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Botz J, Lohner V, Schirmer MD. Spatial patterns of white matter hyperintensities: a systematic review. Front Aging Neurosci 2023; 15:1165324. [PMID: 37251801 PMCID: PMC10214839 DOI: 10.3389/fnagi.2023.1165324] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 04/24/2023] [Indexed: 05/31/2023] Open
Abstract
Background White matter hyperintensities are an important marker of cerebral small vessel disease. This disease burden is commonly described as hyperintense areas in the cerebral white matter, as seen on T2-weighted fluid attenuated inversion recovery magnetic resonance imaging data. Studies have demonstrated associations with various cognitive impairments, neurological diseases, and neuropathologies, as well as clinical and risk factors, such as age, sex, and hypertension. Due to their heterogeneous appearance in location and size, studies have started to investigate spatial distributions and patterns, beyond summarizing this cerebrovascular disease burden in a single metric-its volume. Here, we review the evidence of association of white matter hyperintensity spatial patterns with its risk factors and clinical diagnoses. Design/methods We performed a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement. We used the standards for reporting vascular changes on neuroimaging criteria to construct a search string for literature search on PubMed. Studies written in English from the earliest records available until January 31st, 2023, were eligible for inclusion if they reported on spatial patterns of white matter hyperintensities of presumed vascular origin. Results A total of 380 studies were identified by the initial literature search, of which 41 studies satisfied the inclusion criteria. These studies included cohorts based on mild cognitive impairment (15/41), Alzheimer's disease (14/41), Dementia (5/41), Parkinson's disease (3/41), and subjective cognitive decline (2/41). Additionally, 6 of 41 studies investigated cognitively normal, older cohorts, two of which were population-based, or other clinical findings such as acute ischemic stroke or reduced cardiac output. Cohorts ranged from 32 to 882 patients/participants [median cohort size 191.5 and 51.6% female (range: 17.9-81.3%)]. The studies included in this review have identified spatial heterogeneity of WMHs with various impairments, diseases, and pathologies as well as with sex and (cerebro)vascular risk factors. Conclusion The results show that studying white matter hyperintensities on a more granular level might give a deeper understanding of the underlying neuropathology and their effects. This motivates further studies examining the spatial patterns of white matter hyperintensities.
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Affiliation(s)
- Jonas Botz
- Computational Neuroradiology, Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany
| | - Valerie Lohner
- Cardiovascular Epidemiology of Aging, Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Markus D. Schirmer
- Computational Neuroradiology, Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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2
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Yang Y, Knol MJ, Wang R, Mishra A, Liu D, Luciano M, Teumer A, Armstrong N, Bis JC, Jhun MA, Li S, Adams HHH, Aziz NA, Bastin ME, Bourgey M, Brody JA, Frenzel S, Gottesman RF, Hosten N, Hou L, Kardia SLR, Lohner V, Marquis P, Maniega SM, Satizabal CL, Sorond FA, Valdés Hernández MC, van Duijn CM, Vernooij MW, Wittfeld K, Yang Q, Zhao W, Boerwinkle E, Levy D, Deary IJ, Jiang J, Mather KA, Mosley TH, Psaty BM, Sachdev PS, Smith JA, Sotoodehnia N, DeCarli CS, Breteler MMB, Ikram MA, Grabe HJ, Wardlaw J, Longstreth WT, Launer LJ, Seshadri S, Debette S, Fornage M. Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI. Brain 2023; 146:492-506. [PMID: 35943854 PMCID: PMC9924914 DOI: 10.1093/brain/awac290] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [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: 02/18/2022] [Revised: 06/23/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.
