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Whitsett JA, Kalin TV, Xu Y, Kalinichenko VV. Building and Regenerating the Lung Cell by Cell. Physiol Rev 2019; 99:513-554. [PMID: 30427276 DOI: 10.1152/physrev.00001.2018] [Citation(s) in RCA: 110] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
The unique architecture of the mammalian lung is required for adaptation to air breathing at birth and thereafter. Understanding the cellular and molecular mechanisms controlling its morphogenesis provides the framework for understanding the pathogenesis of acute and chronic lung diseases. Recent single-cell RNA sequencing data and high-resolution imaging identify the remarkable heterogeneity of pulmonary cell types and provides cell selective gene expression underlying lung development. We will address fundamental issues related to the diversity of pulmonary cells, to the formation and function of the mammalian lung, and will review recent advances regarding the cellular and molecular pathways involved in lung organogenesis. What cells form the lung in the early embryo? How are cell proliferation, migration, and differentiation regulated during lung morphogenesis? How do cells interact during lung formation and repair? How do signaling and transcriptional programs determine cell-cell interactions necessary for lung morphogenesis and function?
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Affiliation(s)
- Jeffrey A Whitsett
- Perinatal Institute, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, Division of Neonatology, Perinatal and Pulmonary Biology, Cincinnati, Ohio
| | - Tanya V Kalin
- Perinatal Institute, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, Division of Neonatology, Perinatal and Pulmonary Biology, Cincinnati, Ohio
| | - Yan Xu
- Perinatal Institute, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, Division of Neonatology, Perinatal and Pulmonary Biology, Cincinnati, Ohio
| | - Vladimir V Kalinichenko
- Perinatal Institute, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, Division of Neonatology, Perinatal and Pulmonary Biology, Cincinnati, Ohio
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Ong MS, Mullen MP, Austin ED, Szolovits P, Natter MD, Geva A, Cai T, Kong SW, Mandl KD. Learning a Comorbidity-Driven Taxonomy of Pediatric Pulmonary Hypertension. Circ Res 2017; 121:341-353. [PMID: 28611076 PMCID: PMC5559726 DOI: 10.1161/circresaha.117.310804] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 06/07/2017] [Accepted: 06/12/2017] [Indexed: 11/16/2022]
Abstract
RATIONALE Pediatric pulmonary hypertension (PH) is a heterogeneous condition with varying natural history and therapeutic response. Precise classification of PH subtypes is, therefore, crucial for individualizing care. However, gaps remain in our understanding of the spectrum of PH in children. OBJECTIVE We seek to study the manifestations of PH in children and to assess the feasibility of applying a network-based approach to discern disease subtypes from comorbidity data recorded in longitudinal data sets. METHODS AND RESULTS A retrospective cohort study comprising 6 943 263 children (<18 years of age) enrolled in a commercial health insurance plan in the United States, between January 2010 and May 2013. A total of 1583 (0.02%) children met the criteria for PH. We identified comorbidities significantly associated with PH compared with the general population of children without PH. A Bayesian comorbidity network was constructed to model the interdependencies of these comorbidities, and network-clustering analysis was applied to derive disease subtypes comprising subgraphs of highly connected comorbid conditions. A total of 186 comorbidities were found to be significantly associated with PH. Network analysis of comorbidity patterns captured most of the major PH subtypes with known pathological basis defined by the World Health Organization and Panama classifications. The analysis further identified many subtypes documented in only a few case studies, including rare subtypes associated with several well-described genetic syndromes. CONCLUSIONS Application of network science to model comorbidity patterns recorded in longitudinal data sets can facilitate the discovery of disease subtypes. Our analysis relearned established subtypes, thus validating the approach, and identified rare subtypes that are difficult to discern through clinical observations, providing impetus for deeper investigation of the disease subtypes that will enrich current disease classifications.
