortality (Harrell's C: 0.73, 0.77; AUC: 0.75, 0.79, IDI: 0.02, 0.04 respectively). The inclusion of IgG glycan data did not lead to any statistically significant improvements overall, but it improved the prediction over clinical models for stage 4 patients with the shortest follow-up time until death, with the median gain in the test AUC of 0.08. These glycan differences are consistent with significantly increased IgG pro-inflammatory activity being associated with poorer CRC prognosis, especially in late stage CRC. In the absence of validated biomarkers to improve upon prognostic information from existing clinicopathological factors, the potential of these novel IgG glycan biomarkers merits further investigation.
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Affiliation(s)
- Evropi Theodoratou
- The Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
- Colon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and Medical Research Council Human Genetics Unit, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Kujtim Thaçi
- Genos Glycoscience Research Laboratory, Zagreb, Croatia, HR-10000
| | - Felix Agakov
- Pharmatics Limited, Edinburgh Bioquarter, 9 Little France Road, Edinburgh, EH16 4UX, UK
| | - Maria N. Timofeeva
- Colon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and Medical Research Council Human Genetics Unit, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Jerko Štambuk
- Genos Glycoscience Research Laboratory, Zagreb, Croatia, HR-10000
| | | | - Frano Vučković
- Genos Glycoscience Research Laboratory, Zagreb, Croatia, HR-10000
| | - Peter Orchard
- Pharmatics Limited, Edinburgh Bioquarter, 9 Little France Road, Edinburgh, EH16 4UX, UK
| | - Anna Agakova
- Pharmatics Limited, Edinburgh Bioquarter, 9 Little France Road, Edinburgh, EH16 4UX, UK
| | - Farhat V. N. Din
- Colon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and Medical Research Council Human Genetics Unit, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Ewan Brown
- The Institute of Genetics and Molecular Medicine, Edinburgh Cancer Research Centre, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XR, UK
| | - Pauline M. Rudd
- National Institute for Bioprocessing Research & Training, Fosters Avenue, Mount Merrion, Blackrock, Co. Dublin, Ireland
| | - Susan M. Farrington
- Colon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and Medical Research Council Human Genetics Unit, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Malcolm G. Dunlop
- Colon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and Medical Research Council Human Genetics Unit, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Harry Campbell
- The Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK
- Colon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and Medical Research Council Human Genetics Unit, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Gordan Lauc
- Genos Glycoscience Research Laboratory, Zagreb, Croatia, HR-10000
- University of Zagreb Faculty of Pharmacy and Biochemistry, Zagreb, Croatia, HR-10000
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22
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Orchard P, Mustafa R, Thorn C, Alexander R. The yield of pathology from diagnostic flexible sigmoidoscopy in patients under 40 years. Int J Surg 2015. [DOI: 10.1016/j.ijsu.2015.07.646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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23
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Abstract
OBJECTIVE The purpose of CanTeen's E-Mental Health Service for Young People Living With Cancer (YPLWC) is to meet the unique psychosocial needs of young people (12-24 years) in Australia impacted by cancer (either as a patient or family member of someone with cancer). CONCLUSIONS This online platform will provide the primary site where all YPLWC can find information, connect with others going through a similar experience, express their feelings, utilise tools for support and access professional psychosocial support services that will meet their individual needs. The overall outcome of the service will be to ensure that the YPLWC visiting the site experience optimal psychological wellbeing. Ultimately, the service's value will be in improving the lives of young people who engage with it and the follow-on effect that this will have on their families and communities in the long-term.