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Affiliation(s)
- Yunju Yang
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science at Houston, Houston, TX 77030, USA
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Ruiqi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Aniket Mishra
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, F-33000 Bordeaux, France
| | - Dan Liu
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Michelle Luciano
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17475, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald 17475, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, 15-269, Poland
| | - Nicola Armstrong
- Mathematics and Statistics, Curtin University, 6845 Perth, Australia
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
| | - Min A Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Shuo Li
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Hieab H H Adams
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Nasir Ahmad Aziz
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, 53127 Bonn, Germany
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - Mathieu Bourgey
- Canadian Centre for Computational Genomics, McGill University, Montréal, Quebec, Canada H3A 0G1
- Department for Human Genetics, McGill University Genome Centre, McGill University, Montréal, Quebec, Canada H3A 0G1
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
| | - Rebecca F Gottesman
- Stroke Branch, National Institutes of Neurological Disorders and Stroke, Bethesda, MD 20814, USA
| | - Norbert Hosten
- Department of Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Valerie Lohner
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Pascale Marquis
- Canadian Centre for Computational Genomics, McGill University, Montréal, Quebec, Canada H3A 0G1
- Department for Human Genetics, McGill University Genome Centre, McGill University, Montréal, Quebec, Canada H3A 0G1
| | - Susana Muñoz Maniega
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases and Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX 78229, USA
- The Framingham Heart Study, Framingham, MA 01701, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02115, USA
| | - Farzaneh A Sorond
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Maria C Valdés Hernández
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
- Nuffield Department of Population Health, Oxford University, Oxford, OX3 7LF, UK
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Rostock, Germany
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- The Framingham Heart Study, Framingham, MA 01701, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, University of Texas Health Science at Houston, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Daniel Levy
- The Framingham Heart Study, Framingham, MA 01701, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia
- Neuroscience Research Australia, Sydney, NSW 2031, Australia
| | - Thomas H Mosley
- The Memory Impairment Neurodegenerative Dementia (MIND) Research Center, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
- Department of Epidemiology, University of Washington, Seattle, WA 98104, USA
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital, University of New South Wales, Randwick, NSW 2031, Australia
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48104, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 02115, USA
| | - Charles S DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA 95816, USA
| | - Monique M B Breteler
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, 53127 Bonn, Germany
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 GD, Rotterdam, The Netherlands
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald 17475, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, 17475 Rostock, Germany
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK
| | - W T Longstreth
- Department of Epidemiology, University of Washington, Seattle, WA 98104, USA
- Department of Neurology, University of Washington, Seattle, WA 98104, USA
| | - Lenore J Launer
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases and Department of Population Health Sciences, UT Health San Antonio, San Antonio, TX 78229, USA
- The Framingham Heart Study, Framingham, MA 01701, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02115, USA
| | - Stephanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, F-33000 Bordeaux, France
- Department of Neurology, Boston University School of Medicine, Boston, MA 02115, USA
- CHU de Bordeaux, Department of Neurology, F-33000 Bordeaux, France
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science at Houston, Houston, TX 77030, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science at Houston, Houston, TX 77030, USA
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3
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Lohner V, McNeill A, Schneider S, Vollstädt-Klein S, Andreas M, Szafran D, Grundinger N, Demjén T, Fernandez E, Przewozniak K, Tountas Y, Trofor A, Zatonski W, Willemsen MC, Vardavas C, Fong GT, Mons U. Understanding perceived addiction to and addictiveness of electronic cigarettes among electronic cigarette users: a cross-sectional analysis of the International Tobacco Control Smoking and Vaping (ITC 4CV) England Survey. Addiction 2023. [PMID: 36772958 DOI: 10.1111/add.16162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 01/25/2023] [Indexed: 02/12/2023]
Abstract
BACKGROUND AND AIMS The addictive potential of electronic cigarettes (e-cigarettes) remains to be fully understood. We identified patterns and correlates of perceived addiction to e-cigarettes and perceived addictiveness of e-cigarettes relative to tobacco cigarettes (relative addictiveness) in dual users as well as exclusive e-cigarette users. DESIGN, SETTING AND PARTICIPANTS Observational study using cross-sectional survey data from England (2016) from the International Tobacco Control Project (ITC) Four Country Smoking and Vaping (4CV) survey. The study comprised 832 current e-cigarette users who had been vaping for at least 4 months. MEASUREMENTS Perceived addiction to e-cigarettes and relative addictiveness of e-cigarettes were examined. Socio-demographic factors were age, gender and education; markers of addiction included urge to vape, time to first vape after waking and nicotine strength used; vaping and smoking characteristics included frequency and duration of e-cigarette use, intention to quit, adjustable power or temperature, enjoyment, satisfaction relative to tobacco cigarettes and tobacco cigarette smoking status. FINDINGS A total of 17% of participants reported feeling very addicted to e-cigarettes, while 40% considered e-cigarettes equally/more addictive than tobacco cigarettes. Those who felt very addicted had higher odds of regarding e-cigarettes as more addictive than tobacco cigarettes (odds ratio 3.4, 95% confidence interval 2.3-5.1). All markers of addiction, daily use and enjoyment were associated with higher perceived addiction, whereas time to first vape after waking, daily vaping and perceiving vaping as less satisfying than smoking were associated with relative addictiveness. CONCLUSIONS Markers of addiction to e-cigarettes appear to correspond with perceived addiction to e-cigarettes, suggesting that self-reported perceived addiction might serve as an indicator of addiction. Prevalence both of markers of addiction and perceived addiction were comparatively low overall, suggesting a limited but relevant addictive potential of e-cigarettes. Additionally, positive and negative reinforcement, reflected here by enjoyment and relative satisfaction, might play a role in e-cigarette addiction.