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Affiliation(s)
- Mei-Sing Ong
- From the Computational Health Informatics Program (M.-S.O., M.D.N., A.G., S.W.K., K.D.M.), Department of Cardiology (M.P.M.), Division of Critical Care Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine (A.G.), and Department of Anesthesia (A.G.), Harvard School of Medicine, Boston Children's Hospital, MA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (E.D.A.); Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (P.S.); Department of Pediatrics, Massachusetts General Hospital, Boston (M.D.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, MA. (T.C.).
| | - Mary P Mullen
- From the Computational Health Informatics Program (M.-S.O., M.D.N., A.G., S.W.K., K.D.M.), Department of Cardiology (M.P.M.), Division of Critical Care Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine (A.G.), and Department of Anesthesia (A.G.), Harvard School of Medicine, Boston Children's Hospital, MA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (E.D.A.); Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (P.S.); Department of Pediatrics, Massachusetts General Hospital, Boston (M.D.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, MA. (T.C.)
| | - Eric D Austin
- From the Computational Health Informatics Program (M.-S.O., M.D.N., A.G., S.W.K., K.D.M.), Department of Cardiology (M.P.M.), Division of Critical Care Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine (A.G.), and Department of Anesthesia (A.G.), Harvard School of Medicine, Boston Children's Hospital, MA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (E.D.A.); Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (P.S.); Department of Pediatrics, Massachusetts General Hospital, Boston (M.D.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, MA. (T.C.)
| | - Peter Szolovits
- From the Computational Health Informatics Program (M.-S.O., M.D.N., A.G., S.W.K., K.D.M.), Department of Cardiology (M.P.M.), Division of Critical Care Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine (A.G.), and Department of Anesthesia (A.G.), Harvard School of Medicine, Boston Children's Hospital, MA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (E.D.A.); Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (P.S.); Department of Pediatrics, Massachusetts General Hospital, Boston (M.D.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, MA. (T.C.)
| | - Marc D Natter
- From the Computational Health Informatics Program (M.-S.O., M.D.N., A.G., S.W.K., K.D.M.), Department of Cardiology (M.P.M.), Division of Critical Care Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine (A.G.), and Department of Anesthesia (A.G.), Harvard School of Medicine, Boston Children's Hospital, MA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (E.D.A.); Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (P.S.); Department of Pediatrics, Massachusetts General Hospital, Boston (M.D.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, MA. (T.C.)
| | - Alon Geva
- From the Computational Health Informatics Program (M.-S.O., M.D.N., A.G., S.W.K., K.D.M.), Department of Cardiology (M.P.M.), Division of Critical Care Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine (A.G.), and Department of Anesthesia (A.G.), Harvard School of Medicine, Boston Children's Hospital, MA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (E.D.A.); Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (P.S.); Department of Pediatrics, Massachusetts General Hospital, Boston (M.D.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, MA. (T.C.)
| | - Tianxi Cai
- From the Computational Health Informatics Program (M.-S.O., M.D.N., A.G., S.W.K., K.D.M.), Department of Cardiology (M.P.M.), Division of Critical Care Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine (A.G.), and Department of Anesthesia (A.G.), Harvard School of Medicine, Boston Children's Hospital, MA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (E.D.A.); Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (P.S.); Department of Pediatrics, Massachusetts General Hospital, Boston (M.D.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, MA. (T.C.)
| | - Sek Won Kong
- From the Computational Health Informatics Program (M.-S.O., M.D.N., A.G., S.W.K., K.D.M.), Department of Cardiology (M.P.M.), Division of Critical Care Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine (A.G.), and Department of Anesthesia (A.G.), Harvard School of Medicine, Boston Children's Hospital, MA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (E.D.A.); Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (P.S.); Department of Pediatrics, Massachusetts General Hospital, Boston (M.D.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, MA. (T.C.)
| | - Kenneth D Mandl
- From the Computational Health Informatics Program (M.-S.O., M.D.N., A.G., S.W.K., K.D.M.), Department of Cardiology (M.P.M.), Division of Critical Care Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine (A.G.), and Department of Anesthesia (A.G.), Harvard School of Medicine, Boston Children's Hospital, MA; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN (E.D.A.); Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (P.S.); Department of Pediatrics, Massachusetts General Hospital, Boston (M.D.N.); and Department of Biostatistics, Harvard School of Public Health, Boston, MA. (T.C.)