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Affiliation(s)
- Pandora Patterson
- General Manager Research and Evaluation, CanTeen Australia, Sydney, NSW, Australia
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24
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Schroeder L, Orchard P, Whitley CB, Berry JM, Tolar J, Miller W, Braunlin EA. Cardiac Ultrasound Findings in Infants with Severe (Hurler Phenotype) Untreated Mucopolysaccharidosis (MPS) Type I. JIMD Rep 2013; 10:87-94. [PMID: 23430808 DOI: 10.1007/8904_2012_208] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [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] [Received: 12/12/2012] [Revised: 12/07/2012] [Accepted: 12/13/2012] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Serious cardiac valve disease and left ventricular hypertrophy occur in most untreated older children with severe mucopolysaccharidosis type I. Although it is assumed that early intervention prevents these processes, evaluation of cardiac findings in these infants has not yet been reported. METHODS We reviewed echocardiograms of 13 untreated infants < 1 year of age with severe mucopolysaccharidosis type I who had undergone evaluation for hematopoietic cell transplantation. We recorded left ventricular chamber dimensions, septal and posterior wall thicknesses, ventricular function, and aortic sinus diameters. We evaluated mitral and aortic valves for increased thickness, regurgitation, and stenosis. RESULTS Average age (7M, 6F) was 221 (range 25-347) days. Left ventricular chamber dimension was ≥2 SD of normal in 3/13; wall thicknesses were ≥2 SD of normal in 2/13 infants. Systolic function was normal. Mitral valves were thickened in all infants; mitral regurgitation was present in 9/13, but significant in only three infants. Aortic valves were thickened in 10/13, but no infant had significant aortic regurgitation. Neither mitral nor aortic stenosis occurred. Aortic roots were dilated to ≥2 SD of normal in 5/13. CONCLUSIONS Characteristic cardiac features of severe mucopolysaccharidosis type I can be seen in infancy. Mitral and aortic valve thickening are nearly universally present, even in the youngest infants. In 20-30 % of infants, other abnormalities such as left ventricular dilation, increased wall thickness, and mild mitral/aortic regurgitation may occur. Aortic root dilation is a frequent finding. Early intervention with enzyme replacement therapy may minimize the incidence and severity of cardiac findings in these infants. SUMMARY Serious cardiac valve disease and left ventricular hypertrophy occur in most untreated older children with severe mucopolysaccharidosis type I. Although it is assumed that early intervention prevents these processes, evaluation of cardiac findings in these infants has not yet been reported. In our study of 13 infants with severe untreated MPS I < 1 year of age, mitral and aortic valve thickening was nearly universally present and aortic root dilation was frequent. Despite this, we found a lower incidence of left ventricular hypertrophy and both a lower incidence and milder expression of mitral and aortic valve dysfunction than previously reported in older children. These findings suggest that earlier intervention, including neonatal screening, may be of benefit to children with severe MPS I.
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Affiliation(s)
- L Schroeder
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
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25
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Dickson P, Pariser A, Groft SC, Ishihara R, McNeil D, Tagle D, Griebel D, Kaler S, Mink J, Shapiro E, Bjoraker K, Krivitzky L, Provenzale J, Gropman A, Orchard P, Raymond G, Cohen B, Steiner R, Goldkind SF, Nelson RM, Kakkis E, Patterson M. Research challenges in central nervous system manifestations of inborn errors of metabolism. Mol Genet Metab 2011; 102:326-38. [PMID: 21176882 PMCID: PMC3040279 DOI: 10.1016/j.ymgme.2010.11.164] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2010] [Revised: 11/21/2010] [Accepted: 11/21/2010] [Indexed: 11/28/2022]
Abstract
The Research Challenges in CNS Manifestations of Inborn Errors of Metabolism workshop was designed to address challenges in translating potential therapies for these rare disorders, and to highlight novel therapeutic strategies and innovative approaches to CNS delivery, assessment of effects and directions for the future in the treatment of these diseases. Therapies for the brain in inborn errors represent some of the greatest challenges to translational research due to the special properties of the brain, and of inborn errors themselves. This review covers the proceedings of this workshop as submitted by participants. Scientific, ethical and regulatory issues are discussed, along with ways to measure outcomes and the conduct of clinical trials. Participants included regulatory and funding agencies, clinicians, scientists, industry and advocacy groups.