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Affiliation(s)
- Valerie Lohner
- Cardiovascular Epidemiology of Aging, Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
| | - Ann McNeill
- National Addiction Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Shaping Public Health Policies to Reduce Inequalities and Harm (SPECTRUM), UK
| | - Sven Schneider
- Center for Preventive Medicine and Digital Health Baden-Württemberg, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Sabine Vollstädt-Klein
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Mannheim Center for Translational Neurosciences (MCTN), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marike Andreas
- Center for Preventive Medicine and Digital Health Baden-Württemberg, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Daria Szafran
- Center for Preventive Medicine and Digital Health Baden-Württemberg, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Nadja Grundinger
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Tibor Demjén
- Smoking or Health Hungarian Foundation, Budapest, Hungary
| | - Esteve Fernandez
- Tobacco Control Unit and WHO Collaborating Center for Tobacco Control, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain.,School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain.,Consortium for Biomedical Research in Respiratory Diseases (CIBERES), Madrid, Spain
| | - Krzysztof Przewozniak
- Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland.,Collegium Civitas, Warsaw, Poland.,Health Promotion Foundation, Warsaw, Poland
| | - Yannis Tountas
- Center for Health Services Research, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Antigona Trofor
- University of Medicine and Pharmacy 'Grigore T. Popa' Iasi, Iasi, Romania.,Aer Pur Romania, Bucharest, Romania
| | - Witold Zatonski
- Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland.,European Observatory of Health Inequalities, President Stanisław Wojciechowski State University of Applied Sciences, Kalisz, Poland
| | - Marc C Willemsen
- Maastricht University, Department of Health Promotion (CAPHRI), Maastricht, the Netherlands.,Trimbos Institute, Netherlands Expertise Centre for Tobacco Control, Utrecht, the Netherlands
| | - Constantine Vardavas
- School of Medicine, University of Crete, Crete, Greece.,Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Boston, MA, USA
| | - Geoffrey T Fong
- Department of Psychology, University of Waterloo, Waterloo, ON, Canada.,School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada.,Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Ute Mons
- Cardiovascular Epidemiology of Aging, Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
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4
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Mavragani A, Görig T, Vollstädt-Klein S, Grundinger N, Mons U, Lohner V, Schneider S, Andreas M. Addictive Potential of e-Cigarettes as Reported in e-Cigarette Online Forums: Netnographic Analysis of Subjective Experiences. J Med Internet Res 2023; 25:e41669. [PMID: 36607713 PMCID: PMC9862333 DOI: 10.2196/41669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 11/03/2022] [Accepted: 11/08/2022] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND While e-cigarettes usually contain nicotine, their addictive potential is not yet fully understood. We hypothesized that if e-cigarettes are addictive, users will experience typical symptoms of addiction. OBJECTIVE The aim of our study was to investigate whether and how e-cigarette users report signs of addiction. METHODS We identified 3 large German-language e-cigarette online forums via a systematic Google search. Based on a netnographic approach, we used deductive content analysis to investigate relevant posts in these forums. Netnography has the advantage of limiting the social desirability bias that prevails in face-to-face research, such as focus groups. The data were coded according to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria for tobacco use disorder, adapted for e-cigarettes. The DSM-5 criteria were used to portray a broad spectrum of possible experiences of addiction. RESULTS Overall, 5337 threads in 3 forums were screened, and 451 threads containing relevant information were included in the analysis. Users reported experiences consistent with the DSM-5 criteria, such as craving e-cigarettes, excessive time spent vaping, and health issues related to e-cigarette use. However, our analysis also showed that users reported the absence of typical tobacco use disorder criteria, such as successful attempts to reduce the nicotine dosage. For most themes, reports of their absence were more frequent than of their presence. The absence of perceived addiction was mostly reported in contrast to prior tobacco smoking. CONCLUSIONS This is the first study to use a netnographic approach to explore unfiltered self-reports of experiences of e-cigarette addiction by users in online forums. As hypothesized, some but not all users reported subjective experiences that corresponded to the criteria of tobacco use disorder as defined by the DSM-5. Nevertheless, subjective reports also indicated that many e-cigarette users felt in control of their behavior, especially in contrast to their prior use of tobacco cigarettes. The finding that some e-cigarette users subjectively experience addiction highlights the need for effective cessation programs to support users who experience their e-cigarette use as burdensome. This research can guide the refinement of instruments to assess e-cigarette addiction and guide cessation programs. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.1186/s40359-021-00682-8.