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Prosnitz AR, Leopold J, Irons M, Jenkins K, Roberts AE. Pulmonary vein stenosis in patients with Smith-Lemli-Opitz syndrome. CONGENIT HEART DIS 2017; 12:475-483. [PMID: 28719049 DOI: 10.1111/chd.12471] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2016] [Revised: 03/16/2017] [Accepted: 04/14/2017] [Indexed: 12/13/2022]
Abstract
OBJECTIVE To describe a group of children with co-incident pulmonary vein stenosis and Smith-Lemli-Opitz syndrome and to generate hypotheses as to the shared pathogenesis of these disorders. DESIGN Retrospective case series. PATIENTS Five subjects in a pulmonary vein stenosis cohort of 170 subjects were diagnosed with Smith-Lemli-Opitz syndrome soon after birth. RESULTS All five cases were diagnosed with Smith-Lemli-Opitz syndrome within 6 weeks of life, with no family history of either disorder. All cases had pathologically elevated 7-dehydrocholesterol levels and two of the five cases had previously reported pathogenic 7-dehydrocholesterol reductase mutations. Smith-Lemli-Opitz syndrome severity scores ranged from mild to classical (2-7). Gestational age at birth ranged from 35 to 39 weeks. Four of the cases were male by karyotype. Pulmonary vein stenosis was diagnosed in all cases within 2 months of life, earlier than most published cohorts. All cases progressed to bilateral disease and three cases developed atresia of at least one vein. Despite catheter and surgical interventions, all subjects' pulmonary vein stenosis rapidly recurred and progressed. Three of the subjects died, at 2 months, 3 months, and 11 months. Survival at 16 months after diagnosis was 43%. CONCLUSIONS Patients with pulmonary vein stenosis who have a suggestive syndromic presentation should be screened for Smith-Lemli-Opitz syndrome with easily obtainable serum sterol tests. Echocardiograms should be obtained in all newly diagnosed patients with Smith-Lemli-Opitz syndrome, with a low threshold for repeating the study if new respiratory symptoms of uncertain etiology arise. Further studies into the pathophysiology of pulmonary vein stenosis should consider the role of cholesterol-based signaling pathways in the promotion of intimal proliferation.
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Affiliation(s)
- Aaron R Prosnitz
- Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Jane Leopold
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Mira Irons
- American Board of Medical Specialties, Chicago, Illinois, USA
| | - Kathy Jenkins
- Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Amy E Roberts
- Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA
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Nowaczyk MJM, Irons MB. Smith-Lemli-Opitz syndrome: phenotype, natural history, and epidemiology. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2012; 160C:250-62. [PMID: 23059950 DOI: 10.1002/ajmg.c.31343] [Citation(s) in RCA: 93] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Smith-Lemli-Opitz syndrome (SLOS) is a congenital multiple anomaly/intellectual disability syndrome caused by a deficiency of cholesterol synthesis resulting from a deficiency of 7-dehydrocholesterol (7DHC) reductase encoded by DHCR7. SLOS is inherited in an autosomal recessive pattern. It is characterized by prenatal and postnatal growth retardation, microcephaly, a variable degree of intellectual disability that encompasses normal intelligence to severe intellectual deficiency, and multiple major and minor malformations. External malformations include distinctive facial features, cleft palate, postaxial polydactyly, 2-3 syndactyly of the toes, and underdeveloped external genitalia in males, while internal anomalies may affect every organ system. The clinical spectrum is wide, and rare individuals have been described with normal development and only minor malformations. The clinical diagnosis of SLOS is confirmed by demonstrating an abnormally elevated concentration of the cholesterol precursor, 7DHC, in serum or other tissues, or by the presence of two DHCR7 mutations. The enzymatic deficiency results in decreased cholesterol and increased 7DHC levels, both during embryonic development and after birth. The malformations found in SLOS may result from decreased cholesterol, increased 7DHC or a combination of these two factors. This review discusses the physical and behavioral phenotype of SLOS, the diagnostic approaches, the natural history from the prenatal period to adulthood, and current understanding of the pathophysiology of SLOS.
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Affiliation(s)
- Małgorzata J M Nowaczyk
- Department of Pathology and Molecular Medicine and Department of Pediatrics, McMaster University McMaster University Medical Centre, Room 3N16, 1200 Main Street West, Hamilton ON, Canada L8S 4J9.