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Affiliation(s)
- P.I. Dickson
- Department of Pediatrics, LA Biomedical Research Institute at Harbor-UCLA, 1124 W. Carson St, HH1, Torrance, CA 90502
| | - A.R. Pariser
- Office of New Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Avenue, WO22-6474, Silver Spring, MD 20993-0002
| | - S. C. Groft
- Office of Rare Diseases Research, National Institutes of Health, 6100 Executive Boulevard, Room 3A-07, MSC-7518, Bethesda, MD 20892-7518
| | - R.W. Ishihara
- Division of Gastroenterology Products, Office of New Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Ave, WO22-, Silver Spring, MD 20993-0002
| | - D.E. McNeil
- Office of Orphan Product Development, Office of the Commissioner, Food and Drug Administration, 10903 New Hampshire Ave, WO32-5118, Silver Spring, MD 20993-0002
| | - D. Tagle
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Neuroscience Center, Room 2114, 6001 Executive Boulevard, Bethesda, MD 20892
| | - D.J. Griebel
- Division of Gastroenterology Products, Office of New Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Ave, WO22-5112, Silver Spring, MD 20993-0002
| | - S.G. Kaler
- Unit on Human Copper Metabolism, Molecular Medicine Program, National Institute of Child Health and Human Development, National Institutes of Health, 10 Center Drive, Room 5-2571, MSC 1832, Bethesda, MD 20892-1832
| | - J.W. Mink
- Departments of Neurology and Pediatrics, University of Rochester School of Medicine and Dentistry, 601 Elmwood Avenue, Box 631, Rochester, NY 14642
| | - E.G. Shapiro
- Departments of Neurology and Pediatrics, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN 55455
| | - K.J. Bjoraker
- The Children’s Hospital-Denver, University of Colorado, 13123 East 16 Avenue, B-155, Aurora, CO 80045
| | - L. Krivitzky
- Children’s Research Institute, Center for Neuroscience Research, Children’s National Medical Center, National Rehabilitation Hospital, 102 Irving Street, NW, Washington, DC 20010
| | - J.M. Provenzale
- Department of Radiology, Duke University Medical Center, Box 3808 Med Ctr, Durham, NC 27710, and Departments of Radiology, Oncology and Biomedical Engineering, Emory University School of Medicine, Atlanta, GA 30322
| | - A. Gropman
- Neurogenetics Program, Children’s National Medical Center, 111 Michigan Avenue NW, Washington, DC 20010-2970
| | - P. Orchard
- Department of Pediatrics and Institute of Human Genetics, University of Minnesota, 420 Delaware Street SE, Minneapolis, MN 55455
| | - G. Raymond
- Kennedy Krieger Institute and Department of Neurology, Johns Hopkins University, 707 North Broadway, Suite 500, Baltimore, MD 21205
| | - B.H. Cohen
- Neurological Institute, Brain Tumor and Neuro-Oncology Center, Cleveland Clinic, Mail Code S-60, 9500 Euclid Avenue, Cleveland, OH 44195
| | - R.D. Steiner
- Departments of Pediatrics and Molecular and Medical Genetics, Doernbecher Children’s Hospital, Oregon Health & Science University, Mali Code:CDRC, 707 SW Gaines Road, Portland, OR 97239
| | - S. F. Goldkind
- Office of Good Clinical Practice, Office of the Commissioner, Food and Drug Administration, 10903 New Hampshire Avenue, WO32-5110, Silver Spring, MD 20993-0002
| | - R. M. Nelson
- Office of Pediatric Therapeutics, Office of the Commissioner, Food and Drug Administration, 10903 New Hampshire Avenue, WO32-5126, Silver Spring, MD 20993-0002
| | - E. Kakkis
- Kakkis EveryLife Foundation, 77 Digital Drive, Suite 210, Novato, CA 94949
| | - M.C. Patterson
- Division of Child and Adolescent Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
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26
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Orchard P. The Perils of Humanitarianism: Refugee and IDP Protection in Situations of Regime-induced Displacement. Refugee Survey Quarterly 2010. [DOI: 10.1093/rsq/hdq005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
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Boelens J, Aldenhoven M, Purtill D, Eapen M, DeForr T, Wynn R, Cavazanna-Calvo M, Tolar J, Prasad V, Escolar M, Gluckman E, Orchard P, Veys P, Kurtzberg J, Rocha V. Outcomes Of Transplantation Using A Various Cell Source In Children With Hurlers Syndrome After Myelo-Ablative Conditioning. An Eurocord-EBMT-CIBMTR Collaborative Study. Biol Blood Marrow Transplant 2010. [DOI: 10.1016/j.bbmt.2009.12.091] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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28