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Affiliation(s)
| | - Tatiana Görig
- Department of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Sabine Vollstädt-Klein
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty of Mannheim, University of Heidelberg, Mannheim, Germany.,Mannheim Center for Translational Neurosciences, Medical Faculty of Mannheim, University of Heidelberg, Mannheim, Germany
| | - Nadja Grundinger
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty of Mannheim, University of Heidelberg, Mannheim, Germany
| | - Ute Mons
- Cardiovascular Epidemiology of Aging, Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Valerie Lohner
- Cardiovascular Epidemiology of Aging, Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Sven Schneider
- Division of Public Health, Social and Preventive Medicine, Center for Preventive Medicine and Digital Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marike Andreas
- Division of Public Health, Social and Preventive Medicine, Center for Preventive Medicine and Digital Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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5
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Lohner V, Schneider S, Andreas M, Szafran D, Grundinger N, Vollstädt-Klein S, Fong GT, McNeill A, Mons U. Understanding addiction in e-cigarette users – the EVAPE project. Eur J Public Health 2022. [DOI: 10.1093/eurpub/ckac130.078] [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: 11/12/2022] Open
Abstract
Abstract
Background
Electronic cigarettes (e-cigarettes) are often advertised as a healthier option to combustible cigarettes and as smoking cessation aid. However, e-cigarettes are a growing health concern and their addictive potential remains to be fully understood. Within the EValuation of the Addictive Potential of E-cigarettes (EVAPE) project, we studied subjective and objective measures of addiction in relation to e-cigarette use.
Methods
This cross-sectional analysis was based on 832 participants of the first wave (2016) of England from the ITC Four Country Smoking and Vaping (4CV) Survey, who were using e-cigarettes daily or weekly for at least four months. Perceived addiction to e-cigarettes was categorised as very vs. not/somewhat addicted, and perceived addictiveness of e-cigarettes relative to combustible cigarettes as equally/more addictive vs. less addictive. Objective measures of addiction included urge to vape, time to first vape after waking, frequency of use, and used nicotine strength. We examined associations between these objective and subjective measures of addiction using multivariate logistic regression, adjusted for age, gender, education, and cigarette smoking.
Results
17.8% of participants reported feeling very addicted to e-cigarettes and 42.3% considered e-cigarettes equally/more addictive than combustible cigarettes. Those who felt very addicted had higher odds of regarding e-cigarettes as more addictive (OR 3.43 (95%-CI 2.29-5.19)). All objective measures of addiction were associated with higher perceived addiction, whereas only a shorter time to first vape was associated with perceived product addictiveness.
Conclusions
Subjective measures of addiction to e-cigarettes, in particular perceived addiction, correspond with objective measures. Understanding the addictive potential of e-cigarettes is the cornerstone for developing new strategies for prevention and treatment, and ultimately understanding their role from a public health perspective.
Key messages
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Affiliation(s)
- V Lohner
- Department of Cardiology, University of Cologne , Cologne, Germany
| | - S Schneider
- Medical Faculty Mannheim, University of Heidelberg , Mannheim, Germany
| | - M Andreas
- Medical Faculty Mannheim, University of Heidelberg , Mannheim, Germany
| | - D Szafran
- Medical Faculty Mannheim, University of Heidelberg , Mannheim, Germany
| | - N Grundinger
- Medical Faculty Mannheim, University of Heidelberg , Mannheim, Germany
| | - S Vollstädt-Klein
- Medical Faculty Mannheim, University of Heidelberg , Mannheim, Germany
| | - GT Fong
- Department of Psychology, University of Waterloo , Waterloo, Canada
- School of Public Health Sciences, University of Waterloo , Waterloo, Canada
- Ontario Institute for Cancer Research , Toronto, Canada
| | - A McNeill
- Psychology and Neuroscience, King’s College London , London, UK
- SPECTRUM , London, UK
| | - U Mons
- Department of Cardiology, University of Cologne , Cologne, Germany
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6
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Andreas M, Szafran D, Vollstädt-Klein S, Grundinger N, Mons U, Lohner V, Görig T, Schneider S. „Dauernuckler“ oder „Genussdampfer“?