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Ren G, Jacob RF, Kaulin Y, DiMuzio P, Xie Y, Mason RP, Tint GS, Steiner RD, Roulett JB, Merkens L, Whitaker-Mendez D, Frank PG, Lisanti M, Cox RH, Tulenko TN. Alterations in membrane caveolae and BKCa channel activity in skin fibroblasts in Smith-Lemli-Opitz syndrome. Mol Genet Metab 2011; 104:346-55. [PMID: 21724437 PMCID: PMC3365561 DOI: 10.1016/j.ymgme.2011.04.019] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2011] [Accepted: 04/30/2011] [Indexed: 12/20/2022]
Abstract
The Smith-Lemli-Opitz syndrome (SLOS) is an inherited disorder of cholesterol synthesis caused by mutations in DHCR7 which encodes the final enzyme in the cholesterol synthesis pathway. The immediate precursor to cholesterol synthesis, 7-dehydrocholesterol (7-DHC) accumulates in the plasma and cells of SLOS patients which has led to the idea that the accumulation of abnormal sterols and/or reduction in cholesterol underlies the phenotypic abnormalities of SLOS. We tested the hypothesis that 7-DHC accumulates in membrane caveolae where it disturbs caveolar bilayer structure-function. Membrane caveolae from skin fibroblasts obtained from SLOS patients were isolated and found to accumulate 7-DHC. In caveolar-like model membranes containing 7-DHC, subtle, but complex alterations in intermolecular packing, lipid order and membrane width were observed. In addition, the BK(Ca) K(+) channel, which co-migrates with caveolin-1 in a membrane fraction enriched with cholesterol, was impaired in SLOS cells as reflected by reduced single channel conductance and a 50 mV rightward shift in the channel activation voltage. In addition, a marked decrease in BK(Ca) protein but not mRNA expression levels was seen suggesting post-translational alterations. Accompanying these changes was a reduction in caveolin-1 protein and mRNA levels, but membrane caveolar structure was not altered. These results are consistent with the hypothesis that 7-DHC accumulation in the caveolar membrane results in defective caveolar signaling. However, additional cellular alterations beyond mere changes associated with abnormal sterols in the membrane likely contribute to the pathogenesis of SLOS.
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Affiliation(s)
- Gongyi Ren
- Department of Surgery, Cooper University Hospital, Camden, NJ
| | - Robert F. Jacob
- Elucida Research LLC, Beverly, MA, Department of Surgery, Thomas Jefferson University College of Medicine, Philadelphia, PA
| | - Yuri Kaulin
- Department of Anatomy and Cell Biology, Thomas Jefferson University College of Medicine, Philadelphia, PA
| | - Paul DiMuzio
- Elucida Research LLC, Beverly, MA, Department of Surgery, Thomas Jefferson University College of Medicine, Philadelphia, PA
| | - Yi Xie
- Department of Surgery, Cooper University Hospital, Camden, NJ
| | - R. Preston Mason
- Elucida Research LLC, Beverly, MA, Department of Surgery, Thomas Jefferson University College of Medicine, Philadelphia, PA
- Brigham & Women's Hospital, Harvard Medical School, Boston, MA
| | - G. Stephen Tint
- Research Service, Department of Veterans Affairs Medical Center, East Orange, NJ and Department of Medicine, UMDNJ-New Jersey Medical School, Newark, NJ
| | - Robert D. Steiner
- Departments of Pediatrics and Molecular & Medical Genetics, Child Development and Rehabilitation Center, Doernbecher Children’s Hospital, Oregon Health & Science University, Portland, OR
| | - Jean-Baptiste Roulett
- Departments of Pediatrics and Molecular & Medical Genetics, Child Development and Rehabilitation Center, Doernbecher Children’s Hospital, Oregon Health & Science University, Portland, OR
| | - Louise Merkens
- Departments of Pediatrics and Molecular & Medical Genetics, Child Development and Rehabilitation Center, Doernbecher Children’s Hospital, Oregon Health & Science University, Portland, OR
| | - Diana Whitaker-Mendez
- Department of Stem Cell Biology & Regenerative Medicine, and Cancer Biology, Thomas Jefferson University College of Medicine, Philadelphia, PA
| | - Phillipe G. Frank
- Department of Stem Cell Biology & Regenerative Medicine, and Cancer Biology, Thomas Jefferson University College of Medicine, Philadelphia, PA
| | - Michael Lisanti
- Department of Stem Cell Biology & Regenerative Medicine, and Cancer Biology, Thomas Jefferson University College of Medicine, Philadelphia, PA
| | - Robert H. Cox
- Lankenau Institute for Medical Research, Wynnewood, PA
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