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Kodali D, Cao Q, Young J, Orchard P, Burns L. 77: Impact of Ribavirin Therapy on Respiratory Syncitial Virus Infection Following Hematopoietic Cell Transplantation. Biol Blood Marrow Transplant 2008. [DOI: 10.1016/j.bbmt.2007.12.085] [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: 10/22/2022]
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29
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Verneris M, Gulbahce E, Burke M, Cao Q, MacMillan M, Tolar J, Orchard P, Blazar B, Baker S, Wagner J. 218: Lower Leukemia Relapse in Patients with Pulmonary Cytolytic Thrombi after Allogeneic Hematopoietic Cell Transplant. Biol Blood Marrow Transplant 2008. [DOI: 10.1016/j.bbmt.2007.12.227] [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: 10/22/2022]
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30
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Tolar J, Bonfim C, Grewal S, Orchard P. Engraftment and survival following hematopoietic stem cell transplantation for osteopetrosis using a reduced intensity conditioning regimen. Bone Marrow Transplant 2006; 38:783-7. [PMID: 17086207 DOI: 10.1038/sj.bmt.1705533] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Autosomal recessive osteopetrosis (OP) is a disease characterized by osteoclast dysfunction, leading to multisystem morbidity and death of most affected children. Hematopoietic stem cell transplantation (HSCT) is the treatment of choice for OP, but this patient population is particularly prone to post-transplant complications and death after myeloablative conditioning. To determine the potential of achieving improved overall outcomes in these patients by decreasing pre-transplant mortality, we investigated engraftment and survival following a reduced intensity regimen including busulfan, fludarabine and total lymphoid irradiation. We report outcomes in 11 patients. All six patients who received a bone marrow or peripheral stem cell graft engrafted with >75% donor chimerism. In contrast, all five recipients of unrelated cord blood as a stem cell source for a first graft failed to demonstrate donor hematopoietic chimerism. The day 100 and 6-month mortality was low at 9%. One year after HSCT, six of 11 patients (55%) were surviving. Our data suggest that this regimen results in low peri-transplant mortality without compromising engraftment when a marrow or peripheral stem cell graft is used. An umbilical cord blood graft, however, should be used with caution for patients with OP when this or a similar reduced intensity regimen is used.
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Affiliation(s)
- J Tolar
- Division of Hematology, Oncology, Blood and Marrow Transplantation, Department of Pediatrics, University of Minnesota, Minneapolis, MN 55455, USA.
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31
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Fraser C, Charnas L, Orchard P. Central pontine myelinolysis following bone marrow transplantation complicated by severe hepatic veno-occlusive disease. Bone Marrow Transplant 2005; 36:733-4. [PMID: 16044132 DOI: 10.1038/sj.bmt.1705115] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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32
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Grewal S, Shapiro E, Braunlin E, Charnas L, Krivit W, Orchard P, Peters C. Continued neurocognitive development and prevention of cardiopulmonary complications after successful BMT for I-cell disease: a long-term follow-up report. Bone Marrow Transplant 2003; 32:957-60. [PMID: 14561999 DOI: 10.1038/sj.bmt.1704249] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
I-cell disease or mucolipidosis type II, a rare inherited storage disorder of lysosomal enzyme localization, is characterized by dysostosis multiplex, progressive severe psychomotor retardation and death by 5-8 years from congestive heart failure and recurrent pulmonary infections. A 19-month old girl with I-cell disease received a bone marrow transplant (BMT) from an HLA-identical carrier brother. At the age of 7 years, 5 years after BMT, she has no history of respiratory infections. Her cardiac function remains normal with a shortening fraction of 47%, and she continues to gain neurodevelopmental milestones, albeit at a very slow rate. Musculoskeletal deformities have worsened despite BMT. This is the first report describing neurodevelopmental gains and prevention of cardiopulmonary complications in I-cell disease after BMT.