Eine netnographische Analyse selbstberichteter Anzeichen möglicher
Abhängigkeitssymptome in E-Zigaretten-Online-Foren. Das Gesundheitswesen 2022. [DOI: 10.1055/s-0042-1753571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- M Andreas
- Medical Faculty of Mannheim, University of Heidelberg, Center for
Preventive Medicine and Digital Health Baden-Württemberg (CPD-BW),
Mannheim, Deutschland
| | - D Szafran
- Medical Faculty of Mannheim, University of Heidelberg, Center for
Preventive Medicine and Digital Health Baden-Württemberg (CPD-BW),
Mannheim, Deutschland
| | - S Vollstädt-Klein
- Medical Faculty of Mannheim, University of Heidelberg, Department of
Addictive Behavior and Addiction Medicine, Central Institute of Mental Health,
Mannheim, Deutschland
- Medical Faculty of Mannheim, University of Heidelberg, Mannheim Center
for Translational Neurosciences (MCTN), Mannheim, Deutschland
| | - N Grundinger
- Medical Faculty of Mannheim, University of Heidelberg, Department of
Addictive Behavior and Addiction Medicine, Central Institute of Mental Health,
Mannheim, Deutschland
| | - U Mons
- University of Cologne, Medical Faculty and University Hospital Cologne,
Köln, Deutschland
| | - V Lohner
- University of Cologne, Medical Faculty and University Hospital Cologne,
Köln, Deutschland
| | - T Görig
- Friedrich-Alexander-University Erlangen-Nürnberg, Institute for
Medical Informatics, Biometry and Epidemiology, Erlangen,
Deutschland
| | - S Schneider
- Medical Faculty of Mannheim, University of Heidelberg, Center for
Preventive Medicine and Digital Health Baden-Württemberg (CPD-BW),
Mannheim, Deutschland
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7
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Lohner V, Pehlivan G, Sanroma G, Miloschewski A, Schirmer MD, Stöcker T, Reuter M, Breteler MMB. The Relation Between Sex, Menopause, and White Matter Hyperintensities: The Rhineland Study. Neurology 2022; 99:e935-e943. [PMID: 35768207 DOI: 10.1212/wnl.0000000000200782] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 04/11/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVE Mounting evidence implies that there are sex differences in white matter hyperintensity (WMH) burden in the elderly. Questions remain regarding possible differences in WMH burden between men and women of younger age, sex-specific age trajectories and effects of (un)controlled hypertension, and the effect of menopause on WMH. Therefore, our aim is to investigate these sex differences and age-dependencies in WMH load across the adult life span, and to examine the effect of menopause. METHODS This cross-sectional analysis was based on participants of the population-based Rhineland Study (30 - 95 years) who underwent brain MRI. We automatically quantified WMH using T1-weighted, T2-weighted and FLAIR images. Menopausal status was self-reported. We examined associations of sex and menopause with WMH load (logit-transformed and z-standardised) using linear regression models, while adjusting for age, age-squared, and vascular risk factors. We checked for an age*sex and (un)controlled hypertension*sex interaction and stratified for menopausal status comparing men with premenopausal women (persons aged ≤ 59 years), men with postmenopausal women (persons aged ≥ 45 years), and pre- with postmenopausal women (age range 45 - 59 years). RESULTS Of 3410 participants with a mean age of 54.3 years (SD = 13.7), 1973 (57.9%) were women, of which 1167 (59.1%) were postmenopausal. We found that the increase in WMH load accelerates with age and in a sex-dependent way. Premenopausal women and men of similar age did not differ in WMH burden. WMH burden was higher and accelerated faster in postmenopausal women compared to men of similar age. Additionally, we observed changes related to menopause, in that postmenopausal women had more WMH than premenopausal women of similar age.. Women with uncontrolled hypertension had a higher WMH burden compared to men, which was unrelated to menopausal status. DISCUSSION After menopause, women displayed a higher burden of WMH than contemporary premenopausal women and men, and an accelerated increase in WMH. Sex-specific effects of uncontrolled hypertension on WMH were not related to menopause. Further studies are warranted to investigate menopause-related physiological changes, that may inform on causal mechanisms involved in cerebral small vessel disease progression.
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Affiliation(s)
- Valerie Lohner
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Gökhan Pehlivan
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Gerard Sanroma
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Anne Miloschewski
- Statistics and Machine Learning, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Markus D Schirmer
- J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, Boston.,Clinic for Neuroradiology, University Hospital Bonn, Germany
| | - Tony Stöcker
- MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Physics and Astronomy, University of Bonn, Bonn, Germany
| | - Martin Reuter
- Image Analysis, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany .,Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Germany
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8
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Lohner V, Enkirch SJ, Hattingen E, Stöcker T, Breteler MMB. Safety of Tattoos, Permanent Make-Up, and Medical Implants in Population-Based 3T Magnetic Resonance Brain Imaging: The Rhineland Study. Front Neurol 2022; 13:795573. [PMID: 35392639 PMCID: PMC8980837 DOI: 10.3389/fneur.2022.795573] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 02/25/2022] [Indexed: 11/13/2022] Open
Abstract
Excluding persons from magnetic resonance imaging (MRI) research studies based on their medical history or because they have tattoos, can create bias and compromise the validity and generalizability of study results. In the population-based Rhineland Study, we limited exclusion criteria for MRI and allowed participants with passive medical implants, tattoos or permanent make-up to undergo MRI. Thereby, we could include 16.6% more people than would have been possible based on common recommendations. We observed no adverse events or artifacts. This supports that most passive medical implants, tattoos and permanent make-up are MRI suitable and can be scanned in research settings.
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Affiliation(s)
- Valerie Lohner
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Simon J. Enkirch
- Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Elke Hattingen
- Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Neuroradiology, University Hospital Frankfurt, Frankfurt, Germany
| | - Tony Stöcker
- MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Physics and Astronomy, University of Bonn, Bonn, Germany
| | - Monique M. B. Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
- *Correspondence: Monique M. B. Breteler
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9
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Mauschitz MM, Lohner V, Koch A, Stöcker T, Reuter M, Holz FG, Finger RP, Breteler MMB. Retinal layer assessments as potential biomarkers for brain atrophy in the Rhineland Study. Sci Rep 2022; 12:2757. [PMID: 35177781 PMCID: PMC8854401 DOI: 10.1038/s41598-022-06821-4] [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] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 01/20/2022] [Indexed: 01/09/2023] Open
Abstract
Retinal assessments have been discussed as biomarkers for brain atrophy. However, available studies did not investigate all retinal layers due to older technology, reported inconsistent results, or were based on small sample sizes. We included 2872 eligible participants of the Rhineland Study with data on spectral domain-optical coherence tomography (SD-OCT) and brain magnetic resonance imaging (MRI). We used multiple linear regression to examine relationships between retinal measurements and volumetric brain measures as well as fractional anisotropy (FA) as measure of microstructural integrity of white matter (WM) for different brain regions. Mean (SD) age was 53.8 ± 13.2 years (range 30-94) and 57% were women. Volumes of the inner retina were associated with total brain and grey matter (GM) volume, and even stronger with WM volume and FA. In contrast, the outer retina was mainly associated with GM volume, while both, inner and outer retina, were associated with hippocampus volume. While we extend previously reported associations between the inner retina and brain measures, we found additional associations of the outer retina with parts of the brain. This indicates that easily accessible retinal SD-OCT assessments may serve as biomarkers for clinical monitoring of neurodegenerative diseases and merit further research.
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Affiliation(s)
- Matthias M. Mauschitz
- grid.424247.30000 0004 0438 0426Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127 Bonn, Germany ,grid.15090.3d0000 0000 8786 803XDepartment of Ophthalmology, University Hospital Bonn, Bonn, Germany
| | - Valerie Lohner
- grid.424247.30000 0004 0438 0426Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127 Bonn, Germany
| | - Alexandra Koch
- grid.424247.30000 0004 0438 0426Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127 Bonn, Germany
| | - Tony Stöcker
- grid.424247.30000 0004 0438 0426MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ,grid.10388.320000 0001 2240 3300Department of Physics and Astronomy, University of Bonn, Bonn, Germany
| | - Martin Reuter
- grid.424247.30000 0004 0438 0426Image Analysis, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Frank G. Holz
- grid.15090.3d0000 0000 8786 803XDepartment of Ophthalmology, University Hospital Bonn, Bonn, Germany
| | - Robert P. Finger
- grid.15090.3d0000 0000 8786 803XDepartment of Ophthalmology, University Hospital Bonn, Bonn, Germany
| | - Monique M. B. Breteler
- grid.424247.30000 0004 0438 0426Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127 Bonn, Germany ,grid.10388.320000 0001 2240 3300Institute for Medical Biometry, Informatics and Epidemiology, Faculty of Medicine, University of Bonn, Bonn, Germany
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10
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Lohner V, Lu R, Enkirch SJ, Stöcker T, Hattingen E, Breteler MMB. Correction to: Incidental findings on 3 T neuroimaging: cross-sectional observations from the population-based Rhineland Study. Neuroradiology 2022; 64:633. [PMID: 35022801 DOI: 10.1007/s00234-021-02880-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Valerie Lohner
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Ran Lu
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Simon J Enkirch
- Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Tony Stöcker
- MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Physics and Astronomy, University of Bonn, Bonn, Germany
| | - Elke Hattingen
- Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany.,Department of Neuroradiology, University Hospital Frankfurt, Frankfurt, Germany
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany. .,Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany.