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Affiliation(s)
- S Grewal
- Division of Pediatric Blood and Marrow Transplantation, University of Minnesota, Minneapolis, MN 55455, USA.
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33
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Sobacchi C, Frattini A, Orchard P, Porras O, Tezcan I, Andolina M, Babul-Hirji R, Baric I, Canham N, Chitayat D, Dupuis-Girod S, Ellis I, Etzioni A, Fasth A, Fisher A, Gerritsen B, Gulino V, Horwitz E, Klamroth V, Lanino E, Mirolo M, Musio A, Matthijs G, Nonomaya S, Notarangelo LD, Ochs HD, Superti Furga A, Valiaho J, van Hove JL, Vihinen M, Vujic D, Vezzoni P, Villa A. The mutational spectrum of human malignant autosomal recessive osteopetrosis. Hum Mol Genet 2001; 10:1767-73. [PMID: 11532986 DOI: 10.1093/hmg/10.17.1767] [Citation(s) in RCA: 174] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Human malignant infantile osteopetrosis (arOP; MIM 259700) is a genetically heterogeneous autosomal recessive disorder of bone metabolism, which, if untreated, has a fatal outcome. Our group, as well as others, have recently identified mutations in the ATP6i (TCIRG1) gene, encoding the a3 subunit of the vacuolar proton pump, which mediates the acidification of the bone/osteoclast interface, are responsible for a subset of this condition. By sequencing the ATP6i gene in arOP patients from 44 unrelated families with a worldwide distribution we have now established that ATP6i mutations are responsible for approximately 50% of patients affected by this disease. The vast majority of these mutations (40 out of 42 alleles, including seven deletions, two insertions, 10 nonsense substitutions and 21 mutations in splice sites) are predicted to cause severe abnormalities in the protein product and are likely to represent null alleles. In addition, we have also analysed nine unrelated arOP patients from Costa Rica, where this disease is apparently much more frequent than elsewhere. All nine Costa Rican patients bore either or both of two missense mutations (G405R and R444L) in amino acid residues which are evolutionarily conserved from yeast to humans. The identification of ATP6i gene mutations in two families allowed us for the first time to perform prenatal diagnosis: both fetuses were predicted not to be affected and two healthy babies were born. This study contributes to the determination of genetic heterogeneity of arOP and allows further delineation of the other genetic defects causing this severe condition.
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Affiliation(s)
- C Sobacchi
- Department of Human Genome and Multifactorial Disease, Istituto di Tecnologie, Biomediche Avanzate, Consiglio Nazionale delle Ricerche, via Fratelli Cervi 93, 20090 Segrate (MI), Italy
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Horwitz EM, Prockop DJ, Fitzpatrick LA, Koo WW, Gordon PL, Neel M, Sussman M, Orchard P, Marx JC, Pyeritz RE, Brenner MK. Transplantability and therapeutic effects of bone marrow-derived mesenchymal cells in children with osteogenesis imperfecta. Nat Med 1999; 5:309-13. [PMID: 10086387 DOI: 10.1038/6529] [Citation(s) in RCA: 1303] [Impact Index Per Article: 52.1] [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] [Indexed: 12/14/2022]
Abstract
In principle, transplantation of mesenchymal progenitor cells would attenuate or possibly correct genetic disorders of bone, cartilage and muscle, but clinical support for this concept is lacking. Here we describe the initial results of allogeneic bone marrow transplantation in three children with osteogenesis imperfecta, a genetic disorder in which osteoblasts produce defective type I collagen, leading to osteopenia, multiple fractures, severe bony deformities and considerably shortened stature. Three months after osteoblast engraftment (1.5-2.0% donor cells), representative specimens of trabecular bone showed histologic changes indicative of new dense bone formation. All patients had increases in total body bone mineral content ranging from 21 to 29 grams (median, 28), compared with predicted values of 0 to 4 grams (median, 0) for healthy children with similar changes in weight. These improvements were associated with increases in growth velocity and reduced frequencies of bone fracture. Thus, allogeneic bone marrow transplantation can lead to engraftment of functional mesenchymal progenitor cells, indicating the feasibility of this strategy in the treatment of osteogenesis imperfecta and perhaps other mesenchymal stem cell disorders as well.
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Affiliation(s)
- E M Horwitz
- Cell and Gene Therapy Program, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
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Vaidya S, Orchard P, Schroeder N, Haneke R, Brooks K, Thomas A, Corba A, Asfour A, Fish JC. Clinical importance of pre-morteum blood lymphocytes in cadaver donor tissue typing. Clin Transplant 1995; 9:165-70. [PMID: 7549055] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
We have refined our immunomagnetic bead (IM bead) procedures to isolate pure and viable lymphocyte subpopulation from pre-morteum (PM) blood for cadaver donor HLA typing, preliminary and final crossmatches (XMs). The results of 1220 XMs were compared using T/B lymphocytes isolated either from PM blood or spleen/lymphnode (SPLN) tissue. IM bead technique was used to isolate T/B cells from PM blood and nylon wool column (NWC) technique was used to isolate T/B cells from SPLN. When we compared the outcome of 800 T-cell crossmatches using T cells from PM blood or SPLN of 5 separate cadaver donors, NWC TXMs tended to be more falsenegative for high PRA (> 10%, total 500 XMs) as well as low PRA (< 10%, total 300 XMs) did not reach statistical significance. In contrast, NW BXM (420 B XM) were found to be far more false negative than IM bead BXM regardless of the PRA of the patients. In order to ensure that NWC BXMs were indeed false negative, 23 sera with known anti-DR antibodies were BXMed where antigen-specific B cells were isolated by both the techniques. Our results showed that IM bead BXM identified the DR specificities greater than 90% of the time, the titers of ab specificities were stronger (1:8). In comparison, NWB cell XMs were weak (titers 1:2), and the false negative rate for some ab was as high as 73%. Using IM bead and NWC techniques we compared our turnaround time (TAT) for cadaver donor typing, preliminary and final XMs.(ABSTRACT TRUNCATED AT 250 WORDS)
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Affiliation(s)
- S Vaidya
- Department of Pathology, University of Texas Medical Branch, Galveston 77555 0546, U.S.A
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Vaidya S, Orchard P, Haneke R, Fish J. Primary nonfunction and preformed anti-HLA antibodies. Transplant Proc 1995; 27:1033-5. [PMID: 7878791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- S Vaidya
- Department of Pathology, University of Texas Medical Branch, Galveston 77555-0546
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Orchard P, Corba A, Asfour A, Brooks K, Thomas A, Haneke R, Vaidya S. Removal of IGM antibodies: DTT versus immunoreactive beads. Hum Immunol 1994. [DOI: 10.1016/0198-8859(94)91932-1] [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: 11/29/2022]
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Vaidya S, Schroeder N, Orchard P, Ruth J. Cell crossmatches: A comparative study using B cells separated by nylon wool and dynal beads. Hum Immunol 1991. [DOI: 10.1016/0198-8859(91)90316-2] [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: 11/27/2022]
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Hunt M, Till AR, Blair GJ, Bulo D, Orchard P. Studies on native and improved native pastures in South Sulawesi, Indonesia-Effects of sulfur fertilizer and stocking rate on animal production. Asian Australas J Anim Sci 1991. [DOI: 10.5713/ajas.1991.255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Abstract
A case of B-cell non-Hodgkin's lymphoma, confined to the liver, in a 17-year-old boy is reported. The patient was treated with an extended left hepatectomy and combination chemotherapy: Cytoxan (cyclophosphamide), vincristine, prednisone, and methotrexate (COMP). The patient remains disease free at 1 year.
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Affiliation(s)
- M D Pescovitz
- Department of Surgery, Indiana University, Indianapolis
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