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11
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Lohner V, Lu R, Enkirch SJ, Stöcker T, Hattingen E, Breteler MMB. Incidental findings on 3 T neuroimaging: cross-sectional observations from the population-based Rhineland Study. Neuroradiology 2021; 64:503-512. [PMID: 34842946 PMCID: PMC8850254 DOI: 10.1007/s00234-021-02852-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [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: 09/15/2021] [Accepted: 10/29/2021] [Indexed: 11/30/2022]
Abstract
Purpose Development of best practices for dealing with incidental findings on neuroimaging requires insight in their frequency and clinical relevance. Methods Here, we delineate prevalence estimates with 95% confidence intervals and clinical management of incidental findings, based on the first 3589 participants of the population-based Rhineland Study (age range 30–95 years) who underwent 3 Tesla structural neuroimaging (3D, 0.8 mm3 isotropic resolution). Two trained raters independently assessed all scans for abnormalities, with confirmation and adjudication where needed by neuroradiologists. Participants were referred for diagnostic work-up depending on the potential benefit. Results Of 3589 participants (mean age 55 ± 14 years, 2072 women), 867 had at least one possible incidental finding (24.2%). Most common were pituitary abnormalities (12.3%), arachnoid cysts (4.1%), developmental venous anomalies (2.5%), non-acute infarcts (1.8%), cavernomas (1.0%), and meningiomas (0.7%). Forty-six participants were informed about their findings, which was hitherto unknown in 40 of them (1.1%). Of these, in 19 participants (48%), a wait-and-see policy was applied and nine (23%) received treatment, while lesions in the remainder were benign, could not be confirmed, or the participant refused to inform us about their clinical diagnosis. Conclusion Nearly one-quarter of participants had an incidental finding, but only 5% of those required referral, that mostly remained without direct clinical consequences.
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Affiliation(s)
- Valerie Lohner
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Ran Lu
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Simon J Enkirch
- Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Tony Stöcker
- MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Physics and Astronomy, University of Bonn, Bonn, Germany
| | - Elke Hattingen
- Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany.,Department of Neuroradiology, University Hospital Frankfurt, Frankfurt, Germany
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127, Bonn, Germany. .,Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany.
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12
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Tavares JF, Landstra EN, Brunner J, Boenniger MM, Lohner V, Conrad J, Nöthlings U, Breteler MMB. Associations between dietary spermidine intake, cognition and brain volumes. Alzheimers Dement 2020. [DOI: 10.1002/alz.045750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | - Julia Brunner
- German Center for Neurodegenerative Diseases (DZNE) Bonn Germany
| | - Meta M Boenniger
- German Center for Neurodegenerative Diseases (DZNE) Bonn Germany
| | - Valerie Lohner
- German Center for Neurodegenerative Diseases (DZNE) Bonn Germany
| | | | | | - Monique MB Breteler
- German Center for Neurodegenerative Diseases (DZNE) Bonn Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine University of Bonn Bonn Germany
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13
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van Leijsen EMC, van Uden IWM, Ghafoorian M, Bergkamp MI, Lohner V, Kooijmans ECM, van der Holst HM, Tuladhar AM, Norris DG, van Dijk EJ, Rutten-Jacobs LCA, Platel B, Klijn CJM, de Leeuw FE. Nonlinear temporal dynamics of cerebral small vessel disease: The RUN DMC study. Neurology 2017; 89:1569-1577. [PMID: 28878046 PMCID: PMC5634663 DOI: 10.1212/wnl.0000000000004490] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Accepted: 07/10/2017] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To investigate the temporal dynamics of cerebral small vessel disease (SVD) by 3 consecutive assessments over a period of 9 years, distinguishing progression from regression. METHODS Changes in SVD markers of 276 participants of the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort (RUN DMC) cohort were assessed at 3 time points over 9 years. We assessed white matter hyperintensities (WMH) volume by semiautomatic segmentation and rated lacunes and microbleeds manually. We categorized baseline WMH severity as mild, moderate, or severe according to the modified Fazekas scale. We performed mixed-effects regression analysis including a quadratic term for increasing age. RESULTS Mean WMH progression over 9 years was 4.7 mL (0.54 mL/y; interquartile range 0.95-5.5 mL), 20.3% of patients had incident lacunes (2.3%/y), and 18.9% had incident microbleeds (2.2%/y). WMH volume declined in 9.4% of the participants during the first follow-up interval, but only for 1 participant (0.4%) throughout the whole follow-up. Lacunes disappeared in 3.6% and microbleeds in 5.7% of the participants. WMH progression accelerated over time: including a quadratic term for increasing age during follow-up significantly improved the model (p < 0.001). SVD progression was predominantly seen in participants with moderate to severe WMH at baseline compared to those with mild WMH (odds ratio [OR] 35.5, 95% confidence interval [CI] 15.8-80.0, p < 0.001 for WMH progression; OR 5.7, 95% CI 2.8-11.2, p < 0.001 for incident lacunes; and OR 2.9, 95% CI 1.4-5.9, p = 0.003 for incident microbleeds). CONCLUSIONS SVD progression is nonlinear, accelerating over time, and a highly dynamic process, with progression interrupted by reduction in some, in a population that on average shows progression.
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Affiliation(s)
- Esther M C van Leijsen
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Ingeborg W M van Uden
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Mohsen Ghafoorian
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Mayra I Bergkamp
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Valerie Lohner
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Eline C M Kooijmans
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Helena M van der Holst
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Anil M Tuladhar
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - David G Norris
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Ewoud J van Dijk
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Loes C A Rutten-Jacobs
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Bram Platel
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Catharina J M Klijn
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany
| | - Frank-Erik de Leeuw
- From the Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroscience, Department of Neurology (E.M.C.v.L., I.W.M.v.U., M.I.B., V.L., E.C.M.K., H.M.v.d.H., A.M.T., E.J.v.D., C.J.M.K., F.-E.d.L.), and Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine (M.G., B.P.), Radboud University Medical Centre; Institute for Computing and Information Sciences (M.G.) and Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging (D.G.N.), Radboud University, Nijmegen, the Netherlands; Department of Clinical Neurosciences, Neurology Unit (L.C.A.R.-J.), University of Cambridge, UK; and Erwin L. Hahn Institute for Magnetic Resonance Imaging (D.G.N.), University of Duisburg-Essen, Essen, Germany.
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Möbius M, Tendolkar I, Lohner V, Baltussen M, Becker ES. Refilling the half-empty glass--Investigating the potential role of the Interpretation Modification Paradigm for Depression (IMP-D). J Behav Ther Exp Psychiatry 2015; 49:37-43. [PMID: 25832771 DOI: 10.1016/j.jbtep.2015.03.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2014] [Revised: 01/26/2015] [Accepted: 03/02/2015] [Indexed: 11/24/2022]
Abstract
BACKGROUND AND OBJECTIVES Cognitive biases are known to cause and maintain depression. However, little research has been done on techniques targeting interpretation tendencies found in depression, despite the promising findings of anxiety studies. This paper presents two experiments, investigating the suitability of an Interpretation Modification Paradigm for Depression (IMP-D) in healthy individuals, which has already proven its effectiveness in anxiety (Beard & Amir, 2008). Different from other paradigms, the IMP-D aims at modifying an interpretation bias on response- and on a more implicit reaction time-level, making this task less susceptible to demand effects. METHODS The Word-Sentence Association Paradigm for Depression (Hindash & Amir, 2011) was modified and administered in healthy volunteers (experiment I: N = 81; experiment II: N = 105). To enhance a positive interpretation bias, endorsing benign and rejecting negative interpretations of ambiguous scenarios was reinforced through feedback. This intervention was compared to the opposite training (both experiments) and a control training (experiment II only). RESULTS Both experiments revealed a significant increase in bias towards benign interpretations on the level of overt decisions, while only in the first experiment a change was found on a reaction time level. These modifications are not reflected in group-differences in emotional vulnerability. LIMITATIONS Possible limitations regarding the reliability of inter-dependent response and reaction time measures are discussed. CONCLUSIONS The IMP-D is able to modify interpretation biases, but adaptations are required to maximize its beneficial effects.
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Affiliation(s)
- Martin Möbius
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands.
| | - Indira Tendolkar
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands; Radboud University Medical Centre, Department of Psychiatry, Nijmegen, The Netherlands; University Hospital Essen, Department of Psychiatry and Psychotherapy, Essen, Germany
| | - Valerie Lohner
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Mirte Baltussen
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Eni S Becker
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
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